Determining the Critical Dose Threshold of Electron-Induced Electron Yield for Minimally Charged Highly Insulating Materials

NASA Astrophysics Data System (ADS)

Hoffmann, Ryan; Dennison, J. R.; Abbott, Jonathan

2006-03-01

When incident energetic electrons interact with a material, they excite electrons within the material to escape energies. The electron emission is quantified as the ratio of emitted electrons to incident particle flux, termed electron yield. Measuring the electron yield of insulators is difficult due to dynamic surface charge accumulation which directly affects landing energies and the potential barrier that emitted electrons must overcome. Our recent measurements of highly insulating materials have demonstrated significant changes in total yield curves and yield decay curves for very small electron doses equivalent to a trapped charge density of <10^10 electrons /cm^3. The Chung-Everhart theory provides a basic model for the behavior of the electron emission spectra which we relate to yield decay curves as charge is allowed to accumulate. Yield measurements as a function of dose for polyimide (Kapton^TM) and microcrystalline SiO2 will be presented. We use our data and model to address the question of whether there is a minimal dose threshold at which the accumulated charge no longer affects the yield.

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

PubMed Central

Gary, Christian; Tixier, Philippe; Lechevallier, Esther

2017-01-01

The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production) and secondary yield losses (resulting from negative impacts of the previous year) of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013–2015) and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26%) and even higher secondary yield losses (38%). We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses. PMID:28046054

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

PubMed

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

2017-01-01

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

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

NASA Technical Reports Server (NTRS)

Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam;

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

PubMed

Bassu, Simona; Brisson, Nadine; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W; Rosenzweig, Cynthia; Ruane, Alex C; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; De Sanctis, Giacomo; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izaurralde, Cesar; Jongschaap, Raymond; Kemanian, Armen R; Kersebaum, K Christian; Kim, Soo-Hyung; Kumar, Naresh S; Makowski, David; Müller, Christoph; Nendel, Claas; Priesack, Eckart; Pravia, Maria Virginia; Sau, Federico; Shcherbak, Iurii; Tao, Fulu; Teixeira, Edmar; Timlin, Dennis; Waha, Katharina

2014-07-01

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 diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. © 2014 John Wiley & Sons Ltd.

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments.

PubMed

Boomer, Kathleen B; Weller, Donald E; Jordan, Thomas E

2008-01-01

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Estimating the Depth of the Navy Recruiting Market

DTIC Science & Technology

2016-09-01

recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. 14. SUBJECT...recommend that NRC make use of the Poisson regression model in order to determine high-yield ZIP codes for market depth. vi THIS PAGE INTENTIONALLY LEFT...DEPTH OF THE NAVY RECRUITING MARKET by Emilie M. Monaghan September 2016 Thesis Advisor: Lyn R. Whitaker Second Reader: Jonathan K. Alt

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.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress

PubMed Central

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C.

2014-01-01

Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Methods Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. Key Results To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait ‘total crop nitrogen uptake’ (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10–36 % more yield than those based on markers for yield per se. Conclusions This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. PMID:24984712

Assessing the influence of NOx concentrations and relative humidity on secondary organic aerosol yields from α-pinene photo-oxidation through smog chamber experiments and modelling calculations

NASA Astrophysics Data System (ADS)

Stirnweis, Lisa; Marcolli, Claudia; Dommen, Josef; Barmet, Peter; Frege, Carla; Platt, Stephen M.; Bruns, Emily A.; Krapf, Manuel; Slowik, Jay G.; Wolf, Robert; Prévôt, Andre S. H.; Baltensperger, Urs; El-Haddad, Imad

2017-04-01

Secondary organic aerosol (SOA) yields from the photo-oxidation of α-pinene were investigated in smog chamber (SC) experiments at low (23-29 %) and high (60-69 %) relative humidity (RH), various NOx / VOC ratios (0.04-3.8) and with different aerosol seed chemical compositions (acidic to neutralized sulfate-containing or hydrophobic organic). A combination of a scanning mobility particle sizer and an Aerodyne high-resolution time-of-flight aerosol mass spectrometer was used to determine SOA mass concentration and chemical composition. We used a Monte Carlo approach to parameterize smog chamber SOA yields as a function of the condensed phase absorptive mass, which includes the sum of OA and the corresponding bound liquid water content. High RH increased SOA yields by up to 6 times (1.5-6.4) compared to low RH. The yields at low NOx / VOC ratios were in general higher compared to yields at high NOx / VOC ratios. This NOx dependence follows the same trend as seen in previous studies for α-pinene SOA. A novel approach of data evaluation using volatility distributions derived from experimental data served as the basis for thermodynamic phase partitioning calculations of model mixtures in this study. These calculations predict liquid-liquid phase separation into organic-rich and electrolyte phases. At low NOx conditions, equilibrium partitioning between the gas and liquid phases can explain most of the increase in SOA yields observed at high RH, when in addition to the α-pinene photo-oxidation products described in the literature, fragmentation products are added to the model mixtures. This increase is driven by both the increase in the absorptive mass and the solution non-ideality described by the compounds' activity coefficients. In contrast, at high NOx, equilibrium partitioning alone could not explain the strong increase in the yields with RH. This suggests that other processes, e.g. reactive uptake of semi-volatile species into the liquid phase, may occur and be enhanced at higher RH, especially for compounds formed under high NOx conditions, e.g. carbonyls.

Yield of bedrock wells in the Nashoba terrane, central and eastern Massachusetts

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and hydrogeologic factors that were individually related to well yield, in ways that are consistent with conceptual understanding of their effects, but the models explained only 21 percent (regional model for the entire terrane) and 30 percent (quadrangle model) of the overall variance in yield. Moreover, most of the explained variance was due to well characteristics rather than hydrogeologic factors. Hydrogeologic factors such as topography and geology are likely important. However, the overall high variability in the well-yield data, which results from the high variability in aquifer hydraulic properties as well as from limitations of the dataset, would make it difficult to use hydrogeologic factors to predict well yield in the study area. Geostatistical analysis (variograms), on the other hand, indicated that, although highly variable, the well-yield data are spatially correlated. The spatial continuity appears greater in the northeast-southwest direction and less in the southeast-northwest direction, directions that are parallel and perpendicular, respectively, to the regional geologic structural trends. Geostatistical analysis (kriging), used to estimate yield values throughout the study area, identified regional-scale areas of higher and lower yield that may be related to regional structural features—in particular, to a northeast-southwest trending regional fault zone within the Nashoba terrane. It also would be difficult to use kriging to predict yield at specific locations, however, because of the spatial variability in yield, particularly at small scales. The regional-scale analyses in this study, both with hydrogeologic variables and geostatistics, provide a context for understanding the variability in well yield, rather a basis for precise predictions, and site-specific information would be needed to understand local conditions.

Optimizing Dense Plasma Focus Neutron Yields with Fast Gas Jets

NASA Astrophysics Data System (ADS)

McMahon, Matthew; Kueny, Christopher; Stein, Elizabeth; Link, Anthony; Schmidt, Andrea

2016-10-01

We report a study using the particle-in-cell code LSP to perform fully kinetic simulations modeling dense plasma focus (DPF) devices with high density gas jets on axis. The high density jet models fast gas puffs which allow for more mass on axis while maintaining the optimal pressure for the DPF. As the density of the jet compared to the background fill increases we find the neutron yield increases, as does the variability in the neutron yield. Introducing perturbations in the jet density allow for consistent seeding of the m =0 instability leading to more consistent ion acceleration and higher neutron yields with less variability. Jets with higher on axis density are found to have the greatest yield. The optimal jet configuration is explored. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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.

Enhanced Furfural Yields from Xylose Dehydration in the gamma-Valerolactone/Water Solvent System at Elevated Temperatures.

PubMed

Sener, Canan; Motagamwala, Ali Hussain; Alonso, David Martin; Dumesic, James

2018-05-18

High yields of furfural (>90%) were achieved from xylose dehydration in a sustainable solvent system composed of -valerolactone (GVL), a biomass derived solvent, and water. It is identified that high reaction temperatures (e.g., 498 K) are required to achieve high furfural yield. Additionally, it is shown that the furfural yield at these temperatures is independent of the initial xylose concentration, and high furfural yield is obtained for industrially relevant xylose concentrations (10 wt%). A reaction kinetics model is developed to describe the experimental data obtained with solvent system composed of 80 wt% GVL and 20 wt% water across the range of reaction conditions studied (473 - 523 K, 1-10 mM acid catalyst, 66 - 660 mM xylose concentration). The kinetic model demonstrates that furfural loss due to bimolecular condensation of xylose and furfural is minimized at elevated temperature, whereas carbon loss due to xylose degradation increases with increasing temperature. Accordingly, the optimal temperature range for xylose dehydration to furfural in the GVL/H2O solvent system is identified to be from 480 to 500 K. Under these reaction conditions, furfural yield of 93% is achieved at 97% xylan conversion from lignocellulosic biomass (maple wood). © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Standing wave design and experimental validation of a tandem simulated moving bed process for insulin purification.

PubMed

Xie, Yi; Mun, Sungyong; Kim, Jinhyun; Wang, Nien-Hwa Linda

2002-01-01

A tandem simulated moving bed (SMB) process for insulin purification has been proposed and validated experimentally. The mixture to be separated consists of insulin, high molecular weight proteins, and zinc chloride. A systematic approach based on the standing wave design, rate model simulations, and experiments was used to develop this multicomponent separation process. The standing wave design was applied to specify the SMB operating conditions of a lab-scale unit with 10 columns. The design was validated with rate model simulations prior to experiments. The experimental results show 99.9% purity and 99% yield, which closely agree with the model predictions and the standing wave design targets. The agreement proves that the standing wave design can ensure high purity and high yield for the tandem SMB process. Compared to a conventional batch SEC process, the tandem SMB has 10% higher yield, 400% higher throughput, and 72% lower eluant consumption. In contrast, a design that ignores the effects of mass transfer and nonideal flow cannot meet the purity requirement and gives less than 96% yield.

The yield and post-yield behavior of high-density polyethylene

NASA Technical Reports Server (NTRS)

Semeliss, M. A.; Wong, R.; Tuttle, M. E.

1990-01-01

An experimental and analytical evaluation was made of the yield and post-yield behavior of high-density polyethylene, a semi-crystalline thermoplastic. Polyethylene was selected for study because it is very inexpensive and readily available in the form of thin-walled tubes. Thin-walled tubular specimens were subjected to axial loads and internal pressures, such that the specimens were subjected to a known biaxial loading. A constant octahederal shear stress rate was imposed during all tests. The measured yield and post-yield behavior was compared with predictions based on both isotropic and anisotropic models. Of particular interest was whether inelastic behavior was sensitive to the hydrostatic stress level. The major achievements and conclusions reached are discussed.

Parsing multiple processes of high temperature impacts on corn/soybean yield using a newly developed CLM-APSIM modeling framework

NASA Astrophysics Data System (ADS)

Peng, B.; Guan, K.; Chen, M.

2016-12-01

Future agricultural production faces a grand challenge of higher temperature under climate change. There are multiple physiological or metabolic processes of how high temperature affects crop yield. Specifically, we consider the following major processes: (1) direct temperature effects on photosynthesis and respiration; (2) speed-up growth rate and the shortening of growing season; (3) heat stress during reproductive stage (flowering and grain-filling); (4) high-temperature induced increase of atmospheric water demands. In this work, we use a newly developed modeling framework (CLM-APSIM) to simulate the corn and soybean growth and explicitly parse the above four processes. By combining the strength of CLM in modeling surface biophysical (e.g., hydrology and energy balance) and biogeochemical (e.g., photosynthesis and carbon-nitrogen interactions), as well as that of APSIM in modeling crop phenology and reproductive stress, the newly developed CLM-APSIM modeling framework enables us to diagnose the impacts of high temperature stress through different processes at various crop phenology stages. Ground measurements from the advanced SoyFACE facility at University of Illinois is used here to calibrate, validate, and improve the CLM-APSIM modeling framework at the site level. We finally use the CLM-APSIM modeling framework to project crop yield for the whole US Corn Belt under different climate scenarios.

The genetic and molecular basis of crop height based on a rice model.

PubMed

Liu, Fang; Wang, Pandi; Zhang, Xiaobo; Li, Xiaofei; Yan, Xiaohong; Fu, Donghui; Wu, Gang

2018-01-01

This review presents genetic and molecular basis of crop height using a rice crop model. Height is controlled by multiple genes with potential to be manipulated through breeding strategies to improve productivity. Height is an important factor affecting crop architecture, apical dominance, biomass, resistance to lodging, tolerance to crowding and mechanical harvesting. The impressive increase in wheat and rice yield during the 'green revolution' benefited from a combination of breeding for high-yielding dwarf varieties together with advances in agricultural mechanization, irrigation and agrochemical/fertilizer use. To maximize yield under irrigation and high fertilizer use, semi-dwarfing is optimal, whereas extreme dwarfing leads to decreased yield. Rice plant height is controlled by genes that lie in a complex regulatory network, mainly involved in the biosynthesis or signal transduction of phytohormones such as gibberellins, brassinosteroids and strigolactones. Additional dwarfing genes have been discovered that are involved in other pathways, some of which are uncharacterized. This review discusses our current understanding of the regulation of plant height using rice as a well-characterized model and highlights some of the most promising research that could lead to the development of new, high-yielding varieties. This knowledge underpins future work towards the genetic improvement of plant height in rice and other crops.

Contribution of cosmic ray particles to radiation environment at high mountain altitude: Comparison of Monte Carlo simulations with experimental data.

PubMed

Mishev, A L

2016-03-01

A numerical model for assessment of the effective dose due to secondary cosmic ray particles of galactic origin at high mountain altitude of about 3000 m above the sea level is presented. The model is based on a newly numerically computed effective dose yield function considering realistic propagation of cosmic rays in the Earth magnetosphere and atmosphere. The yield function is computed using a full Monte Carlo simulation of the atmospheric cascade induced by primary protons and α- particles and subsequent conversion of secondary particle fluence (neutrons, protons, gammas, electrons, positrons, muons and charged pions) to effective dose. A lookup table of the newly computed effective dose yield function is provided. The model is compared with several measurements. The comparison of model simulations with measured spectral energy distributions of secondary cosmic ray neutrons at high mountain altitude shows good consistency. Results from measurements of radiation environment at high mountain station--Basic Environmental Observatory Moussala (42.11 N, 23.35 E, 2925 m a.s.l.) are also shown, specifically the contribution of secondary cosmic ray neutrons. A good agreement with the model is demonstrated. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2017-01-01

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI=(1+e−15.2829×(RAGDDi−0.1944))−1−(1+e−11.6517×(RAGDDi−1.0267))−1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status. PMID:28338637

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

PubMed

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

2017-03-24

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

Estimating total maximum daily loads with the Stochastic Empirical Loading and Dilution Model

USGS Publications Warehouse

Granato, Gregory; Jones, Susan Cheung

2017-01-01

The Massachusetts Department of Transportation (DOT) and the Rhode Island DOT are assessing and addressing roadway contributions to total maximum daily loads (TMDLs). Example analyses for total nitrogen, total phosphorus, suspended sediment, and total zinc in highway runoff were done by the U.S. Geological Survey in cooperation with FHWA to simulate long-term annual loads for TMDL analyses with the stochastic empirical loading and dilution model known as SELDM. Concentration statistics from 19 highway runoff monitoring sites in Massachusetts were used with precipitation statistics from 11 long-term monitoring sites to simulate long-term pavement yields (loads per unit area). Highway sites were stratified by traffic volume or surrounding land use to calculate concentration statistics for rural roads, low-volume highways, high-volume highways, and ultraurban highways. The median of the event mean concentration statistics in each traffic volume category was used to simulate annual yields from pavement for a 29- or 30-year period. Long-term average yields for total nitrogen, phosphorus, and zinc from rural roads are lower than yields from the other categories, but yields of sediment are higher than for the low-volume highways. The average yields of the selected water quality constituents from high-volume highways are 1.35 to 2.52 times the associated yields from low-volume highways. The average yields of the selected constituents from ultraurban highways are 1.52 to 3.46 times the associated yields from high-volume highways. Example simulations indicate that both concentration reduction and flow reduction by structural best management practices are crucial for reducing runoff yields.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

PubMed

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Postcalving factors affecting conception risk in Holstein dairy cows in tropical and sub-tropical conditions.

PubMed

Tillard, E; Humblot, P; Faye, B; Lecomte, P; Dohoo, I; Bocquier, F

2008-03-01

The objective was to identify postpartum risk factors between nutritional imbalance and health disorders affecting first-service conception risk (FSCR) in 21 commercial Holstein herds in Reunion Island. Multivariate logistic-regression models including herd as a random effect were used to analyze the relationship between FSCR and energy status, nitrogen status, hepatic function, mineral deficiencies, and postpartum health disorders. Two models (A and B) were built on two subsets of data (n=446 and n=863) with risk indicators measured during the first month of lactation and around time of first service, respectively, adjusted for season, breed, parity, origin, milk yield, calving to first service interval (CS1), and type of estrus (spontaneous vs. induced). The averaged conception risk was 0.266+/-0.015 (n=913) (mean+/-S.E.M.). In both models, FSCR was decreased by CS1 < or = 60 d and induced estrus. In model A, FSCR was decreased (p<0.05) for cows with mean cumulative 100 d daily milk yield < or =23 kg/d and >27 kg/d, with losses of body condition score >1.5, and with retained placenta. In model B, FSCR was decreased (p<0.05) for cows inseminated during wet season, previously raised out of the farm as nulliparous, with blood magnesium concentration < or =0.9 mmol/L, and for high-yielding cows (100 d milk yield > 27 kg/d) with glutamate deshydrogenase>17 UI/L. Hence, high-body-lipid mobilization during the first month of lactation was a strong nutritional predictor of low FSCR together with liver damage in high-yielding cows. Interestingly, our models revealed that infertility is better related to nutritional factors than to postpartum health disorders occurrence.

Optimizing Dense Plasma Focus Neutron Yields With Fast Gas Jets

NASA Astrophysics Data System (ADS)

McMahon, Matthew; Stein, Elizabeth; Higginson, Drew; Kueny, Christopher; Link, Anthony; Schmidt, Andrea

2017-10-01

We report a study using the particle-in-cell code LSP to perform fully kinetic simulations modeling dense plasma focus (DPF) devices with high density gas jets on axis. The high-density jets are modeled in the large-eddy Navier-Stokes code CharlesX, which is suitable for modeling both sub-sonic and supersonic gas flow. The gas pattern, which is essentially static on z-pinch time scales, is imported from CharlesX to LSP for neutron yield predictions. Fast gas puffs allow for more mass on axis while maintaining the optimal pressure for the DPF. As the density of a subsonic jet increases relative to the background fill, we find the neutron yield increases, as does the variability in the neutron yield. Introducing perturbations in the jet density via super-sonic flow (also known as Mach diamonds) allow for consistent seeding of the m =0 instability leading to more consistent ion acceleration and higher neutron yields with less variability. Jets with higher on axis density are found to have the greatest yield. The optimal jet configuration and the necessary jet conditions for increasing neutron yield and reducing yield variability are explored. Simulations of realistic jet profiles are performed and compared to the ideal scenario. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the Laboratory Directed Research and Development Program (15-ERD-034) at LLNL.

Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008

USGS Publications Warehouse

Harden, Stephen L.; Cuffney, Thomas F.; Terziotti, Silvia; Kolb, Katharine R.

2013-01-01

Data collected between 1997 and 2008 at 48 stream sites were used to characterize relations between watershed settings and stream nutrient yields throughout central and eastern North Carolina. The focus of the investigation was to identify environmental variables in watersheds that influence nutrient export for supporting the development and prioritization of management strategies for restoring nutrient-impaired streams. Nutrient concentration data and streamflow data compiled for the 1997 to 2008 study period were used to compute stream yields of nitrate, total nitrogen (N), and total phosphorus (P) for each study site. Compiled environmental data (including variables for land cover, hydrologic soil groups, base-flow index, streams, wastewater treatment facilities, and concentrated animal feeding operations) were used to characterize the watershed settings for the study sites. Data for the environmental variables were analyzed in combination with the stream nutrient yields to explore relations based on watershed characteristics and to evaluate whether particular variables were useful indicators of watersheds having relatively higher or lower potential for exporting nutrients. Data evaluations included an examination of median annual nutrient yields based on a watershed land-use classification scheme developed as part of the study. An initial examination of the data indicated that the highest median annual nutrient yields occurred at both agricultural and urban sites, especially for urban sites having large percentages of point-source flow contributions to the streams. The results of statistical testing identified significant differences in annual nutrient yields when sites were analyzed on the basis of watershed land-use category. When statistical differences in median annual yields were noted, the results for nitrate, total N, and total P were similar in that highly urbanized watersheds (greater than 30 percent developed land use) and (or) watersheds with greater than 10 percent point-source flow contributions to streamflow had higher yields relative to undeveloped watersheds (having less than 10 and 15 percent developed and agricultural land uses, respectively) and watersheds with relatively low agricultural land use (between 15 and 30 percent). The statistical tests further indicated that the median annual yields for total P were statistically higher for watersheds with high agricultural land use (greater than 30 percent) compared to the undeveloped watersheds and watersheds with low agricultural land use. The total P yields also were higher for watersheds with low urban land use (between 10 and 30 percent developed land) compared to the undeveloped watersheds. The study data indicate that grouping and examining stream nutrient yields based on the land-use classifications used in this report can be useful for characterizing relations between watershed settings and nutrient yields in streams located throughout central and eastern North Carolina. Compiled study data also were analyzed with four regression tree models as a means of determining which watershed environmental variables or combination of variables result in basins that are likely to have high or low nutrient yields. The regression tree analyses indicated that some of the environmental variables examined in this study were useful for predicting yields of nitrate, total N, and total P. When the median annual nutrient yields for all 48 sites were evaluated as a group (Model 1), annual point-source flow yields had the greatest influence on nitrate and total N yields observed in streams, and annual streamflow yields had the greatest influence on yields of total P. The Model 1 results indicated that watersheds with higher annual point-source flow yields had higher annual yields of nitrate and total N, and watersheds with higher annual streamflow yields had higher annual yields of total P. When sites with high point-source flows (greater than 10 percent of total streamflow) were excluded from the regression tree analyses (Models 2–4), the percentage of forested land in the watersheds was identified as the primary environmental variable influencing stream yields for both total N and total P. Models 2, 3 and 4 did not identify any watershed environmental variables that could adequately explain the observed variability in the nitrate yields among the set of sites examined by each of these models. The results for Models 2, 3, and 4 indicated that watersheds with higher percentages of forested land had lower annual total N and total P yields compared to watersheds with lower percentages of forested land, which had higher median annual total N and total P yields. Additional environmental variables determined to further influence the stream nutrient yields included median annual percentage of point-source flow contributions to the streams, variables of land cover (percentage of forested land, agricultural land, and (or) forested land plus wetlands) in the watershed and (or) in the stream buffer, and drainage area. The regression tree models can serve as a tool for relating differences in select watershed attributes to differences in stream yields of nitrate, total N, and total P, which can provide beneficial information for improving nutrient management in streams throughout North Carolina and for reducing nutrient loads to coastal waters.

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Developing a scalable model of recombinant protein yield from Pichia pastoris: the influence of culture conditions, biomass and induction regime

PubMed Central

Holmes, William J; Darby, Richard AJ; Wilks, Martin DB; Smith, Rodney; Bill, Roslyn M

2009-01-01

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time. PMID:19570229

Soils Activity Mobility Study: Methodology and Application

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

None, None

2014-09-29

This report presents a three-level approach for estimation of sediment transport to provide an assessment of potential erosion risk for sites at the Nevada National Security Site (NNSS) that are posted for radiological purposes and where migration is suspected or known to occur due to storm runoff. Based on the assessed risk, the appropriate level of effort can be determined for analysis of radiological surveys, field experiments to quantify erosion and transport rates, and long-term monitoring. The method is demonstrated at contaminated sites, including Plutonium Valley, Shasta, Smoky, and T-1. The Pacific Southwest Interagency Committee (PSIAC) procedure is selected asmore » the Level 1 analysis tool. The PSIAC method provides an estimation of the total annual sediment yield based on factors derived from the climatic and physical characteristics of a watershed. If the results indicate low risk, then further analysis is not warranted. If the Level 1 analysis indicates high risk or is deemed uncertain, a Level 2 analysis using the Modified Universal Soil Loss Equation (MUSLE) is proposed. In addition, if a sediment yield for a storm event rather than an annual sediment yield is needed, then the proposed Level 2 analysis should be performed. MUSLE only provides sheet and rill erosion estimates. The U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) provides storm peak runoff rate and storm volumes, the inputs necessary for MUSLE. Channel Sediment Transport (CHAN-SED) I and II models are proposed for estimating sediment deposition or erosion in a channel reach from a storm event. These models require storm hydrograph associated sediment concentration and bed load particle size distribution data. When the Level 2 analysis indicates high risk for sediment yield and associated contaminant migration or when there is high uncertainty in the Level 2 results, the sites can be further evaluated with a Level 3 analysis using more complex and labor- and data-intensive methods. For the watersheds analyzed in this report using the Level 1 PSIAC method, the risk of erosion is low. The field reconnaissance surveys of these watersheds confirm the conclusion that the sediment yield of undisturbed areas at the NNSS would be low. The climate, geology, soils, ground cover, land use, and runoff potential are similar among these watersheds. There are no well-defined ephemeral channels except at the Smoky and Plutonium Valley sites. Topography seems to have the strongest influence on sediment yields, as sediment yields are higher on the steeper hill slopes. Lack of measured sediment yield data at the NNSS does not allow for a direct evaluation of the yield estimates by the PSIAC method. Level 2 MUSLE estimates in all the analyzed watersheds except Shasta are a small percentage of the estimates from PSIAC because MUSLE is not inclusive of channel erosion. This indicates that channel erosion dominates the total sediment yield in these watersheds. Annual sediment yields for these watersheds are estimated using the CHAN-SEDI and CHAN-SEDII channel sediment transport models. Both transport models give similar results and exceed the estimates obtained from PSIAC and MUSLE. It is recommended that the total watershed sediment yield of watersheds at the NNSS with flow channels be obtained by adding the washload estimate (rill and inter-rill erosion) from MUSLE to that obtained from channel transport models (bed load and suspended sediment). PSIAC will give comparable results if factor scores for channel erosion are revised towards the high erosion level. Application of the Level 3 process-based models to estimate sediment yields at the NNSS cannot be recommended at this time. Increased model complexity alone will not improve the certainty of the sediment yield estimates. Models must be calibrated against measured data before model results are accepted as certain. Because no measurements of sediment yields at the NNSS are available, model validation cannot be performed. This is also true for the models used in the Level 2 analyses presented in this study. The need to calibrate MUSLE to local conditions has been discussed. Likewise, the transport equations of CHAN-SEDI and CHAN-SEDII need to be calibrated against local data to assess their applicability under semi-arid conditions and for the ephemeral channels at the NNSS. Before these validations and calibration exercises can be undertaken, a long-term measured sediment yield data set must be developed. Development of long-term measured sediment yield data cannot be overemphasized. Long-term monitoring is essential for accurate characterization of watershed processes. It is recommended that a long-term monitoring program be set up to measure watershed erosion rates and channel sediment transport rates.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Kinetics model of bainitic transformation with stress

NASA Astrophysics Data System (ADS)

Zhou, Mingxing; Xu, Guang; Hu, Haijiang; Yuan, Qing; Tian, Junyu

2018-01-01

Thermal simulations were conducted on a Gleeble 3800 simulator. The main purpose is to investigate the effects of stress on the kinetics of bainitic transformation in a Fe-C-Mn-Si advanced high strength bainitic steel. Previous studies on modeling the kinetics of stress affected bainitic transformation only considered the stress below the yield strength of prior austenite. In the present study, the stress above the yield strength of prior austenite is taken into account. A new kinetics model of bainitic transformation dependent on the stress (including the stresses below and above the yield strength of prior austenite) and the transformation temperature is proposed. The new model presents a good agreement with experimental results. In addition, it is found that the acceleration degree of stress on bainitic transformation increases with the stress whether its magnitude is below or above the yield strength of austenite, but the increasing rate gradually slows down when the stress is above the yield strength of austenite.

