ESTIMATION OF PEA GRAIN YIELD STABILITY (Pisum sativum L.

Directory of Open Access Journals (Sweden)

Tihomir Čupić

2003-06-01

Full Text Available The paper aimed to determine yield and estimate pea grain yield stability of newly-created lines JSG-1 (cultivar in recognition process as well as compare with foreign origin cultivars in agroecological area of east Slavonia. The trial was set up by a randomized block design on the experimental field of Agricultural Institute Osijek in four replicates in the five-year period (1998 – 2002. Six (five foreign and one inland cultivars were included by the trial: Eiffil, Erbi, JP-5, JSG-1 (in a recognition process, Torsz and Baccara. Stability parameters were calculated by the grouping method after Francis and Kannenberg (1978 and by the model of individual stability estimation after Eberhart and Russel method (1966. According to Francis and Kannenberg, cultivars Eiffil, Erbi, JSG-1 and Baccara belonged to group I known for high yield and low trait varying coefficient, thus, represent stabile yield cultivars. According to regression coefficient and regression deviation variance the most stabile cultivar appeared to be cultivar JSG-1 (bi =1.06 and S2 di=0.010 and the lowest one was Torsz (bi =0.67 and S2 di =0.160. Cultivar Baccara (bi = 1.22 and S2 di =0.034 was comprised by the group of unstabile and adaptible for high-yielding environments.

A Comparison of Machine Learning Approaches for Corn Yield Estimation

Science.gov (United States)

Kim, N.; Lee, Y. W.

2017-12-01

Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

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.

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.

Graphical user interface for yield and dose estimations for cyclotron-produced technetium.

Science.gov (United States)

Hou, X; Vuckovic, M; Buckley, K; Bénard, F; Schaffer, P; Ruth, T; Celler, A

2014-07-07

The cyclotron-based (100)Mo(p,2n)(99m)Tc reaction has been proposed as an alternative method for solving the shortage of (99m)Tc. With this production method, however, even if highly enriched molybdenum is used, various radioactive and stable isotopes will be produced simultaneously with (99m)Tc. In order to optimize reaction parameters and estimate potential patient doses from radiotracers labeled with cyclotron produced (99m)Tc, the yields for all reaction products must be estimated. Such calculations, however, are extremely complex and time consuming. Therefore, the objective of this study was to design a graphical user interface (GUI) that would automate these calculations, facilitate analysis of the experimental data, and predict dosimetry. The resulting GUI, named Cyclotron production Yields and Dosimetry (CYD), is based on Matlab®. It has three parts providing (a) reaction yield calculations, (b) predictions of gamma emissions and (c) dosimetry estimations. The paper presents the outline of the GUI, lists the parameters that must be provided by the user, discusses the details of calculations and provides examples of the results. Our initial experience shows that the proposed GUI allows the user to very efficiently calculate the yields of reaction products and analyze gamma spectroscopy data. However, it is expected that the main advantage of this GUI will be at the later clinical stage when entering reaction parameters will allow the user to predict production yields and estimate radiation doses to patients for each particular cyclotron run.

Estimation of rice yield affected by drought and relation between rice yield and TVDI

Science.gov (United States)

Hongo, C.; Tamura, E.; Sigit, G.

2016-12-01

Impact of climate change is not only seen on food production but also on food security and sustainable development of society. Adaptation to climate change is a pressing issue throughout the world to reduce the risks along with the plans and strategies for food security and sustainable development. As a key adaptation to the climate change, agricultural insurance is expected to play an important role in stabilizing agricultural production through compensating the losses caused by the climate change. As the adaptation, the Government of Indonesia has launched agricultural insurance program for damage of rice by drought, flood and pest and disease. The Government started a pilot project in 2013 and this year the pilot project has been extended to 22 provinces. Having the above as background, we conducted research on development of new damage assessment method for rice using remote sensing data which could be used for evaluation of damage ratio caused by drought in West Java, Indonesia. For assessment of the damage ratio, estimation of rice yield is a key. As the result of our study, rice yield affected by drought in dry season could be estimated at level of 1 % significance using SPOT 7 data taken in 2015, and the validation result was 0.8t/ha. Then, the decrease ratio in rice yield about each individual paddy field was calculated using data of the estimated result and the average yield of the past 10 years. In addition, TVDI (Temperature Vegetation Dryness Index) which was calculated from Landsat8 data in heading season indicated the dryness in low yield area. The result suggests that rice yield was affected by irrigation water shortage around heading season as a result of the decreased precipitation by El Nino. Through our study, it becomes clear that the utilization of remote sensing data can be promising for assessment of the damage ratio of rice production precisely, quickly and quantitatively, and also it can be incorporated into the insurance procedures.

Test of two methods for determining herbaceous yield and botanical ...

African Journals Online (AJOL)

Above-ground herbaceous yield was estimated using the comparative yield method to win + 10% (p < 0,05) of the harvested mean using 150 harvested and 600 rated quadrats of 50 x 50 cm. The number of quadrats can be substantially reduced by improved observer rating. Using the dry mass rank method and 240 ...

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.

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 ...

Science yield estimation for AFTA coronagraphs

Science.gov (United States)

Traub, Wesley A.; Belikov, Ruslan; Guyon, Olivier; Kasdin, N. Jeremy; Krist, John; Macintosh, Bruce; Mennesson, Bertrand; Savransky, Dmitry; Shao, Michael; Serabyn, Eugene; Trauger, John

2014-08-01

We describe the algorithms and results of an estimation of the science yield for five candidate coronagraph designs for the WFIRST-AFTA space mission. The targets considered are of three types, known radial-velocity planets, expected but as yet undiscovered exoplanets, and debris disks, all around nearby stars. The results of the original estimation are given, as well as those from subsequently updated designs that take advantage of experience from the initial estimates.

Vineyard Yield Estimation Based on the Analysis of High Resolution Images Obtained with Artificial Illumination at Night

Directory of Open Access Journals (Sweden)

Davinia Font

2015-04-01

Full Text Available This paper presents a method for vineyard yield estimation based on the analysis of high-resolution images obtained with artificial illumination at night. First, this paper assesses different pixel-based segmentation methods in order to detect reddish grapes: threshold based, Mahalanobis distance, Bayesian classifier, linear color model segmentation and histogram segmentation, in order to obtain the best estimation of the area of the clusters of grapes in this illumination conditions. The color spaces tested were the original RGB and the Hue-Saturation-Value (HSV. The best segmentation method in the case of a non-occluded reddish table-grape variety was the threshold segmentation applied to the H layer, with an estimation error in the area of 13.55%, improved up to 10.01% by morphological filtering. Secondly, after segmentation, two procedures for yield estimation based on a previous calibration procedure have been proposed: (1 the number of pixels corresponding to a cluster of grapes is computed and converted directly into a yield estimate; and (2 the area of a cluster of grapes is converted into a volume by means of a solid of revolution, and this volume is converted into a yield estimate; the yield errors obtained were 16% and −17%, respectively.

Performance of a procedure for yield estimation in fruit orchards

DEFF Research Database (Denmark)

Aravena Zamora, Felipe; Potin, Camila; Wulfsohn, Dvora-Laio

Early estimation of expected fruit tree yield is important for the market planning and for growers and exporters to plan for labour and boxes. Large variations in tree yield may be found, posing a challenge for accurate yield estimation. We evaluated a multilevel systematic sampling procedure...

A MONTE-CARLO METHOD FOR ESTIMATING THE CORRELATION EXPONENT

NARCIS (Netherlands)

MIKOSCH, T; WANG, QA

We propose a Monte Carlo method for estimating the correlation exponent of a stationary ergodic sequence. The estimator can be considered as a bootstrap version of the classical Hill estimator. A simulation study shows that the method yields reasonable estimates.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

Science.gov (United States)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, pcrop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Estimating Corporate Yield Curves

OpenAIRE

Antionio Diaz; Frank Skinner

2001-01-01

This paper represents the first study of retail deposit spreads of UK financial institutions using stochastic interest rate modelling and the market comparable approach. By replicating quoted fixed deposit rates using the Black Derman and Toy (1990) stochastic interest rate model, we find that the spread between fixed and variable rates of interest can be modeled (and priced) using an interest rate swap analogy. We also find that we can estimate an individual bank deposit yield curve as a spr...

An evaluation of the use of the dry-weight-rank and the comparative yield biomass estimation methods in paramo ecosystem research

Directory of Open Access Journals (Sweden)

Hofstede Robert G.M.

1993-12-01

Full Text Available The use of the combination of the semi-destructive comparative yield method for overall biomass estimation and the non- destructive dry-weight-rank method for studying botanical composition on a dry weight basis in an undisturbed páramo vegetation in the Los Nevados national park (Colombian Central Cordillera was evaluated. These methods, developed for Australian production grasslands, were adapted for use in the páramo ecosystem. The average above ground biomass in the area was estimated as 2864 g dryweight. m-2 (sd.48, of which the bunchgrass Calamagrostis effusa contributed with ca 70%. When used with some adaptations, the comparative yield method seems suitable for biomass estimations in the páramo ecosystem. The here presented estimation of botanical eomposition with this method gave better results than dry-weight-rank method, which had too many shortcomings for use in the complex páramo grassland ecosystem.Se evaluó la aplicabilidad de una combinación de dos étodos para estimar la biomasa  general y la composición botánica, en una vegetación natural paramuna en el Parque Nacional Natural los Nevados (Cordillera Central de Colombia. El primer método (ecomparative yield determina la biomasa general, destruyendo parcialmente la vegetación de los cuadrantes de muestreo y el segundo (dryweight rank determina la composición botánica con base en el peso seco, sin destruir la vegetación. Estos métodos, inicialmente desarrollados para pajonales forrajeros en Australia, se adaptaron para ser utilizados en el ecosistema paramuno. Como resultado se obtuvo una estimación de la biomasa aérea de 2864 g peso seco m2 (desviación stándard 48 en la cual, la gramínea Calamagrostis effusa contribuyó con el 70%. Puede concluirse que el método de producción comparativa es útil para estimar la biomasa en el ecosistema paramuno, siempre y cuando se utilicen las adaptaciones mencionadas. Por otra parte la estimación de la composición bot

Yield estimation for nuclear explosions of semipalatinsk using rayleigh waves recorded at SRO, Mashhad

International Nuclear Information System (INIS)

Naghizadeh, M.; Javaherian, A.; Sadidkhooy, A.

2005-01-01

Surface wave amplitudes from explosion sources show less variation for a given event than body wave amplitudes, so it is natural to expect that yield estimation derived from surface waves will be more accurate than yield estimation derived from body waves. However yield estimation from surface waves is complicated by the presence of tectonic strain release, which acts like one or more earthquake sources superimposed on the explosion. Explosions on an island or near a mountain slope can exhibit anomalous surface waves similar to those caused by tectonic strain release. One of the methods in estimating the yield of nuclear explosions is to determine a relationship between the magnitude and the yield of an explosion. The kind of magnitude employed has an important role in this regard. In this paper, vertical component of long period seismograms at SRO, Mashhad from explosions occurred in semipalatinsk test site, semipalatinsk test site east of Kazakhstan) are considered. First, by using the relationships of IASPEI and Rezapour and Pearce (1998), we determined surface wave magnitude (MS) which is defined as the logarithm of the amplitude plus a distance correction. Then we derived a relation for M S versus yield for a data set which includes a 15 long period seismograms recorded at SRO Mashhad station from semipalatinsk test site nuclear explosions. Furthermore, by digitizing the vertical component of seismograms and transforming them to the frequency domain, the mean amplitude of records at frequency ranges of 0.04-0.06 Hz were calculated. Then, surface wave magnitudes in the frequency domain (M Sf ) and their corresponding yield-magnitude relationship were obtained. By comparing correlation coefficients of these two yield-magnitude relationships, following relationship M S = 1.079 log(Y) + 1.714, was chosen for estimating the yield of semipalatinsk test site nuclear explosion from seismograms of SRO

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)

Cotton yield estimation using very high-resolution digital images acquired on a low-cost small unmanned aerial vehicle

Science.gov (United States)

Yield estimation is a critical task in crop management. A number of traditional methods are available for crop yield estimation but they are costly, time-consuming and difficult to expand to a relatively large field. Remote sensing provides techniques to develop quick coverage over a field at any sc...

Statistically Efficient Methods for Pitch and DOA Estimation

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt

2013-01-01

, it was recently considered to estimate the DOA and pitch jointly. In this paper, we propose two novel methods for DOA and pitch estimation. They both yield maximum-likelihood estimates in white Gaussian noise scenar- ios, where the SNR may be different across channels, as opposed to state-of-the-art methods......Traditionally, direction-of-arrival (DOA) and pitch estimation of multichannel, periodic sources have been considered as two separate problems. Separate estimation may render the task of resolving sources with similar DOA or pitch impossible, and it may decrease the estimation accuracy. Therefore...

Métodos para a estimativa do potencial de rendimento da soja durante a ontogenia Methods for estimating the soybean potential yield during ontogeny

Directory of Open Access Journals (Sweden)

João Leonardo Fernandes Pires

2005-04-01

Full Text Available O objetivo deste trabalho foi estudar métodos para a estimativa do potencial de rendimento da soja durante a ontogenia. Os experimentos foram realizados em Eldorado do Sul, RS, durante as safras de 1996/1997, 1999/2000 e 2000/2001. Os tratamentos constaram de cinco cultivares de soja, FT-Saray, IAS 5, IAS 4, FT-Abyara e FEPAGRO RS-10. Cinco métodos foram utilizados para estimar o rendimento que seria obtido se todas as estruturas reprodutivas presentes no florescimento e no início do enchimento de grãos, produzissem grãos na maturação. O potencial de rendimento no florescimento e no enchimento de grãos, apresentou alta correlação com o número de flores e estruturas reprodutivas, respectivamente. Verificou-se, também, correspondência entre os métodos. Não houve, na maioria das vezes, correlações significativas entre o potencial, no florescimento e enchimento de grãos, e o rendimento de grãos na maturação. Os métodos estudados constituem ferramentas importantes para o manejo, quando utilizados para comparar o potencial de rendimento durante a ontogenia.The objective of this work was to study methods to estimate the soybean potential yield during ontogeny. The experiments were performed in Eldorado do Sul, RS, during the growing seasons of 1996/1997, 1999/2000 and 2000/2001. The treatments consisted of five soybean cultivars, FT-Saray, IAS 5, IAS 4, FT-Abyara and FEPAGRO RS-10. It was calculated the potential yield of each cultivar, by five methods, in order to estimate the yield that would be obtained if all the reproductive structures during flowering and beginning of pod filling produced grains at the maturity. Potential yield (during flowering and pod filling presented a high correlation with the number of flowers and reproductive structures, respectively. It was also found a correspondence among the methods. Most of the time, it did not occurred significant correlations between potential (during flowering and pod filling

Comparison of specific-yield estimates for calculating evapotranspiration from diurnal groundwater-level fluctuations

Science.gov (United States)

Gribovszki, Zoltán

2018-05-01

Methods that use diurnal groundwater-level fluctuations are commonly used for shallow water-table environments to estimate evapotranspiration (ET) and recharge. The key element needed to obtain reliable estimates is the specific yield (Sy), a soil-water storage parameter that depends on unsaturated soil-moisture and water-table fluxes, among others. Soil-moisture profile measurement down to the water table, along with water-table-depth measurements, can provide a good opportunity to calculate Sy values even on a sub-daily scale. These values were compared with Sy estimates derived by traditional techniques, and it was found that slug-test-based Sy values gave the most similar results in a sandy soil environment. Therefore, slug-test methods, which are relatively cheap and require little time, were most suited to estimate Sy using diurnal fluctuations. The reason for this is that the timeframe of the slug-test measurement is very similar to the dynamic of the diurnal signal. The dynamic characteristic of Sy was also analyzed on a sub-daily scale (depending mostly on the speed of drainage from the soil profile) and a remarkable difference was found in Sy with respect to the rate of change of the water table. When comparing constant and sub-daily (dynamic) Sy values for ET estimation, the sub-daily Sy application yielded higher correlation, but only a slightly smaller deviation from the control ET method, compared with the usage of constant Sy.

Similar estimates of temperature impacts on global wheat yield by three independent methods

NARCIS (Netherlands)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Supit, Iwan; Wolf, Joost

2016-01-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO 2 fertilization effects,

Estimation of 305 Day Milk Yield from Cumulative Monthly and Bimonthly Test Day Records in Indonesian Holstein Cattle

Science.gov (United States)

Rahayu, A. P.; Hartatik, T.; Purnomoadi, A.; Kurnianto, E.

2018-02-01

The aims of this study were to estimate 305 day first lactation milk yield of Indonesian Holstein cattle from cumulative monthly and bimonthly test day records and to analyze its accuracy.The first lactation records of 258 dairy cows from 2006 to 2014 consisted of 2571 monthly (MTDY) and 1281 bimonthly test day yield (BTDY) records were used. Milk yields were estimated by regression method. Correlation coefficients between actual and estimated milk yield by cumulative MTDY were 0.70, 0.78, 0.83, 0.86, 0.89, 0.92, 0.94 and 0.96 for 2-9 months, respectively, meanwhile by cumulative BTDY were 0.69, 0.81, 0.87 and 0.92 for 2, 4, 6 and 8 months, respectively. The accuracy of fitting regression models (R2) increased with the increasing in the number of cumulative test day used. The used of 5 cumulative MTDY was considered sufficient for estimating 305 day first lactation milk yield with 80.6% accuracy and 7% error percentage of estimation. The estimated milk yield from MTDY was more accurate than BTDY by 1.1 to 2% less error percentage in the same time.

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

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY

Yield estimation based on calculated comparisons to particle velocity data recorded at low stress

International Nuclear Information System (INIS)

Rambo, J.

1993-01-01

This paper deals with the problem of optimizing the yield estimation process if some of the material properties are known from geophysical measurements and others are inferred from in-situ dynamic measurements. The material models and 2-D simulations of the event are combined to determine the yield. Other methods of yield determination from peak particle velocity data have mostly been based on comparisons of nearby events in similar media at NTS. These methods are largely empirical and are subject to additional error when a new event has different properties than the population being used for a basis of comparison. The effect of material variations can be examined using LLNL's KDYNA computer code. The data from an NTS event provide the instructive example for simulation

Estimating national crop yield potential and the relevance of weather data sources

Science.gov (United States)

Van Wart, Justin

2011-12-01

To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing

A new system for seismic yield estimation of underground explosions

International Nuclear Information System (INIS)

Murphy, J.R.

1991-01-01

Research conducted over the past decade has led to the development of a number of innovative procedures for estimating the yields of underground nuclear explosions based on systematic analyses of digital seismic data recorded from these tests. In addition, a wide variety of new data regarding the geophysical environments at Soviet test locations have now become available as a result of the Joint Verification Experiment (JVE) and associated data exchanges. The system described in this paper represents an attempt to integrate all these new capabilities and data into a comprehensive operational prototype which can be used to obtain optimum seismic estimates of explosion yield together with quantitative measures of the uncertainty in those estimates. The implementation of this system has involved a wide variety of technical tasks, including the development of a comprehensive seismic database and related database access software, formulation of a graphical test site information interface for accessing available information on explosion source conditions, design of an interactive seismic analyst station for use in processing the observed data to extract the required magnitude measures and the incorporation of formal statistical analysis modules for use in yield estimation and assessment

Site-specific estimates of water yield applied in regional acid sensitivity surveys across western Canada

Directory of Open Access Journals (Sweden)

Patrick D. SHAW

2010-08-01

Full Text Available Runoff or water yield is an important input to the Steady-State Water Chemistry (SSWC model for estimating critical loads of acidity. Herein, we present site-specific water yield estimates for a large number of lakes (779 across three provinces of western Canada (Manitoba, Saskatchewan, and British Columbia using an isotope mass balance (IMB approach. We explore the impact of applying site-specific hydrology as compared to use of regional runoff estimates derived from gridded datasets in assessing critical loads of acidity to these lakes. In general, the average water yield derived from IMB is similar to the long-term average runoff; however, IMB results suggest a much larger range in hydrological settings of the lakes, attributed to spatial heterogeneity in watershed characteristics and landcover. The comparison of critical loads estimates from the two methods suggests that use of average regional runoff data in the SSWC model may overestimate critical loads for the majority of lakes due to systematic skewness in the actual runoff distributions. Implications for use of site-specific hydrology in regional critical loads assessments across western Canada are discussed.

Estimation of Rice Crop Yields Using Random Forests in Taiwan

Science.gov (United States)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2

Lowland rice yield estimates based on air temperature and solar radiation

International Nuclear Information System (INIS)

Pedro Júnior, M.J.; Sentelhas, P.C.; Moraes, A.V.C.; Villela, O.V.

1995-01-01

Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm -2 , day -1 . The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%). (author) [pt

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

Science.gov (United States)

Fieuzal, R.; Marais Sicre, C.; Baup, F.

2017-05-01

The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

Integrating remote sensing, geographic information system and modeling for estimating crop yield

Science.gov (United States)

Salazar, Luis Alonso

This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

Estimated yield of double-strand breaks from internal exposure to tritium.

Science.gov (United States)

Chen, Jing

2012-08-01

Internal exposure to tritium may result in DNA lesions. Of those, DNA double-strand breaks (DSBs) are believed to be important. However, experimental and computational data of DSBs induction by tritium are very limited. In this study, microdosimetric characteristics of uniformly distributed tritium were determined in dimensions of critical significance in DNA DSBs. Those characteristics were used to identify other particles comparable to tritium in terms of microscopic energy deposition. The yield of DSBs could be strongly dependent on biological systems and cellular environments. After reviewing theoretically predicted and experimentally determined DSB yields available in the literature for low-energy electrons and high-energy protons of comparable microdosimetric characteristics to tritium in the dimensions relevant to DSBs, it is estimated that the average DSB yields of 2.7 × 10(-11), 0.93 × 10(-11), 2.4 × 10(-11) and 1.6 × 10(-11) DSBs Gy(-1) Da(-1) could be reasonable estimates for tritium in plasmid DNAs, yeast cells, Chinese hamster V79 cells and human fibroblasts, respectively. If a biological system is not specified, the DSB yield from tritium exposure can be estimated as (2.3 ± 0.7) × 10(-11) DSBs Gy(-1) Da(-1), which is a simple average over experimentally determined yields of DSBs for low-energy electrons in various biological systems without considerations of variations caused by different techniques used and obvious differences among different biological systems where the DSB yield was measured.

Microbial growth yield estimates from thermodynamics and its importance for degradation of pesticides and formation of biogenic non-extractable residues

DEFF Research Database (Denmark)

Brock, Andreas Libonati; Kästner, M.; Trapp, Stefan

2017-01-01

NER. Formation of microbial mass can be estimated from the microbial growth yield, but experimental data is rare. Instead, we suggest using prediction methods for the theoretical yield based on thermodynamics. Recently, we presented the Microbial Turnover to Biomass (MTB) method that needs a minimum...... and using the released CO2 as a measure for microbial activity, we predicted a range for the formation of biogenic NER. For the majority of the pesticides, a considerable fraction of the NER was estimated to be biogenic. This novel approach provides a theoretical foundation applicable to the evaluation...

Exoplanet Yield Estimation for Decadal Study Concepts using EXOSIMS

Science.gov (United States)

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

2016-01-01

The anticipated upcoming large mission study concepts for the direct imaging of exo-earths present an exciting opportunity for exoplanet discovery and characterization. While these telescope concepts would also be capable of conducting a broad range of astrophysical investigations, the most difficult technology challenges are driven by the requirements for imaging exo-earths. The exoplanet science yield for these mission concepts will drive design trades and mission concept comparisons.To assist in these trade studies, the Exoplanet Exploration Program Office (ExEP) is developing a yield estimation tool that emphasizes transparency and consistent comparison of various design concepts. The tool will provide a parametric estimate of science yield of various mission concepts using contrast curves from physics-based model codes and Monte Carlo simulations of design reference missions using realistic constraints, such as solar avoidance angles, the observatory orbit, propulsion limitations of star shades, the accessibility of candidate targets, local and background zodiacal light levels, and background confusion by stars and galaxies. The python tool utilizes Dmitry Savransky's EXOSIMS (Exoplanet Open-Source Imaging Mission Simulator) design reference mission simulator that is being developed for the WFIRST Preliminary Science program. ExEP is extending and validating the tool for future mission concepts under consideration for the upcoming 2020 decadal review. We present a validation plan and preliminary yield results for a point design.

Estimated yield of double-strand breaks from internal exposure to tritium

Energy Technology Data Exchange (ETDEWEB)

Chen, Jing [Health Canada, Radiation Protection Bureau, Ottawa, ON (Canada)

2012-08-15

Internal exposure to tritium may result in DNA lesions. Of those, DNA double-strand breaks (DSBs) are believed to be important. However, experimental and computational data of DSBs induction by tritium are very limited. In this study, microdosimetric characteristics of uniformly distributed tritium were determined in dimensions of critical significance in DNA DSBs. Those characteristics were used to identify other particles comparable to tritium in terms of microscopic energy deposition. The yield of DSBs could be strongly dependent on biological systems and cellular environments. After reviewing theoretically predicted and experimentally determined DSB yields available in the literature for low-energy electrons and high-energy protons of comparable microdosimetric characteristics to tritium in the dimensions relevant to DSBs, it is estimated that the average DSB yields of 2.7 x 10{sup -11}, 0.93 x 10{sup -11}, 2.4 x 10{sup -11} and 1.6 x 10{sup -11} DSBs Gy{sup -1} Da{sup -1} could be reasonable estimates for tritium in plasmid DNAs, yeast cells, Chinese hamster V79 cells and human fibroblasts, respectively. If a biological system is not specified, the DSB yield from tritium exposure can be estimated as (2.3 ± 0.7) x 10{sup -11} DSBs Gy{sup -1} Da{sup -1}, which is a simple average over experimentally determined yields of DSBs for low-energy electrons in various biological systems without considerations of variations caused by different techniques used and obvious differences among different biological systems where the DSB yield was measured. (orig.)

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.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

Energy Technology Data Exchange (ETDEWEB)

Telfeyan, Katherine Christina [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ware, Stuart Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Birdsell, Kay Hanson [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-06

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

Science.gov (United States)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Estimating yield gaps at the cropping system level.

Science.gov (United States)

Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

2017-05-01

Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

Directory of Open Access Journals (Sweden)

Julien Morel

2014-07-01

Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

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

The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs

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

Directory of Open Access Journals (Sweden)

Rebecca Boehm

2016-04-01

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

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.

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

Added-values of high spatiotemporal remote sensing data in crop yield estimation

Science.gov (United States)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate

Multilevel systematic sampling to estimate total fruit number for yield forecasts

DEFF Research Database (Denmark)

Wulfsohn, Dvora-Laio; Zamora, Felipe Aravena; Tellez, Camilla Potin

2012-01-01

procedure for unbiased estimation of fruit number for yield forecasts. In the Spring of 2009 we estimated the total number of fruit in several rows of each of 14 commercial fruit orchards growing apple (11 groves), kiwifruit (two groves), and table grapes (one grove) in central Chile. Survey times were 10...

Estimation of Maize grain yield using multispectral satellite data sets ...

African Journals Online (AJOL)

Dr-Adeline

Crop yield prediction is production estimates that are made a couple of months or ... involving the effect of biotic and abiotic factors cumulatively which could however ...... Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence.

Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology

Science.gov (United States)

Terziotti, Silvia; Capel, Paul D.; Tesoriero, Anthony J.; Hopple, Jessica A.; Kronholm, Scott C.

2018-03-07

The water quality of the Chesapeake Bay may be adversely affected by dissolved nitrate carried in groundwater discharge to streams. To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.

Estimation of heterosis in yield and yield attributing traits in single cross hybrids of maize

Directory of Open Access Journals (Sweden)

Hari Prasad Sharma

2016-12-01

Full Text Available A field experiment was conducted at National Maize Research Program, Rampur, Chitwan, Nepal during winter season from 6th October, 2015 to 5th March 2016 to estimate different heterosis on single cross maize hybrids . Thirteen maize hybrids were tested randomized complete block design with three replications. Hybrid namely RML-98/RL-105 gave the highest standard heterosis (57.5% for grain yield over CP-666 followed by RML-4/NML-2 (32.6%, RML-95/RL-105 (29% and RML-5/RL-105 (20.6%. The hybrid RML-98/RL-105 produced the highest standard heterosis (75.1% for grain yield over Rajkumar followed by RML-4/NML-2(50.2%, RML-95/RL-105(46.6%, RML-5/RL-105 and (35.7%. Mid and better parent heterosis were significantly higher for yield and yield attributes viz. ear length, ear diameter, no of kernel row per ear, no of kernel per row and test weight. The highest positive mid-parent heterosis for grain yield was found in RML-98/RL-105 followed by RML-5/RL-105, RML-95/RL-105, and RML-4/NML-2. For the grain yield the better parent heterosis was the highest in RML-98/RL-105, followed by RML-5/RL-105, RML-95/RL-105, and RML-4/NML-2. These results suggested that maize production can be maximized by cultivating hybrids namely RML-98/RL-105, RML-5/RL-105, RML-95/RL-105, and RML-4/NML-2 .

Systematics of Fission-Product Yields

International Nuclear Information System (INIS)

Wahl, A.C.

2002-01-01

Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z F = 90 thru 98, mass number A F = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru ∼200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from ∼ 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron (∼ fission spectrum) induced fission reactions

Systematics of Fission-Product Yields

Energy Technology Data Exchange (ETDEWEB)

A.C. Wahl

2002-05-01

Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z{sub F} = 90 thru 98, mass number A{sub F} = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru {approx}200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from {approx} 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron ({approx} fission spectrum) induced fission reactions.

Predictive ability of machine learning methods for massive crop yield prediction

Directory of Open Access Journals (Sweden)

Alberto Gonzalez-Sanchez

2014-04-01

Full Text Available An important issue for agricultural planning purposes is the accurate yield estimation for the numerous crops involved in the planning. Machine learning (ML is an essential approach for achieving practical and effective solutions for this problem. Many comparisons of ML methods for yield prediction have been made, seeking for the most accurate technique. Generally, the number of evaluated crops and techniques is too low and does not provide enough information for agricultural planning purposes. This paper compares the predictive accuracy of ML and linear regression techniques for crop yield prediction in ten crop datasets. Multiple linear regression, M5-Prime regression trees, perceptron multilayer neural networks, support vector regression and k-nearest neighbor methods were ranked. Four accuracy metrics were used to validate the models: the root mean square error (RMS, root relative square error (RRSE, normalized mean absolute error (MAE, and correlation factor (R. Real data of an irrigation zone of Mexico were used for building the models. Models were tested with samples of two consecutive years. The results show that M5-Prime and k-nearest neighbor techniques obtain the lowest average RMSE errors (5.14 and 4.91, the lowest RRSE errors (79.46% and 79.78%, the lowest average MAE errors (18.12% and 19.42%, and the highest average correlation factors (0.41 and 0.42. Since M5-Prime achieves the largest number of crop yield models with the lowest errors, it is a very suitable tool for massive crop yield prediction in agricultural planning.

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.

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

Science.gov (United States)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

Estimating milk yield and value losses from increased somatic cell count on US dairy farms.

Science.gov (United States)

Hadrich, J C; Wolf, C A; Lombard, J; Dolak, T M

2018-04-01

Milk loss due to increased somatic cell counts (SCC) results in economic losses for dairy producers. This research uses 10 mo of consecutive dairy herd improvement data from 2013 and 2014 to estimate milk yield loss using SCC as a proxy for clinical and subclinical mastitis. A fixed effects regression was used to examine factors that affected milk yield while controlling for herd-level management. Breed, milking frequency, days in milk, seasonality, SCC, cumulative months with SCC greater than 100,000 cells/mL, lactation, and herd size were variables included in the regression analysis. The cumulative months with SCC above a threshold was included as a proxy for chronic mastitis. Milk yield loss increased as the number of test days with SCC ≥100,000 cells/mL increased. Results from the regression were used to estimate a monetary value of milk loss related to SCC as a function of cow and operation related explanatory variables for a representative dairy cow. The largest losses occurred from increased cumulative test days with a SCC ≥100,000 cells/mL, with daily losses of $1.20/cow per day in the first month to $2.06/cow per day in mo 10. Results demonstrate the importance of including the duration of months above a threshold SCC when estimating milk yield losses. Cows with chronic mastitis, measured by increased consecutive test days with SCC ≥100,000 cells/mL, resulted in higher milk losses than cows with a new infection. This provides farm managers with a method to evaluate the trade-off between treatment and culling decisions as it relates to mastitis control and early detection. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Simple method for quick estimation of aquifer hydrogeological parameters

Science.gov (United States)

Ma, C.; Li, Y. Y.

