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

Yield surface investigation of alloys during model disk spin tests

Directory of Open Access Journals (Sweden)

E. P. Kuzmin

2014-01-01

Full Text Available Gas-turbine engines operate under heavy subsequently static loading conditions. Disks of gas-turbine engine are high loaded parts of irregular shape having intensive stress concentrators wherein a 3D stress strain state occurs. The loss of load-carrying capability or burst of disk can lead to severe accident or disaster. Therefore, development of methods to assess deformations and to predict burst is one of the most important problems.Strength assessment approaches are used at all levels of engine creation. In recent years due to actively developing numerical method, particularly FEA, it became possible to investigate load-carrying capability of irregular shape disks, to use 3D computing schemes including flow theory and different options of force and deformation failure criteria. In spite of a wide progress and practical use of strength assessment approaches, there is a lack of detailed research data on yield surface of disk alloys. The main purpose of this work is to validate the use of basis hypothesis of flow theory and investigate the yield surface of disk alloys during the disks spin test.The results of quasi-static numerical simulation of spin tests of model disk made from high-temperature forged alloy are presented. To determine stress-strain state of disk during loading finite element analysis is used. Simulation of elastic-plastic strain fields was carried out using incremental theory of plasticity with isotropic hardening. Hardening function was taken from the results of specimens tensile test. Specimens were cut from a sinkhead of model disk. The paper investigates the model sensitivity affected by V.Mises and Tresca yield criteria as well as the Hosford model. To identify the material model parameters the eddy current sensors were used in the experimental approach to measure rim radial displacements during the load-unload of spin test. The results of calculation made using different material models were compared with the

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.

NEST: a comprehensive model for scintillation yield in liquid xenon

Energy Technology Data Exchange (ETDEWEB)

Szydagis, M; Barry, N; Mock, J; Stolp, D; Sweany, M; Tripathi, M; Uvarov, S; Walsh, N; Woods, M [University of California, Davis, One Shields Ave., Davis, CA 95616 (United States); Kazkaz, K, E-mail: mmszydagis@ucdavis.edu [Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550 (United States)

2011-10-15

A comprehensive model for explaining scintillation yield in liquid xenon is introduced. We unify various definitions of work function which abound in the literature and incorporate all available data on electron recoil scintillation yield. This results in a better understanding of electron recoil, and facilitates an improved description of nuclear recoil. An incident gamma energy range of O(1 keV) to O(1 MeV) and electric fields between 0 and O(10 kV/cm) are incorporated into this heuristic model. We show results from a Geant4 implementation, but because the model has a few free parameters, implementation in any simulation package should be simple. We use a quasi-empirical approach with an objective of improving detector calibrations and performance verification. The model will aid in the design and optimization of future detectors. This model is also easy to extend to other noble elements. In this paper we lay the foundation for an exhaustive simulation code which we call NEST (Noble Element Simulation Technique).

NEST: a comprehensive model for scintillation yield in liquid xenon

International Nuclear Information System (INIS)

Szydagis, M; Barry, N; Mock, J; Stolp, D; Sweany, M; Tripathi, M; Uvarov, S; Walsh, N; Woods, M; Kazkaz, K

2011-01-01

A comprehensive model for explaining scintillation yield in liquid xenon is introduced. We unify various definitions of work function which abound in the literature and incorporate all available data on electron recoil scintillation yield. This results in a better understanding of electron recoil, and facilitates an improved description of nuclear recoil. An incident gamma energy range of O(1 keV) to O(1 MeV) and electric fields between 0 and O(10 kV/cm) are incorporated into this heuristic model. We show results from a Geant4 implementation, but because the model has a few free parameters, implementation in any simulation package should be simple. We use a quasi-empirical approach with an objective of improving detector calibrations and performance verification. The model will aid in the design and optimization of future detectors. This model is also easy to extend to other noble elements. In this paper we lay the foundation for an exhaustive simulation code which we call NEST (Noble Element Simulation Technique).

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.

Evaluation of weather-based rice yield models in India

Science.gov (United States)

Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

2013-01-01

The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

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.

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.

26Al yields from rotating Wolf--Rayet star models

OpenAIRE

Vuissoz, C.; Meynet, G.; Knoedlseder, J.; Cervino, M.; Schaerer, D.; Palacios, A.; Mowlavi, N.

2003-01-01

We present new $^{26}$Al stellar yields from rotating Wolf--Rayet stellar models which, at solar metallicity, well reproduce the observed properties of the Wolf-Rayet populations. These new yields are enhanced with respect to non--rotating models, even with respect to non--rotating models computed with enhanced mass loss rates. We briefly discuss some implications of the use of these new yields for estimating the global contribution of Wolf-Rayet stars to the quantity of $^{26}$Al now present...

Prediction model of biocrude yield and nitrogen heterocyclic compounds analysis by hydrothermal liquefaction of microalgae with model compounds.

Science.gov (United States)

Sheng, Lili; Wang, Xin; Yang, Xiaoyi

2018-01-01

The model of biocrude yield and the nitrogen heterocyclic compounds in biocrude of microalgae hydrothermal liquefaction are two of the most concerned issues in this field at present. This study explored a hydrothermal liquefaction biocrude yield model involved in the interaction among biochemical compounds in microalgae and analysed nitrogen heterocyclic compounds in biocrude. The model compound (castor oil, soya protein and glucose) and Nanochloropsis were liquefied at 280°C for 1h. The products were analyzed by GC-MS, element analysis and FTIR. The results suggested that interactions among different components in microalgae enhanced biocrude yield. The biocrude yield prediction model involved cross-interactions performed more accurate than previous models.When the ratio of protein and carbohydrate around 3, the cross-interaction and nitrogen heterocyclic compounds in biocrude would both reach the highest extent. Copyright © 2017. Published by Elsevier Ltd.

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.

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

Science.gov (United States)

Cerda, Rolando; Avelino, Jacques; Gary, Christian; Tixier, Philippe; Lechevallier, Esther; Allinne, Clémentine

2017-01-01

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.

Predicting oil and gas compositional yields via chemical structure-chemical yield modeling (CS-CYM): Part 1 - Concepts and implementation

Energy Technology Data Exchange (ETDEWEB)

Freund, H.; Walters, C.C.; Kelemen, S.R.; Siskin, M.; Gorbaty, M.L.; Curry, D.J.; Bence, A.E. [ExxonMobil Research & Engineering Co., Annandale, NJ (United States)

2007-07-01

We have developed a method to calculate the amounts and composition of products resulting from the thermal decomposition of a solid complex carbonaceous material. This procedure provides a means of using laboratory measurements of complex carbonaceous solids to construct a representative model of its chemical structure (CS) that is then coupled with elementary reaction pathways to predict the chemical yield (CY) upon thermal decomposition. Data from elemental analysis, H, N, O, S, solid state {sup 13}C NMR, X-ray photoelectron spectroscopy (XPS), sulfur X-ray absorption structure spectroscopy (XANES), and pyrolysis-gas chromatography (GC) are used to constrain the construction of core molecular structures representative of the complex carbonaceous material. These core structures are expanded stochastically to describe large macromolecules ({gt} 10{sup 6} cores with similar to 10{sup 6} atoms) with bulk properties that match the experimental results. Gas, liquid and solid product yields, resulting from thermal decomposition, are calculated by identifying reactive functional groups within the CS stochastic ensemble and imposing a reaction network constrained by fundamental thermodynamics and kinetics. An expulsion model is added to the decomposition model to calculate the chemical products in open and closed systems. Product yields may then be predicted under a wide range of time-temperature conditions used in rapid laboratory pyrolysis experiments, refinery processes, or geologic maturation.

SiO2-Ta2O5 sputtering yields: simulated and experimental results

International Nuclear Information System (INIS)

Vireton, E.; Ganau, P.; Mackowski, J.M.; Michel, C.; Pinard, L.; Remillieux, A.

1994-09-01

To improve mirrors coating, we have modeled sputtering of binary oxide targets using TRIM code. First, we have proposed a method to calculate TRIM input parameters using on the one hand thermodynamic cycle and on the other hand Malherbe's results. Secondly, an iterative processing has provided for oxide steady targets caused by ionic bombardment. Thirdly, we have exposed a model to get experimental sputtering yields. Fourthly, for (Ar - SiO 2 ) pair, we have determined that steady target is a silica one. A good agreement between simulated and experimental yields versus ion incident angle has been found. For (Ar - Ta 2 O 5 ) pair, we have to introduce preferential sputtering concept to explain discrepancy between simulation and experiment. In this case, steady target is tantalum monoxide. For (Ar - Ta(+O 2 ) pair, tantalum sputtered by argon ions in reactive oxygen atmosphere, we have to take into account new concept of oxidation stimulated by ion beam. We have supposed that tantalum target becomes a Ta 2 O 5 one in reactive oxygen atmosphere. Then, following mechanism is similar to previous pair. We have obtained steady target of tantalum monoxide too. Comparison between simulated and experimental sputtering yields versus ion incident angle has given very good agreement. By simulation, we have found that tantalum monoxide target has at least 15 angstrom thickness. Those results are compatible with Malherbe's and Taglauer's ones. (authors)

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.

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)

MODELING POLLINATION FACTORS THAT INFLUENCE ALFALFA SEED YIELD IN NORTH-CENTRAL NEVADA

OpenAIRE

BREAZEALE, Don; FERNANDEZ, George; NARAYANAN, Rangesan

2008-01-01

The relative importance of both environmental and management factors on alfalfa seed yield was investigated on North–Central Nevada farms. Multiple linear regression models using 2002-2003 data revealed that cumulative tripped fl owers increased seed yield in both years. Field location does not appear to make a difference in the observed variation in tripped fl ower production. The results suggest that seed yield can be increased by (a) by placing bee shelters closer and (b) cultural practice...

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;

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.

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.

Forest Growth and Yield Models Viewed From a Different Perspective

Science.gov (United States)

Jeffery C. Goelz

2002-01-01

Typically, when different forms of growth and yield models are considered, they are grouped into convenient discrete classes. As a heuristic device, I chose to use a contrasting perspective, that all growth and yield models are diameter distribution models that merely differ in regard to which diameter distribution is employed and how the distribution is projected to...

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

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.

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.

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

How model and input uncertainty impact maize yield simulations in West Africa

Science.gov (United States)

Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

2015-02-01

Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

Science.gov (United States)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

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

A global water supply reservoir yield model with uncertainty analysis

International Nuclear Information System (INIS)

Kuria, Faith W; Vogel, Richard M

2014-01-01

Understanding the reliability and uncertainty associated with water supply yields derived from surface water reservoirs is central for planning purposes. Using a global dataset of monthly river discharge, we introduce a generalized model for estimating the mean and variance of water supply yield, Y, expected from a reservoir for a prespecified reliability, R, and storage capacity, S assuming a flow record of length n. The generalized storage–reliability–yield (SRY) relationships reported here have numerous water resource applications ranging from preliminary water supply investigations, to economic and climate change impact assessments. An example indicates how our generalized SRY relationship can be combined with a hydroclimatic model to determine the impact of climate change on surface reservoir water supply yields. We also document that the variability of estimates of water supply yield are invariant to characteristics of the reservoir system, including its storage capacity and reliability. Standardized metrics of the variability of water supply yields are shown to depend only on the sample size of the inflows and the statistical characteristics of the inflow series. (paper)

International codes and model intercomparison for intermediate energy activation yields

International Nuclear Information System (INIS)

Rolf, M.; Nagel, P.

1997-01-01

The motivation for this intercomparison came from data needs of accelerator-based waste transmutation, energy amplification and medical therapy. The aim of this exercise is to determine the degree of reliability of current nuclear reaction models and codes when calculating activation yields in the intermediate energy range up to 5000 MeV. Emphasis has been placed for a wide range of target elements ( O, Al, Fe, Co, Zr and Au). This work is mainly based on calculation of (P,xPyN) integral cross section for incident proton. A qualitative description of some of the nuclear models and code options employed is made. The systematics of graphical presentation of the results allows a quick quantitative measure of agreement or deviation. This code intercomparison highlights the fact that modeling calculations of energy activation yields may at best have uncertainties of a factor of two. The causes of such discrepancies are multi-factorial. Problems are encountered which are connected with the calculation of nuclear masses, binding energies, Q-values, shell effects, medium energy fission and Fermi break-up. (A.C.)

Modeling Growth and Yield of Schizolobium amazonicum under Different Spacings

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Gilson Fernandes da Silva

2013-01-01

Full Text Available This study aimed to present an approach to model the growth and yield of the species Schizolobium amazonicum (Paricá based on a study of different spacings located in Pará, Brazil. Whole-stand models were employed, and two modeling strategies (Strategies A and B were tested. Moreover, the following three scenarios were evaluated to assess the accuracy of the model in estimating total and commercial volumes at five years of age: complete absence of data (S1; available information about the variables basal area, site index, dominant height, and number of trees at two years of age (S2; and this information available at five years of age (S3. The results indicated that the 3 × 2 spacing has a higher mortality rate than normal, and, in general, greater spacing corresponds to larger diameter and average height and smaller basal area and volume per hectare. In estimating the total and commercial volumes for the three scenarios tested, Strategy B seems to be the most appropriate method to estimate the growth and yield of Paricá plantations in the study region, particularly because Strategy A showed a significant bias in its estimates.

The Impact of Statistical Leakage Models on Design Yield Estimation

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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.

Climate Change Modelling and Its Roles to Chinese Crops Yield

Institute of Scientific and Technical Information of China (English)

JU Hui; LIN Er-da; Tim Wheeler; Andrew Challinor; JIANG Shuai

2013-01-01

Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10%for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out.

Strip yielding model for calculation of COD in spheres with short cracks

International Nuclear Information System (INIS)

Miller, A.G.

1981-08-01

The crack opening displacement at the centre of a crack in a sphere with internal pressure has been calculated, using a strip yielding model. The results have been displayed for a range of geometrical parameters and loads. (author)

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...

Supporting Crop Loss Insurance Policy of Indonesia through Rice Yield Modelling and Forecasting

Science.gov (United States)

van Verseveld, Willem; Weerts, Albrecht; Trambauer, Patricia; de Vries, Sander; Conijn, Sjaak; van Valkengoed, Eric; Hoekman, Dirk; Grondard, Nicolas; Hengsdijk, Huib; Schrevel, Aart; Vlasbloem, Pieter; Klauser, Dominik

2017-04-01

The Government of Indonesia has decided on a crop insurance policy to assist Indonesia's farmers and to boost food security. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform implemented in the Delft-FEWS forecasting system (Werner et al., 2013). The integrated platform brings together remote sensed data (both visible and radar) and hydrologic, crop and reservoir modelling and forecasting to improve the modelling and forecasting of rice yield. The hydrological model (wflow_sbm), crop model (wflow_lintul) and reservoir models (RTC-Tools) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in the integrated platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the G4INDO project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010.

Integrated model for predicting rice yield with climate change

Science.gov (United States)

Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

2018-04-01

Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

Modelling of the process yields of a whey fermentation

Energy Technology Data Exchange (ETDEWEB)

Blakebrough, N; Moresi, M

1981-01-01

The biomass yields (y) and COD reduction efficiencies (eta) of a whey fermentation by Kluyveromyces fragilis were studied in a 100-l fermenter at various stirrer speeds and lactose concentrations, and compared to those obtained in 10-l and 15-l fermenters at constant values of the oxygen transfer coefficient (kla) and air velocity. The empirical models previously constructed by using the 15-l fermenter data could be used to predict the yields on the other scales by calculating for each run the 15-l fermenter which would provide the same oxygen transfer coefficient measured by the sulfite method on each fermenter under study. To make this model independent of stirrer speeds used in each generic fermenter, the effect of aeration and mixing was incorporated into an overall parameter (kla) and the values of y and eta were correlated only with temperature, lactose level and kla, since these variables were approximately orthogonal. The validity of this model was finally checked against the yields reported by Wasserman et al. (1961) in a 6-cubic metre fermenter, thus confirming the capability of the model to provide a reliable basis for further scale-up on the production scale. (Refs. 17).

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

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.

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.

Modeling Long Term Corn Yield Response to Nitrogen Rate and Crop Rotation

Directory of Open Access Journals (Sweden)

Laila Alejandra Puntel

2016-11-01

Full Text Available Improved prediction of optimal N fertilizer rates for corn (Zea mays L. can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM to simulate corn and soybean (Glycine max L. yields, the economic optimum N rate (EONR using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1 applied to corn. Our objectives were to: a quantify model prediction accuracy before and after calibration, and report calibration steps; b compare crop model-based techniques in estimating optimal N rate for corn; and c utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simultaneously simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration, which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration. For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-yr mean differences in EONR’s were within the historical N rate error range (40 to 50 kg N ha-1. However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching with precipitation. We concluded that long term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add

Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

Science.gov (United States)

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

2016-01-01

Improved prediction of optimal N fertilizer rates for corn ( Zea mays L. ) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean ( Glycine max L. ) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha -1 ) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha -1 ). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward

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.

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 �

COMPARISON OF THREE MODELS TO PREDICT ANNUAL SEDIMENT YIELD IN CARONI RIVER BASIN, VENEZUELA

Directory of Open Access Journals (Sweden)

Edilberto Guevara-Pérez

2007-01-01

Full Text Available Caroní River Basin is located in the south-eastern part of Venezuela; with an area of 92.000 km2, 40% of which belongs to the main affluent, the Paragua River. Caroní basin is the source of 66% of energy of the country. About 85% of the hydro electrical energy is generated in Guri reservoir located in the lower part of the watershed. To take provisions to avoid the reservoir silting it is very important the study of sediment yield of the basin. In this paper result of three empirical sediment yield models: Langbein- Schumm, Universal Soil Loss Equation-USLE and Poesen, are compared with observed data from five sub basins with records of twenty to thirty years. Men values of sediment yield for low, middle and upper Caroní are of 27, 76, 17 t/km2-year, respectively; and 46 and 78 t/km2-year for low and upper Paragua sub basins are. Standard errors of estimates vary between 13 and 29 for Langbein-Schumm model; between 8 and 32 for USLE procedure; and between 9 and 79, for Poesen model. Sediment yield predictions by Langbein-Schumm model seem to the best in Caroní basin.

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

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

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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.

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.

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)

Precise measurement of {gamma}(K{yields}e {nu}({gamma}))/{gamma}(K{yields}{mu} {nu}({gamma})) and study of K{yields}e {nu} {gamma}

Energy Technology Data Exchange (ETDEWEB)

Ambrosino, F.; Massarotti, P.; Meola, S.; Napolitano, M. [Dipartimento di Scienze Fisiche dell' Universita ' ' Federico II' ' , Napoli (Italy); INFN Sezione di Napoli, Napoli (Italy); Antonelli, A.; Antonelli, M.; Bencivenni, G.; Bloise, C.; Bossi, F.; Capon, G.; Capussela, T.; Ciambrone, P.; De Lucia, E.; De Simone, P.; Dreucci, M.; Felici, G.; Gatti, C.; Giovannella, S.; Jacewicz, M.; Lanfranchi, G.; Miscetti, S.; Moulson, M.; Murtas, F.; Palutan, M.; Santangelo, P.; Sciascia, B.; Sibidanov, A.; Spadaro, T.; Venanzoni, G. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); Archilli, F. [Dipartimento di Fisica dell' Universita ' ' Tor Vergata' ' , Rome (Italy); INFN Sezione di Roma Tor Vergata, Rome (Italy); Beltrame, P.; Denig, A.; Mueller, S. [Johannes Gutenberg-Universitaet, Institut fuer Kernphysik, Mainz (Germany); Bini, C.; De Santis, A.; De Zorzi, G.; Di Domenico, A.; Fiore, S.; Franzini, P.; Gauzzi, P. [Dipartimento di Fisica dell' Universita ' ' La Sapienza' ' , Rome (Italy); INFN Sezione di Roma, Rome (Italy); Bocchetta, S.; Ceradini, F.; Di Micco, B.; Nguyen, F. [Dipartimento di Fisica dell' Universita ' ' Roma Tre' ' , Rome (Italy); INFN Sezione di Roma Tre, Rome (Italy); Branchini, P.; Graziani, E.; Passeri, A.; Tortora, L. [INFN Sezione di Roma Tre, Rome (Italy); Capriotti, D. [Dipartimento di Fisica dell' Universita ' ' Roma Tre' ' , Rome (Italy); Di Donato, C. [INFN Sezione di Napoli, Napoli (Italy); Kulikov, V. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Lee-Franzini, J. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); State University of New York, Physics Department, Stony Brook (United States); Martini, M.; Patera, V.; Versaci, R. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); Dipartimento di Energetica dell' Universita ' ' La Sapienza' ' , Rome (Italy); Valente, P. [INFN Sezione di Roma, Rome (Italy)

2009-12-15

We present a precise measurement of the ratio R{sub K}={gamma}(K{yields}e{nu}({gamma}))/{gamma}(K{yields}{mu}{nu}({gamma})) and a study of the radiative process K{yields}e{nu}{gamma}, performed with the KLOE detector. The results are based on data collected at the Frascati e{sup +}e{sup -} collider DA {phi}NE for an integrated luminosity of 2.2 fb{sup -1}. We find R{sub K}=(2.493{+-}0.025{sub stat}{+-}0.019{sub syst}) x 10{sup -5}, in agreement with the Standard Model expectation. This result is used to improve constraints on parameters of the Minimal Supersymmetric Standard Model with lepton flavor violation. We also measured the differential decay rate d {gamma}(K{yields}e{nu}{gamma})/dE{sub {gamma}} for photon energies 10Results are compared with predictions from theory. (orig.)