High-biomass C4 grasses-Filling the yield gap.

PubMed

Mullet, John E

2017-08-01

A significant increase in agricultural productivity will be required by 2050 to meet the needs of an expanding and rapidly developing world population, without allocating more land and water resources to agriculture, and despite slowing rates of grain yield improvement. This review examines the proposition that high-biomass C 4 grasses could help fill the yield gap. High-biomass C 4 grasses exhibit high yield due to C 4 photosynthesis, long growth duration, and efficient capture and utilization of light, water, and nutrients. These C 4 grasses exhibit high levels of drought tolerance during their long vegetative growth phase ideal for crops grown in water-limited regions of agricultural production. The stems of some high-biomass C 4 grasses can accumulate high levels of non-structural carbohydrates that could be engineered to enhance biomass yield and utility as feedstocks for animals and biofuels production. The regulatory pathway that delays flowering of high-biomass C 4 grasses in long days has been elucidated enabling production and deployment of hybrids. Crop and landscape-scale modeling predict that utilization of high-biomass C 4 grass crops on land and in regions where water resources limit grain crop yield could increase agricultural productivity. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Plasma-screening effects on the electron-impact excitation of hydrogenic ions in dense plasmas

NASA Technical Reports Server (NTRS)

Jung, Young-Dae

1993-01-01

Plasma-screening effects are investigated on electron-impact excitation of hydrogenic ions in dense plasmas. Scaled cross sections Z(exp 4) sigma for 1s yields 2s and 1s yields 2p are obtained for a Debye-Hueckel model of the screened Coulomb interaction. Ground and excited bound wave functions are modified in the screened Coulomb potential (Debye-Hueckel model) using the Ritz variation method. The resulting atomic wave functions and their eigenenergies agree well with the numerical and high-order perturbation theory calculations for the interesting domain of the Debye length not less than 10. The Born approximation is used to describe the continuum states of the projectile electron. Plasma screening effects on the atomic electrons cannot be neglected in the high-density cases. Including these effects, the cross sections are appreciably increased for 1s yields 2s transitions and decreased for 1s yields 2p transitions.

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.

Rheology of dilute acid hydrolyzed corn stover at high solids concentration

Treesearch

M.R. Ehrhardt; T.O. Monz; T.W. Root; R.K. Connelly; Tim Scott; D.J. Klingenberg

2010-01-01

The rheological properties of acid hydrolyzed corn stover at high solids concentration (20–35 wt.%) were investigated using torque rheometry. These materials are yield stress fluids whose rheological properties can be well represented by the Bingham model. Yield stresses increase with increasing solids concentration and decrease with increasing hydrolysis reaction...

High sensitivity tests of the standard model for electroweak interactions. [Lepton-family-number-violating decay; Michel [rho] parameter

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

Koetke, D.D.; Manweiler, R.W.; Shirvel Stanislaus, T.D.

1993-01-01

The work done on this project was focused on two LAMPF experiments. The MEGA experiment, a high-sensitivity search for the lepton-family-number-violating decay [mu] [yields] e [gamma] to a sensitivity which, measured in terms of the branching ratio, BR = [[mu] [yields] e [gamma

Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Cecil, L. Dewayne; Horton, Radley M.; Gordon, Roman; McCollum, Raymond (Brown, Douglas); Brown, Douglas; Killough, Brian; Goldberg, Richard; Greeley, Adam P.; Rosenzweig, Cynthia

2011-01-01

We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the important uncertainties behind the selection of climate change metrics and their performance against more complex process-based crop model simulations, revealing a danger in relying only on long-term mean quantities for crop impact assessment.

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.

Final Report Auto/Steel Partnership Phase II

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

Cady, C.M.; Chen, S.R.; Gray, G.T. III

1999-06-09

This is the final report in which effects of strain-rate, temperature, and stress-state on the yield stress and the strain hardening behavior of many common steels used in automobile construction were investigated. The yield and flow stresses were found to exhibit very high rate sensitivities for most of the steels while the hardening rates were found to be insensitive to strain rate and temperature at lower temperatures or at higher strain rates. This behavior is consistent with the observation that overcoming the intrinsic Peierls stress is shown to be the rate-controlling mechanism in these materials at low temperatures. The dependencemore » of the yield stress on temperature and strain rate was found to decrease while the strain hardening rate increased. The Mechanical Threshold Stress (MTS) model was adopted to model the stress-strain behavior of the steels. Parameters for the constitutive relations were derived for the MTS model and also for the Johnson-Cook (JC) and the Zerilli-Armstrong (ZA) models. The results of this study substantiate the applicability of these models for describing the high strain-rate deformation of these materials. The JC and ZA models, however, due to their use of a power strain hardening law were found to yield constitutive relations for the materials which are strongly dependent on the range of strains for which the models were optimized.« less

Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

NASA Astrophysics Data System (ADS)

Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

2013-04-01

The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the assimilation of the remotely sensed GAI time series. The calibration process led to accurate spatial estimates of GAI, ETR as well as of biomass and yield over the study area (24 km x 24 km window). The results highlight the interest of using a combined approach (crop model coupled with high spatial and temporal resolution remote sensing data) for the estimation of agronomical variables. At local scale, the model reproduced correctly the biomass production and ETR for summer crops (with relative RMSE of 29% and 35%, respectively). At regional scale, estimated yield and water requirement for irrigation were compared to regional statistics of yield and irrigation inventories provided by the local water agency. Results showed good agreements for inter-annual dynamics of yield estimates. Differences between water requirement for irrigation and actual supply were lower than 10% and inter-annual variability was well represented as well. The work, initially focused on summer crops, is being adapted to winter crops.

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

Hurricane, O. A.; Clark, D. S.

The work is summarized from several perspectives: 1D simulation perspective: Post-shot models agree with yield data to within a factor of ~2 at low implosion velocities, but the models diverge from the data as the velocity and convergence ratio increase. 2D simulation perspective: Integrated hohlraum-capsule post-shot models agree with primary data for most implosions, but overpredict yield and DSR for a few of the highest velocity implosions. High-resolution 3D post-shot capsule-only modeling captures much of the delivered performance of the one shot currently simulated.

The Effect of Initial Cell Concentration on Xylose Fermentation by Pichia stipitis

NASA Astrophysics Data System (ADS)

Agbogbo, Frank K.; Coward-Kelly, Guillermo; Torry-Smith, Mads; Wenger, Kevin; Jeffries, Thomas W.

Xylose was fermented using Pichia stipitis CBS 6054 at different initial cell concentrations. A high initial cell concentration increased the rate of xylose utilization, ethanol formation, and the ethanol yield. The highest ethanol concentration of 41.0 g/L and a yield of 0.38 g/g was obtained using an initial cell concentration of 6.5 g/L. Even though more xylitol was produced when the initial cell concentrations were high, cell density had no effect on the final ethanol yield. A two-parameter mathematical model was used to predict the cell population dynamics at the different initial cell concentrations. The model parameters, a and b correlate with the initial cell concentrations used with an R 2 of 0.99.

The carbon dioxide chaperon efficiency for the reaction H + O2 + M yields HO2 + M from ignition delay times behind reflected shock waves

NASA Technical Reports Server (NTRS)

Brabbs, Theodore A.; Robertson, Thomas F.

1987-01-01

Ignition delay times for stoichiometric hydrogen-oxygen in argon with and without carbon dioxide were measured behind reflected shock waves. A 20-reaction kinetic mechanism models the measured hydrogen-oxygen delay times over the temperature range 950 to 1300 K. The chaperon efficiency for carbon dioxide determined for the hydrogen-oxygen carbon dioxide mixture was 7.0. This value is in agreement with literature values but much less than a recent value obtained from flow tube experiments. Delay times measured behind a reflected shock wave were about 20% longer than those measured behind incident shock waves. The kinetic mechanism successfully modeled the high-pressure data of Skinner and the hydrogen-air data of Stack. It is suggested that the lowest temperature points for the hydrogen-air data of Slack are unreliable and that the 0.27-atm data may illustrate a case where vibrational relaxation of nitrogen is important. The reaction pathway HO2 yields H2O2 yields OH yields H was required to model the high-pressure data of Skinner. The successful modeling of the stoichiometric hydrogen-air data demonstrates the appropriateness of deriving kinetic models from data for gas mixtures highly diluted with argon. The technique of reducing a detailed kinetic mechanism to only the important reactions for a limited range of experimental data may render the mechanism useless for other test conditions.

Application of DSSAT-CROPGRO-Cotton Model to Assess Long Term (1924-2012) Cotton Yield under Different Irrigation Management Strategies

NASA Astrophysics Data System (ADS)

Adhikari, P.; Gowda, P. H.; Northup, B. K.; Rocateli, A.

2017-12-01

In this study a well calibrated and validated DSSAT-CROPGRO-Cotton model was used for assessing the irrigation management in the Texas High Plains (THP). Long term (1924-2012) historic lint yield were simulated under different irrigation management practices which were commonly used in the THP. The simulation treatments includes different amount of irrigation water high (H; 6.4 mm d-1), medium (M; 3.2 mm d-1) and low (L; 0 mm d-1) during emergence (S1), vegetative (S2) and maturity (S3) stage. The combination of these treatments resulted into 27 treatments. The amount and date of irrigation for each stage were obtained from the recent cotton irrigation experiment at Halfway, TX (Brodovsky, et al., 2015). Similarly, calibrated model was also used to observe the effect of plantation date on crop yield in the THP regions.

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

PubMed

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

2015-06-01

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

The sensitivity of ecosystem service models to choices of input data and spatial resolution

USGS Publications Warehouse

Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

2018-01-01

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

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.

Weather-based forecasts of California crop yields

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

Lobell, D B; Cahill, K N; Field, C B

2005-09-26

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over themore » 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.« less

Assessing variable rate nitrogen fertilizer strategies within an extensively instrument field site using the MicroBasin model

NASA Astrophysics Data System (ADS)

Ward, N. K.; Maureira, F.; Yourek, M. A.; Brooks, E. S.; Stockle, C. O.

2014-12-01

The current use of synthetic nitrogen fertilizers in agriculture has many negative environmental and economic costs, necessitating improved nitrogen management. In the highly heterogeneous landscape of the Palouse region in eastern Washington and northern Idaho, crop nitrogen needs vary widely within a field. Site-specific nitrogen management is a promising strategy to reduce excess nitrogen lost to the environment while maintaining current yields by matching crop needs with inputs. This study used in-situ hydrologic, nutrient, and crop yield data from a heavily instrumented field site in the high precipitation zone of the wheat-producing Palouse region to assess the performance of the MicroBasin model. MicroBasin is a high-resolution watershed-scale ecohydrologic model with nutrient cycling and cropping algorithms based on the CropSyst model. Detailed soil mapping conducted at the site was used to parameterize the model and the model outputs were evaluated with observed measurements. The calibrated MicroBasin model was then used to evaluate the impact of various nitrogen management strategies on crop yield and nitrate losses. The strategies include uniform application as well as delineating the field into multiple zones of varying nitrogen fertilizer rates to optimize nitrogen use efficiency. We present how coupled modeling and in-situ data sets can inform agricultural management and policy to encourage improved nitrogen management.

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.

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.;

The Ignition Physics Campaign on NIF: Status and Progress

NASA Astrophysics Data System (ADS)

Edwards, M. J.; Ignition Team

2016-03-01

We have made significant progress in ICF implosion performance on NIF since the 2011 IFSA. Employing a 3-shock, high adiabat CH (“High-Foot”) design, total neutron yields have increased 10-fold to 6.3 x1015 (a yield of ∼ 17 kJ, which is greater than the energy invested in the DT fuel ∼ 12kJ). At that level, the yield from alpha self-heating is essentially equivalent to the compression yield, indicating that we are close to the alpha self-heating regime. Low adiabat, 4-shock High Density Carbon (HDC) capsules have been imploded in conventional gas-filled hohlraums, and employing a 6 ns, 2-shock pulse, HDC capsules were imploded in near-vacuum hohlraums with overall coupling ∼ 98%. Both the 4- and 2-shock HDC capsules had very low mix and high yield over simulated performance. Rugby holraums have demonstrated uniform x-ray drive with minimal Cross Beam Energy Transfer (CBET), and we have made good progress in measuring and modelling growth of ablation front hydro instabilities.

Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron Highlands, Pahang, Malaysia

NASA Astrophysics Data System (ADS)

Ghani, A. H. A.; Lihan, T.; Rahim, S. A.; Musthapha, M. A.; Idris, W. M. R.; Rahman, Z. A.

2013-11-01

Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS) environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation type and density, climate and land use within the drainage basin.

e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding.

PubMed

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N; Friggens, N C

2012-06-01

This animal simulation model, named e-Cow, represents a single dairy cow at grazing. The model integrates algorithms from three previously published models: a model that predicts herbage dry matter (DM) intake by grazing dairy cows, a mammary gland model that predicts potential milk yield and a body lipid model that predicts genetically driven live weight (LW) and body condition score (BCS). Both nutritional and genetic drives are accounted for in the prediction of energy intake and its partitioning. The main inputs are herbage allowance (HA; kg DM offered/cow per day), metabolisable energy and NDF concentrations in herbage and supplements, supplements offered (kg DM/cow per day), type of pasture (ryegrass or lucerne), days in milk, days pregnant, lactation number, BCS and LW at calving, breed or strain of cow and genetic merit, that is, potential yields of milk, fat and protein. Separate equations are used to predict herbage intake, depending on the cutting heights at which HA is expressed. The e-Cow model is written in Visual Basic programming language within Microsoft Excel®. The model predicts whole-lactation performance of dairy cows on a daily basis, and the main outputs are the daily and annual DM intake, milk yield and changes in BCS and LW. In the e-Cow model, neither herbage DM intake nor milk yield or LW change are needed as inputs; instead, they are predicted by the e-Cow model. The e-Cow model was validated against experimental data for Holstein-Friesian cows with both North American (NA) and New Zealand (NZ) genetics grazing ryegrass-based pastures, with or without supplementary feeding and for three complete lactations, divided into weekly periods. The model was able to predict animal performance with satisfactory accuracy, with concordance correlation coefficients of 0.81, 0.76 and 0.62 for herbage DM intake, milk yield and LW change, respectively. Simulations performed with the model showed that it is sensitive to genotype by feeding environment interactions. The e-Cow model tended to overestimate the milk yield of NA genotype cows at low milk yields, while it underestimated the milk yield of NZ genotype cows at high milk yields. The approach used to define the potential milk yield of the cow and equations used to predict herbage DM intake make the model applicable for predictions in countries with temperate pastures.

Pricing Weather Index Insurance Based on Artificial Controlled Experiment - A Case Study of Cold Temperature for Early Rice in Jiangxi, China

NASA Astrophysics Data System (ADS)

SUN, Q.; Yang, Z.

2017-12-01

The growth of early rice is often threated by a phenomenon known as Grain Buds Cold, a period of anomalously cold temperature that occurs during the booting and flowering stage. Therefore, quantifying the impact of weather on crop yield is a core issue in design of weather index insurance. A high yield loss will lead to an increasing premium rate. In this paper, we explored a new way to investigate the relationship between yield loss rate and cold temperature durations. A two-year artificial controlled experiment was used to build logarithm and linear yield loss model. Moreover, an information diffusion model was applied to calculate the probability of different durations which lasting for 3-20 days. The results show that pure premium rates of logarithm yield loss model had better premium rates performance than that of linear yield loss model. The premium rates of Grain Buds Cold Weather Index Insurance fluctuated between 7.085% and 10.151% in Jiangxi Province. Compared with common statistical methods, the artificial controlled experiment provides an easier and more robust way to determine the relationship between yield and single meteorological factor. Meanwhile, this experiment would be very important for some regions where were lacking in historical yield data and climate data and could help farmers cope with extreme cold weather risks under varying weather conditions.

Co-pyrolysis characteristics of microalgae Isochrysis and Chlorella: Kinetics, biocrude yield and interaction.

PubMed

Zhao, Bingwei; Wang, Xin; Yang, Xiaoyi

2015-12-01

Co-pyrolysis characteristics of Isochrysis (high lipid) and Chlorella (high protein) were investigated qualitatively and quantitatively based on DTG curves, biocrude yield and composition by individual pyrolysis and co-pyrolysis. DTG curves in co-pyrolysis have been compared accurately with those in individual pyrolysis. An interaction has been detected at 475-500°C in co-pyrolysis based on biocrude yields, and co-pyrolysis reaction mechanism appear three-dimensional diffusion in comparison with random nucleation followed by growth in individual pyrolysis based on kinetic analysis. There is no obvious difference in the maximum biocrude yields for individual pyrolysis and co-pyrolysis, but carboxylic acids (IC21) decreased and N-heterocyclic compounds (IC12) increased in co-pyrolysis. Simulation results of biocrude yield by Components Biofuel Model and Kinetics Biofuel Model indicate that the processes of co-pyrolysis comply with those of individual pyrolysis in solid phase by and large. Variation of percentage content in co-pyrolysis and individual pyrolysis biocrude indicated interaction in gas phase. Copyright © 2015. Published by Elsevier Ltd.

Simulation on Change Law of Runoff, Sediment and Non-point Source Nitrogen and Phosphorus Discharge under Different Land uses Based on SWAT Model: A Case Study of Er hai Lake Small Watershed

NASA Astrophysics Data System (ADS)

Tong, Xiao Xia; Lai Cui, Yuan; Chen, Man Yu; Hu, Bo; Xu, Wen Sheng

2018-05-01

The Er yuan watershed of Er hai district is chosen as the research area, the law of runoff and sediment and non-point source nitrogen and phosphorus discharges under different land uses during 2001 to 2014 are simulated based on SWAT model. Results of simulation indicate that the order of total runoff yield of different land use type from high to low is grassland, paddy fields, dry land. Specifically, the order of surface runoff yield from high to low is paddy fields, dry land, grassland, the order of lateral runoff yield from high to low is paddy fields, dry land, grassland, the order of groundwater runoff yield from high to low is grassland, paddy fields, dry land. The orders of sediment and nitrogen and phosphorus yield per unit area of different land use type are the same, grassland> paddy fields> dry land. It can be seen, nitrogen and phosphorus discharges from paddy fields and dry land are the main sources of agricultural non-point pollution of the irrigated area. Therefore, reasonable field management measures which can decrease the discharge of nitrogen and phosphorus of paddy fields and dry land are the key to agricultural non-point source pollution prevention and control.

Simulation of Oil Palm Shell Pyrolysis to Produce Bio-Oil with Self-Pyrolysis Reactor

NASA Astrophysics Data System (ADS)

Fika, R.; Nelwan, L. O.; Yulianto, M.

2018-05-01

A new self-pyrolysis reactor was designed to reduce the utilization of electric heater due to the energy saving for the production of bio-oil from oil palm shell. The yield of the bio- oil was then evaluated with the developed mathematical model by Sharma [1] with the characteristic of oil palm shell [2]. During the simulation, the temperature on the combustion chamber on the release of the bio-oil was utilized to determine the volatile composition from the combustion of the oil palm shell as fuel. The mass flow was assumed constant for three experiments. The model resulted in a significant difference between the simulated bio-oil and experiments. The bio-oil yields from the simulation were 22.01, 16.36, and 21.89 % (d.b.) meanwhile the experimental yields were 10.23, 9.82, and 8.41% (d.b.). The char yield varied from 30.7 % (d.b.) from the simulation to 40.9 % (d.b.) from the experiment. This phenomenon was due to the development of process temperature over time which was not considered as one of the influential factors in producing volatile matters on the simulation model. Meanwhile the real experiments highly relied on the process conditions (reactor type, temperature over time, gas flow). There was also possibilities of the occurrence of the gasification inside the reactor which caused the liquid yield was not as high as simulated. Further simulation model research on producing the bio-oil yield will be needed to predict the optimum condition and temperature development on the newly self-pyrolysis reactor.

EXTREMELY METAL-POOR STARS AND A HIERARCHICAL CHEMICAL EVOLUTION MODEL

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

Komiya, Yutaka

2011-07-20

Early phases of the chemical evolution of the Galaxy and formation history of extremely metal-poor (EMP) stars are investigated using hierarchical galaxy formation models. We build a merger tree of the Galaxy according to the extended Press-Schechter theory. We follow the chemical evolution along the tree and compare the model results to the metallicity distribution function and abundance ratio distribution of the Milky Way halo. We adopt three different initial mass functions (IMFs). In a previous study, we argued that the typical mass, M{sub md}, of EMP stars should be high, M{sub md} {approx} 10 M{sub sun}, based on studiesmore » of binary origin carbon-rich EMP stars. In this study, we show that only the high-mass IMF can explain an observed small number of EMP stars. For relative element abundances, the high-mass IMF and the Salpeter IMF predict similar distributions. We also investigate dependence on nucleosynthetic yields of supernovae (SNe). The theoretical SN yields by Kobayashi et al. and Chieffi and Limongi show reasonable agreement with observations for {alpha}-elements. Our model predicts a significant scatter of element abundances at [Fe/H] < -3. We adopted the stellar yields derived in the work of Francois et al., which produce the best agreement between the observational data and the one-zone chemical evolution model. Their yields well reproduce a trend of the averaged abundances of EMP stars but predict much larger scatter than do the observations. The model with hypernovae predicts Zn abundance, in agreement with the observations, but other models predict lower [Zn/Fe]. Ejecta from the hypernovae with large explosion energy is mixed in large mass and decreases the scatter of the element abundances.« less

Computational model of chromosome aberration yield induced by high- and low-LET radiation exposures.

PubMed

Ponomarev, Artem L; George, Kerry; Cucinotta, Francis A

2012-06-01

We present a computational model for calculating the yield of radiation-induced chromosomal aberrations in human cells based on a stochastic Monte Carlo approach and calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. A previously developed DNA-fragmentation model for high- and low-LET radiation called the NASARadiationTrackImage model was enhanced to simulate a stochastic process of the formation of chromosomal aberrations from DNA fragments. The current version of the model gives predictions of the yields and sizes of translocations, dicentrics, rings, and more complex-type aberrations formed in the G(0)/G(1) cell cycle phase during the first cell division after irradiation. As the model can predict smaller-sized deletions and rings (<3 Mbp) that are below the resolution limits of current cytogenetic analysis techniques, we present predictions of hypothesized small deletions that may be produced as a byproduct of properly repaired DNA double-strand breaks (DSB) by nonhomologous end-joining. Additionally, the model was used to scale chromosomal exchanges in two or three chromosomes that were obtained from whole-chromosome FISH painting analysis techniques to whole-genome equivalent values.

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.

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.

Estimation of dew yield from radiative condensers by means of an energy balance model

NASA Astrophysics Data System (ADS)

Maestre-Valero, J. F.; Ragab, R.; Martínez-Alvarez, V.; Baille, A.

2012-08-01

SummaryThis paper presents an energy balance modelling approach to predict the nightly water yield and the surface temperature (Tf) of two passive radiative dew condensers (RDCs) tilted 30° from horizontal. One was fitted with a white hydrophilic polyethylene foil recommended for dew harvest and the other with a black polyethylene foil widely used in horticulture. The model was validated in south-eastern Spain by comparing the simulation outputs with field measurements of Tf and dew yield. The results indicate that the model is robust and accurate in reproducing the behaviour of the two RDCs, especially in what refers to Tf, whose estimates were very close to the observations. The results were somewhat less precise for dew yield, with a larger scatter around the 1:1 relationship. A sensitivity analysis showed that the simulated dew yield was highly sensitive to changes in relative humidity and downward longwave radiation. The proposed approach provides a useful tool to water managers for quantifying the amount of dew that could be harvested as a valuable water resource in arid, semiarid and water stressed regions.

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

PubMed

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

PubMed Central

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly. PMID:23967112

Constitutive behavior of tantalum and tantalum-tungsten alloys

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

Chen, S.R.; Gray, G.T. III

1996-10-01

The effects of strain rate, temperature, and tungsten alloying on the yield stress and the strain-hardening behavior of tantalum were investigated. The yield and flow stresses of unalloyed Ta and tantalum-tungsten alloys were found to exhibit very high rate sensitivities, while the hardening rates in Ta and Ta-W alloys were found to be insensitive to strain rate and temperature at lower temperatures or at higher strain rates. This behavior is consistent with the observation that overcoming the intrinsic Peierls stress is shown to be the rate-controlling mechanism in these materials at low temperatures. The dependence of yield stress on temperaturemore » and strain rate was found to decrease, while the strain-hardening rate increased with tungsten alloying content. The mechanical threshold stress (MTS) model was adopted to model the stress-strain behavior of unalloyed Ta and the Ta-W alloys. Parameters for the constitutive relations for Ta and the Ta-W alloys were derived for the MTS model, the Johnson-Cook (JC), and the Zerilli-Armstrong (ZA) models. The results of this study substantiate the applicability of these models for describing the high strain-rate deformation of Ta and Ta-W alloys. The JC and ZA models, however, due to their use of a power strain-hardening law, were found to yield constitutive relations for Ta and Ta-W alloys that are strongly dependent on the range of strains for which the models were optimized.« less

Computing the biomass potentials for maize and two alternative energy crops, triticale and cup plant (Silphium perfoliatum L.), with the crop model BioSTAR in the region of Hannover (Germany).

PubMed

Bauböck, Roland; Karpenstein-Machan, Marianne; Kappas, Martin

2014-01-01

Lower Saxony (Germany) has the highest installed electric capacity from biogas in Germany. Most of this electricity is generated with maize. Reasons for this are the high yields and the economic incentive. In parts of Lower Saxony, an expansion of maize cultivation has led to ecological problems and a negative image of bioenergy as such. Winter triticale and cup plant have both shown their suitability as alternative energy crops for biogas production and could help to reduce maize cultivation. The model Biomass Simulation Tool for Agricultural Resources (BioSTAR) has been validated with observed yield data from the region of Hannover for the cultures maize and winter wheat. Predicted yields for the cultures show satisfactory error values of 9.36% (maize) and 11.5% (winter wheat). Correlations with observed data are significant ( P  < 0.01) with R  = 0.75 for maize and 0.6 for winter wheat. Biomass potential calculations for triticale and cup plant have shown both crops to be high yielding and a promising alternative to maize in the region of Hanover and other places in Lower Saxony. The model BioSTAR simulated yields for maize and winter wheat in the region of Hannover at a good overall level of accuracy (combined error 10.4%). Due to input data aggregation, individual years show high errors though (up to 30%). Nevertheless, the BioSTAR crop model has proven to be a functioning tool for the prediction of agricultural biomass potentials under varying environmental and crop management frame conditions.

