WorldWideScience

Sample records for model yields results

  1. ExEP yield modeling tool and validation test results

    Science.gov (United States)

    Morgan, Rhonda; Turmon, Michael; Delacroix, Christian; Savransky, Dmitry; Garrett, Daniel; Lowrance, Patrick; Liu, Xiang Cate; Nunez, Paul

    2017-09-01

    EXOSIMS is an open-source simulation tool for parametric modeling of the detection yield and characterization of exoplanets. EXOSIMS has been adopted by the Exoplanet Exploration Programs Standards Definition and Evaluation Team (ExSDET) as a common mechanism for comparison of exoplanet mission concept studies. To ensure trustworthiness of the tool, we developed a validation test plan that leverages the Python-language unit-test framework, utilizes integration tests for selected module interactions, and performs end-to-end crossvalidation with other yield tools. This paper presents the test methods and results, with the physics-based tests such as photometry and integration time calculation treated in detail and the functional tests treated summarily. The test case utilized a 4m unobscured telescope with an idealized coronagraph and an exoplanet population from the IPAC radial velocity (RV) exoplanet catalog. The known RV planets were set at quadrature to allow deterministic validation of the calculation of physical parameters, such as working angle, photon counts and integration time. The observing keepout region was tested by generating plots and movies of the targets and the keepout zone over a year. Although the keepout integration test required the interpretation of a user, the test revealed problems in the L2 halo orbit and the parameterization of keepout applied to some solar system bodies, which the development team was able to address. The validation testing of EXOSIMS was performed iteratively with the developers of EXOSIMS and resulted in a more robust, stable, and trustworthy tool that the exoplanet community can use to simulate exoplanet direct-detection missions from probe class, to WFIRST, up to large mission concepts such as HabEx and LUVOIR.

  2. Association between Empirically Estimated Monsoon Dynamics and Other Weather Factors and Historical Tea Yields in China: Results from a Yield Response Model

    Directory of Open Access Journals (Sweden)

    Rebecca Boehm

    2016-04-01

    Full Text Available Farmers in China’s tea-growing regions report that monsoon dynamics and other weather factors are changing and that this is affecting tea harvest decisions. To assess the effect of climate change on tea production in China, this study uses historical weather and production data from 1980 to 2011 to construct a yield response model that estimates the partial effect of weather factors on tea yields in China, with a specific focus on East Asian Monsoon dynamics. Tea (Camellia sinensis (L. Kunze has not been studied using these methods even though it is an important crop for human nutrition and the economic well-being of rural communities in many countries. Previous studies have approximated the monsoon period using historical average onset and retreat dates, which we believe limits our understanding of how changing monsoon patterns affect crop productivity. In our analysis, we instead estimate the monsoon season across China’s tea growing regions empirically by identifying the unknown breakpoints in the year-by-province cumulative precipitation. We find that a 1% increase in the monsoon retreat date is associated with 0.481%–0.535% reduction in tea yield. In the previous year, we also find that a 1% increase in the date of the monsoon retreat is associated with a 0.604% decrease in tea yields. For precipitation, we find that a 1% increase in average daily precipitation occurring during the monsoon period is associated with a 0.184%–0.262% reduction in tea yields. In addition, our models show that 1% increase in the average daily monsoon precipitation from the previous growing season is associated with 0.258%–0.327% decline in yields. We also find that a 1% decrease in solar radiation in the previous growing season is associated with 0.554%-0.864% decrease in tea yields. These findings suggest the need for adaptive management and harvesting strategies given climate change projections and the known negative association between excess

  3. Simulated crop yield in response to changes in climate and agricultural practices: results from a simple process based model

    Science.gov (United States)

    Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.

    2013-12-01

    Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.

  4. Yielding impressive results. The Egyptian experience in family planning communication campaign has been an exemplary model for many developing countries.

    Science.gov (United States)

    Wafai, M

    1994-09-01

    planning IEC has been an exemplary model for many developing countries.

  5. modelling relationship between rainfall variability and yields

    African Journals Online (AJOL)

    yield models should be used for planning and forecasting the yield of millet and sorghum in the study area. Key words: modelling, rainfall, yields, millet, sorghum. INTRODUCTION. Meteorological variables, such as rainfall parameters, temperature, sunshine hours, relative humidity, and wind velocity and soil moisture are.

  6. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    2004-01-01

    This paper considers the problem of mapping spatial variation of yield in a field using data from a yield monitoring system on a combine harvester. The unobserved yield is assumed to be a Gaussian random field and the yield monitoring system data is modelled as a convolution of the yield and an i......This paper considers the problem of mapping spatial variation of yield in a field using data from a yield monitoring system on a combine harvester. The unobserved yield is assumed to be a Gaussian random field and the yield monitoring system data is modelled as a convolution of the yield...... and an impulse response function. This results in an unusual spatial covariance structure (depending on the driving pattern of the combine harverster) for the yield monitoring system data. Parameters of the impulse response function and the spatial covariance function of the yield are estimated using maximum...

  7. Care initiation area yields dramatic results.

    Science.gov (United States)

    2009-03-01

    The ED at Gaston Memorial Hospital in Gastonia, NC, has achieved dramatic results in key department metrics with a Care Initiation Area (CIA) and a physician in triage. Here's how the ED arrived at this winning solution: Leadership was trained in and implemented the Kaizen method, which eliminates redundant or inefficient process steps. Simulation software helped determine additional space needed by analyzing arrival patterns and other key data. After only two days of meetings, new ideas were implemented and tested.

  8. Exploring the performance of the SEDD model to predict sediment yield in eucalyptus plantations. Long-term results from an experimental catchment in Southern Italy

    Science.gov (United States)

    Porto, P.; Cogliandro, V.; Callegari, G.

    2018-01-01

    In this paper, long-term sediment yield data, collected in a small (1.38 ha) Calabrian catchment (W2), reafforested with eucalyptus trees (Eucalyptus occidentalis Engl.) are used to validate the performance of the SEdiment Delivery Distributed Model (SEDD) in areas with high erosion rates. At first step, the SEDD model was calibrated using field data collected in previous field campaigns undertaken during the period 1978-1994. This first phase allowed the model calibration parameter β to be calculated using direct measurements of rainfall, runoff, and sediment output. The model was then validated in its calibrated form for an independent period (2006-2016) for which new measurements of rainfall, runoff and sediment output are also available. The analysis, carried out at event and annual scale showed good agreement between measured and predicted values of sediment yield and suggested that the SEDD model can be seen as an appropriate means of evaluating erosion risk associated with manmade plantations in marginal areas. Further work is however required to test the performance of the SEDD model as a prediction tool in different geomorphic contexts.

  9. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  10. System Model of Daily Sediment Yield

    Science.gov (United States)

    Sharma, T. C.; Dickinson, W. T.

    1980-06-01

    Input-output systems concepts have been applied to the modeling of daily runoff-sediment yield of the Thames River in southern Ontario, Canada. Spectral and correlation techniques have been used to construct a parsimonious model of daily sediment yields. It is shown that a linear discrete dynamic model is possible in terms of the log-transformed daily runoff and sediment yield sequences. The fluvial system of the Thames River watershed exhibits a weak memory on a daily basis, and the noise component corrupting the watershed fluvial system resembles a white noise process.

  11. Validation of crop weather models for crop assessment arid yield ...

    African Journals Online (AJOL)

    IRSIS and CRPSM models were used in this study to see how closely they could predict grain yields for selected stations in Tanzania. Input for the models comprised of weather, crop and soil data collected from five selected stations. Simulation results show that IRSIS model tends to over predict grain yields of maize, ...

  12. Amplitude Models for Discrimination and Yield Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, William Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-01

    This seminar presentation describes amplitude models and yield estimations that look at the data in order to inform legislation. The following points were brought forth in the summary: global models that will predict three-component amplitudes (R-T-Z) were produced; Q models match regional geology; corrected source spectra can be used for discrimination and yield estimation; three-component data increase coverage and reduce scatter in source spectral estimates; three-component efforts must include distance-dependent effects; a community effort on instrument calibration is needed.

  13. ``Models'' CAVEAT EMPTOR!!!: ``Toy Models Too-Often Yield Toy-Results''!!!: Statistics, Polls, Politics, Economics, Elections!!!: GRAPH/Network-Physics: ``Equal-Distribution for All'' TRUMP-ED BEC ``Winner-Take-All'' ``Doctor Livingston I Presume?''

    Science.gov (United States)

    Preibus-Norquist, R. N. C.-Grover; Bush-Romney, G. W.-Willard-Mitt; Dimon, J. P.; Adelson-Koch, Sheldon-Charles-David-Sheldon; Krugman-Axelrod, Paul-David; Siegel, Edward Carl-Ludwig; D. N. C./O. F. P./''47''%/50% Collaboration; R. N. C./G. O. P./''53''%/49% Collaboration; Nyt/Wp/Cnn/Msnbc/Pbs/Npr/Ft Collaboration; Ftn/Fnc/Fox/Wsj/Fbn Collaboration; Lb/Jpmc/Bs/Boa/Ml/Wamu/S&P/Fitch/Moodys/Nmis Collaboration

    2013-03-01

    ``Models''? CAVEAT EMPTOR!!!: ``Toy Models Too-Often Yield Toy-Results''!!!: Goldenfeld[``The Role of Models in Physics'', in Lects.on Phase-Transitions & R.-G.(92)-p.32-33!!!]: statistics(Silver{[NYTimes; Bensinger, ``Math-Geerks Clearly-Defeated Pundits'', LATimes, (11/9/12)])}, polls, politics, economics, elections!!!: GRAPH/network/net/...-PHYSICS Barabasi-Albert[RMP (02)] (r,t)-space VERSUS(???) [Where's the Inverse/ Dual/Integral-Transform???] (Benjamin)Franklin(1795)-Fourier(1795; 1897;1822)-Laplace(1850)-Mellin (1902) Brillouin(1922)-...(k,)-space, {Hubbard [The World According to Wavelets,Peters (96)-p.14!!!/p.246: refs.-F2!!!]},and then (2) Albert-Barabasi[]Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) versus Bianconi[pvt.-comm.; arXiv:cond-mat/0204506; ...] -Barabasi [???] Fermi-Dirac

  14. Top ten models constrained by b {yields} s{gamma}

    Energy Technology Data Exchange (ETDEWEB)

    Hewett, J.L. [Stanford Univ., CA (United States)

    1994-12-01

    The radiative decay b {yields} s{gamma} is examined in the Standard Model and in nine classes of models which contain physics beyond the Standard Model. The constraints which may be placed on these models from the recent results of the CLEO Collaboration on both inclusive and exclusive radiative B decays is summarized. Reasonable bounds are found for the parameters in some cases.

  15. Predicting the Yield Stress of SCC using Materials Modelling

    DEFF Research Database (Denmark)

    Thrane, Lars Nyholm; Hasholt, Marianne Tange; Pade, Claus

    2005-01-01

    A conceptual model for predicting the Bingham rheological parameter yield stress of SCC has been established. The model used here is inspired by previous work of Oh et al. (1), predicting that the yield stress of concrete relative to the yield stress of paste is a function of the relative thickne...... and distribution were varied between SCC types. The results indicate that yield stress of SCC may be predicted using the model.......A conceptual model for predicting the Bingham rheological parameter yield stress of SCC has been established. The model used here is inspired by previous work of Oh et al. (1), predicting that the yield stress of concrete relative to the yield stress of paste is a function of the relative thickness...... of excess paste around the aggregate. The thickness of excess paste is itself a function of particle shape, particle size distribution, and particle packing. Seven types of SCC were tested at four different excess paste contents in order to verify the conceptual model. Paste composition and aggregate shape...

  16. Top ten models constrained by b {yields} s{gamma}

    Energy Technology Data Exchange (ETDEWEB)

    Hewett, J.L.

    1994-05-01

    The radiative decay b {yields} s{gamma} is examined in the Standard Model and in nine classes of models which contain physics beyond the Standard Model. The constraints which may be placed on these models from the recent results of the CLEO Collaboration on both inclusive and exclusive radiative B decays is summarized. Reasonable bounds are found the parameters in some of the models.

  17. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

  18. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of cowpea yield-water use and weather data were collected.

  19. Modelling crop yield in Iberia under drought conditions

    Science.gov (United States)

    Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

    2017-04-01

    The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining

  20. Modeling temporal and spatial variability of crop yield

    Science.gov (United States)

    Bonetti, S.; Manoli, G.; Scudiero, E.; Morari, F.; Putti, M.; Teatini, P.

    2014-12-01

    In a world of increasing food insecurity the development of modeling tools capable of supporting on-farm decision making processes is highly needed to formulate sustainable irrigation practices in order to preserve water resources while maintaining adequate crop yield. The design of these practices starts from the accurate modeling of soil-plant-atmosphere interaction. We present an innovative 3D Soil-Plant model that couples 3D hydrological soil dynamics with a mechanistic description of plant transpiration and photosynthesis, including a crop growth module. Because of its intrinsically three dimensional nature, the model is able to capture spatial and temporal patterns of crop yield over large scales and under various climate and environmental factors. The model is applied to a 25 ha corn field in the Venice coastland, Italy, that has been continuously monitored over the years 2010 and 2012 in terms of both hydrological dynamics and yield mapping. The model results satisfactorily reproduce the large variability observed in maize yield (from 2 to 15 ton/ha). This variability is shown to be connected to the spatial heterogeneities of the farmland, which is characterized by several sandy paleo-channels crossing organic-rich silty soils. Salt contamination of soils and groundwater in a large portion of the area strongly affects the crop yield, especially outside the paleo-channels, where measured salt concentrations are lower than the surroundings. The developed model includes a simplified description of the effects of salt concentration in soil water on transpiration. The results seem to capture accurately the effects of salt concentration and the variability of the climatic conditions occurred during the three years of measurements. This innovative modeling framework paves the way to future large scale simulations of farmland dynamics.

  1. Geoelectrical parameter-based multivariate regression borehole yield model for predicting aquifer yield in managing groundwater resource sustainability

    Directory of Open Access Journals (Sweden)

    Kehinde Anthony Mogaji

    2016-07-01

    Full Text Available This study developed a GIS-based multivariate regression (MVR yield rate prediction model of groundwater resource sustainability in the hard-rock geology terrain of southwestern Nigeria. This model can economically manage the aquifer yield rate potential predictions that are often overlooked in groundwater resources development. The proposed model relates the borehole yield rate inventory of the area to geoelectrically derived parameters. Three sets of borehole yield rate conditioning geoelectrically derived parameters—aquifer unit resistivity (ρ, aquifer unit thickness (D and coefficient of anisotropy (λ—were determined from the acquired and interpreted geophysical data. The extracted borehole yield rate values and the geoelectrically derived parameter values were regressed to develop the MVR relationship model by applying linear regression and GIS techniques. The sensitivity analysis results of the MVR model evaluated at P ⩽ 0.05 for the predictors ρ, D and λ provided values of 2.68 × 10−05, 2 × 10−02 and 2.09 × 10−06, respectively. The accuracy and predictive power tests conducted on the MVR model using the Theil inequality coefficient measurement approach, coupled with the sensitivity analysis results, confirmed the model yield rate estimation and prediction capability. The MVR borehole yield prediction model estimates were processed in a GIS environment to model an aquifer yield potential prediction map of the area. The information on the prediction map can serve as a scientific basis for predicting aquifer yield potential rates relevant in groundwater resources sustainability management. The developed MVR borehole yield rate prediction mode provides a good alternative to other methods used for this purpose.

  2. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  3. Yield models for commercial willow biomass plantations in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Mola-Yudego, Blas [Faculty of Forestry, University of Joensuu, P.O. Box 111, FI-801 01 Joensuu (Finland); Aronsson, Paer [Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), P.O. Box 7016, S-750 07 Uppsala (Sweden)

    2008-09-15

    A yield model for willow plantations for bioenergy production in Sweden was developed based on recorded production of 2082 commercial plantations during the period 1989-2005. The model predicts yield for the first, second and third harvest using oats (avena) production as agro-climatic index. The mean annual yields were 2.6, 4.2 and 4.5 oven dry tonnes (odt) per hectare during the first, second and third cutting cycles, respectively. The yield correlated inversely with the length of the cutting cycle. The results of the study show significant differences between growers, which suggest the importance of proper management in the establishment and tending of the plantations. Model estimates for 25% of the best growers vary from 4.0 to 6.3 odt ha{sup -1} yr{sup -1} in 5-year-rotation plantations during the first cutting cycle, and from 5.4 to 7.1 odt ha{sup -1} yr{sup -1} in 4-year-rotations for the second cutting cycle. The proposed model can be applied in policy making and for management planning. (author)

  4. Donor management parameters and organ yield: single center results.

    Science.gov (United States)

    Marshall, George Ryne; Mangus, Richard S; Powelson, John A; Fridell, Jonathan A; Kubal, Chandrashekhar A; Tector, A Joseph

    2014-09-01

    Management of organ donors in the intensive care unit is an emerging subject in critical care and transplantation. This study evaluates organ yield outcomes for a large number of patients managed by the Indiana Organ Procurement Organization. This is a retrospective review of intensive care unit records from 2008-2012. Donor demographic information and seven donor management parameters (DMP) were recorded at admission, consent, 12 h after consent, and before procurement. Three study groups were created: donors meeting 0-3, 4, or 5-7 DMP. Active donor Organ Procurement Organization management began at consent; so, data analysis focuses on the 12-h postconsent time point. Outcomes included organs transplanted per donor (OTPD) and transplantation of individual solid organs. Complete records for 499 patients were reviewed. Organ yield was 1415 organs of 3992 possible (35%). At 12 h, donors meeting more DMP had more OTPD: 2.2 (0-3) versus 3.0 (4) versus 3.5 (5-7) (P organ except intestine. Oxygen tension, vasopressor use, and central venous pressure were the most frequent independent predictors of organ usage. There were significantly more organs transplanted for donors meeting all three of these parameters (4.5 versus 2.7, P organs, with analysis of individual parameters suggesting that appropriate management of oxygenation, volume status, and vasopressor use could lead to more organs procured per donor. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Atmospheric Deposition Modeling Results

    Data.gov (United States)

    U.S. Environmental Protection Agency — This asset provides data on model results for dry and total deposition of sulfur, nitrogen and base cation species. Components include deposition velocities, dry...

  6. ZNJPrice/Earnings Ratio Model through Dividend Yield and Required Yield Above Expected Inflation

    Directory of Open Access Journals (Sweden)

    Emil Mihalina

    2010-07-01

    Full Text Available Price/earnings ratio is the most popular and most widespread evaluation model used to assess relative capital asset value on financial markets. In functional terms, company earnings in the very long term can be described with high significance. Empirically, it is visible from long-term statistics that the demanded (required yield on capital markets has certain regularity. Thus, investors first require a yield above the stable inflation rate and then a dividend yield and a capital increase caused by the growth of earnings that influence the price, with the assumption that the P/E ratio is stable. By combining the Gordon model for current dividend value, the model of market capitalization of earnings (price/earnings ratio and bearing in mind the influence of the general price levels on company earnings, it is possible to adjust the price/earnings ratio by deriving a function of the required yield on capital markets measured by a market index through dividend yield and inflation rate above the stable inflation rate increased by profit growth. The S&P 500 index for example, has in the last 100 years grown by exactly the inflation rate above the stable inflation rate increased by profit growth. The comparison of two series of price/earnings ratios, a modelled one and an average 7-year ratio, shows a notable correlation in the movement of two series of variables, with a three year deviation. Therefore, it could be hypothesized that three years of the expected inflation level, dividend yield and profit growth rate of the market index are discounted in the current market prices. The conclusion is that, at the present time, the relationship between the adjusted average price/earnings ratio and its effect on the market index on one hand and the modelled price/earnings ratio on the other can clearly show the expected dynamics and course in the following period.

  7. Soybean yield modeling using bootstrap methods for small samples

    Energy Technology Data Exchange (ETDEWEB)

    Dalposso, G.A.; Uribe-Opazo, M.A.; Johann, J.A.

    2016-11-01

    One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters. (Author)

  8. Yield Stress Model for Molten Composition B-3

    Science.gov (United States)

    Davis, Stephen; Zerkle, David

    2017-06-01

    Composition B-3 (Comp B-3) is a melt-castable explosive composed of 60/40 wt% RDX/TNT (hexahydro-1,3,5-trinitro-1,3,5-triazine/2,4,6-trinitrotoluene). During casting operations thermal conditions are controlled which along with the low melting point of TNT and the insensitivity of the mixture to external stimuli leading to safe use. Outside these standard operating conditions a more rigorous model of Comp B-3 rheological properties is necessary to model thermal transport as Comp B-3 evolves from quiescent solid through vaporization/decomposition upon heating. One particular rheological phenomena of interest is Bingham plasticity, where a material behaves as a quiescent solid unless a sufficient load is applied, resulting in fluid flow. In this study falling ball viscometer data is used to model the change in Bingham plastic yield stresses as a function of RDX particle volume fraction; a function of temperature. Results show the yield stress of Comp B-3 (τy) follows the expression τy = B ϕ -ϕc N , where Φ and Φc are the volume fraction of RDX and a critical volume fraction, respectively and B and N are experimentally evaluated constants.

  9. Large-area dry bean yield prediction modeling in Mexico

    Science.gov (United States)

    Given the importance of dry bean in Mexico, crop yield predictions before harvest are valuable for authorities of the agricultural sector, in order to define support for producers. The aim of this study was to develop an empirical model to estimate the yield of dry bean at the regional level prior t...

  10. Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee.

    Directory of Open Access Journals (Sweden)

    Rolando Cerda

    Full Text Available The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production and secondary yield losses (resulting from negative impacts of the previous year of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013-2015 and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26% and even higher secondary yield losses (38%. We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

  11. A physiological production model for cacao : results of model simulations

    NARCIS (Netherlands)

    Zuidema, P.A.; Leffelaar, P.A.

    2002-01-01

    CASE2 is a physiological model for cocoa (Theobroma cacao L.) growth and yield. This report introduces the CAcao Simulation Engine for water-limited production in a non-technical way and presents simulation results obtained with the model.

  12. Estimation of the yield of poplars in plantations of fast-growing species within current results

    Directory of Open Access Journals (Sweden)

    Martin Fajman

    2009-01-01

    Full Text Available Current results are presented of allometric yield estimates of the poplar short rotation coppice. According to a literature review it is obvious that yield estimates, based on measurable quantities of a growing stand, depend not only on the selected tree specie or its clone, but also on the site location. The Jap-105 poplar clone (P. nigra x P. maximowiczii allometric relations were analyzed by regression methods aimed at the creation of the yield estimation methodology at a testing site in Domanínek. Altogether, the twelve polynomial dependences of particular measured quantities approved the high empirical data conformity with the tested regression model (correlation index from 0.9033 to 0.9967. Within the forward stepwise regression, factors were selected, which explain best examined estimates of the total biomass DM; i.e. d.b.h. and stem height. Furthermore, the KESTEMONT’s (1971 mo­del was verified with a satisfying conformity as well. Approving presented yield estimation methods, the presented models will be checked in a large-scale field trial.

  13. Modeling the effects of ozone on soybean growth and yield.

    Science.gov (United States)

    Kobayashi, K; Miller, J E; Flagler, R B; Heck, W W

    1990-01-01

    A simple mechanistic model was developed based on an existing growth model in order to address the mechanisms of the effects of ozone on growth and yield of soybean [Glycine max. (L.) Merr. 'Davis'] and interacting effects of other environmental stresses. The model simulates daily growth of soybean plants using environmental data including shortwave radiation, temperature, precipitation, irrigation and ozone concentration. Leaf growth, dry matter accumulation, water budget, nitrogen input and seed growth linked to senescence and abscission of leaves are described in the model. The effects of ozone are modeled as reduced photosynthate production and accelerated senescence. The model was applied to the open-top chamber experiments in which soybean plants were exposed to ozone under two levels of soil moisture regimes. After calibrating the model to the growth data and seed yield, goodness-of-fit of the model was tested. The model fitted well for top dry weight in the vegetative growth phase and also at maturity. The effect of ozone on seen yield was also described satisfactorily by the model. The simulation showed apparent interaction between the effect of ozone and soil moisture stress on the seed yield. The model revealed that further work is needed concerning the effect of ozone on the senescence process and the consequences of alteration of canopy microclimate by the open-top chambers.

  14. Global evaluation of a semiempirical model for yield anomalies and application to within-season yield forecasting.

    Science.gov (United States)

    Schauberger, Bernhard; Gornott, Christoph; Wechsung, Frank

    2017-11-01

    Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two-thirds (63%-81%) of observed yield anomalies. Its out-of-sample performance (34%-55%) suggests a robust yield projection capacity when applied to unknown weather. Out-of-sample performance is lower when using remote sensing-derived yield data. The share of weather-driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%-84%). But the out-of-sample performance is lower (15%-42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within-season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high-quality yield monitoring and statistics as critical

  15. The Impact of Statistical Leakage Models on Design Yield Estimation

    Directory of Open Access Journals (Sweden)

    Rouwaida Kanj

    2011-01-01

    Full Text Available Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100 nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.

  16. BioSTAR, a New Biomass and Yield Modeling Software

    Science.gov (United States)

    Kappas, M.; Degener, J.; Bauboeck, R.

    2013-12-01

    , sorghum, sunflower and, sugar beet. Calibrations for rye grass, cup plant, poplar and willow still need to be performed. A Comparison of simulated and observed biomass yields for sites in Lower Saxony has rendered good results with errors (RMSE) ranging from below 10% (winter wheat, n= 102) and 18.6 % (sunflower, n=8) (Bauböck, unpublished). Because simulations can be made with limited soil data (soil type or texture class) and a limited climate data set (smallest set can be either monthly means of precipitation, temperature and, radiation or precipitation, temperature and, humidity) and the software is capable of processing large datasets, the model appears to be a promising tool for mid or large scale biomass and yield predictions. Up to now the model has only been used for yield predictions with current state climate and climate change scenarios in Lower Saxony, but comparisons with output data of the model AquaCrop (Steduto, et al., 2009) have shown good performance in arid and semi-arid climates (Bauböck, 2013).

  17. Strong morphological and crystallographic texture and resulting yield strength anisotropy in selective laser melted tantalum

    International Nuclear Information System (INIS)

    Thijs, Lore; Montero Sistiaga, Maria Luz; Wauthle, Ruben; Xie, Qingge; Kruth, Jean-Pierre; Van Humbeeck, Jan

    2013-01-01

    Selective laser melting (SLM) makes use of a high energy density laser beam to melt successive layers of metallic powders in order to create functional parts. The energy density of the laser is high enough to melt refractory metals like Ta and produce mechanically sound parts. Furthermore, the localized heat input causes a strong directional cooling and solidification. Epitaxial growth due to partial remelting of the previous layer, competitive growth mechanism and a specific global direction of heat flow during SLM of Ta result in the formation of long columnar grains with a 〈1 1 1〉 preferential crystal orientation along the building direction. The microstructure was visualized using both optical and scanning electron microscopy equipped with electron backscattered diffraction and the global crystallographic texture was measured using X-ray diffraction. The thermal profile around the melt pool was modeled using a pragmatic model for SLM. Furthermore, rotation of the scanning direction between different layers was seen to promote the competitive growth. As a result, the texture strength increased to as large as 4.7 for rotating the scanning direction 90° every layer. By comparison of the yield strength measured by compression tests in different orientations and the averaged Taylor factor calculated using the viscoplastic self-consistent model, it was found that both the morphological and crystallographic texture observed in SLM Ta contribute to yield strength anisotropy

  18. Assessing disease stress and modeling yield losses in alfalfa

    Science.gov (United States)

    Guan, Jie

    Alfalfa is the most important forage crop in the U.S. and worldwide. Fungal foliar diseases are believed to cause significant yield losses in alfalfa, yet, little quantitative information exists regarding the amount of crop loss. Different fungicides and application frequencies were used as tools to generate a range of foliar disease intensities in Ames and Nashua, IA. Visual disease assessments (disease incidence, disease severity, and percentage defoliation) were obtained weekly for each alfalfa growth cycle (two to three growing cycles per season). Remote sensing assessments were performed using a hand-held, multispectral radiometer to measure the amount and quality of sunlight reflected from alfalfa canopies. Factors such as incident radiation, sun angle, sensor height, and leaf wetness were all found to significantly affect the percentage reflectance of sunlight reflected from alfalfa canopies. The precision of visual and remote sensing assessment methods was quantified. Precision was defined as the intra-rater repeatability and inter-rater reliability of assessment methods. F-tests, slopes, intercepts, and coefficients of determination (R2) were used to compare assessment methods for precision. Results showed that among the three visual disease assessment methods (disease incidence, disease severity, and percentage defoliation), percentage defoliation had the highest intra-rater repeatability and inter-rater reliability. Remote sensing assessment method had better precision than the percentage defoliation assessment method based upon higher intra-rater repeatability and inter-rater reliability. Significant linear relationships between canopy reflectance (810 nm), percentage defoliation and yield were detected using linear regression and percentage reflectance (810 nm) assessments were found to have a stronger relationship with yield than percentage defoliation assessments. There were also significant linear relationships between percentage defoliation, dry

  19. A crop model-based approach for sunflower yields

    Directory of Open Access Journals (Sweden)

    João Guilherme Dal Belo Leite

    2014-10-01

    Full Text Available Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L. production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122 were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield and development stages (crop phenology were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %. Simulated yields were relatively high (1,750 to 4,250 kg ha-1 and the sowing window was fairly wide (Oct to Feb for northwestern locations, where sunflower could be cultivated as a second crop (double cropping at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.

  20. Simultaneous growth and yield models for Eucalyptus grandis (Hill ...

    African Journals Online (AJOL)

    Simultaneous stand-level growth and yield models for Eucalyptus grandis in Zimbabwe were developed from Correlated Curve Trend (CCT) and Nelder wheel experiments replicated on five different sites. Nonlinear three-stage least squares method was used to simultaneously fit prediction and projection equations for ...

  1. Growth and yield models for Eucalyptus grandis grown in Swaziland ...

    African Journals Online (AJOL)

    The aim of this study was to develop a stand-level growth and yield model for short-rotationEucalyptus grandis grown for pulp wood production at Piggs Peak in Swaziland. The data were derived from a Nelder 1a spacing trial established with E. grandis clonal cuttings in 1998 and terminated in 2005. Planting density ...

  2. Local yield stress statistics in model amorphous solids

    Science.gov (United States)

    Barbot, Armand; Lerbinger, Matthias; Hernandez-Garcia, Anier; García-García, Reinaldo; Falk, Michael L.; Vandembroucq, Damien; Patinet, Sylvain

    2018-03-01

    We develop and extend a method presented by Patinet, Vandembroucq, and Falk [Phys. Rev. Lett. 117, 045501 (2016), 10.1103/PhysRevLett.117.045501] to compute the local yield stresses at the atomic scale in model two-dimensional Lennard-Jones glasses produced via differing quench protocols. This technique allows us to sample the plastic rearrangements in a nonperturbative manner for different loading directions on a well-controlled length scale. Plastic activity upon shearing correlates strongly with the locations of low yield stresses in the quenched states. This correlation is higher in more structurally relaxed systems. The distribution of local yield stresses is also shown to strongly depend on the quench protocol: the more relaxed the glass, the higher the local plastic thresholds. Analysis of the magnitude of local plastic relaxations reveals that stress drops follow exponential distributions, justifying the hypothesis of an average characteristic amplitude often conjectured in mesoscopic or continuum models. The amplitude of the local plastic rearrangements increases on average with the yield stress, regardless of the system preparation. The local yield stress varies with the shear orientation tested and strongly correlates with the plastic rearrangement locations when the system is sheared correspondingly. It is thus argued that plastic rearrangements are the consequence of shear transformation zones encoded in the glass structure that possess weak slip planes along different orientations. Finally, we justify the length scale employed in this work and extract the yield threshold statistics as a function of the size of the probing zones. This method makes it possible to derive physically grounded models of plasticity for amorphous materials by directly revealing the relevant details of the shear transformation zones that mediate this process.

  3. Modelling and water yield assessment of Lake Sibhayi | Smithers ...

    African Journals Online (AJOL)

    A yield analysis of simulated results with historical developments in the catchment for the 65-year period of observed climate record was undertaken using both a fixed minimum allowable lake level or a maximum drop from a reference lake level as criteria for system failure. Results from simulating lake levels using the ...

  4. Buffalos milk yield analysis using random regression models

    Directory of Open Access Journals (Sweden)

    A.S. Schierholt

    2010-02-01

    Full Text Available Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed, daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genético de Bubalinos (PROMEBUL and from records of EMBRAPA Amazônia Oriental - EAO herd, located in Belém, Pará, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre’s polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre’s polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

  5. Operational semi-physical spectral-spatial wheat yield model development

    Science.gov (United States)

    Tripathy, R.; Chaudhary, K. N.; Nigam, R.; Manjunath, K. R.; Chauhan, P.; Ray, S. S.; Parihar, J. S.

    2014-11-01

    Spectral yield models based on Vegetation Index (VI) and the mechanistic crop simulation models are being widely used for crop yield prediction. However, past experience has shown that the empirical nature of the VI based models and the intensive data requirement of the complex mechanistic models has limited their use for regional and spatial crop yield prediction especially for operational use. The present study was aimed at development of an intermediate method based on the use of remote sensing and the physiological concepts such as the photo-synthetically active solar radiation (PAR) and the fraction of PAR absorbed by the crop (fAPAR) in Monteith's radiation use efficiency based equation (Monteith, 1977) for operational wheat yield forecasting by the Department of Agriculture (DoA). Net Primary Product (NPP) has been computed using the Monteith model and stress has been applied to convert the potential NPP to actual NPP. Wheat grain yield has been computed using the actual NPP and Harvest index. Kalpana-VHRR insolation has been used for deriving the PAR. Maximum radiation use efficiency has been collected from literature and wheat crop mask was derived at MNCFC, New Delhi using RS2-AWiFS data. Water stress has been derived from the Land Surface Water Index (LSWI) which has been derived periodically from the MODIS surface reflectance data (NIR and SWIR1). Temperature stress has been derived from the interpolated daily mean temperature. Results indicated that this model underestimated the yield by 3.45 % as compared to the reported yield at state level and hence can be used to predict wheat yield at state level. This study will be able to provide the spatial wheat yield map, as well as the district-wise and state level aggregated wheat yield forecast. It is possible to operationalize this remote sensing based modified Monteith's efficiency model for future yield forecasting with around 0.15 t ha-1 RMSE at state level.

  6. An analytical model of nonproportional scintillator light yield in terms of recombination rates

    International Nuclear Information System (INIS)

    Bizarri, G.; Moses, W. W.; Singh, J.; Vasil'ev, A. N.; Williams, R. T.

    2009-01-01

    Analytical expressions for the local light yield as a function of the local deposited energy (-dE/dx) and total scintillation yield integrated over the track of an electron of initial energy E are derived from radiative and/or nonradiative rates of first through third order in density of electronic excitations. The model is formulated in terms of rate constants, some of which can be determined independently from time-resolved spectroscopy and others estimated from measured light yield efficiency as a constraint assumed to apply in each kinetic order. The rates and parameters are used in the theory to calculate scintillation yield versus primary electron energy for comparison to published experimental results on four scintillators. Influence of the track radius on the yield is also discussed. Results are found to be qualitatively consistent with the observed scintillation light yield. The theory can be applied to any scintillator if the rates of the radiative and nonradiative processes are known

  7. Predictive models of prolonged mechanical ventilation yield moderate accuracy.

    Science.gov (United States)

    Figueroa-Casas, Juan B; Dwivedi, Alok K; Connery, Sean M; Quansah, Raphael; Ellerbrook, Lowell; Galvis, Juan

    2015-06-01

    To develop a model to predict prolonged mechanical ventilation within 48 hours of its initiation. In 282 general intensive care unit patients, multiple variables from the first 2 days on mechanical ventilation and their total ventilation duration were prospectively collected. Three models accounting for early deaths were developed using different analyses: (a) multinomial logistic regression to predict duration > 7 days vs duration ≤ 7 days alive vs duration ≤ 7 days death; (b) binary logistic regression to predict duration > 7 days for the entire cohort and for survivors only, separately; and (c) Cox regression to predict time to being free of mechanical ventilation alive. Positive end-expiratory pressure, postoperative state (negatively), and Sequential Organ Failure Assessment score were independently associated with prolonged mechanical ventilation. The multinomial regression model yielded an accuracy (95% confidence interval) of 60% (53%-64%). The binary regression models yielded accuracies of 67% (61%-72%) and 69% (63%-75%) for the entire cohort and for survivors, respectively. The Cox regression model showed an equivalent to area under the curve of 0.67 (0.62-0.71). Different predictive models of prolonged mechanical ventilation in general intensive care unit patients achieve a moderate level of overall accuracy, likely insufficient to assist in clinical decisions. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Dynamic modelling of pectin extraction describing yield and functional characteristics

    DEFF Research Database (Denmark)

    Andersen, Nina Marianne; Cognet, T.; Santacoloma, P. A.

    2017-01-01

    A dynamic model of pectin extraction is proposed that describes pectin yield, degree of esterification and intrinsic viscosity. The dynamic model is one dimensional in the peel geometry and includes mass transport of pectin by diffusion and reaction kinetics of hydrolysis, degradation and de......-esterification. The model takes into account the effects of the process conditions such as temperature and acid concentration on extraction kinetics. It is shown that the model describes pectin bulk solution concentration, degree of esterification and intrinsic viscosity in pilot scale extractions from lime peel...... at different temperatures (60 °C, 70 °C, 80 °C) and pH (1.5, 2.3, 3.1) values....

  9. Performance evaluation of selected crop yield-water use models for wheat crop

    Directory of Open Access Journals (Sweden)

    H. E. Igbadun

    2001-10-01

    Full Text Available Crop yield-water use models that provide useful information about the exact form of crop response to different amounts of water used by the crop throughout its growth stages and those that provide adequate information for decisions on optimal use of water in the farm were evaluated. Three crop yield models: Jensen (1968, Minhas et al., (1974 and Bras and Cordova (1981 additive type models were studied. Wheat (Triticum aestivum was planted at the Institute for Agricultural Research Farm during the 1995/96 and 1996/97 irrigation seasons of November to March. The data collected from the field experiments during the 1995/96 planting season were used to calibrate the models and their stress sensitivity factors estimated for four selected growth stages of the wheat crop. The ability of the model to predict grain yield of wheat with the estimated stress sensitivity factors was evaluated by comparing predicted grain yields by each model with those obtained in the field during the 1996/97 season. The three models performed fairly well in predicting grain yields, as the predicted results were not significantly different from the field measured grain yield at 5% level of significance.

  10. Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

    Science.gov (United States)

    Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; hide

    2017-01-01

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the

  11. A GUIDED SWAT MODEL APPLICATION ON SEDIMENT YIELD MODELING IN PANGANI RIVER BASIN: LESSONS LEARNT

    Directory of Open Access Journals (Sweden)

    Preksedis Marco Ndomba

    2008-12-01

    Full Text Available The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB, the Nyumba Ya Mungu (NYM reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977–1982 of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977–1988 daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005 rating curve. A long-term period over 37 years (i.e. 1969–2005 simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.

  12. A GUIDED SWAT MODEL APPLICATION ON SEDIMENT YIELD MODELING IN PANGANI RIVER BASIN: LESSONS LEARNT

    Directory of Open Access Journals (Sweden)

    Preksedis M. Ndomba

    2008-01-01

    Full Text Available The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB, the Nyumba Ya Mungu (NYM reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977¿1982 of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977-1988 daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005 rating curve. A long-term period over 37 years (i.e. 1969-2005 simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.

  13. Comparison of HSPF and SWAT models performance for runoff and sediment yield prediction.

    Science.gov (United States)

    Im, Sangjun; Brannan, Kevin M; Mostaghimi, Saied; Kim, Sang Min

    2007-09-01

    A watershed model can be used to better understand the relationship between land use activities and hydrologic/water quality processes that occur within a watershed. The physically based, distributed parameter model (SWAT) and a conceptual, lumped parameter model (HSPF), were selected and their performance were compared in simulating runoff and sediment yields from the Polecat Creek watershed in Virginia, which is 12,048 ha in size. A monitoring project was conducted in Polecat Creek watershed during the period of October 1994 to June 2000. The observed data (stream flow and sediment yield) from the monitoring project was used in the calibration/validations of the models. The period of September 1996 to June 2000 was used for the calibration and October 1994 to December 1995 was used for the validation of the models. The outputs from the models were compared to the observed data at several sub-watershed outlets and at the watershed outlet of the Polecat Creek watershed. The results indicated that both models were generally able to simulate stream flow and sediment yields well during both the calibration/validation periods. For annual and monthly loads, HSPF simulated hydrologic and sediment yield more accurately than SWAT at all monitoring sites within the watershed. The results of this study indicate that both the SWAT and HSPF watershed models performed sufficiently well in the simulation of stream flow and sediment yield with HSPF performing moderately better than SWAT for simulation time-steps greater than a month.

  14. Structural Equation Model as a Tool to Assess the Relationship Between Grain Yield Per Plant and Yield Components in Doubled Haploid Spring Barley Lines (Hordeum vulgare L.

    Directory of Open Access Journals (Sweden)

    Mańkowski Dariusz R.

    2016-06-01

    Full Text Available The aim of this study was to describe and characterize the relationships between yielding factors and grain yield per doubled haploid (DH plant of spring barley as well as relation between yield components and duration of each stage of plant development. To describe these relations structure equation modeling was used. The study included plants of doubled haploid spring barley lines (Hordeum vulgare L. derived from two-rowed form of Scarlett cultivar. The SAS® system was used to analyze the model of relationships between grain yield per plant and yield components. Our results indicate that the number of spikes per plant and grain yield per spike had a direct and decisive influence on the grain yield of the investigated DH plants of spring barley. Based on the path model analysis it was found that the most important factor determining grain yield per DH plants of spring barley was the number of spikes per plant and the duration of tillering and shooting stages.

  15. Potential of Cowpea Variety Mixtures to Increase Yield Stability in Subsistence Agriculture: Preliminary Results

    Directory of Open Access Journals (Sweden)

    Joshua S. Okonya

    2014-01-01

    Full Text Available Cowpea Vigna unguiculata (L. Walp. is an important leafy vegetable and grain legume in Uganda. Unlike in commercial agriculture, where variety mixtures are known to give higher and more stable yields, the performance of cowpea variety mixtures in subsistence agriculture is little known. Mixtures containing up to four cowpea varieties were subjected to all possible 2-way, 3-way, and 4-way combinations. These cowpea varieties and mixtures were grown at three locations in Soroti and Kumi districts in order to assess the relative mixture effect, defined as: Mixture effect (% = (mixture yield − pure line component average/pure line component average × 100. Yield data was subjected to one-way ANOVA using the GLM procedure of SYSTAT. PLABSTAT was used to generate ecovalence (Wi values as a measure of stability with low ecovalence values indicating higher stability. The total cowpea dry matter (DM yield was in the range of  3.7–6.7 g/m2 (leaf and 12.1–36.7 g/m2 (grain, respectively. Mixture effects were between  −9.3–14.0% (leaf and −30.3–21.9% (grain. Yield stability spanned  Wi = 0.06–5.30 (leaf and Wi = 4.45–894.84 (grain. The results suggested that yields of cowpea variety mixtures grown in marginal environments were more stable than of single varieties but not all mixtures yielded more than single varieties.

  16. Biomass yield and modeling of logging residues of Terminalia ...

    African Journals Online (AJOL)

    The use of Dbh as an independent variable in the prediction of models for estimating the biomass residues of the tree species was adjudged best because it performed well. The validation results showed that the selected models satisfied the assumptions of regression analysis. The practical implication of the models is that ...

  17. Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota.

    Energy Technology Data Exchange (ETDEWEB)

    Portone, Teresa; Niederhaus, John Henry; Sanchez, Jason James; Swiler, Laura Painton

    2018-02-01

    This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

  18. Estimating crop yield using a satellite-based light use efficiency model

    DEFF Research Database (Denmark)

    Yuan, Wenping; Chen, Yang; Xia, Jiangzhou

    2016-01-01

    for simulating crops’ GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation......Satellite-based techniques that provide temporally and spatially continuous information over vegetated surfaces have become increasingly important in monitoring the global agriculture yield. In this study, we examine the performance of a light use efficiency model (EC-LUE) for simulating the gross...... primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model...

  19. Regression models for estimating charcoal yield in a Eucalyptus ...

    African Journals Online (AJOL)

    ... dbh2H, and the product of dbh and merchantable height [(dbh)MH] as independent variables. Results of residual analysis showed that the models satisfied all the assumptions of regression analysis. Keywords: Models, charcoal production, biomass, Eucalyptus, arid, anergy, allometric. Bowen Journal of Agriculture Vol.

  20. Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts

    NARCIS (Netherlands)

    Wit, de A.J.W.; Diepen, van C.A.

    2007-01-01

    Uncertainty in spatial and temporal distribution of rainfall in regional crop yield simulations comprises a major fraction of the error on crop model simulation results. In this paper we used an Ensemble Kalman filter (EnKF) to assimilate coarse resolution satellite microwave sensor derived soil

  1. Statistics-based model for prediction of chemical biosynthesis yield from Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Leonard Effendi

    2011-06-01

    Full Text Available Abstract Background The robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability. Results Based on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0; 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value Saccharomyces cerevisiae has historically evolved for robust alcohol fermentation. Conclusions We generated simple mathematical models for first-order approximation of chemical production yield from S. cerevisiae. These linear models provide empirical insights to the effects of strain engineering and cultivation conditions toward biosynthetic efficiency. These models may not only provide guidelines for metabolic engineers to synthesize desired products, but also be useful to compare the

  2. Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

    Science.gov (United States)

    Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

    2018-04-01

    Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

  3. Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model

    Directory of Open Access Journals (Sweden)

    W. O. Nyang’au

    2014-01-01

    Full Text Available Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from each irrigation scheme and their farms were used as research fields. Daily maximum and minimum temperatures and precipitation were collected from the weather station in each of the irrigation schemes while daily solar radiation was generated using weatherman in the DSSAT shell. The study revealed that increase in both maximum and minimum temperatures affects Basmati 370 and IR 2793-80-1 grain yield under SRI. Increase in atmospheric CO2 concentration led to an increase in grain yield for both Basmati and IR 2793-80-1 under SRI and increase in solar radiation also had an increasing impact on both Basmati 370 and IR 2793-80-1 grain yield. The results of the study therefore show that weather conditions in Kenya affect rice yield under SRI and should be taken into consideration to improve food security.

  4. [Climate change impacts on yield of Cordyceps sinensis and research on yield prediction model of C. sinensis].

    Science.gov (United States)

    Zhu, Shou-Dong; Huang, Lu-Qi; Guo, Lan-Ping; Ma, Xing-Tian; Hao, Qing-Xiu; Le, Zhi-Yong; Zhang, Xiao-Bo; Yang, Guang; Zhang, Yan; Chen, Mei-Lan

    2017-04-01

    Cordyceps sinensis is a Chinese unique precious herbal material, its genuine producing areas covering Naqu, Changdu in Qinghai Tibet Plateau, Yushu in Qinghai province and other regions. In recent 10 years, C. sinensis resources is decreasing as a result of the blindly and excessively perennial dug. How to rationally protect, develop and utilize of the valuable resources of C. sinensis has been referred to an important field of research on C. sinensis. The ecological environment and climate change trend of Qinghai Tibet plateau happens prior to other regions, which means that the distribution and evolution of C. sinensis are more obvious and intense than those of the other populations. Based on RS (remote sensing)/GIS(geographic information system) technology, this paper utilized the relationship between the snowline elevation, the average temperature, precipitation and sunshine hours in harvest period (April and may) of C. sinensis and the actual production of C. sinensis to establish a weighted geometric mean model. The model's prediction accuracy can reach 82.16% at least in forecasting C. sinensis year yield in Naqu area in every early June. This study can provide basic datum and information for supporting the C. sinensis industry healthful, sustainable development. Copyright© by the Chinese Pharmaceutical Association.

  5. Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

    Science.gov (United States)

    Drewniak, B.

    2017-12-01

    Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical

  6. Getting water right: A case study in water yield modelling based on precipitation data.

    Science.gov (United States)

    Pessacg, Natalia; Flaherty, Silvia; Brandizi, Laura; Solman, Silvina; Pascual, Miguel

    2015-12-15

    Water yield is a key ecosystem service in river basins and especially in dry regions around the World. In this study we carry out a modelling analysis of water yields in the Chubut River basin, located in one of the driest districts of Patagonia, Argentina. We focus on the uncertainty around precipitation data, a driver of paramount importance for water yield. The objectives of this study are to: i) explore the spatial and numeric differences among six widely used global precipitation datasets for this region, ii) test them against data from independent ground stations, and iii) explore the effects of precipitation data uncertainty on simulations of water yield. The simulations were performed using the ecosystem services model InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) with each of the six different precipitation datasets as input. Our results show marked differences among datasets for the Chubut watershed region, both in the magnitude of precipitations and their spatial arrangement. Five of the precipitation databases overestimate the precipitation over the basin by 50% or more, particularly over the more humid western range. Meanwhile, the remaining dataset (Tropical Rainfall Measuring Mission - TRMM), based on satellite measurements, adjusts well to the observed rainfall in different stations throughout the watershed and provides a better representation of the precipitation gradient characteristic of the rain shadow of the Andes. The observed differences among datasets in the representation of the rainfall gradient translate into large differences in water yield simulations. Errors in precipitation of +30% (-30%) amplify to water yield errors ranging from 50 to 150% (-45 to -60%) in some sub-basins. These results highlight the importance of assessing uncertainties in main input data when quantifying and mapping ecosystem services with biophysical models and cautions about the undisputed use of global environmental datasets. Copyright

  7. Reverse transcription using random pentadecamer primers increases yield and quality of resulting cDNA

    DEFF Research Database (Denmark)

    Stangegaard, Michael; Dufva, I.H.; Dufva, Hans Martin

    2006-01-01

    Reverse transcription of RNA is an invaluable method for gene expression analysis by real-time PCR or microarray methods. Random primers of varying lengths were compared with respect to their efficiency of priming reverse transcription reactions. The results showed that l5-nucleotide-long random...... that random pentadecamers can replace random hexamers in reverse transcription reactions on both poly(A) RNA and amplified RNA, resulting in higher cDNA yields and quality....... with cDNA generated with random hexamers. The increased efficiency of priming using random pentadecamers resulted in reverse transcription of > 80% of the template aRNA, while random hexamers induced reverse transcription of only 40% of the template aRNA. This suggests a better coverage...

