Climate change effects on agriculture: economic responses to biophysical shocks.

PubMed

Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-03-04

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Plausible rice yield losses under future climate warming.

PubMed

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Huang, Yao; Ciais, Philippe; Elliott, Joshua; Huang, Mengtian; Janssens, Ivan A; Li, Tao; Lian, Xu; Liu, Yongwen; Müller, Christoph; Peng, Shushi; Wang, Tao; Zeng, Zhenzhong; Peñuelas, Josep

2016-12-19

Rice is the staple food for more than 50% of the world's population 1-3 . Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5.2 ± 1.4% K -1 . Local crop models give a similar sensitivity (-6.3 ± 0.4% K -1 ), but statistical and global gridded crop models both suggest less negative impacts of warming on yields (-0.8 ± 0.3% and -2.4 ± 3.7% K -1 , respectively). Using data from field warming experiments, we further propose a conditional probability approach to constrain the large range of global gridded crop model results for the future yield changes in response to warming by the end of the century (from -1.3% to -9.3% K -1 ). The constraint implies a more negative response to warming (-8.3 ± 1.4% K -1 ) and reduces the spread of the model ensemble by 33%. This yield reduction exceeds that estimated by the International Food Policy Research Institute assessment (-4.2 to -6.4% K -1 ) (ref. 4). Our study suggests that without CO 2 fertilization, effective adaptation and genetic improvement, severe rice yield losses are plausible under intensive climate warming scenarios.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Immune interference in the setting of same-day administration of two similar inactivated alphavirus vaccines: eastern equine and western equine encephalitis.

PubMed

Reisler, Ronald B; Gibbs, Paul H; Danner, Denise K; Boudreau, Ellen F

2012-11-26

We compared the effect on primary vaccination plaque-reduction neutralization 80% titers (PRNT80) responses of same-day administration (at different injection sites) of two similar investigational inactivated alphavirus vaccines, eastern equine encephalitis (EEE) vaccine (TSI-GSD 104) and western equine encephalitis (WEE) vaccine (TSI-GSD 210) to separate administration. Overall, primary response rate for EEE vaccine was 524/796 (66%) and overall primary response rate for WEE vaccine was 291/695 (42%). EEE vaccine same-day administration yielded a 59% response rate and a responder geometric mean titer (GMT)=89 while separate administration yielded a response rate of 69% and a responder GMT=119. WEE vaccine same-day administration yielded a 30% response rate and a responder GMT=53 while separate administration yielded a response rate of 54% and a responder GMT=79. EEE response rates for same-day administration (group A) vs. non-same-day administration (group B) were significantly affected by gender. A logistic regression model predicting response to EEE comparing group B to group A for females yielded an OR=4.10 (95% CL 1.97-8.55; p=.0002) and for males yielded an OR=1.25 (95% CL 0.76-2.07; p=.3768). WEE response rates for same-day administration vs. non-same-day administration were independent of gender. A logistic regression model predicting response to WEE comparing group B to group A yielded an OR=2.14 (95% CL 1.22-3.73; p=.0077). We report immune interference occurring with same-day administration of two completely separate formalin inactivated viral vaccines in humans. These findings combined with the findings of others regarding immune interference would argue for a renewed emphasis on studying the immunological mechanisms of induction of inactivated viral vaccine protection. Copyright © 2012. Published by Elsevier Ltd.

Rising temperatures reduce global wheat production

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Martre, P.; Rötter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.; Reynolds, M. P.; Alderman, P. D.; Prasad, P. V. V.; Aggarwal, P. K.; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A. J.; de Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Koehler, A.-K.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ruane, A. C.; Semenov, M. A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P. J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y.

2015-02-01

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.

Rising Temperatures Reduce Global Wheat Production

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Martre, P.; Rötter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.;

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

NASA Astrophysics Data System (ADS)

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 traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.

PubMed

Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen

2013-12-01

Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.

A systematic approach to parameter selection for CAD-virtual reality data translation using response surface methodology and MOGA-II.

PubMed

Abidi, Mustufa Haider; Al-Ahmari, Abdulrahman; Ahmad, Ali

2018-01-01

Advanced graphics capabilities have enabled the use of virtual reality as an efficient design technique. The integration of virtual reality in the design phase still faces impediment because of issues linked to the integration of CAD and virtual reality software. A set of empirical tests using the selected conversion parameters was found to yield properly represented virtual reality models. The reduced model yields an R-sq (pred) value of 72.71% and an R-sq (adjusted) value of 86.64%, indicating that 86.64% of the response variability can be explained by the model. The R-sq (pred) is 67.45%, which is not very high, indicating that the model should be further reduced by eliminating insignificant terms. The reduced model yields an R-sq (pred) value of 73.32% and an R-sq (adjusted) value of 79.49%, indicating that 79.49% of the response variability can be explained by the model. Using the optimization software MODE Frontier (Optimization, MOGA-II, 2014), four types of response surfaces for the three considered response variables were tested for the data of DOE. The parameter values obtained using the proposed experimental design methodology result in better graphics quality, and other necessary design attributes.

Axisymmetric micromechanics of elastic-perfectly plastic fibrous composites under uniaxial tension loading

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, David H.

1993-01-01

The uniaxial response of a continuous fiber elastic-perfectly plastic composite is modeled herein as a two-element composite cylinder. An axisymmetric analytical micromechanics solution is obtained for the rate-independent elastic-plastic response of the two-element composite cylinder subjected to tensile loading in the fiber direction for the case wherein the core fiber is assumed to be a transversely isotropic elastic-plastic material obeying the Tsai-Hill yield criterion, with yielding simulating fiber failure. The matrix is assumed to be an isotropic elastic-plastic material obeying the Tresca yield criterion. It is found that there are three different circumstances that depend on the fiber and matrix properties: fiber yield, followed by matrix yielding; complete matrix yield, followed by fiber yielding; and partial matrix yield, followed by fiber yielding, followed by complete matrix yield. The order in which these phenomena occur is shown to have a pronounced effect on the predicted uniaxial effective composite response.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Calibrating the Abaqus Crushable Foam Material Model using UNM Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schembri, Philip E.; Lewis, Matthew W.

Triaxial test data from the University of New Mexico and uniaxial test data from W-14 is used to calibrate the Abaqus crushable foam material model to represent the syntactic foam comprised of APO-BMI matrix and carbon microballoons used in the W76. The material model is an elasto-plasticity model in which the yield strength depends on pressure. Both the elastic properties and the yield stress are estimated by fitting a line to the elastic region of each test response. The model parameters are fit to the data (in a non-rigorous way) to provide both a conservative and not-conservative material model. Themore » model is verified to perform as intended by comparing the values of pressure and shear stress at yield, as well as the shear and volumetric stress-strain response, to the test data.« less

Applying the age-shift approach to model responses to midrotation fertilization

Treesearch

Colleen A. Carlson; Thomas R. Fox; H. Lee Allen; Timothy J. Albaugh

2010-01-01

Growth and yield models used to evaluate midrotation fertilization economics require adjustments to account for the typically observed responses. This study investigated the use of age-shift models to predict midrotation fertilizer responses. Age-shift prediction models were constructed from a regional study consisting of 43 installations of a nitrogen (N) by...

Climate change effects on agriculture: Economic responses to biophysical shocks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

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

Treesearch

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

2012-01-01

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

EXPERIMENTAL DESIGN STRATEGY FOR THE WEIBULL DOSE RESPONSE MODEL (JOURNAL VERSION)

EPA Science Inventory

The objective of the research was to determine optimum design point allocation for estimation of relative yield losses from ozone pollution when the true and fitted yield-ozone dose response relationship follows the Weibull. The optimum design is dependent on the values of the We...

Response of wheat growth, grain yield and water use to elevated CO2 under a Free-Air CO2 Enrichment (FACE) experiment and modelling in a semi-arid environment.

PubMed

O'Leary, Garry J; Christy, Brendan; Nuttall, James; Huth, Neil; Cammarano, Davide; Stöckle, Claudio; Basso, Bruno; Shcherbak, Iurii; Fitzgerald, Glenn; Luo, Qunying; Farre-Codina, Immaculada; Palta, Jairo; Asseng, Senthold

2014-12-05

The response of wheat crops to elevated CO 2 (eCO 2 ) was measured and modelled with the Australian Grains Free-Air CO 2 Enrichment experiment, located at Horsham, Australia. Treatments included CO 2 by water, N and temperature. The location represents a semi-arid environment with a seasonal VPD of around 0.5 kPa. Over 3 years, the observed mean biomass at anthesis and grain yield ranged from 4200 to 10 200 kg ha -1 and 1600 to 3900 kg ha -1 , respectively, over various sowing times and irrigation regimes. The mean observed response to daytime eCO 2 (from 365 to 550 μmol mol -1 CO 2 ) was relatively consistent for biomass at stem elongation and at anthesis and LAI at anthesis and grain yield with 21%, 23%, 21% and 26%, respectively. Seasonal water use was decreased from 320 to 301 mm (P = 0.10) by eCO 2 , increasing water use efficiency for biomass and yield, 36% and 31%, respectively. The performance of six models (APSIM-Wheat, APSIM-Nwheat, CAT-Wheat, CROPSYST, OLEARY-CONNOR and SALUS) in simulating crop responses to eCO 2 was similar and within or close to the experimental error for accumulated biomass, yield and water use response, despite some variations in early growth and LAI. The primary mechanism of biomass accumulation via radiation use efficiency (RUE) or transpiration efficiency (TE) was not critical to define the overall response to eCO 2 . However, under irrigation, the effect of late sowing on response to eCO 2 to biomass accumulation at DC65 was substantial in the observed data (~40%), but the simulated response was smaller, ranging from 17% to 28%. Simulated response from all six models under no water or nitrogen stress showed similar response to eCO 2 under irrigation, but the differences compared to the dryland treatment were small. Further experimental work on the interactive effects of eCO 2 , water and temperature is required to resolve these model discrepancies. © 2014 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2017-12-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Yield Model Development (YMD) implementation plan for fiscal years 1981 and 1982

NASA Technical Reports Server (NTRS)

Ambroziak, R. A. (Principal Investigator)

1981-01-01

A plan is described for supporting USDA crop production forecasting and estimation by (1) testing, evaluating, and selecting crop yield models for application testing; (2) identifying areas of feasible research for improvement of models; and (3) conducting research to modify existing models and to develop new crop yield assessment methods. Tasks to be performed for each of these efforts are described as well as for project management and support. The responsibilities of USDA, USDC, USDI, and NASA are delineated as well as problem areas to be addressed.

Winter wheat response to irrigation, nitrogen fertilization, and cold hazards in the Community Land Model 5

NASA Astrophysics Data System (ADS)

Lu, Y.

2017-12-01

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of earth's croplands. As such, it plays an important role in soil carbon balance, and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under changing climate, but also for understanding the energy and water cycles for winter wheat dominated regions. A winter wheat growth model has been developed in the Community Land Model 4.5 (CLM4.5), but its responses to irrigation and nitrogen fertilization have not been validated. In this study, I will validate winter wheat growth response to irrigation and nitrogen fertilization at five winter wheat field sites (TXLU, KSMA, NESA, NDMA, and ABLE) in North America, which were originally designed to understand winter wheat response to nitrogen fertilization and water treatments (4 nitrogen levels and 3 irrigation regimes). I also plan to further update the linkages between winter wheat yield and cold hazards. The previous cold damage function only indirectly affects yield through reduction on leaf area index (LAI) and hence photosynthesis, such approach could sometimes produce an unwanted higher yield when the reduced LAI saved more nutrient in the grain fill stage.

Growth response analysis after early control of woody competition for 14 loblolly pine plantations in the southern U.S.

Treesearch

David B. South; James H. Miller

2007-01-01

Only a few growth and yield programs allow users to model the effects of hardwood competition on yields from pine plantations. Several of these programs were developed with the assumption that reducing hardwood competition would consistently produce a Type 2 growth response where pine volume gains increase over time. However, the actual response is not always a Type 2...

THE IMPACTS OF CLIMATE CHANGE ON RICE YIELD: A COMPARISON OF FOUR MODEL PERFORMANCES

EPA Science Inventory

Increasing concentrations of carbon dioxide (CO2) and other greenhouse gases are expected to modify temperature and rainfall the next 50-100 years. echanisms and hypotheses of plant response to these changes could be incorporated in models predicting crop yield estimates to bette...

Dynamic Multi-Axial Loading Response and Constitutive/Damage Modeling of Titanium and Titanium Alloys

DTIC Science & Technology

2006-06-24

crystals and assume same yield stress in tension and compression. Some anisotropic models have been proposed and used in the literature for HCP poly...2006), etc. These criteria dealt with the modeling of cubic crystals and assume same yield stress in tension an compression. Some anisotropic...Constitutive/Damage Modeling of Titanium and Titanium Alloys Principal Investigator: Akhtar S. Khan

Evaluation of the CEAS model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The CEAS yield model is based upon multiple regression analysis at the CRD and state levels. For the historical time series, yield is regressed on a set of variables derived from monthly mean temperature and monthly precipitation. Technological trend is represented by piecewise linear and/or quadriatic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-79) demonstrated that biases are small and performance as indicated by the root mean square errors are acceptable for intended application, however, model response for individual years particularly unusual years, is not very reliable and shows some large errors. The model is objective, adequate, timely, simple and not costly. It considers scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Unraveling the Age Hardening Response in U-Nb Alloys

DOE PAGES

Hackenberg, Robert Errol; Hemphill, Geralyn M. Sewald; Forsyth, Robert Thomas; ...

2016-11-15

Complicating factors that have stymied understanding of uranium-niobium’s aging response are briefly reviewed, including (1) niobium inhomogeneity, (2) machining damage effects on tensile properties, (3) early-time transients of ductility increase, and (4) the variety of phase transformations. A simple Logistic-Arrhenius model was applied to predict yield and ultimate tensile strengths and tensile elongation of U-4Nb as a function of thermal age. Lastly, fits to each model yielded an apparent activation energy that was compared with phase transformation mechanisms.

Simulating evapotranspiration (ET) yield response of selected corn varieties under full and limited irrigation in the Texas High Plains using DSSAT-CERES-Maize

USDA-ARS?s Scientific Manuscript database

Water scarcity due to drought and groundwater depletion has led to increased interest in deficit irrigation strategies that reduce irrigation requirements while maintaining profitable yields. This has resulted in an increase in the number modeling studies aimed at evaluating crop response to limite...

Behavioural modelling of irrigation decision making under water scarcity

NASA Astrophysics Data System (ADS)

Foster, T.; Brozovic, N.; Butler, A. P.

2013-12-01

Providing effective policy solutions to aquifer depletion caused by abstraction for irrigation is a key challenge for socio-hydrology. However, most crop production functions used in hydrological models do not capture the intraseasonal nature of irrigation planning, or the importance of well yield in land and water use decisions. Here we develop a method for determining stochastic intraseasonal water use that is based on observed farmer behaviour but is also theoretically consistent with dynamically optimal decision making. We use the model to (i) analyse the joint land and water use decision by farmers; (ii) to assess changes in behaviour and production risk in response to water scarcity; and (iii) to understand the limits of applicability of current methods in policy design. We develop a biophysical model of water-limited crop yield building on the AquaCrop model. The model is calibrated and applied to case studies of irrigated corn production in Nebraska and Texas. We run the model iteratively, using long-term climate records, to define two formulations of the crop-water production function: (i) the aggregate relationship between total seasonal irrigation and yield (typical of current approaches); and (ii) the stochastic response of yield and total seasonal irrigation to the choice of an intraseasonal soil moisture target and irrigated area. Irrigated area (the extensive margin decision) and per-area irrigation intensity (the intensive margin decision) are then calculated for different seasonal water restrictions (corresponding to regulatory policies) and well yield constraints on intraseasonal abstraction rates (corresponding to aquifer system limits). Profit- and utility-maximising decisions are determined assuming risk neutrality and varying degrees of risk aversion, respectively. Our results demonstrate that the formulation of the production function has a significant impact on the response to water scarcity. For low well yields, which are the major concern for farmers in areas of aquifer depletion or recurrent drought, the stochastic model demonstrates that partial-area irrigation is optimal irrespective of the size of water supply restrictions. This effect is not produced by the aggregate model, which cannot account for the variability of the production function with changes in irrigated area that control intraseasonal irrigation application rates. In addition, the aggregate model overstates the willingness of a risk-averse farmer to adjust on the intensive margin in response to water supply restrictions. This is due to the inability of aggregate models to specify correctly the production risk associated with intensive margin adjustments. Consequently, aggregate models give unrealistic estimates of water demand and underestimate the negative impacts on profitability of declining groundwater resources. Reliance on aggregate models will limit the ability of socio-hydrology to guide policy responses to groundwater scarcity. Our stochastic methodology provides a more realistic tool to study the management of groundwater in coupled human-water systems.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

PubMed

Battisti, R; Sentelhas, P C; Boote, K J

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

Whole season compared to growth-stage resolved temperature trends: implications for US maize yield

NASA Astrophysics Data System (ADS)

Butler, E. E.; Mueller, N. D.; Huybers, P. J.

2014-12-01

The effect of temperature on maize yield has generally been considered using a single value for the entire growing season. We compare the effect of temperature trends on yield between two distinct models: a single temperature sensitivity for the whole season and a variable sensitivity across four distinct agronomic development stages. The more resolved variable-sensitivity model indicates roughly a factor of two greater influence of temperature on yield than that implied by the single-sensitivity model. The largest discrepancies occur in silking, which is demonstrated to be the most sensitive stage in the variable-sensitivity model. For instance, whereas median yields are observed to be only 53% of typical values during the hottest 1% of silking-stage temperatures, the single-sensitivity model over predicts median yields of 68% whereas the variable-sensitivity model more correctly predicts median yields of 61%. That the variable sensitivity model is also not capable of capturing the full extent of yield losses suggests that further refinement to represent the non-linear response would be useful. Results from the variable sensitivity model also indicate that management decisions regarding planting times, which have generally shifted toward earlier dates, have led to greater yield benefit than that implied by the single-sensitivity model. Together, the variation of both temperature trends and yield variability within growing stages calls for closer attention to how changes in management interact with changes in climate to ultimately affect yields.

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE PAGES

Blanc, Élodie

2017-01-26

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanc, Élodie

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Agricultural response functions to changes in carbon, temperature, and water based on the C3MP data set

NASA Astrophysics Data System (ADS)

Snyder, A.; Ruane, A. C.; Phillips, M.; Calvin, K. V.; Clarke, L.

2017-12-01

Agricultural yields vary depending on temperature, precipitation/irrigation conditions, fertilizer application, and CO2 concentration. The Coordinated Climate-Crop Modeling Project (C3MP), conducted as a component of the Agricultural Model Intercomparison and Improvement Project (AgMIP), organized a sensitivity experiments across carbon-temperature-water (CTW) space across 1100 management conditions in 50+ countries, sampling 15 crop species and 20 crop models. Such coordinated sensitivity tests allow for the building of emulators of yield response to changes in CTW values, allowing rapid estimation of yield changes from the types of climate changes projected by the climate modeling community. The resulting emulator may be used to supply agricultural responses to climate change in any user-defined scenario, rather than the restriction to the RCPs in many past works. We present the resulting emulators built from the C3MP output data set for use in the Global Change Assessment Model (GCAM) integrated assessment model that allows for the co-evolution of socioeconomic development, greenhouse gas emissions, climate change, and agricultural sector ramifications. C3MP-based emulators may be of use in designing agricultural impact studies in other IAMs, and we place them in the context of past crop modeling efforts, including the Challinor et al. Meta-analysis, the AgMIP Wheat team results, the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) fast-track modeling results, and the MACSUR impact response surface results.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

IMPACTS OF CLIMATE CHANGE ON RICE YIELD: EVALUATION OF THE EFFICACITY OF DIFFERENT MODELING APPROACHES

EPA Science Inventory

Increasing concentrations of carbon dioxide (CO2) and other greenhouse gases are expected to modify the climate of the earth in the next 50-100 years. echanisms of plant response to these changes need to be incorporated in models that predict crop yield to obtain an understanding...

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

PubMed

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

2009-12-01

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

Agricultural Intensification as a Mechanism of Adaptation to Climate Change Impacts

NASA Astrophysics Data System (ADS)

Kyle, P.; Calvin, K. V.; le Page, Y.; Patel, P.; West, T. O.; Wise, M. A.

2015-12-01

The research, policy, and NGO communities have devoted significant attention to the potential for agricultural intensification, or closure of "yield gaps," to alleviate future global hunger, poverty, climate change impacts, and other threats. However, because the research to this point has focused on biophysically attainable yields—assuming optimal choices under ideal conditions—the presently available work has not yet addressed the likely responses of the agricultural sector to real-world conditions in the future. This study investigates endogenous agricultural intensification in response to global climate change impacts—that is, intensification independent of policies or other exogenous interventions to promote yield gap closure. The framework for the analysis is a set of scenarios to 2100 in the GCAM global integrated assessment model, enhanced to include endogenous irrigation, fertilizer application, and yields, in each of 283 land use regions, with maximum yields based on the 95th percentile of attainable yields in a recent global assessment. We assess three levels of agricultural climate impacts, using recent global gridded crop model datasets: none, low (LPJmL), and high (Pegasus). Applying formulations for decomposition of climate change impacts response developed in prior AgMIP work, we find that at the global level, availability of high-yielding technologies mitigates price shocks and shifts the agricultural sector's climate response modestly towards intensification, away from cropland expansion and reduced production. At the regional level, the behavior is more complex; nevertheless, availability of high-yielding production technologies enhances the inter-regional shifts in agricultural production that are induced by climate change, complemented by commensurate changes in trade patterns. The results highlight the importance of policies to facilitate yield gap closure and inter-regional trade as mechanisms for adapting to climate change

How do various maize crop models vary in their responses to climate change factors?

USDA-ARS?s Scientific Manuscript database

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models give similar grain yield responses to changes in climatic factors, or whether they agr...

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

Robust features of future climate change impacts on sorghum yields in West Africa

NASA Astrophysics Data System (ADS)

Sultan, B.; Guan, K.; Kouressy, M.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.; Lobell, D. B.

2014-10-01

West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031-2060 compared to a baseline of 1961-1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16-20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate impacts on sorghum yields by about 10%, with drier regions experiencing the largest benefits, though the net impacts of climate change remain negative even after accounting for CO2.

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

PubMed Central

Overman, Allen R.; Scholtz, Richard V.

2011-01-01

Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha−1 and g plant−1) on plant population (plants m−2). Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L.) grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Ym (Mg ha−1) for maximum yield at high plant population and c (m2 plant−1) for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, xc = 1/c (plants m−2). The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of xc were very similar for the three field studies with the same crop species. PMID:21297960

Building a statistical emulator for prediction of crop yield response to climate change: a global gridded panel data set approach

NASA Astrophysics Data System (ADS)

Mistry, Malcolm; De Cian, Enrica; Wing, Ian Sue

2015-04-01

There is widespread concern that trends and variability in weather induced by climate change will detrimentally affect global agricultural productivity and food supplies. Reliable quantification of the risks of negative impacts at regional and global scales is a critical research need, which has so far been met by forcing state-of-the-art global gridded crop models with outputs of global climate model (GCM) simulations in exercises such as the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)-Fastrack. Notwithstanding such progress, it remains challenging to use these simulation-based projections to assess agricultural risk because their gridded fields of crop yields are fundamentally denominated as discrete combinations of warming scenarios, GCMs and crop models, and not as model-specific or model-averaged yield response functions of meteorological shifts, which may have their own independent probability of occurrence. By contrast, the empirical climate economics literature has adeptly represented agricultural responses to meteorological variables as reduced-form statistical response surfaces which identify the crop productivity impacts of additional exposure to different intervals of temperature and precipitation [cf Schlenker and Roberts, 2009]. This raises several important questions: (1) what do the equivalent reduced-form statistical response surfaces look like for crop model outputs, (2) do they exhibit systematic variation over space (e.g., crop suitability zones) or across crop models with different characteristics, (3) how do they compare to estimates based on historical observations, and (4) what are the implications for the characterization of climate risks? We address these questions by estimating statistical yield response functions for four major crops (maize, rice, wheat and soybeans) over the historical period (1971-2004) as well as future climate change scenarios (2005-2099) using ISIMIP-Fastrack data for five GCMs and seven crop models under rain-fed and irrigated management regimes. Our approach, which is patterned after Lobell and Burke [2010], is a novel application of cross-section/time-series statistical techniques from the climate economics literature to large, high-dimension, multi-model datasets, and holds considerable promise as a diagnostic methodology to elucidate uncertainties in the processes simulated by crop models, and to support the development of climate impact intercomparison exercises.

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

NASA Technical Reports Server (NTRS)

Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon;

Modeling irrigation behavior in groundwater systems

NASA Astrophysics Data System (ADS)

Foster, Timothy; Brozović, Nicholas; Butler, Adrian P.

2014-08-01

Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

PubMed Central

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

2009-01-01

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622

Impacts of aerosol mitigation on Chinese rice photosynthesis: An integrated modeling approach

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, T.; Yue, X.; Yang, X.

2017-12-01

Aerosol pollution in China is significantly altering radiative transfer processes and is thereby potentially affecting rice photosynthesis. However, the response of rice photosynthesis to aerosol-induced radiative perturbations is still not well understood. Here, we employ an integrated process-based modeling approach to simulate changes in incoming radiation (RAD) and the diffuse radiation fraction (DF) with aerosol mitigation in China and their associated impacts on rice yields. Aerosol reduction has the positive effect of increasing RAD and the negative effect of decreasing DF on rice photosynthesis and yields. In rice production areas where the average RAD during the growing season is lower than 250 W m-2, aerosol reduction is beneficial for higher rice yields, whereas in areas with RAD>250 W m-2, aerosol mitigation causes yield declines due to the associated reduction in the DF, which decreases the light use efficiency. This response pattern and threshold are similar with observations, even through more data are needed in future investigation. As a net effect, rice yields were estimated to significantly increase by 0.8-2.6% with aerosol concentrations reductions from 20 to 100%, which is lower than the estimates obtained in earlier studies that only considered the effects of RAD. This finding suggests that both RAD and DF are important processes influencing rice yields and should be incorporated into future assessments of agricultural responses to variations in aerosol-induced radiation under climate change.

Optimization of critical medium components using response surface methodology for biomass and extracellular polysaccharide production by Agaricus blazei.

PubMed

Liu, Gao-Qiang; Wang, Xiao-Ling

2007-02-01

Response surface methodology (RSM) was applied to optimize the critical medium ingredients of Agaricus blazei. A three-level Box-Behnken factorial design was employed to determine the maximum biomass and extracellular polysaccharide (EPS) yields at optimum levels for glucose, yeast extract (YE), and peptone. A mathematical model was then developed to show the effect of each medium composition and its interactions on the production of mycelial biomass and EPS. The model predicted the maximum biomass yield of 10.86 g/l that appeared at glucose, YE, peptone of 26.3, 6.84, and 6.62 g/l, respectively, while a maximum EPS yield of 348.4 mg/l appeared at glucose, YE, peptone of 28.4, 4.96, 5.60 g/l, respectively. These predicted values were also verified by validation experiments. The excellent correlation between predicted and measured values of each model justifies the validity of both the response models. The results of bioreactor fermentation also show that the optimized culture medium enhanced both biomass (13.91 +/- 0.71 g/l) and EPS (363 +/- 4.1 mg/l) production by Agaricus blazei in a large-scale fermentation process.

Constitutive Models Based on Compressible Plastic Flows

NASA Technical Reports Server (NTRS)

Rajendran, A. M.

1983-01-01

The need for describing materials under time or cycle dependent loading conditions has been emphasized in recent years by several investigators. In response to the need, various constitutive models describing the nonlinear behavior of materials under creep, fatigue, or other complex loading conditions were developed. The developed models for describing the fully dense (non-porous) materials were mostly based on uncoupled plasticity theory. The improved characterization of materials provides a better understanding of the structual response under complex loading conditions. The pesent studies demonstrate that the rate or time dependency of the response of a porous aggregate can be incorporated into the nonlinear constitutive behavior of a porous solid by appropriately modeling the incompressible matrix behavior. It is also sown that the yield function which wads determined by a continuum mechanics approach must be verified by appropriate experiments on void containing sintered materials in order to obtain meaningful numbers for the constants that appear in the yield function.

Mechanical response of unidirectional boron/aluminum under combined loading

NASA Technical Reports Server (NTRS)

Becker, Wolfgang; Pindera, Marek-Jerzy; Herakovich, Carl T.

1987-01-01

Three test methods were employed to characterize the response of unidirectional Boron/Aluminum metal matrix composite material under monotonic and cyclic loading conditions, namely, losipescu shear, off-axis tension and compression. The characterization of the elastic and plastic response includes the elastic material properties, yielding and subsequent hardening of the unidirectional composite under different stress ratios in the material principal coordinate system. Yield loci generated for different stress ratios are compared for the three different test methods, taking into account residual stresses and specimen geometry. Subsequently, the yield locus for in-plane shear is compared with the prediction of an analytical, micromechanical model. The influence of the scatter in the experimental data on the predicted yield surface is also analyzed. Lastly, the experimental material strengths in tension and compression are correlated with the maximum stress and the Tsai-Wu failure criterion.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2018-06-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2017-12-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

An analytical solution for the elastoplastic response of a continuous fiber composite under uniaxial loading

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, David H.

1990-01-01

A continuous fiber composite is modelled by a two-element composite cylinder in order to predict the elastoplastic response of the composite under a monotonically increasing tensile loading parallel to fibers. The fibers and matrix are assumed to be elastic-perfectly plastic materials obeying Hill's and Tresca's yield criteria, respectively. Here, the composite behavior when the fibers yield prior to the matrix is investigated.

A potato model intercomparison across varying climates and productivity levels.

PubMed

Fleisher, David H; Condori, Bruno; Quiroz, Roberto; Alva, Ashok; Asseng, Senthold; Barreda, Carolina; Bindi, Marco; Boote, Kenneth J; Ferrise, Roberto; Franke, Angelinus C; Govindakrishnan, Panamanna M; Harahagazwe, Dieudonne; Hoogenboom, Gerrit; Naresh Kumar, Soora; Merante, Paolo; Nendel, Claas; Olesen, Jorgen E; Parker, Phillip S; Raes, Dirk; Raymundo, Rubi; Ruane, Alex C; Stockle, Claudio; Supit, Iwan; Vanuytrecht, Eline; Wolf, Joost; Woli, Prem

2017-03-01

A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach. © 2016 John Wiley & Sons Ltd.

Adopting adequate leaching requirement for practical response models of basil to salinity

NASA Astrophysics Data System (ADS)

Babazadeh, Hossein; Tabrizi, Mahdi Sarai; Darvishi, Hossein Hassanpour

2016-07-01

Several mathematical models are being used for assessing plant response to salinity of the root zone. Objectives of this study included quantifying the yield salinity threshold value of basil plants to irrigation water salinity and investigating the possibilities of using irrigation water salinity instead of saturated extract salinity in the available mathematical models for estimating yield. To achieve the above objectives, an extensive greenhouse experiment was conducted with 13 irrigation water salinity levels, namely 1.175 dS m-1 (control treatment) and 1.8 to 10 dS m-1. The result indicated that, among these models, the modified discount model (one of the most famous root water uptake model which is based on statistics) produced more accurate results in simulating the basil yield reduction function using irrigation water salinities. Overall the statistical model of Steppuhn et al. on the modified discount model and the math-empirical model of van Genuchten and Hoffman provided the best results. In general, all of the statistical models produced very similar results and their results were better than math-empirical models. It was also concluded that if enough leaching was present, there was no significant difference between the soil salinity saturated extract models and the models using irrigation water salinity.

Optimization of Enzymatic Saccharification of Alkali Pretreated Parthenium sp. Using Response Surface Methodology

PubMed Central

Pandiyan, K.; Tiwari, Rameshwar; Singh, Surender; Nain, Pawan K. S.; Rana, Sarika; Arora, Anju; Singh, Shashi B.; Nain, Lata

2014-01-01

Parthenium sp. is a noxious weed which threatens the environment and biodiversity due to its rapid invasion. This lignocellulosic weed was investigated for its potential in biofuel production by subjecting it to mild alkali pretreatment followed by enzymatic saccharification which resulted in significant amount of fermentable sugar yield (76.6%). Optimization of enzymatic hydrolysis variables such as temperature, pH, enzyme, and substrate loading was carried out using central composite design (CCD) in response to surface methodology (RSM) to achieve the maximum saccharification yield. Data obtained from RSM was validated using ANOVA. After the optimization process, a model was proposed with predicted value of 80.08% saccharification yield under optimum conditions which was confirmed by the experimental value of 85.80%. This illustrated a good agreement between predicted and experimental response (saccharification yield). The saccharification yield was enhanced by enzyme loading and reduced by temperature and substrate loading. This study reveals that under optimized condition, sugar yield was significantly increased which was higher than earlier reports and promises the use of Parthenium sp. biomass as a feedstock for bioethanol production. PMID:24900917

Split-Ring Springback Simulations with the Non-associated Flow Rule and Evolutionary Elastic-Plasticity Models

NASA Astrophysics Data System (ADS)

Lee, K. J.; Choi, Y.; Choi, H. J.; Lee, J. Y.; Lee, M. G.

2018-03-01

Finite element simulations and experiments for the split-ring test were conducted to investigate the effect of anisotropic constitutive models on the predictive capability of sheet springback. As an alternative to the commonly employed associated flow rule, a non-associated flow rule for Hill1948 yield function was implemented in the simulations. Moreover, the evolution of anisotropy with plastic deformation was efficiently modeled by identifying equivalent plastic strain-dependent anisotropic coefficients. Comparative study with different yield surfaces and elasticity models showed that the split-ring springback could be best predicted when the anisotropy in both the R value and yield stress, their evolution and variable apparent elastic modulus were taken into account in the simulations. Detailed analyses based on deformation paths superimposed on the anisotropic yield functions predicted by different constitutive models were provided to understand the complex springback response in the split-ring test.

Split-Ring Springback Simulations with the Non-associated Flow Rule and Evolutionary Elastic-Plasticity Models

NASA Astrophysics Data System (ADS)

Lee, K. J.; Choi, Y.; Choi, H. J.; Lee, J. Y.; Lee, M. G.

2018-06-01

Finite element simulations and experiments for the split-ring test were conducted to investigate the effect of anisotropic constitutive models on the predictive capability of sheet springback. As an alternative to the commonly employed associated flow rule, a non-associated flow rule for Hill1948 yield function was implemented in the simulations. Moreover, the evolution of anisotropy with plastic deformation was efficiently modeled by identifying equivalent plastic strain-dependent anisotropic coefficients. Comparative study with different yield surfaces and elasticity models showed that the split-ring springback could be best predicted when the anisotropy in both the R value and yield stress, their evolution and variable apparent elastic modulus were taken into account in the simulations. Detailed analyses based on deformation paths superimposed on the anisotropic yield functions predicted by different constitutive models were provided to understand the complex springback response in the split-ring test.

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Simultaneous or separated; comparison approach for saccharification and fermentation process in producing bio-ethanol from EFB

NASA Astrophysics Data System (ADS)

Bardant, Teuku Beuna; Dahnum, Deliana; Amaliyah, Nur

2017-11-01

Simultaneous Saccharification Fermentation (SSF) of palm oil (Elaeis guineensis) empty fruit bunch (EFB) pulp were investigated as a part of ethanol production process. SSF was investigated by observing the effect of substrate loading variation in range 10-20%w, cellulase loading 5-30 FPU/gr substrate and yeast addition 1-2%v to the ethanol yield. Mathematical model for describing the effects of these three variables to the ethanol yield were developed using Response Surface Methodology-Cheminformatics (RSM-CI). The model gave acceptable accuracy in predicting ethanol yield for Simultaneous Saccharification and Fermentation (SSF) with coefficient of determination (R2) 0.8899. Model validation based on data from previous study gave (R2) 0.7942 which was acceptable for using this model for trend prediction analysis. Trend prediction analysis based on model prediction yield showed that SSF gave trend for higher yield when the process was operated in high enzyme concentration and low substrate concentration. On the other hand, even SHF model showed better yield will be obtained if operated in lower substrate concentration, it still possible to operate in higher substrate concentration with slightly lower yield. Opportunity provided by SHF to operate in high loading substrate make it preferable option for application in commercial scale.

Application of response surface methodology to optimise supercritical carbon dioxide extraction of essential oil from Cyperus rotundus Linn.

PubMed

Wang, Hongwu; Liu, Yanqing; Wei, Shoulian; Yan, Zijun

2012-05-01

Supercritical fluid extraction with carbon dioxide (SC-CO2 extraction) was performed to isolate essential oils from the rhizomes of Cyperus rotundus Linn. Effects of temperature, pressure, extraction time, and CO2 flow rate on the yield of essential oils were investigated by response surface methodology (RSM). The oil yield was represented by a second-order polynomial model using central composite rotatable design (CCRD). The oil yield increased significantly with pressure (p<0.0001) and CO2 flow rate (p<0.01). The maximum oil yield from the response surface equation was predicted to be 1.82% using an extraction temperature of 37.6°C, pressure of 294.4bar, extraction time of 119.8 min, and CO2 flow rate of 20.9L/h. Copyright © 2011 Elsevier Ltd. All rights reserved.

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: an integrated modelling approach in maize.

PubMed

Chenu, Karine; Chapman, Scott C; Hammer, Graeme L; McLean, Greg; Salah, Halim Ben Haj; Tardieu, François

2008-03-01

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

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

PubMed Central

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

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments. PMID:28377779

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

PubMed

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

2017-01-01

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

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE PAGES

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

2017-03-21

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

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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

Investigation of the Process Conditions for Hydrogen Production by Steam Reforming of Glycerol over Ni/Al₂O₃ Catalyst Using Response Surface Methodology (RSM).

PubMed

Ebshish, Ali; Yaakob, Zahira; Taufiq-Yap, Yun Hin; Bshish, Ahmed

2014-03-19

In this work; a response surface methodology (RSM) was implemented to investigate the process variables in a hydrogen production system. The effects of five independent variables; namely the temperature (X₁); the flow rate (X₂); the catalyst weight (X₃); the catalyst loading (X₄) and the glycerol-water molar ratio (X₅) on the H₂ yield (Y₁) and the conversion of glycerol to gaseous products (Y₂) were explored. Using multiple regression analysis; the experimental results of the H₂ yield and the glycerol conversion to gases were fit to quadratic polynomial models. The proposed mathematical models have correlated the dependent factors well within the limits that were being examined. The best values of the process variables were a temperature of approximately 600 °C; a feed flow rate of 0.05 mL/min; a catalyst weight of 0.2 g; a catalyst loading of 20% and a glycerol-water molar ratio of approximately 12; where the H₂ yield was predicted to be 57.6% and the conversion of glycerol was predicted to be 75%. To validate the proposed models; statistical analysis using a two-sample t -test was performed; and the results showed that the models could predict the responses satisfactorily within the limits of the variables that were studied.

Ultrasound-Assisted Extraction of Cannabinoids from Cannabis Sativa L. Optimized by Response Surface Methodology.

PubMed

Agarwal, Charu; Máthé, Katalin; Hofmann, Tamás; Csóka, Levente

2018-03-01

Ultrasonication was used to extract bioactive compounds from Cannabis sativa L. such as polyphenols, flavonoids, and cannabinoids. The influence of 3 independent factors (time, input power, and methanol concentration) was evaluated on the extraction of total phenols (TPC), flavonoids (TF), ferric reducing ability of plasma (FRAP) and the overall yield. A face-centered central composite design was used for statistical modelling of the response data, followed by regression and analysis of variance in order to determine the significance of the model and factors. Both the solvent composition and the time significantly affected the extraction while the sonication power had no significant impact on the responses. The response predictions obtained at optimum extraction conditions of 15 min time, 130 W power, and 80% methanol were 314.822 mg GAE/g DW of TPC, 28.173 mg QE/g DW of TF, 18.79 mM AAE/g DW of FRAP, and 10.86% of yield. A good correlation was observed between the predicted and experimental values of the responses, which validated the mathematical model. On comparing the ultrasonic process with the control extraction, noticeably higher values were obtained for each of the responses. Additionally, ultrasound considerably improved the extraction of cannabinoids present in Cannabis. Low frequency ultrasound was employed to extract bioactive compounds from the inflorescence part of Cannabis. The responses evaluated were-total phenols, flavonoids, ferric reducing assay and yield. The solvent composition and time significantly influenced the extraction process. Appreciably higher extraction of cannabinoids was achieved on sonication against control. © 2018 Institute of Food Technologists®.

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; McDermid, Sonali; Rosenzweig, Cynthia; Baigorria, Guillermo A.; Jones, James W.; Romero, Consuelo C.; Cecil, L. DeWayne

2014-01-01

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

Probabilistic estimates of drought impacts on agricultural production

NASA Astrophysics Data System (ADS)

Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

2017-08-01

Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

Predicting the shock compression response of heterogeneous powder mixtures

NASA Astrophysics Data System (ADS)

Fredenburg, D. A.; Thadhani, N. N.

2013-06-01

A model framework for predicting the dynamic shock-compression response of heterogeneous powder mixtures using readily obtained measurements from quasi-static tests is presented. Low-strain-rate compression data are first analyzed to determine the region of the bulk response over which particle rearrangement does not contribute to compaction. This region is then fit to determine the densification modulus of the mixture, σD, an newly defined parameter describing the resistance of the mixture to yielding. The measured densification modulus, reflective of the diverse yielding phenomena that occur at the meso-scale, is implemented into a rate-independent formulation of the P-α model, which is combined with an isobaric equation of state to predict the low and high stress dynamic compression response of heterogeneous powder mixtures. The framework is applied to two metal + metal-oxide (thermite) powder mixtures, and good agreement between the model and experiment is obtained for all mixtures at stresses near and above those required to reach full density. At lower stresses, rate-dependencies of the constituents, and specifically those of the matrix constituent, determine the ability of the model to predict the measured response in the incomplete compaction regime.

Experimental and computational results on exciton/free-carrier ratio, hot/thermalized carrier diffusion, and linear/nonlinear rate constants affecting scintillator proportionality

NASA Astrophysics Data System (ADS)

Williams, R. T.; Grim, Joel Q.; Li, Qi; Ucer, K. B.; Bizarri, G. A.; Kerisit, S.; Gao, Fei; Bhattacharya, P.; Tupitsyn, E.; Rowe, E.; Buliga, V. M.; Burger, A.

2013-09-01

Models of nonproportional response in scintillators have highlighted the importance of parameters such as branching ratios, carrier thermalization times, diffusion, kinetic order of quenching, associated rate constants, and radius of the electron track. For example, the fraction ηeh of excitations that are free carriers versus excitons was shown by Payne and coworkers to have strong correlation with the shape of electron energy response curves from Compton-coincidence studies. Rate constants for nonlinear quenching are implicit in almost all models of nonproportionality, and some assumption about track radius must invariably be made if one is to relate linear energy deposition dE/dx to volume-based excitation density n (eh/cm3) in terms of which the rates are defined. Diffusion, affecting time-dependent track radius and thus density of excitations, has been implicated as an important factor in nonlinear light yield. Several groups have recently highlighted diffusion of hot electrons in addition to thermalized carriers and excitons in scintillators. However, experimental determination of many of these parameters in the insulating crystals used as scintillators has seemed difficult. Subpicosecond laser techniques including interband z scan light yield, fluence-dependent decay time, and transient optical absorption are now yielding experimental values for some of the missing rates and ratios needed for modeling scintillator response. First principles calculations and Monte Carlo simulations can fill in additional parameters still unavailable from experiment. As a result, quantitative modeling of scintillator electron energy response from independently determined material parameters is becoming possible on an increasingly firmer data base. This paper describes recent laser experiments, calculations, and numerical modeling of scintillator response.

Experimental and computational results on exciton/free-carrier ratio, hot/thermalized carrier diffusion, and linear/nonlinear rate constants affecting scintillator proportionality

DOE PAGES

Williams, R. T.; Grim, Joel Q.; Li, Qi; ...

2013-09-26

Models of nonproportional response in scintillators have highlighted the importance of parameters such as branching ratios, carrier thermalization times, diffusion, kinetic order of quenching, associated rate constants, and radius of the electron track. For example, the fraction ηeh of excitations that are free carriers versus excitons was shown by Payne and coworkers to have strong correlation with the shape of electron energy response curves from Compton-coincidence studies. Rate constants for nonlinear quenching are implicit in almost all models of nonproportionality, and some assumption about track radius must invariably be made if one is to relate linear energy deposition dE/dx tomore » volume-based excitation density n (eh/cm 3) in terms of which the rates are defined. Diffusion, affecting time-dependent track radius and thus density of excitations, has been implicated as an important factor in nonlinear light yield. Several groups have recently highlighted diffusion of hot electrons in addition to thermalized carriers and excitons in scintillators. However, experimental determination of many of these parameters in the insulating crystals used as scintillators has seemed difficult. Subpicosecond laser techniques including interband z scan light yield, fluence-dependent decay time, and transient optical absorption are now yielding experimental values for some of the missing rates and ratios needed for modeling scintillator response. First principles calculations and Monte Carlo simulations can fill in additional parameters still unavailable from experiment. As a result, quantitative modeling of scintillator electron energy response from independently determined material parameters is becoming possible on an increasingly firmer data base. This study describes recent laser experiments, calculations, and numerical modeling of scintillator response.« less

Comparison of Response Surface and Kriging Models for Multidisciplinary Design Optimization

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Korte, John J.; Mauery, Timothy M.; Mistree, Farrokh

1998-01-01

In this paper, we compare and contrast the use of second-order response surface models and kriging models for approximating non-random, deterministic computer analyses. After reviewing the response surface method for constructing polynomial approximations, kriging is presented as an alternative approximation method for the design and analysis of computer experiments. Both methods are applied to the multidisciplinary design of an aerospike nozzle which consists of a computational fluid dynamics model and a finite-element model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations, and four optimization problems m formulated and solved using both sets of approximation models. The second-order response surface models and kriging models-using a constant underlying global model and a Gaussian correlation function-yield comparable results.

Modeling the initial mechanical response and yielding behavior of gelled crude oil

NASA Astrophysics Data System (ADS)

Lei, Chen; Gang, Liu; Xingguo, Lu; Minghai, Xu; Yuannan, Tang

2018-05-01

The initial mechanical response and yielding behavior of gelled crude oil under constant shear rate conditions were investigated. By putting the Maxwell mechanical analog and a special dashpot in parallel, a quasi-Jeffreys model was obtained. The kinetic equation of the structural parameter in the Houska model was simplified reasonably so that a simplified constitutive equation of the special dashpot was expressed. By introducing a damage factor into the constitutive equation of the special dashpot and the Maxwell mechanical analog, we established a constitutive equation of the quasi-Jeffreys model. Rheological tests of gelled crude oil were conducted by imposing constant shear rates and the relationship between the shear stress and shear strain under different shear rates was plotted. It is found that the constitutive equation can fit the experimental data well under a wide range of shear rates. Based on the fitted parameters in the quasi-Jeffreys model, the shear stress changing rules of the Maxwell mechanical analog and the special dashpot were calculated and analyzed. It is found that the critical yield strain and the corresponding shear strain where shear stress of the Maxwell analog is the maximum change slightly under different shear rates. And then a critical damage softening strain which is irrelevant to the shearing conditions was put forward to describe the yielding behavior of gelled crude oil.

[Evaluating the response of yield and evapotranspiration of winter wheat and the adaptation by adjusting crop variety to climate change in Huang-Huai-Hai Plain].

PubMed

Hu, Shi; Mo, Xing-guo; Lin, Zhong-hui

2015-04-01

Based on the multi-model datasets of three representative concentration pathway (RCP) emission scenarios from IPCC5, the response of yield and accumulative evapotranspiration (ET) of winter wheat to climate change in the future were assessed by VIP model. The results showed that if effects of CO2 enrichment were excluded, temperature rise would lead to a reduction in the length of the growing period for wheat under the three climate change scenarios, and the wheat yield and ET presented a decrease tendency. The positive effect of atmospheric CO2 enrichment could offset most negative effect introduced by temperature rising, indicating that atmospheric CO2 enrichment would be the prime reason of the wheat yield rising in future. In 2050s, wheat yield would increase 14.8% (decrease 2.5% without CO2 fertilization) , and ET would decrease 2.1% under RCP4.5. By adoption of new crop variety with enhanced requirement on accumulative temperature, the wheat yield would increase more significantly with CO2 fertilization, but the water consumption would also increase. Therefore, cultivar breeding new irrigation techniques and agronomical management should be explored under the challenges of climate change in the future.

Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

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

2017-04-01

The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining vegetation and hydro-meteorological drought indices for the assessment of cereal yield. Moreover, the present study will provide some guidance on user's decision making process in agricultural practices in the IP, assisting farmers in deciding whether to purchase crop insurance. Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). Andreia Ribeiro also thanks FCT for grant PD/BD/114481/2016.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

Extraction optimization of mucilage from Basil (Ocimum basilicum L.) seeds using response surface methodology.

PubMed

Nazir, Sadaf; Wani, Idrees Ahmed; Masoodi, Farooq Ahmad

2017-05-01

Aqueous extraction of basil seed mucilage was optimized using response surface methodology. A Central Composite Rotatable Design (CCRD) for modeling of three independent variables: temperature (40-91 °C); extraction time (1.6-3.3 h) and water/seed ratio (18:1-77:1) was used to study the response for yield. Experimental values for extraction yield ranged from 7.86 to 20.5 g/100 g. Extraction yield was significantly ( P  < 0.05) affected by all the variables. Temperature and water/seed ratio were found to have pronounced effect while the extraction time was found to have minor possible effects. Graphical optimization determined the optimal conditions for the extraction of mucilage. The optimal condition predicted an extraction yield of 20.49 g/100 g at 56.7 °C, 1.6 h, and a water/seed ratio of 66.84:1. Optimal conditions were determined to obtain highest extraction yield. Results indicated that water/seed ratio was the most significant parameter, followed by temperature and time.

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

USGS Publications Warehouse

Perkins, S.P.; Sophocleous, M.

1999-01-01

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

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

PubMed

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Evaluation of Projected Agricultural Climate Risk over the Contiguous US

NASA Astrophysics Data System (ADS)

Zhu, X.; Troy, T. J.; Devineni, N.

2017-12-01

Food demands are rising due to an increasing population with changing food preferences, which places pressure on agricultural production. Additionally, climate extremes have recently highlighted the vulnerability of our agricultural system to climate variability. This study seeks to fill two important gaps in current knowledge: how does the widespread response of irrigated crops differ from rainfed and how can we best account for uncertainty in yield responses. We developed a stochastic approach to evaluate climate risk quantitatively to better understand the historical impacts of climate change and estimate the future impacts it may bring about to agricultural system. Our model consists of Bayesian regression, distribution fitting, and Monte Carlo simulation to simulate rainfed and irrigated crop yields at the US county level. The model was fit using historical data for 1970-2010 and was then applied over different climate regions in the contiguous US using the CMIP5 climate projections. The relative importance of many major growing season climate indices, such as consecutive dry days without rainfall or heavy precipitation, was evaluated to determine what climate indices play a role in affecting future crop yields. The statistical modeling framework also evaluated the impact of irrigation by using county-level irrigated and rainfed yields separately. Furthermore, the projected years with negative yield anomalies were specifically evaluated in terms of magnitude, trend and potential climate drivers. This framework provides estimates of the agricultural climate risk for the 21st century that account for the full uncertainty of climate occurrences, range of crop response, and spatial correlation in climate. The results of this study can contribute to decision making about crop choice and water use in an uncertain future climate.

Biophysical and Economic Uncertainty in the Analysis of Poverty Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Hertel, T. W.; Lobell, D. B.; Verma, M.

2011-12-01

This paper seeks to understand the main sources of uncertainty in assessing the impacts of climate change on agricultural output, international trade, and poverty. We incorporate biophysical uncertainty by sampling from a distribution of global climate model predictions for temperature and precipitation for 2050. The implications of these realizations for crop yields around the globe are estimated using the recently published statistical crop yield functions provided by Lobell, Schlenker and Costa-Roberts (2011). By comparing these yields to those predicted under current climate, we obtain the likely change in crop yields owing to climate change. The economic uncertainty in our analysis relates to the response of the global economic system to these biophysical shocks. We use a modified version of the GTAP model to elicit the impact of the biophysical shocks on global patterns of production, consumption, trade and poverty. Uncertainty in these responses is reflected in the econometrically estimated parameters governing the responsiveness of international trade, consumption, production (and hence the intensive margin of supply response), and factor supplies (which govern the extensive margin of supply response). We sample from the distributions of these parameters as specified by Hertel et al. (2007) and Keeney and Hertel (2009). We find that, even though it is difficult to predict where in the world agricultural crops will be favorably affected by climate change, the responses of economic variables, including output and exports can be far more robust (Table 1). This is due to the fact that supply and demand decisions depend on relative prices, and relative prices depend on productivity changes relative to other crops in a given region, or relative to similar crops in other parts of the world. We also find that uncertainty in poverty impacts of climate change appears to be almost entirely driven by biophysical uncertainty.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Texture-induced anisotropy and high-strain rate deformation in metals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schiferl, S.K.; Maudlin, P.J.

1990-01-01

We have used crystallographic texture calculations to model anisotropic yielding behavior for polycrystalline materials with strong preferred orientations and strong plastic anisotropy. Fitted yield surfaces were incorporated into an explicit Lagrangian finite-element code. We consider different anisotropic orientations, as well as different yield-surface forms, for Taylor cylinder impacts of hcp metals such as titanium and zirconium. Some deformed shapes are intrinsic to anisotropic response. Also, yield surface curvature, as distinct from strength anisotropy, has a strong influence on plastic flow. 13 refs., 5 figs.