Comparison of hadron production models for π±, k±, protons and antiprotons production in proton-carbon interactions at 60 GeV/c

NASA Astrophysics Data System (ADS)

Ajaz, M.; Ullah, S.; Ali, Y.; Younis, H.

2018-02-01

In this research paper, the comprehensive results on the double differential yield of π± and k± mesons, protons and antiprotons as a function of laboratory momentum are reported. These hadrons are produced in proton-carbon interaction at 60 GeV/c. EPOS 1.99, EPOS-LHC and QGSJETII-04 models are used to perform simulations. Comparing the predictions of these models show that QGSJETII-04 model predicts higher yields of all the hadrons in most of the cases at the peak of the distribution. In this interval, the EPOS 1.99 and EPOS-LHC produce similar results. In most of the cases at higher momentum of the hadrons, all the three models are in good agreement. For protons, all models are in good agreement. EPOS-LHC gives high yield of antiprotons at high momentum values as compared to the other two models. EPOS-LHC gives higher prediction at the peak value for π+ mesons and protons at higher polar angle intervals of 100 < 𝜃 < 420 and 100 < 𝜃 < 360, respectively, and EPOS 1.99 gives higher prediction at the peak value for π- mesons for 140 < 𝜃 < 420. The model predictions, except for antiprotons, are compared with the data obtained by the NA61/SHINE experiment at 31 GeV/c proton-carbon collision, which clearly shows that the behavior of the distributions in models are similar to the ones from the data but the yield in data is low because of lower beam energy.

Sources of nitrate yields in the Mississippi River Basin.

PubMed

David, Mark B; Drinkwater, Laurie E; McIsaac, Gregory F

2010-01-01

Riverine nitrate N in the Mississippi River leads to hypoxia in the Gulf of Mexico. Several recent modeling studies estimated major N inputs and suggested source areas that could be targeted for conservation programs. We conducted a similar analysis with more recent and extensive data that demonstrates the importance of hydrology in controlling the percentage of net N inputs (NNI) exported by rivers. The average fraction of annual riverine nitrate N export/NNI ranged from 0.05 for the lower Mississippi subbasin to 0.3 for the upper Mississippi River basin and as high as 1.4 (4.2 in a wet year) for the Embarras River watershed, a mostly tile-drained basin. Intensive corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] watersheds on Mollisols had low NNI values and when combined with riverine N losses suggest a net depletion of soil organic N. We used county-level data to develop a nonlinear model ofN inputs and landscape factors that were related to winter-spring riverine nitrate yields for 153 watersheds within the basin. We found that river runoff times fertilizer N input was the major predictive term, explaining 76% of the variation in the model. Fertilizer inputs were highly correlated with fraction of land area in row crops. Tile drainage explained 17% of the spatial variation in winter-spring nitrate yield, whereas human consumption of N (i.e., sewage effluent) accounted for 7%. Net N inputs were not a good predictor of riverine nitrate N yields, nor were other N balances. We used this model to predict the expected nitrate N yield from each county in the Mississippi River basin; the greatest nitrate N yields corresponded to the highly productive, tile-drained cornbelt from southwest Minnesota across Iowa, Illinois, Indiana, and Ohio. This analysis can be used to guide decisions about where efforts to reduce nitrate N losses can be most effectively targeted to improve local water quality and reduce export to the Gulf of Mexico.

Projected land use changes impacts on water yields in the karst mountain areas of China

NASA Astrophysics Data System (ADS)

Lang, Yanqing; Song, Wei; Deng, Xiangzheng

2018-04-01

Human-induced land use changes over short time scales have significant impacts on water yield, especially in China because of the rapid social economic development. As the biggest developing country of the world, China's economy is expected to continuously grow with a high speed in the next few decades. Therefore, what kind of land use changes will occur in the future in China? How these changes will influence the water yields? To address this issue, we assessed the water yields in the karst mountain area of China during the periods of 1990-2010 and 2010-2030 by coupling an Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and a Conversion of Land Use and its Effects (CLUE) model. Three different land use scenarios i.e. natural growth, economic development, and ecological protection, were developed in 2030 using the CLUE model. It was concluded that, given land use changes between 1990 and 2010, total water yields in the karst mountain area are characterized by a trend towards fluctuating reduction. However, total water yields of 2030 in the economic development scenario revealed an increase of 1.25% compared to the actual water yields in 2010. The economy development in karst mountain areas of China in the future has a slight positive influence on water yields.

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

REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

PubMed

Olivoto, T; Nardino, M; Carvalho, I R; Follmann, D N; Ferrari, M; Szareski, V J; de Pelegrin, A J; de Souza, V Q

2017-03-22

Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R 2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

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

Iavarone, Salvatore; Smith, Sean T.; Smith, Philip J.

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, inmore » the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.« less

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

DOE PAGES

Iavarone, Salvatore; Smith, Sean T.; Smith, Philip J.; ...

2017-06-03

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, inmore » the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.« less

Designing a highly active soluble PQQ-glucose dehydrogenase for efficient glucose biosensors and biofuel cells

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

Durand, Fabien; Stines-Chaumeil, Claire; Flexer, Victoria

2010-11-26

Research highlights: {yields} A new mutant of PQQ-GDH designed for glucose biosensors application. {yields} First mutant of PQQ-GDH with higher activity for D-glucose than the Wild type. {yields} Position N428 is a key point to increase the enzyme activity. {yields} Molecular modeling shows that the N428 C mutant displays a better interaction for PQQ than the WT. -- Abstract: We report for the first time a soluble PQQ-glucose dehydrogenase that is twice more active than the wild type for glucose oxidation and was obtained by combining site directed mutagenesis, modelling and steady-state kinetics. The observed enhancement is attributed to amore » better interaction between the cofactor and the enzyme leading to a better electron transfer. Electrochemical experiments also demonstrate the superiority of the new mutant for glucose oxidation and make it a promising enzyme for the development of high-performance glucose biosensors and biofuel cells.« less

CERES–Maize Model for Determining the Optimum Planting Dates of Early Maturing Maize Varieties in Northern Nigeria

PubMed Central

Adnan, Adnan A.; Jibrin, Jibrin M.; Kamara, Alpha Y.; Abdulrahman, Bassam L.; Shaibu, Abdulwahab S.; Garba, Ismail I.

2017-01-01

Field trials were carried out in the Sudan Savannah of Nigeria to assess the usefulness of CERES–maize crop model as a decision support tool for optimizing maize production through manipulation of plant dates. The calibration experiments comprised of 20 maize varieties planted during the dry and rainy seasons of 2014 and 2015 at Bayero University Kano and Audu Bako College of Agriculture Dambatta. The trials for model evaluation were conducted in 16 different farmer fields across the Sudan (Bunkure and Garun—Mallam) and Northern Guinea (Tudun-Wada and Lere) Savannas using two of the calibrated varieties under four different sowing dates. The model accurately predicted grain yield, harvest index, and biomass of both varieties with low RMSE-values (below 5% of mean), high d-index (above 0.8), and high r-square (above 0.9) for the calibration trials. The time series data (tops weight, stem and leaf dry weights) were also predicted with high accuracy (% RMSEn above 70%, d-index above 0.88). Similar results were also observed for the evaluation trials, where all variables were simulated with high accuracies. Estimation efficiencies (EF)-values above 0.8 were observed for all the evaluation parameters. Seasonal and sensitivity analyses on Typic Plinthiustalfs and Plinthic Kanhaplustults in the Sudan and Northern Guinea Savannas were conducted. Results showed that planting extra early maize varieties in late July and early maize in mid-June leads to production of highest grain yields in the Sudan Savanna. In the Northern Guinea Savanna planting extra-early maize in mid-July and early maize in late July produced the highest grain yields. Delaying planting in both Agro-ecologies until mid-August leads to lower yields. Delaying planting to mid-August led to grain yield reduction of 39.2% for extra early maize and 74.4% for early maize in the Sudan Savanna. In the Northern Guinea Savanna however, delaying planting to mid-August resulted in yield reduction of 66.9 and 94.3% for extra-early and early maize, respectively. PMID:28702039

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield due to flood events during the growing season. Using a 2011 Missouri River flood event as a case study, field-level flood impact map on corn yield throughout the flooded regions was produced and an overall agreement of over 82.2% was achieved when compared with the reference impact map. The future research direction of this dissertation research would be to examine other major crops outside the Corn Belt region of the U.S.

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.

High-resolution modeling of indirectly driven high-convergence layered inertial confinement fusion capsule implosions

DOE PAGES

Haines, Brian M.; Aldrich, C. H.; Campbell, J. M.; ...

2017-04-24

In this study, we present the results of high-resolution simulations of the implosion of high-convergence layered indirect-drive inertial confinement fusion capsules of the type fielded on the National Ignition Facility using the xRAGE radiation-hydrodynamics code. In order to evaluate the suitability of xRAGE to model such experiments, we benchmark simulation results against available experimental data, including shock-timing, shock-velocity, and shell trajectory data, as well as hydrodynamic instability growth rates. We discuss the code improvements that were necessary in order to achieve favorable comparisons with these data. Due to its use of adaptive mesh refinement and Eulerian hydrodynamics, xRAGE is particularlymore » well suited for high-resolution study of multi-scale engineering features such as the capsule support tent and fill tube, which are known to impact the performance of high-convergence capsule implosions. High-resolution two-dimensional (2D) simulations including accurate and well-resolved models for the capsule fill tube, support tent, drive asymmetry, and capsule surface roughness are presented. These asymmetry seeds are isolated in order to study their relative importance and the resolution of the simulations enables the observation of details that have not been previously reported. We analyze simulation results to determine how the different asymmetries affect hotspot reactivity, confinement, and confinement time and how these combine to degrade yield. Yield degradation associated with the tent occurs largely through decreased reactivity due to the escape of hot fuel mass from the hotspot. Drive asymmetries and the fill tube, however, degrade yield primarily via burn truncation, as associated instability growth accelerates the disassembly of the hotspot. Finally, modeling all of these asymmetries together in 2D leads to improved agreement with experiment but falls short of explaining the experimentally observed yield degradation, consistent with previous 2D simulations of such capsules.« less

Evaluating soil moisture and yield of winter wheat in the Great Plains using Landsat data

NASA Technical Reports Server (NTRS)

Heilman, J. L.; Kanemasu, E. T.; Bagley, J. O.; Rasmussen, V. P.

1977-01-01

Locating areas where soil moisture is limiting to crop growth is important for estimating winter-wheat yields on a regional basis. In the 1975-76 growing season, we evaluated soil-moisture conditions and winter-wheat yields for a five-state region of the Great Plains using Landsat estimates of leaf area index (LAI) and an evapotranspiration (ET) model described by Kanemasu et al (1977). Because LAI was used as an input, the ET model responded to changes in crop growth. Estimated soil-water depletions were high for the Nebraska Panhandle, southwestern Kansas, southeastern Colorado, and the Texas Panhandle. Estimated yields in five-state region ranged from 1.0 to 2.9 metric ton/ha.

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

PubMed

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

2009-01-01

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

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

PubMed Central

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

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

An image based method for crop yield prediction using remotely sensed and crop canopy data: the case of Paphos district, western Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Hadjimitsis, D.

2014-08-01

Remote sensing techniques development have provided the opportunity for optimizing yields in the agricultural procedure and moreover to predict the forthcoming yield. Yield prediction plays a vital role in Agricultural Policy and provides useful data to policy makers. In this context, crop and soil parameters along with NDVI index which are valuable sources of information have been elaborated statistically to test if a) Durum wheat yield can be predicted and b) when is the actual time-window to predict the yield in the district of Paphos, where Durum wheat is the basic cultivation and supports the rural economy of the area. 15 plots cultivated with Durum wheat from the Agricultural Research Institute of Cyprus for research purposes, in the area of interest, have been under observation for three years to derive the necessary data. Statistical and remote sensing techniques were then applied to derive and map a model that can predict yield of Durum wheat in this area. Indeed the semi-empirical model developed for this purpose, with very high correlation coefficient R2=0.886, has shown in practice that can predict yields very good. Students T test has revealed that predicted values and real values of yield have no statistically significant difference. The developed model can and will be further elaborated with more parameters and applied for other crops in the near future.

Production of Sn and Sb isotopes in high-energy neutron-induced fission of natU

NASA Astrophysics Data System (ADS)

Mattera, A.; Pomp, S.; Lantz, M.; Rakopoulos, V.; Solders, A.; Al-Adili, A.; Penttilä, H.; Moore, I. D.; Rinta-Antila, S.; Eronen, T.; Kankainen, A.; Pohjalainen, I.; Gorelov, D.; Canete, L.; Nesterenko, D.; Vilén, M.; Äystö, J.

2018-03-01

The first systematic measurement of neutron-induced fission yields has been performed at the upgraded IGISOL-4 facility at the University of Jyväskylä, Finland. The fission products from high-energy neutron-induced fission of nat U were stopped in a gas cell filled with helium buffer gas, and were online separated with a dipole magnet. The isobars, with masses in the range A = 128-133 , were transported to a tape-implantation station and identified using γ -spectroscopy. We report here the relative cumulative isotopic yields of tin ( Z = 50) and the relative independent isotopic yields of antimony ( Z = 51) . Isomeric yield ratios were also obtained for five nuclides. The yields of tin show a staggered behaviour around A = 131 , not observed in the ENDF/B-VII.1 evaluation. The yields of antimony also contradict the trend from the evaluation, but are in agreement with a calculation performed using the GEF model that shows the yield increasing with mass in the range A = 128-133.

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.

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

Earing Prediction in Cup Drawing using the BBC2008 Yield Criterion

NASA Astrophysics Data System (ADS)

Vrh, Marko; Halilovič, Miroslav; Starman, Bojan; Štok, Boris; Comsa, Dan-Sorin; Banabic, Dorel

2011-08-01

The paper deals with constitutive modelling of highly anisotropic sheet metals. It presents FEM based earing predictions in cup drawing simulation of highly anisotropic aluminium alloys where more than four ears occur. For that purpose the BBC2008 yield criterion, which is a plane-stress yield criterion formulated in the form of a finite series, is used. Thus defined criterion can be expanded to retain more or less terms, depending on the amount of given experimental data. In order to use the model in sheet metal forming simulations we have implemented it in a general purpose finite element code ABAQUS/Explicit via VUMAT subroutine, considering alternatively eight or sixteen parameters (8p and 16p version). For the integration of the constitutive model the explicit NICE (Next Increment Corrects Error) integration scheme has been used. Due to the scheme effectiveness the CPU time consumption for a simulation is comparable to the time consumption of built-in constitutive models. Two aluminium alloys, namely AA5042-H2 and AA2090-T3, have been used for a validation of the model. For both alloys the parameters of the BBC2008 model have been identified with a developed numerical procedure, based on a minimization of the developed cost function. For both materials, the predictions of the BBC2008 model prove to be in very good agreement with the experimental results. The flexibility and the accuracy of the model together with the identification and integration procedure guarantee the applicability of the BBC2008 yield criterion in industrial applications.

Supportability of a High-Yield-Stress Slurry in a New Stereolithography-Based Ceramic Fabrication Process

NASA Astrophysics Data System (ADS)

He, Li; Song, Xuan

2018-03-01

In recent years, ceramic fabrication using stereolithography (SLA) has gained in popularity because of its high accuracy and density that can be achieved in the final part of production. One of the key challenges in ceramic SLA is that support structures are required for building overhanging features, whereas removing these support structures without damaging the components is difficult. In this research, a suspension-enclosing projection-stereolithography process is developed to overcome this challenge. This process uses a high-yield-stress ceramic slurry as the feedstock material and exploits the elastic force of the material to support overhanging features without the need for building additional support structures. Ceramic slurries with different solid loadings are studied to identify the rheological properties most suitable for supporting overhanging features. An analytical model of a double doctor-blade module is established to obtain uniform and thin recoating layers from a high-yield-stress slurry. Several test cases highlight the feasibility of using a high-yield-stress slurry to support overhanging features in SLA.

Extraction of anthocyanins from red cabbage using high pressure CO2.

PubMed

Xu, Zhenzhen; Wu, Jihong; Zhang, Yan; Hu, Xiaosong; Liao, Xiaojun; Wang, Zhengfu

2010-09-01

The extraction kinetics of anthocyanins from red cabbage using high pressure CO(2) (HPCD) against conventional acidified water (CAW) was investigated. The HPCD time, temperature, pressure and volume ratio of solid-liquid mixture vs. pressurized CO(2) (R((S+L)/G)) exhibited important roles on the extraction kinetics of anthocyanins. The extraction kinetics showed two phases, the yield increased with increasing the time in the first phase, the yield defined as steady-state yield (y(*)) was constant in the second phase. The y(*) of anthocyanins using HPCD increased with higher temperature, higher pressure and lower R((S+L)/G). The general mass transfer model with higher regression coefficients (R(2)>0.97) fitted the kinetic data better than the Fick's second law diffusion model. As compared with CAW, the time (t(*)) to reach the y(*) of anthocyanins using HPCD was reduced by half while its corresponding overall volumetric mass transfer coefficients k(L)xa from the general mass transfer model increased by two folds. Copyright 2010 Elsevier Ltd. All rights reserved.

Morphology of viscoplastic drop impact on viscoplastic surfaces.

PubMed

Chen, Simeng; Bertola, Volfango

2017-01-25

The impact of viscoplastic drops onto viscoplastic substrates characterized by different magnitudes of the yield stress is investigated experimentally. The interaction between viscoplastic drops and surfaces has an important application in additive manufacturing, where a fresh layer of material is deposited on a partially cured or dried layer of the same material. So far, no systematic studies on this subject have been reported in literature. The impact morphology of different drop/substrate combinations, with yield stresses ranging from 1.13 Pa to 11.7 Pa, was studied by high speed imaging for impact Weber numbers between 15 and 85. Experimental data were compared with one of the existing models for Newtonian drop impact onto liquid surfaces. Results show the magnitude of the yield stress of drop/substrate strongly affects the final shape of the impacting drop, permanently deformed at the end of impact. The comparison between experimental data and model predictions suggests the crater evolution model is only valid when predicting the evolution of the crater at sufficiently high Weber numbers.

Application of a Full Reynolds Stress Model to High Lift Flows

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Eisfeld, B.

2016-01-01

A recently developed second-moment Reynolds stress model was applied to two challenging high-lift flows: (1) transonic flow over the ONERA M6 wing, and (2) subsonic flow over the DLR-F11 wing-body configuration from the second AIAA High Lift Prediction Workshop. In this study, the Reynolds stress model results were contrasted with those obtained from one- and two{equation turbulence models, and were found to be competitive in terms of the prediction of shock location and separation. For an ONERA M6 case, results from multiple codes, grids, and models were compared, with the Reynolds stress model tending to yield a slightly smaller shock-induced separation bubble near the wing tip than the simpler models, but all models were fairly close to the limited experimental surface pressure data. For a series of high-lift DLR{F11 cases, the range of results was more limited, but there was indication that the Reynolds stress model yielded less-separated results than the one-equation model near maximum lift. These less-separated results were similar to results from the one-equation model with a quadratic constitutive relation. Additional computations need to be performed before a more definitive assessment of the Reynolds stress model can be made.

Estimation of total nitrogen and total phosphorus in streams of the Middle Columbia River Basin (Oregon, Washington, and Idaho) using SPARROW models, with emphasis on the Yakima River Basin, Washington

USGS Publications Warehouse

Johnson, Henry M.; Black, Robert W.; Wise, Daniel R.

2013-01-01

The watershed model SPARROW (Spatially Related Regressions on Watershed attributes) was used to predict total nitrogen (TN) and total phosphorus (TP) loads and yields for the Middle Columbia River Basin in Idaho, Oregon, and Washington. The new models build on recently published models for the entire Pacific Northwest, and provide revised load predictions for the arid interior of the region by restricting the modeling domain and recalibrating the models. Results from the new TN and TP models are provided for the entire region, and discussed with special emphasis on the Yakima River Basin, Washington. In most catchments of the Yakima River Basin, the TN and TP in streams is from natural sources, specifically nitrogen fixation in forests (TN) and weathering and erosion of geologic materials (TP). The natural nutrient sources are overshadowed by anthropogenic sources of TN and TP in highly agricultural and urbanized catchments; downstream of the city of Yakima, most of the load in the Yakima River is derived from anthropogenic sources. Yields of TN and TP from catchments with nearly uniform land use were compared with other yield values and export coefficients published in the scientific literature, and generally were in agreement. The median yield of TN was greatest in catchments dominated by agricultural land and smallest in catchments dominated by grass and scrub land. The median yield of TP was greatest in catchments dominated by forest land, but the largest yields (90th percentile) of TP were from agricultural catchments. As with TN, the smallest TP yields were from catchments dominated by grass and scrub land.

Bridging the gap between feedstock growers and users: the study of a coppice poplar-based biorefinery.

PubMed

Dou, Chang; Gustafson, Rick; Bura, Renata

2018-01-01

In the biofuel industry, land productivity is important to feedstock growers and conversion process product yield is important to the biorefinery. The crop productivity, however, may not positively correlate with bioconversion yield. Therefore, it is important to evaluate sugar yield and biomass productivity. In this study, 2-year-old poplar trees harvested in the first coppice cycle, including one low-productivity hybrid and one high-productivity hybrid, were collected from two poplar tree farms. Through steam pretreatment and enzymatic hydrolysis, the bioconversion yields of low- and high-productivity poplar hybrids were compared for both sites. The low-productivity hybrids had 9-19% higher sugar yields than the high-productivity hybrids, although they have the similar chemical composition. Economic calculations show the impact on the plantation and biorefinery of using the two feedstocks. Growing a high-productivity hybrid means the land owner would use 11-26% less land (which could be used for other crops) or collect $2.53-$3.46 MM/year extra revenue from the surplus feedstock. On the other side, the biorefinery would receive 5-10% additional revenue using the low-productivity hybrid. We propose a business model based on the integration of the plantation and the biorefinery. In this model, different feedstocks are assessed using a metric of product tonnage per unit land per year. Use of this new economic metric bridges the gap between feedstock growers and users to maximize the overall production efficiency.

High Useful Yield and Isotopic Analysis of Uranium by Resonance Ionization Mass Spectrometry

DOE PAGES

Savina, Michael R.; Isselhardt, Brett H.; Kucher, Andrew; ...

2017-05-09

Useful yields from resonance ionization mass spectrometry can be extremely high compared to other mass spectrometry techniques, but uranium analysis shows strong matrix effects arising from the tendency of uranium to form strongly bound oxide molecules that do not dissociate appreciably on energetic ion bombardment. Here, we demonstrate a useful yield of 24% for metallic uranium. Modeling the laser ionization and ion transmission processes shows that the high useful yield is attributable to a high ion fraction achieved by resonance ionization. We quantify the reduction of uranium oxide surface layers by Ar + and Ga + sputtering. The useful yieldmore » for uranium atoms from a uranium dioxide matrix is 0.4% and rises to 2% when the surface is in sputter equilibrium with the ion beam. The lower useful yield from the oxide is almost entirely due to uranium oxide molecules reducing the neutral atom content of the sputtered flux. We also demonstrate rapid isotopic analysis of solid uranium oxide at a precision of <0.5% relative standard deviation using relatively broadband lasers to mitigate spectroscopic fractionation.« less

High Useful Yield and Isotopic Analysis of Uranium by Resonance Ionization Mass Spectrometry

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

Savina, Michael R.; Isselhardt, Brett H.; Kucher, Andrew

Useful yields from resonance ionization mass spectrometry can be extremely high compared to other mass spectrometry techniques, but uranium analysis shows strong matrix effects arising from the tendency of uranium to form strongly bound oxide molecules that do not dissociate appreciably on energetic ion bombardment. Here, we demonstrate a useful yield of 24% for metallic uranium. Modeling the laser ionization and ion transmission processes shows that the high useful yield is attributable to a high ion fraction achieved by resonance ionization. We quantify the reduction of uranium oxide surface layers by Ar + and Ga + sputtering. The useful yieldmore » for uranium atoms from a uranium dioxide matrix is 0.4% and rises to 2% when the surface is in sputter equilibrium with the ion beam. The lower useful yield from the oxide is almost entirely due to uranium oxide molecules reducing the neutral atom content of the sputtered flux. We also demonstrate rapid isotopic analysis of solid uranium oxide at a precision of <0.5% relative standard deviation using relatively broadband lasers to mitigate spectroscopic fractionation.« less

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

PubMed

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

2016-04-29

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

Analysis of the efficacy and cost-effectiveness of best management practices for controlling sediment yield: A case study of the Joumine watershed, Tunisia.

PubMed

Mtibaa, Slim; Hotta, Norifumi; Irie, Mitsuteru

2018-03-01

Soil erosion can be reduced through the strategic selection and placement of best management practices (BMPs) in critical source areas (CSAs). In the present study, the Soil Water Assessment Tool (SWAT) model was used to identify CSAs and investigate the effectiveness of different BMPs in reducing sediment yield in the Joumine watershed, an agricultural river catchment located in northern Tunisia. A cost-benefit analysis (CBA) was used to evaluate the cost-effectiveness of different BMP scenarios. The objective of the present study was to determine the most cost-effective management scenario for controlling sediment yield. The model performance for the simulation of streamflow and sediment yield at the outlet of the Joumine watershed was good and satisfactory, respectively. The model indicated that most of the sediment was originated from the cultivated upland area. About 34% of the catchment area consisted of CSAs that were affected by high to very high soil erosion risk (sediment yield >10t/ha/year). Contour ridges were found to be the most effective individual BMP in terms of sediment yield reduction. At the watershed level, implementing contour ridges in the CSAs reduced sediment yield by 59%. Combinations of BMP scenarios were more cost-effective than the contour ridges alone. Combining buffer strips (5-m width) with other BMPs depending on land slope (> 20% slope: conversion to olive orchards; 10-20% slope: contour ridges; 5-10% slope: grass strip cropping) was the most effective approach in terms of sediment yield reduction and economic benefits. This approach reduced sediment yield by 61.84% with a benefit/cost ratio of 1.61. Compared with the cost of dredging, BMPs were more cost-effective for reducing sediment loads to the Joumine reservoir, located downstream of the catchment. Our findings may contribute to ensure the sustainability of future conservation programs in Tunisian regions. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Sorghum production under future climate in the Southwestern USA: model projections of yield, greenhouse gas emissions and soil C fluxes

NASA Astrophysics Data System (ADS)

Duval, B.; Ghimire, R.; Hartman, M. D.; Marsalis, M.