  8. Simulating the potential yield and yield gaps of sugar beet due to water and nitrogen limitations in Khorasan province using SUCROS model

    Directory of Open Access Journals (Sweden)

    R Deihimfard

    2015-12-01

    -specific parameters, and crop management information. Soil water module was used to determine soil water balance under water-limited conditions. Some questionnaires were then sent to extension agents to obtain information from the main sugar beet producing fields in each location. Results and discussion The SUCROSBEET model reasonably well predicted root yield across the study locations. The model could be used to simulate sugar beet yield under potential, water and nitrogen-limited situations. Simulation results of SUCROSBEET model showed that the lowest and highest sugar beet potential yield were obtained in Sabzevar (100 t.ha-1 and Neishaboor (137 t.ha-1, respectively. Total yield gap (the difference between potential and farmer’s yield ranged from 74 to 109 t.ha-1, in Sabzevar and Neishaboor, respectively. Despite the fact that most of the farms had been irrigated up to 20 times over seasons, there were still yield gap of an average 42 t.ha-1 due to water shortage. To reach the potential yield in the study locations, more than 2000 mm water is required in Sabsevar and Torbat-Jam and 1400 to 1500 mm in Ghoochan and Neishaboor, respectively. On average, to fill nitrogen-limited yield gap, 440 to 530 kg.ha-1 of nitrogen for sugar beet uptake are also required. However, the farmers in various locations have been able to apply only 50% of the sugar beet nitrogen demands during the past decade. The results of the current study also suggested that the farmer yields of about 16-48 t.ha-1in the irrigated locations across Khorasan province, were not constrained by low genetic yield potential. It is also needed to irrigate more than two times in some locations for reaching water-limited yield to potential one. Although there is a high potential for production of sugar beet (more than 130 t.ha-1, the ratio of yield production to water consumption (known as water productivity is not suitable in the study locations and production of sugar beet would not be cost-effective. Another issue which

  9. Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction

    Directory of Open Access Journals (Sweden)

    Alberto Gonzalez-Sanchez

    2014-01-01

    Full Text Available Efficient cropping requires yield estimation for each involved crop, where data-driven models are commonly applied. In recent years, some data-driven modeling technique comparisons have been made, looking for the best model to yield prediction. However, attributes are usually selected based on expertise assessment or in dimensionality reduction algorithms. A fairer comparison should include the best subset of features for each regression technique; an evaluation including several crops is preferred. This paper evaluates the most common data-driven modeling techniques applied to yield prediction, using a complete method to define the best attribute subset for each model. Multiple linear regression, stepwise linear regression, M5′ regression trees, and artificial neural networks (ANN were ranked. The models were built using real data of eight crops sowed in an irrigation module of Mexico. To validate the models, three accuracy metrics were used: the root relative square error (RRSE, relative mean absolute error (RMAE, and correlation factor (R. The results show that ANNs are more consistent in the best attribute subset composition between the learning and the training stages, obtaining the lowest average RRSE (86.04%, lowest average RMAE (8.75%, and the highest average correlation factor (0.63.

  10. Recent changes in county-level corn yield variability in the United States from observations and crop models

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Guoyong

    2017-12-01

    The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota, Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated

  11. Recent changes in county-level corn yield variability in the United States from observations and crop models.

    Science.gov (United States)

    Leng, Guoyong

    2017-12-31

    The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota, Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated

  12. Study on the Method of Grass Yield Model in the Source Region of Three Rivers with Multivariate Data

    International Nuclear Information System (INIS)

    You, Haoyan; Luo, Chengfeng; Liu, Zhengjun; Wang, Jiao

    2014-01-01

    This paper uses remote sensing and GIS technology to analyse the Source Region of Three Rivers (SRTR) to establish a grass yield estimation model during 2010 with remote sensing data, meteorological data, grassland type data and ground measured data. Analysis of the correlation between ground measured data, vegetation index based HJ-1A/B satellite data, meteorological data and grassland type data were used to establish the grass yield model. The grass yield model was studied by several statistical methods, such as multiple linear regression and Geographically Weighted Regression (GWR). The model's precision was validated. Finally, the best model to estimate the grass yield of Maduo County in SRTR was contrasted with the TM degraded grassland interpretation image of Maduo County from 2009. The result shows that: (1) Comparing with the multiple linear regression model, the GWR model gave a much better fitting result with the quality of fit increasing significantly from less than 0.3 to more than 0.8; (2) The most sensitive factors affecting the grass yield in SRTR were precipitation from May to August and drought index from May to August. From calculation of the five vegetation indices, MSAVI fitted the best; (3) The Maduo County grass yield estimated by the optimal model was consistent with the TM degraded grassland interpretation image, the spatial distribution of grass yield in Maduo County for 2010 showed a ''high south and low north'' pattern

  13. Water deficit effects on maize yields modeled under current and greenhouse climates

    International Nuclear Information System (INIS)

    Muchow, R.C.; Sinclair, T.R.

    1991-01-01

    The availability of water imposes one of the major limits on rainfed maize (Zea mays L.) productivity. This analysis was undertaken in an attempt to quantify the effects of limited water on maize growth and yield by extending a simple, mechanistic model in which temperature regulates crop development and intercepted solar radiation is used to calculate crop biomass accumulation. A soil water budget was incorporated into the model by accounting for inputs from rainfall and irrigation, and water use by soil evaporation and crop transpiration. The response functions of leaf area development and crop gas exchange to the soil water budget were developed from experimental studies. The model was used to interpret a range of field experiments using observed daily values of temperature, solar radiation, and rainfall or irrigation, where water deficits of varying durations developed at different stages of growth. The relative simplicity of the model and its robustness in simulating maize yields under a range of water-availability conditions allows the model to be readily used for studies of crop performance under alternate conditions. One such study, presented here, was a yield assessment for rainfed maize under possible greenhouse climates where temperature and atmospheric CO 2 concentration were increased. An increase in temperature combined with decreased rainfall lowered grain yield, although the increase in crop water use efficiency associated with elevated CO 2 concentration ameliorated the response to the greenhouse climate. Grain yields for the greenhouse climates as compared to current conditions increased, or decreased only slightly, except when the greenhouse climate was assumed to result in severly decreased rainfall

  14. Impact of parameter representation in gas-particle partitioning on aerosol yield model prediction

    Science.gov (United States)

    Kelly, Janya L.

    A kinetic box model is used to highlight the importance of parameter representation in predicting the formation of secondary organic aerosol (SOA) from the photo-oxidation of toluene through a subset of the University of Leeds Master Chemical Mechanism (MCM) version 3.1, and a kinetically based gas-particle partitioning approach. The model provides a prediction of the total aerosol yield and a tentative speciation of aerosols initialized from experimental data from York University's indoor smog chamber. A series of model sensitivity experiments were performed to study the relative importance of different parameters in SOA formation, with emphasis on vapour pressure, accommodation coefficient and NOx conditions. Early sensitivity experiments indicate vapour pressure to be a critical parameter in the partitioning and final aerosol yield. Current estimation methods are highly sensitive to boiling point temperature and can lead to the propagation of errors in the model. Of concern is the estimation of vapour pressure for compounds containing organic nitrates (major contributors to the aerosol speciation in this study). Results indicate that approximately +/- 80% error can be expected in the final aerosol mass from errors in the boiling point temperature and vapour pressure estimation methods, and, that for most experiments, this error alone cannot account for a general under prediction in the aerosol mass. Current experimental conditions dictate a very high initial NOx environment and a much higher final aerosol yield compared to other smog chamber studies, leading to the question of whether the model results arise from unique experimental conditions (relative to other chambers), from using different pathways in MCMv3.1 leading to different aerosol speciation (from the high NOx conditions), or from the physical representation of partitioning in the model. Results show that the choice of isopropyl nitrite as the hydroxyl radical oxidation source may be contributing to

  15. Models for predicting water use and crop yields - A Cuban experience

    International Nuclear Information System (INIS)

    Ruiz, M.E.; Utset, A.

    2004-01-01

    Modelling has come into agriculture because of several reasons: 1) More comprehension about the processes that take place at the soil water atmosphere continuum SWAC, 2) Specialists from different fields come to work together, 3) Different and more efficient codes for obtaining the solutions of complex equations were introduced, 4) Amazing development of hardware and supporting softwares, 5) Large data banks coming from a lot of years of experimental laboratory and field work (mainly at the developed countries) and 6) Desires to put together as much SWAC processes as possible to get a better comprehension of such a complex system. Here we briefly present some of the results obtained in Cuba using simulation model SWACROP for estimating water use and yields in potato and model SWAP for sugar cane yields. The relationship between estimated and measured soil moisture contents for two different irrigation treatments for potato in a Rhodic Ferralsol is shown. Simulated values matched better the measured values for the higher water level. Estimated and measured potato yields are shown. A determination coefficient of 0.69 was obtained for a 95 % of confidence limit. Although this value could be considered somewhat low, it should be remembered that the soil hydraulic properties used for the simulation were taken from the results of Ruiz and Utset (1992) for this kind of soil, but not determined at the same location where potato yields were measured. Moreover, all the data considering the different irrigation treatments were considered. For sugar cane, a calibration was made for a Rhodic Ferralsol. Later the model was tested for another location. The data of crop yields, seeding dates corresponding to three different soils were used for comparing with simulation results. The SWAP simulations agree with the measured data. However, when averaged values for the input parameters are used in the model, a determination coefficient between simulated and measured output was only 0

  16. Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

    Science.gov (United States)

    Fu, A.; Xue, Y.

    2017-12-01

    Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

  17. Development of a comprehensive watershed model applied to study stream yield under drought conditions

    Science.gov (United States)

    Perkins, S.P.; Sophocleous, M.

    1999-01-01

    We developed a model code to simulate a watershed's hydrology and the hydraulic response of an interconnected stream-aquifer system, and applied the model code to the Lower Republican River Basin in Kansas. The model code links two well-known computer programs: MODFLOW (modular 3-D flow model), which simulates ground water flow and stream-aquifer interaction; and SWAT (soil water assessment tool), a soil water budget simulator for an agricultural watershed. SWAT represents a basin as a collection of subbasins in terms of soil, land use, and weather data, and simulates each subbasin on a daily basis to determine runoff, percolation, evaporation, irrigation, pond seepages and crop growth. Because SWAT applies a lumped hydrologic model to each subbasin, spatial heterogeneities with respect to factors such as soil type and land use are not resolved geographically, but can instead be represented statistically. For the Republican River Basin model, each combination of six soil types and three land uses, referred to as a hydrologic response unit (HRU), was simulated with a separate execution of SWAT. A spatially weighted average was then taken over these results for each hydrologic flux and time step by a separate program, SWBAVG. We wrote a package for MOD-FLOW to associate each subbasin with a subset of aquifer grid cells and stream reaches, and to distribute the hydrologic fluxes given for each subbasin by SWAT and SWBAVG over MODFLOW's stream-aquifer grid to represent tributary flow, surface and ground water diversions, ground water recharge, and evapotranspiration from ground water. The Lower Republican River Basin model was calibrated with respect to measured ground water levels, streamflow, and reported irrigation water use. The model was used to examine the relative contributions of stream yield components and the impact on stream yield and base flow of administrative measures to restrict irrigation water use during droughts. Model results indicate that tributary

  18. Diagnosis of intramammary infection in samples yielding negative results or minor pathogens in conventional bacterial culturing.

    Science.gov (United States)

    Bexiga, Ricardo; Koskinen, Mikko T; Holopainen, Jani; Carneiro, Carla; Pereira, Helena; Ellis, Kathryn A; Vilela, Cristina L

    2011-02-01

    Up to half of quarter milk samples submitted for mastitis diagnosis are culture-negative results or lead to identification of coagulase-negative staphylococci or Corynebacterium bovis in conventional culturing, the so-called minor pathogens. The interpretation and usefulness of these results in terms of udder and animal health management is limited, even though the amount of resources spent is relatively high. This work aimed to test two methods of analysis of milk samples with the goal of increasing detection of intramammary pathogens. In the first study, 783 milk samples were processed in duplicate: before and after freezing at -20°C for 24 h, using standard bacteriological techniques. There was a significant difference between the two methods with samples frozen for 24 h yielding significantly fewer Gram-positive catalase-positive cocci, Gram-negative bacilli, Gram-positive bacilli and significantly more samples leading to no growth, than samples before freezing. The number of samples yielding Gram-positive catalase-negative cocci was not significantly affected by freezing. In the second study, a real-time PCR-based test was performed on milk samples with an individual quarter somatic cell count above 500,000 cells/ml that were either negative (n=51 samples) or that led to the isolation of minor pathogens in culturing: Corynebacterium bovis (n=79 samples) or non-aureus staphylococci (NAS, n=32). A mastitis pathogen, beyond the result obtained with standard bacteriology, was detected on 47% of the no-growth samples, on 35% of the samples from which C. bovis had been isolated and on 25% of the samples from which NAS had been isolated. The most commonly detected major pathogen was Escherichia coli, followed by Streptococcus uberis, Arcanobacterium pyogenes/Peptoniphilus indolicus and Streptococcus dysgalactiae. These results suggest that simply freezing milk samples for 24 h does not increase the detection of intramammary bacteria in milk samples and therefore

  19. Estimation of maize yield by using a process-based model and remote sensing data in the Northeast China Plain

    Science.gov (United States)

    Yao, Fengmei; Tang, Yanjing; Wang, Peijuan; Zhang, Jiahua

    Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

  20. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

    NARCIS (Netherlands)

    Li, T.; Hasegawa, T.; Yin, X.; Zhu, Y.; Boote, K.; Adam, M.; Bregaglio, S.; Buis, S.; Confalonieri, R.; Fumoto, T.; Gaydon, D.; Marcaida III, M.; Nakagawa, H.; Oriol, P.; Ruane, A.C.; Ruget, F.; Singh, B.; Singh, U.; Tang, L.; Yoshida, H.; Zhang, Z.; Bouman, B.

    2015-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We

  1. WFIRST: Integrated Coronagraph Design and Scientific Yield Modeling

    Science.gov (United States)

    Eldorado Riggs, A. J.; Nemati, Bijan; Gersh-Range, Jessica; Kasdin, Jeremy; Balasubramanian, Kunjithapatham; Krist, John; Ruane, Garreth; Sidick, Erkin

    2018-01-01

    The WFIRST Coronagraph Instrument (CGI) will be the first instrument to directly image cool gas giant exoplanets. To achieve its scientific goals of exoplanet imaging, exoplanet characterization, and circumstellar debris disk imaging, the CGI will carry both the shaped pupil coronagraph and hybrid Lyot coronagraph. Ongoing design work is focused on increasing the expected scientific yield by improving coronagraph performance (e.g., throughput or starlight suppression), robustness to observatory dynamics, and robustness to polarization aberrations. We present the design methodology, updated designs, and the evaluation process for choosing the designs with the highest scientific returns.

  2. Modelling of the parametric yield in decananometer SRAM-Arrays

    Directory of Open Access Journals (Sweden)

    Th. Fischer

    2006-01-01

    Full Text Available In today's decananometer (90 nm, 65 nm, ..., CMOS technologies variations of device parameters play an ever more important role. Due to the demand for low leakage systems, supply voltage is decreased on one hand and the transistor threshold voltage is increased on the other hand. This reduces the overdrive voltage of the transistors and leads to decreasing read and write security margins in static memories (SRAM. In addition, smaller dimensions of the devices lead to increasing variations of the device parameters, thus mismatch effects increase. It can be shown that local variations of the transistor parameters limit the functionality of circuits stronger than variations on a global scale or hard defects. We show a method to predict the yield for a large number of SRAM devices without time consuming Monte Carlo simulations in dependence of various parameters (Vdd, temperature, technology options, transistor dimensions, .... This helps the designer to predict the yield for various system options and transistor dimensions, to choose the optimal solution for a specific product.

  3. Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

    Science.gov (United States)

    Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

    2017-12-01

    Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

  4. Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

    Science.gov (United States)

    Cai, Y.

    2017-12-01

    Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

  5. A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Zeli [Pacific Northwest National Laboratory, Richland WA USA; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland WA USA; Li, Hongyi [Montana State University, Bozeman MT USA; Tesfa, Teklu [Pacific Northwest National Laboratory, Richland WA USA; Vanmaercke, Matthias [Département de Géographie, Université de Liège, Liege Belgium; Poesen, Jean [Department of Earth and Environmental Sciences, Division of Geography, KU Leuven, Leuven Belgium; Zhang, Xuesong [Pacific Northwest National Laboratory, Richland WA USA; Lu, Hui [Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing China; Hartmann, Jens [Institute for Geology, Center for Earth System Research and Sustainability, Universität Hamburg, Hamburg Germany

    2017-12-01

    Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1081 and 38 small catchments (0.1-200 km27 ), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.

  6. A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

    Science.gov (United States)

    Tan, Zeli; Leung, L. Ruby; Li, Hongyi; Tesfa, Teklu; Vanmaercke, Matthias; Poesen, Jean; Zhang, Xuesong; Lu, Hui; Hartmann, Jens

    2017-12-01

    Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1,081 and 38 small catchments (0.1-200 km2), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.

  7. Using hardness to model yield and tensile strength

    Energy Technology Data Exchange (ETDEWEB)

    Hawk, Jeffrey A.; Dogan, Omer N.; Schrems, Karol K.

    2005-02-01

    The current direction in hardness research is towards smaller and smaller loads as nano-scale materials are developed. There remains, however, a need to investigate the mechanical behavior of complex alloys for severe environment service. In many instances this entails casting large ingots and making numerous tensile samples as the bounds of the operating environment are explored. It is possible to gain an understanding of the tensile strength of these alloys using room and elevated temperature hardness in conjunction with selected tensile tests. The approach outlined here has its roots in the work done by Tabor for metals and low alloy and carbon steels. This research seeks to extend the work to elevated temperatures for multi-phase, complex alloys. A review of the approach will be given after which the experimental data will be examined. In particular, the yield stress and tensile strength will be compared to their corresponding hardness based values.

  8. Assessment of Potential Yield andClimate Change Sensitivity of Peanut Crop in Cagayan Valley, Philippines using DSSAT Simulation Model

    Science.gov (United States)

    Balderama, O. F.

    2013-12-01

    Peanut is a major upland crop in Cagayan Valley and a leguminous crop that requires less water and therefore, considered an important crop in improving productivity of upland and rainfed areas. However, little information is available on the potential productivity of the crop and analysis on the production constraints including climate change sensitivity. This study was aimed to determine yield potential and production constraints of peanut crop in Cagayan Valley through the use of Decision Support System for Agrotechnology Transfer (DSSAT) simulation modeling; analyze yield gaps between simulated and actual yield levels and to provide decision support to further optimize peanut production under climate change condition. Site of experiment for model calibration and validation was located on-station at Isabela State University, Echague, Isabela. Rainfall and other climatic variables were monitored using a HOBO weather station (Automatic Weather Station) which is strategically installed inside experimental zone.The inputs required to run the CSM model include information on soil and weather conditions, crop management practices and cultivar specific genetic coefficients. In the first step,a model calibration was conducted to determine the cultivar coefficients for certain peanut cultivar that are normally grown in Cagayan Valley. Crop growth and yield simulation modeling was undertaken using the Decision Support System for Agro-Technology Transfer (DSSAT) for small seeded peanut (Pn9). An evaluation of the CSM-CROPGRO-peanut model was performed with data sets from peanut experiment conducted from December 2011 to April 2012. The model was evaluated in the estimation of potential yield of peanut under rainfed condition and low-nitrogen application. Yield potential for peanut limited only by temperature and solar radiation and no-water and nutrient stress, ranged from 3274 to 4805 kg per hectare for six planting dates (October 1, October 15, November 1, November 15

  9. Model prediction of maize yield responses to climate change in ...

    African Journals Online (AJOL)

    Observed data of the last three decades (1971 to 2000) from several climatological stations in north-eastern Zimbabwe and outputs from several global climate models were used. The downscaled model simulations consistently predicted a warming of between 1 and 2 ºC above the baseline period (1971-2000) at most of ...

  10. Modeling of secondary organic aerosol yields from laboratory chamber data

    Directory of Open Access Journals (Sweden)

    M. N. Chan

    2009-08-01

    Full Text Available Laboratory chamber data serve as the basis for constraining models of secondary organic aerosol (SOA formation. Current models fall into three categories: empirical two-product (Odum, product-specific, and volatility basis set. The product-specific and volatility basis set models are applied here to represent laboratory data on the ozonolysis of α-pinene under dry, dark, and low-NOx conditions in the presence of ammonium sulfate seed aerosol. Using five major identified products, the model is fit to the chamber data. From the optimal fitting, SOA oxygen-to-carbon (O/C and hydrogen-to-carbon (H/C ratios are modeled. The discrepancy between measured H/C ratios and those based on the oxidation products used in the model fitting suggests the potential importance of particle-phase reactions. Data fitting is also carried out using the volatility basis set, wherein oxidation products are parsed into volatility bins. The product-specific model is most likely hindered by lack of explicit inclusion of particle-phase accretion compounds. While prospects for identification of the majority of SOA products for major volatile organic compounds (VOCs classes remain promising, for the near future empirical product or volatility basis set models remain the approaches of choice.

  11. Estimation of Winter Wheat Yield with the Assimilation of FY-3 MERSI Data into the WOFOST Crop Growth Model

    Science.gov (United States)

    Xu, Wenbo; Fan, Jinlong

    2014-11-01

    Taking the winter wheat planting area Taihang piedmont as object of the study, and based on WOFST model and FY Satellite 250m-resolution MERSI data, this article launched the assimilation yield estimation study on winter wheat. Firstly, MERSI-LAI data is inversed from the measured biophysics data and MERSI data of winter wheat in growing season within the study area; next, WOFOST model sensitivity analysis was developed and conduct assimilation yield estimation through MERSI-LAI built by SCE algorithm and the minimum cost function of model simulation LAI; finally, conduct comparison validation between the estimation results and MODIS-LAI assimilation yield estimation results as well as the statistical data. The conclusion has been drawn that the estimation accuracy based on FY-3 MERSI data assimilation is higher than that based on MODIS data assimilation, with the RMES being reduced by 750.20kg/ha, and the yield being closer to the statistics.

  12. Agro-climatic zonation of Khouzestan province based on potential yield of irrigated wheat using WOFOST model

    Directory of Open Access Journals (Sweden)

    M.H. Gharineh

    2016-05-01

    Full Text Available By application of climatic zoning methods, it is possible to study different agricultural aspects and then with harmony this aspects, determined similar states in a zone. Today, simulation models are widely used around the world in agricultural research and education and cropland management. Due to the vast extent of the agricultural activities in Iran, application of such models seems to be quite necessary for optimization objectives. The primary focus of this research was climatic zoning of Khouzestan region based on the results from wheat yield potential by means of WOFOST model. First, model performance and the accuracy of its results were evaluated. The findings showed that WOFOST model can adequately simulate phenological phases and grain and dry matter yields. The calculated Root Mean Square Error (RMSE values from blooming and physiologic maturity of crop were 1.97 per day and for seed and dry matter performances 810 and 810 kg ha-1, respectively. Also, one-to-one linear regression values for these stages were 0.96, 0.97, 0.93 and 0.91, respectively. The results of simulations indicated that the potentials of crop yield and the actual yield of farmlands are considerably different. Determination of the yield potentials of crop and its restricting factors were considered as the first step toward higher yield of crop. The results emphasized the fact that maximum and minimum yield potentials were found near the cities of Izeh (9247 kg. ha-1 and Shushtar (7538 kg. ha-1. A comparison of potential and actual crop yield trends revealed that the latter has been decreased might be due to the global warming phenomena resulting from green gases release into atmosphere while the increase of the farmer has been related to genetic modification of crop and management strategic. The results also showed that the poor yield of Mahshahr croplands (65.8% was because of unsuitable soil and high level ground water resources. The lowest performance was found in

  13. VEMAP 1: Selected Model Results

    Data.gov (United States)

    National Aeronautics and Space Administration — The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and...

  14. Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

    Science.gov (United States)

    Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

    2017-12-01

    Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the

  15. Evaluation of Precipitation Indices for Global Crop Modeling and Definition of Drought Response Function to Yields

    Science.gov (United States)

    Kaneko, D.

    2017-12-01

    Climate change initiates abnormal meteorological disasters. Drought causes climate instability, thus producing poor harvests because of low rates of photosynthesis and sterile pollination. This research evaluates drought indices regarding precipitation and includes this data in global geophysical crop models that concern with evaporation, stomata opening, advection-effects from sea surface temperature anomalies, photosynthesis, carbon partitioning, crop yields, and crop production. Standard precipitation index (SPI) is a useful tool because of related variable not used in the stomata model. However, SPI is not an adequate tool for drought in irrigated fields. Contrary to expectations, the global comparisons of spatial characteristics between stomata opening/evapotranspiration and SPI for monitoring continental crop extremes produced serious defects and obvious differences between evapotranspiration and the small stomata-opening phenomena. The reason for this is that SPI does not include surface air temperature in its analysis. The Penman equation (Epen) describes potential evaporation better than SPI for recent hot droughts caused by climate change. However, the distribution of precipitation is a necessary condition for crop monitoring because it affirms the trend of the dry results computed by crop models. Consequently, the author uses global precipitation data observed by microwave passive sensors on TRMM and GCOM-W satellites. This remote sensing data conveniently supplies spatial distributions of global and seasonal precipitation. The author has designed a model to measure the effects of drought on crop yield and the degree of stomata closure related to the photosynthesis rate. To determine yield effects, the drought injury function is defined by integrating stomata closure during the two seasons from flowering to pollination. The stomata, defined by ratio between Epen and Eac, reflect the effects of drought and irrigation. Stomata-closure model includes the

  16. A toy model for the yield of a tamped fission bomb

    Science.gov (United States)

    Reed, B. Cameron

    2018-02-01

    A simple expression is developed for estimating the yield of a tamped fission bomb, that is, a basic nuclear weapon comprising a fissile core jacketed by a surrounding neutron-reflecting tamper. This expression is based on modeling the nuclear chain reaction as a geometric progression in combination with a previously published expression for the threshold-criticality condition for such a core. The derivation is especially straightforward, as it requires no knowledge of diffusion theory and should be accessible to students of both physics and policy. The calculation can be set up as a single page spreadsheet. Application to the Little Boy and Fat Man bombs of World War II gives results in reasonable accord with published yield estimates for these weapons.

  17. VEMAP 1: Selected Model Results

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and...

  18. Planting data and wheat yield models. [Kansas, South Dakota, and U.S.S.R.

    Science.gov (United States)

    Feyerherm, A. M. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

  19. Data assimilation of MODIS and TM observations into CERES-Maize model to estimate regional maize yield

    Science.gov (United States)

    Jin, Huaan; Wang, Jindi; Bo, Yanchen; Chen, Guifen; Xue, Huazhu

    2010-08-01

    Accurate and real-time estimation of crop yield over large areas is critical for many applications such as crop management, and agricultural management decision-making. This study presents a scheme to assimilate multi-temporal MODIS and Landsat TM reflectance data into the CERES-Maize crop growth model which is coupled with the radiative transfer model SAIL for maize yield estimation. We extract the directional reflectance data of MODIS subpixels corresponding to pure maize conditions with the objective to increase time series observations at the TM scale. The variables to be assimilated were chosen by conducting the sensitivity analysis on the coupled model. The SCE-UA algorithm was applied to determine the optimal set of these sensitive variables. Finally the maize yields maps were produced at TM scale with the coupled assimilation model. The proposed scheme was applied over Yushu County located in Jilin province of Northeast China and validated by using field yield measurement dataset during the maize growing season in 2007. The measurement data include the species of planting maize, soil type and fertility, field observed leaf, canopy and soil reflectance data etc. Furthermore, yield data were gained in specially designed experimental campaigns. The validation results indicate that the yield estimation scheme using multiple remote sensing data assimilation is very promising. The accuracy of TM yield map produced by adding time series MODIS subpixel information was improved comparing with that only using TM data.

  20. Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008

    OpenAIRE

    Molenaars, Tomas K.; Reinerink, Nick H.; Hemminga, Marcus A.

    2013-01-01

    We define a parameter representing the relative forecast performance to compare forecasting results of different methods. By using this parameter, we analyze the performance of the dynamic Nelson-Siegel model and, for comparison, the first order autoregressive (AR(1)) model applied to a set of US bond yield data that covers a time span from November 1971 to December 2008. As a reference, we take the random walk model applied to the yield data. Our findings indicate that none of the models can...

  1. Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways

    Directory of Open Access Journals (Sweden)

    D. K. Henze

    2008-05-01

    Full Text Available Formation of SOA from the aromatic species toluene, xylene, and, for the first time, benzene, is added to a global chemical transport model. A simple mechanism is presented that accounts for competition between low and high-yield pathways of SOA formation, wherein secondary gas-phase products react further with either nitric oxide (NO or hydroperoxy radical (HO2 to yield semi- or non-volatile products, respectively. Aromatic species yield more SOA when they react with OH in regions where the [NO]/[HO2] ratios are lower. The SOA yield thus depends upon the distribution of aromatic emissions, with biomass burning emissions being in areas with lower [NO]/[HO2] ratios, and the reactivity of the aromatic with respect to OH, as a lower initial reactivity allows transport away from industrial source regions, where [NO]/[HO2] ratios are higher, to more remote regions, where this ratio is lower and, hence, the ultimate yield of SOA is higher. As a result, benzene is estimated to be the most important aromatic species with regards to global formation of SOA, with a total production nearly equal that of toluene and xylene combined. Global production of SOA from aromatic sources via the mechanisms identified here is estimated at 3.5 Tg/yr, resulting in a global burden of 0.08 Tg, twice as large as previous estimates. The contribution of these largely anthropogenic sources to global SOA is still small relative to biogenic sources, which are estimated to comprise 90% of the global SOA burden, about half of which comes from isoprene. Uncertainty in these estimates owing to factors ranging from the atmospheric relevance of chamber conditions to model deficiencies result in an estimated range of SOA production from aromatics of 2–12 Tg/yr. Though this uncertainty range affords a significant anthropogenic contribution to global SOA, it is evident from comparisons to recent observations that additional pathways for

  2. Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways

    Science.gov (United States)

    Henze, D. K.; Seinfeld, J. H.; Ng, N. L.; Kroll, J. H.; Fu, T.-M.; Jacob, D. J.; Heald, C. L.

    2008-05-01

    Formation of SOA from the aromatic species toluene, xylene, and, for the first time, benzene, is added to a global chemical transport model. A simple mechanism is presented that accounts for competition between low and high-yield pathways of SOA formation, wherein secondary gas-phase products react further with either nitric oxide (NO) or hydroperoxy radical (HO2) to yield semi- or non-volatile products, respectively. Aromatic species yield more SOA when they react with OH in regions where the [NO]/[HO2] ratios are lower. The SOA yield thus depends upon the distribution of aromatic emissions, with biomass burning emissions being in areas with lower [NO]/[HO2] ratios, and the reactivity of the aromatic with respect to OH, as a lower initial reactivity allows transport away from industrial source regions, where [NO]/[HO2] ratios are higher, to more remote regions, where this ratio is lower and, hence, the ultimate yield of SOA is higher. As a result, benzene is estimated to be the most important aromatic species with regards to global formation of SOA, with a total production nearly equal that of toluene and xylene combined. Global production of SOA from aromatic sources via the mechanisms identified here is estimated at 3.5 Tg/yr, resulting in a global burden of 0.08 Tg, twice as large as previous estimates. The contribution of these largely anthropogenic sources to global SOA is still small relative to biogenic sources, which are estimated to comprise 90% of the global SOA burden, about half of which comes from isoprene. Uncertainty in these estimates owing to factors ranging from the atmospheric relevance of chamber conditions to model deficiencies result in an estimated range of SOA production from aromatics of 2-12 Tg/yr. Though this uncertainty range affords a significant anthropogenic contribution to global SOA, it is evident from comparisons to recent observations that additional pathways for production of anthropogenic SOA still exist beyond those accounted

  3. A Study of Estimating Winter Wheat Yields by Using Satellite Data Assimilation with Crop Growth Model

    Science.gov (United States)

    Kuwata, K.

    2013-12-01

    Accurate information of crop yield is important for production planning in agriculture. Crop growth model is a effective tool to comprehend crop growth situation. Accordingly, we use the MOSIS data for two types of utilization to provide necessary information for DSSAT. The objective of this study is developing a method of estimating winter wheat yield without adequate information of the field. The first use is estimation of solar radiation, which is required as input data into DSSAT. Since MODIS is observing the earth everyday, solar radiation can be estimated in a region where a climate observation system is not developed. The second use is data assimilation that provides appropriate parameter of cultivation management to DSSAT. MODIS LAI and Dry Matter Production (DMP) estimated from MODIS GPP are assimilated into DSSAT. Before developing data assimilation, we have accomplished sensitivity analysis of DSSAT. As the result of the analysis, we found that planting date and amount of applied fertilizer have correlated strongly with LAI and Dry Matter (DM) for specific growth period. Based on the result, we estimated winter wheat yield by assimilating MODIS LAI and DMP observed during the specific period. In contrast, previous study estimated crop yield by assimilating satellite data observed for the whole growth period. Three different assimilation schemes were tested to verify the accuracy of our method. Our results showed that the estimated winter wheat yield agreed very well with the Japanese agricultural experiment station data. Among different assimilating scenarios, the best result was obtained when MODIS LAI and DMP observed for specific growth period; the Root Square Mean Error (RMSE) was 406.52 kg ha2. The distribution map of full year incident PAR in Asia. Estimated Winter Wheat Yield in Japan In the case 1, detail information gathered by experiment reports.In the case 2, all management parameters are determined by reference to cultivation manuals.In the

  4. Development of a remote sensing-based rice yield forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Mosleh, M.K.; Hassan, Q.K.; Chowdhury, E.H.

    2016-11-01

    This study aimed to develop a remote sensing-based method for forecasting rice yield by considering vegetation greenness conditions during initial and peak greenness stages of the crop; and implemented for “boro” rice in Bangladeshi context. In this research, we used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived two 16-day composite of normalized difference vegetation index (NDVI) images at 250 m spatial resolution acquired during the initial (January 1 to January 16) and peak greenness (March 23/24 to April 6/7 depending on leap year) stages in conjunction with secondary datasets (i.e., boro suitability map, and ground-based information) during 2007-2012 period. The method consisted of two components: (i) developing a model for delineating area under rice cultivation before harvesting; and (ii) forecasting rice yield as a function of NDVI. Our results demonstrated strong agreements between the model (i.e., MODIS-based) and ground-based area estimates during 2010-2012 period, i.e., coefficient of determination (R2); root mean square error (RMSE); and relative error (RE) in between 0.93 to 0.95; 30,519 to 37,451 ha; and ±10% respectively at the 23 district-levels. We also found good agreements between forecasted (i.e., MODIS-based) and ground-based yields during 2010-2012 period (R2 between 0.76 and 0.86; RMSE between 0.21 and 0.29 Mton/ha, and RE between -5.45% and 6.65%) at the 23 district-levels. We believe that our developments of forecasting the boro rice yield would be useful for the decision makers in addressing food security in Bangladesh. (Author)

  5. Sediment yield model implementation based on check dam infill stratigraphy in a semiarid Mediterranean catchment

    Directory of Open Access Journals (Sweden)

    G. Bussi

    2013-08-01

    Full Text Available Soil loss and sediment transport in Mediterranean areas are driven by complex non-linear processes which have been only partially understood. Distributed models can be very helpful tools for understanding the catchment-scale phenomena which lead to soil erosion and sediment transport. In this study, a modelling approach is proposed to reproduce and evaluate erosion and sediment yield processes in a Mediterranean catchment (Rambla del Poyo, Valencia, Spain. Due to the lack of sediment transport records for model calibration and validation, a detailed description of the alluvial stratigraphy infilling a check dam that drains a 12.9 km2 sub-catchment was used as indirect information of sediment yield data. These dam infill sediments showed evidences of at least 15 depositional events (floods over the time period 1990–2009. The TETIS model, a distributed conceptual hydrological and sediment model, was coupled to the Sediment Trap Efficiency for Small Ponds (STEP model for reproducing reservoir retention, and it was calibrated and validated using the sedimentation volume estimated for the depositional units associated with discrete runoff events. The results show relatively low net erosion rates compared to other Mediterranean catchments (0.136 Mg ha−1 yr−1, probably due to the extensive outcrops of limestone bedrock, thin soils and rather homogeneous vegetation cover. The simulated sediment production and transport rates offer model satisfactory results, further supported by in-site palaeohydrological evidences and spatial validation using additional check dams, showing the great potential of the presented data assimilation methodology for the quantitative analysis of sediment dynamics in ungauged Mediterranean basins.

  6. Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations.

    Directory of Open Access Journals (Sweden)

    Rebeca González-Cabaleiro

    Full Text Available The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors.

  7. Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations.

    Science.gov (United States)

    González-Cabaleiro, Rebeca; Lema, Juan M; Rodríguez, Jorge

    2015-01-01

    The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product) and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors.

  8. Fit of different functions to the individual deviations in random regression test day models for milk yield in dairy cattle

    Directory of Open Access Journals (Sweden)

    L.R. Schaeffer

    2010-04-01

    Full Text Available The shape of individual deviations of milk yield for dairy cattle from the fixed part of a random regression test day model (RRTDM was investigated. Data were 53,217 TD records for milk yield of 6,229 first lactation Canadian Holsteins in Ontario. Data were fitted with a model that included the fixed effects of herd-testdate, DIM interval nested within age and season of calving. Residuals of the model were then fitted with the following functions: Ali and Schaeffer 5 parameter model, fourth-order Legendre Polynomials, and cubic spline with three, four or five knots. Result confirm the great variability of shape that can be found when individual lactation are modeled. Cubic splines gave better fitting pe4rformances although together with a marked tendency to yield aberrant estimates at the edge of the lactation trajectory.

  9. A Model for Quantifying Sources of Variation in Test-day Milk Yield ...

    African Journals Online (AJOL)

    A cow's test-day milk yield is influenced by several systematic environmental effects, which have to be removed when estimating the genetic potential of an animal. The present study quantified the variation due to test date and month of test in test-day lactation yield records using full and reduced models. The data consisted ...

  10. System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

    Science.gov (United States)

    Pervin, Lia; Islam, Md Saiful

    2015-02-01

    The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

  11. Relevance of the Lin's and Host hydropedological models to predict grape yield and wine quality

    Directory of Open Access Journals (Sweden)

    E. A. C. Costantini

    2009-09-01

    Full Text Available The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI, and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing.

    The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW during

  12. Sustainable stemwood yield in relation to the nitrogen balance of forest plantations: a model analysis

    Energy Technology Data Exchange (ETDEWEB)

    Dewar, R. C.; McMurtrie, R. E. [New South Wales Univ., Sydney, NSW (Australia)

    1996-01-01

    An existing analytical model of stemwood growth in relation to nitrogen supply was used to examine the long-term effects of harvesting and fire on tree growth. Balance between nitrogen additions from a variety of sources, such as from deposition, fixation and fertilizer applications, and nitrogen losses from harvesting, regeneration burning, leaching and gaseous emissions, have been considered. Using a hypothetical set of parameters for Eucalyptus, it was concluded that nitrogen loss through fire is the main factor limiting sustainable yield. The analysis technique and the model can also be applied to a simulation of the effects of climate change, or to verifying results of sustainable forest growth obtained by using other models. 24 refs., 5 figs.

  13. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    Science.gov (United States)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2017-11-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  14. Modeling clicks beyond the first result page

    NARCIS (Netherlands)

    Chuklin, A.; Serdyukov, P.; de Rijke, M.

    2013-01-01

    Most modern web search engines yield a list of documents of a fixed length (usually 10) in response to a user query. The next ten search results are usually available in one click. These documents either replace the current result page or are appended to the end. Hence, in order to examine more

  15. Modeling the yield potential of dryland canola under current and future climates in California

    Science.gov (United States)

    George, N.; Kaffka, S.; Beeck, C.; Bucaram, S.; Zhang, J.

    2012-12-01

    -adapted canola varieties can be justified, and the potential value of a California canola industry both now and in the future. Winter annual crops like canola use rainfall in a Mediterranean climate like California more efficiently than spring or summer crops. Our results suggest that under current production costs and seed prices, dry farmed canola will have good potential in certain areas of the California. Canola yields decline with annual winter precipitation, however economically viable yields are still achieved at relatively precipitation levels (200 mm). Results from simulation, combined with related economic modeling (reported elsewhere) suggest that canola will be viable in a variety of production systems in the northern Sacramento Valley and some coastal locations, even under drier future climate scenarios. The in-field evaluation of Australian canola varieties should contribute to maintain or improving resource use efficiency and farm profitability.

  16. A distribution-free newsvendor model with balking penalty and random yield

    Directory of Open Access Journals (Sweden)

    Chongfeng Lan

    2015-05-01

    Full Text Available Purpose: The purpose of this paper is to extend the analysis of the distribution-free newsvendor problem in an environment of customer balking, which occurs when customers are reluctant to buy a product if its available inventory falls below a threshold level. Design/methodology/approach: We provide a new tradeoff tool as a replacement of the traditional one to weigh the holding cost and the goodwill costs segment: in addition to the shortage penalty, we also introduce the balking penalty. Furthermore, we extend our model to the case of random yield. Findings: A model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand. We also study the effects of shortage penalty and the balking penalty on the optimal order quantity, which have been largely bypassed in the existing distribution free single period models with balking. Numerical examples are presented to illustrate the result. Originality/value: The incorporation of balking penalty and random yield represents an important improvement in inventory policy performance for distribution-free newsvendor problem when customer balking occurs and the distributional form of demand is unknown.

  17. Modeling long-term yield trends of Miscanthusxgiganteus using experimental data from across Europe

    DEFF Research Database (Denmark)

    Lesur, Claire; Jeuffroy, Marie-Hélène; Makowski, David

    2013-01-01

    . giganteus is known to have an establishment phase during which annual yields increased as a function of crop age, followed by a ceiling phase, the duration of which is unknown. We built a database including 16 European long-term experiments (i) to describe the yield evolution during the establishment...... and the ceiling phases and (ii) to determine whether M. giganteus ceiling phase is followed by a decline phase where yields decrease across years. Data were analyzed through comparisons between a set of statistical growth models. The model that best fitted the experimental data included a decline phase...

  18. Modelling and computation in the valuation of carbon derivatives with stochastic convenience yields.

    Directory of Open Access Journals (Sweden)

    Shuhua Chang

    Full Text Available The anthropogenic greenhouse gas (GHG emission has risen dramatically during the last few decades, which mainstream researchers believe to be the main cause of climate change, especially the global warming. The mechanism of market-based carbon emission trading is regarded as a policy instrument to deal with global climate change. Although several empirical researches about the carbon allowance and its derivatives price have been made, theoretical results seem to be sparse. In this paper, we theoretically develop a mathematical model to price the CO2 emission allowance derivatives with stochastic convenience yields by the principle of absence of arbitrage opportunities. In the case of American options, we formulate the pricing problem to a linear parabolic variational inequality (VI in two spatial dimensions and develop a power penalty method to solve it. Then, a fitted finite volume method is designed to solve the nonlinear partial differential equation (PDE resulting from the power penalty method and governing the futures, European and American option valuation. Moreover, some numerical results are performed to illustrate the efficiency and usefulness of this method. We find that the stochastic convenience yield does effect the valuation of carbon emission derivatives. In addition, some sensitivity analyses are also made to examine the effects of some parameters on the valuation results.

  19. Modelling and Computation in the Valuation of Carbon Derivatives with Stochastic Convenience Yields

    Science.gov (United States)

    Chang, Shuhua; Wang, Xinyu

    2015-01-01

    The anthropogenic greenhouse gas (GHG) emission has risen dramatically during the last few decades, which mainstream researchers believe to be the main cause of climate change, especially the global warming. The mechanism of market-based carbon emission trading is regarded as a policy instrument to deal with global climate change. Although several empirical researches about the carbon allowance and its derivatives price have been made, theoretical results seem to be sparse. In this paper, we theoretically develop a mathematical model to price the CO2 emission allowance derivatives with stochastic convenience yields by the principle of absence of arbitrage opportunities. In the case of American options, we formulate the pricing problem to a linear parabolic variational inequality (VI) in two spatial dimensions and develop a power penalty method to solve it. Then, a fitted finite volume method is designed to solve the nonlinear partial differential equation (PDE) resulting from the power penalty method and governing the futures, European and American option valuation. Moreover, some numerical results are performed to illustrate the efficiency and usefulness of this method. We find that the stochastic convenience yield does effect the valuation of carbon emission derivatives. In addition, some sensitivity analyses are also made to examine the effects of some parameters on the valuation results. PMID:26010900

  20. Loss of cane and sugar yield resulting from Ceratovacuna lanigera Zehntner damage in cane-growing regions in China.

    Science.gov (United States)

    Li, W F; Zhang, R Y; Huang, Y K; Pu, C H; Yin, J; Cang, X Y; Shan, H L; Wang, X Y; Luo, Z M

    2018-02-01

    Ceratovacuna lanigera Zehntner is a major leaf pest of sugarcane. Widely distributed, it affects both the yield and quality of sugarcane in China. This study aimed to assess real yield and sugar yield losses, and the effect of C. lanigera damage on emergence of newly planted and ratoon cane under current production levels. Field experiments were carried out from 2014 to 2016 in Yunnan Province China. At maturity, plants were harvested and weighed to determine yield, and the effect on sugarcane quality and sucrose content analyzed. Real yield decreased by average of 46,185 kg hm-2 (range: 37,545-61,845 kg hm-2) in damaged versus undamaged areas, with an average yield loss rate of 35.9% (28.5-45.7%). Juice yield decreased by an average of 3.01% (2.4-4.13%) and sucrose content by 6.38% (5.48-8.16%). Juice brix decreased by an average of 7.66°BX (6.95-9.05°BX) and juice gravity purity by 12.35% (8.43-19.97%). In contrast, the reducing sugar content increased by an average of 1.21% (1.01-1.3%). Emergence rates of newly planted cane decreased by an average of 26.0% (24.7-27.3%). The emergence number of ratoon cane decreased by 66,834 hm2 (57,429-76,238 hm-2) and relative emergence loss rates of ratoon cane decreased by an average of 57.8% (57.6-58.0%). These findings confirm that C. lanigera damage severely affects sugarcane yield and quality in Yunnan Province. The results will help the implementation of effective control measures, thereby supporting sustainable development of the Chinese sugar industry.

  1. Defining Primary Care Shortage Areas: Do GIS-based Measures Yield Different Results?

    Science.gov (United States)

    Daly, Michael R; Mellor, Jennifer M; Millones, Marco

    2018-02-12

    To examine whether geographic information systems (GIS)-based physician-to-population ratios (PPRs) yield determinations of geographic primary care shortage areas that differ from those based on bounded-area PPRs like those used in the Health Professional Shortage Area (HPSA) designation process. We used geocoded data on primary care physician (PCP) locations and census block population counts from 1 US state to construct 2 shortage area indicators. The first is a bounded-area shortage indicator defined without GIS methods; the second is a GIS-based measure that measures the populations' spatial proximity to PCP locations. We examined agreement and disagreement between bounded shortage areas and GIS-based shortage areas. Bounded shortage area indicators and GIS-based shortage area indicators agree for the census blocks where the vast majority of our study populations reside. Specifically, 95% and 98% of the populations in our full and urban samples, respectively, reside in census blocks where the 2 indicators agree. Although agreement is generally high in rural areas (ie, 87% of the rural population reside in census blocks where the 2 indicators agree), agreement is significantly lower compared to urban areas. One source of disagreement suggests that bounded-area measures may "overlook" some shortages in rural areas; however, other aspects of the HPSA designation process likely mitigate this concern. Another source of disagreement arises from the border-crossing problem, and it is more prevalent. The GIS-based PPRs we employed would yield shortage area determinations that are similar to those based on bounded-area PPRs defined for Primary Care Service Areas. Disagreement rates were lower than previous studies have found. © 2018 National Rural Health Association.

  2. Assessing sediment yield in Kalaya gauged watershed (Northern Morocco using GIS and SWAT model

    Directory of Open Access Journals (Sweden)

    Hamza Briak

    2016-09-01

    Full Text Available An efficient design for erosion-control structures of any watershed in the world is entrusted with the delicate forecasting of sediment yields. These outlook yields are usually inferred by extrapolations from past observations. Because runoff, as the transporting vehicle, is more closely correlated with sediment yields than any other variable. So, calibration as well as validation of process-based hydrological models are two major processes while estimating the sediment yield in watershed. The actual survey is fulfilled with the aim of developing a trustworthy hydrologic model simulating stream flow discharge and sediment concentration with least uncertainty among the parameters picked out for calibration so as to verify the effect of the scenarios on the spatial distribution of sediment yield (sediments transported from sub-basins to the main channel during the step of time. Soil and Water Assessment Tool (SWAT, version 2012 model integrated with Geographic Information System (GIS, version 10.1 was used to simulate the stream flow and sediment concentration of Kalaya catchment situated in north of Morocco for the period from 1971 to 1993. Model calibration and validation were performed for monthly time periods using Sequential Uncertainty Fitting 2 (SUFI-2, version 2 within SWAT-CUP using 16 parameters. Our calibration outputs for monthly simulation for the period from 1976 to 1984 showed a good model performance for flow rates with NSE and PBIAS values of 0.76 and −11.80, respectively; also a good model performance for sediment concentration with NSE and PBIAS values of 0.69 and 7.12, respectively. Nonetheless, during validation period (1985–1993 for monthly time step, the NSE and PBIAS values were 0.67 and −14.44, respectively for flow rates and these statistical values were 0.70 and 15.51, respectively for sediment concentration; which also means a good model performance for both. Following calibration, the inclusive effect of each

  3. Modeling survival, yield, volume partitioning and their response to thinning for longleaf pine plantations

    Science.gov (United States)

    Carlos A. Gonzalez-Benecke; Salvador A. Gezan; Daniel J. Leduc; Timothy A. Martin; Wendell P. Cropper Jr; Lisa J Samuelson

    2012-01-01

    Longleaf pine (Pinus palustris Mill.) is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI) if dominant height (Hdom) and stand age are known (inversely, the model can project H

  4. Modelling of seed yield and its components in tall fescue ( Festuca ...

    African Journals Online (AJOL)

    Ridge regression analysis was used to derive a steady algorithmic model that related Z to the five components; Y1 to Y5. This model can estimate Z precisely from the values of these components. Furthermore, an approach based on the exponents of the algorithmic model could be applied to the selection for high seed yield ...

  5. Yield responses of crops to changes in environment and management practices: Model sensitivity analysis. II. Rice, wheat, and potato

    Science.gov (United States)

    Terjung, W. H.; Hayes, J. T.; O'Rourke, P. A.; Todhunter, P. E.

    1984-12-01

    This paper is a continuation of our prior examination of yield responses of maize (Terjung et al., 1984b). The analysis of the response of the model YIELD to changes in a variety of basic environmental and decision-making inputs was continued for paddy rice, winter wheat, and early potato. As before, temperature, solar radiation, and relative humidity regimes were analyzed during a growing season along with different water application strategies, irrigation frequencies, soil types, and wind regimes. Among the results, yield decreased on the average by 4.9% (rice) and 6.0% (wheat) per 1‡ (C) increase in air temperature. A 1% change in solar radiation resulted in an average of 1% (wheat) and 0.4% (rice) change in yield. Analogous changes in relative humidity caused yield changes of about 0.8% and nothing for wheat and rice, respectively. For all crops, the relationship between irrigation frequency and yield increase was near-linear for large irrigation intervals. This linearity vanished under high frequency waterings. With respect to irrigation amounts, 1 mm/ha of applied water was related, on the average, to 75 (potato), 19 (grain corn), 8 (rice), and 6 kg/ha (wheat) of harvestable yield.

  6. Model Identification and FE Simulations: Effect of Different Yield Loci and Hardening Laws in Sheet Forming

    International Nuclear Information System (INIS)

    Flores, P.; Lelotte, T.; Bouffioux, C.; El Houdaigui, F.; Habraken, A.M.; Duchene, L.; Bael, A. van; He, S.; Duflou, J.