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

PubMed

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

2016-09-01

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

Investigation of the Process Conditions for Hydrogen Production by Steam Reforming of Glycerol over Ni/Al2O3 Catalyst Using Response Surface Methodology (RSM)

PubMed Central

Ebshish, Ali; Yaakob, Zahira; Taufiq-Yap, Yun Hin; Bshish, Ahmed

2014-01-01

In this work; a response surface methodology (RSM) was implemented to investigate the process variables in a hydrogen production system. The effects of five independent variables; namely the temperature (X1); the flow rate (X2); the catalyst weight (X3); the catalyst loading (X4) and the glycerol-water molar ratio (X5) on the H2 yield (Y1) and the conversion of glycerol to gaseous products (Y2) were explored. Using multiple regression analysis; the experimental results of the H2 yield and the glycerol conversion to gases were fit to quadratic polynomial models. The proposed mathematical models have correlated the dependent factors well within the limits that were being examined. The best values of the process variables were a temperature of approximately 600 °C; a feed flow rate of 0.05 mL/min; a catalyst weight of 0.2 g; a catalyst loading of 20% and a glycerol-water molar ratio of approximately 12; where the H2 yield was predicted to be 57.6% and the conversion of glycerol was predicted to be 75%. To validate the proposed models; statistical analysis using a two-sample t-test was performed; and the results showed that the models could predict the responses satisfactorily within the limits of the variables that were studied. PMID:28788567

Response of vegetation to carbon dioxide. Field studies of plant responses to elevated carbon dioxide levels 1984

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-08-01

In the present study, CO{sub 2} enrichment has been applied to sweet potatoes and cowpeas in order to investigate its effect on their growth, physiology, and yield under field condition. Objectives were: (1) to establish at Tuskegee Institute the facilities for growing crops in the field under enriched CO{sub 2} atmospheric conditions; (2) to obtain field data on the morphological, physiological, biochemical, growth and yield responses of sweet potatoes and cowpeas to elevated levels of CO{sub 2}; (3) to determine the effects of elevated CO{sub 2} in the rate of nitrogen fixation of cowpeas; (4) to provide data for amore » generalized crop growth model for predicting yield of both sweet potatoes and cowpeas as a function of atmospheric CO{sub 2} enrichment.« less

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Some Comments on the Decays of eta (550)

DOE R&D Accomplishments Database

Veltman, M.; Yellin, J.

1966-07-01

Various decay modes of the {eta}(500) are discussed. The relations, through SU{sub 3} and the Gell-Mann, Sharp, Wagner model, between the {eta}-decay modes and the modes {eta} {yields} {pi}{pi}{gamma), {pi}{sup 0} {yields} {gamma}{gamma} are investigated taking into account {eta}-{eta}{sup *} mixing. The present experimental values for the neutral branching ratios plus the shape of the {eta} {yields} {pi}{sup +}{pi}{sup {minus}}{pi}{sup 0} Dalitz plot are shown to require a 25% {vert_bar}{Delta}{rvec I}{vert_bar} = 3 contribution to the {eta} {yields} 3{pi} amplitude. The connection between a possible charge asymmetry in {eta} {yields} {pi}{sup +}{pi}{sup {minus}}{pi}{sup 0} and the branching ratio {Gamma}{sub {eta} {yields} {pi}{sup 0}e{sup +}e{sup {minus}}}/{Gamma}{sub {eta}}{sup all} is investigated in the framework of a model proposed earlier by several authors. It is shown that there is no conflict between the existing data and this model. The Dalitz plot distribution of {eta} {yields} {pi}{sup +}{pi}{sup {minus}}{pi}{sup 0} is discussed under various assumptions about the properties of the interaction responsible for the decay. (auth)

Estimation of a Ramsay-Curve Item Response Theory Model by the Metropolis-Hastings Robbins-Monro Algorithm. CRESST Report 834

ERIC Educational Resources Information Center

Monroe, Scott; Cai, Li

2013-01-01

In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…

Estimation of a Ramsay-Curve Item Response Theory Model by the Metropolis-Hastings Robbins-Monro Algorithm

ERIC Educational Resources Information Center

Monroe, Scott; Cai, Li

2014-01-01

In Ramsay curve item response theory (RC-IRT) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's EM algorithm, which yields maximum marginal likelihood estimates. This method, however, does not produce the…

Plastic flow modeling in glassy polymers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clements, Brad

2010-12-13

Glassy amorphous and semi-crystalline polymers exhibit strong rate, temperature, and pressure dependent polymeric yield. As a rule of thumb, in uniaxial compression experiments the yield stress increases with the loading rate and applied pressure, and decreases as the temperature increases. Moreover, by varying the loading state itself complex yield behavior can be observed. One example that illustrates this complexity is that most polymers in their glassy regimes (i.e., when the temperature is below their characteristic glass transition temperature) exhibit very pronounced yield in their uniaxial stress stress-strain response but very nebulous yield in their uniaxial strain response. In uniaxial compression,more » a prototypical glassy-polymer stress-strain curve has a stress plateau, often followed by softening, and upon further straining, a hardening response. Uniaxial compression experiments of this type are typically done from rates of 10{sup -5} s{sup -1} up to about 1 s{sup -1}. At still higher rates, say at several thousands per second as determined from Split Hopkinson Pressure Bar experiments, the yield can again be measured and is consistent with the above rule of thumb. One might expect that that these two sets of experiments should allow for a successful extrapolation to yet higher rates. A standard means to probe high rates (on the order of 105-107 S-I) is to use a uniaxial strain plate impact experiment. It is well known that in plate impact experiments on metals that the yield stress is manifested in a well-defined Hugoniot Elastic Limit (HEL). In contrast however, when plate impact experiments are done on glassy polymers, the HEL is arguably not observed, let alone observed at the stress estimated by extrapolating from the lower strain rate experiments. One might argue that polymer yield is still active but somehow masked by the experiment. After reviewing relevant experiments, we attempt to address this issue. We begin by first presenting our recently developed glassy polymer model. While polymers are well known for their non-equilibrium deviatoric behavior we have found the need for incorporating both equilibrium and non-equilibrium volumetric behavior into our theory. Experimental evidence supporting the notion of non-equilibrium volumetric behavior will be summarized. Our polymer yield model accurately captures the stress plateau, softening and hardening and its yield stress predictions agree well with measured values for several glassy polymers including PMMA, PC, and an epoxy resin. We then apply our theory to plate impact experiments in an attempt to address the questions associated with high rate polymer yield in uniaxial strain configurations.« less

Field warming experiments shed light on the wheat yield response to temperature in China

PubMed Central

Zhao, Chuang; Piao, Shilong; Huang, Yao; Wang, Xuhui; Ciais, Philippe; Huang, Mengtian; Zeng, Zhenzhong; Peng, Shushi

2016-01-01

Wheat growth is sensitive to temperature, but the effect of future warming on yield is uncertain. Here, focusing on China, we compiled 46 observations of the sensitivity of wheat yield to temperature change (SY,T, yield change per °C) from field warming experiments and 102 SY,T estimates from local process-based and statistical models. The average SY,T from field warming experiments, local process-based models and statistical models is −0.7±7.8(±s.d.)% per °C, −5.7±6.5% per °C and 0.4±4.4% per °C, respectively. Moreover, SY,T is different across regions and warming experiments indicate positive SY,T values in regions where growing-season mean temperature is low, and water supply is not limiting, and negative values elsewhere. Gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project appear to capture the spatial pattern of SY,T deduced from warming observations. These results from local manipulative experiments could be used to improve crop models in the future. PMID:27853151

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong

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

Simple nonlinear modelling of earthquake response in torsionally coupled R/C structures: A preliminary study

NASA Astrophysics Data System (ADS)

Saiidi, M.

1982-07-01

The equivalent of a single degree of freedom (SDOF) nonlinear model, the Q-model-13, was examined. The study intended to: (1) determine the seismic response of a torsionally coupled building based on the multidegree of freedom (MDOF) and (SDOF) nonlinear models; and (2) develop a simple SDOF nonlinear model to calculate displacement history of structures with eccentric centers of mass and stiffness. It is shown that planar models are able to yield qualitative estimates of the response of the building. The model is used to estimate the response of a hypothetical six-story frame wall reinforced concrete building with torsional coupling, using two different earthquake intensities. It is shown that the Q-Model-13 can lead to a satisfactory estimate of the response of the structure in both cases.

Rice: Characterizing the Environmental Response of a Gibberellic Acid-Deficient Rice for Use as a Model Crop

NASA Technical Reports Server (NTRS)

Frantz, Jonathan M.; Pinnock, Derek; Klassen, Steve; Bugbee, Bruce

2004-01-01

Rice (Oryza sativa L.) is a useful model crop plant. Rice was the first crop plant to have its complete genome sequenced. Unfortunately, even semi-dwarf rice cultivars are 60 to 90 an tail, and large plant populations cannot be grown in the confined volumes of greenhouses and growth chambers. We recently identified an extremely short (20 em tall) rice line, which is an ideal model for larger rice cultivars. We called this line "Super Dwarf rice." Here we report the response of Super Dwarf to temperature, photoperiod, photosynthetic photon flux (PPF), and factors that can affect time to head emergence. Vegetative biomass increased 6% per degree Celsius, with increasing temperature from 27 to 31 C. Seed yield decreased by 2% per degree Celsius rise in temperature, and as a result, harvest index decreased from 60 to 54%. The time to heading increased by 2 d for every hour above a 12-h photoperiod. Yield increased with increasing PPF up to the highest level tested at 1800 micro-mol/sq m/s (12-h photoperiod; 77.8 mol/sq m/d). Yield efficiency (grams per mole of photons) increased to 900 micro-mol/sq m/s and then slightly decreased at 1800 micro-mol/sq m/s . Heading was delayed by addition of gibberellic acid 3 (GA,) to the root zone but was hastened under mild N stress. Overall, short stature, high yield, high harvest index, and no extraordinary environmental requirements make Super Dwarf rice an excellent model plant for yield studies in controlled environments.

Optimisation of Croton gratissimus Oil Extraction by n-Hexane and Ethyl Acetate Using Response Surface Methodology.

PubMed

Jiyane, Phiwe Charles; Tumba, Kaniki; Musonge, Paul

2018-04-01

The extraction of oil from Croton gratissimus seeds was studied using the three-factor five-level full-factorial central composite rotatable design (CCRD) of the response surface methodology (RSM). The effect of the three factors selected, viz., extraction time, extraction temperature and solvent-to-feed ratio on the extraction oil yield was investigated when n-hexane and ethyl acetate were used as extraction solvents. The coefficients of determination (R 2 ) of the models developed were 0.98 for n-hexane extraction and 0.97 for ethyl acetate extraction. These results demonstrated that the models developed adequately represented the processes they described. From the optimized model, maximum extraction yield obtained from n-hexane and ethyl acetate extraction were 23.88% and 23.25%, respectively. In both cases the extraction temperature and solvent-to-feed ratio were 35°C and 5 mL/g, respectively. In n-hexane extraction the maximum conditions were reached only after 6 min whereas in ethyl acetate extraction it took 20 min to get the maximum extraction oil yield. Oil extraction of Croton gratissimus seeds, in this work, favoured the use of n-hexane as an extraction solvent as it offered higher oil yields at low temperatures and reduced residence times.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE PAGES

Blanc, Elodie; Caron, Justin; Fant, Charles; ...

2017-06-27

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanc, Elodie; Caron, Justin; Fant, Charles

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Variable-Length Computerized Adaptive Testing Using the Higher Order DINA Model

ERIC Educational Resources Information Center

Hsu, Chia-Ling; Wang, Wen-Chung

2015-01-01

Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent…

An efficient energy response model for liquid scintillator detectors

NASA Astrophysics Data System (ADS)

Lebanowski, Logan; Wan, Linyan; Ji, Xiangpan; Wang, Zhe; Chen, Shaomin

2018-05-01

Liquid scintillator detectors are playing an increasingly important role in low-energy neutrino experiments. In this article, we describe a generic energy response model of liquid scintillator detectors that provides energy estimations of sub-percent accuracy. This model fits a minimal set of physically-motivated parameters that capture the essential characteristics of scintillator response and that can naturally account for changes in scintillator over time, helping to avoid associated biases or systematic uncertainties. The model employs a one-step calculation and look-up tables, yielding an immediate estimation of energy and an efficient framework for quantifying systematic uncertainties and correlations.

A Pressure-Dependent Damage Model for Energetic Materials

DTIC Science & Technology

2013-04-01

appropriate damage nucleation and evolution laws, and the equation of state ) with its reactive response. 15. SUBJECT TERMS pressure-dependent...evolution laws, and the equation of state ) with its reactive response. INTRODUCTION Explosions and deflagrations are classifications of sub-detonative...energetic material’s mechanical response (through the yield criterion, damage evolution and equation of state ) with its reactive response. DAMAGE-FREE

What aspects of future rainfall changes matter for crop yields in West Africa?

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

2015-10-01

How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

Ensembles modeling approach to study Climate Change impacts on Wheat

NASA Astrophysics Data System (ADS)

Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart

2017-04-01

Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.

On universal procrastination

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-09-01

This paper presents a general stochastic model for procrastination with respect to a deadline. The model establishes a universal procrastination pattern that follows an inverse power-law: if the time remaining to the deadline is r then the response is 1/rε , where ɛ is a positive exponent. The model further establishes that the exponent value ε =1 , which yields the harmonic response 1/r , stands out as special and distinguishable. The theoretical results of the model are shown to be in perfect accord with recent empirical findings.

Theoretical Development of an Orthotropic Elasto-Plastic Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Goldberg, Robert; Carney, Kelly; DuBois, Paul; Hoffarth, Canio; Harrington, Joseph; Rajan, Subramaniam; Blankenhorn, Gunther

2014-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. While there are several composite material models currently available within LSDYNA (Livermore Software Technology Corporation), there are several features that have been identified that could improve the predictive capability of a composite model. To address these needs, a combined plasticity and damage model suitable for use with both solid and shell elements is being developed and is being implemented into LS-DYNA as MAT_213. A key feature of the improved material model is the use of tabulated stress-strain data in a variety of coordinate directions to fully define the stress-strain response of the material. To date, the model development efforts have focused on creating the plasticity portion of the model. The Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic yield function with a nonassociative flow rule. The coefficients of the yield function, and the stresses to be used in both the yield function and the flow rule, are computed based on the input stress-strain curves using the effective plastic strain as the tracking variable. The coefficients in the flow rule are computed based on the obtained stress-strain data. The developed material model is suitable for implementation within LS-DYNA for use in analyzing the nonlinear response of polymer composites.

Influence of a surface film on the particles on the electrorheological response

NASA Astrophysics Data System (ADS)

Wu, C. W.; Conrad, H.

1997-01-01

A conduction model is developed for the dc electrorheological (ER) response of highly conducting particles (e.g., metal particles) suspended in a weakly conducting oil. The numerical analyses show that a surface film with some conductivity is desired, but not a completely insulating film as previously proposed. Increasing the film conductivity leads to an increase in the ER yield stress. However, too high a conductivity will give an unacceptable level of current density. The film should also have an intermediate thickness. A small thickness increases the possibility of electrical breakdown in the film; too large a thickness decreases the ER effect. Good agreement exists between the yield stress and the current density predicted by our model and those measured.

Quantifying long-term responses of crop yield and nitrate leaching in an intensive farmland using agro-eco-environmental model.

PubMed

Sun, Mei; Huo, Zailin; Zheng, Yanxia; Dai, Xiaoqin; Feng, Shaoyuan; Mao, Xiaomin

2018-02-01

Quantitatively ascertaining and analyzing long-term responses of crop yield and nitrate leaching on varying irrigation and fertilization treatments are focal points for guaranteeing crop yield and reducing nitrogen loss. The calibrated agricultural-hydrological RZWQM2 model was used to explore the long-term (2003-2013) transport processes of water and nitrogen and the nitrate leaching amount into groundwater in summer maize and winter wheat rotation field in typical intensive plant area in the North China Plain, Daxing district of Beijing. Simulation results showed that application rates of irrigation and nitrogen fertilizer have couple effects on crop yields and nitrogen leaching of root zone. When both the irrigation and fertilizer for summer maize and winter wheat were 400mm and 400kgNha -1 , respectively, nitrate leaching into groundwater accounted for 47.9% of application amount of nitrogen fertilizer. When application amount of irrigation is 200mm and fertilization is 200kgNha -1 , NUPE (nitrogen uptake efficiency), NUE (nitrogen use efficiency), NPFP (nitrogen partial factor productivity), and W pi (irrigation water productive efficiency) were in general higher than that under other irrigation and fertilization condition (irrigation from 104-400mm, fertilizer 104-400kgNha -1 ). Irrigation bigger than 200mm could shorten the response time of nitrate leaching in deeper soil layer in different irrigation treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.

2017-12-01

Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.

On an Extension of the Rasch Model to the Case of Polychotomously Scored Items.

ERIC Educational Resources Information Center

Vogt, Dorothee K.

The Rasch model for the probability of a person's response to an item is extended to the case where this response depends on a set of scoring or category weights, in addition to person and item parameters. The maximum likelihood approach introduced by Wright for the dichotomous case is applicable here also, and it is shown to yield a unique…

Preparation of Curcumin Loaded Egg Albumin Nanoparticles Using Acetone and Optimization of Desolvation Process.

PubMed

Aniesrani Delfiya, D S; Thangavel, K; Amirtham, D

2016-04-01

In this study, acetone was used as a desolvating agent to prepare the curcumin-loaded egg albumin nanoparticles. Response surface methodology was employed to analyze the influence of process parameters namely concentration (5-15%w/v) and pH (5-7) of egg albumin solution on solubility, curcumin loading and entrapment efficiency, nanoparticles yield and particle size. Optimum processing conditions obtained from response surface analysis were found to be the egg albumin solution concentration of 8.85%w/v and pH of 5. At this optimum condition, the solubility of 33.57%, curcumin loading of 4.125%, curcumin entrapment efficiency of 55.23%, yield of 72.85% and particles size of 232.6 nm were obtained and these values were related to the values which are predicted using polynomial model equations. Thus, the model equations generated for each response was validated and it can be used to predict the response values at any concentration and pH.

Aerodynamic mathematical modeling - basic concepts

NASA Technical Reports Server (NTRS)

Tobak, M.; Schiff, L. B.

1981-01-01

The mathematical modeling of the aerodynamic response of an aircraft to arbitrary maneuvers is reviewed. Bryan's original formulation, linear aerodynamic indicial functions, and superposition are considered. These concepts are extended into the nonlinear regime. The nonlinear generalization yields a form for the aerodynamic response that can be built up from the responses to a limited number of well defined characteristic motions, reproducible in principle either in wind tunnel experiments or flow field computations. A further generalization leads to a form accommodating the discontinuous and double valued behavior characteristics of hysteresis in the steady state aerodynamic response.

Phosphorus component in AnnAGNPS

USGS Publications Warehouse

Yuan, Y.; Bingner, R.L.; Theurer, F.D.; Rebich, R.A.; Moore, P.A.

2005-01-01

The USDA Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) has been developed to aid in evaluation of watershed response to agricultural management practices. Previous studies have demonstrated the capability of the model to simulate runoff and sediment, but not phosphorus (P). The main purpose of this article is to evaluate the performance of AnnAGNPS on P simulation using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. A sensitivity analysis was performed to identify input parameters whose impact is the greatest on P yields. Sensitivity analysis results indicate that the most sensitive variables of those selected are initial soil P contents, P application rate, and plant P uptake. AnnAGNPS simulations of dissolved P yield do not agree well with observed dissolved P yield (Nash-Sutcliffe coefficient of efficiency of 0.34, R2 of 0.51, and slope of 0.24); however, AnnAGNPS simulations of total P yield agree well with observed total P yield (Nash-Sutcliffe coefficient of efficiency of 0.85, R2 of 0.88, and slope of 0.83). The difference in dissolved P yield may be attributed to limitations in model simulation of P processes. Uncertainties in input parameter selections also affect the model's performance.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Data-Driven Haptic Modeling and Rendering of Viscoelastic and Frictional Responses of Deformable Objects.

PubMed

Yim, Sunghoon; Jeon, Seokhee; Choi, Seungmoon

2016-01-01

In this paper, we present an extended data-driven haptic rendering method capable of reproducing force responses during pushing and sliding interaction on a large surface area. The main part of the approach is a novel input variable set for the training of an interpolation model, which incorporates the position of a proxy - an imaginary contact point on the undeformed surface. This allows us to estimate friction in both sliding and sticking states in a unified framework. Estimating the proxy position is done in real-time based on simulation using a sliding yield surface - a surface defining a border between the sliding and sticking regions in the external force space. During modeling, the sliding yield surface is first identified via an automated palpation procedure. Then, through manual palpation on a target surface, input data and resultant force data are acquired. The data are used to build a radial basis interpolation model. During rendering, this input-output mapping interpolation model is used to estimate force responses in real-time in accordance with the interaction input. Physical performance evaluation demonstrates that our approach achieves reasonably high estimation accuracy. A user study also shows plausible perceptual realism under diverse and extensive exploration.

Teaching Real Business Cycles to Undergraduates

ERIC Educational Resources Information Center

Brevik, Frode; Gartner, Manfred

2007-01-01

The authors review the graphical approach to teaching the real business cycle model introduced in Barro. They then look at where this approach cuts corners and suggest refinements. Finally, they compare graphical and exact models by means of impulse-response functions. The graphical models yield reliable qualitative results. Sizable quantitative…

Ultrasound-assisted extraction of pectins from grape pomace using citric acid: a response surface methodology approach.

PubMed

Minjares-Fuentes, R; Femenia, A; Garau, M C; Meza-Velázquez, J A; Simal, S; Rosselló, C

2014-06-15

An ultrasound-assisted procedure for the extraction of pectins from grape pomace with citric acid as the extracting agent was established. A Box-Behnken design (BBD) was employed to optimize the extraction temperature (X1: 35-75°C), extraction time (X2: 20-60 min) and pH (X3: 1.0-2.0) to obtain a high yield of pectins with high average molecular weight (MW) and degree of esterification (DE) from grape pomace. Analysis of variance showed that the contribution of a quadratic model was significant for the pectin extraction yield and for pectin MW whereas the DE of pectins was more influenced by a linear model. An optimization study using response surface methodology was performed and 3D response surfaces were plotted from the mathematical model. According to the RSM model, the highest pectin yield (∼32.3%) can be achieved when the UAE process is carried out at 75°C for 60 min using a citric acid solution of pH 2.0. These pectic polysaccharides, composed mainly by galacturonic acid units (<97% of total sugars), have an average MW of 163.9 kDa and a DE of 55.2%. Close agreement between experimental and predicted values was found. These results suggest that ultrasound-assisted extraction could be a good option for the extraction of functional pectins with citric acid from grape pomace at industrial level. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting trends of invasive plants richness using local socio-economic data: An application in North Portugal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos, Mario, E-mail: mgsantoss@gmail.com; Freitas, Raul, E-mail: raulfreitas@portugalmail.com; Crespi, Antonio L., E-mail: aluis.crespi@gmail.com

2011-10-15

This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasingmore » populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology. - Highlights: {yields} Socio-economic data indicate human induced disturbances. {yields} Socio-economic development increase disturbance in ecosystems. {yields} Disturbance promotes opportunities for invasive plants.{yields} Increased opportunities promote richness of invasive plants.{yields} Increase in richness of invasive plants change natural ecosystems.« less

The International Heat Stress Genotype Experiment for Modeling Wheat Response to Heat: Field Experiments and AgMIP-Wheat Multi-Model Simulations

NASA Technical Reports Server (NTRS)

Martre, Pierre; Reynolds, Matthew P.; Asseng, Senthold; Ewert, Frank; Alderman, Phillip D.; Cammarano, Davide; Maiorano, Andrea; Ruane, Alexander C.; Aggarwal, Pramod K.; Anothai, Jakarat;

Hydrodynamics with strength: scaling-invariant solutions for elastic-plastic cavity expansion models

NASA Astrophysics Data System (ADS)

Albright, Jason; Ramsey, Scott; Baty, Roy

2017-11-01

Spherical cavity expansion (SCE) models are used to describe idealized detonation and high-velocity impact in a variety of materials. The common theme in SCE models is the presence of a pressure-driven cavity or void within a domain comprised of plastic and elastic response sub-regions. In past work, the yield criterion characterizing material strength in the plastic sub-region is usually taken for granted and assumed to take a known functional form restrictive to certain classes of materials, e.g. ductile metals or brittle geologic materials. Our objective is to systematically determine a general functional form for the yield criterion under the additional requirement that the SCE admits a similarity solution. Solutions determined under this additional requirement have immediate implications toward development of new compressible flow algorithm verification test problems. However, more importantly, these results also provide novel insight into modeling the yield criteria from the perspective of hydrodynamic scaling.

Including climate variability in determination of the optimum rate of N fertilizer application using a crop model: A case study for rainfed corn in eastern Canada

NASA Astrophysics Data System (ADS)

Mesbah, M.; Pattey, E.; Jégo, G.; Geng, X.; Tremblay, N.; Didier, A.

2017-12-01

Identifying optimum nitrogen (N) application rate is essential for increasing agricultural production while limiting potential environmental contaminations caused by release of reactive N, especially for high demand N crops such as corn. The central question of N management is then how the optimum N rate is affected by climate variability for given soil. The experimental determination of optimum N rates involve the analyses of variance on the mean value of crop yield response to various N application rates used by factorial plot based experiments for a few years in several regions. This traditional approach has limitations to capture 1) the non-linear response of yield to N application rates due to large incremental N rates (often more than 40 kg N ha-1) and 2) the ecophysiological response of the crop to climate variability because of limited numbers of growing seasons considered. Modeling on the other hand, does not have such limitations and hence we use a crop model and propose a model-based methodology called Finding NEMO (N Ecophysiologically Modelled Optimum) to identify the optimum N rates for variable agro-climatic conditions and given soil properties. The performance of the methodology is illustrated using the STICS crop model adapted for rainfed corn in the Mixedwood Plains ecozone of eastern Canada (42.3oN 83oW-46.8oN 71oW) where more than 90% of Canadian corn is produced. The simulations were performed using small increment of preplant N application rate (10 kg N ha -1), long time series of daily climatic data (48 to 61 years) for 5 regions along the ecozone, and three contrasting soils per region. The results show that N recommendations should be region and soil specific. Soils with lower available water capacity required more N compared to soil with higher available water capacity. When N rates were at their ecophysiologically optimum level, 10 to 17 kg increase in dry yield could be achieved by adding 1 kg N. Expected yield also affected the optimum N rates for the region and soil. For instance, the probability to achieve a yield of 9.2 t ha-1 at 15% grain moisture on a loamy soil varied from 0 to 73% along the ecozone. For this level of expected yield, the recommended N rates ranged from 64 to 155 kg ha-1, which are relatively less than current provincial recommendations in Ontario and Quebec (120-170 kg ha-1).

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Interactions of CO2, temperature and management practices: simulations with a modified version of CERES-Wheat

NASA Technical Reports Server (NTRS)

Tubiello, F. N.; Rosenzweig, C.; Volk, T.

1995-01-01

A new growth subroutine was developed for CERES-Wheat, a computer model of wheat (Triticum aestivum) growth and development. The new subroutine simulates canopy photosynthetic response to CO2 concentrations and light levels, and includes the effects of temperature on canopy light-use efficiency. Its performance was compared to the original CERES-Wheat V-2 10 in 30 different cases. Biomass and yield predictions of the two models were well correlated (correlation coefficient r > 0.95). As an application, summer growth of spring wheat was simulated at one site. Modeled crop responses to higher mean temperatures, different amounts of minimum and maximum warming, and doubled CO2 concentrations were compared to observations. The importance of irrigation and nitrogen fertilization in modulating the wheat crop climatic responses were also analyzed. Specifically, in agreement with observations, rainfed crops were found to be more sensitive to CO2 increases than irrigated ones. On the other hand, low nitrogen applications depressed the ability of the wheat crop to respond positively to CO2 increases. In general, the positive effects of high CO2 on grain yield were found to be almost completely counterbalanced by the negative effects of high temperatures. Depending on how temperature minima and maxima were increased, yield changes averaged across management practices ranged from -4% to 8%.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

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

Extraction of Antioxidant Phenolic Compounds from Brewer’s Spent Grain: Optimization and Kinetics Modeling

PubMed Central

Sologubik, Carlos A.; Fernández, María B.; Manrique, Guillermo D.

2018-01-01

The kinetics of polyphenol extraction from brewer’s spent grain (BSG), using a batch system, ultrasound assistance, and microwave assistance and the evolution of antioxidant capacity of these extracts over time, were studied. The main parameters of extraction employed in the batch system were evaluated, and, by applying response surface analysis, the following optimal conditions were obtained: Liquid/solid ratio of 30:1 mL/g at 80 °C, using 72% (v/v) ethanol:water as the solvent system. Under these optimized conditions, ultrasound assistance demonstrated the highest extraction rate and equilibrium yield, as well as shortest extraction times, followed by microwave assistance. Among the mathematical models used, Patricelli’s model proved the most suitable for describing the extraction kinetics for each method tested, and is therefore able to predict the response values and estimate the extraction rates and potential maximum yields in each case. PMID:29570683

A kinematic hardening constitutive model for the uniaxial cyclic stress-strain response of magnesium sheet alloys at room temperature

NASA Astrophysics Data System (ADS)

He, Zhitao; Chen, Wufan; Wang, Fenghua; Feng, Miaolin

2017-11-01

A kinematic hardening constitutive model is presented, in which a modified form of von Mises yield function is adopted, and the initial asymmetric tension and compression yield stresses of magnesium (Mg) alloys at room temperature (RT) are considered. The hardening behavior was classified into slip, twinning, and untwinning deformation modes, and these were described by two forms of back stress to capture the mechanical response of Mg sheet alloys under cyclic loading tests at RT. Experimental values were obtained for AZ31B-O and AZ31B sheet alloys under both tension-compression-tension (T-C-T) and compression-tension (C-T) loadings to calibrate the parameters of back stresses in the proposed model. The predicted parameters of back stresses in the twinning and untwinning modes were expressed as a cubic polynomial. The predicted curves based on these parameters showed good agreement with the tests.

Food for Thought: Crop Yields in the Columbia River Basin in an Altered Future

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Nelson, R.; Stockle, C.; Kruger, C.; Brady, M.; Adam, J. C.

2013-12-01

Growth of global population and food consumption in the next several decades is expected to result in a food security challenge. Strategies to address this challenge, such as enhancing agricultural productivity and resiliency, need to be considered within the context of a full range of plausible consequences so as to identify investments that create win-win-win scenarios for the environment, economy, and society. Regional earth systems models can provide the necessary scale-appropriate framework to inform the decision making context for adaptation strategies, especially in the context of global change. In an altered future, changes to climate, technology and socioeconomics affect regional agriculture both directly and indirectly. These effects are not independent and an integrated process-based model may better capture unanticipated non-linear and non-monotonic responses and feedbacks over time . BioEarth is a research initiative designed to explore the coupling of multiple stand-alone earth systems models to generate usable information for agricultural and natural resource decision making at the regional scale at decadal time-steps. This project focuses on the U.S. Pacific Northwest (PNW) region and is a framework that integrates atmospheric, terrestrial, aquatic, and economic models. We apply component models of BioEarth to the Columbia River basin in the PNW to study the direct and indirect impacts of climate change on regional irrigated and dryland crop yields for a variety of annual and perennial crops. Results indicate that the net effect of climate change on crop yields is dependent on the crop type. There is a negative effect of temperature on yields for most crops. Dryland winter wheat is a notable exception. With warming, although the available growing season increases, faster thermal accumulation results in a shorter time to maturity. Precipitation changes in the region have a positive impact on dryland agriculture. Carbon dioxide (CO2) fertilization has a positive impact on crop yields for most crops. This positive impact is minimal for corn which is a C4 crop that is already CO2 efficient. The net response is an increase in yields for dryland agriculture and depends on the crop type for irrigated agriculture. Although, climate change results in increased water shortages and water rights curtailment in the region, this does not translate into an increased negative effect on yields. This could be attributed to higher water use efficiency under elevated CO2 levels as well crops getting through growth stages earlier in the season with wetter spring conditions. The non linear and non monotonic nature of the response of climate change on crop yields is discussed. In accounting for biophysical effects of climate change on crop yields, socio-economic effects cannot be ignored because biophysical effects are nested with the framework of human decision making. We also discuss our results in the context of socioeconomic factors . Current results assume no adaptation strategies and incorporating this is our next step.

Impacts of aerosol pollutant mitigation on lowland rice yields in China

NASA Astrophysics Data System (ADS)

Zhang, Tianyi; Li, Tao; Yue, Xu; Yang, Xiaoguang

2017-10-01

Aerosol pollution in China is significantly altering radiative transfer processes and is thereby potentially affecting rice photosynthesis and yields. However, the response of rice photosynthesis to aerosol-induced radiative perturbations is still not well understood. Here, we employ a process-based modelling approach to simulate changes in incoming radiation (RAD) and the diffuse radiation fraction (DF) with aerosol mitigation in China and their associated impacts on rice yields. Aerosol reduction has the positive effect of increasing RAD and the negative effect of decreasing DF on rice photosynthesis and yields. In rice production areas where the average RAD during the growing season is lower than 250 W m-2, aerosol reduction is beneficial for higher rice yields, whereas in areas with RAD>250 W m-2, aerosol mitigation causes yield declines due to the associated reduction in the DF, which decreases the light use efficiency. As a net effect, rice yields were estimated to significantly increase by 0.8%-2.6% with aerosol concentrations reductions from 20 to 100%, which is lower than the estimates obtained in earlier studies that only considered the effects of RAD. This finding suggests that both RAD and DF are important processes influencing rice yields and should be incorporated into future assessments of agricultural responses to variations in aerosol-induced radiation under climate change.

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

PubMed Central

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

2016-01-01

Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability. PMID:27891133

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

PubMed

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

2016-01-01

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

Predictive evaluation of size restrictions as management strategies for tennessee reservoir crappie fisheries

USGS Publications Warehouse

Isermann, D.A.; Sammons, S.M.; Bettoli, P.W.; Churchill, T.N.

2002-01-01

We evaluated the potential effect of minimum size restrictions on crappies Pomoxis spp. in 12 large Tennessee reservoirs. A Beverton-Holt equilibrium yield model was used to predict and compare the response of these fisheries to three minimum size restrictions: 178 mm (i.e., pragmatically, no size limit), 229 mm, and the current statewide limit of 254 mm. The responses of crappie fisheries to size limits differed among reservoirs and varied with rates of conditional natural mortality (CM). Based on model results, crappie fisheries fell into one of three response categories: (1) In some reservoirs (N = 5), 254-mm and 229-mm limits would benefit the fishery in terms of yield if CM were low (30%); the associated declines in the number of crappies harvested would be significant but modest when compared with those in other reservoirs. (2) In other reservoirs (N = 6), little difference in yield existed among size restrictions at low to intermediate rates of CM (30-40%). In these reservoirs, a 229-mm limit was predicted to be a more beneficial regulation than the current 254-mm limit. (3) In the remaining reservoir, Tellico, size limits negatively affected all three harvest statistics. Generally, yield was negatively affected by size limits in all populations at a CM of 50%. The number of crappies reaching 300 mm was increased by size limits in most model scenarios: however, associated declines in the total number of crappies harvested often outweighed the benefits to size structure when CM was 40% or higher. When crappie growth was fast (reaching 254 mm in less than 3 years) and CM was low (30%), size limits were most effective in balancing increases in yield and size structure against declines in the total number of crappies harvested. The variability in predicted size-limit responses observed among Tennessee reservoirs suggests that using a categorical approach to applying size limits to crappie fisheries within a state or region would likely be a more effective management strategy than implementing a single, areawide regulation.

Crop yields response to water pressures in the Ebro basin in Spain: risk and water policy implications

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2011-02-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro river basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Selective destruction of mouse islet beta cells by human T lymphocytes in a newly-established humanized type 1 diabetic model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Yong, E-mail: yongzhao@uic.edu; Guo, Chengshan; Hwang, David

2010-09-03

Research highlights: {yields} Establish a human immune-mediated type 1 diabetic model in NOD-scid IL2r{gamma}{sup null} mice. {yields} Using the irradiated diabetic NOD mouse spleen mononuclear cells as trigger. {yields} The islet {beta} cells were selectively destroyed by infiltrated human T cells. {yields} The model can facilitate translational research to find a cure for type 1 diabetes. -- Abstract: Type 1 diabetes (T1D) is caused by a T cell-mediated autoimmune response that leads to the loss of insulin-producing {beta} cells. The optimal preclinical testing of promising therapies would be aided by a humanized immune-mediated T1D model. We develop this model inmore » NOD-scid IL2r{gamma}{sup null} mice. The selective destruction of pancreatic islet {beta} cells was mediated by human T lymphocytes after an initial trigger was supplied by the injection of irradiated spleen mononuclear cells (SMC) from diabetic nonobese diabetic (NOD) mice. This resulted in severe insulitis, a marked loss of total {beta}-cell mass, and other related phenotypes of T1D. The migration of human T cells to pancreatic islets was controlled by the {beta} cell-produced highly conserved chemokine stromal cell-derived factor 1 (SDF-1) and its receptor C-X-C chemokine receptor (CXCR) 4, as demonstrated by in vivo blocking experiments using antibody to CXCR4. The specificity of humanized T cell-mediated immune responses against islet {beta} cells was generated by the local inflammatory microenvironment in pancreatic islets including human CD4{sup +} T cell infiltration and clonal expansion, and the mouse islet {beta}-cell-derived CD1d-mediated human iNKT activation. The selective destruction of mouse islet {beta} cells by a human T cell-mediated immune response in this humanized T1D model can mimic those observed in T1D patients. This model can provide a valuable tool for translational research into T1D.« less

Improving rice models for more reliable prediction of responses of rice yield to CO2 and temperature elevaton

USDA-ARS?s Scientific Manuscript database

Materials and Methods The simulation exercise and model improvement were implemented in phase-wise. In the first modelling activities, the model sensitivities were evaluated to given CO2 concentrations varying from 360 to 720 'mol mol-1 at an interval of 90 'mol mol-1 and air temperature increments...

Precipitation-runoff modeling system; user's manual

USGS Publications Warehouse

Leavesley, G.H.; Lichty, R.W.; Troutman, B.M.; Saindon, L.G.

1983-01-01

The concepts, structure, theoretical development, and data requirements of the precipitation-runoff modeling system (PRMS) are described. The precipitation-runoff modeling system is a modular-design, deterministic, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on streamflow, sediment yields, and general basin hydrology. Basin response to normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water balance relationships, flow regimes, flood peaks and volumes, soil-water relationships, sediment yields, and groundwater recharge. Parameter-optimization and sensitivity analysis capabilites are provided to fit selected model parameters and evaluate their individual and joint effects on model output. The modular design provides a flexible framework for continued model system enhancement and hydrologic modeling research and development. (Author 's abstract)

Modeling agricultural commodity prices and volatility in response to anticipated climate change

NASA Astrophysics Data System (ADS)

Lobell, D. B.; Tran, N.; Welch, J.; Roberts, M.; Schlenker, W.

2012-12-01

Food prices have shown a positive trend in the past decade, with episodes of rapid increases in 2008 and 2011. These increases pose a threat to food security in many regions of the world, where the poor are generally net consumers of food, and are also thought to increase risks of social and political unrest. The role of global warming in these price reversals have been debated, but little quantitative work has been done. A particular challenge in modeling these effects is that they require understanding links between climate and food supply, as well as between food supply and prices. Here we combine the anticipated effects of climate change on yield levels and volatility with an empirical competitive storage model to examine how expected climate change might affect prices and social welfare in the international food commodity market. We show that price level and volatility do increase over time in response to decreasing yield, and increasing yield variability. Land supply and storage demand both increase, but production and consumption continue to fall leading to a decrease in consumer surplus, and a corresponding though smaller increase in producer surplus.

The extraction process optimization of antioxidant polysaccharides from Marshmallow (Althaea officinalis L.) roots.

PubMed

Pakrokh Ghavi, Peyman

2015-04-01

Response surface methodology (RSM) with a central composite rotatable design (CCRD) based on five levels was employed to model and optimize four experimental operating conditions of extraction temperature (10-90 °C) and time (6-30 h), particle size (6-24 mm) and water to solid (W/S, 10-50) ratio, obtaining polysaccharides from Althaea officinalis roots with high yield and antioxidant activity. For each response, a second-order polynomial model with high R(2) values (> 0.966) was developed using multiple linear regression analysis. Results showed that the most significant (P < 0.05) extraction conditions that affect the yield and antioxidant activity of extracted polysaccharides were the main effect of extraction temperature and the interaction effect of the particle size and W/S ratio. The optimum conditions to maximize yield (10.80%) and antioxidant activity (84.09%) for polysaccharides extraction from A. officinalis roots were extraction temperature 60.90 °C, extraction time 12.01 h, particle size 12.0mm and W/S ratio of 40.0. The experimental values were found to be in agreement with those predicted, indicating the models suitability for optimizing the polysaccharides extraction conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

A model for extreme plasticity

NASA Astrophysics Data System (ADS)

Thomson, S. J.; Howell, P. D.

2016-09-01

We present a mathematical model for elastoplasticity in the regime where the applied stress greatly exceeds the yield stress. This scenario is typically found in violent impact testing, where millimetre thick metal samples are subjected to pressures on the order of 10-102 GPa, while the yield stress can be as low as 10-2 GPa. In such regimes the metal can be treated as a barotropic compressible fluid in which the strength, measured by the ratio of the yield stress to the applied stress, is negligible to lowest order. Our approach is to exploit the smallness of this ratio by treating the effects of strength as a small perturbation to a leading order barotropic model. We find that for uniaxial deformations, these additional effects give rise to features in the response of the material which differ significantly from the predictions of barotropic flow.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Productivity and sustainability of rainfed wheat-soybean system in the North China Plain: results from a long-term experiment and crop modelling

PubMed Central

Qin, Wei; Wang, Daozhong; Guo, Xisheng; Yang, Taiming; Oenema, Oene

2015-01-01

A quantitative understanding of yield response to water and nutrients is key to improving the productivity and sustainability of rainfed cropping systems. Here, we quantified the effects of rainfall, fertilization (NPK) and soil organic amendments (with straw and manure) on yields of a rainfed wheat-soybean system in the North China Plain (NCP), using 30-years’ field experimental data (1982–2012) and the simulation model-AquaCrop. On average, wheat and soybean yields were 5 and 2.5 times higher in the fertilized treatments than in the unfertilized control (CK), respectively. Yields of fertilized treatments increased and yields of CK decreased over time. NPK + manure increased yields more than NPK alone or NPK + straw. The additional effect of manure is likely due to increased availability of K and micronutrients. Wheat yields were limited by rainfall and can be increased through soil mulching (15%) or irrigation (35%). In conclusion, combined applications of fertilizer NPK and manure were more effective in sustaining high crop yields than recommended fertilizer NPK applications. Manure applications led to strong accumulation of NPK and relatively low NPK use efficiencies. Water deficiency in wheat increased over time due to the steady increase in yields, suggesting that the need for soil mulching increases. PMID:26627707

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.

Statistical optimization of polysaccharide production by submerged cultivation of Lingzhi or Reishi medicinal mushroom, Ganoderma lucidum (W.Curt.: Fr.) P. Karst. MTCC 1039 (Aphyllophoromycetideae).

PubMed

Baskar, Gurunathan; Sathya, Shree Rajesh K Lakshmi Jai; Jinnah, Riswana Begum; Sahadevan, Renganathan

2011-01-01

Response surface methodology was employed to optimize the concentration of four important cultivation media components such as cottonseed oil cake, glucose, NH4Cl, and MgSO4 for maximum medicinal polysaccharide yield by Lingzhi or Reishi medicinal mushroom, Ganoderma lucidum MTCC 1039 in submerged culture. The second-order polynomial model describing the relationship between media components and polysaccharide yield was fitted in coded units of the variables. The higher value of the coefficient of determination (R2 = 0.953) justified an excellent correlation between media components and polysaccharide yield, and the model fitted well with high statistical reliability and significance. The predicted optimum concentration of the media components was 3.0% cottonseed oil cake, 3.0% glucose, 0.15% NH4Cl, and 0.045% MgSO4, with the maximum predicted polysaccharide yield of 819.76 mg/L. The experimental polysaccharide yield at the predicted optimum media components was 854.29 mg/L, which was 4.22% higher than the predicted yield.

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

NASA Astrophysics Data System (ADS)

Li, Zhiying; Fang, Haiyan

2017-09-01

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

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

PubMed

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

2018-06-15

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

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Unidimensional and Multidimensional Models for Item Response Theory.

ERIC Educational Resources Information Center

McDonald, Roderick P.

This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…

Characterization of structural response to hypersonic boundary-layer transition

DOE PAGES

Riley, Zachary B.; Deshmukh, Rohit; Miller, Brent A.; ...

2016-05-24

The inherent relationship between boundary-layer stability, aerodynamic heating, and surface conditions makes the potential for interaction between the structural response and boundary-layer transition an important and challenging area of study in high-speed flows. This paper phenomenologically explores this interaction using a fundamental two-dimensional aerothermoelastic model under the assumption of an aluminum panel with simple supports. Specifically, an existing model is extended to examine the impact of transition onset location, transition length, and transitional overshoot in heat flux and fluctuating pressure on the structural response of surface panels. Transitional flow conditions are found to yield significantly increased thermal gradients, and theymore » can result in higher maximum panel temperatures compared to turbulent flow. Results indicate that overshoot in heat flux and fluctuating pressure reduces the flutter onset time and increases the strain energy accumulated in the panel. Furthermore, overshoot occurring near the midchord can yield average temperatures and peak displacements exceeding those experienced by the panel subject to turbulent flow. Lastly, these results suggest that fully turbulent flow does not always conservatively predict the thermo-structural response of surface panels.« less

Development of a Microsoft Excel tool for one-parameter Rasch model of continuous items: an application to a safety attitude survey.

PubMed

Chien, Tsair-Wei; Shao, Yang; Kuo, Shu-Chun

2017-01-10

Many continuous item responses (CIRs) are encountered in healthcare settings, but no one uses item response theory's (IRT) probabilistic modeling to present graphical presentations for interpreting CIR results. A computer module that is programmed to deal with CIRs is required. To present a computer module, validate it, and verify its usefulness in dealing with CIR data, and then to apply the model to real healthcare data in order to show how the CIR that can be applied to healthcare settings with an example regarding a safety attitude survey. Using Microsoft Excel VBA (Visual Basic for Applications), we designed a computer module that minimizes the residuals and calculates model's expected scores according to person responses across items. Rasch models based on a Wright map and on KIDMAP were demonstrated to interpret results of the safety attitude survey. The author-made CIR module yielded OUTFIT mean square (MNSQ) and person measures equivalent to those yielded by professional Rasch Winsteps software. The probabilistic modeling of the CIR module provides messages that are much more valuable to users and show the CIR advantage over classic test theory. Because of advances in computer technology, healthcare users who are familiar to MS Excel can easily apply the study CIR module to deal with continuous variables to benefit comparisons of data with a logistic distribution and model fit statistics.

Nonlinear response of unidirectional boron/aluminum

NASA Technical Reports Server (NTRS)

Pindera, M.-J.; Herakovich, C. T.; Becker, W.; Aboudi, J.

1990-01-01

Experimental results obtained for unidirectional boron/aluminum subjected to combined loading using off-axis tension, compression and Iosipescu shear specimens are correlated with a nonlinear micromechanics model. It is illustrated that the nonlinear response in the principal material directions is markedly influenced by the different loading modes and different ratios of the applied stress components. The observed nonlinear response under pure and combined loading is discussed in terms of initial yielding, subsequent hardening, stress-interaction effects and unloading-reloading characteristics. The micromechanics model is based on the concept of a repeating unit cell representative of the composite-at-large and employs the unified theory of Bodner and Partom to model the inelastic response of the matrix. It is shown that the employed micromechanics model is sufficiently general to predict the observed nonlinear response of unidirectional boron/aluminum with good accuracy.

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China

PubMed Central

Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981–2014 and detailed observed data of spring wheat from 1981–2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change. PMID:29099842

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China.

PubMed

Zhao, Junfang; Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981-2014 and detailed observed data of spring wheat from 1981-2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change.

Crop insurance evaluation in response to extreme events

NASA Astrophysics Data System (ADS)

Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

2013-04-01

Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results indicated that when the effect of extreme events was not considered, climate change had a low or no impact on crop yield distribution in 2020 and 2040. This resulted into an expected payout close to what observed in the present period. Conversely, the simulation of the effect of extreme events highly affected the PDFs by reducing the expected yield. This highlights that insured yield in future projections may be overestimated when not considering the impact of extremes, leading to distortions in the risk management of crop insurance companies. References Moriondo M, Giannakopoulos C, Bindi M (2011) Climate ch'ange impact assessment: the role of climate extremes in crop yield simulation. Clim Change 104:679-701 Sherrick BJ, Zanini FC, Schnitkey GD, Irwin SH (2004) Crop Insurance Valuation under Alternative Yield Distributions. American Journal of Agricultural Economics, 86:406-419. van der Linden P, Mitchell JFB (eds) (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3 PB, UK. 160 pp

Effects of diurnal temperature range and drought on wheat yield in Spain

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, S.; Rodriguez-Puebla, C.; Challinor, A. J.

2017-07-01

This study aims to provide new insight on the wheat yield historical response to climate processes throughout Spain by using statistical methods. Our data includes observed wheat yield, pseudo-observations E-OBS for the period 1979 to 2014, and outputs of general circulation models in phase 5 of the Coupled Models Inter-comparison Project (CMIP5) for the period 1901 to 2099. In investigating the relationship between climate and wheat variability, we have applied the approach known as the partial least-square regression, which captures the relevant climate drivers accounting for variations in wheat yield. We found that drought occurring in autumn and spring and the diurnal range of temperature experienced during the winter are major processes to characterize the wheat yield variability in Spain. These observable climate processes are used for an empirical model that is utilized in assessing the wheat yield trends in Spain under different climate conditions. To isolate the trend within the wheat time series, we implemented the adaptive approach known as Ensemble Empirical Mode Decomposition. Wheat yields in the twenty-first century are experiencing a downward trend that we claim is a consequence of widespread drought over the Iberian Peninsula and an increase in the diurnal range of temperature. These results are important to inform about the wheat vulnerability in this region to coming changes and to develop adaptation strategies.

Biogas and methane yield in response to co- and separate digestion of biomass wastes.

PubMed

Adelard, Laetitia; Poulsen, Tjalfe G; Rakotoniaina, Volana

2015-01-01

The impact of co-digestion as opposed to separate digestion, on biogas and methane yield (apparent synergetic effects) was investigated for three biomass materials (pig manure, cow manure and food waste) under mesophilic conditions over a 36 day period. In addition to the three biomass materials (digested separately), 13 biomass mixtures (co-digested) were used. Two approaches for modelling biogas and methane yield during co-digestion, based on volatile solids concentration and ultimate gas and methane potentials, were evaluated. The dependency of apparent synergetic effects on digestion time and biomass mixture composition was further assessed using measured cumulative biogas and methane yields and specific biogas and methane generation rates. Results indicated that it is possible, based on known volatile solids concentration and ultimate biogas or methane yields for a set of biomass materials digested separately, to accurately estimate gas yields for biomass mixtures made from these materials using calibrated models. For the biomass materials considered here, modelling indicated that the addition of pig manure is the main cause of synergetic effects. Co-digestion generally resulted in improved ultimate biogas and methane yields compared to separate digestion. Biogas and methane production was furthermore significantly higher early (0-7 days) and to some degree also late (above 20 days) in the digestion process during co-digestion. © The Author(s) 2014.

Response of wheat yield in Spain to large-scale patterns

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, Sara; Rodriguez-Puebla, Concepcion

2016-04-01

Crops are vulnerable to extreme climate conditions as drought, heat stress and frost risk. In previous study we have quantified the influence of these climate conditions for winter wheat in Spain (Hernandez-Barrera et al. 2015). The climate extremes respond to large-scale atmospheric and oceanic patterns. Therefore, a question emerges in our investigation: How large-scale patterns affect wheat yield? Obtaining and understanding these relationships require different approaches. In this study, we first obtained the leading mode of observed wheat yield variability to characterize the common variability over different provinces in Spain. Then, the wheat variability is related to different modes of mean sea level pressure, jet stream and sea surface temperature by using Partial Least-Squares, which captures the relevant climate drivers accounting for variations in wheat yield from sowing to harvesting. We used the ERA-Interim reanalysis data and the Extended Reconstructed Sea Surface Temperature (SST) (ERSST v3b). The derived model provides insight about the teleconnections between wheat yield and atmospheric and oceanic circulations, which is considered to project the wheat yield trend under global warming using outputs of twelve climate models corresponding to the Coupled Models Intercomparison Project phase 5 (CMIP5). Hernandez-Barrera S., C. Rodríguez-Puebla and A.J. Challinor. Effects of diurnal temperature range and drought on wheat yield in Spain. Theoretical and Applied Climatology (submitted)

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.