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.

Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

Science.gov (United States)

Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.

2011-01-01

to assess the sensitivity of firm-yield estimates to errors in daily-streamflow input data. Results of the Monte Carlo simulations indicate that underestimation in the lowest stream inflows can cause firm yields to be underestimated by an average of 1 to 10 percent. Errors in the stage-storage relation can arise when the point density of bathymetric survey measurements is too low. Existing bathymetric surfaces were resampled using hypothetical transects of varying patterns and point densities in order to quantify the uncertainty in stage-storage relations. Reservoir-volume calculations and resulting firm yields were accurate to within 5 percent when point densities were greater than 20 points per acre of reservoir surface. Methods for incorporating summer water-demand-reduction scenarios into the firm-yield model were developed as well as the ability to relax the no-fail reliability criterion. Although the original firm-yield model allowed monthly reservoir releases to be specified, there have been no previous studies examining the feasibility of controlled releases for downstream flows from Massachusetts reservoirs. Two controlled-release scenarios were tested—with and without a summer water-demand-reduction scenario—for a scenario with a no-fail criterion and a scenario that allows for a 1-percent failure rate over the entire simulation period. Based on these scenarios, about one-third of the reservoir systems were able to support the flow-release scenarios at their 2000–2004 usage rates. Reservoirs with higher storage ratios (reservoir storage capacity to mean annual streamflow) and lower demand ratios (mean annual water demand to annual firm yield) were capable of higher downstream release rates. For the purposes of this research, all reservoir systems were assumed to have structures which enable controlled releases, although this assumption may not be true for many of the reservoirs studied.

Modelling and Forecasting of Rice Yield in support of Crop Insurance

Science.gov (United States)

Weerts, A.; van Verseveld, W.; Trambauer, P.; de Vries, S.; Conijn, S.; van Valkengoed, E.; Hoekman, D.; Hengsdijk, H.; Schrevel, A.

2016-12-01

The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia's farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010 .

Statistical modelling and deconvolution of yield meter data

DEFF Research Database (Denmark)

Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

2004-01-01

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...

Track models and radiation chemical yields

International Nuclear Information System (INIS)

Chatterjee, A.; Magee, J.L.

1987-01-01

The authors are concerned only with systems in which single track effects dominate and radiation chemical yields are sums of yields for individual tracks. The authors know that the energy deposits of heavy particle tracks are composed of spurs along the particle trajectory (about one-half of the energy) and a more diffuse pattern composed of the tracks of knock-on electrons, called the penumbra (about one-half of the energy). The simplest way to introduce the concept of a unified track model for heavy particles is to consider the special case of the track of a heavy particle with an LET below 0.2-0.3eV/A, which in practice limits us to protons, deuterons, or particles with energy above 100 MeV per nucleon. At these LET values, to a good approximation, spurs formed by the main particle track can be considered to remain isolated throughout the radiation chemical reactions

Yield models for Eucalyptus globulus fuelwood plantations in Ethiopia

Energy Technology Data Exchange (ETDEWEB)

Pukkala, T.; Pohjonen, V. (Joensuu Univ. (FI). Faculty of Forestry)

1990-01-01

Based on 53 tree analyses and 105 sample plots of Eucalyptus globulus, models for volume and biomass at single tree and stand levels were developed. The possible growing sites were divided into four site classes. In seedling stands, the site class I corresponds to yield class 44 m{sup 3} ha{sup -1} year{sup -1}, in coppice stands to yield class 46 m{sup 3} ha{sup -1} year{sup -1}. The site class IV corresponds in seedling stand to yield class 9 m{sup 3} ha{sup -1} year{sup -1}, in coppice stands to yield class 13 m{sup 3} ha{sup -1} year{sup -1}. The maximum mean annual increment was reached in seedling stands at the age of 18-19 years, in coppice stands at the age of 14 years. (author).

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.

a metabolic wastage model for the rate-yield trade off

Indian Academy of Sciences (India)

A METABOLIC WASTAGE MODEL FOR THE RATE-YIELD TRADE OFF. There is a growth limiting step in which an intermediate metabolite (m) has to hit a target molecule (t). ... D= rate of diffusing out. S= the rate of formation of the metabolite. The equilibrium loss decides the yield. The no. of activated targets decide the rate ...

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

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.

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.

Response of switchgrass yield to future climate change

International Nuclear Information System (INIS)

Tulbure, Mirela G; Wimberly, Michael C; Owens, Vance N

2012-01-01

A climate envelope approach was used to model the response of switchgrass, a model bioenergy species in the United States, to future climate change. The model was built using general additive models (GAMs), and switchgrass yields collected at 45 field trial locations as the response variable. The model incorporated variables previously shown to be the main determinants of switchgrass yield, and utilized current and predicted 1 km climate data from WorldClim. The models were run with current WorldClim data and compared with results of predicted yield obtained using two climate change scenarios across three global change models for three time steps. Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation. These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy. (letter)

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.

Climate-based statistical regression models for crop yield forecasting of coffee in humid tropical Kerala, India

Science.gov (United States)

Jayakumar, M.; Rajavel, M.; Surendran, U.

2016-12-01

A study on the variability of coffee yield of both Coffea arabica and Coffea canephora as influenced by climate parameters (rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH)) was undertaken at Regional Coffee Research Station, Chundale, Wayanad, Kerala State, India. The result on the coffee yield data of 30 years (1980 to 2009) revealed that the yield of coffee is fluctuating with the variations in climatic parameters. Among the species, productivity was higher for C. canephora coffee than C. arabica in most of the years. Maximum yield of C. canephora (2040 kg ha-1) was recorded in 2003-2004 and there was declining trend of yield noticed in the recent years. Similarly, the maximum yield of C. arabica (1745 kg ha-1) was recorded in 1988-1989 and decreased yield was noticed in the subsequent years till 1997-1998 due to year to year variability in climate. The highest correlation coefficient was found between the yield of C. arabica coffee and maximum temperature during January (0.7) and between C. arabica coffee yield and RH during July (0.4). Yield of C. canephora coffee had highest correlation with maximum temperature, RH and rainfall during February. Statistical regression model between selected climatic parameters and yield of C. arabica and C. canephora coffee was developed to forecast the yield of coffee in Wayanad district in Kerala. The model was validated for years 2010, 2011, and 2012 with the coffee yield data obtained during the years and the prediction was found to be good.

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

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....... The decline intensity and the value of several other model parameters, such as the maximum yield reached during the ceiling phase or the duration of the establishment phase, were highly variable. The highest maximum yields were obtained in the experiments located in the southern part of the studied area....... 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...

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

Sequential Path Model for Grain Yield in Soybean

Directory of Open Access Journals (Sweden)

Mohammad SEDGHI

2010-09-01

Full Text Available This study was performed to determine some physiological traits that affect soybean,s grain yield via sequential path analysis. In a factorial experiment, two cultivars (Harcor and Williams were sown under four levels of nitrogen and two levels of weed management at the research station of Tabriz University, Iran, during 2004 and 2005. Grain yield, some yield components and physiological traits were measured. Correlation coefficient analysis showed that grain yield had significant positive and negative association with measured traits. A sequential path analysis was done in order to evaluate associations among grain yield and related traits by ordering the various variables in first, second and third order paths on the basis of their maximum direct effects and minimal collinearity. Two first-order variables, namely number of pods per plant and pre-flowering net photosynthesis revealed highest direct effect on total grain yield and explained 49, 44 and 47 % of the variation in grain yield based on 2004, 2005, and combined datasets, respectively. Four traits i.e. post-flowering net photosynthesis, plant height, leaf area index and intercepted radiation at the bottom layer of canopy were found to fit as second-order variables. Pre- and post-flowering chlorophyll content, main root length and intercepted radiation at the middle layer of canopy were placed at the third-order path. From the results concluded that, number of pods per plant and pre-flowering net photosynthesis are the best selection criteria in soybean for grain yield.

[Response of water yield function of ecosystem to land use change in Nansi Lake Basin based on CLUE-S model and InVEST model .

Science.gov (United States)

Guo, Hong Wei; Sun, Xiao Yin; Lian, Li Shu; Zhang, Da Zhi; Xu, Yan

2016-09-01

Land use change has an important role in hydrological processes and utilization of water resources, and is the main driving force of water yield function of ecosystem. This paper analyzed the change of land use from 1990 to 2013 in Nansi Lake Basin, Shandong Province. The future land use in 2030 was also predicted and simulated by CLUE-S model. Based on land use scenarios, we analyzed the influence of land use change on ecosystem function of water yield in nearly 25 years through InVEST water yield model and spatial mapping. The results showed that the area of construction land increased by 3.5% in 2013 because of burgeoning urbanization process, but farmland area decreased by 2.4% which was conversed to construction land mostly. The simulated result of InVEST model suggested that water yield level of whole basin decreased firstly and increased subsequently during last 25 years and peaked at 232.1 mm in 2013. The construction land area would increase by 6.7% in 2030 based on the land use scenarios of fast urbanization, which would lead to a remarkable growth for water yield and risk of flowing flooding. However, the water yield level of whole basin would decrease by 1.2 % in 2013 if 300 meter-wide forest buffer strips around Nansi Lake were built up.

An advanced constitutive model in the sheet metal forming simulation: the Teodosiu microstructural model and the Cazacu Barlat yield criterion

International Nuclear Information System (INIS)

Alves, J.L.; Oliveira, M.C.; Menezes, L.F.

2004-01-01

Two constitutive models used to describe the plastic behavior of sheet metals in the numerical simulation of sheet metal forming process are studied: a recently proposed advanced constitutive model based on the Teodosiu microstructural model and the Cazacu Barlat yield criterion is compared with a more classical one, based on the Swift law and the Hill 1948 yield criterion. These constitutive models are implemented into DD3IMP, a finite element home code specifically developed to simulate sheet metal forming processes, which generically is a 3-D elastoplastic finite element code with an updated Lagrangian formulation, following a fully implicit time integration scheme, large elastoplastic strains and rotations. Solid finite elements and parametric surfaces are used to model the blank sheet and tool surfaces, respectively. Some details of the numerical implementation of the constitutive models are given. Finally, the theory is illustrated with the numerical simulation of the deep drawing of a cylindrical cup. The results show that the proposed advanced constitutive model predicts with more exactness the final shape (medium height and ears profile) of the formed part, as one can conclude from the comparison with the experimental results

``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

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.

Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

Directory of Open Access Journals (Sweden)

Jakob Geipel

2014-10-01

Full Text Available Precision Farming (PF management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs enable advanced methods for crop yield prediction. This work utilizes an Unmanned Aircraft System (UAS to capture standard RGB imagery datasets for corn grain yield prediction at three early- to mid-season growth stages. The imagery is processed into simple VI-orthoimages for crop/non-crop classification and 3D CSMs for crop height determination at different spatial resolutions. Three linear regression models are tested on their prediction ability using site-specific (i unclassified mean heights, (ii crop-classified mean heights and (iii a combination of crop-classified mean heights with according crop coverages. The models show determination coefficients \\({R}^{2}\\ of up to 0.74, whereas model (iii performs best with imagery captured at the end of stem elongation and intermediate spatial resolution (0.04m\\(\\cdot\\px\\(^{-1}\\.Following these results, combined spectral and spatial modeling, based on aerial images and CSMs, proves to be a suitable method for mid-season corn yield prediction.

Simulation Models of Leaf Area Index and Yield for Cotton Grown with Different Soil Conditioners.

Directory of Open Access Journals (Sweden)

Lijun Su

Full Text Available Simulation models of leaf area index (LAI and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modified Gaussian, log normal, and cubic polynomial models. Universal models for simulating the relative leaf area index (RLAI were established in which the application rate of soil conditioner was used to estimate the maximum LAI (LAIm. In addition, the relationships between LAIm and dry matter mass, yield, and the harvest index were investigated, and a simulation model for yield is proposed. A feasibility analysis of the models indicated that the cubic polynomial and Gaussian models were less accurate than the other three models for simulating increases in RLAI. Despite significant differences in LAIs under the type and amount of soil conditioner applied, LAIm could be described by aboveground dry matter using Michaelis-Menten kinetics. Moreover, the simulation model for cotton yield based on LAIm and the harvest index presented in this work provided important theoretical insights for improving water use efficiency in cotton cultivation and for identifying optimal application rates of soil conditioners.

An adapted yield criterion for the evolution of subsequent yield surfaces

Science.gov (United States)

Küsters, N.; Brosius, A.

2017-09-01

In numerical analysis of sheet metal forming processes, the anisotropic material behaviour is often modelled with isotropic work hardening and an average Lankford coefficient. In contrast, experimental observations show an evolution of the Lankford coefficients, which can be associated with a yield surface change due to kinematic and distortional hardening. Commonly, extensive efforts are carried out to describe these phenomena. In this paper an isotropic material model based on the Yld2000-2d criterion is adapted with an evolving yield exponent in order to change the yield surface shape. The yield exponent is linked to the accumulative plastic strain. This change has the effect of a rotating yield surface normal. As the normal is directly related to the Lankford coefficient, the change can be used to model the evolution of the Lankford coefficient during yielding. The paper will focus on the numerical implementation of the adapted material model for the FE-code LS-Dyna, mpi-version R7.1.2-d. A recently introduced identification scheme [1] is used to obtain the parameters for the evolving yield surface and will be briefly described for the proposed model. The suitability for numerical analysis will be discussed for deep drawing processes in general. Efforts for material characterization and modelling will be compared to other common yield surface descriptions. Besides experimental efforts and achieved accuracy, the potential of flexibility in material models and the risk of ambiguity during identification are of major interest in this paper.

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.

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.

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

International Nuclear Information System (INIS)

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A.

2017-01-01

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.

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

International Nuclear Information System (INIS)

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

2009-01-01

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.

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.

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.

Growth models for ponderosa pine: I. Yield of unthinned plantations in northern California.

Science.gov (United States)

William W. Oliver; Robert F. Powers

1978-01-01

Yields for high-survival, unthinned ponderosa pine (Pinus ponderosa Laws.) plantations in northern California are estimated. Stems of 367 trees in 12 plantations were analyzed to produce a growth model simulating stand yields. Diameter, basal area, and net cubic volume yields by Site Indices50 40 through 120 are tabulated for...

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.

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

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.

Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

Science.gov (United States)

Zhang, J.; Yang, J.; Pan, S.; Tian, H.

2016-12-01

China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level

Science.gov (United States)

Rajbhandaril, Narayan; Crosson, William; Tsegaye, Teferi; Coleman, Tommy; Liu, Yaping; Soman, Vishwas

1998-01-01

Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.

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.

Radiative leptonic decay: B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma} in a relativistic independent quark model

Energy Technology Data Exchange (ETDEWEB)

Barik, N [Department of Physics, Utkal University, Bhubaneswar-751004 (India); Naimuddin, Sk; Dash, P C [Department of Physics, Prananath Autonomous College, Khurda-752057 (India); Kar, Susmita [Department of Physics, North Orissa University, Baripada-757003 (India)

2008-01-01

We study the radiative leptonic decay, B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma}, in the framework of a relativistic independent quark model, based on the confining potential in the scalar-vector harmonic form. As expected, we find that the photon emission in this decay overcomes the so-called helicity suppression inevitable in the case of pure leptonic decay (B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}). Our result for the branching ratio is Br(B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma})=1.70x10{sup -6}, which is comparable with other model predictions within the current experimental upper limit. The photon energy spectrum predicted in the model is slightly asymmetric with the peak value around 1.45 GeV, which should render it quite accessible to experimental analysis.

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.

Modelling of the process yields of a whey fermentation

Energy Technology Data Exchange (ETDEWEB)

Blakebrough, N; Moresi, M

1981-09-01

The biomass yields (y) and COD reduction efficiencies (eta) of a whey fermentation by Kluyveromyces fragilis were studied in a 100-l fermenter at various stirrer speeds and lactose concentrations, and compared to those obtained in 10-l and 15-l fermenters at constant values of the oxygen transfer coefficient (ksub(L)a) and air velocity. The empirical models previously constructed by using the 15-l fermenter data could be used to predict the yields on the other scales by calculating for each run the 15-l fermenter which would provide the same oxygen transfer coefficient measured by the sulphite method on each fermenter under study. To make this model independent of stirrer speeds used in each generic fermenter, the effect of aeration and mixing was incorporated into an overall parameter (ksub(L)a) and the values of y and eta were correlated only with temperature, lactose level and ksub(L)a since these variables were approximately orthogonal.

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.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

Science.gov (United States)

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

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

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.

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 ...

An alternative approach for modeling strength differential effect in sheet metals with symmetric yield functions

Science.gov (United States)

Kurukuri, Srihari; Worswick, Michael J.

2013-12-01

An alternative approach is proposed to utilize symmetric yield functions for modeling the tension-compression asymmetry commonly observed in hcp materials. In this work, the strength differential (SD) effect is modeled by choosing separate symmetric plane stress yield functions (for example, Barlat Yld 2000-2d) for the tension i.e., in the first quadrant of principal stress space, and compression i.e., third quadrant of principal stress space. In the second and fourth quadrants, the yield locus is constructed by adopting interpolating functions between uniaxial tensile and compressive stress states. In this work, different interpolating functions are chosen and the predictive capability of each approach is discussed. The main advantage of this proposed approach is that the yield locus parameters are deterministic and relatively easy to identify when compared to the Cazacu family of yield functions commonly used for modeling SD effect observed in hcp materials.

Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

International Nuclear Information System (INIS)

Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

2015-01-01

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. (letter)

Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds

Science.gov (United States)

Pope, Katherine S.; Dose, Volker; Da Silva, David; Brown, Patrick H.; DeJong, Theodore M.

2015-06-01

Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond ( Prunus dulcis), pistachio ( Pistacia vera), and walnut ( Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

Rice yield estimation with multi-temporal Radarsat-2 data

Science.gov (United States)

Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru

2015-04-01

Rice is the most important food crop in Taiwan. Monitoring rice crop yield is thus crucial for agronomic planners to formulate successful strategies to address national food security and rice grain export issues. However, there is a real challenge for this monitoring purpose because the size of rice fields in Taiwan was generally small and fragmented, and the cropping calendar was also different from region to region. Thus, satellite-based estimation of rice crop yield requires the data that have sufficient spatial and temporal resolutions. This study aimed to develop models to estimate rice crop yield from multi-temporal Radarsat-2 data (5 m resolution). Data processing were carried out for the first rice cropping season from February to July in 2014 in the western part of Taiwan, consisting of four main steps: (1) constructing time-series backscattering coefficient data, (2) spatiotemporal noise filtering of the time-series data, (3) establishment of crop yield models using the time-series backscattering coefficients and in-situ measured yield data, and (4) model validation using field data and government's yield statistics. The results indicated that backscattering behavior varied from region to region due to changes in cultural practices and cropping calendars. The highest correlation coefficient (R2 > 0.8) was obtained at the ripening period. The robustness of the established models was evaluated by comparisons between the estimated yields and in-situ measured yield data showed satisfactory results, with the root mean squared error (RMSE) smaller than 10%. Such results were reaffirmed by the correlation analysis between the estimated yields and government's rice yield statistics (R2 > 0.8). This study demonstrates advantages of using multi-temporal Radarsat-2 backscattering data for estimating rice crop yields in Taiwan prior to the harvesting period, and thus the methods were proposed for rice yield monitoring in other regions.