2017-08-01

Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

Explosive Yield Estimation using Fourier Amplitude Spectra of Velocity Histories

Science.gov (United States)

Steedman, D. W.; Bradley, C. R.

2016-12-01

The Source Physics Experiment (SPE) is a series of explosive shots of various size detonated at varying depths in a borehole in jointed granite. The testbed includes an extensive array of accelerometers for measuring the shock environment close-in to the explosive source. One goal of SPE is to develop greater understanding of the explosion phenomenology in all regimes: from near-source, non-linear response to the far-field linear elastic region, and connecting the analyses from the respective regimes. For example, near-field analysis typically involves review of kinematic response (i.e., acceleration, velocity and displacement) in the time domain and looks at various indicators (e.g., peaks, pulse duration) to facilitate comparison among events. Review of far-field data more often is based on study of response in the frequency domain to facilitate comparison of event magnitudes. To try to "bridge the gap" between approaches, we have developed a scaling law for Fourier amplitude spectra of near-field velocity histories that successfully collapses data from a wide range of yields (100 kg to 5000 kg) and range to sensors in jointed granite. Moreover, we show that we can apply this scaling law to data from a new event to accurately estimate the explosive yield of that event. This approach presents a new way of working with near-field data that will be more compatible with traditional methods of analysis of seismic data and should serve to facilitate end-to-end event analysis. The goal is that this new approach to data analysis will eventually result in improved methods for discrimination of event type (i.e., nuclear or chemical explosion, or earthquake) and magnitude.

Remote Estimation of Vegetation Fraction and Yield in Oilseed Rape with Unmanned Aerial Vehicle Data

Science.gov (United States)

Peng, Y.; Fang, S.; Liu, K.; Gong, Y.

2017-12-01

This study developed an approach for remote estimation of Vegetation Fraction (VF) and yield in oilseed rape, which is a crop species with conspicuous flowers during reproduction. Canopy reflectance in green, red, red edge and NIR bands was obtained by a camera system mounted on an unmanned aerial vehicle (UAV) when oilseed rape was in the vegetative growth and flowering stage. The relationship of several widely-used Vegetation Indices (VI) vs. VF was tested and found to be different in different phenology stages. At the same VF when oilseed rape was flowering, canopy reflectance increased in all bands, and the tested VI decreased. Therefore, two algorithms to estimate VF were calibrated respectively, one for samples during vegetative growth and the other for samples during flowering stage. During the flowering season, we also explored the potential of using canopy reflectance or VIs to estimate Flower Fraction (FF) in oilseed rape. Based on FF estimates, rape yield can be estimated using canopy reflectance data. Our model was validated in oilseed rape planted under different nitrogen fertilization applications and in different phenology stages. The results showed that it was able to predict VF and FF accurately in oilseed rape with estimation error below 6% and predict yield with estimation error below 20%.

Dual ant colony operational modal analysis parameter estimation method

Science.gov (United States)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

Science.gov (United States)

Adushkin, V. V.

- A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.

Effects of nitrogen application method and weed control on corn yield and yield components.

Science.gov (United States)

Sepahvand, Pariya; Sajedi, Nurali; Mousavi, Seyed Karim; Ghiasvand, Mohsen

2014-04-01

The effects of nitrogen fertilizer application and different methods for weed control on yield and yield components of corn was evaluated in Khorramabad in 2011. The experiment was conducted as a split plot based on randomized complete block design in 3 replications. Nitrogen application was as main plot in 4 levels (no nitrogen, broadcasting nitrogen, banding nitrogen and sprayed nitrogen) and methods of weed control were in 4 levels (non-control weeds, application Equip herbicide, once hand control of weeds and application Equip herbicide+once time weeding) was as subplots. Result illustrated that effects of nitrogen fertilizer application were significant on grain and forage yield, 100 seeds weight, harvest index, grain number per row and cob weight per plant. Grain yield increased by 91.4 and 3.9% in application banding and broadcasting for nitrogen fertilizer, respectively, compared to the no fertilizer treatment. The results show improved efficiency of nitrogen utilization by banding application. Grain yield, harvest index, seed rows per cob, seeds per row and cob weight were increased by weed control. In the application of Equip herbicide+ hand weeding treatment corn grain yield was increased 126% in comparison to weedy control. It represents of the intense affects of weed competition with corn. The highest corn grain yield (6758 kg h(-1)) was related to the application banding of nitrogen fertilizer and Equip herbicide+once hand weeding.

Slifers revisited: a method for determining yields independent of radiochemical measurements

International Nuclear Information System (INIS)

Rambo, J.T.

1976-01-01

It would be very desirable if an independent method other than radiochemical measurement were available to determine the yields of low-yield events in the alluviums and tuffs of areas 2, 9, and 10 at the Nevada Test Site. The successful application of slifers to the measurement of yields from high-yield events suggests that under some conditions they may also be usable with low-yield events. This view is supported by the evidence discussed here, which is based on direct experience with slifer yield measurements for low-yield events in porous media. Suggested methods for improving slifer yield determinations and a method for determining yields independent of radiochemical measurements are offered

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

Science.gov (United States)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

A General Method to Estimate Earthquake Moment and Magnitude using Regional Phase Amplitudes

Energy Technology Data Exchange (ETDEWEB)

Pasyanos, M E

2009-11-19

This paper presents a general method of estimating earthquake magnitude using regional phase amplitudes, called regional M{sub o} or regional M{sub w}. Conceptually, this method uses an earthquake source model along with an attenuation model and geometrical spreading which accounts for the propagation to utilize regional phase amplitudes of any phase and frequency. Amplitudes are corrected to yield a source term from which one can estimate the seismic moment. Moment magnitudes can then be reliably determined with sets of observed phase amplitudes rather than predetermined ones, and afterwards averaged to robustly determine this parameter. We first examine in detail several events to demonstrate the methodology. We then look at various ensembles of phases and frequencies, and compare results to existing regional methods. We find regional M{sub o} to be a stable estimator of earthquake size that has several advantages over other methods. Because of its versatility, it is applicable to many more events, particularly smaller events. We make moment estimates for earthquakes ranging from magnitude 2 to as large as 7. Even with diverse input amplitude sources, we find magnitude estimates to be more robust than typical magnitudes and existing regional methods and might be tuned further to improve upon them. The method yields a more meaningful quantity of seismic moment, which can be recast as M{sub w}. Lastly, it is applied here to the Middle East region using an existing calibration model, but it would be easy to transport to any region with suitable attenuation calibration.

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

Estimates of Sputter Yields of Solar-Wind Heavy Ions of Lunar Regolith Materials

Science.gov (United States)

Barghouty, Abdulmasser F.; Adams, James H., Jr.

2008-01-01

At energies of approximately 1 keV/amu, solar-wind protons and heavy ions interact with the lunar surface materials via a number of microscopic interactions that include sputtering. Solar-wind induced sputtering is a main mechanism by which the composition of the topmost layers of the lunar surface can change, dynamically and preferentially. This work concentrates on sputtering induced by solar-wind heavy ions. Sputtering associated with slow (speeds the electrons speed in its first Bohr orbit) and highly charged ions are known to include both kinetic and potential sputtering. Potential sputtering enjoys some unique characteristics that makes it of special interest to lunar science and exploration. Unlike the yield from kinetic sputtering where simulation and approximation schemes exist, the yield from potential sputtering is not as easy to estimate. This work will present a preliminary numerical scheme designed to estimate potential sputtering yields from reactions relevant to this aspect of solar-wind lunar-surface coupling.

Harvesting Method Affects Water Dynamics and Yield of Sweet Orange with Huanglongbing

Directory of Open Access Journals (Sweden)

Said A. Hamido

2018-03-01

Full Text Available Changes in grove management practices may change crop water dynamics. The objective of this study was to estimate sap flow, stem water potential (Ψstem, and citrus yield as affected by harvesting methods in sweet orange (Citrus sinensis trees affected by Huanglongbing. The study was initiated in March 2015 for two years on five-year-old commercial sweet orange trees at a commercial grove located at Felda, Florida (26.61° N, 81.48° W on Felda fine sand soil (Loamy, siliceous, superactive, hyperthermic Arenic Endoaqualfs. All measurements were replicated before and after harvest in four experiments (A, B, C and D under hand and mechanical harvesting treatments. Sap flow measurements were taken on four trees per treatment with two sensors per tree. Sap flow measured by the heat balance method at hourly intervals during March and April of 2015 and 2016 significantly declined after harvesting by 25% and 35% after hand and mechanical harvesting, respectively. Ψstem measured after harvest was significantly higher than measurements before harvest. The average value of Ψstem measured increased by 10% and 6% after hand and mechanical harvesting, respectively. Mechanical harvesting exhibited lower fruit yields that averaged between 83%, 63%, 49% and 36% of hand-harvested trees under A, B, C and D experiments, respectively. It is concluded that the hand harvesting method is less stressful and less impactful on tree water uptake and fruit yield compared with mechanical harvesting.

A Remote-Sensing Driven Tool for Estimating Crop Stress and Yields

Directory of Open Access Journals (Sweden)

Martha C. Anderson

2013-07-01

Full Text Available Biophysical crop simulation models are normally forced with precipitation data recorded with either gauges or ground-based radar. However, ground-based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would be to employ satellite-based observations of either precipitation or soil moisture. Satellite observations of precipitation are currently not considered capable of forcing the models with sufficient accuracy for crop yield predictions. However, deduction of soil moisture from space-based platforms is in a more advanced state than are precipitation estimates so that these data may be capable of forcing the models with better accuracy. In this study, a mature two-source energy balance model, the Atmosphere Land Exchange Inverse (ALEXI model, was used to deduce root zone soil moisture for an area of North Alabama, USA. The soil moisture estimates were used in turn to force the state-of-the-art Decision Support System for Agrotechnology Transfer (DSSAT crop simulation model. The study area consisted of a mixture of rainfed and irrigated cornfields. The results indicate that the model forced with the ALEXI moisture estimates produced yield simulations that compared favorably with observed yields and with the rainfed model. The data appear to indicate that the ALEXI model did detect the soil moisture signal from the mixed rainfed/irrigation corn fields and this signal was of sufficient strength to produce adequate simulations of recorded yields over a 10 year period.

Maximizing the ExoEarth candidate yield from a future direct imaging mission

International Nuclear Information System (INIS)

Stark, Christopher C.; Roberge, Aki; Mandell, Avi; Robinson, Tyler D.

2014-01-01

ExoEarth yield is a critical science metric for future exoplanet imaging missions. Here we estimate exoEarth candidate yield using single visit completeness for a variety of mission design and astrophysical parameters. We review the methods used in previous yield calculations and show that the method choice can significantly impact yield estimates as well as how the yield responds to mission parameters. We introduce a method, called Altruistic Yield Optimization, that optimizes the target list and exposure times to maximize mission yield, adapts maximally to changes in mission parameters, and increases exoEarth candidate yield by up to 100% compared to previous methods. We use Altruistic Yield Optimization to estimate exoEarth candidate yield for a large suite of mission and astrophysical parameters using single visit completeness. We find that exoEarth candidate yield is most sensitive to telescope diameter, followed by coronagraph inner working angle, followed by coronagraph contrast, and finally coronagraph contrast noise floor. We find a surprisingly weak dependence of exoEarth candidate yield on exozodi level. Additionally, we provide a quantitative approach to defining a yield goal for future exoEarth-imaging missions.

Comparative study of various methods of primary energy estimation in nucleon-nucleon interactions

International Nuclear Information System (INIS)

Goyal, D.P.; Yugindro Singh, K.; Singh, S.

1986-01-01

The various available methods for the estimation of primary energy in nucleon-nucleon interactions have been examined by using the experimental data on angular distributions of shower particles from p-N interactions at two accelerator energies, 67 and 400 GeV. Three different groups of shower particle multiplicities have been considered for interactions at both energies. It is found that the different methods give quite different estimates of primary energy. Moreover, each method is found to give different values of energy according to the choice of multiplicity groups. It is concluded that the E ch method is relatively the better method among all the methods available, and that within this method, the consideration of the group of small multiplicities gives a much better result. The method also yields plausible estimates of inelasticity in high energy nucleon-nucleon interactions. (orig.)

Comparison of the methods for determination of scintillation light yield

CERN Document Server

Sysoeva, E; Zelenskaya, O

2002-01-01

One of the most important characteristics of scintillators is the light yield. It depends not only on the properties of scintillators, but also on the conditions of measurements. Even for widely used crystals, such as alkali halide scintillators NaI(Tl) and CsI(Tl), light yield data, obtained by various authors, are different. Therefore, it is very important to choose the convenient method of the light yield measurements. In the present work, methods for the determination of the physical light yield, based on measurements of pulse amplitude, single-electron pulses and intrinsic photomultiplier resolution are discussed. These methods have been used for the measurements of light yield of alkali halide crystals and oxide scintillators. Repeatability and reproducibility of results were determined. All these methods are rather complicated in use, not for measurements, but for further data processing. Besides that, they demand a precise determination of photoreceiver's parameters, as well as determination of light ...

Use of vegetation health data for estimation of aus rice yield in bangladesh.

Science.gov (United States)

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

Directory of Open Access Journals (Sweden)

Mohammad Nizamuddin

2009-04-01

Full Text Available Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH Indices [Vegetation Condition Index (VCI, Temperature Condition Index (TCI and Vegetation Health Index (VHI] computed from Advanced Very High Resolution Radiometer (AVHRR data covering a period of 15 years (1991–2005. A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8–13 of the year, several months in advance of the rice harvest. Stepwise principal component regression (PCR was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves.

Science.gov (United States)

Pérez-Patricio, Madaín; Camas-Anzueto, Jorge Luis; Sanchez-Alegría, Avisaí; Aguilar-González, Abiel; Gutiérrez-Miceli, Federico; Escobar-Gómez, Elías; Voisin, Yvon; Rios-Rojas, Carlos; Grajales-Coutiño, Ruben

2018-02-22

This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD) meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica , Canavalia ensiforme , and Lycopersicon esculentum . Experimental results showed that-in terms of accuracy and processing speed-the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica , where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves

Directory of Open Access Journals (Sweden)

Madaín Pérez-Patricio

2018-02-01

Full Text Available This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance, a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica, Canavalia ensiforme, and Lycopersicon esculentum. Experimental results showed that—in terms of accuracy and processing speed—the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica, where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.

FlorNExT®, a cloud computing application to estimate growth and yield of maritime pine (Pinus pinaster Ait.) stands in Northeastern Portugal

Energy Technology Data Exchange (ETDEWEB)

Barreiro, S.; Rua, J.; Tomé, M.

2016-07-01

Aim of the study. To introduce and describe FlorNExT®, a free cloud computing application to estimate growth and yield of maritime pine (Pinus pinaster Ait.) even-aged stands in the Northeast of Portugal (NE Portugal). Area of study: NE Portugal. Material and methods: FlorNExT® implements a dynamic growth and yield modelling framework which integrates transition functions for dominant height (site index curves) and basal area, as well as output functions for tree and stand volume, biomass, and carbon content. Main results: FlorNExT® is freely available from any device with an Internet connection at: http://flornext.esa.ipb.pt/. Research highlights: This application has been designed to make it possible for any stakeholder to easily estimate standing volume, biomass, and carbon content in maritime pine stands from stand data, as well as to estimate growth and yield based on four stand variables: age, density, dominant height, and basal area. FlorNExT® allows planning thinning treatments. FlorNExT® is a fundamental tool to support forest mobilization at local and regional scales in NE Portugal. (Author)

Exoplanet Classification and Yield Estimates for Direct Imaging Missions

Science.gov (United States)

Kopparapu, Ravi Kumar; Hébrard, Eric; Belikov, Rus; Batalha, Natalie M.; Mulders, Gijs D.; Stark, Chris; Teal, Dillon; Domagal-Goldman, Shawn; Mandell, Avi

2018-04-01

Future NASA concept missions that are currently under study, like the Habitable Exoplanet Imaging Mission (HabEx) and the Large Ultra-violet Optical Infra Red Surveyor, could discover a large diversity of exoplanets. We propose here a classification scheme that distinguishes exoplanets into different categories based on their size and incident stellar flux, for the purpose of providing the expected number of exoplanets observed (yield) with direct imaging missions. The boundaries of this classification can be computed using the known chemical behavior of gases and condensates at different pressures and temperatures in a planetary atmosphere. In this study, we initially focus on condensation curves for sphalerite ZnS, {{{H}}}2{{O}}, {CO}}2, and {CH}}4. The order in which these species condense in a planetary atmosphere define the boundaries between different classes of planets. Broadly, the planets are divided into rocky planets (0.5–1.0 R ⊕), super-Earths (1.0–1.75 R ⊕), sub-Neptunes (1.75–3.5 R ⊕), sub-Jovians (3.5–6.0 R ⊕), and Jovians (6–14.3 R ⊕) based on their planet sizes, and “hot,” “warm,” and “cold” based on the incident stellar flux. We then calculate planet occurrence rates within these boundaries for different kinds of exoplanets, η planet, using the community coordinated results of NASA’s Exoplanet Program Analysis Group’s Science Analysis Group-13 (SAG-13). These occurrence rate estimates are in turn used to estimate the expected exoplanet yields for direct imaging missions of different telescope diameters.

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.

Reliability of Estimation Pile Load Capacity Methods

Directory of Open Access Journals (Sweden)

Yudhi Lastiasih

2014-04-01

Full Text Available None of numerous previous methods for predicting pile capacity is known how accurate any of them are when compared with the actual ultimate capacity of piles tested to failure. The author’s of the present paper have conducted such an analysis, based on 130 data sets of field loading tests. Out of these 130 data sets, only 44 could be analysed, of which 15 were conducted until the piles actually reached failure. The pile prediction methods used were: Brinch Hansen’s method (1963, Chin’s method (1970, Decourt’s Extrapolation Method (1999, Mazurkiewicz’s method (1972, Van der Veen’s method (1953, and the Quadratic Hyperbolic Method proposed by Lastiasih et al. (2012. It was obtained that all the above methods were sufficiently reliable when applied to data from pile loading tests that loaded to reach failure. However, when applied to data from pile loading tests that loaded without reaching failure, the methods that yielded lower values for correction factor N are more recommended. Finally, the empirical method of Reese and O’Neill (1988 was found to be reliable enough to be used to estimate the Qult of a pile foundation based on soil data only.

Comparison of breeding methods for forage yield in red clover

Directory of Open Access Journals (Sweden)

Libor Jalůvka

2009-01-01

Full Text Available Three methods of red clover (Trifolium pratense L. breeding for forage yield in two harvest years on locations in Bredelokke (Denmark, Hladké Životice (Czech Republic and Les Alleuds (France were compared. Three types of 46 candivars1, developed by A recurrent selection in subsequent generations (37 candivars, divided into early and late group, B polycross progenies (4 candivars and C ge­no-phe­no­ty­pic selection (5 candivars were compared. The trials were sown in 2005 and cut three times in 2006 and 2007; their evaluation is based primarily on total yield of dry matter. The candivars developed by polycross and geno-phenotypic selections gave significantly higher yields than candivars from the recurrent selection. However, the candivars developed by the methods B and C did not differ significantly. The candivars developed by these progressive methods were suitable for higher yielding and drier environment in Hladké Životice (where was the highest yield level even if averaged annual precipitation were lower by 73 and 113 mm in comparison to other locations, respectively; here was ave­ra­ge yield higher by 19 and 13% for B and C in comparison to A method. Highly significant interaction of the candivars with locations was found. It can be concluded that varieties specifically aimed to different locations by the methods B and C should be bred; also the parental entries should be selected there.

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

Science.gov (United States)

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

2017-04-01

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

A high throughput DNA extraction method with high yield and quality

Directory of Open Access Journals (Sweden)

Xin Zhanguo

2012-07-01

Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

A Theoretical Model for Estimation of Yield Strength of Fiber Metal Laminate

Science.gov (United States)

Bhat, Sunil; Nagesh, Suresh; Umesh, C. K.; Narayanan, S.

2017-08-01

The paper presents a theoretical model for estimation of yield strength of fiber metal laminate. Principles of elasticity and formulation of residual stress are employed to determine the stress state in metal layer of the laminate that is found to be higher than the stress applied over the laminate resulting in reduced yield strength of the laminate in comparison with that of the metal layer. The model is tested over 4A-3/2 Glare laminate comprising three thin aerospace 2014-T6 aluminum alloy layers alternately bonded adhesively with two prepregs, each prepreg built up of three uni-directional glass fiber layers laid in longitudinal and transverse directions. Laminates with prepregs of E-Glass and S-Glass fibers are investigated separately under uni-axial tension. Yield strengths of both the Glare variants are found to be less than that of aluminum alloy with use of S-Glass fiber resulting in higher laminate yield strength than with the use of E-Glass fiber. Results from finite element analysis and tensile tests conducted over the laminates substantiate the theoretical model.

Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

DEFF Research Database (Denmark)

Diouf, Abdoul Aziz; Hiernaux, Pierre; Brandt, Martin Stefan

2016-01-01

evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483...... kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase...

FlorNExT®, a cloud computing application to estimate growth and yield of maritime pine (Pinus pinaster Ait. stands in Northeastern Portugal

Directory of Open Access Journals (Sweden)

Fernando Pérez-Rodríguez

2016-07-01

Full Text Available Aim of the study: To introduce and describe FlorNExT®, a free cloud computing application to estimate growth and yield of maritime pine (Pinus pinaster Ait. even-aged stands in the Northeast of Portugal (NE Portugal. Area of study: NE Portugal. Material and methods: FlorNExT® implements a dynamic growth and yield modelling framework which integrates transition functions for dominant height (site index curves and basal area, as well as output functions for tree and stand volume, biomass, and carbon content. Main results: FlorNExT® is freely available from any device with an Internet connection at: http://flornext.esa.ipb.pt/. Research highlights: This application has been designed to make it possible for any stakeholder to easily estimate standing volume, biomass, and carbon content in maritime pine stands from stand data, as well as to estimate growth and yield based on four stand variables: age, density, dominant height, and basal area. FlorNExT® allows planning thinning treatments. FlorNExT® is a fundamental tool to support forest mobilization at local and regional scales in NE Portugal. Keywords: forest management; maritime pine; forest modelling; knowledge transfer tool.

A comparison of short-term dispersion estimates resulting from various atmospheric stability classification methods

International Nuclear Information System (INIS)

Mitchell, A.E. Jr.

1982-01-01

Four methods of classifying atmospheric stability class are applied at four sites to make short-term (1-h) dispersion estimates from a ground-level source based on a model consistent with U.S. Nuclear Regulatory Commission practice. The classification methods include vertical temperature gradient, standard deviation of horizontal wind direction fluctuations (sigma theta), Pasquill-Turner, and modified sigma theta which accounts for meander. Results indicate that modified sigma theta yields reasonable dispersion estimates compared to those produced using methods of vertical temperature gradient and Pasquill-Turner, and can be considered as a potential economic alternative in establishing onsite monitoring programs. (author)

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

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

Science.gov (United States)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Methods for measurement of electron emission yield under low energy electron-irradiation by collector method and Kelvin probe method

Energy Technology Data Exchange (ETDEWEB)

Tondu, Thomas; Belhaj, Mohamed; Inguimbert, Virginie [Onera, DESP, 2 Avenue Edouard Belin, 31400 Toulouse (France); Onera, DESP, 2 Avenue Edouard Belin, 31400 Toulouse, France and Fondation STAE, 4 allee Emile Monso, BP 84234-31432, Toulouse Cedex 4 (France); Onera, DESP, 2 Avenue Edouard Belin, 31400 Toulouse (France)

2010-09-15

Secondary electron emission yield of gold under electron impact at normal incidence below 50 eV was investigated by the classical collector method and by the Kelvin probe method. The authors show that biasing a collector to ensure secondary electron collection while keeping the target grounded can lead to primary electron beam perturbations. Thus reliable secondary electron emission yield at low primary electron energy cannot be obtained with a biased collector. The authors present two collector-free methods based on current measurement and on electron pulse surface potential buildup (Kelvin probe method). These methods are consistent, but at very low energy, measurements become sensitive to the earth magnetic field (below 10 eV). For gold, the authors can extrapolate total emission yield at 0 eV to 0.5, while a total electron emission yield of 1 is obtained at 40{+-}1 eV.

Methods for measurement of electron emission yield under low energy electron-irradiation by collector method and Kelvin probe method

International Nuclear Information System (INIS)

Tondu, Thomas; Belhaj, Mohamed; Inguimbert, Virginie

2010-01-01

Secondary electron emission yield of gold under electron impact at normal incidence below 50 eV was investigated by the classical collector method and by the Kelvin probe method. The authors show that biasing a collector to ensure secondary electron collection while keeping the target grounded can lead to primary electron beam perturbations. Thus reliable secondary electron emission yield at low primary electron energy cannot be obtained with a biased collector. The authors present two collector-free methods based on current measurement and on electron pulse surface potential buildup (Kelvin probe method). These methods are consistent, but at very low energy, measurements become sensitive to the earth magnetic field (below 10 eV). For gold, the authors can extrapolate total emission yield at 0 eV to 0.5, while a total electron emission yield of 1 is obtained at 40±1 eV.

Distributed specific sediment yield estimations in Japan attributed to extreme-rainfall-induced slope failures under a changing climate

Directory of Open Access Journals (Sweden)

K. Ono

2011-01-01

Full Text Available The objective of this study was to estimate the potential sediment yield distribution in Japan attributed to extreme-rainfall-induced slope failures in the future. For this purpose, a regression relationship between the slope failure probability and the subsequent sediment yield was developed by using sediment yield observations from 59 dams throughout Japan. The slope failure probability accounts for the effects of topography (as relief energy, geology and hydro-climate variations (hydraulic gradient changes due to extreme rainfall variations and determines the potential slope failure occurrence with a 1-km resolution. The applicability of the developed relationship was then validated by comparing the simulated and observed sediment yields in another 43 dams. To incorporate the effects of a changing climate, extreme rainfall variations were estimated by using two climate change scenarios (the MRI-RCM20 Ver.2 model A2 scenario and the MIROC A1B scenario for the future and by accounting for the slope failure probability through the effect of extreme rainfall on the hydraulic gradient. Finally, the developed slope failure hazard-sediment yield relationship was employed to estimate the potential sediment yield distribution under a changing climate in Japan.

Time series analyses of annual sediment yields covering 15–20 years in 59 dams reveal that extreme sedimentation events have a high probability of occurring on average every 5–7 years. Therefore, the extreme-rainfall-induced slope failure probability with a five-year return period has a statistically robust relationship with specific sediment yield observations (with r² = 0.65. The verification demonstrated that the model is effective for use in simulating specific sediment yields with r² = 0.74. The results of the GCM scenarios suggest that the sediment yield issue will be critical in Japan in the future. When the spatially averaged sediment

A Remote Sensing-Derived Corn Yield Assessment Model

Science.gov (United States)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could

Remote sensing and gis based wheat crop acreage and yield estimation of district hyderabad, pakistan

International Nuclear Information System (INIS)

Siyal, A.

2015-01-01

Pre-harvest reliable and timely yield forecast and area estimates of cropped area is vital to planners and policy makers for making important and timely decisions with respect to food security in a country. The present study was conducted to estimate the wheat cropped area and crop yield in Hyderabad District, Pakistan from the Landsat 8 satellite imagery for Rabi 2013-14 and ground trothing. The required imagery of district Hyderabad was acquired from GLOVIS and was classified with maximum likelihood algorithm using ArcGIS 10.1. The classified image revealed that in district Hyderabad wheat covered 10,210 hectares (9.74% of total area) during Rabi season 2013-14 against 15,000 hectares (14.3% of total area) reported by Crop reporting Services (CRS), Sindh which is 30% less than that of reported by CRS. A positive linear relation between the wheat crop yield and the peak NDVI with coefficient of determination R2 = 0.91 was observed. Crop area and yield forecast through remote sensing is easy, cost effective, quick and reliable hence this technology needs to be introduced and propagated in the concerned government departments of Pakistan. (author)

Are rapid population estimates accurate? A field trial of two different assessment methods.

Science.gov (United States)

Grais, Rebecca F; Coulombier, Denis; Ampuero, Julia; Lucas, Marcelino E S; Barretto, Avertino T; Jacquier, Guy; Diaz, Francisco; Balandine, Serge; Mahoudeau, Claude; Brown, Vincent

2006-09-01

Emergencies resulting in large-scale displacement often lead to populations resettling in areas where basic health services and sanitation are unavailable. To plan relief-related activities quickly, rapid population size estimates are needed. The currently recommended Quadrat method estimates total population by extrapolating the average population size living in square blocks of known area to the total site surface. An alternative approach, the T-Square, provides a population estimate based on analysis of the spatial distribution of housing units taken throughout a site. We field tested both methods and validated the results against a census in Esturro Bairro, Beira, Mozambique. Compared to the census (population: 9,479), the T-Square yielded a better population estimate (9,523) than the Quadrat method (7,681; 95% confidence interval: 6,160-9,201), but was more difficult for field survey teams to implement. Although applicable only to similar sites, several general conclusions can be drawn for emergency planning.

Machine-smoking studies of cigarette filter color to estimate tar yield by visual assessment and through the use of a colorimeter.

Science.gov (United States)

Morton, Michael J; Williams, David L; Hjorth, Heather B; Smith, Jennifer H

2010-04-01

This paper explores using the intensity of the stain on the end of the filter ("filter color") as a vehicle for estimating cigarette tar yield, both by instrument reading of the filter color and by visual comparison to a template. The correlation of machine-measured tar yield to filter color measured with a colorimeter was reasonably strong and was relatively unaffected by different puff volumes or different tobacco moistures. However, the correlation of filter color to machine-measured nicotine yield was affected by the moisture content of the cigarette. Filter color, as measured by a colorimeter, was generally comparable to filter extraction of either nicotine or solanesol in its correlation to machine-smoked tar yields. It was found that the color of the tar stain changes over time. Panelists could generally correctly order the filters from machine-smoked cigarettes by tar yield using the intensity of the tar stain. However, there was considerable variation in the panelist-to-panelist tar yield estimates. The wide person-to-person variation in tar yield estimates, and other factors discussed in the text could severely limit the usefulness and practicality of this approach for visually estimating the tar yield of machine-smoked cigarettes. Copyright 2009 Elsevier Inc. All rights reserved.

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.

Estimation of the Hiroshima bomb yield and weather conditions at the time of the bomb

International Nuclear Information System (INIS)

Tajima, Eizo

1984-01-01

The results of the survey made immediately after the bombings in Hiroshima and Nagasaki were compiled in Collection of Reports on the Investigation of the Atomic Bomb Casualties published in 1953. Much valuable information for the reassessment of dose are included in this document. One of the major problems to be solved for the dose reassessment is the yield of the Hiroshima bomb. Two articles with relatively detailed description were selected, and the estimation of the yield was attempted, based on them. The data on roof tile melting were used for the purpose. Assuming the yield of the Nagasaki bomb as 22 kt, the yield of the Hiroshima bomb was given as 12.4 kt. By the experiment using the charred state of cypress boards, the total radiant energy from the bomb was calculated as 4.6 x 10 12 cal, and the yield of the Hiroshima bomb was estimated as 14.2 kt and 13.2 kt. The true value is likely between 12 and 13 kt. The vapor pressure at the time of bombing significantly affected the neutron spectrum. On the day of bombing, Japan was covered by hot, humid maritime air mass, namely summer monsoon pattern. The air density and water vapor content in the atmosphere were determined by the Japan Weather Association, and compared with the data of Dr. Kerr et al. (Kako, I.)

Experimental formulas and curves for estimating reactivity loss and radio-isotope yields on HWRR

International Nuclear Information System (INIS)

Liu Xi Zhi; Zhu HuanNan

1999-01-01

Based on the elemental conception of reactor physics and experiments on HWRR for years. A set of experimental formulas and curves has been got, which can be used to estimate reactivity loss and radio isotopes yield. (author)

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Directory of Open Access Journals (Sweden)

Makram J. Geha

2011-01-01

Full Text Available Milk yield records (305d, 2X, actual milk yield of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e ,quadratic regression, (y = β0 + β1X + β2X2 + e cubic regression (y = β0 + β1X + β2X2 + β3X3 + e and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc. The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as "traditional", AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used.

Using normalized difference vegetation index (NDVI) to estimate sugarcane yield and yield components

Science.gov (United States)

Sugarcane (Saccharum spp.) yield and yield components are important traits for growers and scientists to evaluate and select cultivars. Collection of these yield data would be labor intensive and time consuming in the early selection stages of sugarcane breeding cultivar development programs with a ...