PubMed

Pezzopane, José Ricardo Macedo; da Cruz, Pedro Gomes; Santos, Patricia Menezes; Bosi, Cristiam; de Araujo, Leandro Coelho

2014-09-01

The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42″ S, longitude 47°50'28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, potential evapotranspiration or degree-days) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on degree-days corrected by the water deficit factor.

Weed Diversity Affects Soybean and Maize Yield in a Long Term Experiment in Michigan, USA.

PubMed

Ferrero, Rosana; Lima, Mauricio; Davis, Adam S; Gonzalez-Andujar, Jose L

2017-01-01

Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability.

Weed Diversity Affects Soybean and Maize Yield in a Long Term Experiment in Michigan, USA

PubMed Central

Ferrero, Rosana; Lima, Mauricio; Davis, Adam S.; Gonzalez-Andujar, Jose L.

2017-01-01

Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability. PMID:28286509

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

NASA Astrophysics Data System (ADS)

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 various regions across the globe and with different remote sensing inputs, given its interpretability, low data requirement, flexibility, and high correlation with in situ data.

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

NASA Technical Reports Server (NTRS)

Jones, M.R; Singels, A.; Ruane, A. C.

2015-01-01

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Predicting the Impacts of Climate Change on Agricultural Yields and Water Resources in the Maumee River Watershed

NASA Astrophysics Data System (ADS)

Nagelkirk, R. L.; Kendall, A. D.; Basso, B.; Hyndman, D. W.

2012-12-01

Climate change will likely have considerable effects on agriculture in the Midwestern United States. Under current climate projections, end-of-century temperatures rise by approximately 4 C, while precipitation stays relatively unchanged despite a potential increase in heavy rainfall events. These trends have already been observed over the last century: rising temperatures have extended the growing season two days per decade and heavy rainfall events have become twice as common. In an effort to understand the likely effects of climate change on agriculture, maize and soybean yields in the Maumee River Watershed were simulated using the Systems Approach to Land Use Sustainability (SALUS) crop model. SALUS calculates daily crop growth in response to changing climate, soil, and management conditions. We test the hypotheses that 1) despite any positive effects of CO2 fertilization and allowing for higher yielding varieties, longer and warmer growing seasons will lead to excessive water- and heat-stress, lowering yields under current management practices, and 2) that double-cropping maize and soybeans successively in the same season to offset these losses may become feasible if sufficient late-season soil moisture is made available. Outputs of daily Leaf Area Index (LAI) and root mass from a range of SALUS models are then distributed spatially to drive regional hydrologic simulations using the Integrated Landscape Hydrology Model (ILHM). These coupled simulations demonstrate the response of streamflow and groundwater levels to different management strategies.

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

A comprehensive constitutive law for waxy crude oil: a thixotropic yield stress fluid.

PubMed

Dimitriou, Christopher J; McKinley, Gareth H

2014-09-21

Guided by a series of discriminating rheometric tests, we develop a new constitutive model that can quantitatively predict the key rheological features of waxy crude oils. We first develop a series of model crude oils, which are characterized by a complex thixotropic and yielding behavior that strongly depends on the shear history of the sample. We then outline the development of an appropriate preparation protocol for carrying out rheological measurements, to ensure consistent and reproducible initial conditions. We use RheoPIV measurements of the local kinematics within the fluid under imposed deformations in order to validate the selection of a particular protocol. Velocimetric measurements are also used to document the presence of material instabilities within the model crude oil under conditions of imposed steady shearing. These instabilities are a result of the underlying non-monotonic steady flow curve of the material. Three distinct deformation histories are then used to probe the material's constitutive response. These deformations are steady shear, transient response to startup of steady shear with different aging times, and large amplitude oscillatory shear (LAOS). The material response to these three different flows is used to motivate the development of an appropriate constitutive model. This model (termed the IKH model) is based on a framework adopted from plasticity theory and implements an additive strain decomposition into characteristic reversible (elastic) and irreversible (plastic) contributions, coupled with the physical processes of isotropic and kinematic hardening. Comparisons of experimental to simulated response for all three flows show good quantitative agreement, validating the chosen approach for developing constitutive models for this class of materials.

Biocontrol in an impulsive predator-prey model.

PubMed

Terry, Alan J

2014-10-01

We study a model for biological pest control (or "biocontrol") in which a pest population is controlled by a program of periodic releases of a fixed yield of predators that prey on the pest. Releases are represented as impulsive increases in the predator population. Between releases, predator-pest dynamics evolve according to a predator-prey model with some fairly general properties: the pest population grows logistically in the absence of predation; the predator functional response is either of Beddington-DeAngelis type or Holling type II; the predator per capita birth rate is bounded above by a constant multiple of the predator functional response; and the predator per capita death rate is allowed to be decreasing in the predator functional response and increasing in the predator population, though the special case in which it is constant is permitted too. We prove that, when the predator functional response is of Beddington-DeAngelis type and the predators are not sufficiently voracious, then the biocontrol program will fail to reduce the pest population below a particular economic threshold, regardless of the frequency or yield of the releases. We prove also that our model possesses a pest-eradication solution, which is both locally and globally stable provided that predators are sufficiently voracious and that releases occur sufficiently often. We establish, curiously, that the pest-eradication solution can be locally stable whilst not being globally stable, the upshot of which is that, if we delay a biocontrol response to a new pest invasion, then this can change the outcome of the response from pest eradication to pest persistence. Finally, we state a number of specific examples for our model, and, for one of these examples, we corroborate parts of our analysis by numerical simulations. Copyright © 2014 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

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

NASA Technical Reports Server (NTRS)

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

Estimating the responses of winter wheat yields to moisture variations in the past 35 years in Jiangsu Province of China

PubMed Central

Ding, Jinfeng; Li, Chunyan

2018-01-01

Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen’s Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21st century were more favorable than in the last 20 years of the 20th century for wheat production in Jiangsu. PMID:29329353

Estimating the responses of winter wheat yields to moisture variations in the past 35 years in Jiangsu Province of China.

PubMed

Xu, Xiangying; Gao, Ping; Zhu, Xinkai; Guo, Wenshan; Ding, Jinfeng; Li, Chunyan

2018-01-01

Jiangsu is an important agricultural province in China. Winter wheat, as the second major grain crop in the province, is greatly affected by moisture variations. The objective of this study was to investigate whether there were significant trends in changes in the moisture conditions during wheat growing seasons over the past decades and how the wheat yields responded to different moisture levels by means of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The study started with a trend analysis and quantification of the moisture conditions with the Mann-Kendall test and Sen's Slope method, respectively. Then, correlation analysis was carried out to determine the relationship between de-trended wheat yields and multi-scalar SPEI. Finally, a multivariate panel regression model was established to reveal the quantitative yield responses to moisture variations. The results showed that the moisture conditions in Jiangsu were generally at a normal level, but this century appeared slightly drier in because of the relatively high temperatures. There was a significant correlation between short time scale SPEI values and wheat yields. Among the three critical stages of wheat development, the SPEI values in the late growth stage (April-June) had a closer linkage to the yields than in the seedling stage (October-November) and the over-wintering stage (December-February). Moreover, the yield responses displayed an asymmetric characteristic, namely, moisture excess led to higher yield losses compared to moisture deficit in this region. The maximum yield increment could be obtained under the moisture level of slight drought according to the 3-month SPEI at the late growth stage, while extreme wetting resulted in the most severe yield losses. The moisture conditions in the first 15 years of the 21st century were more favorable than in the last 20 years of the 20th century for wheat production in Jiangsu.

Atmospheric CO2 concentration impacts on maize yield performance under dry conditions: do crop model simulate it right ?

NASA Astrophysics Data System (ADS)

Durand, Jean-Louis; Delusca, Kénel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Jochaim Weigel, Hans; Ruane, Alex C.; Rosenzweig, Cynthia; Jones, Jim; Ahuja, Laj; Anapalli, Saseendran; Basso, Bruno; Baron, Christian; Bertuzzi, Patrick; Biernath, Christian; Deryng, Delphine; Ewert, Frank; Gaiser, Thomas; Gayler, Sebastian; Heinlein, Florian; Kersebaum, Kurt Christian; Kim, Soo-Hyung; Müller, Christoph; Nendel, Claas; Olioso, Albert; Priesack, Eckhart; Ramirez-Villegas, Julian; Ripoche, Dominique; Rötter, Reimund; Seidel, Sabine; Srivastava, Amit; Tao, Fulu; Timlin, Dennis; Twine, Tracy; Wang, Enli; Webber, Heidi; Zhao, Shigan

2017-04-01

In most regions of the world, maize yields are at risk of be reduced due to rising temperatures and reduced water availability. Rising temperature tends to reduce the length of the growth cycle and the amount of intercepted solar energy. Water deficits reduce the leaf area expansion, photosynthesis and sometimes, with an even more pronounced impact, severely reduce the efficiency of kernel set. In maize, the major consequence of atmospheric CO2 concentration ([CO2]) is the stomatal closure-induced reduction of leaf transpiration rate, which tends to mitigate those negative impacts. Indeed FACE studies report significant positive responses to CO2 of maize yields (and other C4 crops) under dry conditions only. Given the projections by climatologists (typically doubling of [CO2] by the end of this century) projected impacts must take that climate variable into account. However, several studies show a large incertitude in estimating the impact of increasing [CO2] on maize remains using the main crop models. The aim of this work was to compare the simulations of different models using input data from a FACE experiment conducted in Braunschweig during 2 years under limiting and non-limiting water conditions. Twenty modelling groups using different maize models were given the same instructions and input data. Following calibration of cultivar parameters under non-limiting water conditions and under ambient [CO2] treatments of both years, simulations were undertaken for the other treatments: High [ CO2 ] (550 ppm) 2007 and 2008 in both irrigation regimes, and DRY AMBIENT 2007 and 2008. Only under severe water deficits did models simulate an increase in yield for CO2 enrichment, which was associated with higher harvest index and, for those models which simulated it, higher grain number. However, the CO2 enhancement under water deficit simulated by the 20 models was 20 % at most and 10 % on average only, i.e. twice less than observed in that experiment. As in the experiment, the simulated impact of [CO2 ] on water use was negligible, with a general displacement of the water deficit toward later phases of the crop along with longer green leaf area duration at reduced transpiration rate. In general models which used explicit response functions of stomatal conductance to [CO2] performed significantly better than those which did not. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase. We shall discuss the various ways of simulating the response of stomatal conductance to [CO2] and the response of kernel set to water deficits.

Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation?

PubMed

Humpenöder, Florian; Popp, Alexander; Stevanovic, Miodrag; Müller, Christoph; Bodirsky, Benjamin Leon; Bonsch, Markus; Dietrich, Jan Philipp; Lotze-Campen, Hermann; Weindl, Isabelle; Biewald, Anne; Rolinski, Susanne

2015-06-02

Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling.

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

NASA Astrophysics Data System (ADS)

Kaneko, D.

2017-12-01

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

Response of winter and spring wheat grain yields to meteorological variation

NASA Technical Reports Server (NTRS)

Feyerherm, A. M.; Kanemasu, E. T.; Paulsen, G. M.

1977-01-01

Mathematical models which quantify the relation of wheat yield to selected weather-related variables are presented. Other sources of variation (amount of applied nitrogen, improved varieties, cultural practices) have been incorporated in the models to explain yield variation both singly and in combination with weather-related variables. Separate models were developed for fall-planted (winter) and spring-planted (spring) wheats. Meteorological variation is observed, basically, by daily measurements of minimum and maximum temperatures, precipitation, and tabled values of solar radiation at the edge of the atmosphere and daylength. Two different soil moisture budgets are suggested to compute simulated values of evapotranspiration; one uses the above-mentioned inputs, the other uses the measured temperatures and precipitation but replaces the tabled values (solar radiation and daylength) by measured solar radiation and satellite-derived multispectral scanner data to estimate leaf area index. Weather-related variables are defined by phenological stages, rather than calendar periods, to make the models more universally applicable.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

Optimizing rice yields while minimizing yield-scaled global warming potential.

PubMed

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.

Data-driven reduced order models for effective yield strength and partitioning of strain in multiphase materials

NASA Astrophysics Data System (ADS)

Latypov, Marat I.; Kalidindi, Surya R.

2017-10-01

There is a critical need for the development and verification of practically useful multiscale modeling strategies for simulating the mechanical response of multiphase metallic materials with heterogeneous microstructures. In this contribution, we present data-driven reduced order models for effective yield strength and strain partitioning in such microstructures. These models are built employing the recently developed framework of Materials Knowledge Systems that employ 2-point spatial correlations (or 2-point statistics) for the quantification of the heterostructures and principal component analyses for their low-dimensional representation. The models are calibrated to a large collection of finite element (FE) results obtained for a diverse range of microstructures with various sizes, shapes, and volume fractions of the phases. The performance of the models is evaluated by comparing the predictions of yield strength and strain partitioning in two-phase materials with the corresponding predictions from a classical self-consistent model as well as results of full-field FE simulations. The reduced-order models developed in this work show an excellent combination of accuracy and computational efficiency, and therefore present an important advance towards computationally efficient microstructure-sensitive multiscale modeling frameworks.

Testing the responses of four wheat crop models to heat stress at anthesis and grain filling.

PubMed

Liu, Bing; Asseng, Senthold; Liu, Leilei; Tang, Liang; Cao, Weixing; Zhu, Yan

2016-05-01

Higher temperatures caused by future climate change will bring more frequent heat stress events and pose an increasing risk to global wheat production. Crop models have been widely used to simulate future crop productivity but are rarely tested with observed heat stress experimental datasets. Four wheat models (DSSAT-CERES-Wheat, DSSAT-Nwheat, APSIM-Wheat, and WheatGrow) were evaluated with 4 years of environment-controlled phytotron experimental datasets with two wheat cultivars under heat stress at anthesis and grain filling stages. Heat stress at anthesis reduced observed grain numbers per unit area and individual grain size, while heat stress during grain filling mainly decreased the size of the individual grains. The observed impact of heat stress on grain filling duration, total aboveground biomass, grain yield, and grain protein concentration (GPC) varied depending on cultivar and accumulated heat stress. For every unit increase of heat degree days (HDD, degree days over 30 °C), grain filling duration was reduced by 0.30-0.60%, total aboveground biomass was reduced by 0.37-0.43%, and grain yield was reduced by 1.0-1.6%, but GPC was increased by 0.50% for cv Yangmai16 and 0.80% for cv Xumai30. The tested crop simulation models could reproduce some of the observed reductions in grain filling duration, final total aboveground biomass, and grain yield, as well as the observed increase in GPC due to heat stress. Most of the crop models tended to reproduce heat stress impacts better during grain filling than at anthesis. Some of the tested models require improvements in the response to heat stress during grain filling, but all models need improvements in simulating heat stress effects on grain set during anthesis. The observed significant genetic variability in the response of wheat to heat stress needs to be considered through cultivar parameters in future simulation studies. © 2016 John Wiley & Sons Ltd.

Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications.

PubMed

Schäffer, Beat; Pieren, Reto; Mendolia, Franco; Basner, Mathias; Brink, Mark

2017-05-01

Noise exposure-response relationships are used to estimate the effects of noise on individuals or a population. Such relationships may be derived from independent or repeated binary observations, and modeled by different statistical methods. Depending on the method by which they were established, their application in population risk assessment or estimation of individual responses may yield different results, i.e., predict "weaker" or "stronger" effects. As far as the present body of literature on noise effect studies is concerned, however, the underlying statistical methodology to establish exposure-response relationships has not always been paid sufficient attention. This paper gives an overview on two statistical approaches (subject-specific and population-averaged logistic regression analysis) to establish noise exposure-response relationships from repeated binary observations, and their appropriate applications. The considerations are illustrated with data from three noise effect studies, estimating also the magnitude of differences in results when applying exposure-response relationships derived from the two statistical approaches. Depending on the underlying data set and the probability range of the binary variable it covers, the two approaches yield similar to very different results. The adequate choice of a specific statistical approach and its application in subsequent studies, both depending on the research question, are therefore crucial.

A Scaling Model for the Anthropocene Climate Variability with Projections to 2100

NASA Astrophysics Data System (ADS)

Hébert, Raphael; Lovejoy, Shaun

2017-04-01

The determination of the climate sensitivity to radiative forcing is a fundamental climate science problem with important policy implications. We use a scaling model, with a limited set of parameters, which can directly calculate the forced globally-average surface air temperature response to anthropogenic and natural forcings. At timescales larger than an inner scale τ, which we determine as the ocean-atmosphere coupling scale at around 2 years, the global system responds, approximately, linearly, so that the variability may be decomposed into additive forced and internal components. The Ruelle response theory extends the classical linear response theory for small perturbations to systems far from equilibrium. Our model thus relates radiative forcings to a forced temperature response by convolution with a suitable Green's function, or climate response function. Motivated by scaling symmetries which allow for long range dependence, we assume a general scaling form, a scaling climate response function (SCRF) which is able to produce a wide range of responses: a power-law truncated at τ. This allows us to analytically calculate the climate sensitivity at different time scales, yielding a one-to-one relation from the transient climate response to the equilibrium climate sensitivity which are estimated, respectively, as 1.6+0.3-0.2K and 2.4+1.3-0.6K at the 90 % confidence level. The model parameters are estimated within a Bayesian framework, with a fractional Gaussian noise error model as the internal variability, from forcing series, instrumental surface temperature datasets and CMIP5 GCMs Representative Concentration Pathways (RCP) scenario runs. This observation based model is robust and projections for the coming century are made following the RCP scenario 2.6, 4.5 and 8.5, yielding in the year 2100, respectively : 1.5 +0.3)_{-0.2K, 2.3 ± 0.4 K and 4.0 ± 0.6 K at the 90 % confidence level. For comparison, the associated projections from a CMIP5 multi-model ensemble(MME) (32 models) are: 1.7 ± 0.8 K, 2.6 ± 0.8 K and 4.8 ± 1.3 K. Therefore, our projection uncertainty is less than half the structural uncertainty of this CMIP5 MME.

A Global Analysis of Light and Charge Yields in Liquid Xenon

DOE PAGES

Lenardo, Brian; Kazkaz, Kareem; Manalaysay, Aaron; ...

2015-11-04

Here, we present an updated model of light and charge yields from nuclear recoils in liquid xenon with a simultaneously constrained parameter set. A global analysis is performed using measurements of electron and photon yields compiled from all available historical data, as well as measurements of the ratio of the two. These data sweep over energies from keV and external applied electric fields from V/cm. The model is constrained by constructing global cost functions and using a simulated annealing algorithm and a Markov Chain Monte Carlo approach to optimize and find confidence intervals on all free parameters in the model.more » This analysis contrasts with previous work in that we do not unnecessarily exclude datasets nor impose artificially conservative assumptions, do not use spline functions, and reduce the number of parameters used in NEST v 0.98. Here, we report our results and the calculated best-fit charge and light yields. These quantities are crucial to understanding the response of liquid xenon detectors in the energy regime important for rare event searches such as the direct detection of dark matter particles.« less

A constitutive model for AS4/PEEK thermoplastic composites under cyclic loading

NASA Technical Reports Server (NTRS)

Rui, Yuting; Sun, C. T.

1990-01-01

Based on the basic and essential features of the elastic-plastic response of the AS4/PEEK thermoplastic composite subjected to off-axis cyclic loadings, a simple rate-independent constitutive model is proposed to describe the orthotropic material behavior for cyclic loadings. A one-parameter memory surface is introduced to distinguish the virgin deformation and the subsequent deformation process and to characterize the loading range effect. Cyclic softening is characterized by the change of generalized plastic modulus. By the vanishing yield surface assumption, a yield criterion is not needed and it is not necessary to consider loading and unloading separately. The model is compared with experimental results and good agreement is obtained.

Olive response to water availability: yield response functions, soil water content indicators and evaluation of adaptability to climate change

NASA Astrophysics Data System (ADS)

Riccardi, Maria; Alfieri, Silvia Maria; Basile, Angelo; Bonfante, Antonello; Menenti, Massimo; Monaco, Eugenia; De Lorenzi, Francesca

2013-04-01

Climate evolution, with the foreseen increase of temperature and frequency of drought events during the summer, could cause significant changes in the availability of water resources specially in the Mediterranean region. European countries need to encourage sustainable agriculture practices, reducing inputs, especially of water, and minimizing any negative impact on crop quantity and quality. Olive is an important crop in the Mediterranean region that has traditionally been cultivated with no irrigation and is known to attain acceptable production under dry farming. Therefore this crop will not compete for foreseen reduced water resources. However, a good quantitative knowledge must be available about effects of reduced precipitation and water availability on yield. Yield response functions, coupled with indicators of soil water availability, provide a quantitative description of the cultivar- specific behavior in relation to hydrological conditions. Yield response functions of 11 olive cultivars, typical of Mediterranean environment, were determined using experimental data (unpublished or reported in scientific literature). The yield was expressed as relative yield (Yr); the soil water availability was described by means of different indicators: relative soil water deficit (RSWD), relative evapotranspiration (RED) and transpiration deficit (RTD). Crops can respond nonlinearly to changes in their growing conditions and exhibit threshold responses, so for the yield functions of each olive cultivar both linear regression and threshold-slope models were considered to evaluate the best fit. The level of relative yield attained in rain-fed conditions was identified and defined as the acceptable yield level (Yrrainfed). The value of the indicator (RSWD, RED and RTD) corresponding to Yrrainfed was determined for each cultivar and indicated as the critical value of water availability. The error in the determination of the critical value was estimated. By means of a simulation model of the water flow in the soil-plant-atmosphere system, the indicators of soil water availability were calculated for different soil units in an area of Southern Italy, traditionally cultivated with olive. Simulations were performed for two climate scenarios: reference (1961-90) and future climate (2021-50). The potentiality of the indicators RSWD, RED and RTD to describe soil water availability was evaluated using simulated and experimental data. The analysis showed that RED values were correlated to RTD. The analysis demonstrated that RTD was more effective than RED in representing crop water availability RSWD is very well correlated to RTD and the degree of correlation depends of the period of deficit considered. The probability of adaptation of each cultivar was calculated for both climatic periods by comparing the critical values (and their error distribution) with soil availability indicators. Keywords: Olea europaea, soil water deficit, water availability critical value. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Immunity to viruses: learning from successful human vaccines.

PubMed

Pulendran, Bali; Oh, Jason Z; Nakaya, Helder I; Ravindran, Rajesh; Kazmin, Dmitri A

2013-09-01

For more than a century, immunologists and vaccinologists have existed in parallel universes. Immunologists have for long reveled in using 'model antigens', such as chicken egg ovalbumin or nitrophenyl haptens, to study immune responses in model organisms such as mice. Such studies have yielded many seminal insights about the mechanisms of immune regulation, but their relevance to humans has been questioned. In another universe, vaccinologists have relied on human clinical trials to assess vaccine efficacy, but have done little to take advantage of such trials for studying the nature of immune responses to vaccination. The human model provides a nexus between these two universes, and recent studies have begun to use this model to study the molecular profile of innate and adaptive responses to vaccination. Such 'systems vaccinology' studies are beginning to provide mechanistic insights about innate and adaptive immunity in humans. Here, we present an overview of such studies, with particular examples from studies with the yellow fever and the seasonal influenza vaccines. Vaccination with the yellow fever vaccine causes a systemic acute viral infection and thus provides an attractive model to study innate and adaptive responses to a primary viral challenge. Vaccination with the live attenuated influenza vaccine causes a localized acute viral infection in mucosal tissues and induces a recall response, since most vaccinees have had prior exposure to influenza, and thus provides a unique opportunity to study innate and antigen-specific memory responses in mucosal tissues and in the blood. Vaccination with the inactivated influenza vaccine offers a model to study immune responses to an inactivated immunogen. Studies with these and other vaccines are beginning to reunite the estranged fields of immunology and vaccinology, yielding unexpected insights about mechanisms of viral immunity. Vaccines that have been proven to be of immense benefit in saving lives offer us a new fringe benefit: lessons in viral immunology. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Integrating predictive information into an agro-economic model to guide agricultural management

NASA Astrophysics Data System (ADS)

Zhang, Y.; Block, P.

2016-12-01

Skillful season-ahead climate predictions linked with responsive agricultural planning and management have the potential to reduce losses, if adopted by farmers, particularly for rainfed-dominated agriculture such as in Ethiopia. Precipitation predictions during the growing season in major agricultural regions of Ethiopia are used to generate predicted climate yield factors, which reflect the influence of precipitation amounts on crop yields and serve as inputs into an agro-economic model. The adapted model, originally developed by the International Food Policy Research Institute, produces outputs of economic indices (GDP, poverty rates, etc.) at zonal and national levels. Forecast-based approaches, in which farmers' actions are in response to forecasted conditions, are compared with no-forecast approaches in which farmers follow business as usual practices, expecting "average" climate conditions. The effects of farmer adoption rates, including the potential for reduced uptake due to poor predictions, and increasing forecast lead-time on economic outputs are also explored. Preliminary results indicate superior gains under forecast-based approaches.

Annual Corn Yield Estimation through Multi-temporal MODIS Data

NASA Astrophysics Data System (ADS)

Shao, Y.; Zheng, B.; Campbell, J. B.

2013-12-01

This research employed 13 years of the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate annual corn yield for the Midwest of the United States. The overall objective of this study was to examine if annual corn yield could be accurately predicted using MODIS time-series NDVI (Normalized Difference Vegetation Index) and ancillary data such monthly precipitation and temperature. MODIS-NDVI 16-Day composite images were acquired from the USGS EROS Data Center for calendar years 2000 to 2012. For the same time-period, county level corn yield statistics were obtained from the National Agricultural Statistics Service (NASS). The monthly precipitation and temperature measures were derived from Precipitation-Elevation Regressions on Independent Slopes Model (PRISM) climate data. A cropland mask was derived using 2006 National Land Cover Database. For each county and within the cropland mask, the MODIS-NDVI time-series data and PRISM climate data were spatially averaged, at their respective time steps. We developed a random forest predictive model with the MODIS-NDVI and climate data as predictors and corn yield as response. To assess the model accuracy, we used twelve years of data as training and the remaining year as hold-out testing set. The training and testing procedures were repeated 13 times. The R2 ranged from 0.72 to 0.83 for testing years. It was also found that the inclusion of climate data did not improve the model predictive performance. MODIS-NDVI time-series data alone might provide sufficient information for county level corn yield prediction.

Crop responses to climatic variation

PubMed Central

Porter, John R; Semenov, Mikhail A

2005-01-01

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal resolution. This paper demonstrates the impacts of climate variability for crop production in a number of crops. Increasing temperature and precipitation variability increases the risks to yield, as shown via computer simulation and experimental studies. The issue of food quality has not been given sufficient importance when assessing the impact of climate change for food and this is addressed. Using simulation models of wheat, the concentration of grain protein is shown to respond to changes in the mean and variability of temperature and precipitation events. The paper concludes with discussion of adaptation possibilities for crops in response to drought and argues that characters that enable better exploration of the soil and slower leaf canopy expansion could lead to crop higher transpiration efficiency. PMID:16433091

Modelling and validation of magnetorheological brake responses using parametric approach

NASA Astrophysics Data System (ADS)

Z, Zainordin A.; A, Abdullah M.; K, Hudha

2013-12-01

Magnetorheological brake (MR Brake) is one x-by-wire systems which performs better than conventional brake systems. MR brake consists of a rotating disc that is immersed with Magnetorheological Fluid (MR Fluid) in an enclosure of an electromagnetic coil. The applied magnetic field will increase the yield strength of the MR fluid where this fluid was used to decrease the speed of the rotating shaft. The purpose of this paper is to develop a mathematical model to represent MR brake with a test rig. The MR brake model is developed based on actual torque characteristic which is coupled with motion of a test rig. Next, the experimental are performed using MR brake test rig and obtained three output responses known as angular velocity response, torque response and load displacement response. Furthermore, the MR brake was subjected to various current. Finally, the simulation results of MR brake model are then verified with experimental results.

A Multidimensional Ideal Point Item Response Theory Model for Binary Data.

PubMed

Maydeu-Olivares, Albert; Hernández, Adolfo; McDonald, Roderick P

2006-12-01

We introduce a multidimensional item response theory (IRT) model for binary data based on a proximity response mechanism. Under the model, a respondent at the mode of the item response function (IRF) endorses the item with probability one. The mode of the IRF is the ideal point, or in the multidimensional case, an ideal hyperplane. The model yields closed form expressions for the cell probabilities. We estimate and test the goodness of fit of the model using only information contained in the univariate and bivariate moments of the data. Also, we pit the new model against the multidimensional normal ogive model estimated using NOHARM in four applications involving (a) attitudes toward censorship, (b) satisfaction with life, (c) attitudes of morality and equality, and (d) political efficacy. The normal PDF model is not invariant to simple operations such as reverse scoring. Thus, when there is no natural category to be modeled, as in many personality applications, it should be fit separately with and without reverse scoring for comparisons.

[Optimization of ultrasonic-assisted extraction of total flavonoids from leaves of the Artocarpus heterophyllus by response surface methodology].

PubMed

Wang, Hong-wu; Liu, Yan-qing; Wang, Yuan-hong

2011-07-01

To investigate the ultrasonic-assisted extract on of total flavonoids from leaves of the Artocarpus heterophyllus. Investigated the effects of ethanol concentration, extraction time, and liquid-solid ratio on flavonoids yield. A 17-run response surface design involving three factors at three levels was generated by the Design-Expert software and experimental data obtained were subjected to quadratic regression analysis to create a mathematical model describing flavonoids extraction. The optimum ultrasonic assisted extraction conditions were: ethanol volume fraction 69.4% and liquid-solid ratio of 22.6:1 for 32 min. Under these optimized conditions, the yield of flavonoids was 7.55 mg/g. The Box-Behnken design and response surface analysis can well optimize the ultrasonic-assisted extraction of total flavonoids from Artocarpus heterophyllus.

The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations

USDA-ARS?s Scientific Manuscript database

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during...

A cell-centered Lagrangian finite volume approach for computing elasto-plastic response of solids in cylindrical axisymmetric geometries

NASA Astrophysics Data System (ADS)

Sambasivan, Shiv Kumar; Shashkov, Mikhail J.; Burton, Donald E.

2013-03-01

A finite volume cell-centered Lagrangian formulation is presented for solving large deformation problems in cylindrical axisymmetric geometries. Since solid materials can sustain significant shear deformation, evolution equations for stress and strain fields are solved in addition to mass, momentum and energy conservation laws. The total strain-rate realized in the material is split into an elastic and plastic response. The elastic and plastic components in turn are modeled using hypo-elastic theory. In accordance with the hypo-elastic model, a predictor-corrector algorithm is employed for evolving the deviatoric component of the stress tensor. A trial elastic deviatoric stress state is obtained by integrating a rate equation, cast in the form of an objective (Jaumann) derivative, based on Hooke's law. The dilatational response of the material is modeled using an equation of state of the Mie-Grüneisen form. The plastic deformation is accounted for via an iterative radial return algorithm constructed from the J2 von Mises yield condition. Several benchmark example problems with non-linear strain hardening and thermal softening yield models are presented. Extensive comparisons with representative Eulerian and Lagrangian hydrocodes in addition to analytical and experimental results are made to validate the current approach.

Palm-based medium-and-long-chain triacylglycerol (P-MLCT): production via enzymatic interesterification and optimization using response surface methodology (RSM).

PubMed

Lee, Yee-Ying; Tang, Teck-Kim; Phuah, Eng-Tong; Karim, Nur Azwani Ab; Alwi, Siti Maslina Mohd; Lai, Oi-Ming

2015-02-01

Structured lipid such as medium-and long-chain triacylglycerol (MLCT) is claimed to be able to suppress body fat accumulation and be used to manage obesity. Response surface methodology (RSM) with four factors and three levels (+1,0,-1) faced centered composite design (FCCD) was employed for optimization of the enzymatic interesterification conditions of palm-based MLCT (P-MLCT) production. The effect of the four variables namely: substrate ratio palm kernel oil: palm oil, PKO:PO (40:60-100:0 w/w), temperature (50-70 °C), reaction time (0.5-7.5 h) and enzyme load (5-15 % w/w) on the P-MLCT yield (%) and by products (%) produced were investigated. The responses were determined via acylglycerol composition obtained from high performance liquid chromatography. Well-fitted models were successfully established for both responses: P-MLCT yield (R (2) = 0.9979) and by-products (R (2) = 0.9892). The P-MLCT yield was significantly (P < 0.05) affected by substrate ratio, reaction time and reaction temperature but not enzyme load (P > 0.05). Substrate ratio PKO: PO (100:0 w/w) gave the highest yield of P-MLCT (61 %). Nonetheless, substrate ratio of PKO: PO (90:10w/w) was chosen to improve the fatty acid composition of the P-MLCT. The optimized conditions for substrate ratio PKO: PO (90:10 w/w) was 7.26 h, 50 °C and 5 % (w/w) Lipozyme TLIM lipase, which managed to give 60 % yields of P-MLCT. Up scaled results in stirred tank batch reactor gave similar yields as lab scale. A 20 % increase in P-MLCT yield was obtained via RSM. The effect of enzymatic interesterification on the physicochemical properties of PKO:PO (90:10 w/w) were also studied. Thermoprofile showed that the P-MLCT oil melted below body temperature of 37 °C.

A dose-response relationship for marketable yield reduction of two lettuce (Lactuca sativa L.) cultivars exposed to tropospheric ozone in Southern Europe.

PubMed

Marzuoli, Riccardo; Finco, Angelo; Chiesa, Maria; Gerosa, Giacomo

2017-12-01

The present study investigated the response to ozone (O 3 ) of two cultivars (cv.'Romana' and cv. 'Canasta') of irrigated lettuce grown in an open-top chamber (OTC) experiment in Mediterranean conditions. Two different levels of O 3 were applied, ambient O 3 in non-filtered OTCs (NF-OTCs) and -40% of ambient O 3 in charcoal-filtered OTCs (CF-OTCs), during four consecutive growing cycles. At the end of each growing cycle, the marketable yield (fresh biomass) was assessed while during the growing periods, measurements of the stomatal conductance at leaf level were performed and used to define a stomatal conductance model for calculation of the phytotoxic ozone dose (POD) absorbed by the plants.Results showed that O 3 caused statistically significant yield reductions in the first and in the last growing cycle. In general, the marketable yield of the NF-OTC plants was always lower than the CF-OTC plants for both cultivars, with mean reductions of -18.5 and -14.5% for 'Romana' and 'Canasta', respectively. On the contrary, there was no statistically significant difference in marketable yield due to the cultivar factor or to the interaction between O 3 and cultivar in any of the growing cycle performed.Dose-response relationships for the marketable relative yield based on the POD values were calculated according to different flux threshold values (Y). The best regression fit was obtained using an instantaneous flux threshold of 6 nmol O 3 m -2  s -1 (POD 6 ); the same value was obtained also for other crops. According to the generic lettuce dose-response relationship, an O 3 critical level of 1 mmol O 3 m -2 of POD 6 for a 15% of marketable yield loss was found.

Clinic expert information extraction based on domain model and block importance model.

PubMed

Zhang, Yuanpeng; Wang, Li; Qian, Danmin; Geng, Xingyun; Yao, Dengfu; Dong, Jiancheng

2015-11-01

To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling yield and biomass responses of maize cultivars to climate change under full and deficit irrigation

USDA-ARS?s Scientific Manuscript database

As climate change becomes inevitable, the agricultural community is concerned about its possible effects on crop production and developing strategies to adapt to this change. In this study, the Root Zone Water Quality Model (RZWQM2) was calibrated with four years of maize data from central Colorado ...

Extraction of gelatin from salmon (Salmo salar) fish skin using trypsin-aided process: optimization by Plackett-Burman and response surface methodological approaches.

PubMed

Fan, HuiYin; Dumont, Marie-Josée; Simpson, Benjamin K

2017-11-01

Gelatin from salmon ( Salmo salar ) skin with high molecular weight protein chains ( α -chains) was extracted using trypsin-aided process. Response surface methodology was used to optimise the extraction parameters. Yield, hydroxyproline content and protein electrophoretic profile via sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of gelatin were used as responses in the optimization study. The optimum conditions were determined as: trypsin concentration at 1.49 U/g; extraction temperature at 45 °C; and extraction time at 6 h 16 min. This response surface optimized model was significant and produced an experimental value (202.04 ± 8.64%) in good agreement with the predicted value (204.19%). Twofold higher yields of gelatin with high molecular weight protein chains were achieved in the optimized process with trypsin treatment when compared to the process without trypsin.

Analysis of the neutron time-of-flight spectra from inertial confinement fusion experiments

NASA Astrophysics Data System (ADS)

Hatarik, R.; Sayre, D. B.; Caggiano, J. A.; Phillips, T.; Eckart, M. J.; Bond, E. J.; Cerjan, C.; Grim, G. P.; Hartouni, E. P.; Knauer, J. P.; Mcnaney, J. M.; Munro, D. H.

2015-11-01

Neutron time-of-flight diagnostics have long been used to characterize the neutron spectrum produced by inertial confinement fusion experiments. The primary diagnostic goals are to extract the d + t → n + α (DT) and d + d → n + 3He (DD) neutron yields and peak widths, and the amount DT scattering relative to its unscattered yield, also known as the down-scatter ratio (DSR). These quantities are used to infer yield weighted plasma conditions, such as ion temperature (Tion) and cold fuel areal density. We report on novel methodologies used to determine neutron yield, apparent Tion, and DSR. These methods invoke a single temperature, static fluid model to describe the neutron peaks from DD and DT reactions and a spline description of the DT spectrum to determine the DSR. Both measurements are performed using a forward modeling technique that includes corrections for line-of-sight attenuation and impulse response of the detection system. These methods produce typical uncertainties for DT Tion of 250 eV, 7% for DSR, and 9% for the DT neutron yield. For the DD values, the uncertainties are 290 eV for Tion and 10% for the neutron yield.

Adapting wheat in Europe for climate change.

PubMed

Semenov, M A; Stratonovitch, P; Alghabari, F; Gooding, M J

2014-05-01

Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat.

Detailed high-resolution three-dimensional simulations of OMEGA separated reactants inertial confinement fusion experiments

DOE PAGES

Haines, Brian Michael; Grim, Gary P.; Fincke, James R.; ...

2016-07-29

Here, we present results from the comparison of high-resolution three-dimensional (3D) simulations with data from the implosions of inertial confinement fusion capsules with separated reactants performed on the OMEGA laser facility. Each capsule, referred to as a “CD Mixcap,” is filled with tritium and has a polystyrene (CH) shell with a deuterated polystyrene (CD) layer whose burial depth is varied. In these implosions, fusion reactions between deuterium and tritium ions can occur only in the presence of atomic mix between the gas fill and shell material. The simulations feature accurate models for all known experimental asymmetries and do not employmore » any adjustable parameters to improve agreement with experimental data. Simulations are performed with the RAGE radiation-hydrodynamics code using an Implicit Large Eddy Simulation (ILES) strategy for the hydrodynamics. We obtain good agreement with the experimental data, including the DT/TT neutron yield ratios used to diagnose mix, for all burial depths of the deuterated shell layer. Additionally, simulations demonstrate good agreement with converged simulations employing explicit models for plasma diffusion and viscosity, suggesting that the implicit sub-grid model used in ILES is sufficient to model these processes in these experiments. In our simulations, mixing is driven by short-wavelength asymmetries and longer-wavelength features are responsible for developing flows that transport mixed material towards the center of the hot spot. Mix material transported by this process is responsible for most of the mix (DT) yield even for the capsule with a CD layer adjacent to the tritium fuel. Consistent with our previous results, mix does not play a significant role in TT neutron yield degradation; instead, this is dominated by the displacement of fuel from the center of the implosion due to the development of turbulent instabilities seeded by long-wavelength asymmetries. Through these processes, the long-wavelength asymmetries degrade TT yield more than the DT yield and thus bring DT/TT neutron yield ratios into agreement with experiment. Finally, we present a detailed comparison of the flows in 2D and 3D simulations.« less

Detailed high-resolution three-dimensional simulations of OMEGA separated reactants inertial confinement fusion experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haines, Brian M., E-mail: bmhaines@lanl.gov; Fincke, James R.; Shah, Rahul C.

We present results from the comparison of high-resolution three-dimensional (3D) simulations with data from the implosions of inertial confinement fusion capsules with separated reactants performed on the OMEGA laser facility. Each capsule, referred to as a “CD Mixcap,” is filled with tritium and has a polystyrene (CH) shell with a deuterated polystyrene (CD) layer whose burial depth is varied. In these implosions, fusion reactions between deuterium and tritium ions can occur only in the presence of atomic mix between the gas fill and shell material. The simulations feature accurate models for all known experimental asymmetries and do not employ anymore » adjustable parameters to improve agreement with experimental data. Simulations are performed with the RAGE radiation-hydrodynamics code using an Implicit Large Eddy Simulation (ILES) strategy for the hydrodynamics. We obtain good agreement with the experimental data, including the DT/TT neutron yield ratios used to diagnose mix, for all burial depths of the deuterated shell layer. Additionally, simulations demonstrate good agreement with converged simulations employing explicit models for plasma diffusion and viscosity, suggesting that the implicit sub-grid model used in ILES is sufficient to model these processes in these experiments. In our simulations, mixing is driven by short-wavelength asymmetries and longer-wavelength features are responsible for developing flows that transport mixed material towards the center of the hot spot. Mix material transported by this process is responsible for most of the mix (DT) yield even for the capsule with a CD layer adjacent to the tritium fuel. Consistent with our previous results, mix does not play a significant role in TT neutron yield degradation; instead, this is dominated by the displacement of fuel from the center of the implosion due to the development of turbulent instabilities seeded by long-wavelength asymmetries. Through these processes, the long-wavelength asymmetries degrade TT yield more than the DT yield and thus bring DT/TT neutron yield ratios into agreement with experiment. Finally, we present a detailed comparison of the flows in 2D and 3D simulations.« less

Detailed high-resolution three-dimensional simulations of OMEGA separated reactants inertial confinement fusion experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haines, Brian Michael; Grim, Gary P.; Fincke, James R.

Here, we present results from the comparison of high-resolution three-dimensional (3D) simulations with data from the implosions of inertial confinement fusion capsules with separated reactants performed on the OMEGA laser facility. Each capsule, referred to as a “CD Mixcap,” is filled with tritium and has a polystyrene (CH) shell with a deuterated polystyrene (CD) layer whose burial depth is varied. In these implosions, fusion reactions between deuterium and tritium ions can occur only in the presence of atomic mix between the gas fill and shell material. The simulations feature accurate models for all known experimental asymmetries and do not employmore » any adjustable parameters to improve agreement with experimental data. Simulations are performed with the RAGE radiation-hydrodynamics code using an Implicit Large Eddy Simulation (ILES) strategy for the hydrodynamics. We obtain good agreement with the experimental data, including the DT/TT neutron yield ratios used to diagnose mix, for all burial depths of the deuterated shell layer. Additionally, simulations demonstrate good agreement with converged simulations employing explicit models for plasma diffusion and viscosity, suggesting that the implicit sub-grid model used in ILES is sufficient to model these processes in these experiments. In our simulations, mixing is driven by short-wavelength asymmetries and longer-wavelength features are responsible for developing flows that transport mixed material towards the center of the hot spot. Mix material transported by this process is responsible for most of the mix (DT) yield even for the capsule with a CD layer adjacent to the tritium fuel. Consistent with our previous results, mix does not play a significant role in TT neutron yield degradation; instead, this is dominated by the displacement of fuel from the center of the implosion due to the development of turbulent instabilities seeded by long-wavelength asymmetries. Through these processes, the long-wavelength asymmetries degrade TT yield more than the DT yield and thus bring DT/TT neutron yield ratios into agreement with experiment. Finally, we present a detailed comparison of the flows in 2D and 3D simulations.« less

Detailed high-resolution three-dimensional simulations of OMEGA separated reactants inertial confinement fusion experiments

NASA Astrophysics Data System (ADS)

Haines, Brian M.; Grim, Gary P.; Fincke, James R.; Shah, Rahul C.; Forrest, Chad J.; Silverstein, Kevin; Marshall, Frederic J.; Boswell, Melissa; Fowler, Malcolm M.; Gore, Robert A.; Hayes-Sterbenz, Anna C.; Jungman, Gerard; Klein, Andreas; Rundberg, Robert S.; Steinkamp, Michael J.; Wilhelmy, Jerry B.

2016-07-01

We present results from the comparison of high-resolution three-dimensional (3D) simulations with data from the implosions of inertial confinement fusion capsules with separated reactants performed on the OMEGA laser facility. Each capsule, referred to as a "CD Mixcap," is filled with tritium and has a polystyrene (CH) shell with a deuterated polystyrene (CD) layer whose burial depth is varied. In these implosions, fusion reactions between deuterium and tritium ions can occur only in the presence of atomic mix between the gas fill and shell material. The simulations feature accurate models for all known experimental asymmetries and do not employ any adjustable parameters to improve agreement with experimental data. Simulations are performed with the RAGE radiation-hydrodynamics code using an Implicit Large Eddy Simulation (ILES) strategy for the hydrodynamics. We obtain good agreement with the experimental data, including the DT/TT neutron yield ratios used to diagnose mix, for all burial depths of the deuterated shell layer. Additionally, simulations demonstrate good agreement with converged simulations employing explicit models for plasma diffusion and viscosity, suggesting that the implicit sub-grid model used in ILES is sufficient to model these processes in these experiments. In our simulations, mixing is driven by short-wavelength asymmetries and longer-wavelength features are responsible for developing flows that transport mixed material towards the center of the hot spot. Mix material transported by this process is responsible for most of the mix (DT) yield even for the capsule with a CD layer adjacent to the tritium fuel. Consistent with our previous results, mix does not play a significant role in TT neutron yield degradation; instead, this is dominated by the displacement of fuel from the center of the implosion due to the development of turbulent instabilities seeded by long-wavelength asymmetries. Through these processes, the long-wavelength asymmetries degrade TT yield more than the DT yield and thus bring DT/TT neutron yield ratios into agreement with experiment. Finally, we present a detailed comparison of the flows in 2D and 3D simulations.

Indirect selection for resistance to ear rot and leaf diseases in maize lines using biplots.

PubMed

Pereira, G S; Camargos, R B; Balestre, M; Von Pinho, R G; C Melo, W M

2015-09-21

Leaf disease and ear rot have caused reductions in maize yield in Brazil and other producer countries. Therefore, the aims of this study were to analyze the association between husked ear yield and the severity of maize white spot, gray leaf spot, helminthosporium, and ear rot caused by Fusarium verticillioides and Diplodia maydis using biplots in a mixed-model approach. The responses of 238 lines introduced to Brazil and four controls were evaluated using an incomplete block design with three replicates in two locations: Lavras and Uberlândia, Minas Gerais, Brazil. Two experiments were conducted in each location, one with F. verticillioides and the other with D. maydis. The mixed models elucidated the relationship between yield, leaf disease, and ear disease. Significant genotype x environment and genotype x pathogen interactions were observed. In conclusion, husked ear yield is more associated with ear rot than with the leaf diseases evaluated, justifying the indirect selection for resistance to kernel rot in maize-F. verticillioides and maize-D. maydis pathosystems by yield evaluation.

Effect of rumen-protected methionine on feed intake, milk production, true milk protein concentration, and true milk protein yield, and the factors that influence these effects: a meta-analysis.

PubMed

Patton, R A

2010-05-01

A meta-analysis of published studies was used to investigate the effect of rumen-protected methionine (RPM) added to the diets of lactating dairy cattle on dry matter intake, milk production, true milk protein (TMP) production, and milk fat yield. Differences in responses between 2 commonly used RPM products, Mepron (Evonik Industries, Hanau, Germany) and Smartamine (Adisseo, Antony, France), were investigated as well as dietary and animal factors that could influence responses. Diets were coded with respect to the amino acid (AA) deficiency of the control diet as predicted by the AminoCow model (version 3.5.2, http://www.makemilknotmanure.com/aminocow.php; 0=no AA deficiency, 1=Met deficiency, 2=Met and Lys deficiency, 3=Met and Lys plus at least 1 other AA deficiency) to test the effect of AA deficiencies on RPM response. Thirty-five studies were identified, 17 studies evaluating Mepron, 18 studies evaluating Smartamine, and 1 study evaluating both. This permitted 75 dietary comparisons between control and RPM-added diets. Diets were entered into the AminoCow and the 2001 National Research Council models to compare predictions of Met, Lys, and metabolizable protein (MP) flow. Mean Met and Lys in diets where RPM was fed were estimated to be 2.35 and 6.33% of MP, respectively. Predictions of flows between models were similar. Overall, RPM addition to diets increased production of TMP, both as percentage (0.07%) and yield (27 g/d). Dry matter intake and milk fat percentage were slightly decreased, whereas milk production was slightly increased. Differences between products were detected for all production variables, with Mepron-fed cows producing less TMP percentage but greater milk production, resulting in twice as much TMP yield. Milk protein response to RPM was not related to predicted AA deficiency, calculated Met deficiency, or Met as a percentage of MP. Other dietary factors, including Lys flow (g/d), Lys as percentage of MP, neutral detergent fiber percentage, crude protein percentage, or energy balance, had no detectable effects on TMP response. When cows with a predicted positive AA balance were fed RPM, milk production increased, but when AA balance was negative, milk production decreased. Amount of RPM added to the diet was not correlated to TMP response. This study does not support the necessity of a high Lys level as a prerequisite to obtaining a TMP response to feeding RPM or the MP requirement suggested by the National Research Council model (2001). However, more dose-response studies over a wide range of milk production and dietary regimens will be required to more clearly establish AA requirements and to predict responses to RPM supplementation. Copyright 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Climate Change Impacts on Sediment Yield in Headwaters of a High-latitude Region in China

NASA Astrophysics Data System (ADS)

Zhou, Y.; Xu, Y. J.; Wang, J., , Dr; Weihua, X.; Huang, Y.

2017-12-01

Climate change is expected to have strongest effects in higher latitude regions. Despite intensive research on possible hydrological responses to global warming in these regions, our knowledge of climate change on surface erosion and sediment yield in high-latitude headwaters is limited. In this study, we used the Soil and Water Assessment Tool (SWAT) to predict future runoff and sediment yield from the headwaters of a high-latitude river basin in China's far northeast. The SWAT model was first calibrated with historical discharge records and the model parameterization achieved satisfactory validation. The calibrated model was then applied to two greenhouse gas concentration trajectories, RCP4.5 and RCP8.5, for the period from 2020 to 2050 to estimate future runoff. Sediment yields for this period were predicted using a discharge-sediment load rating curve developed from field measurements in the past nine years. Our preliminary results show an increasing trend of sediment yield under both climate change scenarios, and that the increase is more pronounced in the summer and autumn months. Changes in precipitation and temperature seem to exert variable impacts on runoff and sediment yield at interannual and seasonal scales in these headwaters. These findings imply that the current river basin management in the region needs to be reviewed and improved in order to be effective under a changing climate.

Investigation of optimal conditions for production of highly crystalline nanocellulose with increased yield via novel Cr(III)-catalyzed hydrolysis: Response surface methodology.

PubMed

Chen, You Wei; Lee, Hwei Voon; Abd Hamid, Sharifah Bee

2017-12-15

For the first time, a highly efficient Cr(NO 3 ) 3 catalysis system was proposed for optimization the yield and crystallinity of nanocellulose end product. A five-level three-factor central composite design coupled with response surface methodology was employed to elucidate parameters interactions between three design factors, namely reaction temperature (x 1 ), reaction time (x 2 ) and concentration of Cr(NO 3 ) 3 (x 3 ) over a broad range of process conditions and determine the effect on crystallinity index and product yield. The developed models predicted the maximum nanocellulose yield of 87% at optimum process conditions of 70.6°C, 1.48h, and 0.48M Cr(NO 3 ) 3 . At these conditions, the obtained nanocellulose presented high crystallinity index (75.3%), spider-web-like interconnected network morphology with the average width of 31.2±14.3nm. In addition, the yielded nanocellulose rendered a higher thermal stability than that of original cellulosic source and expected to be widely used as reinforcement agent in bio-nanocomposites materials. Copyright © 2017 Elsevier Ltd. All rights reserved.

An assessment of irrigation needs and crop yield for the United States under potential climate changes

USGS Publications Warehouse

Brumbelow, Kelly; Georgakakos, Aris P.

2000-01-01

Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.

Spectroscopic measurements of soybeans used to parameterize physiological traits in the AgroIBIS ecosystem model

NASA Astrophysics Data System (ADS)

Singh, A.; Serbin, S.; Kucharik, C. J.; Townsend, P. A.

2014-12-01

Ecosystem models such AgroIBIS require detailed parameterizations of numerous vegetation traits related to leaf structure, biochemistry and photosynthetic capacity to properly assess plant carbon assimilation and yield response to environmental variability. In general, these traits are estimated from a limited number of field measurements or sourced from the literature, but rarely is the full observed range of variability in these traits utilized in modeling activities. In addition, pathogens and pests, such as the exotic soybean aphid (Aphis glycines), which affects photosynthetic pathways in soybean plants by feeding on phloem and sap, can potentially impact plant productivity and yields. Capturing plant responses to pest pressure in conjunction with environmental variability is of considerable interest to managers and the scientific community alike. In this research, we employed full-range (400-2500 nm) field and laboratory spectroscopy to rapidly characterize the leaf biochemical and physiological traits, namely foliar nitrogen, specific leaf area (SLA) and the maximum rate of RuBP carboxylation by the enzyme RuBisCo (Vcmax) in soybean plants, which experienced a broad range of environmental conditions and soybean aphid pressures. We utilized near-surface spectroscopic remote sensing measurements as a means to capture the spatial and temporal patterns of aphid impacts across broad aphid pressure levels. In addition, we used the spectroscopic data to generate a much larger dataset of key model parameters required by AgroIBIS than would be possible through traditional measurements of biochemistry and leaf-level gas exchange. The use of spectroscopic retrievals of soybean traits allowed us to better characterize the variability of plant responses associated with aphid pressure to more accurately model the likely impacts of soybean aphid on soybeans. Our next steps include the coupling of the information derived from our spectral measurements with the AgroIBIS model to project the impacts of increasing aphid pressures on yields expected with continued global change and altered environmental conditions.