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.

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

An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

Science.gov (United States)

Darbandi, Payam; Pourboghrat, Farhang

2011-08-01

Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

International Nuclear Information System (INIS)

Darbandi, Payam; Pourboghrat, Farhang

2011-01-01

Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

Science.gov (United States)

Assefa S. Desta

2006-01-01

A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

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

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.

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.

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.

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.

Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

Science.gov (United States)

Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

2017-12-01

Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

Science.gov (United States)

Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

2013-12-01

Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

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

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.

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

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.

EMPIRICALLY DERIVED INTEGRATED STELLAR YIELDS OF Fe-PEAK ELEMENTS

International Nuclear Information System (INIS)

Henry, R. B. C.; Cowan, John J.; Sobeck, Jennifer

2010-01-01

We present here the initial results of a new study of massive star yields of Fe-peak elements. We have compiled from the literature a database of carefully determined solar neighborhood stellar abundances of seven iron-peak elements, Ti, V, Cr, Mn, Fe, Co, and Ni, and then plotted [X/Fe] versus [Fe/H] to study the trends as functions of metallicity. Chemical evolution models were then employed to force a fit to the observed trends by adjusting the input massive star metallicity-sensitive yields of Kobayashi et al. Our results suggest that yields of Ti, V, and Co are generally larger as well as anticorrelated with metallicity, in contrast to the Kobayashi et al. predictions. We also find the yields of Cr and Mn to be generally smaller and directly correlated with metallicity compared to the theoretical results. Our results for Ni are consistent with theory, although our model suggests that all Ni yields should be scaled up slightly. The outcome of this exercise is the computation of a set of integrated yields, i.e., stellar yields weighted by a slightly flattened time-independent Salpeter initial mass function and integrated over stellar mass, for each of the above elements at several metallicity points spanned by the broad range of observations. These results are designed to be used as empirical constraints on future iron-peak yield predictions by stellar evolution modelers. Special attention is paid to the interesting behavior of [Cr/Co] with metallicity-these two elements have opposite slopes-as well as the indirect correlation of [Ti/Fe] with [Fe/H]. These particular trends, as well as those exhibited by the inferred integrated yields of all iron-peak elements with metallicity, are discussed in terms of both supernova nucleosynthesis and atomic physics.

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.

Influence of yield surface curvature on the macroscopic yielding and ductile failure of isotropic porous plastic materials

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Dæhli, Lars Edvard Bryhni; Morin, David; Børvik, Tore; Hopperstad, Odd Sture

2017-10-01

Numerical unit cell models of an approximative representative volume element for a porous ductile solid are utilized to investigate differences in the mechanical response between a quadratic and a non-quadratic matrix yield surface. A Hershey equivalent stress measure with two distinct values of the yield surface exponent is employed as the matrix description. Results from the unit cell calculations are further used to calibrate a heuristic extension of the Gurson model which incorporates effects of the third deviatoric stress invariant. An assessment of the porous plasticity model reveals its ability to describe the unit cell response to some extent, however underestimating the effect of the Lode parameter for the lower triaxiality ratios imposed in this study when compared to unit cell simulations. Ductile failure predictions by means of finite element simulations using a unit cell model that resembles an imperfection band are then conducted to examine how the non-quadratic matrix yield surface influences the failure strain as compared to the quadratic matrix yield surface. Further, strain localization predictions based on bifurcation analyses and imperfection band analyses are undertaken using the calibrated porous plasticity model. These simulations are then compared to the unit cell calculations in order to elucidate the differences between the various modelling strategies. The current study reveals that strain localization analyses using an imperfection band model and a spatially discretized unit cell are in reasonable agreement, while the bifurcation analyses predict higher strain levels at localization. Imperfection band analyses are finally used to calculate failure loci for the quadratic and the non-quadratic matrix yield surface under a wide range of loading conditions. The underlying matrix yield surface is demonstrated to have a pronounced influence on the onset of strain localization.

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

Science.gov (United States)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

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.

ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TO GEOMORPHIC MODELLING OF SEDIMENT YIELD FOR UNGAUGED CATCHMENTS, ALGERIA

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Khanchoul Kamel

2014-01-01

Full Text Available Knowledge of sediment yield and the factors controlling it provides useful information for estimating erosion intensities within river basins. The objective of this study was to build a model from which suspended sediment yield could be estimated from ungauged rivers using computed sediment yield and physical factors. Researchers working on suspended sediment transported by wadis in the Maghreb are usually facing the lack of available data for such river types. Further study of the prediction of sediment transport in these regions and its variability is clearly required. In this work, ANNs were built between sediment yield established from longterm measurement series at gauging stations in Algerian catchments and corresponding basic physiographic parameters such as rainfall, runoff, lithology index, coefficient of torrentiality, and basin area. The proposed Levenberg-Marquardt and Multilayer Perceptron algorithms to train the neural networks of the current research study was based on the feed-forward backpropagation method with combinations of number of neurons in each hidden layer, transfer function, error goal. Additionally, three statistical measurements, namely the root mean square error (RMSE, the coefficient of determination (R², and the efficiency factor (EF have been reported for examining the forecasting accuracy of the developed model. Single plot displays of network outputs with respect to targets for training have provided good performance results and good fitting . Thus, ANNs were a promising method for predicting suspended sediment yield in ungauged Algerian catchments.

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

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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

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.

Modeling the impact of climate change on watershed discharge and sediment yield in the black soil region, northeastern China

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Li, Zhiying; Fang, Haiyan

2017-09-01

Climate change is expected to impact discharge and sediment yield in watersheds. The purpose of this paper is to assess the potential impacts of climate change on water discharge and sediment yield for the Yi'an watershed of the black soil region, northeastern China, based on the newly released Representative Concentration Pathways (RCPs) during 2071-2099. For this purpose, the TETIS model was implemented to simulate the hydrological and sedimentological responses to climate change. The model calibration (1971-1977) and validation (1978-1987) performances were rated as satisfactory. The modeling results for the four RCP scenarios relative to the control scenario under the same land use configuration indicated an increase in discharge of 16.3% (RCP 2.6), 14.3% (RCP 4.5), 36.7% (RCP 6.0) and 71.4% (RCP 8.5) and an increase in the sediment yield of 16.5% (RCP 2.6), 32.4% (RCP 4.5), 81.8% (RCP 6.0) and 170% (RCP 8.5). This implies that the negative impact of climate change on sediment yield is generally greater than that on discharge. At the monthly scale, both discharge and sediment yield increased dramatically in April to June and August to September. A more vigorous hydrological cycle and an increase in high values of sediment yield are also expected. These changes in annual discharge and sediment yield were closely linked with changes in precipitation, whereas monthly changes in late spring and autumn were mainly related to temperature. This study highlights the possible adverse impact of climate change on discharge and sediment yield in the black soil region of northeastern China and could provide scientific basis for adaptive management.

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)

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

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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.

Spatial model of land use change related to sediment yield (case study: Cipeles and Cilutung watershed, West Java)

Science.gov (United States)

Wulandari, D. W.; Kusratmoko, E.; Indra, T. L.

2018-05-01

Land use changes (LUC) as a result of increasing human need for space are likely to destroy the hydrological function of the watershed, increase land degradation, stimulate erosion and drive the process of sedimentation. This study aimed to predict LUC during the period 1990 to 2030 in relation to sediment yield in Cilutung and Cipeles Watershed, West Java. LUC were simulated following the model of Cellular Automata-Marcov Chain, whereas land use composition in 2030 was predicted using Land Change Modeler on Idrisi Selva Software. Elevation, slope, distance from road, distance from river, and distance from settlement were selected as driving factors for LUC in this study. Erosion and sediment yield were predicted using WATEM/SEDEM model based on land use, rainfall, soil texture and topography. The results showed that the areas of forest and shrub have slightly declined up to 5% during the period 1990 to 2016, generally being converted into rice fields, settlements, non-irrigated fields and plantations. In addition, rice fields, settlements, and plantations were expected to substantially increase up to 50% in 2030. Furthermore, the study also revealed that erosion and sediment yield tend to increase every year. This is likely associated with LUC occurring in Cipeles and Cilutung Watershed.

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)

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

Science.gov (United States)

Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

2003-11-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

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Nathaniel K. Newlands

2014-06-01

Full Text Available We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting it and comparing its forecasts against available historical data (1987-2011 for spring wheat (Triticum aestivum L.. The model was also validated for the 2012 growing season by comparing its forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1-4 % in mid-season and over-estimated by 1 % at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space.

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

observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE...... and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index...... of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all...

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.

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

African Journals Online (AJOL)

kusimi

sediment delivery ratio; soil erosion modelling; sediment yield modelling. .... The basin falls within the wet semi-equitorial climatic belt which is ... influence of the moist south-west monsoons during the rainy season, with high .... availability of good satellite images covering the study area; because of thick cloud cover most.

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.

Simulation of nitrous oxide effluxes, crop yields and soil physical properties using the LandscapeDNDC model in managed ecosystem

Science.gov (United States)

Nyckowiak, Jedrzej; Lesny, Jacek; Haas, Edwin; Juszczak, Radoslaw; Kiese, Ralf; Butterbach-Bahl, Klaus; Olejnik, Janusz

2014-05-01

Modeling of nitrous oxide emissions from soil is very complex. Many different biological and chemical processes take place in soils which determine the amount of emitted nitrous oxide. Additionaly, biogeochemical models contain many detailed factors which may determine fluxes and other simulated variables. We used the LandscapeDNDC model in order to simulate N2O emissions, crop yields and soil physical properties from mineral cultivated soils in Poland. Nitrous oxide emissions from soils were modeled for fields with winter wheat, winter rye, spring barley, triticale, potatoes and alfalfa crops. Simulations were carried out for the plots of the Brody arable experimental station of Poznan University of Life Science in western Poland and covered the period 2003 - 2012. The model accuracy and its efficiency was determined by comparing simulations result with measurements of nitrous oxide emissions (measured with static chambers) from about 40 field campaigns. N2O emissions are strongly dependent on temperature and soil water content, hence we compared also simulated soil temperature at 10cm depth and soil water content at the same depth with the daily measured values of these driving variables. We compared also simulated yield quantities for each individual experimental plots with yield quantities which were measured in the period 2003-2012. We conclude that the LandscapeDNDC model is capable to simulate soil N2O emissions, crop yields and physical properties of soil with satisfactorily good accuracy and efficiency.

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

Effects of Source RDP Models and Near-source Propagation: Implication for Seismic Yield Estimation

Science.gov (United States)

Saikia, C. K.; Helmberger, D. V.; Stead, R. J.; Woods, B. B.

- It has proven difficult to uniquely untangle the source and propagation effects on the observed seismic data from underground nuclear explosions, even when large quantities of near-source, broadband data are available for analysis. This leads to uncertainties in our ability to quantify the nuclear seismic source function and, consequently the accuracy of seismic yield estimates for underground explosions. Extensive deterministic modeling analyses of the seismic data recorded from underground explosions at a variety of test sites have been conducted over the years and the results of these studies suggest that variations in the seismic source characteristics between test sites may be contributing to the observed differences in the magnitude/yield relations applicable at those sites. This contributes to our uncertainty in the determination of seismic yield estimates for explosions at previously uncalibrated test sites. In this paper we review issues involving the relationship of Nevada Test Site (NTS) source scaling laws to those at other sites. The Joint Verification Experiment (JVE) indicates that a magnitude (mb) bias (δmb) exists between the Semipalatinsk test site (STS) in the former Soviet Union (FSU) and the Nevada test site (NTS) in the United States. Generally this δmb is attributed to differential attenuation in the upper-mantle beneath the two test sites. This assumption results in rather large estimates of yield for large mb tunnel shots at Novaya Zemlya. A re-examination of the US testing experiments suggests that this δmb bias can partly be explained by anomalous NTS (Pahute) source characteristics. This interpretation is based on the modeling of US events at a number of test sites. Using a modified Haskell source description, we investigated the influence of the source Reduced Displacement Potential (RDP) parameters ψ ∞ , K and B by fitting short- and long-period data simultaneously, including the near-field body and surface waves. In general

Changes in diurnal temperature range and national cereal yields

Energy Technology Data Exchange (ETDEWEB)

Lobell, D

2007-04-26

Models of yield responses to temperature change have often considered only changes in average temperature (Tavg), with the implicit assumption that changes in the diurnal temperature range (DTR) can safely be ignored. The goal of this study was to evaluate this assumption using a combination of historical datasets and climate model projections. Data on national crop yields for 1961-2002 in the 10 leading producers of wheat, rice, and maize were combined with datasets on climate and crop locations to evaluate the empirical relationships between Tavg, DTR, and crop yields. In several rice and maize growing regions, including the two major nations for each crop, there was a clear negative response of yields to increased DTR. This finding reflects a nonlinear response of yields to temperature, which likely results from greater water and heat stress during hot days. In many other cases, the effects of DTR were not statistically significant, in part because correlations of DTR with other climate variables and the relatively short length of the time series resulted in wide confidence intervals for the estimates. To evaluate whether future changes in DTR are relevant to crop impact assessments, yield responses to projected changes in Tavg and DTR by 2046-2065 from 11 climate models were estimated. The mean climate model projections indicated an increase in DTR in most seasons and locations where wheat is grown, mixed projections for maize, and a general decrease in DTR for rice. These mean projections were associated with wide ranges that included zero in nearly all cases. The estimated impacts of DTR changes on yields were generally small (<5% change in yields) relative to the consistently negative impact of projected warming of Tavg. However, DTR changes did significantly affect yield responses in several cases, such as in reducing US maize yields and increasing India rice yields. Because DTR projections tend to be positively correlated with Tavg, estimates of yields

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.

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.

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

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 ...

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 ...

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.

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

oligonucleotides (pentadecamers) consistently, yielded at least 2 fold as much cDNA as did random hexamers using either-poly(A) RNA or an amplified version of messenger RNA (aRNA) as a template. The cDNA generated using pentadecamers did not differ in size distribution or the amount of incorporated label compared...... 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...... 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....

Statistical modelling and deconvolution of yield meter data

DEFF Research Database (Denmark)

Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

Data for yield maps can be obtained from modern combine harvesters equipped with a differential global positioning system and a yield monitoring system. Due to delay and smoothing effects in the combine harvester the recorded yield data for a location represents a shifted weighted average of yiel...

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.

Heavy-element yields and abundances of asymptotic giant branch models with a Small Magellanic Cloud metallicity

Science.gov (United States)

Karakas, Amanda I.; Lugaro, Maria; Carlos, Marília; Cseh, Borbála; Kamath, Devika; García-Hernández, D. A.

2018-06-01

We present new theoretical stellar yields and surface abundances for asymptotic giant branch (AGB) models with a metallicity appropriate for stars in the Small Magellanic Cloud (SMC, Z = 0.0028, [Fe/H] ≈ -0.7). New evolutionary sequences and post-processing nucleosynthesis results are presented for initial masses between 1 and 7 M⊙, where the 7 M⊙ is a super-AGB star with an O-Ne core. Models above 1.15 M⊙ become carbon rich during the AGB, and hot bottom burning begins in models M ≥ 3.75 M⊙. We present stellar surface abundances as a function of thermal pulse number for elements between C to Bi and for a selection of isotopic ratios for elements up to Fe and Ni (e.g. 12C/13C), which can be compared to observations. The integrated stellar yields are presented for each model in the grid for hydrogen, helium, and all stable elements from C to Bi. We present evolutionary sequences of intermediate-mass models between 4 and 7 M⊙ and nucleosynthesis results for three masses (M = 3.75, 5, and 7 M⊙) including s-process elements for two widely used AGB mass-loss prescriptions. We discuss our new models in the context of evolved AGB and post-AGB stars in the SMCs, barium stars in our Galaxy, the composition of Galactic globular clusters including Mg isotopes with a similar metallicity to our models, and to pre-solar grains which may have an origin in metal-poor AGB stars.

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)

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.

Satellite-based assessment of grassland yields

Science.gov (United States)

Grant, K.; Siegmund, R.; Wagner, M.; Hartmann, S.

2015-04-01

Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

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.

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,

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

Stock vs. Bond Yields, and Demographic Fluctuations

DEFF Research Database (Denmark)

Gozluklu, Arie; Morin, Annaïg

This paper analyzes the strong comovement between real stock and nominal bond yields at generational (low) frequencies. Life-cycle patterns in savings behavior in an overlapping generations model with cash-in-advance constraints explain this persistent comovement between financial yields. We argue...... that the slow-evolving time-series covariation due to changing population age structure accounts for the equilibrium relation between stock and bond markets. As a result, by exploiting the demographic information into distant future, the forecasting performance of evaluation models improves. Finally, using...

Extrapolating effects of conservation tillage on yield, soil moisture and dry spell mitigation using simulation modelling

Science.gov (United States)

Mkoga, Z. J.; Tumbo, S. D.; Kihupi, N.; Semoka, J.

There is big effort to disseminate conservation tillage practices in Tanzania. Despite wide spread field demonstrations there has been some field experiments meant to assess and verify suitability of the tillage options in local areas. Much of the experiments are short lived and thus long term effects of the tillage options are unknown. Experiments to study long term effects of the tillage options are lacking because they are expensive and cannot be easily managed. Crop simulation models have the ability to use long term weather data and the local soil parameters to assess long term effects of the tillage practices. The Agricultural Production Systems Simulator (APSIM) crop simulation model; was used to simulate long term production series of soil moisture and grain yield based on the soil and weather conditions in Mkoji sub-catchment of the great Ruaha river basin in Tanzania. A 24 year simulated maize yield series based on conventional tillage with ox-plough, without surface crop residues (CT) treatment was compared with similar yield series based on conservation tillage (ox-ripping, with surface crop residues (RR)). Results showed that predicted yield averages were significantly higher in conservation tillage than in conventional tillage ( P APSIM simulation model, showed that average soil moisture in the conservation tillage was significantly higher ( P < 0.05) (about 0.29 mm/mm) than in conventional tillage (0.22 mm/mm) treatment during the seasons which received rainfall between 468 and 770 mm. Similarly the conservation tillage treatment recorded significantly higher yields (4.4 t/ha) ( P < 0.01) than the conventional tillage (3.6 t/ha) treatment in the same range of seasonal rainfall. On the other hand there was no significant difference in soil moisture for the seasons which received rainfall above 770 mm. In these seasons grain yield in conservation tillage treatment was significantly lower (3.1 kg/ha) than in the conventional tillage treatment (4.8 kg

[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.

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.

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

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.

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.

Yield surface evolution for columnar ice

Science.gov (United States)

Zhou, Zhiwei; Ma, Wei; Zhang, Shujuan; Mu, Yanhu; Zhao, Shunpin; Li, Guoyu

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.

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.

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

Combined use of Azolla and loach suppressed paddy weeds and increased organic rice yield: second season results

Directory of Open Access Journals (Sweden)

Weiguo Cheng

2015-01-01

Full Text Available Organic farming uses alternatives to agricultural chemicals such as synthetic fertilizers and pesticides. The primary challenge in organic rice farming is controlling weeds without using herbicides and improving rice yield without chemical fertilizers. In our previous paper entitled as combined use of Azolla and loach suppressed weed Monochoria vaginalis and increased rice yield without agrochemicals, we reported the first year rice growth season results from an in situ container experiment. The experiment was designed with 4 treatments—control (with neither Azolla nor loach, Azolla (Azolla alone, loach (loach alone, and Az+Lo (combined Azolla and loach—with 3 replications each. The first year results showed that combined use of Azolla and loach was successful in weed suppression and increase in rice yield in 2012. In this paper, we report the second year results from the continuous container experiment in 2013. M.vaginalis emergences were very low in second year rice growth season on all treatments. Compared first year, the rice yields decreased in second year on all treatments due to different weather condition and with or without organic soybean oil cake application between two rice growth seasons. The second year results also showed the raising loach had a stronger effect to increase tiller and panicle numbers, and spikelet number per panicle, then improve rice yields to 2.3 times than control. The Azolla residues left from first year have weaker effect on rice growth and yield, but increase soil organic matter accumulation at second year. The two years study indicated that combined use of Azolla and loach can meet two of the greatest challenges in organic rice production: providing effective weed control and improving rice nutrition without agrochemicals.

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...... (If), deficit irrigated (Id) and not irrigated (I0) were investigated in three-years potato field experiment (2013–15) with four replicates in randomized complete block design. Tuber and total dry matter yield, canopy cover, dry matter production during the crop growth season, and soil water content...