2016-12-01

Large tracts of semi-arid land in the Southwestern USA are relatively less important for food production than the US Corn Belt, and represent a promising area for expansion of biofuel/bioproduct crops. However, high temperatures, low available water and high solar radiation in the SW represent a challenge to suitable feedstock development, and future climate change scenarios predict that portions of the SW will experience increased temperature and temporal shifts in precipitation distribution. Sorghum (Sorghum bicolor) is a valuable forage crop with promise as a biofuel feedstock, given its high biomass under semi-arid conditions, relatively lower N fertilizer requirements compared to corn, and salinity tolerance. To evaluate the environmental impact of expanded sorghum cultivation under future climate in the SW USA, we used the DayCent model in concert with a suite of downscaled future weather projections to predict biogeochemical consequences (greenhouse gas flux and impacts on soil carbon) of sorghum cultivation in New Mexico. The model showed good correspondence with yield data from field trials including both dryland and irrigated sorghum (measured vs. modeled; r2 = 0.75). Simulation experiments tested the effect of dryland production versus irrigation, low N versus high N inputs and delayed fertilizer application. Nitrogen application timing and irrigation impacted yield and N2O emissions less than N rate and climate. Across N and irrigation treatments, future climate simulations resulted in 6% increased yield and 20% lower N2O emissions compared to current climate. Soil C pools declined under future climate. The greatest declines in soil C were from low N input sorghum simulations, regardless of irrigation (>20% declines in SOM in both cases), and requires further evaluation to determine if changing future climate is driving these declines, or if they are a function of prolonged sorghum-fallow rotations in the model. The relatively small gain in yield for irrigated sorghum, and strong control of N rate on N2O emissions suggests that a dryland sorghum bioproduct system could be environmentally sustainable in the Southwestern US with effective N management, and warrants further investigation in field trials.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

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.

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

PubMed

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

2015-05-01

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

Initial yield to depth relation for water wells drilled into crystalline bedrock - Pinardville quadrangle, New Hampshire

USGS Publications Warehouse

Drew, L.J.; Schuenemeyer, J.H.; Amstrong, T.R.; Sutphin, D.M.

2001-01-01

A model is proposed to explain the statistical relations between the mean initial water well yields from eight time increments from 1984 to 1998 for wells drilled into the crystalline bedrock aquifer system in the Pinardville area of southern New Hampshire and the type of bedrock, mean well depth, and mean well elevation. Statistical analyses show that the mean total yield of drilling increments is positively correlated with mean total well depth and mean well elevation. In addition, the mean total well yield varies with rock type from a minimum of 46.9 L/min (12.4 gpm) in the Damon Pond granite to a maximum of 74.5 L/min (19.7 gpm) in the Permian pegmatite and granite unit. Across the eight drilling increments that comprise 211 wells each, the percentages of very low-yield wells (1.9 L/min [0.5 gpm] or less) and high-yield wells (151.4 L/min [40 gpm] or more) increased, and those of intermediate-yield wells decreased. As housing development progressed during the 1984 to 1998 interval, the mean depth of the wells and their elevations increased, and the mix of percentages of the bedrock types drilled changed markedly. The proposed model uses a feed-forward mechanism to explain the interaction between the increasing mean elevation, mean well depth, and percentages of very low-yielding wells and the mean well yield. The increasing percentages of very low-yielding wells through time and the economics of the housing market may control the system that forces the mean well depths, percentages of high-yield wells, and mean well yields to increase. The reason for the increasing percentages of very low-yield wells is uncertain, but the explanation is believed to involve the complex structural geology and tectonic history of the Pinardville quadrangle.

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.

Mapping intra-field yield variation using high resolution satellite imagery to integrate bioenergy and environmental stewardship in an agricultural watershed

DOE PAGES

Hamada, Yuki; Ssegane, Herbert; Negri, Maria Cristina

2015-07-31

Biofuels are important alternatives for meeting our future energy needs. Successful bioenergy crop production requires maintaining environmental sustainability and minimum impacts on current net annual food, feed, and fiber production. The objectives of this study were to: (1) determine under-productive areas within an agricultural field in a watershed using a single date; high resolution remote sensing and (2) examine impacts of growing bioenergy crops in the under-productive areas using hydrologic modeling in order to facilitate sustainable landscape design. Normalized difference indices (NDIs) were computed based on the ratio of all possible two-band combinations using the RapidEye and the National Agriculturalmore » Imagery Program images collected in summer 2011. A multiple regression analysis was performed using 10 NDIs and five RapidEye spectral bands. The regression analysis suggested that the red and near infrared bands and NDI using red-edge and near infrared that is known as the red-edge normalized difference vegetation index (RENDVI) had the highest correlation (R 2 = 0.524) with the reference yield. Although predictive yield map showed striking similarity to the reference yield map, the model had modest correlation; thus, further research is needed to improve predictive capability for absolute yields. Forecasted impact using the Soil and Water Assessment Tool model of growing switchgrass ( Panicum virgatum) on under-productive areas based on corn yield thresholds of 3.1, 4.7, and 6.3 Mg·ha -1 showed reduction of tile NO 3-N and sediment exports by 15.9%–25.9% and 25%–39%, respectively. Corresponding reductions in water yields ranged from 0.9% to 2.5%. While further research is warranted, the study demonstrated the integration of remote sensing and hydrologic modeling to quantify the multifunctional value of projected future landscape patterns in a context of sustainable bioenergy crop production.« less

Mapping intra-field yield variation using high resolution satellite imagery to integrate bioenergy and environmental stewardship in an agricultural watershed

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

Hamada, Yuki; Ssegane, Herbert; Negri, Maria Cristina

Biofuels are important alternatives for meeting our future energy needs. Successful bioenergy crop production requires maintaining environmental sustainability and minimum impacts on current net annual food, feed, and fiber production. The objectives of this study were to: (1) determine under-productive areas within an agricultural field in a watershed using a single date; high resolution remote sensing and (2) examine impacts of growing bioenergy crops in the under-productive areas using hydrologic modeling in order to facilitate sustainable landscape design. Normalized difference indices (NDIs) were computed based on the ratio of all possible two-band combinations using the RapidEye and the National Agriculturalmore » Imagery Program images collected in summer 2011. A multiple regression analysis was performed using 10 NDIs and five RapidEye spectral bands. The regression analysis suggested that the red and near infrared bands and NDI using red-edge and near infrared that is known as the red-edge normalized difference vegetation index (RENDVI) had the highest correlation (R 2 = 0.524) with the reference yield. Although predictive yield map showed striking similarity to the reference yield map, the model had modest correlation; thus, further research is needed to improve predictive capability for absolute yields. Forecasted impact using the Soil and Water Assessment Tool model of growing switchgrass ( Panicum virgatum) on under-productive areas based on corn yield thresholds of 3.1, 4.7, and 6.3 Mg·ha -1 showed reduction of tile NO 3-N and sediment exports by 15.9%–25.9% and 25%–39%, respectively. Corresponding reductions in water yields ranged from 0.9% to 2.5%. While further research is warranted, the study demonstrated the integration of remote sensing and hydrologic modeling to quantify the multifunctional value of projected future landscape patterns in a context of sustainable bioenergy crop production.« less

Curved-flow, rolling-flow, and oscillatory pure-yawing wind-tunnel test methods for determination of dynamic stability derivatives

NASA Technical Reports Server (NTRS)

Chambers, J. R.; Grafton, S. B.; Lutze, F. H.

1981-01-01

Dynamic stability derivatives are evaluated on the basis of rolling-flow, curved-flow and snaking tests. Attention is given to the hardware associated with curved-flow, rolling-flow and oscillatory pure-yawing wind-tunnel tests. It is found that the snaking technique, when combined with linear- and forced-oscillation methods, yields an important method for evaluating beta derivatives for current configurations at high angles of attack. Since the rolling flow model is fixed during testing, forced oscillations may be imparted to the model, permitting the measurement of damping and cross-derivatives. These results, when coupled with basic rolling-flow or rotary-balance data, yield a highly accurate mathematical model for studies of incipient spin and spin entry.

A thermalized ion explosion model for high energy sputtering and track registration

NASA Technical Reports Server (NTRS)

Seiberling, L. E.; Griffith, J. E.; Tombrello, T. A.

1980-01-01

A velocity spectrum of neutral sputtered particles as well as a low resolution mass spectrum of sputtered molecular ions was measured for 4.74 MeV F-19(+2) incident of UF4. The velocity spectrum is dramatically different from spectra taken with low energy (keV) bombarding ions, and is shown to be consistent with a hot plasma of atoms in thermal equilibrium inside the target. A thermalized ion explosion model is proposed for high energy sputtering which is expected to describe track formation in dielectric materials. The model is shown to be consistent with the observed total sputtering yield and the dependence of the yield on the primary ionization rate of the incident ion.

Data error and highly parameterized groundwater models

USGS Publications Warehouse

Hill, M.C.

2008-01-01

Strengths and weaknesses of highly parameterized models, in which the number of parameters exceeds the number of observations, are demonstrated using a synthetic test case. Results suggest that the approach can yield close matches to observations but also serious errors in system representation. It is proposed that avoiding the difficulties of highly parameterized models requires close evaluation of: (1) model fit, (2) performance of the regression, and (3) estimated parameter distributions. Comparisons to hydrogeologic information are expected to be critical to obtaining credible models. Copyright ?? 2008 IAHS Press.

Human impact on sediment fluxes within the Blue Nile and Atbara River basins

NASA Astrophysics Data System (ADS)

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

2013-01-01

A regional assessment of the spatial variability in sediment yields allows filling the gap between detailed, process-based understanding of erosion at field scale and empirical sediment flux models at global scale. In this paper, we focus on the intrabasin variability in sediment yield within the Blue Nile and Atbara basins as biophysical and anthropogenic factors are presumably acting together to accelerate soil erosion. The Blue Nile and Atbara River systems are characterized by an important spatial variability in sediment fluxes, with area-specific sediment yield (SSY) values ranging between 4 and 4935 t/km2/y. Statistical analyses show that 41% of the observed variation in SSY can be explained by remote sensing proxy data of surface vegetation cover, rainfall intensity, mean annual temperature, and human impact. The comparison of a locally adapted regression model with global predictive sediment flux models indicates that global flux models such as the ART and BQART models are less suited to capture the spatial variability in area-specific sediment yields (SSY), but they are very efficient to predict absolute sediment yields (SY). We developed a modified version of the BQART model that estimates the human influence on sediment yield based on a high resolution composite measure of local human impact (human footprint index) instead of countrywide estimates of GNP/capita. Our modified version of the BQART is able to explain 80% of the observed variation in SY for the Blue Nile and Atbara basins and thereby performs only slightly less than locally adapted regression models.

Evolution of plastic anisotropy for high-strain-rate computations

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

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

1994-12-01

A model for anisotropic material strength, and for changes in the anisotropy due to plastic strain, is described. This model has been developed for use in high-rate, explicit, Lagrangian multidimensional continuum-mechanics codes. The model handles anisotropies in single-phase materials, in particular the anisotropies due to crystallographic texture--preferred orientations of the single-crystal grains. Textural anisotropies, and the changes in these anisotropies, depend overwhelmingly no the crystal structure of the material and on the deformation history. The changes, particularly for a complex deformations, are not amenable to simple analytical forms. To handle this problem, the material model described here includes a texturemore » code, or micromechanical calculation, coupled to a continuum code. The texture code updates grain orientations as a function of tensor plastic strain, and calculates the yield strength in different directions. A yield function is fitted to these yield points. For each computational cell in the continuum simulation, the texture code tracks a particular set of grain orientations. The orientations will change due to the tensor strain history, and the yield function will change accordingly. Hence, the continuum code supplies a tensor strain to the texture code, and the texture code supplies an updated yield function to the continuum code. Since significant texture changes require relatively large strains--typically, a few percent or more--the texture code is not called very often, and the increase in computer time is not excessive. The model was implemented, using a finite-element continuum code and a texture code specialized for hexagonal-close-packed crystal structures. The results for several uniaxial stress problems and an explosive-forming problem are shown.« less

Spallation of Cu by 500- and 1570-MeV. pi. /sup -/

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

Haustein, P.E.; Ruth, T.J.

1978-11-01

Relative yields of 36 products extending from /sup 7/Be to /sup 65/Zn have been measured for the interaction of 500- and 1570-MeV negative pions with Cu. These results are compared with calculations from the ISOBAR model, with earlier studies of Cu spallation with lower (resonance) energy pions, energetic protons, and heavy ions. Relative yield patterns at both ..pi../sup -/ energies show only slight differences when compared to spallation by protons of comparable energy. Calculations from the ISOBAR model adequately reproduce the shapes of the mass yield and charge yield of the experimental data for 500-MeV ..pi../sup -/. The calculation, however,more » overestimates the yield of neutron-rich isotopes from deep spallation. At the 1570-MeV ..pi../sup -/ energy the yield patterns, charge-dispersion, and mass-yield curves are nearly identical to those for 2-GeV proton spallation. These results suggest that pion-nucleon resonance effects probably decrease at higher energies and that limiting fragmentation and factorization concepts may be applied to understanding high-energy pion spallation.« less

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials

PubMed Central

2018-01-01

Objective The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. Conclusion These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins. PMID:28823122

Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials.

PubMed

Ben Zaabza, Hafedh; Ben Gara, Abderrahmen; Rekik, Boulbaba

2018-05-01

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from 0.78±0.01 to 0.82±0.03, between the first and second parities, from 0.73±0.03 to 0.8±0.04 between the first and third parities, and from 0.82±0.02 to 0.84±0.04 between the second and third parities. These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

NASA Technical Reports Server (NTRS)

Ponomarev, Artem; Cucinotta, F.

2011-01-01

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

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.

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

NASA Astrophysics Data System (ADS)

Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

2018-04-01

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

Estimates of spatial and temporal variation of energy crops biomass yields in the US

NASA Astrophysics Data System (ADS)

Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

2013-12-01

Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors. For example, the yield in HS zone is depended on soil and topography factors. However, the yields in HU zone are more controlled by climate factors, leading to a large uncertainty in yield potential of bioenergy grasses under future climate change.

Integrated modeling of cryogenic layered highfoot experiments at the NIF

NASA Astrophysics Data System (ADS)

Kritcher, A. L.; Hinkel, D. E.; Callahan, D. A.; Hurricane, O. A.; Clark, D.; Casey, D. T.; Dewald, E. L.; Dittrich, T. R.; Döppner, T.; Barrios Garcia, M. A.; Haan, S.; Berzak Hopkins, L. F.; Jones, O.; Landen, O.; Ma, T.; Meezan, N.; Milovich, J. L.; Pak, A. E.; Park, H.-S.; Patel, P. K.; Ralph, J.; Robey, H. F.; Salmonson, J. D.; Sepke, S.; Spears, B.; Springer, P. T.; Thomas, C. A.; Town, R.; Celliers, P. M.; Edwards, M. J.

2016-05-01

Integrated radiation hydrodynamic modeling in two dimensions, including the hohlraum and capsule, of layered cryogenic HighFoot Deuterium-Tritium (DT) implosions on the NIF successfully predicts important data trends. The model consists of a semi-empirical fit to low mode asymmetries and radiation drive multipliers to match shock trajectories, one dimensional inflight radiography, and time of peak neutron production. Application of the model across the HighFoot shot series, over a range of powers, laser energies, laser wavelengths, and target thicknesses predicts the neutron yield to within a factor of two for most shots. The Deuterium-Deuterium ion temperatures and the DT down scattered ratios, ratio of (10-12)/(13-15) MeV neutrons, roughly agree with data at peak fuel velocities <340 km/s and deviate at higher peak velocities, potentially due to flows and neutron scattering differences stemming from 3D or capsule support tent effects. These calculations show a significant amount alpha heating, 1-2.5× for shots where the experimental yield is within a factor of two, which has been achieved by increasing the fuel kinetic energy. This level of alpha heating is consistent with a dynamic hot spot model that is matched to experimental data and as determined from scaling of the yield with peak fuel velocity. These calculations also show that low mode asymmetries become more important as the fuel velocity is increased, and that improving these low mode asymmetries can result in an increase in the yield by a factor of several.

Continuous Flow Aerobic Alcohol Oxidation Reactions Using a Heterogeneous Ru(OH)x/Al2O3 Catalyst

PubMed Central

2015-01-01

Ru(OH)x/Al2O3 is among the more versatile catalysts for aerobic alcohol oxidation and dehydrogenation of nitrogen heterocycles. Here, we describe the translation of batch reactions to a continuous-flow method that enables high steady-state conversion and single-pass yields in the oxidation of benzylic alcohols and dehydrogenation of indoline. A dilute source of O2 (8% in N2) was used to ensure that the reaction mixture, which employs toluene as the solvent, is nonflammable throughout the process. A packed bed reactor was operated isothermally in an up-flow orientation, allowing good liquid–solid contact. Deactivation of the catalyst during the reaction was modeled empirically, and this model was used to achieve high conversion and yield during extended operation in the aerobic oxidation of 2-thiophene methanol (99+% continuous yield over 72 h). PMID:25620869

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.

Asymmetric Yield Function Based on the Stress Invariants for Pressure Sensitive Metals

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

Jeong Wahn Yoon; Yanshan Lou; Jong Hun Yoon

A general asymmetric yield function is proposed with dependence on the stress invariants for pressure sensitive metals. The pressure sensitivity of the proposed yield function is consistent with the experimental result of Spitzig and Richmond (1984) for steel and aluminum alloys while the asymmetry of the third invariant is preserved to model strength differential (SD) effect of pressure insensitive materials. The proposed yield function is transformed in the space of the stress triaxaility, the von Mises stress and the normalized invariant to theoretically investigate the possible reason of the SD effect. The proposed plasticity model is further extended to characterizemore » the anisotropic behavior of metals both in tension and compression. The extension of the yield function is realized by introducing two distinct fourth-order linear transformation tensors of the stress tensor for the second and third invariants, respectively. The extended yield function reasonably models the evolution of yield surfaces for a zirconium clock-rolled plate during in-plane and through-thickness compression reported by Plunkett et al. (2007). The extended yield function is also applied to describe the orthotropic behavior of a face-centered cubic metal of AA 2008-T4 and two hexagonal close-packed metals of high-purity-titanium and AZ31 magnesium alloy. The orthotropic behavior predicted by the generalized model is compared with experimental results of these metals. The comparison validates that the proposed yield function provides sufficient predictability on SD effect and anisotropic behavior both in tension and compression. When it is necessary to consider r-value anisotropy, the proposed function is efficient to be used with nonassociated flow plasticity by introducing a separate plastic potential for the consideration of r-values as shown in Stoughton & Yoon (2004, 2009).« less

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.

Long-range climate impacts on crop yield and the implications of enacting global carbon mitigation policies

EPA Science Inventory

Research on climate impacts and agriculture over the past two decades has applied simulation models at a range of scales and future climate scenarios, finding that crop growth and yield responds to changing climate conditions, and that the impacts are regional and highly depende...

A data-oriented semi-process model for evaluating the yields of major crops at global scale (PRYSBI-2)

NASA Astrophysics Data System (ADS)

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

2013-12-01

Demand for major cereal crops will double by 2050 compared to the amount in 2005 due to the population growth, dietary change, and increase in biofuel use. This requires substantial efforts to increase crop yields under changing climate, water resources, and land use. In order to explore possible paths to meet the supply target, global crop modeling is a useful approach. To that end, we developed a process-based large-area crop model (called PRYSBIE-2) for major crops, including soybean. This model consisted of the enzyme kinetics model for photosynthetic carbon assimilation and soil water balance model from SWAT. The parameter values on water stress, nitrogen stress were calibrated over global croplands from one grid cell to another (1.125° in latitude and longitude) using Markov Chain Monte Carlo (MCMC) methods. The historical yield data collected from major crop-producing countries on a state, county, or prefecture scale were used as the calibration data. Then we obtained the model parameter sets that can give high correlation coefficients between the historical and estimated yield time series for the period 1980-2006. We analyzed the impacts on soybean yields in the three top soybean-producing countries (the USA, China, and Brazil) associated with the changes in climate and CO2 during the period 1980-2006, using the model. We found that, given the simulated yields and reported harvested areas, the estimated average net benefit from the CO2 fertilization effect (with one standard deviation) in the USA, Brazil, and China in the years was 42.70×32.52 Mt, 35.30×28.55 Mt, and 12.52×15.11 Mt, respectively. Results suggest that the CO2-induced increases in soybean yields in the USA and China likely offset a part of the negative impacts on yields due to the historical temperature rise. In contrast, the net effect of the past change in climate and CO2 in Brazil appeared to be positive. This study demonstrates a quantitative estimation of the impacts of the changes in climate and CO2 during the past few decades using a new global crop model.

Dynamic consideration of smog chamber experiments

NASA Astrophysics Data System (ADS)

Chuang, Wayne K.; Donahue, Neil M.

2017-08-01

Recent studies of the α-pinene + ozone reaction that address particle nucleation show relatively high molar yields of highly oxidized multifunctional organic molecules with very low saturation concentrations that can form and grow new particles on their own. However, numerous smog-chamber experiments addressing secondary organic aerosol (SOA) mass yields, interpreted via equilibrium partitioning theory, suggest that the vast majority of SOA from α-pinene is semivolatile. We explore this paradox by employing a dynamic volatility basis set (VBS) model that reproduces the new-particle growth rates observed in the CLOUD experiment at CERN and then modeling SOA mass yield experiments conducted at Carnegie Mellon University (CMU). We find that the base-case simulations do overpredict observed SOA mass but by much less than an equilibrium analysis would suggest; this is because delayed condensation of vapors suppresses the apparent mass yields early in the chamber experiments. We further find that a second VBS model featuring substantial oligomerization of semivolatile monomers can match the CLOUD growth rates with substantially lower SOA mass yields; this is because the lighter monomers have a higher velocity and thus a higher condensation rate for a given mass concentration. The oligomerization simulations are a closer match to the CMU experiments than the base-case simulations, though they overpredict the observations somewhat. However, we also find that if the chemical conditions in CLOUD and the CMU chamber were identical, substantial nucleation would have occurred in the CMU experiments when in fact none occurred. This suggests that the chemical mechanisms differed in the two experiments, perhaps because the high oxidation rates in the SOA formation experiments led to rapid termination of peroxy radical chemistry.

Cosmological implications of baryon acoustic oscillation measurements

DOE PAGES

Aubourg, Eric

2015-12-01

Here, we derive constraints on cosmological parameters and tests of dark energy models from the combination of baryon acoustic oscillation (BAO) measurements with cosmic microwave background (CMB) data and a recent reanalysis of Type Ia supernova (SN) data. Particularly, we take advantage of high-precision BAO measurements from galaxy clustering and the Lyman-α forest (LyaF) in the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Treating the BAO scale as an uncalibrated standard ruler, BAO data alone yield a high confidence detection of dark energy; in combination with the CMB angular acoustic scale they further imply a nearly flat universe. Adding the CMB-calibratedmore » physical scale of the sound horizon, the combination of BAO and SN data into an “inverse distance ladder” yields a measurement of H 0=67.3±1.1 km s -1 Mpc -1, with 1.7% precision. This measurement assumes standard prerecombination physics but is insensitive to assumptions about dark energy or space curvature, so agreement with CMB-based estimates that assume a flat ΛCDM cosmology is an important corroboration of this minimal cosmological model. For constant dark energy (Λ), our BAO+SN+CMB combination yields matter density Ω m=0.301±0.008 and curvature Ω k=-0.003±0.003. When we allow more general forms of evolving dark energy, the BAO+SN+CMB parameter constraints are always consistent with flat ΛCDM values at ≈1σ. And while the overall χ 2 of model fits is satisfactory, the LyaF BAO measurements are in moderate (2–2.5σ) tension with model predictions. Models with early dark energy that tracks the dominant energy component at high redshift remain consistent with our expansion history constraints, and they yield a higher H 0 and lower matter clustering amplitude, improving agreement with some low redshift observations. Expansion history alone yields an upper limit on the summed mass of neutrino species, Σm ν<0.56 eV (95% confidence), improving to Σm ν<0.25 eV if we include the lensing signal in the Planck CMB power spectrum. In a flat ΛCDM model that allows extra relativistic species, our data combination yields N eff=3.43±0.26; while the LyaF BAO data prefer higher Neff when excluding galaxy BAO, the galaxy BAO alone favor N eff≈3. Finally, when structure growth is extrapolated forward from the CMB to low redshift, standard dark energy models constrained by our data predict a level of matter clustering that is high compared to most, but not all, observational estimates.« less

Quantifying yield gaps in wheat production in Russia

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

Technologies Enabling Scientific Exploration of Asteroids and Moons

NASA Astrophysics Data System (ADS)

Shaw, A.; Fulford, P.; Chappell, L.

2016-12-01

Scientific exploration of moons and asteroids is enabled by several key technologies that yield topographic information, allow excavation of subsurface materials, and allow delivery of higher-mass scientific payloads to moons and asteroids. These key technologies include lidar systems, robotics, and solar-electric propulsion spacecraft buses. Many of these technologies have applications for a variety of planetary targets. Lidar systems yield high-resolution shape models of asteroids and moons. These shape models can then be combined with radio science information to yield insight into density and internal structure. Further, lidar systems allow investigation of topographic surface features, large and small, which yields information on regolith properties. Robotic arms can be used for a variety of purposes, especially to support excavation, revealing subsurface material and acquiring material from depth for either in situ analysis or sample return. Robotic arms with built-in force sensors can also be used to gauge the strength of materials as a function of depth, yielding insight into regolith physical properties. Mobility systems allow scientific exploration of multiple sites, and also yield insight into regolith physical properties due to the interaction of wheels with regolith. High-power solar electric propulsion (SEP) spacecraft bus systems allow more science instruments to be included on missions given their ability to support greater payload mass. In addition, leveraging a cost-effective commercially-built SEP spacecraft bus can significantly reduce mission cost.

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.

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

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.

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.

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

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;

The effect of level of feeding, genetic merit, body condition score and age on biological parameters of a mammary gland model.

PubMed

Bryant, J R; Lopez-Villalobos, N; Holmes, C W; Pryce, J E; Pitman, G D; Davis, S R

2007-03-01

An evolutionary algorithm was applied to a mechanistic model of the mammary gland to find the parameter values that minimised the difference between predicted and actual lactation curves of milk yields in New Zealand Jersey cattle managed at different feeding levels. The effect of feeding level, genetic merit, body condition score at parturition and age on total lactation yields of milk, fat and protein, days in milk, live weight and evolutionary algorithm derived mammary gland parameters was then determined using a multiple regression model. The mechanistic model of the mammary gland was able to fit lactation curves that corresponded to actual lactation curves with a high degree of accuracy. The senescence rate of quiescent (inactive) alveoli was highest at the very low feeding level. The active alveoli population at peak lactation was highest at very low feeding levels, but lower nutritional status at this feeding level prevented high milk yields from being achieved. Genetic merit had a significant linear effect on the active alveoli population at peak and mid to late lactation, with higher values in animals, which had higher breeding values for milk yields. A type of genetic merit × feeding level scaling effect was observed for total yields of milk and fat, and total number of alveoli produced from conception until the end of lactation with the benefits of increases in genetic merit being greater at high feeding levels. A genetic merit × age scaling effect was observed for total lactation protein yields. Initial rates of differentiation of progenitor cells declined with age. Production levels of alveoli from conception to the end of lactation were lowest in 5- to 8-year-old animals; however, in these older animals, quiescent alveoli were reactivated more frequently. The active alveoli population at peak lactation and rates of active alveoli proceeding to quiescence were highest in animals of intermediate body condition scores of 4.0 to 5.0. The results illustrate the potential uses of a mechanistic model of the mammary gland to fit a lactation curve and to quantify the effects of feeding level, genetic merit, body condition score, and age on mammary gland dynamics throughout lactation.