The strain path dependence of plastic deformation response of AA5754: Experiment and modeling

NASA Astrophysics Data System (ADS)

Pham, Minh-Son; Hu, Lin; Iadicola, Mark; Creuziger, Adam; Rollett, Anthony D.

2013-12-01

This work presents modeling of experiments on a balanced biaxial (BB) pre-strained AA5754 alloy, subsequently reloaded uniaxially along the rolling direction and transverse direction. The material exhibits a complex plastic deformation response during the change in strain path due to 1) crystallographic texture, 2) aging (interactions between dislocations and Mg atoms) and 3) recovery (annihilation and re-arrangement of dislocations). With a BB prestrain of about 5 %, the aging process is dominant, and the yield strength for uniaxially deformed samples is observed to be higher than the flow stress during BB straining. The strain hardening rate after changing path is, however, lower than that for pre-straining. Higher degrees of pre-straining make the dynamic recovery more active. The dynamic recovery at higher strain levels compensates for the aging effect, and results in: 1) a reduction of the yield strength, and 2) an increase in the hardening rate of re-strained specimens along other directions. The yield strength of deformed samples is further reduced if these samples are left at room temperature to let static recovery occur. The synergistic influences of texture condition, aging and recovery processes on the material response make the modeling of strain path dependence of mechanical behavior of AA5754 challenging. In this study, the influence of crystallographic texture is taken into account by incorporating the latent hardening into a visco-plastic self-consistent model. Different strengths of dislocation glide interaction models in 24 slip systems are used to represent the latent hardening. Moreover, the aging and recovery effects are also included into the latent hardening model by considering strong interactions between dislocations and dissolved atom Mg and the microstructural evolution. These microstructural considerations provide a powerful capability to successfully describe the strain path dependence of plastic deformation behavior of AA5754.

Improved partition equilibrium model for predicting analyte response in electrospray ionization mass spectrometry.

PubMed

Du, Lihong; White, Robert L

2009-02-01

A previously proposed partition equilibrium model for quantitative prediction of analyte response in electrospray ionization mass spectrometry is modified to yield an improved linear relationship. Analyte mass spectrometer response is modeled by a competition mechanism between analyte and background electrolytes that is based on partition equilibrium considerations. The correlation between analyte response and solution composition is described by the linear model over a wide concentration range and the improved model is shown to be valid for a wide range of experimental conditions. The behavior of an analyte in a salt solution, which could not be explained by the original model, is correctly predicted. The ion suppression effects of 16:0 lysophosphatidylcholine (LPC) on analyte signals are attributed to a combination of competition for excess charge and reduction of total charge due to surface tension effects. In contrast to the complicated mathematical forms that comprise the original model, the simplified model described here can more easily be employed to predict analyte mass spectrometer responses for solutions containing multiple components. Copyright (c) 2008 John Wiley & Sons, Ltd.

Antioxidant Response of Osteoblasts to Doxycycline in an Inflammatory Model Induced by C-reactive Protein and Interleukin-6

PubMed Central

Tilakaratne, A.; Soory, Mena

2016-01-01

Objectives: Investigation of osteoblastic responses to oxidative stress, induced by C-reactive protein (CRP) and IL-6 and ameliorating effects of doxycycline (Dox); using assays for 5-alpha dihydrotestosterone (DHT) as an antioxidant marker of healing. IL-6 and CRP are risk markers of periodontitis and prevalent comorbidities in periodontitis subjects. Methods: Confluent monolayer cultures of osteoblasts were incubated with radiolabelled testosterone (14C-T) as substrate, in the presence or absence (Control) of pre-determined optimal concentrations of CRP, IL-6, Dox; alone and in combination (n=8) for 24h in MEM. The eluent was solvent-extracted for steroid metabolites. They were separated using TLC in a benzene/ acetone solvent system 4:1 v/v; and quantified using radioisotope scanning. The identity of formed metabolites was confirmed using the mobility of cold standards added to the samples and disclosed in iodine. Further confirmation of the authenticity of DHT was carried out by combined gas chromatrography-mass spectrometry, after derivatization to pentafluorobenzyloxime trimethyl silyl ether. Results: The yields of DHT from 14C-testosterone showed 2-fold and 1.8-fold- inhibition in response to IL-6 and CRP respectively and 28% stimulation in response to Dox, via the 5-alpha reductase pathway. The combination of IL-6 + CRP showed a 2-fold reduction in the yields of DHT, elevated to control values when combined with Dox (n=8; p<0.001). Yields of 4-androstenedione showed an inverse relationship to those of DHT, in response to the agents tested, in keeping with the 17-beta hydroxysteroid dehydrogenase pathway. Conclusions: Inhibition of DHT synthesis in osteoblasts by IL-6 and CRP was overcome by doxycycline. Oxidative actions of IL-6 and CRP; and antioxidant actions of Dox are reinforced by the metabolic yields of DHT in response to agents tested. Using a novel metabolically active model allows closer extrapolation to in vivo conditions; in the context of adjunctive therapeutic applications for periodontitis and prevalent comorbidities. PMID:25159306

Potential individual versus simultaneous climate change effects on soybean (C 3) and maize (C 4) crops: An agrotechnology model based study

NASA Astrophysics Data System (ADS)

Mera, Roberto J.; Niyogi, Dev; Buol, Gregory S.; Wilkerson, Gail G.; Semazzi, Fredrick H. M.

2006-11-01

Landuse/landcover change induced effects on regional weather and climate patterns and the associated plant response or agricultural productivity are coupled processes. Some of the basic responses to climate change can be detected via changes in radiation ( R), precipitation ( P), and temperature ( T). Past studies indicate that each of these three variables can affect LCLUC response and the agricultural productivity. This study seeks to address the following question: What is the effect of individual versus simultaneous changes in R, P, and T on plant response such as crop yields in a C 3 and a C 4 plant? This question is addressed by conducting model experiments for soybean (C 3) and maize (C 4) crops using the DSSAT: Decision Support System for Agrotechnology Transfer, CROPGRO (soybean), and CERES-Maize (maize) models. These models were configured over an agricultural experiment station in Clayton, NC [35.65°N, 78.5°W]. Observed weather and field conditions corresponding to 1998 were used as the control. In the first set of experiments, the CROPGRO (soybean) and CERES-Maize (maize) responses to individual changes in R and P (25%, 50%, 75%, 150%) and T (± 1, ± 2 °C) with respect to control were studied. In the second set, R, P, and T were simultaneously changed by 50%, 150%, and ± 2 °C, and the interactions and direct effects of individual versus simultaneous variable changes were analyzed. For the model setting and the prescribed environmental changes, results from the first set of experiments indicate: (i) precipitation changes were most sensitive and directly affected yield and water loss due to evapotranspiration; (ii) radiation changes had a non-linear effect and were not as prominent as precipitation changes; (iii) temperature had a limited impact and the response was non-linear; (iv) soybeans and maize responded differently for R, P, and T, with maize being more sensitive. The results from the second set of experiments indicate that simultaneous change analyses do not necessarily agree with those from individual changes, particularly for temperature changes. Our analysis indicates that for the changing climate, precipitation (hydrological), temperature, and radiative feedbacks show a non-linear effect on yield. Study results also indicate that for studying the feedback between the land surface and the atmospheric changes, (i) there is a need for performing simultaneous parameter changes in the response assessment of cropping patterns and crop yield based on ensembles of projected climate change, and (ii) C 3 crops are generally considered more sensitive than C 4; however, the temperature-radiation related changes shown in this study also effected significant changes in C 4 crops. Future studies assessing LCLUC impacts, including those from agricultural cropping patterns and other LCULC-climate couplings, should advance beyond the sensitivity mode and consider multivariable, ensemble approaches to identify the vulnerability and feedbacks in estimating climate-related impacts.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Modelling of loading, stress relaxation and stress recovery in a shape memory polymer.

PubMed

Sweeney, J; Bonner, M; Ward, I M

2014-09-01

A multi-element constitutive model for a lactide-based shape memory polymer has been developed that represents loading to large tensile deformations, stress relaxation and stress recovery at 60, 65 and 70°C. The model consists of parallel Maxwell arms each comprising neo-Hookean and Eyring elements. Guiu-Pratt analysis of the stress relaxation curves yields Eyring parameters. When these parameters are used to define the Eyring process in a single Maxwell arm, the resulting model yields at too low a stress, but gives good predictions for longer times. Stress dip tests show a very stiff response on unloading by a small strain decrement. This would create an unrealistically high stress on loading to large strain if it were modelled by an elastic element. Instead it is modelled by an Eyring process operating via a flow rule that introduces strain hardening after yield. When this process is incorporated into a second parallel Maxwell arm, there results a model that fully represents both stress relaxation and stress dip tests at 60°C. At higher temperatures a third arm is required for valid predictions. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The role of interior watershed processes in improving parameter estimation and performance of watershed models.

PubMed

Yen, Haw; Bailey, Ryan T; Arabi, Mazdak; Ahmadi, Mehdi; White, Michael J; Arnold, Jeffrey G

2014-09-01

Watershed models typically are evaluated solely through comparison of in-stream water and nutrient fluxes with measured data using established performance criteria, whereas processes and responses within the interior of the watershed that govern these global fluxes often are neglected. Due to the large number of parameters at the disposal of these models, circumstances may arise in which excellent global results are achieved using inaccurate magnitudes of these "intra-watershed" responses. When used for scenario analysis, a given model hence may inaccurately predict the global, in-stream effect of implementing land-use practices at the interior of the watershed. In this study, data regarding internal watershed behavior are used to constrain parameter estimation to maintain realistic intra-watershed responses while also matching available in-stream monitoring data. The methodology is demonstrated for the Eagle Creek Watershed in central Indiana. Streamflow and nitrate (NO) loading are used as global in-stream comparisons, with two process responses, the annual mass of denitrification and the ratio of NO losses from subsurface and surface flow, used to constrain parameter estimation. Results show that imposing these constraints not only yields realistic internal watershed behavior but also provides good in-stream comparisons. Results further demonstrate that in the absence of incorporating intra-watershed constraints, evaluation of nutrient abatement strategies could be misleading, even though typical performance criteria are satisfied. Incorporating intra-watershed responses yields a watershed model that more accurately represents the observed behavior of the system and hence a tool that can be used with confidence in scenario evaluation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Direct CP Violation in Charmless Hadronic B-Meson Decays at the PEP-II Asymmetric B-Meson Factory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telnov, Alexandre Valerievich; /UC, Berkeley

2005-05-06

The study of the quark transition b {yields} s{bar s}s, which is a pure loop-level (''penguin'') process leading to several B-meson-decay final states, most notably {phi}K, is arguably the hottest topic in B-meson physics today. The reason is the sensitivity of the amplitudes and the CP-violating asymmetries in such processes to physics beyond the Standard Model. By performing these measurements, we improve our understanding of the phenomenon of combined-parity (CP) violation, which is believed to be responsible for the dominance of matter over antimatter in our Universe. Here, we present measurements of branching fractions and charge asymmetries in the decaysmore » B{sup +} {yields} {phi}K{sup +} and B{sup 0} {yields} {phi}K{sup 0} in a sample of approximately 89 million B{bar B} pairs collected by the BABAR detector at the PEP-II asymmetric-energy B-meson Factory at SLAC. We determine {Beta}(B{sup +} {yields} {phi}K{sup +}) = (10.0{sub -0.8}{sup +0.9} {+-} 0.5) x 10{sup -6} and {Beta}(B{sup 0} {yields} {phi}K{sup 0}) = (8.4{sub -1.3}{sup +1.5} {+-} 0.5) x 10{sup -6}, where the first error is statistical and the second is systematic. Additionally, we measure the CP-violating charge asymmetry {Alpha}{sub CP}(B{sup {+-}} {yields} {phi}K{sup {+-}}) = 0.04 {+-} 0.09 {+-} 0.01, with a 90% confidence-level interval of [-0.10, 0.18], and set an upper limit on the CKM- and color-suppressed decay B{sup +} {yields} {phi}{pi}{sup +}, {Beta}(B{sup +} {yields} {phi}{pi}{sup +}) < 0.41 x 10{sup -6} (at the 90% confidence level). Our results are consistent with the Standard Model, which predicts {Alpha}{sub CP}(B{sup {+-}} {yields} {phi}K{sup {+-}}) {approx}< 1% and {Beta}(B {yields} {phi}{tau}) << 10{sup -7}. Since many models of physics beyond the Standard Model introduce additional loop diagrams with new heavy particles and new CP-violating phases that would contribute to these decays, potentially making {Alpha}{sub CP} (B{sup {+-}} {yields} {phi}K{sup {+-}}) and {Beta}(B {yields} {phi}{pi}) quite large, our results can be used to substantially constrain the parameter spaces of such models.« less

Evaluating mountain meadow groundwater response to Pinyon-Juniper and temperature in a great basin watershed

USGS Publications Warehouse

Carroll, Rosemary W.H.; Huntington, Justin L.; Snyder, Keirith A.; Niswonger, Richard G.; Morton, Charles; Stringham, Tamzen K.

2017-01-01

This research highlights development and application of an integrated hydrologic model (GSFLOW) to a semiarid, snow-dominated watershed in the Great Basin to evaluate Pinyon-Juniper (PJ) and temperature controls on mountain meadow shallow groundwater. The work used Google Earth Engine Landsat satellite and gridded climate archives for model evaluation. Model simulations across three decades indicated that the watershed operates on a threshold response to precipitation (P) >400 mm/y to produce a positive yield (P-ET; 9%) resulting in stream discharge and a rebound in meadow groundwater levels during these wetter years. Observed and simulated meadow groundwater response to large P correlates with above average predicted soil moisture and with a normalized difference vegetation index threshold value >0.3. A return to assumed pre-expansion PJ conditions or an increase in temperature to mid-21st century shifts yielded by only ±1% during the multi-decade simulation period; but changes of approximately ±4% occurred during wet years. Changes in annual yield were largely dampened by the spatial and temporal redistribution of evapotranspiration across the watershed: Yet the influence of this redistribution and vegetation structural controls on snowmelt altered recharge to control water table depth in the meadow. Even a small-scale removal of PJ (0.5 km2) proximal to the meadow will promote a stable, shallow groundwater system resilient to droughts, while modest increases in temperature will produce a meadow susceptible to declining water levels and a community structure likely to move toward dry and degraded conditions.

Application of artificial neural networks in nonlinear analysis of trusses

NASA Technical Reports Server (NTRS)

Alam, J.; Berke, L.

1991-01-01

A method is developed to incorporate neural network model based upon the Backpropagation algorithm for material response into nonlinear elastic truss analysis using the initial stiffness method. Different network configurations are developed to assess the accuracy of neural network modeling of nonlinear material response. In addition to this, a scheme based upon linear interpolation for material data, is also implemented for comparison purposes. It is found that neural network approach can yield very accurate results if used with care. For the type of problems under consideration, it offers a viable alternative to other material modeling methods.

Estimating disease prevalence from two-phase surveys with non-response at the second phase

PubMed Central

Gao, Sujuan; Hui, Siu L.; Hall, Kathleen S.; Hendrie, Hugh C.

2010-01-01

SUMMARY In this paper we compare several methods for estimating population disease prevalence from data collected by two-phase sampling when there is non-response at the second phase. The traditional weighting type estimator requires the missing completely at random assumption and may yield biased estimates if the assumption does not hold. We review two approaches and propose one new approach to adjust for non-response assuming that the non-response depends on a set of covariates collected at the first phase: an adjusted weighting type estimator using estimated response probability from a response model; a modelling type estimator using predicted disease probability from a disease model; and a regression type estimator combining the adjusted weighting type estimator and the modelling type estimator. These estimators are illustrated using data from an Alzheimer’s disease study in two populations. Simulation results are presented to investigate the performances of the proposed estimators under various situations. PMID:10931514

Noise effects in nonlinear biochemical signaling

NASA Astrophysics Data System (ADS)

Bostani, Neda; Kessler, David A.; Shnerb, Nadav M.; Rappel, Wouter-Jan; Levine, Herbert

2012-01-01

It has been generally recognized that stochasticity can play an important role in the information processing accomplished by reaction networks in biological cells. Most treatments of that stochasticity employ Gaussian noise even though it is a priori obvious that this approximation can violate physical constraints, such as the positivity of chemical concentrations. Here, we show that even when such nonphysical fluctuations are rare, an exact solution of the Gaussian model shows that the model can yield unphysical results. This is done in the context of a simple incoherent-feedforward model which exhibits perfect adaptation in the deterministic limit. We show how one can use the natural separation of time scales in this model to yield an approximate model, that is analytically solvable, including its dynamical response to an environmental change. Alternatively, one can employ a cutoff procedure to regularize the Gaussian result.

A redefinition of the representation of mammary cells and enzyme activities in a lactating dairy cow model.

PubMed

Hanigan, M D; Rius, A G; Kolver, E S; Palliser, C C

2007-08-01

The Molly model predicts various aspects of digestion and metabolism in the cow, including nutrient partitioning between milk and body stores. It has been observed previously that the model underpredicts milk component yield responses to nutrition and consequently overpredicts body energy store responses. In Molly, mammary enzyme activity is represented as an aggregate of mammary cell numbers and activity per cell with minimal endocrine regulation. Work by others suggests that mammary cells can cycle between active and quiescent states in response to various stimuli. Simple models of milk production have demonstrated the utility of this representation when using the model to simulate variable milking and nutrient restriction. It was hypothesized that replacing the current representation of mammary cells and enzyme activity in Molly with a representation of active and quiescent cells and improving the representation of endocrine control of cell activity would improve predictions of milk component yield. The static representation of cell numbers was replaced with a representation of cell growth during gestation and early lactation periods and first-order cell death. Enzyme capacity for fat and protein synthesis was assumed to be proportional to cell numbers. Enzyme capacity for lactose synthesis was represented with the same equation form as for cell numbers. Data used for parameter estimation were collected as part of an extended lactation trial. Cows with North American or New Zealand genotypes were fed 0, 3, or 6 kg of concentrate dry matter daily during a 600-d lactation. The original model had root mean square prediction errors of 17.7, 22.3, and 19.8% for lactose, protein, and fat yield, respectively, as compared with values of 8.3, 9.4, and 11.7% for the revised model, respectively. The original model predicted body weight with an error of 19.7% vs. 5.7% for the revised model. Based on these observations, it was concluded that representing mammary synthetic capacity as a function of active cell numbers and revisions to endocrine control of cell activity was meritorious.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

NASA Astrophysics Data System (ADS)

Suarez, L. A.; Apan, A.; Werth, J.

2016-10-01

Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14 and 28 days after the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP = 2.6 and R2 = 0.88), followed by 28 DAE (RMSEP = 3.2 and R2 = 0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.

Genetic parameters of milk production traits in response to a short once-daily milking period in crossbred Holstein × Normande dairy cows.

PubMed

Charton, C; Guinard-Flament, J; Lefebvre, R; Barbey, S; Gallard, Y; Boichard, D; Larroque, H

2018-03-01

Despite its potential utility for predicting cows' milk yield responses to once-daily milking (ODM), the genetic basis of cow milk trait responses to ODM has been scarcely if ever described in the literature, especially for short ODM periods. This study set out to (1) estimate the genetic determinism of milk yield and composition during a 3-wk ODM period, (2) estimate the genetic determinism of milk yield responses (i.e., milk yield loss upon switching cows to ODM and milk yield recovery upon switching them back to twice-daily milking; TDM), and (3) seek predictors of milk yield responses to ODM, in particular using the first day of ODM. Our trial used 430 crossbred Holstein × Normande cows and comprised 3 successive periods: 1 wk of TDM (control), 3 wk of ODM, and 2 wk of TDM. Implementing ODM for 3 wk reduced milk yield by 27.5% on average, and after resuming TDM cows recovered on average 57% of the milk lost. Heritability estimates in the TDM control period and 3-wk ODM period were, respectively, 0.41 and 0.35 for milk yield, 0.66 and 0.61 for milk fat content, 0.60 and 0.80 for milk protein content, 0.66 and 0.36 for milk lactose content, and 0.20 and 0.15 for milk somatic cell score content. Milk yield and composition during 3-wk ODM and TDM periods were genetically close (within-trait genetic correlations between experimental periods all exceeding 0.80) but were genetically closer within the same milking frequency. Heritabilities of milk yield loss observed upon switching cows to ODM (0.39 and 0.34 for milk yield loss in kg/d and %, respectively) were moderate and similar to milk yield heritabilities. Milk yield recovery (kg/d) upon resuming TDM was a trait of high heritability (0.63). Because they are easy to measure, TDM milk yield and composition and milk yield responses on the first day of ODM were investigated as predictors of milk yield responses to a 3-wk ODM to easily detect animals that are well adapted to ODM. Twice-daily milking milk yield and composition were found to be partly genetically correlated with milk yield responses but not closely enough for practical application. With genetic correlations of 0.98 and 0.96 with 3-wk ODM milk yield losses (in kg/d and %, respectively), milk yield losses on the first day of ODM proved to be more accurate in predicting milk yield responses on longer term ODM than TDM milk yield. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Response surface methodology to optimise Accelerated Solvent Extraction of steviol glycosides from Stevia rebaudiana Bertoni leaves.

PubMed

Jentzer, Jean-Baptiste; Alignan, Marion; Vaca-Garcia, Carlos; Rigal, Luc; Vilarem, Gérard

2015-01-01

Following the approval of steviol glycosides as a food additive in Europe in December 2011, large-scale stevia cultivation will have to be developed within the EU. Thus there is a need to increase the efficiency of stevia evaluation through germplasm enhancement and agronomic improvement programs. To address the need for faster and reproducible sample throughput, conditions for automated extraction of dried stevia leaves using Accelerated Solvent Extraction were optimised. A response surface methodology was used to investigate the influence of three factors: extraction temperature, static time and cycle number on the stevioside and rebaudioside A extraction yields. The model showed that all the factors had an individual influence on the yield. Optimum extraction conditions were set at 100 °C, 4 min and 1 cycle, which yielded 91.8% ± 3.4% of total extractable steviol glycosides analysed. An additional optimisation was achieved by reducing the grind size of the leaves giving a final yield of 100.8% ± 3.3%. Copyright © 2014 Elsevier Ltd. All rights reserved.

Target Soil Impact Verification: Experimental Testing and Kayenta Constitutive Modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broome, Scott Thomas; Flint, Gregory Mark; Dewers, Thomas

2015-11-01

This report details experimental testing and constitutive modeling of sandy soil deformation under quasi - static conditions. This is driven by the need to understand constitutive response of soil to target/component behavior upon impact . An experimental and constitutive modeling program was followed to determine elastic - plastic properties and a compressional failure envelope of dry soil . One hydrostatic, one unconfined compressive stress (UCS), nine axisymmetric compression (ACS) , and one uniaxial strain (US) test were conducted at room temperature . Elastic moduli, assuming isotropy, are determined from unload/reload loops and final unloading for all tests pre - failuremore » and increase monotonically with mean stress. Very little modulus degradation was discernable from elastic results even when exposed to mean stresses above 200 MPa . The failure envelope and initial yield surface were determined from peak stresses and observed onset of plastic yielding from all test results. Soil elasto - plastic behavior is described using the Brannon et al. (2009) Kayenta constitutive model. As a validation exercise, the ACS - parameterized Kayenta model is used to predict response of the soil material under uniaxial strain loading. The resulting parameterized and validated Kayenta model is of high quality and suitable for modeling sandy soil deformation under a range of conditions, including that for impact prediction.« less

Use of selection indices to model the functional response of predators

USGS Publications Warehouse

Joly, D.O.; Patterson, B.R.

2003-01-01

The functional response of a predator to changing prey density is an important determinant of stability of predatora??prey systems. We show how Manly's selection indices can be used to distinguish between hyperbolic and sigmoidal models of a predator functional response to primary prey density in the presence of alternative prey. Specifically, an inverse relationship between prey density and preference for that prey results in a hyperbolic functional response while a positive relationship can yield either a hyperbolic or sigmoidal functional response, depending on the form and relative magnitudes of the density-dependent preference model, attack rate, and handling time. As an example, we examine wolf (Canis lupus) functional response to moose (Alces alces) density in the presence of caribou (Rangifer tarandus). The use of selection indices to evaluate the form of the functional response has significant advantages over previous attempts to fit Holling's functional response curves to killing-rate data directly, including increased sensitivity, use of relatively easily collected data, and consideration of other explanatory factors (e.g., weather, seasons, productivity).

CPEB1 modulates lipopolysaccharide-mediated iNOS induction in rat primary astrocytes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Ki Chan; Hyun Joo, So; Shin, Chan Young, E-mail: chanyshin@kku.ac.kr

2011-06-17

Highlights: {yields} Expression and phosphorylation of CPEB1 is increased by LPS stimulation in rat primary astrocytes. {yields} JNK regulates expression and phosphorylation of CPEB1 in reactive astrocytes. {yields} Down-regulation of CPEB1 using siRNA inhibits oxidative stress and iNOS induction by LPS stimulation. {yields} CPEB1 may play an important role in regulating inflammatory responses in reactive astrocytes induced by LPS. -- Abstract: Upon CNS damage, astrocytes undergo a series of biological changes including increased proliferation, production of inflammatory mediators and morphological changes, in a response collectively called reactive gliosis. This process is an essential part of the brains response to injury,more » yet much is unknown about the molecular mechanism(s) that induce these changes. In this study, we investigated the role of cytoplasmic polyadenylation element binding protein 1 (CPEB1) in the regulation of inflammatory responses in a model of reactive gliosis, lipopolysaccharide-stimulated astrocytes. CPEB1 is an mRNA-binding protein recently shown to be expressed in astrocytes that may play a role in astrocytes migration. After LPS stimulation, the expression and phosphorylation of CPEB1 was increased in rat primary astrocytes in a JNK-dependent process. siRNA-induced knockdown of CPEB1 expression inhibited the LPS-induced up-regulation of iNOS as well as NO and ROS production, a hallmark of immunological activation of astrocytes. The results from the study suggest that CPEB1 is actively involved in the regulation of inflammatory responses in astrocytes, which might provide new insights into the regulatory mechanism after brain injury.« less

A probabilistic model framework for evaluating year-to-year variation in crop productivity

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Iizumi, T.; Tao, F.

2008-12-01

Most models describing the relation between crop productivity and weather condition have so far been focused on mean changes of crop yield. For keeping stable food supply against abnormal weather as well as climate change, evaluating the year-to-year variations in crop productivity rather than the mean changes is more essential. We here propose a new framework of probabilistic model based on Bayesian inference and Monte Carlo simulation. As an example, we firstly introduce a model on paddy rice production in Japan. It is called PRYSBI (Process- based Regional rice Yield Simulator with Bayesian Inference; Iizumi et al., 2008). The model structure is the same as that of SIMRIW, which was developed and used widely in Japan. The model includes three sub- models describing phenological development, biomass accumulation and maturing of rice crop. These processes are formulated to include response nature of rice plant to weather condition. This model inherently was developed to predict rice growth and yield at plot paddy scale. We applied it to evaluate the large scale rice production with keeping the same model structure. Alternatively, we assumed the parameters as stochastic variables. In order to let the model catch up actual yield at larger scale, model parameters were determined based on agricultural statistical data of each prefecture of Japan together with weather data averaged over the region. The posterior probability distribution functions (PDFs) of parameters included in the model were obtained using Bayesian inference. The MCMC (Markov Chain Monte Carlo) algorithm was conducted to numerically solve the Bayesian theorem. For evaluating the year-to-year changes in rice growth/yield under this framework, we firstly iterate simulations with set of parameter values sampled from the estimated posterior PDF of each parameter and then take the ensemble mean weighted with the posterior PDFs. We will also present another example for maize productivity in China. The framework proposed here provides us information on uncertainties, possibilities and limitations on future improvements in crop model as well.

Makeup of the genetic correlation between milk production traits using genome-wide single nucleotide polymorphism information.

PubMed

van Binsbergen, R; Veerkamp, R F; Calus, M P L

2012-04-01

The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

CT contrast predicts pancreatic cancer treatment response to verteporfin-based photodynamic therapy

NASA Astrophysics Data System (ADS)

Jermyn, Michael; Davis, Scott C.; Dehghani, Hamid; Huggett, Matthew T.; Hasan, Tayyaba; Pereira, Stephen P.; Bown, Stephen G.; Pogue, Brian W.

2014-04-01

The goal of this study was to determine dominant factors affecting treatment response in pancreatic cancer photodynamic therapy (PDT), based on clinically available information in the VERTPAC-01 trial. This trial investigated the safety and efficacy of verteporfin PDT in 15 patients with locally advanced pancreatic adenocarcinoma. CT scans before and after contrast enhancement from the 15 patients in the VERTPAC-01 trial were used to determine venous-phase blood contrast enhancement and this was correlated with necrotic volume determined from post-treatment CT scans, along with estimation of optical absorption in the pancreas for use in light modeling of the PDT treatment. Energy threshold contours yielded estimates for necrotic volume based on this light modeling. Both contrast-derived venous blood content and necrotic volume from light modeling yielded strong correlations with observed necrotic volume (R2 = 0.85 and 0.91, respectively). These correlations were much stronger than those obtained by correlating energy delivered versus necrotic volume in the VERTPAC-01 study and in retrospective analysis from a prior clinical study. This demonstrates that contrast CT can provide key surrogate dosimetry information to assess treatment response. It also implies that light attenuation is likely the dominant factor in the VERTPAC treatment response, as opposed to other factors such as drug distribution. This study is the first to show that contrast CT provides needed surrogate dosimetry information to predict treatment response in a manner which uses standard-of-care clinical images, rather than invasive dosimetry methods.

A Model for Simulating the Response of Aluminum Honeycomb Structure to Transverse Loading

NASA Technical Reports Server (NTRS)

Ratcliffe, James G.; Czabaj, Michael W.; Jackson, Wade C.

2012-01-01

A 1-dimensional material model was developed for simulating the transverse (thickness-direction) loading and unloading response of aluminum honeycomb structure. The model was implemented as a user-defined material subroutine (UMAT) in the commercial finite element analysis code, ABAQUS(Registered TradeMark)/Standard. The UMAT has been applied to analyses for simulating quasi-static indentation tests on aluminum honeycomb-based sandwich plates. Comparison of analysis results with data from these experiments shows overall good agreement. Specifically, analyses of quasi-static indentation tests yielded accurate global specimen responses. Predicted residual indentation was also in reasonable agreement with measured values. Overall, this simple model does not involve a significant computational burden, which makes it more tractable to simulate other damage mechanisms in the same analysis.

Simulating large-scale crop yield by using perturbed-parameter ensemble method

NASA Astrophysics Data System (ADS)

Iizumi, T.; Yokozawa, M.; Sakurai, G.; Nishimori, M.

2010-12-01

Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence is still high in most grids regardless of the countries. However, the model showed comparatively low reproducibility in the slope areas, such as around the Rocky Mountains in South Dakota, around the Great Xing'anling Mountains in Heilongjiang, and around the Brazilian Plateau. As there is a wide-ranging local climate conditions in the complex terrain, such as the slope of mountain, the GCM grid-scale weather inputs is likely one of major sources of error. The results of this study highlight the benefits of the perturbed-parameter ensemble method in simulating crop yield on a GCM grid scale: (1) the posterior PDF of parameter could quantify the uncertainty of parameter value of the crop model associated with the local crop production aspects; (2) the method can explicitly account for the uncertainty of parameter value in the crop model simulations; (3) the method achieve a Monte Carlo approximation of probability of sub-grid scale yield, accounting for the nonlinear response of crop yield to weather and management; (4) the method is therefore appropriate to aggregate the simulated sub-grid scale yields to a grid-scale yield and it may be a reason for high performance of the model in capturing inter-annual variation of yield.

Dynamic responses of concrete-filled steel tubular member under axial compression considering creep effect

NASA Astrophysics Data System (ADS)

Jiang, X. T.; Wang, Y. D.; Dai, C. H.; Ding, M.

2017-08-01

The finite element model of concrete-filled steel tubular member was established by the numerical analysis software considering material nonlinearity to analyze concrete creep effect on the dynamic responses of the member under axial compression and lateral impact. In the model, the constitutive model of core concrete is the plastic damage model, that of steel is the Von Mises yield criterion and kinematic hardening model, and the creep effect at different ages is equivalent to the change of concrete elastic modulus. Then the dynamic responses of concrete-filled steel tubular member considering creep effects was simulated, and the effects of creep on contact time, impact load, deflection, stress and strain were discussed. The fruits provide a scientific basis for the design of the impact resistance of concrete filled steel tubular members.

Optimization of production conditions for activated carbons from Tamarind wood by zinc chloride using response surface methodology.

PubMed

Sahu, J N; Acharya, Jyotikusum; Meikap, B C

2010-03-01

The low-cost activated carbon was prepared from Tamarind wood an agricultural waste material, by chemical activation with zinc chloride. Activated carbon adsorption is an effective means for reducing organic chemicals, chlorine, heavy metals and unpleasant tastes and odours in effluent or colored substances from gas or liquid streams. Central composite design (CCD) was applied to study the influence of activation temperature, chemical ratio of zinc chloride to Tamarind wood and activation time on the chemical activation process of Tamarind wood. Two quadratic models were developed for yield of activated carbon and adsorption of malachite green oxalate using Design-Expert software. The models were used to calculate the optimum operating conditions for production of activated carbon providing a compromise between yield and adsorption of the process. The yield (45.26 wt.%) and adsorption (99.9%) of the activated carbon produced at these operating conditions showed an excellent agreement with the amounts predicted by the models. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Optimization of microwave-assisted extraction (MAE) of coriander phenolic antioxidants - response surface methodology approach.

PubMed

Zeković, Zoran; Vladić, Jelena; Vidović, Senka; Adamović, Dušan; Pavlić, Branimir

2016-10-01

Microwave-assisted extraction (MAE) of polyphenols from coriander seeds was optimized by simultaneous maximization of total phenolic (TP) and total flavonoid (TF) yields, as well as maximized antioxidant activity determined by 1,1-diphenyl-2-picrylhydrazyl and reducing power assays. Box-Behnken experimental design with response surface methodology (RSM) was used for optimization of MAE. Extraction time (X1 , 15-35 min), ethanol concentration (X2 , 50-90% w/w) and irradiation power (X3 , 400-800 W) were investigated as independent variables. Experimentally obtained values of investigated responses were fitted to a second-order polynomial model, and multiple regression analysis and analysis of variance were used to determine fitness of the model and optimal conditions. The optimal MAE conditions for simultaneous maximization of polyphenol yield and increased antioxidant activity were an extraction time of 19 min, an ethanol concentration of 63% and an irradiation power of 570 W, while predicted values of TP, TF, IC50 and EC50 at optimal MAE conditions were 311.23 mg gallic acid equivalent per 100 g dry weight (DW), 213.66 mg catechin equivalent per 100 g DW, 0.0315 mg mL(-1) and 0.1311 mg mL(-1) respectively. RSM was successfully used for multi-response optimization of coriander seed polyphenols. Comparison of optimized MAE with conventional extraction techniques confirmed that MAE provides significantly higher polyphenol yields and extracts with increased antioxidant activity. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Neutron - Alpha irradiation response of superheated emulsion detectors

NASA Astrophysics Data System (ADS)

Felizardo, M.; Morlat, T.; Girard, T. A.; Kling, A.; Fernandes, A. C.; Marques, J. G.; Carvalho, F.; Ramos, A. R.

2017-08-01

We report new experimental investigations of the response of single superheated emulsion detectors with small droplet (<30 μm radii) size distributions to both α- and neutron irradiations. Analysis of the results in terms of the underlying detector physics yields a toy model which reasonably reproduces the observations, and identifies the initial energy of the α in the liquid and distribution of droplet sizes as primarily responsible for the detector capacity to distinguish between nuclear recoil and α events.

Response Surface Methodology for Optimizing the Production of Biosurfactant by Candida tropicalis on Industrial Waste Substrates

PubMed Central

Almeida, Darne G.; Soares da Silva, Rita de Cássia F.; Luna, Juliana M.; Rufino, Raquel D.; Santos, Valdemir A.; Sarubbo, Leonie A.

2017-01-01

Biosurfactant production optimization by Candida tropicalis UCP0996 was studied combining central composite rotational design (CCRD) and response surface methodology (RSM). The factors selected for optimization of the culture conditions were sugarcane molasses, corn steep liquor, waste frying oil concentrations and inoculum size. The response variables were surface tension and biosurfactant yield. All factors studied were important within the ranges investigated. The two empirical forecast models developed through RSM were found to be adequate for describing biosurfactant production with regard to surface tension (R2 = 0.99833) and biosurfactant yield (R2 = 0.98927) and a very strong, negative, linear correlation was found between the two response variables studied (r = −0.95). The maximum reduction in surface tension and the highest biosurfactant yield were 29.98 mNm−1 and 4.19 gL−1, respectively, which were simultaneously obtained under the optimum conditions of 2.5% waste frying oil, 2.5%, corn steep liquor, 2.5% molasses, and 2% inoculum size. To validate the efficiency of the statistically optimized variables, biosurfactant production was also carried out in 2 and 50 L bioreactors, with yields of 5.87 and 7.36 gL−1, respectively. Finally, the biosurfactant was applied in motor oil dispersion, reaching up to 75% dispersion. Results demonstrated that the CCRD was suitable for identifying the optimum production conditions and that the new biosurfactant is a promising dispersant for application in the oil industry. PMID:28223971

Modeling human vestibular responses during eccentric rotation and off vertical axis rotation

NASA Technical Reports Server (NTRS)

Merfeld, D. M.; Paloski, W. H. (Principal Investigator)

1995-01-01

A mathematical model has been developed to help explain human multi-sensory interactions. The most important constituent of the model is the hypothesis that the nervous system incorporates knowledge of sensory dynamics into an "internal model" of these dynamics. This internal model allows the nervous system to integrate the sensory information from many different sensors into a coherent estimate of self-motion. The essence of the model is unchanged from a previously published model of monkey eye movement responses; only a few variables have been adjusted to yield the prediction of human responses. During eccentric rotation, the model predicts that the axis of eye rotation shifts slightly toward alignment with gravito-inertial force. The model also predicts that the time course of the perception of tilt following the acceleration phase of eccentric rotation is much slower than that during deceleration. During off vertical axis rotation (OVAR) the model predicts a small horizontal bias along with small horizontal, vertical, and torsional oscillations. Following OVAR stimulation, when stopped right- or left-side down, a small vertical component is predicted that decays with the horizontal post-rotatory response. All of the predictions are consistent with measurements of human responses.

A Novel mouse model of enhanced proteostasis: Full-length human heat shock factor 1 transgenic mice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, Anson, E-mail: piercea2@uthscsa.edu; Barshop Institute for Longevity and Aging Studies, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229; The Department of Veteran's Affairs, South Texas Veterans Health Care System, San Antonio, Texas, 78284

2010-11-05

Research highlights: {yields} Development of mouse overexpressing native human HSF1 in all tissues including CNS. {yields} HSF1 overexpression enhances heat shock response at whole-animal and cellular level. {yields} HSF1 overexpression protects from polyglutamine toxicity and favors aggresomes. {yields} HSF1 overexpression enhances proteostasis at the whole-animal and cellular level. -- Abstract: The heat shock response (HSR) is controlled by the master transcriptional regulator heat shock factor 1 (HSF1). HSF1 maintains proteostasis and resistance to stress through production of heat shock proteins (HSPs). No transgenic model exists that overexpresses HSF1 in tissues of the central nervous system (CNS). We generated a transgenicmore » mouse overexpressing full-length non-mutant HSF1 and observed a 2-4-fold increase in HSF1 mRNA and protein expression in all tissues studied of HSF1 transgenic (HSF1{sup +/0}) mice compared to wild type (WT) littermates, including several regions of the CNS. Basal expression of HSP70 and 90 showed only mild tissue-specific changes; however, in response to forced exercise, the skeletal muscle HSR was more elevated in HSF1{sup +/0} mice compared to WT littermates and in fibroblasts following heat shock, as indicated by levels of inducible HSP70 mRNA and protein. HSF1{sup +/0} cells elicited a significantly more robust HSR in response to expression of the 82 repeat polyglutamine-YFP fusion construct (Q82YFP) and maintained proteasome-dependent processing of Q82YFP compared to WT fibroblasts. Overexpression of HSF1 was associated with fewer, but larger Q82YFP aggregates resembling aggresomes in HSF1{sup +/0} cells, and increased viability. Therefore, our data demonstrate that tissues and cells from mice overexpressing full-length non-mutant HSF1 exhibit enhanced proteostasis.« less

Comparison of SVAT models for simulating and optimizing deficit irrigation systems in arid and semi-arid countries under climate variability

NASA Astrophysics Data System (ADS)

Kloss, Sebastian; Schuetze, Niels; Schmitz, Gerd H.

2010-05-01

The strong competition for fresh water in order to fulfill the increased demand for food worldwide has led to a renewed interest in techniques to improve water use efficiency (WUE) such as controlled deficit irrigation. Furthermore, as the implementation of crop models into complex decision support systems becomes more and more common, it is imperative to reliably predict the WUE as ratio of water consumption and yield. The objective of this paper is the assessment of the problems the crop models - such as FAO-33, DAISY, and APSIM in this study - face when maximizing the WUE. We applied these crop models for calculating the risk in yield reduction in view of different sources of uncertainty (e.g. climate) employing a stochastic framework for decision support for the planning of water supply in irrigation. The stochastic framework consists of: (i) a weather generator for simulating regional impacts of climate change; (ii) a new tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (iii) the above mentioned models for simulating water transport and crop growth in a sound manner. The results present stochastic crop water production functions (SCWPF) for different crops which can be used as basic tools for assessing the impact of climate variability on the risk for the potential yield. Case studies from India, Oman, Malawi, and France are presented to assess the differences in modeling water stress and yield response for the different crop models.

Bayesian Correction for Misclassification in Multilevel Count Data Models.

PubMed

Nelson, Tyler; Song, Joon Jin; Chin, Yoo-Mi; Stamey, James D

2018-01-01

Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rubin, M. B.; Vorobiev, O.; Vitali, E.

Here, a large deformation thermomechanical model is developed for shock loading of a material that can exhibit elastic and inelastic anisotropy. Use is made of evolution equations for a triad of microstructural vectors m i(i=1,2,3) which model elastic deformations and directions of anisotropy. Specific constitutive equations are presented for a material with orthotropic elastic response. The rate of inelasticity depends on an orthotropic yield function that can be used to model weak fault planes with failure in shear and which exhibits a smooth transition to isotropic response at high compression. Moreover, a robust, strongly objective numerical algorithm is proposed formore » both rate-independent and rate-dependent response. The predictions of the continuum model are examined by comparison with exact steady-state solutions. Also, the constitutive equations are used to obtain a simplified continuum model of jointed rock which is compared with high fidelity numerical solutions that model a persistent system of joints explicitly in the rock medium.« less

Robust Adaptive Control Using a Filtering Action

DTIC Science & Technology

2009-09-01

research performed on this class of control systems , sensitivity to external disturbances and modeling errors together with poor transient response...dissertation, we address the problems of designing a class of Adaptive Control systems which yield fast adaptation, thus good transient response, and...unable to stabilize the system . Although this approach requires more knowledge about the system in order to control it, it is still attractive in cases

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies.

PubMed

Davis, Michael J; Janke, Robert

2018-01-04

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

NASA Astrophysics Data System (ADS)

Davis, Michael J.; Janke, Robert

2018-05-01

The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs). The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quantified previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

Dry-bean production under climate change conditions in the north of Argentina: Risk assessment and economic implications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feijoo, M.; Mestre, F.; Castagnaro, A.

This study evaluates the potential effect of climate change on Dry-bean production in Argentina, combining climate models, a crop productivity model and a yield response model estimation of climate variables on crop yields. The study was carried out in the North agricultural regions of Jujuy, Salta, Santiago del Estero and Tucuman which include the largest areas of Argentina where dry beans are grown as a high input crop. The paper combines the output from a crop model with different techniques of analysis. The scenarios used in this study were generated from the output of two General Circulation Models (GCMs): themore » Goddard Institute for Space Studies model (GISS) and the Canadian Climate Change Model (CCCM). The study also includes a preliminary evaluation of the potential changes in monetary returns taking into account the possible variability of yields and prices, using mean-Gini stochastic dominance (MGSD). The results suggest that large climate change may have a negative impact on the Argentine agriculture sector, due to the high relevance of this product in the export sector. The difference negative effect depends on the varieties of dry bean and also the General Circulation Model scenarios considered for double levels of atmospheric carbon dioxide.« less

Acute promyelocytic leukemia: new issues on pathogenesis and treatment response.

PubMed

Vitoux, Dominique; Nasr, Rihab; de The, Hugues

2007-01-01

Pathogenesis of acute promyelocytic leukemia appears to be one of the best understood among human malignancies. The ability of retinoic acid (RA) and arsenic trioxide to directly target the oncogenic promyelocytic leukemia-retinoic receptor A (PML-RARA) fusion protein also made this disease the first model for oncogene-targeted therapies. A set of recent data has significantly increased the complexity of our view of acute promyelocytic leukemia pathogenesis, as well as of therapeutic response. This review summarizes and discusses these findings, which yield novels questions and models.

Modeling lateral geniculate nucleus response with contrast gain control. Part 2: Analysis

PubMed Central

Cope, Davis; Blakeslee, Barbara; McCourt, Mark E.

2014-01-01

Cope, Blakeslee and McCourt (2013) proposed a class of models for LGN ON-cell behavior consisting of a linear response with divisive normalization by local stimulus contrast. Here we analyze a specific model with the linear response defined by a difference-of-Gaussians filter and a circular Gaussian for the gain pool weighting function. For sinusoidal grating stimuli, the parameter region for band-pass behavior of the linear response is determined, the gain control response is shown to act as a switch (changing from “off” to “on” with increasing spatial frequency), and it is shown that large gain pools stabilize the optimal spatial frequency of the total nonlinear response at a fixed value independent of contrast and stimulus magnitude. Under- and super-saturation as well as contrast saturation occur as typical effects of stimulus magnitude. For circular spot stimuli, it is shown that large gain pools stabilize the spot size that yields the maximum response. PMID:24562034

Development and Characterization of a Rate-Dependent Three-Dimensional Macroscopic Plasticity Model Suitable for Use in Composite Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Rajan, Subramaniam; Blankenhorn, Gunther

2015-01-01

Several key capabilities have been identified by the aerospace community as lacking in the material/models for composite materials currently available within commercial transient dynamic finite element codes such as LS-DYNA. Some of the specific desired features that have been identified include the incorporation of both plasticity and damage within the material model, the capability of using the material model to analyze the response of both three-dimensional solid elements and two dimensional shell elements, and the ability to simulate the response of composites composed with a variety of composite architectures, including laminates, weaves and braids. In addition, a need has been expressed to have a material model that utilizes tabulated experimentally based input to define the evolution of plasticity and damage as opposed to utilizing discrete input parameters (such as modulus and strength) and analytical functions based on curve fitting. To begin to address these needs, an orthotropic macroscopic plasticity based model suitable for implementation within LS-DYNA has been developed. Specifically, the Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The coefficients in the yield function are determined based on tabulated stress-strain curves in the various normal and shear directions, along with selected off-axis curves. Incorporating rate dependence into the yield function is achieved by using a series of tabluated input curves, each at a different constant strain rate. The non-associative flow-rule is used to compute the evolution of the effective plastic strain. Systematic procedures have been developed to determine the values of the various coefficients in the yield function and the flow rule based on the tabulated input data. An algorithm based on the radial return method has been developed to facilitate the numerical implementation of the material model. The presented paper will present in detail the development of the orthotropic plasticity model and the procedures used to obtain the required material parameters. Methods in which a combination of actual testing and selective numerical testing can be combined to yield the appropriate input data for the model will be described. A specific laminated polymer matrix composite will be examined to demonstrate the application of the model.

Analysis of the neutron time-of-flight spectra from inertial confinement fusion experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hatarik, R., E-mail: hatarik1@llnl.gov; Sayre, D. B.; Caggiano, J. A.

2015-11-14

Neutron time-of-flight diagnostics have long been used to characterize the neutron spectrum produced by inertial confinement fusion experiments. The primary diagnostic goals are to extract the d + t → n + α (DT) and d + d → n + {sup 3}He (DD) neutron yields and peak widths, and the amount DT scattering relative to its unscattered yield, also known as the down-scatter ratio (DSR). These quantities are used to infer yield weighted plasma conditions, such as ion temperature (T{sub ion}) and cold fuel areal density. We report on novel methodologies used to determine neutron yield, apparent T{sub ion}, and DSR. These methods invoke a single temperature,more » static fluid model to describe the neutron peaks from DD and DT reactions and a spline description of the DT spectrum to determine the DSR. Both measurements are performed using a forward modeling technique that includes corrections for line-of-sight attenuation and impulse response of the detection system. These methods produce typical uncertainties for DT T{sub ion} of 250 eV, 7% for DSR, and 9% for the DT neutron yield. For the DD values, the uncertainties are 290 eV for T{sub ion} and 10% for the neutron yield.« less

Factor regression for interpreting genotype-environment interaction in bread-wheat trials.

PubMed

Baril, C P

1992-05-01

The French INRA wheat (Triticum aestivum L. em Thell.) breeding program is based on multilocation trials to produce high-yielding, adapted lines for a wide range of environments. Differential genotypic responses to variable environment conditions limit the accuracy of yield estimations. Factor regression was used to partition the genotype-environment (GE) interaction into four biologically interpretable terms. Yield data were analyzed from 34 wheat genotypes grown in four environments using 12 auxiliary agronomic traits as genotypic and environmental covariates. Most of the GE interaction (91%) was explained by the combination of only three traits: 1,000-kernel weight, lodging susceptibility and spike length. These traits are easily measured in breeding programs, therefore factor regression model can provide a convenient and useful prediction method of yield.

Toward disentangling the effect of hydrologic and nitrogen source changes from 1992 to 2001 on incremental nitrogen yield in the contiguous United States

NASA Astrophysics Data System (ADS)

Alam, Md Jahangir; Goodall, Jonathan L.

2012-04-01

The goal of this research was to quantify the relative impact of hydrologic and nitrogen source changes on incremental nitrogen yield in the contiguous United States. Using nitrogen source estimates from various federal data bases, remotely sensed land use data from the National Land Cover Data program, and observed instream loadings from the United States Geological Survey National Stream Quality Accounting Network program, we calibrated and applied the spatially referenced regression model SPARROW to estimate incremental nitrogen yield for the contiguous United States. We ran different model scenarios to separate the effects of changes in source contributions from hydrologic changes for the years 1992 and 2001, assuming that only state conditions changed and that model coefficients describing the stream water-quality response to changes in state conditions remained constant between 1992 and 2001. Model results show a decrease of 8.2% in the median incremental nitrogen yield over the period of analysis with the vast majority of this decrease due to changes in hydrologic conditions rather than decreases in nitrogen sources. For example, when we changed the 1992 version of the model to have nitrogen source data from 2001, the model results showed only a small increase in median incremental nitrogen yield (0.12%). However, when we changed the 1992 version of the model to have hydrologic conditions from 2001, model results showed a decrease of approximately 8.7% in median incremental nitrogen yield. We did, however, find notable differences in incremental yield estimates for different sources of nitrogen after controlling for hydrologic changes, particularly for population related sources. For example, the median incremental yield for population related sources increased by 8.4% after controlling for hydrologic changes. This is in contrast to a 2.8% decrease in population related sources when hydrologic changes are included in the analysis. Likewise we found that median incremental yield from urban watersheds increased by 6.8% after controlling for hydrologic changes—in contrast to the median incremental nitrogen yield from cropland watersheds, which decreased by 2.1% over the same time period. These results suggest that, after accounting for hydrologic changes, population related sources became a more significant contributor of nitrogen yield to streams in the contiguous United States over the period of analysis. However, this study was not able to account for the influence of human management practices such as improvements in wastewater treatment plants or Best Management Practices that likely improved water quality, due to a lack of data for quantifying the impact of these practices for the study area.

Use of Drought Index and Crop Modelling for Drought Impacts Analysis on Maize (Zea mays L.) Yield Loss in Bandung District

NASA Astrophysics Data System (ADS)

Kurniasih, E.; Impron; Perdinan

2017-03-01

Drought impacts on crop yield loss depend on drought magnitude and duration and on plant genotype at every plant growth stages when droughts occur. This research aims to assess the difference calculation results of 2 drought index methods and to study the maize yield loss variability impacted by drought magnitude and duration during maize growth stages in Bandung district, province of West Java, Indonesia. Droughts were quantified by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at 1- to 3-month lags for the January1986-December 2015 period data. Maize yield responses to droughts were simulated by AquaCrop for the January 1986-May 2016 period of growing season. The analysis showed that the SPI and SPEI methods provided similar results in quantifying drought event. Droughts during maize reproductive stages caused the highest maize yield loss.

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

Genetic improvement of total milk yield and total lactation persistency of the first three lactations in dairy cattle.