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

Science.gov (United States)

Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

2011-03-01

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

Principal component regression for crop yield estimation

CERN Document Server

Suryanarayana, T M V

2016-01-01

This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

Simulation of runoff and sediment yield from a hilly watershed in the eastern Himalaya, India using the WEPP model

Science.gov (United States)

Singh, R. K.; Panda, R. K.; Satapathy, K. K.; Ngachan, S. V.

2011-08-01

spading and country plough. Installation of 8 check dams and 18 trash barriers in the drainage line was predicted to reduce sediment yield from the Umroi watershed substantially with reduction of 54.67%. Simulations of combinations of management practices indicted that soybean and peanut in upland situations with field cultivator or drill-no-tillage system, and structural control in the drainage line has potential to make agriculture sustainable in the Umroi watershed with sediment yield reduction up to 78.40%. The results of the study indicate that the WEPP model can be successfully used for developing conservation management practices in high rainfall and high slope conditions of eastern Himalaya.

Simulation of Wild oat (Avena ludoviciana L. Competition on Winter Wheat (Triticum astivum Growth and Yield. I: Model Description and Validation

Directory of Open Access Journals (Sweden)

F Mondani

2015-09-01

Full Text Available Crop growth models could stimulate growth and development based on science principles and mathematical equations. They also able to evaluate effects of climate, soil, water and agronomic management practices on crop yield. In the present study, an eco-physiological simulation model developed to assess wild oat damage to winter wheat growth and yield. The general structure of this model is derived from LINTUL1 model which modified to wild oat competition against winter wheat. LINTUL1 model was developed for simulation of spring wheat potential production level. In this study, first, we added development stage (DVS and vernalization to LINTUL1 for simulation of winter wheat growth and development and then the model calibrated for potential production level. Finally, we incorporate harmful effects of wild oat to winter wheat growth and yield. Weather data used as input were average daily minimum and maximum temperature (°C and daily global radiation (MJ m-2 in Mashhad, Iran. Parameter values were derived from the literature. The model is written in Fortran Simulation Translator (FST programming language and then validated based on an experiment data. For these purposes different wild oat plant densities were arranged. The data of this experiment does not use for calibration. The results showed that this model was in general able to simulate the temporal changes in DVS of winter wheat and wild oat, total dry matter (TDM of winter wheat and wild oat and yield loss of wheat due to wild oat competition in all treatments, satisfactorily. Root mean square error (RMSE for winter wheat DVS, wild oat DVS, average winter wheat TDM, average wild oat TDM, and yield loss of winter wheat was 10.4, 14.5, 5.8, 7.6 and 7.5, respectively.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

Science.gov (United States)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and

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.

Supersymmetric contribution to B{yields}{rho}K and B{yields}{pi}K{sup Low-Asterisk} decays in SCET

Energy Technology Data Exchange (ETDEWEB)

Faisel, Gaber, E-mail: gfaisel@cc.ncu.edu.tw [Department of Physics and Center for Mathematics and Theoretical Physics, National Central University, Chung-li, 32054, Taiwan (China); Egyptian Center for Theoretical Physics, Modern University for Information and Technology, Cairo (Egypt); Delepine, David [Departamento de Fisica, DCI, Campus Leon, Universidad de Guanajuato, C.P. 37150, Leon, Guanajuato (Mexico); Shalaby, M. [Ain Shams University, Faculty of Science, Cairo 11566 (Egypt)

2011-11-17

We analyze the supersymmetric contributions to the direct CP asymmetries of the decays B{yields}{pi}K{sup Low-Asterisk} and B{yields}{rho}K within Soft Collinear Effective Theory. We extend the Standard Model analysis of these asymmetries to include the next leading order QCD corrections. We find that, even with QCD correction, the Standard Model predictions cannot accommodate the direct CP asymmetries in these decay modes. Using Mass Insertion Approximation (MIA), we show that non-minimal flavor SUSY contributions mediated by gluino exchange can enhance the CP asymmetries significantly and thus can accommodate the experimental results.

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

Yield stress independent column buckling curves

DEFF Research Database (Denmark)

Stan, Tudor‐Cristian; Jönsson, Jeppe

2017-01-01

of the yield stress is to some inadequate degree taken into account in the Eurocode by specifying that steel grades of S460 and higher all belong to a common set of “raised” buckling curves. This is not satisfying as it can be shown theoretically that the current Eurocode formulation misses an epsilon factor......Using GMNIA and shell finite element modelling of steel columns it is ascertained that the buckling curves for given imperfections and residual stresses are not only dependent on the relative slenderness ratio and the cross section shape but also on the magnitude of the yield stress. The influence...... in the definition of the normalised imperfection magnitudes. By introducing this factor it seems that the GMNIA analysis and knowledge of the independency of residual stress levels on the yield stress can be brought together and give results showing consistency between numerical modelling and a simple modified...

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.

Study of asymmetric fission yield behavior from neutron-deficient Hg isotope

International Nuclear Information System (INIS)

Perkasa, Y. S.; Waris, A.; Kurniadi, R.; Su'ud, Z.

2014-01-01

A study of asymmetric fission yield behavior from a neutron-deficient Hg isotope has been conducted. The fission yield calculation of the neutron-deficient Hg isotope using Brownian Metropolis shape had showed unusual result at decreasing energy. In this paper, this interesting feature will be validated by using nine degree of scission shapes parameterization from Brosa model that had been implemented in TALYS nuclear reaction code. This validation is intended to show agreement between both model and the experiment result. The expected result from these models considered to be different due to dynamical properties that implemented in both models

Portfolio Effects of Renewable Energies - Basics, Models, Exemplary Results

Energy Technology Data Exchange (ETDEWEB)

Wiese, Andreas; Herrmann, Matthias

2007-07-01

The combination of sites and technologies to so-called renewable energy portfolios, which are being developed and implemented under the same financing umbrella, is currently the subject of intense discussion in the finance world. The resulting portfolio effect may allow the prediction of a higher return with the same risk or the same return with a lower risk - always in comparison with the investment in a single project. Models are currently being developed to analyse this subject and derive the portfolio effect. In particular, the effect of the spatial distribution, as well as the effects of using different technologies, suppliers and cost assumptions with different level of uncertainties, are of importance. Wind parks, photovoltaic, biomass, biogas and hydropower are being considered. The status of the model development and first results are being presented in the current paper. In a first example, the portfolio effect has been calculated and analysed using selected parameters for a wind energy portfolio of 39 sites distributed over Europe. Consequently it has been shown that the predicted yield, with the predetermined probabilities between 75 to 90%, is 3 - 8% higher than the sum of the yields for the individual wind parks using the same probabilities. (auth)

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

Search for B {yields} K{ell}{sup +}{ell}{sup -} and B {yields} K*(892){ell}{sup +}{ell}{sup -}

Energy Technology Data Exchange (ETDEWEB)

Aubert, B.

2004-02-12

The authors present preliminary results from a search for the flavor-changing neutral current decays B {yields} K{ell}{sup +}{ell}{sup -} and B {yields} K*(892){ell}{sup +}{ell}{sup -} using a sample of 22.7 x 10{sup 6} {Upsilon}(4S) {yields} B{bar B} decays collected with the BABAR detector at the PEP-II B Factory. They have reconstructed the following final states: B{sup +} {yields} K{sup +}{ell}{sup +}{ell}{sup -}, B{sup 0} {yields} K{sup 0}{ell}{sup +}{ell}{sup -} (K{sub s}{sup 0} {yields} {pi}{sup +} {pi}{sup -}), B{sup +} {yields} K*{sup +}{ell}{sup +}{ell}{sup -} (K*{sup +} {yields} K{sub s}{sup 0}{pi}{sup +}), and B{sup 0} {yields} K*{sup 0}{ell}{sup +}{ell}{sup -} (K*{sup 0} {yields} K{sup +}{pi}{sup -}), where {ell}{sup +}{ell}{sup -} is either an e{sup +}e{sup -} or {mu}{sup +}{mu}{sup -} pair. They obtain the 90% C.L. upper limits {Beta}(B {yields} K{ell}{sup +}{ell}{sup -}) < 0.6 x 10{sup -6} and {Beta}(B {yields} K*{ell}{sup +}{ell}{sup -}) < 2.5 x 10{sup -6}, close to the Standard Model predictions for these branching fractions.

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.

New approach for regional crop yield gap analysis in the Borujen ...

African Journals Online (AJOL)

enoh

2012-03-20

Mar 20, 2012 ... for model calibration and evaluation of WOFOST as a crop growth ... In general, simulated results matched well with the measured ... regional-scale yield prediction and assessment (Jagtap ... the benchmark value and most of the variation in yield ... The model simulates daily crop growth rate, based on.

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

Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

NARCIS (Netherlands)

Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.

2015-01-01

Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield

MODIS Data Assimilation in the CROPGRO model for improving soybean yield estimations

Science.gov (United States)

Richetti, J.; Monsivais-Huertero, A.; Ahmad, I.; Judge, J.

2017-12-01

Soybean is one of the main agricultural commodities in the world. Thus, having better estimates of its agricultural production is important. Improving the soybean crop models in Brazil is crucial for better understanding of the soybean market and enhancing decision making, because Brazil is the second largest soybean producer in the world, Parana state is responsible for almost 20% of it, and by itself would be the fourth greatest soybean producer in the world. Data assimilation techniques provide a method to improve spatio-temporal continuity of crops through integration of remotely sensed observations and crop growth models. This study aims to use MODIS EVI to improve DSSAT-CROPGRO soybean yield estimations in the Parana state, southern Brazil. The method uses the Ensemble Kalman filter which assimilates MODIS Terra and Aqua combined products (MOD13Q1 and MYD13Q1) into the CROPGRO model to improve the agricultural production estimates through update of light interception data over time. Expected results will be validated with monitored commercial farms during the period of 2013-2014.

Quantifying yield gaps in wheat production in Russia

International Nuclear Information System (INIS)

Schierhorn, Florian; Prishchepov, Alexander V; Koch, Friedrich J; Müller, Daniel; Faramarzi, Monireh

2014-01-01

Crop yields must increase substantially to meet the increasing demands for agricultural products. Crop yield increases are particularly important for Russia because low crop yields prevail across Russia’s widespread and fertile land resources. However, reliable data are lacking regarding the spatial distribution of potential yields in Russia, which can be used to determine yield gaps. We used a crop growth model to determine the yield potentials and yield gaps of winter and spring wheat at the provincial level across European Russia. We modeled the annual yield potentials from 1995 to 2006 with optimal nitrogen supplies for both rainfed and irrigated conditions. Overall, the results suggest yield gaps of 1.51–2.10 t ha −1 , or 44–52% of the yield potential under rainfed conditions. Under irrigated conditions, yield gaps of 3.14–3.30 t ha −1 , or 62–63% of the yield potential, were observed. However, recurring droughts cause large fluctuations in yield potentials under rainfed conditions, even when the nitrogen supply is optimal, particularly in the highly fertile black soil areas of southern European Russia. The highest yield gaps (up to 4 t ha −1 ) under irrigated conditions were detected in the steppe areas in southeastern European Russia along the border of Kazakhstan. Improving the nutrient and water supply and using crop breeds that are adapted to the frequent drought conditions are important for reducing yield gaps in European Russia. Our regional assessment helps inform policy and agricultural investors and prioritize research that aims to increase crop production in this important region for global agricultural markets. (letter)

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Science.gov (United States)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

Science.gov (United States)

Veerkamp, R F; Koenen, E P; De Jong, G

2001-10-01

Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

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....

Yield trends and yield gap analysis of major crops in the world

OpenAIRE

Hengsdijk, H.; Langeveld, J.W.A.

2009-01-01

This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are quantified, yield gaps evaluated by crop experts, current yield progress by breeding estimated, and different yield projections compared. Results show decreasing yield growth for wheat and rice, but ...

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.

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......, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area...... ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi...

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

Analysis of effects of updated decay and fission yield data on ORIGEN 2 results

International Nuclear Information System (INIS)

Daniel, P.R.

1993-01-01

Work has been performed to improve the accuracy of ORIGEN2 results by updating both the decay library and the fission yield data in the cross-section library. This effort was performed under the auspices of Oak Ridge National Laboratory (ORNL) to ensure that ORIGEN2 uses the most up-to-date data. The impact of the new data was then quantitatively evaluated by solving a set of standard light water reactor (LWR) problems solved with ORIGEN2. The ORIGEN code, developed at ORNL in the late 1960's, is a point depletion code used to determine the composition and characteristics of spent fuel. The results from calculations performed with the code often form the basis for the study and design of reprocessing plants, spent-fuel shipping casks, waste treatment systems, and disposal facilities. The decay data were updated using data from ENDF/B-VI; fission yield data were updated using data from ENDF/B-V. The impact of these new data was then evaluated

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

Yield performance and stability of CMS-based triticale hybrids.

Science.gov (United States)

Mühleisen, Jonathan; Piepho, Hans-Peter; Maurer, Hans Peter; Reif, Jochen Christoph

2015-02-01

CMS-based triticale hybrids showed only marginal midparent heterosis for grain yield and lower dynamic yield stability compared to inbred lines. Hybrids of triticale (×Triticosecale Wittmack) are expected to possess outstanding yield performance and increased dynamic yield stability. The objectives of the present study were to (1) examine the optimum choice of the biometrical model to compare yield stability of hybrids versus lines, (2) investigate whether hybrids exhibit a more pronounced grain yield performance and yield stability, and (3) study optimal strategies to predict yield stability of hybrids. Thirteen female and seven male parental lines and their 91 factorial hybrids as well as 30 commercial lines were evaluated for grain yield in up to 20 environments. Hybrids were produced using a cytoplasmic male sterility (CMS)-inducing cytoplasm that originated from Triticumtimopheevii Zhuk. We found that the choice of the biometrical model can cause contrasting results and concluded that a group-by-environment interaction term should be added to the model when estimating stability variance of hybrids and lines. midparent heterosis for grain yield was on average 3 % with a range from -15.0 to 11.5 %. No hybrid outperformed the best inbred line. Hybrids had, on average, lower dynamic yield stability compared to the inbred lines. Grain yield performance of hybrids could be predicted based on midparent values and general combining ability (GCA)-predicted values. In contrast, stability variance of hybrids could be predicted only based on GCA-predicted values. We speculated that negative effects of the used CMS cytoplasm might be the reason for the low performance and yield stability of the hybrids. For this purpose a detailed study on the reasons for the drawback of the currently existing CMS system in triticale is urgently required comprising also the search of potentially alternative hybridization systems.

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

DEFF Research Database (Denmark)

Boldrini, Lorenzo; Hillebrand, Eric Tobias

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...

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory.

Science.gov (United States)

Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

2016-07-27

The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R(2) of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system.

Exclusive nonleptonic B{yields}VV decays

Energy Technology Data Exchange (ETDEWEB)

Barik, N [Department of Physics, Utkal University, Bhubaneswar-751004 (India); Naimuddin, Sk [Department of Physics, Maharishi College of Natural Law, Bhubaneswar-751007 (India); Dash, P C [Department of Physics, Prananath Autonomous College, Khurda-752057 (India); Kar, Susmita [Department of Physics, North Orissa University, Baripada-757003 (India)

2009-07-01

The exclusive two-body nonleptonic B{yields}VV decays are investigated, within the factorization approximation, in the relativistic independent quark model based on a confining potential in the scalar-vector harmonic form. The branching ratios and the longitudinal polarization fraction (R{sub L}) are calculated yielding the model predictions in agreement with experiment. Our predicted CP-odd fraction (R{sub perpendicular}) for B{yields}D*D{sub (s)}* decays are in general agreement with other model predictions and within the existing experimental limit.

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Directory of Open Access Journals (Sweden)

Mohsen Janmohammadi

2014-01-01

Full Text Available Development of new bread wheat cultivars needs efficient tools to monitor trait association in a breeding program. This investigation was aimed to characterize grain yield components and some agronomic traits related to bread wheat grain yield. The efficiency of a breeding program depends mainly on the direction of the correlation between different traits and the relative importance of each component involved in contributing to grain yield. Correlation and path analysis were carried out in 56 bread wheat genotypes grown under field conditions of Maragheh, Iran. Observations were recorded on 18 wheat traits and correlation coefficient analysis revealed grain yield was positively correlated with stem diameter, spike length, floret number, spikelet number, grain diameter, grain length and 1000 seed weight traits. According to the variance inflation factor (VIF and tolerance as multicollinearity statistics, there are inconsistent relationships among the variables and all traits could be considered as first-order variables (Model I with grain yield as the response variable due to low multicollinearity of all measured traits. In the path coefficient analysis, grain yield represented the dependent variable and the spikelet number and 1000 seed weight traits were the independent ones. Our results indicated that the number of spikelets per spikes and leaf width and 1000 seed weight traits followed by the grain length, grain diameter and grain number per spike were the traits related to higher grain yield. The above mentioned traits along with their indirect causal factors should be considered simultaneously as an effective selection criteria evolving high yielding genotype because of their direct positive contribution to grain yield.

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.

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

Science.gov (United States)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

Yield, yield components and dry matter digestibility of alfalfa experimental populations

Directory of Open Access Journals (Sweden)

Katić Slobodan

2010-01-01

Full Text Available Alfalfa is the most important forage crop grown in the temperate regions. It is cultivated for production of vegetative aerial mass used fresh or as hay, and recently as haylage and silage. In many centres worldwide, efforts are made to breed and create new alfalfa cultivars with both higher yields and of higher nutritional value. The aim of this paper was to determine yield and digestibility of 12 experimental populations of alfalfa, and to compare their results to the yields of well-known domestic alfalfa commercial cultivars. The results show significant differences in yield of green forage and dry matter among alfalfa populations, as well as in yield components, height, proportion of leaves in yield and growth rate (tab. 1, 2 and 3. Differences between in vitro digestible dry matter (% and yields of in vitro digestible dry matter (t ha-1 were also significant (tab. 5 and 6. Yield and quality of experimental populations were at the same level or higher than of control cultivars. Synthetic SINUSA exceeded the control cutivars (NS Mediana ZMS V and Banat VS in yield and quality of dry matter. .

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.

INTRAVAL test case 1b - modelling results

International Nuclear Information System (INIS)

Jakob, A.; Hadermann, J.

1991-07-01

This report presents results obtained within Phase I of the INTRAVAL study. Six different models are fitted to the results of four infiltration experiments with 233 U tracer on small samples of crystalline bore cores originating from deep drillings in Northern Switzerland. Four of these are dual porosity media models taking into account advection and dispersion in water conducting zones (either tubelike veins or planar fractures), matrix diffusion out of these into pores of the solid phase, and either non-linear or linear sorption of the tracer onto inner surfaces. The remaining two are equivalent porous media models (excluding matrix diffusion) including either non-linear sorption onto surfaces of a single fissure family or linear sorption onto surfaces of several different fissure families. The fits to the experimental data have been carried out by Marquardt-Levenberg procedure yielding error estimates of the parameters, correlation coefficients and also, as a measure for the goodness of the fits, the minimum values of the χ 2 merit function. The effects of different upstream boundary conditions are demonstrated and the penetration depth for matrix diffusion is discussed briefly for both alternative flow path scenarios. The calculations show that the dual porosity media models are significantly more appropriate to the experimental data than the single porosity media concepts. Moreover, it is matrix diffusion rather than the non-linearity of the sorption isotherm which is responsible for the tailing part of the break-through curves. The extracted parameter values for some models for both the linear and non-linear (Freundlich) sorption isotherms are consistent with the results of independent static batch sorption experiments. From the fits, it is generally not possible to discriminate between the two alternative flow path geometries. On the basis of the modelling results, some proposals for further experiments are presented. (author) 15 refs., 23 figs., 7 tabs

Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

Science.gov (United States)

Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

2015-06-01

The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

Recent Results from Lohengrin on Fission Yields and Related Decay Properties

Science.gov (United States)

Serot, O.; Amouroux, C.; Bidaud, A.; Capellan, N.; Chabod, S.; Ebran, A.; Faust, H.; Kessedjian, G.; Köester, U.; Letourneau, A.; Litaize, O.; Martin, F.; Materna, T.; Mathieu, L.; Panebianco, S.; Regis, J.-M.; Rudigier, M.; Sage, C.; Urban, W.