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

Inter-annual variations in water yield to lakes in northeastern Alberta: implications for estimating critical loads of acidity

Directory of Open Access Journals (Sweden)

Roderick HAZEWINKEL

2010-08-01

Full Text Available Stable isotopes of water were applied to estimate water yield to fifty lakes in northeastern Alberta as part of an acid sensitivity study underway since 2002 in the Athabasca Oil Sands Region (AOSR. Herein, we apply site-specific water yields for each lake to calculate critical loads of acidity using water chemistry data and a steady-state water chemistry model. The main goal of this research was to improve site-specific critical load estimates and to understand the sensitivity to hydrologic variability across a Boreal Plains region under significant oil sands development pressure. Overall, catchment water yields were found to vary significantly over the seven year monitoring period, with distinct variations among lakes and between different regions, overprinted by inter-annual climate-driven shifts. Analysis of critical load estimates based on site-specific water yields suggests that caution must be applied to establish hydrologic conditions and define extremes at specific sites in order to protect more sensitive ecosystems. In general, lakes with low (high water yield tended to be more (less acid sensitive but were typically less (more affected by interannual hydrological variations. While it has been customary to use long-term water yields to define a static critical load for lakes, we find that spatial and temporal variability in water yield may limit effectiveness of this type of assessment in areas of the Boreal Plain characterized by heterogeneous runoff and without a long-term lake-gauging network. Implications for predicting acidification risk are discussed for the AOSR.

Accounting for the decrease of photosystem photochemical efficiency with increasing irradiance to estimate quantum yield of leaf photosynthesis.

Science.gov (United States)

Yin, Xinyou; Belay, Daniel W; van der Putten, Peter E L; Struik, Paul C

2014-12-01

Maximum quantum yield for leaf CO2 assimilation under limiting light conditions (Φ CO2LL) is commonly estimated as the slope of the linear regression of net photosynthetic rate against absorbed irradiance over a range of low-irradiance conditions. Methodological errors associated with this estimation have often been attributed either to light absorptance by non-photosynthetic pigments or to some data points being beyond the linear range of the irradiance response, both causing an underestimation of Φ CO2LL. We demonstrate here that a decrease in photosystem (PS) photochemical efficiency with increasing irradiance, even at very low levels, is another source of error that causes a systematic underestimation of Φ CO2LL. A model method accounting for this error was developed, and was used to estimate Φ CO2LL from simultaneous measurements of gas exchange and chlorophyll fluorescence on leaves using various combinations of species, CO2, O2, or leaf temperature levels. The conventional linear regression method under-estimated Φ CO2LL by ca. 10-15%. Differences in the estimated Φ CO2LL among measurement conditions were generally accounted for by different levels of photorespiration as described by the Farquhar-von Caemmerer-Berry model. However, our data revealed that the temperature dependence of PSII photochemical efficiency under low light was an additional factor that should be accounted for in the model.

Estimates of genetics and phenotypics parameters for the yield and quality of soybean seeds.

Science.gov (United States)

Zambiazzi, E V; Bruzi, A T; Guilherme, S R; Pereira, D R; Lima, J G; Zuffo, A M; Ribeiro, F O; Mendes, A E S; Godinho, S H M; Carvalho, M L M

2017-09-27

Estimating genotype x environment (GxE) parameters for quality and yield in soybean seed grown in different environments in Minas Gerais State was the goal of this study, as well as to evaluate interaction effects of GxE for soybean seeds yield and quality. Seeds were produced in three locations in Minas Gerais State (Lavras, Inconfidentes, and Patos de Minas) in 2013/14 and 2014/15 seasons. Field experiments were conducted in randomized blocks in a factorial 17 x 6 (GxE), and three replications. Seed yield and quality were evaluated for germination in substrates paper and sand, seedling emergence, speed emergency index, mechanical damage by sodium hypochlorite, electrical conductivity, speed aging, vigor and viability of seeds by tetrazolium test in laboratory using completely randomized design. Quadratic component genotypic, GXE variance component, genotype determination coefficient, genetic variation coefficient and environmental variation coefficient were estimated using the Genes software. Percentage analysis of genotypes contribution, environments and genotype x environment interaction were conducted by sites combination two by two and three sites combination, using the R software. Considering genotypes selection of broad adaptation, TMG 1179 RR, CD 2737 RR, and CD 237 RR associated better yield performance at high physical and physiological potential of seed. Environmental effect was more expressive for most of the characters related to soybean seed quality. GxE interaction effects were expressive though genotypes did not present coincidental behavior in different environments.

Electrical estimating methods

CERN Document Server

Del Pico, Wayne J

2014-01-01

Simplify the estimating process with the latest data, materials, and practices Electrical Estimating Methods, Fourth Edition is a comprehensive guide to estimating electrical costs, with data provided by leading construction database RS Means. The book covers the materials and processes encountered by the modern contractor, and provides all the information professionals need to make the most precise estimate. The fourth edition has been updated to reflect the changing materials, techniques, and practices in the field, and provides the most recent Means cost data available. The complexity of el

A method for developing a large-scale sediment yield index for European river basins

Energy Technology Data Exchange (ETDEWEB)

Delmas, Magalie; Cerdan, Olivier; Garcin, Manuel [BRGM ARN/ESL, Orleans (France); Mouchel, Jean-Marie [UMR Sisyphe, Univ. P and M Curie, Paris (France)

2009-12-15

Background, aim, and scope: Sediment fluxes within continental areas play a major role in biogeochemical cycles and are often the cause of soil surface degradation as well as water and ecosystem pollution. In a situation where a high proportion of the land surface is experiencing significant global land use and climate changes, it appears important to establish sediment budgets considering the major processes forcing sediment redistribution within drainage areas. In this context, the aim of this study is to test a methodology to estimate a sediment yield index at a large spatial resolution for European river basins. Data and methods: Four indicators representing processes respectively considered as sources (mass movement and hillslope erosion), sinks (deposits), and transfers of sediments (drainage density) are defined using distributed data. Using these indicators we propose a basic conceptual approach to test the possibility of explaining sediment yield observed at the outlet of 29 selected European river basins. We propose an index which adds the two sources and transfers, and subsequently subtracts the sink term. This index is then compared to observed sediment yield data. Results: With this approach, variability between river basins is observed and the evolution of each indicator analyzed. A linear regression shows a correlation coefficient of 0.83 linking observed specific sediment yield (SSY) with the SSY index. Discussion: To improve this approach at this large river basin scale, basin classification is further refined using the relation between the observed SSY and the index obtained from the four indicators. It allows a refinement of the results. Conclusions: This study presents a conceptual approach offering the advantages of using spatially distributed data combined with major sediment redistribution processes to estimate the sediment yield observed at the outlet of river basins. Recommendations and perspectives: Inclusion of better information on

Materials and methods to increase plant growth and yield

Science.gov (United States)

Kirst, Matias

2017-05-16

The present invention relates to materials and methods for modulating growth rates, yield, and/or resistance to drought conditions in plants. In one embodiment, a method of the invention comprises increasing expression of an hc1 gene (or a homolog thereof that provides for substantially the same activity), or increasing expression or activity of the protein encoded by an hc1 gene thereof, in a plant, wherein expression of the hc1 gene or expression or activity of the protein encoded by an hc1 gene results in increased growth rate, yield, and/or drought resistance in the plant.

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

Analysis of meteorological variations on wheat yield and its estimation using remotely sensed data. A case study of selected districts of Punjab Province, Pakistan (2001-14

Directory of Open Access Journals (Sweden)

Rafia Mumtaz

2017-10-01

method is capable of providing yield estimates with competitive accuracies prior to crop harvest, which can significantly aid the policy guidance and contributes to better and timely decisions.

Crop yield, genetic parameter estimation and selection of sacha inchi in central Amazon

Directory of Open Access Journals (Sweden)

Mágno Sávio Ferreira Valente

2017-06-01

Full Text Available In Brazil, sacha inchi oil is produced by hand from plant materials with no breeding or detailed information about the chemical composition of seeds. In addition, most of the current information on the agronomic traits of this species originates from research carried out in the Peruvian Amazon. In order to promote the research and cultivation of sacha inchi in the Brazilian territory, this study aimed to analyze, in the central Amazon region, different accessions of this oilseed for characteristics of production and quality of fruits and seeds, as well as to estimate genetic parameters, through mixed models, with identification of superior accessions, for breeding purposes. A total of 37 non-domesticated accessions were evaluated in a randomized block design, with five replications and two plants per plot. The average oil content in seeds was 29.07 % and unsaturated fatty acids amounted to 91.5 % of the total fat content. For the yield traits, the estimates of individual broad-sense heritability were moderate (~0.33, while the heritability based on the average of progenies resulted in a selective accuracy of approximately 0.85. The use of the selection index provided simultaneous gains for yield traits (> 40 % and oil yield. A high genetic variability was observed for the main traits of commercial interest for the species, as well as promising perspectives for the development of superior varieties for agro-industrial use.

Yield estimation using SPOT-VEGETATION products: A case study of wheat in European countries

NARCIS (Netherlands)

Kowalik, W.; Dabrowska-Zielinska, K.; Meroni, M.; Raczka, T.U.; Wit, de A.J.W.

2014-01-01

In the period 1999-2009 ten-day SPOT-VEGETATION products of the Normalized Difference Vegetation Index (NDVI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 1 km spatial resolution were used in order to estimate and forecast the wheat yield over Europe. The products were

Comparison of methods used to estimate conventional undiscovered petroleum resources: World examples

Science.gov (United States)

Ahlbrandt, T.S.; Klett, T.R.

2005-01-01

Various methods for assessing undiscovered oil, natural gas, and natural gas liquid resources were compared in support of the USGS World Petroleum Assessment 2000. Discovery process, linear fractal, parabolic fractal, engineering estimates, PETRIMES, Delphi, and the USGS 2000 methods were compared. Three comparisons of these methods were made in: (1) the Neuquen Basin province, Argentina (different assessors, same input data); (2) provinces in North Africa, Oman, and Yemen (same assessors, different methods); and (3) the Arabian Peninsula, Arabian (Persian) Gulf, and North Sea (different assessors, different methods). A fourth comparison (same assessors, same assessment methods but different geologic models), between results from structural and stratigraphic assessment units in the North Sea used only the USGS 2000 method, and hence compared the type of assessment unit rather than the method. In comparing methods, differences arise from inherent differences in assumptions regarding: (1) the underlying distribution of the parent field population (all fields, discovered and undiscovered), (2) the population of fields being estimated; that is, the entire parent distribution or the undiscovered resource distribution, (3) inclusion or exclusion of large outlier fields; (4) inclusion or exclusion of field (reserve) growth, (5) deterministic or probabilistic models, (6) data requirements, and (7) scale and time frame of the assessment. Discovery process, Delphi subjective consensus, and the USGS 2000 method yield comparable results because similar procedures are employed. In mature areas such as the Neuquen Basin province in Argentina, the linear and parabolic fractal and engineering methods were conservative compared to the other five methods and relative to new reserve additions there since 1995. The PETRIMES method gave the most optimistic estimates in the Neuquen Basin. In less mature areas, the linear fractal method yielded larger estimates relative to other methods

Human body mass estimation: a comparison of "morphometric" and "mechanical" methods.

Science.gov (United States)

Auerbach, Benjamin M; Ruff, Christopher B

2004-12-01

In the past, body mass was reconstructed from hominin skeletal remains using both "mechanical" methods which rely on the support of body mass by weight-bearing skeletal elements, and "morphometric" methods which reconstruct body mass through direct assessment of body size and shape. A previous comparison of two such techniques, using femoral head breadth (mechanical) and stature and bi-iliac breadth (morphometric), indicated a good general correspondence between them (Ruff et al. [1997] Nature 387:173-176). However, the two techniques were never systematically compared across a large group of modern humans of diverse body form. This study incorporates skeletal measures taken from 1,173 Holocene adult individuals, representing diverse geographic origins, body sizes, and body shapes. Femoral head breadth, bi-iliac breadth (after pelvic rearticulation), and long bone lengths were measured on each individual. Statures were estimated from long bone lengths using appropriate reference samples. Body masses were calculated using three available femoral head breadth (FH) formulae and the stature/bi-iliac breadth (STBIB) formula, and compared. All methods yielded similar results. Correlations between FH estimates and STBIB estimates are 0.74-0.81. Slight differences in results between the three FH estimates can be attributed to sampling differences in the original reference samples, and in particular, the body-size ranges included in those samples. There is no evidence for systematic differences in results due to differences in body proportions. Since the STBIB method was validated on other samples, and the FH methods produced similar estimates, this argues that either may be applied to skeletal remains with some confidence. 2004 Wiley-Liss, Inc.

Effects of Salinity and Nitrogen Application Methods on Yield and Yield Components of Wheat (Triticum aestivum L.

Directory of Open Access Journals (Sweden)

R Farshid

2012-07-01

Full Text Available To evaluate interaction of salinity stress and nitrogen use methods on yield and yield components, in experiment was conducted in split plot in randomized complete block with 3 replications. Treatments included: salinity of irrigation water levels 1.5, 4.4 and 7.9 ds/m as main plots, and nitrogen treatments 1. using N fertilizer at 3 stage in soil, 2. using two third N fertilizer in soil at planting and tillering and heading and one third in form of foliar application of N at tillering, 4. using and one third in form of foliar application at heading, 3. Using two third of N fertilizer in soil at planting one third of N fertilizer in soil at planting and two third in form of foliar application at tillering and heading, as sub plots. Results this study showed that increased in salt stress significant decreased total yield components such that showed decrease 41/5 kg/h in yield with increase in per unite salinity. Also methods of nitrogen application in salinity condition, have significant effects on total yield components. At the tillering, one stage of foliar with soil application of urea could increase spike no. m-2 and kernels of spike compared with other treatments. Foliar application of urea at heading stage increased kernels weight.

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

A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China

Directory of Open Access Journals (Sweden)

Dengxiao Lang

2017-09-01

Full Text Available Potential evapotranspiration (PET is crucial for water resources assessment. In this regard, the FAO (Food and Agriculture Organization–Penman–Monteith method (PM is commonly recognized as a standard method for PET estimation. However, due to requirement of detailed meteorological data, the application of PM is often constrained in many regions. Under such circumstances, an alternative method with similar efficiency to that of PM needs to be identified. In this study, three radiation-based methods, Makkink (Mak, Abtew (Abt, and Priestley–Taylor (PT, and five temperature-based methods, Hargreaves–Samani (HS, Thornthwaite (Tho, Hamon (Ham, Linacre (Lin, and Blaney–Criddle (BC, were compared with PM at yearly and seasonal scale, using long-term (50 years data from 90 meteorology stations in southwest China. Indicators, viz. (videlicet Nash–Sutcliffe efficiency (NSE, relative error (Re, normalized root mean squared error (NRMSE, and coefficient of determination (R2 were used to evaluate the performance of PET estimations by the above-mentioned eight methods. The results showed that the performance of the methods in PET estimation varied among regions; HS, PT, and Abt overestimated PET, while others underestimated. In Sichuan basin, Mak, Abt and HS yielded similar estimations to that of PM, while, in Yun-Gui plateau, Abt, Mak, HS, and PT showed better performances. Mak performed the best in the east Tibetan Plateau at yearly and seasonal scale, while HS showed a good performance in summer and autumn. In the arid river valley, HS, Mak, and Abt performed better than the others. On the other hand, Tho, Ham, Lin, and BC could not be used to estimate PET in some regions. In general, radiation-based methods for PET estimation performed better than temperature-based methods among the selected methods in the study area. Among the radiation-based methods, Mak performed the best, while HS showed the best performance among the temperature

Influence of micronutrients and their method of application on yield and yield components of sunflower

International Nuclear Information System (INIS)

Baraich, A.A.K.; Gandahi, A.W.

2016-01-01

The sunflower (Helianthus annuus L.) has been recognized as a crop with high potentials that can successfully meet future oil requirements of the country. Formulation of micronutrients (MN) based fertilizer, in terms of application rate and method, and uptake of MN by sunflower has the ability not only to ensure nutrients availability to plants particularly in MN-limiting environments but also can manipulate the environmental hazards associated with over inorganic fertilization. To support this view, clear experimental evidence is still lacking. In addition, the current experiments aimed to evaluate the influence of MN and its method of application on yield and yield components of sunflower cultivars/hybrids. Three sunflower cultivars (HO-1, Hysun-39 and Ausigold-62) along with three MN (Z, B and Fe) and two application methods (soil and foliar) were used in the experiment. Three Zn application rate (3, 5 and 8 kg ha-1) along with 0.75 kg ha-1 B and 0.30 kg Fe ha-1 were used in four combinations such as 0-0-0, 0-0.75-0.30, 0-0.75-0.30, 3-0.75-0.30, 5-0.75-0.30, 8-0.75-0.30 kg Z, B and Fe ha-1, respectively. A control (no MN) treatment was also included for comparison. Two year averaged study exhibited that foliar application of Zn, B and Fe at rate of 8-0.30-0.75 kg ha-1 increased stem girth, head diameter, number of seeds head-1, seed weight head-1, seed index, oil content and seed yield by 21%, 27%, 13%, 34%, 19%, 24 and 31%, respectively over control. Among cultivars/hybrids, the hybrids HO-1 and Hysun-39 had taller plants, seed weight head-1, seeds head-1 and earlier in flowering and maturity. Flowering and maturity was delayed in Ausi Gold-62 with higher seed index and oil content. It is concluded that foliar application of micronutrients at the rate of 8+0.75+0.30 Zn, B and Fe kg ha-1 had substantially improved yield and yield related traits of sunflower cultivars HO-1, Hysun-39 and Ausi gold-62. (author)

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.

Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.

Science.gov (United States)

Antwi, Philip; Li, Jianzheng; Boadi, Portia Opoku; Meng, Jia; Shi, En; Deng, Kaiwen; Bondinuba, Francis Kwesi

2017-03-01

Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW). Anaerobic process parameters were optimized to identify their importance on methanation. pH, total chemical oxygen demand, ammonium, alkalinity, total Kjeldahl nitrogen, total phosphorus, volatile fatty acids and hydraulic retention time selected based on principal component analysis were used as input variables, whiles biogas and methane yield were employed as target variables. Quasi-Newton method and conjugate gradient backpropagation algorithms were best among eleven training algorithms. Coefficient of determination (R 2 ) of the BP-ANN reached 98.72% and 97.93% whiles MnLR model attained 93.9% and 91.08% for biogas and methane yield, respectively. Compared with the MnLR model, BP-ANN model demonstrated significant performance, suggesting possible control of the anaerobic digestion process with the BP-ANN model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive Methods for Permeability Estimation and Smart Well Management

Energy Technology Data Exchange (ETDEWEB)

Lien, Martha Oekland

2005-04-01

The main focus of this thesis is on adaptive regularization methods. We consider two different applications, the inverse problem of absolute permeability estimation and the optimal control problem of estimating smart well management. Reliable estimates of absolute permeability are crucial in order to develop a mathematical description of an oil reservoir. Due to the nature of most oil reservoirs, mainly indirect measurements are available. In this work, dynamic production data from wells are considered. More specifically, we have investigated into the resolution power of pressure data for permeability estimation. The inversion of production data into permeability estimates constitutes a severely ill-posed problem. Hence, regularization techniques are required. In this work, deterministic regularization based on adaptive zonation is considered, i.e. a solution approach with adaptive multiscale estimation in conjunction with level set estimation is developed for coarse scale permeability estimation. A good mathematical reservoir model is a valuable tool for future production planning. Recent developments within well technology have given us smart wells, which yield increased flexibility in the reservoir management. In this work, we investigate into the problem of finding the optimal smart well management by means of hierarchical regularization techniques based on multiscale parameterization and refinement indicators. The thesis is divided into two main parts, where Part I gives a theoretical background for a collection of research papers that has been written by the candidate in collaboration with others. These constitutes the most important part of the thesis, and are presented in Part II. A brief outline of the thesis follows below. Numerical aspects concerning calculations of derivatives will also be discussed. Based on the introduction to regularization given in Chapter 2, methods for multiscale zonation, i.e. adaptive multiscale estimation and refinement

Frost trends and their estimated impact on yield in the Australian wheatbelt.

Science.gov (United States)

Zheng, Bangyou; Chapman, Scott C; Christopher, Jack T; Frederiks, Troy M; Chenu, Karine

2015-06-01

Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957-2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20% through (i) reduced frost damage (~10% improvement) and (ii) the ability to use earlier sowing dates (adding a further 10% improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Estimated suspended-sediment loads and yields in the French and Brandywine Creek Basins, Chester County, Pennsylvania, water years 2008-09

Science.gov (United States)

Sloto, Ronald A.; Olson, Leif E.

2011-01-01

Turbidity and suspended-sediment concentration data were collected by the U.S. Geological Survey (USGS) at four stream stations--French Creek near Phoenixville, West Branch Brandywine Creek near Honey Brook, West Branch Brandywine Creek at Modena, and East Branch Brandywine Creek below Downingtown--in Chester County, Pa. Sedimentation and siltation is the leading cause of stream impairment in Chester County, and these data are critical for quantifying sediment transport. This study was conducted by the USGS in cooperation with the Chester County Water Resources Authority and the Chester County Health Department. Data from optical turbidity sensors deployed at the four stations were recorded at 15- or 30-minute intervals by a data logger and uploaded every 1 to 4 hours to the USGS database. Most of the suspended-sediment samples were collected using automated samplers. The use of optical sensors to continuously monitor turbidity provided an accurate estimate of sediment fluctuations without the collection and analysis costs associated with intensive sampling during storms. Turbidity was used as a surrogate for suspended-sediment concentration (SSC), which is a measure of sedimentation and siltation. Regression models were developed between SSC and turbidity for each of the monitoring stations using SSC data collected from the automated samplers and turbidity data collected at each station. Instantaneous suspended-sediment loads (SSL) were computed from time-series turbidity and discharge data for the 2008 and 2009 water years using the regression equations. The instantaneous computations of SSL were summed to provide daily, storm, and water year annual loads. The annual SSL contributed from each basin was divided by the upstream drainage area to estimate the annual sediment yield. For all four basins, storms provided more than 96 percent of the annual SSL. In each basin, four storms generally provided over half the annual SSL each water year. Stormflows with the

Sampling designs and methods for estimating fish-impingement losses at cooling-water intakes

International Nuclear Information System (INIS)

Murarka, I.P.; Bodeau, D.J.

1977-01-01

Several systems for estimating fish impingement at power plant cooling-water intakes are compared to determine the most statistically efficient sampling designs and methods. Compared to a simple random sampling scheme the stratified systematic random sampling scheme, the systematic random sampling scheme, and the stratified random sampling scheme yield higher efficiencies and better estimators for the parameters in two models of fish impingement as a time-series process. Mathematical results and illustrative examples of the applications of the sampling schemes to simulated and real data are given. Some sampling designs applicable to fish-impingement studies are presented in appendixes

Estimating the number of HIV-infected injection drug users in Bangkok: a capture--recapture method.

Science.gov (United States)

Mastro, T D; Kitayaporn, D; Weniger, B G; Vanichseni, S; Laosunthorn, V; Uneklabh, T; Uneklabh, C; Choopanya, K; Limpakarnjanarat, K

1994-07-01

The purpose of the study was to estimate the number of injection drug users infected with the human immunodeficiency virus (HIV) in Bangkok to allow planning for health services for this population. A two-sample capture-recapture method was used. The first capture listed all persons on methadone treatment for opiate addiction from April 17 through May 17, 1991, at 18 facilities in Bangkok. The second capture involved urine testing of persons held at 72 Bangkok police stations from June 3 through September 30, 1991. Persons whose urine tests were positive for opiate metabolites or methadone were included on the second list. The first capture comprised 4064 persons and the recapture 1540 persons. There were 171 persons included on both lists, yielding an estimate of 36,600 opiate users in Bangkok. Existing data indicate that 89% of opiate users in Bangkok inject drugs and that about one third are infected with HIV, yielding an estimate of approximately 12,000 HIV-infected injection drug users in Bangkok in 1991. During the 1990s the number of cases of acquired immunodeficiency syndrome (AIDS) and other HIV-related diseases, including tuberculosis, in the population of HIV-infected injection drug users in Bangkok will increase dramatically, placing new demands on existing health care facilities. The capture-recapture method may be useful in estimating difficult-to-count populations, including injection drug users.

Estimation of variation and correlation analysis for yield components in black currant cultivars

Directory of Open Access Journals (Sweden)

Rakonjac Vera

2015-01-01

Full Text Available Creating genotypes that will be characterized by high yields, good quality and other favorable agronomic characters is a major objective of most currant breeding programs worldwide. For easier and faster achievement of these goals and identification of superior genotypes suitable for use as parents in future hybridization programs, study of genetic parameters seems to be obligatory. In this regard, the aims of our study were to estimate components of variability and heritability, and do correlation analysis for yield components in order to determine efficient strategies for improving yield in black currant breeding programs. Significant differences between cultivars were established for all studied traits. A high proportion of genotypic variance was found with bush width, no. of shoots per bush, bunch weight and berry weight indicating that genetic improvement for these traits through breeding was achievable. Opposite, seasonal variance was high for bush height, no. of bunch per bush and yield. The high heritability coefficients (0.80-0.94 detected for all traits studied reflect the close agreement between their phenotypic and genotypic values. Also, most pairs of traits were similarly correlated at both phenotypic and genotypic levels. So, yield was significantly and positively correlated with bush height, no of bunch per bush and bunch weight. These results imply a rapid response of black currants to selection. [Projekat Ministarstva nauke Republike Srbije, br. 46013 i FP7 Project AREA 316004

Unrecorded Alcohol Consumption: Quantitative Methods of Estimation

OpenAIRE

Razvodovsky, Y. E.

2010-01-01

unrecorded alcohol; methods of estimation In this paper we focused on methods of estimation of unrecorded alcohol consumption level. Present methods of estimation of unrevorded alcohol consumption allow only approximate estimation of unrecorded alcohol consumption level. Tacking into consideration the extreme importance of such kind of data, further investigation is necessary to improve the reliability of methods estimation of unrecorded alcohol consumption.

Estimating grain yield losses caused by septoria leaf blotch on durum wheat in Tunisia

Directory of Open Access Journals (Sweden)

Samia Berraies

2014-12-01

Full Text Available Septoria leaf blotch (SLB, caused by Zymoseptoria tritici (Desm. Quaedvlieg & Crous, 2011 (teleomorph: Mycosphaerella graminicola (Fuckel J. Schrot., is an important wheat disease in the Mediterranean region. In Tunisia, SLB has become a major disease of durum wheat (Triticum turgidum L. subsp. durum [Desf.] Husn. particularly during favorable growing seasons where significant yield losses and increase of fungicides use were recorded over the last three decades. The objectives of this study were to evaluate the effect of SLB severity on grain yield of new elite durum wheat breeding lines and to measure the relative effect of fungicide control on grain yield. Experiments were conducted during 2007-2008 and 2008-2009 cropping seasons. A set of 800 breeding lines were screened for reaction to SLB under natural infection at Beja research station. To estimate the disease effect, correlation between disease severity at early grain filling stage and grain yield was performed. Results showed that susceptible varieties yield was significantly reduced by SLB. Average yield reduction was as high as 384 and 325 kg ha-1 for every increment in disease severity on a 0-9 scale in both seasons, respectively. A negative correlation coefficient varied between -0.61 and -0.66 in both seasons. Treated and untreated trials conducted during 2008-2009 and 2009-2010 showed that yield of treated plots increased by 50% on the commonly cultivated susceptible varieties. The results of this investigation suggested that septoria incidence is related to large grain yield losses particularly on susceptible high yielding cultivars. However, appropriate fungicide application at booting growth stage could be beneficial for farmers. The development and use of more effective fungicide could be sought to alleviate the disease effects and therefore could be considered as a part of the integrated pest management and responsible use strategy on septoria leaf blotch in Tunisia.

Assessment of Cane Yields on Well-drained Ferralsols in the Sugar-cane Estate of Central Cameroon

Directory of Open Access Journals (Sweden)

Van Ranst, E.

1999-01-01

Full Text Available The potential yields of irrigated and of rainfed sugar-cane on three ferrallitic soil series, well represented in the Nkoteng sugar-cane estate of Central Cameroon, are estimated following different methods. The potential yield of irrigated sugar-cane is estimated from the total maximum evapotranspiration during the crop cycle. The potential yield of rainfed sugar-cane is estimated following two methods for the establishment of a water balance and for the determination of a yield reduction as a result of a water deficit. The calculated potential yields are higher than the observed ones. The yield reduction due to rain fed cropping can mainly be attributed to water shortage during the late yield formation and the ripening periods. A supplementary yield decline is due to a combined action of an acid soil reaction, a possible Al-toxicity a low base saturation, an inadequate CEC, organic matter content and P-availability which may adequately explain the actual yield level.

Methods for high yield production of terpenes

Energy Technology Data Exchange (ETDEWEB)

Kutchan, Toni; Higashi, Yasuhiro; Feng, Xiaohong

2017-01-03

Provided are enhanced high yield production systems for producing terpenes in plants via the expression of fusion proteins comprising various combinations of geranyl diphosphate synthase large and small subunits and limonene synthases. Also provided are engineered oilseed plants that accumulate monoterpene and sesquiterpene hydrocarbons in their seeds, as well as methods for producing such plants, providing a system for rapidly engineering oilseed crop production platforms for terpene-based biofuels.

High-yield Synthesis of Multiwalled Carbon Nanotube by Mechanothermal Method

Directory of Open Access Journals (Sweden)

Manafi SA

2009-01-01

Full Text Available Abstract This study reports on the mechanothermal synthesis of multiwalled carbon nanotube (MWCNTs from elemental graphite powder. Initially, high ultra-active graphite powder can be obtained by mechanical milling under argon atmosphere. Finally, the mechanical activation product is heat-treated at 1350°C for 2–4 h under argon gas flow. After heat-treatment, active graphite powders were successfully changed into MWCNTs with high purity. The XRD analyses showed that in the duration 150 h of milling, all the raw materials were changed to the desired materials. From the broadening of the diffraction lines in the XRD patterns, it was concluded that the graphite crystallites were nanosized, and raising the milling duration resulted in the fineness of the particles and the increase of the strain. The structure and morphology of MWCNTs were investigated using scanning electron microscopy (SEM and high-resolution transmission electron microscopy (HRTEM. The yield of MWCNTs was estimated through SEM and TEM observations of the as-prepared samples was to be about 90%. Indeed, mechanothermal method is of interest for fundamental understanding and improvement of commercial synthesis of carbon nanotubes (CNTs. As a matter of fact, the method of mechanothermal guarantees the production of MWCNTs suitable for different applications.

Heritability estimates for yield and related traits in bread wheat

International Nuclear Information System (INIS)

Din, R.; Jehan, S.; Ibraullah, A.