PubMed

Togashi, K; Lin, C Y

2008-07-01

The objective of this study was to compare 6 selection criteria in terms of 3-parity total milk yield and 9 selection criteria in terms of total net merit (H) comprising 3-parity total milk yield and total lactation persistency. The 6 selection criteria compared were as follows: first-parity milk estimated breeding value (EBV; M1), first 2-parity milk EBV (M2), first 3-parity milk EBV (M3), first-parity eigen index (EI(1)), first 2-parity eigen index (EI(2)), and first 3-parity eigen index (EI(3)). The 9 selection criteria compared in terms of H were M1, M2, M3, EI(1), EI(2), EI(3), and first-parity, first 2-parity, and first 3-parity selection indices (I(1), I(2), and I(3), respectively). In terms of total milk yield, selection on M3 or EI(3) achieved the greatest genetic response, whereas selection on EI(1) produced the largest genetic progress per day. In terms of total net merit, selection on I(3) brought the largest response, whereas selection EI(1) yielded the greatest genetic progress per day. A multiple-lactation random regression test-day model simultaneously yields the EBV of the 3 lactations for all animals included in the analysis even though the younger animals do not have the opportunity to complete the first 3 lactations. It is important to use the first 3 lactation EBV for selection decision rather than only the first lactation EBV in spite of the fact that the first-parity selection criteria achieved a faster genetic progress per day than the 3-parity selection criteria. Under a multiple-lactation random regression animal model analysis, the use of the first 3 lactation EBV for selection decision does not prolong the generation interval as compared with the use of only the first lactation EBV. Thus, it is justified to compare genetic response on a lifetime basis rather than on a per-day basis. The results suggest the use of M3 or EI(3) for genetic improvement of total milk yield and the use of I(3) for genetic improvement of total net merit H. Although this study deals with selection for 3-parity milk production, the same principle applies to selection for lifetime milk production.

Modelling drought-related yield losses in Iberia using remote sensing and multiscalar indices

NASA Astrophysics Data System (ADS)

Ribeiro, Andreia F. S.; Russo, Ana; Gouveia, Célia M.; Páscoa, Patrícia

2018-04-01

The response of two rainfed winter cereal yields (wheat and barley) to drought conditions in the Iberian Peninsula (IP) was investigated for a long period (1986-2012). Drought hazard was evaluated based on the multiscalar Standardized Precipitation Evapotranspiration Index (SPEI) and three remote sensing indices, namely the Vegetation Condition (VCI), the Temperature Condition (TCI), and the Vegetation Health (VHI) Indices. A correlation analysis between the yield and the drought indicators was conducted, and multiple linear regression (MLR) and artificial neural network (ANN) models were established to estimate yield at the regional level. The correlation values suggested that yield reduces with moisture depletion (low values of VCI) during early-spring and with too high temperatures (low values of TCI) close to the harvest time. Generally, all drought indicators displayed greatest influence during the plant stages in which the crop is photosynthetically more active (spring and summer), rather than the earlier moments of plants life cycle (autumn/winter). Our results suggested that SPEI is more relevant in the southern sector of the IP, while remote sensing indices are rather good in estimating cereal yield in the northern sector of the IP. The strength of the statistical relationships found by MLR and ANN methods is quite similar, with some improvements found by the ANN. A great number of true positives (hits) of occurrence of yield-losses exhibiting hit rate (HR) values higher than 69% was obtained.

Modeling and optimization of anaerobic codigestion of potato waste and aquatic weed by response surface methodology and artificial neural network coupled genetic algorithm.

PubMed

Jacob, Samuel; Banerjee, Rintu

2016-08-01

A novel approach to overcome the acidification problem has been attempted in the present study by codigesting industrial potato waste (PW) with Pistia stratiotes (PS, an aquatic weed). The effectiveness of codigestion of the weed and PW was tested in an equal (1:1) proportion by weight with substrate concentration of 5g total solid (TS)/L (2.5gPW+2.5gPS) which resulted in enhancement of methane yield by 76.45% as compared to monodigestion of PW with a positive synergistic effect. Optimization of process parameters was conducted using central composite design (CCD) based response surface methodology (RSM) and artificial neural network (ANN) coupled genetic algorithm (GA) model. Upon comparison of these two optimization techniques, ANN-GA model obtained through feed forward back propagation methodology was found to be efficient and yielded 447.4±21.43LCH4/kgVSfed (0.279gCH4/kgCODvs) which is 6% higher as compared to the CCD-RSM based approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Box-Behnken design for investigation of microwave-assisted extraction of patchouli oil

NASA Astrophysics Data System (ADS)

Kusuma, Heri Septya; Mahfud, Mahfud

2015-12-01

Microwave-assisted extraction (MAE) technique was employed to extract the essential oil from patchouli (Pogostemon cablin). The optimal conditions for microwave-assisted extraction of patchouli oil were determined by response surface methodology. A Box-Behnken design (BBD) was applied to evaluate the effects of three independent variables (microwave power (A: 400-800 W), plant material to solvent ratio (B: 0.10-0.20 g mL-1) and extraction time (C: 20-60 min)) on the extraction yield of patchouli oil. The correlation analysis of the mathematical-regression model indicated that quadratic polynomial model could be employed to optimize the microwave extraction of patchouli oil. The optimal extraction conditions of patchouli oil was microwave power 634.024 W, plant material to solvent ratio 0.147648 g ml-1 and extraction time 51.6174 min. The maximum patchouli oil yield was 2.80516% under these optimal conditions. Under the extraction condition, the experimental values agreed with the predicted results by analysis of variance. It indicated high fitness of the model used and the success of response surface methodology for optimizing and reflect the expected extraction condition.

Microwave optimization of mucilage extraction from Opuntia ficus indica Cladodes.

PubMed

Felkai-Haddache, Lamia; Dahmoune, Farid; Remini, Hocine; Lefsih, Khalef; Mouni, Lotfi; Madani, Khodir

2016-03-01

In this study, microwave-assisted extraction (MAE) of polysaccharides from Opuntia ficus indica Cladodes were investigated using response surface methodology (RSM). The effects of three extraction factors on the yield of mucilage were examined. The results indicated that the optimum extraction conditions were determined as follows: microwave power X1, 700 W; extraction time X2, 5.15 minand ratio water/raw material X3, 4.83 mL/g at fixed pH 11. Under these optimal extraction conditions, mucilage yield was found to be Y, 25.6%. A comparison between the model results and experimental data gave a high correlation coefficient (R(2)=0.88), adjusted coefficient (Radj=0.83) and low root mean square error (RMSE=2.45) and showed that the two models were able to predict a mucilage yield by green extraction microwave process. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of process variables by response surface methodology for malachite green dye removal using lime peel activated carbon

NASA Astrophysics Data System (ADS)

Ahmad, Mohd Azmier; Afandi, Nur Syahidah; Bello, Olugbenga Solomon

2017-05-01

This study investigates the adsorptive removal of malachite green (MG) dye from aqueous solutions using chemically modified lime-peel-based activated carbon (LPAC). The adsorbent prepared was characterized using FTIR, SEM, Proximate analysis and BET techniques, respectively. Central composite design (CCD) in response surface methodology (RSM) was used to optimize the adsorption process. The effects of three variables: activation temperature, activation time and chemical impregnation ratio (IR) using KOH and their effects on percentage of dye removal and LPAC yield were investigated. Based on CCD design, quadratic models and two factor interactions (2FI) were developed correlating the adsorption variables to the two responses. Analysis of variance (ANOVA) was used to judge the adequacy of the model. The optimum conditions of MG dye removal using LPAC are: activation temperature (796 °C), activation time (1.0 h) and impregnation ratio (2.6), respectively. The percentage of MG dye removal obtained was 94.68 % resulting in 17.88 % LPAC yield. The percentage of error between predicted and experimental results for the removal of MG dye is 0.4 %. Model prediction was in good agreement with experimental results and LPAC was found to be effective in removing MG dye from aqueous solution.

A study on the plasticity of soda-lime silica glass via molecular dynamics simulations.

PubMed

Urata, Shingo; Sato, Yosuke

2017-11-07

Molecular dynamics (MD) simulations were applied to construct a plasticity model, which enables one to simulate deformations of soda-lime silica glass (SLSG) by using continuum methods. To model the plasticity, stress induced by uniaxial and a variety of biaxial deformations was measured by MD simulations. We found that the surfaces of yield and maximum stresses, which are evaluated from the equivalent stress-strain curves, are reasonably represented by the Mohr-Coulomb ellipsoid. Comparing a finite element model using the constructed plasticity model to a large scale atomistic model on a nanoindentation simulation of SLSG reveals that the empirical method is accurate enough to evaluate the SLSG mechanical responses. Furthermore, the effect of ion-exchange on the SLSG plasticity was examined by using MD simulations. As a result, it was demonstrated that the effects of the initial compressive stress on the yield and maximum stresses are anisotropic contrary to our expectations.

A study on the plasticity of soda-lime silica glass via molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Urata, Shingo; Sato, Yosuke

2017-11-01

Molecular dynamics (MD) simulations were applied to construct a plasticity model, which enables one to simulate deformations of soda-lime silica glass (SLSG) by using continuum methods. To model the plasticity, stress induced by uniaxial and a variety of biaxial deformations was measured by MD simulations. We found that the surfaces of yield and maximum stresses, which are evaluated from the equivalent stress-strain curves, are reasonably represented by the Mohr-Coulomb ellipsoid. Comparing a finite element model using the constructed plasticity model to a large scale atomistic model on a nanoindentation simulation of SLSG reveals that the empirical method is accurate enough to evaluate the SLSG mechanical responses. Furthermore, the effect of ion-exchange on the SLSG plasticity was examined by using MD simulations. As a result, it was demonstrated that the effects of the initial compressive stress on the yield and maximum stresses are anisotropic contrary to our expectations.

Simulation of crop yield variability by improved root-soil-interaction modelling

NASA Astrophysics Data System (ADS)

Duan, X.; Gayler, S.; Priesack, E.

2009-04-01

Understanding the processes and factors that govern the within-field variability in crop yield has attached great importance due to applications in precision agriculture. Crop response to environment at field scale is a complex dynamic process involving the interactions of soil characteristics, weather conditions and crop management. The numerous static factors combined with temporal variations make it very difficult to identify and manage the variability pattern. Therefore, crop simulation models are considered to be useful tools in analyzing separately the effects of change in soil or weather conditions on the spatial variability, in order to identify the cause of yield variability and to quantify the spatial and temporal variation. However, tests showed that usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability, while their performance on crop growth simulation under more homogeneous and mainly non-limiting conditions was sufficent to simulate average yields at the field-scale. On a study site in South Germany, within-field variability in crop growth has been documented since years. After detailed analysis and classification of the soil patterns, two site specific factors, the plant-available-water and the O2 deficiency, were considered as the main causes of the crop growth variability in this field. Based on our measurement of root distribution in the soil profile, we hypothesize that in our case the insufficiency of the applied crop models to simulate the yield variability can be due to the oversimplification of the involved root models which fail to be sensitive to different soil conditions. In this study, the root growth model described by Jones et al. (1991) was adapted by using data of root distributions in the field and linking the adapted root model to the CERES crop model. The ability of the new root model to increase the sensitivity of the CERES crop models to different enviromental conditions was then evaluated by means of comparison of the simualtion results with measured data and by scenario calculations.

LABORATORY-SCALE SIMULATION OF RUNOFF RESPONSE FROM PERVIOUS-IMPERVIOUS SYSTEMS

EPA Science Inventory

Urban development yields landscapes that are composites of impervious and pervious areas, with a consequent reduction in infiltration and increase in stormwater runoff. Although basic rainfall-runoff models are used in the vast majority of runoff prediction in urban landscapes, t...

Barley (Hordeum vulgare) circadian clock genes can respond rapidly to temperature in an EARLY FLOWERING 3-dependent manner

PubMed Central

Ford, Brett; Deng, Weiwei; Clausen, Jenni; Oliver, Sandra; Boden, Scott; Hemming, Megan; Trevaskis, Ben

2016-01-01

An increase in global temperatures will impact future crop yields. In the cereal crops wheat and barley, high temperatures accelerate reproductive development, reducing the number of grains per plant and final grain yield. Despite this relationship between temperature and cereal yield, it is not clear what genes and molecular pathways mediate the developmental response to increased temperatures. The plant circadian clock can respond to changes in temperature and is important for photoperiod-dependent flowering, and so is a potential mechanism controlling temperature responses in cereal crops. This study examines the relationship between temperature, the circadian clock, and the expression of flowering-time genes in barley (Hordeum vulgare), a crop model for temperate cereals. Transcript levels of barley core circadian clock genes were assayed over a range of temperatures. Transcript levels of core clock genes CCA1, GI, PRR59, PRR73, PRR95, and LUX are increased at higher temperatures. CCA1 and PRR73 respond rapidly to a decrease in temperature whereas GI and PRR59 respond rapidly to an increase in temperature. The response of GI and the PRR genes to changes in temperature is lost in the elf3 mutant indicating that their response to temperature may be dependent on a functional ELF3 gene. PMID:27580625

Climate Change and Projected Impacts in Agriculture: an Example on Mediterranean Crops

NASA Astrophysics Data System (ADS)

Ferrise, R.; Moriondo, M.; Bindi, M.

2009-04-01

Recently, the availability of multi-model ensemble prediction methods has permitted the assignment of likelihoods to future climate projections. This allowed moving from the scenario-based approach to the risk-based approach in assessing the effects of climate change, thus providing more useful information for decision-makers that, as reported by Schneider (2001), need probability estimates to assess the seriousness of the projected impacts. The probabilistic approach to evaluate crop response to climate change mainly consists in applying an impact model (such as crop growth model) to a very large number of climate projections so to provide a probabilistic distribution of the variable selected to evaluate the impact. By comparing the outputs of the multi-simulation with a critical threshold (such as minimum yield below which it is not admissible to fall), it is possible to evaluate the risk related to future climate conditions. Unfortunately, such an approach is a time-consuming process due to the large number of model runs needed for such a procedure. An alternative method relies on the set up of impact response surfaces (RS) with respect to key climatic variables on which a probabilistic representation of projected changes in the same climatic variables may be overlaid (Fronzek et al. 2008). This approach was exploited within the ENSEMBLES EU Project aiming at assessing climate change impact on typical Mediterranean crops. This work presents the results of the project with a particular concerning about the assessment of risk, of durum wheat (T. turgidum L. subsp. durum (Desf.) Husn) and grapevine (Vitis vinifera L.) yield falling below fixed thresholds, using probabilistic information about future climate. Methodology The simple mechanistic crop growth models, SIRIUS Quality (Jamieson et al., 1998) and VITE-model (Bindi et al., 1997a,b), were selected to respectively simulate durum wheat and grapevine yields in present and future scenarios. SIRIUS Quality is a wheat simulation model that calculates biomass production from photosynthetically active radiation and grain growth from simple partition rules. VITE-model is a model that uses a simplified mechanistic approach based on the accumulated degree days, the radiation use efficiency and the fruit biomass index to simulate the main processes regulating grapevine development, growth and yield. The selected crop growth models were adopted to create yield RSs of both crops over the suitable cultivated area in the Mediterranean Basin. Yield RSs were calculated performing a scenario sensitivity analysis by altering the baseline climate with respect to temperature and precipitation changes. The baseline climate consisted of 30 years (1975-2005) of daily minimum and maximum temperatures, rainfall and global radiation. Meteorological data were extracted from the MARS JRC Archive and are referred to a grid with a spatial resolution of 50 Km x 50 Km covering the whole European area. The sensitivity analysis was performed for precipitation changes (from -40% to 20%) and temperature changes (from 0°C to +8°C), uniformly applied across all the year. To take in account for the effect of rising CO2, the yield RSs for future periods, were produced considering CO2 air concentration level according to the A1B SRES emission scenario. For each rainfall and temperature combination the average yield over the 30-years period was calculated. The probabilistic distribution of future yields was estimated by applying a bilinear interpolative method to overlap, onto the RSs, the data from perturbed physics experiment of Hadley Centre for future scenarios (joint distribution of annual temperature and rainfall changes). Critical thresholds of impact were determined by calculating, for each grid cell, the distribution of the 30-years average yield according to the joint distribution data for present period (1990-2010) and selecting the values that correspond to the 20th percentile of the cumulative distribution. Finally, future yields were compared with yield threshold to assess the risk of yield shortfall that, in each time period, was defined as the percentage of projected yields that not overcome the selected threshold. Results Maps of durum wheat and grapevine low productivity risk were generated for the next century over the Mediterranean Basin. For durum wheat, with the exception of Portugal and Southern Spain, in the next 30 years risk of low crop productivity shows an overall reduction, due to the fertilizing effect of CO2 increase that counterbalances for the negative impact of rising temperature and reducing rainfall. Thereafter, these latter negative effects become greater and the risk progressively increases starting from lower latitudes. Maximum risk was estimated in 2060 when strong reductions in yield were accounted all over the study area. The smaller reductions in risk, estimated for the end of the next century, may be explained by the greater uncertainty in climate projections. South Portugal, South Spain and Peloponnesus resulted the most vulnerable areas showing increase in risk probability up to 50%, while risk in Galicia, Slovenia, Croatia and central-southern France always resulted lower then present time. As regard grapevine, in the great part of the case study area, the yield seems to have beneficial effect from future climate change. In Central-Western Europe and at lower latitudes the projected yields never fall below the risk threshold, indicating a prevailing effect of CO2 fertilisation. By the other hand, Central-Northern Italy and North of Greece result the most vulnerable areas. In these regions the likelihood of reduced yields quickly rises and remains very high (>50%) until the end of the century, denoting a greater negative effect of temperature and rainfall. Conclusions From these results it may be argued that the impact of future climate change on crop yields is the resultant of the contrasting effects of changes in temperature and precipitation, CO2 increase and uncertainty in climate projections. The intensity of these effects is very site and crop dependent and may vary with time, differently affecting the assessment of risk. As a consequence, the patterns of risk of low crop productivity will change depending on which of these effects will prevail. References Bindi M. et al., 1997a "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). I. Model description". Vitis 36:67-71 Bindi M. et al., 1997b "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). II. Model validation". Vitis 36:73-76 Carter T. et al., 2006 "". Fronzek S. et al 2008 "Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia". Climatic Change (submitted) Jamieson et al., 1998 "Sirius: a mechanistic model of wheat response to environmental variation". Eur. J. Agron. 8:161-179. Schneider S. 2001 "What is ‘dangerous' climate change?". Nature 411:17-19

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Subcritical water liquefaction of oil palm fruit press fiber in the presence of sodium hydroxide: an optimisation study using response surface methodology.

PubMed

Mazaheri, Hossein; Lee, Keat Teong; Bhatia, Subhash; Mohamed, Abdul Rahman

2010-12-01

Thermal decomposition of oil palm fruit press fiber (FPF) into a liquid product (LP) was achieved using subcritical water treatment in the presence of sodium hydroxide in a high pressure batch reactor. This study uses experimental design and process optimisation tools to maximise the LP yield using response surface methodology (RSM) with central composite rotatable design (CCRD). The independent variables were temperature, residence time, particle size, specimen loading, and additive loading. The mathematical model that was developed fit the experimental results well for all of the response variables that were studied. The optimal conditions were found to be a temperature of 551 K, a residence time of 40 min, a particle size of 710-1000 microm, a specimen loading of 5 g, and a additive loading of 9 wt.% to achieve a LP yield of 76.16%. 2010 Elsevier Ltd. All rights reserved.

Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes.

PubMed

Song, Yi; Du, Bingjian; Zhou, Ting; Han, Bing; Yu, Fei; Yang, Rui; Hu, Xiaosong; Ni, Yuanying; Li, Quanhong

2011-02-01

In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from defatted peanut cake. A central composite design including independent variables, such as extraction temperature (x(1)), extraction time (x(2)), and ethanol concentration (x(3)) was used. Selected response which evaluates the extraction process was polysaccharide yield, and the second-order model obtained for polysaccharide yield revealed coefficient of determination of 97.81%. The independent variable with the largest effect on response was ethanol concentration (x(3)). The optimum extraction conditions were found to be extraction temperature 48.7°C, extraction time 1.52 h, and ethanol concentration of 61.9% (v/v), respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 25.89%. The results of structural analysis showed that the main composition of defatted peanut cake polysaccharide was α-galactose. 2010 Elsevier Ltd. All rights reserved.

3D Material Response Analysis of PICA Pyrolysis Experiments

NASA Technical Reports Server (NTRS)

Oliver, Brandon A.

2017-01-01

Primarily interested in improving ablation modeling for use in inverse reconstruction of flight environments on ablative heat shields. Ablation model is essentially a component of the heat flux sensor, so model uncertainties lead to measurement uncertainties. Non-equilibrium processes have been known to be significant in low density ablators for a long time, but increased accuracy requirements of the reconstruction process necessitates incorporating this physical effect. Attempting to develop a pyrolysis model for implementation in material response based on the PICA data produced by Bessire and Minton. Pyrolysis gas species molar yields as a function of temperature and heating rate. Several problems encountered while trying to fit Arrhenius models to the data led to further investigation of the experimental setup.

Quantification of ozone exposure- and stomatal uptake-yield response relationships for soybean in Northeast China.

PubMed

Zhang, Weiwei; Feng, Zhaozhong; Wang, Xiaoke; Liu, Xiaobing; Hu, Enzhu

2017-12-01

High ground-level O 3 is a new threat to agricultural production in Northeast China with the increasing ambient O 3 concentration. Little is known about its impacts on soybean production in this key agricultural region. Accumulated O 3 exposure-response and stomatal O 3 flux-response relationships were developed during two continuous growing seasons to evaluate O 3 -induced yield reduction of four typical soybean cultivars in Northeast China. Results showed that critical levels of AOT40 (accumulated hourly O 3 concentrations over a threshold of 40nmol·mol -1 ), SUM06 (sum of all hourly average O 3 concentrations over 0.06μmol·mol -1 ) and W126 (sum of O 3 concentrations weighted by a sigmoidal function) in relation to 5% reduction in relative seed yield were 4.2, 7.6 and 6.8μmol·mol -1 ·h, respectively. The effect of O 3 on plants was influenced by leaf position in canopy. An improved Jarvis stomatal conductance model including leaf (node) position fitted well with field measurements. The best linear relationship between stomatal O 3 flux and relative soybean yield was obtained when phytotoxic ozone dose was integrated over a threshold of 9.6nmol·m -2 ·s -1 (POD 9.6 ) to represent the detoxification capacity of soybean. POD 9.6 and the commonly used POD 6 in relation to 5% reduction in relative seed yield of soybean were 0.9mmol·m -2 and 1.8mmol·m -2 , respectively. O 3 concentrations above ~38nmol·mol -1 contributed to POD 9.6 and caused seed yield loss in soybean. Current annual yield loss of soybean at ambient O 3 was estimated to range between 23.4% and 30.2%. The O 3 dose-response relationships and corresponding thresholds obtained here will benefit regional O 3 risk assessment on soybean production in Northeast China. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment

NASA Astrophysics Data System (ADS)

Yang, Yanmin; Liu, De Li; Anwar, Muhuddin Rajin; Zuo, Heping; Yang, Yonghui

2014-02-01

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO2) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO2 concentration, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO2 emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021-2040 compared to the baseline period of 1961-1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021-2040) over the baseline (1961-1990) varies from +3.4 to -14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for early sowing wheat varieties with longer growing duration will be a desirable adaptation strategy for mitigating the impact of changing climate on wheat yield.

Quantifying the thermal heat requirement of Brassica in assessing biophysical parameters under semi-arid microenvironments

NASA Astrophysics Data System (ADS)

Adak, Tarun; Chakravarty, N. V. K.

2010-07-01

Evaluation of the thermal heat requirement of Brassica spp. across agro-ecological regions is required in order to understand the further effects of climate change. Spatio-temporal changes in hydrothermal regimes are likely to affect the physiological growth pattern of the crop, which in turn will affect economic yields and crop quality. Such information is helpful in developing crop simulation models to describe the differential thermal regimes that prevail at different phenophases of the crop. Thus, the current lack of quantitative information on the thermal heat requirement of Brassica crops under debranched microenvironments prompted the present study, which set out to examine the response of biophysical parameters [leaf area index (LAI), dry biomass production, seed yield and oil content] to modified microenvironments. Following 2 years of field experiments on Typic Ustocrepts soils under semi-arid climatic conditions, it was concluded that the Brassica crop is significantly responsive to microenvironment modification. A highly significant and curvilinear relationship was observed between LAI and dry biomass production with accumulated heat units, with thermal accumulation explaining ≥80% of the variation in LAI and dry biomass production. It was further observed that the economic seed yield and oil content, which are a function of the prevailing weather conditions, were significantly responsive to the heat units accumulated from sowing to 50% physiological maturity. Linear regression analysis showed that growing degree days (GDD) could indicate 60-70% variation in seed yield and oil content, probably because of the significant response to differential thermal microenvironments. The present study illustrates the statistically strong and significant response of biophysical parameters of Brassica spp. to microenvironment modification in semi-arid regions of northern India.

Support vector machine learning-based fMRI data group analysis.

PubMed

Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A

2007-07-15

To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.

Optimization of microwave-assisted extraction (MAP) for ginseng components by response surface methodology.

PubMed

Kwon, Joong-Ho; Bélanger, Jacqueline M R; Paré, J R Jocelyn

2003-03-26

Response surface methodology (RSM) was applied to predict optimum conditions for microwave-assisted extraction-a MAP technology-of saponin components from ginseng roots. A central composite design was used to monitor the effect of ethanol concentration (30-90%, X(1)) and extraction time (30-270 s, X(2)) on dependent variables, such as total extract yield (Y(1)), crude saponin content (Y(2)), and saponin ratio (Y(3)), under atmospheric pressure conditions when focused microwaves were applied at an emission frequency of 2450 MHz. In MAP under pre-established conditions, correlation coefficients (R (2)) of the models for total extract yield and crude saponin were 0.9841 (p < 0.001) and 0.9704 (p < 0.01). Optimum extraction conditions were predicted for each variable as 52.6% ethanol and 224.7 s in extract yield and as 77.3% ethanol and 295.1 s in crude saponins, respectively. Estimated maximum values at predicted optimum conditions were in good agreement with experimental values.

Optimization of isolation of cellulose from orange peel using sodium hydroxide and chelating agents.

PubMed

Bicu, Ioan; Mustata, Fanica

2013-10-15

Response surface methodology was used to optimize cellulose recovery from orange peel using sodium hydroxide (NaOH) as isolation reagent, and to minimize its ash content using ethylenediaminetetraacetic acid (EDTA) as chelating agent. The independent variables were NaOH charge, EDTA charge and cooking time. Other two constant parameters were cooking temperature (98 °C) and liquid-to-solid ratio (7.5). The dependent variables were cellulose yield and ash content. A second-order polynomial model was used for plotting response surfaces and for determining optimum cooking conditions. The analysis of coefficient values for independent variables in the regression equation showed that NaOH and EDTA charges were major factors influencing the cellulose yield and ash content, respectively. Optimum conditions were defined by: NaOH charge 38.2%, EDTA charge 9.56%, and cooking time 317 min. The predicted cellulose yield was 24.06% and ash content 0.69%. A good agreement between the experimental values and the predicted was observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A glycerol-free process to produce biodiesel by supercritical methyl acetate technology: an optimization study via Response Surface Methodology.

PubMed

Tan, Kok Tat; Lee, Keat Teong; Mohamed, Abdul Rahman

2010-02-01

In this study, fatty acid methyl esters (FAME) have been successfully produced from transesterification reaction between triglycerides and methyl acetate, instead of alcohol. In this non-catalytic supercritical methyl acetate (SCMA) technology, triacetin which is a valuable biodiesel additive is produced as side product rather than glycerol, which has lower commercial value. Besides, the properties of the biodiesel (FAME and triacetin) were found to be superior compared to those produced from conventional catalytic reactions (FAME only). In this study, the effects of various important parameters on the yield of biodiesel were optimized by utilizing Response Surface Methodology (RSM) analysis. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum yield of biodiesel. The optimum conditions were found to be 399 degrees C for reaction temperature, 30 mol/mol of methyl acetate to oil molar ratio and reaction time of 59 min to achieve 97.6% biodiesel yield.

Process optimization of an auger pyrolyzer with heat carrier using response surface methodology.

PubMed

Brown, J N; Brown, R C

2012-01-01

A 1 kg/h auger reactor utilizing mechanical mixing of steel shot heat carrier was used to pyrolyze red oak wood biomass. Response surface methodology was employed using a circumscribed central composite design of experiments to optimize the system. Factors investigated were: heat carrier inlet temperature and mass flow rate, rotational speed of screws in the reactor, and volumetric flow rate of sweep gas. Conditions for maximum bio-oil and minimum char yields were high flow rate of sweep gas (3.5 standard L/min), high heat carrier temperature (∼600 °C), high auger speeds (63 RPM) and high heat carrier mass flow rates (18 kg/h). Regression models for bio-oil and char yields are described including identification of a novel interaction effect between heat carrier mass flow rate and auger speed. Results suggest that auger reactors, which are rarely described in literature, are well suited for bio-oil production. The reactor achieved liquid yields greater than 73 wt.%. Copyright © 2011 Elsevier Ltd. All rights reserved.

Theoretical Development of an Orthotropic Elasto-Plastic Generalized Composite Material Model

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Hoffarth, Canio; Harrington, Joseph; Subramanian, Rajan; Blankenhorn, Gunther

2014-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. While there are several composite material models currently available within LS-DYNA (Registered), there are several features that have been identified that could improve the predictive capability of a composite model. To address these needs, a combined plasticity and damage model suitable for use with both solid and shell elements is being developed and is being implemented into LS-DYNA as MAT_213. A key feature of the improved material model is the use of tabulated stress-strain data in a variety of coordinate directions to fully define the stress-strain response of the material. To date, the model development efforts have focused on creating the plasticity portion of the model. The Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic material model with a non-associative flow rule. The coefficients of the yield function, and the stresses to be used in both the yield function and the flow rule, are computed based on the input stress-strain curves using the effective plastic strain as the tracking variable. The coefficients in the flow rule are computed based on the obtained stress-strain data. The developed material model is suitable for implementation within LS-DYNA for use in analyzing the nonlinear response of polymer composites.

Modeling Fan Effects on the Time Course of Associative Recognition

PubMed Central

Schneider, Darryl W.; Anderson, John R.

2011-01-01

We investigated the time course of associative recognition using the response signal procedure, whereby a stimulus is presented and followed after a variable lag by a signal indicating that an immediate response is required. More specifically, we examined the effects of associative fan (the number of associations that an item has with other items in memory) on speed–accuracy tradeoff functions obtained in a previous response signal experiment involving briefly studied materials and in a new experiment involving well-learned materials. High fan lowered asymptotic accuracy or the rate of rise in accuracy across lags, or both. We developed an Adaptive Control of Thought–Rational (ACT-R) model for the response signal procedure to explain these effects. The model assumes that high fan results in weak associative activation that slows memory retrieval, thereby decreasing the probability that retrieval finishes in time and producing a speed–accuracy tradeoff function. The ACT-R model provided an excellent account of the data, yielding quantitative fits that were as good as those of the best descriptive model for response signal data. PMID:22197797

Evaluation of limited irrigation strategies to improve water use efficiency and wheat yield in the North China Plain.

PubMed

Zhang, Di; Li, Ruiqi; Batchelor, William D; Ju, Hui; Li, Yanming

2018-01-01

The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain.

Agriculture Impacts of Regional Nuclear Conflict

NASA Astrophysics Data System (ADS)

Xia, Lili; Robock, Alan; Mills, Michael; Toon, Owen Brian

2013-04-01

One of the major consequences of nuclear war would be climate change due to massive smoke injection into the atmosphere. Smoke from burning cities can be lofted into the stratosphere where it will have an e-folding lifetime more than 5 years. The climate changes include significant cooling, reduction of solar radiation, and reduction of precipitation. Each of these changes can affect agricultural productivity. To investigate the response from a regional nuclear war between India and Pakistan, we used the Decision Support System for Agrotechnology Transfer agricultural simulation model. We first evaluated the model by forcing it with daily weather data and management practices in China and the USA for rice, maize, wheat, and soybeans. Then we perturbed observed weather data using monthly climate anomalies for a 10-year period due to a simulated 5 Tg soot injection that could result from a regional nuclear war between India and Pakistan, using a total of 100 15 kt atomic bombs, much less than 1% of the current global nuclear arsenal. We computed anomalies using the NASA Goddard Institute for Space Studies ModelE and NCAR's Whole Atmosphere Community Climate Model (WACCM). We perturbed each year of the observations with anomalies from each year of the 10-year nuclear war simulations. We found that different regions respond differently to a regional nuclear war; southern regions show slight increases of crop yields while in northern regions crop yields drop significantly. Sensitivity tests show that temperature changes due to nuclear war are more important than precipitation and solar radiation changes in affecting crop yields in the regions we studied. In total, crop production in China and the USA would decrease 15-50% averaged over the 10 years using both models' output. Simulations forced by ModelE output show smaller impacts than simulations forced by WACCM output at the end of the 10 year period because of the different temperature responses in the two models.

US major crops’ uncertain climate change risks and greenhouse gas mitigation benefits

DOE PAGES

Wing, Ian Sue; Monier, Erwan; Stern, Ari; ...

2015-10-28

In this study, we estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops' yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. Uncontrolled warming's economic effects on major cropsmore » are slightly positive—annual benefits <$4 B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17 B under moderate mitigation, but only $7 B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18 B, generating benefits to moderate (stringent) mitigation as large as $26 B ($20 B).« less

US major crops’ uncertain climate change risks and greenhouse gas mitigation benefits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wing, Ian Sue; Monier, Erwan; Stern, Ari

In this study, we estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops' yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. Uncontrolled warming's economic effects on major cropsmore » are slightly positive—annual benefits <$4 B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17 B under moderate mitigation, but only $7 B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18 B, generating benefits to moderate (stringent) mitigation as large as $26 B ($20 B).« less

Field camera measurements of gradient and shim impulse responses using frequency sweeps.

PubMed

Vannesjo, S Johanna; Dietrich, Benjamin E; Pavan, Matteo; Brunner, David O; Wilm, Bertram J; Barmet, Christoph; Pruessmann, Klaas P

2014-08-01

Applications of dynamic shimming require high field fidelity, and characterizing the shim field dynamics is therefore necessary. Modeling the system as linear and time-invariant, the purpose of this work was to measure the impulse response function with optimal sensitivity. Frequency-swept pulses as inputs are analyzed theoretically, showing that the sweep speed is a key factor for the measurement sensitivity. By adjusting the sweep speed it is possible to achieve any prescribed noise profile in the measured system response. Impulse response functions were obtained for the third-order shim system of a 7 Tesla whole-body MR scanner. Measurements of the shim fields were done with a dynamic field camera, yielding also cross-term responses. The measured shim impulse response functions revealed system characteristics such as response bandwidth, eddy currents and specific resonances, possibly of mechanical origin. Field predictions based on the shim characterization were shown to agree well with directly measured fields, also in the cross-terms. Frequency sweeps provide a flexible tool for shim or gradient system characterization. This may prove useful for applications involving dynamic shimming by yielding accurate estimates of the shim fields and a basis for setting shim pre-emphasis. Copyright © 2013 Wiley Periodicals, Inc.

A new approach to synthesis of benzyl cinnamate: Optimization by response surface methodology.

PubMed

Zhang, Dong-Hao; Zhang, Jiang-Yan; Che, Wen-Cai; Wang, Yun

2016-09-01

In this work, the new approach to synthesis of benzyl cinnamate by enzymatic esterification of cinnamic acid with benzyl alcohol is optimized by response surface methodology. The effects of various reaction conditions, including temperature, enzyme loading, substrate molar ratio of benzyl alcohol to cinnamic acid, and reaction time, are investigated. A 5-level-4-factor central composite design is employed to search for the optimal yield of benzyl cinnamate. A quadratic polynomial regression model is used to analyze the experimental data at a 95% confidence level (P<0.05). The coefficient of determination of this model is found to be 0.9851. Three sets of optimum reaction conditions are established, and the verified experimental trials are performed for validating the optimum points. Under the optimum conditions (40°C, 31mg/mL enzyme loading, 2.6:1 molar ratio, 27h), the yield reaches 97.7%, which provides an efficient processes for industrial production of benzyl cinnamate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of Web tools to predict axillary lymph node metastasis and pathological response to neoadjuvant chemotherapy in breast cancer patients.

PubMed

Sugimoto, Masahiro; Takada, Masahiro; Toi, Masakazu

2014-12-09

Nomograms are a standard computational tool to predict the likelihood of an outcome using multiple available patient features. We have developed a more powerful data mining methodology, to predict axillary lymph node (AxLN) metastasis and response to neoadjuvant chemotherapy (NAC) in primary breast cancer patients. We developed websites to use these tools. The tools calculate the probability of AxLN metastasis (AxLN model) and pathological complete response to NAC (NAC model). As a calculation algorithm, we employed a decision tree-based prediction model known as the alternative decision tree (ADTree), which is an analog development of if-then type decision trees. An ensemble technique was used to combine multiple ADTree predictions, resulting in higher generalization abilities and robustness against missing values. The AxLN model was developed with training datasets (n=148) and test datasets (n=143), and validated using an independent cohort (n=174), yielding an area under the receiver operating characteristic curve (AUC) of 0.768. The NAC model was developed and validated with n=150 and n=173 datasets from a randomized controlled trial, yielding an AUC of 0.787. AxLN and NAC models require users to input up to 17 and 16 variables, respectively. These include pathological features, including human epidermal growth factor receptor 2 (HER2) status and imaging findings. Each input variable has an option of "unknown," to facilitate prediction for cases with missing values. The websites developed facilitate the use of these tools, and serve as a database for accumulating new datasets.

Towards a Simple Constitutive Model for Bread Dough

NASA Astrophysics Data System (ADS)

Tanner, Roger I.

2008-07-01

Wheat flour dough is an example of a soft solid material consisting of a gluten (rubbery) network with starch particles as a filler. The volume fraction of the starch filler is high-typically 60%. A computer-friendly constitutive model has been lacking for this type of material and here we report on progress towards finding such a model. The model must describe the response to small strains, simple shearing starting from rest, simple elongation, biaxial straining, recoil and various other transient flows. A viscoelastic Lodge-type model involving a damage function. which depends on strain from an initial reference state fits the given data well, and it is also able to predict the thickness at exit from dough sheeting, which has been a long-standing unsolved puzzle. The model also shows an apparent rate-dependent yield stress, although no explicit yield stress is built into the model. This behaviour agrees with the early (1934) observations of Schofield and Scott Blair on dough recoil after unloading.

Quantifying the mechanical effects of He, W and He + W ion irradiation on tungsten with spherical nanoindentation

DOE PAGES

Weaver, Jordan S.; Sun, Cheng; Wang, Yongqiang; ...

2017-12-19

Here, recent advances in spherical nanoindentation protocols have proven very useful for capturing the grain-scale mechanical response of different metals. This is achieved by converting the load–displacement response into an effective indentation stress–strain response which reveals latent information such as the elastic–plastic transition or indentation yield strength and work-hardening behavior and subsequently correlating the response with the material structure (e.g., crystal orientation) at the indentation site. Using these protocols, we systematically study and quantify the microscale mechanical effects of He, W, and He + W ion irradiation on commercially pure, polycrystalline tungsten. The indentation stress–strain response is correlated with themore » crystal orientation from electron backscatter diffraction, the defect structure from transmission electron microscopy micrographs, and the stopping range of ions in matter calculations of displacement damage and He concentration. He-implanted grains show a much higher indentation yield strength and saturation stress compared to W-ion-irradiated grains for the same displacement damage. There is also good agreement between the dispersed barrier hardening model with a barrier strength of 0.5–0.8 and void models (Bacon–Kochs–Scattergood and Osetsky–Bacon models) with the experimentally observed changes in indentation strength due to the presence of He bubbles. This finding indicates that a high density (~ 9 × 10 23 m –3) and concentration (~ 1.5 at.%) of small (~ 1 nm diameter) He bubbles can be moderate to strong barriers to dislocation slip in tungsten.« less

Quantifying the mechanical effects of He, W and He + W ion irradiation on tungsten with spherical nanoindentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weaver, Jordan S.; Sun, Cheng; Wang, Yongqiang

Here, recent advances in spherical nanoindentation protocols have proven very useful for capturing the grain-scale mechanical response of different metals. This is achieved by converting the load–displacement response into an effective indentation stress–strain response which reveals latent information such as the elastic–plastic transition or indentation yield strength and work-hardening behavior and subsequently correlating the response with the material structure (e.g., crystal orientation) at the indentation site. Using these protocols, we systematically study and quantify the microscale mechanical effects of He, W, and He + W ion irradiation on commercially pure, polycrystalline tungsten. The indentation stress–strain response is correlated with themore » crystal orientation from electron backscatter diffraction, the defect structure from transmission electron microscopy micrographs, and the stopping range of ions in matter calculations of displacement damage and He concentration. He-implanted grains show a much higher indentation yield strength and saturation stress compared to W-ion-irradiated grains for the same displacement damage. There is also good agreement between the dispersed barrier hardening model with a barrier strength of 0.5–0.8 and void models (Bacon–Kochs–Scattergood and Osetsky–Bacon models) with the experimentally observed changes in indentation strength due to the presence of He bubbles. This finding indicates that a high density (~ 9 × 10 23 m –3) and concentration (~ 1.5 at.%) of small (~ 1 nm diameter) He bubbles can be moderate to strong barriers to dislocation slip in tungsten.« less

Optimization of critical quality attributes in continuous twin-screw wet granulation via design space validated with pilot scale experimental data.

PubMed

Liu, Huolong; Galbraith, S C; Ricart, Brendon; Stanton, Courtney; Smith-Goettler, Brandye; Verdi, Luke; O'Connor, Thomas; Lee, Sau; Yoon, Seongkyu

2017-06-15

In this study, the influence of key process variables (screw speed, throughput and liquid to solid (L/S) ratio) of a continuous twin screw wet granulation (TSWG) was investigated using a central composite face-centered (CCF) experimental design method. Regression models were developed to predict the process responses (motor torque, granule residence time), granule properties (size distribution, volume average diameter, yield, relative width, flowability) and tablet properties (tensile strength). The effects of the three key process variables were analyzed via contour and interaction plots. The experimental results have demonstrated that all the process responses, granule properties and tablet properties are influenced by changing the screw speed, throughput and L/S ratio. The TSWG process was optimized to produce granules with specific volume average diameter of 150μm and the yield of 95% based on the developed regression models. A design space (DS) was built based on volume average granule diameter between 90 and 200μm and the granule yield larger than 75% with a failure probability analysis using Monte Carlo simulations. Validation experiments successfully validated the robustness and accuracy of the DS generated using the CCF experimental design in optimizing a continuous TSWG process. Copyright © 2017 Elsevier B.V. All rights reserved.

An airport community noise-impact assessment model

NASA Technical Reports Server (NTRS)

Deloach, R.

1980-01-01

A computer model was developed to assess the noise impact of an airport on the community which it serves. Assessments are made using the Fractional Impact Method by which a single number describes the community aircraft noise environment in terms of exposed population and multiple event noise level. The model is comprised of three elements: a conventional noise footprint model, a site specific population distribution model, and a dose response transfer function. The footprint model provides the noise distribution for a given aircraft operating scenario. This is combined with the site specific population distribution obtained from a national census data base to yield the number of residents exposed to a given level of noise. The dose response relationship relates noise exposure levels to the percentage of individuals highly annoyed by those levels.

Ultrasonic-assisted extraction and in-vitro antioxidant activity of polysaccharide from Hibiscus leaf.

PubMed

Afshari, Kasra; Samavati, Vahid; Shahidi, Seyed-Ahmad

2015-03-01

The effects of ultrasonic power, extraction time, extraction temperature, and the water-to-raw material ratio on extraction yield of crude polysaccharide from the leaf of Hibiscus rosa-sinensis (HRLP) were optimized by statistical analysis using response surface methodology. The response surface methodology (RSM) was used to optimize HRLP extraction yield by implementing the Box-Behnken design (BBD). The experimental data obtained were fitted to a second-order polynomial equation using multiple regression analysis and also analyzed by appropriate statistical methods (ANOVA). Analysis of the results showed that the linear and quadratic terms of these four variables had significant effects. The optimal conditions for the highest extraction yield of HRLP were: ultrasonic power, 93.59 W; extraction time, 25.71 min; extraction temperature, 93.18°C; and the water to raw material ratio, 24.3 mL/g. Under these conditions, the experimental yield was 9.66±0.18%, which is well in close agreement with the value predicted by the model 9.526%. The results demonstrated that HRLP had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Copyright © 2014 Elsevier B.V. All rights reserved.

Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobell, D; Field, C; Cahill, K

2006-01-10

Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiplemore » climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.« less

Pit-1 gene polymorphism, milk yield, and conformation traits for Italian Holstein-Friesian bulls.

PubMed

Renaville, R; Gengler, N; Vrech, E; Prandi, A; Massart, S; Corradini, C; Bertozzi, C; Mortiaux, F; Burny, A; Portetelle, D

1997-12-01

The growth hormone factor-1/pituitary-specific transcription factor Pit-1 is responsible for the expression of growth hormone in mammals. Mutations in Pit-1 have been found in growth hormone disorders of mice and humans. We studied the eventual association between Pit-1 polymorphism using the HinfI enzyme and the milk yield and conformation traits of 89 Italian Holstein-Friesian bulls. A strategy employing polymerase chain reaction was used to amplify a 451-bp fragment from semen DNA. Digestion of polymerase chain reaction products with HinfI revealed two alleles: allele A was not digested (451-bp fragment), and allele B was cut at one restriction site, generating two fragments of 244 and 207 bp. Three patterns were observed; frequencies were 2.2, 31.5, and 66.3% for AA, AB, and BB, respectively. Fixed and mixed linear models were fitted on daughter yield deviations for milk yields and on deregressed proofs for conformation traits. Predictions were weighted using the inverse of the estimated variance of records. The models used contained mean and gene substitution effects for Pit-1 A allele as fixed effects and random sire effect for the mixed model. The A allele was found to be superior for milk and protein yields, inferior for fat percentage, and superior for body depth, angularity, and rear leg set, which is difficult to explain. A canonical transformation revealed that Pit-1 had three actions, one linked to milk yield traits and angularity, a second linked to body depth and rear leg set, and a third linked to lower fat yields and to higher angularity.

Random regression models to account for the effect of genotype by environment interaction due to heat stress on the milk yield of Holstein cows under tropical conditions.

PubMed

Santana, Mário L; Bignardi, Annaiza Braga; Pereira, Rodrigo Junqueira; Menéndez-Buxadera, Alberto; El Faro, Lenira

2016-02-01

The present study had the following objectives: to compare random regression models (RRM) considering the time-dependent (days in milk, DIM) and/or temperature × humidity-dependent (THI) covariate for genetic evaluation; to identify the effect of genotype by environment interaction (G×E) due to heat stress on milk yield; and to quantify the loss of milk yield due to heat stress across lactation of cows under tropical conditions. A total of 937,771 test-day records from 3603 first lactations of Brazilian Holstein cows obtained between 2007 and 2013 were analyzed. An important reduction in milk yield due to heat stress was observed for THI values above 66 (-0.23 kg/day/THI). Three phases of milk yield loss were identified during lactation, the most damaging one at the end of lactation (-0.27 kg/day/THI). Using the most complex RRM, the additive genetic variance could be altered simultaneously as a function of both DIM and THI values. This model could be recommended for the genetic evaluation taking into account the effect of G×E. The response to selection in the comfort zone (THI ≤ 66) is expected to be higher than that obtained in the heat stress zone (THI > 66) of the animals. The genetic correlations between milk yield in the comfort and heat stress zones were less than unity at opposite extremes of the environmental gradient. Thus, the best animals for milk yield in the comfort zone are not necessarily the best in the zone of heat stress and, therefore, G×E due to heat stress should not be neglected in the genetic evaluation.

The Effect of Calf Gender on Milk Production in Seasonal Calving Cows and Its Impact on Genetic Evaluations

PubMed Central

Hess, Melanie K.; Hess, Andrew S.; Garrick, Dorian J.

2016-01-01

Gender of the calf whose birth initiates lactation could influence whole lactation milk yield of the dam due to hormonal influences on mammary gland development, or through calf gender effects on gestation length. Fetal gender could influence late lactation yields because cows become pregnant at peak lactation. The effects of calf gender sequences in parities 1–3 were assessed by separately fitting animal models to datasets from New Zealand comprising 274 000 Holstein Friesian and 85 000 Jersey cows, decreasing to 12 000 and 4 000 cows by parity 3. The lactation initiated by the birth of a female rather than a male calf was associated with a 0.33–1.1% (p≤0.05) higher milk yield. Female calf gender had carryover effects associated with higher milk yield in second lactations for Holstein Friesians (0.24%; p = 0.01) and third lactations for Jerseys (1.1%; p = 0.01). Cows giving birth to bull calves have 2 day longer gestations, which reduces lactation length in seasonal calving herds. Adding a covariate for lactation length to the animal model eroded some of these calf gender effects, such that calving a female led to higher milk yield only for second lactation Holstein Friesians (1.6%; p = 0.002). The interval centering method generates lower estimates of whole lactation yield when Wood’s lactation curves are shifted to the right by 2 days for male calves and this explained the higher yield in female calves when differences in lactation length were considered. Correlations of estimated breeding values between models including or excluding calf gender sequence were 1.00 for bulls or cows. Calf gender primarily influences milk yield through increased gestation length of male calves, and bias associated with the interval centering method used to estimate whole lactation milk yields. Including information on calf gender is unlikely to have an effect on selection response in New Zealand dairy cattle. PMID:26974166

How changes of climate extremes affect summer and winter crop yields and water productivity in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, D.; Cammarano, D.

2017-12-01

Modeling changes of crop production at regional scale is important to make adaptation measures for sustainably food supply under global change. In this study, we explore how changing climate extremes in the 20th and 21st century affect maize (summer crop) and wheat (winter crop) yields in an agriculturally important region: the southeast United States. We analyze historical (1950-1999) and projected (2006-2055) precipitation and temperature extremes by calculating the changes of 18 climate extreme indices using the statistically downscaled CMIP5 data from 10 general circulation models (GCMs). To evaluate how these climate extremes affect maize and wheat yields, historical baseline and projected maize and wheat yields under RCP4.5 and RCP8.5 scenarios are simulated using the DSSAT-CERES maize and wheat models driven by the same downscaled GCMs data. All of the changes are examined at 110 locations over the study region. The results show that most of the precipitation extreme indices do not have notable change; mean precipitation, precipitation intensity, and maximum 1-day precipitation are generally increased; the number of rainy days is decreased. The temperature extreme indices mostly showed increased values on mean temperature, number of high temperature days, diurnal temperature range, consecutive high temperature days, maximum daily maximum temperature, and minimum daily minimum temperature; the number of low temperature days and number of consecutive low temperature days are decreased. The conditional probabilistic relationships between changes in crop yields and changes in extreme indices suggested different responses of crop yields to climate extremes during sowing to anthesis and anthesis to maturity periods. Wheat yields and crop water productivity for wheat are increased due to an increased CO2 concentration and minimum temperature; evapotranspiration, maize yields, and crop water productivity for wheat are decreased owing to the increased temperature extremes. We found the effects of precipitation changes on both yields are relatively uncertain.

Radiotherapy Dose Fractionation under Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Davison, Matt; Kim, Daero; Keller, Harald

2011-11-01

In radiotherapy, radiation is directed to damage a tumor while avoiding surrounding healthy tissue. Tradeoffs ensue because dose cannot be exactly shaped to the tumor. It is particularly important to ensure that sensitive biological structures near the tumor are not damaged more than a certain amount. Biological tissue is known to have a nonlinear response to incident radiation. The linear quadratic dose response model, which requires the specification of two clinically and experimentally observed response coefficients, is commonly used to model this effect. This model yields an optimization problem giving two different types of optimal dose sequences (fractionation schedules). Which fractionation schedule is preferred depends on the response coefficients. These coefficients are uncertainly known and may differ from patient to patient. Because of this not only the expected outcomes but also the uncertainty around these outcomes are important, and it might not be prudent to select the strategy with the best expected outcome.

Using the hydrologic model mike she to assess disturbance impacts on watershed process and responses across the Southeastern U.S.

Treesearch

Ge Sun; Jianbiao Lu; Steven G. McNulty; James M. Vose; Devendra M. Amayta

2006-01-01

A clear understanding of the basic hydrologic processes is needed to restore and manage watersheds across the diverse physiologic gradients in the Southeastern U.S. We evaluated a physically based, spatially distributed watershed hydrologic model called MIKE SHE/MIKE 11 to evaluate disturbance impacts on water use and yield across the region. Long-term forest...

An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Liu, Yanlou; Tian, Wei; Xin, Tao

2016-01-01

The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-02-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of biomass demand for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Rooting traits of peanut genotypes with different yield responses to terminal drought

USDA-ARS?s Scientific Manuscript database

Drought at pod filling can severely reduce yield of peanut. Better root systems can reduce yield loss from drought. However, the relationship of root characters with yield under terminal drought is not well understood. The objective of this study was to investigate the responses of peanut genotyp...

Crop yield responses to a hardwood biochar across varied soils and climate conditions

USDA-ARS?s Scientific Manuscript database

Biochars applied to soil for crop yield improvements have produced mixed results. The assorted crop yield responses may be linked to employing biochars with diverse chemical and physical characteristics. To clarify if biochars can improve crop yields, it may be prudent to evaluate one biochar type...