2014-05-01

The Lohengrin mass spectrometer is one of the 40 instruments built around the reactor of the Institute Laue-Langevin (France) which delivers a very intense thermal neutron flux. Usually, Lohengrin was combined with a high-resolution ionization chamber in order to obtain good nuclear charge discrimination within a mass line, yielding an accurate isotopic yield determination. Unfortunately, this experimental procedure can only be applied for fission products with a nuclear charge less than about 42, i.e. in the light fission fragment region. Since 2008, a large collaboration has started with the aim of studying various fission aspects, mainly in the heavy fragment region. For that, a new experimental setup which allows isotopic identification by γ-ray spectrometry has been developed and validated. This technique was applied on the 239Pu(nth,f) reaction where about 65 fission product yields were measured with an uncertainty that has been reduced on average by a factor of 2 compared with what was that previously available in nuclear data libraries. The same γ-ray spectrometric technique is currently being applied to the study of the 233U(nth,f) reaction. Our aim is to deduce charge and mass distributions of the fission products and to complete the experimental data that exist mainly for light fission fragments. The measurement of 41 mass yields from the 241Am(2nth,f) reaction has been also performed. In addition to these activities on fission yield measurements, various new nanosecond isomers were discovered. Their presence can be revealed from a strong deformed ionic charge distribution compared to a 'normal' Gaussian shape. Finally, a new neutron long-counter detector designed to have a detection efficiency independent of the detected neutron energy has been built. Combining this neutron device with a Germanium detector and a beta-ray detector array allowed us to measure the beta-delayed neutron emission probability Pn of some important fission products for reactor

Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

Science.gov (United States)

Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

2009-12-01

Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

Energy Technology Data Exchange (ETDEWEB)

Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S [Department of Medical Physics, Juravinski Cancer Centre and McMaster University, 699 Concession Street, Hamilton, Ontario L8V 5C2 (Canada)

2003-12-21

Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS{sub 4}), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS{sub 4}). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS{sub 4} and TPPS{sub 4} were calculated to be 0.59 {+-} 0.03 and 0.121 {+-} 0

Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

International Nuclear Information System (INIS)

Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S

2003-01-01

Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS 4 ), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS 4 ). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS 4 and TPPS 4 were calculated to be 0.59 ± 0.03 and 0.121 ± 0.001 respectively using the point

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

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

International Nuclear Information System (INIS)

Akel, M.

2015-01-01

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 t he 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 Po, z0 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 Lo, varying z0 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 propor ties on soft x-ray emission and its propor ties 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 k A. The results show that the line radiation emission and

Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

Science.gov (United States)

Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

2015-04-01

Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from

Sensitivity of CERES-Maize yield simulation to the selected weather data

International Nuclear Information System (INIS)

Zalud, Z.; Stastna, M.

2000-01-01

Sensitivity analysis of selected weather data runs after successful parametrization and validation of the CERES-Maize simulation model. Estimation of the potential yield has been carried out during the long term experiment (1980-1997) as well as the estimation of influence of meteorological parameters on the simulation results for the water-limited yield. 10 % under and over stimulation of global radiation and precipitation as well as increasing and decreasing temperature by 1 deg C on simulated potential and water-limited yield have been done. In most of the years, air temperature underestimation resulted in a higher simulated grain yield and overstimulation shown a lower yield for water limited level. Overestimation of precipitation during wet days in growing period of the maize leads to an increase of amount of water available for the plant and to increase the yield. Underestimation of global radiation by 10 % resulted in a decline in simulated grain yield from -8.8 to -9.9 %. The overestimation caused increase of the yield from 7.8 to 10 %. Overestimation by 10 % resulted in a slight underestimation of the yield in low yielding years and underestimation of global radiation by 10 % in overestimation of the yield. The effect was opposite in high yielding years

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....

Modeling the impacts of climate change and technical progress on the wheat yield in inland China: An autoregressive distributed lag approach.

Science.gov (United States)

Zhai, Shiyan; Song, Genxin; Qin, Yaochen; Ye, Xinyue; Lee, Jay

2017-01-01

This study aims to evaluate the impacts of climate change and technical progress on the wheat yield per unit area from 1970 to 2014 in Henan, the largest agricultural province in China, using an autoregressive distributed lag approach. The bounded F-test for cointegration among the model variables yielded evidence of a long-run relationship among climate change, technical progress, and the wheat yield per unit area. In the long run, agricultural machinery and fertilizer use both had significantly positive impacts on the per unit area wheat yield. A 1% increase in the aggregate quantity of fertilizer use increased the wheat yield by 0.19%. Additionally, a 1% increase in machine use increased the wheat yield by 0.21%. In contrast, precipitation during the wheat growth period (from emergence to maturity, consisting of the period from last October to June) led to a decrease in the wheat yield per unit area. In the short run, the coefficient of the aggregate quantity of fertilizer used was negative. Land size had a significantly positive impact on the per unit area wheat yield in the short run. There was no significant short-run or long-run impact of temperature on the wheat yield per unit area in Henan Province. The results of our analysis suggest that climate change had a weak impact on the wheat yield, while technical progress played an important role in increasing the wheat yield per unit area. The results of this study have implications for national and local agriculture policies under climate change. To design well-targeted agriculture adaptation policies for the future and to reduce the adverse effects of climate change on the wheat yield, climate change and technical progress factors should be considered simultaneously. In addition, adaptive measures associated with technical progress should be given more attention.

Modeling the impacts of climate change and technical progress on the wheat yield in inland China: An autoregressive distributed lag approach.

Directory of Open Access Journals (Sweden)

Shiyan Zhai

Full Text Available This study aims to evaluate the impacts of climate change and technical progress on the wheat yield per unit area from 1970 to 2014 in Henan, the largest agricultural province in China, using an autoregressive distributed lag approach. The bounded F-test for cointegration among the model variables yielded evidence of a long-run relationship among climate change, technical progress, and the wheat yield per unit area. In the long run, agricultural machinery and fertilizer use both had significantly positive impacts on the per unit area wheat yield. A 1% increase in the aggregate quantity of fertilizer use increased the wheat yield by 0.19%. Additionally, a 1% increase in machine use increased the wheat yield by 0.21%. In contrast, precipitation during the wheat growth period (from emergence to maturity, consisting of the period from last October to June led to a decrease in the wheat yield per unit area. In the short run, the coefficient of the aggregate quantity of fertilizer used was negative. Land size had a significantly positive impact on the per unit area wheat yield in the short run. There was no significant short-run or long-run impact of temperature on the wheat yield per unit area in Henan Province. The results of our analysis suggest that climate change had a weak impact on the wheat yield, while technical progress played an important role in increasing the wheat yield per unit area. The results of this study have implications for national and local agriculture policies under climate change. To design well-targeted agriculture adaptation policies for the future and to reduce the adverse effects of climate change on the wheat yield, climate change and technical progress factors should be considered simultaneously. In addition, adaptive measures associated with technical progress should be given more attention.

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

Evolution of uranium fission-fragment charge yields with neutron number. Strong effect of multi-chance fission on yield asymmetries

Energy Technology Data Exchange (ETDEWEB)

Moeller, Peter [Los Alamos National Laboratory, Theoretical Division, Los Alamos, NM (United States); Schmitt, Christelle [CEA/DSM-CNRS/IN2P3, Grand Accelerateur National d' Ions Lourds, Caen (France)

2017-01-15

We use the Brownian shape-motion model, with its recent extensions, which allow modeling of odd-even staggering, to calculate the evolution of fission-fragment charge distributions with neutron number for the compound-system sequence {sup 234}U, {sup 236}U, {sup 238}U, and {sup 240}U. We compare to experimental data where available, for neutron- and electromagnetic-induced fission over a compound-nucleus excitation energy range from about 6 to 20 MeV. A notable result of the study is that the evolution of the location of the peak charge yield from Z = 54 in {sup 234}U towards Z = 52 in heavier isotopes, seen in the experimental data, is present also in the calculated yields. We further show that to describe yields at higher compound-nucleus excitation energies, then, already at 20 MeV, it is necessary to take multi-chance fission into account. (orig.)

Long Term Evaluation of Yield Stability Trend for Cereal Crops in Iran

Directory of Open Access Journals (Sweden)

mehdi nassiri mahalati

2016-05-01

Full Text Available During the last few decades cereals yield have increased drastically at the national level however, information about yield stability and its resistance to annual environmental variability are scare. In this study long term stability of grin yield of wheat, barley, rice, corn and overall cereals in Iran were evaluated during a 40-year period (1971-2011. Stability analysis was conducted using two different methods. In the first method the residuals of regression between crop yield and time (years were calculated as stability index. For this different segmented regression models including linear, bi-linear and tri-linear were fitted to yield trend data and the best model for each crop was selected based on statistical measures. Absolute residuals (the difference between actual and predicted yields for each year as well as relative residuals (absolute residuals as percent of predicted yield were estimated. In the second method yield stability was estimated from the slope of the regression line between average annual yield of all cereals (environmental index and the yield of each crop in the same year. Results indicted that in wheat and barley absolute and relative residuals were increased during the study period leading to reduction of stability despite considerable yield increment. However, for rice and corn residuals followed a decreasing trend and therefore yield stability of these crops was increased during the last 40 years. The same result was obtained with the environmental index but in this method reduction of yield stability in barley was lower than wheat. Based on the results, yield and yield stability of cereals crops in Iran increased during the last 40 years. However, the percentage increase in stability is lower than that of yield. Application of nitrogen fertilizers was led to reduction in stability. Yield stability of wheat, barley, rice, corn and overall cereals was improved with increasing their cultivated area.

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.

Yield and crop growth of table potato affected by different split-N fertigation regimes in sandy soil

DEFF Research Database (Denmark)

Zhenjiang, Zhou; Plauborg, Finn; Liu, Fulai

2018-01-01

accumulation. In all three years, the highest fresh yield and marketable yield was obtained when 180 kg N ha−1 was applied. Compared to the 180 kg N ha−1 treatment, real-time model-based N fertilization resulted in comparable yield (not different) in all seasons. Nevertheless, model-based N fertilization...... model)-based N fertilization method, as well as three irrigation levels. Results showed that prolonged N fertigation increased yield consistently but N fertigation should be carried out early so that shoot growth is optimized and prolonged N have sufficient time to take effect on tuber yield...

Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

OpenAIRE

Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

2010-01-01

Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

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

Measurement of jets production in association with a Z boson and in the search for the SM Higgs boson via H {yields} {tau}{tau} {yields} ll + 4{nu} with ATLAS

Energy Technology Data Exchange (ETDEWEB)

Psoroulas, Serena

2012-10-15

Three measurements focussing on the understanding of jet final states in ATLAS, in dijet, Z and Higgs boson candidate events, using data corresponding to an integrated luminosity of 35 pb{sup -1} in 2010 and 4.7 fb{sup -1} in 2011, are presented. In the first part, a calibration method, based on the transverse momentum balance in dijet events, is described. The method is used to estimate the uncertainty of the jet energy scale in the forward region. The results show that the parton shower models are limited in reproducing the results in data, mostly for jets of low transverse momentum. In the second part, the differential cross section measurement of the Z{yields}ll+jets process is reported. Phase space regions not been previously studied at other experiments are investigated. The models used for the theory predictions provide a good description of the data, within the relative uncertainties. In the last part, two contribution to the Higgs searches in the H {yields}{tau}{tau} channel are shown: the modelling of the Z{yields}{tau}{tau} background, and the modelling of jet final states. The Z{yields}{tau}{tau} background is derived from data and validated in the H{yields}{tau}{tau}{yields}ll+4{nu} channel. The modelling of jet final states in simulations is in good agreement with the data, when low-energy pile-up effects are subtracted.

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.

On the yield stress of complex materials

Science.gov (United States)

Calderas, F.; Herrera-Valencia, E. E.; Sanchez-Solis, A.; Manero, O.; Medina-Torres, L.; Renteria, A.; Sanchez-Olivares, G.

2013-11-01

In the present work, the yield stress of complex materials is analyzed and modeled using the Bautista-Manero-Puig (BMP) constitutive equation, consisting of the upper-convected Maxwell equation coupled to a kinetic equation to account for the breakdown and reformation of the fluid structure. BMP model predictions for a complex fluid in different flow situations are analyzed and compared with yield stress predictions of other rheological models, and with experiments on fluids that exhibit yield stresses. It is shown that one of the main features of the BMP model is that it predicts a real yield stress (elastic solid or Hookean behavior) as one of the material parameters, the zero shear-rate fluidity, is zero. In addition, the transition to fluid-like behavior is continuous, as opposed to predictions of more empirical models.

Predicting spring barley yield from variety-specific yield potential, disease resistance and straw length, and from environment-specific disease loads and weed pressure

DEFF Research Database (Denmark)

Østergård, Hanne; Kristensen, Kristian; Pinnschmidt, Hans O.

2008-01-01

For low-input crop production, well-characterised varieties increase the possibilities of managing diseases and weeds. This analysis aims at developing a framework for analyzing grain yield using external varietal information about disease resistance, weed competitiveness and yield potential and ...... growth habit. Higher grain yield was thus predicted for taller plants under weed pressure. The results are discussed in relation to the model framework, impact of the considered traits and use of information from conventional variety testing in organic cropping systems....

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.

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

The main aim of the present study was to examine the economic consequences of a reduction in the incidence of clinical mastitis (CM) at herd level under current Swedish farming conditions. A second objective was to ask whether the estimated cost of CM alters depending upon whether the model...... with 150 cows (9000 kg of energy-corrected milk per cow-year). Four herd types, defined by production level and reproductive performance, were modelled to investigate possible interactions between herd type and response to a reduction in the risk of CM. Technical and economic results, given the initial...... incidence of CM (25.6 per 100 cow-years), were studied together with the consequences of reducing the initial risk of CM by 50% and 90% throughout lactation and the consequences of reducing the initial risk by 50% and 90% before peak yield. A conventional way of modelling yield losses - i.e. one employing...

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Science.gov (United States)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Genetic Parameters for Body condition score, Body weigth, Milk yield and Fertility estimated using random regression models

NARCIS (Netherlands)

Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

2003-01-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields

Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.

Science.gov (United States)

Jin, Zhenong; Zhuang, Qianlai; Tan, Zeli; Dukes, Jeffrey S; Zheng, Bangyou; Melillo, Jerry M

2016-09-01

Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models. © 2016 John

Application of the continuously-yielding joint model for studying disposal of high-level nuclear waste in crystalline rock

International Nuclear Information System (INIS)

Hakala, M.; Johansson, E.; Simonen, A.

1993-04-01

The non-linear Continuously-Yielding (CY) joint model and its use in numerical analyses of a nuclear waste repository are studied in the report. On major advantage of using CY-model is that laboratory test results, if available, can directly be used in analyses thus reducing uncertainties about joint input parameters. The new testing machine MTS-815 of Helsinki University of Technology was used to determine the joint behaviour of some granitic joints from the depth of 400-600 m below the ground surface. The procedure for triaxial joint tests was refined during this work. Two programs called NormFit and SherFit were developed and tested to determine the best fit parameter values for CY-model from laboratory test results

Analysis of the static yield stress for giant electrorheological fluids

Science.gov (United States)

Seo, Youngwook P.; Choi, Hyoung Jin; Seo, Yongsok

2017-08-01

Cheng et al. (2010)'s experimental results for the static yield stress of giant electrorheological (GER) fluids over the full range of electric field strengths were reanalyzed by applying Seo's scaling function which could include both the polarization and the conductivity models. The Seo's scaling function could correctly fit the yield stress behavior of GER suspensions behavior after if a proper normalization of the yield stress data was taken which collapse them onto a single curve. The model predictions were also contrasted with recently proposed Choi et al.'s scaling function to rouse the attention for a proper consideration of the GER fluid mechanisms.

Yield Strength Testing in Human Cadaver Nasal Septal Cartilage and L-Strut Constructs.

Science.gov (United States)

Liu, Yuan F; Messinger, Kelton; Inman, Jared C

2017-01-01

To our knowledge, yield strength testing in human nasal septal cartilage has not been reported to date. An understanding of the basic mechanics of the nasal septum may help surgeons decide how much of an L-strut to preserve and how much grafting is needed. To determine the factors correlated with yield strength of the cartilaginous nasal septum and to explore the association between L-strut width and thickness in determining yield strength. In an anatomy laboratory, yield strength of rectangular pieces of fresh cadaver nasal septal cartilage was measured, and regression was performed to identify the factors correlated with yield strength. To measure yield strength in L-shaped models, 4 bonded paper L-struts models were constructed for every possible combination of the width and thickness, for a total of 240 models. Mathematical modeling using the resultant data with trend lines and surface fitting was performed to quantify the associations among L-strut width, thickness, and yield strength. The study dates were November 1, 2015, to April 1, 2016. The factors correlated with nasal cartilage yield strength and the associations among L-strut width, thickness, and yield strength in L-shaped models. Among 95 cartilage pieces from 12 human cadavers (mean [SD] age, 67.7 [12.6] years) and 240 constructed L-strut models, L-strut thickness was the only factor correlated with nasal septal cartilage yield strength (coefficient for thickness, 5.54; 95% CI, 4.08-7.00; P cadaver nasal septal cartilage, L-strut thickness was significantly associated with yield strength. In a bonded paper L-strut model, L-strut thickness had a more important role in determining yield strength than L-strut width. Surgeons should consider the thickness of potential L-struts when determining the amount of cartilaginous septum to harvest and graft. NA.

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.

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.

Predicting Great Lakes fish yields: tools and constraints

Science.gov (United States)

Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

1987-01-01

Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

ENDF/B yield evaluation for 1992: Methods and content

International Nuclear Information System (INIS)

England, T.R.; Rider, B.F.

1992-01-01

The basic evaluation process, completed in May 1992, for 60 independent, plus corresponding cumulative yield sets is described thirty-six fissioning nuclides at one-or-more neutron fission energies or spontaneous fission are included. The resulting recommended yields include approximately 1200 nuclides per set; these will be slightly extended to encompass all nuclides in the ENDF/B-VI decay files and issued as the second release of ENDF/B-VI yields. All current yield sets in ENDF/B-VI have been reevaluated using ∼3000 new measurements and model parameters for distribution along mass chains. Compiled measurements through 1992 will be included in the documentation of the recommended yields. This paper can only summarize the primary features of the evaluations

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

A comparative ideotype, yield component and cultivation value analysis for spring wheat adaptation in Finland

Directory of Open Access Journals (Sweden)

Heikki Laurila

2012-12-01

Full Text Available In this study Mixed structural covariance, Path and Cultivation Value analyses and the CERES-Wheat crop model were used to evaluate vegetation and yield component variation affecting yield potential between different high-latitude (> 60° N lat. and mid-European (< 60° N lat. spring wheat (Triticum aestivum L. genotypes currently cultivated in southern Finland. Path modeling results from this study suggest that especially grains/ear, harvest index (HI and maximum 1000 kernel weight were significant factors defining the highest yield potential. Mixed and Cultivation value modeling results suggest that when compared with genotypes introduced for cultivation before 1990s, modern spring wheat genotypes have a significantly higher yielding capacity, current high yielding mid-European genotypes even exceeding the 5 t ha-1 non-potential baseline yield level (yb. Because of a forthcoming climate change, the new high yielding wheat genotypes have to adapt for elevated temperatures and atmospheric CO2 growing conditions in northern latitudes. The optimized ideotype profiles derived from the generic high-latitude and mid-European genotypes are presented in the results. High-latitude and mid-European ideotype profiles with factors estimating the effects of concurrent elevated CO2 and temperature levels with photoperiodical daylength effects can be utilized when designing future high yielding ideotypes adapted to future growing conditions. The CERES-Wheat ideotype modeling results imply, that with new high yielding mid-European ideotypes, the non-potential baseline yield (yb would be on average 5150 kg ha-1 level (+ 108 % vs. new high-latitude ideotypes (yb 4770 kg ha-1, 100% grown under the elevated CO2(700ppm×temperature(+3ºC growing conditions projected by the year 2100 climate change scenario in southern Finland.

Compressive yielding of tungsten fiber reinforced bulk metallic glass composites

Energy Technology Data Exchange (ETDEWEB)

Clausen, B.; Lee, S.-Y.; Uestuendag, E.; Aydiner, C.C.; Conner, R.D.; Bourke, M.A.M

2003-07-15

In-situ uniaxial compression tests were conducted on four tungsten fiber reinforced bulk metallic glass matrix composites using neutron diffraction. The results were interpreted with a finite element model. Both phases were seen to approximately obey the von Mises yield criterion. The fibers were observed to yield first and then transfer load to the matrix.