2009-01-01

A set of 22 experimental wheat lines along with four check cultivars were evaluated in in-irrigated and unirrgated environments with objectives to determine genetic and phenotypic variation and heritability estimates for yield and its traits- The two environments were statistically at par for physiological maturity, plant height, spikes m/sub -2/. spike lets spike/sup -1/ and 1000-grain weight. Highly significant genetic variability existed among wheat lines (P < 0.0 I) in the combined analysis across two test environments for traits except 1000- grain weight. Genotypes x environment interactions were non-significant for traits indicating consistent performance of lines in two test environments. However lines and check cultivars were two to five days early in maturity under unirrigated environment. Plant height, spikes m/sup -2/ and 1000-grain weight also reduced under unirrigated environments. Genetic variances were greater than Environmental variances for most of traits- Heritability estimates were of higher magnitude (0.74 to 0.96) for plant height, medium (0.31 to 0.56) for physiological maturity. spikelets spike/sup -1/ (unirrigated) and 1000-grain weight, and low for spikes m/sup -2/. (author)

Soybean (Glycine max L. Merr. Yield Gap Analysis using Boundary Line Method in Gorgan and Aliabad Katul

Directory of Open Access Journals (Sweden)

Alireza Nehbandani

2017-12-01

Full Text Available Introduction Increasing the production of crops has been a necessity to reach food security for growing population. Since "expanding acreage" is almost impossible, "increasing the yield per unit of area", is the only possible option. Closing the gap between actual yield and potential yield (yield gap is one of the important methods to increase yield per unit of area. It is necessary to increase yield to primarily identify the factors that contributing in the yield gap in each area. Recognizing potentials as well as the impact of each limiting factor on yield individually, plays an important role in determining the alternative management strategies to achieve maximum performance. Therefore, the present study was conducted in Gorgan and Aliabad Katul county for simultaneous recognition of best management practices, percentage of the affected fields, estimation of soybean yield potential and gaps using boundary line analysis. Material and Methods To quantify the production and estimation of soybean yield gap in Gorgan and Aliabad Katul, Farm management information of 224 soybean farms in the years 2010, 2011, 2013 and 2014 were collected. This information was collected through continuous farm monitoring during the growing season as along with face to face interviews with the farmers. Farms were selected by consulting with agricultural service centers expert in Gorgan and Aliabad districts. Based on the available information at the service centers, only farms , which is different in terms of acreage, cultural practices and harvesting operations were selected. In this study, by plotting the distribution of the yield obtained in each field as the dependent variable against the independent variables (crop management activities, using SAS software and an appropriate function was fitted on the upper edge of the data distribution. Results and Discussion The results showed that the average yield on the farms surveyed was 3507 Kg.ha-1 and by improving crop

Estimation of erosion and sedimentation yield in the Ucayali river basin, a Peruvian tributary of the Amazon River, using ground and satellite methods

Science.gov (United States)

Santini, William; Martinez, Jean-Michel; Guyot, Jean-Loup; Espinoza, Raul; Vauchel, Philippe; Lavado, Waldo

2014-05-01

Since 2003, the works of HYBAM observatory (www.ore-hybam.org) has allowed to quantify with accuracy, precision and over a long period Amazon's main rivers discharges and sediments loads. In Peru, a network of 8 stations is regularly gauged and managed in association with the national meteorological and Hydrological service (SENAMHI), the UNALM (National Agrological University of La Molina) and the National Water Agency (ANA). Nevertheless, some current processes of erosion and sedimentation in the foreland basins are still little known, both in volumes and in localization. The sedimentary contributions of Andean tributaries could be there considerable, masking a very strong sedimentation in subsidence zones localized between the control points of the HYBAM's network. The development of spatial techniques such as the Altimetry and reflectance measurement allows us today to complete the ground's network: HYBAM's works have allowed establishing a relation between surface concentration and reflectance in Amazonian rivers (Martinez et al., 2009, Espinoza et al., 2012) and reconstituting water levels series (Calmant et al., 2006, 2008). If the difficulty of calibration of these techniques increases towards the upstream, their use can allow a first characterization of the tributaries contributions and sedimentation zones. At world level, erosion and sedimentation yields in the upper Ucayali are exceptional, favored by a marked seasonality in this region (Espinoza et al., 2009, Lavado, 2010, Pépin et al., 2010) and the presence of cells of extreme precipitation ("Hotspots") (Johnson et al., 1976, Espinoza et al, 2009a). The upper Ucayali drainage basin is a Piggyback where the River run with a low slope, parallel to the Andean range, deposing by gravity hundred millions a year of sands, silts and clays. In this work, we thus propose an estimation of sedimentation and erosion yield in the Ucayali river basin using ground and satellite methods.

Estimating crop yields and crop evapotranspiration distributions from remote sensing and geospatial agricultural data

Science.gov (United States)

Smith, T.; McLaughlin, D.

2017-12-01

Growing more crops to provide a secure food supply to an increasing global population will further stress land and water resources that have already been significantly altered by agriculture. The connection between production and resource use depends on crop yields and unit evapotranspiration (UET) rates that vary greatly, over both time and space. For regional and global analyses of food security it is appropriate to treat yield and UET as uncertain variables conditioned on climatic and soil properties. This study describes how probability distributions of these variables can be estimated by combining remotely sensed land use and evapotranspiration data with in situ agronomic and soils data, all available at different resolutions and coverages. The results reveal the influence of water and temperature stress on crop yield at large spatial scales. They also provide a basis for stochastic modeling and optimization procedures that explicitly account for uncertainty in the environmental factors that affect food production.

The Effect of Rate and Application Method of Potassium on Yield and Yield Components of Cotton in Saline Condition

Directory of Open Access Journals (Sweden)

A Ardakani

2016-12-01

Full Text Available Introduction Salinity is a major abiotic stress that affects approximately 7% of the world’s total land area. Cotton (Gossypium barbadense L. is considered as one of the most important cash crops which is widely used for agricultural and industrial purposes. Although, cotton is classified as one of the most salt-tolerant major crops but its growth and development are adversely affected by soil or water salinity. Understanding salinity and fertilizer interaction can mitigate salinity stress and improving crop yield. Potassium (K is an essential nutrient that affects most of the biochemical and physiological processes that are involved in plant resistance to biotic and abiotic stresses. Proper management of K fertilizer is especially important in saline soils where K application might reduce the adverse effects of salinity on plant growth and yield. There is a little information about rate and application method of K on yield and yield component of cotton in saline condition. The objective of this study was to determine the effects of rate and application method of K on yield and yield component of cotton in soil and water saline condition. Materials and Methods The experiment was carried out at Sabzevar Agriculture and Natural Resources Research center (Haresabad, 30km southwest of Sabzevar (32◦32N, 51◦23E and 1630 above mean sea level,in 2014.This experiment was conducted as split plot design based on randomized complete block design with three replications. Factors were: K rate (75 and 150kg ha-1 Solopotash (containing 50% K2O and 18% S comprising the main plot and application method (25%at planting+25% at first flowering and 50%at early boll development (25P+25F+50B, 25%at planting+50% at first flowering and 25%at early boll development (25P+50F+25B, 25%at planting+25% at vegetative stage (5-8 leaves stage, 25% at first flowering and 25% at early boll development (25P+25V+25F+50B, 25% at planting+25% at vegetative stage and 50% at first

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.

Investigating the Importance of the Pocket-estimation Method in Pocket-based Approaches: An Illustration Using Pocket-ligand Classification.

Science.gov (United States)

Caumes, Géraldine; Borrel, Alexandre; Abi Hussein, Hiba; Camproux, Anne-Claude; Regad, Leslie

2017-09-01

Small molecules interact with their protein target on surface cavities known as binding pockets. Pocket-based approaches are very useful in all of the phases of drug design. Their first step is estimating the binding pocket based on protein structure. The available pocket-estimation methods produce different pockets for the same target. The aim of this work is to investigate the effects of different pocket-estimation methods on the results of pocket-based approaches. We focused on the effect of three pocket-estimation methods on a pocket-ligand (PL) classification. This pocket-based approach is useful for understanding the correspondence between the pocket and ligand spaces and to develop pharmacological profiling models. We found pocket-estimation methods yield different binding pockets in terms of boundaries and properties. These differences are responsible for the variation in the PL classification results that can have an impact on the detected correspondence between pocket and ligand profiles. Thus, we highlighted the importance of the pocket-estimation method choice in pocket-based approaches. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Directory of Open Access Journals (Sweden)

Javier Hernandez

2015-02-01

Full Text Available Plant breeding based on grain yield (GY is an expensive and time-consuming method, so new indirect estimation techniques to evaluate the performance of crops represent an alternative method to improve grain yield. The present study evaluated the ability of canopy reflectance spectroscopy at the range from 350 to 2500 nm to predict GY in a large panel (368 genotypes of wheat (Triticum aestivum L. through multivariate ridge regression models. Plants were treated under three water regimes in the Mediterranean conditions of central Chile: severe water stress (SWS, rain fed, mild water stress (MWS; one irrigation event around booting and full irrigation (FI with mean GYs of 1655, 4739, and 7967 kg∙ha−1, respectively. Models developed from reflectance data during anthesis and grain filling under all water regimes explained between 77% and 91% of the GY variability, with the highest values in SWS condition. When individual models were used to predict yield in the rest of the trials assessed, models fitted during anthesis under MWS performed best. Combined models using data from different water regimes and each phenological stage were used to predict grain yield, and the coefficients of determination (R2 increased to 89.9% and 92.0% for anthesis and grain filling, respectively. The model generated during anthesis in MWS was the best at predicting yields when it was applied to other conditions. Comparisons against conventional reflectance indices were made, showing lower predictive abilities. It was concluded that a Ridge Regression Model using a data set based on spectral reflectance at anthesis or grain filling represents an effective method to predict grain yield in genotypes under different water regimes.

Three methods to determine the yields of DNA double-strand breaks

International Nuclear Information System (INIS)

Erzgraeber, G.; Lapidus, I.L.

1985-01-01

A possibility of determining the yield of DNA double-strand breaks in cells of the Chinese hamster (V79-4) by finding the amount of DNA released as a result of breaks and by determining the relative sedimentation velocity of DNA-membrane complexes affected by ionizing radiations with different physical characteristics is discussed. Results of the analysis are compared with the data obtained by a traditional method of sedimentation in the neutral sucrose density gradient. Comparative characterization of the methods is discussed. The yields of DNA double-strand breaks determined by the suggested independent methods are in good agreement, which opens possibilities of studying induction and repair of double-strand breaks by means of simpler and more reliable methods

VARIABILITY OF YIELD AND YIELD COMPONENTS IN “EGUSI ...

African Journals Online (AJOL)

journal

Estimate of expected genetic advance in seed yield plant-1 ranged between. 25.90-48.40%. ..... values in fruit and seed yield characters have been reported in culinary melon, ... and Khund, A. 2004. Extent of heterosis and heritability in some.

Advances in regional crop yield estimation over the United States using satellite remote sensing data

Science.gov (United States)

Johnson, D. M.; Dorn, M. F.; Crawford, C.

2015-12-01

Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

Science.gov (United States)

Sulistyo, A.; Purwantoro; Sari, K. P.

2018-01-01

Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

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 ...

Using groundwater levels to estimate recharge

Science.gov (United States)

Healy, R.W.; Cook, P.G.

2002-01-01

Accurate estimation of groundwater recharge is extremely important for proper management of groundwater systems. Many different approaches exist for estimating recharge. This paper presents a review of methods that are based on groundwater-level data. The water-table fluctuation method may be the most widely used technique for estimating recharge; it requires knowledge of specific yield and changes in water levels over time. Advantages of this approach include its simplicity and an insensitivity to the mechanism by which water moves through the unsaturated zone. Uncertainty in estimates generated by this method relate to the limited accuracy with which specific yield can be determined and to the extent to which assumptions inherent in the method are valid. Other methods that use water levels (mostly based on the Darcy equation) are also described. The theory underlying the methods is explained. Examples from the literature are used to illustrate applications of the different methods.

PROMAB-GIS: A GIS based Tool for Estimating Runoff and Sediment Yield in running Waters

Science.gov (United States)

Jenewein, S.; Rinderer, M.; Ploner, A.; Sönser, T.

2003-04-01

In recent times settlements have expanded, traffic and tourist activities have increased in most alpine regions. As a consequence, on the one hand humans and goods are affected by natural hazard processes more often, while on the other hand the demand for protection by both technical constructions and planning measures carried out by public authorities is growing. This situation results in an ever stronger need of reproducibility, comparability, transparency of all methods applied in modern natural hazard management. As a contribution to a new way of coping this situation Promab-GIS Version 1.0 has been developed. Promab-Gis has been designed as a model for time- and space-dependent determination of both runoff and bedload transport in rivers of small alpine catchment areas. The estimation of the unit hydrograph relies upon the "rational formula" and the time-area curves of the watershed. The time area diagram is a graph of cumulative drainage area contributing to discharge at the watershed outlet within a specified time of travel. The sediment yield is estimated for each cell of the channel network by determining the actual process type (erosion, transport or accumulation). Two types of transport processes are considered, sediment transport and debris flows. All functions of Promab-GIS are integrated in the graphical user interface of ArcView as pull-up menus and tool buttons. Hence the application of Promab-GIS does not rely on a sophisticated knowledge of GIS in general, respectively the ArcView software. However, despite the use of computer assistance, Promab-GIS still is an expert support system. In order to obtain plausible results, the users must be familiar with all the relevant processes controlling runoff and sediment yield in torrent catchments.

A novel method of basal crevasse height estimation and subsequent rifting

Science.gov (United States)

Logan, L.; Catania, G. A.; Lavier, L. L.; Choi, E.

2012-12-01

Basal crevasses may play an important precursory role in the location and propagation of rifts and in ice shelf disintegration. Here we develop a novel method for estimating the locations and heights of basal crevasses formed at the grounding line of ice shelves and ice streams. We assume a thin-elastic beam formulation (TEB) with a tensional plastic yielding criterion to capture the physics of a tidally flexed grounding line. Observations of basal crevasses in the Siple Coast area match well with predictions produced by this method. Areas with large misfit can be delineated by examining the strain rate field; indeed, in our estimations those crevasses which deviate most from the TEB prediction lie directly in a shear margin. We test the method against other areas in the Larsen Ice Shelf, and find again a good match. Thus we suggest the TEB as an alternative to other crevasse estimation methods, as it produces a good fit in predominantly tensile regions, requires no tuning or prior information, and is computationally free to implement into large scale ice models which aim at physically simulating calving and fracture processes. We pursue modeling basal crevasses as they evolve with a thermomechanical finite-difference 3-dimensional model called SNAC. Viscoelastoplastic ice follows Mohr-Coulomb tension failure with Glen's flow law. We examine the conditions necessary for a basal crevasse formed on the downstream side of an ice rise to propagate the full thickness of the ice, developing into a rift.

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.

Boundary methods for mode estimation

Science.gov (United States)

Pierson, William E., Jr.; Ulug, Batuhan; Ahalt, Stanley C.

1999-08-01

This paper investigates the use of Boundary Methods (BMs), a collection of tools used for distribution analysis, as a method for estimating the number of modes associated with a given data set. Model order information of this type is required by several pattern recognition applications. The BM technique provides a novel approach to this parameter estimation problem and is comparable in terms of both accuracy and computations to other popular mode estimation techniques currently found in the literature and automatic target recognition applications. This paper explains the methodology used in the BM approach to mode estimation. Also, this paper quickly reviews other common mode estimation techniques and describes the empirical investigation used to explore the relationship of the BM technique to other mode estimation techniques. Specifically, the accuracy and computational efficiency of the BM technique are compared quantitatively to the a mixture of Gaussian (MOG) approach and a k-means approach to model order estimation. The stopping criteria of the MOG and k-means techniques is the Akaike Information Criteria (AIC).

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

Science.gov (United States)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Estimation of Corn Yield and Soil Nitrogen via Soil Electrical Conductivity Measurement Treated with Organic, Chemical and Biological Fertilizers

Directory of Open Access Journals (Sweden)

H. Khalilzade

2016-02-01

Full Text Available Introduction Around the world maize is the second crop with the most cultivated areas and amount of production, so as the most important strategic crop, have a special situation in policies, decision making, resources and inputs allocation. On the other side, negative environmental consequences of intensive consumption of agrochemicals resulted to change view concerning food production. One of the most important visions is sustainable production of enough food plus attention to social, economic and environmental aspects. Many researchers stated that the first step to achieve this goal is optimization and improvement of resources use efficiencies. According to little knowledge on relation between soil electrical conductivity and yield of maize, beside the environmental concerns about nitrogen consumption and need to replace chemical nitrogen by ecological inputs, this study designed and aimed to evaluate agroecological characteristics of corn and some soil characteristics as affected by application of organic and biological fertilizers under field conditions. Materials and Methods In order to probing the possibility of grain yield and soil nitrogen estimation via measurement of soil properties, a field experiment was conducted during growing season 2010 at Research Station, Ferdowsi University of Mashhad, Iran. A randomized complete block design (RCBD with three replications was used. Treatments included: 1- manure (30 ton ha-1, 2-vermicompost (10 ton ha-1, 3- nitroxin (containing Azotobacter sp. and Azospirillum sp., inoculation was done according to Kennedy et al., 4- nitrogen as urea (400 kg ha-1 and 5- control (without fertilizer. Studied traits were soil pH, soil EC, soil respiration rate, N content of soil and maize yield. Soil respiration rate was measured using equation 1: CO2= (V0- V× N×22 Equation 1 In which V0 is the volume of consumed acid for control treatment titration, V is of the volume of consumed acid for sample treatment

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

Directory of Open Access Journals (Sweden)

Kehinde Anthony Mogaji

2016-07-01

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

A novel OPC method to reduce mask volume with yield-aware dissection

International Nuclear Information System (INIS)

Xie Chunlei; Chen Ye; Shi Zheng

2013-01-01

Growing data volume of masks tremendously increases manufacture cost. The cost increase is partially due to the complicated optical proximity corrections applied on mask design. In this paper, a yield-aware dissection method is presented. Based on the recognition of yield related mask context, the dissection result provides sufficient degrees of freedom to keep fidelity on critical sites while still retaining the frugality of modified designs. Experiments show that the final mask volume using the new method is reduced to about 50% of the conventional method. (semiconductor technology)

Effect of Different Tillage Methods and Cover Crop Types on Yield and Yield Components of Wheat

Directory of Open Access Journals (Sweden)

Z Sharefee

2018-05-01

Full Text Available Introduction Conservation agriculture is an appropriate strategy for maintaining and improving agricultural resources which increases crop production and stability and also provides environmental protection. This attitude contributes to the conservation of natural resources (soil, water, and air and is one of the most effective ways to overcome the drought crisis, water management and compensation of soil organic matter in arid and semi-arid regions. The practice of zero-tillage decreases the mineralization of organic matter and contributes to the sequestration of organic carbon in the soil. Higher amounts of organic matter in the soil improve soil structure and root growth, water infiltration and retention, and cation exchange capacity. In addition, zero-tillage reduces soil compaction and crop production costs. Cover crops are cultivated to protect the soil from erosion and elements loss by leaching or runoff and also improve the soil moisture and temperature. Given that South Khorasan farmers still use traditional methods of cultivation of wheat, and cover crops have no place in their farming systems, the aim of this study was to investigate the effect of cover crops types and tillage systems on yield and yield components of wheat in Birjand region. Materials and Methods A split plot field experiment was conducted based on randomized complete block design with three replications at the Research Farm of the University of Birjand over the growing season of 2014-2015. The main factor was the type of tillage (no-till, reduced tillage and conventional tillage and cover crop type (chickling pea (Lathyrus sativus, rocket salad (Eruca sativa, triticale (X Triticosecale witmack, barley (Hordeum vulgaris and control (no cover crop was considered as sub plots. Cover crops were planted on July 2014. Before planting wheat, cover crops were dried through spraying paraquat herbicide using a backpack sprayer at a rate of 3 L ha-1. Then the three tillage

Soviet test yields

Science.gov (United States)

Vergino, Eileen S.

Soviet seismologists have published descriptions of 96 nuclear explosions conducted from 1961 through 1972 at the Semipalatinsk test site, in Kazakhstan, central Asia [Bocharov et al., 1989]. With the exception of releasing news about some of their peaceful nuclear explosions (PNEs) the Soviets have never before published such a body of information.To estimate the seismic yield of a nuclear explosion it is necessary to obtain a calibrated magnitude-yield relationship based on events with known yields and with a consistent set of seismic magnitudes. U.S. estimation of Soviet test yields has been done through application of relationships to the Soviet sites based on the U.S. experience at the Nevada Test Site (NTS), making some correction for differences due to attenuation and near-source coupling of seismic waves.

Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India

Science.gov (United States)

Swarnkar, Somil; Malini, Anshu; Tripathi, Shivam; Sinha, Rajiv

2018-04-01

High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha-1 yr-1) with higher values in the upper mountainous region (92 ± 15.2 t ha-1 yr-1) compared to the lower alluvial plains (19.3 ± 4 t ha-1 yr-1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin - Nanak Sagar Dam (NSD) for the period 1962-2008 and Husepur gauging station (HGS) for 1987-2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 105 t yr-1 and 6.7 ± 1.4 × 106 t yr-1, respectively, and the estimated 90 % interval contains the observed values of 6.4 × 105 t yr-1 and 7.2 × 106 t yr-1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.

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.

The universal library of fission products and delayed neutron group yields

International Nuclear Information System (INIS)

Koldobskiy, A.B.; Zhivun, V.M.

1997-01-01

A new fission product yield library based on the Semiempirical method for the estimation of their mass and charge distribution is described. Contrary to other compilations, this library can be used with all possible excitation energies of fissionable actinides. The library of delayed neutron group yields, based on the fission product yield compilation, is described as well. (author). 15 refs, 4 tabs

Application of a rising plate meter to estimate forage yield on dairy farms in Pennsylvania

Science.gov (United States)

Accurately assessing pasture forage yield is necessary for producers who want to budget feed expenses and make informed pasture management decisions. Clipping and weighing forage from a known area is a direct method to measure pasture forage yield, however it is time consuming. The rising plate mete...

Modeling of Yield Estimation for The Main Crops in Iran Based on Mechanization Index (hp ha-1

Directory of Open Access Journals (Sweden)

K Abbasi

2014-09-01

Full Text Available Agricultural mechanization is a method for transiting from traditional agriculture towards industrial and sustainable one. Due to the limitation of natural resources and increasing population we need to have economical production of agricultural crops. For reaching this destination; agricultural mechanization has a remarkable role. So it is necessary to have an extensive view for mechanization, because with the help of mechanization the agricultural inputs such as seeds, fertilizer and even water and soil can effectively be managed for an economical and sustainable production. This study has been carried out in many provinces of Iran. The data of agricultural tractors and cereal combine harvesters were firstly gathered by means of questionnaire. The tractors were categorized in four power levels of less than 45, 45 to 80, 80 to 110, and more than 110 hp. In addition, it was also carried out for cereal combine harvesters; it was in three power levels, i.e. between 100 to 110, 110 to 155 and 155 to 210 horse-power in 3 ages, i.e. less than 13, between 13 to 20, and more than 20 years. Information regarding to cultivation areas, production volume, and yield of main crops gathered from statistics of Ministry of Jihad-e-Agriculture. Then agriculture mechanization level index (hp ha-1 in each province was calculated. Four main crops including irrigated and rain-fed wheat and irrigated and rain-fed barley, which met the required criteria to be used in the model, were statistically analyzed. Correlation analysis was carried out in order to get an effective model between yield of the four main crops in Iran and agriculture mechanization level index. Pearson correlation index showed that there is a direct and significant correlation between these variables. Subsequently, outliers were identified in order to get a model with necessary efficiency to predict the yield through mechanization level index, by scatter diagram and estimating regression lines in 1

A simplified method of estimating noise power spectra

International Nuclear Information System (INIS)

Hanson, K.M.

1998-01-01

A technique to estimate the radial dependence of the noise power spectrum of images is proposed in which the calculations are conducted solely in the spatial domain of the noise image. The noise power spectrum averaged over a radial spatial-frequency interval is obtained form the variance of a noise image that has been convolved with a small kernel that approximates a Laplacian operator. Recursive consolidation of the image by factors of two in each dimension yields estimates of the noise power spectrum over that full range of spatial frequencies

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.

Estimation of subcriticality of TCA using 'indirect estimation method for calculation error'

International Nuclear Information System (INIS)

Naito, Yoshitaka; Yamamoto, Toshihiro; Arakawa, Takuya; Sakurai, Kiyoshi

1996-01-01

To estimate the subcriticality of neutron multiplication factor in a fissile system, 'Indirect Estimation Method for Calculation Error' is proposed. This method obtains the calculational error of neutron multiplication factor by correlating measured values with the corresponding calculated ones. This method was applied to the source multiplication and to the pulse neutron experiments conducted at TCA, and the calculation error of MCNP 4A was estimated. In the source multiplication method, the deviation of measured neutron count rate distributions from the calculated ones estimates the accuracy of calculated k eff . In the pulse neutron method, the calculation errors of prompt neutron decay constants give the accuracy of the calculated k eff . (author)

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Science.gov (United States)

Nearing, Grey S.; Crow, Wade T.; Thorp, Kelly R.; Moran, Mary S.; Reichle, Rolf H.; Gupta, Hoshin V.

2012-01-01

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Heuristic introduction to estimation methods

International Nuclear Information System (INIS)

Feeley, J.J.; Griffith, J.M.

1982-08-01

The methods and concepts of optimal estimation and control have been very successfully applied in the aerospace industry during the past 20 years. Although similarities exist between the problems (control, modeling, measurements) in the aerospace and nuclear power industries, the methods and concepts have found only scant acceptance in the nuclear industry. Differences in technical language seem to be a major reason for the slow transfer of estimation and control methods to the nuclear industry. Therefore, this report was written to present certain important and useful concepts with a minimum of specialized language. By employing a simple example throughout the report, the importance of several information and uncertainty sources is stressed and optimal ways of using or allowing for these sources are presented. This report discusses optimal estimation problems. A future report will discuss optimal control problems

Using operational data to estimate the reliable yields of water-supply wells

Science.gov (United States)

Misstear, Bruce D. R.; Beeson, Sarah

The reliable yield of a water-supply well depends on many different factors, including the properties of the well and the aquifer; the capacities of the pumps, raw-water mains, and treatment works; the interference effects from other wells; and the constraints imposed by ion licences, water quality, and environmental issues. A relatively simple methodology for estimating reliable yields has been developed that takes into account all of these factors. The methodology is based mainly on an analysis of water-level and source-output data, where such data are available. Good operational data are especially important when dealing with wells in shallow, unconfined, fissure-flow aquifers, where actual well performance may vary considerably from that predicted using a more analytical approach. Key issues in the yield-assessment process are the identification of a deepest advisable pumping water level, and the collection of the appropriate well, aquifer, and operational data. Although developed for water-supply operators in the United Kingdom, this approach to estimating the reliable yields of water-supply wells using operational data should be applicable to a wide range of hydrogeological conditions elsewhere. Résumé La productivité d'un puits capté pour l'adduction d'eau potable dépend de différents facteurs, parmi lesquels les propriétés du puits et de l'aquifère, la puissance des pompes, le traitement des eaux brutes, les effets d'interférences avec d'autres puits et les contraintes imposées par les autorisations d'exploitation, par la qualité des eaux et par les conditions environnementales. Une méthodologie relativement simple d'estimation de la productivité qui prenne en compte tous ces facteurs a été mise au point. Cette méthodologie est basée surtout sur une analyse des données concernant le niveau piézométrique et le débit de prélèvement, quand ces données sont disponibles. De bonnes données opérationnelles sont particuli

Direct and indirect selection responses for seed yield and its components in

Directory of Open Access Journals (Sweden)

rasoul dehghan

2017-06-01

Full Text Available Breeding based on selection indices is an effective method for improving complex traits such as yield. To assess the efficiency of different selection method, 83 exotic along with 17 Iranian safflower genotypes were evaluated at the research farm of Isfahan University of Technology using 10×10 simple lattice design with three replications in 2011. In this study, the selection indices of Smith-Hazel and Pesek-Baker were determined based on the number of capitulum per plant, number of seeds per capitulum and 1000-seed weight. Also response to selection and relative selection efficiency were estimated for traits under study and seed yield. The highest estimated selection efficiency for genetic improvement of seed yield was obtained via selection for number of capitulum per plant. Therefore, this trait can be used as an appropriate selection criterion for improvement of seed yield. The results showed that seed yield was highly correlated with each of these indices and the estimated efficiency of indirect selection via these indices was relatively high. Thus, it seems that these selection indices can be effectively used for seed yield improvement. Results of present study showed that the efficiency of Smith-Hazel indices for simultaneous improvement of number of capitulum per plant, number of seeds per capitulum and 1000-seed weight was higher than that of Pesek-Baker index.

Estimating the effect of urease inhibitor on rice yield based on NDVI at key growth stages

Directory of Open Access Journals (Sweden)

Kailou LIU,Yazhen LI,Huiwen HU

2014-06-01

Full Text Available The effect of the urease inhibitor, N-(n-butyl thiophosphoric triamide (NBPT at a range of application rates on rice production was examined in a field experiment at Jinxian County, Jiangxi Province, China. The normalized difference vegetation index (NDVI was measured at key growth stages in both early and late rice. The results showed that the grain yield increased significantly when urea was applied with NBPT, with the highest yield observed at 1.00% NBPT (wt/wt. NDVI differed with the growth stage of rice; it remained steady from the heading to the filling stage. Rice yield could be predicted from the NDVI taken at key rice growing stages, with R2 ranging from 0.34 to 0.69 in early rice and 0.49 to 0.70 in late rice. The validation test showed that RMSE (t·hm-2 values were 0.77 and 0.87 in early and late rice, respectively. Therefore, it was feasible to estimate rice yield for different amounts of urease inhibitor using NDVI.

Comparison of Four Weighting Methods in Fuzzy-based Land Suitability to Predict Wheat Yield

Directory of Open Access Journals (Sweden)

Fatemeh Rahmati

2017-06-01

Full Text Available Introduction: Land suitability evaluation is a process to examine the degree of land fitness for specific utilization and also makes it possible to estimate land productivity potential. In 1976, FAO provided a general framework for land suitability classification. It has not been proposed a specific method to perform this classification in the framework. In later years, a collection of methods was presented based on the FAO framework. In parametric method, different land suitability aspects are defined as completely discrete groups and are separated from each other by distinguished and consistent ranges. Therefore, land units that have moderate suitability can only choose one of the characteristics of predefined classes of land suitability. Fuzzy logic is an extension of Boolean logic by LotfiZadeh in 1965 based on the mathematical theory of fuzzy sets, which is a generalization of the classical set theory. By introducing the notion of degree in the verification of a condition, fuzzy method enables a condition to be in a state other than true or false, as well as provides a very valuable flexibility for reasoning, which makes it possible to take into account inaccuracies and uncertainties. One advantage of fuzzy logic in order to formalize human reasoning is that the rules are set in natural language. In evaluation method based on fuzzy logic, the weights are used for land characteristics. The objective of this study was to compare four methods of weight calculation in the fuzzy logic to predict the yield of wheat in the study area covering 1500 ha in Kian town in Shahrekord (Chahrmahal and Bakhtiari province, Iran. Materials and Methods: In such investigations, climatic factors, and soil physical and chemical characteristics are studied. This investigation involves several studies including a lab study, and qualitative and quantitative land suitability evaluation with fuzzy logic for wheat. Factors affecting the wheat production consist of

Utilization of the cropgro-soybean model to estimate yield loss caused by Asian rust in cultivars with different cycle

Directory of Open Access Journals (Sweden)

Rafael de Ávila Rodrigues

2012-01-01

Full Text Available In recent years, crop models have increasingly been used to simulate agricultural features. The DSSAT (Decision Support System for Agrotechnology Transfer is an important tool in modeling growth; however, one of its limitations is related to the unaccounted-for effect of diseases. Therefore, the goals of this study were to calibrate and validate the CSM CROPGRO-Soybean for the soybean cultivars M-SOY 6101 and MG/BR 46 (Conquista, analyze the performance and the effect of Asian soybean rust on these cultivars under the environmental conditions of Viçosa, Minas Gerais, Brazil. The experimental data for the evaluation, testing, and adjustment of the genetic coefficients for the cultivars, M-SOY 6101 and MG/BR 46 (Conquista, were obtained during the 2006/2007, 2007/2008 and 2009/2010 growing seasons. GLUE (Generalized Likelihood Uncertainty Estimation was used for the estimation of the genetic coefficients, and pedotransfer functions have been utilized to estimate the physical characteristics of the soil. For all of the sowing dates, the early season cultivar, M-SOY 6101, exhibited a lower variance in yield, which represents more stability with regard to the interannual climate variability, i.e., the farmers who use this cultivar will have in 50% of the crop years analyzed, a higher yield than a late-season cultivar. The MG/BR 46 (Conquista cultivar demonstrated a greater probability of obtaining higher yield in years with favorable weather conditions. However, in the presence of the Asian soybean rust, yield is heavily affected. The early cultivar, M-SOY 6101, showed a lower risk of being affected by the rust and consequently exhibited less yield loss considering the scenario D90 (condensation on the leaf surface occurs when the relative humidity is greater than or equal to 90%, for a sowing date of November 14.

Use of 15N dilution method for screening soybean lines with high yield and high nitrogen fixation ability

International Nuclear Information System (INIS)

Li Haixian; Li Xinmin; Danso, S.K.A.