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing.

PubMed

Duncan, John M A; Dash, Jadunandan; Atkinson, Peter M

2015-04-01

Remote sensing-derived wheat crop yield-climate models were developed to highlight the impact of temperature variation during thermo-sensitive periods (anthesis and grain-filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north-west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start-of-season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature-induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands. © 2014 John Wiley & Sons Ltd.

Fourier modeling of the BOLD response to a breath-hold task: Optimization and reproducibility.

PubMed

Pinto, Joana; Jorge, João; Sousa, Inês; Vilela, Pedro; Figueiredo, Patrícia

2016-07-15

Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD-fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter. Copyright © 2016 Elsevier Inc. All rights reserved.

Systematic optimization of fed-batch simultaneous saccharification and fermentation at high-solid loading based on enzymatic hydrolysis and dynamic metabolic modeling of Saccharomyces cerevisiae.

PubMed

Unrean, Pornkamol; Khajeeram, Sutamat; Laoteng, Kobkul

2016-03-01

An integrative simultaneous saccharification and fermentation (SSF) modeling is a useful guiding tool for rapid process optimization to meet the techno-economic requirement of industrial-scale lignocellulosic ethanol production. In this work, we have developed the SSF model composing of a metabolic network of a Saccharomyces cerevisiae cell associated with fermentation kinetics and enzyme hydrolysis model to quantitatively capture dynamic responses of yeast cell growth and fermentation during SSF. By using model-based design of feeding profiles for substrate and yeast cell in the fed-batch SSF process, an efficient ethanol production with high titer of up to 65 g/L and high yield of 85 % of theoretical yield was accomplished. The ethanol titer and productivity was increased by 47 and 41 %, correspondingly, in optimized fed-batch SSF as compared to batch process. The developed integrative SSF model is, therefore, considered as a promising approach for systematic design of economical and sustainable SSF bioprocessing of lignocellulose.

Hydrostatic Stress Effect On the Yield Behavior of Inconel 100

NASA Technical Reports Server (NTRS)

Allen, Phillip A.; Wilson, Christopher D.

2002-01-01

Classical metal plasticity theory assumes that hydrostatic stress has no effect on the yield and postyield behavior of metals. Recent reexaminations of classical theory have revealed a significant effect of hydrostatic stress on the yield behavior of notched geometries. New experiments and nonlinear finite element analyses (FEA) of Inconel 100 (IN 100) equal-arm bend and double-edge notch tension (DENT) test specimens have revealed the effect of internal hydrostatic tensile stresses on yielding. Nonlinear FEA using the von Mises (yielding is independent of hydrostatic stress) and the Drucker-Prager (yielding is linearly dependent on hydrostatic stress) yield functions was performed. In all test cases, the von Mises constitutive model, which is independent of hydrostatic pressure, overestimated the load for a given displacement or strain. Considering the failure displacements or strains, the Drucker-Prager FEMs predicted loads that were 3% to 5% lower than the von Mises values. For the failure loads, the Drucker Prager FEMs predicted strains that were 20% to 35% greater than the von Mises values. The Drucker-Prager yield function seems to more accurately predict the overall specimen response of geometries with significant internal hydrostatic stress influence.

SIR-B ocean-wave enhancement with fast Fourier transform techniques

NASA Technical Reports Server (NTRS)

Tilley, David G.

1987-01-01

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

On use of the multistage dose-response model for assessing laboratory animal carcinogenicity

PubMed Central

Nitcheva, Daniella; Piegorsch, Walter W.; West, R. Webster

2007-01-01

We explore how well a statistical multistage model describes dose-response patterns in laboratory animal carcinogenicity experiments from a large database of quantal response data. The data are collected from the U.S. EPA’s publicly available IRIS data warehouse and examined statistically to determine how often higher-order values in the multistage predictor yield significant improvements in explanatory power over lower-order values. Our results suggest that the addition of a second-order parameter to the model only improves the fit about 20% of the time, while adding even higher-order terms apparently does not contribute to the fit at all, at least with the study designs we captured in the IRIS database. Also included is an examination of statistical tests for assessing significance of higher-order terms in a multistage dose-response model. It is noted that bootstrap testing methodology appears to offer greater stability for performing the hypothesis tests than a more-common, but possibly unstable, “Wald” test. PMID:17490794

Optimisation of steam distillation extraction oil from onion by response surface methodology and its chemical composition.

PubMed

Wang, Zhao Dan; Li, Li Hua; Xia, Hui; Wang, Feng; Yang, Li Gang; Wang, Shao Kang; Sun, Gui Ju

2018-01-01

Oil extraction from onion was performed by steam distillation. Response surface methodology was applied to evaluate the effects of ratio of water to raw material, extraction time, zymolysis temperature and distillation times on yield of onion oil. The maximum extraction yield (1.779%) was obtained as following conditions: ratio of water to raw material was 1, extraction time was 2.5 h, zymolysis temperature was 36° and distillation time was 2.6 h. The experimental values agreed well with those predicted by regression model. The chemical composition of extracted onion oil under the optimum conditions was analysed by gas chromatography-mass spectrometry technology. The results showed that sulphur compounds, like alkanes, sulphide, alkenes, ester and alcohol, were the major components of onion oil.

Improving Rice Modeling Success Rate with Ternary Non-structural Fertilizer Response Model.

PubMed

Li, Juan; Zhang, Mingqing; Chen, Fang; Yao, Baoquan

2018-06-13

Fertilizer response modelling is an important technical approach to realize metrological fertilization on rice. With the goal of solving the problems of a low success rate of a ternary quadratic polynomial model (TPFM) and to expand the model's applicability, this paper established a ternary non-structural fertilizer response model (TNFM) based on the experimental results from N, P and K fertilized rice fields. Our research results showed that the TNFM significantly improved the modelling success rate by addressing problems arising from setting the bias and multicollinearity in a TPFM. The results from 88 rice field trials in China indicated that the proportion of typical TNFMs that satisfy the general fertilizer response law of plant nutrition was 40.9%, while the analogous proportion of TPFMs was only 26.1%. The recommended fertilization showed a significant positive linear correlation between the two models, and the parameters N 0 , P 0 and K 0 that estimated the value of soil supplying nutrient equivalents can be used as better indicators of yield potential in plots where no N or P or K fertilizer was applied. The theoretical analysis showed that the new model has a higher fitting accuracy and a wider application range.

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

Solvent refined coal (SRC) process. Annual technical progress report, January 1979-December 1979

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1980-11-01

A set of statistically designed experiments was used to study the effects of several important operating variables on coal liquefaction product yield structures. These studies used a Continuous Stirred-Tank Reactor to provide a hydrodynamically well-defined system from which kinetic data could be extracted. An analysis of the data shows that product yield structures can be adequately represented by a correlative model. It was shown that second-order effects (interaction and squared terms) are necessary to provide a good model fit of the data throughout the range studied. Three reports were issued covering the SRC-II database and yields as functions of operatingmore » variables. The results agree well with the generally-held concepts of the SRC reaction process, i.e., liquid phase hydrogenolysis of liquid coal which is time-dependent, thermally activated, catalyzed by recycle ash, and reaction rate-controlled. Four reports were issued summarizing the comprehensive SRC reactor thermal response models and reporting the results of several studies made with the models. Analytical equipment for measuring SRC off-gas composition and simulated distillation of coal liquids and appropriate procedures have been established.« less

New AgMIP Scenarios: Impacts of Volcanic Eruptions, Geoengineering, or Nuclear War on Agriculture

NASA Astrophysics Data System (ADS)

Robock, A.; Xia, L.

2016-12-01

Climate is one of the most important factors determining crop yields and world food supplies. To be well prepared for possible futures, it is necessary to study yield changes of major crops in response to different climate forcings. Previous studies mainly focus on the impact from global warming. Here we propose that the AgMIP community also study the impacts of stratospheric aerosols on agriculture. While nature can load the stratosphere with sulfate aerosols for several years from large volcanic eruptions, humans could also put sulfate aerosols into the stratosphere on purpose through geoengineering or soot as a result of the fires from a nuclear war. Stratospheric aerosols would change the temperature, precipitation, total insolation, and fraction of diffuse radiation due to their radiative impacts, and could produce more ultraviolet radiation by ozone destruction. Surface ozone concentration could also change by changed transport from the stratosphere as well as changed tropospheric chemistry. As a demonstration of these effects, using the crop model in the NCAR Community Land Model (CLM-crop), we have studied sulfate injection geoengineering and nuclear war impacts on global agriculture in response to temperature, precipitation and radiation changes, and found significant changes in patterns of global food production. With the new ozone module in CLM-crop, we simulated how surface ozone concentration change under sulfate injection geoengineering would change the agriculture response. Agriculture would benefit from less surface ozone concentration associated with the specific geoengineering scenario comparing with the global warming scenario. Here, we would like to encourage more crop modelers to improve crop models in terms of crop responses to ozone, ultraviolet radiation, and diffuse radiation. We also invite more global crop modeling groups to use the climate forcing we would be happy to provide to gain a better understanding of global agriculture responses under different future climate scenarios with stratospheric aerosols.

Deciphering the complexity of acute inflammation using mathematical models.

PubMed

Vodovotz, Yoram

2006-01-01

Various stresses elicit an acute, complex inflammatory response, leading to healing but sometimes also to organ dysfunction and death. We constructed both equation-based models (EBM) and agent-based models (ABM) of various degrees of granularity--which encompass the dynamics of relevant cells, cytokines, and the resulting global tissue dysfunction--in order to begin to unravel these inflammatory interactions. The EBMs describe and predict various features of septic shock and trauma/hemorrhage (including the response to anthrax, preconditioning phenomena, and irreversible hemorrhage) and were used to simulate anti-inflammatory strategies in clinical trials. The ABMs that describe the interrelationship between inflammation and wound healing yielded insights into intestinal healing in necrotizing enterocolitis, vocal fold healing during phonotrauma, and skin healing in the setting of diabetic foot ulcers. Modeling may help in understanding the complex interactions among the components of inflammation and response to stress, and therefore aid in the development of novel therapies and diagnostics.

A Multi-Route Model of Nicotine-Cotinine Pharmacokinetics, Pharmacodynamics and Brain Nicotinic Acetylcholine Receptor Binding in Humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teeguarden, Justin G.; Housand, Conrad; Smith, Jordan N.

The pharmacokinetics of nicotine, the pharmacologically active alkaloid in tobacco responsible for addiction, are well characterized in humans. We developed a physiologically based pharmacokinetic/pharmacodynamic model of nicotine pharmacokinetics, brain dosimetry and brain nicotinic acetylcholine receptor (nAChRs) occupancy. A Bayesian framework was applied to optimize model parameters against multiple human data sets. The resulting model was consistent with both calibration and test data sets, but in general underestimated variability. A pharmacodynamic model relating nicotine levels to increases in heart rate as a proxy for the pharmacological effects of nicotine accurately described the nicotine related changes in heart rate and the developmentmore » and decay of tolerance to nicotine. The PBPK model was utilized to quantitatively capture the combined impact of variation in physiological and metabolic parameters, nicotine availability and smoking compensation on the change in number of cigarettes smoked and toxicant exposure in a population of 10,000 people presented with a reduced toxicant (50%), reduced nicotine (50%) cigarette Across the population, toxicant exposure is reduced in some but not all smokers. Reductions are not in proportion to reductions in toxicant yields, largely due to partial compensation in response to reduced nicotine yields. This framework can be used as a key element of a dosimetry-driven risk assessment strategy for cigarette smoke constituents.« less

Effects of temperature on consumer-resource interactions.

PubMed

Amarasekare, Priyanga

2015-05-01

Understanding how temperature variation influences the negative (e.g. self-limitation) and positive (e.g. saturating functional responses) feedback processes that characterize consumer-resource interactions is an important research priority. Previous work on this topic has yielded conflicting outcomes with some studies predicting that warming should increase consumer-resource oscillations and others predicting that warming should decrease consumer-resource oscillations. Here, I develop a consumer-resource model that both synthesizes previous findings in a common framework and yields novel insights about temperature effects on consumer-resource dynamics. I report three key findings. First, when the resource species' birth rate exhibits a unimodal temperature response, as demonstrated by a large number of empirical studies, the temperature range over which the consumer-resource interaction can persist is determined by the lower and upper temperature limits to the resource species' reproduction. This contrasts with the predictions of previous studies, which assume that the birth rate exhibits a monotonic temperature response, that consumer extinction is determined by temperature effects on consumer species' traits, rather than the resource species' traits. Secondly, the comparative analysis I have conducted shows that whether warming leads to an increase or decrease in consumer-resource oscillations depends on the manner in which temperature affects intraspecific competition. When the strength of self-limitation increases monotonically with temperature, warming causes a decrease in consumer-resource oscillations. However, if self-limitation is strongest at temperatures physiologically optimal for reproduction, a scenario previously unanalysed by theory but amply substantiated by empirical data, warming can cause an increase in consumer-resource oscillations. Thirdly, the model yields testable comparative predictions about consumer-resource dynamics under alternative hypotheses for how temperature affects competitive and resource acquisition traits. Importantly, it does so through empirically quantifiable metrics for predicting temperature effects on consumer viability and consumer-resource oscillations, which obviates the need for parameterizing complex dynamical models. Tests of these metrics with empirical data on a host-parasitoid interaction yield realistic estimates of temperature limits for consumer persistence and the propensity for consumer-resource oscillations, highlighting their utility in predicting temperature effects, particularly warming, on consumer-resource interactions in both natural and agricultural settings. © 2014 The Author. Journal of Animal Ecology © 2014 British Ecological Society.

Flapping response characteristics of hingeless rotor blades by a gereralized harmonic balance method

NASA Technical Reports Server (NTRS)

Peters, D. A.; Ormiston, R. A.

1975-01-01

Linearized equations of motion for the flapping response of flexible rotor blades in forward flight are derived in terms of generalized coordinates. The equations are solved using a matrix form of the method of linear harmonic balance, yielding response derivatives for each harmonic of the blade deformations and of the hub forces and moments. Numerical results and approximate closed-form expressions for rotor derivatives are used to illustrate the relationships between rotor parameters, modeling assumptions, and rotor response characteristics. Finally, basic hingeless rotor response derivatives are presented in tabular and graphical form for a wide range of configuration parameters and operating conditions.

Inelastic response of metal matrix composites under biaxial loading

NASA Technical Reports Server (NTRS)

Mirzadeh, F.; Pindera, Marek-Jerzy; Herakovich, Carl T.

1990-01-01

Elements of the analytical/experimental program to characterize the response of silicon carbide titanium (SCS-6/Ti-15-3) composite tubes under biaxial loading are outlined. The analytical program comprises prediction of initial yielding and subsequent inelastic response of unidirectional and angle-ply silicon carbide titanium tubes using a combined micromechanics approach and laminate analysis. The micromechanics approach is based on the method of cells model and has the capability of generating the effective thermomechanical response of metal matrix composites in the linear and inelastic region in the presence of temperature and time-dependent properties of the individual constituents and imperfect bonding on the initial yield surfaces and inelastic response of (0) and (+ or - 45)sub s SCS-6/Ti-15-3 laminates loaded by different combinations of stresses. The generated analytical predictions will be compared with the experimental results. The experimental program comprises generation of initial yield surfaces, subsequent stress-strain curves and determination of failure loads of the SCS-6/Ti-15-3 tubes under selected loading conditions. The results of the analytical investigation are employed to define the actual loading paths for the experimental program. A brief overview of the experimental methodology is given. This includes the test capabilities of the Composite Mechanics Laboratory at the University of Virginia, the SCS-6/Ti-15-3 composite tubes secured from McDonnell Douglas Corporation, a text fixture specifically developed for combined axial-torsional loading, and the MTS combined axial-torsion loader that will be employed in the actual testing.

Optimization of mucilage extraction from chia seeds (Salvia hispanica L.) using response surface methodology.

PubMed

Orifici, Stefania C; Capitani, Marianela I; Tomás, Mabel C; Nolasco, Susana M

2018-02-25

Chia mucilage has potential application as a functional ingredient; advances on maximizing its extraction yield could represent a significant technological and economic impact for the food industry. Thus, first, the effect of mechanical agitation time (1-3 h) on the exudation of chia mucilage was analyzed. Then, response surface methodology was used to determine the optimal combination of the independent variables temperature (15-85 °C) and seed: water ratio (1: 12-1: 40.8 w/v) for the 2 h exudation that give maximum chia mucilage yield. Experiments were designed according to central composite rotatable design. A second-order polynomial model predicted the variation in extraction mucilage yield with the variables temperature and seed: water ratio. The optimal operating conditions were found to be temperature 85 °C and a seed: water ratio of 1: 31 (w/v), reaching an experimental extraction yield of 116 ± 0.21 g kg -1 (dry basis). The mucilage obtained exhibited good functional properties, mainly in terms of water-holding capacity, emulsifying activity, and emulsion stability. The results obtained show that temperature, seed: water ratio, and exudation time are important variables of the process that affect the extraction yield and the quality of the chia mucilage, determined according to its physicochemical and functional properties. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Risk of water scarcity and water policy implications for crop production in the Ebro Basin in Spain

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2010-08-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro River Basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

The Long-Term Effects of Youth Unemployment

ERIC Educational Resources Information Center

Mroz, Thomas A.; Savage, Timothy H.

2006-01-01

Using NLSY data, we examine the long-term effects of youth unemployment on later labor market outcomes. Involuntary unemployment may yield suboptimal investments in human capital in the short run. A theoretical model of dynamic human capital investment predicts a rational "catch-up" response. Using semiparametric techniques to control for the…

The uncertainty of crop yield projections is reduced by improved temperature response functions

USDA-ARS?s Scientific Manuscript database

Increasing the accuracy of crop productivity estimates is a key Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on cr...

Predicting maize phenology: Intercomparison of functions for developmental response to temperature

USDA-ARS?s Scientific Manuscript database

Accurate prediction of phenological development in maize is fundamental to determining crop adaptation and yield potential. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. The objectives of this study were t...

Biological profiling and dose-response modeling tools, characterizing uncertainty

EPA Science Inventory

Through its ToxCast project, the U.S. EPA has developed a battery of in vitro high throughput screening (HTS) assays designed to assess the potential toxicity of environmental chemicals. At present, over 1800 chemicals have been tested in up to 600 assays, yielding a large number...

The development and use of a molecular model for soybean maturity groups

USDA-ARS?s Scientific Manuscript database

Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and rep...

Application of Box-Behnken design for ultrasonic-assisted extraction of polysaccharides from Paeonia emodi.

PubMed

Ahmad, Ajaz; Alkharfy, Khalid M; Wani, Tanveer A; Raish, Mohammad

2015-01-01

The objective of the present work was to study the ultrasonic assisted extraction and optimization of polysaccharides from Paeonia emodi and evaluation of its anti-inflammatory response. Specifically, the optimization of polysaccharides was carried out using Box-Behnken statistical experimental design. Response surface methodology (RSM) of three factors (extraction temperature, extraction time and liquid solid ratio) was employed to optimize the percentage yield of the polysaccharides. The experimental data were fitted to quadratic response surface models using multiple regression analysis with high coefficient of determination value (R) of 0.9906. The highest polysaccharide yield (8.69%) as per the Derringer's desirability prediction tool was obtained under the optimal extraction condition (extraction temperature 47.03 °C, extraction time 15.68 min, and liquid solid ratio 1.29 ml/g) with a desirability value of 0.98. These optimized values of tested parameters were validated under similar conditions (n = 6), an average of 8.13 ± 2.08% of polysaccharide yield was obtained in an optimized extraction conditions with 93.55% validity. The anti-inflammatory effect of polysaccharides of P. emodi were studied on carrageenan induced paw edema. In vivo results showed that the P. emodi 200mg/kg of polysaccharide extract exhibited strong potential against inflammatory response induced by 1% suspension of carrageenean in normal saline. Copyright © 2014 Elsevier B.V. All rights reserved.

Gene Expression Biomarkers Provide Sensitive Indicators of in Planta Nitrogen Status in Maize[W][OA

PubMed Central

Yang, Xiaofeng S.; Wu, Jingrui; Ziegler, Todd E.; Yang, Xiao; Zayed, Adel; Rajani, M.S.; Zhou, Dafeng; Basra, Amarjit S.; Schachtman, Daniel P.; Peng, Mingsheng; Armstrong, Charles L.; Caldo, Rico A.; Morrell, James A.; Lacy, Michelle; Staub, Jeffrey M.

2011-01-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields. PMID:21980173

Gene expression biomarkers provide sensitive indicators of in planta nitrogen status in maize.

PubMed

Yang, Xiaofeng S; Wu, Jingrui; Ziegler, Todd E; Yang, Xiao; Zayed, Adel; Rajani, M S; Zhou, Dafeng; Basra, Amarjit S; Schachtman, Daniel P; Peng, Mingsheng; Armstrong, Charles L; Caldo, Rico A; Morrell, James A; Lacy, Michelle; Staub, Jeffrey M

2011-12-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Environmental limitation mapping of potential biomass resources across the conterminous United States

DOE PAGES

Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ...

2017-12-22

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less

Testing and Refining the Ohio Nowcast at Two Lake Erie Beaches-2008

USGS Publications Warehouse

Francy, Donna S.; Bertke, Erin E.; Darner, Robert A.

2009-01-01

The Ohio Nowcast has been providing real-time beach advisories to the public on the basis of predictive models since 2006. In support of the nowcast, data were collected during the recreational season of 2008 to validate and refine predictive models at two Lake Erie beaches. Predictive models yield data on the probability that the single-sample bathing-water standard for E. coli will be exceeded. Field personnel collected or compiled data on Escherichia coli (E. coli) concentrations as well as variables expected to affect these concentrations, including manual and automated measurements of turbidity, wave height, and water temperature; lake level; and radar and airport rainfall amounts. Two new variables were measured during 2008 - photosynthetically-active radiation at Huntington (Bay Village) and foreshore head at Edgewater (Cleveland). (The foreshore is a strip of land along a body of water between low and high water marks.) The performance of the nowcast was monitored during 2008. The Huntington nowcast yielded a greater percentage of correct responses (84.9 percent) than did the previous day's E. coli concentration (75.2 percent). In contrast, at Edgewater, the nowcast yielded a slightly higher percentage of correct responses (61.0 percent) as compared to the previous day's E. coli concentration (56.5 percent), but both percentages were relatively low. Lake levels in 2008 were significantly higher than levels in the data used to develop the Edgewater models (2004-7), confounding their abilities to provide correct responses. At Edgewater during 2008, the strongest relation (as measured by Pearson's correlation) was between E. coli concentrations and the difference in foreshore head over the past 24 hours (r=0.48), a variable not included in the models. At Huntington, photosynthetically-active radiation on the previous day showed a significant negative relation to E. coli concentrations (r=-0.33) during 2008. Refined models were developed for Huntington and Edgewater using data collected from 2005-8. The refined models included the variables wave height, log turbidity, radar or airport rainfall, and day of the year in various combinations for different dated segments of the recreational season. Water-resource managers will determine which models to apply to the Ohio Nowcast for issuing water-quality advisories in 2009.

Estimating Single-Trial Responses in EEG

NASA Technical Reports Server (NTRS)

Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; Fu, K. G.; Johnston, T. A.; Ding, M.; Bressler, S. L.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Increased evapotranspiration demand in a Mediterranean climate might cause a decline in fungal yields under global warming.

PubMed

Ágreda, Teresa; Águeda, Beatriz; Olano, José M; Vicente-Serrano, Sergio M; Fernández-Toirán, Marina

2015-09-01

Wild fungi play a critical role in forest ecosystems, and its recollection is a relevant economic activity. Understanding fungal response to climate is necessary in order to predict future fungal production in Mediterranean forests under climate change scenarios. We used a 15-year data set to model the relationship between climate and epigeous fungal abundance and productivity, for mycorrhizal and saprotrophic guilds in a Mediterranean pine forest. The obtained models were used to predict fungal productivity for the 2021-2080 period by means of regional climate change models. Simple models based on early spring temperature and summer-autumn rainfall could provide accurate estimates for fungal abundance and productivity. Models including rainfall and climatic water balance showed similar results and explanatory power for the analyzed 15-year period. However, their predictions for the 2021-2080 period diverged. Rainfall-based models predicted a maintenance of fungal yield, whereas water balance-based models predicted a steady decrease of fungal productivity under a global warming scenario. Under Mediterranean conditions fungi responded to weather conditions in two distinct periods: early spring and late summer-autumn, suggesting a bimodal pattern of growth. Saprotrophic and mycorrhizal fungi showed differences in the climatic control. Increased atmospheric evaporative demand due to global warming might lead to a drop in fungal yields during the 21st century. © 2015 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m3. The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater.

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

PubMed Central

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

2017-01-01

Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m3. The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater. PMID:28220874

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

PubMed

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

2017-02-21

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

The Bulk Lunar Electrical Conductivity. Ph.D. Thesis. Final Report; [from Explorer 35 satellite and the Apollo 12 flight

NASA Technical Reports Server (NTRS)

Leavy, Donald Lucien

1975-01-01

The electrical conductivity structure was studied of a spherically layered moon consistent with the very low frequency magnetic data collected on the lunar surface and by Explorer 35. In order to obtain good agreement with the lunar surface magnetometer observations, the inclusion of a void cavity behind the moon requires a conductivity at shallow depths higher than that of models having the solar wind impinging on all sides. By varying only the source parameters, a conductivity model can be found that yields a good fit to both the tangential response upstream and the radial response downstream. This model also satisfies the dark side tangential response in the frequency range above 0.006 Hz, but the few data points presently available below this range do not seem to agree with the theory.

Are We on the Right Track: Can Our Understanding of Abscission in Model Systems Promote or Derail Making Improvements in Less Studied Crops?

PubMed Central

Patterson, Sara E.; Bolivar-Medina, Jenny L.; Falbel, Tanya G.; Hedtcke, Janet L.; Nevarez-McBride, Danielle; Maule, Andrew F.; Zalapa, Juan E.

2016-01-01

As the world population grows and resources and climate conditions change, crop improvement continues to be one of the most important challenges for agriculturalists. The yield and quality of many crops is affected by abscission or shattering, and environmental stresses often hasten or alter the abscission process. Understanding this process can not only lead to genetic improvement, but also changes in cultural practices and management that will contribute to higher yields, improved quality and greater sustainability. As plant scientists, we have learned significant amounts about this process through the study of model plants such as Arabidopsis, tomato, rice, and maize. While these model systems have provided significant valuable information, we are sometimes challenged to use this knowledge effectively as variables including the economic value of the crop, the uniformity of the crop, ploidy levels, flowering and crossing mechanisms, ethylene responses, cultural requirements, responses to changes in environment, and cellular and tissue specific morphological differences can significantly influence outcomes. The value of genomic resources for lesser-studied crops such as cranberries and grapes and the orphan crop fonio will also be considered. PMID:26858730

Are We on the Right Track: Can Our Understanding of Abscission in Model Systems Promote or Derail Making Improvements in Less Studied Crops?

PubMed

Patterson, Sara E; Bolivar-Medina, Jenny L; Falbel, Tanya G; Hedtcke, Janet L; Nevarez-McBride, Danielle; Maule, Andrew F; Zalapa, Juan E

2015-01-01

As the world population grows and resources and climate conditions change, crop improvement continues to be one of the most important challenges for agriculturalists. The yield and quality of many crops is affected by abscission or shattering, and environmental stresses often hasten or alter the abscission process. Understanding this process can not only lead to genetic improvement, but also changes in cultural practices and management that will contribute to higher yields, improved quality and greater sustainability. As plant scientists, we have learned significant amounts about this process through the study of model plants such as Arabidopsis, tomato, rice, and maize. While these model systems have provided significant valuable information, we are sometimes challenged to use this knowledge effectively as variables including the economic value of the crop, the uniformity of the crop, ploidy levels, flowering and crossing mechanisms, ethylene responses, cultural requirements, responses to changes in environment, and cellular and tissue specific morphological differences can significantly influence outcomes. The value of genomic resources for lesser-studied crops such as cranberries and grapes and the orphan crop fonio will also be considered.

Nuclear structure for SNe r- and neutrino processes

NASA Astrophysics Data System (ADS)

Suzuki, Toshio

2014-09-01

SNe r- and neutrino-processes are investigated based on recent advances in the studies of spin responses in nuclei. New shell-model Hamiltonians, which can well describe spin responses in nuclei with proper tensor components, are used to make accurate evaluations of reaction cross sections and rates in astrophysical processes. Nucleosyntheses in SNe r- and ν -processes as well as rp-processes are discussed with these new reaction rates with improved accuracies. (1) Beta-decay rates for N = 126 isotones are evaluated by shell-model calculations, and new rates are applied to study r-process nucleosynthesis in SNe's around its third peak as well as beyond the peak region up to uranium. (2) ν -processes for light-element synthesis in core-collapse SNe are studied with a new shell-model Hamiltonian in p-shell, SFO. Effects of MSW ν -oscillations on the production yields of 7Li and 11B and sensitivity of the yield ratio on ν -oscillation parameters are discussed. ν -induced reactions on 16O are also studied. (3) A new shell-model Hamiltonian in pf-shell, GXPF1J, is used to evaluate e-capture rates in pf-shell nuclei at stellar environments. New e-capture rates are applied to study nucleosynthesis in type-Ia supernova explosions, rp-process and X-ray bursts.

A GIS model-based assessment of the environmental distribution of gamma-hexachlorocyclohexane in European soils and waters.

PubMed

Vizcaíno, P; Pistocchi, A

2010-10-01

The MAPPE GIS based multimedia model is used to produce a quantitative description of the behaviour of gamma-hexachlorocyclohexane (gamma-HCH) in Europe, with emphasis on continental surface waters. The model is found to reasonably reproduce gamma-HCH distributions and variations along the years in atmosphere and soil; for continental surface waters, concentrations were reasonably well predicted for year 1995, when lindane was still used in agriculture, while for 2005, assuming severe restrictions in use, yields to substantial underestimation. Much better results were yielded when same mode of release as in 1995 was considered, supporting the conjecture that for gamma-HCH, emission data rather that model structure and parameterization can be responsible for wrong estimation of concentrations. Future research should be directed to improve the quality of emission data. Joint interpretation of monitoring and modelling results, highlights that lindane emissions in Europe, despite the marked decreasing trend, persist beyond the provisions of existing legislation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Non-linear modelling and control of semi-active suspensions with variable damping

NASA Astrophysics Data System (ADS)

Chen, Huang; Long, Chen; Yuan, Chao-Chun; Jiang, Hao-Bin

2013-10-01

Electro-hydraulic dampers can provide variable damping force that is modulated by varying the command current; furthermore, they offer advantages such as lower power, rapid response, lower cost, and simple hardware. However, accurate characterisation of non-linear f-v properties in pre-yield and force saturation in post-yield is still required. Meanwhile, traditional linear or quarter vehicle models contain various non-linearities. The development of a multi-body dynamics model is very complex, and therefore, SIMPACK was used with suitable improvements for model development and numerical simulations. A semi-active suspension was built based on a belief-desire-intention (BDI)-agent model framework. Vehicle handling dynamics were analysed, and a co-simulation analysis was conducted in SIMPACK and MATLAB to evaluate the BDI-agent controller. The design effectively improved ride comfort, handling stability, and driving safety. A rapid control prototype was built based on dSPACE to conduct a real vehicle test. The test and simulation results were consistent, which verified the simulation.

A trans-phase granular continuum relation and its use in simulation

NASA Astrophysics Data System (ADS)

Kamrin, Ken; Dunatunga, Sachith; Askari, Hesam

The ability to model a large granular system as a continuum would offer tremendous benefits in computation time compared to discrete particle methods. However, two infamous problems arise in the pursuit of this vision: (i) the constitutive relation for granular materials is still unclear and hotly debated, and (ii) a model and corresponding numerical method must wear ``many hats'' as, in general circumstances, it must be able to capture and accurately represent the material as it crosses through its collisional, dense-flowing, and solid-like states. Here we present a minimal trans-phase model, merging an elastic response beneath a fictional yield criterion, a mu(I) rheology for liquid-like flow above the static yield criterion, and a disconnection rule to model separation of the grains into a low-temperature gas. We simulate our model with a meshless method (in high strain/mixing cases) and the finite-element method. It is able to match experimental data in many geometries, including collapsing columns, impact on granular beds, draining silos, and granular drag problems.

Spectral reflectance indices as a selection criterion for yield improvement in wheat

NASA Astrophysics Data System (ADS)

Babar, Md. Ali

2005-11-01

Scope and methods of study. Yield in wheat ( Triticum aestivum L.) is a complex trait and influenced by many environmental factors, and yield improvement is a daunting task for wheat breeders. Spectral reflectance indices (SRIs) have been used to study different physiological traits in wheat. SRIs have the potential to differentiate genotypes for grain yield. SRIs strongly associated with grain yield can be used to achieve effective genetic gain in wheat under different environments. Three experiments (15 adapted genotypes, 25 and 36 random sister lines derived from two different crosses) under irrigated conditions, and three experiments (each with 30 advanced genotypes) under water-limited conditions were conducted in three successive years in Northwest Mexico at the CIMMYT (International Maize and wheat Improvement Center) experimental station. SRIs and different agronomic data were collected for three years, and biomass was harvested for two years. Phenotypic and genetic correlations between SRIs and grain yield, between SRIs and biomass, realized and broad sense heritability, direct and correlated selection responses for grain yield, and SRIs were calculated. Findings and conclusion. Seven SRIs were calculated, and three near infrared based indices (WI, NWI-1 and NWI-2) showed higher level of genetic and phenotypic correlations with grain yield, yield components and biomass than other SRIs (PRI, RNDVI, GNDVI, and SR) under both irrigated and water limiting environments. Moderate to high realized and broad sense heritability, and selection response were demonstrated by the three NIR based indices. High efficiency of correlated response for yield estimation was demonstrated by the three NIR based indices. The ratio between the correlated response to grain yield based on the three NIR based indices and direct selection response for grain yield was very close to one. The NIR based indices showed very high accuracy in selecting superior genotypes for grain yield under both well-watered and water-limited conditions. These results demonstrated that effective genetic gain in grain yield improvement can be achieved by making selections with the three NIR based indices.

Positive and normative modeling for Palmer amaranth control and herbicide resistance management.

PubMed

Frisvold, George B; Bagavathiannan, Muthukumar V; Norsworthy, Jason K

2017-06-01

Dynamic optimization models are normative; they solve for what growers 'ought to do' to maximize some objective, such as long-run profits. While valuable for research, such models are difficult to solve computationally, limiting their applicability to grower resistance management education. While discussing properties of normative models in general, this study presents results of a specific positive model of herbicide resistance management, applied to Palmer amaranth control on a representative cotton farm. This positive model compares a proactive resistance management strategy to a reactive strategy with lower short-run costs, but greater risk of herbicide resistance developing. The proactive strategy can pay for itself within 1-4 years, with a yield advantage of 4% or less if the yield advantage begins within 1-2 years of adoption. Whether the proactive strategy is preferable is sensitive to resistance onset and yield losses, but less sensitive to cotton prices or baseline yields. Industry rebates to encourage residual herbicide use (to delay resistance to post-emergence treatments) may be too small to alter grower behavior or they may be paid to growers who would have used residuals anyway. Rebates change grower behavior over a relatively narrow range of model parameters. The size of rebates needed to induce a grower to adopt the proactive strategy declines significantly if growers extend their planning horizon from 1 year to 3-4 years. Whether proactive resistance management is more profitable than a reactive strategy is more sensitive to biological parameters than economic ones. Simulation results suggest growers with longer time horizons (perhaps younger ones) would be more responsive to rebate programs. More empirical work is needed to determine how much rebates increase residual use above what would occur without them. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Nonlinear 2D arm dynamics in response to continuous and pulse-shaped force perturbations.

PubMed

Happee, Riender; de Vlugt, Erwin; van Vliet, Bart

2015-01-01

Ample evidence exists regarding the nonlinearity of the neuromuscular system but linear models are widely applied to capture postural dynamics. This study quantifies the nonlinearity of human arm postural dynamics applying 2D continuous force perturbations (0.2-40 Hz) inducing three levels of hand displacement (5, 15, 45 mm RMS) followed by force-pulse perturbations inducing large hand displacements (up to 250 mm) in a position task (PT) and a relax task (RT) recording activity of eight shoulder and elbow muscles. The continuous perturbation data were used to analyze the 2D endpoint dynamics in the frequency domain and to identify reflexive and intrinsic parameters of a linear neuromuscular shoulder-elbow model. Subsequently, it was assessed to what extent the large displacements in response to force pulses could be predicted from the 'small amplitude' linear neuromuscular model. Continuous and pulse perturbation responses with varying amplitudes disclosed highly nonlinear effects. In PT, a larger continuous perturbation induced stiffening with a factor of 1.5 attributed to task adaptation evidenced by increased co-contraction and reflexive activity. This task adaptation was even more profound in the pulse responses where reflexes and displacements were strongly affected by the presence and amplitude of preceding continuous perturbations. In RT, a larger continuous perturbation resulted in yielding with a factor of 3.8 attributed to nonlinear mechanical properties as no significant reflexive activity was found. Pulse perturbations always resulted in yielding where a model fitted to the preceding 5-mm continuous perturbations predicted only 37% of the recorded peak displacements in RT and 79% in PT. This demonstrates that linear neuromuscular models, identified using continuous perturbations with small amplitudes, strongly underestimate displacements in pulse-shaped (e.g., impact) loading conditions. The data will be used to validate neuromuscular models including nonlinear muscular (e.g., Hill and Huxley) and reflexive components.

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate.

PubMed

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Thorburn, Peter J; Castellano, Michael J; Moore, Kenneth J; VanLoocke, Andrew; Heaton, Emily A; Archontoulis, Sotirios V

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time ( R 2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity ( R 2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined ( n = 31) with an average error range of ±38 kg N ha -1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost.

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

PubMed Central

Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Thorburn, Peter J.; Castellano, Michael J.; Moore, Kenneth J.; VanLoocke, Andrew; Heaton, Emily A.; Archontoulis, Sotirios V.

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost. PMID:29706974

Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

NASA Astrophysics Data System (ADS)

Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

2017-12-01

Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

Modeling riverine nitrate export from an East-Central Illinois watershed using SWAT.

PubMed

Hu, X; McIsaac, G F; David, M B; Louwers, C A L

2007-01-01

Reliable water quality models are needed to forecast the water quality consequences of different agricultural nutrient management scenarios. In this study, the Soil and Water Assessment Tool (SWAT), version 2000, was applied to simulate streamflow, riverine nitrate (NO(3)) export, crop yield, and watershed nitrogen (N) budgets in the upper Embarras River (UER) watershed in east-central Illinois, which has extensive maize-soybean cultivation, large N fertilizer input, and extensive tile drainage. During the calibration (1994-2002) and validation (1985-1993) periods, SWAT simulated monthly and annual stream flows with Nash-Sutcliffe coefficients (E) ranging from 0.67 to 0.94 and R(2) from 0.75 to 0.95. For monthly and annual NO(3) loads, E ranged from -0.16 to 0.45 and R(2) from 0.36 to 0.74. Annual maize and soybean yields were simulated with relative errors ranging from -10 to 6%. The model was then used to predict the changes in NO(3) output with N fertilizer application rates 10 to 50% lower than original application rates in UER. The calibrated SWAT predicted a 10 to 43% decrease in NO(3) export from UER and a 6 to 38% reduction in maize yield in response to the reduction in N fertilizer. The SWAT model markedly overestimated NO(3) export during major wet periods. Moreover, SWAT estimated soybean N fixation rates considerably greater than literature values, and some simulated changes in the N cycle in response to fertilizer reduction seemed to be unrealistic. Improving these aspects of SWAT could lead to more reliable predictions in the water quality outcomes of nutrient management practices in tile-drained watersheds.

Bayesian Mapping Reveals That Attention Boosts Neural Responses to Predicted and Unpredicted Stimuli.

PubMed

Garrido, Marta I; Rowe, Elise G; Halász, Veronika; Mattingley, Jason B

2018-05-01

Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between 2 alternative computational models. The "Opposition" model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the "Interaction" model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modeling showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.

Enhancing photocurrent transient spectroscopy by electromagnetic modeling.

PubMed

Diesinger, H; Panahandeh-Fard, M; Wang, Z; Baillargeat, D; Soci, C

2012-05-01

The shape and duration of photocurrent transients generated by a photoconductive switch depend on both the intrinsic response of the active material and the geometry of the transmission line structure. The present electromagnetic model decouples both shape forming contributions. In contrast to previously published work, it accounts for the particular operating mode of transient spectroscopy. The objective is to increase the time resolution by two approaches, by optimizing structural response and by deconvolving it from experimental data. The switch structure is represented by an effective transimpedance onto which the active material acts as current generator. As proof of concept, the response of a standard microstrip switch is modeled and deconvolved from experimental data acquired in GaAs, yielding a single exponential material response and hence supporting the validity of the approach. Beyond compensating for the response deterioration by the structure, switch architectures can be a priori optimized with respect to frequency response. As an example, it is shown that a microstrip gap that can be deposited on materials incompatible with standard lithography reduces pulse broadening by an order of magnitude if it is provided with transitions to coplanar access lines.

Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies.

PubMed

Geeleher, Paul; Zhang, Zhenyu; Wang, Fan; Gruener, Robert F; Nath, Aritro; Morrison, Gladys; Bhutra, Steven; Grossman, Robert L; Huang, R Stephanie

2017-10-01

Obtaining accurate drug response data in large cohorts of cancer patients is very challenging; thus, most cancer pharmacogenomics discovery is conducted in preclinical studies, typically using cell lines and mouse models. However, these platforms suffer from serious limitations, including small sample sizes. Here, we have developed a novel computational method that allows us to impute drug response in very large clinical cancer genomics data sets, such as The Cancer Genome Atlas (TCGA). The approach works by creating statistical models relating gene expression to drug response in large panels of cancer cell lines and applying these models to tumor gene expression data in the clinical data sets (e.g., TCGA). This yields an imputed drug response for every drug in each patient. These imputed drug response data are then associated with somatic genetic variants measured in the clinical cohort, such as copy number changes or mutations in protein coding genes. These analyses recapitulated drug associations for known clinically actionable somatic genetic alterations and identified new predictive biomarkers for existing drugs. © 2017 Geeleher et al.; Published by Cold Spring Harbor Laboratory Press.

Quality by Design approach to spray drying processing of crystalline nanosuspensions.

PubMed

Kumar, Sumit; Gokhale, Rajeev; Burgess, Diane J

2014-04-10

Quality by Design (QbD) principles were explored to understand spray drying process for the conversion of liquid nanosuspensions into solid nano-crystalline dry powders using indomethacin as a model drug. The effects of critical process variables: inlet temperature, flow and aspiration rates on critical quality attributes (CQAs): particle size, moisture content, percent yield and crystallinity were investigated employing a full factorial design. A central cubic design was employed to generate the response surface for particle size and percent yield. Multiple linear regression analysis and ANOVA were employed to identify and estimate the effect of critical parameters, establish their relationship with CQAs, create design space and model the spray drying process. Inlet temperature was identified as the only significant factor (p value <0.05) to affect dry powder particle size. Higher inlet temperatures caused drug surface melting and hence aggregation of the dried nano-crystalline powders. Aspiration and flow rates were identified as significant factors affecting yield (p value <0.05). Higher yields were obtained at higher aspiration and lower flow rates. All formulations had less than 3% (w/w) moisture content. Formulations dried at higher inlet temperatures had lower moisture compared to those dried at lower inlet temperatures. Published by Elsevier B.V.

Increasing Crop Yields in Water Stressed Countries by Combining Operations of Freshwater Reservoir and Wastewater Reclamation Plant

NASA Astrophysics Data System (ADS)

Bhushan, R.; Ng, T. L.

2015-12-01

Freshwater resources around the world are increasing in scarcity due to population growth, industrialization and climate change. This is a serious concern for water stressed countries, including those in Asia and North Africa where future food production is expected to be negatively affected by this. To address this problem, we investigate the potential of combining freshwater reservoir and wastewater reclamation operations. Reservoir water is the cheaper source of irrigation, but is often limited and climate sensitive. Treated wastewater is a more reliable alternative for irrigation, but often requires extensive further treatment which can be expensive. We propose combining the operations of a reservoir and a wastewater reclamation plant (WWRP) to augment the supply from the reservoir with reclaimed water for increasing crop yields in water stressed regions. The joint system of reservoir and WWRP is modeled as a multi-objective optimization problem with the double objective of maximizing the crop yield and minimizing total cost, subject to constraints on reservoir storage, spill and release, and capacity of the WWRP. We use the crop growth model Aquacrop, supported by The Food and Agriculture Organization of the United Nations (FAO), to model crop growth in response to water use. Aquacrop considers the effects of water deficit on crop growth stages, and from there estimates crop yield. We generate results comparing total crop yield under irrigation with water from just the reservoir (which is limited and often interrupted), and yield with water from the joint system (which has the potential of higher supply and greater reliability). We will present results for locations in India and Africa to evaluate the potential of the joint operations for improving food security in those areas for different budgets.

Reaction norm model to describe environmental sensitivity across first lactation in dairy cattle under tropical conditions.

PubMed

Bignardi, Annaiza Braga; El Faro, Lenira; Pereira, Rodrigo Junqueira; Ayres, Denise Rocha; Machado, Paulo Fernando; de Albuquerque, Lucia Galvão; Santana, Mário Luiz

2015-10-01

Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

Optimization of ultrasound assisted extraction of bioactive components from brown seaweed Ascophyllum nodosum using response surface methodology.

PubMed

Kadam, Shekhar U; Tiwari, Brijesh K; Smyth, Thomas J; O'Donnell, Colm P

2015-03-01

The objective of this study was to investigate the effect of key extraction parameters of extraction time (5-25 min), acid concentration (0-0.06 M HCl) and ultrasound amplitude (22.8-114 μm) on yields of bioactive compounds (total phenolics, fucose and uronic acid) from Ascophyllumnodosum. Response surface methodology was employed to optimize the extraction variables for bioactive compounds' yield. A second order polynomial model was fitted well to the extraction experimental data with (R(2)>0.79). Extraction yields of 143.12 mgGAE/gdb, 87.06 mg/gdb and 128.54 mg/gdb were obtained for total phenolics, fucose and uronic acid respectively at optimized extraction conditions of extraction time (25 min), acid concentration (0.03 M HCl) and ultrasonic amplitude (114 μm). Mass spectroscopy analysis of extracts show that ultrasound enhances the extraction of high molecular weight phenolic compounds from A. nodosum. This study demonstrates that ultrasound assisted extraction (UAE) can be employed to enhance extraction of bioactive compounds from seaweed. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of limited irrigation strategies to improve water use efficiency and wheat yield in the North China Plain

PubMed Central

Zhang, Di; Li, Ruiqi; Batchelor, William D.; Ju, Hui

2018-01-01

The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3–4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994–2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain. PMID:29370186

Analysis of the inter- and extracellular formation of platinum nanoparticles by Fusarium oxysporum f. sp. lycopersici using response surface methodology

NASA Astrophysics Data System (ADS)

Riddin, T. L.; Gericke, M.; Whiteley, C. G.

2006-07-01

Fusarium oxysporum fungal strain was screened and found to be successful for the inter- and extracellular production of platinum nanoparticles. Nanoparticle formation was visually observed, over time, by the colour of the extracellular solution and/or the fungal biomass turning from yellow to dark brown, and their concentration was determined from the amount of residual hexachloroplatinic acid measured from a standard curve at 456 nm. The extracellular nanoparticles were characterized by transmission electron microscopy. Nanoparticles of varying size (10-100 nm) and shape (hexagons, pentagons, circles, squares, rectangles) were produced at both extracellular and intercellular levels by the Fusarium oxysporum. The particles precipitate out of solution and bioaccumulate by nucleation either intercellularly, on the cell wall/membrane, or extracellularly in the surrounding medium. The importance of pH, temperature and hexachloroplatinic acid (H2PtCl6) concentration in nanoparticle formation was examined through the use of a statistical response surface methodology. Only the extracellular production of nanoparticles proved to be statistically significant, with a concentration yield of 4.85 mg l-1 estimated by a first-order regression model. From a second-order polynomial regression, the predicted yield of nanoparticles increased to 5.66 mg l-1 and, after a backward step, regression gave a final model with a yield of 6.59 mg l-1.

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

National Peanut Research Laboratory, Dawson, GA 39842. Proper crop rotation is essential to maintaining high peanut yield and quality. However, the economic considerations of maintaining or altering crop rotation sequences must incorporate the commodity prices, production costs, and yield responses...

Optimization of extraction of polysaccharides from fruiting body of Cordyceps militaris (L.) link using response surface methodology

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Chinh; Thi, Dinh Huynh Mong; Pham, Dinh Chuong

2018-04-01

Polysaccharides from fruiting body of Cordyceps militaris (L.) Link possess various pharmaceutical activities. In this study, polysaccharides from the fruiting body of C. militaris were extracted with different solvents. Of those solvents tested, distilled water was identified as the most efficient solvent for the extraction, resulting in a significant increase in polysaccharides yield. Response surface methodology was then used to optimize the extraction conditions and establish a reliable mathematical model for prediction. A maximum polysaccharides yield of 11.07% was reached at a ratio of water to raw material of 23.2:1 mL/g, an extraction time of 76 min, and a temperature of 93.6°C. This study indicates that the obtained optimal extraction conditions are an efficient method for extraction of polysaccharides from the fruiting body of C. militaris.

Nandrolone reduces activation of Notch signaling in denervated muscle associated with increased Numb expression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xin-Hua; Department of Medicine, Mount Sinai School of Medicine, New York, NY 10029; Yao, Shen

2011-10-14

Highlights: {yields} Nerve transection increased Notch signaling in paralyzed muscle. {yields} Nandrolone prevented denervation-induced Notch signaling. {yields} Nandrolone induced the expression of an inhibitor of the Notch signaling, Numb. {yields} Reduction of denervation-induced Notch signaling by nandrolone is likely through upregulation of Numb. -- Abstract: Nandrolone, an anabolic steroid, slows denervation-atrophy in rat muscle. The molecular mechanisms responsible for this effect are not well understood. Androgens and anabolic steroids activate Notch signaling in animal models of aging and thereby mitigate sarcopenia. To explore the molecular mechanisms by which nandrolone prevents denervation-atrophy, we investigated the effects of nandrolone on Notch signalingmore » in denervated rat gastrocnemius muscle. Denervation significantly increased Notch activity reflected by elevated levels of nuclear Notch intracellular domain (NICD) and expression of Hey1 (a Notch target gene). Activation was greatest at 7 and 35 days after denervation but remained present at 56 days after denervation. Activation of Notch in denervated muscle was prevented by nandrolone associated with upregulated expression of Numb mRNA and protein. These data demonstrate that denervation activates Notch signaling, and that nandrolone abrogates this response associated with increased expression of Numb, suggesting a potential mechanism by which nandrolone reduces denervation-atrophy.« less

Analysis of utilization of desert habitats with dynamic simulation

USGS Publications Warehouse

Williams, B.K.

1986-01-01

The effects of climate and herbivores on cool desert shrubs in north-western Utah were investigated with a dynamic simulation model. Cool desert shrublands are extensively managed as grazing lands, and are defoliated annually by domestic livestock. A primary production model was used to simulate harvest yields and shrub responses under a variety of climatic regimes and defoliation patterns. The model consists of six plant components, and it is based on equations of growth analysis. Plant responses were simulated under various combinations of 20 annual weather patterns and 14 defoliation strategies. Results of the simulations exhibit some unexpected linearities in model behavior, and emphasize the importance of both the pattern of climate and the level of plant vigor in determining optimal harvest strategies. Model behaviors are interpreted in terms of shrub morphology, physiology and ecology.

Hot spots of wheat yield decline with rising temperatures.

PubMed

Asseng, Senthold; Cammarano, Davide; Basso, Bruno; Chung, Uran; Alderman, Phillip D; Sonder, Kai; Reynolds, Matthew; Lobell, David B

2017-06-01

Many of the irrigated spring wheat regions in the world are also regions with high poverty. The impacts of temperature increase on wheat yield in regions of high poverty are uncertain. A grain yield-temperature response function combined with a quantification of model uncertainty was constructed using a multimodel ensemble from two key irrigated spring wheat areas (India and Sudan) and applied to all irrigated spring wheat regions in the world. Southern Indian and southern Pakistani wheat-growing regions with large yield reductions from increasing temperatures coincided with high poverty headcounts, indicating these areas as future food security 'hot spots'. The multimodel simulations produced a linear absolute decline of yields with increasing temperature, with uncertainty varying with reference temperature at a location. As a consequence of the linear absolute yield decline, the relative yield reductions are larger in low-yielding environments (e.g., high reference temperature areas in southern India, southern Pakistan and all Sudan wheat-growing regions) and farmers in these regions will be hit hardest by increasing temperatures. However, as absolute yield declines are about the same in low- and high-yielding regions, the contributed deficit to national production caused by increasing temperatures is higher in high-yielding environments (e.g., northern India) because these environments contribute more to national wheat production. Although Sudan could potentially grow more wheat if irrigation is available, grain yields would be low due to high reference temperatures, with future increases in temperature further limiting production. © 2016 John Wiley & Sons Ltd.

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Assessing Sediment Yield for Selected Watersheds in the Laurentian Great Lakes Basin Under Future Agricultural Scenarios

EPA Science Inventory

In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) withing a GIS modeling environme...