Compressive yielding of tungsten fiber reinforced bulk metallic glass composites

International Nuclear Information System (INIS)

Clausen, B.; Lee, S.-Y.; Uestuendag, E.; Aydiner, C.C.; Conner, R.D.; Bourke, M.A.M.

2003-01-01

In-situ uniaxial compression tests were conducted on four tungsten fiber reinforced bulk metallic glass matrix composites using neutron diffraction. The results were interpreted with a finite element model. Both phases were seen to approximately obey the von Mises yield criterion. The fibers were observed to yield first and then transfer load to the matrix

Effect of Climate and Management Factors on Potential and Gap of Wheat Yield in Iran with Using WOFOST Model

Directory of Open Access Journals (Sweden)

A Koocheki

2017-10-01

intensification. We estimated a stochastic frontier production function to calculate global datasets of maximum attainable grain yields, yield gaps, and efficiencies of grain production at. Applying a stochastic frontier production function facilitates estimating the yield gap based on the actual grain yield data only, instead of using actual and potential grain yield data from different sources. Therefore, the method allows for a robust and consistent analysis of the yield gap. The factors determining the yield gap are quantified at both global and regional scales. For this purpose, climatic information and wheat yield of different provinces were obtained from Iran meteorological organization and Agriculture Jahade organization, respectively. Wheat potential yield in different provinces was simulated by WOFOST model. Wheat gap was gained by difference between actual and potential yield in different provinces. Relative share of climatic variables in potential yield and also relative share of management variables included irrigation, fertilizer application, mechanization, pesticide application and manure in wheat yield gap was calculated by frontier production function. Results and Discussion The results showed that the effect of precipitation and radiation on wheat potential yield was positive and the impact of temperature was negative. Precipitation had the highest impact on wheat potential yield among other climatic variables. The range of wheat yield gap was from 1646 to 4470 kg ha-1 and 29 to 58% in Iran. Generally, the effect of all management variables on wheat yield gap was negative so that wheat yield gap was reduced by improving of these variables. Among studied management variables, irrigation had the highest effect on yield gap reduction, especially in dry-warm climate and fertilizer application was the second factor which had high effect on yield gap reduction. Therefore, to reduce wheat yield gap in Iran, irrigation management and fertilizer application should be

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.

Yield surfaces for perforated plates with square arrays of holes

International Nuclear Information System (INIS)

Bhattacharya, A.; Venkat Raj, V.

2004-01-01

A symmetric model of a perforated plate containing a 3x3 array of circular holes, arranged in a square pattern, was chosen and elastoplastic finite element analyses were carried out to determine the limit stresses for both pitch and diagonal directions of loading, for different values of biaxiality ratios. Plane stress conditions were assumed and the Tresca and von Mises yield criteria were employed to obtain two different sets of results. Yield surfaces were constructed and 'general cut-out factors' were determined for four different ligament efficiencies. The FEM results obtained by the authors using the Tresca and von Mises yield criteria were compared with the corresponding results of [J. Pressure Vessel Technol. Trans. ASME (1975) 146-154] and [J. Pressure Vessel Technol. Trans. ASME (1997) 122-126], respectively. The results based on the Tresca yield criterion obtained by the present authors and those in [J. Pressure Vessel Technol. Trans. ASME (1975) 146-154] were found to agree well with each other. In the case of the von Mises yield criterion, the agreement with [J. Pressure Vessel Technol. Trans. ASME 122-126] is generally good. The estimates based on the Tresca yield criterion are seen to result in lower values of limit stresses and cut-out factors as compared to those based on the von Mises yield criterion. The difference is attributed to the yield criterion and the flow rule chosen for the analysis. The shape as well as the size of the yield surface was found to depend on the ligament efficiency

Comparing predicted yield and yield stability of willow and Miscanthus across Denmark

DEFF Research Database (Denmark)

Larsen, Søren; Jaiswal, Deepak; Bentsen, Niclas Scott

2016-01-01

was 12.1 Mg DM ha−1 yr−1 for willow and 10.2 Mg DM ha−1 yr−1 for Miscanthus. Coefficent of variation as a measure for yield stability was poorest on the sandy soils of northern and western Jutland and the year-to-year variation in yield was greatest on these soils. Willow was predicted to outyield...... Miscanthus on poor, sandy soils whereas Miscanthus was higher yielding on clay-rich soils. The major driver of yield in both crops was variation in soil moisture, with radiation and precipitation exerting less influence. This is the first time these two major feedstocks for northern Europe have been compared....... The semi-mechanistic crop model BioCro was used to simulate the production of both short rotation coppice (SRC) willow and Miscanthus across Denmark. Predictions were made from high spatial resolution soil data and weather records across this area for 1990-2010. The potential average, rain-fed mean yield...

Using MODIS Data to Predict Regional Corn Yields

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Ho-Young Ban

2016-12-01

Full Text Available A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data, which are eight-day interval surface reflectance data, were obtained from day of the year (DOY 89 to 337 to calculate the leaf area index (LAI. The sum of the LAI from early in the season to a given date in the season (end of DOY (EOD was well fitted to a logistic function and represented seasonal changes in leaf area duration (LAD. A simple phenology model was derived to estimate the dates of emergence and maturity using the LAD-logistic function parameters b1 and b2, which represented the rate of increase in LAI and the date of maximum LAI, respectively. The phenology model predicted emergence and maturity dates fairly well, with root mean square error (RMSE values of 6.3 and 4.9 days for the validation dataset, respectively. Two simple linear regression models (YP and YF were established using LAD as the variable to predict corn yield. The yield model YP used LAD from predicted emergence to maturity, and the yield model YF used LAD for a predetermined period from DOY 89 to a particular EOD. When state/province corn yields for the validation dataset were predicted at DOY 321, near completion of the corn harvest, the YP model, including the predicted phenology, performed much better than the YF model, with RMSE values of 0.68 t/ha and 0.66 t/ha for Illinois and Heilongjiang, respectively. The YP model showed similar or better performance, even for the much earlier pre-harvest yield prediction at DOY 257. In addition, the model performance showed no difference between the two study regions with very different climates and cultivation methods, including cultivar and irrigation management. These results suggested that the approach described in this paper has potential for application to

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;

The stochastic seasonal behavior of energy commodity convenience yields

International Nuclear Information System (INIS)

Mirantes, Andrés García; Población, Javier; Serna, Gregorio

2013-01-01

This paper contributes to the commodity pricing literature by consistently modeling the convenience yield with its empirically observed properties. Specifically, in this paper, we show how a four-factor model for the stochastic behavior of commodity prices, with two long- and short-term factors and two additional seasonal factors, may accommodate some of the most important empirically observed characteristics of commodity convenience yields, such as the mean reversion and stochastic seasonality. Based on this evidence, a theoretical model is presented and estimated to characterize the commodity convenience yield dynamics that are consistent with previous findings. We also show that commodity price seasonality is better estimated through convenience yields than through futures prices. - Highlights: • Energy commodity convenience yields exhibit mean reversion and stochastic seasonality. • We present a model for convenience yields accounting for their observed characteristics. • Commodity price seasonality is better estimated through convenience yields

Measurements of beryllium sputtering yields at JET

Science.gov (United States)

Jet-Efda Contributors Stamp, M. F.; Krieger, K.; Brezinsek, S.

2011-08-01

The lifetime of the beryllium first wall in ITER will depend on erosion and redeposition processes. The physical sputtering yields for beryllium (both deuterium on beryllium (Be) and Be on Be) are of crucial importance since they drive the erosion process. Literature values of experimental sputtering yields show an order of magnitude variation so predictive modelling of ITER wall lifetimes has large uncertainty. We have reviewed the old beryllium yield experiments on JET and used current beryllium atomic data to produce revised beryllium sputtering yields. These experimental measurements have been compared with a simple physical sputtering model based on TRIM.SP beryllium yield data. Fair agreement is seen for beryllium yields from a clean beryllium limiter. However the yield on a beryllium divertor tile (with C/Be co-deposits) shows poor agreement at low electron temperatures indicating that the effect of the higher sputtering threshold for beryllium carbide is important.

Fluence dependent changes of erosion yields and surface morphology of the iron-tungsten model system: SDTrimSP-2D simulation studies

Directory of Open Access Journals (Sweden)

U. von Toussaint

2017-08-01

Full Text Available The effect of different sample structures of an iron-tungsten model system (as a surrogate for reduced activation ferritic martensitic steels like EUROFER on the development of surface morphologies, tungsten surface enrichment and sputter yields under low-energy monoenergetic perpendicular 200 eV deuterium bombardment has been studied with SDTrimSP-2d simulations. Previous modeling studies considering diffusive effects also could reasonably reproduce and explain the experimental results for a large set of experimental parameters like temperature, flux and sample concentration. However, for settings with negligible Fe-W-interdiffusion the fluence needed for steady-state conditions differed between the experiments and the simulations. Thus, the main focus of the present study is directed towards the elucidation of this fluence mismatch. Comparison of one and two-dimensional simulation results reveal a strong dependency of the tungsten enrichment on the sample homogeneity and a significantly delayed reduction of the erosion yield due to a pronounced formation of surface structures from initially flat sample surfaces.

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.

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.

Quantification of the specific yield in a two-layer hard-rock aquifer model

Science.gov (United States)

Durand, Véronique; Léonardi, Véronique; de Marsily, Ghislain; Lachassagne, Patrick

2017-08-01

Hard rock aquifers (HRA) have long been considered to be two-layer systems, with a mostly capacitive layer just below the surface, the saprolite layer, and a mainly transmissive layer underneath, the fractured layer. Although this hydrogeological conceptual model is widely accepted today within the scientific community, it is difficult to quantify the respective storage properties of each layer with an equivalent porous medium model. Based on an HRA field site, this paper attempts to quantify in a distinct manner the respective values of the specific yield (Sy) in the saprolite and the fractured layer, with the help of a deterministic hydrogeological model. The study site is the Plancoët migmatitic aquifer located in north-western Brittany, France, with piezometric data from 36 observation wells surveyed every two weeks for eight years. Whereas most of the piezometers (26) are located where the water table lies within the saprolite, thus representing the specific yield of the unconfined layer (Sy1), 10 of them are representative of the unconfined fractured layer (Sy2), due to their position where the saprolite is eroded or unsaturated. The two-layer model, based on field observations of the layer geometry, runs with the MODFLOW code. 81 values of the Sy1/Sy2 parameter sets were tested manually, as an inverse calibration was not able to calibrate these parameters. In order to calibrate the storage properties, a new quality-of-fit criterion called ;AdVar; was also developed, equal to the mean squared deviation of the seasonal piezometric amplitude variation. Contrary to the variance, AdVar is able to select the best values for the specific yield in each layer. It is demonstrated that the saprolite layer is about 2.5 times more capacitive than the fractured layer, with Sy1 = 10% (7% < Sy1 < 15%) against Sy2 = 2% (1% < Sy2 < 3%), in this particular example.

A Covariance Generation Methodology for Fission Product Yields

Directory of Open Access Journals (Sweden)

Terranova N.

2016-01-01

Full Text Available Recent safety and economical concerns for modern nuclear reactor applications have fed an outstanding interest in basic nuclear data evaluation improvement and completion. It has been immediately clear that the accuracy of our predictive simulation models was strongly affected by our knowledge on input data. Therefore strong efforts have been made to improve nuclear data and to generate complete and reliable uncertainty information able to yield proper uncertainty propagation on integral reactor parameters. Since in modern nuclear data banks (such as JEFF-3.1.1 and ENDF/BVII.1 no correlations for fission yields are given, in the present work we propose a covariance generation methodology for fission product yields. The main goal is to reproduce the existing European library and to add covariance information to allow proper uncertainty propagation in depletion and decay heat calculations. To do so, we adopted the Generalized Least Square Method (GLSM implemented in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation, developed at CEA-Cadarache. Theoretical values employed in the Bayesian parameter adjustment are delivered thanks to a convolution of different models, representing several quantities in fission yield calculations: the Brosa fission modes for pre-neutron mass distribution, a simplified Gaussian model for prompt neutron emission probability, theWahl systematics for charge distribution and the Madland-England model for the isomeric ratio. Some results will be presented for the thermal fission of U-235, Pu-239 and Pu-241.

Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties

Science.gov (United States)

Sankey, Joel B.; McVay, Jason C.; Kreitler, Jason R.; Hawbaker, Todd J.; Vaillant, Nicole; Lowe, Scott

2015-01-01

Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

Science.gov (United States)

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Comparison of inverse modeling results with measured and interpolated hydraulic head data

International Nuclear Information System (INIS)

Jacobson, E.A.

1986-12-01

Inverse modeling of aquifers involves identification of effective parameters, such as transmissivities, based on hydraulic head data. The result of inverse modeling is a calibrated ground water flow model that reproduces the measured hydraulic head data as closely as is statistically possible. An inverse method that includes prior information about the parameters (i.e., kriged log transmissivity) was applied to the Avra Valley aquifer of southern Arizona using hydraulic heads obtained in three ways: measured at well locations, estimated at nodes by hand contouring, and estimated at nodes by kriging. Hand contouring yields only estimates of hydraulic head at node points, whereas kriging yields hydraulic head estimates at node points and their corresponding estimation errors. A comparison of the three inverse applications indicates the variations in the ground water flow model caused by the different treatments of the hydraulic head data. Estimates of hydraulic head computed by all three inverse models were more representative of the measured or interpolated hydraulic heads than those computed using the kriged estimates of log transmissivity. The large-scale trends in the estimates of log transmissivity determined by the three inverse models were generally similar except in the southern portion of the study area. The hydraulic head values and gradients produced by the three inverse models were similar in the interior of the study area, while the major differences between the inverse models occurred along the boundaries. 17 refs., 18 figs., 1 tab

CROP YIELD AND CO2 FIXATION MONITORING IN ASIA USING A PHOTOSYNTHETICSTERILITY MODEL WITH SATELLITES AND METEOROLOGICAL DATA

Energy Technology Data Exchange (ETDEWEB)

Daijiro Kaneko [Department of Civil and Environmental Engineering, Matsue National College of Technology, Matsue (Japan); Toshiro Kumakura [Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka (Japan); Peng Yang [Laboratory of Resources Remote Sensing and Digital Agriculture, Ministry of Agriculture, Beijing (China)

2008-09-30

This study is intended to develop a model for estimating carbon dioxide (CO{sub 2}) fixation in the carbon cycle and for monitoring grain yields using a photosynthetic-sterility model, which integrates solar radiation and air temperature effects on photosynthesis, along with grain-filling from heading to ripening. Grain production monitoring would support orderly crisis management to maintain food security in Asia, which is facing climate fluctuation through this century of global warming. The author improved a photosynthesis-and-sterility model to compute both the crop yield and crop situation index CSI, which gives a percentage of rice yields compared to normal annual production. The model calculates photosynthesis rates including biomass effects, lowtemperature sterility, and high-temperature injury by incorporating solar radiation, effective air temperature, the normalized difference vegetation index NDVI, and the effect of temperature on photosynthesis by grain plant leaves. A decision-tree method classifies the distribution of crop fields in Asia using MODIS fundamental landcover and SPOT VEGETATION data, which include the Normalized Vegetation index (NDVI) and Land Surface Water Index (LSWI). This study provides daily distributions of the photosynthesis rate, which is the CO2 fixation in Asian areas combined with the land-cover distribution, the Japanese geostationary meteorological satellite (GMS), and meteorological re-analysis data by National Centers for Environmental Prediction (NCEP). The method is based on routine observation data, enabling automated monitoring of crop yields.

Dimension 7 operators in the b{yields}s transition

Energy Technology Data Exchange (ETDEWEB)

Chalons, G. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Theoretische Teilchenphysik; Domingo, F. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2013-03-15

We extend the low-energy effective field theory relevant for b{yields}s transitions up to operators of mass-dimension 7 and compute the associated anomalous-dimension matrix. We then compare our findings to the known results for dimension 6 operators and derive a solution for the renormalization group equations involving operators of dimension 7. We finally apply our analysis to a particularly simple case where the Standard Model is extended by an electroweak-magnetic operator and consider limits on this scenario from the decays B{sub s}{yields}{mu}{sup +}{mu}{sup -} and B{yields}K{nu} anti {nu}.

Assessing the impacts of climate change on rice yields in the main rice areas of China

International Nuclear Information System (INIS)

Yao, Fengmei; Xu, Yinglong; Lin, Erda; Yokozawa, Masayuki; Zhang, Jiahua

2007-01-01

This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within ± 10% of observed flowering duration and ± 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO2 direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO2 direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO2 direct effect on rice yield, rice yield increase in all selected stations

Assessing the impacts of climate change on rice yields in the main rice areas of China

Energy Technology Data Exchange (ETDEWEB)

Yao, Fengmei [College of Earth Sciences, The Graduate University of the Chinese Academy of Sciences, 19A, Yuquan Road, Beijing, 100049 (China); Xu, Yinglong; Lin, Erda [Agricultural Environment and Sustainable Development Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081 (China); Yokozawa, Masayuki [National Institute for Agro-environmental Sciences, Tsukuba 305-8604 (Japan); Zhang, Jiahua [Chinese Academy of Meteorological Sciences, Beijing, 100081 (China)

2007-02-15

This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within {+-} 10% of observed flowering duration and {+-} 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO2 direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO2 direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO2 direct effect on rice yield, rice yield increase in all selected stations.

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.)

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.

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

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.

Modelling soil erosion and associated sediment yield for small headwater catchments of the Daugava spillway valley, Latvia

Science.gov (United States)

Soms, Juris

2015-04-01

The accelerated soil erosion by water and associated fine sediment transfer in river catchments has various negative environmental as well as economic implications in many EU countries. Hence, the scientific community had recognized and ranked soil erosion among other environmental problems. Moreover, these matters might worsen in the near future in the countries of the Baltic Region, e.g. Latvia considering the predicted climate changes - more precisely, the increase in precipitation and shortening of return periods of extreme rainfall events, which in their turn will enable formation of surface runoff, erosion and increase of sediment delivery to receiving streams. Thereby it is essential to carry out studies focused on these issues in order to obtain reliable data in terms of both scientific and applied aims, e.g. environmental protection and sustainable management of soils as well as water resources. During the past decades, many of such studies of soil erosion had focused on the application of modelling techniques implemented in a GIS environment, allowing indirectly to estimate the potential soil losses and to quantify related sediment yield. According to research results published in the scientific literature, this approach currently is widely used all over the world, and most of these studies are based on the USLE model and its revised and modified versions. Considering that, the aim of this research was to estimate soil erosion rates and sediment transport under different hydro-climatic conditions in south-eastern Latvia by application of GIS-based modelling. For research purposes, empirical RUSLE model and ArcGIS software were applied, and five headwater catchments were chosen as model territories. The selected catchments with different land use are located in the Daugava spillway valley, which belongs to the upper Daugava River drainage basin. Considering lithological diversity of Quaternary deposits, a variety of soils can be identified, i.e., Stagnic

Implications of a visco-elastic model of the lithosphere for calculating yield strength envelopes

NARCIS (Netherlands)

Ershov, A.V.; Stephenson, R.A.

2006-01-01

The dominant deformation mechanism in the ductile part of the lithosphere is creep. From a mechanical point of view, creep can be modelled as a viscous phenomenon. On the other hand, yield-strength envelopes (YSEs), commonly used to describe lithosphere rheology, are constructed supposing creep to

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.

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

Simulation of corn yields and parameters uncertainties analysis in Hebei and Sichuang, China

Science.gov (United States)

Fu, A.; Xue, Y.; Hartman, M. D.; Chandran, A.; Qiu, B.; Liu, Y.