Integrated model for predicting rice yield with climate change

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Application of artificial intelligent tools to modeling of glucosamine preparation from exoskeleton of shrimp.

PubMed

Valizadeh, Hadi; Pourmahmood, Mohammad; Mojarrad, Javid Shahbazi; Nemati, Mahboob; Zakeri-Milani, Parvin

2009-04-01

The objective of this study was to forecast and optimize the glucosamine production yield from chitin (obtained from Persian Gulf shrimp) by means of genetic algorithm (GA), particle swarm optimization (PSO), and artificial neural networks (ANNs) as tools of artificial intelligence methods. Three factors (acid concentration, acid solution to chitin ratio, and reaction time) were used as the input parameters of the models investigated. According to the obtained results, the production yield of glucosamine hydrochloride depends linearly on acid concentration, acid solution to solid ratio, and time and also the cross-product of acid concentration and time and the cross-product of solids to acid solution ratio and time. The production yield significantly increased with an increase of acid concentration, acid solution ratio, and reaction time. The production yield is inversely related to the cross-product of acid concentration and time. It means that at high acid concentrations, the longer reaction times give lower production yields. The results revealed that the average percent error (PE) for prediction of production yield by GA, PSO, and ANN are 6.84, 7.11, and 5.49%, respectively. Considering the low PE, it might be concluded that these models have a good predictive power in the studied range of variables and they have the ability of generalization to unknown cases.

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.

Relationships between milk culture results and milk yield in Norwegian dairy cattle.

PubMed

Reksen, O; Sølverød, L; Østerås, O

2007-10-01

Associations between test-day milk yield and positive milk cultures for Staphylococcus aureus, Streptococcus spp., and other mastitis pathogens or a negative milk culture for mastitis pathogens were assessed in quarter milk samples from randomly sampled cows selected without regard to current or previous udder health status. Staphylococcus aureus was dichotomized according to sparse (< or =1,500 cfu/mL of milk) or rich (>1,500 cfu/mL of milk) growth of the bacteria. Quarter milk samples were obtained on 1 to 4 occasions from 2,740 cows in 354 Norwegian dairy herds, resulting in a total of 3,430 samplings. Measures of test-day milk yield were obtained monthly and related to 3,547 microbiological diagnoses at the cow level. Mixed model linear regression models incorporating an autoregressive covariance structure accounting for repeated test-day milk yields within cow and random effects at the herd and sample level were used to quantify the effect of positive milk cultures on test-day milk yields. Identical models were run separately for first-parity, second-parity, and third-parity or older cows. Fixed effects were days in milk, the natural logarithm of days in milk, sparse and rich growth of Staph. aureus (1/0), Streptococcus spp. (1/0), other mastitis pathogens (1/0), calving season, time of test-day milk yields relative to time of microbiological diagnosis (test day relative to time of diagnosis), and the interaction terms between microbiological diagnosis and test day relative to time of diagnosis. The models were run with the logarithmically transformed composite milk somatic cell count excluded and included. Rich growth of Staph. aureus was associated with decreased production levels in first-parity cows. An interaction between rich growth of Staph. aureus and test day relative to time of diagnosis also predicted a decline in milk production in third-parity or older cows. Interaction between sparse growth of Staph. aureus and test day relative to time of diagnosis predicted declining test-day milk yields in first-parity cows. Sparse growth of Staph. aureus was associated with high milk yields in third-parity or older cows after including the logarithmically transformed composite milk somatic cell count in the model, which illustrates that lower production levels are related to elevated somatic cell counts in high-producing cows. The same association with test-day milk yield was found among Streptococcus spp.-positive pluriparous cows.

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...

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.

Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

Derivation of intermediate to silicic magma from the basalt analyzed at the Vega 2 landing site, Venus.

PubMed

Shellnutt, J Gregory

2018-01-01

Geochemical modeling using the basalt composition analyzed at the Vega 2 landing site indicates that intermediate to silicic liquids can be generated by fractional crystallization and equilibrium partial melting. Fractional crystallization modeling using variable pressures (0.01 GPa to 0.5 GPa) and relative oxidation states (FMQ 0 and FMQ -1) of either a wet (H2O = 0.5 wt%) or dry (H2O = 0 wt%) parental magma can yield silicic (SiO2 > 60 wt%) compositions that are similar to terrestrial ferroan rhyolite. Hydrous (H2O = 0.5 wt%) partial melting can yield intermediate (trachyandesite to andesite) to silicic (trachydacite) compositions at all pressures but requires relatively high temperatures (≥ 950°C) to generate the initial melt at intermediate to low pressure whereas at high pressure (0.5 GPa) the first melts will be generated at much lower temperatures (< 800°C). Anhydrous partial melt modeling yielded mafic (basaltic andesite) and alkaline compositions (trachybasalt) but the temperature required to produce the first liquid is very high (≥ 1130°C). Consequently, anhydrous partial melting is an unlikely process to generate derivative liquids. The modeling results indicate that, under certain conditions, the Vega 2 composition can generate silicic liquids that produce granitic and rhyolitic rocks. The implication is that silicic igneous rocks may form a small but important component of the northeast Aphrodite Terra.

Derivation of intermediate to silicic magma from the basalt analyzed at the Vega 2 landing site, Venus

PubMed Central

2018-01-01

Geochemical modeling using the basalt composition analyzed at the Vega 2 landing site indicates that intermediate to silicic liquids can be generated by fractional crystallization and equilibrium partial melting. Fractional crystallization modeling using variable pressures (0.01 GPa to 0.5 GPa) and relative oxidation states (FMQ 0 and FMQ -1) of either a wet (H2O = 0.5 wt%) or dry (H2O = 0 wt%) parental magma can yield silicic (SiO2 > 60 wt%) compositions that are similar to terrestrial ferroan rhyolite. Hydrous (H2O = 0.5 wt%) partial melting can yield intermediate (trachyandesite to andesite) to silicic (trachydacite) compositions at all pressures but requires relatively high temperatures (≥ 950°C) to generate the initial melt at intermediate to low pressure whereas at high pressure (0.5 GPa) the first melts will be generated at much lower temperatures (< 800°C). Anhydrous partial melt modeling yielded mafic (basaltic andesite) and alkaline compositions (trachybasalt) but the temperature required to produce the first liquid is very high (≥ 1130°C). Consequently, anhydrous partial melting is an unlikely process to generate derivative liquids. The modeling results indicate that, under certain conditions, the Vega 2 composition can generate silicic liquids that produce granitic and rhyolitic rocks. The implication is that silicic igneous rocks may form a small but important component of the northeast Aphrodite Terra. PMID:29584745

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.

Identification and delineation of areas flood hazard using high accuracy of DEM data

NASA Astrophysics Data System (ADS)

Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

2018-05-01

Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches

PubMed Central

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance. PMID:23457417

[Effects of Chemical Fertilizers and Organic Fertilizer on Yield of Ligusticum chuanxiong Rhizome].

PubMed

Liang, Qin; Chen, Xing-fu; Li, Yan; Zhang, Jun; Meng, Jie; Peng, Shi-ming

2015-10-01

To study the effects of different N, P, K and organic fertilizer (OF) on yield of Ligusticum chuanxiong rhizome, in order to provide the theoretical foundation for the establishment of standardization cultivation techniques. The field plot experiments used Ligusticum chuanxiong rhizome which planted in Pengshan as material, and were studied by the four factors and five levels with quadratic regression rotation-orthogonal combination design. According to the data obtained, a function model which could predict the fertilization and yield of Ligusticum chuanxiong rhizome accurately was established. The model analysis showed that the yields of Ligusticum chuanxiong rhizome were significantly influenced by the N, P, K and OF applications. Among these factors, the order of increase rates by the fertilizers was K > OF > N > P; The effect of interaction between N and K, N and OF, K and OF on the yield of Ligusticum chuanxiong rhizome were significantly different. High levels of N and P, N and organic fertilizer, K and organic fertilizer were conducive to improve the yield of Ligusticum chuanxiong rhizome. The results showed that the optimal fertilizer application rates of N was 148.20 - 172.28 kg/hm2, P was 511.92 - 599.40 kg/hm2, K was 249.70 - 282.37 kg/hm2, and OF was 940.00 - 1 104.00 kg/hm2. N, P, K and OF obviously affect the yield of Ligusticum chuanxiong rhizome. K and OF can significantly increase the yield of Ligusticum chuanxiong rhizome. Thus it is suggested that properly high mount of K and OF and appropriate increasing N are two favorable factors for cultivating Ligusticum chuanxiong.

Nitrate radical oxidation of γ-terpinene: hydroxy nitrate, total organic nitrate, and secondary organic aerosol yields

NASA Astrophysics Data System (ADS)

Slade, Jonathan H.; de Perre, Chloé; Lee, Linda; Shepson, Paul B.

2017-07-01

Polyolefinic monoterpenes represent a potentially important but understudied source of organic nitrates (ONs) and secondary organic aerosol (SOA) following oxidation due to their high reactivity and propensity for multi-stage chemistry. Recent modeling work suggests that the oxidation of polyolefinic γ-terpinene can be the dominant source of nighttime ON in a mixed forest environment. However, the ON yields, aerosol partitioning behavior, and SOA yields from γ-terpinene oxidation by the nitrate radical (NO3), an important nighttime oxidant, have not been determined experimentally. In this work, we present a comprehensive experimental investigation of the total (gas + particle) ON, hydroxy nitrate, and SOA yields following γ-terpinene oxidation by NO3. Under dry conditions, the hydroxy nitrate yield = 4(+1/-3) %, total ON yield = 14(+3/-2) %, and SOA yield ≤ 10 % under atmospherically relevant particle mass loadings, similar to those for α-pinene + NO3. Using a chemical box model, we show that the measured concentrations of NO2 and γ-terpinene hydroxy nitrates can be reliably simulated from α-pinene + NO3 chemistry. This suggests that NO3 addition to either of the two internal double bonds of γ-terpinene primarily decomposes forming a relatively volatile keto-aldehyde, reconciling the small SOA yield observed here and for other internal olefinic terpenes. Based on aerosol partitioning analysis and identification of speciated particle-phase ON applying high-resolution liquid chromatography-mass spectrometry, we estimate that a significant fraction of the particle-phase ON has the hydroxy nitrate moiety. This work greatly contributes to our understanding of ON and SOA formation from polyolefin monoterpene oxidation, which could be important in the northern continental US and the Midwest, where polyolefinic monoterpene emissions are greatest.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

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.

Regional yield predictions of malting barley by remote sensing and ancillary data

NASA Astrophysics Data System (ADS)

Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

2004-02-01

Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

MULTI-KEV X-RAY YIELDS FROM HIGH-Z GAS TARGETS FIELDED AT OMEGA

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

Kane, J O; Fournier, K B; May, M J

2010-11-04

The authors report on modeling of x-ray yield from gas-filled targets shot at the OMEGA laser facility. The OMEGA targets were 1.8 mm long, 1.95 mm in diameter Be cans filled with either a 50:50 Ar:Xe mixture, pure Ar, pure Kr or pure Xe at {approx} 1 atm. The OMEGA experiments heated the gas with 20 kJ of 3{omega} ({approx} 350 nm) laser energy delivered in a 1 ns square pulse. the emitted x-ray flux was monitored with the x-ray diode based DANTE instruments in the sub-keV range. Two-dimensional x-ray images (for energies 3-5 keV) of the targets were recordedmore » with gated x-ray detectors. The x-ray spectra were recorded with the HENWAY crystal spectrometer at OMEGA. Predictions are 2D r-z cylindrical with DCA NLTE atomic physics. Models generally: (1) underpredict the Xe L-shell yields; (2) overpredict the Ar K-shell yields; (3) correctly predict the Xe thermal yields; and (4) greatly underpredict the Ar thermal yields. However, there are spreads within the data, e.g. the DMX Ar K-shell yields are correctly predicted. The predicted thermal yields show strong angular dependence.« less

A regionally-adapted implementation of conservation agriculture delivers rapid improvements to soil properties associated with crop yield stability.

PubMed

Williams, Alwyn; Jordan, Nicholas R; Smith, Richard G; Hunter, Mitchell C; Kammerer, Melanie; Kane, Daniel A; Koide, Roger T; Davis, Adam S

2018-05-31

Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.

Capsule symmetry sensitivity and hohlraum symmetry calculations for the z-pinch driven hohlraum high-yield concept

NASA Astrophysics Data System (ADS)

Vesey, Roger; Cuneo, M. E.; Hanson Porter, D. L., Jr.; Mehlhorn, T. A.; Ruggles, L. E.; Simpson, W. W.; Hammer, J. H.; Landen, O.

2000-10-01

Capsule radiation symmetry is a crucial issue in the design of the z-pinch driven hohlraum approach to high-yield inertial confinement fusion [1]. Capsule symmetry may be influenced by power imbalance of the two z-pinch x-ray sources, and by hohlraum effects (geometry, time-dependent albedo, wall motion). We have conducted two-dimensional radiation-hydrodynamics calculations to estimate the symmetry sensitivity of the 220 eV beryllium ablator capsule that nominally yields 400 MJ in this concept. These estimates then determine the symmetry requirements to be met by the hohlraum design (for even Legendre modes) and by the top-bottom pinch imbalance and mistiming (for odd Legendre modes). We have used a combination of 2- and 3-D radiosity ("viewfactor"), and 2-D radiation-hydrodynamics calculations to identify hohlraum geometries that meet these symmetry requirements for high-yield, and are testing these models against ongoing Z foam ball symmetry experiments. 1. J. H. Hammer et al., Phys. Plas. 6, 2129 (1999).

Heat tolerance around flowering in wheat identified as a key trait for increased yield potential in Europe under climate change

PubMed Central

Stratonovitch, Pierre; Semenov, Mikhail A.

2015-01-01

To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, the Sirius wheat model was refined by incorporating the effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number, and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. The model was used to optimize wheat ideotypes for CMIP5-based climate scenarios for 2050 at six sites in Europe with diverse climates. The yield potential for heat-tolerant ideotypes can be substantially increased in the future (e.g. by 80% at Seville, 100% at Debrecen) compared with the current cultivars by selecting an optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, at two sites, Seville and Debrecen, the grain yields of heat-sensitive ideotypes were substantially lower (by 54% and 16%) and more variable compared with heat-tolerant ideotypes, because the extended grain filling required for the increased yield potential was in conflict with episodes of high temperature during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. PMID:25750425

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Examining the effect of down regulation under high [CO2] on the growth of soybean assimilating a semi process-based model and FACE data

NASA Astrophysics Data System (ADS)

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

2011-12-01

The actual impact of elevated [CO2] with the interaction of the other climatic factors on the crop growth is still debated. In many process-based crop models, the response of photosynthesis per single leaf to environmental factors is basically described using the biochemical model of Farquhar et al. (1980). However, the decline in photosynthetic enhancement known as down regulation has not been taken into account. On the other hand, the mechanisms causing photosynthetic down regulation is still unknown, which makes it difficult to include the effect of down regulation into process-based crop models. The current results of Free-air CO2 enrichment (FACE) experiments have reported the effect of down regulation under actual environments. One of the effective approaches to involve these results into future crop yield prediction is developing a semi process-based crop growth model, which includes the effect of photosynthetic down regulation as a statistical model, and assimilating the data obtained in FACE experiments. In this study, we statistically estimated the parameters of a semi process-based model for soybean growth ('SPM-soybean') using a hierarchical Baysian method with the FACE data on soybeans (Morgan et al. 2005). We also evaluated the effect of down regulation on the soybean yield in future climatic conditions. The model selection analysis showed that the effective correction to the overestimation of the Farquhar's biochemical C3 model was to reduce the maximum rate of carboxylation (Vcmax) under elevated [CO2]. However, interestingly, the difference in the estimated final crop yields between the corrected model and the non-corrected model was very slight (Fig.1a) for future projection under climate change scenario (Miroc-ESM). This was due to that the reduction in Vcmax also brought about the reduction of the base dark respiration rate of leaves. Because the dark respiration rate exponentially increases with temperature, the slight difference in base respiration rate becomes a large difference under high temperature under the future climate scenarios. In other words, if the temperature rise is very small or zero under elevated [CO2] condition, the effect of down regulation significantly appears (Fig.1b). This result suggest that further experimental data that considering high CO2 effect and high temperature effect in field conditions should be important and elaborate the model projection of the future crop yield through data assimilation method.

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.

Assessing the impacts of crop-rotation and tillage on crop yields and sediment yield using a modeling approach

USDA-ARS?s Scientific Manuscript database

This study was conducted in the Big Sunflower River Watershed (BSRW), north-west, Mississippi. The watershed has been identified as “impaired waters” under Section 303(d) of the Federal Clean Water Act due to high levels of sediment and total phosphorus. This excess is then transported to the Gulf o...

Estimating yields of unthinned eastern white pine plantations from current stocking in the Southern Appalachians

Treesearch

Todd E. Hepp; John P. Vimmerstedt; Glendon W. Smalley; W. Henry McNab

2015-01-01

Eastern white pine (Pinus strobus L.) is a highly productive native conifer of the southern Appalachian Mountains that has long been established in plantations for conventional purposes of afforestation and timber production and potentially for carbon sequestration both within and outside its natural range. Growth-and-yield models are not available, however, for use by...

Studies of fission fragment yields via high-resolution γ-ray spectroscopy

NASA Astrophysics Data System (ADS)

Wilson, J. N.; Lebois, M.; Qi, L.; Amador-Celdran, P.; Bleuel, D.; Briz, J. A.; Carroll, R.; Catford, W.; Witte, H. De; Doherty, D. T.; Eloirdi, R.; Georgiev, G.; Gottardo, A.; Goasduff, A.; Hadyñska-Klek, K.; Hauschild, K.; Hess, H.; Ingeberg, V.; Konstantinopoulos, T.; Ljungvall, J.; Lopez-Martens, A.; Lorusso, G.; Lozeva, R.; Lutter, R.; Marini, P.; Matea, I.; Materna, T.; Mathieu, L.; Oberstedt, A.; Oberstedt, S.; Panebianco, S.; Podolyak, Zs.; Porta, A.; Regan, P. H.; Reiter, P.; Rezynkina, K.; Rose, S. J.; Sahin, E.; Seidlitz, M.; Serot, O.; Shearman, R.; Siebeck, B.; Siem, S.; Smith, A. G.; Tveten, G. M.; Verney, D.; Warr, N.; Zeiser, F.; Zielinska, M.

2018-03-01

Precise spectroscopic information on the fast neutron induced fission of the 238U(n,f) reaction was recently gained using a new technique which involved coupling of the Miniball high resolution y-ray spectrometer and the LICORNE directional neutron source. The experiment allowed measurement of the isotopic fission yields for around 40 even-even nuclei at an incident neutron energy of around 2 MeV where yield data are very sparse. In addition spectroscopic information on very neutron-rich fission products was obtained. Results were compared to models, both the JEFF-3.1.1 data base and the GEF code, and large discrepancies for the S1 fission mode in the Sn/Mo isotope pair were discovered. This suggests that current models are overestimating the role played by spherical shell effects in fast neutron induced fission. In late 2017 and 2018 the nu-ball hybrid spectrometer will be constructed at the IPN Orsay to perform further experimental investigations with directional neutrons coupled to a powerful hybrid Ge/LaBr3 detector array. This will open up new possibilities for measurements of fission yields for fast-neutron-induced fission using the spectroscopic technique and will be complimentary to other methods being developed.

Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data.

PubMed

Ogutu, Booker O; Dash, Jadunandan; Dawson, Terence P

2013-09-01

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C3 and C4 ) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPARps ) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R(2)  > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry-grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R(2)  > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPARps ) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPARps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution. © 2013 John Wiley & Sons Ltd.

Modeling applications for precision agriculture in the California Central Valley

NASA Astrophysics Data System (ADS)

Marklein, A. R.; Riley, W. J.; Grant, R. F.; Mezbahuddin, S.; Mekonnen, Z. A.; Liu, Y.; Ying, S.

2017-12-01

Drought in California has increased the motivation to develop precision agriculture, which uses observations to make site-specific management decisions throughout the growing season. In agricultural systems that are prone to drought, these efforts often focus on irrigation efficiency. Recent improvements in soil sensor technology allow the monitoring of plant and soil status in real-time, which can then inform models aimed at improving irrigation management. But even on farms with resources to deploy soil sensors across the landscape, leveraging that sensor data to design an efficient irrigation scheme remains a challenge. We conduct a modeling experiment aimed at simulating precision agriculture to address several questions: (1) how, when, and where does irrigation lead to optimal yield? and (2) What are the impacts of different precision irrigation schemes on yields, soil organic carbon (SOC), and total water use? We use the ecosys model to simulate precision agriculture in a conventional tomato-corn rotation in the California Central Valley with varying soil water content thresholds for irrigation and soil water sensor depths. This model is ideal for our question because it includes explicit process-based functions for the plant growth, plant water use, soil hydrology, and SOC, and has been tested extensively in agricultural ecosystems. Low irrigation thresholds allows the soil to become drier before irrigating compared to high irrigation thresholds; as such, we found that the high irrigation thresholds use more irrigation over the course of the season, have higher yields, and have lower water use efficiency. The irrigation threshold did not affect SOC. Yields and water use are highest at sensor depths of 0.5 to 0.15 m, but water use efficiency was also lowest at these depths. We found SOC to be significantly affected by sensor depth, with the highest SOC at the shallowest sensor depths. These results will help regulate irrigation water while maintaining yield in California, especially with uncertain precipitation regimes.

Quantitative description of realistic wealth distributions by kinetic trading models

NASA Astrophysics Data System (ADS)

Lammoglia, Nelson; Muñoz, Víctor; Rogan, José; Toledo, Benjamín; Zarama, Roberto; Valdivia, Juan Alejandro

2008-10-01

Data on wealth distributions in trading markets show a power law behavior x-(1+α) at the high end, where, in general, α is greater than 1 (Pareto’s law). Models based on kinetic theory, where a set of interacting agents trade money, yield power law tails if agents are assigned a saving propensity. In this paper we are solving the inverse problem, that is, in finding the saving propensity distribution which yields a given wealth distribution for all wealth ranges. This is done explicitly for two recently published and comprehensive wealth datasets.

N*(1535) electroproduction at high Q2

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

G. Ramalho, M.T. Pena, K. Tsushima

2012-04-01

A covariant spectator quark model is applied to study the {gamma}N {yields} N*(1535) reaction in the large Q{sup 2} region. Starting from the relation between the nucleon and N*(1535) systems, the N*(1535) valence quark wave function is determined without the addition of any parameters. The model is then used to calculate the {gamma}N {yields} N*(1535) transition form factors. A very interesting, useful relation between the A{sub 1/2} and S{sub 1/2} helicity amplitudes for Q{sup 2} > GeV{sup 2}, is also derived.

Ensemble yield simulations: Using heat-tolerant and later-maturing varieties to adapt to climate warming.

PubMed

Zhang, Yi; Zhao, Yanxia

2017-01-01

The use of modern crop varieties is a dominant method of obtaining high yields in crop production. Efforts to identify suitable varieties, with characteristics that would increase crop yield under future climate conditions, remain essential to developing sustainable agriculture and food security. This work aims to evaluate potential genotypic adaptations (i.e., using varieties with increased ability to produce desirable grain numbers under high temperatures and with enhanced thermal time requirements during the grain-filling period) to cope with the negative impacts of climate change on maize yield. The contributions of different options were investigated at six sites in the North China Plain using the APSIM model and the outputs of 8 GCMs under RCP4.5 scenarios. It was found that without considering adaptation options, mean maize yield would decrease by 7~18% during 2010-2039 relative to 1976-2005. A large decrease in grain number relative to stabilized grain weight decreased maize yield under future climate scenarios. Using heat-tolerant varieties, maize yield could increase on average by 6% to 10%. Using later maturing varieties, e.g., enhanced thermal time requirements during the grain-filling period, maize yield could increase by 7% to 10%. The optimal adaptation options were site specific.

Ensemble yield simulations: Using heat-tolerant and later-maturing varieties to adapt to climate warming

PubMed Central

Zhang, Yi

2017-01-01

The use of modern crop varieties is a dominant method of obtaining high yields in crop production. Efforts to identify suitable varieties, with characteristics that would increase crop yield under future climate conditions, remain essential to developing sustainable agriculture and food security. This work aims to evaluate potential genotypic adaptations (i.e., using varieties with increased ability to produce desirable grain numbers under high temperatures and with enhanced thermal time requirements during the grain-filling period) to cope with the negative impacts of climate change on maize yield. The contributions of different options were investigated at six sites in the North China Plain using the APSIM model and the outputs of 8 GCMs under RCP4.5 scenarios. It was found that without considering adaptation options, mean maize yield would decrease by 7~18% during 2010–2039 relative to 1976–2005. A large decrease in grain number relative to stabilized grain weight decreased maize yield under future climate scenarios. Using heat-tolerant varieties, maize yield could increase on average by 6% to 10%. Using later maturing varieties, e.g., enhanced thermal time requirements during the grain-filling period, maize yield could increase by 7% to 10%. The optimal adaptation options were site specific. PMID:28459880

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Biogas production from Pongamia biomass wastes and a model to estimate biodegradability from their composition.

PubMed

Gunaseelan, Victor Nallathambi

2014-02-01

In this study, I investigated the chemical characteristics, biochemical methane potential, conversion kinetics and biodegradability of untreated and NaOH-treated Pongamia plant parts, and pod husk and press cake from the biodiesel industry to evaluate their suitability as an alternative feedstock for biogas production. The untreated Pongamia seeds exhibited the maximum CH4 yield of 473 ml g (-1) volatile solid (VS) added. Yellow, withered leaves gave a yield as low as 122 ml CH4 g (-1) VS added. There were significant variations in the CH4 production rate constants, which ranged from 0.02 to 0.15 d (-1), and biodegradability, which ranged from 0.25 to 0.98. NaOH treatment of leaf and pod husk, which were highly rich in fibers, increased the yields by 15-22% and CH4 production rate constants by 20-75%. Utilization of Pongamia wastes in biogas digesters not only influences the economics of biodiesel production but also yields CH4 fuel and protects the environment. The experimental data from this study were used to develop a multiple regression model, which could estimate biodegradability based on biochemical characteristics. The model predicted the biodegradability of previously published biomass wastes (r(2) = 0.88) from their biochemical composition. The theoretical CH4 yields estimated as 350 ml g(-1) chemical oxygen demand destroyed are much higher than the experimental yields as 100% biodegradability is assumed for each substrate. Upon correcting the theoretical CH4 yields with biodegradability data obtained from chemical analyses of substrates, their ultimate CH4 yields could be predicted rapidly.