1998-01-01

15 N dilution method was used for screening soybean lines with high nitrogen fixation ability. Screened lines 1005, 8502, 2096, 943, 1454 and Dongnong-42 have high nitrogen fixation ability with their % Ndfa of about 70%. 1454 and 1555 are both high yield and high nitrogen fixation lines. The ability of nitrogen fixation was not related to the yield, but related to maturing time. The cultivars with different maturing time have different levels of nitrogen fixation ability. The longer the maturing period is, the greater the ability of nitrogen fixation it has. There were ten cultivars or lines used in the test of 1992 and 1994. Although the weather condition were greatly different between the two years the results of seven cultivars or lines were the same, indicating that nitrogen fixation ability of the soybean is stable with years. Using 15 N dilution method to estimate nitrogen fixation ability of soybean is reliable, however, the % Ndfa of lines 8502 and 2096 increased by 19% in 1994, a rainy year, indicating that a change in % Ndfa with a few varieties maybe caused by weather

A Method of Nuclear Software Reliability Estimation

International Nuclear Information System (INIS)

Park, Gee Yong; Eom, Heung Seop; Cheon, Se Woo; Jang, Seung Cheol

2011-01-01

A method on estimating software reliability for nuclear safety software is proposed. This method is based on the software reliability growth model (SRGM) where the behavior of software failure is assumed to follow the non-homogeneous Poisson process. Several modeling schemes are presented in order to estimate and predict more precisely the number of software defects based on a few of software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating the software test cases into the model. It is identified that this method is capable of accurately estimating the remaining number of software defects which are on-demand type directly affecting safety trip functions. The software reliability can be estimated from a model equation and one method of obtaining the software reliability is proposed

Myocardial blood flow estimates from dynamic contrast-enhanced magnetic resonance imaging: three quantitative methods

Science.gov (United States)

Borrazzo, Cristian; Galea, Nicola; Pacilio, Massimiliano; Altabella, Luisa; Preziosi, Enrico; Carnì, Marco; Ciolina, Federica; Vullo, Francesco; Francone, Marco; Catalano, Carlo; Carbone, Iacopo

2018-02-01

Dynamic contrast-enhanced cardiovascular magnetic resonance imaging can be used to quantitatively assess the myocardial blood flow (MBF), recovering the tissue impulse response function for the transit of a gadolinium bolus through the myocardium. Several deconvolution techniques are available, using various models for the impulse response. The method of choice may influence the results, producing differences that have not been deeply investigated yet. Three methods for quantifying myocardial perfusion have been compared: Fermi function modelling (FFM), the Tofts model (TM) and the gamma function model (GF), with the latter traditionally used in brain perfusion MRI. Thirty human subjects were studied at rest as well as under cold pressor test stress (submerging hands in ice-cold water), and a single bolus of gadolinium weighing 0.1  ±  0.05 mmol kg-1 was injected. Perfusion estimate differences between the methods were analysed by paired comparisons with Student’s t-test, linear regression analysis, and Bland-Altman plots, as well as also using the two-way ANOVA, considering the MBF values of all patients grouped according to two categories: calculation method and rest/stress conditions. Perfusion estimates obtained by various methods in both rest and stress conditions were not significantly different, and were in good agreement with the literature. The results obtained during the first-pass transit time (20 s) yielded p-values in the range 0.20-0.28 for Student’s t-test, linear regression analysis slopes between 0.98-1.03, and R values between 0.92-1.01. From the Bland-Altman plots, the paired comparisons yielded a bias (and a 95% CI)—expressed as ml/min/g—for FFM versus TM, -0.01 (-0.20, 0.17) or 0.02 (-0.49, 0.52) at rest or under stress respectively, for FFM versus GF, -0.05 (-0.29, 0.20) or  -0.07 (-0.55, 0.41) at rest or under stress, and for TM versus GF, -0.03 (-0.30, 0.24) or  -0.09 (-0.43, 0.26) at rest or under stress. With the

Yield strength measurement of shock-loaded metal by flyer-impact perturbation method

Science.gov (United States)

Ma, Xiaojuan; Shi, Zhan

2018-06-01

Yield strength is one of the most important physical properties of a solid material, especially far from its melting line. The flyer-impact perturbation method measures material yield strength on the basis of correlation between the yield strength under shock compression and the damping of oscillatory perturbations in the shape of a shock front passing through the material. We used flyer-impact experiments on targets with machined grooves on the impact surface of shock 6061-T6 aluminum to between 32 and 61 GPa and recorded the evolution of the shock front perturbation amplitude in the sample with electric pins. Simulations using the elastic-plastic model can be matched to the experiments, explaining well the form of the perturbation decay and constraining the yield strength of 6061-T6 aluminum to be 1.31-1.75 GPa. These results are in agreement with values obtained from reshock and release wave profiles. We conclude that the flyer-impact perturbation method is indeed a new means to measure material strength.

Method-related estimates of sperm vitality.

Science.gov (United States)

Cooper, Trevor G; Hellenkemper, Barbara

2009-01-01

Comparison of methods that estimate viability of human spermatozoa by monitoring head membrane permeability revealed that wet preparations (whether using positive or negative phase-contrast microscopy) generated significantly higher percentages of nonviable cells than did air-dried eosin-nigrosin smears. Only with the latter method did the sum of motile (presumed live) and stained (presumed dead) preparations never exceed 100%, making this the method of choice for sperm viability estimates.

Planting pattern and weed control method influence on yield production of corn (Zea mays L.)

Science.gov (United States)

Purba, E.; Nasution, D. P.

2018-02-01

Field experiment was carried out to evaluate the influence of planting patterns and weed control methods on the growth and yield of corn. The effect of the planting pattern and weed control method was studied in a split plot design. The main plots were that of planting pattern single row (25cm x 60cm), double row (25cm x 25cm x 60cm) and triangle row ( 25cm x 25cm x 25cm). Subplot was that of weed control method consisted five methods namely weed free throughout the growing season, hand weeding, sprayed with glyphosate, sprayed with paraquat, and no weeding.. Result showed that both planting pattern and weed control method did not affect the growth of corn. However, planting pattern and weed control method significantly affected yield production. Yield resulted from double row and triangle planting pattern was 14% and 41% higher, consecutively, than that of single row pattern. The triangle planting pattern combined with any weed control method produced the highest yield production of corn.

Tillage methods and mulch on water saving and yield of spring maize in Chitwan

Directory of Open Access Journals (Sweden)

Ishwari Prasad Upadhyay

2016-12-01

Full Text Available Tillage methods and mulch influences the productivity and water requirement of spring maize hence a field experiment was conducted at the National Maize Research Program, Rampur in spring seasons of 2011 and 2012 with the objectives to evaluate different tillage methods with and without mulch on water requirement and grain yield of spring maize. The experiment was laid out in two factors factorial randomized complete design with three replications. The treatments consisted of tillage methods (Permanent bed, Zero tillage and Conventional tillage and mulch (with and without. Irrigation timing was fixed as knee high stage, tasseling stage and milking/dough stage. Data on number of plants, number of ears, thousand grain weight and grain yield were recorded and analysed using GenStat. Two years combined result showed that the effect of tillage methods and mulch significant influenced grain yield and water requirement of spring maize. The maize grain yield was the highest in permanent beds with mulch (4626 kg ha-1 followed by zero tillage with mulch (3838 kg ha-1. Whereas total water applied calculated during the crop period were the highest in conventional tillage without mulch followed by conventional tillage with mulch. The permanent bed with mulch increased the yield and reduced the water requirement of spring maize in Chitwan.

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

Science.gov (United States)

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

2017-05-01

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

Genetic parameters estimate for milk and mozzarella cheese yield, fat and protein percentage in dairy buffaloes in Brazil

Directory of Open Access Journals (Sweden)

H. Tonhati

2010-02-01

Full Text Available The aim of this study was analyze the (covariance components and genetic and phenotypic relationships in the following traits: accumulated milk yield at 270 days (MY270, observed until 305 days of lactation; accumulated milk yield at 270 days (MY270/ A and at 305 days (MY305, observed until 335 days of lactation; mozzarella cheese yield (MCY and fat (FP and protein (PP percentage, observed until 335 days of lactation. The (covariance components were estimated by Restricted Maximum Likelihood methodology in analyses single, two and three-traits using animal models. Heritability estimated for MY270, MY270/A, MY305, MCY, FP and PP were 0.22; 0.24, 0.25, 0.14, 0.29 and 0.40 respectively. The genetic correlations between MCY and the variables MY270, MY270/A, MY305, PP and FP was: 0.85; 1.00; 0.89; 0.14 and 0.06, respectively. This way, the selection for the production of milk in long period should increase MCY. However, in the search of animals that produce milk with quality, the genetic parameters suggest that another index should be composed allying these studied traits.

Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India

Directory of Open Access Journals (Sweden)

S. Swarnkar

2018-04-01

Full Text Available High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE and the sediment delivery ratio (SDR equations are used to estimate the spatial pattern of soil erosion (SE and sediment yield (SY in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha−1 yr−1 with higher values in the upper mountainous region (92 ± 15.2 t ha−1 yr−1 compared to the lower alluvial plains (19.3 ± 4 t ha−1 yr−1. Furthermore, the topographic steepness (LS and crop practice (CP factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar Dam (NSD for the period 1962–2008 and Husepur gauging station (HGS for 1987–2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2  ×  105 t yr−1 and 6.7 ± 1.4  ×  106 t yr−1, respectively, and the estimated 90 % interval contains the observed values of 6.4  ×  105 t yr−1 and 7.2  ×  106 t yr−1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and

Advances in estimation methods of vegetation water content based on optical remote sensing techniques

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

Science.gov (United States)

Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

2017-08-01

Objective. Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking. Approach. We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing. Main results. Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators. Significance. Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically

Effect of Planting Methods on Maturity and Yield of Onion (Allium ...

African Journals Online (AJOL)

Key words: onion, planting method, sets, transplantings, direct seeding, bulb yield. .... The central four rows of each plot were harvested and ... Means with lower case letters represent values for planting methods effects and means with upper .... Acta Hort. 84: 27-32. Brewster, J.L. 2002. Onions and other vegetable Alliums.

A study of health effect estimates using competing methods to model personal exposures to ambient PM2.5.

Science.gov (United States)

Strand, Matthew; Hopke, Philip K; Zhao, Weixiang; Vedal, Sverre; Gelfand, Erwin; Rabinovitch, Nathan

2007-09-01

Various methods have been developed recently to estimate personal exposures to ambient particulate matter less than 2.5 microm in diameter (PM2.5) using fixed outdoor monitors as well as personal exposure monitors. One class of estimators involves extrapolating values using ambient-source components of PM2.5, such as sulfate and iron. A key step in extrapolating these values is to correct for differences in infiltration characteristics of the component used in extrapolation (such as sulfate within PM2.5) and PM2.5. When this is not done, resulting health effect estimates will be biased. Another class of approaches involves factor analysis methods such as positive matrix factorization (PMF). Using either an extrapolation or a factor analysis method in conjunction with regression calibration allows one to estimate the direct effects of ambient PM2.5 on health, eliminating bias caused by using fixed outdoor monitors and estimated personal ambient PM2.5 concentrations. Several forms of the extrapolation method are defined, including some new ones. Health effect estimates that result from the use of these methods are compared with those from an expanded PMF analysis using data collected from a health study of asthmatic children conducted in Denver, Colorado. Examining differences in health effect estimates among the various methods using a measure of lung function (forced expiratory volume in 1 s) as the health indicator demonstrated the importance of the correction factor(s) in the extrapolation methods and that PMF yielded results comparable with the extrapolation methods that incorporated correction factors.

Effect of Harvest Methods on Yield and Quaiityof·Marketable ...

African Journals Online (AJOL)

cultivars of (ii1ferent growth habits: '0~'cf/~~' 'q;a~i/Giulq' rffP ... Key words: Greerihollse' rose, h~est methods, growth-habits, 'yield and guality of flowers. ,-. ',' ! ' ! ' . • . . ) Introduction .... dure" and "Duncan's Multiple Range test'''·re- spedivel~' of a ...

Model uncertainty of various settlement estimation methods in shallow tunnels excavation; case study: Qom subway tunnel

Science.gov (United States)

Khademian, Amir; Abdollahipour, Hamed; Bagherpour, Raheb; Faramarzi, Lohrasb

2017-10-01

In addition to the numerous planning and executive challenges, underground excavation in urban areas is always followed by certain destructive effects especially on the ground surface; ground settlement is the most important of these effects for which estimation there exist different empirical, analytical and numerical methods. Since geotechnical models are associated with considerable model uncertainty, this study characterized the model uncertainty of settlement estimation models through a systematic comparison between model predictions and past performance data derived from instrumentation. To do so, the amount of surface settlement induced by excavation of the Qom subway tunnel was estimated via empirical (Peck), analytical (Loganathan and Poulos) and numerical (FDM) methods; the resulting maximum settlement value of each model were 1.86, 2.02 and 1.52 cm, respectively. The comparison of these predicted amounts with the actual data from instrumentation was employed to specify the uncertainty of each model. The numerical model outcomes, with a relative error of 3.8%, best matched the reality and the analytical method, with a relative error of 27.8%, yielded the highest level of model uncertainty.

Responses of Seed Yield, Yield Components and Some Morpho-physiological Traits of Wheat Cultivars (Triticum aestivum to the Application Methods of Fulzyme Biofertilizer

Directory of Open Access Journals (Sweden)

A. Eslami

2014-10-01

Full Text Available To study the effect of application methods of Fulzym biofertilizer (containing Bacillus subtilis on yield, yield components and some morpho-physiological characteristics of four cultivars wheat, an experiment was conducted in field of Astan Quds Razavi in 2010- 2011. The experiment performed was in split plot based on randomized complete block design with three replications. Four wheat cultivars (Falat, Pishtaz, Bahar and Toos were assigned to main plots and four biofertilizer application methods (as seed inoculation, using in irrigation water, seed inoculation and irrigation and control to sub plots. Results indicated that Falat had the lowest plant height (61.5 cm than other varieties. Plant height of Toos and Pishtaz were about 14.5 percent higher than Falat. Application methods of Fulzym increased chlorophyll content and plant height. Highest chlorophyll contents were obtained when seeds inoculated by Fulzyme and used through irrigation. At the end of growing season, it was found that chlorophyll content of Falat and Toos flag leaves were higher than Pishtaz and Bahar. It was also revealed that Bahar when Fulzyme was used showed a better response to treatments than other varieties as for as biological and seed yields were concerned. Highest seed yield produced by irrigation and combination of seed inoculation and irrigation (9063 and 8609 kg.ha-1 and lowest seed yield (5858 kg.ha-1 to Falat in the control treatment.

Spectrum estimation method based on marginal spectrum

International Nuclear Information System (INIS)

Cai Jianhua; Hu Weiwen; Wang Xianchun

2011-01-01

FFT method can not meet the basic requirements of power spectrum for non-stationary signal and short signal. A new spectrum estimation method based on marginal spectrum from Hilbert-Huang transform (HHT) was proposed. The procession of obtaining marginal spectrum in HHT method was given and the linear property of marginal spectrum was demonstrated. Compared with the FFT method, the physical meaning and the frequency resolution of marginal spectrum were further analyzed. Then the Hilbert spectrum estimation algorithm was discussed in detail, and the simulation results were given at last. The theory and simulation shows that under the condition of short data signal and non-stationary signal, the frequency resolution and estimation precision of HHT method is better than that of FFT method. (authors)

Infant attachment and toddlers' sleep assessed by maternal reports and actigraphy: different measurement methods yield different relations.

Science.gov (United States)

Simard, Valérie; Bernier, Annie; Bélanger, Marie-Ève; Carrier, Julie

2013-06-01

To investigate relations between children's attachment and sleep, using objective and subjective sleep measures. Secondarily, to identify the most accurate actigraphy algorithm for toddlers. 55 mother-child dyads took part in the Strange Situation Procedure (18 months) to assess attachment. At 2 years, children wore an Actiwatch for a 72-hr period, and their mothers completed a sleep diary. The high sensitivity (80) and smoothed actigraphy algorithms provided the most plausible sleep data. Maternal diaries yielded longer estimated sleep duration and shorter wake duration at night and showed poor agreement with actigraphy. More resistant attachment behavior was not associated with actigraphy-assessed sleep, but was associated with longer nocturnal wake duration as estimated by mothers, and with a reduced actigraphy-diary discrepancy. Mothers of children with resistant attachment are more aware of their child's nocturnal awakenings. Researchers and clinicians should select the best sleep measurement method for their specific needs.

Estimation of genetic parameters for milk traits in Romanian local sheep breed

Directory of Open Access Journals (Sweden)

Pelmus RS

2014-03-01

Full Text Available Objective. Estimate the genetic parameters for milk traits in a Romanian local sheep population Teleorman Black Head. Material and methods. Records of 262 sheep belonging to 17 rams and 139 ewes were used in the study. The following traits were investigated: milk yield, fat yield, protein yield, fat percentage and protein percentage. The genetic parameters were estimated using the Restricted Maximum Likelihood method, with a model including maternal effects. Results. The results from our study revealed that direct heritability estimates were moderate for milk yield (0.449, fat yield (0.442, protein yield (0.386 while for protein percentage (0.708 and fat percentage (0.924 were high. The high direct and maternal genetic correlation was between milk yield and protein yield (0.979, 0.973 and between protein yield and fat yield (0.952, 0.913 while the phenotypic correlation between the milk yield and fat yield (0.968, the milk yield and protein yield (0.967, fat yield and protein yield (0.936 was high and positive. Conclusions. The genetic parameters are important in selection program on this breed for genetic improvement.

Comparison of 3 estimation methods of mycophenolic acid AUC based on a limited sampling strategy in renal transplant patients.

Science.gov (United States)

Hulin, Anne; Blanchet, Benoît; Audard, Vincent; Barau, Caroline; Furlan, Valérie; Durrbach, Antoine; Taïeb, Fabrice; Lang, Philippe; Grimbert, Philippe; Tod, Michel

2009-04-01

A significant relationship between mycophenolic acid (MPA) area under the plasma concentration-time curve (AUC) and the risk for rejection has been reported. Based on 3 concentration measurements, 3 approaches have been proposed for the estimation of MPA AUC, involving either a multilinear regression approach model (MLRA) or a Bayesian estimation using either gamma absorption or zero-order absorption population models. The aim of the study was to compare the 3 approaches for the estimation of MPA AUC in 150 renal transplant patients treated with mycophenolate mofetil and tacrolimus. The population parameters were determined in 77 patients (learning study). The AUC estimation methods were compared in the learning population and in 73 patients from another center (validation study). In the latter study, the reference AUCs were estimated by the trapezoidal rule on 8 measurements. MPA concentrations were measured by liquid chromatography. The gamma absorption model gave the best fit. In the learning study, the AUCs estimated by both Bayesian methods were very similar, whereas the multilinear approach was highly correlated but yielded estimates about 20% lower than Bayesian methods. This resulted in dosing recommendations differing by 250 mg/12 h or more in 27% of cases. In the validation study, AUC estimates based on the Bayesian method with gamma absorption model and multilinear regression approach model were, respectively, 12% higher and 7% lower than the reference values. To conclude, the bicompartmental model with gamma absorption rate gave the best fit. The 3 AUC estimation methods are highly correlated but not concordant. For a given patient, the same estimation method should always be used.

Effect of extraction method on the yield of furanocoumarins from fruits of Archangelica officinalis Hoffm.

Science.gov (United States)

Waksmundzka-Hajnos, M; Petruczynik, A; Dragan, A; Wianowska, D; Dawidowicz, A L

2004-01-01

Optimal conditions for the extraction and analysis of furanocoumarins from fruits of Archangelica officinalis Hoffm. have been determined. The following extraction methods were used: exhaustive extraction in a Soxhlet apparatus, ultrasonication at 25 and 60 degrees C, microwave-assisted solvent extraction in open and closed systems, and accelerated solvent extraction (ASE). In most cases the yields of furanocoumarins were highest using the ASE method. The effects of extracting solvent, temperature and time of extraction using this method were investigated. The highest yield of furanocoumarins by ASE was obtained with methanol at 100-130 degrees C for 10 min. The extraction yields of furanocoumarins from plant material by ultrasonication at 60 degrees C and microwave-assisted solvent extraction in an open system were comparable to the extraction yields obtained in the time- and solvent-consuming exhaustive process involving the Soxhlet apparatus.

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien; Claudel, Christian G.

2015-01-01

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

System and method for traffic signal timing estimation

KAUST Repository

Dumazert, Julien

2015-12-30

A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

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.

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

Science.gov (United States)

Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.

2010-01-01

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed

A fast and reliable method for simultaneous waveform, amplitude and latency estimation of single-trial EEG/MEG data.

Directory of Open Access Journals (Sweden)

Wouter D Weeda

Full Text Available The amplitude and latency of single-trial EEG/MEG signals may provide valuable information concerning human brain functioning. In this article we propose a new method to reliably estimate single-trial amplitude and latency of EEG/MEG signals. The advantages of the method are fourfold. First, no a-priori specified template function is required. Second, the method allows for multiple signals that may vary independently in amplitude and/or latency. Third, the method is less sensitive to noise as it models data with a parsimonious set of basis functions. Finally, the method is very fast since it is based on an iterative linear least squares algorithm. A simulation study shows that the method yields reliable estimates under different levels of latency variation and signal-to-noise ratioÕs. Furthermore, it shows that the existence of multiple signals can be correctly determined. An application to empirical data from a choice reaction time study indicates that the method describes these data accurately.

Higgs production in vector boson fusion in the H{yields} {tau}{tau} {yields} ll + 4{nu} final state with ATLAS. A sensitivity study

Energy Technology Data Exchange (ETDEWEB)

Schmitz, Martin

2011-05-15

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 rst 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

Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

NARCIS (Netherlands)

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

2003-01-01

(Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

Reverse survival method of fertility estimation: An evaluation

Directory of Open Access Journals (Sweden)

Thomas Spoorenberg

2014-07-01

Full Text Available Background: For the most part, demographers have relied on the ever-growing body of sample surveys collecting full birth history to derive total fertility estimates in less statistically developed countries. Yet alternative methods of fertility estimation can return very consistent total fertility estimates by using only basic demographic information. Objective: This paper evaluates the consistency and sensitivity of the reverse survival method -- a fertility estimation method based on population data by age and sex collected in one census or a single-round survey. Methods: A simulated population was first projected over 15 years using a set of fertility and mortality age and sex patterns. The projected population was then reverse survived using the Excel template FE_reverse_4.xlsx, provided with Timæus and Moultrie (2012. Reverse survival fertility estimates were then compared for consistency to the total fertility rates used to project the population. The sensitivity was assessed by introducing a series of distortions in the projection of the population and comparing the difference implied in the resulting fertility estimates. Results: The reverse survival method produces total fertility estimates that are very consistent and hardly affected by erroneous assumptions on the age distribution of fertility or by the use of incorrect mortality levels, trends, and age patterns. The quality of the age and sex population data that is 'reverse survived' determines the consistency of the estimates. The contribution of the method for the estimation of past and present trends in total fertility is illustrated through its application to the population data of five countries characterized by distinct fertility levels and data quality issues. Conclusions: Notwithstanding its simplicity, the reverse survival method of fertility estimation has seldom been applied. The method can be applied to a large body of existing and easily available population data

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

Science.gov (United States)

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

A method for estimating age of medieval sub-adults from infancy to adulthood based on long bone length

DEFF Research Database (Denmark)

Primeau, Charlotte; Friis, Laila Saidane; Sejrsen, Birgitte

2016-01-01

OBJECTIVES: To develop a series of regression equations for estimating age from length of long bones for archaeological sub-adults when aging from dental development cannot be performed. Further, to compare derived ages when using these regression equations, and two other methods. MATERIAL AND ME...... as later than the medieval period, although this would require further testing. The quadratic equations are suggested to yield more accurate ages then using simply linear regression equations. Am J Phys Anthropol, 2015. © 2015 Wiley Periodicals, Inc.......OBJECTIVES: To develop a series of regression equations for estimating age from length of long bones for archaeological sub-adults when aging from dental development cannot be performed. Further, to compare derived ages when using these regression equations, and two other methods. MATERIAL...... AND METHODS: A total of 183 skeletal sub-adults from the Danish medieval period, were aged from radiographic images. Linear regression formulae were then produced for individual bones. Age was then estimated from the femur length using three different methods: equations developed in this study, data based...

A Concurrent Mixed Methods Approach to Examining the Quantitative and Qualitative Meaningfulness of Absolute Magnitude Estimation Scales in Survey Research

Science.gov (United States)

Koskey, Kristin L. K.; Stewart, Victoria C.

2014-01-01

This small "n" observational study used a concurrent mixed methods approach to address a void in the literature with regard to the qualitative meaningfulness of the data yielded by absolute magnitude estimation scaling (MES) used to rate subjective stimuli. We investigated whether respondents' scales progressed from less to more and…

Two methods for estimating limits to large-scale wind power generation.

Science.gov (United States)

Miller, Lee M; Brunsell, Nathaniel A; Mechem, David B; Gans, Fabian; Monaghan, Andrew J; Vautard, Robert; Keith, David W; Kleidon, Axel

2015-09-08

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 10(5) km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m(-2), whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m(-2), with VKE capturing this combination in a comparatively simple way.

HIGH YIELD AND RAPID SYNTHESES METHODS FOR PRODUCING METALLO-ORGANIC SALTS

DEFF Research Database (Denmark)

2005-01-01

A new method for preparing salts of metal cations and organic acids, especially divalent salts of alkaline earth metal ions from group II of the periodic system and carboxylic acids. The method comprising the use of a high temperature (about 90° or more) and, optionally. high pressure, in order...... to obtain a higher yield, purity and faster reaction speed than obtained with known synthesis methods. In particular, the present invention relates to the production of strontium salts of carboxylic acids. Novel strontium salts are also provided by the present method....

A Fast Soft Bit Error Rate Estimation Method

Directory of Open Access Journals (Sweden)

Ait-Idir Tarik

2010-01-01

Full Text Available We have suggested in a previous publication a method to estimate the Bit Error Rate (BER of a digital communications system instead of using the famous Monte Carlo (MC simulation. This method was based on the estimation of the probability density function (pdf of soft observed samples. The kernel method was used for the pdf estimation. In this paper, we suggest to use a Gaussian Mixture (GM model. The Expectation Maximisation algorithm is used to estimate the parameters of this mixture. The optimal number of Gaussians is computed by using Mutual Information Theory. The analytical expression of the BER is therefore simply given by using the different estimated parameters of the Gaussian Mixture. Simulation results are presented to compare the three mentioned methods: Monte Carlo, Kernel and Gaussian Mixture. We analyze the performance of the proposed BER estimator in the framework of a multiuser code division multiple access system and show that attractive performance is achieved compared with conventional MC or Kernel aided techniques. The results show that the GM method can drastically reduce the needed number of samples to estimate the BER in order to reduce the required simulation run-time, even at very low BER.

Coalescent methods for estimating phylogenetic trees.

Science.gov (United States)

Liu, Liang; Yu, Lili; Kubatko, Laura; Pearl, Dennis K; Edwards, Scott V

2009-10-01

We review recent models to estimate phylogenetic trees under the multispecies coalescent. Although the distinction between gene trees and species trees has come to the fore of phylogenetics, only recently have methods been developed that explicitly estimate species trees. Of the several factors that can cause gene tree heterogeneity and discordance with the species tree, deep coalescence due to random genetic drift in branches of the species tree has been modeled most thoroughly. Bayesian approaches to estimating species trees utilizes two likelihood functions, one of which has been widely used in traditional phylogenetics and involves the model of nucleotide substitution, and the second of which is less familiar to phylogeneticists and involves the probability distribution of gene trees given a species tree. Other recent parametric and nonparametric methods for estimating species trees involve parsimony criteria, summary statistics, supertree and consensus methods. Species tree approaches are an appropriate goal for systematics, appear to work well in some cases where concatenation can be misleading, and suggest that sampling many independent loci will be paramount. Such methods can also be challenging to implement because of the complexity of the models and computational time. In addition, further elaboration of the simplest of coalescent models will be required to incorporate commonly known issues such as deviation from the molecular clock, gene flow and other genetic forces.

Statistical error estimation of the Feynman-α method using the bootstrap method

International Nuclear Information System (INIS)

Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho

2016-01-01

Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)

A rapid and highly selective method for the estimation of pyro-, tri- and orthophosphates.

Science.gov (United States)

Kamat, D R; Savant, V V; Sathyanarayana, D N

1995-03-01

A rapid, highly selective and simple method has been developed for the quantitative determination of pyro-, tri- and orthophosphates. The method is based on the formation of a solid complex of bis(ethylenediamine)cobalt(III) species with pyrophosphate at pH 4.2-4.3, with triphosphate at pH 2.0-2.1 and with orthophosphate at pH 8.2-8.6. The proposed method for pyro- and triphosphates differs from the available method, which is based on the formation of an adduct with tris(ethylenediamine)cobalt(III) species. The complexes have the composition [Co(en)(2)HP(2)O(7)]4H(2)O and [Co(en)(2)H(2)P(3)O(10)]2H(2)O, respectively. The precipitation is instantaneous and quantitative under the recommended optimum conditions giving 99.5% gravimetric yield in both cases. There is no interferences from orthophosphate, trimetaphosphate and pyrophosphate species in the triphosphate estimation up to 5% of each component. The efficacy of the method has been established by determining pyrophosphate and triphosphate contents in various matrices. In the case of orthophosphate, the proposed method differs from the available methods such as ammonium phosphomolybdate, vanadophosphomolybdate and quinoline phosphomolybdate, which are based on the formation of a precipitate, followed by either titrimetry or gravimetry. The precipitation is instantaneous and the method is simple. Under the recommended pH and other reaction conditions, gravimetric yields of 99.6-100% are obtainable. The method is applicable to orthophosphoric acid and a variety of phosphate salts.

Spectral Velocity Estimation in the Transverse Direction

DEFF Research Database (Denmark)

Jensen, Jørgen Arendt

2013-01-01

A method for estimating the velocity spectrum for a fully transverse flow at a beam-to-flow angle of 90is described. The approach is based on the transverse oscillation (TO) method, where an oscillation across the ultrasound beam is made during receive processing. A fourth-order estimator based...... on the correlation of the received signal is derived. A Fourier transform of the correlation signal yields the velocity spectrum. Performing the estimation for short data segments gives the velocity spectrum as a function of time as for ordinary spectrograms, and it also works for a beam-to-flow angle of 90...... estimation scheme can reliably find the spectrum at 90, where a traditional estimator yields zero velocity. Measurements have been conducted with the SARUS experimental scanner and a BK 8820e convex array transducer (BK Medical, Herlev, Denmark). A CompuFlow 1000 (Shelley Automation, Inc, Toronto, Canada...

Genetic analysis of yield and yield components in Oryza sativa x ...

African Journals Online (AJOL)

... inheritance of yield and yield components and to estimate the heritabilities of important quantitative traits in rice (Oryza sativa L.). Six generations viz., P1, P2, F1, F2, BCP1 and BCP2 of a cross between IET6279 and IR70445-146-3-3 were used for the study. Generation mean analysis suggested that additive effects had a ...

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.

Soybean yield estimation by an agrometeorological model in a GIS Produtividade de soja estimada por modelo agrometeorológico num SIG

Directory of Open Access Journals (Sweden)

Luciana Miura Sugawara Berka

2003-01-01

Full Text Available Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L. Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P > 0.05 were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield.Os modelos agrometeorológicos integrados em Sistemas de Informação Geográfica - SIG são uma alternativa para simular e quantificar o efeito da variabilidade espacial e temporal do clima sobre a produtividade agrícola. O objetivo deste trabalho foi adaptar e integrar um modelo agrometeorológico num SIG para estimar a produtividade da soja [Glycine max (L. Merr.]. Foram geradas estimativas de produtividade para 144 municípios do Estado do Paraná, responsáveis por 90% da produção de soja no Estado, em cinco anos-safra no período de 1996/1997 a 2000/2001. O modelo utiliza parâmetros agronômicos e

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.

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.

Reliable yields of public water-supply wells in the fractured-rock aquifers of central Maryland, USA

Science.gov (United States)

Hammond, Patrick A.

2018-02-01

Most studies of fractured-rock aquifers are about analytical models used for evaluating aquifer tests or numerical methods for describing groundwater flow, but there have been few investigations on how to estimate the reliable long-term drought yields of individual hard-rock wells. During the drought period of 1998 to 2002, many municipal water suppliers in the Piedmont/Blue Ridge areas of central Maryland (USA) had to institute water restrictions due to declining well yields. Previous estimates of the yields of those wells were commonly based on extrapolating drawdowns, measured during short-term single-well hydraulic pumping tests, to the first primary water-bearing fracture in a well. The extrapolations were often made from pseudo-equilibrium phases, frequently resulting in substantially over-estimated well yields. The methods developed in the present study to predict yields consist of extrapolating drawdown data from infinite acting radial flow periods or by fitting type curves of other conceptual models to the data, using diagnostic plots, inverse analysis and derivative analysis. Available drawdowns were determined by the positions of transition zones in crystalline rocks or thin-bedded consolidated sandstone/limestone layers (reservoir rocks). Aquifer dewatering effects were detected by type-curve matching of step-test data or by breaks in the drawdown curves constructed from hydraulic tests. Operational data were then used to confirm the predicted yields and compared to regional groundwater levels to determine seasonal variations in well yields. Such well yield estimates are needed by hydrogeologists and water engineers for the engineering design of water systems, but should be verified by the collection of long-term monitoring data.

A Generalized Autocovariance Least-Squares Method for Covariance Estimation

DEFF Research Database (Denmark)

Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2007-01-01

A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....