    2005-01-01

    The bi-axial experimental equipment developed by Flores enables to perform Baushinger shear tests and successive or simultaneous simple shear tests and plane-strain tests. Such experiments and classical tensile tests investigate the material behavior in order to identify the yield locus and the hardening models. With tests performed on two steel grades, the methods applied to identify classical yield surfaces such as Hill or Hosford ones as well as isotropic Swift type hardening or kinematic Armstrong-Frederick hardening models are explained. Comparison with the Taylor-Bishop-Hill yield locus is also provided. The effect of both yield locus and hardening model choice will be presented for two applications: Single Point Incremental Forming (SPIF) and a cup deep drawing

  7. Model Identification and FE Simulations: Effect of Different Yield Loci and Hardening Laws in Sheet Forming

    Science.gov (United States)

    Flores, P.; Duchêne, L.; Lelotte, T.; Bouffioux, C.; El Houdaigui, F.; Van Bael, A.; He, S.; Duflou, J.; Habraken, A. M.

    2005-08-01

    The bi-axial experimental equipment developed by Flores enables to perform Baushinger shear tests and successive or simultaneous simple shear tests and plane-strain tests. Such experiments and classical tensile tests investigate the material behavior in order to identify the yield locus and the hardening models. With tests performed on two steel grades, the methods applied to identify classical yield surfaces such as Hill or Hosford ones as well as isotropic Swift type hardening or kinematic Armstrong-Frederick hardening models are explained. Comparison with the Taylor-Bishop-Hill yield locus is also provided. The effect of both yield locus and hardening model choice will be presented for two applications: Single Point Incremental Forming (SPIF) and a cup deep drawing.

  8. A Unified Model for the Prediction of Yield Strength in Particulate-Reinforced Metal Matrix Nanocomposites

    Directory of Open Access Journals (Sweden)

    F. A. Mirza

    2015-08-01

    Full Text Available Lightweighting in the transportation industry is today recognized as one of the most important strategies to improve fuel efficiency and reduce anthropogenic climate-changing, environment-damaging, and human death-causing emissions. However, the structural applications of lightweight alloys are often limited by some inherent deficiencies such as low stiffness, high wear rate and inferior strength. These properties could be effectively enhanced by the addition of stronger and stiffer reinforcements, especially nano-sized particles, into metal matrix to form composites. In most cases three common strengthening mechanisms (load-bearing effect, mismatch of coefficients of thermal expansion, and Orowan strengthening have been considered to predict the yield strength of metal matrix nanocomposites (MMNCs. This study was aimed at developing a unified model by taking into account the matrix grain size and porosity (which is unavoidable in the materials processing such as casting and powder metallurgy in the prediction of the yield strength of MMNCs. The Zener pinning effect of grain boundaries by the nano-sized particles has also been integrated. The model was validated using the experimental data of magnesium- and titanium-based nanocomposites containing different types of nano-sized particles (namely, Al2O3, Y2O3, and carbon nanotubes. The predicted results were observed to be in good agreement with the experimental data reported in the literature.

  9. Spatial Rice Yield Estimation Based on MODIS and Sentinel-1 SAR Data and ORYZA Crop Growth Model

    Directory of Open Access Journals (Sweden)

    Tri D. Setiyono

    2018-02-01

    Full Text Available Crop insurance is a viable solution to reduce the vulnerability of smallholder farmers to risks from pest and disease outbreaks, extreme weather events, and market shocks that threaten their household food and income security. In developing and emerging countries, the implementation of area yield-based insurance, the form of crop insurance preferred by clients and industry, is constrained by the limited availability of detailed historical yield records. Remote-sensing technology can help to fill this gap by providing an unbiased and replicable source of the needed data. This study is dedicated to demonstrating and validating the methodology of remote sensing and crop growth model-based rice yield estimation with the intention of historical yield data generation for application in crop insurance. The developed system combines MODIS and SAR-based remote-sensing data to generate spatially explicit inputs for rice using a crop growth model. MODIS reflectance data were used to generate multitemporal LAI maps using the inverted Radiative Transfer Model (RTM. SAR data were used to generate rice area maps using MAPScape-RICE to mask LAI map products for further processing, including smoothing with logistic function and running yield simulation using the ORYZA crop growth model facilitated by the Rice Yield Estimation System (Rice-YES. Results from this study indicate that the approach of assimilating MODIS and SAR data into a crop growth model can generate well-adjusted yield estimates that adequately describe spatial yield distribution in the study area while reliably replicating official yield data with root mean square error, RMSE, of 0.30 and 0.46 t ha−1 (normalized root mean square error, NRMSE of 5% and 8% for the 2016 spring and summer seasons, respectively, in the Red River Delta of Vietnam, as evaluated at district level aggregation. The information from remote-sensing technology was also useful for identifying geographic locations with

  10. Crop Rotational Effects on Yield Formation in Current Sugar Beet Production – Results From a Farm Survey and Field Trials

    Directory of Open Access Journals (Sweden)

    Heinz-Josef Koch

    2018-03-01

    Full Text Available In Europe, the framework for sugar beet (Beta vulgaris L. production was subject to considerable changes and for the future it is expected that sugar beet cultivation might concentrate around the sugar factories for economic reasons. Based on data from a national sugar beet farmers’ survey and multi-year crop rotation trials, the effects of cropping interval (number of years in between two subsequent sugar beet crops and of preceding crops on sugar yield were elucidated under current Central European management conditions. The dominating sugar beet cropping interval was ≥4 years in the farm survey with pronounced differences between regions. However, the cropping intervals 2, 3, and ≥4 years did not affect the sugar yield. Therefore, significant differences in sugar yield between regions were assumed to be caused by multiple interactions between year, site, and farmers’ skills. Throughout Germany, the dominating preceding crops in sugar beet cultivation were winter wheat (Triticum aestivum L. and winter barley (Hordeum vulgare L.. In the field trials, the sugar yield was 5% higher after pea (Pisum sativum L. compared to maize (Zea mays L. as preceding crop, while differences between the preceding crops pea and winter wheat, and wheat and maize were not significant. Repeated measurements of canopy development and leaf color during the growing season revealed a higher N-availability after pea as preceding crop. However, decreased growth after maize was not completely compensated for by high N-fertilizer doses. Overall, the causes for the differences in sugar yield between the preceding crops remained open. The results do not support concerns about substantial yield losses in sugar beet production due to a reduction in the cropping interval from 3 to 2 years. Nevertheless, short rotations with maize and sugar beet might increase the risk of Rhizoctonia solani crown and root rot infestation. Leguminous crops such as pea offer the potential

  11. Crop Rotational Effects on Yield Formation in Current Sugar Beet Production – Results From a Farm Survey and Field Trials

    Science.gov (United States)

    Koch, Heinz-Josef; Trimpler, Kerrin; Jacobs, Anna; Stockfisch, Nicol

    2018-01-01

    In Europe, the framework for sugar beet (Beta vulgaris L.) production was subject to considerable changes and for the future it is expected that sugar beet cultivation might concentrate around the sugar factories for economic reasons. Based on data from a national sugar beet farmers’ survey and multi-year crop rotation trials, the effects of cropping interval (number of years in between two subsequent sugar beet crops) and of preceding crops on sugar yield were elucidated under current Central European management conditions. The dominating sugar beet cropping interval was ≥4 years in the farm survey with pronounced differences between regions. However, the cropping intervals 2, 3, and ≥4 years did not affect the sugar yield. Therefore, significant differences in sugar yield between regions were assumed to be caused by multiple interactions between year, site, and farmers’ skills. Throughout Germany, the dominating preceding crops in sugar beet cultivation were winter wheat (Triticum aestivum L.) and winter barley (Hordeum vulgare L.). In the field trials, the sugar yield was 5% higher after pea (Pisum sativum L.) compared to maize (Zea mays L.) as preceding crop, while differences between the preceding crops pea and winter wheat, and wheat and maize were not significant. Repeated measurements of canopy development and leaf color during the growing season revealed a higher N-availability after pea as preceding crop. However, decreased growth after maize was not completely compensated for by high N-fertilizer doses. Overall, the causes for the differences in sugar yield between the preceding crops remained open. The results do not support concerns about substantial yield losses in sugar beet production due to a reduction in the cropping interval from 3 to 2 years. Nevertheless, short rotations with maize and sugar beet might increase the risk of Rhizoctonia solani crown and root rot infestation. Leguminous crops such as pea offer the potential for higher

  12. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  13. Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China.

    Science.gov (United States)

    Zhang, Jie; Balkovič, Juraj; Azevedo, Ligia B; Skalský, Rastislav; Bouwman, Alexander F; Xu, Guang; Wang, Jinzhou; Xu, Minggang; Yu, Chaoqing

    2018-06-15

    This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China. Copyright © 2018. Published by Elsevier B.V.

  14. A meteorologically-driven yield reduction model for spring and winter wheat

    Science.gov (United States)

    Ravet, F. W.; Cremins, W. J.; Taylor, T. W.; Ashburn, P.; Smika, D.; Aaronson, A. (Principal Investigator)

    1983-01-01

    A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.

  15. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

    OpenAIRE

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-01-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used in...

  16. Determinants of the Government Bond Yield in Spain: A Loanable Funds Model

    Directory of Open Access Journals (Sweden)

    Yu Hsing

    2015-07-01

    Full Text Available This paper applies demand and supply analysis to examine the government bond yield in Spain. The sample ranges from 1999.Q1 to 2014.Q2. The EGARCH model is employed in empirical work. The Spanish government bond yield is positively associated with the government debt/GDP ratio, the short-term Treasury bill rate, the expected inflation rate, the U.S. 10 year government bond yield and a dummy variable representing the debt crisis and negatively affected by the GDP growth rate and the expected nominal effective exchange rate.

  17. Modelling daily sediment yield from a meso-scale catchment, a case study in SW Poland

    Energy Technology Data Exchange (ETDEWEB)

    Keesstra, S. D.; Schoorl, J.; Temme, A. J. A. M.

    2009-07-01

    For management purposes it is important to be able to assess the sediment yield of a catchment. however, at this moment models designed for estimating sediment yield are only capable to give either very detailed storm-based information or year averages. The storm-based models require input data that are not available for most catchment. However, models that estimate yearly averages, ignore a lot of other detailed information, like daily discharge and precipitation data. There are currently no models available that model sediment yield on the temporal scale of one day and the spatial scale of a meso-scale catchment, without making use of very detailed input data. To fill this scientific and management gap, landscape evolution model LAPSUS has been adapted to model sediment yield on a daily basis. This model has the water balance as a base. To allow calibration with the discharge at the outlet, a subsurface flow module has been added to the model. (Author) 12 refs.

  18. Model of Yield Response of Corn to Plant Population and Absorption of Solar Energy

    OpenAIRE

    Overman, Allen R.; Scholtz, Richard V.

    2011-01-01

    Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha(-1) and g plant(-1)) on plant population (plants m(-2)). Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L.) grown in the United States. Data are analyzed with a simple exponential mathematical model ...

  19. Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?

    Directory of Open Access Journals (Sweden)

    Branislava Lalić

    2014-12-01

    Full Text Available The impact of adverse weather conditions (AWCs on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical (“event scenario” approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs.

  20. Identifying critical nitrogen application rate for maize yield and nitrate leaching in a Haplic Luvisol soil using the DNDC model.

    Science.gov (United States)

    Zhang, Yitao; Wang, Hongyuan; Liu, Shen; Lei, Qiuliang; Liu, Jian; He, Jianqiang; Zhai, Limei; Ren, Tianzhi; Liu, Hongbin

    2015-05-01

    Identification of critical nitrogen (N) application rate can provide management supports for ensuring grain yield and reducing amount of nitrate leaching to ground water. A five-year (2008-2012) field lysimeter (1 m × 2 m × 1.2 m) experiment with three N treatments (0, 180 and 240 kg Nha(-1)) was conducted to quantify maize yields and amount of nitrate leaching from a Haplic Luvisol soil in the North China Plain. The experimental data were used to calibrate and validate the process-based model of Denitrification-Decomposition (DNDC). After this, the model was used to simulate maize yield production and amount of nitrate leaching under a series of N application rates and to identify critical N application rate based on acceptable yield and amount of nitrate leaching for this cropping system. The results of model calibration and validation indicated that the model could correctly simulate maize yield and amount of nitrate leaching, with satisfactory values of RMSE-observation standard deviation ratio, model efficiency and determination coefficient. The model simulations confirmed the measurements that N application increased maize yield compared with the control, but the high N rate (240 kg Nha(-1)) did not produce more yield than the low one (120 kg Nha(-1)), and that the amount of nitrate leaching increased with increasing N application rate. The simulation results suggested that the optimal N application rate was in a range between 150 and 240 kg ha(-1), which would keep the amount of nitrate leaching below 18.4 kg NO₃(-)-Nha(-1) and meanwhile maintain acceptable maize yield above 9410 kg ha(-1). Furthermore, 180 kg Nha(-1) produced the highest yields (9837 kg ha(-1)) and comparatively lower amount of nitrate leaching (10.0 kg NO₃(-)-Nha(-1)). This study will provide a valuable reference for determining optimal N application rate (or range) in other crop systems and regions in China. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

    Science.gov (United States)

    Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

    2016-12-01

    The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas

  2. Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

    2012-12-01

    uptake of water (root profile), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients). We find that the optimal carboxylation rate and optimal photosynthesis temperature parameters contribute most to the uncertainty in NPP and GPP simulations whereas stomatal conductance is the most sensitive parameter controlling SH, followed by optimal photosynthesis temperature and optimal carboxylation rate. The spatial variation of the ranked correlation between input parameters and output variables is well explained by rain and temperature drivers, suggesting that climate mediated regionally different sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil.

  3. Crop yield and CO2 fixation monitoring over Asia by a photosynthetic-sterility model comparing with MODIS and carbon amounts in grain yields

    Science.gov (United States)

    Kaneko, Daijiro; Yang, Peng; Kumakura, Toshiro

    2009-08-01

    The authors have developed a photosynthesis crop model for grain production under the background of climate change and Asian economic growth in developing countries. This paper presents an application of the model to grain fields of paddy rice, winter wheat, and maize in China and Southeast Asia. The carbon hydrate in grains has the same chemical formula as that of cellulose in grain vegetation. The partitioning of carbon in grain plants can validate fixation amounts of computed carbon using a satellite-based photosynthesis model. The model estimates the photosynthesis fixation of rice reasonably in Japan and China. Results were validated through examination of carbon in grains, but the model tends to underestimate results for winter wheat and maize. This study also provides daily distributions of the PSN, which is the CO2 fixation in Asian areas combined with a land-cover distribution classified from MODIS data, NDVI from SPOT VEGETATION, and meteorological re-analysis data by European Centre for Medium-Range Forecasts (ECMWF). The mean CO2 and carbon fixation rates in paddy areas were 25.92 (t CO2/ha) and 5.28 (t/ha) in Japan, respectively. The method is based on routine observation data, enabling automated monitoring of crop yields.

  4. The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach

    DEFF Research Database (Denmark)

    Boldrini, Lorenzo; Hillebrand, Eric Tobias

    We study the forecast power of the yield curve for macroeconomic time series, such as consumer price index, personal consumption expenditures, producer price index, real disposable income, unemployment rate, and industrial production. We employ a state-space model in which the forecasting objective...... is included in the state vector. This amounts to an augmented dynamic factor model in which the factors (level, slope, and curvature of the yield curve) are supervised for the macroeconomic forecast target. In other words, the factors are informed about the dynamics of the forecast objective. The factor...... loadings have the Nelson and Siegel (1987) structure and we consider one forecast target at a time. We compare the forecasting performance of our specification to benchmark models such as principal components regression, partial least squares, and ARMA(p,q) processes. We use the yield curve data from G...

  5. MODELING OF YIELD AND QUALITY OF TABLE ROOT CROPS WITH THE USE OF DIFFERENT AGROTECHNICAL METHODS

    Directory of Open Access Journals (Sweden)

    S. M. Nadezhkin

    2017-01-01

    Full Text Available The effects of different fertilizer rates, irrigation, sowing rate for carrot and red beet were studied in the field condition in food-hills zone of Chechen Republic. The use of N40-80P40-80K40-80 caused the increase in yield from 22.8 to 30.8-33.2 t/ha or by 35-46%, when cultivating a carrot crop. Under irrigation the yield increases by 30-33%. Application of N40P40K40 and maintenance of soil moisture at 70% of moisture rate provoked the improvement in value, market and biochemical characteristics of roots; where the increased contents of dry matter, total sugar and vitamins were observed. The mathematical modeling for the process of yielding abilities and root quality in carrot and red beet showed that highest productivity can be achieved on chernozem soil at Central Pre-Caucasus zone when the level of mineral plant nutrition was N40-60P40-60K40-60. The further increment in fertilizer doses does not bring an improvement to yields and leads to decrease in quality of yields. The increased level of antecedent soil water moisture 70-75% of moisture rates does not raise the yield, on the contrary decreasing at the same time the root quality. The use of mathematical modeling enables to rationally define the fertilizer rates depending on application of irrigation and sowing rates in cultivation of carrot and red beet.

  6. A Modified Strip-Yield-Saturation-Induction Model Solution for Cracked Piezoelectromagnetic Plate

    Directory of Open Access Journals (Sweden)

    R. R. Bhargava

    2014-01-01

    Full Text Available A strip-yield-saturation-induction model is proposed for an impermeable crack embedded in piezoelectromagnetic plate. The developed slide-yield, saturation, and induction zones are arrested by distributing, respectively, mechanical, electrical, and magnetic loads over their rims. Two cases are considered: when saturation zone exceeds induction zone and vice-versa. It is assumed that developed slide-yield zone is the smallest because of the brittle nature of piezoelectromagnetic material. Fourier integral transform technique is employed to obtain the solution. Closed form analytic expressions are derived for developed zones lengths, crack sliding displacement, crack opening potential drop, crack opening induction drop, and energy release rate. Case study presented for BaTiO3–CoFe2O4 shows that crack arrest is possible under small-scale mechanical, electrical, and magnetic yielding.

  7. Assessments of Maize Yield Potential in the Korean Peninsula Using Multiple Crop Models

    Science.gov (United States)

    Kim, S. H.; Myoung, B.; Lim, C. H.; Lee, S. G.; Lee, W. K.; Kafatos, M.

    2015-12-01

    The Korean Peninsular has unique agricultural environments due to the differences in the political and socio-economical systems between the Republic of Korea (SK, hereafter) and the Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering from the lack of food supplies caused by natural disasters, land degradation and failed political system. The neighboring developed country SK has a better agricultural system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we have utilized multiple process-based crop models capable of regional-scale assessments to evaluate maize Yp over the Korean Peninsula - the GIS version of EPIC model (GEPIC) and APSIM model that can be expanded to regional scales (APSIM regions). First we evaluated model performance and skill for 20 years from 1991 to 2010 using reanalysis data (Local Data Assimilation and Prediction System (LDAPS); 1.5km resolution) and observed data. Each model's performances were compared over different regions within the Korean Peninsula of different regional climate characteristics. To quantify the major influence of individual climate variables, we also conducted a sensitivity test using 20 years of climatology. Lastly, a multi-model ensemble analysis was performed to reduce crop model uncertainties. The results will provide valuable information for estimating the climate change or variability impacts on Yp over the Korean Peninsula.

  8. Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

    Science.gov (United States)

    Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi

    2017-09-01

    Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

  9. Dependence of simulated positron emitter yields in ion beam cancer therapy on modeling nuclear fragmentation

    DEFF Research Database (Denmark)

    Lühr, Armin; Priegnitz, Marlen; Fiedler, Fine

    2014-01-01

    In ion beam cancer therapy, range verification in patients using positron emission tomography (PET) requires the comparison of measured with simulated positron emitter yields. We found that (1) changes in modeling nuclear interactions strongly affected the positron emitter yields and that (2) Monte...... Carlo simulations with SHIELD-HIT10A reasonably matched the most abundant PET isotopes 11C and 15O. We observed an ion-energy (i.e., depth) dependence of the agreement between SHIELD-HIT10A and measurement. Improved modeling requires more accurate measurements of cross-section values....

  10. Assimilation of Remotely Sensed Soil Moisture Profiles into a Crop Modeling Framework for Reliable Yield Estimations

    Science.gov (United States)

    Mishra, V.; Cruise, J.; Mecikalski, J. R.

    2017-12-01

    Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the

  11. Yield curve event tree construction for multi stage stochastic programming models

    DEFF Research Database (Denmark)

    Rasmussen, Kourosh Marjani; Poulsen, Rolf

    Dynamic stochastic programming (DSP) provides an intuitive framework for modelling of financial portfolio choice problems where market frictions are present and dynamic re--balancing has a significant effect on initial decisions. The application of these models in practice, however, is limited by...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....

  12. Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model

    Science.gov (United States)

    2014-09-01

    Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and... Basal Area Relationships of Open-Grown Southern Pines for Modeling Competition and Growth.” Canadian Journal of of Forest Research 22: 341–347... Forest Growth and Yield Model Co ns tr uc tio n En gi ne er in g R es ea rc h La bo ra to ry Scott A. Tweddale, Patrick J. Guertin, and

  13. Gun Shows and Gun Violence: Fatally Flawed Study Yields Misleading Results

    Science.gov (United States)

    Hemenway, David; Webster, Daniel; Pierce, Glenn; Braga, Anthony A.

    2010-01-01

    A widely publicized but unpublished study of the relationship between gun shows and gun violence is being cited in debates about the regulation of gun shows and gun commerce. We believe the study is fatally flawed. A working paper entitled “The Effect of Gun Shows on Gun-Related Deaths: Evidence from California and Texas” outlined this study, which found no association between gun shows and gun-related deaths. We believe the study reflects a limited understanding of gun shows and gun markets and is not statistically powered to detect even an implausibly large effect of gun shows on gun violence. In addition, the research contains serious ascertainment and classification errors, produces results that are sensitive to minor specification changes in key variables and in some cases have no face validity, and is contradicted by 1 of its own authors’ prior research. The study should not be used as evidence in formulating gun policy. PMID:20724672

  14. Gun shows and gun violence: fatally flawed study yields misleading results.

    Science.gov (United States)

    Wintemute, Garen J; Hemenway, David; Webster, Daniel; Pierce, Glenn; Braga, Anthony A

    2010-10-01

    A widely publicized but unpublished study of the relationship between gun shows and gun violence is being cited in debates about the regulation of gun shows and gun commerce. We believe the study is fatally flawed. A working paper entitled "The Effect of Gun Shows on Gun-Related Deaths: Evidence from California and Texas" outlined this study, which found no association between gun shows and gun-related deaths. We believe the study reflects a limited understanding of gun shows and gun markets and is not statistically powered to detect even an implausibly large effect of gun shows on gun violence. In addition, the research contains serious ascertainment and classification errors, produces results that are sensitive to minor specification changes in key variables and in some cases have no face validity, and is contradicted by 1 of its own authors' prior research. The study should not be used as evidence in formulating gun policy.

  15. Model of yield response of corn to plant population and absorption of solar energy.

    Science.gov (United States)

    Overman, Allen R; Scholtz, Richard V

    2011-01-31

    Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha(-1) and g plant(-1)) on plant population (plants m(-2)). Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L.) grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Y(m) (Mg ha(-1)) for maximum yield at high plant population and c (m(2) plant(-1)) for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, x(c) = 1/c (plants m(-2)). The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of x(c) were very similar for the three field studies with the same crop species.

  16. Model of yield response of corn to plant population and absorption of solar energy.

    Directory of Open Access Journals (Sweden)

    Allen R Overman

    Full Text Available Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha(-1 and g plant(-1 on plant population (plants m(-2. Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L. grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Y(m (Mg ha(-1 for maximum yield at high plant population and c (m(2 plant(-1 for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, x(c = 1/c (plants m(-2. The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of x(c were very similar for the three field studies with the same crop species.

  17. The Effects of Mixing, Reaction Rates, and Stoichiometry on Yield for Mixing Sensitive Reactions—Part I: Model Development

    Directory of Open Access Journals (Sweden)

    Syed Imran A. Shah

    2012-01-01

    Full Text Available There are two classes of mixing sensitive reactions: competitive-consecutive and competitive-parallel. The yield of desired product from these coupled reactions depends on how fast the reactants are brought together. Recent experimental results have suggested that the mixing effect may depend strongly on the stoichiometry of the reactions. To investigate this, a 1D, dimensionless, reaction-diffusion model at the micromixing scale was developed. Assuming constant mass concentration and mass diffusivities, systems of PDE's were derived on a mass fraction basis for both types of reactions. Two dimensionless reaction rate ratios and a single general Damköhler number emerged from the analysis. The resulting dimensionless equations were used to investigate the effects of mixing, reaction rate ratio, and reaction stoichiometry. As expected, decreasing either the striation thickness or the dimensionless rate ratio maximizes yield, the reaction stoichiometry has a considerable effect on yield, and all three variables interact strongly.

  18. Modelling crop yield, soil organic C and P under variable long-term fertilizer management in China

    Science.gov (United States)

    Zhang, Jie; Xu, Guang; Xu, Minggang; Balkovič, Juraj; Azevedo, Ligia B.; Skalský, Rastislav; Wang, Jinzhou; Yu, Chaoqing

    2016-04-01

    Phosphorus (P) is a major limiting nutrient for plant growth. P, as a nonrenewable resource and the controlling factor of aquatic entrophication, is critical for food security and human future, and concerns sustainable resource use and environmental impacts. It is thus essential to find an integrated and effective approach to optimize phosphorus fertilizer application in the agro-ecosystem while maintaining crop yield and minimizing environmental risk. Crop P models have been used to simulate plant-soil interactions but are rarely validated with scattered long-term fertilizer control field experiments. We employed a process-based model named Environmental Policy Integrated Climate model (EPIC) to simulate grain yield, soil organic carbon (SOC) and soil available P based upon 8 field experiments in China with 11 years dataset, representing the typical Chinese soil types and agro-ecosystems of different regions. 4 treatments, including N, P, and K fertilizer (NPK), no fertilizer (CK), N and K fertilizer (NK) and N, P, K and manure (NPKM) were measured and modelled. A series of sensitivity tests were conducted to analyze the sensitivity of grain yields and soil available P to sequential fertilizer rates in typical humid, normal and drought years. Our results indicated that the EPIC model showed a significant agreement for simulating grain yields with R2=0.72, index of agreement (d)=0.87, modeling efficiency (EF)=0.68, p<0.01 and SOC with R2=0.70, d=0.86, EF=0.59, and p<0.01. EPIC can well simulate soil available P moderately and capture the temporal changes in soil P reservoirs. Both of Crop yields and soil available were found more sensitive to the fertilizer P rates in humid than drought year and soil available P is closely linked to concentrated rainfall. This study concludes that EPIC model has great potential to simulate the P cycle in croplands in China and can explore the optimum management practices.

  19. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  20. Milk yield persistency in Brazilian Gyr cattle based on a random regression model.

    Science.gov (United States)

    Pereira, R J; Verneque, R S; Lopes, P S; Santana, M L; Lagrotta, M R; Torres, R A; Vercesi Filho, A E; Machado, M A

    2012-06-15

    With the objective of evaluating measures of milk yield persistency, 27,000 test-day milk yield records from 3362 first lactations of Brazilian Gyr cows that calved between 1990 and 2007 were analyzed with a random regression model. Random, additive genetic and permanent environmental effects were modeled using Legendre polynomials of order 4 and 5, respectively. Residual variance was modeled using five classes. The average lactation curve was modeled using a fourth-order Legendre polynomial. Heritability estimates for measures of persistency ranged from 0.10 to 0.25. Genetic correlations between measures of persistency and 305-day milk yield (Y305) ranged from -0.52 to 0.03. At high selection intensities for persistency measures and Y305, few animals were selected in common. As the selection intensity for the two traits decreased, a higher percentage of animals were selected in common. The average predicted breeding values for Y305 according to year of birth of the cows had a substantial annual genetic gain. In contrast, no improvement in the average persistency breeding value was observed. We conclude that selection for total milk yield during lactation does not identify bulls or cows that are genetically superior in terms of milk yield persistency. A measure of persistency represented by the sum of deviations of estimated breeding value for days 31 to 280 in relation to estimated breeding value for day 30 should be preferred in genetic evaluations of this trait in the Gyr breed, since this measure showed a medium heritability and a genetic correlation with 305-day milk yield close to zero. In addition, this measure is more adequate at the time of peak lactation, which occurs between days 25 and 30 after calving in this breed.

  1. Soil Erosion and Sediment Yield Modelling in the Pra River Basin of ...

    African Journals Online (AJOL)

    Parameters of the model were formatted as raster layers and multiplied using the raster calculator module in ArcGIS to produce a soil erosion map. The concept of sediment delivery ratio (SDR) was used to determine the annual sediment yield of the catchment by integrating a raster SDR layer with that of the soil erosion ...

  2. Development of Models for Predicting the Yield and Quality of Soymilk

    African Journals Online (AJOL)

    Models were developed to predict the yield and quality of soymilk, one of soybean products. The quality characteristics investigated were total solids, protein content and fat content. The processing parameters considered were Amount of water added during grinding per Kg of dry seed, AW; Blanching time, BT and Heating ...

  3. Crop growth modelling and crop yield forecasting using satellite derived meteorological inputs

    NARCIS (Netherlands)

    Wit, de A.J.W.; Diepen, van K.

    2006-01-01

    One of the key challenges for operational crop monitoring and yield forecasting using crop models is to find spatially representative meteorological input data. Currently, weather inputs are often interpolated from low density networks of weather stations or derived from output from coarse (0.5

  4. Bibliography of forest water yields, flooding issues, and the hydrologic modeling of extreme flood events

    Science.gov (United States)

    Mark H. Eisenbies; M.B. Adams; W. Michael Aust; James A. Burger

    2007-01-01

    Floods continue to cause significant damage in the United States and elsewhere, and questions about the causes of flooding continue to be debated. A significant amount of research has been conducted on the relationship between forest management activities and water yield, peak flows, and flooding; somewhat less research has been conducted on the modeling of these...

  5. Soil Erosion and Sediment Yield Modelling in the Pra River Basin of ...

    African Journals Online (AJOL)

    kusimi

    are applicable at catchment scale; event based; and continuous models of spatially and temporally distribution (i.e., 2D) (e.g., Amore et al., 2004; Fistikoglu ..... the integration of RUSLE into GIS give a vivid spatial dimension in soil erosion and sediment yield in the Pra Basin. Given the elements and processes prevailing in ...

  6. Climate Impacts on Chinese Corn Yields: A Fractional Polynomial Regression Model

    NARCIS (Netherlands)

    Kooten, van G.C.; Sun, Baojing

    2012-01-01

    In this study, we examine the effect of climate on corn yields in northern China using data from ten districts in Inner Mongolia and two in Shaanxi province. A regression model with a flexible functional form is specified, with explanatory variables that include seasonal growing degree days,

  7. Evolution Projects Yield Results

    Science.gov (United States)

    Sparks, Sarah D.

    2010-01-01

    When a federal court in 2005 rejected an attempt by the Dover, Pennsylvania, school board to introduce intelligent design as an alternative to evolution to explain the development of life on Earth, it sparked a renaissance in involvement among scientists in K-12 science instruction. Now, some of those teaching programs, studies, and research…

  8. Determining the Threshold Value of Basil Yield Reduction and Evaluation of Water Uptake Models under Salinity Stress Condition

    Directory of Open Access Journals (Sweden)

    M. Sarai Tabrizi

    2016-10-01

    by calculating statistical indices such as maximum error (ME, normalized root mean square error (nRMSE, modeling efficiency (EF, and coefficient of residual mass (CRM. At the end of the experiment, dry matter yield at the different treatments was measured and relative yield was calculated by dividing dry matter yield of treatments on dry matter yield at no stress treatment (control treatment. Leaching requirement in experimental treatments was calculated by Ayarset al., (2012 equation. Results and Discussion: The results indicated that Basil threshold value based on soil salinity was 2.25 dSm-1 with the yield reduction of 7.2% per dSm-1. The mathematical model of van Genuchten and Hoffman (1984 had a higher precision than other models in simulating Basil yield reduction function based on saturated soil extract salinity. The overall observations revealed that van Genuchten and Hoffman (1984, Steppuhnet al., (2005 and Homaeeet al., (2002 models were accurate for simulating Basil root water uptake and yield response to saturated soil extract salinity. Considering the presented results, it seems that among math-empirical models for salinity stress conditions, model of van Genuchten and Hoffman (1984 is more accurate than Maas and Hoffman (1977, Dirksen and Augustijn (1988 and Homaeeet al., (2002a models. The works of Green et al., (2006 and Skaggs et al., (2006 came to the same conclusion. Our work indicated that mostly statistical models have lower precision than math-empirical models. Steppuhn et al., (2005a reported that statistical models had the higher accuracy than math-empirical model of Maas and Hoffman (1977 and among statistical models, the modified Weibull model had the best fit on measured data which is in good agreement with the results of this study. Conclusion: The goals of this research were to evaluate Basil response to saturated soil extract salinity, to estimate threshold value of Basil crop coefficients, to obtain yield reduction gradient, and also to

  9. SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

    Science.gov (United States)

    Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

    2009-01-01

    This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

  10. Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models

    Science.gov (United States)

    Moore, Frances C.; Baldos, Uris Lantz C.; Hertel, Thomas

    2017-06-01

    A large number of studies have been published examining the implications of climate change for agricultural productivity that, broadly speaking, can be divided into process-based modeling and statistical approaches. Despite a general perception that results from these methods differ substantially, there have been few direct comparisons. Here we use a data-base of yield impact studies compiled for the IPCC Fifth Assessment Report (Porter et al 2014) to systematically compare results from process-based and empirical studies. Controlling for differences in representation of CO2 fertilization between the two methods, we find little evidence for differences in the yield response to warming. The magnitude of CO2 fertilization is instead a much larger source of uncertainty. Based on this set of impact results, we find a very limited potential for on-farm adaptation to reduce yield impacts. We use the Global Trade Analysis Project (GTAP) global economic model to estimate welfare consequences of yield changes and find negligible welfare changes for warming of 1 °C-2 °C if CO2 fertilization is included and large negative effects on welfare without CO2. Uncertainty bounds on welfare changes are highly asymmetric, showing substantial probability of large declines in welfare for warming of 2 °C-3 °C even including the CO2 fertilization effect.

  11. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

    Science.gov (United States)

    Khanali, Majid; Mobli, Hossein; Hosseinzadeh-Bandbafha, Homa

    2017-12-01

    In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R 2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for

  12. Modelling spatial and temporal variations of annual suspended sediment yields from small agricultural catchments.

    Science.gov (United States)

    Rymszewicz, A; Bruen, M; O'Sullivan, J J; Turner, J N; Lawler, D M; Harrington, J R; Conroy, E; Kelly-Quinn, M

    2018-04-01

    Estimates of sediment yield are important for ecological and geomorphological assessment of fluvial systems and for assessment of soil erosion within a catchment. Many regulatory frameworks, such as the Convention for the Protection of the Marine Environment of the North-East Atlantic, derived from the Oslo and Paris Commissions (OSPAR) require reporting of annual sediment fluxes. While they may be measured in large rivers, sediment flux is rarely measured in smaller rivers. Measurements of sediment transport at a national scale can be also challenging and therefore, sediment yield models are often utilised by water resource managers for the predictions of sediment yields in the ungauged catchments. Regression based models, calibrated to field measurements, can offer an advantage over complex and computational models due to their simplicity, easy access to input data and due to the additional insights into factors controlling sediment export in the study sites. While traditionally calibrated to long-term average values of sediment yields such predictions cannot represent temporal variations. This study addresses this issue in a novel way by taking account of the variation from year to year in hydrological variables in the developed models (using annual mean runoff, annual mean flow, flows exceeded in five percentage of the time (Q5) and seasonal rainfall estimated separately for each year of observations). Other parameters included in the models represent spatial differences influenced by factors such as soil properties (% poorly drained soils and % peaty soils), land-use (% pasture or % arable lands), channel slope (S1085) and drainage network properties (drainage density). Catchment descriptors together with year-specific hydrological variables can explain both spatial differences and inter-annual variability of suspended sediment yields. The methodology is demonstrated by deriving equations from Irish data-sets (compiled in this study) with the best model

  13. Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance

    Science.gov (United States)

    Raymond, G. M.; Bassingthwaighte, J. B.

    2016-01-01

    This is a practical example of a powerful research strategy: putting together data from studies covering a diversity of conditions can yield a scientifically sound grasp of the phenomenon when the individual observations failed to provide definitive understanding. The rationale is that defining a realistic, quantitative, explanatory hypothesis for the whole set of studies, brings about a “consilience” of the often competing hypotheses considered for individual data sets. An internally consistent conjecture linking multiple data sets simultaneously provides stronger evidence on the characteristics of a system than does analysis of individual data sets limited to narrow ranges of conditions. Our example examines three very different data sets on the clearance of salicylic acid from humans: a high concentration set from aspirin overdoses; a set with medium concentrations from a research study on the influences of the route of administration and of sex on the clearance kinetics, and a set on low dose aspirin for cardiovascular health. Three models were tested: (1) a first order reaction, (2) a Michaelis-Menten (M-M) approach, and (3) an enzyme kinetic model with forward and backward reactions. The reaction rates found from model 1 were distinctly different for the three data sets, having no commonality. The M-M model 2 fitted each of the three data sets but gave a reliable estimates of the Michaelis constant only for the medium level data (Km = 24±5.4 mg/L); analyzing the three data sets together with model 2 gave Km = 18±2.6 mg/L. (Estimating parameters using larger numbers of data points in an optimization increases the degrees of freedom, constraining the range of the estimates). Using the enzyme kinetic model (3) increased the number of free parameters but nevertheless improved the goodness of fit to the combined data sets, giving tighter constraints, and a lower estimated Km = 14.6±2.9 mg/L, demonstrating that fitting diverse data sets with a single model

  14. Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance.

    Science.gov (United States)

    Raymond, G M; Bassingthwaighte, J B

    This is a practical example of a powerful research strategy: putting together data from studies covering a diversity of conditions can yield a scientifically sound grasp of the phenomenon when the individual observations failed to provide definitive understanding. The rationale is that defining a realistic, quantitative, explanatory hypothesis for the whole set of studies, brings about a "consilience" of the often competing hypotheses considered for individual data sets. An internally consistent conjecture linking multiple data sets simultaneously provides stronger evidence on the characteristics of a system than does analysis of individual data sets limited to narrow ranges of conditions. Our example examines three very different data sets on the clearance of salicylic acid from humans: a high concentration set from aspirin overdoses; a set with medium concentrations from a research study on the influences of the route of administration and of sex on the clearance kinetics, and a set on low dose aspirin for cardiovascular health. Three models were tested: (1) a first order reaction, (2) a Michaelis-Menten (M-M) approach, and (3) an enzyme kinetic model with forward and backward reactions. The reaction rates found from model 1 were distinctly different for the three data sets, having no commonality. The M-M model 2 fitted each of the three data sets but gave a reliable estimates of the Michaelis constant only for the medium level data (K m = 24±5.4 mg/L); analyzing the three data sets together with model 2 gave K m = 18±2.6 mg/L. (Estimating parameters using larger numbers of data points in an optimization increases the degrees of freedom, constraining the range of the estimates). Using the enzyme kinetic model (3) increased the number of free parameters but nevertheless improved the goodness of fit to the combined data sets, giving tighter constraints, and a lower estimated K m = 14.6±2.9 mg/L, demonstrating that fitting diverse data sets with a single model

  15. Determining Rheological Parameters of Generalized Yield-Power-Law Fluid Model

    Directory of Open Access Journals (Sweden)

    Stryczek Stanislaw

    2004-09-01

    Full Text Available The principles of determining rheological parameters of drilling muds described by a generalized yield-power-law are presented in the paper. Functions between tangent stresses and shear rate are given. The conditions of laboratory measurements of rheological parameters of generalized yield-power-law fluids are described and necessary mathematical relations for rheological model parameters given. With the block diagrams, the methodics of numerical solution of these relations has been presented. Rheological parameters of an exemplary drilling mud have been calculated with the use of this numerical program.

  16. Applicability of multiple yield model to earthquake response analysis for foundation rock of large-scale structure

    International Nuclear Information System (INIS)

    Yoshinaka, Ryunoshin; Iwata, Naoki; Sasaki, Takeshi

    2012-01-01

    The authors are analyzed the large-scale structure build on the discontinuous rock foundation by earthquake response analysis with non-linear FEM considering the rock joint system using the actual earthquake record. The earthquake response analysis was performed by equivalent continuum finite element method as Multiple Yield Model (MYM) introducing cyclic loading elastic-plastic deformation characteristics of rock joints, and the analytical results were compared with the observed earthquake response. As a result, adequate modeling of discontinuities and appropriate setting of mechanical properties of rock and discontinuities give the good results corresponding with the observations. We confirmed the applicability of MYM to earthquake response. (author)

  17. Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Xiuliang Jin

    2016-11-01

    Full Text Available Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices to calibrate the AquaCrop model using the particle swarm optimization (PSO algorithm to improve biomass and yield estimations. Spectral reflectance and concurrent biomass and yield were measured at the Xiaotangshan experimental site in Beijing, China, during four winter wheat-growing seasons. The results showed that all of the measured spectral indices were correlated with biomass to varying degrees. The normalized difference matter index (NDMI was the best spectral index for estimating biomass, with the coefficient of determination (R2, root mean square error (RMSE, and relative RMSE (RRMSE values of 0.77, 1.80 ton/ha, and 25.75%, respectively. The data assimilation method (R2 = 0.83, RMSE = 1.65 ton/ha, and RRMSE = 23.60% achieved the most accurate biomass estimations compared with the spectral index method. The estimated yield was in good agreement with the measured yield (R2 = 0.82, RMSE = 0.55 ton/ha, and RRMSE = 8.77%. This study offers a new method for agricultural resource management through consistent assessments of winter wheat biomass and yield based on the AquaCrop model and remote sensing data.

  18. Creep-fatigue modelling in structural steels using empirical and constitutive creep methods implemented in a strip-yield model

    Science.gov (United States)

    Andrews, Benjamin J.

    The phenomena of creep and fatigue have each been thoroughly studied. More recently, attempts have been made to predict the damage evolution in engineering materials due to combined creep and fatigue loading, but these formulations have been strictly empirical and have not been used successfully outside of a narrow set of conditions. This work proposes a new creep-fatigue crack growth model based on constitutive creep equations (adjusted to experimental data) and Paris law fatigue crack growth. Predictions from this model are compared to experimental data in two steels: modified 9Cr-1Mo steel and AISI 316L stainless steel. Modified 9Cr-1Mo steel is a high-strength steel used in the construction of pressure vessels and piping for nuclear and conventional power plants, especially for high temperature applications. Creep-fatigue and pure creep experimental data from the literature are compared to model predictions, and they show good agreement. Material constants for the constitutive creep model are obtained for AISI 316L stainless steel, an alloy steel widely used for temperature and corrosion resistance for such components as exhaust manifolds, furnace parts, heat exchangers and jet engine parts. Model predictions are compared to pure creep experimental data, with satisfactory results. Assumptions and constraints inherent in the implementation of the present model are examined. They include: spatial discretization, similitude, plane stress constraint and linear elasticity. It is shown that the implementation of the present model had a non-trivial impact on the model solutions in 316L stainless steel, especially the spatial discretization. Based on these studies, the following conclusions are drawn: 1. The constitutive creep model consistently performs better than the Nikbin, Smith and Webster (NSW) model for predicting creep and creep-fatigue crack extension. 2. Given a database of uniaxial creep test data, a constitutive material model such as the one developed for

  19. Sustainable fisheries in shallow lakes: an independent empirical test of the Chinese mitten crab yield model

    Science.gov (United States)

    Wang, Haijun; Liang, Xiaomin; Wang, Hongzhu

    2017-07-01

    Next to excessive nutrient loading, intensive aquaculture is one of the major anthropogenic impacts threatening lake ecosystems. In China, particularly in the shallow lakes of mid-lower Changjiang (Yangtze) River, continuous overstocking of the Chinese mitten crab ( Eriocheir sinensis) could deteriorate water quality and exhaust natural resources. A series of crab yield models and a general optimum-stocking rate model have been established, which seek to benefit both crab culture and the environment. In this research, independent investigations were carried out to evaluate the crab yield models and modify the optimum-stocking model. Low percentage errors (average 47%, median 36%) between observed and calculated crab yields were obtained. Specific values were defined for adult crab body mass (135 g/ind.) and recapture rate (18% and 30% in lakes with submerged macrophyte biomass above and below 1 000 g/m2) to modify the optimum-stocking model. Analysis based on the modified optimum-stocking model indicated that the actual stocking rates in most lakes were much higher than the calculated optimum-stocking rates. This implies that, for most lakes, the current stocking rates should be greatly reduced to maintain healthy lake ecosystems.

  20. The Load Capacity Model and Experimental Tests of a New Yielding Steel Prop

    Directory of Open Access Journals (Sweden)

    Yanlong Chen

    2017-01-01

    Full Text Available As the mining depth increases year by year, the deformation and failure of deep roadway become more and more serious, and new support equipment with high supporting force and yieldable character is quite necessary for mining safety. In this research, a new yielding steel prop with high stable load capacity was introduced, which features sustaining large deformation in the field. Based on principle stress method and elastic-plastic theory, a mathematical model of load capacity was proposed for the new prop. The results show that the stable load capacity of the prop increases linearly with the increase of the effective number of the steel balls. Meanwhile, the stable load capacity of the prop increases initially and decreases afterwards with the increase of the radius of the steel ball. Under the fixed radius of the steel ball, the stable load capacity will increase with the decrease of the gap between the inner tube and the outer tube. The stable load capacity of the prop calculated using the theoretical model quantitatively agrees with that of the experimental tests, with only an error within 5%.

  1. Surrogate models for identifying robust, high yield regions of parameter space for ICF implosion simulations

    Science.gov (United States)

    Humbird, Kelli; Peterson, J. Luc; Brandon, Scott; Field, John; Nora, Ryan; Spears, Brian

    2016-10-01

    Next-generation supercomputer architecture and in-transit data analysis have been used to create a large collection of 2-D ICF capsule implosion simulations. The database includes metrics for approximately 60,000 implosions, with x-ray images and detailed physics parameters available for over 20,000 simulations. To map and explore this large database, surrogate models for numerous quantities of interest are built using supervised machine learning algorithms. Response surfaces constructed using the predictive capabilities of the surrogates allow for continuous exploration of parameter space without requiring additional simulations. High performing regions of the input space are identified to guide the design of future experiments. In particular, a model for the yield built using a random forest regression algorithm has a cross validation score of 94.3% and is consistently conservative for high yield predictions. The model is used to search for robust volumes of parameter space where high yields are expected, even given variations in other input parameters. Surrogates for additional quantities of interest relevant to ignition are used to further characterize the high yield regions. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, Lawrence Livermore National Security, LLC. LLNL-ABS-697277.

  2. Sustainable stemwood yield in relation to the nitrogen balance of forest plantations: a model analysis.

    Science.gov (United States)

    Dewar, Roderick C.; McMurtrie, Ross E.

    1996-01-01

    We used an existing analytical model of stemwood growth in relation to nitrogen supply, which we describe in an accompanying paper, to examine the long-term effects of harvesting and fire on tree growth. Our analysis takes into account the balance between nitrogen additions from deposition, fixation, and fertilizer applications, and nitrogen losses from stemwood harvesting, regeneration burning, leaching and gaseous emissions. Using a plausible set of parameter values for Eucalyptus, we conclude that nitrogen loss through fire is the main factor limiting sustainable yield, defined as the maximum mean annual stemwood volume increment obtained in the steady state, if management practices are continued indefinitely. The sustainable yield is 30 m(3) ha(-1) year(-1) with harvesting only, 15 m(3) ha(-1) year(-1) with harvesting and regeneration burning, and 13 m(3) ha(-1) year(-1) with harvesting, fire, leaching and gaseous emissions combined. Our approach uses a simple graphical analysis that provides a useful framework for examining the factors affecting sustainable yield. The graphical analysis is also useful for extending the application of the present model to the effects of climate change on sustainable yield, or for interpreting the behavior of other models of sustainable forest growth.

  3. Microplasticity of MMC. Experimental results and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Maire, E. (Groupe d' Etude de Metallurgie Physique et de Physique des Materiaux, INSA, 69 Villeurbanne (France)); Lormand, G. (Groupe d' Etude de Metallurgie Physique et de Physique des Materiaux, INSA, 69 Villeurbanne (France)); Gobin, P.F. (Groupe d' Etude de Metallurgie Physique et de Physique des Materiaux, INSA, 69 Villeurbanne (France)); Fougeres, R. (Groupe d' Etude de Metallurgie Physique et de Physique des Materiaux, INSA, 69 Villeurbanne (France))

    1993-11-01

    The microplastic behavior of several MMC is investigated by means of tension and compression tests. This behavior is assymetric : the proportional limit is higher in tension than in compression but the work hardening rate is higher in compression. These differences are analysed in terms of maxium of the Tresca's shear stress at the interface (proportional limit) and of the emission of dislocation loops during the cooling (work hardening rate). On another hand, a model is proposed to calculate the value of the yield stress, describing the composite as a material composed of three phases : inclusion, unaffected matrix and matrix surrounding the inclusion having a gradient in the density of the thermally induced dilocations. (orig.).

  4. A model independent determination of the B{yields}X{sub s}{gamma} decay rate

    Energy Technology Data Exchange (ETDEWEB)

    Bernlochner, Florian U. [Victoria Univ., BC (Canada); Lacker, Heiko [Humboldt-Universitaet, Berlin (Germany); Ligeti, Zoltan [California Univ., Berkeley, CA (United States). Ernest Orlando Lawrence Berkeley National Laboratory; Stewart, Iain W. [Massachusetts Institute of Technology, Cambridge, MA (United States). Center for Theoretical Physics; Tackmann, Frank J.; Tackmann, Kerstin [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2013-03-15

    The goal of the SIMBA collaboration is to provide a global fit to the available measurements of inclusive B{yields}X{sub s}{gamma} and B{yields}X{sub u}l{nu} decays. By performing a global fit one is able to simultaneously determine the relevant normalizations, i.e. the total B{yields}X{sub s}{gamma} rate and the CKM-matrix element vertical stroke Vub vertical stroke, together with the required hadronic parameters, most importantly the b-quark mass and the b-quark distribution function in the B-meson, called the shape function. In this talk, the current status on the model-independent determination of the shape function and vertical stroke C{sub 7}{sup incl}V{sub tb}V{sub ts}{sup *} vertical stroke, which parametrizes the total B{yields}X{sub s}{gamma} rate, from a global fit to the available B{yields}X{sub s}{gamma} measurements from Babar and Belle is presented. In particular, the theoretical uncertainties originating from variations of the different factorization scales are evaluated.

  5. Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

    Energy Technology Data Exchange (ETDEWEB)

    Andrews, Brett H. [PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260 (United States); Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A., E-mail: andrewsb@pitt.edu [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States)

    2017-02-01

    Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

  6. Low apparent quantum yield in Arctic plants suggests that terrestrial biosphere models will over estimate carbon assimilation at high latitudes

    Science.gov (United States)

    Rogers, A.; Serbin, S.; Ely, K.; Wullschleger, S.