Modelling the endothelial blood-CNS barriers: a method for the production of robust in vitro models of the rat blood-brain barrier and blood-spinal cord barrier

PubMed Central

2013-01-01

Background Modelling the blood-CNS barriers of the brain and spinal cord in vitro continues to provide a considerable challenge for research studying the passage of large and small molecules in and out of the central nervous system, both within the context of basic biology and for pharmaceutical drug discovery. Although there has been considerable success over the previous two decades in establishing useful in vitro primary endothelial cell cultures from the blood-CNS barriers, no model fully mimics the high electrical resistance, low paracellular permeability and selective influx/efflux characteristics of the in vivo situation. Furthermore, such primary-derived cultures are typically labour-intensive and generate low yields of cells, limiting scope for experimental work. We thus aimed to establish protocols for the high yield isolation and culture of endothelial cells from both rat brain and spinal cord. Our aim was to optimise in vitro conditions for inducing phenotypic characteristics in these cells that were reminiscent of the in vivo situation, such that they developed into tight endothelial barriers suitable for performing investigative biology and permeability studies. Methods Brain and spinal cord tissue was taken from the same rats and used to specifically isolate endothelial cells to reconstitute as in vitro blood-CNS barrier models. Isolated endothelial cells were cultured to expand the cellular yield and then passaged onto cell culture inserts for further investigation. Cell culture conditions were optimised using commercially available reagents and the resulting barrier-forming endothelial monolayers were characterised by functional permeability experiments and in vitro phenotyping by immunocytochemistry and western blotting. Results Using a combination of modified handling techniques and cell culture conditions, we have established and optimised a protocol for the in vitro culture of brain and, for the first time in rat, spinal cord endothelial cells. High yields of both CNS endothelial cell types can be obtained, and these can be passaged onto large numbers of cell culture inserts for in vitro permeability studies. The passaged brain and spinal cord endothelial cells are pure and express endothelial markers, tight junction proteins and intracellular transport machinery. Further, both models exhibit tight, functional barrier characteristics that are discriminating against large and small molecules in permeability assays and show functional expression of the pharmaceutically important P-gp efflux transporter. Conclusions Our techniques allow the provision of high yields of robust sister cultures of endothelial cells that accurately model the blood-CNS barriers in vitro. These models are ideally suited for use in studying the biology of the blood-brain barrier and blood-spinal cord barrier in vitro and for pre-clinical drug discovery. PMID:23773766

Modelling the endothelial blood-CNS barriers: a method for the production of robust in vitro models of the rat blood-brain barrier and blood-spinal cord barrier.

PubMed

Watson, P Marc D; Paterson, Judy C; Thom, George; Ginman, Ulrika; Lundquist, Stefan; Webster, Carl I

2013-06-18

Modelling the blood-CNS barriers of the brain and spinal cord in vitro continues to provide a considerable challenge for research studying the passage of large and small molecules in and out of the central nervous system, both within the context of basic biology and for pharmaceutical drug discovery. Although there has been considerable success over the previous two decades in establishing useful in vitro primary endothelial cell cultures from the blood-CNS barriers, no model fully mimics the high electrical resistance, low paracellular permeability and selective influx/efflux characteristics of the in vivo situation. Furthermore, such primary-derived cultures are typically labour-intensive and generate low yields of cells, limiting scope for experimental work. We thus aimed to establish protocols for the high yield isolation and culture of endothelial cells from both rat brain and spinal cord. Our aim was to optimise in vitro conditions for inducing phenotypic characteristics in these cells that were reminiscent of the in vivo situation, such that they developed into tight endothelial barriers suitable for performing investigative biology and permeability studies. Brain and spinal cord tissue was taken from the same rats and used to specifically isolate endothelial cells to reconstitute as in vitro blood-CNS barrier models. Isolated endothelial cells were cultured to expand the cellular yield and then passaged onto cell culture inserts for further investigation. Cell culture conditions were optimised using commercially available reagents and the resulting barrier-forming endothelial monolayers were characterised by functional permeability experiments and in vitro phenotyping by immunocytochemistry and western blotting. Using a combination of modified handling techniques and cell culture conditions, we have established and optimised a protocol for the in vitro culture of brain and, for the first time in rat, spinal cord endothelial cells. High yields of both CNS endothelial cell types can be obtained, and these can be passaged onto large numbers of cell culture inserts for in vitro permeability studies. The passaged brain and spinal cord endothelial cells are pure and express endothelial markers, tight junction proteins and intracellular transport machinery. Further, both models exhibit tight, functional barrier characteristics that are discriminating against large and small molecules in permeability assays and show functional expression of the pharmaceutically important P-gp efflux transporter. Our techniques allow the provision of high yields of robust sister cultures of endothelial cells that accurately model the blood-CNS barriers in vitro. These models are ideally suited for use in studying the biology of the blood-brain barrier and blood-spinal cord barrier in vitro and for pre-clinical drug discovery.

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

PubMed

Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

Clinical relevance of combined FSH and AMH observations in infertile women.

PubMed

Gleicher, Norbert; Kim, Ann; Kushnir, Vitaly; Weghofer, Andrea; Shohat-Tal, Aya; Lazzaroni, Emanuela; Lee, Ho-Joon; Barad, David H

2013-05-01

FSH and anti-Müllerian hormone (AMH) are, individually, widely used to assess functional ovarian reserve (FOR) but demonstrate discrepancies in efficacy. How predictive they are combined is unknown. The purpose of this study was to assess predictive values of different FSH and AMH combinations on in vitro fertilization (IVF). FSH and AMH levels in patients were categorized as low, normal, and high, based on age-specific 95% confidence intervals. This allowed for establishment of nine combinations of low, normal, or high FSH/AMH patient categories. With use of various statistical methods, patients in individual categories were then compared in outcomes. We investigated 544 consecutive infertility patients in their first IVF cycles. IVF cycles were managed. Oocyte yields and implantation and pregnancy rates, adjusted for age and fragile X mental retardation 1 (FMR1) genotypes/subgenotypes, were measured. The most notable repeated finding was a strong statistical association of the FSH/AMH high/high category (characterized by abnormally high FSH and AMH levels) with favorable IVF outcomes compared with outcomes for other FSH/AMH variations (4.34 times odds of high oocyte yields and 1.93 times odds of clinical pregnancy). Addition of age to the model only minimally further improved the odds of pregnancy to 2.03 times. The positive association with high oocyte yields, however, turned negative (0.75 times lower yields) with addition of FMR1 to the model for women with FSH/AMH high/high and the het-norm/low FMR1 subgenotype compared with women with the norm FMR1 genotype and other FSH/AMH categories. In the absence of het-norm/low FMR1, abnormally high FSH and AMH, a seemingly contradictory combination, reflects highly beneficial outcomes in IVF compared with the other FSH/AMH categories, suggesting greater importance of FSH in early follicle maturation than currently recognized. The study also confirms adverse outcome effects of het-norm/low FMR1 and, therefore, the gene's importance for reproductive success.

Use of the Richtmyer-Meshkov Instability to Infer Yield Stress at High-Energy Densities

NASA Astrophysics Data System (ADS)

Dimonte, Guy; Terrones, G.; Cherne, F. J.; Germann, T. C.; Dupont, V.; Kadau, K.; Buttler, W. T.; Oro, D. M.; Morris, C.; Preston, D. L.

2011-12-01

We use the Richtmyer-Meshkov instability (RMI) at a metal-gas interface to infer the metal’s yield stress (Y) under shock loading and release. We first model how Y stabilizes the RMI using hydrodynamics simulations with a perfectly plastic constitutive relation for copper (Cu). The model is then tested with molecular dynamics (MD) of crystalline Cu by comparing the inferred Y from RMI simulations with direct stress-strain calculations, both with MD at the same conditions. Finally, new RMI experiments with solid Cu validate our simulation-based model and infer Y˜0.47GPa for a 36 GPa shock.

A quantitative approach to combine sources in stable isotope mixing models

EPA Science Inventory

Stable isotope mixing models, used to estimate source contributions to a mixture, typically yield highly uncertain estimates when there are many sources and relatively few isotope elements. Previously, ecologists have either accepted the uncertain contribution estimates for indiv...

Simplified method to isolate highly pure canine pancreatic islets.

PubMed

Woolcott, Orison O; Bergman, Richard N; Richey, Joyce M; Kirkman, Erlinda L; Harrison, L Nicole; Ionut, Viorica; Lottati, Maya; Zheng, Dan; Hsu, Isabel R; Stefanovski, Darko; Kabir, Morvarid; Kim, Stella P; Catalano, Karyn J; Chiu, Jenny D; Chow, Robert H

2012-01-01

The canine model has been used extensively to improve the human pancreatic islet isolation technique. At the functional level, dog islets show high similarity to human islets and thus can be a helpful tool for islet research. We describe and compare 2 manual isolation methods, M1 (initial) and M2 (modified), and analyze the variables associated with the outcomes, including islet yield, purity, and glucose-stimulated insulin secretion (GSIS). Male mongrel dogs were used in the study. M2 (n = 7) included higher collagenase concentration, shorter digestion time, faster shaking speed, colder purification temperature, and higher differential density gradient than M1 (n = 7). Islet yield was similar between methods (3111.0 ± 309.1 and 3155.8 ± 644.5 islets/g, M1 and M2, respectively; P = 0.951). Pancreas weight and purity together were directly associated with the yield (adjusted R(2) = 0.61; P = 0.002). Purity was considerably improved with M2 (96.7% ± 1.2% vs 75.0% ± 6.3%; P = 0.006). M2 improved GSIS (P = 0.021). Independently, digestion time was inversely associated with GSIS. We describe an isolation method (M2) to obtain a highly pure yield of dog islets with adequate β-cell glucose responsiveness. The isolation variables associated with the outcomes in our canine model confirm previous reports in other species, including humans.

Simplified Method to Isolate Highly Pure Canine Pancreatic Islets

PubMed Central

Woolcott, Orison O.; Bergman, Richard N.; Richey, Joyce M.; Kirkman, Erlinda L.; Harrison, L. Nicole; Ionut, Viorica; Lottati, Maya; Zheng, Dan; Hsu, Isabel R.; Stefanovski, Darko; Kabir, Morvarid; Kim, Stella P.; Catalano, Karyn J.; Chiu, Jenny D.; Chow, Robert H.

2015-01-01

Objectives The canine model has been used extensively to improve the human pancreatic islet isolation technique. At the functional level, dog islets show high similarity to human islets and thus can be a helpful tool for islet research. We describe and compare 2 manual isolation methods, M1 (initial) and M2 (modified), and analyze the variables associated with the outcomes, including islet yield, purity, and glucose-stimulated insulin secretion (GSIS). Methods Male mongrel dogs were used in the study. M2 (n = 7) included higher collagenase concentration, shorter digestion time, faster shaking speed, colder purification temperature, and higher differential density gradient than M1 (n = 7). Results Islet yield was similar between methods (3111.0 ± 309.1 and 3155.8 ± 644.5 islets/g, M1 and M2, respectively; P = 0.951). Pancreas weight and purity together were directly associated with the yield (adjusted R2 = 0.61; P = 0.002). Purity was considerably improved with M2 (96.7% ± 1.2% vs 75.0% ± 6.3%; P = 0.006). M2 improved GSIS (P = 0.021). Independently, digestion time was inversely associated with GSIS. Conclusions We describe an isolation method (M2) to obtain a highly pure yield of dog islets with adequate β-cell glucose responsiveness. The isolation variables associated with the outcomes in our canine model confirm previous reports in other species, including humans. PMID:21792087

Modelling multi-phase liquid-sediment scour and resuspension induced by rapid flows using Smoothed Particle Hydrodynamics (SPH) accelerated with a Graphics Processing Unit (GPU)

NASA Astrophysics Data System (ADS)

Fourtakas, G.; Rogers, B. D.

2016-06-01

A two-phase numerical model using Smoothed Particle Hydrodynamics (SPH) is applied to two-phase liquid-sediments flows. The absence of a mesh in SPH is ideal for interfacial and highly non-linear flows with changing fragmentation of the interface, mixing and resuspension. The rheology of sediment induced under rapid flows undergoes several states which are only partially described by previous research in SPH. This paper attempts to bridge the gap between the geotechnics, non-Newtonian and Newtonian flows by proposing a model that combines the yielding, shear and suspension layer which are needed to predict accurately the global erosion phenomena, from a hydrodynamics prospective. The numerical SPH scheme is based on the explicit treatment of both phases using Newtonian and the non-Newtonian Bingham-type Herschel-Bulkley-Papanastasiou constitutive model. This is supplemented by the Drucker-Prager yield criterion to predict the onset of yielding of the sediment surface and a concentration suspension model. The multi-phase model has been compared with experimental and 2-D reference numerical models for scour following a dry-bed dam break yielding satisfactory results and improvements over well-known SPH multi-phase models. With 3-D simulations requiring a large number of particles, the code is accelerated with a graphics processing unit (GPU) in the open-source DualSPHysics code. The implementation and optimisation of the code achieved a speed up of x58 over an optimised single thread serial code. A 3-D dam break over a non-cohesive erodible bed simulation with over 4 million particles yields close agreement with experimental scour and water surface profiles.

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.

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.

Low-high junction theory applied to solar cells

NASA Technical Reports Server (NTRS)

Godlewski, M. P.; Baraona, C. R.; Brandhorst, H. W., Jr.

1974-01-01

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open-circuit voltage and improved radiation resistance. Several analytical models for open-circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero surface recombination velocity (SRV) case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells.

High-resolution model for estimating the economic and policy implications of agricultural soil salinization in California

NASA Astrophysics Data System (ADS)

Welle, Paul D.; Mauter, Meagan S.

2017-09-01

This work introduces a generalizable approach for estimating the field-scale agricultural yield losses due to soil salinization. When integrated with regional data on crop yields and prices, this model provides high-resolution estimates for revenue losses over large agricultural regions. These methods account for the uncertainty inherent in model inputs derived from satellites, experimental field data, and interpreted model results. We apply this method to estimate the effect of soil salinity on agricultural outputs in California, performing the analysis with both high-resolution (i.e. field scale) and low-resolution (i.e. county-scale) data sources to highlight the importance of spatial resolution in agricultural analysis. We estimate that soil salinity reduced agricultural revenues by 3.7 billion (1.7-7.0 billion) in 2014, amounting to 8.0 million tons of lost production relative to soil salinities below the crop-specific thresholds. When using low-resolution data sources, we find that the costs of salinization are underestimated by a factor of three. These results highlight the need for high-resolution data in agro-environmental assessment as well as the challenges associated with their integration.

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.

The effects of climate change on instream nitrogen transport in the contiguous United States

NASA Astrophysics Data System (ADS)

Alam, M. J.; Goodall, J. L.

2011-12-01

Excessive nitrogen loading has caused significant environmental impacts such as eutrophication and hypoxia in waterbodies around the world. Nitrogen loading is largely dependent on nonpoint source pollution and nitrogen transport from nonpoint source pollution is greatly impacted by climate conditions. For example, increased precipitation leads to more runoff and a higher nitrogen yield. However, higher temperatures also impact nitrogen transport in that higher temperatures increase denitrification and therefore reduce nitrogen yield. The purpose of this research is to quantify potential changes in nitrogen yield for the contiguous United States under predicted climate change scenarios, specifically changes in precipitation and air temperature. The analysis was performed for high (A2) and low (B1) emission scenarios and for the year 2030, 2050 and 2090. We used 11 different IPCC (The Intergovernmental Panel on Climate Change) models predicted precipitation and temperature estimates to capture uncertainty. The SPARROW model was calibrated using historical nitrogen loading data and used to predict nitrogen yields for future climate conditions. We held nitrogen source data constant in order to isolate the impact of predicted precipitation and temperature changes for each model scenario. Preliminary results suggest an overall decrease in nitrogen yield if climate change impacts are considered in isolation. For the A2 scenario, the model results indicated an overall incremental nitrogen yield decrease of 2-17% by the year 2030, 4-26% by the year 2050, and 11-45% by the year 2090. The B1 emission scenario also indicated an incremental yield decrease, but at lesser amounts of 2-18%, 5-21% and 10-38% by the years 2030, 2050, and 2090, respectively. This decrease is mainly due to higher predicted temperatures that result in increased denitrification rates.

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.

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

Global scale modeling of riverine sediment loads: tropical rivers in a global context

NASA Astrophysics Data System (ADS)

Cohen, Sagy; Syvitski, James; Kettner, Albert

2015-04-01

A global scale riverine sediment flux model (termed WBMsed) is introduced. The model predicts spatially and temporally explicit water, suspended sediment and nutrients flux in relatively high resolutions (6 arc-min and daily). Modeled riverine suspended sediment flux through global catchments is used in conjunction with observational data for 35 tropical basins to highlight key basin scaling relationships. A 50 year, daily model simulation illuminates how precipitation, relief, lithology and drainage basin area affect sediment load, yield and concentration. Tropical river systems, wherein much of a drainage basin experiences tropical climate are strongly influenced by the annual and inter-annual variations of the Inter-tropical Convergence Zone (ITCZ) and its derivative monsoonal winds, have comparatively low inter-annual variation in sediment yield. Rivers draining rainforests and those subjected to tropical monsoons typically demonstrate high runoff, but with notable exceptions. High rainfall intensities from burst weather events are common in the tropics. The release of rain-forming aerosols also appears to uniquely increase regional rainfall, but its geomorphic manifestation is hard to detect. Compared to other more temperate river systems, climate-driven tropical rivers do not appear to transport a disproportionate amount of particulate load to the world's oceans, and their warmer, less viscous waters are less competent. Multiple-year hydrographs reveal that seasonality is a dominant feature of most tropical rivers, but the rivers of Papua New Guinea are somewhat unique being less seasonally modulated. Local sediment yield within the Amazon is highest near the Andes, but decreases towards the ocean as the river's discharge is diluted by water influxes from sediment-deprived rainforest tributaries

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.

Subscale HDC implosions driven at high radiation temperature using advanced hohlraums

NASA Astrophysics Data System (ADS)

Ho, D.; Amendt, P.; Jones, O.; Berzak Hopkins, L.; Le Pape, S.

2017-10-01

Implosions using HDC ablators have received increased attention because of shorter pulse length and can access higher implosion velocity than CH ablators. Recent HDC midscale (979 m radius) implosion experiments have achieved DT neutron yields of 1.5e16. Our 2D simulations show that subscale (890 m radius) HDC capsules can achieve robust high-yield performance if driven at high enough radiation temperature 330 eV, because the penalty for less fuel mass can be offset by higher implosion velocity. To achieve 330 eV will likely require the use of innovative hohlraum concepts, e.g., subscale rugby-shaped hohlraum using 1.3 MJ of laser energy without incurring a risk of high laser backscatter. Radiation symmetry is currently under study. Confidence in our modeling of HDC implosions is high in part because our 2D modeling of recent HDC implosions experiments show good agreement with data. Work performed under auspices of U.S. DOE by LLNL under 15-ERD-058.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Suspended-Sediment Loads and Yields in the North Santiam River Basin, Oregon, Water Years 1999-2004

USGS Publications Warehouse

Bragg, Heather M.; Sobieszczyk, Steven; Uhrich, Mark A.; Piatt, David R.

2007-01-01

The North Santiam River provides drinking water to the residents and businesses of the city of Salem, Oregon, and many surrounding communities. Since 1998, water-quality data, including turbidity, were collected continuously at monitoring stations throughout the basin as part of the North Santiam River Basin Turbidity and Suspended Sediment Study. In addition, sediment samples have been collected over a range of turbidity and streamflow values. Regression models were developed between the instream turbidity and suspended-sediment concentration from the samples collected from each monitoring station. The models were then used to estimate the daily and annual suspended-sediment loads and yields. For water years 1999-2004, suspended-sediment loads and yields were estimated for each station. Annual suspended-sediment loads and yields were highest during water years 1999 and 2000. A drought during water year 2001 resulted in the lowest suspended-sediment loads and yields for all monitoring stations. High-turbidity events that were unrelated or disproportional to increased streamflow occurred at several of the monitoring stations during the period of study. These events highlight the advantage of estimating suspended-sediment loads and yields from instream turbidity rather than from streamflow alone.

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.

A CMIP5 Ensemble Assessment of Climate Change Impact on Durum Wheat Production in North Dakota, USA

NASA Astrophysics Data System (ADS)

Dillon, T. D.; Kirilenko, A.

2016-12-01

North Dakota is the main US and one of the world's leading producers of durum wheat (Triticum durum), the hardest wheat variety with high protein content, used in multiple food products. We investigated potential change in durum wheat production in connection with climate change. The study accounted for variations in environmental conditions by running a dynamic wheat yield model in thirteen climatically different regions of the state. North Dakota climate is representative of highly productive agricultural lands of the Northern Great Plains, which encompass five US states and two Canadian provinces. Eastern part of North Dakota has humid continental climate while the western past is semi-desert with distinct west-to east precipitation gradient. Low mean average temperatures (cir. +4C), and high temperature variability lead to relatively short growing season (cir. 130 days). Combined with limited rainfall (cir. 350 mm in the East and 560 mm in the West), it makes agriculture highly dependent on temperature and precipitation. Accordingly, climate change has high potential impact on crop production in the region. We used the ALMANAC crop growth model to simulate the production of durum wheat. Model performance was estimated by comparison of simulated yields with historical observations; and was found satisfactory (RMSE < 1.00 T/ha*yr). To account for uncertainty in projected future climate, we used an ensemble of 17 CMIP5 GCMs run under four IPCC AR5 RCP scenarios, for two time periods characteristic of the 2040s and the 2070s. GCM output data were further downscaled using MarkSim weather generator. We found statistically significant reductions in mean yields in 96% of model runs for both time periods (t-test for independent samples; p<.05). In 2040s climate, yield decrease varied from 17% for RCP 2.6 to 45% for RCP 8.5; in 2070s climate - from 35% for RCP2.6 to 73% for RCP 8.5. Further research will concentrate on crop fail risk analysis and geographical heterogeneity of simulated changes.

Modulus and yield stress of drawn LDPE

NASA Astrophysics Data System (ADS)

Thavarungkul, Nandh

Modulus and yield stress were investigated in drawn low density polyethylene (LDPE) film. Uniaxially drawn polymeric films usually show high values of modulus and yield stress, however, studies have normally only been conducted to identify the structural features that determine modulus. In this study small-angle x-ray scattering (SAXS), thermal shrinkage, birefringence, differential scanning calorimetry (DSC), and dynamic mechanical thermal analysis (DMTA) were used to examine, directly and indirectly, the structural features that determine both modulus and yield stress, which are often closely related in undrawn materials. Shish-kebab structures are proposed to account for the mechanical properties in drawn LDPE. The validity of this molecular/morphological model was tested using relationships between static mechanical data and structural and physical parameters. In addition, dynamic mechanical results are also in line with static data in supporting the model. In the machine direction (MD), "shish" and taut tie molecules (TTM) anchored in the crystalline phase account for E; whereas crystal lamellae with contributions from "shish" and TTM determine yield stress. In the transverse direction (TD), the crystalline phase plays an important roll in both modulus and yield stress. Modulus is determined by crystal lamellae functioning as platelet reinforcing elements in the amorphous matrix with an additional contributions from TTM and yield stress is determined by the crystal lamellae's resistance to deformation.

Study of optimal extraction conditions for achieving high yield and antioxidant activity of tomato seed oil.

PubMed

Shao, Dongyan; Atungulu, Griffiths G; Pan, Zhongli; Yue, Tianli; Zhang, Ang; Li, Xuan

2012-08-01

Value of tomato seed has not been fully recognized. The objectives of this research were to establish suitable processing conditions for extracting oil from tomato seed by using solvent, determine the impact of processing conditions on yield and antioxidant activity of extracted oil, and elucidate kinetics of the oil extraction process. Four processing parameters, including time, temperature, solvent-to-solid ratio and particle size were studied. A second order model was established to describe the oil extraction process. Based on the results, increasing temperature, solvent-to-solid ratio, and extraction time increased oil yield. In contrast, larger particle size reduced the oil yield. The recommended oil extraction conditions were 8 min of extraction time at temperature of 25 °C, solvent-to-solids ratio of 5/1 (v/w) and particle size of 0.38 mm, which gave oil yield of 20.32% with recovery rate of 78.56%. The DPPH scavenging activity of extracted oil was not significantly affected by the extraction parameters. The inhibitory concentration (IC(50) ) of tomato seed oil was 8.67 mg/mL which was notably low compared to most vegetable oils. A 2nd order model successfully described the kinetics of tomato oil extraction process and parameters of extraction kinetics including initial extraction rate (h), equilibrium concentration of oil (C(s) ), and the extraction rate constant (k) could be precisely predicted with R(2) of at least 0.957. The study revealed that tomato seed which is typically treated as a low value byproduct of tomato processing has great potential in producing oil with high antioxidant capability. The impact of processing conditions including time, temperature, solvent-to-solid ratio and particle size on yield, and antioxidant activity of extracted tomato seed oil are reported. Optimal conditions and models which describe the extraction process are recommended. The information is vital for determining the extraction processing conditions for industrial production of high quality tomato seed oil. Journal of Food Science © 2012 Institute of Food Technologists® No claim to original US government works.

Assessment of 1.5°C and 2°C climate change scenarios impact on wheat production in Tunisia

NASA Astrophysics Data System (ADS)

Bergaoui, karim; Belhaj Fraj, Makram; Zaaboul, Rashyd; Allen, Myles; Mitchell, Dann; Schleussner, Carl-Friedrich; Saeed, Fahad; Mc Donnell, Rachael

2017-04-01

Wheat is the main staple crop in North Africa region and contributes the most to food security. It is almost entirely grown under rainfed conditions and its yield is highly impacted by the climate variability, e. g. dry winters, a late autumn or late spring. Irregular rainfall or drought events particularly at key stages of the growing season, lead to both early and terminal wheat stresses and high inter-year variation in yield. The goal of this study was to explore the impacts of future climate on wheat production in Tunisia using an ensemble of regional bias corrected climate models outputs for the 1.5°C and 2°C warming above the pre-industrial levels. By examining the outputs on wheat yield levels the study would help answer the question of whether the ambitious climate change mitigation efforts involved in stabilizing temperatures at 1.5°C would bring the cereal yields needed in North Africa. Tunisia was chosen as the focus country because its wheat systems are found across a wide diversity in biophysical and farming conditions so giving insight on more localized effects. Data availability across a wide range of wheat management systems from subsistence farming systems to highly mechanized agribusinesses also supported work here as model results could be readily validated for the historical period. Two scenarios were obtained using the RCP2.6 as boundary conditions for 1.5 scenario and a weighted combination of RCP2.6 and RCP4.5 for the 2°C scenario using their respective CO2 levels in the future. We calibrated and validated a dynamical crop model, DSSAT, to simulate the national wheat production and to understand the impact of drought on growth and development that causes yield variation. DSSAT simulations were driven by CHIRPS and ERA-Interim reanalysis data as daily climate forcings. The simulations were validated in a set of farmer fields which were representative of the dominant cropping systems in the country. Then, the model was validated with 10 years' state-level production data. Finally, we forced the crop model with HAPPI bias corrected outputs using ISI-MIP approach where the trend and the long-term mean are well represented and we assessed the impact of each scenario on the wheat production at the national level. The results highlighted a difference in wheat yield in some biophysical areas and farming systems. This insight is important as countries develop mitigation and adaptation strategies as the impact costs can be included.