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

A Test-Length Correction to the Estimation of Extreme Proficiency Levels

ERIC Educational Resources Information Center

Magis, David; Beland, Sebastien; Raiche, Gilles

2011-01-01

In this study, the estimation of extremely large or extremely small proficiency levels, given the item parameters of a logistic item response model, is investigated. On one hand, the estimation of proficiency levels by maximum likelihood (ML), despite being asymptotically unbiased, may yield infinite estimates. On the other hand, with an…

Sepsis and Inflammatory Response Mechanisms: An Activity Stress Model in Humans

DTIC Science & Technology

2001-01-31

anaerobic threshold yielded the reactions most typical of trauma. However, no mode of laboratory exercise induced a sustained and prolonged inflammatory...mobilization ....................................................................................... 9 8. Anaerobic threshold as a marker of the critical...after epmnephriei injection. Lymphocyte retention by lymph nodes, however, may contribute to post-injection lymphopenia. 8. Anaerobic Threshold as a

The Rangeland Hydrology and Erosion Model: A Dynamic Approach for Predicting Soil Loss on Rangelands

NASA Astrophysics Data System (ADS)

Hernandez, Mariano; Nearing, Mark A.; Al-Hamdan, Osama Z.; Pierson, Frederick B.; Armendariz, Gerardo; Weltz, Mark A.; Spaeth, Kenneth E.; Williams, C. Jason; Nouwakpo, Sayjro K.; Goodrich, David C.; Unkrich, Carl L.; Nichols, Mary H.; Holifield Collins, Chandra D.

2017-11-01

In this study, we present the improved Rangeland Hydrology and Erosion Model (RHEM V2.3), a process-based erosion prediction tool specific for rangeland application. The article provides the mathematical formulation of the model and parameter estimation equations. Model performance is assessed against data collected from 23 runoff and sediment events in a shrub-dominated semiarid watershed in Arizona, USA. To evaluate the model, two sets of primary model parameters were determined using the RHEM V2.3 and RHEM V1.0 parameter estimation equations. Testing of the parameters indicated that RHEM V2.3 parameter estimation equations provided a 76% improvement over RHEM V1.0 parameter estimation equations. Second, the RHEM V2.3 model was calibrated to measurements from the watershed. The parameters estimated by the new equations were within the lowest and highest values of the calibrated parameter set. These results suggest that the new parameter estimation equations can be applied for this environment to predict sediment yield at the hillslope scale. Furthermore, we also applied the RHEM V2.3 to demonstrate the response of the model as a function of foliar cover and ground cover for 124 data points across Arizona and New Mexico. The dependence of average sediment yield on surface ground cover was moderately stronger than that on foliar cover. These results demonstrate that RHEM V2.3 predicts runoff volume, peak runoff, and sediment yield with sufficient accuracy for broad application to assess and manage rangeland systems.

Key Response Planning Factors for the Aftermath of Nuclear Terrorism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buddemeier, B R; Dillon, M B

Despite hundreds of above-ground nuclear tests and data gathered from Hiroshima and Nagasaki, the effects of a ground-level, low-yield nuclear detonation in a modern urban environment are still the subject of considerable scientific debate. Extensive review of nuclear weapon effects studies and discussions with nuclear weapon effects experts from various federal agencies, national laboratories, and technical organizations have identified key issues and bounded some of the unknowns required to support response planning for a low-yield, ground-level nuclear detonation in a modern U.S. city. This study, which is focused primarily upon the hazards posed by radioactive fallout, used detailed fallout predictionsmore » from the advanced suite of three-dimensional (3-D) meteorology and plume/fallout models developed at Lawrence Livermore National Laboratory (LLNL), including extensive global Key Response Planning Factors for the Aftermath of Nuclear Terrorism geographical and real-time meteorological databases to support model calculations. This 3-D modeling system provides detailed simulations that account for complex meteorology and terrain effects. The results of initial modeling and analysis were presented to federal, state, and local working groups to obtain critical, broad-based review and feedback on strategy and messaging. This effort involved a diverse set of communities, including New York City, National Capitol Regions, Charlotte, Houston, Portland, and Los Angeles. The largest potential for reducing casualties during the post-detonation response phase comes from reducing exposure to fallout radiation. This can be accomplished through early, adequate sheltering followed by informed, delayed evacuation.B The response challenges to a nuclear detonation must be solved through multiple approaches of public education, planning, and rapid response actions. Because the successful response will require extensive coordination of a large number of organizations, supplemented by appropriate responses by local responders and the general population within the hazard zones, regional planning is essential to success. The remainder of this Executive Summary provides summary guidance for response planning in three areas: (1) Public Protection Strategy details the importance of early, adequate shelter followed by informed evacuation. (2) Responder Priorities identify how to protect response personnel, perform regional situational assessment, and support public safety. (3) Key Planning Considerations refute common myths and provide important information on planning how to respond in the aftermath of nuclear terrorism.« less

Socio-climatic Exposure of an Afghan Poppy Farmer

NASA Astrophysics Data System (ADS)

Mankin, J. S.; Diffenbaugh, N. S.

2011-12-01

Many posit that climate impacts from anthropogenic greenhouse gas emissions will have consequences for the natural and agricultural systems on which humans rely for food, energy, and livelihoods, and therefore, on stability and human security. However, many of the potential mechanisms of action in climate impacts and human systems response, as well as the differential vulnerabilities of such systems, remain underexplored and unquantified. Here I present two initial steps necessary to characterize and quantify the consequences of climate change for farmer livelihood in Afghanistan, given both climate impacts and farmer vulnerabilities. The first is a conceptual model mapping the potential relationships between Afghanistan's climate, the winter agricultural season, and the country's political economy of violence and instability. The second is a utility-based decision model for assessing farmer response sensitivity to various climate impacts based on crop sensitivities. A farmer's winter planting decision can be modeled roughly as a tradeoff between cultivating the two crops that dominate the winter growing season-opium poppy (a climate tolerant cash crop) and wheat (a climatically vulnerable crop grown for household consumption). Early sensitivity analysis results suggest that wheat yield dominates farmer decision making variability; however, such initial results may dependent on the relative parameter ranges of wheat and poppy yields. Importantly though, the variance in Afghanistan's winter harvest yields of poppy and wheat is tightly linked to household livelihood and thus, is indirectly connected to the wider instability and insecurity within the country. This initial analysis motivates my focused research on the sensitivity of these crops to climate variability in order to project farmer well-being and decision sensitivity in a warmer world.

A Point-process Response Model for Spike Trains from Single Neurons in Neural Circuits under Optogenetic Stimulation

PubMed Central

Luo, X.; Gee, S.; Sohal, V.; Small, D.

2015-01-01

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high frequency point process (neuronal spikes) while the input is another high frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, Point-process Responses for Optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the- curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters. PMID:26411923

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

Proper crop rotation is essential to maintaining high peanut yield and quality. However, the economic considerations of maintaining or altering crop rotation sequences must incorporate the commodity prices, production costs, and yield responses of all crops in, or potentially in, the crop rotation ...

A thermomechanical anisotropic model for shock loading of elastic-plastic and elastic-viscoplastic materials with application to jointed rock

DOE PAGES

Rubin, M. B.; Vorobiev, O.; Vitali, E.

2016-04-21

Here, a large deformation thermomechanical model is developed for shock loading of a material that can exhibit elastic and inelastic anisotropy. Use is made of evolution equations for a triad of microstructural vectors m i(i=1,2,3) which model elastic deformations and directions of anisotropy. Specific constitutive equations are presented for a material with orthotropic elastic response. The rate of inelasticity depends on an orthotropic yield function that can be used to model weak fault planes with failure in shear and which exhibits a smooth transition to isotropic response at high compression. Moreover, a robust, strongly objective numerical algorithm is proposed formore » both rate-independent and rate-dependent response. The predictions of the continuum model are examined by comparison with exact steady-state solutions. Also, the constitutive equations are used to obtain a simplified continuum model of jointed rock which is compared with high fidelity numerical solutions that model a persistent system of joints explicitly in the rock medium.« less

Construction of a memory battery for computerized administration, using item response theory.

PubMed

Ferreira, Aristides I; Almeida, Leandro S; Prieto, Gerardo

2012-10-01

In accordance with Item Response Theory, a computer memory battery with six tests was constructed for use in the Portuguese adult population. A factor analysis was conducted to assess the internal structure of the tests (N = 547 undergraduate students). According to the literature, several confirmatory factor models were evaluated. Results showed better fit of a model with two independent latent variables corresponding to verbal and non-verbal factors, reproducing the initial battery organization. Internal consistency reliability for the six tests were alpha = .72 to .89. IRT analyses (Rasch and partial credit models) yielded good Infit and Outfit measures and high precision for parameter estimation. The potential utility of these memory tasks for psychological research and practice willbe discussed.

Modeling and optimization aspects of radiation induced grafting of 4-vinylpyridene onto partially fluorinated films

NASA Astrophysics Data System (ADS)

Nasef, Mohamed Mahmoud; Ahmad Ali, Amgad; Saidi, Hamdani; Ahmad, Arshad

2014-01-01

Modeling and optimization aspects of radiation induced grafting (RIG) of 4-vinylpyridine (4-VP) onto partially fluorinated polymers such as poly(ethylene-co-tetrafluoroethene) (ETFE) and poly(vinylidene fluoride) (PVDF) films were comparatively investigated using response surface method (RSM). The effects of independent parameters: absorbed dose, monomer concentration, grafting time and reaction temperature on the response, grafting yield (GY) were correlated through two quadratic models. The results of this work confirm that RSM is a reliable tool not only for optimization of the reaction parameters and prediction of GY in RIG processes, but also for the reduction of the number of the experiments, monomer consumption and absorbed dose leading to an improvement of the overall reaction cost.

Fewer not more leaves - Key to obtaining the needed jump in crop yield potential and water use efficiency

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Kumar, P.; Long, S.

2013-12-01

Word food and feed supply needs to increase by 75% by 2050 to meet the increasing demands of our growing population. Soybean which is the world`s fourth most important crop in terms of total production at 250 million Mt/yr is a key protein source, and together with rice and wheat, are experiencing declining global yield increases year on year. At present rates of improvement, 2050 targets cannot be reached without new innovations. In this study we demonstrate an innovative approach that could provide a yield jump. While, natural selection favors individual plants to maximize leaf production to maximize light interception and shade competitors, the presence of this trait in domestic crops could be disadvantageous. In addition, rising CO2 causes increased leaf production further exacerbating the problem. Here, we show by mathematical model and field experiment that, a modern cultivar growing at the center of US soy cultivation produces too many leaves and reduction to an optimal level would increase yield. Our model results indicate that an LAI of 3.5 and 3.8 produces maximal rates of net canopy assimilation under ambient and elevated CO2 conditions respectively. However, observed peak LAI values are 6.9 and 7.5 under ambient and elevated CO2 conditions respectively. This results in a NPP loss of 30% and 20% under ambient and elevated CO2 conditions respectively. Furthermore, the optimal LAI results in a decreased transpiration of up to 30% thus increasing water use efficiency. We show that as LAI increases, the tradeoffs between diminishing day time gains in NPP, and increasing losses in respiration is responsible for this effect. By designing a more optimum canopy, we can increase NPP and this potentially translates to increased seed yield. To test this model result, we perform canopy manipulation experiments on soybean plants, where we artificially decrease LAI by periodically removing young and emerging leaves throughout the growing season (after pod onset), and measure the seed yield under ambient and elevated CO2 conditions. Our experimental results show that an LAI reduction of 0.5 results in an increased seed yield of 8.1% validating our model results. We propose that, by achieving a stronger LAI reduction, we can improve seed yields by up to 24% providing the much needed jump in yield to achieve future food security.

Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

NASA Astrophysics Data System (ADS)

Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

2017-02-01

The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

An evolving effective stress approach to anisotropic distortional hardening

DOE PAGES

Lester, B. T.; Scherzinger, W. M.

2018-03-11

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

An evolving effective stress approach to anisotropic distortional hardening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lester, B. T.; Scherzinger, W. M.

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

Equilibrium Atmospheric Response to North Atlantic SST Anomalies.

NASA Astrophysics Data System (ADS)

Kushnir, Yochanan; Held, Isaac M.

1996-06-01

The equilibrium general circulation model (GCM) response to sea surface temperature (SST) anomalies in the western North Atlantic region is studied. A coarse resolution GCM, with realistic lower boundary conditions including topography and climatological SST distribution, is integrated in perpetual January and perpetual October modes, distinguished from one another by the strength of the midlatitude westerlies. An SST anomaly with a maximum of 4°C is added to the climatological SST distribution of the model with both positive and negative polarity. These anomaly runs are compared to one another, and to a control integration, to determine the atmospheric response. In all cases warming (cooling) of the midlatitude ocean surface yields a warming (cooling) of the atmosphere over and to the east of the SST anomaly center. The atmospheric temperature change is largest near the surface and decreases upward. Consistent with this simple thermal response, the geopotential height field displays a baroclinic response with a shallow anomalous low somewhat downstream from the warm SST anomaly. The equivalent barotropic, downstream response is weak and not robust. To help interpret the results, the realistic GCM integrations are compared with parallel idealized model runs. The idealized model has full physics and a similar horizontal and vertical resolution, but an all-ocean surface with a single, permanent zonal asymmetry. The idealized and realistic versions of the GCM display compatible response patterns that are qualitatively consistent with stationary, linear, quasigeostrophic theory. However, the idealized model response is stronger and more coherent. The differences between the two model response patterns can be reconciled based on the size of the anomaly, the model treatment of cloud-radiation interaction, and the static stability of the model atmosphere in the vicinity of the SST anomaly. Model results are contrasted with other GCM studies and observations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akerib, DS; Alsum, S; Araújo, HM

The LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Alsum, S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Brás, P.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; Dobi, A.; Dobson, J. E. Y.; Druszkiewicz, E.; Edwards, B. N.; Faham, C. H.; Fallon, S. R.; Fan, A.; Fiorucci, S.; Gaitskell, R. J.; Gehman, V. M.; Genovesi, J.; Ghag, C.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Jacobsen, R. G.; Ji, W.; Kamdin, K.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Palladino, K. J.; Pease, E. K.; Reichhart, L.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solmaz, M.; Solovov, V. N.; Sorensen, P.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W. C.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Velan, V.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Xu, J.; Yazdani, K.; Young, S. K.; Zhang, C.; LUX Collaboration

2018-05-01

The LUX experiment has performed searches for dark-matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived from 1.4 ×104 kg days of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.

Modelling the future impacts of climate and land-use change on suspended sediment transport in the River Thames (UK)

NASA Astrophysics Data System (ADS)

Bussi, Gianbattista; Dadson, Simon J.; Prudhomme, Christel; Whitehead, Paul G.

2016-11-01

The effects of climate change and variability on river flows have been widely studied. However the impacts of such changes on sediment transport have received comparatively little attention. In part this is because modelling sediment production and transport processes introduces additional uncertainty, but it also results from the fact that, alongside the climate change signal, there have been and are projected to be significant changes in land cover which strongly affect sediment-related processes. Here we assess the impact of a range of climatic variations and land covers on the River Thames catchment (UK). We first calculate a response of the system to climatic stressors (average precipitation, average temperature and increase in extreme precipitation) and land-cover stressors (change in the extent of arable land). To do this we use an ensemble of INCA hydrological and sediment behavioural models. The resulting system response, which reveals the nature of interactions between the driving factors, is then compared with climate projections originating from the UKCP09 assessment (UK Climate Projections 2009) to evaluate the likelihood of the range of projected outcomes. The results show that climate and land cover each exert an individual control on sediment transport. Their effects vary depending on the land use and on the level of projected climate change. The suspended sediment yield of the River Thames in its lowermost reach is expected to change by -4% (-16% to +13%, confidence interval, p = 0.95) under the A1FI emission scenario for the 2030s, although these figures could be substantially altered by an increase in extreme precipitation, which could raise the suspended sediment yield up to an additional +10%. A 70% increase in the extension of the arable land is projected to increase sediment yield by around 12% in the lowland reaches. A 50% reduction is projected to decrease sediment yield by around 13%.

Modeling heat stress effect on Holstein cows under hot and dry conditions: selection tools.

PubMed

Carabaño, M J; Bachagha, K; Ramón, M; Díaz, C

2014-12-01

Data from milk recording of Holstein-Friesian cows together with weather information from 2 regions in Southern Spain were used to define the models that can better describe heat stress response for production traits and somatic cell score (SCS). Two sets of analyses were performed, one aimed at defining the population phenotypic response and the other at studying the genetic components. The first involved 2,514,762 test-day records from up to 5 lactations of 128,112 cows. Two models, one fitting a comfort threshold for temperature and a slope of decay after the threshold, and the other a cubic Legendre polynomial (LP) model were tested. Average (TAVE) and maximum daily temperatures were alternatively considered as covariates. The LP model using TAVE as covariate showed the best goodness of fit for all traits. Estimated rates of decay from this model for production at 25 and 34°C were 36 and 170, 3.8 and 3.0, and 3.9 and 8.2g/d per degree Celsius for milk, fat, and protein yield, respectively. In the second set of analyses, a sample of 280,958 test-day records from first lactations of 29,114 cows was used. Random regression models including quadratic or cubic LP regressions (TEM_) on TAVE or a fixed threshold and an unknown slope (DUMMY), including or not cubic regressions on days in milk (DIM3_), were tested. For milk and SCS, the best models were the DIM3_ models. In contrast, for fat and protein yield, the best model was TEM3. The DIM3DUMMY models showed similar performance to DIM3TEM3. The estimated genetic correlations between the same trait under cold and hot temperatures (ρ) indicated the existence of a large genotype by environment interaction for fat (ρ=0.53 for model TEM3) and protein yield (ρ around 0.6 for DIM3TEM3) and for SCS (ρ=0.64 for model DIM3TEM3), and a small genotype by environment interaction for milk (ρ over 0.8). The eigendecomposition of the additive genetic covariance matrix from model TEM3 showed the existence of a dominant component, a constant term that is not affected by temperature, representing from 64% of the variation for SCS to 91% of the variation for milk. The second component, showing a flat pattern at intermediate temperatures and increasing or decreasing slopes for the extremes, gathered 15, 11, and 24% of the variation for fat and protein yield and SCS, respectively. This component could be further evaluated as a selection criterion for heat tolerance independently of the production level. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Crop yield response to increasing biochar rates

USDA-ARS?s Scientific Manuscript database

The benefit or detriment to crop yield from biochar application varies with biochar type/rate, soil, crop, or climate. The objective of this research was to identify yield response of cotton (Gossypium hirsutum L.), corn (Zea mayes L.), and peanut (Arachis hypogaea L.) to hardwood biochar applied at...

Depression of Photosynthesis, Growth, and Yield in Field-Grown Green Pepper (Capsicum annuum L.) Exposed to Acidic Fog and Ambient Ozone 1

PubMed Central

Takemoto, Brent K.; Bytnerowicz, Andrzej; Olszyk, David M.

1988-01-01

The relationship among physiological, injury, growth, and yield responses was examined in field-grown green pepper (Capsicum annuum L. `California Wonder') subjected to two airborne environmental stresses. The primary objectives were to determine if the stresses could cause alterations in the plant responses, and to determine if any stress induced alterations in physiological or injury responses were correlated with effects on growth or yield. Responses were monitored in green pepper exposed to simulated acidic fog alone, or in combination with ambient concentrations of ozone in open-top field chambers. Both highly acidic fog and ambient ozone depressed green pepper growth and yield responses via the inhibition of photosynthesis. Applications of highly acidic fog (i.e. two exposures of pH 1.68 fog per week for 11 weeks) caused a significant depression of net photosynthesis, reduction in leaf buffering capacity, and an extensive amount of leaf injury. These alterations closely paralleled decreases in growth and yield on a percentage basis. In contrast, ambient ozone had similar impacts on net photosynthesis, growth and yield, but enhanced leaf buffering capacity, and caused no visible injury. The pollutant-specific differences in plant response are discussed with respect to whole-plant carbon metabolism and physiological compensation. PMID:16666330

A design methodology of magentorheological fluid damper using Herschel-Bulkley model

NASA Astrophysics Data System (ADS)

Liao, Linqing; Liao, Changrong; Cao, Jianguo; Fu, L. J.

2003-09-01

Magnetorheological fluid (MR fluid) is highly concentrated suspension of very small magnetic particle in inorganic oil. The essential behavior of MR fluid is its ability to reversibly change from free-flowing, linear viscous liquids to semi-solids having controllable yield strength in milliseconds when exposed to magnetic field. This feature provides simple, quiet, rapid-response interfaces between electronic controls and mechanical systems. In this paper, a mini-bus MR fluid damper based on plate Poiseuille flow mode is typically analyzed using Herschel-Bulkley model, which can be used to account for post-yield shear thinning or thickening under the quasi-steady flow condition. In the light of various value of flow behavior index, the influences of post-yield shear thinning or thickening on flow velocity profiles of MR fluid in annular damping orifice are examined numerically. Analytical damping coefficient predictions also are compared via the nonlinear Bingham plastic model and Herschel-Bulkley constitutive model. A MR fluid damper, which is designed and fabricated according to design method presented in this paper, has tested by electro-hydraulic servo vibrator and its control system in National Center for Test and Supervision of Coach Quality. The experimental results reveal that the analysis methodology and design theory are reasonable and MR fluid damper can be designed according to the design methodology.

From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

NASA Astrophysics Data System (ADS)

JÉGO, G.; Pattey, E.; Liu, J.

2013-12-01

The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%

Supercritical Carbon Dioxide Extraction of Flavonoids from Pomelo (Citrus grandis (L.) Osbeck) Peel and Their Antioxidant Activity

PubMed Central

He, Jin-Zhe; Shao, Ping; Liu, Jian-Hua; Ru, Qiao-Mei

2012-01-01

Supercritical carbon dioxide (SC-CO2) extraction of flavonoids from pomelo (Citrus grandis (L.) Osbeck) peel and their antioxidant activity were investigated. Box-Behnken design combined with response surface methodology was employed to maximize the extraction yield of flavonoids. Correlation analysis of the mathematical-regression model indicated that a quadratic polynomial model could be used to optimize the SC-CO2 extraction of flavonoids. The optimal conditions for obtaining the highest extraction yield of flavonoids from pomelo peel were a temperature of 80 °C, a pressure of 39 MPa and a static extraction time of 49 min in the presence of 85% ethanol as modifier. Under these conditions, the experimental yield was 2.37%, which matched positively with the value predicted by the model. Furthermore, flavonoids obtained by SC-CO2 extraction showed a higher scavenging activity on hydroxyl, 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) radicals than those obtained by conventional solvent extraction (CSE). Therefore, SC-CO2 extraction can be considered as a suitable technique for the obtainment of flavonoids from pomelo peel. PMID:23202938

Source-sink interaction: a century old concept under the light of modern molecular systems biology.

PubMed

Chang, Tian-Gen; Zhu, Xin-Guang; Raines, Christine

2017-07-20

Many approaches to engineer source strength have been proposed to enhance crop yield potential. However, a well-co-ordinated source-sink relationship is required finally to realize the promised increase in crop yield potential in the farmer's field. Source-sink interaction has been intensively studied for decades, and a vast amount of knowledge about the interaction in different crops and under different environments has been accumulated. In this review, we first introduce the basic concepts of source, sink and their interactions, then summarize current understanding of how source and sink can be manipulated through both environmental control and genetic manipulations. We show that the source-sink interaction underlies the diverse responses of crops to the same perturbations and argue that development of a molecular systems model of source-sink interaction is required towards a rational manipulation of the source-sink relationship for increased yield. We finally discuss both bottom-up and top-down routes to develop such a model and emphasize that a community effort is needed for development of this model. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Nanomechanics of slip avalanches in amorphous plasticity

NASA Astrophysics Data System (ADS)

Cao, Penghui; Dahmen, Karin A.; Kushima, Akihiro; Wright, Wendelin J.; Park, Harold S.; Short, Michael P.; Yip, Sidney

2018-05-01

Discrete stress relaxations (slip avalanches) in a model metallic glass under uniaxial compression are studied using a metadynamics algorithm for molecular simulation at experimental strain rates. The onset of yielding is observed at the first major stress drop, accompanied, upon analysis, by the formation of a single localized shear band region spanning the entire system. During the elastic response prior to yielding, low concentrations of shear transformation deformation events appear intermittently and spatially uncorrelated. During serrated flow following yielding, small stress drops occur interspersed between large drops. The simulation results point to a threshold value of stress dissipation as a characteristic feature separating major and minor avalanches consistent with mean-field modeling analysis and mechanical testing experiments. We further interpret this behavior to be a consequence of a nonlinear interplay of two prevailing mechanisms of amorphous plasticity, thermally activated atomic diffusion and stress-induced shear transformations, originally proposed by Spaepen and Argon, respectively. Probing the atomistic processes at widely separate strain rates gives insight to different modes of shear band formation: percolation of shear transformations versus crack-like propagation. Additionally a focus on crossover avalanche size has implications for nanomechanical modeling of spatially and temporally heterogeneous dynamics.

Comparing Benign and Malignant Neoplasia and DSB Induction for Low-and High-LET Radiation

NASA Astrophysics Data System (ADS)

Burns, Fredric; Tang, Moon-Shong Eric; Wu, Feng

One-and 2-stage models based on DNA double strand breaks (DSBs) have been developed to describe the dose and LET dependence of cancer induction in rat skin exposed to the Bragg plateau of several ion beams or electron radiation. Data are presented showing that carcinomas (malignant) and fibromas (benign) are induced differently by low and high LET radiation. DSBs are subject to complex repair processes, including homologous and non-homologous end joining, that slowly eliminate broken chromosome ends but at the expense of elevating genomic instability that increases the risk of neoplasia. In this formulation the initial molecular lesion in radiation carcinogenesis is assumed to be a DNA double strand break (DSB). The 2-event model assumes that pairs of DSBs join to create cellular genomic instability that eventually progresses to malignancy. The 1-event model assumes that joining is insignificant but that unrepaired DSBs remain and are sufficiently destabilizing to produce low-grade neoplasias. The respective expected relationships between neoplasia yield (Y), radiation dose (D) and LET (L) are: Y(D) = CLD + BD2 (A) for 2-events and Y(D) = CLD (B) for 1-event. Respective B and C values have been evaluated empirically for carcinomas, fibromas and DSBs, the latter via the -H2Ax technique in surrogate keratinocytes, for several types of radiations, including, 40Ar ions, 56Fe ions, 20Ne ions, protons, electrons and x-rays. Fibromas outnumber carcinomas by about 6:1 but are more sensitive than carcinomas to the cytolethal effect of the radiations. The 2-event model agrees well with carcinoma yields in rat skin but fails to model fibromas correctly. Instead the fibroma yields best fitted with the 1-event model for the high LET ion radiations, but at very low LET (electron radiation), an empirical D3 component becomes apparent which is not currently incorporated into the theoretical model. At higher LET values, the D3 component was not detected. The overall results are summarized as follows: 1) DSBs predict carcinoma yields in regard to dose and LET in conformity to Equation A, 2) fibroma yields for 40Ar and 20Ne ions conform to Equation B, i.e. yield proportionality to D and L and 3) the positive slope of the fibroma yield to electron radiation is a third order discrepancy suggesting a more complicated response that has yet to be incorporated into the model. The results provide encouragement that once calibrated for humans, a short-term test of DSB yield might be capable of predicting cancer risks for a variety of space radiation exposure scenarios.

Optimization of extraction parameters of pentacyclic triterpenoids from Swertia chirata stem using response surface methodology.

PubMed

Pandey, Devendra Kumar; Kaur, Prabhjot

2018-03-01

In the present investigation, pentacyclic triterpenoids were extracted from different parts of Swertia chirata by solid-liquid reflux extraction methods. The total pentacyclic triterpenoids (UA, OA, and BA) in extracted samples were determined by HPTLC method. Preliminary studies showed that stem part contains the maximum pentacyclic triterpenoid and was chosen for further studies. Response surface methodology (RSM) has been employed successfully by solid-liquid reflux extraction methods for the optimization of different extraction variables viz., temperature ( X 1 35-70 °C), extraction time ( X 2 30-60 min), solvent composition ( X 3 20-80%), solvent-to-solid ratio ( X 4 30-60 mlg -1 ), and particle size ( X 5 3-6 mm) on maximum recovery of triterpenoid from stem parts of Swertia chirata . A Plackett-Burman design has been used initially to screen out the three extraction factors viz., particle size, temperature, and solvent composition on yield of triterpenoid. Moreover, central composite design (CCD) was implemented to optimize the significant extraction parameters for maximum triterpenoid yield. Three extraction parameters viz., mean particle size (3 mm), temperature (65 °C), and methanol-ethyl acetate solvent composition (45%) can be considered as significant for the better yield of triterpenoid A second-order polynomial model satisfactorily fitted the experimental data with the R 2 values of 0.98 for the triterpenoid yield ( p  < 0.001), implying good agreement between the experimental triterpenoid yield (3.71%) to the predicted value (3.79%).

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

NASA Astrophysics Data System (ADS)

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.

Plant ecosystem responses to rising atmospheric CO2: applying a "two-timing" approach to assess alternative hypotheses for mechanisms of nutrient limitation

NASA Astrophysics Data System (ADS)

Medlyn, B.; Jiang, M.; Zaehle, S.

2017-12-01

There is now ample experimental evidence that the response of terrestrial vegetation to rising atmospheric CO2 concentration is modified by soil nutrient availability. How to represent nutrient cycling processes is thus a key consideration for vegetation models. We have previously used model intercomparison to demonstrate that models incorporating different assumptions predict very different responses at Free-Air CO2 Enrichment experiments. Careful examination of model outputs has provided some insight into the reasons for the different model outcomes, but it is difficult to attribute outcomes to specific assumptions. Here we investigate the impact of individual assumptions in a generic plant carbon-nutrient cycling model. The G'DAY (Generic Decomposition And Yield) model is modified to incorporate alternative hypotheses for nutrient cycling. We analyse the impact of these assumptions in the model using a simple analytical approach known as "two-timing". This analysis identifies the quasi-equilibrium behaviour of the model at the time scales of the component pools. The analysis provides a useful mathematical framework for probing model behaviour and identifying the most critical assumptions for experimental study.

Ozone risk assessment for agricultural crops in Europe: Further development of stomatal flux and flux-response relationships for European wheat and potato

NASA Astrophysics Data System (ADS)

Pleijel, H.; Danielsson, H.; Emberson, L.; Ashmore, M. R.; Mills, G.

Applications of a parameterised Jarvis-type multiplicative stomatal conductance model with data collated from open-top chamber experiments on field grown wheat and potato were used to derive relationships between relative yield and stomatal ozone uptake. The relationships were based on thirteen experiments from four European countries for wheat and seven experiments from four European countries for potato. The parameterisation of the conductance model was based both on an extensive literature review and primary data. Application of the stomatal conductance models to the open-top chamber experiments resulted in improved linear regressions between relative yield and ozone uptake compared to earlier stomatal conductance models, both for wheat ( r2=0.83) and potato ( r2=0.76). The improvement was largest for potato. The relationships with the highest correlation were obtained using a stomatal ozone flux threshold. For both wheat and potato the best performing exposure index was AF st6 (accumulated stomatal flux of ozone above a flux rate threshold of 6 nmol ozone m -2 projected sunlit leaf area, based on hourly values of ozone flux). The results demonstrate that flux-based models are now sufficiently well calibrated to be used with confidence to predict the effects of ozone on yield loss of major arable crops across Europe. Further studies, using innovations in stomatal conductance modelling and plant exposure experimentation, are needed if these models are to be further improved.

Response to Comment by H. Lough, Department of Civil Engineering, University of Canterbury, Christchurch, New Zealand, on the Paper " Stream Depletion Predictions using Pumping Test Data from A Heterogeneous Stream-Aquifer System (A Case Study from the Gr

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kollet, S J; Zlotnik, V A

2004-12-20

We thank H. Lough for her interest in our data set and the attempt to re-analyze our results (Kollet and Zlotnik, 2003) using the recent model by Hunt (2003). We welcome others to share our unique data set of the pumping test from the Prairie Creek site, Nebraska, USA. Nevertheless we believe that this particular attempt failed, because H. Lough selected a wrong model of semi-confined aquifer conditions for the interpretation of the pumping test data, which was collected in an unconfined aquifer. H. Lough based her selection on the three distinct drawdown segments observed during the test. It ismore » well known that geologically distinct aquifers can yield a three-segment drawdown response under pumping conditions (e.g., Streltsova, 1988). Examples include unconfined aquifers (e.g., Neuman, 1972; Moench, 1997), aquifers with double porosity or fractures (e.g., Barenblatt et al., 1960; Boulton and Streltsova-Adams, 1978), and (semi-) confined aquifers in contact with aquitards (e.g. Cooley and Case, 1973; Moench, 1985). At the Prairie Creek site the aquifer is unconfined. The interpretation of the pumping test data collected at the site using type curves that are valid for an aquifer-aquitard system is a mistake. In fact, this approach illustrates a typical problem associated with inverse modeling: drastically different models can closely reproduce a system response and yield some parameter estimates, although the models do not represent the real system adequately. Here, the improper model yields some parameter estimates for an aquitard, although the aquitard does not exist at the Prairie Creek test site. We must also unequivocally state that the model by Hunt (2003) is clearly formulated and correct for stream-aquifer-aquitard systems within the stated limitations (pumping wells screened only in the lowest stratigraphic layer, etc.). However, the Hunt (1999) or BZT (Butler et al., 2001) models should be used for interpreting pumping tests near streams in non-leaky aquifers as outlined in our study (Kollet and Zlotnik, 2003). The purpose of the comment by H. Lough is to examine three drawdown segments and results from Kollet and Zlotnik (2003) using a newer analytical model of stream-aquifer interactions by Hunt (2003). We will address the key issues of this comment in this paper.« less

Responses of inulin content and inulin yield of Jerusalem artichoke genotypes to seasonal environments

USDA-ARS?s Scientific Manuscript database

Seasonal variation (e.g. temperature and photoperiod) between growing seasons might affect inulin content and inulin yield of Jerusalem artichoke. However, there is limited information on genotypic response to seasons for inulin content and inulin yield. The objective of this study was to investig...

Interaction of potato production systems and the environment: a case of waste water irrigation in central Washington.

PubMed

Wang, H Holly; Tan, Tih Koon; Schotzko, R Thomas

2007-02-01

Potato production and processing are very important activities in the agricultural economy of the Pacific Northwest. Part of the reason for the development of this industry has been the availability of water for both growing and processing. A great amount of water is used in processing potato products, such as frozen French fries, and the waste water is a pollutant because it contains high levels of nitrate and other nutrients. Using this waste water to irrigate the fields can be a suitable disposal method. Field application will reduce potato fertilizer costs, but it can also cause underground water contamination if over-applied to the field. In this econometric study, we used field data associated with current waste water applications in central Washington to examine the yield response as well as the soil nitrogen content response to waste water applications. Our results from the production model show that both water and nitrogen positively affect crop yields at the current levels of application, but potassium has been over applied. This implies that replacing some waste water with fresh water and nitrogen fertilizer will increase production. The environmental model results show that applying more nitrogen to the soil leads to more movement below the root zone. The results also suggest that higher crop yields lead to less nitrogen in the soil, and applying more water increases crop yields, which can reduce the nitrogen left in the soil. Therefore, relative to the current practice, waste water application rates should be reduced and supplemented with fresh water to enhance nitrogen use by plants and reduce residual nitrogen in the soil.

Impacts of Farmers' Knowledge Increase on Farm Profit and Watershed Water Quality

NASA Astrophysics Data System (ADS)

Ding, D.; Bennett, D. A.

2013-12-01

This study explores the impact that an increase in real-time data might have on farmers' nitrogen management, on-farm profit, and watershed water quality in the Midwestern US. In this study, an agent-based model (ABM) is used to simulate farmers' decisions about nitrogen application rate and timing in corn fields. SWAT (soil-water assessment tool) is used to generate a database that characterizes the response of corn yields to nitrogen fertilizer application and the dynamics of nitrogen loss under different scenarios of rainfall events. The database simulates a scenario where farmers would receive real-time feedback about the fate and impact of nitrogen applied to their fields from in-situ sensors. The ability to transform these data into optimal actions is simulated at multiple levels for farmer agents. In a baseline scenario, the farmer agent is only aware of the yield potential of the land field and single values of N rates for achieving the yield potential and is not aware of N loss from farm fields. Knowledge increase is represented by greater accuracy in predicting rainfall events, and the increase of the number of discrete points in a field-specific quadratic curve that captures crop yield response to various levels of nitrogen perceived by farmer agents. In addition, agents perceive N loss from farm fields at increased temporal resolutions. Correspondingly, agents make adjustments to the rate of N application for crops and the timing of fertilizer application given the rainfall events predictions. Farmers' decisions simulated by the ABM are input into SWAT to model nitrogen concentration in impacted streams. Farm profit statistics and watershed-level nitrogen loads are compared among different scenarios of knowledge increase. The hypothesis that the increase of farmers' knowledge benefits both farm profits and watershed water quality is tested through the comparison.

Response surface optimization of the thermal acid pretreatment of sugar beet pulp for bioethanol production using Trichoderma viride and Saccharomyces cerevisiae.

PubMed

El-Gendy, Nour Sh; Madian, Hekmat R; Nassar, Hussein N; Abu Amr, Salem S

2015-01-01

Worldwide nowadays, relying on the second generation bioethanol from the lignocellulosic feedstock is a mandatory aim. However, one of the major drawbacks for high ethanol yield is the physical and chemical pretreatment of this kind of feedstock. As the pretreatment is a crucial process operation that modifies the lignocellulosic structure and enhances its accessibility for the high cost hydrolytic enzymes in an attempt to maximize the yield of the fermentable sugars. The objective of this work was to optimize and integrate a physicochemical pretreatment of one of the major agricultural wastes in Egypt; the sugar beet pulp (SBP) and the enzymatic saccharification of the pretreated SBP using a whole fungal cells with a separate bioethanol fermentation batch processes to maximize the bioethanol yield. The response surface methodology was employed in this study to statistically evaluate and optimize the conditions for a thermal acid pretreatment of SBP. The significance and the interaction effects of the concentrations of HCl and SBP and the reaction temperature and time were studied using a three-level central composite design of experiments. A quadratic model equation was obtained to maximize the production of the total reducing sugars. The validity of the predicted model was confirmed. The thermally acid pretreated SBP was further subjected to a solid state fermentation batch process using Trichoderma viride F94. The thermal acid pretreatment and fungal hydrolyzes were integrated with two parallel batch fermentation processes of the produced hydrolyzates using Saccharomyces cerevisiae Y39, that yielded a total of ≈ 48 g/L bioethanol, at a conversion rate of ≈ 0.32 g bioethanol/ g SBP. Applying the proposed integrated process, approximately 97.5 gallon of ethanol would be produced from a ton (dry weight) of SBP.

Response surface optimization of the thermal acid pretreatment of sugar beet pulp for bioethanol production using Trichoderma viride and Saccharomyces cerevisiae.

PubMed

El-Gendy, Nour Sh; Madian, Hekmat R; Nassar, Hussein N; Amr, Salem S Abu

2015-09-15

Worldwide nowadays, relying on the second generation bioethanol from the lignocellulosic feedstock is a mandatory aim. However, one of the major drawbacks for high ethanol yield is the physical and chemical pretreatment of this kind of feedstock. As the pretreatment is a crucial process operation that modifies the lignocellulosic structure and enhances its accessibility for the high cost hydrolytic enzymes in an attempt to maximize the yield of the fermentable sugars. The objective of this work was to optimize and integrate a physicochemical pretreatment of one of the major agricultural wastes in Egypt; the sugar beet pulp (SBP) and the enzymatic saccharification of the pretreated SBP using a whole fungal cells with a separate bioethanol fermentation batch processes to maximize the bioethanol yield. The response surface methodology was employed in this study to statistically evaluate and optimize the conditions for a thermal acid pretreatment of SBP. The significance and the interaction effects of the concentrations of HCl and SBP and the reaction temperature and time were studied using a three-level central composite design of experiments. A quadratic model equation was obtained to maximize the production of the total reducing sugars. The validity of the predicted model was confirmed. The thermally acid pretreated SBP was further subjected to a solid state fermentation batch process using Trichoderma viride F94. The thermal acid pretreatment and fungal hydrolyzes were integrated with two parallel batch fermentation processes of the produced hydrolyzates using Saccharomyces cerevisiae Y39, that yielded a total of ≈ 48 g/L bioethanol, at a conversion rate of ≈ 0.32 g bioethanol/ g SBP. Applying the proposed integrated process, approximately 97.5 gallon of ethanol would be produced from a ton (dry weight) of SBP.

Improved Understanding of the Photosynthetic Response of Seven Rice Genotypes with Different Drought Sensitivity using Light and CO2 Response Curves

NASA Astrophysics Data System (ADS)

Mitra, B.; Basu, S.; Bereznyakov, D.; Pereira, A.; Naithani, K. J.

2015-12-01

Drought across different agro-climatic regions of the world has the capacity to drastically impact the yield potential of rice. Consequently, there is growing interest in developing drought tolerant rice varieties with high yield. We parameterized two photosynthesis models based on light and CO2 response curves for seven different rice genotypes with different drought survival mechanisms: sensitive (Nipponbar, TEJ), resistance (Bengal, TRJ), avoidance by osmotic adjustment (Kaybonnet, TRJ; IRAT177, TRJ; N22, Aus; Vandana, Aus; and O Glabberrima, 316603). All rice genotypes were grown in greenhouse conditions (24 °C ± 3°C air temperature and ~ 600 μmol m-2 s-1 light intensity) with light/dark cycles of 10/14 h in water filled trays simulating flooded conditions. Measurements were conducted on fully grown plants (35 - 60 days old) under simulated flooded and drought conditions. Preliminary results have shown that the drought sensitive genotype, Nipponbare has the lowest photosynthetic carboxylation capacity (Vcmax) and a similar electron transport rate (Jmax) compared to the drought resistant genotype IRAT 177. Mitochondrial respiration (Rd) of all the genotypes were similar while quantum yield of the drought sensitive genotype was greater than that of the drought resistant genotypes. While both drought tolerant and drought sensitive rice genotypes have the same photosynthetic yield, from an irrigation perspective the former would require less 'drop per grain'. This has enormous economic and management implications on account of dwindling water resources across the world due to drought.

Chemical combination effects predict connectivity in biological systems

PubMed Central

Lehár, Joseph; Zimmermann, Grant R; Krueger, Andrew S; Molnar, Raymond A; Ledell, Jebediah T; Heilbut, Adrian M; Short, Glenn F; Giusti, Leanne C; Nolan, Garry P; Magid, Omar A; Lee, Margaret S; Borisy, Alexis A; Stockwell, Brent R; Keith, Curtis T

2007-01-01

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured. PMID:17332758

Study of the Gastroprotective Effect of Extracts and Semipurified Fractions of Chresta martii DC. and Identification of Its Principal Compounds

PubMed Central

Franco, E. S.; Mélo, M. E. B.; Jatobá, B. J. A.; Santana, A. L. B. D.; Silva, A. A. R.; Silva, T. G.; Nascimento, M. S.; Maia, M. B. S.

2015-01-01

Chresta martii (Asteraceae) is a species widely used by the population of the Xingu region of Sergipe, Brazil, in the form of a decoction (aerial parts) for the treatment of gastrointestinal diseases. The study aims to assess the gastroprotective activity of organic extracts and semipurified fractions and identify the principal compounds present in C. martii responsible for such activity. The organic extracts (cyclohexane: ECCm, ethyl acetate: EACm, and ethanol: EECm) were obtained from the dried aerial parts (500 g) of C. martii. For evaluation of the gastroprotective activity of extracts (50, 100, or 200 mg/kg; p.o.), male Swiss Webster mice (25–30 g) were used which had gastric ulcers induced by indomethacin (40 mg/kg, s.c.) or ethanol (0.2 mL/animal; p.o.). Among the extracts evaluated, EACm exhibited significant (P < 0.05) gastroprotective activity in the models used. The fractionation of EACm was performed in a silica gel column 60 eluted with the following compounds: [chloroform—F1 yield (10%)], [chloroform/ethyl acetate (1/1)—F2 yield (6%)], [ethyl acetate—F3 yield (8%)], and [ethyl/methanol acetate (1/1)—F4 yield (5%)]. Of the fractions described above, the F1 (25 mg/kg; p.o.) had greater gastroprotective activity (P < 0.05) than that displayed by ranitidine (80 mg/kg; p.o.) in the ethanol-induced ulcer model. The refractionation of F1 produced 23 subfractions and from these two yellow amorphous compounds were obtained by recrystallization, Rf: 0.46 and 0.31 (ethyl acetate : chloroform 5 : 5). The compounds isolated were characterized by nuclear magnetic resonance spectroscopy (1H-NMR and 13C-NMR) and identified as flavones: chrysoeriol (yield: 0.43%) and 3′,4′-dimethoxyluteolin (yield: 0.58%). Conclusion. Flavone 3′,4′-dimethoxyluteolin is the principal compound present in the species C. martii and is probably responsible for gastroprotective activity observed in this species. PMID:25866537

Study of the Gastroprotective Effect of Extracts and Semipurified Fractions of Chresta martii DC. and Identification of Its Principal Compounds.

PubMed

Franco, E S; Mélo, M E B; Jatobá, B J A; Santana, A L B D; Silva, A A R; Silva, T G; Nascimento, M S; Maia, M B S

2015-01-01

Chresta martii (Asteraceae) is a species widely used by the population of the Xingu region of Sergipe, Brazil, in the form of a decoction (aerial parts) for the treatment of gastrointestinal diseases. The study aims to assess the gastroprotective activity of organic extracts and semipurified fractions and identify the principal compounds present in C. martii responsible for such activity. The organic extracts (cyclohexane: ECCm, ethyl acetate: EACm, and ethanol: EECm) were obtained from the dried aerial parts (500 g) of C. martii. For evaluation of the gastroprotective activity of extracts (50, 100, or 200 mg/kg; p.o.), male Swiss Webster mice (25-30 g) were used which had gastric ulcers induced by indomethacin (40 mg/kg, s.c.) or ethanol (0.2 mL/animal; p.o.). Among the extracts evaluated, EACm exhibited significant (P < 0.05) gastroprotective activity in the models used. The fractionation of EACm was performed in a silica gel column 60 eluted with the following compounds: [chloroform-F1 yield (10%)], [chloroform/ethyl acetate (1/1)-F2 yield (6%)], [ethyl acetate-F3 yield (8%)], and [ethyl/methanol acetate (1/1)-F4 yield (5%)]. Of the fractions described above, the F1 (25 mg/kg; p.o.) had greater gastroprotective activity (P < 0.05) than that displayed by ranitidine (80 mg/kg; p.o.) in the ethanol-induced ulcer model. The refractionation of F1 produced 23 subfractions and from these two yellow amorphous compounds were obtained by recrystallization, Rf: 0.46 and 0.31 (ethyl acetate : chloroform 5 : 5). The compounds isolated were characterized by nuclear magnetic resonance spectroscopy ((1)H-NMR and (13)C-NMR) and identified as flavones: chrysoeriol (yield: 0.43%) and 3',4'-dimethoxyluteolin (yield: 0.58%). Conclusion. Flavone 3',4'-dimethoxyluteolin is the principal compound present in the species C. martii and is probably responsible for gastroprotective activity observed in this species.

Psychometric properties for the Balanced Inventory of Desirable Responding: dichotomous versus polytomous conventional and IRT scoring.

PubMed

Vispoel, Walter P; Kim, Han Yi

2014-09-01

[Correction Notice: An Erratum for this article was reported in Vol 26(3) of Psychological Assessment (see record 2014-16017-001). The mean, standard deviation and alpha coefficient originally reported in Table 1 should be 74.317, 10.214 and .802, respectively. The validity coefficients in the last column of Table 4 are affected as well. Correcting this error did not change the substantive interpretations of the results, but did increase the mean, standard deviation, alpha coefficient, and validity coefficients reported for the Honesty subscale in the text and in Tables 1 and 4. The corrected versions of Tables 1 and Table 4 are shown in the erratum.] Item response theory (IRT) models were applied to dichotomous and polytomous scoring of the Self-Deceptive Enhancement and Impression Management subscales of the Balanced Inventory of Desirable Responding (Paulhus, 1991, 1999). Two dichotomous scoring methods reflecting exaggerated endorsement and exaggerated denial of socially desirable behaviors were examined. The 1- and 2-parameter logistic models (1PLM, 2PLM, respectively) were applied to dichotomous responses, and the partial credit model (PCM) and graded response model (GRM) were applied to polytomous responses. For both subscales, the 2PLM fit dichotomous responses better than did the 1PLM, and the GRM fit polytomous responses better than did the PCM. Polytomous GRM and raw scores for both subscales yielded higher test-retest and convergent validity coefficients than did PCM, 1PLM, 2PLM, and dichotomous raw scores. Information plots showed that the GRM provided consistently high measurement precision that was superior to that of all other IRT models over the full range of both construct continuums. Dichotomous scores reflecting exaggerated endorsement of socially desirable behaviors provided noticeably weak precision at low levels of the construct continuums, calling into question the use of such scores for detecting instances of "faking bad." Dichotomous models reflecting exaggerated denial of the same behaviors yielded much better precision at low levels of the constructs, but it was still less precision than that of the GRM. These results support polytomous over dichotomous scoring in general, alternative dichotomous scoring for detecting faking bad, and extension of GRM scoring to situations in which IRT offers additional practical advantages over classical test theory (adaptive testing, equating, linking, scaling, detecting differential item functioning, and so forth). PsycINFO Database Record (c) 2014 APA, all rights reserved.

Individual and culture-level components of survey response styles: A multi-level analysis using cultural models of selfhood.

PubMed

Smith, Peter B; Vignoles, Vivian L; Becker, Maja; Owe, Ellinor; Easterbrook, Matthew J; Brown, Rupert; Bourguignon, David; Garðarsdóttir, Ragna B; Kreuzbauer, Robert; Cendales Ayala, Boris; Yuki, Masaki; Zhang, Jianxin; Lv, Shaobo; Chobthamkit, Phatthanakit; Jaafar, Jas Laile; Fischer, Ronald; Milfont, Taciano L; Gavreliuc, Alin; Baguma, Peter; Bond, Michael Harris; Martin, Mariana; Gausel, Nicolay; Schwartz, Seth J; Des Rosiers, Sabrina E; Tatarko, Alexander; González, Roberto; Didier, Nicolas; Carrasco, Diego; Lay, Siugmin; Nizharadze, George; Torres, Ana; Camino, Leoncio; Abuhamdeh, Sami; Macapagal, Ma Elizabeth J; Koller, Silvia H; Herman, Ginette; Courtois, Marie; Fritsche, Immo; Espinosa, Agustín; Villamar, Juan A; Regalia, Camillo; Manzi, Claudia; Brambilla, Maria; Zinkeng, Martina; Jalal, Baland; Kusdil, Ersin; Amponsah, Benjamin; Çağlar, Selinay; Mekonnen, Kassahun Habtamu; Möller, Bettina; Zhang, Xiao; Schweiger Gallo, Inge; Prieto Gil, Paula; Lorente Clemares, Raquel; Campara, Gabriella; Aldhafri, Said; Fülöp, Márta; Pyszczynski, Tom; Kesebir, Pelin; Harb, Charles

2016-12-01

Variations in acquiescence and extremity pose substantial threats to the validity of cross-cultural research that relies on survey methods. Individual and cultural correlates of response styles when using 2 contrasting types of response mode were investigated, drawing on data from 55 cultural groups across 33 nations. Using 7 dimensions of self-other relatedness that have often been confounded within the broader distinction between independence and interdependence, our analysis yields more specific understandings of both individual- and culture-level variations in response style. When using a Likert-scale response format, acquiescence is strongest among individuals seeing themselves as similar to others, and where cultural models of selfhood favour harmony, similarity with others and receptiveness to influence. However, when using Schwartz's (2007) portrait-comparison response procedure, acquiescence is strongest among individuals seeing themselves as self-reliant but also connected to others, and where cultural models of selfhood favour self-reliance and self-consistency. Extreme responding varies less between the two types of response modes, and is most prevalent among individuals seeing themselves as self-reliant, and in cultures favouring self-reliance. As both types of response mode elicit distinctive styles of response, it remains important to estimate and control for style effects to ensure valid comparisons. © 2016 International Union of Psychological Science.