Measurement of ground-water storage change and specific yield using the temporal-gravity method near Rillito Creek, Tucson, Arizona

Science.gov (United States)

Pool, Donald R.; Schmidt, Werner

1997-01-01

The temporal-gravity method was used to estimate ground-water storage change and specific -yield values at wells near Rillito Creek, Tucson, Arizona, between early December 1992 and early January 1994. The method applies Newton's Law of Gravitation to measure changes in the local gravitational field of the Earth that are caused by changes in the mass and volume of ground water. Gravity at 50 stations in a 6-square-mile area was measured repeatedly relative to gravity at two bedrock stations. Ephemeral recharge through streamflow infiltration during the winter of 1992-93 resulted in water-level rises and gravity increases near Rillito Creek as the volume of ground water in storage increased. Water levels in wells rose as much as 30 feet, and gravity increased as much as 90 microgals. Water levels declined and gravity decreased near the stream after the last major winter flow but continued to rise and increase, respectively, in downgradient areas. Water levels and gravity relative to bedrock were measured at 10 wells. Good linear correlations between water levels and gravity values at five wells nearest the stream allowed for the estimation of specific-yield values for corresponding stratigraphic units assuming the mass change occurred in an infinite horizonal slab of uniform thickness. Specific-yield values for the stream-channel deposits at three wells ranged from 0.15 to 0.34, and correlation coefficients ranged from 0.81 to 0.99. Specific-yield values for the Fort Lowell Formation at three wells ranged from 0.07 to 0.18, and correlation coefficients ranged from 0.82 to 0.93. Specific-yield values were not calculated for the five wells farthest from the stream because of insufficient water-level and gravity change or poor correlations between water level and gravity. Poor correlations between water levels and gravity resulted from ground-water storage change in perched aquifers and in the unsaturated zone near ephemeral streams. Seasonal distributions of ground

Investigations on evaluation method for yield strength of round bar undermatched joint

International Nuclear Information System (INIS)

Matsumoto, Toshimi; Satoh, Hiroshi; Wadayama, Yoshihide

1988-01-01

The objective values of the yield strength and fracture toughness are respectively more than 1200 MPa and 200 MPa √m at 4K on the structural material for the superconducting magnet container in the Fusion Reactor. It should be desirable to assure the above value for the properties of the weld metal used for the containers. The initial yielding behavior of the undermatched joint is investigated in this paper. Results are as follows. (1) On the nominal stress vs. nominal strain relationship at the central section of the undermatched metal of the joint, the stress increases higher than the yield stress of undermatched metal itself then gradually comes up to a constant value, after the whole area of the undermatched metal starts to generate plastic deformation as the stress reaches the yield stress of the metal. (2) The increase in the stress is caused by the restraint effect of the base metal on the plasticity, and the stress becomes larger with the larger strength ratio of the undermatched metal to the basemetal and with the smaller relative thickness of the joint. (3) The strain does not distribute uniformly at the central section of the undermatched metal along the radial direction during the initial yielding process of the joint. (4) In the case that the yield strength of the joints is considered as the proof stress desided for a constant offset strain, the relationship between the dimensionless yield strength of the joint to the yield stress of the base metal and the relative yield strength of the undermatched metal to the base metal cannot be not established consistently. (5) The assumption that the base metal is rigid, causes the excessive evaluation of the joint yield strength of theoretical analysis. (6) As the quantitative evaluation method, the stress vs. strain relationship and then the algebraic expression has been formulated for the initial yielding behavior of the joint. (author)

Estimates of fission yields in nuclear criticality excursions

International Nuclear Information System (INIS)

Choi, J.S.; Thompson, J.W.; Reed, R.

1995-06-01

There is a need for computer simulation of hypothetical criticality excursions involving significant quantities of fissionable materials, especially in fissile aqueous system. The need arises due to the requirements for the emergency planning of facilities where the fissionable materials are handled, processed, or stored; and the regulatory requirements associated with facility operation or conversion. It is proposed here that a data base of fission yeilds for critical experiments and known accidents (both aqueous and solid) should be generated by using existing or new computer codes. The success in compiling this data base would provide useful source-terms for criticality excursions, realistic estimates of emergency-response boundary, as well as a replacement for the ''rule-of-thumb'' or ''bounding'' method. 10 refs

Unemployment estimation: Spatial point referenced methods and models

KAUST Repository

Pereira, Soraia

2017-06-26

Portuguese Labor force survey, from 4th quarter of 2014 onwards, started geo-referencing the sampling units, namely the dwellings in which the surveys are carried. This opens new possibilities in analysing and estimating unemployment and its spatial distribution across any region. The labor force survey choose, according to an preestablished sampling criteria, a certain number of dwellings across the nation and survey the number of unemployed in these dwellings. Based on this survey, the National Statistical Institute of Portugal presently uses direct estimation methods to estimate the national unemployment figures. Recently, there has been increased interest in estimating these figures in smaller areas. Direct estimation methods, due to reduced sampling sizes in small areas, tend to produce fairly large sampling variations therefore model based methods, which tend to

Development and Clinical Evaluation of a Three-Dimensional Cone-Beam Computed Tomography Estimation Method Using a Deformation Field Map

International Nuclear Information System (INIS)

Ren, Lei; Chetty, Indrin J.; Zhang Junan; Jin Jianyue; Wu, Q. Jackie; Yan Hui; Brizel, David M.; Lee, W. Robert; Movsas, Benjamin; Yin Fangfang

2012-01-01

Purpose: To develop a three-dimensional (3D) cone-beam computed tomography (CBCT) estimation method using a deformation field map, and to evaluate and optimize the efficiency and accuracy of the method for use in the clinical setting. Methods and Materials: We propose a method to estimate patient CBCT images using prior information and a deformation model. Patients’ previous CBCT data are used as the prior information, and the new CBCT volume to be estimated is considered as a deformation of the prior image volume. The deformation field map is solved by minimizing deformation energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. This method was implemented in 3D form using hardware acceleration and multi-resolution scheme, and it was evaluated for different scan angles, projection numbers, and scan directions using liver, lung, and prostate cancer patient data. The accuracy of the estimation was evaluated by comparing the organ volume difference and the similarity between estimated CBCT and the CBCT reconstructed from fully sampled projections. Results: Results showed that scan direction and number of projections do not have significant effects on the CBCT estimation accuracy. The total scan angle is the dominant factor affecting the accuracy of the CBCT estimation algorithm. Larger scan angles yield better estimation accuracy than smaller scan angles. Lung cancer patient data showed that the estimation error of the 3D lung tumor volume was reduced from 13.3% to 4.3% when the scan angle was increased from 60° to 360° using 57 projections. Conclusions: The proposed estimation method is applicable for 3D DTS, 3D CBCT, four-dimensional CBCT, and four-dimensional DTS image estimation. This method has the potential for significantly reducing the imaging dose and improving the image quality by removing the organ distortion artifacts and streak artifacts shown in images reconstructed by the conventional Feldkamp�

On the Methods for Estimating the Corneoscleral Limbus.

Science.gov (United States)

Jesus, Danilo A; Iskander, D Robert

2017-08-01

The aim of this study was to develop computational methods for estimating limbus position based on the measurements of three-dimensional (3-D) corneoscleral topography and ascertain whether corneoscleral limbus routinely estimated from the frontal image corresponds to that derived from topographical information. Two new computational methods for estimating the limbus position are proposed: One based on approximating the raw anterior eye height data by series of Zernike polynomials and one that combines the 3-D corneoscleral topography with the frontal grayscale image acquired with the digital camera in-built in the profilometer. The proposed methods are contrasted against a previously described image-only-based procedure and to a technique of manual image annotation. The estimates of corneoscleral limbus radius were characterized with a high precision. The group average (mean ± standard deviation) of the maximum difference between estimates derived from all considered methods was 0.27 ± 0.14 mm and reached up to 0.55 mm. The four estimating methods lead to statistically significant differences (nonparametric ANOVA (the Analysis of Variance) test, p 0.05). Precise topographical limbus demarcation is possible either from the frontal digital images of the eye or from the 3-D topographical information of corneoscleral region. However, the results demonstrated that the corneoscleral limbus estimated from the anterior eye topography does not always correspond to that obtained through image-only based techniques. The experimental findings have shown that 3-D topography of anterior eye, in the absence of a gold standard, has the potential to become a new computational methodology for estimating the corneoscleral limbus.

Comparing two survey methods for estimating maternal and perinatal mortality in rural Cambodia.

Science.gov (United States)

Chandy, Hoeuy; Heng, Yang Van; Samol, Ha; Husum, Hans

2008-03-01

We need solid estimates of maternal mortality rates (MMR) to monitor the impact of maternal care programs. Cambodian health authorities and WHO report the MMR in Cambodia at 450 per 100,000 live births. The figure is drawn from surveys where information is obtained by interviewing respondents about the survival of all their adult sisters (sisterhood method). The estimate is statistically imprecise, 95% confidence intervals ranging from 260 to 620/100,000. The MMR estimate is also uncertain due to under-reporting; where 80-90% of women deliver at home maternal fatalities may go undetected especially where mortality is highest, in remote rural areas. The aim of this study was to attain more reliable MMR estimates by using survey methods other than the sisterhood method prior to an intervention targeting obstetric rural emergencies. The study was carried out in rural Northwestern Cambodia where access to health services is poor and poverty, endemic diseases, and land mines are endemic. Two survey methods were applied in two separate sectors: a community-based survey gathering data from public sources and a household survey gathering data direct from primary sources. There was no statistically significant difference between the two survey results for maternal deaths, both types of survey reported mortality rates around the public figure. The household survey reported a significantly higher perinatal mortality rate as compared to the community-based survey, 8.6% versus 5.0%. Also the household survey gave qualitative data important for a better understanding of the many problems faced by mothers giving birth in the remote villages. There are detection failures in both surveys; the failure rate may be as high as 30-40%. PRINCIPLE CONCLUSION: Both survey methods are inaccurate, therefore inappropriate for evaluation of short-term changes of mortality rates. Surveys based on primary informants yield qualitative information about mothers' hardships important for the design

Combination of inoculation methods of Azospirilum brasilense with broadcasting of nitrogen fertilizer increases corn yield

Directory of Open Access Journals (Sweden)

Tânia Maria Müller

2015-01-01

Full Text Available Nitrogen (N is the most limiting nutrient for corn production. Thereby, the goal of the paper was to evaluate inoculation methods of Azospirillum brasilense in order to partially supply N required by the crop. The experiment was carried out in Guarapuava, PR, Brasil, in 2011/2012 growing season. Randomized blocks with factorial 3 inoculation methods (seed treatment, planting furrow and non-inoculated control x 5 doses of nitrogen (0, 75, 150, 225 and 300kg ha-1 x 8 replications was used as the experimental design. Leaf are index, foliar nitrogen content, total chlorophyll, grains per ear and yield were evaluated. There was significant interaction between inoculation methods and nitrogen fertilization to leaf area index, but not for yield. Inoculation with the diazotrophic bacteria provided yield increase of 702kg ha-1 for inoculation in seeding furrow and 432kg ha-1 for inoculation in seed treatment compared to the control, but both treatments did not differ between each other. Furthermore, total chlorophyll, grains per ear and yield were positively affected, with quadratic response, by the nitrogen fertilization in broadcasting

Comparison of methods for estimating carbon in harvested wood products

International Nuclear Information System (INIS)

Claudia Dias, Ana; Louro, Margarida; Arroja, Luis; Capela, Isabel

2009-01-01

There is a great diversity of methods for estimating carbon storage in harvested wood products (HWP) and, therefore, it is extremely important to agree internationally on the methods to be used in national greenhouse gas inventories. This study compares three methods for estimating carbon accumulation in HWP: the method suggested by Winjum et al. (Winjum method), the tier 2 method proposed by the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (GPG LULUCF) (GPG tier 2 method) and a method consistent with GPG LULUCF tier 3 methods (GPG tier 3 method). Carbon accumulation in HWP was estimated for Portugal under three accounting approaches: stock-change, production and atmospheric-flow. The uncertainty in the estimates was also evaluated using Monte Carlo simulation. The estimates of carbon accumulation in HWP obtained with the Winjum method differed substantially from the estimates obtained with the other methods, because this method tends to overestimate carbon accumulation with the stock-change and the production approaches and tends to underestimate carbon accumulation with the atmospheric-flow approach. The estimates of carbon accumulation provided by the GPG methods were similar, but the GPG tier 3 method reported the lowest uncertainties. For the GPG methods, the atmospheric-flow approach produced the largest estimates of carbon accumulation, followed by the production approach and the stock-change approach, by this order. A sensitivity analysis showed that using the ''best'' available data on production and trade of HWP produces larger estimates of carbon accumulation than using data from the Food and Agriculture Organization. (author)

Photovoltaic yield: correction method for the mismatch between the solar spectrum and the reference ASTMG AM1.5G spectrum

Directory of Open Access Journals (Sweden)

Mambrini Thomas

2015-01-01

Full Text Available We propose a method for a spectral correction of the predicted PV yield and we show the importance of the spectral mismatch on the solar cell. Indeed, currently predicted PV yield are made considering solar irradiation, ambient temperature, incidence angle and partially (or not the solar spectrum. However, the solar spectrum is not always the same. It varies depending on the site location, atmospheric conditions, time of the day...This may impact the photovoltaic solar cells differently according to their technology (crystalline Silicon, thin film, multi-junctions... This paper presents a method for calculating the correction of the short-circuit current of a photovoltaic cell due to the mismatch of the solar spectrum with the reference ASTM AM1.5G spectrum, for a specific site, throughout the year, using monthly data of AERONET (AErosol RObotic NETwork established by NASA and CNRS and the model SMARTS (simple model for atmospheric transmission of sunshine developed by the NREL. We applied this correction method on the site of Palaiseau (France, 48.7°N, 2.2°E, 156 m, close to our laboratory, just for comparison and the example of Blida (Algeria, 36°N, 2°E, 230 m is given for one year. This example illustrates the importance of this spectral correction to better estimate the photovoltaic yield. To be more precise, instead of modeling the solar spectral distribution, one can measure it with a spectro-radiometer, and then, derive the spectral mismatch correction. Some of our typical measurements are presented in this paper.

Linkages among climate change, crop yields and Mexico-US cross-border migration.

Science.gov (United States)

Feng, Shuaizhang; Krueger, Alan B; Oppenheimer, Michael

2010-08-10

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately -0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15-65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.

Evaluating direct medical expenditures estimation methods of adults using the medical expenditure panel survey: an example focusing on head and neck cancer.

Science.gov (United States)

Coughlan, Diarmuid; Yeh, Susan T; O'Neill, Ciaran; Frick, Kevin D

2014-01-01

To inform policymakers of the importance of evaluating various methods for estimating the direct medical expenditures for a low-incidence condition, head and neck cancer (HNC). Four methods of estimation have been identified: 1) summing all health care expenditures, 2) estimating disease-specific expenditures consistent with an attribution approach, 3) estimating disease-specific expenditures by matching, and 4) estimating disease-specific expenditures by using a regression-based approach. A literature review of studies (2005-2012) that used the Medical Expenditure Panel Survey (MEPS) was undertaken to establish the most popular expenditure estimation methods. These methods were then applied to a sample of 120 respondents with HNC, derived from pooled data (2003-2008). The literature review shows that varying expenditure estimation methods have been used with MEPS but no study compared and contrasted all four methods. Our estimates are reflective of the national treated prevalence of HNC. The upper-bound estimate of annual direct medical expenditures of adult respondents with HNC between 2003 and 2008 was $3.18 billion (in 2008 dollars). Comparable estimates arising from methods focusing on disease-specific and incremental expenditures were all lower in magnitude. Attribution yielded annual expenditures of $1.41 billion, matching method of $1.56 billion, and regression method of $1.09 billion. This research demonstrates that variation exists across and within expenditure estimation methods applied to MEPS data. Despite concerns regarding aspects of reliability and consistency, reporting a combination of the four methods offers a degree of transparency and validity to estimating the likely range of annual direct medical expenditures of a condition. © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Published by International Society for Pharmacoeconomics and Outcomes Research (ISPOR) All rights reserved.

Effect of harvest methods on yield and quality of Marketable flowers ...

African Journals Online (AJOL)

This study was carried out to determine the effects of harvest methods (proximal and median harvests) on yield and quality of marketable flowers of greenhouse hybrid tea rose (Rosa hybrida L.) cultivars of different growth habits. The cultivar Grant Galla represented cultivars of vigorous growth habit whereas 'Vivaldi' ...

Evaluation of non cyanide methods for hemoglobin estimation

Directory of Open Access Journals (Sweden)

Vinaya B Shah

2011-01-01

Full Text Available Background: The hemoglobincyanide method (HiCN method for measuring hemoglobin is used extensively worldwide; its advantages are the ready availability of a stable and internationally accepted reference standard calibrator. However, its use may create a problem, as the waste disposal of large volumes of reagent containing cyanide constitutes a potential toxic hazard. Aims and Objective: As an alternative to drabkin`s method of Hb estimation, we attempted to estimate hemoglobin by other non-cyanide methods: alkaline hematin detergent (AHD-575 using Triton X-100 as lyser and alkaline- borax method using quarternary ammonium detergents as lyser. Materials and Methods: The hemoglobin (Hb results on 200 samples of varying Hb concentrations obtained by these two cyanide free methods were compared with a cyanmethemoglobin method on a colorimeter which is light emitting diode (LED based. Hemoglobin was also estimated in one hundred blood donors and 25 blood samples of infants and compared by these methods. Statistical analysis used was Pearson`s correlation coefficient. Results: The response of the non cyanide method is linear for serially diluted blood samples over the Hb concentration range from 3gm/dl -20 gm/dl. The non cyanide methods has a precision of + 0.25g/dl (coefficient of variation= (2.34% and is suitable for use with fixed wavelength or with colorimeters at wavelength- 530 nm and 580 nm. Correlation of these two methods was excellent (r=0.98. The evaluation has shown it to be as reliable and reproducible as HiCN for measuring hemoglobin at all concentrations. The reagents used in non cyanide methods are non-biohazardous and did not affect the reliability of data determination and also the cost was less than HiCN method. Conclusions: Thus, non cyanide methods of Hb estimation offer possibility of safe and quality Hb estimation and should prove useful for routine laboratory use. Non cyanide methods is easily incorporated in hemobloginometers

Water Quality in the Upper Anacostia River, Maryland: Continuous and Discrete Monitoring with Simulations to Estimate Concentrations and Yields, 2003-05

Science.gov (United States)

Miller, Cherie V.; Gutierrez-Magness, Angelica L.; Feit Majedi, Brenda L.; Foster, Gregory D.

2007-01-01

concentrations of total phosphorus and total nitrogen had lower values of multiple R2 than suspended sediment, but the estimated bias for all the models was similar. The models for total nitrogen and total phosphorus tended to under-predict high concentrations and to over-predict low concentrations as compared to measured values. Annual yields (loads per square area in kilograms per year per square kilometer) were estimated for suspended sediment, total nitrogen, and total phosphorus using the U.S. Geological Survey models ESTIMATOR and LOADEST. The model LOADEST used hourly time steps and allowed the use of turbidity, which is strongly correlated to concentrations of suspended sediment, as a predictor variable. Annual yields for total nitrogen and total phosphorus were slightly higher but similar to previous estimates for other watersheds of the Chesapeake Bay, but annual yields for suspended sediment were higher by an order of magnitude for the two Anacostia River stations. Annual yields of suspended sediment at the two Anacostia River stations ranged from 131,000 to 248,000 kilograms per year per square kilometer for 2004 and 2005. LOADEST estimates were similar to those determined with ESTIMATOR, but had reduced errors associated with the estimates.

Estimation of groundwater consumption by phreatophytes using diurnal water table fluctuations: A saturated‐unsaturated flow assessment

Science.gov (United States)

Loheide, Steven P.; Butler, James J.; Gorelick, Steven M.

2005-01-01

Groundwater consumption by phreatophytes is a difficult‐to‐measure but important component of the water budget in many arid and semiarid environments. Over the past 70 years the consumptive use of groundwater by phreatophytes has been estimated using a method that analyzes diurnal trends in hydrographs from wells that are screened across the water table (White, 1932). The reliability of estimates obtained with this approach has never been rigorously evaluated using saturated‐unsaturated flow simulation. We present such an evaluation for common flow geometries and a range of hydraulic properties. Results indicate that the major source of error in the White method is the uncertainty in the estimate of specific yield. Evapotranspirative consumption of groundwater will often be significantly overpredicted with the White method if the effects of drainage time and the depth to the water table on specific yield are ignored. We utilize the concept of readily available specific yield as the basis for estimation of the specific yield value appropriate for use with the White method. Guidelines are defined for estimating readily available specific yield based on sediment texture. Use of these guidelines with the White method should enable the evapotranspirative consumption of groundwater to be more accurately quantified.

Estimating diversification rates for higher taxa: BAMM can give problematic estimates of rates and rate shifts.

Science.gov (United States)

Meyer, Andreas L S; Wiens, John J

2018-01-01

Estimates of diversification rates are invaluable for many macroevolutionary studies. Recently, an approach called BAMM (Bayesian Analysis of Macro-evolutionary Mixtures) has become widely used for estimating diversification rates and rate shifts. At the same time, several articles have concluded that estimates of net diversification rates from the method-of-moments (MS) estimators are inaccurate. Yet, no studies have compared the ability of these two methods to accurately estimate clade diversification rates. Here, we use simulations to compare their performance. We found that BAMM yielded relatively weak relationships between true and estimated diversification rates. This occurred because BAMM underestimated the number of rates shifts across each tree, and assigned high rates to small clades with low rates. Errors in both speciation and extinction rates contributed to these errors, showing that using BAMM to estimate only speciation rates is also problematic. In contrast, the MS estimators (particularly using stem group ages), yielded stronger relationships between true and estimated diversification rates, by roughly twofold. Furthermore, the MS approach remained relatively accurate when diversification rates were heterogeneous within clades, despite the widespread assumption that it requires constant rates within clades. Overall, we caution that BAMM may be problematic for estimating diversification rates and rate shifts. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Methods for estimating the semivariogram

DEFF Research Database (Denmark)

Lophaven, Søren Nymand; Carstensen, Niels Jacob; Rootzen, Helle

2002-01-01

. In the existing literature various methods for modelling the semivariogram have been proposed, while only a few studies have been made on comparing different approaches. In this paper we compare eight approaches for modelling the semivariogram, i.e. six approaches based on least squares estimation...... maximum likelihood performed better than the least squares approaches. We also applied maximum likelihood and least squares estimation to a real dataset, containing measurements of salinity at 71 sampling stations in the Kattegat basin. This showed that the calculation of spatial predictions...

Bayesian Inference Methods for Sparse Channel Estimation

DEFF Research Database (Denmark)

Pedersen, Niels Lovmand

2013-01-01

This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...

Heavy metals effects on forage crops yields and estimation of elements accumulation in plants as affected by soil

International Nuclear Information System (INIS)

Grytsyuk, N.; Arapis, G.; Perepelyatnikova, L.; Ivanova, T.; Vynograds'ka, V.

2006-01-01

Heavy metals (Cu, Cd, Pb, Zn) effect on the productivity of forage crops (clover and perennial cereal grasses) and their accumulation in plants, depending on the concentration of these elements in a soil, has been studied in micro-field experiments on three types of soil. The principle objective was to determine regularities of heavy metals migration in a soil-plant system aiming the estimation of permissible levels of heavy metals content in soils with the following elaboration of methods, which regulate the toxicants transfer to plants. Methods of field experiments, agrochemical and atomic absorption analysis were used. Results were statistically treated by Statistica 6.0, S-Plus 6. Experimental results have shown that the intensity of heavy metals accumulation in plants depends on the type of the soil, the species of plants, the physicochemical properties of heavy metals and their content in the soil. Logarithmic interdependency of heavy metals concentration in soils and their accumulation in plants is suggested. However, the strong correlation between the different heavy metals concentrations in the various soils and the yield of crops was not observed. Toxicants accumulation in crops decreased in time

Heavy metals effects on forage crops yields and estimation of elements accumulation in plants as affected by soil.

Science.gov (United States)

Grytsyuk, N; Arapis, G; Perepelyatnikova, L; Ivanova, T; Vynograds'ka, V

2006-02-01

Heavy metals (Cu, Cd, Pb, Zn) effect on the productivity of forage crops (clover and perennial cereal grasses) and their accumulation in plants, depending on the concentration of these elements in a soil, has been studied in micro-field experiments on three types of soil. The principle objective was to determine regularities of heavy metals migration in a soil-plant system aiming the estimation of permissible levels of heavy metals content in soils with the following elaboration of methods, which regulate the toxicants transfer to plants. Methods of field experiments, agrochemical and atomic absorption analysis were used. Results were statistically treated by Statistica 6.0, S-Plus 6. Experimental results have shown that the intensity of heavy metals accumulation in plants depends on the type of the soil, the species of plants, the physicochemical properties of heavy metals and their content in the soil. Logarithmic interdependency of heavy metals concentration in soils and their accumulation in plants is suggested. However, the strong correlation between the different heavy metals concentrations in the various soils and the yield of crops was not observed. Toxicants accumulation in crops decreased in time.

Calculational estimations of neutron yield from ADS target

International Nuclear Information System (INIS)

Degtyarev, I.I.; Liashenko, O.A.; Yazynin, I.A.; Belyakov-Bodin, V.I.; Blokhin, A.I.

2002-01-01

Results of computational studies of high power spallation thick ADS (Accelerator-Driven System) targets with 0.8-1.2 GeV proton beams are given. Comparisons of experiments and calculations of double differential and integral n/p yield are also described. (author)

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

Science.gov (United States)

Meneghini, R.; Jones, J. A.; Iguchi, T.; Okamoto, K.; Liao, L.; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by

Soil erosion planning using sediment yield index method in the Nun Nadi watershed, India

Directory of Open Access Journals (Sweden)

Hasan Raja Naqvi

2015-06-01

Full Text Available The study identifies the extent of soil loss and proposes a method for prioritization of micro-watershed in the Nun Nadi watershed. The study used the Sediment Yield Index (SYI method, based on weighted overlays of soil, topography, rainfall erosivity and land use parameters in 24 micro watersheds. Accordingly the values and thematic layers were integrated as per the SYI model, and minimum and maximum sediment yield values were calculated. The priority ranks as per the sediment yield values were assigned to all micro-watersheds. Then the values were classified into four priority zones according to their composite scores. Almost 14 percent area of three micro-watersheds (SW5b, SW6a and SW7b showed very high priority; approximately 30.57 percent of the study area fell under the high priority zones. These areas require immediate attention. Conservation methods are suggested, and the locations of check dams are proposed after considering drainage, slope and soil loss. Keywords: Check dam, Prioritization, Nun Nadi watershed, Soil loss, SYI

Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

DEFF Research Database (Denmark)

Drews, Martin; Lauritzen, Bent; Madsen, Henrik

2005-01-01

A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

Order statistics & inference estimation methods

CERN Document Server

Balakrishnan, N

1991-01-01

The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A co

Investigation of MLE in nonparametric estimation methods of reliability function

International Nuclear Information System (INIS)

Ahn, Kwang Won; Kim, Yoon Ik; Chung, Chang Hyun; Kim, Kil Yoo

2001-01-01

There have been lots of trials to estimate a reliability function. In the ESReDA 20 th seminar, a new method in nonparametric way was proposed. The major point of that paper is how to use censored data efficiently. Generally there are three kinds of approach to estimate a reliability function in nonparametric way, i.e., Reduced Sample Method, Actuarial Method and Product-Limit (PL) Method. The above three methods have some limits. So we suggest an advanced method that reflects censored information more efficiently. In many instances there will be a unique maximum likelihood estimator (MLE) of an unknown parameter, and often it may be obtained by the process of differentiation. It is well known that the three methods generally used to estimate a reliability function in nonparametric way have maximum likelihood estimators that are uniquely exist. So, MLE of the new method is derived in this study. The procedure to calculate a MLE is similar just like that of PL-estimator. The difference of the two is that in the new method, the mass (or weight) of each has an influence of the others but the mass in PL-estimator not

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

Methods to estimate the genetic risk

International Nuclear Information System (INIS)

Ehling, U.H.

1989-01-01

The estimation of the radiation-induced genetic risk to human populations is based on the extrapolation of results from animal experiments. Radiation-induced mutations are stochastic events. The probability of the event depends on the dose; the degree of the damage dose not. There are two main approaches in making genetic risk estimates. One of these, termed the direct method, expresses risk in terms of expected frequencies of genetic changes induced per unit dose. The other, referred to as the doubling dose method or the indirect method, expresses risk in relation to the observed incidence of genetic disorders now present in man. The advantage of the indirect method is that not only can Mendelian mutations be quantified, but also other types of genetic disorders. The disadvantages of the method are the uncertainties in determining the current incidence of genetic disorders in human and, in addition, the estimasion of the genetic component of congenital anomalies, anomalies expressed later and constitutional and degenerative diseases. Using the direct method we estimated that 20-50 dominant radiation-induced mutations would be expected in 19 000 offspring born to parents exposed in Hiroshima and Nagasaki, but only a small proportion of these mutants would have been detected with the techniques used for the population study. These methods were used to predict the genetic damage from the fallout of the reactor accident at Chernobyl in the vicinity of Southern Germany. The lack of knowledge for the interaction of chemicals with ionizing radiation and the discrepancy between the high safety standards for radiation protection and the low level of knowledge for the toxicological evaluation of chemical mutagens will be emphasized. (author)

A method of estimating log weights.

Science.gov (United States)

Charles N. Mann; Hilton H. Lysons

1972-01-01

This paper presents a practical method of estimating the weights of logs before they are yarded. Knowledge of log weights is required to achieve optimum loading of modern yarding equipment. Truckloads of logs are weighed and measured to obtain a local density index (pounds per cubic foot) for a species of logs. The density index is then used to estimate the weights of...

A Fast LMMSE Channel Estimation Method for OFDM Systems

Directory of Open Access Journals (Sweden)

Zhou Wen

2009-01-01

Full Text Available A fast linear minimum mean square error (LMMSE channel estimation method has been proposed for Orthogonal Frequency Division Multiplexing (OFDM systems. In comparison with the conventional LMMSE channel estimation, the proposed channel estimation method does not require the statistic knowledge of the channel in advance and avoids the inverse operation of a large dimension matrix by using the fast Fourier transform (FFT operation. Therefore, the computational complexity can be reduced significantly. The normalized mean square errors (NMSEs of the proposed method and the conventional LMMSE estimation have been derived. Numerical results show that the NMSE of the proposed method is very close to that of the conventional LMMSE method, which is also verified by computer simulation. In addition, computer simulation shows that the performance of the proposed method is almost the same with that of the conventional LMMSE method in terms of bit error rate (BER.

A Computationally Efficient Method for Polyphonic Pitch Estimation

Directory of Open Access Journals (Sweden)

Ruohua Zhou

2009-01-01

Full Text Available This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

A Comparative Study of Distribution System Parameter Estimation Methods

Energy Technology Data Exchange (ETDEWEB)

Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

2016-07-17

In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of both methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.

Genetic potential and heritability estimates of yield traits in F3 segregating populations of bread wheat

Directory of Open Access Journals (Sweden)

Soshma Jan

2015-06-01

Full Text Available An experiment comprising of 24 wheat genotypes was undertaken during 2011-12, at New Developmental Research Farm, The University of Agriculture Peshawar, to elucidate information on the nature and magnitude of genetic variability, index of transmissibility and assessing the level of genetic improvement of the quantitative characters. The experimental material comprising 19 F3 populations along with their 5 parents of bread wheat were evaluated in randomized complete block design (RCBD with three replications. Analysis of variance exhibited highly significant (P ≤ 0.01 differences among genotypes for all the traits studied. F3 population Ghaznavi-98 x Pirsabak-05 showed maximum mean value for 1000-grain weight (47.3 g and biological yield (11474.9 kg ha-1, whereas, maximum values for grain yield (4027.3 kg ha-1, and harvest index (48.1% were observed for Pirsabak-05 x AUP-4006. Moreover, maximum spike length (11 cm was recorded for cross combination Pirsabak-05 x Pirsabak-04 and Janbaz x Pirsabak-05, respectively. In addition, Pirsabak-04 showed maximum value for number of grains spike-1 (55.0. Genetic variances were of greater magnitude than environmental variances for all the traits except for spike length and 1000-grain weight. Heritability estimates were of higher magnitude ranged from 0.64 to 0.92 for harvest index, biological yield, grain yield, and grains spike-1. Moderate to low heritability (0.40-0.46 was observed for 1000-grain weight, and spike length, respectively. Genetic gain was for spike length (0.48 cm, grains spike-1 (8.57, 1000-grain weight (2.93 g, grain yield (639.87 kg ha-1, biological yield (1790.03 kg ha-1, and harvest index (5.32 %. From high values of heritability and genetic advance, it could be concluded that selection for traits like grains spike-1 suggested good selection criteria and could be effective for future breeding programs. DOI: http://dx.doi.org/10.3126/ije.v4i2.12630 International Journal of Environment

Evaluation of three paediatric weight estimation methods in Singapore.