Multiyear high-resolution carbon exchange over European croplands from the integration of observed crop yields into CarbonTracker Europe

NASA Astrophysics Data System (ADS)

Combe, Marie; Vilà-Guerau de Arellano, Jordi; de Wit, Allard; Peters, Wouter

2016-04-01

Carbon exchange over croplands plays an important role in the European carbon cycle over daily-to-seasonal time scales. Not only do crops occupy one fourth of the European land area, but their photosynthesis and respiration are large and affect CO2 mole fractions at nearly every atmospheric CO2 monitoring site. A better description of this crop carbon exchange in our CarbonTracker Europe data assimilation system - which currently treats crops as unmanaged grasslands - could strongly improve its ability to constrain terrestrial carbon fluxes. Available long-term observations of crop yield, harvest, and cultivated area allow such improvements, when combined with the new crop-modeling framework we present. This framework can model the carbon fluxes of 10 major European crops at high spatial and temporal resolution, on a 12x12 km grid and 3-hourly time-step. The development of this framework is threefold: firstly, we optimize crop growth using the process-based WOrld FOod STudies (WOFOST) agricultural crop growth model. Simulated yields are downscaled to match regional crop yield observations from the Statistical Office of the European Union (EUROSTAT) by estimating a yearly regional parameter for each crop species: the yield gap factor. This step allows us to better represent crop phenology, to reproduce the observed multiannual European crop yields, and to construct realistic time series of the crop carbon fluxes (gross primary production, GPP, and autotrophic respiration, Raut) on a fine spatial and temporal resolution. Secondly, we combine these GPP and Raut fluxes with a simple soil respiration model to obtain the total ecosystem respiration (TER) and net ecosystem exchange (NEE). And thirdly, we represent the horizontal transport of carbon that follows crop harvest and its back-respiration into the atmosphere during harvest consumption. We distribute this carbon using observations of the density of human and ruminant populations from EUROSTAT. We assess the model's ability to represent the seasonal GPP, TER and NEE fluxes using observations at 6 European FluxNet winter wheat and grain maize sites and compare it with the fluxes of the current terrestrial carbon cycle model of CarbonTracker Europe: the Simple Biosphere - Carnegie-Ames-Stanford Approach (SiBCASA) model. We find that the new model framework provides a detailed, realistic, and strongly observation-driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal, and serve as a new cropland component in CarbonTracker Europe flux estimates.

Kinetics of carbon clustering in detonation of high explosives: Does theory match experiment?

NASA Astrophysics Data System (ADS)

Velizhanin, Kirill; Watkins, Erik; Dattelbaum, Dana; Gustavsen, Richard; Aslam, Tariq; Podlesak, David; Firestone, Millicent; Huber, Rachel; Ringstrand, Bryan; Willey, Trevor; Bagge-Hansen, Michael; Hodgin, Ralph; Lauderbach, Lisa; van Buuren, Tony; Sinclair, Nicholas; Rigg, Paulo; Seifert, Soenke; Gog, Thomas

2017-06-01

Chemical reactions in detonation of carbon-rich high explosives yield carbon clusters as major constituents of the products. Efforts to model carbon clustering as a diffusion-limited irreversible coagulation of carbon clusters go back to the seminal paper by Shaw and Johnson. However, first direct experimental observations of the kinetics of clustering yielded cluster growth one to two orders of magnitude slower than theoretical predictions. Multiple efforts were undertaken to test and revise the basic assumptions of the model in order to achieve better agreement with experiment. We discuss our very recent direct experimental observations of carbon clustering dynamics and demonstrate that these new results are in much better agreement with the modified Shaw-Johnson model. The implications of this much better agreement on our present understanding of detonation carbon clustering processes and possible ways to increase the agreement between theory and experiment even further are discussed.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Scaling and Thermal Evolution of Internally Heated Planets: Yield Stress and Thermal History.

NASA Astrophysics Data System (ADS)

Weller, M. B.; Lenardic, A.; Moore, W. B.

2014-12-01

Using coupled 3D mantle convection and planetary tectonics models of bi-stable systems, we show how system behaviors for mobile-lid and stagnant-lid states scale as functions of internal heating rates (Q) and basal Ra (Rab). With parameter ranges for temperature- and depth-dependant viscosities: 1e4 - 3e4, Rab: 1e5- 3e5, Q: 0 - 100, and yield stress: 1e4 - 2e5, it can be shown the internal temperatures, velocities, heat fluxes, and system behaviors for mobile-lid and stagnant-lid states diverge, for equivalent parameter values, as a function of increasing Q. For the mobile-lid regime, yielding behavior in the upper boundary layer strongly influences the dynamics of the system. Internal temperatures, and consequently temperature-dependant viscosities, vary strongly as a function of yield stress for a given Q. The temperature distribution across the upper and lower mantles are sub-adiabatic for low to moderate yield stress, and adiabatic to super-adiabatic for high yield stresses. Across the parameter range considered, and for fixed yield stress, the Nu across the basal boundary (Nub) is positive and only weakly dependant on Q (varies by ~ 9%). Nub varies strongly as a function of yield stress (maximum variation of ~84%). Both mobile-lid velocities and lid-thicknesses are yield stress dependant for a given Q and Ra. In contrast to mobile-lids, the stagnant-lid regime is governed by the relative inefficiency of heat transport through the surface boundary layer. Internal temperatures are yield stress independent, and are on average 30% greater. Nub has a strong dependence on heating rates and surface boundary layer thicknesses. Within the parameter space considered, the maximum stagnant-lid Nub corresponds to the minimum mobile-lid Nub (for high yield stress), and decreases with increasing Q. For high Q, super-heated stagnant-lids may develop, with Nub< 0, and changes in trends for system behaviors. Planets with high levels of internal heating and/or high yield stresses (e.g. Super-Earths), may favor super-heated stagnant-lids early in their evolution. These regimes indicate reduced heat transport efficiencies (from the nominal stagnant-lid), and as a result, increasing heat flux into the core with increasing Q. Implications for terrestrial and Super-Earth planetary evolution will be discussed.

Canopy temperature for simulation of heat stress in irrigated wheat in a semi-arid environment: a multi-model comparison

USDA-ARS?s Scientific Manuscript database

Mounting evidence suggests that even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals, a phenomenon referred to as heat stress. Recently, ecophysiological models of crops models have begun to represent such phenomena. M...

Geology and ground-water resources in the Zebulon area, Georgia

USGS Publications Warehouse

Chapman, M.J.; Milby, B.J.; Peck, M.F.

1993-01-01

The current (1991) surface-water source of drinking-water supply for the city of Zebulon, Pike County, Georgia, no longer provides an adequate water supply and periodically does not meet water-quality standards. The hydrogeology of crystalline rocks in the Zebulon area was evaluated to assess the potential of ground-water resources as a supplemental or alternative source of water to present surface-water supplies. As part of the ground-water resource evaluation, well location and construction data were compiled, a geologic map was constructed, and ground water was sampled and analyzed. Three mappable geologic units delineated during this study provide a basic understanding of hydrogeologic settings in the Zebulon area. Rock types include a variety of aluminosilicate schists, granitic rocks, amphibolites/honblende gneisses, and gondites. Several geologic features that may enhance ground-water availability were identified in the study area. These features include contacts between contrasting rock types, where a high degree of differential weathering has occurred, and well-developed structural features, such as foliation and jointing are present. High-yielding wells (greater than 25 gallons per minute) and low-yielding wells (less than one gallon per minute) were located in all three geologic units in a variety of topographic settings. Well yields range from less than one gallon per minute to 250 gallons per minute. The variable total depths and wide ranges of casing depths of the high-yielding wells are indicative of variations in depths to water-bearing zones and regolith thicknesses, respectively. The depth of water-bearing zones is highly variable, even on a local scale. Analyses of ground-water samples indicate that the distribution of iron concentration is as variable as well yield in the study area and does not seem to be related to a particular rock type. Iron concentrations in ground-water samples ranged from 0.02 to 5.3 milligrams per liter. Both iron concentration and well yield vary substantially over a relatively small area. Implementation and Verification of a One-Dimensional, Unsteady-Flow Model for Spring Brook near Warrenville, Illinois By Mary J. Turner, Anthony P. Pulokas, and Audrey L. Ishii Abstract A one-dimensional, unsteady-flow model, Full EQuations (FEQ) model, based on de Saint-Venant equations for dynamic flow in open channels, was calibrated and verified for a 0.75-mile reach of Spring Brook, a tributary to the West Branch Du Page River, near Warrenville in northeastern Illinois. The model was used to simulate streamflow in a small urban stream reach with two short culverts, one with overbank flow around the culvert during high flows. Streamflow data were collected on the reach during three high-flow periods. Data from one period were used to calibrate the model, and data from the other two periods were used to verify the model. Stages and discharges over the periods were simulated, and the results were compared graphically with stage and discharge data collected at 10 sites in the study reach. Errors in simulated stage and discharge were small except when debris, not represented in the model, clogged the culvert. The effects of changes in physical and computational model parameters also were studied. The model was insensit'lve to replacement of measured cross sections with interpolated cross sections, especially if the measured thalweg elevation was preserved. Variation of the roughness, slope, and length of the culvert over-bank section, as well as the chosen representative measured cross section, caused only slight changes in the simulated peak stage and discharge. Changes in the modeled culvert area caused large differences in the simulated highflows in the vicinity of the culvert, whereas simulated low flows were unaffected. At all flows, the misrepresentation of the culvert area caused the simulated water-surface elevations to deviate from the measured elevations, especially on the falling

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

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

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph

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

A combinatorial model for dentate gyrus sparse coding

DOE PAGES

Severa, William; Parekh, Ojas; James, Conrad D.; ...

2016-12-29

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation—similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus’s (DG) coding. We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal.To explore the value of this model framework, we assess how suitable it is for twomore » notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG. We find tailoring the model to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Lastly, we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.« less

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

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in Sorghum bicolor

PubMed Central

2013-01-01

Background A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency. Results A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R 2 ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R 2 of 0.94 and RMSEP of 0.64 μg.mgDW-1.h-1. Conclusions This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential. PMID:24365407

Influence of Different Yield Loci on Failure Prediction with Damage Models

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

A Structural Evaluation of a Large-Scale Quasi-Experimental Microfinance Initiative.

PubMed

Kaboski, Joseph P; Townsend, Robert M

2011-09-01

This paper uses a structural model to understand, predict, and evaluate the impact of an exogenous microcredit intervention program, the Thai Million Baht Village Fund program. We model household decisions in the face of borrowing constraints, income uncertainty, and high-yield indivisible investment opportunities. After estimation of parameters using pre-program data, we evaluate the model's ability to predict and interpret the impact of the village fund intervention. Simulations from the model mirror the data in yielding a greater increase in consumption than credit, which is interpreted as evidence of credit constraints. A cost-benefit analysis using the model indicates that some households value the program much more than its per household cost, but overall the program costs 20 percent more than the sum of these benefits.

Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

USGS Publications Warehouse

Robertson, Dale M.; Schwarz, Gregory E.; Saad, David A.; Alexander, Richard B.

2009-01-01

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Monte Carlo simulation of ionizing radiation induced DNA strand breaks utilizing coarse grained high-order chromatin structures.

PubMed

Liang, Ying; Yang, Gen; Liu, Feng; Wang, Yugang

2016-01-07

Ionizing radiation threatens genome integrity by causing DNA damage. Monte Carlo simulation of the interaction of a radiation track structure with DNA provides a powerful tool for investigating the mechanisms of the biological effects. However, the more or less oversimplification of the indirect effect and the inadequate consideration of high-order chromatin structures in current models usually results in discrepancies between simulations and experiments, which undermine the predictive role of the models. Here we present a biophysical model taking into consideration factors that influence indirect effect to simulate radiation-induced DNA strand breaks in eukaryotic cells with high-order chromatin structures. The calculated yields of single-strand breaks and double-strand breaks (DSBs) for photons are in good agreement with the experimental measurements. The calculated yields of DSB for protons and α particles are consistent with simulations by the PARTRAC code, whereas an overestimation is seen compared with the experimental results. The simulated fragment size distributions for (60)Co γ irradiation and α particle irradiation are compared with the measurements accordingly. The excellent agreement with (60)Co irradiation validates our model in simulating photon irradiation. The general agreement found in α particle irradiation encourages model applicability in the high linear energy transfer range. Moreover, we demonstrate the importance of chromatin high-order structures in shaping the spectrum of initial damage.

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.

Ionic liquid [OMIm][OAc] directly inducing oxidation cleavage of the β-O-4 bond of lignin model compounds.

PubMed

Yang, Yingying; Fan, Honglei; Meng, Qinglei; Zhang, Zhaofu; Yang, Guanying; Han, Buxing

2017-08-03

We explored the oxidation reactions of lignin model compounds directly induced by ionic liquids under metal-free conditions. In this work, it was found that ionic liquid 1-octyl-3-methylimidazolium acetate as a solvent could promote the aerobic oxidation of lignin model compound 2-phenoxyacetophenone (1) and the yields of phenol and benzoic acid from 1 could be as high as 96% and 86%, respectively. A possible reaction pathway was proposed based on a series of control experiments. An acetate anion from the ionic liquid attacked the hydrogen from the β-carbon thereby inducing the cleavage of the C-O bond of the aromatic ether. Furthermore, it was found that 2-(2-methoxyphenoxy)-1-phenylethanone (4) with a methoxyl group could also be transformed into aromatic products in this simple reaction system and the yields of phenol and benzoic acid from 4 could be as high as 98% and 85%, respectively. This work provides a simple way for efficient transformation of lignin model compounds.

Trabecular Bone Strength Predictions of HR-pQCT and Individual Trabeculae Segmentation (ITS)-Based Plate and Rod Finite Element Model Discriminate Postmenopausal Vertebral Fractures

PubMed Central

Liu, X. Sherry; Wang, Ji; Zhou, Bin; Stein, Emily; Shi, Xiutao; Adams, Mark; Shane, Elizabeth; Guo, X. Edward

2013-01-01

While high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (μFE) prediction of yield strength by HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high resolution μCT voxel model of 19 trabecular sub-volumes from human cadaveric tibiae samples. Both Young’s modulus and yield strength of HR-pQCT PR models strongly correlated with those of μCT voxel models (r2=0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and CPU time (>1,200-fold). Then, we applied PR model μFE analysis to HR-pQCT images of 60 postmenopausal women with (n=30) and without (n=30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young’s modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for aBMD T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against μCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear μFE prediction of HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. PMID:23456922

Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India

PubMed Central

A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

2017-01-01

India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future. PMID:28753605

Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India.

PubMed

A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

2017-01-01

India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.

Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Akgöl, Batuhan; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2017-02-01

Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.

An analytical model of non-photorespiratory CO₂release in the light and dark in leaves of C₃species based on stoichiometric flux balance.

PubMed

Buckley, Thomas N; Adams, Mark A

2011-01-01

Leaf respiration continues in the light but at a reduced rate. This inhibition is highly variable, and the mechanisms are poorly known, partly due to the lack of a formal model that can generate testable hypotheses. We derived an analytical model for non-photorespiratory CO₂ release by solving steady-state supply/demand equations for ATP, NADH and NADPH, coupled to a widely used photosynthesis model. We used this model to evaluate causes for suppression of respiration by light. The model agrees with many observations, including highly variable suppression at saturating light, greater suppression in mature leaves, reduced assimilatory quotient (ratio of net CO₂ and O₂ exchange) concurrent with nitrate reduction and a Kok effect (discrete change in quantum yield at low light). The model predicts engagement of non-phosphorylating pathways at moderate to high light, or concurrent with processes that yield ATP and NADH, such as fatty acid or terpenoid synthesis. Suppression of respiration is governed largely by photosynthetic adenylate balance, although photorespiratory NADH may contribute at sub-saturating light. Key questions include the precise diel variation of anabolism and the ATP : 2e⁻ ratio for photophosphorylation. Our model can focus experimental research and is a step towards a fully process-based model of CO₂ exchange. © 2010 Blackwell Publishing Ltd.

Using Epidemiological Principles to Explain Fungicide Resistance Management Tactics: Why do Mixtures Outperform Alternations?

PubMed

Elderfield, James A D; Lopez-Ruiz, Francisco J; van den Bosch, Frank; Cunniffe, Nik J

2018-07-01

Whether fungicide resistance management is optimized by spraying chemicals with different modes of action as a mixture (i.e., simultaneously) or in alternation (i.e., sequentially) has been studied by experimenters and modelers for decades. However, results have been inconclusive. We use previously parameterized and validated mathematical models of wheat Septoria leaf blotch and grapevine powdery mildew to test which tactic provides better resistance management, using the total yield before resistance causes disease control to become economically ineffective ("lifetime yield") to measure effectiveness. We focus on tactics involving the combination of a low-risk and a high-risk fungicide, and the case in which resistance to the high-risk chemical is complete (i.e., in which there is no partial resistance). Lifetime yield is then optimized by spraying as much low-risk fungicide as is permitted, combined with slightly more high-risk fungicide than needed for acceptable initial disease control, applying these fungicides as a mixture. That mixture rather than alternation gives better performance is invariant to model parameterization and structure, as well as the pathosystem in question. However, if comparison focuses on other metrics, e.g., lifetime yield at full label dose, either mixture or alternation can be optimal. Our work shows how epidemiological principles can explain the evolution of fungicide resistance, and also highlights a theoretical framework to address the question of whether mixture or alternation provides better resistance management. It also demonstrates that precisely how spray tactics are compared must be given careful consideration. [Formula: see text] Copyright © 2018 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Possibilities for specific utilization of material properties for an optimal part design

NASA Astrophysics Data System (ADS)

Beier, T.; Gerlach, J.; Roettger, R.; Kuhn, P.

2017-09-01

High-strength, cold-formable steels offer great potential for meeting cost and safety requirements in the automotive industry. In view of strengths of up to 1200 MPa now attainable, certain aspects need to be analysed and evaluated in advance in the development process using these materials. In addition to early assessment of crash properties, it is also highly important to adapt the forming process to match the material potential. The steel making companies have widened their portfolios of cold-rolled dual-phase steels well beyond the conventional high-strength steels. There are added new grades which offer a customized selection of high energy absorption, deformation resistance or enhanced cold-forming properties. In this article the necessary components for material modelling for finite element simulation are discussed. Additionally the required tests for material model calibration are presented and the potentials of the thyssenkrupp Steel material data base are introduced. Besides classical tensile tests at different angles to rolling direction and the forming limit curve, the hydraulic bulge test is now available for a wide range of modern steel grades. Using the conventional DP-K®60/98 and the DP-K®700Y980T with higher yield strength the method for calibrating yield locus, hardening and formability is given. With reference to the examples of an A-pillar reinforcement and different crash tests the procedure is shown how the customer can evaluate an optimal steel grade for specific requirements. Although the investigated materials have different yield strengths, no large differences in the forming process between the two steel grades can be found. However some advantages of the high-yield grade can be detected in crash performance depending on the specific boundary and loading conditions.

Yield and Failure Behavior Investigated for Cross-Linked Phenolic Resins Using Molecular Dynamics

NASA Technical Reports Server (NTRS)

Monk, Joshua D.; Lawson, John W.

2016-01-01

Molecular dynamics simulations were conducted to fundamentally evaluate the yield and failure behavior of cross-linked phenolic resins at temperatures below the glass transition. Yield stress was investigated at various temperatures, strain rates, and degrees of cross-linking. The onset of non-linear behavior in the cross-linked phenolic structures was caused by localized irreversible molecular rearrangements through the rotation of methylene linkers followed by the formation or annihilation of neighboring hydrogen bonds. The yield stress results, with respect to temperature and strain rate, could be fit by existing models used to describe yield behavior of amorphous glasses. The degree of cross-linking only indirectly influences the maximum yield stress through its influence on glass transition temperature (Tg), however there is a strong relationship between the degree of cross-linking and the failure mechanism. Low cross-linked samples were able to separate through void formation, whereas the highly cross-linked structures exhibited bond scission.

Wheat yield dynamics: a structural econometric analysis.

PubMed

Sahin, Afsin; Akdi, Yilmaz; Arslan, Fahrettin

2007-10-15

In this study we initially have tried to explore the wheat situation in Turkey, which has a small-open economy and in the member countries of European Union (EU). We have observed that increasing the wheat yield is fundamental to obtain comparative advantage among countries by depressing domestic prices. Also the changing structure of supporting schemes in Turkey makes it necessary to increase its wheat yield level. For this purpose, we have used available data to determine the dynamics of wheat yield by Ordinary Least Square Regression methods. In order to find out whether there is a linear relationship among these series we have checked each series whether they are integrated at the same order or not. Consequently, we have pointed out that fertilizer usage and precipitation level are substantial inputs for producing high wheat yield. Furthermore, in respect for our model, fertilizer usage affects wheat yield more than precipitation level.

Adaptability and Stability Study of Selected Sweet Sorghum Genotypes for Ethanol Production under Different Environments Using AMMI Analysis and GGE Biplots

PubMed Central

Cheruiyot, Erick Kimutai; Othira, Jacktone Odongo; Njuguna, Virginia Wanjiku; Macharia, Joseph Kinyoro; Owuoche, James; Oyier, Moses; Kange, Alex Machio

2016-01-01

The genotype and environment interaction influences the selection criteria of sorghum (Sorghum bicolor) genotypes. Eight sweet sorghum genotypes were evaluated at five different locations in two growing seasons of 2014. The aim was to determine the interaction between genotype and environment on cane, juice, and ethanol yield and to identify best genotypes for bioethanol production in Kenya. The experiments were conducted in a randomized complete block design replicated three times. Sorghum canes were harvested at hard dough stage of grain development and passed through rollers to obtain juice that was then fermented to obtain ethanol. Cane, juice, and ethanol yield was analyzed using the additive main effect and multiplication interaction model (AMMI) and genotype plus genotype by environment (GGE) biplot. The combined analysis of variance of cane and juice yield of sorghum genotypes showed that sweet sorghum genotypes were significantly (P < 0.05) affected by environments (E), genotypes (G) and genotype by environment interaction (GEI). GGE biplot showed high yielding genotypes EUSS10, ACFC003/12, SS14, and EUSS11 for cane yield; EUSS10, EUSS11, and SS14 for juice yield; and EUSS10, SS04, SS14, and ACFC003/12 for ethanol yield. Genotype SS14 showed high general adaptability for cane, juice, and ethanol yield. PMID:27777968

Adaptability and Stability Study of Selected Sweet Sorghum Genotypes for Ethanol Production under Different Environments Using AMMI Analysis and GGE Biplots.

PubMed

Rono, Justice Kipkorir; Cheruiyot, Erick Kimutai; Othira, Jacktone Odongo; Njuguna, Virginia Wanjiku; Macharia, Joseph Kinyoro; Owuoche, James; Oyier, Moses; Kange, Alex Machio

2016-01-01

The genotype and environment interaction influences the selection criteria of sorghum ( Sorghum bicolor ) genotypes. Eight sweet sorghum genotypes were evaluated at five different locations in two growing seasons of 2014. The aim was to determine the interaction between genotype and environment on cane, juice, and ethanol yield and to identify best genotypes for bioethanol production in Kenya. The experiments were conducted in a randomized complete block design replicated three times. Sorghum canes were harvested at hard dough stage of grain development and passed through rollers to obtain juice that was then fermented to obtain ethanol. Cane, juice, and ethanol yield was analyzed using the additive main effect and multiplication interaction model (AMMI) and genotype plus genotype by environment (GGE) biplot. The combined analysis of variance of cane and juice yield of sorghum genotypes showed that sweet sorghum genotypes were significantly ( P < 0.05) affected by environments (E), genotypes (G) and genotype by environment interaction (GEI). GGE biplot showed high yielding genotypes EUSS10, ACFC003/12, SS14, and EUSS11 for cane yield; EUSS10, EUSS11, and SS14 for juice yield; and EUSS10, SS04, SS14, and ACFC003/12 for ethanol yield. Genotype SS14 showed high general adaptability for cane, juice, and ethanol yield.

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Y.; Xiao, J.

2017-12-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of vegetation greening particularly afforestation on the hydrologic cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China's land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation greening and browning on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield or weakened the increase in water yield; vegetation browning reduced ET and increased water yield or weakened the decrease in water yield. At the large river basin and national scales, the greening trends had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the greenness changes on ET and water yield varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrologic cycle are needed to account for the feedbacks to the climate.

Fission fragment yields from heavy-ion-induced reactions measured with a fragment separator

NASA Astrophysics Data System (ADS)

Tarasov, O. B.; Delaune, O.; Farget, F.; Morrissey, D. J.; Amthor, A. M.; Bastin, B.; Bazin, D.; Blank, B.; Cacéres, L.; Chbihi, A.; Fernández-Dominguez, B.; Grévy, S.; Kamalou, O.; Lukyanov, S. M.; Mittig, W.; Pereira, J.; Perrot, L.; Saint-Laurent, M.-G.; Savajols, H.; Sherrill, B. M.; Stodel, C.; Thomas, J. C.; Villari, A. C.

2018-04-01

The systematic study of fission fragment yields under different initial conditions has provided valuable experimental data for benchmarking models of fission product yields. Nuclear reactions using inverse kinematics coupled to the use of a high-resolution spectrometer with good fragment identification are shown here to be a powerful tool to measure the inclusive isotopic yields of fission fragments. In-flight fusion-fission was used in this work to produce secondary beams of neutron-rich isotopes in the collisions of a 238U beam at 24 MeV/u with 9Be and 12C targets at GANIL using the LISE3 fragment separator. Unique identification of the A, Z, and atomic charge state, q, of fission products was attained with the Δ E- TKE-B ρ- ToF measurement technique. Mass, and atomic number distributions are reported for the two reactions. The results show the importance of different reaction mechanisms in the two cases. The optimal target material for higher yields of neutron-rich high- Z isotopes produced in fusion-fission reactions as a function of projectile energy is discussed.

Modeling the Complex Impacts of Timber Harvests to Find Optimal Management Regimes for Amazon Tidal Floodplain Forests

PubMed Central

Fortini, Lucas B.; Cropper, Wendell P.; Zarin, Daniel J.

2015-01-01

At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region’s ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation. PMID:26322896

Modeling the complex impacts of timber harvests to find optimal management regimes for Amazon tidal floodplain forests

USGS Publications Warehouse

Fortini, Lucas B.; Cropper, Wendell P.; Zarin, Daniel J.

2015-01-01

At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region’s ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation.

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.

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.

Method for factor analysis of GC/MS data

DOEpatents

Van Benthem, Mark H; Kotula, Paul G; Keenan, Michael R

2012-09-11

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

Enhanced production of medicinal polysaccharide by submerged fermentation of Lingzhi or Reishi medicinal mushroom Ganoderma lucidium (W.Curt.:Fr.) P. Karst. Using statistical and evolutionary optimization methods.