2016-12-01

Corn is one of most important agricultural production in China. Research on the impacts of climate change and human activities on corn yields is important in understanding and mitigating the negative effects of environmental factors on corn yields and maintaining the stable corn production. Using climatic data, including daily temperature, precipitation, and solar radiation from 1948 to 2010, soil properties, observed corn yields, and farmland management information, corn yields in Sichuang and Hebei Provinces of China in the past 63 years were simulated using the Daycent model, and the results was evaluated using Root mean square errors, bias, simulation efficiency, and standard deviation. The primary climatic factors influencing corn yields were examined, the uncertainties of climatic factors was analyzed, and the uncertainties of human activity parameters were also studied by changing fertilization levels and cultivated ways. The results showed that: (1) Daycent model is capable to simulate corn yields in Sichuang and Hebei provinces of China. Observed and simulated corn yields have the similar increasing trend with time. (2) The minimum daily temperature is the primary factor influencing corn yields in Sichuang. In Hebei Province, daily temperature, precipitation and wind speed significantly affect corn yields.(3) When the global warming trend of original data was removed, simulated corn yields were lower than before, decreased by about 687 kg/hm2 from 1992 to 2010; When the fertilization levels, cultivated ways were increased and decreased by 50% and 75%, respectively in the Schedule file in Daycent model, the simulated corn yields increased by 1206 kg/hm2 and 776 kg/hm2, respectively, with the enhancement of fertilization level and the improvement of cultivated way. This study provides a scientific base for selecting a suitable fertilization level and cultivated way in corn fields in China.

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)

Prediction of the Dynamic Yield Strength of Metals Using Two Structural-Temporal Parameters

Science.gov (United States)

Selyutina, N. S.; Petrov, Yu. V.

2018-02-01

The behavior of the yield strength of steel and a number of aluminum alloys is investigated in a wide range of strain rates, based on the incubation time criterion of yield and the empirical models of Johnson-Cook and Cowper-Symonds. In this paper, expressions for the parameters of the empirical models are derived through the characteristics of the incubation time criterion; a satisfactory agreement of these data and experimental results is obtained. The parameters of the empirical models can depend on some strain rate. The independence of the characteristics of the incubation time criterion of yield from the loading history and their connection with the structural and temporal features of the plastic deformation process give advantage of the approach based on the concept of incubation time with respect to empirical models and an effective and convenient equation for determining the yield strength in a wider range of strain rates.

African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption

Science.gov (United States)

van der Velde, Marijn; Folberth, Christian; Balkovič, Juraj; Ciais, Philippe; Fritz, Steffen; Janssens, Ivan A.; Obersteiner, Michael; See, Linda; Skalský, Rastislav; Xiong, Wei; Peñuealas, Josep

2014-05-01

The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N:P applications under low, medium, and high input scenarios, for past (1975), current, and future N:P mass ratios of respectively, 1:0.29, 1:0.15, and 1:0.05. At low N inputs (10 kg/ha), current yield deficits amount to 10% but will increase up to 27% under the assumed future N:P ratio, while at medium N inputs (50 kg N/ha), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N:P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1:0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.

Study of pp{yields}pp{eta} reaction at threshold; Etude de la reaction pp{yields}pp{eta} au seuil

Energy Technology Data Exchange (ETDEWEB)

Taleb, A

1994-11-01

The {eta} production has been studied through the pp {yields} pp{eta} reaction at threshold. Data were taken at the Synchrotron of the ``Laboratoire National Saturne``. The detection in coincidence of the two protons scattered near 0 deg and analysed with the magnetic spectrometer SPES3 allows the reconstruction of missing mass spectra for the {eta} signature. A simulation program which takes into account all the experimental set up characteristics has been realized and tested through the pp {yields} d{pi}{sup +} reaction detected simultaneously with pp {yields} pp{eta}. The generated proton momentum spectra for pp {yields} pp{eta} show a pronounced {eta} mass dependence. This characteristic, connected to the kinematical properties of pp {yields} pp{eta} at threshold, is used to extract the mass of the meson {eta}. The obtained value, m{sub {eta}} = 547.65 {+-} 0.18 MeV, is in good agreement with measurement done recently through the pd {yields} {sup H}e{eta} reaction. The total cross section {sigma}{sub t} of pp {yields} pp{eta} measured at 1260, 1265 and 1300 MeV presents a strong energy dependence. This cross section increases less with energy than the phase-space. The influence of p-p and {eta}-p final state interactions in our measurements is studied. Our results are compared with theoretical predictions and assess the dominant character of the baryonic resonance N{sup *}(1535) in the {eta} mechanism production at threshold. These experimental results give an energy dependence which is not well reproduced by the theoretical predictions. This discrepancy could be an incorrect description of the {eta}-p interaction in the models. (author). 48 refs., 60 figs., 15 tabs.

Status of fission yield data

International Nuclear Information System (INIS)

England, T.R.; Blachot, J.

1988-01-01

In this paper we summarize the current status of the recent US evaluation for 34 fissioning nuclides at one or more neutron incident energies and for spontaneous fission. Currently there are 50 yields sets, and for each we have independent and cumulative yields and uncertainties for approximately 1100 fission products. When finalized the recommended data will become part of Version VI of the US ENDF/B. Other major evaluations in progress that are included in a recently formed IAEA Coordinated Research Program are also summarized. In a second part we review two empirical models in use to estimate independent yields. Comparison of model estimates with measured data is presented, including a comparison with some recent data obtained from Lohengrin (Cf-249 T). 18 refs., 13 figs., 3 tabs

Crop insurance demand in wheat production: focusing on yield gaps and asymmetric information

International Nuclear Information System (INIS)

Castañeda-Vera, A.; Saa-Requejo, A.; Mínguez, I.; Garrido, A.

2017-01-01

Analysis of yield gaps were conducted in the context of crop insurance and used to build an indicator of asymmetric information. The possible influence of asymmetric information in the decision of Spanish wheat producers to contract insurance was additionally evaluated. The analysis includes simulated yield using a validated crop model, CERES-Wheat previously selected among others, whose suitability to estimate actual risk when no historical data are available was assessed. Results suggest that the accuracy in setting the insured yield is decisive in farmers’ willingness to contract crop insurance under the wider coverage. Historical insurance data, when available, provide a more robust technical basis to evaluate and calibrate insurance parameters than simulated data, using crop models. Nevertheless, the use of crop models might be useful in designing new insurance packages when no historical data is available or to evaluate scenarios of expected changes. In that case, it is suggested that yield gaps be estimated and considered when using simulated attainable yields.

Crop insurance demand in wheat production: focusing on yield gaps and asymmetric information

Energy Technology Data Exchange (ETDEWEB)

Castañeda-Vera, A.; Saa-Requejo, A.; Mínguez, I.; Garrido, A.

2017-07-01

Analysis of yield gaps were conducted in the context of crop insurance and used to build an indicator of asymmetric information. The possible influence of asymmetric information in the decision of Spanish wheat producers to contract insurance was additionally evaluated. The analysis includes simulated yield using a validated crop model, CERES-Wheat previously selected among others, whose suitability to estimate actual risk when no historical data are available was assessed. Results suggest that the accuracy in setting the insured yield is decisive in farmers’ willingness to contract crop insurance under the wider coverage. Historical insurance data, when available, provide a more robust technical basis to evaluate and calibrate insurance parameters than simulated data, using crop models. Nevertheless, the use of crop models might be useful in designing new insurance packages when no historical data is available or to evaluate scenarios of expected changes. In that case, it is suggested that yield gaps be estimated and considered when using simulated attainable yields.

Anisotropic yield surfaces in bi-axial cyclic plasticity

International Nuclear Information System (INIS)

Rider, R.J.; Harvey, S.J.; Breckell, T.H.

1985-01-01

Some aspects of the behaviour of yield surfaces and work-hardening surfaces occurring in biaxial cyclic plasticity have been studied experimentally and theoretically. The experimental work consisted of subjecting thin-walled tubular steel specimens to cyclic plastic torsion in the presence of sustained axial loads of various magnitudes. The experimental results show that considerable anisotropy is induced when the cyclic shear strains are dominant. Although the true shapes of yield and work-hardening surfaces can be very complex, a mathematical model is presented which includes both anisotropy and Bauschinger effects. The model is able to qualitatively predict the deformation patterns during a cycle of applied plastic shear strain for a range of sustained axial stresses and also indicate the material response to changes in axial stress. (orig.)

Fission product yield data for the transmutation of minor actinide nuclear waste

International Nuclear Information System (INIS)

2008-04-01

dependences and they were adapted in the course of the CRP to predict fission product yields. The valuable role of the CRP in such work became evident during the meetings, at which the discussions formed a fruitful basis for improvements to the models. The benchmark exercise revealed the true worth and predictive capabilities of the systematics and theoretical models developed during the course of the CRP. Necessary improvements and the direction of future studies were also revealed. These models have the potential to give reliable predictions after implementation of the improvements suggested in this report. A brief introduction and the various studies undertaken by individual participants are given at the beginning of this publication, followed by a detailed description of the resulting overall achievements, conclusions and recommendations of the CRP and a summary of the benchmark exercise and results. Additional material is included on the enclosed CD-ROM, including compilations of the fission product yields, unedited papers and all details of the benchmark exercise

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

Directory of Open Access Journals (Sweden)

Kaare Græsbøll

2016-12-01

Full Text Available Typically, central milk recording data from dairy herds are recorded less than monthly. Over-fitting early in lactation periods is a challenge, which we explored in different ways by reducing the number of parameters needed to describe the milk yield and somatic cell count of individual cows. 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 (SCC for fitting to sparse data to parameterise herd- and cow-specific simulation of dairy herds.Data from 610 Danish Holstein herds were used to determine parity traits in milk production regarding milk yield and SCC of individual cows. Parity was stratified in first, second and third and higher for milk, and first to sixth and higher for SCC. Fitting of herd level parameters allowed for cow level lactation curves with three, two or one-parameters per lactation. Correlations of milk yield and SCC were estimated between lactations and between dam and offspring.The shape of the lactation curves varied markedly between farms. The correlation between lactations for milk yield and SCC were 0.2-0.6 and significant on more than 95% of farms. The variation in the daily milk yield was observed to be a source of variation to the SCC, and the total SCC was less correlated with the milk production than somatic cells per ml. A positive correlation was found between relative levels of the total SCC and the milk yield.The variation of lactation and SCC curves between farms highlights the importance of a herd level approach. The one-parameter per cow model 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

Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

Science.gov (United States)

Mann, M.; Warner, J.

2015-12-01

Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

Science.gov (United States)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

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.

Simulating maize yield and bomass with spatial variability of soil field capacity

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Derivation of ozone flux-yield relationships for lettuce: A key horticultural crop

International Nuclear Information System (INIS)

Goumenaki, Eleni; Fernandez, Ignacio Gonzalez; Papanikolaou, Antigoni; Papadopoulou, Despoina; Askianakis, Christos; Kouvarakis, George; Barnes, Jeremy

2007-01-01

Ozone flux-response relationships were derived for lettuce, employing a multiplicative approach to model the manner in which stomatal conductance is influenced by key environmental variables, using a dataset collected during field experimentation in Crete and yield-response relationships derived from parallel open-top chamber experiments. Regional agronomic practices were adopted throughout. Computed versus measured data revealed that the derived model explained 51% (P -2 s -1 . Regressions employing very low or zero flux thresholds resulted in the strongest yield-flux relationships (explaining ∼80% (P < 0.05) of the variation in the dataset). - Establishment of ozone flux-yield relationships for a commercially-important horticultural crop grown widely in the Mediterranean

Fluence-dependent sputtering yield of micro-architectured materials

Energy Technology Data Exchange (ETDEWEB)

Matthes, Christopher S.R.; Ghoniem, Nasr M., E-mail: ghoniem@ucla.edu; Li, Gary Z.; Matlock, Taylor S.; Goebel, Dan M.; Dodson, Chris A.; Wirz, Richard E.

2017-06-15

Highlights: • Sputtering yield is shown to be transient and heavily dependent on surface architecture. • Fabricated nano- and Microstructures cause geometric re-trapping of sputtered material, which leads to a self-healing mechanism. • Initially, the sputtering yield of micro-architectured Mo is approximately 1/2 the value as that of a planar surface. • The study demonstrates that the sputtering yield is a dynamic property, dependent on the surface structure of a material. • A developed phenomenological model mathematically describes the transient behavior of the sputtering yield as a function of plasma fluence. - Abstract: We present an experimental examination of the relationship between the surface morphology of Mo and its instantaneous sputtering rate as function of low-energy plasma ion fluence. We quantify the dynamic evolution of nano/micro features of surfaces with built-in architecture, and the corresponding variation in the sputtering yield. Ballistic deposition of sputtered atoms as a result of geometric re-trapping is observed, and re-growth of surface layers is confirmed. This provides a self-healing mechanism of micro-architectured surfaces during plasma exposure. A variety of material characterization techniques are used to show that the sputtering yield is not a fundamental property, but that it is quantitatively related to the initial surface architecture and to its subsequent evolution. The sputtering yield of textured molybdenum samples exposed to 300 eV Ar plasma is roughly 1/2 of the corresponding value for flat samples, and increases with ion fluence. Mo samples exhibited a sputtering yield initially as low as 0.22 ± 5%, converging to 0.4 ± 5% at high fluence. The sputtering yield exhibits a transient behavior as function of the integrated ion fluence, reaching a steady-state value that is independent of initial surface conditions. A phenomenological model is proposed to explain the observed transient sputtering phenomenon, and to

A Remote Sensing Based Forage Biomass Yield Inversion Model of Alpine-cold Meadow during Grass-withering Period in Sanjiangyuan Area

International Nuclear Information System (INIS)

Song, Weize; Jia, Haifeng; Liang, Shidong; Wang, Zheng; Liu, Shujie; Hao, Lizhuang; Chai, Shatuo

2014-01-01

Estimating forage biomass yield remotely from space is still challenging nowadays. Field experiments were conducted and ground measurements correlated to remote sensing data to estimate the forage biomass yield of Alpine-cold meadow grassland during the grass and grass-withering period in Sanjiangyuan area in Yushu county. Both Shapiro-Wilk and Kolmogorov-Smirnov two-tailed tests showed that the field training samples are normally distributed, the Spearman coefficient indicated that the parametric correlation analysis had significant differences. The optimal regression models were developed based on the Landsat Thematic Mapper Normalized Difference Vegetation Index (TM-NDVI) and the forage biomass field data during the grass and the grass-withering periods, respectively. Then an integration model was used to predict forage biomass yield of alpine-cold meadow in the grass-withering period. The model showed good prediction accuracy and reliability. It was found that this approach can not only estimate forage yield in large scale efficiently but also overcome the seasonal limitation of remote sensing inversion. This technique can provides valuable guidance to animal husbandry to resource more efficiently in winter

Slope Controls Grain Yield and Climatic Yield in Mountainous Yunnan province, China

Science.gov (United States)

Duan, X.; Rong, L.; Gu, Z.; Feng, D.

2017-12-01

Mountainous regions are increasingly vulnerable to food insecurity because of limited arable land, growing population pressure, and climate change. Development of sustainable mountain agriculture will require an increased understanding of the effects of environmental factors on grain and climatic yields. The objective of this study was to explore the relationships between actual grain yield, climatic yield, and environmental factors in a mountainous region in China. We collected data on the average grain yield per unit area in 119 counties in Yunnan province from 1985 to 2012, and chose 17 environmental factors for the same period. Our results showed that actual grain yield ranged from 1.43 to 6.92 t·ha-1, and the climatic yield ranged from -0.15 to -0.01 t·ha-1. Lower climatic yield but higher grain yield was generally found in central areas and at lower slopes and elevations in the western and southwestern counties of Yunnan province. Higher climatic yield but lower grain yield were found in northwestern parts of Yunnan province on steep slopes. Annual precipation and temperature had a weak influence on the climatic yield. Slope explained 44.62 and 26.29% of the variation in grain yield and climatic yield. The effects of topography on grain and climatic yields were greater than climatic factors. Slope was the most important environmental variable for the variability in climatic and grain yields in the mountainous Yunnan province due to the highly heterogeneous topographic conditions. Conversion of slopes to terraces in areas with higher climatic yields is an effective way to maintain grain production in response to climate variability. Additionally, soil amendments and soil and water conservation measures should be considered to maintain soil fertility and aid in sustainable development in central areas, and in counties at lower slopes and elevations in western and southwestern Yunnan province.

Correlation maps to assess soybean yield from EVI data in Paraná State, Brazil

Directory of Open Access Journals (Sweden)

Gleyce Kelly Dantas Araújo Figueiredo

Full Text Available ABSTRACT Vegetation indices are widely used to monitor crop development and generally used as input data in models to forecast yield. The first step of this study consisted of using monthly Maximum Value Composites to create correlation maps using Enhanced Vegetation Index (EVI from Moderate Resolution Imaging Spectroradiometer (MODIS sensor mounted on Terra satellite and historical yield during the soybean crop cycle in Paraná State, Brazil, from 2000/2001 to 2010/2011. We compared the ability of forecasting crop yield based on correlation maps and crop specific masks. We ran a preliminary regression model to test its ability on yield estimation for four municipalities during the soybean growing season. A regression model was developed for both methodologies to forecast soybean crop yield using leave-one-out cross validation. The Root Mean Squared Error (RMSE values in the implementation of the model ranged from 0.037 t ha−1 to 0.19 t ha−1 using correlation maps, while for crop specific masks, it varied from 0.21 t ha−1 to 0.35 t ha−1. The model was able to explain 96 % to 98 % of the variance in estimated yield from correlation maps, while it was able to explain only 2 % to 67 % for crop specific mask approach. The results showed that the correlation maps could be used to predict crop yield more effectively than crop specific masks. In addition, this method can provide an indication of soybean yield prior to harvesting.

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

Directory of Open Access Journals (Sweden)

José Eduardo Boffino de Almeida Monteiro

2013-02-01

Full Text Available The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1' ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.

Comparison of winter wheat yield sensitivity to climate variables under irrigated and rain-fed conditions

Science.gov (United States)

Xiao, Dengpan; Shen, Yanjun; Zhang, He; Moiwo, Juana P.; Qi, Yongqing; Wang, Rende; Pei, Hongwei; Zhang, Yucui; Shen, Huitao

2016-09-01

Crop simulation models provide alternative, less time-consuming, and cost-effective means of determining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat ( Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (CO2) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCP. The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCP. There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2°C was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1°C decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rainfed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to 560 ppm, and yield under YY increased linearly by ≈7.0% for the same increase in CO2 concentration.

Multiscale simulation of yield strength in reduced-activation ferritic/martensitic steel

Energy Technology Data Exchange (ETDEWEB)

Wang, Chen Chong; Zhang, Chi; Yang, Zhigang [Key Laboratory of Advanced Materials of Ministry of Education, School of Materials Science and Engineering, Tsinghua University, Beijing (China); Zhao, Ji Jun [State Key Laboratory of Materials Modification by Laser, Electron, and Ion Beams, School of Physics and Optoelectronic Technology and College of Advanced Science and Technology, Dalian University of Technology, Dalian (China)

2017-04-15

One of the important requirements for the application of reduced-activation ferritic/martensitic (RAFM) steel is to retain proper mechanical properties under irradiation and high-temperature conditions. To simulate the yield strength and stress-strain curve of steels during high-temperature and irradiation conditions, a multiscale simulation method consisting of both microstructure and strengthening simulations was established. The simulation results of microstructure parameters were added to a superposition strengthening model, which consisted of constitutive models of different strengthening methods. Based on the simulation results, the strength contribution for different strengthening methods at both room temperature and high-temperature conditions was analyzed. The simulation results of the yield strength in irradiation and high-temperature conditions were mainly consistent with the experimental results. The optimal application field of this multiscale model was 9Cr series (7–9 wt.%Cr) RAFM steels in a condition characterized by 0.1–5 dpa (or 0 dpa) and a temperature range of 25–500°C.

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.

Yield stress of alumina-zirconia suspensions

International Nuclear Information System (INIS)

Ramakrishnan, V.; Pradip; Malghan, S.G.