Science.gov (United States)

Loo, Pei Ying; Chong, Shu-Ling; Lek, Ngee; Bautista, Dianne; Ng, Kee Chong

2013-04-01

Rapid paediatric weight estimation methods in the emergency setting have not been evaluated for South East Asian children. This study aims to assess the accuracy and precision of three such methods in Singapore children: Broselow-Luten (BL) tape, Advanced Paediatric Life Support (APLS) (estimated weight (kg) = 2 (age + 4)) and Luscombe (estimated weight (kg) = 3 (age) + 7) formulae. We recruited 875 patients aged 1-10 years in a Paediatric Emergency Department in Singapore over a 2-month period. For each patient, true weight and height were determined. True height was cross-referenced to the BL tape markings and used to derive estimated weight (virtual BL tape method), while patient's round-down age (in years) was used to derive estimated weights using APLS and Luscombe formulae, respectively. The percentage difference between the true and estimated weights was calculated. For each method, the bias and extent of agreement were quantified using Bland-Altman method (mean percentage difference (MPD) and 95% limits of agreement (LOA)). The proportion of weight estimates within 10% of true weight (p₁₀) was determined. The BL tape method marginally underestimated weights (MPD +0.6%; 95% LOA -26.8% to +28.1%; p₁₀ 58.9%). The APLS formula underestimated weights (MPD +7.6%; 95% LOA -26.5% to +41.7%; p₁₀ 45.7%). The Luscombe formula overestimated weights (MPD -7.4%; 95% LOA -51.0% to +36.2%; p₁₀ 37.7%). Of the three methods we evaluated, the BL tape method provided the most accurate and precise weight estimation for Singapore children. The APLS and Luscombe formulae underestimated and overestimated the children's weights, respectively, and were considerably less precise. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Joint Pitch and DOA Estimation Using the ESPRIT method

DEFF Research Database (Denmark)

Wu, Yuntao; Amir, Leshem; Jensen, Jesper Rindom

2015-01-01

In this paper, the problem of joint multi-pitch and direction-of-arrival (DOA) estimation for multi-channel harmonic sinusoidal signals is considered. A spatio-temporal matrix signal model for a uniform linear array is defined, and then the ESPRIT method based on subspace techniques that exploits...... the invariance property in the time domain is first used to estimate the multi pitch frequencies of multiple harmonic signals. Followed by the estimated pitch frequencies, the DOA estimations based on the ESPRIT method are also presented by using the shift invariance structure in the spatial domain. Compared...... to the existing stateof-the-art algorithms, the proposed method based on ESPRIT without 2-D searching is computationally more efficient but performs similarly. An asymptotic performance analysis of the DOA and pitch estimation of the proposed method are also presented. Finally, the effectiveness of the proposed...

Linkages among climate change, crop yields and Mexico–US cross-border migration

Science.gov (United States)

Feng, Shuaizhang; Krueger, Alan B.; Oppenheimer, Michael

2010-01-01

Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately −0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15–65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming. PMID:20660749

New method of measuring the K-shell fluorescence yield of As

Energy Technology Data Exchange (ETDEWEB)

Singh, K; Sahota, H S

1984-02-01

A new method for the determination of the K-shell fluorescence yield from the analysis of sum peaks observed with a high-resolution intrinsic Ge semiconductor detector in the decay of /sup 75/Se is described. The value found is ..omega..sub(K)(As)=0.574(18), which is in agreement with the fitted value of previous authors.

Methods for estimating drought streamflow probabilities for Virginia streams

Science.gov (United States)

Austin, Samuel H.

2014-01-01

Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.

Effect of Integrated Weed Management Methods on Yield and Yield Components of Corn (Zea mays L. in Kermanshah Province, Iran

Directory of Open Access Journals (Sweden)

R. Amini

2017-08-01

Full Text Available Introduction: Corn (Zea mays L. is cultivated widely throughout the world and has the highest production among the cerealsafter rice and wheat. In Iran the total production of corn in 2013 was more than 2540000 tons. Weeds are one of the greatest limiting factors to decrease corn yield in Iran as the average yield loss due to weeds in the fields of Kermanshah in 2009 was 17.32 %. The herbicides are the main weed control method in conventional cropping systems but their application has been increased herbicide resistant weeds and environmental pollution. Integrated weed management combines all applicable including chemical and non-chemical methods to reduce the effect of weeds in the cropping systems. Thus, Weed control strategies such as tillage, mulch, cover crops and intercropping could be used for integrated weed management of corn. Previous studies showed that crop residues such as rye (Secale sereal L., wheat (Triticum aestivum L., barley (Hordeum vulgare L. and clover (Trifolium sp., cover crops and living mulch could inhibit weed germination and growth. Therefore the objective of this study was evaluating the effects of some integrated weed management treatments on weed characteristics, yield components and grain yield of corn. Materials and methods: In order to evaluate the effect of some weed management treatments on corn (Zea mays L. yield an experiment was conducted in 2014 in Ravansar, Kermanshah, Iran. This study was arranged based on randomized complete block design with 10 treatments and three replications. The weed management treatments were including 1-chemical control followed by mechanical control (application of nicosulfuron at a dose of 80 g.a.i.ha-1 + cultivator 40 days after emergence 2- chemical control followed by mechanical control (application of 2,4-D+MCPA at a dose of 675 g.a.i.ha-1 + cultivator 40 days after emergence 3- cultural control followed by mechanical control (planting hairy vetch (Vicia villosa in the fall

A Channelization-Based DOA Estimation Method for Wideband Signals

Directory of Open Access Journals (Sweden)

Rui Guo

2016-07-01

Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

Long-term yield effects of establishment method and weed control in willow for short rotation coppice (SRC)

DEFF Research Database (Denmark)

Larsen, Søren Ugilt; Jørgensen, Uffe; Kjeldsen, Jens Bonderup

2014-01-01

matter (DM) yield was measured over 6 harvest rotations corresponding to 16 years. In 1st rotation, yield differed significantly between establishment methods with highest yield for 1.8 m rods (10.4 Mg ha−1 year−1), intermediate yield for cuttings and 0.2 m billets (8.6 and 8.5 Mg ha−1 year−1...... establishment methods; 1) vertical planting of standard 0.2 m cuttings; 2) horizontal planting of 0.1 m billets; 3) horizontal planting of 0.2 m billets; 4) horizontal planting of 1.8 m rods. All establishment methods were combined with mechanical and chemical weed control during the establishment year. Dry......, respectively) and lowest for 0.1 m billets (5.6 Mg ha−1 year−1). No differences were found in 2nd rotation. Over 1st and 2nd rotation, mechanical weed control resulted in significantly lower yield than chemical control when combined with 0.1 m billets. Cuttings and 1.8 m rods were compared over 1st, 2nd, 3rd...

Determination of the ultimate load in concrete slabs by the yield line finite element method

International Nuclear Information System (INIS)

Vaz, L.E.; Feijo, B.; Martha, L.F.R.; Lopes, M.M.

1984-01-01

A method for calculating the ultimate load in reinforced concrete slabs is proposed. The method follows the finite element aproach representating the continuum slab as an assembly of rigid triangular plates connected along their sides through yield line elements. This approach leads to the definition of the displacement configuration of the plate only as a function of the transversal displacement at the nodes of the mesh (1 DOF per node) reducing significantly the number of DOF's in relation to the conventional formulation by means of the finite element method (minimum of 3 DOF per node). Nonlinear behaviour of the reinforced concrete section is considered in the definition of the moment rotation curve of the yield lines. The effect of the in plane forces acting in the middle surface of the plate is also taken into account. The validity of the model is verified comparing the numerical solutions with the results of the classical yield line theory. (Author) [pt

Aircraft height estimation using 2-D radar

CSIR Research Space (South Africa)

Hakl, H

2010-01-01

Full Text Available A method to infer height information from an aircraft tracked with a single 2-D search radar is presented. The method assumes level flight in the target aircraft and a good estimate of the speed of the aircraft. The method yields good results...

Multi-approach assessment of the spatial distribution of the specific yield: application to the Crau plain aquifer, France

Science.gov (United States)

Seraphin, Pierre; Gonçalvès, Julio; Vallet-Coulomb, Christine; Champollion, Cédric

2018-03-01

Spatially distributed values of the specific yield, a fundamental parameter for transient groundwater mass balance calculations, were obtained by means of three independent methods for the Crau plain, France. In contrast to its traditional use to assess recharge based on a given specific yield, the water-table fluctuation (WTF) method, applied using major recharging events, gave a first set of reference values. Then, large infiltration processes recorded by monitored boreholes and caused by major precipitation events were interpreted in terms of specific yield by means of a one-dimensional vertical numerical model solving Richards' equations within the unsaturated zone. Finally, two gravity field campaigns, at low and high piezometric levels, were carried out to assess the groundwater mass variation and thus alternative specific yield values. The range obtained by the WTF method for this aquifer made of alluvial detrital material was 2.9- 26%, in line with the scarce data available so far. The average spatial value of specific yield by the WTF method (9.1%) is consistent with the aquifer scale value from the hydro-gravimetric approach. In this investigation, an estimate of the hitherto unknown spatial distribution of the specific yield over the Crau plain was obtained using the most reliable method (the WTF method). A groundwater mass balance calculation over the domain using this distribution yielded similar results to an independent quantification based on a stable isotope-mixing model. This agreement reinforces the relevance of such estimates, which can be used to build a more accurate transient hydrogeological model.

Effects of different irrigation methods on pepper yield and soilborne diseases incidence

Directory of Open Access Journals (Sweden)

Seral YÜCEL

2013-12-01

Full Text Available In this study, the effect of different irrigation strategies and irrigation methods on yields and the incidence of wilt (Fusarium oxysporum and root rot (Fusarium solani and Macrophomina phaseolina diseases causing significant yield losses on field grown processing red pepper is determined. Experiments were carried out at Topçu Station of the Soil and Water Resources Research Institute of Tarsus in 2010 and 2011. Karaisalı processing pepper (Capsicum annuum L. was used in the experiments. Three furrows and five drip irrigation treatments were used in the study. The disease incidence rates were found 8.0-18.2% in furrow irrigation plots and 4.5-10.0% in drip irrigation plots in 2010, while it was 3.4-9.7% in furrow irrigation plots and 2.2-4.5% in drip irrigation plots in 2011. Pepper yields ranged from 3 416 to 4 417 kg da-1 and 3 376 to 4 779 kg da-1 in drip irrigated plots in 2010 and 2011, respectively. However, yields varied between 3 172-3 559 kg da-1 and 2 932-4 150 kg da-1 in furrow irrigated plots in 2010 and 2011 growing seasons.

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

Directory of Open Access Journals (Sweden)

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.

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

Yield Gap analysis - Rationale, methods and applications - Introduction to the Special Issue

NARCIS (Netherlands)

Ittersum, van M.K.; Cassman, K.G.

2013-01-01

Yield gap analysis is an increasingly popular concept. It is a powerful method to reveal and understand the biophysical opportunities to meet the projected increase in demand for agricultural products towards 2050, and to support decision making on research, policies, development and investment that

Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

Science.gov (United States)

A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

Assessment of sediment yield using RS and GIS at two sub-basins of Dez Watershed, Iran

Directory of Open Access Journals (Sweden)

Hamed Noori

2016-09-01

Full Text Available Soil erosion is a serious threat to soil and water resources in semi-arid regions. Modified Pacific South-west Inter Agency Committee (MPSIAC and Erosion Potential Method (EPM, as two well-known models, have shown their performance in many case studies. The goal of present study is to assess the efficiency of these methods for estimating the sediments yield and erosion intensity within short-term and long-term timeframes over two sub-basins of Dez watershed, west of Iran. The results showed that the study area can be categorized into slight, moderate, high and very high erosion zones. Almost half of the study area is highly susceptible to erosion due to the geological formations and land cover. Moreover, the long-term (i.e. 30 years sediment yield of 387 and 615 (kton y−1 estimated by MPSIAC and EPM models demonstrated the superiority of EPM. Compared to the measured value of 612 (kton y−1, the performance of EPM was astonishing. By splitting the dataset into six periods of five years, the sediment yield was predicted in short-term periods by both aforementioned methods. Such segmentation provides the opportunity to evaluate the impact of extreme flooding events on the models performances. The results showed that both models failed in estimation of sediment load during flood conditions. Nevertheless, the correlation coefficients for estimating the sediment yield were found to be R=0.93 and R=0.85 for EPM and MPSIAC models respectively, for short-term simulations.

Assessing Sediment Yield and the Effect of Best Management Practices on Sediment Yield Reduction for Tutuila Island, American Samoa

Science.gov (United States)

Leta, O. T.; Dulai, H.; El-Kadi, A. I.

2017-12-01

Upland soil erosion and sedimentation are the main threats for riparian and coastal reef ecosystems in Pacific islands. Here, due to small size of the watersheds and steep slope, the residence time of rainfall runoff and its suspended load is short. Fagaalu bay, located on the island of Tutuila (American Samoa) has been identified as a priority watershed, due to degraded coral reef condition and reduction of stream water quality from heavy anthropogenic activity yielding high nutrients and sediment loads to the receiving water bodies. This study aimed to estimate the sediment yield to the Fagaalu stream and assess the impact of Best Management Practices (BMP) on sediment yield reduction. For this, the Soil and Water Assessment Tool (SWAT) model was applied, calibrated, and validated for both daily streamflow and sediment load simulation. The model also estimated the sediment yield contributions from existing land use types of Fagaalu and identified soil erosion prone areas for introducing BMP scenarios in the watershed. Then, three BMP scenarios, such as stone bund, retention pond, and filter strip were treated on bare (quarry area), agricultural, and shrub land use types. It was found that the bare land with quarry activity yielded the highest annual average sediment yield of 133 ton per hectare (t ha-1) followed by agriculture (26.1 t ha-1) while the lowest sediment yield of 0.2 t ha-1 was estimated for the forested part of the watershed. Additionally, the bare land area (2 ha) contributed approximately 65% (207 ha) of the watershed's sediment yield, which is 4.0 t ha-1. The latter signifies the high impact as well as contribution of anthropogenic activity on sediment yield. The use of different BMP scenarios generally reduced the sediment yield to the coastal reef of Fagaalu watershed. However, treating the quarry activity area with stone bund showed the highest sediment yield reduction as compared to the other two BMP scenarios. This study provides an estimate

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

Estimation of pump operational state with model-based methods

International Nuclear Information System (INIS)

Ahonen, Tero; Tamminen, Jussi; Ahola, Jero; Viholainen, Juha; Aranto, Niina; Kestilae, Juha

2010-01-01

Pumps are widely used in industry, and they account for 20% of the industrial electricity consumption. Since the speed variation is often the most energy-efficient method to control the head and flow rate of a centrifugal pump, frequency converters are used with induction motor-driven pumps. Although a frequency converter can estimate the operational state of an induction motor without external measurements, the state of a centrifugal pump or other load machine is not typically considered. The pump is, however, usually controlled on the basis of the required flow rate or output pressure. As the pump operational state can be estimated with a general model having adjustable parameters, external flow rate or pressure measurements are not necessary to determine the pump flow rate or output pressure. Hence, external measurements could be replaced with an adjustable model for the pump that uses estimates of the motor operational state. Besides control purposes, modelling the pump operation can provide useful information for energy auditing and optimization purposes. In this paper, two model-based methods for pump operation estimation are presented. Factors affecting the accuracy of the estimation methods are analyzed. The applicability of the methods is verified by laboratory measurements and tests in two pilot installations. Test results indicate that the estimation methods can be applied to the analysis and control of pump operation. The accuracy of the methods is sufficient for auditing purposes, and the methods can inform the user if the pump is driven inefficiently.

Population Estimation with Mark and Recapture Method Program

International Nuclear Information System (INIS)

Limohpasmanee, W.; Kaewchoung, W.

1998-01-01

Population estimation is the important information which required for the insect control planning especially the controlling with SIT. Moreover, It can be used to evaluate the efficiency of controlling method. Due to the complexity of calculation, the population estimation with mark and recapture methods were not used widely. So that, this program is developed with Qbasic on the purpose to make it accuracy and easier. The program evaluation consists with 6 methods; follow Seber's, Jolly-seber's, Jackson's Ito's, Hamada's and Yamamura's methods. The results are compared with the original methods, found that they are accuracy and more easier to applied

A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

Science.gov (United States)

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

2007-11-01

Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

Science.gov (United States)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

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

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

Science.gov (United States)

Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

Directory of Open Access Journals (Sweden)

Bin Ran

Full Text Available Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

Simple Method to Estimate Mean Heart Dose From Hodgkin Lymphoma Radiation Therapy According to Simulation X-Rays

Energy Technology Data Exchange (ETDEWEB)

Nimwegen, Frederika A. van [Department of Psychosocial Research, Epidemiology, and Biostatistics, The Netherlands Cancer Institute, Amsterdam (Netherlands); Cutter, David J. [Clinical Trial Service Unit, University of Oxford, Oxford (United Kingdom); Oxford Cancer Centre, Oxford University Hospitals NHS Trust, Oxford (United Kingdom); Schaapveld, Michael [Department of Psychosocial Research, Epidemiology, and Biostatistics, The Netherlands Cancer Institute, Amsterdam (Netherlands); Rutten, Annemarieke [Department of Radiology, The Netherlands Cancer Institute, Amsterdam (Netherlands); Kooijman, Karen [Department of Psychosocial Research, Epidemiology, and Biostatistics, The Netherlands Cancer Institute, Amsterdam (Netherlands); Krol, Augustinus D.G. [Department of Radiation Oncology, Leiden University Medical Center, Leiden (Netherlands); Janus, Cécile P.M. [Department of Radiation Oncology, Erasmus MC Cancer Center, Rotterdam (Netherlands); Darby, Sarah C. [Clinical Trial Service Unit, University of Oxford, Oxford (United Kingdom); Leeuwen, Flora E. van [Department of Psychosocial Research, Epidemiology, and Biostatistics, The Netherlands Cancer Institute, Amsterdam (Netherlands); Aleman, Berthe M.P., E-mail: b.aleman@nki.nl [Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam (Netherlands)

2015-05-01

Purpose: To describe a new method to estimate the mean heart dose for Hodgkin lymphoma patients treated several decades ago, using delineation of the heart on radiation therapy simulation X-rays. Mean heart dose is an important predictor for late cardiovascular complications after Hodgkin lymphoma (HL) treatment. For patients treated before the era of computed tomography (CT)-based radiotherapy planning, retrospective estimation of radiation dose to the heart can be labor intensive. Methods and Materials: Patients for whom cardiac radiation doses had previously been estimated by reconstruction of individual treatments on representative CT data sets were selected at random from a case–control study of 5-year Hodgkin lymphoma survivors (n=289). For 42 patients, cardiac contours were outlined on each patient's simulation X-ray by 4 different raters, and the mean heart dose was estimated as the percentage of the cardiac contour within the radiation field multiplied by the prescribed mediastinal dose and divided by a correction factor obtained by comparison with individual CT-based dosimetry. Results: According to the simulation X-ray method, the medians of the mean heart doses obtained from the cardiac contours outlined by the 4 raters were 30 Gy, 30 Gy, 31 Gy, and 31 Gy, respectively, following prescribed mediastinal doses of 25-42 Gy. The absolute-agreement intraclass correlation coefficient was 0.93 (95% confidence interval 0.85-0.97), indicating excellent agreement. Mean heart dose was 30.4 Gy with the simulation X-ray method, versus 30.2 Gy with the representative CT-based dosimetry, and the between-method absolute-agreement intraclass correlation coefficient was 0.87 (95% confidence interval 0.80-0.95), indicating good agreement between the two methods. Conclusion: Estimating mean heart dose from radiation therapy simulation X-rays is reproducible and fast, takes individual anatomy into account, and yields results comparable to the labor

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.

A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation

DEFF Research Database (Denmark)

Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri

2013-01-01

representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...

Estimation of genetic divergence in rice (oryza sativa l) germplasms on the basis of paddy yield and rice stem borer's (pyralidae: lepidoptera) resistance

International Nuclear Information System (INIS)

Sarwar, M.

2013-01-01

Field trials were carried out to estimate resistance along with paddy yield in 55 rice germplasm lines (35 aromatic and 20 non-aromatic genotypes) for rice stem borers (Pyralidae: Lepidoptera) to expose their potential in pest management approach. The results expressed significant differences for pest damage build-up and paddy yield among the rice germplasm lines. The findings clearly portrayed that based upon the percentage of pest invasions (dead hearts and white heads damage), no genotype was exclusively resistant to stem borers damage under field conditions. Two aromatic genotypes, Jajai-15A/97 and Basmati-Cr-34, exhibited least borers prevalence and amplified paddy yield while Sonehri Sugdasi (P) and Sada Gulab (P) pointed out a peak pest invasion and declined paddy yield. The estimation of pest incidence build-up and paddy productivity within non-aromatic genotypes confirmed that IR8 (P), IR6-15-2 and IR6 (P) were mainly proficient for bearing condensed pest invasion and augmented paddy yield. IR8-2.5-4, IR6-15-10 and IR6-20-9 demonstrated elevated pest susceptibility and gave poor yield. Rest of the germplasms appeared to be least tolerant or vulnerable to pest build-up and reduced paddy production. The tolerant and high yielding genotypes should be popularised in rice borers endemic areas and can be used in varietals resistance breeding strategy. The outcome of current studies necessitates the integration of existing host plant tolerance along with other management strategies to accomplish a suitable control of rice stem borers and enhance paddy yield. (author)

Yield loss prediction models based on early estimation of weed pressure

DEFF Research Database (Denmark)

Asif, Ali; Streibig, Jens Carl; Andreasen, Christian

2013-01-01

thresholds are more relevant for site-specific weed management, because weeds are unevenly distributed in fields. Precision of prediction of yield loss is influenced by various factors such as locations, yield potential at the site, variation in competitive ability of mix stands of weed species and emergence...

Estimation methods for nonlinear state-space models in ecology

DEFF Research Database (Denmark)

Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

2011-01-01

The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

Simple method to estimate mean heart dose from Hodgkin lymphoma radiation therapy according to simulation X-rays.

Science.gov (United States)

van Nimwegen, Frederika A; Cutter, David J; Schaapveld, Michael; Rutten, Annemarieke; Kooijman, Karen; Krol, Augustinus D G; Janus, Cécile P M; Darby, Sarah C; van Leeuwen, Flora E; Aleman, Berthe M P

2015-05-01

To describe a new method to estimate the mean heart dose for Hodgkin lymphoma patients treated several decades ago, using delineation of the heart on radiation therapy simulation X-rays. Mean heart dose is an important predictor for late cardiovascular complications after Hodgkin lymphoma (HL) treatment. For patients treated before the era of computed tomography (CT)-based radiotherapy planning, retrospective estimation of radiation dose to the heart can be labor intensive. Patients for whom cardiac radiation doses had previously been estimated by reconstruction of individual treatments on representative CT data sets were selected at random from a case-control study of 5-year Hodgkin lymphoma survivors (n=289). For 42 patients, cardiac contours were outlined on each patient's simulation X-ray by 4 different raters, and the mean heart dose was estimated as the percentage of the cardiac contour within the radiation field multiplied by the prescribed mediastinal dose and divided by a correction factor obtained by comparison with individual CT-based dosimetry. According to the simulation X-ray method, the medians of the mean heart doses obtained from the cardiac contours outlined by the 4 raters were 30 Gy, 30 Gy, 31 Gy, and 31 Gy, respectively, following prescribed mediastinal doses of 25-42 Gy. The absolute-agreement intraclass correlation coefficient was 0.93 (95% confidence interval 0.85-0.97), indicating excellent agreement. Mean heart dose was 30.4 Gy with the simulation X-ray method, versus 30.2 Gy with the representative CT-based dosimetry, and the between-method absolute-agreement intraclass correlation coefficient was 0.87 (95% confidence interval 0.80-0.95), indicating good agreement between the two methods. Estimating mean heart dose from radiation therapy simulation X-rays is reproducible and fast, takes individual anatomy into account, and yields results comparable to the labor-intensive representative CT-based method. This simpler method may produce a

Bin mode estimation methods for Compton camera imaging

International Nuclear Information System (INIS)

Ikeda, S.; Odaka, H.; Uemura, M.; Takahashi, T.; Watanabe, S.; Takeda, S.

2014-01-01

We study the image reconstruction problem of a Compton camera which consists of semiconductor detectors. The image reconstruction is formulated as a statistical estimation problem. We employ a bin-mode estimation (BME) and extend an existing framework to a Compton camera with multiple scatterers and absorbers. Two estimation algorithms are proposed: an accelerated EM algorithm for the maximum likelihood estimation (MLE) and a modified EM algorithm for the maximum a posteriori (MAP) estimation. Numerical simulations demonstrate the potential of the proposed methods

Methods for the estimation of uranium ore reserves

International Nuclear Information System (INIS)

1985-01-01

The Manual is designed mainly to provide assistance in uranium ore reserve estimation methods to mining engineers and geologists with limited experience in estimating reserves, especially to those working in developing countries. This Manual deals with the general principles of evaluation of metalliferous deposits but also takes into account the radioactivity of uranium ores. The methods presented have been generally accepted in the international uranium industry

Invited review: A commentary on predictive cheese yield formulas.

Science.gov (United States)

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion

Modeling Growth and Yield of Schizolobium amazonicum under Different Spacings

Directory of Open Access Journals (Sweden)

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.

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 SOFTWARE RELIABILITY ESTIMATION METHOD TO NUCLEAR SAFETY SOFTWARE

Directory of Open Access Journals (Sweden)

GEE-YONG PARK

2014-02-01

Full Text Available A method for estimating software reliability for nuclear safety software is proposed in this paper. This method is based on the software reliability growth model (SRGM, where the behavior of software failure is assumed to follow a non-homogeneous Poisson process. Two types of modeling schemes based on a particular underlying method are proposed in order to more precisely estimate and predict the number of software defects based on very rare software failure data. The Bayesian statistical inference is employed to estimate the model parameters by incorporating software test cases as a covariate into the model. It was identified that these models are capable of reasonably estimating the remaining number of software defects which directly affects the reactor trip functions. The software reliability might be estimated from these modeling equations, and one approach of obtaining software reliability value is proposed in this paper.

The effects of planting methods and head pruning on seed yield and yield components of medicinal pumpkin (Cucurbita pepo subsp. Pepo convar. Pepo var. styriaca) at low temperature areas.

Science.gov (United States)

Bahrami, R Nikkhah; Khodadadi, M; Pirivatlo, S Piry; Hassanpanah, D

2009-03-15

This experiment carried out to evaluate the effects of planting methods (seed sowing and transplanting) and head pruning (no pruning, pruning after 12th node and pruning after 16th node) on yield and yield components such as number of branches (sub-branches) per plant, fruits per plant, growth, fruit size, weight of fresh fruit, weight of seeds per fruit, number of seeds per fruit and seed yield of medicinal pumpkin. The experiment was carried out based of factorial experiment with Randomized Completely Blocks Design (RCBD) by three replications in Ardabil Agricultural and Natural Resources Researches Station at 2007. Seedlings were grown in heated greenhouse. When the climatic condition became suitable and seedlings were at the four leaves stage, both seeds and seedlings were planted at the same time in the farm. Maintenance operations were done during the growth season. Head pruning treatments were done the forecast time. The results showed that the planting methods had significant effect on the number of ripen fruits per plant, fruits diameter, weight of seeds per fruit, weight of 1000 seeds and seed yield and had no significant effect on the other traits. Also the results indicated that head pruning treatments had significant effects on the number of branches per plant, growth and seed yield and no significant on the other traits. In this experiment the most seed yield (997.8 kg ha(-1)) obtained from transplanting method with head pruning after 12th node and the least seed yield obtained from control.

Climate change impacts on crop yield: evidence from China.

Science.gov (United States)

Wei, Taoyuan; Cherry, Todd L; Glomrød, Solveig; Zhang, Tianyi

2014-11-15

When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation and reliability of bone histological age estimation methods

African Journals Online (AJOL)

Human age estimation at death plays a vital role in forensic anthropology and bioarchaeology. Researchers used morphological and histological methods to estimate human age from their skeletal remains. This paper discussed different histological methods that used human long bones and ribs to determine age ...

Research Notes Use of the dry-weight-rank method of botanical ...

African Journals Online (AJOL)

When used in combination with the double sampling (or comparative yield) method of yield estimation, the dry-weight-rank method of botanical analysis provides a rapid non-destructive means of estimating botanical composition. The composition is expressed in terms of the contribution of individual species to total herbage ...

The estimation of rust disease of daylily leaf images with GLCM based different classification methods

OpenAIRE

ÖZERDEM, Mehmet Siraç; ACAR, Emrullah

2011-01-01

Crop diseases can affect yield and/or quality of the harvested commodity. This can influence profitability and raise the risks of farming. When the diseases are estimated early, the yield will increase by taking measures thanks to farmers. The rust disease is one of the most major crop diseases that affect crop yield. Rust disease can be defined as a fungus; it makes the crops weak by blocking food to the roots and leaves. It is named “rust” disease, since the spots on the leaves look like gr...

An Innovative Method for Estimating Soil Retention at a ...

Science.gov (United States)

Planning for a sustainable future should include an accounting of services currently provided by ecosystems such as erosion control. Retention of soil improves fertility, increases water retention, and decreases sedimentation in streams and rivers. Landscapes patterns that facilitate these services could help reduce costs for flood control, dredging of reservoirs and waterways, while maintaining habitat for fish and other species important to recreational and tourism industries. Landscape scale geospatial data available for the continental United States was leveraged to estimate sediment erosion (RUSLE-based, Renard, et al. 1997) employing recent geospatial techniques of sediment delivery ratio (SDR) estimation (Cavalli, et al. 2013). The approach was designed to derive a quantitative approximation of the ecological services provided by vegetative cover, management practices, and other surface features with respect to protecting soils from the erosion processes of detachment, transport, and deposition. Quantities of soil retained on the landscape and potential erosion for multiple land cover scenarios relative to current (NLCD 2011) conditions were calculated for each calendar month, and summed to yield annual estimations at a 30-meter grid cell. Continental-scale data used included MODIS NDVI data (2000-2014) to estimate monthly USLE C-factors, gridded soil survey geographic (gSSURGO) soils data (annual USLE K factor), PRISM rainfall data (monthly USLE

EFFECT OF SOWING DATE AND WEED CONTROL METHOD ON THE GROWTH AND YIELD OF SOYBEAN

Directory of Open Access Journals (Sweden)

Nasrin Akter

2016-06-01

Full Text Available Sowing date and weed management play a significant role in determining soybean growth, development and seed yield. Results showed that different sowing date and weed control methods had significant effect on relative weed density, weed biomass, weed control efficiency, plant height, dry weight plant-1 and seed yield of soybean. Among the infested weed species in the experimental field the dominant weeds were Lindernia procumbens (44.78%, Echinochloa colonum (26.39% and Cynodon dactylon (16.30%. The results also revealed that early sowing (2 January brought about the highest seed yield (2.17 t ha-1 and sowing delay (1 February resulted in the lowest yield (1.64 t ha-1. Two times hand weeding (20 and 40 DAS controlled the weeds most effectively and led to highest seed yield (2.23 t ha-1 which was statistically similar (2.19 t ha-1 with herbicide application. Combination effect showed that the highest seed yield (2.50 t ha-1 was obtained from 2 January sowing when the crop was weeded by hand at 20 and 40 DAS.

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

Science.gov (United States)

Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

2013-12-01

Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

Study on Top-Down Estimation Method of Software Project Planning

Institute of Scientific and Technical Information of China (English)

ZHANG Jun-guang; L(U) Ting-jie; ZHAO Yu-mei

2006-01-01

This paper studies a new software project planning method under some actual project data in order to make software project plans more effective. From the perspective of system theory, our new method regards a software project plan as an associative unit for study. During a top-down estimation of a software project, Program Evaluation and Review Technique (PERT) method and analogy method are combined to estimate its size, then effort estimation and specific schedules are obtained according to distributions of the phase effort. This allows a set of practical and feasible planning methods to be constructed. Actual data indicate that this set of methods can lead to effective software project planning.