    2017-12-01

    Estimates of Gross Primary Productivity (GPP) by terrestrial biosphere models (TBMs) rely on accurate model representation of photosynthesis. In the Arctic, TBM uncertainty over GPP is the dominant driver of an uncertain Arctic carbon cycle. Previously we have shown that TBMs underestimate light saturated photosynthesis due to poor model representation of maximum carboxylation capacity and maximum electron transport. Here we extend this work to investigate model representation of the response of photosynthesis to irradiance. TBMs use an empirical relationship, typically a non-rectangular hyperbola, to estimate potential electron transport rate from incident irradiance. The key model inputs used to parameterize this formulation are; absorptance, quantum yield, and a curvature factor. TBMs show a high divergence in the response of photosynthesis to irradiance driven in part by variation in these parameters. In addition, most existing measurements used to parameterize TBMs have been made within a narrow temperature range (20-30°C) and the scarcity of data collected at low temperature has been highlighted as an important driver of model uncertainty at high latitudes. To address this issue we measured photosynthetic light response curves at 5 and 15°C and the leaf optical properties of six species growing on the Barrow Environmental Observatory, Barrow, Alaska. We determined leaf absorbtance, the convexity term, and apparent quantum yield. Our key finding was that measured apparent quantum yield was lower than model estimates, particularly at 5°C. Our results show that TBMs that rely on relatively high theoretical estimates of apparent quantum yield will likely overestimate carbon assimilation at low temperature and low irradiance.

  7. Comparison of parametric, orthogonal, and spline functions to model individual lactation curves for milk yield in Canadian Holsteins

    Directory of Open Access Journals (Sweden)

    Corrado Dimauro

    2010-11-01

    Full Text Available Test day records for milk yield of 57,390 first lactation Canadian Holsteins were analyzed with a linear model that included the fixed effects of herd-test date and days in milk (DIM interval nested within age and calving season. Residuals from this model were analyzed as a new variable and fitted with a five parameter model, fourth-order Legendre polynomials, with linear, quadratic and cubic spline models with three knots. The fit of the models was rather poor, with about 30-40% of the curves showing an adjusted R-square lower than 0.20 across all models. Results underline a great difficulty in modelling individual deviations around the mean curve for milk yield. However, the Ali and Schaeffer (5 parameter model and the fourth-order Legendre polynomials were able to detect two basic shapes of individual deviations among the mean curve. Quadratic and, especially, cubic spline functions had better fitting performances but a poor predictive ability due to their great flexibility that results in an abrupt change of the estimated curve when data are missing. Parametric and orthogonal polynomials seem to be robust and affordable under this standpoint.

  8. Models and tests of optimal density and maximal yield for crop plants.

    Science.gov (United States)

    Deng, Jianming; Ran, Jinzhi; Wang, Zhiqiang; Fan, Zhexuan; Wang, Genxuan; Ji, Mingfei; Liu, Jing; Wang, Yun; Liu, Jianquan; Brown, James H

    2012-09-25

    We introduce a theoretical framework that predicts the optimum planting density and maximal yield for an annual crop plant. Two critical parameters determine the trajectory of plant growth and the optimal density, N(opt), where canopies of growing plants just come into contact, and competition: (i) maximal size at maturity, M(max), which differs among varieties due to artificial selection for different usable products; and (ii) intrinsic growth rate, g, which may vary with variety and environmental conditions. The model predicts (i) when planting density is less than N(opt), all plants of a crop mature at the same maximal size, M(max), and biomass yield per area increases linearly with density; and (ii) when planting density is greater than N(opt), size at maturity and yield decrease with -4/3 and -1/3 powers of density, respectively. Field data from China show that most annual crops, regardless of variety and life form, exhibit similar scaling relations, with maximal size at maturity, M(max), accounting for most of the variation in optimal density, maximal yield, and energy use per area. Crops provide elegantly simple empirical model systems to study basic processes that determine the performance of plants in agricultural and less managed ecosystems.

  9. Estimation of effects of photosynthesis response functions on rice yields and seasonal variation of CO2 fixation using a photosynthesis-sterility type of crop yield model

    International Nuclear Information System (INIS)

    Kaneko, D.; Moriwaki, Y.

    2008-01-01

    This study presents a crop production model improvement: the previously adopted Michaelis-Menten (MM) type photosynthesis response function (fsub(rad-MM)) was replaced with a Prioul-Chartier (PC) type function (fsub(rad-PC)). The authors' analysis reflects concerns regarding the background effect of global warming, under simultaneous conditions of high air temperature and strong solar radiation. The MM type function fsub(rad-MM) can give excessive values leading to an overestimate of photosynthesis rate (PSN) and grain yield for paddy-rice. The MM model is applicable to many plants whose (PSN) increases concomitant with increased insolation: wheat, maize, soybean, etc. For paddy rice, the PSN apparently shows a maximum PSN. This paper proves that the MM model overestimated the PSN for paddy rice for sufficient solar radiation: the PSN using the PC model yields 10% lower values. However, the unit crop production index (CPIsub(U)) is almost independent of the MM and PC models because of respective standardization of both PSN and crop production index using average PSNsub(0) and CPIsub(0). The authors improved the estimation method using a photosynthesis-and-sterility based crop situation index (CSIsub(E)) to produce a crop yield index (CYIsub(E)), which is used to estimate rice yields in place of the crop situation index (CSI); the CSI gives a percentage of rice yields compared to normal annual production. The model calculates PSN including biomass effects, low-temperature sterility, and high-temperature injury by incorporating insolation, effective air temperature, the normalized difference vegetation index (NDVI), and effects of temperature on photosynthesis. Based on routine observation data, the method enables automated crop-production monitoring in remote regions without special observations. This method can quantify grain production early to raise an alarm in Southeast Asian countries, which must confront climate fluctuation through this era of global

  10. Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, D.; Singh, U.P.; Ray, K.; Das, A.

    2016-11-01

    In direct seeded rice (DSR) cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN) models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE) herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST) following PRE herbicides (clomazone or pendimethalin) or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times) over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI) of herbicides was most important than their weed control efficiency (WCE). Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR. (Author)

  11. Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: Model description, evaluation and application

    NARCIS (Netherlands)

    Hoffmann, M.; Castaneda Vera, A.; Wijk, van M.T.; Giller, K.E.; Oberthür, T.; Donough, C.; Whitbread, A.M.

    2014-01-01

    Reducing the gap between water-limited potential yield and actual yield in oil palm production systems through intensification is seen as an important option for sustainably increasing palm oil production. Simulation models can play an important role in quantifying water-limited potential yield, and

  12. Mechanical responses, texture evolution, and yield loci of extruded AZ31 magnesium alloy under various loading conditions: Experiment and modeling

    Science.gov (United States)

    Kabirian, Farhoud

    Mechanical responses and texture evolution of extruded AZ31 Mg are measured under uniaxial (tension-compression) and multiaxial (free-end torsion) loadings. Compression loading is carried out in three different directions at temperature and strain rate ranges of 77-423 K and 10-4 -3000 s -1, respectively. Texture evolution at different intermediate strains reveals that crystal reorientation is exhausted at smaller strains with increase in strain rate while increase in temperature retards twinning. In addition to the well-known tension-compression yield asymmetry, a strong anisotropy in strain hardening response is observed. Strain hardening during the compression experiment is intensified with decreasing and increasing temperature and strain rate, respectively. This complex behavior is explained through understanding the roles of deformation mechanisms using the Visco-Plastic Self Consistent (VPSC) model. In order to calibrate the VPSC model's constants as accurate as possible, a vast number of mechanical responses including stress-strain curves in tension, compression in three directions, and free-end torsion, texture evolution at different strains, lateral strains of compression samples, twin volume fraction, and axial strain during the torsion experiment. Modeling results show that depending on the number of measurements used for calibration, roles of different mechanisms in plastic deformation change significantly. In addition, a precise definition of yield is established for the extruded AZ31magnesium alloy after it is subjected to different loading conditions (uniaxial to multiaxial) at four different plastic strains. The yield response is measured in ?-? space. Several yield criteria are studied to predict yield response of extruded AZ31. This study proposes an asymmetrical fourth-order polynomial yield function. Material constants in this model can be directly calculated using mechanical measurements. Convexity of the proposed model is discussed, and

  13. A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

    Science.gov (United States)

    Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

    2018-04-01

    In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

  14. Changing forest water yields in response to climate warming: results from long-term experimental watershed sites across North America

    Science.gov (United States)

    Irena F. Creed; Adam T. Spargo; Julia A. Jones; Jim M. Buttle; Mary B. Adams; Fred D. Beall; Eric G. Booth; John L. Campbell; Dave Clow; Kelly Elder; Mark B. Green; Nancy B. Grimm; Chelcy Miniat; Patricia Ramlal; Amartya Saha; Stephen Sebestyen; Dave Spittlehouse; Shannon Sterling; Mark W. Williams; Rita Winkler; Huaxia. Yao

    2014-01-01

    Climate warming is projected to affect forest water yields but the effects are expected to vary.We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long-term experimental catchments across Canada and the United States over 5-year cool and warm...

  15. Simulation of Sediment Yield in a Semi-Arid River Basin under Changing Land Use: An Integrated Approach of Hydrologic Modelling and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Charles Gyamfi

    2016-11-01

    Full Text Available Intensified human activities over the past decades have culminated in the prevalence of dire environmental consequences of sediment yield resulting mainly from land use changes. Understanding the role that land use changes play in the dynamics of sediment yield would greatly enhance decision-making processes related to land use and water resources management. In this study, we investigated the impacts of land use and cover changes on sediment yield dynamics through an integrated approach of hydrologic modelling and principal component analysis (PCA. A three-phase land use scenario (2000, 2007 and 2013 employing the “fix-changing” method was used to simulate the sediment yield of the Olifants Basin. Contributions in the changes in individual land uses to sediment yield were assessed using the component and pattern matrixes of PCA. Our results indicate that sediment yield dynamics in the study area is significantly attributed to the changes in agriculture, urban and forested lands. Changes in agriculture and urban lands were directly proportional to sediment yield dynamics of the Olifants Basin. On the contrary, forested areas had a negative relationship with sediment yield indicating less sediment yield from these areas. The output of this research work provides a simplistic approach of evaluating the impacts of land use changes on sediment yield. The tools and methods used are relevant for policy directions on land and water resources planning and management.

  16. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle.

    Science.gov (United States)

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-10-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre's polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre's polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from -0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from -0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

  17. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle

    Directory of Open Access Journals (Sweden)

    Ali William Canaza-Cayo

    2015-10-01

    Full Text Available A total of 32,817 test-day milk yield (TDMY records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM using Legendre’s polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi and the genetic trend of 305-day milk yield (305MY were evaluated. The fit quality criteria used indicated RRM employing the Legendre’s polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from −0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from −0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

  18. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Science.gov (United States)

    Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

    2015-01-01

    Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology

  19. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  20. Critical-point model to estimate yield loss caused by Asian soybean rust

    Directory of Open Access Journals (Sweden)

    Anderson Luiz Durante Danelli

    2015-12-01

    Full Text Available ABSTRACTA model to estimate yield loss caused by Asian soybean rust (ASR (Phakopsora pachyrhizi was developed by collecting data from field experiments during the growing seasons 2009/10 and 2010/11, in Passo Fundo, RS. The disease intensity gradient, evaluated in the phenological stages R5.3, R5.4 and R5.5 based on leaflet incidence (LI and number of uredinium and lesions/cm2, was generated by applying azoxystrobin 60 g a.i/ha + cyproconazole 24 g a.i/ha + 0.5% of the adjuvant Nimbus. The first application occurred when LI = 25% and the remaining ones at 10, 15, 20 and 25-day intervals. Harvest occurred at physiological maturity and was followed by grain drying and cleaning. Regression analysis between the grain yield and the disease intensity assessment criteria generated 56 linear equations of the yield loss function. The greatest loss was observed in the earliest growth stage, and yield loss coefficients ranged from 3.41 to 9.02 kg/ha for each 1% LI for leaflet incidence, from 13.34 to 127.4 kg/ha/1 lesion/cm2 for lesion density and from 5.53 to 110.0 kg/ha/1 uredinium/cm2 for uredinium density.

  1. Radiation utilization efficiency, nitrogen uptake and modeling crop growth and yield of rainfed rice under different nitrogen rates

    International Nuclear Information System (INIS)

    Gouranga, Kar; Ashwani Kumar; Mohapatra, Sucharita

    2014-01-01

    Optimum utilization of photosynthetically active radiation (PAR) along with proper nitrogen (N) management for sustainable rice production is still a promising management recommendation for sustainable rainfed rice cultivation in eastern India. The objective of this investigation was to study radiation utilization efficiency (RUE), N uptake and modeling growth and productivity of wet/rainy season rice (cv. Lalat and Gayatri) under 0, 50, 90, 120 and 150 kg ha -1 N application. Results showed that N rates significantly affected plant biomass, leaf area index (LAI), biological yield (straw and grain yield) and N uptake for both the varieties. The intercepted photosynthetically active radiation (IPAR) and spectral reflectance based vegetation indices (IR/R, NDVI) were also different between two varieties and among N rates. Higher rate of N increased the RUE significantly; averaged over years and varieties, mean values of RUE were 1.35, 1.70, 2.01, 2.15 and 2.17 g MJ -1 under 0, 50, 90, 120 and 150 kg N ha -1 , respectively. Though crop growth, yield, N uptake and RUE were higher at 150 kg N ha -1 but the results were at par with 120 kg N ha -1 . Agronomic N use efficiency (ANUE) was also low at 150 kg N ha -1 . The DSSAT v 4.5 model was applied to simulate crop growth, yield and phenology of the crop under different N rates. Model performance was found to be poor at low N rates (0, 50 kg N ha -1 ), but the model performed fairly well at higher N rates (90 kg ha -1 and above). (author)

  2. Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

    Directory of Open Access Journals (Sweden)

    Jingting Zhang

    2015-08-01

    Full Text Available Rice (Oryza sativa L. is one of the most important staple crops in China. Increasing atmospheric greenhouse gas concentrations and associated climate change may greatly affect rice production. We assessed the potential impacts of climate change on cold rice production in the Heilongjiang province, one of China's most important rice production regions. Data for a baseline period (1961–1990 and the period 2010–2050 in A2 and B2 scenarios were used as input to drive the rice model ORYZA2000 with and without accounting for the effects of increasing atmospheric CO2 concentration. The results indicate that mean, maximum, and minimum temperature during the rice growing season, in the future period considered, would increase by 1.8 °C under the A2 scenario and by 2.2 °C under the B2 scenario compared with those in the baseline. The rate of change in average maximum and minimum temperatures would increase by 0.6 °C per 10-year period under the A2 scenario and by 0.4 °C per 10-year period under the B2 scenario. Precipitation would increase slightly in the rice growing season over the next 40 years. The rice growing season would be shortened and the yield would increase in most areas in the Heilongjiang province. Without accounting for CO2 effect, the rice growing season in the period 2010–2050 would be shortened by 4.7 and 5.8 days, and rice yields would increase by 11.9% and 7.9%, under the A2 and B2 scenarios, respectively. Areas with simulated rice yield increases greater than 30.0% were in the Xiaoxing'an Mountain region. The simulation indicated a decrease in yield of less than 15% in the southwestern Songnen Plain. The rate of change in simulated rice yield was 5.0% and 2.5% per 10 years under the A2 and B2 scenarios, respectively. When CO2 effect was accounted for, rice yield increased by 44.5% and 31.3% under the A2 and B2 scenarios, respectively. The areas of increasing yield were sharply expanded. The area of decreasing yield in the

  3. Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

    Science.gov (United States)

    French, V. (Principal Investigator)

    1982-01-01

    An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

  4. Influence of Different Yield Loci on Failure Prediction with Damage Models

    Science.gov (United States)

    Heibel, S.; Nester, W.; Clausmeyer, T.; Tekkaya, A. E.

    2017-09-01

    Advanced high strength steels are widely used in the automotive industry to simultaneously improve crash performance and reduce the car body weight. A drawback of these multiphase steels is their sensitivity to damage effects and thus the reduction of ductility. For that reason the Forming Limit Curve is only partially suitable for this class of steels. An improvement in failure prediction can be obtained by using damage mechanics. The objective of this paper is to comparatively review the phenomenological damage model GISSMO and the Enhanced Lemaitre Damage Model. GISSMO is combined with three different yield loci, namely von Mises, Hill48 and Barlat2000 to investigate the influence of the choice of the plasticity description on damage modelling. The Enhanced Lemaitre Model is used with Hill48. An inverse parameter identification strategy for a DP1000 based on stress-strain curves and optical strain measurements of shear, uniaxial, notch and (equi-)biaxial tension tests is applied to calibrate the models. A strong dependency of fracture strains on the choice of yield locus can be observed. The identified models are validated on a cross-die cup showing ductile fracture with slight necking.

  5. Analysis of yield of retinal imaging in a rural diabetes eye care model

    Directory of Open Access Journals (Sweden)

    Padmaja Kumari Rani

    2018-01-01

    Full Text Available Purpose: The aim of this study is to analyze the yield of retinal images obtained in a rural diabetes eye care model. Methods: An analysis of a sample of nonmydriatic fundus photography (NMFP of posterior segment ophthalmic images, obtained by an indigenous equipment (3 nethra-Forus Royal, was done in a district-wide rural diabetic retinopathy (DR screening program; a trained optometrist did the initial image grading. DR and diabetic macular edema (DME were classified based on international DR and DME severity scale. The agreement between the optometrist and retina specialist was very good (κ = 0.932; standard error = 0.030; 95% confidence interval = 0.874–0.991. Results: Posterior segment images of 2000 eyes of 1000 people with diabetes mellitus (DM were graded. The mean age of the participants was 55.7 ± 11.5 standard deviation years. Nearly 42% of the screened participants (n = 420/1000 needed referral. The most common referable posterior segment abnormality was DR (8.2%. The proportion of people with any form of DR was seen in 110/1225 eyes, and sight-threatening DR was seen in 35/1225 eyes. About 62% of posterior segment images were gradable. The reasons for ungradable posterior segment images (34% were small pupil, unfocused/partially available field of images, and cataract. Conclusion: A NMFP model was able to detect referable posterior segment abnormalities in a rural diabetes eye care program. Reasons found for ungradability of images in the present study can be addressed while designing future DR screening programs in the rural areas.

  6. Aspects of modeling regarding the contribution of nitrogen to the formation of grape yields

    Science.gov (United States)

    Blidariu, Cosmin; Boldea, Marius; Sala, Florin

    2013-10-01

    The research focused on determining the influence of organic fertilization equivalent to 150, 200 and 250 kg ha-1 nitrogen, on the productivity indices that participate in the formation of the grape yield: grape berry weight, number of grape berries, rachis weight. Quality indices of grapes were also analyzed: structure index, berry index, as well as yield quality, through dry matter. The distribution analysis of the experimental data revealed that production increase dy/dx increases dramatically with the total fertilizer dose (x + x0), it being proportional to the saturation deficit (a-y), where a is the biologically maximum yield (asymptote). Constants a, b and x0 for each parameter were determined by confrontation with the experimental data, through the least square method, and they were used in modeling the contribution of nitrogen to the formation of grape yields. Although the equivalent quantity of nitrogen in the soil is 150 units, its use is different in the proposed model, depending on the parameter under study. When the focus is on grape berry weight, the enhancement of this parameter is at the level of 97 units, whereas the enhancement of dry matter is 300 units. Analysis of the experimental data revealed that productive parameters are in positive correlation with different intensity levels. Regression analysis, Stuart, A., 1987, facilitated prediction models for the productive characters under study, with high to very high degree of certainty ((Gb = f(Nb):r2 = 0.880;p<0.01;Gs = f(NrB):r2 = 0.852;p<0.01).

  7. Modelling the impact of forest loss on shallow landslide sediment yield, Ijuez river catchment, Spanish Pyrenees

    Directory of Open Access Journals (Sweden)

    2007-01-01

    Full Text Available The SHETRAN model for simulating the sediment yield arising from shallow landslides at the scale of a river catchment was applied to the 45-km2 Ijuez catchment in the central Spanish Pyrenees, to investigate the effect of loss of forest cover on landslide and debris flow incidence and on catchment sediment yield. The application demonstrated how such a model, with a large number of parameters to be evaluated, can be used even when directly measured data are not available: rainfall and discharge time series were generated by reference to other local records and data providing the basis for a soil map were obtained by a short field campaign. Uncertainty bounds for the outputs were determined as a function of the uncertainty in the values of key model parameters. For a four-year period and for the existing forested state of the catchment, a good ability to simulate the observed long term spatial distribution of debris flows (represented by a 45-year inventory and to determine catchment sediment yield within the range of regional observations was demonstrated. The lower uncertainty bound on simulated landslide occurrence approximated the observed annual rate of landsliding and suggests that landslides provide a relatively minor proportion of the total sediment yield, at least in drier years. A scenario simulation in which the forest cover was replaced by grassland indicated an increase in landsliding but a decrease in the number of landslides which evolve into debris flows and, at least for drier years, a reduction in sediment delivery to the channel network.

  8. Simulation of potato yield in temperate condition by the AquaCrop model

    DEFF Research Database (Denmark)

    Razzaghi, Fatemeh; Zhenjiang, Zhou; Andersen, Mathias Neumann

    2017-01-01

    Potato production ranks fourth in the world after rice, wheat, and maize and it is highly sensitive to water stress. It is thus very important to implement irrigation management strategies to minimize the effects of water stress under different climate conditions. The use of modelling tools...... to calculate the soil water balance on a daily basis has become widespread in the last decades. Therefore, this study was performed to simulate potato yield, dry matter and soil water content under different water stress condition using the AquaCrop model. Three levels of irrigation comprising full irrigated...... was simulated using the AquaCrop model. Data from full irrigated treatment of 2014 was used for model calibration and data from 2013 (If, Id, and I0 treatments), 2014 (Id, and I0 treatments) and 2015 (If, Id, and I0 treatments) were used for model validation. The sensitivity analysis of different parameters...

  9. Yield response of winter wheat cultivars to environments modeled by different variance-covariance structures in linear mixed models

    Energy Technology Data Exchange (ETDEWEB)

    Studnicki, M.; Mądry, W.; Noras, K.; Wójcik-Gront, E.; Gacek, E.

    2016-11-01

    The main objectives of multi-environmental trials (METs) are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E) interactions. Linear mixed models (LMMs) with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011) from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset. (Author)

  10. Yield response of winter wheat cultivars to environments modeled by different variance-covariance structures in linear mixed models

    Directory of Open Access Journals (Sweden)

    Marcin Studnicki

    2016-06-01

    Full Text Available The main objectives of multi-environmental trials (METs are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E interactions. Linear mixed models (LMMs with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011 from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset.

  11. Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

    Science.gov (United States)

    Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

    2017-04-01

    Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed

  12. Updated stomatal flux and flux-effect models for wheat for quantifying effects of ozone on grain yield, grain mass and protein yield.

    Science.gov (United States)

    Grünhage, Ludger; Pleijel, Håkan; Mills, Gina; Bender, Jürgen; Danielsson, Helena; Lehmann, Yvonne; Castell, Jean-Francois; Bethenod, Olivier

    2012-06-01

    Field measurements and open-top chamber experiments using nine current European winter wheat cultivars provided a data set that was used to revise and improve the parameterisation of a stomatal conductance model for wheat, including a revised value for maximum stomatal conductance and new functions for phenology and soil moisture. For the calculation of stomatal conductance for ozone a diffusivity ratio between O(3) and H(2)O in air of 0.663 was applied, based on a critical review of the literature. By applying the improved parameterisation for stomatal conductance, new flux-effect relationships for grain yield, grain mass and protein yield were developed for use in ozone risk assessments including effects on food security. An example of application of the flux model at the local scale in Germany shows that negative effects of ozone on wheat grain yield were likely each year and on protein yield in most years since the mid 1980s. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Results of steel containment vessel model test

    International Nuclear Information System (INIS)

    Luk, V.K.; Ludwigsen, J.S.; Hessheimer, M.F.; Komine, Kuniaki; Matsumoto, Tomoyuki; Costello, J.F.

    1998-05-01

    A series of static overpressurization tests of scale models of nuclear containment structures is being conducted by Sandia National Laboratories for the Nuclear Power Engineering Corporation of Japan and the US Nuclear Regulatory Commission. Two tests are being conducted: (1) a test of a model of a steel containment vessel (SCV) and (2) a test of a model of a prestressed concrete containment vessel (PCCV). This paper summarizes the conduct of the high pressure pneumatic test of the SCV model and the results of that test. Results of this test are summarized and are compared with pretest predictions performed by the sponsoring organizations and others who participated in a blind pretest prediction effort. Questions raised by this comparison are identified and plans for posttest analysis are discussed

  14. Multiple linear regression and artificial neural networks for delta-endotoxin and protease yields modelling of Bacillus thuringiensis.

    Science.gov (United States)

    Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil

    2017-07-01

    The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.

  15. Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

    Science.gov (United States)

    Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

    2017-10-01

    , with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

  16. Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

    Directory of Open Access Journals (Sweden)

    Zhiqiang Cheng

    2016-04-01

    Full Text Available Field crop yield prediction is crucial to grain storage, agricultural field management, and national agricultural decision-making. Currently, crop models are widely used for crop yield prediction. However, they are hampered by the uncertainty or similarity of input parameters when extrapolated to field scale. Data assimilation methods that combine crop models and remote sensing are the most effective methods for field yield estimation. In this study, the World Food Studies (WOFOST model is used to simulate the growing process of spring maize. Common assimilation methods face some difficulties due to the scarce, constant, or similar nature of the input parameters. For example, yield spatial heterogeneity simulation, coexistence of common assimilation methods and the nutrient module, and time cost are relatively important limiting factors. To address the yield simulation problems at field scale, a simple yet effective method with fast algorithms is presented for assimilating the time-series HJ-1 A/B data into the WOFOST model in order to improve the spring maize yield simulation. First, the WOFOST model is calibrated and validated to obtain the precise mean yield. Second, the time-series leaf area index (LAI is calculated from the HJ data using an empirical regression model. Third, some fast algorithms are developed to complete assimilation. Finally, several experiments are conducted in a large farmland (Hongxing to evaluate the yield simulation results. In general, the results indicate that the proposed method reliably improves spring maize yield estimation in terms of spatial heterogeneity simulation ability and prediction accuracy without affecting the simulation efficiency.

  17. Interpreting Results from the Multinomial Logit Model

    DEFF Research Database (Denmark)

    Wulff, Jesper

    2015-01-01

    This article provides guidelines and illustrates practical steps necessary for an analysis of results from the multinomial logit model (MLM). The MLM is a popular model in the strategy literature because it allows researchers to examine strategic choices with multiple outcomes. However, there seem...... to be systematic issues with regard to how researchers interpret their results when using the MLM. In this study, I present a set of guidelines critical to analyzing and interpreting results from the MLM. The procedure involves intuitive graphical representations of predicted probabilities and marginal effects...... suitable for both interpretation and communication of results. The pratical steps are illustrated through an application of the MLM to the choice of foreign market entry mode....

  18. A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

    Science.gov (United States)

    Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

    2018-02-07

    The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small

  19. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.

    Science.gov (United States)

    Torres, F E; Teodoro, P E; Rodrigues, E V; Santos, A; Corrêa, A M; Ceccon, G

    2016-04-29

    The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

  20. Economic impact of clinical mastitis in a dairy herd assessed by stochastic simulation using different methods to model yield losses

    DEFF Research Database (Denmark)

    Hagnestam-Nielsen, Christel; Østergaard, Søren

    2009-01-01

    reflects the fact that in different stages of lactation, CM gives rise to different yield-loss patterns or postulates just one type of yield-loss pattern irrespective of when, during lactation, CM occurs. A dynamic and stochastic simulation model, SimHerd, was used to study the effects of CM in a herd...... a single yield-loss pattern irrespective of when, during the lactation period, the cow develops CM - was compared with a new modelling strategy in which CM was assumed to affect production differently depending on its lactational timing. The effect of the choice of reference level when estimating yield...

  1. Spatially distinct response of rice yield to autonomous adaptation under the CMIP5 multi-model projections

    Science.gov (United States)

    Shin, Yonghee; Lee, Eun-Jeong; Im, Eun-Soon; Jung, Il-Won

    2017-02-01

    Rice ( Oryza sativa L.) is a very important staple crop, as it feeds more than half of the world's population. Numerous studies have focused on the negative impacts of climate change on rice production. However, there is little debate on which region of the world is more vulnerable to climate change and how adaptation to this change can mitigate the negative impacts on rice production. We investigated the impacts of climate change on rice yield, based on simulations combining a global crop model, M-GAZE, and Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model projections. Our focus was the impact of mitigating emission forcings (representative concentration pathway RCP 4.5 vs. RCP 8.5) and autonomous adaptation (i.e., changing crop variety and planting date) on rice yield. In general, our results showed that climate change due to anthropogenic warming leads to a significant reduction in rice yield. However, autonomous adaptation provides the potential to reduce the negative impact of global warming on rice yields in a spatially distinct manner. The adaptation was less beneficial for countries located at a low latitude (e.g., Cambodia, Thailand, Brazil) compared to mid-latitude countries (e.g., USA, China, Pakistan), as regional climates at the lower latitudes are already near the upper temperature thresholds for acceptable rice growth. These findings suggest that the socioeconomic effects from rice production in lowlatitude countries can be highly vulnerable to anthropogenic global warming. Therefore, these countries need to be accountable to develop transformative adaptation strategies, such as adopting (or developing) heat-tolerant varieties, and/or improve irrigation systems and fertilizer use efficiency.

  2. Modelling climate change impacts on viticultural yield, phenology and stress conditions in Europe.

    Science.gov (United States)

    Fraga, Helder; García de Cortázar Atauri, Iñaki; Malheiro, Aureliano C; Santos, João A

    2016-11-01

    Viticulture is a key socio-economic sector in Europe. Owing to the strong sensitivity of grapevines to atmospheric factors, climate change may represent an important challenge for this sector. This study analyses viticultural suitability, yield, phenology, and water and nitrogen stress indices in Europe, for present climates (1980-2005) and future (2041-2070) climate change scenarios (RCP4.5 and 8.5). The STICS crop model is coupled with climate, soil and terrain databases, also taking into account CO 2 physiological effects, and simulations are validated against observational data sets. A clear agreement between simulated and observed phenology, leaf area index, yield and water and nitrogen stress indices, including the spatial differences throughout Europe, is shown. The projected changes highlight an extension of the climatic suitability for grapevines up to 55°N, which may represent the emergence of new winemaking regions. Despite strong regional heterogeneity, mean phenological timings (budburst, flowering, veraison and harvest) are projected to undergo significant advancements (e.g. budburst/harvest can be >1 month earlier), with implications also in the corresponding phenophase intervals. Enhanced dryness throughout Europe is also projected, with severe water stress over several regions in southern regions (e.g. southern Iberia and Italy), locally reducing yield and leaf area. Increased atmospheric CO 2 partially offsets dryness effects, promoting yield and leaf area index increases in central/northern Europe. Future biomass changes may lead to modifications in nitrogen demands, with higher stress in northern/central Europe and weaker stress in southern Europe. These findings are critical decision support systems for stakeholders from the European winemaking sector. © 2016 John Wiley & Sons Ltd.

  3. Adapting SWAT hillslope erosion model to predict sediment concentrations and yields in large Basins.

    Science.gov (United States)

    Vigiak, Olga; Malagó, Anna; Bouraoui, Fayçal; Vanmaercke, Matthias; Poesen, Jean

    2015-12-15

    The Soil and Water Assessment Tool (SWAT) is used worldwide for water quality assessment and planning. This paper aimed to assess and adapt SWAT hillslope sediment yield model (Modified Universal Soil Loss Equation, MUSLE) for applications in large basins, i.e. when spatial data is coarse and model units are large; and to develop a robust sediment calibration method for large regions. The Upper Danube Basin (132,000km(2)) was used as case study representative of large European Basins. The MUSLE was modified to reduce sensitivity of sediment yields to the Hydrologic Response Unit (HRU) size, and to identify appropriate algorithms for estimating hillslope length (L) and slope-length factor (LS). HRUs gross erosion was broadly calibrated against plot data and soil erosion map estimates. Next, mean annual SWAT suspended sediment concentrations (SSC, mg/L) were calibrated and validated against SSC data at 55 gauging stations (622 station-years). SWAT annual specific sediment yields in subbasin reaches (RSSY, t/km(2)/year) were compared to yields measured at 33 gauging stations (87station-years). The best SWAT configuration combined a MUSLE equation modified by the introduction of a threshold area of 0.01km(2) where L and LS were estimated with flow accumulation algorithms. For this configuration, the SSC residual interquartile was less than +/-15mg/L both for the calibration (1995-2004) and the validation (2005-2009) periods. The mean SSC percent bias for 1995-2009 was 24%. RSSY residual interquartile was within +/-10t/km(2)/year, with a mean RSSY percent bias of 12%. Residuals showed no bias with respect to drainage area, slope, or spatial distribution. The use of multiple data types at multiple sites enabled robust simulation of sediment concentrations and yields of the region. The MUSLE modifications are recommended for use in large basins. Based on SWAT simulations, we present a sediment budget for the Upper Danube Basin. Copyright © 2015. Published by Elsevier B.V.

  4. Changing forest water yields in response to climate warming: results from long-term experimental watershed sites across North America.

    Science.gov (United States)

    Creed, Irena F; Spargo, Adam T; Jones, Julia A; Buttle, Jim M; Adams, Mary B; Beall, Fred D; Booth, Eric G; Campbell, John L; Clow, Dave; Elder, Kelly; Green, Mark B; Grimm, Nancy B; Miniat, Chelcy; Ramlal, Patricia; Saha, Amartya; Sebestyen, Stephen; Spittlehouse, Dave; Sterling, Shannon; Williams, Mark W; Winkler, Rita; Yao, Huaxia

    2014-10-01

    Climate warming is projected to affect forest water yields but the effects are expected to vary. We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long-term experimental catchments across Canada and the United States over 5-year cool and warm periods. Using the theoretical framework of the Budyko curve, we calculated the effects of climate warming on the annual partitioning of precipitation (P) into evapotranspiration (ET) and water yield. Deviation (d) was defined as a catchment's change in actual ET divided by P [AET/P; evaporative index (EI)] coincident with a shift from a cool to a warm period - a positive d indicates an upward shift in EI and smaller than expected water yields, and a negative d indicates a downward shift in EI and larger than expected water yields. Elasticity was defined as the ratio of interannual variation in potential ET divided by P (PET/P; dryness index) to interannual variation in the EI - high elasticity indicates low d despite large range in drying index (i.e., resilient water yields), low elasticity indicates high d despite small range in drying index (i.e., nonresilient water yields). Although the data needed to fully evaluate ecosystems based on these metrics are limited, we were able to identify some characteristics of response among forest types. Alpine sites showed the greatest sensitivity to climate warming with any warming leading to increased water yields. Conifer forests included catchments with lowest elasticity and stable to larger water yields. Deciduous forests included catchments with intermediate elasticity and stable to smaller water yields. Mixed coniferous/deciduous forests included catchments with highest elasticity and stable water yields. Forest type appeared to influence the resilience of catchment water yields to climate warming, with conifer and deciduous catchments more susceptible to

  5. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling

    Directory of Open Access Journals (Sweden)

    Piotr Tompalski

    2018-02-01

    Full Text Available The increasing availability of highly detailed three-dimensional remotely-sensed data depicting forests, including airborne laser scanning (ALS and digital aerial photogrammetric (DAP approaches, provides a means for improving stand dynamics information. The availability of data from ALS and DAP has stimulated attempts to link these datasets with conventional forestry growth and yield models. In this study, we demonstrated an approach whereby two three-dimensional point cloud datasets (one from ALS and one from DAP, acquired over the same forest stands, at two points in time (circa 2008 and 2015, were used to derive forest inventory information. The area-based approach (ABA was used to predict top height (H, basal area (BA, total volume (V, and stem density (N for Time 1 and Time 2 (T1, T2. We assigned individual yield curves to 20 × 20 m grid cells for two scenarios. The first scenario used T1 estimates only (approach 1, single date, while the second scenario combined T1 and T2 estimates (approach 2, multi-date. Yield curves were matched by comparing the predicted cell-level attributes with a yield curve template database generated using an existing growth simulator. Results indicated that the yield curves using the multi-date data of approach 2 were matched with slightly higher accuracy; however, projections derived using approach 1 and 2 were not significantly different. The accuracy of curve matching was dependent on the ABA prediction error. The relative root mean squared error of curve matching in approach 2 for H, BA, V, and N, was 18.4, 11.5, 25.6, and 27.53% for observed (plot data, and 13.2, 44.6, 50.4 and 112.3% for predicted data, respectively. The approach presented in this study provides additional detail on sub-stand level growth projections that enhances the information available to inform long-term, sustainable forest planning and management.

  6. Partial ion yield and NEXAFS of 2-(perfluorooctyl)ethanethiol self-assembled monolayer: Comparison with PTFE results

    CERN Document Server

    Setoyama, H; Murase, T; Imamura, M; Mase, K; Okudaira, K K; Hara, M; Ueno, N

    2003-01-01

    Partial-ion-yield (PIY) spectra using ion time-of-flight (TOF) method and near-edge absorption fine structure (NEXAFS) spectra were measured for 2-(perfluorooctyl)ethanethiol [CF sub 3 (CF sub 2) sub 7 (CH sub 2) sub 2 SH] self-assembled monolayer (F8-SAM) on Au(1 1 1) near carbon K-edge. The PIY spectra of the F8-SAM at the magic angle, where -CF sub 3 groups exist at the surface were compared with those of the rubbed polytetrafluoroethylene (PTFE) thin film. The F sup + intensity from the F8-SAM at the photon energy of the sharp peak of the NEXAFS, which originates from the excitation of C1s electron to sigma sup * (C-F) states at -CF sub 2 - chain, was extremely smaller than that from the rubbed PTFE film. This result clearly indicates that the ions observed by PIY do not originate from the film inside but from the surface. This was confirmed by changes in ion-TOF mass spectra during soft X-ray induced etching of the F8-SAM. The NEXAFS peaks of the F8-SAM were also assigned by considering PIY results.

  7. An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows.

    Science.gov (United States)

    Brun-Lafleur, L; Cutullic, E; Faverdin, P; Delaby, L; Disenhaus, C

    2013-08-01

    To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rates.

  8. Modeling dependence structure between stock market volatility and sukuk yields: A nonlinear study in the case of Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Nader Naifar

    2016-09-01

    Full Text Available The aim of this paper is to investigate the dependence structure between sukuk (Islamic bonds yields and stock market (returns and volatility in the case of Saudi Arabia. We consider three Archimedean copula models with different tail dependence structures namely Gumbel, Clayton, and Frank. This study shows that the sukuk yields exhibit significant dependence only with stock market volatility. In addition, the dependence structure between sukuk yields and stock market volatility are symmetric and linked with the same intensity.

  9. Development of yield prediction models in the maize crop using spectral data for precisión agriculture applications

    OpenAIRE

    Rueda Ayala, Victor Patricio

    2015-01-01

    Yield estimation for the maize crop (Zea mays L.) is required in Ecuador for decision making on imports and commercialization. In the literature many yield predictive models have been developed for different crops, but they need to be adapted to the local conditions. In this study, machine learning techniques and statistical tools such as simple, logistic and polynomial regression were applied in order to develop yield predictive algorithms. Spectral information was gathered from ...

  10. Kinetic modeling of solid yields formation in the fast pyrolysis of mahogany wood

    Science.gov (United States)

    Wijayanti, W.; Sasongko, M. N.

    2016-03-01

    There have been many research of biomass pyrolysis not only in heat transfer point of view but also in chemical reaction point of view. In the present study, the rate of reaction (kinetic rate) formation of solid yield was calculated by varying the pyrolysis temperature that gives a chance of 250 °C, 350 °C, 450 °C, 500 °C, 600 °C, 700 °C, until 800°C with heating rate around 700 °C/hour. The heating rate used was the fast pyrolysis in which the heating rate for heating furnaces takes place quickly. Pyrolysis was accomplished by direct pyrolysis process in which each process was conducted at the certain pyrolysis temperature variation that took over 3 hours. Biomass used was mahogany wood, while the inert gas used to hold in order to avoid combustion was nitrogen gas. The decreasing of solid yields formation obtained was used to calculate the kinetic rate of the pyrolysis process. It was calculated by using the similar Arrhenius equation that considering the temperature changes during the process and the decreasing mass of solid yield formation occurred. The kinetic rate results showed the decomposition of biomass occurs tended in two stages, namely a stage of water evaporation and degradation of biomass solid yield coal followed by a stage of constant formation. The decomposition is expressed by the magnitude of the rate of reaction at 25˚C-517˚C temperature range with a reaction rate constant k1 = 2151.67 exp (-2141/Tp). While at pyrolysis temperatures above 517˚C, the reaction rate constant is expressed with k2 = 32.20 exp (-127.8 / Tp).

  11. Prediction of grain yield using optical remote sensing and a growth model: application on Merguellil catchment (Tunisia)

    Science.gov (United States)

    Chahbi, A.; Zribi, M.; Lili-Chabaane, Z.; Duchemin, B.; Shabou, M.; Mougenot, B.; Boulet, G.

    2012-04-01

    key biophysical functioning of plant canopies (LAI). The inversion of this relationship can provide estimation of leaf area index with spatialisation over the entire site. The second axis of research concerns the estimation of the grain yield. The approach was tested against 27 fields, selected with a large range of sowing date as well as irrigation and fertilisation schedules. Based on grain yield measures on the test plots, a relationship is established between NDVI and grain yield for 19/02, 17/03, 05/04 and 28/04/2011 dates. The results show that earlier forecasts are possible from the mid-March to mid-April with approximately a root mean square error (RMSE) equal to 25.46kg/ha and an average yield equal to 280.5 kg/ha for test fields. For the third axis, we used the SAFY model. It provides simulations of LAI, DAM time courses and GY space variations. The approach validated over test fields, offers the advantage of being quite simple, without requiring any data on agricultural practices (sowing, irrigation and fertilisation). This makes it very attractive for operational application at a regional scale. Key-words: cereals prediction, optical satellite, SAFY

  12. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France

    Science.gov (United States)

    Canal, N.; Calvet, J.-C.; Decharme, B.; Carrer, D.; Lafont, S.; Pigeon, G.

    2014-12-01

    The simulation of root water uptake in land surface models is affected by large uncertainties. The difficulty in mapping soil depth and in describing the capacity of plants to develop a rooting system is a major obstacle to the simulation of the terrestrial water cycle and to the representation of the impacts of drought. In this study, long time series of agricultural statistics are used to evaluate and constrain root water uptake models. The inter-annual variability of cereal grain yield and permanent grassland dry matter yield is simulated over France by the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) generic land surface model (LSM). The two soil profile schemes available in the model are used to simulate the above-ground biomass (Bag) of cereals and grasslands: a two-layer force-restore (FR-2L) bulk reservoir model and a multi-layer diffusion (DIF) model. The DIF model is implemented with or without deep soil layers below the root zone. The evaluation of the various root water uptake models is achieved by using the French agricultural statistics of Agreste over the 1994-2010 period at 45 cropland and 48 grassland départements, for a range of rooting depths. The number of départements where the simulated annual maximum Bag presents a significant correlation with the yield observations is used as a metric to benchmark the root water uptake models. Significant correlations (p value neutral impact of the most refined versions of the model is found with respect to the simplified soil hydrology scheme. This shows that efforts should be made in future studies to reduce other sources of uncertainty, e.g. by using a more detailed soil and root density profile description together with satellite vegetation products. It is found that modelling additional subroot-zone base flow soil layers does not improve (and may even degrade) the representation of the inter-annual variability of the vegetation above-ground biomass. These results are

  13. Low-frequency ac electroporation shows strong frequency dependence and yields comparable transfection results to dc electroporation.

    Science.gov (United States)

    Zhan, Yihong; Cao, Zhenning; Bao, Ning; Li, Jianbo; Wang, Jun; Geng, Tao; Lin, Hao; Lu, Chang

    2012-06-28

    Conventional electroporation has been conducted by employing short direct current (dc) pulses for delivery of macromolecules such as DNA into cells. The use of alternating current (ac) field for electroporation has mostly been explored in the frequency range of 10kHz-1MHz. Based on Schwan equation, it was thought that with low ac frequencies (10Hz-10kHz), the transmembrane potential does not vary with the frequency. In this report, we utilized a flow-through electroporation technique that employed continuous 10Hz-10kHz ac field (based on either sine waves or square waves) for electroporation of cells with defined duration and intensity. Our results reveal that electropermeabilization becomes weaker with increased frequency in this range. In contrast, transfection efficiency with DNA reaches its maximum at medium frequencies (100-1000Hz) in the range. We postulate that the relationship between the transfection efficiency and the ac frequency is determined by combined effects from electrophoretic movement of DNA in the ac field, dependence of the DNA/membrane interaction on the ac frequency, and variation of transfection under different electropermeabilization intensities. The fact that ac electroporation in this frequency range yields high efficiency for transfection (up to ~71% for Chinese hamster ovary cells) and permeabilization suggests its potential for gene delivery. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

    Directory of Open Access Journals (Sweden)

    Lorenčič Eva

    2016-06-01

    Full Text Available Understanding the relationship between interest rates and term to maturity of securities is a prerequisite for developing financial theory and evaluating whether it holds up in the real world; therefore, such an understanding lies at the heart of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why the testing of various models for estimating and predicting the term structure of interest rates is an important topic in finance that has received considerable attention for many decades. In this paper, we empirically contrast the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main conclusion that can be drawn from the results of the calculations is that the Nelson-Siegel model outperforms cubic splines at the short end of the yield curve (up to 2 years, whereas for medium-term maturities (2 to 10 years the fitting performance of both models is comparable.

  15. Numerical experiments on plasma focus for soft x-ray yield scaling laws derivation using Lee model

    International Nuclear Information System (INIS)

    Akel, M.

    2012-09-01

    The required plasma parameters of krypton and xenon at different temperatures were calculated, the x-ray emission properties of plasmas were studied, and based on the corona model the suitable temperature range for generating H-like and He-like ions (therefore soft x-ray emissions) of different gases plasma were found. The code is applied to characterize the plasma focus in different plasma focus devices, and for optimizing the nitrogen, oxygen, neon, argon, krypton and xenon soft x-ray yields based on bank, tubes and operating parameters. It is found that the soft x-ray yield increases with changing pressure until it reaches the maximum value for each plasma focus device. Keeping the bank parameters, operational voltage unchanged but systematically changing other parameters, numerical experiments were performed finding the optimum combination of P o , Z o and 'a' for the maximum soft x-ray yield. Thus we expect to increase the soft x-ray yield of plasma focus device several-fold from its present typical operation; without changing the capacitor bank, merely by changing the electrode configuration and the operating pressure. The Lee model code was also used to run numerical experiments on plasma focus devices for optimizing soft x-ray yield with reducing L o , varying L o and 'a' to get engineering designs with maximum soft x-ray yield for these devices at different experimental conditions and gases. Numerical experiments showed the influence of the gas used in plasma focus and its properties on soft x-ray emission and its properties and then on its applications. Scaling laws for soft x-ray of nitrogen, oxygen, neon, argon, krypton and xenon plasma focus, in terms of energy, peak discharge current and focus pinch current were found. Radiative cooling effects are studied indicating that radiative collapse may be observed for heavy noble gases (Ar, Kr, Xe) for pinch currents even below 100 kA. The results show that the line radiation emission and tube voltages have

  16. Modelling predicts that tolerance to drought during reproductive development will be required for high yield potential and stability of wheat in Europe

    Science.gov (United States)

    Semenov, Mikhail A.; Stratonovitch, Pierre; Paul, Matthew J.

    2017-04-01

    Short periods of extreme weather, such as a spell of high temperature or drought during a sensitive stage of development, could result in substantial yield losses due to reduction in grain number and grain size. In a modelling study (Stratonovitch & Semenov 2015), heat tolerance around flowering in wheat was identified as a key trait for increased yield potential in Europe under climate change. Ji et all (Ji et al. 2010) demonstrated cultivar specific responses of yield to drought stress around flowering in wheat. They hypothesised that carbohydrate supply to anthers may be the key in maintaining pollen fertility and grain number in wheat. It was shown in (Nuccio et al. 2015) that genetically modified varieties of maize that increase the concentration of sucrose in ear spikelets, performed better under non-drought and drought conditions in field experiments. The objective of this modelling study was to assess potential benefits of tolerance to drought during reproductive development for wheat yield potential and yield stability across Europe. We used the Sirius wheat model to optimise wheat ideotypes for 2050 (HadGEM2, RCP8.5) climate scenarios at selected European sites. Eight cultivar parameters were optimised to maximise mean yields, including parameters controlling phenology, canopy growth and water limitation. At those sites where water could be limited, ideotypes sensitive to drought produced substantially lower mean yields and higher yield variability compare with tolerant ideotypes. Therefore, tolerance to drought during reproductive development is likely to be required for wheat cultivars optimised for the future climate in Europe in order to achieve high yield potential and yield stability.

  17. Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium

    Directory of Open Access Journals (Sweden)

    Pierre Coenraets

    1997-01-01

    Full Text Available Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (covariance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires estimated with the single-trait and multiple-trait models were over .98 (.99 in fat yield and over .99 (.99 in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1% in milk yield, 6% (3% in fat yield, and .4% (.2% in protein yield for cows (for sires. Relative genetic gains were 3% (1%, 6% (2% and .5% (.2% respectively in milk, fat and protein yields for cows (for sires. The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.

  18. A Model of Equilibrium Conditions of Roof Rock Mass Giving Consideration to the Yielding Capacity of Powered Supports

    Science.gov (United States)

    Jaszczuk, Marek; Pawlikowski, Arkadiusz

    2017-12-01

    units giving consideration to the load of the caving shield, a model of support unit was used that allows for unequivocal determination of the yielding capacity of the support with consideration given to the height of the unit in use and the change in the inclination of the canopy resulting from the displacement of the roof of the longwall. The yielding capacity of the support unit and its point of application on the canopy was determined using the method of units which allows for the internal forces to be manifested. The weight of the rock mass depends on the geological and mining conditions, for which the shape and dimensions of the rock mass affecting the support unit are determined. The resultant force of the pressure of gob on the gob shield was calculated by assuming that the load may be understood as a pressure of ground on a wall. This required the specification of the volume of the fallen rocks that affect the unit of powered roof supports (Fig. 2). To determine the support of the roof rock mass by the coal seam, experience of the Australian mining industry was used. Experiments regarding the strength properties of coal have exhibited that vertical deformation, at which the highest seam reaction occurs while supporting the roof rock mass, amounts to 0.5% of the longwall's height. The measure of the width of the contact area between the rock mass and the seam is the width of the additional uncovering of the face roof due to spalling of seam topcorners da (Fig. 2). With the above parameters and the value of the modulus of elasticity of coal in mind, the value of the seam's reaction may be estimated using the dependence (2). The vertical component of the goafs' reaction may be determined based on the strength characteristics of the fallen roof, the contact area of the rock mass with the fallen roof and the mean strain of the fallen roof at the area of contact. In the work by Pawlikowski (2014), a research procedure was proposed which encompasses model tests and

  19. Models for the transport of low energy electrons in water and the yield of hydrated electrons at early times

    International Nuclear Information System (INIS)

    Brenner, D.J.; Miller, J.H.; Ritchie, R.H.; Bichsel, H.