1996-01-01

The yield stress of concentrated suspensions of alumina, zirconia, and mixed alumina-zirconia powders was measured by the vane technique as a function of solids loading, relative amounts of alumina and zirconia, and pH. At the isoelectric point (IEP), the yield stress varied as the fourth power of the solids loading. The relative ratio of alumina and zirconia particles was important in determining the yield stress of the suspension at the IEP. The yield stress of single and mixed suspensions showed a marked variation with pH. The maximum value occurred at or near the IEP of the suspension. The effect of electrical double-layer forces on the yield stress can be described on the basis of the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. A normalized yield stress--that is, the ratio of the yield stress at a given pH to the yield stress at the IEP predicted by this model--showed good correlation with experimental data

Mapping Smallholder Wheat Yields and Sowing Dates Using Micro-Satellite Data

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Meha Jain

2016-10-01

Full Text Available Remote sensing offers a low-cost method for developing spatially continuous crop production statistics across large areas and through time. Nevertheless, it has been difficult to characterize the production of individual smallholder farms, given that the land-holding size in most areas of South Asia (<2 ha is smaller than the spatial resolution of most freely available satellite imagery, like Landsat and MODIS. In addition, existing methods to map yield require field-level data to develop and parameterize predictive algorithms that translate satellite vegetation indices to yield, yet these data are costly or difficult to obtain in many smallholder systems. To overcome these challenges, this study explores two issues. First, we employ new high spatial (2 m and temporal (bi-weekly resolution micro-satellite SkySat data to map sowing dates and yields of smallholder wheat fields in Bihar, India in the 2014–2015 and 2015–2016 growing seasons. Second, we compare how well we predict sowing date and yield when using ground data, like crop cuts and self-reports, versus using crop models, which require no on-the-ground data, to develop and parameterize prediction models. Overall, sow dates were predicted well (R2 = 0.41 in 2014–2015 and R2 = 0.62 in 2015–2016, particularly when using models that were parameterized using self-report sow dates collected close to the time of planting and when using imagery that spanned the entire growing season. We were also able to map yields fairly well (R2 = 0.27 in 2014–2015 and R2 = 0.33 in 2015–2016, with crop cut parameterized models resulting in the highest accuracies. While less accurate, we were able to capture the large range in sow dates and yields across farms when using models parameterized with crop model data and these estimates were able to detect known relationships between management factors (e.g., sow date, fertilizer, and irrigation and yield. While these results are specific to our study

Manufacturing of par-fried french-fries. Part 2: Modelling yield efficiency of peeling

NARCIS (Netherlands)

Somsen, D.J.; Capelle, A.; Tramper, J.

2004-01-01

The paper outlines the yield efficiency of steam peeling. It was proven that peeling potatoes manually with sandpaper results in the lowest possible peel losses. These losses were desired or wanted losses. However, in practice steam peeling results not only in wanted losses but also in substantial

Clinical and pathologic factors affecting lymph node yields in colorectal cancer.

Directory of Open Access Journals (Sweden)

Ta-Wen Hsu

Full Text Available OBJECTIVE: Lymph node yield is recommended as a benchmark of quality care in colorectal cancer. The objective of this study was to evaluate the impact of various factors upon lymph node yield and to identify independent factors associated with lymph node harvest. MATERIALS AND METHODS: The records of 162 patients with Stage I to Stage III colorectal cancers seen in one institution were reviewed. These patients underwent radical surgery as definitive therapy; high-risk patients then received adjuvant treatment. Pathologic and demographic data were recorded and analyzed. The subgroup analysis of lymph node yields was determined using a t-test and analysis of variants. Linear regression model and multivariable analysis were used to perform potential confounding and predicting variables. RESULTS: Five variables had significant association with lymph node yield after adjustment for other factors in a multiple linear regression model. These variables were: tumor size, surgical method, specimen length, and individual surgeon and pathologist. The model with these five significant variables interpreted 44.4% of the variation. CONCLUSIONS: Patients, tumor characteristics and surgical variables all influence the number of lymph nodes retrieved. Physicians are the main gatekeepers. Adequate training and optimized guidelines could greatly improve the quality of lymph node yields.

Effect of sulfur and iron fertilizers on yield, yield components and ...

African Journals Online (AJOL)

Jane

2011-06-13

Jun 13, 2011 ... per plant. Interaction between water stress and combination of iron and sulfur fertilizers had significant .... Results of analysis of variance (ANOVA) of water stress (W), sulfur (B) and iron (C), and their interaction with gain yield, yield components and ... the soil structure and it increased the usefulness of other.

Single Degenerate Models for Type Ia Supernovae: Progenitor's Evolution and Nucleosynthesis Yields

Science.gov (United States)

Nomoto, Ken'ichi; Leung, Shing-Chi

2018-06-01

We review how the single degenerate models for Type Ia supernovae (SNe Ia) works. In the binary star system of a white dwarf (WD) and its non-degenerate companion star, the WD accretes either hydrogen-rich matter or helium and undergoes hydrogen and helium shell-burning. We summarize how the stability and non-linear behavior of such shell-burning depend on the accretion rate and the WD mass and how the WD blows strong wind. We identify the following evolutionary routes for the accreting WD to trigger a thermonuclear explosion. Typically, the accretion rate is quite high in the early stage and gradually decreases as a result of mass transfer. With decreasing rate, the WD evolves as follows: (1) At a rapid accretion phase, the WD increase its mass by stable H burning and blows a strong wind to keep its moderate radius. The wind is strong enough to strip a part of the companion star's envelope to control the accretion rate and forms circumstellar matter (CSM). If the WD explodes within CSM, it is observed as an "SN Ia-CSM". (X-rays emitted by the WD are absorbed by CSM.) (2) If the WD continues to accrete at a lower rate, the wind stops and an SN Ia is triggered under steady-stable H shell-burning, which is observed as a super-soft X-ray source: "SN Ia-SSXS". (3) If the accretion continues at a still lower rate, H shell-burning becomes unstable and many flashes recur. The WD undergoes recurrent nova (RN) whose mass ejection is smaller than the accreted matter. Then the WD evolves to an "SN Ia-RN". (4) If the companion is a He star (or a He WD), the accretion of He can trigger He and C double detonations at the sub-Chandrasekhar mass or the WD grows to the Chandrasekhar mass while producing a He-wind: "SN Ia-He CSM". (5) If the accreting WD rotates quite rapidly, the WD mass can exceed the Chandrasekhar mass of the spherical WD, which delays the trigger of an SN Ia. After angular momentum is lost from the WD, the (super-Chandra) WD contracts to become a delayed SN Ia

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

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.

Changes in yields and their variability at different levels of global warming

Science.gov (United States)

Childers, Katelin

2015-04-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the political discussion about mitigation targets as well as for the inclusion of climate change impacts in Integrated Assessment Models (IAMs) that generally only provide global mean temperature change as an indicator of climate change. While there is a well-established framework for the scalability of regional temperature and precipitation changes with global mean temperature change we provide an assessment of the extent to which impacts such as crop yield changes can also be described in terms of global mean temperature changes without accounting for the specific underlying emissions scenario. Based on multi-crop-model simulations of the four major cereal crops (maize, rice, soy, and wheat) on a 0.5 x 0.5 degree global grid generated within ISI-MIP, we show the average spatial patterns of projected crop yield changes at one half degree warming steps. We find that emissions scenario dependence is a minor component of the overall variance of projected yield changes at different levels of global warming. Furthermore, scenario dependence can be reduced by accounting for the direct effects of CO2 fertilization in each global climate model (GCM)/impact model combination through an inclusion of the global atmospheric CO2 concentration as a second predictor. The choice of GCM output used to force the crop model simulations accounts for a slightly larger portion of the total yield variance, but the greatest contributor to variance in both global and regional crop yields and at all levels of warming, is the inter-crop-model spread. The unique multi impact model ensemble available with ISI-MIP data also indicates that the overall variability of crop yields is projected to increase in conjunction with increasing global mean temperature. This result is consistent throughout the ensemble of impact models and across many world regions. Such a hike in yield volatility could have

Bulk yields of nucleosynthesis from massive stars

International Nuclear Information System (INIS)

Arnett, W.D.

1978-01-01

Preliminary estimates are made of the absolute yields of abundant nuclei synthesized in observed stars. The compositions of nine helium stars of mass 3 or =10M/sub sun/ is estimated. A variety of choices for the initial mass function (IMF) are used to calculate the yield per stellar generation. For standard choices of the (IMF) the absolute and relative yields of 12 C, 16 O, 20 Ne, 24 Mg, the Si to Ca group, and the iron group agree with solar system values, to the accuracy of the calculations. The relative yields are surprisingly insensitive to the slope of the IMF. In a second approach, using standard estimates (Ostriker, Richstone, and Thuan) for the current rate of stellar death, I find the present rate of nucleosynthesis in the solar neighborhood to be about 10%of the average rate over galactic history. This result is consistent with many standard models of galactic evolution (for example, the Schmidt model in which star formation goes as gas density squared). It appears that if the star formation rate is high enough to produce the stars we see around us, then the nucleosynthesis rate is large enough to produce the processed nuclei (except 4 He) seen in those stars. The typical nucleosynthesis source is massive (Mapprox. =30 M/sub sun/); the death rate of such stars is a small fraction (3-10%) of recent estimates of the total rate of supernovae

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.

Modeling contribution of shallow groundwater to evapotranspiration and yield of maize in an arid area.

Science.gov (United States)

Gao, Xiaoyu; Huo, Zailin; Qu, Zhongyi; Xu, Xu; Huang, Guanhua; Steenhuis, Tammo S

2017-02-21

Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m 3 . The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater.

Dynamic growth and yield model for Black pine stands in Spain

Energy Technology Data Exchange (ETDEWEB)

Mora, J. V.; Rio, M. del; Bravo-Oviedo, A.

2012-07-01

In a forestry context, modelling stand development over time relies on estimates of different stand characteristics obtained from equations which usually constitute a multivariate system. In this study we have developed a stand growth model for even-aged stands of Black pine (Pinus nigra Arn.) in Spain. The 53 plots used to fit the equations came from the permanent sample plot network established by the Forest Research Centre (INIA) in 1963 and 1964 in the main distribution regions of Black pine. The model is made up of a system of equations to predict growth and yield in volume and basal area. In the fitting phase we took into account the correlation between the measurements within the same plot and the cross-equation residual correlations. The model incorporates a control function to estimate the thinning effect and a function for predicting the reduction in tree number due to regular mortality. In addition, we use the three parameter Weibull distribution function to estimate the number of trees in each diameter class by recovering the parameters using the moment method. The developed model is useful for simulating the evolution of even-aged stands with and without thinnings and allows the estimation of number of trees by diameter classes. (Author) 44 refs.

Climate impacts on palm oil yields in the Nigerian Niger Delta

Science.gov (United States)

Okoro, Stanley U.; Schickhoff, Udo; Boehner, Juergen; Schneider, Uwe A.; Huth, Neil

2016-04-01

Palm oil production has increased in recent decades and is estimated to increase further. The optimal role of palm oil production, however, is controversial because of resource conflicts with alternative land uses. Local conditions and climate change affect resource competition and the desirability of palm oil production. Based on this, crop yield simulations using different climate model output under different climate scenarios could be important tool in addressing the problem of uncertainty quantification among different climate model outputs. Previous studies on this region have focused mostly on single experimental fields, not considering variations in Agro-Ecological Zones, climatic conditions, varieties and management practices and, in most cases not extending to various IPCC climate scenarios and were mostly based on single climate model output. Furthermore, the uncertainty quantification of the climate- impact model has rarely been investigated on this region. To this end we use the biophysical simulation model APSIM (Agricultural Production Systems Simulator) to simulate the regional climate impact on oil palm yield over the Nigerian Niger Delta. We also examine whether the use of crop yield model output ensemble reduces the uncertainty rather than the use of climate model output ensemble. The results could serve as a baseline for policy makers in this region in understanding the interaction between potentials of energy crop production of the region as well as its food security and other negative feedbacks that could be associated with bioenergy from oil palm. Keywords: Climate Change, Climate impacts, Land use and Crop yields.

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield.

Directory of Open Access Journals (Sweden)

Meike T Wortel

2018-02-01

Full Text Available Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.

Accelerated yield learning in agressive lithography

Science.gov (United States)

Monahan, Kevin M.; Ashkenaz, Scott M.; Chen, Xing; Lord, Patrick J.; Merrill, Mark A.; Quattrini, Rich; Wiley, James N.

2000-06-01

As exposure wavelengths decrease from 248 nm to 193, 157, and even 13 nm (EUV), small process defects can cause collapse of the lithographic process window near the limits of resolution, particularly for the gate and contact structures in high- performance devices. Such sensitivity poses a challenge for lithography process module control. In this work, we show that yield loss can be caused by a combination of macro, micro, CD, and overlay defects. A defect is defined as any yield- affecting process variation. Each defect, regardless of cause, is assumed to have a specific 'kill potential.' The accuracy of the lithographic yield model can be improved by identifying those defects with the highest kill potential or, more importantly, those that pose the highest economic risk. Such economic considerations have led us to develop a simple heuristic model for understanding sampling strategies in defect metrology and for linking metrology capability to yield and profitability.

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.

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

Science.gov (United States)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

Optomechanical Control of Quantum Yield in Trans-Cis Ultrafast Photoisomerization of a Retinal Chromophore Model.

Science.gov (United States)

Valentini, Alessio; Rivero, Daniel; Zapata, Felipe; García-Iriepa, Cristina; Marazzi, Marco; Palmeiro, Raúl; Fdez Galván, Ignacio; Sampedro, Diego; Olivucci, Massimo; Frutos, Luis Manuel

2017-03-27

The quantum yield of a photochemical reaction is one of the most fundamental quantities in photochemistry, as it measures the efficiency of the transduction of light energy into chemical energy. Nature has evolved photoreceptors in which the reactivity of a chromophore is enhanced by its molecular environment to achieve high quantum yields. The retinal chromophore sterically constrained inside rhodopsin proteins represents an outstanding example of such a control. In a more general framework, mechanical forces acting on a molecular system can strongly modify its reactivity. Herein, we show that the exertion of tensile forces on a simplified retinal chromophore model provokes a substantial and regular increase in the trans-to-cis photoisomerization quantum yield in a counterintuitive way, as these extension forces facilitate the formation of the more compressed cis photoisomer. A rationale for the mechanochemical effect on this photoisomerization mechanism is also proposed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Simulating the effect of vegetation cover on the sediment yield of mediterranean catchments using SHETRAN

Science.gov (United States)

Lukey, B. T.; Sheffield, J.; Bathurst, J. C.; Lavabre, J.; Mathys, N.; Martin, C.

1995-08-01

The sediment yield of two catchments in southern France was modelled using the newly developed sediment code of SHETRAN. A fire in August 1990 denuded the Rimbaud catchment, providing an opportunity to study the effect of vegetation cover on sediment yield by running the model for both pre-and post-fire cases. Model output is in the form of upper and lower bounds on sediment discharge, reflecting the uncertainty in the erodibility of the soil. The results are encouraging since measured sediment discharge falls largely between the predicted bounds, and simulated sediment yield is dramatically lower for the catchment before the fire which matches observation. SHETRAN is also applied to the Laval catchment, which is subject to Badlands gulley erosion. Again using the principle of generating upper and lower bounds on sediment discharge, the model is shown to be capable of predicting the bulk sediment discharge over periods of months. To simulate the effect of reforestation, the model is run with vegetation cover equivalent to a neighbouring fully forested basin. The results obtained indicate that SHETRAN provides a powerful tool for predicting the impact of environmental change and land management on sediment yield.

Measurements of fission yields

International Nuclear Information System (INIS)

Denschlag, H.O.

2000-01-01

After some historical introductory remarks on the discovery of nuclear fission and early fission yield determinations, the present status of knowledge on fission yields is briefly reviewed. Practical and fundamental reasons motivating the pursuit of fission yield measurements in the coming century are pointed out. Recent results and novel techniques are described that promise to provide new interesting insights into the fission process during the next century. (author)

Simulation of water management for fodder beet to reduce yield losses under late season drought

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T. Noreldin

2016-12-01

Full Text Available The objectives of this study were to calibrate CropSyst model for fodder beet grown under full and late season drought and to use the simulation results to analyze the relationship between irrigation amount and yield, as well as in water management to reduce yield losses under full and late season drought. For this reason, two field experiments were implemented at El-Serw Agricultural Research Station in Demiatte governorate, during 2011/12 and 2012/13 growing seasons. Two irrigation treatments were studied: full irrigation and late season drought. The model was calibrated using the data obtained from the two seasons. Results indicated that the reduction in fodder beet yield under late season drought was 11 and 12% in 2011/12 and 2012/13 growing seasons, respectively. Calibration of CropSyst revealed that the percentage of difference between measured and predicted values were low in both growing seasons. The results also indicated that changing irrigation schedule after examining water stress index under full and late season drought led to increase in fodder beet yield, as well as water and land productivity. Thus, CropSyst model can give insight into when to apply irrigation water to minimize yield losses under late season drought.

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

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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

Yield gap mapping as a support tool for risk management in agriculture

Science.gov (United States)

Lahlou, Ouiam; Imani, Yasmina; Slimani, Imane; Van Wart, Justin; Yang, Haishun

2016-04-01

The increasing frequency and magnitude of droughts in Morocco and the mounting losses from extended droughts in the agricultural sector emphasized the need to develop reliable and timely tools to manage drought and to mitigate resulting catastrophic damage. In 2011, Morocco launched a cereals multi-risk insurance with drought as the most threatening and the most frequent hazard in the country. However, and in order to assess the gap and to implement the more suitable compensation, it is essential to quantify the potential yield in each area. In collaboration with the University of Nebraska-Lincoln, a study is carried out in Morocco and aims to determine the yield potentials and the yield gaps in the different agro-climatic zones of the country. It fits into the large project: Global Yield Gap and Water Productivity Atlas: http://www.yieldgap.org/. The yield gap (Yg) is the magnitude and difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual yields, reached by farmers. World Food Studies (WOFOST), which is a Crop simulation mechanistic model, has been used for this purpose. Prior to simulations, reliable information about actual yields, weather data, crop management data and soil data have been collected in 7 Moroccan buffer zones considered, each, within a circle of 100 km around a weather station point, homogenously spread across the country and where cereals are widely grown. The model calibration was also carried out using WOFOST default varieties data. The map-based results represent a robust tool, not only for drought insurance organization, but for agricultural and agricultural risk management. Moreover, accurate and geospatially granular estimates of Yg and Yw will allow to focus on regions with largest unexploited yield gaps and greatest potential to close them, and consequently to improve food security in the country.

Using Ridge Regression Models to Estimate Grain Yield from Field Spectral Data in Bread Wheat (Triticum Aestivum L. Grown under Three Water Regimes

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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.

Comments on the Dutton-Puls model: Temperature and yield stress dependences of crack growth rate in zirconium alloys

International Nuclear Information System (INIS)

Kim, Young S.

2010-01-01

Research highlights: → This study shows first that temperature and yield stress dependences of crack growth rate in zirconium alloys can analytically be understood not by the Dutton-Puls model but by Kim's new DHC model. → It is demonstrated that the driving force for DHC is ΔC, not the stress gradient, which is the core of Kim's DHC model. → The Dutton-Puls model reveals the invalidity of Puls' claim that the crack tip solubility would increase to the cooling solvus. - Abstract: This work was prompted by the publication of Puls's recent papers claiming that the Dutton-Puls model is valid enough to explain the stress and temperature dependences of the crack growth rate (CGR) in zirconium alloys. The first version of the Dutton-Puls model shows that the CGR has positive dependences on the concentration difference ΔC, hydrogen diffusivity D H , and the yield strength, and a negative dependence on the applied stress intensity factor K I , which is one of its critical defects. Thus, the Dutton-Puls model claiming that the temperature dependence of CGR is determined by D H C H turns out to be incorrect. Given that ΔC is independent of the stress, it is evident that the driving force for DHC is ΔC, not the stress gradient, corroborating the validity of Kim's model. Furthermore, the predicted activation energy for CGR in a cold-worked Zr-2.5Nb tube disagrees with the measured one for the Zr-2.5Nb tube, showing that the Dutton-Puls model is too defective to explain the temperature dependence of CGR. It is demonstrated that the revised Dutton-Puls model also cannot explain the yield stress dependence of CGR.

Simulating potential growth and yield of oil palm with PALMSIM

NARCIS (Netherlands)

Hoffmann, M.P.; Vera, A.C.; Wijk, van M.T.; Giller, K.E.; Oberthur, R.; Donough, C.; Whitbread, A.M.; Fisher, M.J.

2014-01-01

The growing demand for palm oil can be met by reducing the gap between potential yield and actual yield. Simulation models can quantify potential yield, and therefore indicate the scope for intensification. A relatively simple physiological approach was used to develop PALMSIM, which is a model that

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)

The In Vitro Mass-Produced Model Mycorrhizal Fungus, Rhizophagus irregularis, Significantly Increases Yields of the Globally Important Food Security Crop Cassava

Science.gov (United States)

Ceballos, Isabel; Ruiz, Michael; Fernández, Cristhian; Peña, Ricardo

2013-01-01

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. PMID:23950975

The in vitro mass-produced model mycorrhizal fungus, Rhizophagus irregularis, significantly increases yields of the globally important food security crop cassava.

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