Modelling the structural response of cotton plants to mepiquat chloride and population density

PubMed Central

Gu, Shenghao; Evers, Jochem B.; Zhang, Lizhen; Mao, Lili; Zhang, Siping; Zhao, Xinhua; Liu, Shaodong; van der Werf, Wopke; Li, Zhaohu

2014-01-01

Background and Aims Cotton (Gossypium hirsutum) has indeterminate growth. The growth regulator mepiquat chloride (MC) is used worldwide to restrict vegetative growth and promote boll formation and yield. The effects of MC are modulated by complex interactions with growing conditions (nutrients, weather) and plant population density, and as a result the effects on plant form are not fully understood and are difficult to predict. The use of MC is thus hard to optimize. Methods To explore crop responses to plant density and MC, a functional–structural plant model (FSPM) for cotton (named CottonXL) was designed. The model was calibrated using 1 year's field data, and validated by using two additional years of detailed experimental data on the effects of MC and plant density in stands of pure cotton and in intercrops of cotton with wheat. CottonXL simulates development of leaf and fruits (square, flower and boll), plant height and branching. Crop development is driven by thermal time, population density, MC application, and topping of the main stem and branches. Key Results Validation of the model showed good correspondence between simulated and observed values for leaf area index with an overall root-mean-square error of 0·50 m2 m−2, and with an overall prediction error of less than 10 % for number of bolls, plant height, number of fruit branches and number of phytomers. Canopy structure became more compact with the decrease of leaf area index and internode length due to the application of MC. Moreover, MC did not have a substantial effect on boll density but increased lint yield at higher densities. Conclusions The model satisfactorily represents the effects of agronomic measures on cotton plant structure. It can be used to identify optimal agronomic management of cotton to achieve optimal plant structure for maximum yield under varying environmental conditions. PMID:24489020

Structural evolution of Colloidal Gels under Flow

NASA Astrophysics Data System (ADS)

Boromand, Arman; Maia, Joao; Jamali, Safa

Colloidal suspensions are ubiquitous in different industrial applications ranging from cosmetic and food industries to soft robotics and aerospace. Owing to the fact that mechanical properties of colloidal gels are controlled by its microstructure and network topology, we trace the particles in the networks formed under different attraction potentials and try to find a universal behavior in yielding of colloidal gels. Many authors have implemented different simulation techniques such as molecular dynamics (MD) and Brownian dynamics (BD) to capture better picture during phase separation and yielding mechanism in colloidal system with short-ranged attractive force. However, BD neglects multi-body hydrodynamic interactions (HI) which are believed to be responsible for the second yielding of colloidal gels. We envision using dissipative particle dynamics (DPD) with modified depletion potential and hydrodynamic interactions, as a coarse-grain model, can provide a robust simulation package to address the gel formation process and yielding in short ranged-attractive colloidal systems. The behavior of colloidal gels with different attraction potentials under flow is examined and structural fingerprints of yielding in these systems will be discussed.

Accelerating yield ramp through design and manufacturing collaboration

NASA Astrophysics Data System (ADS)

Sarma, Robin C.; Dai, Huixiong; Smayling, Michael C.; Duane, Michael P.

2004-12-01

Ramping an integrated circuit from first silicon bring-up to production yield levels is a challenge for all semiconductor products on the path to profitable market entry. Two approaches to accelerating yield ramp are presented. The first is the use of laser mask writers for fast throughput, high yield, and cost effective pattern transfer. The second is the use of electrical test to find a defect and identify the physical region to probe in failure analysis that is most likely to uncover the root cause. This provides feedback to the design team on modifications to make to the design to avoid the yield issue in a future tape-out revision. Additionally, the process parameter responsible for the root cause of the defect is forward annotated through the design, mask and wafer coordinate systems so it can be monitored in-line on subsequent lots of the manufacturing run. This results in an improved recipe for the manufacturing equipment to potentially prevent the recurrence of the defect and raise yield levels on the following material. The test diagnostics approach is enabled by the seamless traceability of a feature across the design, photomask and wafer, made possible by a common data model for design, mask pattern generation and wafer fabrication.

The separation distance distribution in electron-donor-acceptor systems and the wavelength dependence of free ion yields

NASA Astrophysics Data System (ADS)

Zhou, Jinwei; Findley, Bret R.; Braun, Charles L.; Sutin, Norman

2001-06-01

We recently reported that free radical ion quantum yields for electron-donor-acceptor (EDA) systems of alkylbenzenes-tetracyanoethylene (TCNE) exhibit a remarkable wavelength dependence in dichloromethane, a medium polarity solvent. We proposed that weak absorption by long-distance, unassociated or "random" D⋯A pairs is mainly responsible for the free radical ion yield. Here a model for the wavelength dependence of the free ion yield is developed for four systems in which differing degrees of EDA complex formation are present: 1,3,5-tri-tert-butylbenzene-TCNE in which only random pairs exist due to the bulky groups on the electron donor, and toluene—TCNE, 1,3,5-triethylbenzene-TCNE and 1,3,5-trimethylbenzene-TCNE. Mulliken-Hush theory is used to determine the excitation distance distribution of unassociated, random pairs at different wavelengths. For each absorption distribution, free radical ion yields at different wavelengths are then calculated using Onsager's result for the ion separation probability. Encouraging agreement between the calculated yields and our experimental results is obtained. As far as we are aware, this is the first time that photoexcitation of unassociated donor/acceptor pairs has been invoked as the source of separated radical ion pairs.

Measuring the Cognitions, Emotions, and Motivation Associated With Avoidance Behaviors in the Context of Pain: Preliminary Development of the Negative Responsivity to Pain Scales.

PubMed

Jensen, Mark P; Ward, L Charles; Thorn, Beverly E; Ehde, Dawn M; Day, Melissa A

2017-04-01

We recently proposed a Behavioral Inhibition System-Behavioral Activation System (BIS-BAS) model to help explain the effects of pain treatments. In this model, treatments are hypothesized to operate primarily through their effects on the domains within 2 distinct neurophysiological systems that underlie approach (BAS) and avoidance (BIS) behaviors. Measures of the model's domains are needed to evaluate and modify the model. An item pool of negative responses to pain (NRP; hypothesized to be BIS related) and positive responses (PR; hypothesized to be BAS related) were administered to 395 undergraduates, 325 of whom endorsed recurrent pain. The items were administered to 176 of these individuals again 1 week later. Analyses were conducted to develop and validate scales assessing NRP and PR domains. Three NRP scales (Despondent Response to Pain, Fear of Pain, and Avoidant Response to Pain) and 2 PR scales (Happy/Hopeful Responses and Approach Response) emerged. Consistent with the model, the scales formed 2 relatively independent overarching domains. The scales also demonstrated excellent internal consistency, and associations with criterion variables supported their validity. However, whereas the NRP scales evidenced adequate test-retest stability, the 2 PR scales were not adequately stable. The study yielded 3 brief scales assessing NRP, which may be used to further evaluate the BIS-BAS model and to advance research elucidating the mechanisms of psychosocial pain treatments. The findings also provide general support for the BIS-BAS model, while also suggesting that some minor modifications in the model are warranted.

Source parameters and effects of bandwidth and local geology on high- frequency ground motions observed for aftershocks of the northeastern Ohio earthquake of 31 January 1986

USGS Publications Warehouse

Glassmoyer, G.; Borcherdt, R.D.

1990-01-01

A 10-station array (GEOS) yielded recordings of exceptional bandwidth (400 sps) and resolution (up to 96 dB) for the aftershocks of the moderate (mb???4.9) earthquake that occurred on 31 January 1986 near Painesville, Ohio. Nine aftershocks were recorded with seismic moments ranging between 9 ?? 1016 and 3 ?? 1019 dyne-cm (MW: 0.6 to 2.3). The aftershock recordings at a site underlain by ???8m of lakeshore sediments show significant levels of high-frequency soil amplification of vertical motion at frequencies near 8, 20 and 70 Hz. Viscoelastic models for P and SV waves incident at the base of the sediments yield estimates of vertical P-wave response consistent with the observed high-frequency site resonances, but suggest additional detailed shear-wave logs are needed to account for observed S-wave response. -from Authors

Representation of high frequency Space Shuttle data by ARMA algorithms and random response spectra

NASA Technical Reports Server (NTRS)

Spanos, P. D.; Mushung, L. J.

1990-01-01

High frequency Space Shuttle lift-off data are treated by autoregressive (AR) and autoregressive-moving-average (ARMA) digital algorithms. These algorithms provide useful information on the spectral densities of the data. Further, they yield spectral models which lend themselves to incorporation to the concept of the random response spectrum. This concept yields a reasonably smooth power spectrum for the design of structural and mechanical systems when the available data bank is limited. Due to the non-stationarity of the lift-off event, the pertinent data are split into three slices. Each of the slices is associated with a rather distinguishable phase of the lift-off event, where stationarity can be expected. The presented results are rather preliminary in nature; it is aimed to call attention to the availability of the discussed digital algorithms and to the need to augment the Space Shuttle data bank as more flights are completed.

Bladder pain in an LL-37 interstitial cystitis and painful bladder syndrome model.

PubMed

Jia, Wanjian; Schults, Austin J; Jensen, Mark Martin; Ye, Xiangyang; Alt, Jeremiah A; Prestwich, Glenn D; Oottamasathien, Siam

2017-01-01

Our goal was to evaluate the pain response in an LL-37 induced murine model for interstitial cystitis/painful bladder syndrome (IC/PBS). In particular, we sought to characterize the dose dependence, time-course, and relationship of LL-37 induced bladder inflammation and pain. The IC/PBS model was induced in C57Bl/6 mice by instilling 50 μL of LL-37, an immunomodulatory human cathelicidin (anti-microbial peptide), in the bladder for 1 hr. Pain responses were measured using von Frey filaments (0.04 gm to 4.0 gm) before and after LL-37 instillation. Inflammation was evaluated using tissue myeloperoxidase (MPO) assay, gross inspection, and microscopic histologic examination. The dose response experiment demonstrated a graded pain response, with higher concentrations of LL-37 challenge yielding higher pain responses across all stimuli tested. Statistical significance was seen when comparing 1.0 gm von Frey filament results at 320 μM (68 ± 8% response) vs. 0 μM (38 ± 6% response). Interestingly, pain responses did not attenuate across time but increased significantly after 5 (p=0.0012) and 7 days (p=0.0096). Comparison with MPO data suggested that pain responses could be independent of inflammation. We demonstrated within our LL-37 induced IC/PBS model pain occurs in a dose-dependent fashion, pain responses persist beyond the initial point of insult, and our dose response and time course experiments demonstrated that pain was independent of inflammation.

CQESTR simulated response of soil organic carbon to management, yield, and climate change in northern Great Plains region

USDA-ARS?s Scientific Manuscript database

Traditional dryland crop management includes fallow and intensive tillage, which have reduced soil organic carbon (SOC) over the past century raising concerns regarding soil health and sustainability. The objectives of this study were to: 1) use CQESTR, a process-based C model, to simulate SOC dynam...

More grain per drop of water: Screening rice genotype for physiological parameters of drought tolerance

NASA Astrophysics Data System (ADS)

Massanelli, J.; Meadows-McDonnell, M.; Konzelman, C.; Moon, J. B.; Kumar, A.; Thomas, J.; Pereira, A.; Naithani, K. J.

2016-12-01

Meeting agricultural water demands is becoming progressively difficult due to population growth and changes in climate. Breeding stress-resilient crops is a viable solution, as information about genetic variation and their role in stress tolerance is becoming available due to advancement in technology. In this study we screened eight diverse rice genotypes for photosynthetic capacity under greenhouse conditions. These include the Asian rice (Oryza sativa) genotypes, drought sensitive Nipponbare, and a transgenic line overexpressing the HYR gene in Nipponbare; six genotypes (Vandana, Bengal, Nagina-22, Glaberrima, Kaybonnet, Ai Chueh Ta Pai Ku) and an African rice O. glaberrima, all selected for varying levels of drought tolerance. We collected CO2 and light response curve data under well-watered and simulated drought conditions in greenhouse. From these curves we estimated photosynthesis model parameters, such as the maximum carboxylation rate (Vcmax), the maximum electron transport rate (Jmax), the maximum gross photosynthesis rate, daytime respiration (Rd), and quantum yield (f). Our results suggest that O. glaberrima and Nipponbare were the most sensitive to drought because Vcmax and Pgmax declined under drought conditions; other drought tolerant genotypes did not show significant changes in these model parameters. Our integrated approach, combining genetic information and photosynthesis modeling, shows promise to quantify drought response parameters and improve crop yield under drought stress conditions.

Properties of model-averaged BMDLs: a study of model averaging in dichotomous response risk estimation.

PubMed

Wheeler, Matthew W; Bailer, A John

2007-06-01

Model averaging (MA) has been proposed as a method of accounting for model uncertainty in benchmark dose (BMD) estimation. The technique has been used to average BMD dose estimates derived from dichotomous dose-response experiments, microbial dose-response experiments, as well as observational epidemiological studies. While MA is a promising tool for the risk assessor, a previous study suggested that the simple strategy of averaging individual models' BMD lower limits did not yield interval estimators that met nominal coverage levels in certain situations, and this performance was very sensitive to the underlying model space chosen. We present a different, more computationally intensive, approach in which the BMD is estimated using the average dose-response model and the corresponding benchmark dose lower bound (BMDL) is computed by bootstrapping. This method is illustrated with TiO(2) dose-response rat lung cancer data, and then systematically studied through an extensive Monte Carlo simulation. The results of this study suggest that the MA-BMD, estimated using this technique, performs better, in terms of bias and coverage, than the previous MA methodology. Further, the MA-BMDL achieves nominal coverage in most cases, and is superior to picking the "best fitting model" when estimating the benchmark dose. Although these results show utility of MA for benchmark dose risk estimation, they continue to highlight the importance of choosing an adequate model space as well as proper model fit diagnostics.

Linking MODFLOW with an agent-based land-use model to support decision making

USGS Publications Warehouse

Reeves, H.W.; Zellner, M.L.

2010-01-01

The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

Cortical dynamics of feature binding and reset: control of visual persistence.

PubMed

Francis, G; Grossberg, S; Mingolla, E

1994-04-01

An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing of visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greater persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence due to adaptation with a stimulus of like orientation, an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

A physiologically based nonhomogeneous Poisson counter model of visual identification.

PubMed

Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus; Kyllingsbæk, Søren

2018-04-30

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The potential for using canopy spectral reflectance as an indirect selection tool for yield improvement in winter wheat

NASA Astrophysics Data System (ADS)

Prasad, Bishwajit

Scope and methods of study. Complementing breeding effort by deploying alternative methods of identifying higher yielding genotypes in a wheat breeding program is important for obtaining greater genetic gains. Spectral reflectance indices (SRI) are one of the many indirect selection tools that have been reported to be associated with different physiological process of wheat. A total of five experiments (a set of 25 released cultivars from winter wheat breeding programs of the U.S. Great Plains and four populations of randomly derived recombinant inbred lines having 25 entries in each population) were conducted in two years under Great Plains winter wheat rainfed environments at Oklahoma State University research farms. Grain yield was measured in each experiment and biomass was measured in three experiments at three growth stages (booting, heading, and grainfilling). Canopy spectral reflectance was measured at three growth stages and eleven SRI were calculated. Correlation (phenotypic and genetic) between grain yield and SRI, biomass and SRI, heritability (broad sense) of the SRI and yield, response to selection and correlated response, relative selection efficiency of the SRI, and efficiency in selecting the higher yielding genotypes by the SRI were assessed. Findings and conclusions. The genetic correlation coefficients revealed that the water based near infrared indices (WI and NWI) were strongly associated with grain yield and biomass production. The regression analysis detected a linear relationship between the water based indices with grain yield and biomass. The two newly developed indices (NWI-3 and NWI-4) gave higher broad sense heritability than grain yield, higher direct response to selection compared to grain yield, correlated response equal to or higher than direct response for grain yield, relative selection efficiency greater than one, and higher efficiency in selecting higher yielding genotypes. Based on the overall genetic analysis required to establish any trait as an efficient indirect selection tool, the water based SRI (especially NWI-3 and NWI-4) have the potential to complement the classical breeding effort for selecting genotypes with higher yield potential in a winter wheat breeding program.

Thermo-electric transport in gauge/gravity models with momentum dissipation

NASA Astrophysics Data System (ADS)

Amoretti, Andrea; Braggio, Alessandro; Maggiore, Nicola; Magnoli, Nicodemo; Musso, Daniele

2014-09-01

We present a systematic definition and analysis of the thermo-electric linear response in gauge/gravity systems focusing especially on models with massive gravity in the bulk and therefore momentum dissipation in the dual field theory. A precise treatment of finite counter-terms proves to be essential to yield a consistent physical picture whose hydrodynamic and beyond-hydrodynamics behaviors noticeably match with field theoretical expectations. The model furnishes a possible gauge/gravity description of the crossover from the quantum-critical to the disorder-dominated Fermi-liquid behaviors, as expected in graphene.

An integrated utility-based model of conflict evaluation and resolution in the Stroop task.

PubMed

Chuderski, Adam; Smolen, Tomasz

2016-04-01

Cognitive control allows humans to direct and coordinate their thoughts and actions in a flexible way, in order to reach internal goals regardless of interference and distraction. The hallmark test used to examine cognitive control is the Stroop task, which elicits both the weakly learned but goal-relevant and the strongly learned but goal-irrelevant response tendencies, and requires people to follow the former while ignoring the latter. After reviewing the existing computational models of cognitive control in the Stroop task, its novel, integrated utility-based model is proposed. The model uses 3 crucial control mechanisms: response utility reinforcement learning, utility-based conflict evaluation using the Festinger formula for assessing the conflict level, and top-down adaptation of response utility in service of conflict resolution. Their complex, dynamic interaction led to replication of 18 experimental effects, being the largest data set explained to date by 1 Stroop model. The simulations cover the basic congruency effects (including the response latency distributions), performance dynamics and adaptation (including EEG indices of conflict), as well as the effects resulting from manipulations applied to stimulation and responding, which are yielded by the extant Stroop literature. (c) 2016 APA, all rights reserved).

Rooting traits of peanut genotypes with different yield response to terminal drought

USDA-ARS?s Scientific Manuscript database

Drought at pod filling and maturity stages can severely reduce yield of peanut. Better root systems can reduce yield loss from drought. The goal of this study was to investigate the responses to terminal drought of peanut genotypes for root dry weight and root length density. A field experiment was ...

Yield estimation of sugarcane based on agrometeorological-spectral models

NASA Technical Reports Server (NTRS)

Rudorff, Bernardo Friedrich Theodor; Batista, Getulio Teixeira

1990-01-01

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

Development of Phaleria macrocarpa (Scheff.) Boerl Fruits Using Response Surface Methodology Focused on Phenolics, Flavonoids and Antioxidant Properties.

PubMed

Mohamed Mahzir, Khurul Ain; Abd Gani, Siti Salwa; Hasanah Zaidan, Uswatun; Halmi, Mohd Izuan Effendi

2018-03-22

In this study, the optimal conditions for the extraction of antioxidants from the Buah Mahkota Dewa fruit ( Phaleria macrocarpa) was determined by using Response Surface Methodology (RSM). The optimisation was applied using a Central Composite Design (CCD) to investigate the effect of three independent variables, namely extraction temperature (°C), extraction time (minutes) and extraction solvent to-feed ratio (% v / v ) on four responses: free radical scavenging activity (DPPH), ferric ion reducing power assay (FRAP), total phenolic content (TPC) and total flavonoid content (TFC). The optimal conditions for the antioxidants extraction were found to be 64 °C extraction temperature, 66 min extraction time and 75% v / v solvent to-feed ratio giving the highest percentage yields of DPPH, FRAP, TPC and TFC of 86.85%, 7.47%, 292.86 mg/g and 3.22 mg/g, respectively. Moreover, the data were subjected to Response Surface Methodology (RSM) and the results showed that the polynomial equations for all models were significant, did not show lack of fit, and presented adjusted determination coefficients ( R ²) above 99%, proving that the yield of phenolic, flavonoid and antioxidants activities obtained experimentally were close to the predicted values and the suitability of the model employed in RSM to optimise the extraction conditions. Hence, in this study, the fruit from P. macrocarpa could be considered to have strong antioxidant ability and can be used in various cosmeceutical or medicinal applications.

Modeling the adequacy of dietary fiber in dairy cows based on the responses of ruminal pH and milk fat production to composition of the diet.

PubMed

Zebeli, Q; Dijkstra, J; Tafaj, M; Steingass, H; Ametaj, B N; Drochner, W

2008-05-01

The main objective of this study was to develop practical models to assess and predict the adequacy of dietary fiber in high-yielding dairy cows. We used quantitative methods to analyze relevant research data and critically evaluate and determine the responses of ruminal pH and production performance to different variables including physical, chemical, and starch-degrading characteristics of the diet. Further, extensive data were used to model the magnitude of ruminal pH fluctuations and determine the threshold for the development of subacute ruminal acidosis (SARA). Results of this study showed that to minimize the risk of SARA, the following events should be avoided: 1) a daily mean ruminal pH lower than 6.16, and 2) a time period in which ruminal pH is <5.8 for more than 5.24 h/d. As the content of physically effective neutral detergent fiber (peNDF) or the ratio between peNDF and rumen-degradable starch from grains in the diet increased up to 31.2 +/- 1.6% [dry matter (DM) basis] or 1.45 +/- 0.22, respectively, so did the daily mean ruminal pH, for which a asymptotic plateau was reached at a pH of 6.20 to 6.27. This study also showed that digestibility of fiber in the total tract depends on ruminal pH and outflow rate of digesta from reticulorumen; thereby both variables explained 62% of the variation of fiber digestibility. Feeding diets with peNDF content up to 31.9 +/- 1.97% (DM basis) slightly decreased DM intake and actual milk yield; however, 3.5% fat-corrected milk and milk fat yield were increased, resulting in greater milk energy efficiency. In conclusion, a level of about 30 to 33% peNDF in the diet may be considered generally optimal for minimizing the risk of SARA without impairing important production responses in high-yielding dairy cows. In terms of improvement of the accuracy to assessing dietary fiber adequacy, it is suggested that the content of peNDF required to stabilize ruminal pH and maintain milk fat content without compromising milk energy efficiency can be arranged based on grain or starch sources included in the diet, on feed intake level, and on days in milk of the cows.

Examining the Latent Class Structure of CO2 Hypersensitivity using Time Course Trajectories of Panic Response Systems

PubMed Central

Roberson-Nay, Roxann; Beadel, Jessica R.; Gorlin, Eugenia I.; Latendresse, Shawn J.; Teachman, Bethany A.

2014-01-01

Background and Objectives Carbon dioxide (CO2) hypersensitivity is hypothesized to be a robust endophenotypic marker of panic spectrum vulnerability. The goal of the current study was to explore the latent class trajectories of three primary response systems theoretically associated with CO2 hypersensitivity: subjective anxiety, panic symptoms, and respiratory rate (fR). Methods Participants (n=376; 56% female) underwent a maintained 7.5% CO2 breathing task that included three phases: baseline, CO2 air breathing, and recovery. Growth mixture modeling was used to compare response classes (1..n) to identify the best-fit model for each marker. Panic correlates also were examined to determine class differences in panic vulnerability. Results For subjective anxiety ratings, a three-class model was selected, with individuals in one class reporting an acute increase in anxiety during 7.5% CO2 breathing and a return to pre-CO2 levels during recovery. A second, smaller latent class was distinguished by elevated anxiety across all three phases. The third class reported low anxiety reported during room air, a mild increase in anxiety during 7.5% CO2 breathing, and a return to baseline during recovery. Latent class trajectories for fR yielded one class whereas panic symptom response yielded two classes. Limitations This study examined CO2 hypersensitivity in one of the largest samples to date, but did not ascertain a general population sample thereby limiting generalizability. Moreover, a true resting baseline measure of fR was not measured. Conclusions Two classes potentially representing different risk pathways were observed. Implications of results will be discussed in the context of panic risk research. PMID:25496936

Impact of Soil and Water Conservation Interventions on Watershed Runoff Response in a Tropical Humid Highland of Ethiopia.

PubMed

Sultan, Dagnenet; Tsunekawa, Atsushi; Haregeweyn, Nigussie; Adgo, Enyew; Tsubo, Mitsuru; Meshesha, Derege Tsegaye; Masunaga, Tsugiyuki; Aklog, Dagnachew; Fenta, Ayele Almaw; Ebabu, Kindiye

2018-05-01

Various soil and water conservation measures (SWC) have been widely implemented to reduce surface runoff in degraded and drought-prone watersheds. But little quantitative study has been done on to what extent such measures can reduce watershed-scale runoff, particularly from typical humid tropical highlands of Ethiopia. The overall goal of this study is to analyze the impact of SWC interventions on the runoff response by integrating field measurement with a hydrological CN model which gives a quantitative analysis future thought. Firstly, a paired-watershed approach was employed to quantify the relative difference in runoff response for the Kasiry (treated) and Akusty (untreated) watersheds. Secondly, a calibrated curve number hydrological modeling was applied to investigate the effect of various SWC management scenarios for the Kasiry watershed alone. The paired-watershed approach showed a distinct runoff response between the two watersheds however the effect of SWC measures was not clearly discerned being masked by other factors. On the other hand, the model predicts that, under the current SWC coverage at Kasiry, the seasonal runoff yield is being reduced by 5.2%. However, runoff yields from Kasiry watershed could be decreased by as much as 34% if soil bunds were installed on cultivated land and trenches were installed on grazing and plantation lands. In contrast, implementation of SWC measures on bush land and natural forest would have little effect on reducing runoff. The results on the magnitude of runoff reduction under optimal combinations of SWC measures and land use will support decision-makers in selection and promotion of valid management practices that are suited to particular biophysical niches in the tropical humid highlands of Ethiopia.

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

USGS Publications Warehouse

Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.

2012-01-01

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications.

PubMed

Silvestro, Paolo Cosmo; Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio; Casa, Raffaele

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PubMed Central

Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations. PMID:29107963

Production responses of Holstein dairy cows when fed supplemental fat containing saturated free fatty acids: a meta-analysis

PubMed Central

Hu, Wenping; Boerman, Jacquelyn P.; Aldrich, James M.

2017-01-01

Objective A meta-analysis was conducted to evaluate the effects of supplemental fat containing saturated free fatty acids (FA) on milk performance of Holstein dairy cows. Methods A database was developed from 21 studies published between 1991 and 2016 that included 502 dairy cows and a total of 29 to 30 comparisons between dietary treatment and control without fat supplementation. Only saturated free FA (>80% of total FA) was considered as the supplemental fat. Concentration of the supplemental fat was not higher than 3.5% of diet dry matter (DM). Dairy cows were offered total mixed ration, and fed individually. Statistical analysis was conducted using random- or mixed-effects models with Metafor package in R. Results Sub-group analysis showed that there were no differences in studies between randomized block design and Latin square/crossover design for dry matter intake (DMI) and milk production responses to the supplemental fat (all response variables, p≥0.344). The supplemental fat across all studies improved milk yield, milk fat concentration and yield, and milk protein yield by 1.684 kg/d (p<0.001), 0.095 percent unit (p = 0.003), 0.072 kg/d (p<0.001), and 0.036 kg/d (p<0.001), respectively, but tended to decrease milk protein concentration (mean difference = −0.022 percent unit; p = 0.063) while DMI (mean difference = 0.061 kg/d; p = 0.768) remained unchanged. The assessment of heterogeneity suggested that no substantial heterogeneity occurred among all studies for DMI and milk production responses to the supplemental fat (all response variables, I2≤24.1%; p≥0.166). Conclusion The effects of saturated free FA were quantitatively evaluated. Higher milk production and yields of milk fat and protein, with DMI remaining unchanged, indicated that saturated free FA, supplemented at ≤3.5% dietary DM from commercially available fat sources, likely improved the efficiency of milk production. Nevertheless, more studies are needed to assess the variation of production responses to different saturated free FA, either C16:0 or C18:0 alone, or in combination with potentially optimal ratio, when supplemented in dairy cow diets. PMID:28183166

A triangular climate-based decision model to forecast crop anomalies in Kenya

NASA Astrophysics Data System (ADS)

Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

2017-12-01

By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

Modeling and control study of the NASA 0.3-meter transonic cryogenic tunnel for use with sulfur hexafluoride medium

NASA Technical Reports Server (NTRS)

Balakrishna, S.; Kilgore, W. Allen

1992-01-01

The NASA Langley 0.3-m Transonic Cryogenic Tunnel is to be modified to operate with sulfur hexafluoride gas while retaining its present capability to operate with nitrogen. The modified tunnel will provide high Reynolds number flow on aerodynamic models with two different test gases. The document details a study of the SF6 tunnel performance boundaries, thermodynamic modeling of the tunnel process, nonlinear dynamical simulation of math model to yield tunnel responses, the closed loop control requirements, control laws, and mechanization of the control laws on the microprocessor based controller.

Brassinosteroid and gibberellin control of seedling traits in maize (Zea mays L.).

PubMed

Hu, Songlin; Sanchez, Darlene L; Wang, Cuiling; Lipka, Alexander E; Yin, Yanhai; Gardner, Candice A C; Lübberstedt, Thomas

2017-10-01

In this study, we established two doubled haploid (DH) libraries with a total of 207 DH lines. We applied BR and GA inhibitors to all DH lines at seedling stage and measured seedling BR and GA inhibitor responses. Moreover, we evaluated field traits for each DH line (untreated). We conducted genome-wide association studies (GWAS) with 62,049 genome wide SNPs to explore the genetic control of seedling traits by BR and GA. In addition, we correlate seedling stage hormone inhibitor response with field traits. Large variation for BR and GA inhibitor response and field traits was observed across these DH lines. Seedling stage BR and GA inhibitor response was significantly correlate with yield and flowering time. Using three different GWAS approaches to balance false positive/negatives, multiple SNPs were discovered to be significantly associated with BR/GA inhibitor responses with some localized within gene models. SNPs from gene model GRMZM2G013391 were associated with GA inhibitor response across all three GWAS models. This gene is expressed in roots and shoots and was shown to regulate GA signaling. These results show that BRs and GAs have a great impact for controlling seedling growth. Gene models from GWAS results could be targets for seeding traits improvement. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental and numerical characterisation of the elasto-plastic properties of bovine trabecular bone and a trabecular bone analogue.

PubMed

Kelly, Nicola; McGarry, J Patrick

2012-05-01

The inelastic pressure dependent compressive behaviour of bovine trabecular bone is investigated through experimental and computational analysis. Two loading configurations are implemented, uniaxial and confined compression, providing two distinct loading paths in the von Mises-pressure stress plane. Experimental results reveal distinctive yielding followed by a constant nominal stress plateau for both uniaxial and confined compression. Computational simulation of the experimental tests using the Drucker-Prager and Mohr-Coulomb plasticity models fails to capture the confined compression behaviour of trabecular bone. The high pressure developed during confined compression does not result in plastic deformation using these formulations, and a near elastic response is computed. In contrast, the crushable foam plasticity models provide accurate simulation of the confined compression tests, with distinctive yield and plateau behaviour being predicted. The elliptical yield surfaces of the crushable foam formulations in the von Mises-pressure stress plane accurately characterise the plastic behaviour of trabecular bone. Results reveal that the hydrostatic yield stress is equal to the uniaxial yield stress for trabecular bone, demonstrating the importance of accurate characterisation and simulation of the pressure dependent plasticity. It is also demonstrated in this study that a commercially available trabecular bone analogue material, cellular rigid polyurethane foam, exhibits similar pressure dependent yield behaviour, despite having a lower stiffness and strength than trabecular bone. This study provides a novel insight into the pressure dependent yield behaviour of trabecular bone, demonstrating the inadequacy of uniaxial testing alone. For the first time, crushable foam plasticity formulations are implemented for trabecular bone. The enhanced understanding of the inelastic behaviour of trabecular bone established in this study will allow for more realistic simulation of orthopaedic device implantation and failure. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling in Real Time During the Ebola Response.

PubMed

Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L

2016-07-08

To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence

NASA Technical Reports Server (NTRS)

Mark, W. D.

1981-01-01

A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.

Heterogeneous benefits of precision nitrogen management over the Midwestern US: evidence from 1,000 fields derived by satellite imagery and crop modeling

NASA Astrophysics Data System (ADS)

Jin, Z.; Archontoulis, S.; Lobell, D. B.

2017-12-01

The wise management of nitrogen (N) fertilizer is important for both economic and environmental considerations. The variable rate technology (VRT) that applies different rates of N fertilizer by fully taking account of the spatial heterogeneity within fields has gained popularity with the recent advent of high-resolution satellites and spectrometers, but its profitability is still uncertain given the dependence of corn-nitrogen responses to soil and climate. To our knowledge, the benefits of adopting VRT in the vast Midwestern US agricultural zones have only been assessed at a very limited number of fields based on labor-costing on-farm samplings. Here we present a study that integrates a range of geospatial tools and data to quantifying the economic benefit of VRT versus uniform N application over 1,000 randomly selected corn fields in the US Midwest. We employed the Google Earth Engine (GEE) and Landsat-5, 7 and 8 collections to derive 30m-resolution yield map for years 2007-2015, and used the multi-year averaged yields to characterize the yield variation and hence the management zones for each field and zone-specific yield goal. The yield goals as well as the Soil Survey Geographic Database (SSURGO) data were then used to calibrate the Agricultural Production Systems sIMulator (APSIM) model, which generated a range of variables such as yields, N balance and leaching. Our preliminary results showed that the calibrated APSIM model was able to capture about 60% of the variation in the satellite-based yield estimates, and more than 70% of the yield spread (i.e. maximum - minimum yield). Regardless of the overall environmental benefits of less N loss through leaching, the economic difference between adopting VRT and uniform application ranged from -50 to 200 per acre, with the majority lay between -10 and 40 per acre. Fields with a wider range of yield spread benefited more from adopting VRT, yet the conclusion varies upon weather, especially the precipitation. Our study confirmed that adopting VRT in the US Midwest was economically feasible under most cases, and highlighted the potential of using big-data platform to facilitate precision N management over a large scale. The methodology developed in this study can serve as a good foundation for other precision management applications over the world.

Implementation of DSC model and application for analysis of field pile tests under cyclic loading

NASA Astrophysics Data System (ADS)

Shao, Changming; Desai, Chandra S.

2000-05-01

The disturbed state concept (DSC) model, and a new and simplified procedure for unloading and reloading behavior are implemented in a nonlinear finite element procedure for dynamic analysis for coupled response of saturated porous materials. The DSC model is used to characterize the cyclic behavior of saturated clays and clay-steel interfaces. In the DSC, the relative intact (RI) behavior is characterized by using the hierarchical single surface (HISS) plasticity model; and the fully adjusted (FA) behavior is modeled by using the critical state concept. The DSC model is validated with respect to laboratory triaxial tests for clay and shear tests for clay-steel interfaces. The computer procedure is used to predict field behavior of an instrumented pile subjected to cyclic loading. The predictions provide very good correlation with the field data. They also yield improved results compared to those from a HISS model with anisotropic hardening, partly because the DSC model allows for degradation or softening and interface response.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

Detecting Structural Failures Via Acoustic Impulse Responses

NASA Technical Reports Server (NTRS)

Bayard, David S.; Joshi, Sanjay S.

1995-01-01

Advanced method of acoustic pulse reflectivity testing developed for use in determining sizes and locations of failures within structures. Used to detect breaks in electrical transmission lines, detect faults in optical fibers, and determine mechanical properties of materials. In method, structure vibrationally excited with acoustic pulse (a "ping") at one location and acoustic response measured at same or different location. Measured acoustic response digitized, then processed by finite-impulse-response (FIR) filtering algorithm unique to method and based on acoustic-wave-propagation and -reflection properties of structure. Offers several advantages: does not require training, does not require prior knowledge of mathematical model of acoustic response of structure, enables detection and localization of multiple failures, and yields data on extent of damage at each location.

Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lefantzi, Sophia; Ray, Jaideep; Arunajatesan, Srinivasan

2014-11-01

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of themore » calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C μ, C ε2 , C ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal values of the turbulence model parameters, was parametric uncertainty, which was rectified by calibration. Post-calibration, the dominant contribution to model inaccuraries are due to the structural errors in RANS.« less

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

Batch anaerobic digestion of synthetic military base food waste and cardboard mixtures.

PubMed

Asato, Caitlin M; Gonzalez-Estrella, Jorge; Jerke, Amber C; Bang, Sookie S; Stone, James J; Gilcrease, Patrick C

2016-09-01

Austere US military bases typically dispose of solid wastes, including large fractions of food waste (FW) and corrugated cardboard (CCB), by open dumping, landfilling, or burning. Anaerobic digestion (AD) offers an opportunity to reduce pollution and recover useful energy. This study aimed to evaluate the rates and yields of AD for FW-CCB mixtures. Batch AD was analyzed at substrate concentrations of 1-50g total chemical oxygen demand (COD)L(-1) using response surface methodology. At low concentrations, higher proportions of FW were correlated with faster specific methanogenic activities and greater final methane yields; however, concentrations of FW ⩾18.75gCODL(-1) caused inhibition. Digestion of mixtures with ⩾75% CCB occurred slowly but achieved methane yields >70%. Greater shifts in microbial communities were observed at higher substrate concentrations. Statistical models of methane yield and specific methanogenic activity indicated that FW and CCB exhibited no considerable interactions as substrates for AD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling of yield surface evolution in uniaxial and biaxial loading conditions using a prestrained large scale specimen

NASA Astrophysics Data System (ADS)

Zaman, Shakil Bin; Barlat, Frédéric; Kim, Jin Hwan

2018-05-01

Large-scale advanced high strength steel (AHSS) sheet specimens were deformed in uniaxial tension, using a novel grip system mounted on a MTS universal tension machine. After pre-strain, they were used as a pre-strained material to examine the anisotropic response in the biaxial tension tests with various load ratios, and orthogonal tension tests at 45° and 90° from the pre-strain axis. The flow curve and the instantaneous r-value of the pre-strained steel in each of the aforementioned uniaxial testing conditions were also measured and compared with those of the undeformed steel. Furthermore, an exhaustive analysis of the yield surface was also conducted and the results, prior and post-prestrain were represented and compared. The homogeneous anisotropic hardening (HAH) model [1] was employed to predict the behavior of the pre-strained material. It was found that the HAH-predicted flow curves after non-linear strain path change and the yield loci after uniaxial pre-strain were in good agreement with the experiments, while the r-value evolution after strain path change was qualitatively well predicted.

Spectral behavior of wheat yield variety trials

NASA Technical Reports Server (NTRS)

Hatfield, J. L.

1981-01-01

Little variation between varieties is seen at jointing, but the variability is found to increase during grain filling and decline again at maturity. No relationship is found between spectral response and yield, and when yields are segregated into various classes the spectral response is the same. Spring and winter nurseries are found to separate during the reproductive stage because of differences in dates of heading and maturity, but they exhibit similar spectral responses. The transformed normalized difference is at a minimum after the maximum grain weight occurs and the leaves begin to brown and fall off. These data of 100% ground cover demonstrate that it is not possible to predict grain yield from only spectral data. This, however, may not apply when reduced yields are caused by less-than-full ground cover

Corrigendum to “High-fidelity micro-scale modeling of the thermo-visco-plastic behavior of carbon fiber polymer matrix composites” [Compos Struct 134 (2015) 132–141

DOE PAGES

Bai, Xiaoming; Bessa, Miguel A.; Melro, Antonio R.; ...

2016-10-01

The authors would like to inform that one of the modifications proposed in the article “High-fidelity micro-scale modeling of the thermo-visco-plastic behavior of carbon fiber polymer matrix composites” [1] was found to be unnecessary: the paraboloid yield criterion is sufficient to describe the shear behavior of the epoxy matrix considered (Epoxy 3501-6). The authors recently noted that the experimental work [2] used to validate the pure matrix response considered engineering shear strain instead of its tensorial counter-part, which caused the apparent inconsistency with the paraboloid yield criterion. A recently proposed temperature dependency law for glassy polymers is evaluated herein, thusmore » better agreement with the experimental results for this epoxy is observed.« less

Corrigendum to “High-fidelity micro-scale modeling of the thermo-visco-plastic behavior of carbon fiber polymer matrix composites” [Compos Struct 134 (2015) 132–141

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bai, Xiaoming; Bessa, Miguel A.; Melro, Antonio R.

The authors would like to inform that one of the modifications proposed in the article “High-fidelity micro-scale modeling of the thermo-visco-plastic behavior of carbon fiber polymer matrix composites” [1] was found to be unnecessary: the paraboloid yield criterion is sufficient to describe the shear behavior of the epoxy matrix considered (Epoxy 3501-6). The authors recently noted that the experimental work [2] used to validate the pure matrix response considered engineering shear strain instead of its tensorial counter-part, which caused the apparent inconsistency with the paraboloid yield criterion. A recently proposed temperature dependency law for glassy polymers is evaluated herein, thusmore » better agreement with the experimental results for this epoxy is observed.« less

Kinetic operational models of agonism for G-protein-coupled receptors.

PubMed

Hoare, Samuel R J; Pierre, Nicolas; Moya, Arturo Gonzalez; Larson, Brad

2018-06-07

The application of kinetics to research and therapeutic development of G-protein-coupled receptors has become increasingly valuable. Pharmacological models provide the foundation of pharmacology, providing concepts and measurable parameters such as efficacy and potency that have underlain decades of successful drug discovery. Currently there are few pharmacological models that incorporate kinetic activity in such a way as to yield experimentally-accessible drug parameters. In this study, a kinetic model of pharmacological response was developed that provides a kinetic descriptor of efficacy (the transduction rate constant, k τ ) and allows measurement of receptor-ligand binding kinetics from functional data. The model assumes: (1) receptor interacts with a precursor of the response ("Transduction potential") and converts it to the response. (2) The response can decay. Familiar response vs time plots emerge, depending on whether transduction potential is depleted and/or response decays. These are the straight line, the "association" exponential curve, and the rise-and-fall curve. Convenient, familiar methods are described for measuring the model parameters and files are provided for the curve-fitting program Prism (GraphPad Software) that can be used as a guide. The efficacy parameter k τ is straightforward to measure and accounts for receptor reserve; all that is required is measurement of response over time at a maximally-stimulating concentration of agonist. The modular nature of the model framework allows it to be extended. Here this is done to incorporate antagonist-receptor binding kinetics and slow agonist-receptor equilibration. In principle, the modular framework can incorporate other cellular processes, such as receptor desensitization. The kinetic response model described here can be applied to measure kinetic pharmacological parameters than can be used to advance the understanding of GPCR pharmacology and optimize new and improved therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Design of experiments utilization to map the processing capabilities of a micro-spray dryer: particle design and throughput optimization in support of drug discovery.

PubMed

Ormes, James D; Zhang, Dan; Chen, Alex M; Hou, Shirley; Krueger, Davida; Nelson, Todd; Templeton, Allen

2013-02-01

There has been a growing interest in amorphous solid dispersions for bioavailability enhancement in drug discovery. Spray drying, as shown in this study, is well suited to produce prototype amorphous dispersions in the Candidate Selection stage where drug supply is limited. This investigation mapped the processing window of a micro-spray dryer to achieve desired particle characteristics and optimize throughput/yield. Effects of processing variables on the properties of hypromellose acetate succinate were evaluated by a fractional factorial design of experiments. Parameters studied include solid loading, atomization, nozzle size, and spray rate. Response variables include particle size, morphology and yield. Unlike most other commercial small-scale spray dryers, the ProCepT was capable of producing particles with a relatively wide mean particle size, ca. 2-35 µm, allowing material properties to be tailored to support various applications. In addition, an optimized throughput of 35 g/hour with a yield of 75-95% was achieved, which affords to support studies from Lead-identification/Lead-optimization to early safety studies. A regression model was constructed to quantify the relationship between processing parameters and the response variables. The response surface curves provide a useful tool to design processing conditions, leading to a reduction in development time and drug usage to support drug discovery.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

The Thermoluminescence Response of Ge-Doped Flat Fibers to Gamma Radiation

PubMed Central

Mat Nawi, Siti Nurasiah Binti; Wahib, Nor Fadira Binti; Zulkepely, Nurul Najua Binti; Amin, Yusoff Bin Mohd; Min, Ung Ngie; Bradley, David Andrew; Md Nor, Roslan Bin; Maah, Mohd Jamil

2015-01-01

Study has been undertaken of the thermoluminescence (TL) yield of various tailor-made flat cross-section 6 mol% Ge-doped silica fibers, differing only in respect of external dimensions. Key TL dosimetric characteristics have been investigated, including glow curves, dose response, sensitivity, fading and reproducibility. Using a 60Co source, the samples were irradiated to doses within the range 1 to 10 Gy. Prior to irradiation, the flat fibers were sectioned into 6 mm lengths, weighed, and annealed at 400 °C for 1 h. TL readout was by means of a Harshaw Model 3500 TLD reader, with TLD-100 chips (LiF:Mg, Ti) used as a reference dosimeter to allow the relative response of the fibers to be evaluated. The fibers have been found to provide highly linear dose response and excellent reproducibility over the range of doses investigated, demonstrating high potential as TL-mode detectors in radiation medicine applications. Mass for mass, the results show the greatest TL yield to be provided by fibers of the smallest cross-section, analysis indicating this to be due to minimal light loss in transport of the TL through the bulk of the silica medium. PMID:26307987

Solar Signals in CMIP-5 Simulations: The Stratospheric Pathway

NASA Technical Reports Server (NTRS)

Mitchell, D.M.; Misios, S.; Gray, L. J.; Tourpali, K.; Matthes, K.; Hood, L.; Schmidt, H.; Chiodo, G.; Thieblemont, R.; Rozanov, E.;

An economic assessment of the health effects and crop yield losses caused by air pollution in mainland China.

PubMed

Miao, Weijie; Huang, Xin; Song, Yu

2017-06-01

Air pollution is severe in China, and pollutants such as PM 2.5 and surface O 3 may cause major damage to human health and crops, respectively. Few studies have considered the health effects of PM 2.5 or the loss of crop yields due to surface O 3 using model-simulated air pollution data in China. We used gridded outputs from the WRF-Chem model, high resolution population data, and crop yield data to evaluate the effects on human health and crop yield in mainland China. Our results showed that outdoor PM 2.5 pollution was responsible for 1.70-1.99 million cases of all-cause mortality in 2006. The economic costs of these health effects were estimated to be 151.1-176.9 billion USD, of which 90% were attributed to mortality. The estimated crop yield losses for wheat, rice, maize, and soybean were approximately 9, 4.6, 0.44, and 0.34 million tons, respectively, resulting in economic losses of 3.4 billion USD. The total economic losses due to ambient air pollution were estimated to be 154.5-180.3 billion USD, accounting for approximately 5.7%-6.6% of the total GDP of China in 2006. Our results show that both population health and staple crop yields in China have been significantly affected by exposure to air pollution. Measures should be taken to reduce emissions, improve air quality, and mitigate the economic loss. Copyright © 2016. Published by Elsevier B.V.

Multimodel Surface Temperature Responses to Removal of U.S. Sulfur Dioxide Emissions

NASA Astrophysics Data System (ADS)

Conley, A. J.; Westervelt, D. M.; Lamarque, J.-F.; Fiore, A. M.; Shindell, D.; Correa, G.; Faluvegi, G.; Horowitz, L. W.

2018-03-01

Three Earth System models are used to derive surface temperature responses to removal of U.S. anthropogenic SO2 emissions. Using multicentury perturbation runs with and without U.S. anthropogenic SO2 emissions, the local and remote surface temperature changes are estimated. In spite of a temperature drift in the control and large internal variability, 200 year simulations yield statistically significant regional surface temperature responses to the removal of U.S. SO2 emissions. Both local and remote surface temperature changes occur in all models, and the patterns of changes are similar between models for northern hemisphere land regions. We find a global average temperature sensitivity to U.S. SO2 emissions of 0.0055 K per Tg(SO2) per year with a range of (0.0036, 0.0078). We examine global and regional responses in SO4 burdens, aerosol optical depths (AODs), and effective radiative forcing (ERF). While changes in AOD and ERF are concentrated near the source region (United States), the temperature response is spread over the northern hemisphere with amplification of the temperature increase toward the Arctic. In all models, we find a significant response of dust concentrations, which affects the AOD but has no obvious effect on surface temperature. Temperature sensitivity to the ERF of U.S. SO2 emissions is found to differ from the models' sensitivity to radiative forcing of doubled CO2.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research--past, present, and future.

PubMed

Rauch, Scott L; Shin, Lisa M; Phelps, Elizabeth A

2006-08-15

The prevailing neurocircuitry models of anxiety disorders have been amygdalocentric in form. The bases for such models have progressed from theoretical considerations, extrapolated from research in animals, to in vivo human imaging data. For example, one current model of posttraumatic stress disorder (PTSD) has been highly influenced by knowledge from rodent fear conditioning research. Given the phenomenological parallels between fear conditioning and the pathogenesis of PTSD, we have proposed that PTSD is characterized by exaggerated amygdala responses (subserving exaggerated acquisition of fear associations and expression of fear responses) and deficient frontal cortical function (mediating deficits in extinction and the capacity to suppress attention/response to trauma-related stimuli), as well as deficient hippocampal function (mediating deficits in appreciation of safe contexts and explicit learning/memory). Neuroimaging studies have yielded convergent findings in support of this model. However, to date, neuroimaging investigations of PTSD have not principally employed conditioning and extinction paradigms per se. The recent development of such imaging probes now sets the stage for directly testing hypotheses regarding the neural substrates of fear conditioning and extinction abnormalities in PTSD.

A model-based approach to investigating the pathophysiological mechanisms of hypertension and response to antihypertensive therapies: extending the Guyton model.

PubMed

Hallow, K Melissa; Lo, Arthur; Beh, Jeni; Rodrigo, Manoj; Ermakov, Sergey; Friedman, Stuart; de Leon, Hector; Sarkar, Anamika; Xiong, Yuan; Sarangapani, Ramesh; Schmidt, Henning; Webb, Randy; Kondic, Anna Georgieva

2014-05-01

Reproducibly differential responses to different classes of antihypertensive agents are observed among hypertensive patients and may be due to interindividual differences in hypertension pathology. Computational models provide a tool for investigating the impact of underlying disease mechanisms on the response to antihypertensive therapies with different mechanisms of action. We present the development, calibration, validation, and application of an extension of the Guyton/Karaaslan model of blood pressure regulation. The model incorporates a detailed submodel of the renin-angiotensin-aldosterone system (RAAS), allowing therapies that target different parts of this pathway to be distinguished. Literature data on RAAS biomarker and blood pressure responses to different classes of therapies were used to refine the physiological actions of ANG II and aldosterone on renin secretion, renal vascular resistance, and sodium reabsorption. The calibrated model was able to accurately reproduce the RAAS biomarker and blood pressure responses to combinations of dual-RAAS agents, as well as RAAS therapies in combination with diuretics or calcium channel blockers. The final model was used to explore the impact of underlying mechanisms of hypertension on the blood pressure response to different classes of antihypertensive agents. Simulations indicate that the underlying etiology of hypertension can impact the magnitude of response to a given class of therapy, making a patient more sensitive to one class and less sensitive others. Given that hypertension is usually the result of multiple mechanisms, rather than a single factor, these findings yield insight into why combination therapy is often required to adequately control blood pressure.

High fidelity computational characterization of the mechanical response of thermally aged polycarbonate

NASA Astrophysics Data System (ADS)

Zhang, Zesheng; Zhang, Lili; Jasa, John; Li, Wenlong; Gazonas, George; Negahban, Mehrdad

2017-07-01

A representative all-atom molecular dynamics (MD) system of polycarbonate (PC) is built and conditioned to capture and predict the behaviours of PC in response to a broad range of thermo-mechanical loadings for various thermal aging. The PC system is constructed to have a distribution of molecular weights comparable to a widely used commercial PC (LEXAN 9034), and thermally conditioned to produce models for aged and unaged PC. The MD responses of these models are evaluated through comparisons to existing experimental results carried out at much lower loading rates, but done over a broad range of temperatures and loading modes. These experiments include monotonic extension/compression/shear, unilaterally and bilaterally confined compression, and load-reversal during shear. It is shown that the MD simulations show both qualitative and quantitative similarity with the experimental response. The quantitative similarity is evaluated by comparing the dilatational response under bilaterally confined compression, the shear flow viscosity and the equivalent yield stress. The consistency of the in silico response to real laboratory experiments strongly suggests that the current PC models are physically and mechanically relevant and potentially can be used to investigate thermo-mechanical response to loading conditions that would not easily be possible. These MD models may provide valuable insight into the molecular sources of certain observations, and could possibly offer new perspectives on how to develop constitutive models that are based on better understanding the response of PC under complex loadings. To this latter end, the models are used to predict the response of PC to complex loading modes that would normally be difficult to do or that include characteristics that would be difficult to measure. These include the responses of unaged and aged PC to unilaterally confined extension/compression, cyclic uniaxial/shear loadings, and saw-tooth extension/compression/shear.

Yield model development project implementation plan

NASA Technical Reports Server (NTRS)

Ambroziak, R. A.

1982-01-01

Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.

Meta-analysis of free-response studies, 1992-2008: assessing the noise reduction model in parapsychology.

PubMed

Storm, Lance; Tressoldi, Patrizio E; Di Risio, Lorenzo

2010-07-01

We report the results of meta-analyses on 3 types of free-response study: (a) ganzfeld (a technique that enhances a communication anomaly referred to as "psi"); (b) nonganzfeld noise reduction using alleged psi-enhancing techniques such as dream psi, meditation, relaxation, or hypnosis; and (c) standard free response (nonganzfeld, no noise reduction). For the period 1997-2008, a homogeneous data set of 29 ganzfeld studies yielded a mean effect size of 0.142 (Stouffer Z = 5.48, p = 2.13 x 10(-8)). A homogeneous nonganzfeld noise reduction data set of 16 studies yielded a mean effect size of 0.110 (Stouffer Z = 3.35, p = 2.08 x 10(-4)), and a homogeneous data set of 14 standard free-response studies produced a weak negative mean effect size of -0.029 (Stouffer Z = -2.29, p = .989). The mean effect size value of the ganzfeld database was significantly higher than the mean effect size of the standard free-response database but was not higher than the effect size of the nonganzfeld noise reduction database [corrected].We also found that selected participants (believers in the paranormal, meditators, etc.) had a performance advantage over unselected participants, but only if they were in the ganzfeld condition.