    1985-01-01

    An insulator model with four experimental energy bands was used to fit the optical properties of liquid water and to extend these data to non-zero momentum transfer. Inelastic mean free paths derived from this dielectric response function provided the basic information necessary to degrade high energy electrons to the subexcitation energy domain. Two approaches for the transport of subexcitation electrons were investigated. (i) Gas phase cross sections were used to degrade subexcitation electrons to thermal energy and the thermalization lengths were scaled to unit density. (ii) Thermalization lengths were estimated by age-diffusion theory with a stopping power deduced from the data on liquid water and transport cross sections derived from elastic scattering in water vapor. Theoretical ranges were compared to recent experimental results. A stochastic model was used to calculate the rapid diffusion and reaction of hydrated electrons with other radiolysis products. The sensitivity of the calculated yields to the model assumptions and comparison with experimental data are discussed

  20. Relationship between soybean yield/quality and soil quality in a major soybean-producing area based on a 2D-QSAR model

    Science.gov (United States)

    Gao, Ming; Li, Shiwei

    2017-05-01

    Based on experimental data of the soybean yield and quality from 30 sampling points, a quantitative structure-activity relationship model (2D-QSAR) was established using the soil quality (elements, pH, organic matter content and cation exchange capacity) as independent variables and soybean yield or quality as the dependent variable, with SPSS software. During the modeling, the full data set (30 and 14 compounds) was divided into a training set (24 and 11 compounds) for model generation and a test set (6 and 3 compounds) for model validation. The R2 values of the resulting models and data were 0.826 and 0.808 for soybean yield and quality, respectively, and all regression coefficients were significant (P test set were 0.961 and 0.956, respectively, indicating that the models had a good predictive ability. Moreover, the Mo, Se, K, N and organic matter contents and the cation exchange capacity of soil had a positive effect on soybean production, and the B, Mo, Se, K and N contents and cation exchange coefficient had a positive effect on soybean quality. The results are instructive for enhancing soils to improve the yield and quality of soybean, and this method can also be used to study other crops or regions, providing a theoretical basis to improving the yield and quality of crops.

  1. Modeling future water footprint of barley production in Alberta, Canada: Implications for water use and yields to 2064.

    Science.gov (United States)

    Masud, Mohammad Badrul; McAllister, Tim; Cordeiro, Marcos R C; Faramarzi, Monireh

    2018-03-01

    Despite the perception of being one of the most agriculturally productive regions globally, crop production in Alberta, a western province of Canada, is strongly dependent on highly variable climate and water resources. We developed agro-hydrological models to assess the water footprint (WF) of barley by simulating future crop yield (Y) and consumptive water use (CWU) within the agricultural region of Alberta. The Soil and Water Assessment Tool (SWAT) was used to develop rainfed and irrigated barley Y simulation models adapted to sixty-seven and eleven counties, respectively through extensive calibration, validation, sensitivity, and uncertainty analysis. Eighteen downscaled climate projections from nine General Circulation Models (GCMs) under the Representative Concentration Pathways 2.6 and 8.5 for the 2040-2064 period were incorporated into the calibrated SWAT model. Based on the ensemble of GCMs, rainfed barley yield is projected to increase while irrigated barley is projected to remain unchanged in Alberta. Results revealed a considerable decrease (maximum 60%) in WF to 2064 relative to the simulated baseline 1985-2009 WF. Less water will also be required to produce barley in northern Alberta (rainfed barley) than southern Alberta (irrigated barley) due to reduced water consumption. The modeled WF data adjusted for water stress conditions and found a remarkable change (increase/decrease) in the irrigated counties. Overall, the research framework and the locally adapted regional model results will facilitate the development of future water policies in support of better climate adaptation strategies by providing improved WF projections. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

    Science.gov (United States)

    Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

    2016-09-01

    Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

  3. Nuclear reaction rate uncertainties and astrophysical modeling: Carbon yields from low-mass giants

    International Nuclear Information System (INIS)

    Herwig, Falk; Austin, Sam M.; Lattanzio, John C.

    2006-01-01

    Calculations that demonstrate the influence of three key nuclear reaction rates on the evolution of asymptotic giant branch stars have been carried out. We study the case of a star with an initial mass of 2 M · and a metallicity of Z=0.01, somewhat less than the solar metallicity. The dredge-up of nuclear processed material from the interior of the star and the yield predictions for carbon are sensitive to the rate of the 14 N(p,γ) 15 O and triple-α reactions. These reactions dominate the H- and He-burning shells of stars in this late evolutionary phase. Published uncertainty estimates for each of these two rates propagated through stellar evolution calculations cause uncertainties in carbon enrichment and yield predictions of about a factor of 2. The other important He-burning reaction, 12 C(α,γ) 16 O, although associated with the largest uncertainty in our study, does not have a significant influence on the abundance evolution compared with other modeling uncertainties. This finding remains valid when the entire evolution from the main sequence to the tip of the asymptotic giant branch is considered. We discuss the experimental sources of the rate uncertainties addressed here and give some outlooks for future work

  4. Mixed models for selection of Jatropha progenies with high adaptability and yield stability in Brazilian regions.

    Science.gov (United States)

    Teodoro, P E; Bhering, L L; Costa, R D; Rocha, R B; Laviola, B G

    2016-08-19

    The aim of this study was to estimate genetic parameters via mixed models and simultaneously to select Jatropha progenies grown in three regions of Brazil that meet high adaptability and stability. From a previous phenotypic selection, three progeny tests were installed in 2008 in the municipalities of Planaltina-DF (Midwest), Nova Porteirinha-MG (Southeast), and Pelotas-RS (South). We evaluated 18 families of half-sib in a randomized block design with three replications. Genetic parameters were estimated using restricted maximum likelihood/best linear unbiased prediction. Selection was based on the harmonic mean of the relative performance of genetic values method in three strategies considering: 1) performance in each environment (with interaction effect); 2) performance in each environment (with interaction effect); and 3) simultaneous selection for grain yield, stability and adaptability. Accuracy obtained (91%) reveals excellent experimental quality and consequently safety and credibility in the selection of superior progenies for grain yield. The gain with the selection of the best five progenies was more than 20%, regardless of the selection strategy. Thus, based on the three selection strategies used in this study, the progenies 4, 11, and 3 (selected in all environments and the mean environment and by adaptability and phenotypic stability methods) are the most suitable for growing in the three regions evaluated.

  5. A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

    Directory of Open Access Journals (Sweden)

    Suhartono Suhartono

    2005-01-01

    Full Text Available Many business and economic time series are non-stationary time series that contain trend and seasonal variations. Seasonality is a periodic and recurrent pattern caused by factors such as weather, holidays, or repeating promotions. A stochastic trend is often accompanied with the seasonal variations and can have a significant impact on various forecasting methods. In this paper, we will investigate and compare some forecasting methods for modeling time series with both trend and seasonal patterns. These methods are Winter's, Decomposition, Time Series Regression, ARIMA and Neural Networks models. In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method. We use a real data, that is airline passenger data. The result shows that the more complex model does not always yield a better result than a simpler one. Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition (as data preprocessing and neural network model.

  6. Anthropogenic factors as an element of uncertainty in hydrological modelling of water yield with SWAT

    Directory of Open Access Journals (Sweden)

    R. Corobov

    2016-05-01

    Full Text Available In 2014 the SWAT (Soil and Water Assessment Tool model was used as a basis for follow-up investigations of Moldova’s small rivers potential flow. The first step of the study included the validation of SWAT for local conditions. As an experimental area, the Cogilnic River watershed was selected. Interim steps included the watershed delineation aimed to identify the subwatersheds and the Hydrological Response Units (small entities with the same characteristics of hydrologic soil type, land use and slopes. To address these tasks, the land cover, soil and slope layers, based on the Digital Elevation Model, were integrated in the SWAT environment. These thematic layers, alongside with long-term information on local monthly maximum and minimum temperatures and precipitation, enabled reflecting the differences in hydrological conditions and defining the watershed runoff. However, the validation of the modelling outputs, carried out through comparison of a simulated water yield from the studied watershed with actual Cogilnic streamflow measures, observed in 2010-2012, showed a great discrepancy between these parameters caused by anthropogenic loading on this small river. Thus, a ‘classical’ SWAT modelling needs to account for real environmental conditions and water use in the study area.

  7. Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments.

    Science.gov (United States)

    Hasegawa, Toshihiro; Li, Tao; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Baker, Jeffrey; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fugice, Job; Fumoto, Tamon; Gaydon, Donald; Kumar, Soora Naresh; Lafarge, Tanguy; Marcaida Iii, Manuel; Masutomi, Yuji; Nakagawa, Hiroshi; Oriol, Philippe; Ruget, Françoise; Singh, Upendra; Tang, Liang; Tao, Fulu; Wakatsuki, Hitomi; Wallach, Daniel; Wang, Yulong; Wilson, Lloyd Ted; Yang, Lianxin; Yang, Yubin; Yoshida, Hiroe; Zhang, Zhao; Zhu, Jianguo

    2017-11-01

    The CO 2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO 2 ] (E-[CO 2 ]) by comparison to free-air CO 2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO 2 ] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO 2 ] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO 2 ] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO 2 ] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO 2 ] × N interactions is necessary to better evaluate management practices under climate change.

  8. The Danish national passenger modelModel specification and results

    DEFF Research Database (Denmark)

    Rich, Jeppe; Hansen, Christian Overgaard

    2016-01-01

    , the paper provides a description of a large-scale forecast model with a discussion of the linkage between population synthesis, demand and assignment. Secondly, the paper gives specific attention to model specification and in particular choice of functional form and cost-damping. Specifically we suggest...... a family of logarithmic spline functions and illustrate how it is applied in the model. Thirdly and finally, we evaluate model sensitivity and performance by evaluating the distance distribution and elasticities. In the paper we present results where the spline-function is compared with more traditional...... function types and it is indicated that the spline-function provides a better description of the data. Results are also provided in the form of a back-casting exercise where the model is tested in a back-casting scenario to 2002....

  9. Assessment of water-limited winter wheat yield potential at spatially contrasting sites in Ireland using a simple growth and development model

    Directory of Open Access Journals (Sweden)

    Lynch J.P.

    2017-09-01

    Full Text Available Although Irish winter wheat yields are among the highest globally, increases in the profitability of this crop are required to maintain its economic viability. However, in order to determine if efforts to further increase Irish wheat yields are likely to be successful, an accurate estimation of the yield potential is required for different regions within Ireland. A winter wheat yield potential model (WWYPM was developed, which estimates the maximum water-limited yield achievable, within the confines of current genetic resources and technologies, using parameters for winter wheat growth and development observed recently in Ireland and a minor amount of daily meteorological input (maximum and minimum daily temperature, total daily rainfall and total daily incident radiation. The WWYPM is composed of three processes: (i an estimation of potential green area index, (ii an estimation of light interception and biomass accumulation and (iii an estimation of biomass partitioning to grain yield. Model validation indicated that WWYPM estimations of water-limited yield potential (YPw were significantly related to maximum yields recorded in variety evaluation trials as well as regional average and maximum farm yields, reflecting the model’s sensitivity to alterations in the climatic environment with spatial and seasonal variations. Simulations of YPw for long-term average weather data at 12 sites located at spatially contrasting regions of Ireland indicated that the typical YPw varied between 15.6 and 17.9 t/ha, with a mean of 16.7 t/ha at 15% moisture content. These results indicate that the majority of sites in Ireland have the potential to grow high-yielding crops of winter wheat when the effects of very high rainfall and other stresses such as disease incidence and nutrient deficits are not considered.

  10. Optimizing selective cutting strategies for maximum carbon stocks and yield of Moso bamboo forest using BIOME-BGC model.

    Science.gov (United States)

    Mao, Fangjie; Zhou, Guomo; Li, Pingheng; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

    2017-04-15

    The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation. Then four selective cutting scenarios were simulated by the improved BIOME-BGC model to optimize the selective cutting timings, intervals, retained ages and intensities. The improved model matched the observed aboveground carbon density and yield of different plots, with a range of relative error from 9.83% to 15.74%. The results of different selective cutting scenarios suggested that the optimal selective cutting measure should be cutting 30% culms of age 6, 80% culms of age 7, and all culms thereafter (above age 8) in winter every other year. The vegetation carbon density and harvested carbon density of this selective cutting method can increase by 74.63% and 21.5%, respectively, compared with the current selective cutting measure. The optimized selective cutting measure developed in this study can significantly promote carbon density, yield, and carbon sink capacity in Moso bamboo forests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Theoretical modeling of yields for proton-induced reactions on natural and enriched molybdenum targets

    Energy Technology Data Exchange (ETDEWEB)

    Celler, A; Hou, X [University of British Columbia, Vancouver, BC, Canada, (Canada); Benard, F; Ruth, T, E-mail: aceller@physics.ubc.ca, E-mail: xinchi@phas.ubc.ca, E-mail: fbenard@bccrc.ca, E-mail: truth@triumf.ca [BC Cancer Agency, Vancouver, BC (Canada)

    2011-09-07

    Recent acute shortage of medical radioisotopes prompted investigations into alternative methods of production and the use of a cyclotron and {sup 100}Mo(p,2n){sup 99m}Tc reaction has been considered. In this context, the production yields of {sup 99m}Tc and various other radioactive and stable isotopes which will be created in the process have to be investigated, as these may affect the diagnostic outcome and radiation dosimetry in human studies. Reaction conditions (beam and target characteristics, and irradiation and cooling times) need to be optimized in order to maximize the amount of {sup 99m}Tc and minimize impurities. Although ultimately careful experimental verification of these conditions must be performed, theoretical calculations can provide the initial guidance allowing for extensive investigations at little cost. We report the results of theoretically determined reaction yields for {sup 99m}Tc and other radioactive isotopes created when natural and enriched molybdenum targets are irradiated by protons. The cross-section calculations were performed using a computer program EMPIRE for the proton energy range 6-30 MeV. A computer graphical user interface for automatic calculation of production yields taking into account various reaction channels leading to the same final product has been created. The proposed approach allows us to theoretically estimate the amount of {sup 99m}Tc and its ratio relative to {sup 99g}Tc and other radioisotopes which must be considered reaction contaminants, potentially contributing to additional patient dose in diagnostic studies.

  12. Global sensitivity analysis of a local water balance model predicting evaporation, water yield and drought

    Science.gov (United States)

    Speich, Matthias; Zappa, Massimiliano; Lischke, Heike

    2017-04-01

    Evaporation and transpiration affect both catchment water yield and the growing conditions for vegetation. They are driven by climate, but also depend on vegetation, soil and land surface properties. In hydrological and land surface models, these properties may be included as constant parameters, or as state variables. Often, little is known about the effect of these variables on model outputs. In the present study, the effect of surface properties on evaporation was assessed in a global sensitivity analysis. To this effect, we developed a simple local water balance model combining state-of-the-art process formulations for evaporation, transpiration and soil water balance. The model is vertically one-dimensional, and the relative simplicity of its process formulations makes it suitable for integration in a spatially distributed model at regional scale. The main model outputs are annual total evaporation (TE, i.e. the sum of transpiration, soil evaporation and interception), and a drought index (DI), which is based on the ratio of actual and potential transpiration. This index represents the growing conditions for forest trees. The sensitivity analysis was conducted in two steps. First, a screening analysis was applied to identify unimportant parameters out of an initial set of 19 parameters. In a second step, a statistical meta-model was applied to a sample of 800 model runs, in which the values of the important parameters were varied. Parameter effect and interactions were analyzed with effects plots. The model was driven with forcing data from ten meteorological stations in Switzerland, representing a wide range of precipitation regimes across a strong temperature gradient. Of the 19 original parameters, eight were identified as important in the screening analysis. Both steps highlighted the importance of Plant Available Water Capacity (AWC) and Leaf Area Index (LAI). However, their effect varies greatly across stations. For example, while a transition from a

  13. Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

    Science.gov (United States)

    Hoffman, A.; Forest, C. E.; Kemanian, A.

    2016-12-01

    A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with

  14. Scale Model Thruster Acoustic Measurement Results

    Science.gov (United States)

    Vargas, Magda; Kenny, R. Jeremy

    2013-01-01

    The Space Launch System (SLS) Scale Model Acoustic Test (SMAT) is a 5% scale representation of the SLS vehicle, mobile launcher, tower, and launch pad trench. The SLS launch propulsion system will be comprised of the Rocket Assisted Take-Off (RATO) motors representing the solid boosters and 4 Gas Hydrogen (GH2) thrusters representing the core engines. The GH2 thrusters were tested in a horizontal configuration in order to characterize their performance. In Phase 1, a single thruster was fired to determine the engine performance parameters necessary for scaling a single engine. A cluster configuration, consisting of the 4 thrusters, was tested in Phase 2 to integrate the system and determine their combined performance. Acoustic and overpressure data was collected during both test phases in order to characterize the system's acoustic performance. The results from the single thruster and 4- thuster system are discussed and compared.

  15. CMS standard model Higgs boson results

    Directory of Open Access Journals (Sweden)

    Garcia-Abia Pablo

    2013-11-01

    Full Text Available In July 2012 CMS announced the discovery of a new boson with properties resembling those of the long-sought Higgs boson. The analysis of the proton-proton collision data recorded by the CMS detector at the LHC, corresponding to integrated luminosities of 5.1 fb−1 at √s = 7 TeV and 19.6 fb−1 at √s = 8 TeV, confirm the Higgs-like nature of the new boson, with a signal strength associated with vector bosons and fermions consistent with the expectations for a standard model (SM Higgs boson, and spin-parity clearly favouring the scalar nature of the new boson. In this note I review the updated results of the CMS experiment.

  16. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  17. a deterministic model for predicting water yield from two different watersheds

    Directory of Open Access Journals (Sweden)

    Putu Sudira

    2013-07-01

    The final test of the adequacy of the model lay in a comparison of observed and simulated runoff The comparison showed that the observed and simulated runoff values are not significantly different. This was based on the results obtained from statistical measures to test the model. The model did a better simulation in the smaller watershed (Pogung-Code sub watershed than in the larger one (Pulo-Opak sub watershed.

  18. Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

    Science.gov (United States)

    Truong, Sandra K; McCormick, Ryan F; Mullet, John E

    2017-01-01

    Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development

  19. A Spatially Distributed Conceptual Model for Estimating Suspended Sediment Yield in Alpine catchments

    Science.gov (United States)

    Costa, Anna; Molnar, Peter; Anghileri, Daniela

    2017-04-01

    Suspended sediment is associated with nutrient and contaminant transport in water courses. Estimating suspended sediment load is relevant for water-quality assessment, recreational activities, reservoir sedimentation issues, and ecological habitat assessment. Suspended sediment concentration (SSC) along channels is usually reproduced by suspended sediment rating curves, which relate SSC to discharge with a power law equation. Large uncertainty characterizes rating curves based only on discharge, because sediment supply is not explicitly accounted for. The aim of this work is to develop a source-oriented formulation of suspended sediment dynamics and to estimate suspended sediment yield at the outlet of a large Alpine catchment (upper Rhône basin, Switzerland). We propose a novel modelling approach for suspended sediment which accounts for sediment supply by taking into account the variety of sediment sources in an Alpine environment, i.e. the spatial location of sediment sources (e.g. distance from the outlet and lithology) and the different processes of sediment production and transport (e.g. by rainfall, overland flow, snowmelt). Four main sediment sources, typical of Alpine environments, are included in our model: glacial erosion, hillslope erosion, channel erosion and erosion by mass wasting processes. The predictive model is based on gridded datasets of precipitation and air temperature which drive spatially distributed degree-day models to simulate snowmelt and ice-melt, and determine erosive rainfall. A mass balance at the grid scale determines daily runoff. Each cell belongs to a different sediment source (e.g. hillslope, channel, glacier cell). The amount of sediment entrained and transported in suspension is simulated through non-linear functions of runoff, specific for sediment production and transport processes occurring at the grid scale (e.g. rainfall erosion, snowmelt-driven overland flow). Erodibility factors identify different lithological units

  20. Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

    Science.gov (United States)

    Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

    2013-12-01

    /ha in many areas. The simulated yield changes in the future were both spatially explicit and dependent on the GCM used. The effectiveness of agronomic practices was highly varied across the region depending on soil type, agro-ecological zone and projected climate change. The results have critical implications for agronomic research and policy. The study challenges using a ';one size fits all' approach in the identification of potential adaptation strategies. The goal is to use models to target local, optimized solutions as part of the broader need for impact assessments at coarser scales.

  1. Revisiting Runoff Model Calibration: Airborne Snow Observatory Results Allow Improved Modeling Results

    Science.gov (United States)

    McGurk, B. J.; Painter, T. H.

    2014-12-01

    Deterministic snow accumulation and ablation simulation models are widely used by runoff managers throughout the world to predict runoff quantities and timing. Model fitting is typically based on matching modeled runoff volumes and timing with observed flow time series at a few points in the basin. In recent decades, sparse networks of point measurements of the mountain snowpacks have been available to compare with modeled snowpack, but the comparability of results from a snow sensor or course to model polygons of 5 to 50 sq. km is suspect. However, snowpack extent, depth, and derived snow water equivalent have been produced by the NASA/JPL Airborne Snow Observatory (ASO) mission for spring of 20013 and 2014 in the Tuolumne River basin above Hetch Hetchy Reservoir. These high-resolution snowpack data have exposed the weakness in a model calibration based on runoff alone. The U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) calibration that was based on 30-years of inflow to Hetch Hetchy produces reasonable inflow results, but modeled spatial snowpack location and water quantity diverged significantly from the weekly measurements made by ASO during the two ablation seasons. The reason is that the PRMS model has many flow paths, storages, and water transfer equations, and a calibrated outflow time series can be right for many wrong reasons. The addition of a detailed knowledge of snow extent and water content constrains the model so that it is a better representation of the actual watershed hydrology. The mechanics of recalibrating PRMS to the ASO measurements will be described, and comparisons in observed versus modeled flow for both a small subbasin and the entire Hetch Hetchy basin will be shown. The recalibrated model provided a bitter fit to the snowmelt recession, a key factor for water managers as they balance declining inflows with demand for power generation and ecosystem releases during the final months of snow melt runoff.

  2. Observed light yield of scintillation pixels: Extending the two-ray model

    Science.gov (United States)

    Kantorski, Igor; Jurkowski, Jacek; Drozdowski, Winicjusz

    2016-09-01

    In this paper we propose an extended, two dimensional model describing the propagation of scintillation photons inside a cuboid crystal until they reach a PMT window. In the simplest approach the model considers two main reasons for light losses: standard absorption obeying the classical Lambert-Beer law and non-ideal reflectivity of the "mummy" covering formed by several layers of Teflon tape wrapping the sample. Results of the model calculations are juxtaposed with experimental data as well as with predictions of an earlier, one dimensional model.

  3. Immersive visualization of dynamic CFD model results

    International Nuclear Information System (INIS)

    Comparato, J.R.; Ringel, K.L.; Heath, D.J.

    2004-01-01

    With immersive visualization the engineer has the means for vividly understanding problem causes and discovering opportunities to improve design. Software can generate an interactive world in which collaborators experience the results of complex mathematical simulations such as computational fluid dynamic (CFD) modeling. Such software, while providing unique benefits over traditional visualization techniques, presents special development challenges. The visualization of large quantities of data interactively requires both significant computational power and shrewd data management. On the computational front, commodity hardware is outperforming large workstations in graphical quality and frame rates. Also, 64-bit commodity computing shows promise in enabling interactive visualization of large datasets. Initial interactive transient visualization methods and examples are presented, as well as development trends in commodity hardware and clustering. Interactive, immersive visualization relies on relevant data being stored in active memory for fast response to user requests. For large or transient datasets, data management becomes a key issue. Techniques for dynamic data loading and data reduction are presented as means to increase visualization performance. (author)

  4. Simplified geometric model for the calculation of neutron yield in an accelerator of 18 MV for radiotherapy

    International Nuclear Information System (INIS)

    Paredes G, L.C.; Balcazar G, M.; Francois L, J.L.; Azorin N, J.

    2008-01-01

    The results of the neutrons yield in different components of the bolster of an accelerator Varian Clinac 2100C of 18 MV for radiotherapy are presented, which contribute to the radiation of flight of neutrons in the patient and bolster planes. For the calculation of the neutrons yield, a simplified geometric model of spherical cell for the armor-plating of the bolster with Pb and W was used. Its were considered different materials for the Bremsstrahlung production and of neutrons produced through the photonuclear reactions and of electro disintegration, in function of the initial energy of the electron. The theoretical result of the total yield of neutrons is of 1.17x10 -3 n/e, considering to the choke in position of closed, in the patient plane with a distance source-surface of 100 cm; of which 15.73% corresponds to the target, 58.72% to the primary collimator, 4.53% to the levelled filter of Fe, 4.87% to the levelled filter of Ta and 16.15% to the closed choke. For an initial energy of the electrons of 18 MeV, a half energy of the neutrons of 2 MeV was obtained. The calculated values for radiation of experimental neutrons flight are inferior to the maxima limit specified in the NCRP-102 and IEC-60601-201.Ed.2.0 reports. The absorbed dose of neutrons determined through the measurements with TLD dosemeters in the isocenter to 100 cm of the target when the choke is closed one, is approximately 3 times greater that the calculated for armor-plating of W and 1.9 times greater than an armor-plating of Pb. (Author)

  5. Linkage of PRA models. Phase 1, Results

    Energy Technology Data Exchange (ETDEWEB)

    Smith, C.L.; Knudsen, J.K.; Kelly, D.L.

    1995-12-01

    The goal of the Phase I work of the ``Linkage of PRA Models`` project was to postulate methods of providing guidance for US Nuclear Regulator Commission (NRC) personnel on the selection and usage of probabilistic risk assessment (PRA) models that are best suited to the analysis they are performing. In particular, methods and associated features are provided for (a) the selection of an appropriate PRA model for a particular analysis, (b) complementary evaluation tools for the analysis, and (c) a PRA model cross-referencing method. As part of this work, three areas adjoining ``linking`` analyses to PRA models were investigated: (a) the PRA models that are currently available, (b) the various types of analyses that are performed within the NRC, and (c) the difficulty in trying to provide a ``generic`` classification scheme to groups plants based upon a particular plant attribute.

  6. Engineering Glass Passivation Layers -Model Results

    Energy Technology Data Exchange (ETDEWEB)

    Skorski, Daniel C.; Ryan, Joseph V.; Strachan, Denis M.; Lepry, William C.

    2011-08-08

    The immobilization of radioactive waste into glass waste forms is a baseline process of nuclear waste management not only in the United States, but worldwide. The rate of radionuclide release from these glasses is a critical measure of the quality of the waste form. Over long-term tests and using extrapolations of ancient analogues, it has been shown that well designed glasses exhibit a dissolution rate that quickly decreases to a slow residual rate for the lifetime of the glass. The mechanistic cause of this decreased corrosion rate is a subject of debate, with one of the major theories suggesting that the decrease is caused by the formation of corrosion products in such a manner as to present a diffusion barrier on the surface of the glass. Although there is much evidence of this type of mechanism, there has been no attempt to engineer the effect to maximize the passivating qualities of the corrosion products. This study represents the first attempt to engineer the creation of passivating phases on the surface of glasses. Our approach utilizes interactions between the dissolving glass and elements from the disposal environment to create impermeable capping layers. By drawing from other corrosion studies in areas where passivation layers have been successfully engineered to protect the bulk material, we present here a report on mineral phases that are likely have a morphological tendency to encrust the surface of the glass. Our modeling has focused on using the AFCI glass system in a carbonate, sulfate, and phosphate rich environment. We evaluate the minerals predicted to form to determine the likelihood of the formation of a protective layer on the surface of the glass. We have also modeled individual ions in solutions vs. pH and the addition of aluminum and silicon. These results allow us to understand the pH and ion concentration dependence of mineral formation. We have determined that iron minerals are likely to form a complete incrustation layer and we plan

  7. Assessment of AquaCrop model in the simulation of durum wheat (Triticum aestivum L. growth and yield under different water regimes in Tadla- Morocco

    Directory of Open Access Journals (Sweden)

    Bassou BOUAZZAM

    2017-09-01

    Full Text Available Simulation models that clarify the effects of water on crop yield are useful tools for improving farm level water management and optimizing water use efficiency. In this study, AquaCrop was evaluated for Karim genotype which is the main durum winter wheat (Triticum aestivum L. practiced in Tadla. AquaCrop is based on the water-driven growth module, in that transpiration is converted into biomass through a water productivity parameter. The model was calibrated on data from a full irrigation treatment in 2014/15 and validated on other stressed and unstressed treatments including rain-fed conditions in 2014/15 and 2015/16. Results showed that the model provided excellent simulations of canopy cover, biomass and grain yield. Overall, the relationship between observed and modeled wheat grain yield for all treatments combined produced an R2 of 0.79, a mean squared error of 1.01 t ha-1 and an efficiency coefficient of 0.68. The model satisfactory predicted the trend of soil water reserve. Consequently, AquaCrop can be a valuable tool for simulating wheat grain yield in Tadla plain, particularly considering the fact that the model requires a relatively small number of input data. However, the performance of the model has to be fine-tuned under a wider range of conditions.

  8. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model

    Science.gov (United States)

    Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

    2017-04-01

    The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEIG90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding

  9. Yield strengths of flows on the earth, Mars, and moon. [application of Bingham plastic model to lava flows

    Science.gov (United States)

    Moore, H. J.; Arthur, D. W. G.; Schaber, G. G.

    1978-01-01

    Dimensions of flows on the earth, Mars, and moon and their topographic gradients obtained from remote measurements are used to calculate yield strengths with a view to explore the validity of the Bingham plastic model and determine whether there is a relation between yield strengths and silica contents. Other factors are considered such as the vagaries of natural phenomena that might contribute to erroneous interpretations and measurements. Comparison of yield strengths of Martian and lunar flows with terrestrial flows suggests that the Martian and lunar flows are more akin to terrestrial basalts than they are to terrestrial andesites, trachytes, and rhyolites.

  10. Modeling and Field Results from Seismic Stimulation

    International Nuclear Information System (INIS)

    Majer, E.; Pride, S.; Lo, W.; Daley, T.; Nakagawa, Seiji; Sposito, Garrison; Roberts, P.

    2006-01-01

    Modeling the effect of seismic stimulation employing Maxwell-Boltzmann theory shows that the important component of stimulation is mechanical rather than fluid pressure effects. Modeling using Biot theory (two phases) shows that the pressure effects diffuse too quickly to be of practical significance. Field data from actual stimulation will be shown to compare to theory

  11. Modeling of the Strain Rate Dependency of Polycarbonate’s Yield Stress: Evaluation of Four Constitutive Equations

    OpenAIRE

    Abdullah A. Al-Juaid; Ramzi Othman

    2016-01-01

    The main focus of this paper is in evaluating four constitutive relations which model the strain rate dependency of polymers yield stress. Namely, the two-term power-law, the Ree-Eyring, the cooperative, and the newly modified-Eyring equations are used to fit tensile and compression yield stresses of polycarbonate, which are obtained from the literature. The four equations give good agreement with the experimental data. Despite using only three material constants, the modified-Eyring equation...

  12. Prediction of 305 d milk yield in Jersey Cattle Using ANN Modelling

    African Journals Online (AJOL)

    ozcan_eren

    The accurate measurement or prediction of milk yield is essential to their economy (Fernandez et al., 2007). ... economic predictions, and in medical diagnoses. ..... Jadhav, R.G., Vaıdya, M.S. & Toro, V.A., 1998. Prediction of first lactation milk yield based on part lactation performance in crossbred cows. J. Bombay Vet. Coll.

  13. Quantitatively Verifying the Results' Rationality for Farmland Quality Evaluation with Crop Yield, a Case Study in the Northwest Henan Province, China

    Science.gov (United States)

    Huang, Junchang; Wang, Song

    2016-01-01

    Evaluating the assessing results’ rationality for farmland quality (FQ) is usually qualitative and based on farmers and experts’ perceptions of soil quality and crop yield. Its quantitative checking still remains difficult and is likely ignored. In this paper, FQ in Xiuwu County, the Northwest Henan Province, China was evaluated by the gray relational analysis (GRA) method and the traditional analytic hierarchy process (AHP) method. The consistency rate of two results was analysed. Research focused on proposing one method of testing the evaluation results’ rationality for FQ based on the crop yield. Firstly generating a grade map of crop yield and overlying it with the FQ evaluation maps. Then analysing their consistency rate for each grade in the same spatial position. Finally examining the consistency effects and allowing for a decision on adopting the results. The results showed that the area rate consistency and matching evaluation unit numbers between the two methods were 84.68% and 87.29%, respectively, and the space distribution was approximately equal. The area consistency rates between crop yield level and FQ evaluation levels by GRA and AHP were 78.15% and 74.29%, respectively. Therefore, the verifying effects of GRA and AHP were near, good and acceptable, and the FQ results from both could reflect the crop yield levels. The evaluation results by GCA, as a whole, were slightly more rational than that by AHP. PMID:27490247

  14. Acetic acid and pepsin result in high yield, high purity and low macrophage response collagen for biomedical applications.

    Science.gov (United States)

    Delgado, Luis M; Shologu, Naledi; Fuller, Kieran; Zeugolis, Dimitrios I

    2017-10-25

    Collagen based devices are frequently associated with foreign body response. Although several pre- (e.g. species, state of animal, tissue) and post- (e.g. cross-linking, scaffold architecture) extraction method factors have a profound effect on foreign body response, little is known about which and how during the extraction process factors mediate foreign body response. In this study, we assessed the influence of acetic acid and hydrochloric acid and the utilisation or not of pepsin or salt precipitation during collagen extraction on the yield, purity, free amines, denaturation temperature, resistance to collagenase degradation and macrophage response. Acetic acid/pepsin extracted collagen exhibited the highest yield, purity and free amine content and the lowest denaturation temperature. No differences in resistance to collagenase digestion were detected between the groups. Although all treatments exhibited similar macrophage morphology comprised of round cells (M1 phenotype), elongated cells (M2 phenotype) and cell aggregates (foreign body response), significantly more elongated cells were observed on HC films. Although no differences in metabolic activity were observed between the groups, the DNA concentration was significantly lower for the hydrochloric acid treatments. Further, cytokine analysis revealed that hydrochloric acid treatments induced significantly higher IL-1β and TNF-α release with respect to acetic acid treatments. Salt precipitation did not influence the parameters assessed. Collectively, these data suggest that during the collagen extraction process variables should also be monitored as, evidently, they affect the physicochemical and biological properties of collagen preparations.

  15. Determining the Threshold Value of Basil Yield Reduction and Evaluation of Water Uptake Models under Salinity Stress Condition

    OpenAIRE

    M. Sarai Tabrizi; H. Babazadeh; M. Homaee; F. Kaveh Kaveh; M. Parsinejad

    2016-01-01

    Introduction: Several mathematical models are being used for assessing the plant response to the salinity of the root zone. The salinity of the soil and water resources is a major challenge for agricultural sector in Iran. Several mathematical models have been developed for plant responses to the salinity stress. However, these models are often applicable in particular conditions. The objectives of this study were to evaluate the threshold value of Basil yield reduction, modeling Basil respon...

  16. Crop modelling as a tool to separate the influence of the soil and weather on crop yields

    Science.gov (United States)

    Mathe-Gaspar, Gabriella; Fodor, Nandor; Pokovai, Klara; Kovacs, Geza Janos

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

  17. Crop modelling as a tool to separate the influences of the soil and weather on crop yields

    Science.gov (United States)

    Mathe-Gaspar, G.; Fodor, N.; Pokovai, K.; Kovacs, G. J.

    2003-04-01

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

  18. Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

    Science.gov (United States)

    Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

    2015-12-01

    Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

  19. Integrating remotely sensed leaf area index and leaf nitrogen accumulation with RiceGrow model based on particle swarm optimization algorithm for rice grain yield assessment

    Science.gov (United States)

    Wang, Hang; Zhu, Yan; Li, Wenlong; Cao, Weixing; Tian, Yongchao

    2014-01-01

    A regional rice (Oryza sativa) grain yield prediction technique was proposed by integration of ground-based and spaceborne remote sensing (RS) data with the rice growth model (RiceGrow) through a new particle swarm optimization (PSO) algorithm. Based on an initialization/parameterization strategy (calibration), two agronomic indicators, leaf area index (LAI) and leaf nitrogen accumulation (LNA) remotely sensed by field spectra and satellite images, were combined to serve as an external assimilation parameter and integrated with the RiceGrow model for inversion of three model management parameters, including sowing date, sowing rate, and nitrogen rate. Rice grain yield was then predicted by inputting these optimized parameters into the reinitialized model. PSO was used for the parameterization and regionalization of the integrated model and compared with the shuffled complex evolution-University of Arizona (SCE-UA) optimization algorithm. The test results showed that LAI together with LNA as the integrated parameter performed better than each alone for crop model parameter initialization. PSO also performed better than SCE-UA in terms of running efficiency and assimilation results, indicating that PSO is a reliable optimization method for assimilating RS information and the crop growth model. The integrated model also had improved precision for predicting rice grain yield.

  20. Modeling the Seasonal Response of Sediment Yield to Climate Change in the Laos-Vietnam Transnational Upper Ca River Watershed

    Directory of Open Access Journals (Sweden)

    Pham Quy Giang

    2014-06-01

    Full Text Available Changes in stream sediment yield impact material fluxes, water quality, aquatic geochemistry, stream morphology, and aquatic habitats. Quantifying sediment yield is important for predicting watershed erosion and understanding sediment transport processes. In the context of a changing climate, this is important for the management and conservation of soil and water to cope with the effects of increasingly severe climate conditions that are likely to occur in the near future. This study aims to predict seasonal trends in sediment yield under climate change impacts in the Laos-Vietnam transnational Upper Ca River Watershed. The SWAT model was used for hydrological simulation, coupled with future climate projections under three IPCC emission scenarios, B1, B2, and A2. We found an increase in the seasonality of sediment yield due to increases in the seasonality of both rainfall and runoff. However, the increase of sediment yield in the wet season appeared more significant than its decrease in the dry season, due to more significant increases in rainfall as well as runoff in that season compared to decreases in these factors in the dry season. Consequently, annual sediment yield is predicted to increase, with a rate ranging from 12.1% to 16.5% by the end of this century, depending on emission scenario. The seasonal sensitivity of sediment yield to climate change found in this study is expected to be useful in collaborative management initiatives related to soil and water resources in the watershed.

  1. Coupled Michigan MHD - Rice Convection Model Results

    Science.gov (United States)

    de Zeeuw, D.; Sazykin, S.; Wolf, D.; Gombosi, T.; Powell, K.

    2002-12-01

    A new high performance Rice Convection Model (RCM) has been coupled to the adaptive-grid Michigan MHD model (BATSRUS). This fully coupled code allows us to self-consistently simulate the physics in the inner and middle magnetosphere. A study will be presented of the basic characteristics of the inner and middle magnetosphere in the context of a single coupled-code run for idealized storm inputs. The analysis will include region-2 currents, shielding of the inner magnetosphere, partial ring currents, pressure distribution, magnetic field inflation, and distribution of pV^gamma.

  2. Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

    Science.gov (United States)

    Franch, B.; Vermote, E.; Roger, J. C.; Skakun, S.; Becker-Reshef, I.; Justice, C. O.

    2017-12-01

    Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season and the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data. These methods were applied to MODIS CMG data in Ukraine, the US and China with errors around 10%. However, the NDVI is saturated for yield values higher than 4 MT/ha. As a consequence, the model had to be re-calibrated in each country and the validation of the national yields showed low correlation coefficients. In this study we present a new model based on the extrapolation of the pure wheat signal (100% of wheat within the pixel) from MODIS data at 1km resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national yield of winter wheat in the United States and Ukraine from 2001 to 2016.

  3. Graphical interpretation of numerical model results

    International Nuclear Information System (INIS)

    Drewes, D.R.

    1979-01-01

    Computer software has been developed to produce high quality graphical displays of data from a numerical grid model. The code uses an existing graphical display package (DISSPLA) and overcomes some of the problems of both line-printer output and traditional graphics. The software has been designed to be flexible enough to handle arbitrarily placed computation grids and a variety of display requirements

  4. Modelling Pasture-based Automatic Milking System Herds: The Impact of Large Herd on Milk Yield and Economics

    Directory of Open Access Journals (Sweden)

    M. R. Islam

    2015-07-01

    Full Text Available The aim of this modelling study was to investigate the effect of large herd size (and land areas on walking distances and milking interval (MI, and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR in an automatic milking system (AMS. Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows, 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as ‘moderate’; optimum pasture utilisation of 19.7 t DM/ha, termed as ‘high’ and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance

  5. Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model

    Directory of Open Access Journals (Sweden)

    Bello Al-Amin D.

    2017-09-01

    Full Text Available Abundant rainfall areas promote sediment yield at both sub-watershed and watershed scale due to soil erosion and increase siltation of river channel, but it can be curtailed through planned urbanization. The urbanization of Skudai watershed is analysed from historical and future perspective. A GIS-based model (Hydrological Simulation Programme-FORTRAN-HSPF is used to modelled sediment flow using basin-wide simulation, and the output result is utilized in evaluating sediment yield reduction due to increased urbanization by swapping multiple temporal land-use of decadent time-steps. The analysis indicates that sediment yield reduces with increase urban built-up and decrease forest and agricultural land. An estimated 12 400 tons of sediment will be reduced for every 27% increase in built-up areas under high rainfall condition and 1 490 tons at low rainfall. The sensitivity analysis of land-use classes shows that built-up, forest and barren are more sensitive to sediment yield reduction compared to wetland and agricultural land at both high and low rainfall. The result of the study suggests that increased urbanization reduced sediment yield in proportion to the rainfall condition and can be used as an alternative approach for soil conservation at watershed scale independent of climate condition.

  6. Hybrid life cycle assessment (LCA) does not necessarily yield more accurate results than process-based LCA

    NARCIS (Netherlands)

    Yang, Yi; Heijungs, Reinout; Brandão, Miguel

    2017-01-01

    Hybrid life cycle assessment (LCA), through combining input-output (IO) models and process-based LCA for a complete system boundary, is widely recognized as a more accurate approach than process-based LCA with an incomplete system boundary. Without a complete process model for verification, however,

  7. Visual Mapping of Sedimentary Facies Can Yield Accurate And Geomorphically Meaningful Results at Morphological Unit to River Segment Scales

    Science.gov (United States)

    Pasternack, G. B.; Wyrick, J. R.; Jackson, J. R.

    2014-12-01

    Long practiced in fisheries, visual substrate mapping of coarse-bedded rivers is eschewed by geomorphologists for inaccuracy and limited sizing data. Geomorphologists perform time-consuming measurements of surficial grains, with the few locations precluding spatially explicit mapping and analysis of sediment facies. Remote sensing works for bare land, but not vegetated or subaqueous sediments. As visual systems apply the log2 Wentworth scale made for sieving, they suffer from human inability to readily discern those classes. We hypothesized that size classes centered on the PDF of the anticipated sediment size distribution would enable field crews to accurately (i) identify presence/absence of each class in a facies patch and (ii) estimate the relative amount of each class to within 10%. We first tested 6 people using 14 measured samples with different mixtures. Next, we carried out facies mapping for ~ 37 km of the lower Yuba River in California. Finally, we tested the resulting data to see if it produced statistically significant hydraulic-sedimentary-geomorphic results. Presence/absence performance error was 0-4% for four people, 13% for one person, and 33% for one person. The last person was excluded from further effort. For the abundance estimation performance error was 1% for one person, 7-12% for three people, and 33% for one person. This last person was further trained and re-tested. We found that the samples easiest to visually quantify were unimodal and bimodal, while those most difficult had nearly equal amounts of each size. This confirms psychological studies showing that humans have a more difficult time quantifying abundances of subgroups when confronted with well-mixed groups. In the Yuba, mean grain size decreased downstream, as is typical for an alluvial river. When averaged by reach, mean grain size and bed slope were correlated with an r2 of 0.95. At the morphological unit (MU) scale, eight in-channel bed MU types had an r2 of 0.90 between mean

  8. Drought mitigation in perennial crops by fertilization and adjustments of regional yield models for future climate variability

    Science.gov (United States)

    Kantola, I. B.; Blanc-Betes, E.; Gomez-Casanovas, N.; Masters, M. D.; Bernacchi, C.; DeLucia, E. H.

    2017-12-01

    Increased variability and intensity of precipitation in the Midwest agricultural belt due to climate change is a major concern. The success of perennial bioenergy crops in replacing maize for bioethanol production is dependent on sustained yields that exceed maize, and the marketing of perennial crops often emphasizes the resilience of perennial agriculture to climate stressors. Land conversion from maize for bioethanol to Miscanthus x giganteus (miscanthus) increases yields and annual evapotranspiration rates (ET). However, establishment of miscanthus also increases biome water use efficiency (the ratio between net ecosystem productivity after harvest and ET), due to greater belowground biomass in miscanthus than in maize or soybean. In 2012, a widespread drought reduced the yield of 5-year-old miscanthus plots in central Illinois by 36% compared to the previous two years. Eddy covariance data indicated continued soil water deficit during the hydrologically-normal growing season in 2013 and miscanthus yield failed to rebound as expected, lagging behind pre-drought yields by an average of 53% over the next three years. In early 2014, nitrogen fertilizer was applied to half of mature (7-year-old) miscanthus plots in an effort to improve yields. In plots with annual post-emergence application of 60 kg ha-1 of urea, peak biomass was 29% greater than unfertilized miscanthus in 2014, and 113% greater in 2015, achieving statistically similar yields to the pre-drought average. Regional-scale models of perennial crop productivity use 30-year climate averages that are inadequate for predicting long-term effects of short-term extremes on perennial crops. Modeled predictions of perennial crop productivity incorporating repeated extreme weather events, observed crop response, and the use of management practices to mitigate water deficit demonstrate divergent effects on predicted yields.

  9. What is the Best Model Specification and Earth Observation Product for Predicting Regional Grain Yields in Food Insecure Countries?

    Science.gov (United States)

    Davenport, F., IV; Harrison, L.; Shukla, S.; Husak, G. J.; Funk, C. C.

    2017-12-01

    We evaluate the predictive accuracy of an ensemble of empirical model specifications that use earth observation data to predict sub-national grain yields in Mexico and East Africa. Products that are actively used for seasonal drought monitoring are tested as yield predictors. Our research is driven by the fact that East Africa is a region where decisions regarding agricultural production are critical to preventing the loss of economic livelihoods and human life. Regional grain yield forecasts can be used to anticipate availability and prices of key staples, which can turn can inform decisions about targeting humanitarian response such as food aid. Our objective is to identify-for a given region, grain, and time year- what type of model and/or earth observation can most accurately predict end of season yields. We fit a set of models to county level panel data from Mexico, Kenya, Sudan, South Sudan, and Somalia. We then examine out of sample predicative accuracy using various linear and non-linear models that incorporate spatial and time varying coefficients. We compare accuracy within and across models that use predictor variables from remotely sensed measures of precipitation, temperature, soil moisture, and other land surface processes. We also examine at what point in the season a given model or product is most useful for determining predictive accuracy. Finally we compare predictive accuracy across a variety of agricultural regimes including high intensity irrigated commercial agricultural and rain fed subsistence level farms.

  10. Ignalina NPP Safety Analysis: Models and Results

    International Nuclear Information System (INIS)

    Uspuras, E.

    1999-01-01

    Research directions, linked to safety assessment of the Ignalina NPP, of the scientific safety analysis group are presented: Thermal-hydraulic analysis of accidents and operational transients; Thermal-hydraulic assessment of Ignalina NPP Accident Localization System and other compartments; Structural analysis of plant components, piping and other parts of Main Circulation Circuit; Assessment of RBMK-1500 reactor core and other. Models and main works carried out last year are described. (author)

  11. Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

    Directory of Open Access Journals (Sweden)

    Jaime Araujo Cobuci

    2005-03-01

    Full Text Available Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Covariance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56 were higher than those obtained by RRM2 (0.15 to 0.31. Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

  12. Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

    Science.gov (United States)

    Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

    2017-03-24

    The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

  13. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

    Science.gov (United States)

    Marshall, M.; Tu, K. P.

    2015-12-01

    Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

  14. Constraints on the rare tau decays from {mu} {yields} e{gamma} in the supersymmetric see-saw model

    Energy Technology Data Exchange (ETDEWEB)

    Ibarra, A. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Simonetto, C. [Technische Univ., Muenchen (Germany). Physik-Department

    2008-02-15

    It is now a firmly established fact that all family lepton numbers are violated in Nature. In this paper we discuss the implications of this observation for future searches for rare tau decays in the supersymmetric see-saw model. Using the two loop renormalization group evolution of the soft terms and the Yukawa couplings we show that there exists a lower bound on the rate of the rare process {mu}{yields}e{gamma} of the form BR({mu}{yields}e{gamma})>or similar C x BR({tau}{yields}{mu}{gamma})BR({tau}{yields}e{gamma}), where C is a constant that depends on supersymmetric parameters. Our only assumption is the absence of cancellations among the high-energy see-saw parameters. We also discuss the implications of this bound for future searches for rare tau decays. In particular, for large regions of the mSUGRA parameter space, we show that present B-factories could discover either {tau}{yields}{mu}{gamma} or {tau}{yields}e{gamma}, but not both. (orig.)

  15. How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

    Science.gov (United States)

    Durand, Jean-Louis; Delusca, Kenel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Weigel, Hans Johachim; Ruane, Alexander Clark; Rosenzweig, Cynthia E.; Jones, Jim; Ahuja, Laj; hide

    2017-01-01

    This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

  16. A major challenge for modeling conservation-based water use reductions in aquifers supporting irrigated agriculture: The specific yield quandary

    Science.gov (United States)

    Butler, J. J., Jr.; Whittemore, D. O.; Wilson, B. B.; Bohling, G.

    2017-12-01

    Many large regional aquifers supporting irrigated agriculture are experiencing high rates of water-level decline. The primary means of moderating these rates is to reduce pumping. The key question is what percent pumping reduction will significantly impact decline rates. We have recently developed a water-balance approach to address this question for subareas (100s to 1000s km2 in size) of seasonally pumped aquifers (Butler et al., GRL, 2016). This approach also provides an estimate of specific yield (Sy), which has been difficult to estimate from field data at the scale of modeling analyses. When applied to subareas of the High Plains aquifer in Kansas, this approach reveals that the Sy estimate is much lower (as much as a factor of five or more) than expected for an unconsolidated aquifer. One explanation is that the aquifer is heterogeneous with considerable amounts of fine material, whereas field data, such as drillers' logs, are often biased towards coarser intervals. An additional explanation, which appears to have received little attention, is the impact of entrapped air. In seasonally pumped systems, water levels pass through the same aquifer intervals multiple times, giving ample opportunity for air to be entrapped. This entrapped air imbues the aquifer with a specific yield that is considerably lower than what would be expected from lithology. If unrecognized, a larger-than-actual Sy value is input into the aquifer model. This can lead to the inadvertent use of the same-year recharge assumption, which may not be appropriate for many conditions (e.g., large depths to water), and can also result in artificially low estimates of net inflow for a depleting aquifer. Moreover, failure to recognize this condition can bedevil efforts to model conservation-based water use reductions. In that case, models will leave the range of conditions for which they have been calibrated and can become more vulnerable to parameter errors. Conservation-based water use reductions

  17. A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US

    Directory of Open Access Journals (Sweden)

    Andrew E. Suyker

    2013-11-01

    Full Text Available Remote sensing techniques that provide synoptic and repetitive observations over large geographic areas have become increasingly important in studying the role of agriculture in global carbon cycles. However, it is still challenging to model crop yields based on remotely sensed data due to the variation in radiation use efficiency (RUE across crop types and the effects of spatial heterogeneity. In this paper, we propose a production efficiency model-based method to estimate corn and soybean yields with MODerate Resolution Imaging Spectroradiometer (MODIS data by explicitly handling the following two issues: (1 field-measured RUE values for corn and soybean are applied to relatively pure pixels instead of the biome-wide RUE value prescribed in the MODIS vegetation productivity product (MOD17; and (2 contributions to productivity from vegetation other than crops in mixed pixels are deducted at the level of MODIS resolution. Our estimated yields statistically correlate with the national survey data for rainfed counties in the Midwestern US with low errors for both corn (R2 = 0.77; RMSE = 0.89 MT/ha and soybeans (R2 = 0.66; RMSE = 0.38 MT/ha. Because the proposed algorithm does not require any retrospective analysis that constructs empirical relationships between the reported yields and remotely sensed data, it could monitor crop yields over large areas.