Gold nanoparticles production using reactor and cyclotron based methods in assessment of {sup 196,198}Au production yields by {sup 197}Au neutron absorption for therapeutic purposes

Energy Technology Data Exchange (ETDEWEB)

Khorshidi, Abdollah, E-mail: abkhorshidi@yahoo.com

2016-11-01

Medical nano-gold radioisotopes is produced regularly using high-flux nuclear reactors, and an accelerator-driven neutron activator can turn out higher yield of {sup 197}Au(n,γ){sup 196,198}Au reactions. Here, nano-gold production via radiative/neutron capture was investigated using irradiated Tehran Research Reactor flux and also simulated proton beam of Karaj cyclotron in Iran. {sup 197}Au nano-solution, including 20 nm shaped spherical gold and water, was irradiated under Tehran reactor flux at 2.5E + 13 n/cm{sup 2}/s for {sup 196,198}Au activity and production yield estimations. Meanwhile, the yield was examined using 30 MeV proton beam of Karaj cyclotron via simulated new neutron activator containing beryllium target, bismuth moderator around the target, and also PbF{sub 2} reflector enclosed the moderator region. Transmutation in {sup 197}Au nano-solution samples were explored at 15 and 25 cm distances from the target. The neutron flux behavior inside the water and bismuth moderators was investigated for nano-gold particles transmutation. The transport of fast neutrons inside bismuth material as heavy nuclei with a lesser lethargy can be contributed in enhanced nano-gold transmutation with long duration time than the water moderator in reactor-based method. Cyclotron-driven production of βeta-emitting radioisotopes for brachytherapy applications can complete the nano-gold production technology as a safer approach as compared to the reactor-based method. - Graphical abstract: This figure describes gold nanoparticles production via cyclotron based method. The aim of investigating is to estimate activity and saturation yield of {sup 197}Au(n,γ){sup 198}Au and {sup 197}Au(n,2n){sup 196}Au reactions using Karaj cyclotron available in Iran. The feasibility of a cyclotron-driven production of βeta-emitting radioisotopes was investigated for therapeutic applications via a new neutron activator design. - Highlights: • Nano-gold radioisotope production

Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models

Directory of Open Access Journals (Sweden)

Herbert Formayer

2007-10-01

Full Text Available The results of previous studies have suggested that estimated daily globalradiation (RG values contain an error that could compromise the precision of subsequentcrop model applications. The following study presents a detailed site and spatial analysis ofthe RG error propagation in CERES and WOFOST crop growth models in Central Europeanclimate conditions. The research was conducted i at the eight individual sites in Austria andthe Czech Republic where measured daily RG values were available as a reference, withseven methods for RG estimation being tested, and ii for the agricultural areas of the CzechRepublic using daily data from 52 weather stations, with five RG estimation methods. In thelatter case the RG values estimated from the hours of sunshine using the ångström-Prescottformula were used as the standard method because of the lack of measured RG data. At thesite level we found that even the use of methods based on hours of sunshine, which showedthe lowest bias in RG estimates, led to a significant distortion of the key crop model outputs.When the ångström-Prescott method was used to estimate RG, for example, deviationsgreater than ±10 per cent in winter wheat and spring barley yields were noted in 5 to 6 percent of cases. The precision of the yield estimates and other crop model outputs was lowerwhen RG estimates based on the diurnal temperature range and cloud cover were used (mean bias error 2.0 to 4.1 per cent. The methods for estimating RG from the diurnal temperature range produced a wheat yield bias of more than 25 per cent in 12 to 16 per cent of the seasons. Such uncertainty in the crop model outputs makes the reliability of any seasonal yield forecasts or climate change impact assessments questionable if they are based on this type of data. The spatial assessment of the RG data uncertainty propagation over the winter wheat yields also revealed significant differences within the study area. We

Estimation in adults of the glomerular filtration rate in [99mTc] DTPA renography - the rate constant method

International Nuclear Information System (INIS)

Carlsen, Ove

2004-01-01

The purpose of this study was to design an alternative and robust method for estimation of glomerular filtration rate (GFR) in [ 99 mTc]-diethylenetriaminepentaacetic acid ([ 99 mTc] -DTPA renography with a reliability not significantly lower than that of the conventional Gates' method. Methods: The method is based on renographies lasting 40 min in which regions of interest (ROIs) are manually created over selected parts of certain blood pools (e.g. heart, lungs, spleen, and liver). For each ROI the corresponding time-activity curve (TAC) was generated, decay corrected and exposed to a monoexponential fit in the time interval 10 to 40 min postinjection. The rate constant in min-1 of the monoexponential fit was denoted BETA. Following an iterative procedure comprising usually 5-10 manually created ROIs, the monoexponential fit with the maximum rate constant (BETA max ) was used for estimation of GFR. Results: In a patient material of 54 adult subjects in whom GFR was determined with multiple or one sample techniques with [ 51 Cr]-ethylenediaminetetraacetic acid ([ 51 Cr]-EDTA) the regression curve of standard GFR (GFR std ) (i.e. GFR adjusted to 1.73 m 2 body surface area) showed a close, non-linear relationship with BETA max with a correlation coefficient of 95%. The standard errors of estimate (SEE) were 6.6, 10.6 and 16.8 for GFR std equal to 30, 60, and 120 ml/(min .73 m 2 ), respectively. The corresponding SEE values for almost the same patient material using Gates' method were 8.4, 11.9, and 16.8 ml/(min 1.73 m 2 ). Conclusions: The alternative rate constant method yields estimates of GFR std with SEE values equal to or slightly smaller than in Gates' method. The two methods provide statistically uncorrelated estimates of GFR std . Therefore, pooled estimates of GFR std can be calculated with SEE values approximately 1.41 times smaller than those mentioned above. The reliabilities of the pooled estimate of GFR std separately and of the multiple samples method

An improved method for estimating the frequency correlation function

KAUST Repository

Chelli, Ali; Pä tzold, Matthias

2012-01-01

For time-invariant frequency-selective channels, the transfer function is a superposition of waves having different propagation delays and path gains. In order to estimate the frequency correlation function (FCF) of such channels, the frequency averaging technique can be utilized. The obtained FCF can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs are caused by the autocorrelation of individual path components. The CTs are due to the cross-correlation of different path components. These CTs have no physical meaning and leads to an estimation error. We propose a new estimation method aiming to improve the estimation accuracy of the FCF of a band-limited transfer function. The basic idea behind the proposed method is to introduce a kernel function aiming to reduce the CT effect, while preserving the ATs. In this way, we can improve the estimation of the FCF. The performance of the proposed method and the frequency averaging technique is analyzed using a synthetically generated transfer function. We show that the proposed method is more accurate than the frequency averaging technique. The accurate estimation of the FCF is crucial for the system design. In fact, we can determine the coherence bandwidth from the FCF. The exact knowledge of the coherence bandwidth is beneficial in both the design as well as optimization of frequency interleaving and pilot arrangement schemes. © 2012 IEEE.

An improved method for estimating the frequency correlation function

KAUST Repository

Chelli, Ali

2012-04-01

For time-invariant frequency-selective channels, the transfer function is a superposition of waves having different propagation delays and path gains. In order to estimate the frequency correlation function (FCF) of such channels, the frequency averaging technique can be utilized. The obtained FCF can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs are caused by the autocorrelation of individual path components. The CTs are due to the cross-correlation of different path components. These CTs have no physical meaning and leads to an estimation error. We propose a new estimation method aiming to improve the estimation accuracy of the FCF of a band-limited transfer function. The basic idea behind the proposed method is to introduce a kernel function aiming to reduce the CT effect, while preserving the ATs. In this way, we can improve the estimation of the FCF. The performance of the proposed method and the frequency averaging technique is analyzed using a synthetically generated transfer function. We show that the proposed method is more accurate than the frequency averaging technique. The accurate estimation of the FCF is crucial for the system design. In fact, we can determine the coherence bandwidth from the FCF. The exact knowledge of the coherence bandwidth is beneficial in both the design as well as optimization of frequency interleaving and pilot arrangement schemes. © 2012 IEEE.

Closing Yield Gaps: How Sustainable Can We Be?

Directory of Open Access Journals (Sweden)

Prajal Pradhan

Full Text Available Global food production needs to be increased by 60-110% between 2005 and 2050 to meet growing food and feed demand. Intensification and/or expansion of agriculture are the two main options available to meet the growing crop demands. Land conversion to expand cultivated land increases GHG emissions and impacts biodiversity and ecosystem services. Closing yield gaps to attain potential yields may be a viable option to increase the global crop production. Traditional methods of agricultural intensification often have negative externalities. Therefore, there is a need to explore location-specific methods of sustainable agricultural intensification. We identified regions where the achievement of potential crop calorie production on currently cultivated land will meet the present and future food demand based on scenario analyses considering population growth and changes in dietary habits. By closing yield gaps in the current irrigated and rain-fed cultivated land, about 24% and 80% more crop calories can respectively be produced compared to 2000. Most countries will reach food self-sufficiency or improve their current food self-sufficiency levels if potential crop production levels are achieved. As a novel approach, we defined specific input and agricultural management strategies required to achieve the potential production by overcoming biophysical and socioeconomic constraints causing yield gaps. The management strategies include: fertilizers, pesticides, advanced soil management, land improvement, management strategies coping with weather induced yield variability, and improving market accessibility. Finally, we estimated the required fertilizers (N, P2O5, and K2O to attain the potential yields. Globally, N-fertilizer application needs to increase by 45-73%, P2O5-fertilizer by 22-46%, and K2O-fertilizer by 2-3 times compared to the year 2010 to attain potential crop production. The sustainability of such agricultural intensification largely depends

A comparison of analysis methods to estimate contingency strength.

Science.gov (United States)

Lloyd, Blair P; Staubitz, Johanna L; Tapp, Jon T

2018-05-09

To date, several data analysis methods have been used to estimate contingency strength, yet few studies have compared these methods directly. To compare the relative precision and sensitivity of four analysis methods (i.e., exhaustive event-based, nonexhaustive event-based, concurrent interval, concurrent+lag interval), we applied all methods to a simulated data set in which several response-dependent and response-independent schedules of reinforcement were programmed. We evaluated the degree to which contingency strength estimates produced from each method (a) corresponded with expected values for response-dependent schedules and (b) showed sensitivity to parametric manipulations of response-independent reinforcement. Results indicated both event-based methods produced contingency strength estimates that aligned with expected values for response-dependent schedules, but differed in sensitivity to response-independent reinforcement. The precision of interval-based methods varied by analysis method (concurrent vs. concurrent+lag) and schedule type (continuous vs. partial), and showed similar sensitivities to response-independent reinforcement. Recommendations and considerations for measuring contingencies are identified. © 2018 Society for the Experimental Analysis of Behavior.

Plant-available soil water capacity: estimation methods and implications

Directory of Open Access Journals (Sweden)

Bruno Montoani Silva

2014-04-01

Full Text Available The plant-available water capacity of the soil is defined as the water content between field capacity and wilting point, and has wide practical application in planning the land use. In a representative profile of the Cerrado Oxisol, methods for estimating the wilting point were studied and compared, using a WP4-T psychrometer and Richards chamber for undisturbed and disturbed samples. In addition, the field capacity was estimated by the water content at 6, 10, 33 kPa and by the inflection point of the water retention curve, calculated by the van Genuchten and cubic polynomial models. We found that the field capacity moisture determined at the inflection point was higher than by the other methods, and that even at the inflection point the estimates differed, according to the model used. By the WP4-T psychrometer, the water content was significantly lower found the estimate of the permanent wilting point. We concluded that the estimation of the available water holding capacity is markedly influenced by the estimation methods, which has to be taken into consideration because of the practical importance of this parameter.

Nonparametric methods for volatility density estimation

NARCIS (Netherlands)

Es, van Bert; Spreij, P.J.C.; Zanten, van J.H.

2009-01-01

Stochastic volatility modelling of financial processes has become increasingly popular. The proposed models usually contain a stationary volatility process. We will motivate and review several nonparametric methods for estimation of the density of the volatility process. Both models based on

Fusion rule estimation using vector space methods

International Nuclear Information System (INIS)

Rao, N.S.V.

1997-01-01

In a system of N sensors, the sensor S j , j = 1, 2 .... N, outputs Y (j) element-of Re, according to an unknown probability distribution P (Y(j) /X) , corresponding to input X element-of [0, 1]. A training n-sample (X 1 , Y 1 ), (X 2 , Y 2 ), ..., (X n , Y n ) is given where Y i = (Y i (1) , Y i (2) , . . . , Y i N ) such that Y i (j) is the output of S j in response to input X i . The problem is to estimate a fusion rule f : Re N → [0, 1], based on the sample, such that the expected square error is minimized over a family of functions Y that constitute a vector space. The function f* that minimizes the expected error cannot be computed since the underlying densities are unknown, and only an approximation f to f* is feasible. We estimate the sample size sufficient to ensure that f provides a close approximation to f* with a high probability. The advantages of vector space methods are two-fold: (a) the sample size estimate is a simple function of the dimensionality of F, and (b) the estimate f can be easily computed by well-known least square methods in polynomial time. The results are applicable to the classical potential function methods and also (to a recently proposed) special class of sigmoidal feedforward neural networks

A Benchmark Estimate for the Capital Stock. An Optimal Consistency Method

OpenAIRE

Jose Miguel Albala-Bertrand

2001-01-01

There are alternative methods to estimate a capital stock for a benchmark year. These methods, however, do not allow for an independent check, which could establish whether the estimated benchmark level is too high or too low. I propose here an optimal consistency method (OCM), which may allow estimating a capital stock level for a benchmark year and/or checking the consistency of alternative estimates of a benchmark capital stock.

Thermodynamic properties of organic compounds estimation methods, principles and practice

CERN Document Server

Janz, George J

1967-01-01

Thermodynamic Properties of Organic Compounds: Estimation Methods, Principles and Practice, Revised Edition focuses on the progression of practical methods in computing the thermodynamic characteristics of organic compounds. Divided into two parts with eight chapters, the book concentrates first on the methods of estimation. Topics presented are statistical and combined thermodynamic functions; free energy change and equilibrium conversions; and estimation of thermodynamic properties. The next discussions focus on the thermodynamic properties of simple polyatomic systems by statistical the

Estimating the potential intensification of global grazing systems based on climate adjusted yield gap analysis

Science.gov (United States)

Sheehan, J. J.

2016-12-01

We report here a first-of-its-kind analysis of the potential for intensification of global grazing systems. Intensification is calculated using the statistical yield gap methodology developed previously by others (Mueller et al 2012 and Licker et al 2010) for global crop systems. Yield gaps are estimated by binning global pasture land area into 100 equal area sized bins of similar climate (defined by ranges of rainfall and growing degree days). Within each bin, grid cells of pastureland are ranked from lowest to highest productivity. The global intensification potential is defined as the sum of global production across all bins at a given percentile ranking (e.g. performance at the 90th percentile) divided by the total current global production. The previous yield gap studies focused on crop systems because productivity data on these systems is readily available. Nevertheless, global crop land represents only one-third of total global agricultural land, while pasture systems account for the remaining two-thirds. Thus, it is critical to conduct the same kind of analysis on what is the largest human use of land on the planet—pasture systems. In 2013, Herrero et al announced the completion of a geospatial data set that augmented the animal census data with data and modeling about production systems and overall food productivity (Herrero et al, PNAS 2013). With this data set, it is now possible to apply yield gap analysis to global pasture systems. We used the Herrero et al data set to evaluate yield gaps for meat and milk production from pasture based systems for cattle, sheep and goats. The figure included with this abstract shows the intensification potential for kcal per hectare per year of meat and milk from global cattle, sheep and goats as a function of increasing levels of performance. Performance is measured as the productivity achieved at a given ranked percentile within each bin.We find that if all pasture land were raised to their 90th percentile of

A Group Contribution Method for Estimating Cetane and Octane Numbers

Energy Technology Data Exchange (ETDEWEB)

Kubic, William Louis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Process Modeling and Analysis Group

2016-07-28

Much of the research on advanced biofuels is devoted to the study of novel chemical pathways for converting nonfood biomass into liquid fuels that can be blended with existing transportation fuels. Many compounds under consideration are not found in the existing fuel supplies. Often, the physical properties needed to assess the viability of a potential biofuel are not available. The only reliable information available may be the molecular structure. Group contribution methods for estimating physical properties from molecular structure have been used for more than 60 years. The most common application is estimation of thermodynamic properties. More recently, group contribution methods have been developed for estimating rate dependent properties including cetane and octane numbers. Often, published group contribution methods are limited in terms of types of function groups and range of applicability. In this study, a new, broadly-applicable group contribution method based on an artificial neural network was developed to estimate cetane number research octane number, and motor octane numbers of hydrocarbons and oxygenated hydrocarbons. The new method is more accurate over a greater range molecular weights and structural complexity than existing group contribution methods for estimating cetane and octane numbers.

Estimated harvesting on jellyfish in Sarawak

Science.gov (United States)

Bujang, Noriham; Hassan, Aimi Nuraida Ali

2017-04-01

There are three species of jellyfish recorded in Sarawak which are the Lobonema smithii (white jellyfish), Rhopilema esculenta (red jellyfish) and Mastigias papua. This study focused on two particular species which are L.smithii and R.esculenta. This study was done to estimate the highest carrying capacity and the population growth rate of both species by using logistic growth model. The maximum sustainable yield for the harvesting of this species was also determined. The unknown parameters in the logistic model were estimated using center finite different method. As for the results, it was found that the carrying capacity for L.smithii and R.esculenta were 4594.9246456819 tons and 5855.9894242086 tons respectively. Whereas, the population growth rate for both L.smithii and R.esculenta were estimated at 2.1800463754 and 1.144864086 respectively. Hence, the estimated maximum sustainable yield for harvesting for L.smithii and R.esculenta were 2504.2872047638 tons and 1676.0779949431 tons per year.

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

Science.gov (United States)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been

Finite Element Method Application in Areal Rainfall Estimation Case Study; Mashhad Plain Basin

Directory of Open Access Journals (Sweden)

M. Irani

2016-10-01

7.08 software environment. The finite element method is a numerical procedure for obtaining solutions to many of the problems encountered in engineering analysis. First, it utilizes discrete elements to obtain the joint displacements and member forces of a structural framework and estimate areal precipitation. Second, it uses the continuum elements to obtain approximate solutions to heat transfer, fluid mechanics, and solid mechanics problems. Galerkin’s method is used to develop the finite element equations for the field problems. It uses the same functions for Ni(x that was used in the approximating equations. This approach is the basis of finite element method for problems involving first-derivative terms. This method yields the same result as the variational method when applied to differential equations that are self-adjoints. Galerkin’s method is almost simple and eliminates bias by representing the relief by suitable mathematical model and incorporating this into the integration. In this paper, two powerful techniques were introduced which was applied in Galerkin’s method: The use of interpolation functions to transform the shape of the element to a perfect square. The use of Gaussian quadrature to calculate rainfall depth numerically . In this study, Mashhad plain is divided to 40 elements which are quadrilateral. In each element, the rain gauge was situated on the node of the stations. The coordinates are given according to UTM, where x and y are the horizontal and z, the vertical (altitude coordinate. It was necessary at the outset to number the corner nodes in a set manner and for the purpose of this paper, an anticlockwise convention was adopted. Results and Discussion: This paper represented the estimation of mean precipitation (daily, monthly and annual in Mashhad plain by Galerkin’s method which was compared with arithmetic mean, Thiessen, kriging and IDW. The values of Galerkin’s method by Matlab7.08 software and Thiessen, kriging and IDW by

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.

Motion estimation using point cluster method and Kalman filter.

Science.gov (United States)

Senesh, M; Wolf, A

2009-05-01

The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal

Estimating Security Betas Using Prior Information Based on Firm Fundamentals

NARCIS (Netherlands)

Cosemans, Mathijs; Frehen, Rik; Schotman, Peter; Bauer, Rob

2016-01-01

We propose a hybrid approach for estimating beta that shrinks rolling window estimates toward firm-specific priors motivated by economic theory. Our method yields superior forecasts of beta that have important practical implications. First, unlike standard rolling window betas, hybrid betas carry a

Estimating surface area in early hominins.

Directory of Open Access Journals (Sweden)

Alan Cross

Full Text Available Height and weight-based methods of estimating surface area have played an important role in the development of the current consensus regarding the role of thermoregulation in human evolution. However, such methods may not be reliable when applied to early hominins because their limb proportions differ markedly from those of humans. Here, we report a study in which this possibility was evaluated by comparing surface area estimates generated with the best-known height and weight-based method to estimates generated with a method that is sensitive to proportional differences. We found that the two methods yield indistinguishable estimates when applied to taxa whose limb proportions are similar to those of humans, but significantly different results when applied to taxa whose proportions differ from those of humans. We also found that the discrepancy between the estimates generated by the two methods is almost entirely attributable to inter-taxa differences in limb proportions. One corollary of these findings is that we need to reassess hypotheses about the role of thermoregulation in human evolution that have been developed with the aid of height and weight-based methods of estimating body surface area. Another is that we need to use other methods in future work on fossil hominin body surface areas.

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.

A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

Science.gov (United States)

Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

2015-12-01

Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

The influence of the plantation establishment method on the yield of marshmallow (Althaea officinalis L. flowers

Directory of Open Access Journals (Sweden)

Sylwia Andruszczak

2012-12-01

Full Text Available The field experiment with one- and two-year-old marshmallow plants was carried out in Zamość on brown soil of loess origin in 2002-2004. There were four methods of plantation establishment: 1 direct sowing in the field (control object; 2 direct sowing in the field with cover of polypropylene sheet; 3 by seedlings from a plastic house; 4 by seedlings produced in multi-cell propagation trays. It was found that, in the case of one-year-old plants, all the methods of plantation establishment significantly increased the yield and the number of marshmallow flowers, as compared to the control object, but the best results were obtained when the plants were propagated from seedlings produced in multi-cell trays. Taking into account the two-year-old plants, no significant impact of the plantation establishment method on flower yield was found. On average, total yields of flowers varied from 17.2 dt×ha-1 in the first year of vegetation to 27.8 dt×ha-1 in the case of the two-year-old plants.

An Estimation Method for number of carrier frequency

Directory of Open Access Journals (Sweden)

Xiong Peng

2015-01-01

Full Text Available This paper proposes a method that utilizes AR model power spectrum estimation based on Burg algorithm to estimate the number of carrier frequency in single pulse. In the modern electronic and information warfare, the pulse signal form of radar is complex and changeable, among which single pulse with multi-carrier frequencies is the most typical one, such as the frequency shift keying (FSK signal, the frequency shift keying with linear frequency (FSK-LFM hybrid modulation signal and the frequency shift keying with bi-phase shift keying (FSK-BPSK hybrid modulation signal. In view of this kind of single pulse which has multi-carrier frequencies, this paper adopts a method which transforms the complex signal into AR model, then takes power spectrum based on Burg algorithm to show the effect. Experimental results show that the estimation method still can determine the number of carrier frequencies accurately even when the signal noise ratio (SNR is very low.

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

Science.gov (United States)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Empirical estimates of the NAIRU

DEFF Research Database (Denmark)

Madsen, Jakob Brøchner

2005-01-01

equations. In this paper it is shown that a high proportion of the constant term is a statistical artefact and suggests a new method which yields approximately unbiased estimates of the time-invariant NAIRU. Using data for OECD countries it is shown that the constant-term correction lowers the unadjusted...

Wind power error estimation in resource assessments.

Directory of Open Access Journals (Sweden)

Osvaldo Rodríguez

Full Text Available Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

Wind power error estimation in resource assessments.

Science.gov (United States)

Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel

2015-01-01

Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

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

Consumptive use of upland rice as estimated by different methods

International Nuclear Information System (INIS)

Chhabda, P.R.; Varade, S.B.

1985-01-01

The consumptive use of upland rice (Oryza sativa Linn.) grown during the wet season (kharif) as estimated by modified Penman, radiation, pan-evaporation and Hargreaves methods showed a variation from computed consumptive use estimated by the gravimetric method. The variability increased with an increase in the irrigation interval, and decreased with an increase in the level of N applied. The average variability was less in pan-evaporation method, which could reliably be used for estimating water requirement of upland rice if percolation losses are considered

Automatic yield-line analysis of slabs using discontinuity layout optimization.

Science.gov (United States)

Gilbert, Matthew; He, Linwei; Smith, Colin C; Le, Canh V

2014-08-08

The yield-line method of analysis is a long established and extremely effective means of estimating the maximum load sustainable by a slab or plate. However, although numerous attempts to automate the process of directly identifying the critical pattern of yield-lines have been made over the past few decades, to date none has proved capable of reliably analysing slabs of arbitrary geometry. Here, it is demonstrated that the discontinuity layout optimization (DLO) procedure can successfully be applied to such problems. The procedure involves discretization of the problem using nodes inter-connected by potential yield-line discontinuities, with the critical layout of these then identified using linear programming. The procedure is applied to various benchmark problems, demonstrating that highly accurate solutions can be obtained, and showing that DLO provides a truly systematic means of directly and reliably automatically identifying yield-line patterns. Finally, since the critical yield-line patterns for many problems are found to be quite complex in form, a means of automatically simplifying these is presented.

Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation

Science.gov (United States)

Sills, Erin O.; Herrera, Diego; Kirkpatrick, A. Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

2015-01-01

Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts’ selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal “blacklist” that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on

Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

Science.gov (United States)

Sills, Erin O; Herrera, Diego; Kirkpatrick, A Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

2015-01-01

Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on policies

Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

Directory of Open Access Journals (Sweden)

Erin O Sills

Full Text Available Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012. This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and

Estimating security betas using prior information based on firm fundamentals

NARCIS (Netherlands)

Cosemans, Mathijs; Frehen, Rik; Schotman, Peter; Bauer, Rob

We propose a hybrid approach for estimating beta that shrinks rolling window estimates towards firm-specific priors motivated by economic theory. Our method yields superior forecasts of beta that have important practical implications. First, hybrid betas carry a significant price of risk in the

Determination of the alcohol-yielding capacity of cereals. A method for the determination of the alcohol-yielding capacity

Energy Technology Data Exchange (ETDEWEB)

Frey, A; Hoppe, W

1957-01-01

A laboratory method is reported for the determination of the alcohol yielding capacity of starch-containing distillery raw materials. The starch is inverted with dilute HCl under pressure, after which the material is fermented with yeast at pH 5.4. After distillation, the alcohol is determined pyknometrically. The influence of such factors as amount of yeast was determined experimentally. Analysis of the time curves for the hydrolysis of starch (by paper-chromatographic techniques) in relation to pH showed glucose to be the principal reaction product, with only slight amounts of maltose and higher sugars being formed.

Methods for estimating low-flow statistics for Massachusetts streams

Science.gov (United States)

Ries, Kernell G.; Friesz, Paul J.

2000-01-01

Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The

Comparing Methods for Estimating Direct Costs of Adverse Drug Events.

Science.gov (United States)

Gyllensten, Hanna; Jönsson, Anna K; Hakkarainen, Katja M; Svensson, Staffan; Hägg, Staffan; Rehnberg, Clas

2017-12-01

To estimate how direct health care costs resulting from adverse drug events (ADEs) and cost distribution are affected by methodological decisions regarding identification of ADEs, assigning relevant resource use to ADEs, and estimating costs for the assigned resources. ADEs were identified from medical records and diagnostic codes for a random sample of 4970 Swedish adults during a 3-month study period in 2008 and were assessed for causality. Results were compared for five cost evaluation methods, including different methods for identifying ADEs, assigning resource use to ADEs, and for estimating costs for the assigned resources (resource use method, proportion of registered cost method, unit cost method, diagnostic code method, and main diagnosis method). Different levels of causality for ADEs and ADEs' contribution to health care resource use were considered. Using the five methods, the maximum estimated overall direct health care costs resulting from ADEs ranged from Sk10,000 (Sk = Swedish krona; ~€1,500 in 2016 values) using the diagnostic code method to more than Sk3,000,000 (~€414,000) using the unit cost method in our study population. The most conservative definitions for ADEs' contribution to health care resource use and the causality of ADEs resulted in average costs per patient ranging from Sk0 using the diagnostic code method to Sk4066 (~€500) using the unit cost method. The estimated costs resulting from ADEs varied considerably depending on the methodological choices. The results indicate that costs for ADEs need to be identified through medical record review and by using detailed unit cost data. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Phase difference estimation method based on data extension and Hilbert transform

International Nuclear Information System (INIS)

Shen, Yan-lin; Tu, Ya-qing; Chen, Lin-jun; Shen, Ting-ao

2015-01-01

To improve the precision and anti-interference performance of phase difference estimation for non-integer periods of sampling signals, a phase difference estimation method based on data extension and Hilbert transform is proposed. Estimated phase difference is obtained by means of data extension, Hilbert transform, cross-correlation, auto-correlation, and weighted phase average. Theoretical analysis shows that the proposed method suppresses the end effects of Hilbert transform effectively. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of phase difference estimation and has better performance of phase difference estimation than the correlation, Hilbert transform, and data extension-based correlation methods, which contribute to improving the measurement precision of the Coriolis mass flowmeter. (paper)

Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

Directory of Open Access Journals (Sweden)

Wang Yanqing

2014-04-01

Full Text Available During environment testing, the estimation of random vibration signals (RVS is an important technique for the airborne platform safety and reliability. However, the available methods including extreme value envelope method (EVEM, statistical tolerances method (STM and improved statistical tolerance method (ISTM require large samples and typical probability distribution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method (GBM is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated interval, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method (BM and gray method (GM in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.

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

Simple method for the estimation of glomerular filtration rate

Energy Technology Data Exchange (ETDEWEB)

Groth, T [Group for Biomedical Informatics, Uppsala Univ. Data Center, Uppsala (Sweden); Tengstroem, B [District General Hospital, Skoevde (Sweden)

1977-02-01

A simple method is presented for indirect estimation of the glomerular filtration rate from two venous blood samples, drawn after a single injection of a small dose of (/sup 125/I)sodium iothalamate (10 ..mu..Ci). The method does not require exact dosage, as the first sample, taken after a few minutes (t=5 min) after injection, is used to normilize the value of the second sample, which should be taken in between 2 to 4 h after injection. The glomerular filtration rate, as measured by standard insulin clearance, may then be predicted from the logarithm of the normalized value and linear regression formulas with a standard error of estimate of the order of 1 to 2 ml/min/1.73 m/sup 2/. The slope-intercept method for direct estimation of glomerular filtration rate is also evaluated and found to significantly underestimate standard insulin clearance. The normalized 'single-point' method is concluded to be superior to the slope-intercept method and more sophisticated methods using curve fitting technique, with regard to predictive force and clinical applicability.

Weed-crop competition effects on growth and yield of sugarcane planted using two methods

International Nuclear Information System (INIS)

Zafar, M.; Tanveer, A.; Cheema, Z.A.; Ashraf, M.

2010-01-01

Effect of planting techniques and weed-crop competition periods on yield potential of spring planted sugarcane variety HSF-240 was studied at the Ayub Agricultural Research Institute, Faisalabad, Pakistan. The experiment was laid out in RCBD with a split-plot arrangement, with four replications and net plot size of 3.6m x 10m. In the experiment, two planting techniques viz., 60 cm apart rows in flat sowing technique and 120 cm apart rows in trench sowing technique were randomized in main plots. Seven weed-crop competition periods viz., Zero (weed free), weed-crop competition for 45, 60, 75, 90, 105 days after sowing (DAS) and weedy check (full season weed-crop competition) were randomized in sub-plots. Sugarcane sown by trench method exhibited more leaf area index (LAI), average crop growth rate (ACGR) and yield contributing attributes. Trench sowing by yielding 72.22 and 75.08 t ha/sup -1/ stripped cane yields, significantly showed superiority over the flat sowing, which gave 64.13 and 66.04 t ha/sup -1/ stripped cane yields in 2005-06 and 2006- 07, respectively. Generally, there was an increase in weed population and biomass but decrease in leaf area index, crop growth rate and yield components with an increase in weed-crop competition period. A decrease of 10.06, 17.90, 22.42, 28.65, 37.64 and 56.89% in stripped cane yield was observed for weed-crop competition periods of 45, 60, 75, 90, 105 DAS and weedy check as compared with zero competition in 2005-06, respectively. In 2006-07, the respective decrease in stripped cane yield was 9.84, 18.76, 22.92, 27.98, 38.75, and 54.98%. Trench sowing at 1.2 m row spacing proved better sowing technique and 45 DAS was the critical period of weed-crop competition. (author)

Comparison of methods for estimating premorbid intelligence

OpenAIRE

Bright, Peter; van der Linde, Ian

2018-01-01

To evaluate impact of neurological injury on cognitive performance it is typically necessary to derive a baseline (or ‘premorbid’) estimate of a patient’s general cognitive ability prior to the onset of impairment. In this paper, we consider a range of common methods for producing this estimate, including those based on current best performance, embedded ‘hold/no hold’ tests, demographic information, and word reading ability. Ninety-two neurologically healthy adult participants were assessed ...