  18. Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

    Science.gov (United States)

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

  19. Simulation of spring barley yield in different climatic zones of Northern and Central Europe. A comparison of nine crop models

    Czech Academy of Sciences Publication Activity Database

    Rötter, R.P.; Palosuo, T.; Kersebaum, K. C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J. E.; Patil, R. H.; Ruget, F.; Takáč, J.; Trnka, Miroslav

    2012-01-01

    Roč. 133, July 2012 (2012), s. 23-36 ISSN 0378-4290 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073 Institutional research plan: CEZ:AV0Z60870520 Keywords : Climate * Crop growth simulation * Model comparison * Spring barley * Yield variability * Uncertainty Subject RIV: EH - Ecology, Behaviour Impact factor: 2.474, year: 2012

  20. Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson-Siegel Model

    DEFF Research Database (Denmark)

    Exterkate, Peter; Dijk, Dick van; Heij, Christiaan

    2013-01-01

    This paper compares various ways of extracting macroeconomic information from a data-rich environment for forecasting the yield curve using the Nelson–Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of the availabl...

  1. Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

    Science.gov (United States)

    The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

  2. Estimation of rice grain yield from dual-polarization Radarsat-2 SAR data by integrating a rice canopy scattering model and a genetic algorithm

    Science.gov (United States)

    Zhang, Yuan; Yang, Bin; Liu, Xiaohui; Wang, Cuizhen

    2017-05-01

    Fast and accurate estimation of rice yield plays a role in forecasting rice productivity for ensuring regional or national food security. Microwave synthetic aperture radar (SAR) data has been proved to have a great potential for rice monitoring and parameters retrieval. In this study, a rice canopy scattering model (RCSM) was revised and then was applied to simulate the backscatter of rice canopy. The combination of RCSM and genetic algorithm (GA) was proposed for retrieving two important rice parameters relating to grain yield, ear length and ear number density, from a C-band, dual-polarization (HH and HV) Radarsat-2 SAR data. The stability of retrieved results of GA inversion was also evaluated by changing various parameter configurations. Results show that RCSM can effectively simulate backscattering coefficients of rice canopy at HH and HV mode with an error of <1 dB. Reasonable selection of GA's parameters is essential for stability and efficiency of rice parameter retrieval. Two rice parameters are retrieved by the proposed RCSM-GA technology with better accuracy. The rice ear length are estimated with error of <1.5 cm, and ear number density with error of <23 #/m2. Rice grain yields are effectively estimated and mapped by the retrieved ear length and number density via a simple yield regression equation. This study further illustrates the capability of C-band Radarsat-2 SAR data on retrieval of rice ear parameters and the practicability of radar remote sensing technology for operational yield estimation.

  3. The estimation of rice paddy yield with GRAMI crop model and Geostationary Ocean Color Imager (GOCI) image over South Korea

    Science.gov (United States)

    Yeom, J. M.; Kim, H. O.

    2014-12-01

    In this study, we estimated the rice paddy yield with moderate geostationary satellite based vegetation products and GRAMI model over South Korea. Rice is the most popular staple food for Asian people. In addition, the effects of climate change are getting stronger especially in Asian region, where the most of rice are cultivated. Therefore, accurate and timely prediction of rice yield is one of the most important to accomplish food security and to prepare natural disasters such as crop defoliation, drought, and pest infestation. In the present study, GOCI, which is world first Geostationary Ocean Color Image, was used for estimating temporal vegetation indices of the rice paddy by adopting atmospheric correction BRDF modeling. For the atmospheric correction with LUT method based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S), MODIS atmospheric products such as MOD04, MOD05, MOD07 from NASA's Earth Observing System Data and Information System (EOSDIS) were used. In order to correct the surface anisotropy effect, Ross-Thick Li-Sparse Reciprocal (RTLSR) BRDF model was performed at daily basis with 16day composite period. The estimated multi-temporal vegetation images was used for crop classification by using high resolution satellite images such as Rapideye, KOMPSAT-2 and KOMPSAT-3 to extract the proportional rice paddy area in corresponding a pixel of GOCI. In the case of GRAMI crop model, initial conditions are determined by performing every 2 weeks field works at Chonnam National University, Gwangju, Korea. The corrected GOCI vegetation products were incorporated with GRAMI model to predict rice yield estimation. The predicted rice yield was compared with field measurement of rice yield.

  4. Development of growth and yield models for southern hardwoods: site index determinations

    Science.gov (United States)

    John Paul McTague; Daniel J. Robison; David O' Loughlin; Joseph Roise; Robert Kellison

    2006-01-01

    Growth and yield data from across 13 southern States, collected from 1967 to 2004 from fully-stocked even-aged southern hardwood forests on a variety of site types, was used to calculate site index curves. These derived curves provide an efficient means to evaluate the productivity-age relation which varies across many sites. These curves were derived for mixed-species...

  5. Modeling osmotic salinity effects on yield characteristics of substrate-grown greenhouse crops

    NARCIS (Netherlands)

    Sonneveld, C.; Bos, van den A.L.; Voogt, W.

    2004-01-01

    In a series of experiments with different osmotic potentials in the root environment, various vegetables, and ornamentals were grown in a substrate system. The osmotic potential was varied by addition of nutrients. Yield characteristics of the crop were related to the osmotic potential of the

  6. Crop Yields and Climate Change to the Year 2000. Volume 2: Climate Model and Technical Appendixes.

    Science.gov (United States)

    1988-01-01

    it encounters the relatively flat region where yields are less sensitive to fluctuations of annual temperature and precipitation than they are in...the others are transpacific in nature (e.g., a negative correlation between the precipitation affec- ting wheat in Argentina and Australia). Hayes

  7. Developing a Coffee Yield Prediction and Integrated Soil Fertility Management Recommendation Model for Northern Tanzania

    NARCIS (Netherlands)

    Maro, G.P.; Mrema, J.P.; Msanya, B.M.; Janssen, B.H.; Teri, J.M.

    2014-01-01

    The aim of this study was to develop a simple and quantitative system for coffee yield estimation and nutrient input advice, so as to address the problem of declining annual coffee production in Tanzania (particularly in its Northern coffee zone), which is related to declining soil fertility. The

  8. Modelling of seed yield and its components in tall fescue (Festuca ...

    African Journals Online (AJOL)

    AJL

    2011-10-03

    Oct 3, 2011 ... number spikelet -1 (Y4), seed weight (Y5), and the seed yield (Z) of tall fescue were determined in field experiments from 2003 to .... the time of fertilisation (X1), the quantity of irrigation (X2), the amount of N applied (X3), the ...... certain agronomical traits in soybean [Glycine max (L.) Merr.]. Afr. J. Biotechnol.

  9. Yield and economic performance of organic and conventional cotton-based farming systems--results from a field trial in India.

    Science.gov (United States)

    Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M; Mäder, Paul

    2013-01-01

    The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007-2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1(st) crop cycle (cycle 1: 2007-2008) for cotton (-29%) and wheat (-27%), whereas in the 2(nd) crop cycle (cycle 2: 2009-2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (-1% in cycle 1, -11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and

  10. Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

    Science.gov (United States)

    Jégo, Guillaume; Pattey, Elizabeth; Mesbah, S. Morteza; Liu, Jiangui; Duchesne, Isabelle

    2015-09-01

    The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha-1). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha-1 for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha-1. Changes in rainfall distribution

  11. Calculations to support JET neutron yield calibration: Modelling of neutron emission from a compact DT neutron generator

    Energy Technology Data Exchange (ETDEWEB)

    Čufar, Aljaž, E-mail: aljaz.cufar@ijs.si [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Batistoni, Paola [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Conroy, Sean [Uppsala University, Department of Physics and Astronomy, PO Box 516, SE-75120 Uppsala (Sweden); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Ghani, Zamir [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Lengar, Igor [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Milocco, Alberto; Packer, Lee [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Pillon, Mario [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Popovichev, Sergey [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Snoj, Luka [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom)

    2017-03-01

    At the Joint European Torus (JET) the ex-vessel fission chambers and in-vessel activation detectors are used as the neutron production rate and neutron yield monitors respectively. In order to ensure that these detectors produce accurate measurements they need to be experimentally calibrated. A new calibration of neutron detectors to 14 MeV neutrons, resulting from deuterium–tritium (DT) plasmas, is planned at JET using a compact accelerator based neutron generator (NG) in which a D/T beam impinges on a solid target containing T/D, producing neutrons by DT fusion reactions. This paper presents the analysis that was performed to model the neutron source characteristics in terms of energy spectrum, angle–energy distribution and the effect of the neutron generator geometry. Different codes capable of simulating the accelerator based DT neutron sources are compared and sensitivities to uncertainties in the generator's internal structure analysed. The analysis was performed to support preparation to the experimental measurements performed to characterize the NG as a calibration source. Further extensive neutronics analyses, performed with this model of the NG, will be needed to support the neutron calibration experiments and take into account various differences between the calibration experiment and experiments using the plasma as a source of neutrons.

  12. Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties.

    Science.gov (United States)

    Parker, Sarah M; Serre, Thomas

    2015-01-01

    Non-accidental properties (NAPs) correspond to image properties that are invariant to changes in viewpoint (e.g., straight vs. curved contours) and are distinguished from metric properties (MPs) that can change continuously with in-depth object rotation (e.g., aspect ratio, degree of curvature, etc.). Behavioral and electrophysiological studies of shape processing have demonstrated greater sensitivity to differences in NAPs than in MPs. However, previous work has shown that such sensitivity is lacking in multiple-views models of object recognition such as Hmax. These models typically assume that object processing is based on populations of view-tuned neurons with distributed symmetrical bell-shaped tuning that are modulated at least as much by differences in MPs as in NAPs. Here, we test the hypothesis that unsupervised learning of invariances to object transformations may increase the sensitivity to differences in NAPs vs. MPs in Hmax. We collected a database of video sequences with objects slowly rotating in-depth in an attempt to mimic sequences viewed during object manipulation by young children during early developmental stages. We show that unsupervised learning yields shape-tuning in higher stages with greater sensitivity to differences in NAPs vs. MPs in agreement with monkey IT data. Together, these results suggest that greater NAP sensitivity may arise from experiencing different in-depth rotations of objects.

  13. Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties

    Directory of Open Access Journals (Sweden)

    Thomas eSerre

    2015-10-01

    Full Text Available Non-accidental properties (NAPs correspond to image properties that are invariant to changes in viewpoint (e.g., straight vs. curved contours and are distinguished from metric properties (MPs that can change continuously with in-depth object rotation (e.g., aspect ratio, degree of curvature, etc. Behavioral and electrophysiological studies of shape processing have demonstrated greater sensitivity to differences in NAPs than in MPs. However, previous work has shown that such sensitivity is lacking in multiple-views models of object recognition such as textsc{Hmax}. These models typically assume that object processing is based on populations of view-tuned neurons with distributed symmetrical bell-shaped tuning that are modulated at least as much by differences in MPs as in NAPs.Here, we test the hypothesis that unsupervised learning of invariances to object transformations may increase the sensitivity to differences in NAPs vs. MPs in textsc{Hmax}. We collected a database of video sequences with objects slowly rotating in-depth in an attempt to mimic sequences viewed during object manipulation by young children during early developmental stages. We show that unsupervised learning yields shape-tuning in higher stages with greater sensitivity to differences in NAPs vs. MPs in agreement with monkey IT data. Together, these results suggest that greater NAP sensitivity may arise from experiencing different in-depth rotations of objects.

  14. Calculations to support JET neutron yield calibration: Modelling of neutron emission from a compact DT neutron generator

    Science.gov (United States)

    Čufar, Aljaž; Batistoni, Paola; Conroy, Sean; Ghani, Zamir; Lengar, Igor; Milocco, Alberto; Packer, Lee; Pillon, Mario; Popovichev, Sergey; Snoj, Luka; JET Contributors

    2017-03-01

    At the Joint European Torus (JET) the ex-vessel fission chambers and in-vessel activation detectors are used as the neutron production rate and neutron yield monitors respectively. In order to ensure that these detectors produce accurate measurements they need to be experimentally calibrated. A new calibration of neutron detectors to 14 MeV neutrons, resulting from deuterium-tritium (DT) plasmas, is planned at JET using a compact accelerator based neutron generator (NG) in which a D/T beam impinges on a solid target containing T/D, producing neutrons by DT fusion reactions. This paper presents the analysis that was performed to model the neutron source characteristics in terms of energy spectrum, angle-energy distribution and the effect of the neutron generator geometry. Different codes capable of simulating the accelerator based DT neutron sources are compared and sensitivities to uncertainties in the generator's internal structure analysed. The analysis was performed to support preparation to the experimental measurements performed to characterize the NG as a calibration source. Further extensive neutronics analyses, performed with this model of the NG, will be needed to support the neutron calibration experiments and take into account various differences between the calibration experiment and experiments using the plasma as a source of neutrons.

  15. Proposed Model of Predicting the Reduced Yield Axial Load of Reinforced Concrete Columns Due to Casting Deficiency Effect

    Directory of Open Access Journals (Sweden)

    Achillopoulou Dimitra

    2014-12-01

    Full Text Available The study deals with the investigation of the effect of casting deficiencies- both experimentally and analytically on axial yield load or reinforced concrete columns. It includes 6 specimens of square section (150x150x500 mm of 24.37 MPa nominal concrete strength with 4 longitudinal steel bars of 8 mm (500 MPa nominal strength with confinement ratio ωc=0.15. Through casting procedure the necessary provisions defined by International Standards were not applied strictly in order to create construction deficiencies. These deficiencies are quantified geometrically without the use of expensive and expertise non-destructive methods and their effect on the axial load capacity of the concrete columns is calibrated trough a novel and simplified prediction model extracted by an experimental and analytical investigation that included 6 specimens. It is concluded that: a even with suitable repair, load reduction up to 22% is the outcome of the initial construction damage presence, b the lower dispersion is noted for the section damage index proposed, c extended damage alters the failure mode to brittle accompanied with longitudinal bars buckling, d the proposed model presents more than satisfying results to the load capacity prediction of repaired columns.

  16. Ordering blood tests for patients with unexplained fatigue in general practice: what does it yield? Results of the VAMPIRE trial.

    NARCIS (Netherlands)

    Koch, H.; Bokhoven, M.A. van; Riet, G. ter; Alphen-Jager, J.T. van; Weijden, T.T. van der; Dinant, G.J.; Bindels, P.J.

    2009-01-01

    BACKGROUND: Unexplained fatigue is frequently encountered in general practice. Because of the low prior probability of underlying somatic pathology, the positive predictive value of abnormal (blood) test results is limited in such patients. AIM: The study objectives were to investigate the

  17. Ordering blood tests for patients with unexplained fatigue in general practice: what does it yield? Results of the VAMPIRE trial

    NARCIS (Netherlands)

    Koch, Hèlen; van Bokhoven, Marloes A.; ter Riet, Gerben; van Alphen-Jager, Jm Tineke; van der Weijden, Trudy; Dinant, Geert-Jan; Bindels, Patrick Je

    2009-01-01

    Background Unexplained fatigue is frequently encountered in general practice. Because of the low prior probability of underlying somatic pathology, the positive predictive value of abnormal (blood) test results is limited in such patients. Aim The study objectives were to investigate the

  18. Combining forming results via weld models to powerful numerical assemblies

    NARCIS (Netherlands)

    Kose, K.; Rietman, Bert

    2004-01-01

    Forming simulations generally give satisfying results with respect to thinning, stresses, changed material properties and, with a proper springback calculation, the geometric form. The joining of parts by means of welding yields an extra change of the material properties and the residual stresses.

  19. Modelling the response of yields and tissue C : N to changes in atmospheric CO2 and N management in the main wheat regions of western Europe

    DEFF Research Database (Denmark)

    Olin, S.; Schurgers, Guy; Lindeskog, M.

    2015-01-01

    for processes in managed ecosystems in large-scale models. Our results highlight the importance of accounting for C–N interactions when modelling agricultural ecosystems, and it is an important step towards accounting for the combined impacts of changes in climate, [CO2] and land use on terrestrial...... (DVMs) aim to accurately represent both natural vegetation and managed land, not only from a carbon cycle perspective but increasingly so also for a wider range of processes including crop yields. We present here the extended version of the DVM LPJ-GUESS that accounts for N limitation in crops...... production, tissue C to N ratios (C: N) and phenology. To test the model’s applicability for larger regions, simulations are subsequently performed that cover the wheatdominated regions of western Europe. When compared to regional yield statistics, the inclusion of C–N dynamics in the model substantially...

  20. Modeling of the Strain Rate Dependency of Polycarbonate’s Yield Stress: Evaluation of Four Constitutive Equations

    Directory of Open Access Journals (Sweden)

    Abdullah A. Al-Juaid

    2016-01-01

    Full Text Available The main focus of this paper is in evaluating four constitutive relations which model the strain rate dependency of polymers yield stress. Namely, the two-term power-law, the Ree-Eyring, the cooperative, and the newly modified-Eyring equations are used to fit tensile and compression yield stresses of polycarbonate, which are obtained from the literature. The four equations give good agreement with the experimental data. Despite using only three material constants, the modified-Eyring equation, which considers a strain rate-dependent activation volume, gives slightly worse fit than the three other equations. The two-term power-law and the cooperative equation predict a progressive increase in the strain rate sensitivity of the yield stress. Oppositely, the Ree-Eyring and the modified-Eyring equations show a clear transition between the low and high strain rate ranges. Namely, they predict a linear dependency of the yield stress in terms of the strain rate at the low strain rate range. Crossing a threshold strain rate, the yield stress sensitivity sharply increases as the strain rate increases. Hence, two different behaviors were observed though the four equations fit well the experimental data. More experimental data, mainly at the intermediate strain rate range, are needed to conclude which, of the two behaviors, is more appropriate for polymers.

  1. Associations Between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

    OpenAIRE

    Hannah Lyden; Sarah I. Gimbel; Larissa Del Piero; A. Bryna Tsai; Matthew Elliott Sachs; Matthew Elliott Sachs; Jonas T Kaplan; Gayla Margolin; Darby Saxbe

    2016-01-01

    Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation appr...

  2. Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

    OpenAIRE

    Lyden, Hannah; Gimbel, Sarah I.; Del Piero, Larissa; Tsai, A. Bryna; Sachs, Matthew E.; Kaplan, Jonas T.; Margolin, Gayla; Saxbe, Darby

    2016-01-01

    Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation appr...

  3. Associations Between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

    Directory of Open Access Journals (Sweden)

    Hannah Lyden

    2016-09-01

    Full Text Available Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant. The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations between early family aggression exposure and brain volume depending on the segmentation method used.

  4. Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results.

    Science.gov (United States)

    Lyden, Hannah; Gimbel, Sarah I; Del Piero, Larissa; Tsai, A Bryna; Sachs, Matthew E; Kaplan, Jonas T; Margolin, Gayla; Saxbe, Darby

    2016-01-01

    Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.

  5. Science yield modeling with the Exoplanet Open-Source Imaging Mission Simulator (EXOSIMS)

    Science.gov (United States)

    Delacroix, Christian; Savransky, Dmitry; Garrett, Daniel; Lowrance, Patrick; Morgan, Rhonda

    2016-08-01

    We report on our ongoing development of EXOSIMS and mission simulation results for WFIRST. We present the interface control and the modular structure of the software, along with corresponding prototypes and class definitions for some of the software modules. More specifically, we focus on describing the main steps of our high-fidelity mission simulator EXOSIMS, i.e., the completeness, optical system and zodiacal light modules definition, the target list module filtering, and the creation of a planet population within our simulated universe module. For the latter, we introduce the integration of a recent mass-radius model from the FORECASTER software. We also provide custom modules dedicated to WFIRST using both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC) for detection and characterization, respectively. In that context, we show and discuss the results of some preliminary WFIRST simulations, focusing on comparing different methods of integration time calculation, through ensembles (large numbers) of survey simulations.

  6. Predicting Alkylate Yield and its Hydrocarbon Composition for Sulfuric Acid Catalyzed Isobutane Alkylation with Olefins Using the Method of Mathematical Modeling

    OpenAIRE

    Nurmakanova, А. Е.; Ivashkina, Elena Nikolaevna; Ivanchina, Emilia Dmitrievna; Dolganov, I. A.; Boychenko, S. S.

    2015-01-01

    The article provides the results of applied mathematical model of isobutane alkylation with olefins catalyzed by sulfuric acid to predict yield and hydrocarbon composition of alkylate caused by the changes in the feedstock composition and process parameters. It is shown that the alkylate produced from feedstock with less mass fraction of isobutane has lower octane value. Wherein the difference in composition of the feedstock contributes to antiknock index by the amount of 1.0-2.0 points.

  7. Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

    Science.gov (United States)

    Zhang, Kefeng; Bosch-Serra, Angela D; Boixadera, Jaume; Thompson, Andrew J

    2015-01-01

    Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3) cm(-3) and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l) for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was

  8. Stand-level growth and yield component models for red oak-sweetgum forests on Mid-South minor stream bottoms

    Science.gov (United States)

    Emily B. Schultz; J. Clint Iles; Thomas G. Matney; Andrew W. Ezell; James S. Meadows; Theodor D. Leininger; al. et.

    2010-01-01

    Greater emphasis is being placed on Southern bottomland hardwood management, but relatively few growth and yield prediction systems exist that are based on sufficient measurements. We present the aggregate stand-level expected yield and structural component equations for a red oak (Quercus section Lobatae)-sweetgum (Liquidambar styraciflua L.) growth and yield model....

  9. The results of an experimental indoor hydroponic Cannabis growing study, using the 'Screen of Green' (ScrOG) method-Yield, tetrahydrocannabinol (THC) and DNA analysis.

    Science.gov (United States)

    Knight, Glenys; Hansen, Sean; Connor, Mark; Poulsen, Helen; McGovern, Catherine; Stacey, Janet

    2010-10-10

    The results of an indoor hydroponic Cannabis growth study are presented. It is intended that this work will be of assistance to those with an interest in determining an estimation of yield and value of Cannabis crops. Three cycles of six plants were grown over a period of 1 year in order to ascertain the potential yield of female flowering head material from such an operation. The cultivation methods used were selected to replicate typical indoor hydroponic Cannabis growing operations, such as are commonly encountered by the New Zealand Police. The plants were also tested to ascertain the percentage of the psychoactive chemical Δ-9 tetrahydrocannabinol (THC) present in the flowering head material, and were genetically profiled by STR analysis. Phenotypic observations are related to the data collected. The inexperience of the growers was evidenced by different problems encountered in each of the three cycles, each of which would be expected to negatively impact the yield and THC data obtained. These data are therefore considered to be conservative. The most successful cycle yielded an average of 881g (31.1oz) of dry, groomed female flowering head per plant, and over the whole study the 18 plants yielded a total of 12,360g (436.0oz), or an average of 687g (24.2oz) of dry head per plant. THC data shows significant intra-plant variation and also demonstrates inter-varietal variation. THC values for individual plants ranged from 4.3 to 25.2%. The findings of this study and a separate ESR research project illustrate that the potency of Cannabis grown in New Zealand has dramatically increased in recent years. DNA analysis distinguished distinct groups in general agreement with the phenotypic variation observed. One plant however, exhibiting a unique triallelic pattern at two of the five loci tested, while remaining phenotypically indistinguishable from three other plants within the same grow. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  10. Streamflow response and sediment yield after farmland abandonment: results from a small experimental catchment in the Central Spanish Pyrenees

    Directory of Open Access Journals (Sweden)

    Serrano-Muela, M. P.

    2010-12-01

    Full Text Available A small catchment affected by agricultural practices in the past, then progressively abandoned and naturally re-vegetated was monitored in the central Spanish Pyrenees. The results obtained over a 9-year period revealed the complexity of its hydrological and geomorphological behaviour. Several runoff generation processes can occur at the same time and in different parts of the catchment, depending on the water reserves conditions and rainfall characteristics. Sediment response is mainly controlled by the spatial and temporal dynamics of water and sediment contributing areas within the catchment. The sediment output illustrates the complexity of the geomorphic response of mountain environments modified by past farmland activities.

    Se presenta una síntesis de la investigación realizada en una pequeña cuenca experimental afectada por una intensa actividad agraria en el pasado y sujeta a un proceso de revegetación natural en la actualidad en el Pirineo Central. Los principales resultados obtenidos demuestran su complejo comportamiento hidrogeomorfológico. El análisis de la información hidrológica sugiere que diferentes procesos dominantes de generación de escorrentía pueden ocurrir de manera simultánea en diferentes áreas de la cuenca, en función del estado de humedad de la misma y de las características de la precipitación. La respuesta sedimentológica está principalmente controlada por la dinámica espacio-temporal de las áreas fuente de escorrentía y de sedimento. La exportación de sedimento ilustra la complejidad de la respuesta geomorfológica en los ambientes de montaña afectados por actividades agrarias en el pasado.

  11. Equity yields

    NARCIS (Netherlands)

    Vrugt, E.; van Binsbergen, J.H.; Koijen, R.S.J.; Hueskes, W.

    2013-01-01

    We study a new data set of dividend futures with maturities up to ten years across three world regions: the US, Europe, and Japan. We use these asset prices to construct equity yields, analogous to bond yields. We decompose the equity yields to obtain a term structure of expected dividend growth

  12. Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

    OpenAIRE

    Zhiqiang Cheng; Jihua Meng; Yiming Wang

    2016-01-01

    Field crop yield prediction is crucial to grain storage, agricultural field management, and national agricultural decision-making. Currently, crop models are widely used for crop yield prediction. However, they are hampered by the uncertainty or similarity of input parameters when extrapolated to field scale. Data assimilation methods that combine crop models and remote sensing are the most effective methods for field yield estimation. In this study, the World Food Studies (WOFOST) model is u...

  13. The effect of high-sugar grass on predicted nitrogen excretion and milk yield simulated using a dynamic model

    NARCIS (Netherlands)

    Ellis, J.L.; Dijkstra, J.; Bannink, A.; Parsons, A.J.; Rasmussen, S.; Edwards, G.R.; Kebreab, E.; France, J.

    2011-01-01

    High-sugar grass varieties have received considerable attention for their potential to reduce nitrogen (N) excretion and increase milk yield in cattle. However, considerable variation exists in the magnitude of response in published results. The purpose of this study is to explain the variation in

  14. EXPLORING CLIMATE CHANGE EFFECTS ON WATERSHED SEDIMENT YIELD AND LAND COVER-BASED MITIGATION MEASURES USING SWAT MODEL, RS AND GIS: CASE OF CAGAYAN RIVER BASIN, PHILIPPINES

    Directory of Open Access Journals (Sweden)

    J. A. Principe

    2012-07-01

    Full Text Available The impact of climate change in the Philippines was examined in the country's largest basin–the Cagayan River Basin–by predicting its sediment yield for a long period of time. This was done by integrating the Soil and Water Assessment Tool (SWAT model, Remote Sensing (RS and Geographic Information System (GIS. A set of Landsat imageries were processed to include an atmospheric correction and a filling procedure for cloud and cloud-shadow infested pixels was used to maximize each downloaded scene for a subsequent land cover classification using Maximum Likelihood classifier. The Shuttle Radar Topography Mission (SRTM-DEM was used for the digital elevation model (DEM requirement of the model while ArcGIS™ provided the platform for the ArcSWAT extension, for storing data and displaying spatial data. The impact of climate change was assessed by varying air surface temperature and amount of precipitation as predicted in the Intergovernmental Panel on Climate Change (IPCC scenarios. A Nash-Sutcliff efficiency (NSE > 0.4 and coefficient of determination (R2 > 0.5 for both the calibration and validation of the model showed that SWAT model can realistically simulate the hydrological processes in the study area. The model was then utilized for land cover change and climate change analyses and their influence on sediment yield. Results showed a significant relationship exists among the changes in the climate regime, land cover distributions and sediment yield. Finally, the study suggested land cover distribution that can potentially mitigate the serious negative effects of climate change to a regional watershed's sediment yield.

  15. The in vitro mass-produced model mycorrhizal fungus, Rhizophagus irregularis, significantly increases yields of the globally important food security crop cassava.

    Directory of Open Access Journals (Sweden)

    Isabel Ceballos

    Full Text Available The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF and plant roots. The fungi provide the plant with inorganic phosphate (P. The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was double the recommended dose and was calculated with European, not Colombian, inoculum prices. R. irregularis can also be manipulated genetically in vitro, leading to improved plant growth. We conclude that application of in vitro R. irregularis is currently a way of increasing cassava yields, that there is a strong potential for it to be economically profitable and that there is enormous potential to improve this efficiency further in the future.

  16. Utilization of the cropgro-soybean model to estimate yield loss caused by Asian rust in cultivars with different cycle

    Directory of Open Access Journals (Sweden)

    Rafael de Ávila Rodrigues

    2012-01-01

    Full Text Available In recent years, crop models have increasingly been used to simulate agricultural features. The DSSAT (Decision Support System for Agrotechnology Transfer is an important tool in modeling growth; however, one of its limitations is related to the unaccounted-for effect of diseases. Therefore, the goals of this study were to calibrate and validate the CSM CROPGRO-Soybean for the soybean cultivars M-SOY 6101 and MG/BR 46 (Conquista, analyze the performance and the effect of Asian soybean rust on these cultivars under the environmental conditions of Viçosa, Minas Gerais, Brazil. The experimental data for the evaluation, testing, and adjustment of the genetic coefficients for the cultivars, M-SOY 6101 and MG/BR 46 (Conquista, were obtained during the 2006/2007, 2007/2008 and 2009/2010 growing seasons. GLUE (Generalized Likelihood Uncertainty Estimation was used for the estimation of the genetic coefficients, and pedotransfer functions have been utilized to estimate the physical characteristics of the soil. For all of the sowing dates, the early season cultivar, M-SOY 6101, exhibited a lower variance in yield, which represents more stability with regard to the interannual climate variability, i.e., the farmers who use this cultivar will have in 50% of the crop years analyzed, a higher yield than a late-season cultivar. The MG/BR 46 (Conquista cultivar demonstrated a greater probability of obtaining higher yield in years with favorable weather conditions. However, in the presence of the Asian soybean rust, yield is heavily affected. The early cultivar, M-SOY 6101, showed a lower risk of being affected by the rust and consequently exhibited less yield loss considering the scenario D90 (condensation on the leaf surface occurs when the relative humidity is greater than or equal to 90%, for a sowing date of November 14.

  17. Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

    Czech Academy of Sciences Publication Activity Database

    Pirttioja, N. K.; Carter, T. R.; Fronzek, S.; Bindi, M.; Hoffmann, H. D.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, Miroslav; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M. F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, Petr; Jacquemin, I.; Kersebaum, K. C.; Kollas, C.; Krzyszczak, J.; Lorite, I. J.; Minet, J.; Minquez, M. I.; Montesino, M.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodriguez, A.; Ruane, A. C.; Ruget, F.; Sanna, M.; Semenov, M. A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R. P.

    2015-01-01

    Roč. 65, č. 31 (2015), s. 87-105 ISSN 0936-577X R&D Projects: GA MZe QJ1310123; GA MŠk(CZ) LD13030 Grant - others:German Federal Ministries of Education and Research, and Food and Agriculture(DE) 2812ERA115 Institutional support: RVO:67179843 Keywords : climate * crop model * impact response surface * IRS * sensitivity analysis * wheat * yield Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.690, year: 2015

  18. A Comparison of Crop Yields Using El Nino and Non-El Nino Climatological Data in a Crop Model

    Science.gov (United States)

    1990-01-01

    CERES- Maize ..... 65 Appendix F: Palmer Drought Severity Index (PDSI). 76 Appendix G: Yearly Corn Yield Averages for the U. S. and the Five Midwestern...model for predicting corn ( Zea mays L.) performance in the tropics. Ph.D. diss. University of Hawaii, Honolulu. Skaggs, R.H., and D.G. Baker. 1985...predicting corn ( Zea mays L.) performance in the tropics. Ph.D. diss. University of Hawaii, Honolulu. Skaggs, R.H., and D.G. Baker. 1985. Fluctuations

  19. SELECTION VIA MIXED MODELS IN SEGREGATING GUAVA FAMILIES BASED ON YIELD AND QUALITY TRAITS

    Directory of Open Access Journals (Sweden)

    SILVANA SILVA RED QUINTAL

    Full Text Available ABSTRACT Aiming at the generation of new guava varieties with superior attributes, we conducted this study adopting the REML/BLUP procedure at individual level. Seventeen segregating guava families were evaluated in a randomized-block design with two replicates and 12 plants per plot. Families were obtained after controlled biparental pollination. The studied individuals showed high genotypic variance for fruit weight (FW, total yield (YLD, and ascorbic acid content (AAC. The heritability coefficients of the mean of progenies led to high progeny-selection accuracy for pulp yield (PY, soluble solids content (SSC, in addition to FW, YLD, and AAC; moderate accuracy for fruit acidity (FA and SSC/FA ratio; and low accuracy for mesocarp thickness (MT and pH. Selection among families (h2mp indicated the highest values for FW, PY, YLD, SSC, and AAC, revealing that, for the present study, this practice would be effective, since these traits allowed for the highest selection accuracy values among families. As for the ranking of individuals, families originating from crosses UENF 1835 × UENF 1834, UENF 1831 × UENF 1832, and UENF 1831 × UENF 3739 stood out, occupying the first positions for most traits.

  20. European-wide simulations of croplands using an improved terrestrial biosphere model: 2. Interannual yields and anomalous CO2 fluxes in 2003

    Science.gov (United States)

    Smith, P. C.; Ciais, P.; Peylin, P.; de Noblet-Ducoudré, N.; Viovy, N.; Meurdesoif, Y.; Bondeau, A.

    2010-12-01

    Aiming at producing improved estimates of carbon source/sink spatial and interannual patterns across Europe (35% croplands), this work uses the ORCHIDEE-STICS terrestrial biosphere model including a more realistic representation of croplands, described in part 1 (Smith et al., 2010). Crop yield is derived from annual Net Primary Productivity and compared with wheat and grain maize harvest data for five European countries. Over a 34 year period, the best correlation coefficient obtained between observed and simulated yield time series is for irrigated maize in Italy (R = 0.73). In the data as well as in the model, 1976 and 2003 appear as climate anomalies causing a ≈40% yield drop in the most affected regions. Simulated interannual yield anomalies and the spatial pattern of the yield drop in 2003 are found to be more realistic than the results from ORCHIDEE with no representation of croplands. The simulated 2003 anomalous carbon source from European ecosystems to the atmosphere due to the 2003 summer heat wave is in good agreement with atmospheric inversions (0.20GtC, from May to October). The anomaly is twice too large in the ORCHIDEE alone simulation, owing to the unrealistically high exposure of herbaceous plants to the extreme summer conditions. The mechanisms linking abnormally high summer temperatures, the crop productivity drop, and significant carbon source from European ecosystems in 2003 are discussed. Overall, this study highlights the importance of accounting for the specific phenologies of crops sown both in winter and in spring and for irrigation applied to summer crops in regional/global models of the terrestrial carbon cycle.

  1. Application of DSSAT-CROPGRO-Cotton Model to Assess Long Term (1924-2012) Cotton Yield under Different Irrigation Management Strategies

    Science.gov (United States)

    Adhikari, P.; Gowda, P. H.; Northup, B. K.; Rocateli, A.

    2017-12-01

    In this study a well calibrated and validated DSSAT-CROPGRO-Cotton model was used for assessing the irrigation management in the Texas High Plains (THP). Long term (1924-2012) historic lint yield were simulated under different irrigation management practices which were commonly used in the THP. The simulation treatments includes different amount of irrigation water high (H; 6.4 mm d-1), medium (M; 3.2 mm d-1) and low (L; 0 mm d-1) during emergence (S1), vegetative (S2) and maturity (S3) stage. The combination of these treatments resulted into 27 treatments. The amount and date of irrigation for each stage were obtained from the recent cotton irrigation experiment at Halfway, TX (Brodovsky, et al., 2015). Similarly, calibrated model was also used to observe the effect of plantation date on crop yield in the THP regions.

  2. Regression models of ultimate methane yields of fruits and vegetable solid wastes, sorghum and napiergrass on chemical composition

    Energy Technology Data Exchange (ETDEWEB)

    Gunaseelan, V.N. [PSG College of Arts and Science, Coimbatore (India). Department of Zoology

    2007-04-15

    Several fractions of fruits and vegetable solid wastes (FVSW), sorghum and napiergrass were analyzed for total solids (TS), volatile solids (VS), total organic carbon, total kjeldahl nitrogen, total soluble carbohydrate, extractable protein, acid-detergent fiber (ADF), lignin, cellulose and ash contents. Their ultimate methane yields (B{sub o}) were determined using the biochemical methane potential (BMP) assay. A series of simple and multiple regression models relating the B{sub o} to the various substrate constituents were generated and evaluated using computer statistical software, Statistical Package for Social Sciences (SPSS). The results of simple regression analyses revealed that, only weak relationship existed between the individual components such as carbohydrate, protein, ADF, lignin and cellulose versus B{sub o}. A regression of B{sub o} versus combination of two variables as a single independent variable such as carbohydrate/ADF and carbohydrate + protein/ADF also showed that the relationship is not strong. Thus it does not appear possible to relate the B{sub o} of FVSW, sorghum and napiergrass with single compositional characteristics. The results of multiple regression analyses showed promise and the relationship appeared to be good. When ADF and lignin/ADF were used as independent variables, the percentage of variation accounted for by the model is low for FVSW (r{sup 2}=0.665) and sorghum and napiergrass (r{sup 2}=0.746). Addition of nitrogen, ash and total soluble carbohydrate data to the model had a significantly higher effect on prediction of B{sub o} of these wastes with the r{sup 2} values ranging from 0.9 to 0.99. More than 90% of variation in B{sub o} of FVSW could be accounted for by the models when the variables carbohydrate, lignin, lignin/ADF, nitrogen and ash (r{sup 2}=0.904), carbohydrate, ADF, lignin/ADF, nitrogen and ash (r{sup 2}=0.90) and carbohydrate/ADF, lignin/ADF, lignin and ash (r{sup 2}=0.901) were used. All the models have

  3. A GIS-based model of potential groundwater yield zonation for a sandstone aquifer in the Juye Coalfield, Shangdong, China

    Science.gov (United States)

    Yin, Huiyong; Shi, Yongli; Niu, Huigong; Xie, Daolei; Wei, Jiuchuan; Lefticariu, Liliana; Xu, Shuanxiang

    2018-02-01

    Resolving the potential groundwater yield zonation of sandstone aquifers occurring at depths of several hundred meters has been an important and challenging objective of the hydrogeological research focused on preventing flood hazards in coal mines. Using accessible geological exploration data we put forward a method of predicting the spatial distribution of groundwater storage potential in sandstone aquifers from Permian-age coal deposits in Juye Coalfield, Shangdong, China. A Geological, Tectonic and Lithological Composition Index (GTLCI) model was created using the following parameters: sandstone depth and thickness, faults length density (FaLD), faults density (FaD), fault frequency density (FaFD), fault scale density (FaSD), variation coefficient of the slope (VCS) of the coal seam, intensity index of folds in horizontal direction (IIFoH), and lithological composition index (LCI). Each of these factors was subsequently divided into 5 classes. The analytic hierarchy process (AHP) and trapezoidal fuzzy number (TFN) method was applied to calculate the weight of the conditioning factor and their respective sub-classes. Groundwater yield potential contour map, which was initially constructed using the GTLCI values revealed four groundwater abundance zones. The map was further refined by taking into account hydrogeologic data collected during mining activities. The GTLCI model predictive success rate of 80% was explained by the limited number of boreholes available for validation. It is considered that the GTLCI model is effective at predicting zonation of groundwater yield in the sandstone aquifers from Permian- age coal deposits in Juye Coalfield, China.

  4. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  5. CERES-Maize model-based simulation of climate change impacts on maize yields and potential adaptive measures in Heilongjiang Province, China.

    Science.gov (United States)

    Lin, Yumei; Wu, Wenxiang; Ge, Quansheng

    2015-11-01

    Climate change would cause negative impacts on future agricultural production and food security. Adaptive measures should be taken to mitigate the adverse effects. The objectives of this study were to simulate the potential effects of climate change on maize yields in Heilongjiang Province and to evaluate two selected typical household-level autonomous adaptive measures (cultivar changes and planting time adjustments) for mitigating the risks of climate change based on the CERES-Maize model. The results showed that flowering duration and maturity duration of maize would be shortened in the future climate and thus maize yield would reduce by 11-46% during 2011-2099 relative to 1981-2010. Increased CO2 concentration would not benefit maize production significantly. However, substituting local cultivars with later-maturing ones and delaying the planting date could increase yields as the climate changes. The results provide insight regarding the likely impacts of climate change on maize yields and the efficacy of selected adaptive measures by presenting evidence-based implications and mitigation strategies for the potential negative impacts of future climate change. © 2014 Society of Chemical Industry.

  6. Genetic Analysis of Milk Yield Using Random Regression Test Day Model in Tehran Province Holstein Dairy Cow

    Directory of Open Access Journals (Sweden)

    A. Seyeddokht

    2012-09-01

    Full Text Available In this research a random regression test day model was used to estimate heritability values and calculation genetic correlations between test day milk records. a total of 140357 monthly test day milk records belonging to 28292 first lactation Holstein cattle(trice time a day milking distributed in 165 herd and calved from 2001 to 2010 belonging to the herds of Tehran province were used. The fixed effects of herd-year-month of calving as contemporary group and age at calving and Holstein gene percentage as covariate were fitted. Orthogonal legendre polynomial with a 4th-order was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. RRM using Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data. The results showed that the average of heritability for the second half of lactation period was higher than that of the first half. The heritability value for the first month was lowest (0.117 and for the eighth month of the lactation was highest (0.230 compared to the other months of lactation. Because of genetic variation was increased gradually, and residual variance was high in the first months of lactation, heritabilities were different over the course of lactation. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. In this research estimation of genetic parameters, and calculation genetic correlations were implemented by random regression test day model, therefore using this method is the exact way to take account of parameters rather than the other ways.

  7. A phenomenological molecular model for yielding and brittle-ductile transition of polymer glasses.

    Science.gov (United States)

    Wang, Shi-Qing; Cheng, Shiwang; Lin, Panpan; Li, Xiaoxiao

    2014-09-07

    This work formulates, at a molecular level, a phenomenological theoretical description of the brittle-ductile transition (BDT) in tensile extension, exhibited by all polymeric glasses of high molecular weight (MW). The starting point is our perception of a polymer glass (under large deformation) as a structural hybrid, consisting of a primary structure due to the van der Waals bonding and a chain network whose junctions are made of pairs of hairpins and function like chemical crosslinks due to the intermolecular uncrossability. During extension, load-bearing strands (LBSs) emerge between the junctions in the affinely strained chain network. Above the BDT, i.e., at "warmer" temperatures where the glass is less vitreous, the influence of the chain network reaches out everywhere by activating all segments populated transversely between LBSs, starting from those adjacent to LBSs. It is the chain network that drives the primary structure to undergo yielding and plastic flow. Below the BDT, the glassy state is too vitreous to yield before the chain network suffers a structural breakdown. Thus, brittle failure becomes inevitable. For any given polymer glass of high MW, there is one temperature TBD or a very narrow range of temperature where the yielding of the glass barely takes place as the chain network also reaches the point of a structural failure. This is the point of the BDT. A theoretical analysis of the available experimental data reveals that (a) chain pullout occurs at the BDT when the chain tension builds up to reach a critical value f(cp) during tensile extension; (b) the limiting value of f(cp), extrapolated to far below the glass transition temperature T(g), is of a universal magnitude around 0.2-0.3 nN, for all eight polymers examined in this work; (c) pressurization, which is known [K. Matsushige, S. V. Radcliffe, and E. Baer, J. Appl. Polym. Sci. 20, 1853 (1976)] to make brittle polystyrene (PS) and poly(methyl methacrylate) (PMMA) ductile at room

  8. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

    Science.gov (United States)

    Rollin, Joseph A.; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K.; Wu, Chang-Hao; Adams, Michael W. W.; Senger, Ryan S.; Zhang, Y.-H. Percival

    2015-01-01

    The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L−1⋅h−1. The productivity was further enhanced to 54 mmol H2⋅L−1⋅h−1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production. PMID:25848015

  9. A new model of dependence of secondary electron emission yield on primary electron energy for application to polymers

    Energy Technology Data Exchange (ETDEWEB)

    Cazaux, J [LASSI/UTAP, Faculte des Sciences, BP1039, 51687 Reims Cedex 2 (France)

    2005-07-21

    A new analytical model for the secondary electron (SE) emission yield, {delta}, is applied to polymers. It involves a parameter k, k = z{sub C}/R, between the most probable energy dissipation depth, z{sub C}, of primary electrons (PE) and their range R, where k ranges from 0.5 and 0.45 for low-density, low atomic-weight materials. Reduced yield curves (RYC), {delta}/{delta}{sub (max)} versus E{sup 0}/E{sup 0}{sub (max)}, and normal yield curves, {delta} versus E{sup 0}, obtained from published experimental data on a wide variety of polymers (polystyrene, PET, polyimide; Kapton; PTFE; Teflon, PMMA, nylon, polyurethane) are compared with the calculated change of {delta} with PE energy, E{sup 0}. In contrast to the use of the conventional constant loss model where the best fit requires an empirical change in the exponent 'n' in the power law expression of the PE range, R versus E{sup 0}, the present approach is based on the usual choice for n, n = 1.35, and on a choice for k governed by physical arguments. This physical basis then enables one to predict the RYC of other polymers. Finally, values of the SE escape probability and SE attenuation length are estimated for the polymers of interest and a new mechanism is suggested for the contrast reversal in scanning electron microscopy.

  10. A new model of dependence of secondary electron emission yield on primary electron energy for application to polymers

    International Nuclear Information System (INIS)

    Cazaux, J

    2005-01-01

    A new analytical model for the secondary electron (SE) emission yield, δ, is applied to polymers. It involves a parameter k, k = z C /R, between the most probable energy dissipation depth, z C , of primary electrons (PE) and their range R, where k ranges from 0.5 and 0.45 for low-density, low atomic-weight materials. Reduced yield curves (RYC), δ/δ (max) versus E 0 /E 0 (max) , and normal yield curves, δ versus E 0 , obtained from published experimental data on a wide variety of polymers (polystyrene, PET, polyimide; Kapton; PTFE; Teflon, PMMA, nylon, polyurethane) are compared with the calculated change of δ with PE energy, E 0 . In contrast to the use of the conventional constant loss model where the best fit requires an empirical change in the exponent 'n' in the power law expression of the PE range, R versus E 0 , the present approach is based on the usual choice for n, n = 1.35, and on a choice for k governed by physical arguments. This physical basis then enables one to predict the RYC of other polymers. Finally, values of the SE escape probability and SE attenuation length are estimated for the polymers of interest and a new mechanism is suggested for the contrast reversal in scanning electron microscopy

  11. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

    NARCIS (Netherlands)

    Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; Asseng, Senthold; Baranowski, Piotr; Basso, Bruno; Bodin, Per; Buis, Samuel; Cammarano, Davide; Deligios, Paola; Destain, Marie France; Dumont, Benjamin; Ewert, Frank; Ferrise, Roberto; François, Louis; Gaiser, Thomas; Hlavinka, Petr; Jacquemin, Ingrid; Kersebaum, Kurt Christian; Kollas, Chris; Krzyszczak, Jaromir; Lorite, Ignacio J.; Minet, Julien; Minguez, M.I.; Montesino, Manuel; Moriondo, Marco; Müller, Christoph; Nendel, Claas; Öztürk, Isik; Perego, Alessia; Rodríguez, Alfredo; Ruane, Alex C.; Ruget, Françoise; Sanna, Mattia; Semenov, Mikhail A.; Slawinski, Cezary; Stratonovitch, Pierre; Supit, Iwan; Waha, Katharina; Wang, Enli; Wu, Lianhai; Zhao, Zhigan; Rötter, Reimund P.

    2018-01-01

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in

  12. Defensive Egotism and Bullying: Gender Differences Yield Qualified Support for the Compensation Model of Aggression

    Science.gov (United States)

    Nail, Paul R.; Simon, Joan B.; Bihm, Elson M.; Beasley, William Howard

    2016-01-01

    According to the compensation model of aggression (Staub, 1989), some people bully to defend against their own feelings of weakness and vulnerability. Classmates and teachers rated a sample of American sixth graders in terms of trait: defensiveness (i.e., defensive egotism), self-esteem, bullying, and related behaviors. Consistent with the model,…

  13. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

    Czech Academy of Sciences Publication Activity Database

    Fronzek, S.; Pirttioja, N. K.; Carter, T. R.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, Miroslav; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M. F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, Petr; Jacquemin, I.; Kersebaum, K. C.; Kollas, C.; Krzyszczak, J.; Lorite, I. J.; Minet, J.; Ines Minguez, M.; Montesino, M.; Moriondo, M.; Mueller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodriguez, A.; Ruane, A. C.; Ruget, F.; Sanna, M.; Semenov, M. A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R.

    2018-01-01

    Roč. 159, jan (2018), s. 209-224 ISSN 0308-521X Keywords : climate-change * crop models * probabilistic assessment * simulating impacts * british catchments * uncertainty * europe * productivity * calibration * adaptation * Classification * Climate change * Crop model * Ensemble * Sensitivity analysis * Wheat Impact factor: 2.571, year: 2016

  14. ANN-based sediment yield models for Vamsadhara river basin (India)

    African Journals Online (AJOL)

    High numbers of iterations adopted for model development were found to reduce the value of the objective function, but with model's over-learning and that is reflected? Unclear what is meant by an increase and decrease of the performance in calibration and cross-validation, respectively. The generalised pattern- learned ...

  15. Uncertainty modelling and analysis of environmental systems: a river sediment yield example

    NARCIS (Netherlands)

    Keesman, K.J.; Koskela, J.; Guillaume, J.H.; Norton, J.P.; Croke, B.; Jakeman, A.

    2011-01-01

    Abstract: Throughout the last decades uncertainty analysis has become an essential part of environmental model building (e.g. Beck 1987; Refsgaard et al., 2007). The objective of the paper is to introduce stochastic and setmembership uncertainty modelling concepts, which basically differ in the

  16. Use of Aquacrop Model to predict Maize Yields under Varying Rainfall and Temperature in a Semi-Arid Environment in Kenya

    International Nuclear Information System (INIS)

    Wamari, O. J.; Sijali, V. I; Heng, N. K; Joseph Mutwiri Miriti, M. J; Esilaba, O A

    2012-01-01

    There has been increasing concern that drier and hotter seasons are becoming more frequent due to climate change especially in semi-arid environments causing adverse effects on agricultural production. Analysis of long-term (1980-2010) trends of rainfall in the first growing season (i.e. March and July) at Katumani, Kenya showed that about 55% of the seasons were below the long-term average, with an all time low occurring in the year 2000. Although the wettest years (1998 and 1985 ) had relatively higher percentages above the long-term average (143.9% and 138.4% ) compared to lower percentages ( 61.7% and 59.7%) of the driest years ( 2000 and 1987), the latter were relatively less in numbers (i.e. 45%). Mean seasonal temperatures however did not show high variation from the long term mean implying that rainfall was the main cause of yield variation in this area. The AquaCrop model (Ver. 3.1) evaluated using three years (i.e. 1999, 2000 and 2001) of experimental results at Katumani, gave reasonable estimates of above ground biomass and grain yield of Katumani composite maize variety. The model was then used to predict Katumani maize yields under 20% depletion of rainfall and 3°C temperature elevation scenarios. Biomass and grain yields simulated respectively ranged between 2.971 to 6.558 and 0.910 to 2.564 T Ha-1 with probabilities of obtaining 3-5 T Ha-1 biomass and 1-2 T Ha-1 grain yields each dropping from 98 to 25%. Adaptation measures are given as management recommendations in line with the changed climatic scenario. (author)

  17. Performance Evaluation of FAO Model for Prediction of Yield Production, Soil Water and Solute Balance under Environmental Stresses (Case Study Winter Wheat

    Directory of Open Access Journals (Sweden)

    V. Rezaverdinejad

    2014-11-01

    Full Text Available In this study, the FAO agro-hydrological model was investigated and evaluated to predict of yield production, soil water and solute balance by winter wheat field data under water and salt stresses. For this purpose, a field experimental was conducted with three salinity levels of irrigation water include: S1, S2 and S3 corresponding to 1.4, 4.5 and 9.6 dS/m, respectively, and four irrigation depth levels include: I1, I2, I3 and I4 corresponding to 50, 75, 100 and 125% of crop water requirement, respectively, for two varieties of winter wheat: Roshan and Ghods, with three replications in an experimental farm of Birjand University for 1384-85 period. Based on results, the mean relative error of the model in yield prediction for Roshan and Ghods were obtained 9.2 and 26.1%, respectively. The maximum error of yield prediction in both of the Roshan and Ghods varieties, were obtained for S1I1, S2I1 and S3I1 treatments. The relative error of Roshan yield prediction for S1I1, S2I1 and S3I1 were calculated 20.0, 28.1 and 26.6%, respectively and for Ghods variety were calculated 61, 94.5 and 99.9%, respectively, that indicated a significant over estimate error under higher water stress. The mean relative error of model for all treatments, in prediction of soil water depletion and electrical conductivity of soil saturation extract, were calculated 7.1 and 5.8%, respectively, that indicated proper accuracy of model in prediction of soil water content and soil salinity.

  18. Stress Resultant Based Elasto-Viscoplastic Thick Shell Model

    Directory of Open Access Journals (Sweden)

    Pawel Woelke

    2012-01-01

    Full Text Available The current paper presents enhancement introduced to the elasto-viscoplastic shell formulation, which serves as a theoretical base for the finite element code EPSA (Elasto-Plastic Shell Analysis [1–3]. The shell equations used in EPSA are modified to account for transverse shear deformation, which is important in the analysis of thick plates and shells, as well as composite laminates. Transverse shear forces calculated from transverse shear strains are introduced into a rate-dependent yield function, which is similar to Iliushin's yield surface expressed in terms of stress resultants and stress couples [12]. The hardening rule defined by Bieniek and Funaro [4], which allows for representation of the Bauschinger effect on a moment-curvature plane, was previously adopted in EPSA and is used here in the same form. Viscoplastic strain rates are calculated, taking into account the transverse shears. Only non-layered shells are considered in this work.

  19. Study of Z' {yields} e{sup +}e{sup -} in full simulation with regard to discrimination between models beyond the standard model

    Energy Technology Data Exchange (ETDEWEB)

    Schafer, M

    2004-09-01

    Although experimental results so far agree with predictions of the standard model, it is widely felt to be incomplete. Many prospective theories beyond the standard model predict extra neutral gauge bosons, denoted by Z', which might be light enough to be accessible at the LHC. Observables sensitive to the properties of these extra gauge bosons might be used to discriminate between the different theories beyond the standard model. In the present work several of these observables (total decay width, leptonic cross-section and forward-backward asymmetries) are studied at generation level and with a full simulation in the ATLAS detector. The Z' {yields} e{sup +}e{sup -} decay channel was chosen and 2 values for the mass of Z': 1.5 TeV and 4 TeV. Background is studied as well and it is confirmed that a Z' boson could easily be discovered at the chosen masses. It is shown that even in full simulation the studied observables can be determined with a good precision. In a next step a discrimination strategy has to be developed given the presented methods to extract the variables and their precision. (author)

  20. YIELD INDICATORS

    African Journals Online (AJOL)

    International Institute of Tropical Agriculture, East and Southern Africa, Centre, P.O. Box 7878,. Kampala, Uganda. Makerere ... would have great potential in terms of human nutrition. Storage root yield , the ... Inter-relationships among traits and path analysis for yield components of cassava. 604 collected included plant ...

  1. Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

    Science.gov (United States)

    Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

    2017-06-01

    At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

  2. Assessment of the AquaCrop model for use in simulation of irrigated winter wheat canopy cover, biomass, and grain yield in the North China Plain.

    Directory of Open Access Journals (Sweden)

    Xiu-liang Jin

    Full Text Available Improving winter wheat water use efficiency in the North China Plain (NCP, China is essential in light of current irrigation water shortages. In this study, the AquaCrop model was used to calibrate, and validate winter wheat crop performance under various planting dates and irrigation application rates. All experiments were conducted at the Xiaotangshan experimental site in Beijing, China, during seasons of 2008/2009, 2009/2010, 2010/2011 and 2011/2012. This model was first calibrated using data from 2008/2009 and 2009/2010, and subsequently validated using data from 2010/2011 and 2011/2012. The results showed that the simulated canopy cover (CC, biomass yield (BY and grain yield (GY were consistent with the measured CC, BY and GY, with corresponding coefficients of determination (R(2 of 0.93, 0.91 and 0.93, respectively. In addition, relationships between BY, GY and transpiration (T, (R(2 = 0.57 and 0.71, respectively was observed. These results suggest that frequent irrigation with a small amount of water significantly improved BY and GY. Collectively, these results indicate that the AquaCrop model can be used in the evaluation of various winter wheat irrigation strategies. The AquaCrop model predicted winter wheat CC, BY and GY with acceptable accuracy. Therefore, we concluded that AquaCrop is a useful decision-making tool for use in efforts to optimize wheat winter planting dates, and irrigation strategies.

  3. Assessment of the AquaCrop model for use in simulation of irrigated winter wheat canopy cover, biomass, and grain yield in the North China Plain.

    Science.gov (United States)

    Jin, Xiu-liang; Feng, Hai-kuan; Zhu, Xin-kai; Li, Zhen-hai; Song, Sen-nan; Song, Xiao-yu; Yang, Gui-Jun; Xu, Xin-gang; Guo, Wen-shan

    2014-01-01

    Improving winter wheat water use efficiency in the North China Plain (NCP), China is essential in light of current irrigation water shortages. In this study, the AquaCrop model was used to calibrate, and validate winter wheat crop performance under various planting dates and irrigation application rates. All experiments were conducted at the Xiaotangshan experimental site in Beijing, China, during seasons of 2008/2009, 2009/2010, 2010/2011 and 2011/2012. This model was first calibrated using data from 2008/2009 and 2009/2010, and subsequently validated using data from 2010/2011 and 2011/2012. The results showed that the simulated canopy cover (CC), biomass yield (BY) and grain yield (GY) were consistent with the measured CC, BY and GY, with corresponding coefficients of determination (R(2)) of 0.93, 0.91 and 0.93, respectively. In addition, relationships between BY, GY and transpiration (T), (R(2) = 0.57 and 0.71, respectively) was observed. These results suggest that frequent irrigation with a small amount of water significantly improved BY and GY. Collectively, these results indicate that the AquaCrop model can be used in the evaluation of various winter wheat irrigation strategies. The AquaCrop model predicted winter wheat CC, BY and GY with acceptable accuracy. Therefore, we concluded that AquaCrop is a useful decision-making tool for use in efforts to optimize wheat winter planting dates, and irrigation strategies.

  4. A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield

    Science.gov (United States)

    Fan, Y.; Roupsard, O.; Bernoux, M.; Le Maire, G.; Panferov, O.; Kotowska, M. M.; Knohl, A.

    2015-11-01

    In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land-atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm - the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics

  5. Craters in concrete slabs due to detonation – drawbacks of material models with a Mohr-Coulomb yield surface

    Directory of Open Access Journals (Sweden)

    Conrad Markus

    2015-01-01

    Full Text Available Numerical simulations have been performed with a commercial distributed explicit FE-solver and the results have been compared with experiments. High explosive was placed in front of different concrete slabs with the dimension 100 × 100 × 16 cm. Some of the results of the simulations, in particular the profile of the craters, are not in agreement with the test results. Therefore the key characteristics of the constitutive equation based on Mohr-Coulomb yield surfaces and a damage evolution linked to the plastic strain has been reviewed.

  6. Effect of sowing density and nitrogen top-dress fertilisation on growth and yield of chia (Salvia hispanica L. in a Mediterranean environment: first results

    Directory of Open Access Journals (Sweden)

    Rocco Bochicchio

    2015-09-01

    Full Text Available The demand for sources of nutraceuticals has led to the rediscovery and diffusion of traditional crops such as chia (Salvia hispanica L., whose leaves and fruits are rich in W3 fatty acids and anti-oxidants. Chia originates in Central America but it is rapidly expanding to new areas. A field experiment conducted at Atella in Basilicata (Southern Italy was set up to test the response of chia to N top-dress fertilisation (0 and 20 kg ha–1 and to sowing density (D1=125, D2=25, D3=8 and D4=4 plants m–2 in a split-plot design with three replications. First results show maximum leaf area index values up to 7.1 and fresh vegetative biomass production at early flowering ranging between 50.87 (D4 and 59.71 (D1 t ha–1. Yield increased with plant density: a significantly (P<0.01 higher production (398 kg ha–1 was reached in D1. N top-dressing had a detrimental effect on yield and corresponded to higher lodging and lower maturation percentage of seeds, though non-significant. Based on our first results it seems worthwhile to continue agronomical trials for chia in herbaceous systems of southern Italy for leaf production based on traditional genotypes, while fruit production might be pursued by adopting high sowing density and the search for longer-day genotypes.

  7. Diagnostic yield and clinical impact of routine cell culture for respiratory viruses among children with a negative multiplex RT-PCR result.

    Science.gov (United States)

    AlGhounaim, M; Xiao, Y; Caya, C; Papenburg, J

    2017-09-01

    Polymerase chain reaction (PCR) is the reference standard for respiratory virus testing. However, cell culture may still have added value in identifying viruses not detected by PCR. We aimed to estimate the yield and clinical impact of routine respiratory virus culture among children with a negative PCR result. A retrospective cohort study was performed from Jan. 2013 to Sept. 2015. Respiratory samples from hospitalized or immunocompromised patients culture monolayers if they tested negative by a PCR assay for 12 respiratory viruses. We studied patients with a respiratory specimen negative by PCR and positive by culture. Duplicates and samples of sold services were excluded. Data on demographics, clinical history, laboratory findings, and patient management were collected from patients' charts. Descriptive and multivariate statistics were performed. Overall, 4638 PCR-negative samples were inoculated in cell culture. Of those, 196 (4.2%) were cell culture positive, and 144 met study inclusion criteria. Most subjects (81.9%) were hospitalized. Mean age was 2.4±3.4years. The viruses most frequently isolated were cytomegalovirus (33.3%) and enteroviruses (19.4%). Cell culture results prompted a change in management in 5 patients (3.5%), all of whom had acyclovir initiated for localized HSV-1 infection. Four of these had skin or mucosal lesions that could be sampled to establish a diagnosis. In children, routine viral culture on respiratory specimens that were negative by PCR has low yield and minimal clinical impact. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Models to Estimate Lactation Curves of Milk Yield and Somatic Cell Count in Dairy Cows at the Herd Level for the Use in Simulations and Predictive Models

    DEFF Research Database (Denmark)

    Græsbøll, Kaare; Kirkeby, Carsten Thure; Nielsen, Søren Saxmose

    2016-01-01

    using a herd level curve allows for estimating the cow production level from first the recording in the parity, while a two-parameter model requires more recordings for a credible estimate, but may more precisely predict persistence, and given the independence of parameters, these can be easily drawn....... Furthermore, we investigated how the parameters of lactation models correlate between parities and from dam to offspring. The aim of the study was to provide simple and robust models for cow level milk yield and somatic cell count for fitting to sparse data to parameterize herd- and cow-specific simulation...... than somatic cells per milliliter. A positive correlation was found between relative levels of the total somatic cell count and the milk yield. The variation of lactation and somatic cell count curves between farms highlights the importance of a herd level approach. The one-parameter per cow model...

  9. Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization

    DEFF Research Database (Denmark)

    Salo, T J; Palosuo, T; Kersebaum, K C

    2016-01-01

    Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen...

  10. Intercropping reduces nitrate leaching from under field crops without loss of yield: A modelling study

    NARCIS (Netherlands)

    Whitmore, A.P.; Schröder, J.J.

    2007-01-01

    A model of soil nitrogen dynamics under competing intercrops is described and used to interpret two sets of experimental field data from the literature. In one series of experiments, maize received slurry and mineral nitrogen (N) fertiliser or mineral N alone and was grown either alone or

  11. Improving the CROPGRO-Tomato model for predicting growth and yield to temperature

    NARCIS (Netherlands)

    Boote, K.J.; Rybak, M.R.; Scholberg, J.M.S.; Jones, J.W.

    2012-01-01

    Parameterizing crop models for more accurate response to climate factors such as temperature is important considering potential temperature increases associated with climate change, particularly for tomato (Lycopersicon esculentum Mill.), which is a heat-sensitive crop. The objective of this work

  12. Validation of Crop Weather Models for'Crop Assessment arid Yield ...

    African Journals Online (AJOL)

    R.W. 1997. CRPSM - Crop,growth and irrigation scheduling model. Software user manual. Biolog- ical & Irrigation Engineering Department. Utah. State University. Logan, UT 84322-4105, 204 p. Jensen. M.E. 1968. Water consumption by agricultural plants. 111: T. T. Kozlowski (Eds.), Vo1.2, Water deficits and plant growth.

  13. Models for Broad Area Event Identification and Yield Estimation: Multiple Coda Types

    Science.gov (United States)

    2011-09-01

    microearthquakes accompanying hydraulic fracturing in granitic rock, Bull. Seism . Soc. Am., 81, 553-575, 1991. Fisk, M. and S. R. Taylor, (2007...146882, pp. 13. Yang, X., T. Lay, X.-B. Xie, and M. S. Thorne (2007). Geometric spreading of Pn and Sn in a spherical Earth model, Bull. Seism . Soc

  14. Modelling of bio-oil yield from fast pyrolysis of sawdust | Kuye ...

    African Journals Online (AJOL)

    Bio-oil has received great attention due to the environmental concerns associated with the usage of fossil fuels and the predicted inability of these fuels to cope with future increases in energy demands. In this work an existing kinetic model equation has been modified using polynomial equations in conjunction with ...

  15. Changes in water budgets and sediment yields from a hypothetical agricultural field as a function of landscape and management characteristics--A unit field modeling approach

    Science.gov (United States)

    Roth, Jason L.; Capel, Paul D.

    2012-01-01

    Crop agriculture occupies 13 percent of the conterminous United States. Agricultural management practices, such as crop and tillage types, affect the hydrologic flow paths through the landscape. Some agricultural practices, such as drainage and irrigation, create entirely new hydrologic flow paths upon the landscapes where they are implemented. These hydrologic changes can affect the magnitude and partitioning of water budgets and sediment erosion. Given the wide degree of variability amongst agricultural settings, changes in the magnitudes of hydrologic flow paths and sediment erosion induced by agricultural management practices commonly are difficult to characterize, quantify, and compare using only field observations. The Water Erosion Prediction Project (WEPP) model was used to simulate two landscape characteristics (slope and soil texture) and three agricultural management practices (land cover/crop type, tillage type, and selected agricultural land management practices) to evaluate their effects on the water budgets of and sediment yield from agricultural lands. An array of sixty-eight 60-year simulations were run, each representing a distinct natural or agricultural scenario with various slopes, soil textures, crop or land cover types, tillage types, and select agricultural management practices on an isolated 16.2-hectare field. Simulations were made to represent two common agricultural climate regimes: arid with sprinkler irrigation and humid. These climate regimes were constructed with actual climate and irrigation data. The results of these simulations demonstrate the magnitudes of potential changes in water budgets and sediment yields from lands as a result of landscape characteristics and agricultural practices adopted on them. These simulations showed that variations in landscape characteristics, such as slope and soil type, had appreciable effects on water budgets and sediment yields. As slopes increased, sediment yields increased in both the arid and

  16. Effects of metal nanoparticles on the secondary ion yields of a model alkane molecule upon atomic and polyatomic projectiles in secondary ion mass spectrometry.

    Science.gov (United States)

    Wehbe, Nimer; Heile, Andreas; Arlinghaus, Heinrich F; Bertrand, Patrick; Delcorte, Arnaud

    2008-08-15

    A model alkane molecule, triacontane, is used to assess the effects of condensed gold and silver nanoparticles on the molecular ion yields upon atomic (Ga(+) and In(+)) and polyatomic (C60(+) and Bi3(+)) ion bombardment in metal-assisted secondary ion mass spectrometry (MetA-SIMS). Molecular films spin-coated on silicon were metallized using a sputter-coater system, in order to deposit controlled quantities of gold and silver on the surface (from 0 to 15 nm equivalent thickness). The effects of gold and silver islets condensed on triacontane are also compared to the situation of thin triacontane overlayers on metallic substrates (gold and silver). The results focus primarily on the measured yields of quasi-molecular ions, such as (M - H)(+) and (2M - 2H)(+), and metal-cationized molecules, such as (M + Au)(+) and (M + Ag)(+), as a function of the quantity of metal on the surface. They confirm the absence of a simple rule to explain the secondary ion yield improvement in MetA-SIMS. The behavior is strongly dependent on the specific projectile/metal couple used for the experiment. Under atomic bombardment (Ga(+), In(+)), the characteristic ion yields an increase with the gold dose up to approximately 6 nm equivalent thickness. The yield enhancement factor between gold-metallized and pristine samples can be as large as approximately 70 (for (M - H)(+) under Ga(+) bombardment; 10 nm of Au). In contrast, with cluster projectiles such as Bi3(+) and C60(+), the presence of gold and silver leads to a dramatic molecular ion yield decrease. Cluster projectiles prove to be beneficial for triacontane overlayers spin-coated on silicon or metal substrates (Au, Ag) but not in the situation of MetA-SIMS. The fundamental difference of behavior between atomic and cluster primary ions is tentatively explained by arguments involving the different energy deposition mechanisms of these projectiles. Our results also show that Au and Ag nanoparticles do not induce the same behavior in Met

  17. A comparative study of secondary ion yield from model biological membranes using Au n+ and C60+ primary ion sources

    International Nuclear Information System (INIS)

    Baker, M.J.; Fletcher, J.S.; Jungnickel, H.; Lockyer, N.P.; Vickerman, J.C.

    2006-01-01

    Au n + and C 60 + primary ion sources have been used to acquire spectra from phospholipids, symmetric liposomes and asymmetric liposomes. We demonstrate that when using different ion beams different chemical information can be obtained. Symmetric and asymmetric liposomes, with 95% asymmetry, were produced and analysed with Au + , Au 3 + and C 60 + primary ion beams. C 60 + gave the greatest yield from the symmetric liposome but after correcting for the yield effects on the data obtained from the asymmetric liposome it has been shown that C 60 + is the most surface sensitive, providing the least information from the inner leaflet of the liposome. Au n + provides the greatest amount of information from the inner leaflet. The results present the possibility of designing ToF-SIMS experiments that selectively probe specific regions of a (bio)molecular surface

  18. Genomics approaches to unlock the high yield potential of cassava, a tropical model plant

    Directory of Open Access Journals (Sweden)

    Shengkui ZHANG,Ping'an MA,Haiyan WANG,Cheng LU,Xin CHEN,Zhiqiang XIA,Meiling ZOU,Xinchen ZHOU,Wenquan WANG

    2014-12-01

    Full Text Available Cassava, a tropical food, feed and biofuel crop, has great capacity for biomass accumulation and an extraordinary efficiency in water use and mineral nutrition, which makes it highly suitable as a model plant for tropical crops. However, the understanding of the metabolism and genomics of this important crop is limited. The recent breakthroughs in the genomics of cassava, including whole-genome sequencing and transcriptome analysis, as well as advances in the biology of photosynthesis, starch biosynthesis, adaptation to drought and high temperature, and resistance to virus and bacterial diseases, are reviewed here. Many of the new developments have come from comparative analyses between a wild ancestor and existing cultivars. Finally, the current challenges and future potential of cassava as a model plant are discussed.

  19. Regional crop yield forecasting using probalistic crop growth modelling and remote sensing data assimilation

    OpenAIRE

    Wit, de, A.J.W.

    2007-01-01

    Een belangrijk onderdeel van het MARS oogstvoorspellingssysteem is het zogenaamde CGMS (crop growth monitoring system). CGMS gebruikt een gewasgroeimodel om het effect van bodem, weer en teeltmaatregelen op de groei van het gewas te bepalen. Hiervoor worden relevante gegevens verzameld over Europa. Op basis van deze gegevens simuleert het model WOFOST de gewasgroei. In dit proefschrift wordt op praktische en theoretische gronden beargumenteerd dat de onzekerheid in het weer de bepalende facto...

  20. Using the CLM Crop Model to assess the impacts of changes in Climate, Atmospheric CO2, Irrigation, Fertilizer and Geographic Distribution on Historical and Future Crop Yields

    Science.gov (United States)

    Lawrence, P.

    2015-12-01

    Since the start of the green revolution global crop yields have increased linearly for most major cereal crops, so that present day global values are around twice those of the 1960s. The increase in crop yields have allowed for large increases in global agricultural production without correspondingly large increases in cropping area. Future projections under the Shared Socio-economic Pathways (SSP) framework and other assessments result in increases of global crop production of greater than 100% by the year 2050. In order to meet this increased agricultural demand within the available arable land, future production gains need to be understood in terms of the yield changes due to changes in climate, atmospheric CO2, and adaptive management such as irrigation and fertilizer application. In addition to the changes in crop yield, future agricultural demand will need to be met through increasing cropping areas into what are currently marginal lands at the cost of existing forests and other natural ecosystems. In this study we assess the utility of the crop model within the Community Land Model (CLM Crop) to provide both historical and future guidance on changes in crop yields under a range of global idealized crop modeling experiments. The idealized experiments follow the experimental design of the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) in which CLM Crop is a participating model. The idealized experiments consist of global crop simulations for Cotton, Maize, Rice, Soy, Sugarcane, and Wheat under various climate, atmospheric CO2 levels, irrigation prescription, and nitrogen fertilizer application. The time periods simulated for the experiments are for the Historical period (1901 - 2005), and for the two Representative Concentration Pathways of RCP 4.5 and RCP 8.5 (2006 - 2100). Each crop is simulated on all land grid cells globally for each time period with atmospheric forcing that is a combination of: 1. transient climate and CO2; 2. transient climate

  1. Comparison of Fixed Regression and Random Regression Test-Day Models for genetic evaluation of milk yield trait in Holstein cows Razavi Khorasan province

    Directory of Open Access Journals (Sweden)

    Y Shamshirgaran

    2011-12-01

    Full Text Available The Fixed Regression Test-Day Model (FRM and Random Regression Test-Day Model (RRM for genetic evaluation of milk yield trait of dairy cattle in Khorasan Razavi province were studied. Breeding values and genetic parameters of milk yield trait from two models were compared. A total of 164391 monthly test day milk records (three times milking per day obtained from 19217 Holstein cows distributed in 172 herds and calved from 1991 to 2008, were used to estimate genetic parameters and to predict breeding values. The contemporary group of herd- year- month of production was fitted as fixed effects in the models. Also linear and quadratic forms of age at calving and Holstein gene percentage were fitted as covariate. The random factors of the models were additive genetic and permanent environmental effects. In the random regression model, orthogonal legendre polynomial up to order 4(cubic was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. Heritability estimates resulted from the FRM was 0.15. The average heritability estimates resulted from the RRM of monthly test day milk production for the second half of the lactation was higher than that of the first half of lactation period. The highest and lowest heritability values were found for the first (0.102 and sixth (0.235 month of lactation. Breeding value of animals predicted from FRM and RRM were also compared. The results showed similar ranking of animals based on their breeding values from both models.

  2. Sensitivity of the ATLAS experiment to discover the decay H{yields} {tau}{tau} {yields}ll+4{nu} of the Standard Model Higgs Boson produced in vector boson fusion

    Energy Technology Data Exchange (ETDEWEB)

    Schmitz, Martin

    2011-05-17

    A study of the expected sensitivity of the ATLAS experiment to discover the Standard Model Higgs boson produced via vector boson fusion (VBF) and its decay to H{yields} {tau}{tau}{yields} ll+4{nu} is presented. The study is based on simulated proton-proton collisions at a centre-of-mass energy of 14 TeV. For the first time the discovery potential is evaluated in the presence of additional proton-proton interactions (pile-up) to the process of interest in a complete and consistent way. Special emphasis is placed on the development of background estimation techniques to extract the main background processes Z{yields}{tau}{tau} and t anti t production using data. The t anti t background is estimated using a control sample selected with the VBF analysis cuts and the inverted b-jet veto. The dominant background process Z{yields}{tau}{tau} is estimated using Z{yields}{mu}{mu} events. Replacing the muons of the Z{yields}{mu}{mu} event with simulated {tau}-leptons, Z{yields}{tau}{tau} events are modelled to high precision. For the replacement of the Z boson decay products a dedicated method based on tracks and calorimeter cells is developed. Without pile-up a discovery potential of 3{sigma} to 3.4{sigma} in the mass range 115 GeV

  3. Some results regarding the comparison of the Earth's atmospheric models

    Directory of Open Access Journals (Sweden)

    Šegan S.

    2005-01-01

    Full Text Available In this paper we examine air densities derived from our realization of aeronomic atmosphere models based on accelerometer measurements from satellites in a low Earth's orbit (LEO. Using the adapted algorithms we derive comparison parameters. The first results concerning the adjustment of the aeronomic models to the total-density model are given.

  4. Bohman-Frieze-Wormald model on the lattice, yielding a discontinuous percolation transition

    Science.gov (United States)

    Schrenk, K. J.; Felder, A.; Deflorin, S.; Araújo, N. A. M.; D'Souza, R. M.; Herrmann, H. J.

    2012-03-01

    The BFW model introduced by Bohman, Frieze, and Wormald [Random Struct. Algorithms1042-983210.1002/rsa.20038, 25, 432 (2004)], and recently investigated in the framework of discontinuous percolation by Chen and D'Souza [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.106.115701 106, 115701 (2011)], is studied on the square and simple-cubic lattices. In two and three dimensions, we find numerical evidence for a strongly discontinuous transition. In two dimensions, the clusters at the threshold are compact with a fractal surface of fractal dimension df=1.49±0.02. On the simple-cubic lattice, distinct jumps in the size of the largest cluster are observed. We proceed to analyze the tree-like version of the model, where only merging bonds are sampled, for dimension two to seven. The transition is again discontinuous in any considered dimension. Finally, the dependence of the cluster-size distribution at the threshold on the spatial dimension is also investigated.

  5. A Coupled Crystal Plasticity and Anisotropic Yield Function Model to Identify the Anisotropic Plastic Properties and Friction Behavior of an AA 3003 Alloy

    Science.gov (United States)

    Bong, Hyuk Jong; Leem, Dohyun; Lee, Jinwoo; Ha, Jinjin; Lee, Myoung-Gyu

    2018-01-01

    A multi-scale simulation of the tip test, developed to determine the tribological characteristics of the back-extrusion process, was conducted on an AA 3003 alloy. A microstructure-level simulation, coupled with crystal plasticity finite element (CPFE) analysis, was utilized to characterize the macro-mechanical properties of the AA 3003. Owing to the limited size of the material provided, we performed CPFE analyses rather than multiple mechanical tests to determine the plastic anisotropy characteristics of the AA 3003 alloy. A three-dimensional finite element (FE) model of the tip test was developed using two different yield functions, namely the generalized von Mises yield function and Hill's (1948) yield function, with material parameters identified from the CPFE analyses. The results revealed the following: 1. The directionality observed during the tip test is governed by the plastic anisotropy, rather than the frictional conditions. 2. The plastic anisotropy results in different Coulomb friction values. Therefore, the anisotropy should be carefully addressed in the tip test.

  6. Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model.

    Science.gov (United States)

    DeGroot, B J; Keown, J F; Van Vleck, L D; Kachman, S D

    2007-06-30

    Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.

  7. A new prediction model for grain yield in Northeast China based on spring North Atlantic Oscillation and late-winter Bering Sea ice cover

    Science.gov (United States)

    Zhou, Mengzi; Wang, Huijun; Huo, Zhiguo

    2017-04-01

    Accurate estimations of grain output in the agriculturally important region of Northeast China are of great strategic significance for guaranteeing food security. New prediction models for maize and rice yields are built in this paper based on the spring North Atlantic Oscillation index and the Bering Sea ice cover index. The year-to-year increment is first forecasted and then the original yield value is obtained by adding the historical yield of the previous year. The multivariate linear prediction model of maize shows good predictive ability, with a low normalized root-mean-square error (NRMSE) of 13.9%, and the simulated yield accounts for 81% of the total variance of the observation. To improve the performance of the multivariate linear model, a combined forecasting model of rice is built by considering the weight of the predictors. The NRMSE of the model is 12.9% and the predicted rice yield explains 71% of the total variance. The corresponding cross-validation test and independent samples test further demonstrate the efficiency of the models. It is inferred that the statistical models established here by applying year-to-year increment approach could make rational prediction for the maize and rice yield in Northeast China before harvest. The present study may shed new light on yield prediction in advance by use of antecedent large-scale climate signals adequately.

  8. Simulation of rice yield under different irrigation and nitrogen application managements by CropSyst model

    Directory of Open Access Journals (Sweden)

    Narjes ZARE

    2015-12-01

    Full Text Available The aim of this study was the calibration and validation of CropSyst model for rice in the city of Rasht. The necessary data were extracted from a field experiment which was carried out during 2005-2007 in a split-plot design. The main plots were irrigation regimes including continuous flooding irrigation and 5-day irrigation intervals. The subplots consisted of four nitrogen levels: zero N application, 45, 60 and 75 kg N ha-1. Normalized Root Mean Squared Error (nRMSE and Residual Mass Coefficient (Crm in calibration years were 9.3 % and 0.06, respectively. In validation year, nRMSE and Crm were 9.7 % and 0.11, respectively. According to other indices to assess irrigation regimes and fertilizer levels, the most suitable treatments regarding environmental aspect were 5-day irrigation regime and 45 kg N ha-1.

  9. Interpolating the South African Yield Curve using Principal ...

    African Journals Online (AJOL)

    A principal-components analysis of the South African yield curve suggests that two factors explain most of the variability in both yields and changes in yields. This result is used to select which two interest rates to model and, given a model for these rates, how to use them to reproduce the entire curve. The objective of this ...

  10. Verification of aseismic design model by using experimental results

    International Nuclear Information System (INIS)

    Mizuno, N.; Sugiyama, N.; Suzuki, T.; Shibata, Y.; Miura, K.; Miyagawa, N.

    1985-01-01

    A lattice model is applied as an analysis model for an aseismic design of the Hamaoka nuclear reactor building. With object to verify an availability of this design model, two reinforced concrete blocks are constructed on the ground and the forced vibration tests are carried out. The test results are well followed by simulation analysis using the lattice model. Damping value of the ground obtained from the test is more conservative than the design value. (orig.)

  11. Strategies for narrowing the maize yield gap of household farms through precision fertigation under irrigated conditions using CERES-Maize model.

    Science.gov (United States)

    Liu, Jiangang; Wang, Guangyao; Chu, Qingquan; Chen, Fu

    2017-07-01

    Nitrogen (N) application significantly increases maize yield; however, the unreasonable use of N fertilizer is common in China. The analysis of crop yield gaps can reveal the limiting factors for yield improvement, but there is a lack of practical strategies for narrowing yield gaps of household farms. The objectives of this study were to assess the yield gap of summer maize using an integrative method and to develop strategies for narrowing the maize yield gap through precise N fertilization. The results indicated that there was a significant difference in maize yield among fields, with a low level of variation. Additionally, significant differences in N application rate were observed among fields, with high variability. Based on long-term simulation results, the optimal N application rate was 193 kg ha -1 , with a corresponding maximum attainable yield (AY max ) of 10 318 kg ha -1 . A considerable difference between farmers' yields and AY max was observed. Low agronomic efficiency of applied N fertilizer (AE N ) in farmers' fields was exhibited. The integrative method lays a foundation for exploring the specific factors constraining crop yield gaps at the field scale and for developing strategies for rapid site-specific N management. Optimization strategies to narrow the maize yield gap include increasing N application rates and adjusting the N application schedule. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  12. Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models

    DEFF Research Database (Denmark)

    Palosuo, Taru; Kersebaum, Kurt Christian; Angulo, Carlos

    2011-01-01

    We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central and sout......We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central...... values were lowest (1428 and 1603 kg ha−1) and the index of agreement (0.71 and 0.74) highest. CROPSYST systematically underestimated yields (MBE – 1186 kg ha−1), whereas HERMES, STICS and WOFOST clearly overestimated them (MBE 1174, 1272 and 1213 kg ha−1, respectively). APES, DAISY, HERMES, STICS...

  13. Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

    Directory of Open Access Journals (Sweden)

    Kefeng Zhang

    Full Text Available Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190 uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3 cm(-3 and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model

  14. Response model of vegetation parameters and yield in maize under the influence of Lithovit fertilizer

    Science.gov (United States)

    Gigel, Prisecaru; Florin, Sala

    2017-07-01

    Control of plant nutrition and photosynthetic processes through fertilization is a necessary and current practice, to corn crop. This study aimed to assess the influence of Lithovit fertilizer, a product with a balanced content of nutrients, on chlorophyll content as an indicator of physiological status of plants and production of maize, hybrid Andreea. In the range of concentrations tested (0.3%, 0.5%, 0.75% and 1%), along with a control variant, product Lithovit generated the best results at concentrations of 0.5% and 0.7%, safely statistics (p the values of chlorophyll content in the stages of growth, BBCH 30 (R2 = 0.998, p the production of corn, safely statistics. The behavior of response curves was described by polynomial functions of order 3, which capture the inflection points as a result of how to variation of chlorophyll content, amid treatments applied.

  15. An RF Performance Sensitivity and Process Yield Model for MIMIC CAD applications. MIMIC Program. Phase 3

    Science.gov (United States)

    1991-09-16

    process and RF simulators would be closed, and much time, effort, and expense would be saved since device optimization studies could be performed...gain compression measures result from solution of (PIdB(PgdB) - Pgd )- (Gt - Gc) = 0 Pg,W E R. Where Gt is computed by the formula above and Gc is a...conditions. Since simulations can be performed before fabrication, significant time, effort, and expense can be saved in the development of advanced

  16. Hot topic: Bovine milk samples yielding negative or nonspecific results in bacterial culturing--the possible role of PCR-single strand conformation polymorphism in mastitis diagnosis.

    Science.gov (United States)

    Schwaiger, K; Wimmer, M; Huber-Schlenstedt, R; Fehlings, K; Hölzel, C S; Bauer, J

    2012-01-01

    A large proportion of mastitis milk samples yield negative or nonspecific results (i.e., no mastitis pathogen can be identified) in bacterial culturing. Therefore, the culture-independent PCR-single strand conformation polymorphism method was applied to the investigation of bovine mastitis milk samples. In addition to the known mastitis pathogens, the method was suitable for the detection of fastidious bacteria such as Mycoplasma spp., which are often missed by conventional culturing methods. The detection of Helcococcus ovis in 4 samples might indicate an involvement of this species in pathogenesis of bovine mastitis. In conclusion, PCR-single-strand conformation polymorphism is a promising tool for gaining new insights into the bacteriological etiology of mastitis. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  17. Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    (Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

  18. Assessment of potential suspended sediment yield in Japan in the 21st century with reference to the general circulation model climate change scenarios

    Science.gov (United States)

    Mouri, Goro; Golosov, Valentin; Chalov, Sergey; Takizawa, Satoshi; Oguma, Kumiko; Yoshimura, Kei; Shiiba, Michiharu; Hori, Tomoharu; Oki, Taikan

    2013-03-01

    In recent decades, soil erosion by water has become a worldwide problem, especially with climate change and progressive declines in the ratio of natural resources to human populations. Changes in future climate will influence soil erosion, particularly suspended sediment (SS) yield, and alter the effectiveness of water resources management strategies from a water quality perspective. We qualitatively assessed future changes in SS yield in Japan. We focused on the impacts of future hydrological changes projected by two models, the Model for Interdisciplinary Research on Climate (MIROC) and the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), whose results have produced monthly data sets for the whole of Japan. The impacts of future climate changes on SS in Japan depend on the balance between changes in climatic and geologic factors. Methods for assessing impact using the catchment simulator were expanded to estimate the SS yield for the whole of Japan. The results indicated that SS generation will increase by the 2090s, with an 8% increase predicted using MRI-GCM data and a 24% increase using MIROC data, compared to present-day values measured by the Automated Meteorological Data Acquisition System (AMEDAS) of the Japan Meteorological Agency. Analysis by month showed the largest increases in SS in September, related to the frequency of extreme events such as typhoons. Increased SS can have negative effects on both society and the environment, including reduced crop productivity, worsened water quality, lower effective reservoir water levels, flooding and habitat destruction. Prediction of the impacts of future climate change on SS generation is crucial for effective environmental planning and management.

  19. Spatial analysis of the dairy yield using a conditional autoregressive model / Análise espacial da produção leiteira usando um modelo autoregressivo condicional

    Directory of Open Access Journals (Sweden)

    João Domingos Scalon

    2010-07-01

    Full Text Available The dairy yield is one of the most important activities for the Brazilian economy and the use of statistical models may improve the decision making in this productive sector. The aim of this paper was to compare the performance of both the traditional linear regression model and the spatial regression model called conditional autoregressive (CAR to explain how some covariates may contribute for the dairy yield. This work used a database on dairy yield supplied by the Brazilian Institute of Geography and Statistics (IBGE and another database on geographical information of the state of Minas Gerais provided by the Integrated Program of Technological Use of Geographical Information (GEOMINAS. The results showed the superiority of the CAR model over the traditional linear regression model to explain the dairy yield. The CAR model allowed the identification of two different spatial clusters of counties related to the dairy yield in the state of Minas Gerais. The first cluster represents the region where one observes the biggest levels of dairy yield. It is formed by the counties of the Triângulo Mineiro. The second cluster is formed by the northern counties of the state that present the lesser levels of dairy yield. A produção de leite é uma das atividades mais importantes para a economia brasileira e o uso de modelos estatísticos pode auxiliar a tomada de decisão neste setor produtivo. O objetivo deste artigo foi comparar o desempenho do modelo de regressão linear tradicional e do modelo de regressão espacial, denominado de autoregressivo condicional (CAR, para explicar como algumas variáveis preditoras contribuem para a quantidade de leite produzido. Este trabalho usou uma base de dados sobre a produção de leite fornecida pelo Instituto Brasileiro de Geografia e Estatística (IBGE e outra base de dados sobre informações geográficas do estado de Minas Gerais, fornecida pelo Programa Integrado de Uso da Tecnologia de Geoprocessamento

  20. Steel Containment Vessel Model Test: Results and Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Costello, J.F.; Hashimote, T.; Hessheimer, M.F.; Luk, V.K.

    1999-03-01

    A high pressure test of the steel containment vessel (SCV) model was conducted on December 11-12, 1996 at Sandia National Laboratories, Albuquerque, NM, USA. The test model is a mixed-scaled model (1:10 in geometry and 1:4 in shell thickness) of an improved Mark II boiling water reactor (BWR) containment. A concentric steel contact structure (CS), installed over the SCV model and separated at a nominally uniform distance from it, provided a simplified representation of a reactor shield building in the actual plant. The SCV model and contact structure were instrumented with strain gages and displacement transducers to record the deformation behavior of the SCV model during the high pressure test. This paper summarizes the conduct and the results of the high pressure test and discusses the posttest metallurgical evaluation results on specimens removed from the SCV model.

  1. Identifiability Results for Several Classes of Linear Compartment Models.

    Science.gov (United States)

    Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

    2015-08-01

    Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

  2. The yield of a positive MRI of the spine as imaging criterion in the ASAS classification criteria for axial spondyloarthritis: results from the SPACE and DESIR cohorts.

    Science.gov (United States)

    Ez-Zaitouni, Zineb; Bakker, Pauline Ac; van Lunteren, Miranda; de Hooge, Manouk; van den Berg, Rosaline; Reijnierse, Monique; Fagerli, Karen Minde; Landewé, Robert Bm; Ramonda, Roberta; Jacobsson, Lennart Th; Saraux, Alain; Lenczner, Gregory; Feydy, Antoine; Pialat, Jean Baptiste; Thévenin, Fabrice; van Gaalen, Floris A; van der Heijde, Désirée

    2017-10-01

    To assess the prevalence of spinal inflammation on MRI in patients with chronic back pain (CBP) of maximally 3 years duration and to evaluate the yield of adding a positive MRI-spine as imaging criterion to the Assessment of SpondyloArthritis international Society (ASAS) classification criteria for axial spondyloarthritis (axSpA). Baseline imaging of the sacroiliac joints (X-SI), MRI of the sacroiliac joints (MRI-SI) and MRI-spine were scored by ≥2 experienced central readers per modality in the SPondyloArthritis Caught Early (SPACE) and DEvenir des Spondylarthropathies Indifférenciées Récentes (DESIR) cohorts. Inflammation suggestive of axSpA was assessed in the entire spine. A positive MRI-spine was defined by the presence of ≥5 inflammatory lesions. Alternative less strict definitions were also tested. In this study, 541 and 650 patients with CBP from the SPACE and DESIR cohorts were included. Sacroiliitis on X-SI and MRI-SI was found in 40/541 (7%) and 76/541 (14%) patients in SPACE, and in DESIR in 134/650 (21%) and 231/650 (36%) patients, respectively. In SPACE and DESIR, a positive MRI-spine was seen in 4/541 (1%) and 48/650 (7%) patients. Of the patients without sacroiliitis on imaging, 3/447 (1%) (SPACE) and 8/382 (2%) (DESIR) patients had a positive MRI-spine. Adding positive MRI-spine as imaging criterion led to new classification in only one patient in each cohort, as the other patients already fulfilled the clinical arm. Other definitions of a positive MRI-spine yielded similar results. In two cohorts of patients with CBP with a maximum symptom duration of 3 years, a positive MRI-spine was rare in patients without sacroiliitis on MRI-SI and X-SI. Addition of MRI-spine as imaging criterion to the ASAS axSpA criteria had a low yield of newly classified patients and is therefore not recommended. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is

  3. Optimization model of peach production relevant to input energies – Yield function in Chaharmahal va Bakhtiari province, Iran

    International Nuclear Information System (INIS)

    Ghatrehsamani, Shirin; Ebrahimi, Rahim; Kazi, Salim Newaz; Badarudin Badry, Ahmad; Sadeghinezhad, Emad

    2016-01-01

    The aim of this study was to determine the amount of input–output energy used in peach production and to develop an optimal model of production in Chaharmahal va Bakhtiari province, Iran. Data were collected from 100 producers by administering a questionnaire in face-to-face interviews. Farms were selected based on random sampling method. Results revealed that the total energy of production is 47,951.52 MJ/ha and the highest share of energy consumption belongs to chemical fertilizers (35.37%). Consumption of direct energy was 47.4% while indirect energy was 52.6%. Also, Total energy consumption was divided into two groups; renewable and non-renewable (19.2% and 80.8% respectively). Energy use efficiency, Energy productivity, Specific energy and Net energy were calculated as 0.433, 0.228 (kg/MJ), 4.38 (MJ/kg) and −27,161.722 (MJ/ha), respectively. According to the negative sign for Net energy, if special strategy is used, energy dismiss will decrease and negative effect of some parameters could be omitted. In the present case the amount is indicating decimate of production energy. In addition, energy efficiency was not high enough. Some of the input energies were applied to machinery, chemical fertilizer, water irrigation and electricity which had significant effect on increasing production and MPP (marginal physical productivity) was determined for variables. This parameter was positive for energy groups namely; machinery, diesel fuel, chemical fertilizer, water irrigation and electricity while it was negative for other kind of energy such as chemical pesticides and human labor. Finally, there is a need to pursue a new policy to force producers to undertake energy-efficient practices to establish sustainable production systems without disrupting the natural resources. In addition, extension activities are needed to improve the efficiency of energy consumption and to sustain the natural resources. - Highlights: • Replacing non-renewable energy with renewable

  4. Quantifying long-term responses of crop yield and nitrate leaching in an intensive farmland using agro-eco-environmental model.

    Science.gov (United States)

    Sun, Mei; Huo, Zailin; Zheng, Yanxia; Dai, Xiaoqin; Feng, Shaoyuan; Mao, Xiaomin

    2018-02-01

    Quantitatively ascertaining and analyzing long-term responses of crop yield and nitrate leaching on varying irrigation and fertilization treatments are focal points for guaranteeing crop yield and reducing nitrogen loss. The calibrated agricultural-hydrological RZWQM2 model was used to explore the long-term (2003-2013) transport processes of water and nitrogen and the nitrate leaching amount into groundwater in summer maize and winter wheat rotation field in typical intensive plant area in the North China Plain, Daxing district of Beijing. Simulation results showed that application rates of irrigation and nitrogen fertilizer have couple effects on crop yields and nitrogen leaching of root zone. When both the irrigation and fertilizer for summer maize and winter wheat were 400mm and 400kgNha -1 , respectively, nitrate leaching into groundwater accounted for 47.9% of application amount of nitrogen fertilizer. When application amount of irrigation is 200mm and fertilization is 200kgNha -1 , NUPE (nitrogen uptake efficiency), NUE (nitrogen use efficiency), NPFP (nitrogen partial factor productivity), and W pi (irrigation water productive efficiency) were in general higher than that under other irrigation and fertilization condition (irrigation from 104-400mm, fertilizer 104-400kgNha -1 ). Irrigation bigger than 200mm could shorten the response time of nitrate leaching in deeper soil layer in different irrigation treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. A model of a successful utilization of a high genetic potential of maize yield

    Directory of Open Access Journals (Sweden)

    Pavlov Milovan

    2008-01-01

    Full Text Available The principle of a system, defined as a ZP system, implying corresponding relationship among research, seed production and seed marketing, is that each segment within the system has its tasks and responsibilities, as well as, a clear interest. This system was established at the Maize Research Institute, Zemun Polje, almost half a century ago. The crucial characteristic is that this system encompasses obtained results of scientific accomplishments (patent - a released hybrid, optimal utilisation of the environmental conditions, facilities for seed drying, processing and packing, staff and transport capacities. The ZP system provides the economic interest of all participants in studies and the maize seed production. The fundamental base of the quality seed production within the ZP system is a multidisciplinary programme on maize breeding, as well as, 535 released hybrids with standard and specific traits. According to regulations in foreign countries, approximately 100 ZP maize hybrids have been released abroad. Agroecological conditions in Serbia are favorable for the development of the best genotypes and the production of basic and certified maize seed. There 10 processing plants that apply recent technologies in the maize seed processing procedure. Several generations of experts have been trained and gained experience within the maize seed production. Three seed testing laboratories have been accredited by the International Seed Testing Association. According to regulations in Serbia, monitoring of seed production under field conditions, and further on, during the processing practice is done only by designate authorities. This study presents one of successful systems of the seed production organization applicable in countries with similar conditions.

  6. Results of the Marine Ice Sheet Model Intercomparison Project, MISMIP

    Directory of Open Access Journals (Sweden)

    F. Pattyn

    2012-05-01

    Full Text Available Predictions of marine ice-sheet behaviour require models that are able to robustly simulate grounding line migration. We present results of an intercomparison exercise for marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no effects of lateral buttressing. Unique steady state grounding line positions exist for ice sheets on a downward sloping bed, while hysteresis occurs across an overdeepened bed, and stable steady state grounding line positions only occur on the downward-sloping sections. Models based on the shallow ice approximation, which does not resolve extensional stresses, do not reproduce the approximate analytical results unless appropriate parameterizations for ice flux are imposed at the grounding line. For extensional-stress resolving "shelfy stream" models, differences between model results were mainly due to the choice of spatial discretization. Moving grid methods were found to be the most accurate at capturing grounding line evolution, since they track the grounding line explicitly. Adaptive mesh refinement can further improve accuracy, including fixed grid models that generally perform poorly at coarse resolution. Fixed grid models, with nested grid representations of the grounding line, are able to generate accurate steady state positions, but can be inaccurate over transients. Only one full-Stokes model was included in the intercomparison, and consequently the accuracy of shelfy stream models as approximations of full-Stokes models remains to be determined in detail, especially during transients.

  7. Yield surface evolution for columnar ice

    Directory of Open Access Journals (Sweden)

    Zhiwei Zhou

    Full Text Available A series of triaxial compression tests, which has capable of measuring the volumetric strain of the sample, were conducted on columnar ice. A new testing approach of probing the experimental yield surface was performed from a single sample in order to investigate yield and hardening behaviors of the columnar ice under complex stress states. Based on the characteristic of the volumetric strain, a new method of defined the multiaxial yield strengths of the columnar ice is proposed. The experimental yield surface remains elliptical shape in the stress space of effective stress versus mean stress. The effect of temperature, loading rate and loading path in the initial yield surface and deformation properties of the columnar ice were also studied. Subsequent yield surfaces of the columnar ice have been explored by using uniaxial and hydrostatic paths. The evolution of the subsequent yield surface exhibits significant path-dependent characteristics. The multiaxial hardening law of the columnar ice was established experimentally. A phenomenological yield criterion was presented for multiaxial yield and hardening behaviors of the columnar ice. The comparisons between the theoretical and measured results indicate that this current model is capable of giving a reasonable prediction for the multiaxial yield and post-yield properties of the columnar ice subjected to different temperature, loading rate and path conditions. Keywords: Columnar ice, Multiaxial loading, Hardening rule, Path dependency, Yield criterion

  8. Integrating landscape and hydrologic simulation models to assess the influence of fire-suppression on water yield from forested Rocky Mountain watersheds

    Science.gov (United States)

    Ahl, R. S.; Woods, S.; Diluzio, M.

    2005-12-01

    Most of the water supply for semi-arid western North America originates as snow that is deposited and temporarily stored in forested, high elevation watersheds. Snow accumulation in these watersheds varies with climate, elevation, topography and forest vegetation characteristics. Canopy structure is an especially important vegetation characteristic because of its effect on the interception component of the water budget and the wind speed and solar radiation flux at the snow surface. Canopy structure is a function of forest composition, structure and extent, all of which are shaped by disturbance processes such as fire, insect and disease outbreaks, and human-induced changes. Changes in the frequency and magnitude of these disturbance processes such as those that have occurred due to fire suppression lead to changes in forest structure, and this may result in long term reductions in water yield from forested watersheds. We have developed a methodology for linking, spatially explicit, time-series, landcover and hydrologic analysis at the watershed scale, with the goal of quantifying changes in long term water yield due to fire suppression and other management scenarios. Output from the SIMPPLLE (Simulating Patterns and Processes at Landscape Scales) vegetation simulation model is classified and processed to provide input to the SWAT (Soil and Water Assessment Tool) hydrologic model. SIMPPLLE integrates various data sources to simulate vegetation growth and disturbance pathways for forested environments in the Rocky Mountains. We used SIMPPLLE to simulate landcover change 300 years forward from current conditions for 1) fire suppression and 2) natural succession management scenarios. Grid-based maps were produced for each scenario at decadal intervals and used as input for SWAT. SWAT was calibrated using current landcover data and five years of daily streamflow records, and a Nash-Sutcliffe model efficiency of 0.90 was achieved. The calibrated SWAT model was then used

  9. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM considering different order of Legendre polynomial for the additive genetic effect (4th order and the permanent environmental effect (5th order. Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11 to 0.99 (TD-4 and TD-5. The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  10. e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding.

    Science.gov (United States)

    Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N; Friggens, N C

    2012-06-01

    This animal simulation model, named e-Cow, represents a single dairy cow at grazing. The model integrates algorithms from three previously published models: a model that predicts herbage dry matter (DM) intake by grazing dairy cows, a mammary gland model that predicts potential milk yield and a body lipid model that predicts genetically driven live weight (LW) and body condition score (BCS). Both nutritional and genetic drives are accounted for in the prediction of energy intake and its partitioning. The main inputs are herbage allowance (HA; kg DM offered/cow per day), metabolisable energy and NDF concentrations in herbage and supplements, supplements offered (kg DM/cow per day), type of pasture (ryegrass or lucerne), days in milk, days pregnant, lactation number, BCS and LW at calving, breed or strain of cow and genetic merit, that is, potential yields of milk, fat and protein. Separate equations are used to predict herbage intake, depending on the cutting heights at which HA is expressed. The e-Cow model is written in Visual Basic programming language within Microsoft Excel®. The model predicts whole-lactation performance of dairy cows on a daily basis, and the main outputs are the daily and annual DM intake, milk yield and changes in BCS and LW. In the e-Cow model, neither herbage DM intake nor milk yield or LW change are needed as inputs; instead, they are predicted by the e-Cow model. The e-Cow model was validated against experimental data for Holstein-Friesian cows with both North American (NA) and New Zealand (NZ) genetics grazing ryegrass-based pastures, with or without supplementary feeding and for three complete lactations, divided into weekly periods. The model was able to predict animal performance with satisfactory accuracy, with concordance correlation coefficients of 0.81, 0.76 and 0.62 for herbage DM intake, milk yield and LW change, respectively. Simulations performed with the model showed that it is sensitive to genotype by feeding environment

  11. Results on the symmetries of integrable fermionic models on chains

    International Nuclear Information System (INIS)

    Dolcini, F.; Montorsi, A.

    2001-01-01

    We investigate integrable fermionic models within the scheme of the graded quantum inverse scattering method, and prove that any symmetry imposed on the solution of the Yang-Baxter equation reflects on the constants of motion of the model; generalizations with respect to known results are discussed. This theorem is shown to be very effective when combined with the polynomial R-matrix technique (PRT): we apply both of them to the study of the extended Hubbard models, for which we find all the subcases enjoying several kinds of (super)symmetries. In particular, we derive a geometrical construction expressing any gl(2,1)-invariant model as a linear combination of EKS and U-supersymmetric models. Further, we use the PRT to obtain 32 integrable so(4)-invariant models. By joint use of the Sutherland's species technique and η-pairs construction we propose a general method to derive their physical features, and we provide some explicit results

  12. Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes.

    Science.gov (United States)

    Sesana, R C; Bignardi, A B; Borquis, R R A; El Faro, L; Baldi, F; Albuquerque, L G; Tonhati, H

    2010-10-01

    The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes. Copyright 2010 Blackwell Verlag GmbH.

  13. The mCK-5 multiprobe RNase protection assay kit can yield erroneous results for the murine chemokines IP-10 and MCP-1.

    Science.gov (United States)

    Luckow, B; Maier, H; Chilla, S; Pérez de Lema, G

    2000-11-15

    The ribonuclease protection assay (RPA) represents a sensitive method to detect and quantify RNA levels. It can be adapted to allow the simultaneous analysis of more than 10 different mRNAs. The multiprobe RPA kit mCK-5 from PharMingen was used to analyze the expression of chemokines in CCR5 chemokine receptor knockout mice. Upon careful analysis it was found that the mCK-5 kit is defective and can lead to false results for the chemokines IP-10 and MCP-1. The problem is caused by a long-known sequence polymorphism within the 3'-untranslated region of the murine IP-10 gene. This polymorphism leads to a protected IP-10 fragment approximately 20 nucleotides shorter than expected, yielding a length similar to the protected MCP-1 fragment from the mCK-5 kit. Since the identification of specific transcripts with this kit is based exclusively on the size of the various protected fragments, false-negative results for IP-10 together with false-positive results for MCP-1 can be obtained. Interestingly, the polymorphism was found not only in 129/CD-1 mice, but also in MRL and SJL/J mice. To facilitate troubleshooting in the future, all templates from the mCK-5 set were isolated and sequenced. Copyright 2000 Academic Press.

  14. Effects of ocean acidification on fishery yields and profits of red king crab in Bristol Bay from model studies (NCEI Accession 0127395)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This archival package contains model output data that were collected to examine the impact of ocean acidification on fishery yields and profits of red king crab in...

  15. From model to crop: functional characterization of SPL8 in M. truncatula led to genetic improvement of biomass yield and abiotic stress tolerance in alfalfa.

    Science.gov (United States)

    Gou, Jiqing; Debnath, Smriti; Sun, Liang; Flanagan, Amy; Tang, Yuhong; Jiang, Qingzhen; Wen, Jiangqi; Wang, Zeng-Yu

    2018-04-01

    Biomass yield, salt tolerance and drought tolerance are important targets for alfalfa (Medicago sativa L.) improvement. Medicago truncatula has been developed into a model plant for alfalfa and other legumes. By screening a Tnt1 retrotransposon-tagged M. truncatula mutant population, we identified three mutants with enhanced branching. Branch development determines shoot architecture which affects important plant functions such as light acquisition, resource use and ultimately impacts biomass production. Molecular analyses revealed that the mutations were caused by Tnt1 insertions in the SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 8 (SPL8) gene. The M. truncatula spl8 mutants had increased biomass yield, while overexpression of SPL8 in M. truncatula suppressed branching and reduced biomass yield. Scanning electron microscopy (SEM) analysis showed that SPL8 inhibited branching by directly suppressing axillary bud formation. Based on the M. truncatula SPL8 sequence, alfalfa SPL8 (MsSPL8) was cloned and transgenic alfalfa plants were produced. MsSPL8 down-regulated or up-regulated alfalfa plants exhibited similar phenotypes to the M. truncatula mutants or overexpression lines, respectively. Specifically, the MsSPL8 down-regulated alfalfa plants showed up to 43% increase in biomass yield in the first harvest. The impact was even more prominent in the second harvest, with up to 86% increase in biomass production compared to the control. Furthermore, down-regulation of MsSPL8 led to enhanced salt and drought tolerance in transgenic alfalfa. Results from this research offer a valuable approach to simultaneously improve biomass production and abiotic stress tolerance in legumes. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  16. Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-06-01

    parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

  17. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-01-01

    parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

  18. Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2016-02-01

    Full Text Available Introduction: FAO AquaCrop model (Raes et al., 2009a; Steduto et al., 2009 is a user-friendly and practitioner oriented type of model, because it maintains an optimal balance between accuracy, robustness, and simplicity; and it requires a relatively small number of model input parameters. The FAO AquaCrop model predicts crop productivity, water requirement, and water use efficiency under water-limiting and saline water conditions. This model has been tested and validated for different crops such as maize, sunflower and wheat (T. aestivum L. under diverse environments. In most of arid and semi-arid regions water shortage is associated with reduction in water quality (i.e. increasing salinity. Plants in these regions in terms of water quality and quantity may be affected by simultaneous salinity and water stress. Therefore, in this study, the AquaCrop model was evaluated under simultaneous salinity and water stress. In this study, AquaCrop Model (v4.0 was used. This version was developed in 2012 to quantify the effects of salinity. Therefore, the objectives of this study were: i evaluation of AquaCrop model (v4.0 to simulate wheat yield and water use efficiency under simultaneous salinity and water stress conditions in an arid region of Birjand, Iran and ii Using different treatments for nested calibration and validation of AquaCrop model. Materials and Methods: This study was carried out as split plot design (factorial form in Birjand, east of Iran, in order to evaluate the AquaCrop model.Treatments consisted of three levels of irrigation water salinity (S1, S2, S3 corresponding to 1.4, 4.5, 9.6 dS m-1 as main plot, two wheat varieties (Ghods and Roshan, and four levels of irrigation water amount (I1, I2, I3, I4 corresponding to 125, 100, 75, 50% water requirement as sub plot. First, AquaCrop model was run with the corresponding data of S1 treatments (for all I1, I2, I3, and I4 and the results (wheat grain yield, average of soil water content

  19. Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition.

    Science.gov (United States)

    Lloyd, Simon J; Kovats, R Sari; Chalabi, Zaid

    2011-12-01

    Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health. We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050. We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change). We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia). Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.

  20. Comparative analyses of B{yields}K{sub 2}{sup *}l{sup +}l{sup -} in the standard model and new physics scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Li, Run-Hui [Institute of High Energy Physics, Beijing (China); Yonsei Univ., Seoul (Korea, Republic of). Dept. of Physics and IPAP; Lue, Cai-Dian [Institute of High Energy Physics, Beijing (China); Wang, Wei [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2010-12-15

    We analyze the B {yields} K{sub 2}{sup *}({yields} K{pi})l{sup +}l{sup -} (with l=e,{mu},{tau}) decay in the standard model and two new physics scenarios: vector-like quark model and family non-universal Z{sup '} model. We derive the differential angular distributions of the quasi-four-body decay, using the recently calculated form factors in the perturbative QCD approach. Branching ratios, polarizations, forward-backward asymmetries and transversity amplitudes are predicted, from which we find a promising prospective to observe this channel on the future experiment. We also update the constraints on effective Wilson coefficients and/or free parameters in these two new physics scenarios by making use of the experimental data of B{yields}K{sup *}l{sup +}l{sup -} and b{yields}sl{sup +}l{sup -}. Their impact on B{yields}K{sub 2}{sup *}l{sup +}l{sup -} is subsequently explored and in particular the zero-crossing point for the forward-backward asymmetry in these new physics scenarios can sizably deviate from the SM scenario. In addition we also generalize the analysis to a similar mode B{sub s}{yields}f{sup '}{sub 2}(1525)({yields}K{sup +}K{sup -})l{sup +}l{sup -}. (orig.)

  1. Modeling the Impacts of Historic Climate Change and Extreme Droughts on Water Yield and Productivity of National Forests over the Conterminous U.S

    Science.gov (United States)

    Sun, S.; Sun, G.; Caldwell, P. V.; McNulty, S. G.; Zhang, Y.

    2014-12-01

    Quantifying the impacts of droughts on the U.S National Forests (NFs) is necessary to develop sound forest management plans to mitigate and adapt to climate change. This study applied a water balance model (WaSSI) to 170 National Forests (NFs) over the conterminous U.S to examine how long-term climatic change and extreme climate events impacted forest water yield and productivity. Our model predicted that mean water yield decreased by 5% while mean productivity increased by 10% between 1961-2012 across the NFs. Overall 32% of NFs showed a significant increasing trend in forest gross ecosystem productivity (GEP), while 5% of the NFs had a significant decreasing trend. This study also suggested that the extent and severity of drought events occurring in the NFs had an increasing trend during the past 50 years. Taking the 170 NFs as a whole, the top-five droughts were characterized by a 261 mm/yr (or 30%) reduction in precipitation, that resulted in reductions in evapotranspiration by 55 mm/yr (or 10%), water yield by 154 mm/yr (or 49%) and GEP by 121 gC/m2/yr (or 10%). However, distribution of these changes varied spatially due to differences in vegetation types, weather, and geography. Overall, this study provided an assessment of historical impacts of droughts on forest watershed hydrology and productivity across diverse geographic regions using a consistent database. The study also identified forest watersheds that were severely influenced by historical drought, and provided a reference to develop appropriate adaptation strategies for potential future extreme droughts on the forest ecosystem services of NFs.

  2. Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

    Science.gov (United States)

    Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

    2017-12-01

    Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

  3. Convergence models for cylindrical caverns and the resulting ground subsidence

    Energy Technology Data Exchange (ETDEWEB)

    Haupt, W.; Sroka, A.; Schober, F.

    1983-02-01

    The authors studied the effects of different convergence characteristics on surface soil response for the case of narrow, cylindrical caverns. Maximum ground subsidence - a parameter of major importance in this type of cavern - was calculated for different convergence models. The models were established without considering the laws of rock mechanics and rheology. As a result, two limiting convergence models were obtained that describe an interval of expectation into which all other models fit. This means that ground movements over cylindrical caverns can be calculated ''on the safe side'', correlating the trough resulting on the surface with the convergence characterisitcs of the cavern. Among other applications, the method thus permits monitoring of caverns.

  4. Meteorological Uncertainty of atmospheric Dispersion model results (MUD)

    DEFF Research Database (Denmark)

    Havskov Sørensen, Jens; Amstrup, Bjarne; Feddersen, Henrik

    . However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties......The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario...... of the meteorological model results. These uncertainties stem from e.g. limits in meteorological obser-vations used to initialise meteorological forecast series. By perturbing the initial state of an NWP model run in agreement with the available observa-tional data, an ensemble of meteorological forecasts is produced...

  5. Meteorological Uncertainty of atmospheric Dispersion model results (MUD)

    DEFF Research Database (Denmark)

    Havskov Sørensen, Jens; Amstrup, Bjarne; Feddersen, Henrik

    ’ dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent......The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the ‘most likely...... uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble...

  6. The 2013 European Seismic Hazard Model: key components and results

    OpenAIRE

    Jochen Woessner; Danciu Laurentiu; Domenico Giardini; Helen Crowley; Fabrice Cotton; G. Grünthal; Gianluca Valensise; Ronald Arvidsson; Roberto Basili; Mine Betül Demircioglu; Stefan Hiemer; Carlo Meletti; Roger W. Musson; Andrea N. Rovida; Karin Sesetyan

    2015-01-01

    The 2013 European Seismic Hazard Model (ESHM13) results from a community-based probabilistic seismic hazard assessment supported by the EU-FP7 project “Seismic Hazard Harmonization in Europe” (SHARE, 2009–2013). The ESHM13 is a consistent seismic hazard model for Europe and Turkey which overcomes the limitation of national borders and includes a through quantification of the uncertainties. It is the first completed regional effort contributing to the “Global Earthquake Model” initiative. It m...

  7. Random regression test day models to estimate genetic parameters for milk yield and milk components in Philippine dairy buffaloes.

    Science.gov (United States)

    Flores, E B; van der Werf, J

    2015-08-01

    Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Leg(m)) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits. © 2015 Blackwell Verlag GmbH.

  8. Hydroclimatology of the Nile: results from a regional climate model

    Directory of Open Access Journals (Sweden)

    Y. A. Mohamed

    2005-01-01

    Full Text Available This paper presents the result of the regional coupled climatic and hydrologic model of the Nile Basin. For the first time the interaction between the climatic processes and the hydrological processes on the land surface have been fully coupled. The hydrological model is driven by the rainfall and the energy available for evaporation generated in the climate model, and the runoff generated in the catchment is again routed over the wetlands of the Nile to supply moisture for atmospheric feedback. The results obtained are quite satisfactory given the extremely low runoff coefficients in the catchment. The paper presents the validation results over the sub-basins: Blue Nile, White Nile, Atbara river, the Sudd swamps, and the Main Nile for the period 1995 to 2000. Observational datasets were used to evaluate the model results including radiation, precipitation, runoff and evaporation data. The evaporation data were derived from satellite images over a major part of the Upper Nile. Limitations in both the observational data and the model are discussed. It is concluded that the model provides a sound representation of the regional water cycle over the Nile. The sources of atmospheric moisture to the basin, and location of convergence/divergence fields could be accurately illustrated. The model is used to describe the regional water cycle in the Nile basin in terms of atmospheric fluxes, land surface fluxes and land surface-climate feedbacks. The monthly moisture recycling ratio (i.e. locally generated/total precipitation over the Nile varies between 8 and 14%, with an annual mean of 11%, which implies that 89% of the Nile water resources originates from outside the basin physical boundaries. The monthly precipitation efficiency varies between 12 and 53%, and the annual mean is 28%. The mean annual result of the Nile regional water cycle is compared to that of the Amazon and the Mississippi basins.

  9. Results of a model for premixed combustion oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Janus, M.C.; Richards, G.A.

    1996-09-01

    Combustion oscillations are receiving renewed research interest due to increasing use of lean premix (LPM) combustion to gas turbines. A simple, nonlinear model for premixed combustion is described in this paper. The model was developed to help explain specific experimental observations and to provide guidance for development of active control schemes based on nonlinear concepts. The model can be used to quickly examine instability trends associated with changes in equivalence ratio, mass flow rate, geometry, ambient conditions, etc. The model represents the relevant processes occurring in a fuel nozzle and combustor which are analogous to current LPM turbine combustors. Conservation equations for the fuel nozzle and combustor are developed from simple control volume analysis, providing a set of ordinary differential equations that can be solved on a personal computer. Combustion is modeled as a stirred reactor, with a bimolecular reaction rate between fuel and air. A variety of numerical results and comparisons to experimental data are presented to demonstrate the utility of the model. Model results are used to understand the fundamental mechanisms which drive combustion oscillations, effects of inlet air temperature and nozzle geometry on instability, and effectiveness of open loop control schemes.

  10. Modeling the yield of double-strand breaks due to formation of multiply damaged sites in irradiated plasmid DNA

    International Nuclear Information System (INIS)

    Xapsos, M.A.; Pogozelski, W.K.

    1996-01-01

    Although double-strand breaks have long been recognized as an important type of DNa lesion, it is well established that this broad class of damage does not correlate well with indicators of the effectiveness of radiation as the cellular level. Assays of double-strand breaks do not distinguish the degree of complexity or clustering of singly damaged sites produced in a single energy deposition event, which is currently hypothesized to be key to understanding cellular end points. As a step toward this understanding, double-strand breaks that are formed proportionally to dose in plasmid DNA are analyzed from the mechanistic aspect to evaluate the yield that arises from multiply damaged sites as hypothesized by Ward (Prog. Nucleic Acid Res. Mol. Biol. 35, 95-125, 1988) and Goodhead (Int. J. Radiat. Biol. 65, 7-17, 1994) as opposed to the yield that arises form single hydroxyl radicals as hypothesized by Siddiqi and Bothe (Radiat. Res. 112, 449-463, 1987). For low-LET radiation such as γ rays, the importance of multiply damaged sites is shown to increase with the solution's hydroxyl radical scavenging capacity. For moderately high-LET radiation such as 100 keV/μm helium ions, a much different behavior is observed. In this case, a large fraction of double-strand breaks are formed as a result of multiply damaged sties over a broad range of scavenging conditions. Results also indicate that the RBE for common cellular end points correlates more closely with the RBE for common cellular end points correlates more closely with the RBE for multiply damaged sites than with the RBE for total double-strand breaks over a range of LET up to at least 100 keV/μm. 22 refs., 3 figs., 2 tabs

  11. Summary of FY15 results of benchmark modeling activities

    Energy Technology Data Exchange (ETDEWEB)

    Arguello, J. Guadalupe [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2015-08-01

    Sandia is participating in the third phase of an is a contributing partner to a U.S.-German "Joint Project" entitled "Comparison of current constitutive models and simulation procedures on the basis of model calculations of the thermo-mechanical behavior and healing of rock salt." The first goal of the project is to check the ability of numerical modeling tools to correctly describe the relevant deformation phenomena in rock salt under various influences. Achieving this goal will lead to increased confidence in the results of numerical simulations related to the secure storage of radioactive wastes in rock salt, thereby enhancing the acceptance of the results. These results may ultimately be used to make various assertions regarding both the stability analysis of an underground repository in salt, during the operating phase, and the long-term integrity of the geological barrier against the release of harmful substances into the biosphere, in the post-operating phase.

  12. Quantifying potential yield and water-limited yield of summer maize in the North China Plain

    Science.gov (United States)

    Jiang, Mingnuo; Liu, Chaoshun; Chen, Maosi

    2017-09-01

    The North China Plain is a major food producing region in China, and climate change could pose a threat to food production in the region. Based on China Meteorological Forcing Dataset, simulating the growth of summer maize in North China Plain from 1979 to 2015 with the regional implementation of crop growth model WOFOST. The results showed that the model can reflect the potential yield and water-limited yield of Summer Maize in North China Plain through the calibration and validation of WOFOST model. After the regional implementation of model, combined with the reanalysis data, the model can better reproduce the regional history of summer maize yield in the North China Plain. The yield gap in Southeastern Beijing, southern Tianjin, southern Hebei province, Northwestern Shandong province is significant, these means the water condition is the main factor to summer maize yield in these regions.

  13. Genetic analysis of coagulation properties, curd firming modeling, milk yield, composition, and acidity in Sarda dairy sheep.

    Science.gov (United States)

    Bittante, G; Cipolat-Gotet, C; Pazzola, M; Dettori, M L; Vacca, G M; Cecchinato, A

    2017-01-01

    Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CF t ) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k 20 , min), and 3measures of curd firmness (a 30 , a 45 , and a 60 , mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCT eq ), the asymptotic potential curd firmness (CF P ), the curd firming instant rate constant (k CF ), and the syneresis instant rate constant (k SR ). Two other derived traits were also calculated (CF max , the maximum curd firmness value; and t max , the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CF t with the other traits; statistical inference was based on the marginal posterior distributions of the parameters of concern. The marginal posterior distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an

  14. Genetic analysis of yield in peanut ( Arachis hypogaea L.) using ...

    African Journals Online (AJOL)

    The yield had significant major gene effect and the results implied that not only should the two major genes' effects be considered but also the polygene's effect should be considered in breeding to increase peanut yield. Key words: Peanut, yield, major gene plus polygene inheritance model, genetic analysis.

  15. Relationship Marketing results: proposition of a cognitive mapping model

    Directory of Open Access Journals (Sweden)

    Iná Futino Barreto

    2015-12-01

    Full Text Available Objective - This research sought to develop a cognitive model that expresses how marketing professionals understand the relationship between the constructs that define relationship marketing (RM. It also tried to understand, using the obtained model, how objectives in this field are achieved. Design/methodology/approach – Through cognitive mapping, we traced 35 individual mental maps, highlighting how each respondent understands the interactions between RM elements. Based on the views of these individuals, we established an aggregate mental map. Theoretical foundation – The topic is based on a literature review that explores the RM concept and its main elements. Based on this review, we listed eleven main constructs. Findings – We established an aggregate mental map that represents the RM structural model. Model analysis identified that CLV is understood as the final result of RM. We also observed that the impact of most of the RM elements on CLV is brokered by loyalty. Personalization and quality, on the other hand, proved to be process input elements, and are the ones that most strongly impact others. Finally, we highlight that elements that punish customers are much less effective than elements that benefit them. Contributions - The model was able to insert core elements of RM, but absent from most formal models: CLV and customization. The analysis allowed us to understand the interactions between the RM elements and how the end result of RM (CLV is formed. This understanding improves knowledge on the subject and helps guide, assess and correct actions.

  16. Optimizing rice yields while minimizing yield-scaled global warming potential.

    Science.gov (United States)

    Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

    2014-05-01

    To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

  17. Marginal production in the Gulf of Mexico - II. Model results

    International Nuclear Information System (INIS)

    Kaiser, Mark J.; Yu, Yunke

    2010-01-01

    In the second part of this two-part article on marginal production in the Gulf of Mexico, we estimate the number of committed assets in water depth less than 1000 ft that are expected to be marginal over a 60-year time horizon. We compute the expected quantity and value of the production and gross revenue streams of the gulf's committed asset inventory circa. January 2007 using a probabilistic model framework. Cumulative hydrocarbon production from the producing inventory is estimated to be 1056 MMbbl oil and 13.3 Tcf gas. Marginal production from the committed asset inventory is expected to contribute 4.1% of total oil production and 5.4% of gas production. A meta-evaluation procedure is adapted to present the results of sensitivity analysis. Model results are discussed along with a description of the model framework and limitations of the analysis. (author)

  18. Marginal production in the Gulf of Mexico - II. Model results

    Energy Technology Data Exchange (ETDEWEB)

    Kaiser, Mark J.; Yu, Yunke [Center for Energy Studies, Louisiana State University, Baton Rouge, LA 70803 (United States)

    2010-08-15

    In the second part of this two-part article on marginal production in the Gulf of Mexico, we estimate the number of committed assets in water depth less than 1000 ft that are expected to be marginal over a 60-year time horizon. We compute the expected quantity and value of the production and gross revenue streams of the gulf's committed asset inventory circa. January 2007 using a probabilistic model framework. Cumulative hydrocarbon production from the producing inventory is estimated to be 1056 MMbbl oil and 13.3 Tcf gas. Marginal production from the committed asset inventory is expected to contribute 4.1% of total oil production and 5.4% of gas production. A meta-evaluation procedure is adapted to present the results of sensitivity analysis. Model results are discussed along with a description of the model framework and limitations of the analysis. (author)

  19. Accelerating the domestication of a bioenergy crop: identifying and modelling morphological targets for sustainable yield increase in Miscanthus.

    Science.gov (United States)

    Robson, Paul; Jensen, Elaine; Hawkins, Sarah; White, Simon R; Kenobi, Kim; Clifton-Brown, John; Donnison, Iain; Farrar, Kerrie

    2013-11-01

    To accelerate domestication of Miscanthus, an important energy crop, 244 replicated genotypes, including two different species and their hybrids, were analysed for morphological traits and biomass yield over three growing seasons following an establishment phase of 2 years in the largest Miscanthus diversity trial described to date. Stem and leaf traits were selected that contributed both directly and indirectly to total harvested biomass yield, and there was variation in all traits measured. Morphological diversity within the population was correlated with dry matter yield (DMY) both as individual traits and in combination, in order to determine the respective contributions of the traits to biomass accumulation and to identify breeding targets for yield improvement. Predictive morphometric analysis was possible at year 3 within Miscanthus sinensis genotypes but not between M. sinensis, Miscanthus sacchariflorus, and interspecific hybrids. Yield is a complex trait, and no single simple trait explained more than 33% of DMY, which varied from 1 to 5297 g among genotypes within this trial. Associating simple traits increased the power of the morphological data to predict yield to 60%. Trait variety, in combination, enabled multiple ideotypes, thereby increasing the potential diversity of the crop for multiple growth locations and end uses. Both triploids and interspecific hybrids produced the highest mature yields, indicating that there is significant heterosis to be exploited within Miscanthus that might be overlooked in early selection screens within years 1-3. The potential for optimizing biomass yield by selecting on the basis of morphology is discussed.

  20. Benefits of seasonal forecasts of crop yields

    Science.gov (United States)

    Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

    2017-12-01

    Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

  1. Analysis of strengthening in AA6111 during the early stages of aging: Atom probe tomography and yield stress modelling

    International Nuclear Information System (INIS)

    Marceau, R.K.W.; Vaucorbeil, A. de; Sha, G.; Ringer, S.P.; Poole, W.J.

    2013-01-01

    In this work, a series of aging treatments has been conducted on AA6111 alloy samples for various times at ambient temperature (so-called natural aging) and at temperatures between 60 and 180 °C (artificially aged). The time at artificial ageing was chosen such that samples with approximately the same yield stress were produced. The microstructures of these alloy samples have been carefully characterized using atom probe tomography together with advanced cluster-finding techniques in order to obtain quantitative information about the changes in distribution of both the solute clusters and early-stage precipitates that are formed. The size distribution of clusters has been mapped onto the glide plane and then the stress necessary for a dislocation to pass through the range of obstacles has been estimated using an areal glide model where the dislocation–obstacle interaction strength has been assumed to be related to the obstacle size on the glide plane. It is demonstrated that the contribution of cluster strengthening during artificial aging at higher temperatures is dominated by the high number density of small clusters (Guinier radius <1 nm), whereas the situation during room temperature natural aging is more complex

  2. Visual Basic Growth-and-Yield Models With A Merchandising Optimizer For Planted Slash and Loblolly Pine in the West Gulf Region

    Science.gov (United States)

    R.L. Busby; S.J. Chang; P.R. Pasala; J.C.G. Goelz

    2004-01-01

    We developed two growth-and-yield models for thinned and unthinned plantations of slash pine (Pinus elliottii Engelm. var elliottii) and loblolly pine (P. taeda L.). The models, VB Merch-Slash and VB Merch-Lob, can be used to forecast product volumes and stand values for stands partitioned into 1-inch diameter-at...

  3. Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

    Science.gov (United States)

    Shanlei Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter V. Caldwell; Kai Duan; Yang Zhang

    2016-01-01

    Quantifying the potential impacts of climatechange on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, andecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and StressIndex, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled...

  4. Simulation of herbage yield and growth components of Cock’s foot (Dactylis glomerata L. in Jablje using the calibrated LINGRA-N model

    Directory of Open Access Journals (Sweden)

    Tjaša POGAČAR

    2015-11-01

    Full Text Available In the study the previously calibrated LINGRA-N model was used for a long term simulation (1964–2013 of the herbage  dry matter yield (GRASS and growth analysis of Cock’s foot (Dactylis glomerata L. in Jablje. Changes in the yearly  GRASS variability are reflected in the appearance of outliers in  the second half of the study period. The biggest reductions in GRASS are seen in the years 1992, 1993 and 2003. These are  the driest years according to meteorological variables (high  maximum and minimum air temp eratures, low precipitation  and also according to the simulations, with the lowest  reduction factor for crop growth due to drought. The potential  yield (YIELD is not linearly dependent on meteorological  variables. Some growth compone nts were compared on a daily  basis in a dry year (1993 and an average year (1994. In 1993, for instance, 53 % of photosynth etically active radiation was  intercepted, against 75 % in  1994. Seasonal development of  the actual soil moisture content was linked to the development  of the leaf area index and consequently to the mass of green  leaves, to the roots mass, to the mass of dead leaves and to  GRASS. The results highlight the need for further research, on  field and with simulations. As re gards the latter, we have to  keep in mind that they inevitably involve various  uncertainties.   

  5. Modeling Results For the ITER Cryogenic Fore Pump. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Pfotenhauer, John M. [University of Wisconsin, Madison, WI (United States); Zhang, Dongsheng [University of Wisconsin, Madison, WI (United States)

    2014-03-31

    A numerical model characterizing the operation of a cryogenic fore-pump (CFP) for ITER has been developed at the University of Wisconsin – Madison during the period from March 15, 2011 through June 30, 2014. The purpose of the ITER-CFP is to separate hydrogen isotopes from helium gas, both making up the exhaust components from the ITER reactor. The model explicitly determines the amount of hydrogen that is captured by the supercritical-helium-cooled pump as a function of the inlet temperature of the supercritical helium, its flow rate, and the inlet conditions of the hydrogen gas flow. Furthermore the model computes the location and amount of hydrogen captured in the pump as a function of time. Throughout the model’s development, and as a calibration check for its results, it has been extensively compared with the measurements of a CFP prototype tested at Oak Ridge National Lab. The results of the model demonstrate that the quantity of captured hydrogen is very sensitive to the inlet temperature of the helium coolant on the outside of the cryopump. Furthermore, the model can be utilized to refine those tests, and suggests methods that could be incorporated in the testing to enhance the usefulness of the measured data.

  6. Fuel assembly bow: analytical modeling and resulting design improvements

    International Nuclear Information System (INIS)

    Stabel, J.; Huebsch, H.P.

    1995-01-01

    The bowing of fuel assemblies may result in a contact between neighbouring fuel assemblies and in connection with a vibration to a resulting wear or even perforation at the corners of the spacer grids of neighbouring assemblies. Such events allowed reinsertion of a few fuel assemblies in Germany only after spacer repair. In order to identify the most sensitive parameters causing the observed bowing of fuel assemblies a new computer model was develop which takes into a account the highly nonlinear behaviour of the interaction between fuel rods and spacers. As a result of the studies performed with this model, design improvements such as a more rigid connection between guide thimbles and spacer grids, could be defined. First experiences with this improved design show significantly better fuel behaviour. (author). 5 figs., 1 tabs

  7. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield?

    Science.gov (United States)

    Murphy, Steven C; Martin, Nicole H; Barbano, David M; Wiedmann, Martin

    2016-12-01

    This article provides an overview of the influence of raw milk quality on the quality of processed dairy products and offers a perspective on the merits of investing in quality. Dairy farmers are frequently offered monetary premium incentives to provide high-quality milk to processors. These incentives are most often based on raw milk somatic cell and bacteria count levels well below the regulatory public health-based limits. Justification for these incentive payments can be based on improved processed product quality and manufacturing efficiencies that provide the processor with a return on their investment for high-quality raw milk. In some cases, this return on investment is difficult to measure. Raw milks with high levels of somatic cells and bacteria are associated with increased enzyme activity that can result in product defects. Use of raw milk with somatic cell counts >100,000cells/mL has been shown to reduce cheese yields, and higher levels, generally >400,000 cells/mL, have been associated with textural and flavor defects in cheese and other products. Although most research indicates that fairly high total bacteria counts (>1,000,000 cfu/mL) in raw milk are needed to cause defects in most processed dairy products, receiving high-quality milk from the farm allows some flexibility for handling raw milk, which can increase efficiencies and reduce the risk of raw milk reaching bacterial levels of concern. Monitoring total bacterial numbers in regard to raw milk quality is imperative, but determining levels of specific types of bacteria present has gained increasing importance. For example, spores of certain spore-forming bacteria present in raw milk at very low levels (e.g., products to levels that result in defects. With the exception of meeting product specifications often required for milk powders, testing for specific spore-forming groups is currently not used in quality incentive programs in the United States but is used in other countries (e.g., the

  8. The yield of a positive MRI of the spine as imaging criterion in the ASAS classification criteria for axial spondyloarthritis: results from the SPACE and DESIR cohorts

    NARCIS (Netherlands)

    Ez-Zaitouni, Zineb; Bakker, Pauline A. C.; van Lunteren, Miranda; de Hooge, Manouk; van den Berg, Rosaline; Reijnierse, Monique; Fagerli, Karen Minde; Landewé, Robert B. M.; Ramonda, Roberta; Jacobsson, Lennart T. H.; Saraux, Alain; Lenczner, Gregory; Feydy, Antoine; Pialat, Jean Baptiste; Thévenin, Fabrice; van Gaalen, Floris A.; van der Heijde, Désirée

    2017-01-01

    To assess the prevalence of spinal inflammation on MRI in patients with chronic back pain (CBP) of maximally 3 years duration and to evaluate the yield of adding a positive MRI-spine as imaging criterion to the Assessment of SpondyloArthritis international Society (ASAS) classification criteria for

  9. Methodology and Results of Mathematical Modelling of Complex Technological Processes

    Science.gov (United States)

    Mokrova, Nataliya V.

    2018-03-01

    The methodology of system analysis allows us to draw a mathematical model of the complex technological process. The mathematical description of the plasma-chemical process was proposed. The importance the quenching rate and initial temperature decrease time was confirmed for producing the maximum amount of the target product. The results of numerical integration of the system of differential equations can be used to describe reagent concentrations, plasma jet rate and temperature in order to achieve optimal mode of hardening. Such models are applicable both for solving control problems and predicting future states of sophisticated technological systems.

  10. Modeling vertical loads in pools resulting from fluid injection. [BWR

    Energy Technology Data Exchange (ETDEWEB)

    Lai, W.; McCauley, E.W.

    1978-06-15

    Table-top model experiments were performed to investigate pressure suppression pool dynamics effects due to a postulated loss-of-coolant accident (LOCA) for the Peachbottom Mark I boiling water reactor containment system. The results guided subsequent conduct of experiments in the /sup 1///sub 5/-scale facility and provided new insight into the vertical load function (VLF). Model experiments show an oscillatory VLF with the download typically double-spiked followed by a more gradual sinusoidal upload. The load function contains a high frequency oscillation superimposed on a low frequency one; evidence from measurements indicates that the oscillations are initiated by fluid dynamics phenomena.

  11. Modeling vertical loads in pools resulting from fluid injection

    International Nuclear Information System (INIS)

    Lai, W.; McCauley, E.W.

    1978-01-01

    Table-top model experiments were performed to investigate pressure suppression pool dynamics effects due to a postulated loss-of-coolant accident (LOCA) for the Peachbottom Mark I boiling water reactor containment system. The results guided subsequent conduct of experiments in the 1 / 5 -scale facility and provided new insight into the vertical load function (VLF). Model experiments show an oscillatory VLF with the download typically double-spiked followed by a more gradual sinusoidal upload. The load function contains a high frequency oscillation superimposed on a low frequency one; evidence from measurements indicates that the oscillations are initiated by fluid dynamics phenomena

  12. Some results on the dynamics generated by the Bazykin model

    Directory of Open Access Journals (Sweden)

    Georgescu, R M

    2006-07-01

    Full Text Available A predator-prey model formerly proposed by A. Bazykin et al. [Bifurcation diagrams of planar dynamical systems (1985] is analyzed in the case when two of the four parameters are kept fixed. Dynamics and bifurcation results are deduced by using the methods developed by D. K. Arrowsmith and C. M. Place [Ordinary differential equations (1982], S.-N. Chow et al. [Normal forms and bifurcation of planar fields (1994], Y. A. Kuznetsov [Elements of applied bifurcation theory (1998], and A. Georgescu [Dynamic bifurcation diagrams for some models in economics and biology (2004]. The global dynamic bifurcation diagram is constructed and graphically represented. The biological interpretation is presented, too.

  13. Results of the eruptive column model inter-comparison study

    Science.gov (United States)

    Costa, Antonio; Suzuki, Yujiro; Cerminara, M.; Devenish, Ben J.; Esposti Ongaro, T.; Herzog, Michael; Van Eaton, Alexa; Denby, L.C.; Bursik, Marcus; de' Michieli Vitturi, Mattia; Engwell, S.; Neri, Augusto; Barsotti, Sara; Folch, Arnau; Macedonio, Giovanni; Girault, F.; Carazzo, G.; Tait, S.; Kaminski, E.; Mastin, Larry G.; Woodhouse, Mark J.; Phillips, Jeremy C.; Hogg, Andrew J.; Degruyter, Wim; Bonadonna, Costanza

    2016-01-01

    This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~ 20% for the weak plume and ~ 10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simplified treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.

  14. Updating Finite Element Model of a Wind Turbine Blade Section Using Experimental Modal Analysis Results

    Directory of Open Access Journals (Sweden)

    Marcin Luczak

    2014-01-01

    Full Text Available This paper presents selected results and aspects of the multidisciplinary and interdisciplinary research oriented for the experimental and numerical study of the structural dynamics of a bend-twist coupled full scale section of a wind turbine blade structure. The main goal of the conducted research is to validate finite element model of the modified wind turbine blade section mounted in the flexible support structure accordingly to the experimental results. Bend-twist coupling was implemented by adding angled unidirectional layers on the suction and pressure side of the blade. Dynamic test and simulations were performed on a section of a full scale wind turbine blade provided by Vestas Wind Systems A/S. The numerical results are compared to the experimental measurements and the discrepancies are assessed by natural frequency difference and modal assurance criterion. Based on sensitivity analysis, set of model parameters was selected for the model updating process. Design of experiment and response surface method was implemented to find values of model parameters yielding results closest to the experimental. The updated finite element model is producing results more consistent with the measurement outcomes.

  15. Development of a benchmark parameter scan for Higgs bosons in the NMSSM Model and a study of the sensitivity for H{yields}AA{yields}4{tau} in vector boson fusion with the ATLAS detector

    Energy Technology Data Exchange (ETDEWEB)

    Rottlaender, Iris

    2008-08-15

    An evaluation of the discovery potential for NMSSM Higgs bosons of the ATLAS experiment at the LHC is presented. For this purpose, seven two-dimensional benchmark planes in the six-dimensional parameter space of the NMSSM Higgs sector are defined. These planes include different types of phenomenology for which the discovery of NMSSM Higgs bosons is especially challenging and which are considered typical for the NMSSM. They are subsequently used to give a detailed evaluation of the Higgs boson discovery potential based on Monte Carlo studies from the ATLAS collaboration. Afterwards, the possibility of discovering NMSSM Higgs bosons via the H{sub 1}{yields}A{sub 1}A{sub 1}{yields}4{tau}{yields}4{mu}+8{nu} decay chain and with the vector boson fusion production mode is investigated. A particular emphasis is put on the mass reconstruction from the complex final state. Furthermore, a study of the jet reconstruction performance at the ATLAS experiment which is of crucial relevance for vector boson fusion searches is presented. A good detectability of the so-called tagging jets that originate from the scattered partons in the vector boson fusion process is of critical importance for an early Higgs boson discovery in many models and also within the framework of the NMSSM. (orig.)

  16. Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

    Science.gov (United States)

    Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

    2016-03-01

    Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

  17. Using Ridge Regression Models to Estimate Grain Yield from Field Spectral Data in Bread Wheat (Triticum Aestivum L. Grown under Three Water Regimes

    Directory of Open Access Journals (Sweden)

    Javier Hernandez

    2015-02-01

    Full Text Available Plant breeding based on grain yield (GY is an expensive and time-consuming method, so new indirect estimation techniques to evaluate the performance of crops represent an alternative method to improve grain yield. The present study evaluated the ability of canopy reflectance spectroscopy at the range from 350 to 2500 nm to predict GY in a large panel (368 genotypes of wheat (Triticum aestivum L. through multivariate ridge regression models. Plants were treated under three water regimes in the Mediterranean conditions of central Chile: severe water stress (SWS, rain fed, mild water stress (MWS; one irrigation event around booting and full irrigation (FI with mean GYs of 1655, 4739, and 7967 kg∙ha−1, respectively. Models developed from reflectance data during anthesis and grain filling under all water regimes explained between 77% and 91% of the GY variability, with the highest values in SWS condition. When individual models were used to predict yield in the rest of the trials assessed, models fitted during anthesis under MWS performed best. Combined models using data from different water regimes and each phenological stage were used to predict grain yield, and the coefficients of determination (R2 increased to 89.9% and 92.0% for anthesis and grain filling, respectively. The model generated during anthesis in MWS was the best at predicting yields when it was applied to other conditions. Comparisons against conventional reflectance indices were made, showing lower predictive abilities. It was concluded that a Ridge Regression Model using a data set based on spectral reflectance at anthesis or grain filling represents an effective method to predict grain yield in genotypes under different water regimes.

  18. Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process.

    Science.gov (United States)

    Cipolat-Gotet, C; Cecchinato, A; De Marchi, M; Bittante, G

    2013-01-01

    procedure was used to process individual milk samples obtained from 1,167 Brown Swiss cows reared in 85 herds of the province of Trento (Italy). The assessed traits exhibited almost normal distributions, with the exception of REC(FAT). The average values (± SD) were as follows: %CY(CURD)=14.97±1.86, %CY(SOLIDS)=7.18±0.92, %CY(WATER)=7.77±1.27, dCY(CURD)=3.63±1.17, dCY(SOLIDS)=1.74±0.57, dCY(WATER)=1.88±0.63, REC(FAT)=89.79±3.55, REC(PROTEIN)=78.08±2.43, REC(SOLIDS)=51.88±3.52, and REC(ENERGY)=67.19±3.29. All traits were highly influenced by herd-test-date and days in milk of the cow, moderately influenced by parity, and weakly influenced by the utilized vat. Both %CY(CURD) and dCY(CURD) depended not only on the fat and protein (casein) contents of the milk, but also on their proportions retained in the curd; the water trapped in curd presented an higher variability than that of %CY(SOLIDS). All REC traits were variable and affected by days in milk and parity of the cows. The described model cheese-making procedure and the results obtained provided new insight into the phenotypic variation of cheese yield and recovery traits at the individual level. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  19. Initial CGE Model Results Summary Exogenous and Endogenous Variables Tests

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, Brian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Boero, Riccardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rivera, Michael Kelly [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-08-07

    The following discussion presents initial results of tests of the most recent version of the National Infrastructure Simulation and Analysis Center Dynamic Computable General Equilibrium (CGE) model developed by Los Alamos National Laboratory (LANL). The intent of this is to test and assess the model’s behavioral properties. The test evaluated whether the predicted impacts are reasonable from a qualitative perspective. This issue is whether the predicted change, be it an increase or decrease in other model variables, is consistent with prior economic intuition and expectations about the predicted change. One of the purposes of this effort is to determine whether model changes are needed in order to improve its behavior qualitatively and quantitatively.

  20. Interaction between subducting plates: results from numerical and analogue modeling

    Science.gov (United States)

    Kiraly, Agnes; Capitanio, Fabio A.; Funiciello, Francesca; Faccenna, Claudio

    2016-04-01

    The tectonic setting of the Alpine-Mediterranean area is achieved during the late Cenozoic subduction, collision and suturing of several oceanic fragments and continental blocks. In this stage, processes such as interactions among subducting slabs, slab migrations and related mantle flow played a relevant role on the resulting tectonics. Here, we use numerical models to first address the mantle flow characteristic in 3D. During the subduction of a single plate the strength of the return flow strongly depends on the slab pull force, that is on the plate's buoyancy, however the physical properties of the slab, such as density, viscosity or width, do not affect largely the morphology of the toroidal cell. Instead, dramatic effects on the geometry and the dynamics of the toroidal cell result in models where the thickness of the mantle is varied. The vertical component of the vorticity vector is used to define the characteristic size of the toroidal cell, which is ~1.2-1.3 times the mantle depth. This latter defines the range of viscous stress propagation through the mantle and consequent interactions with other slabs. We thus further investigate on this setup where two separate lithospheric plates subduct in opposite sense, developing opposite polarities and convergent slab retreat, and model different initial sideways distance between the plates. The stress profiles in time illustrate that the plates interacts when slabs are at the characteristic distance and the two slabs toroidal cells merge. Increased stress and delayed slab migrations are the results. Analogue models of double-sided subduction show similar maximum distance and allow testing the additional role of stress propagated through the plates. We use a silicon plate subducting on its two opposite margins, which is either homogeneous or comprises oceanic and continental lithospheres, differing in buoyancy. The modeling results show that the double-sided subduction is strongly affected by changes in plate

  1. First experiments results about the engineering model of Rapsodie

    International Nuclear Information System (INIS)

    Chalot, A.; Ginier, R.; Sauvage, M.

    1964-01-01

    This report deals with the first series of experiments carried out on the engineering model of Rapsodie and on an associated sodium facility set in a laboratory hall of Cadarache. It conveys more precisely: 1/ - The difficulties encountered during the erection and assembly of the engineering model and a compilation of the results of the first series of experiments and tests carried out on this installation (loading of the subassemblies preheating, thermal chocks...). 2/ - The experiments and tests carried out on the two prototypes control rod drive mechanisms which brought to the choice for the design of the definitive drive mechanism. As a whole, the results proved the validity of the general design principles adopted for Rapsodie. (authors) [fr

  2. Workshop to transfer VELMA watershed model results to ...

    Science.gov (United States)

    An EPA Western Ecology Division (WED) watershed modeling team has been working with the Snoqualmie Tribe Environmental and Natural Resources Department to develop VELMA watershed model simulations of the effects of historical and future restoration and land use practices on streamflow, stream temperature, and other habitat characteristics affecting threatened salmon populations in the 100 square mile Tolt River watershed in Washington state. To date, the WED group has fully calibrated the watershed model to simulate Tolt River flows with a high degree of accuracy under current and historical conditions and practices, and is in the process of simulating long-term responses to specific watershed restoration practices conducted by the Snoqualmie Tribe and partners. On July 20-21 WED Researchers Bob McKane, Allen Brookes and ORISE Fellow Jonathan Halama will be attending a workshop at the Tolt River site in Carnation, WA, to present and discuss modeling results with the Snoqualmie Tribe and other Tolt River watershed stakeholders and land managers, including the Washington Departments of Ecology and Natural Resources, U.S. Forest Service, City of Seattle, King County, and representatives of the Northwest Indian Fisheries Commission. The workshop is being co-organized by the Snoqualmie Tribe, EPA Region 10 and WED. The purpose of this 2-day workshop is two-fold. First, on Day 1, the modeling team will perform its second site visit to the watershed, this time focus

  3. Meteorological uncertainty of atmospheric dispersion model results (MUD)

    International Nuclear Information System (INIS)

    Havskov Soerensen, J.; Amstrup, B.; Feddersen, H.

    2013-08-01

    The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble of meteorological forecasts is produced from which uncertainties in the various meteorological parameters are estimated, e.g. probabilities for rain. Corresponding ensembles of atmospheric dispersion can now be computed from which uncertainties of predicted radionuclide concentration and deposition patterns can be derived. (Author)

  4. Some results on hyperscaling in the 3D Ising model

    Energy Technology Data Exchange (ETDEWEB)

    Baker, G.A. Jr. [Los Alamos National Lab., NM (United States). Theoretical Div.; Kawashima, Naoki [Univ. of Tokyo (Japan). Dept. of Physics

    1995-09-01

    The authors review exact studies on finite-sized 2 dimensional Ising models and show that the point for an infinite-sized model at the critical temperature is a point of nonuniform approach in the temperature-size plane. They also illuminate some strong effects of finite-size on quantities which do not diverge at the critical point. They then review Monte Carlo studies for 3 dimensional Ising models of various sizes (L = 2--100) at various temperatures. From these results they find that the data for the renormalized coupling constant collapses nicely when plotted against the correlation length, determined in a system of edge length L, divided by L. They also find that {zeta}{sub L}/L {ge} 0.26 is definitely too large for reliable studies of the critical value, g*, of the renormalized coupling constant. They have reasonable evidence that {zeta}{sub L}/L {approx} 0.1 is adequate for results that are within one percent of those for the infinite system size. On this basis, they have conducted a series of Monte Carlo calculations with this condition imposed. These calculations were made practical by the development of improved estimators for use in the Swendsen-Wang cluster method. The authors found from these results, coupled with a reversed limit computation (size increases with the temperature fixed at the critical temperature), that g* > 0, although there may well be a sharp downward drop in g as the critical temperature is approached in accord with the predictions of series analysis. The results support the validity of hyperscaling in the 3 dimensional Ising model.

  5. Presenting results of software model checker via debugging interface

    OpenAIRE

    Kohan, Tomáš

    2012-01-01

    Title: Presenting results of software model checker via debugging interface Author: Tomáš Kohan Department: Department of Software Engineering Supervisor of the master thesis: RNDr. Ondřej Šerý, Ph.D., Department of Distributed and Dependable Systems Abstract: This thesis is devoted to design and implementation of the new debugging interface of the Java PathFinder application. As a suitable inte- face container was selected the Eclipse development environment. The created interface should vis...

  6. A hierarchy of models for simulating experimental results from a 3D heterogeneous porous medium

    Science.gov (United States)

    Vogler, Daniel; Ostvar, Sassan; Paustian, Rebecca; Wood, Brian D.

    2018-04-01

    In this work we examine the dispersion of conservative tracers (bromide and fluorescein) in an experimentally-constructed three-dimensional dual-porosity porous medium. The medium is highly heterogeneous (σY2 = 5.7), and consists of spherical, low-hydraulic-conductivity inclusions embedded in a high-hydraulic-conductivity matrix. The bimodal medium was saturated with tracers, and then flushed with tracer-free fluid while the effluent breakthrough curves were measured. The focus for this work is to examine a hierarchy of four models (in the absence of adjustable parameters) with decreasing complexity to assess their ability to accurately represent the measured bre