PubMed

Baskar, Gurunathan; Sathya, Shree Rajesh K

2011-01-01

Statistical and evolutionary optimization of media composition was employed for the production of medicinal exopolysaccharide (EPS) by Lingzhi or Reishi medicinal mushroom Ganoderma lucidium MTCC 1039 using soya bean meal flour as low-cost substrate. Soya bean meal flour, ammonium chloride, glucose, and pH were identified as the most important variables for EPS yield using the two-level Plackett-Burman design and further optimized using the central composite design (CCD) and the artificial neural network (ANN)-linked genetic algorithm (GA). The high value of coefficient of determination of ANN (R² = 0.982) indicates that the ANN model was more accurate than the second-order polynomial model of CCD (R² = 0.91) for representing the effect of media composition on EPS yield. The predicted optimum media composition using ANN-linked GA was soybean meal flour 2.98%, glucose 3.26%, ammonium chloride 0.25%, and initial pH 7.5 for the maximum predicted EPS yield of 1005.55 mg/L. The experimental EPS yield obtained using the predicted optimum media composition was 1012.36 mg/L, which validates the high degree of accuracy of evolutionary optimization for enhanced production of EPS by submerged fermentation of G. lucidium.

Modeling SOA production from the oxidation of intermediate volatility alkanes

NASA Astrophysics Data System (ADS)

Aumont, B.; Mouchel-Vallon, C.; Camredon, M.; Lee-Taylor, J.; Madronich, S.

2012-12-01

Secondary Organic Aerosols (SOA) production and ageing is a multigenerational oxidation process involving the formation of successive organic compounds with higher oxidation degree and lower vapour pressure. This process was investigated using the explicit oxidation model GECKO-A (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere). Results for the C8-C24 n-alkane series show the expected trends, i.e. (i) SOA yield grows with the carbon backbone of the parent hydrocarbon, (ii) SOA yields decreases with the decreasing pre-existing organic aerosol concentration, (iii) the number of generations required to describe SOA production increases when the pre-existing organic aerosol concentration decreases. Most SOA contributors were found to be not oxidized enough to be categorized as highly oxygenated organic aerosols (OOA) but reduced enough to be categorized as hydrocarbon like organic aerosols (HOA). Branched alkanes are more prone to fragment in the early stage of the oxidation than their corresponding linear analogues. Fragmentation is expected to alter both the yield and the mean oxidation state of the SOA. Here, GECKO-A is applied to generate highly detailed oxidation schemes for various series of branched and cyclised alkanes. Branching and cyclisation effects on SOA yields and oxidation states will be examined.

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

PubMed

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

2017-03-27

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

Yielding and deformation behavior of the single crystal nickel-base superalloy PWA 1480

NASA Technical Reports Server (NTRS)

Milligan, W. W., Jr.

1986-01-01

Interrupted tensile tests were conducted to fixed plastic strain levels in 100 ordered single crystals of the nickel based superalloy PWA 1480. Testing was done in the range of 20 to 1093 C, at strain rate of 0.5 and 50%/min. The yield strength was constant from 20 to 760 C, above which the strength dropped rapidly and became a stong function of strain rate. The high temperature data were represented very well by an Arrhenius type equation, which resulted in three distinct temperature regimes. The deformation substructures were grouped in the same three regimes, indicating that there was a fundamental relationship between the deformation mechanisms and activation energies. Models of the yielding process were considered, and it was found that no currently available model was fully applicable to this alloy. It was also demonstrated that the initial deformation mechanism (during yielding) was frequently different from that which would be inferred by examining specimens which were tested to failure.

Pressure and temperature dependence of shear modulus and yield strength for aluminum, copper, and tungsten under shock compression

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

Peng Jianxiang; Jing Fuqian; Li Dahong

2005-07-01

Experimental data for the shear modulus and yield strength of shocked aluminum, copper, and tungsten were systematically analyzed. Comparisons between these data and calculations using the Steinberg-Cochran-Guinan (SCG) constitutive model [D. J. Steinberg, S. G. Cochran, and M. W. Guinan, J. Appl. Phys. 51, 1498 (1980)] indicate that the yield strength has the same dependence on pressure and temperature as the shear modulus for aluminum for shock pressures up to 50 GPa, for copper to 100 GPa, and for tungsten to 200 GPa. Therefore, the assumption of Y{sub p}{sup '}/Y{sub 0}=G{sub p}{sup '}/G{sub 0},Y{sub T}{sup '}/Y{sub 0}=G{sub T}{sup '}/G{sub 0}more » is basically acceptable for these materials, and the SCG model can be used to describe the shear modulus and yield strength of the shocked material at high pressure and temperature.« less

Economic Risk of Bee Pollination in Maine Wild Blueberry, Vaccinium angustifolium.

PubMed

Asare, Eric; Hoshide, Aaron K; Drummond, Francis A; Criner, George K; Chen, Xuan

2017-10-01

Recent pollinator declines highlight the importance of evaluating economic risk of agricultural systems heavily dependent on rented honey bees or native pollinators. Our study analyzed variability of native bees and honey bees, and the risks these pose to profitability of Maine's wild blueberry industry. We used cross-sectional data from organic, low-, medium-, and high-input wild blueberry producers in 1993, 1997-1998, 2005-2007, and from 2011 to 2015 (n = 162 fields). Data included native and honey bee densities (count/m2/min) and honey bee stocking densities (hives/ha). Blueberry fruit set, yield, and honey bee hive stocking density models were estimated. Fruit set is impacted about 1.6 times more by native bees than honey bees on a per bee basis. Fruit set significantly explained blueberry yield. Honey bee stocking density in fields predicted honey bee foraging densities. These three models were used in enterprise budgets for all four systems from on-farm surveys of 23 conventional and 12 organic producers (2012-2013). These budgets formed the basis of Monte Carlo simulations of production and profit. Stochastic dominance of net farm income (NFI) cumulative distribution functions revealed that if organic yields are high enough (2,345 kg/ha), organic systems are economically preferable to conventional systems. However, if organic yields are lower (724 kg/ha), it is riskier with higher variability of crop yield and NFI. Although medium-input systems are stochastically dominant with lower NFI variability compared with other conventional systems, the high-input system breaks even with the low-input system if honey bee hive rental prices triple in the future. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America.

Reduction of ethanol yield from switchgrass infected with rust caused by Puccinia emaculata

DOE PAGES

Sykes, Virginia R.; Allen, Fred L.; Mielenz, Jonathan R.; ...

2015-10-16

Switchgrass ( Panicum virgatum) is an important biofuel crop candidate thought to have low disease susceptibility. As switchgrass production becomes more prevalent, monoculture and production fields in close proximity to one another may increase the spread and severity of diseases such as switchgrass rust caused by the pathogen Puccinia emaculata. The objective of this research was to examine the impact of rust on ethanol yield in switchgrass. In 2010 and 2012, naturally infected leaves from field-grown Alamo and Kanlow in Knoxville, TN (2010, 2012) and Crossville, TN (2012) were visually categorized as exhibiting low, medium, or high disease based onmore » the degree of chlorosis and sporulation. P. emaculata was isolated from each disease range to confirm infection. Samples from 2010 were acid/heat pretreated and subjected to two runs of simultaneous saccharification and fermentation (SSF) with Saccharomyces cerevisiae D 5A to measure ethanol yield. Near-infrared spectroscopy (NIRS) was used to estimate ethanol yield for 2012 samples. SSF and NIRS data were analyzed separately using ANOVA. Disease level effects were significant within both models (P < 0.05) and both models explained a large amount of variation in ETOH (SSF: R 2 = 0.99, NIRS: R 2 = 0.99). In the SSF dataset, ethanol was reduced by 35 % in samples exhibiting medium disease symptoms and by 55 % in samples exhibiting high disease symptoms. In the NIRS dataset, estimated ethanol was reduced by 10 % in samples exhibiting medium disease symptoms and by 21 % in samples exhibiting high disease symptoms. Lastly, results indicate that switchgrass rust will likely have a negative impact on ethanol yield in switchgrass grown as a biofuel crop.« less

Reduction of ethanol yield from switchgrass infected with rust caused by Puccinia emaculata

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

Sykes, Virginia R.; Allen, Fred L.; Mielenz, Jonathan R.

Switchgrass ( Panicum virgatum) is an important biofuel crop candidate thought to have low disease susceptibility. As switchgrass production becomes more prevalent, monoculture and production fields in close proximity to one another may increase the spread and severity of diseases such as switchgrass rust caused by the pathogen Puccinia emaculata. The objective of this research was to examine the impact of rust on ethanol yield in switchgrass. In 2010 and 2012, naturally infected leaves from field-grown Alamo and Kanlow in Knoxville, TN (2010, 2012) and Crossville, TN (2012) were visually categorized as exhibiting low, medium, or high disease based onmore » the degree of chlorosis and sporulation. P. emaculata was isolated from each disease range to confirm infection. Samples from 2010 were acid/heat pretreated and subjected to two runs of simultaneous saccharification and fermentation (SSF) with Saccharomyces cerevisiae D 5A to measure ethanol yield. Near-infrared spectroscopy (NIRS) was used to estimate ethanol yield for 2012 samples. SSF and NIRS data were analyzed separately using ANOVA. Disease level effects were significant within both models (P < 0.05) and both models explained a large amount of variation in ETOH (SSF: R 2 = 0.99, NIRS: R 2 = 0.99). In the SSF dataset, ethanol was reduced by 35 % in samples exhibiting medium disease symptoms and by 55 % in samples exhibiting high disease symptoms. In the NIRS dataset, estimated ethanol was reduced by 10 % in samples exhibiting medium disease symptoms and by 21 % in samples exhibiting high disease symptoms. Lastly, results indicate that switchgrass rust will likely have a negative impact on ethanol yield in switchgrass grown as a biofuel crop.« less

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

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

Tan, Zeli; Leung, L. Ruby; Li, Hongyi

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

Model based adaptive control of a continuous capture process for monoclonal antibodies production.

PubMed

Steinebach, Fabian; Angarita, Monica; Karst, Daniel J; Müller-Späth, Thomas; Morbidelli, Massimo

2016-04-29

A two-column capture process for continuous processing of cell-culture supernatant is presented. Similar to other multicolumn processes, this process uses sequential countercurrent loading of the target compound in order maximize resin utilization and productivity for a given product yield. The process was designed using a novel mechanistic model for affinity capture, which takes both specific adsorption as well as transport through the resin beads into account. Simulations as well as experimental results for the capture of an IgG antibody are discussed. The model was able to predict the process performance in terms of yield, productivity and capacity utilization. Compared to continuous capture with two columns operated batch wise in parallel, a 2.5-fold higher capacity utilization was obtained for the same productivity and yield. This results in an equal improvement in product concentration and reduction of buffer consumption. The developed model was used not only for the process design and optimization but also for its online control. In particular, the unit operating conditions are changed in order to maintain high product yield while optimizing the process performance in terms of capacity utilization and buffer consumption also in the presence of changing upstream conditions and resin aging. Copyright © 2016 Elsevier B.V. All rights reserved.

A High-Resolution Integrated Model of the National Ignition Campaign Cryogenic Layered Experiments

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

Jones, O. S.; Callahan, D. A.; Cerjan, C. J.

A detailed simulation-based model of the June 2011 National Ignition Campaign (NIC) cryogenic DT experiments is presented. The model is based on integrated hohlraum-capsule simulations that utilize the best available models for the hohlraum wall, ablator, and DT equations of state and opacities. The calculated radiation drive was adjusted by changing the input laser power to match the experimentally measured shock speeds, shock merger times, peak implosion velocity, and bangtime. The crossbeam energy transfer model was tuned to match the measured time-dependent symmetry. Mid-mode mix was included by directly modeling the ablator and ice surface perturbations up to mode 60.more » Simulated experimental values were extracted from the simulation and compared against the experiment. The model adjustments brought much of the simulated data into closer agreement with the experiment, with the notable exception of the measured yields, which were 15-40% of the calculated yields.« less

A High-Resolution Integrated Model of the National Ignition Campaign Cryogenic Layered Experiments

DOE PAGES

Jones, O. S.; Callahan, D. A.; Cerjan, C. J.; ...

2012-05-29

A detailed simulation-based model of the June 2011 National Ignition Campaign (NIC) cryogenic DT experiments is presented. The model is based on integrated hohlraum-capsule simulations that utilize the best available models for the hohlraum wall, ablator, and DT equations of state and opacities. The calculated radiation drive was adjusted by changing the input laser power to match the experimentally measured shock speeds, shock merger times, peak implosion velocity, and bangtime. The crossbeam energy transfer model was tuned to match the measured time-dependent symmetry. Mid-mode mix was included by directly modeling the ablator and ice surface perturbations up to mode 60.more » Simulated experimental values were extracted from the simulation and compared against the experiment. The model adjustments brought much of the simulated data into closer agreement with the experiment, with the notable exception of the measured yields, which were 15-40% of the calculated yields.« less

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

Spatially Explicit Estimates of Suspended Sediment and Bedload Transport Rates for Western Oregon and Northwestern California

NASA Astrophysics Data System (ADS)

O'Connor, J. E.; Wise, D. R.; Mangano, J.; Jones, K.

2015-12-01

Empirical analyses of suspended sediment and bedload transport gives estimates of sediment flux for western Oregon and northwestern California. The estimates of both bedload and suspended load are from regression models relating measured annual sediment yield to geologic, physiographic, and climatic properties of contributing basins. The best models include generalized geology and either slope or precipitation. The best-fit suspended-sediment model is based on basin geology, precipitation, and area of recent wildfire. It explains 65% of the variance for 68 suspended sediment measurement sites within the model area. Predicted suspended sediment yields range from no yield from the High Cascades geologic province to 200 tonnes/ km2-yr in the northern Oregon Coast Range and 1000 tonnes/km2-yr in recently burned areas of the northern Klamath terrain. Bed-material yield is similarly estimated from a regression model based on 22 sites of measured bed-material transport, mostly from reservoir accumulation analyses but also from several bedload measurement programs. The resulting best-fit regression is based on basin slope and the presence/absence of the Klamath geologic terrane. For the Klamath terrane, bed-material yield is twice that of the other geologic provinces. This model explains more than 80% of the variance of the better-quality measurements. Predicted bed-material yields range up to 350 tonnes/ km2-yr in steep areas of the Klamath terrane. Applying these regressions to small individual watersheds (mean size; 66 km2 for bed-material; 3 km2 for suspended sediment) and cumulating totals down the hydrologic network (but also decreasing the bed-material flux by experimentally determined attrition rates) gives spatially explicit estimates of both bed-material and suspended sediment flux. This enables assessment of several management issues, including the effects of dams on bedload transport, instream gravel mining, habitat formation processes, and water-quality. The combined fluxes can also be compared to long-term rock uplift and cosmogenically determined landscape erosion rates.

Nuclear model calculation and targetry recipe for production of 110mIn.

PubMed

Kakavand, T; Mirzaii, M; Eslami, M; Karimi, A

2015-10-01

(110m)In is potentially an important positron emitting that can be used in positron emission tomography. In this work, the excitation functions and production yields of (110)Cd(d, 2n), (111)Cd(d, 3n), (nat)Cd(d, xn), (110)Cd(p, n), (111)Cd(p, 2n), (112)Cd(p, 3n) and (nat)Cd(p, xn) reactions to produce the (110m)In were calculated using nuclear model code TALYS and compared with the experimental data. The yield of isomeric state production of (110)In was also compared with ground state production ones to reach the optimal energy range of projectile for the high yield production of metastable state. The results indicate that the (110)Cd(p, n)(110m)In is a high yield reaction with an isomeric ratio (σ(m)/σ(g)) of about 35 within the optimal incident energy range of 15-5 MeV. To make the target, cadmium was electroplated on a copper substrate in varying electroplating conditions such as PH, DC current density, temperature and time. A set of cold tests were also performed on the final sample under several thermal shocks to verify target resistance. The best electroplated cadmium target was irradiated with 15 MeV protons at current of 100 µA for one hour and the production yield of (110m)In and other byproducts were measured. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the effect of shear strength on isentropic compression experiments

NASA Astrophysics Data System (ADS)

Thomson, Stuart; Howell, Peter; Ockendon, John; Ockendon, Hilary

2017-01-01

Isentropic compression experiments (ICE) are a way of obtaining equation of state information for metals undergoing violent plastic deformation. In a typical experiment, millimetre thick metal samples are subjected to pressures on the order of 10 - 102 GPa, while the yield strength of the material can be as low as 10-2 GPa. The analysis of such experiments has so far neglected the effect of shear strength, instead treating the highly plasticised metal as an inviscid compressible fluid. However making this approximation belies the basic elastic nature of a solid object. A more accurate method should strive to incorporate the small but measurable effects of shear strength. Here we present a one-dimensional mathematical model for elastoplasticity at high stress which allows for both compressibility and the shear strength of the material. In the limit of zero yield stress this model reproduces the hydrodynamic models currently used to analyse ICEs. Numerical solutions of the governing equations will then be presented for problems relevant to ICEs in order to investigate the effects of shear strength compared with a model based purely on hydrodynamics.

Modeling Propagation of Shock Waves in Metals

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

Howard, W M; Molitoris, J D

2005-08-19

We present modeling results for the propagation of strong shock waves in metals. In particular, we use an arbitrary Lagrange Eulerian (ALE3D) code to model the propagation of strong pressure waves (P {approx} 300 to 400 kbars) generated with high explosives in contact with aluminum cylinders. The aluminum cylinders are assumed to be both flat-topped and have large-amplitude curved surfaces. We use 3D Lagrange mechanics. For the aluminum we use a rate-independent Steinberg-Guinan model, where the yield strength and shear modulus depend on pressure, density and temperature. The calculation of the melt temperature is based on the Lindermann law. Atmore » melt the yield strength and shear modulus is set to zero. The pressure is represented as a seven-term polynomial as a function of density. For the HMX-based high explosive, we use a JWL, with a program burn model that give the correct detonation velocity and C-J pressure (P {approx} 390 kbars). For the case of the large-amplitude curved surface, we discuss the evolving shock structure in terms of the early shock propagation experiments by Sakharov.« less

Modeling Propagation of Shock Waves in Metals

NASA Astrophysics Data System (ADS)

Howard, W. M.; Molitoris, J. D.

2006-07-01

We present modeling results for the propagation of strong shock waves in metals. In particular, we use an arbitrary Lagrange Eulerian (ALE3D) code to model the propagation of strong pressure waves (P ˜ 300 to 400 kbars) generated with high explosives in contact with aluminum cylinders. The aluminum cylinders are assumed to be both flat-topped and have large-amplitude curved surfaces. We use 3D Lagrange mechanics. For the aluminum we use a rate-independent Steinberg-Guinan model, where the yield strength and shear modulus depend on pressure, density and temperature. The calculation of the melt temperature is based on the Lindermann law. At melt the yield strength and shear modulus is set to zero. The pressure is represented as a seven-term polynomial as a function of density. For the HMX-based high explosive, we use a JWL, with a program burn model that give the correct detonation velocity and C-J pressure (P ˜ 390 kbars). For the case of the large-amplitude curved surface, we discuss the evolving shock structure in terms of the early shock propagation experiments by Sakharov.

The atmosphere of the primitive earth and the prebiotic synthesis of organic compounds

NASA Technical Reports Server (NTRS)

Miller, S. L.; Schlesinger, G.

1983-01-01

The prebiotic synthesis of organic compounds is investigated using a spark discharge on various simulated prebiotic atmospheres at 25 C. It is found that glycine is almost the only amino acid produced from the model atmospheres containing CO and CO2. These results show that the maximum yield is about the same for the three carbon sources (CO, CO2, and CH4) at high H2/carbon ratios, but that CH4 is superior at low H2/carbon ratios. CH4 is found to yield a much greater variety of amino acids than either CO or CO2. If it is assumed that amino acids more complex than glycine were required for the origin of life, then these findings indicate the need for CH4 in the primitive atmosphere. The yields of cyanide and formaldehyde are shown to parallel the amino acid results, with yields of HCN and H2CO as high as 13 percent based on carbon. Ammonia is also found to be produced from N2 in experiments with no added NH3 in yields as high as 4.9 percent. These results indicate that large amounts of NH3 would have been synthesized on the primitive earth by electric discharges.

Isochoric Implosions for Fast Ignition

NASA Astrophysics Data System (ADS)

Clark, Daniel; Tabak, Max

2006-10-01

Various gain models have shown the potentially great advantages of Fast Ignition (FI) Inertial Confinement Fusion (ICF) over its conventional hotspot ignition counterpart. These gain models, however, all assume nearly uniform-density fuel assemblies. By contrast, typical ICF implosions yield hollowed fuel assemblies with a high-density shell of fuel surrounding a low-density, high-pressure hotspot. To realize fully the advantages of FI, then, an alternative implosion design must be found which yields nearly isochoric fuel assemblies without substantial hotspots. Here, it is shown that a self-similar spherical implosion of the type originally studied by Guderley [Luftfahrtforschung 19, 302 (1942)] may be employed to yield precisely such quasi-isochoric imploded states. The difficulty remains, however, of accessing these self-similarly imploding configurations from initial conditions representing an actual ICF target, namely a uniform, solid-density shell at rest. Furthermore, these specialized implosions must be realized for practicable drive parameters, i.e., accessible peak pressures, shell aspect ratios, etc. An implosion scheme is presented which meets all of these requirements, suggesting the possibility of genuinely isochoric implosions for FI.

Modeling SOA formation from the oxidation of intermediate volatility n-alkanes

NASA Astrophysics Data System (ADS)

Aumont, B.; Valorso, R.; Mouchel-Vallon, C.; Camredon, M.; Lee-Taylor, J.; Madronich, S.

2012-08-01

The chemical mechanism leading to SOA formation and ageing is expected to be a multigenerational process, i.e. a successive formation of organic compounds with higher oxidation degree and lower vapor pressure. This process is here investigated with the explicit oxidation model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere). Gas phase oxidation schemes are generated for the C8-C24 series of n-alkanes. Simulations are conducted to explore the time evolution of organic compounds and the behavior of secondary organic aerosol (SOA) formation for various preexisting organic aerosol concentration (COA). As expected, simulation results show that (i) SOA yield increases with the carbon chain length of the parent hydrocarbon, (ii) SOA yield decreases with decreasing COA, (iii) SOA production rates increase with increasing COA and (iv) the number of oxidation steps (i.e. generations) needed to describe SOA formation and evolution grows when COA decreases. The simulated oxidative trajectories are examined in a two dimensional space defined by the mean carbon oxidation state and the volatility. Most SOA contributors are not oxidized enough to be categorized as highly oxygenated organic aerosols (OOA) but reduced enough to be categorized as hydrocarbon like organic aerosols (HOA), suggesting that OOA may underestimate SOA. Results show that the model is unable to produce highly oxygenated aerosols (OOA) with large yields. The limitations of the model are discussed.

Modeling SOA formation from the oxidation of intermediate volatility n-alkanes

NASA Astrophysics Data System (ADS)

Aumont, B.; Valorso, R.; Mouchel-Vallon, C.; Camredon, M.; Lee-Taylor, J.; Madronich, S.

2012-06-01

The chemical mechanism leading to SOA formation and ageing is expected to be a multigenerational process, i.e. a successive formation of organic compounds with higher oxidation degree and lower vapor pressure. This process is here investigated with the explicit oxidation model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere). Gas phase oxidation schemes are generated for the C8-C24 series of n-alkanes. Simulations are conducted to explore the time evolution of organic compounds and the behavior of secondary organic aerosol (SOA) formation for various preexisting organic aerosol concentration (COA). As expected, simulation results show that (i) SOA yield increases with the carbon chain length of the parent hydrocarbon, (ii) SOA yield decreases with decreasing COA, (iii) SOA production rates increase with increasing COA and (iv) the number of oxidation steps (i.e. generations) needed to describe SOA formation and evolution grows when COA decreases. The simulated oxidative trajectories are examined in a two dimensional space defined by the mean carbon oxidation state and the volatility. Most SOA contributors are not oxidized enough to be categorized as highly oxygenated organic aerosols (OOA) but reduced enough to be categorized as hydrocarbon like organic aerosols (HOA), suggesting that OOA may underestimate SOA. Results show that the model is unable to produce highly oxygenated aerosols (OOA) with large yields. The limitations of the model are discussed.

Vulnerability of Agriculture to Climate Change as Revealed by Relationships between Simulated Crop Yield and Climate Change Indices

NASA Astrophysics Data System (ADS)

King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.

2012-12-01

The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of vulnerability analysis. They also contribute to considerations of adaptation, focusing attention on adapting to increased variability in yield rather than just reductions in yield. For example, in the face of increased variability or reduced reliability, hedging and risk spreading strategies may be more important than technological innovations such as drought-resistant crops or other optimization strategies. Our findings also have implications for the choice and application of climate extreme indices, demands on models used to project climate change and the development of next generation integrated assessment models (IAM) that incorporate the agricultural sector, and especially adaption within that sector, in energy and broader more general markets.

Application of activated barrier hopping theory to viscoplastic modeling of glassy polymers

NASA Astrophysics Data System (ADS)

Sweeney, J.; Spencer, P. E.; Vgenopoulos, D.; Babenko, M.; Boutenel, F.; Caton-Rose, P.; Coates, P. D.

2018-05-01

An established statistical mechanical theory of amorphous polymer deformation has been incorporated as a plastic mechanism into a constitutive model and applied to a range of polymer mechanical deformations. The temperature and rate dependence of the tensile yield of PVC, as reported in early studies, has been modeled to high levels of accuracy. Tensile experiments on PET reported here are analyzed similarly and good accuracy is also achieved. The frequently observed increase in the gradient of the plot of yield stress against logarithm of strain rate is an inherent feature of the constitutive model. The form of temperature dependence of the yield that is predicted by the model is found to give an accurate representation. The constitutive model is developed in two-dimensional form and implemented as a user-defined subroutine in the finite element package ABAQUS. This analysis is applied to the tensile experiments on PET, in some of which strain is localized in the form of shear bands and necks. These deformations are modeled with partial success, though adiabatic heating of the instability causes inaccuracies for this isothermal implementation of the model. The plastic mechanism has advantages over the Eyring process, is equally tractable, and presents no particular difficulties in implementation with finite elements.

Application of activated barrier hopping theory to viscoplastic modeling of glassy polymers

NASA Astrophysics Data System (ADS)

Sweeney, J.; Spencer, P. E.; Vgenopoulos, D.; Babenko, M.; Boutenel, F.; Caton-Rose, P.; Coates, P. D.

2017-10-01

An established statistical mechanical theory of amorphous polymer deformation has been incorporated as a plastic mechanism into a constitutive model and applied to a range of polymer mechanical deformations. The temperature and rate dependence of the tensile yield of PVC, as reported in early studies, has been modeled to high levels of accuracy. Tensile experiments on PET reported here are analyzed similarly and good accuracy is also achieved. The frequently observed increase in the gradient of the plot of yield stress against logarithm of strain rate is an inherent feature of the constitutive model. The form of temperature dependence of the yield that is predicted by the model is found to give an accurate representation. The constitutive model is developed in two-dimensional form and implemented as a user-defined subroutine in the finite element package ABAQUS. This analysis is applied to the tensile experiments on PET, in some of which strain is localized in the form of shear bands and necks. These deformations are modeled with partial success, though adiabatic heating of the instability causes inaccuracies for this isothermal implementation of the model. The plastic mechanism has advantages over the Eyring process, is equally tractable, and presents no particular difficulties in implementation with finite elements.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

Effects of geoengineering on crop yields

NASA Astrophysics Data System (ADS)

Pongratz, J.; Lobell, D. B.; Cao, L.; Caldeira, K.

2011-12-01

The potential of "solar radiation management" (SRM) to reduce future climate change and associated risks has been receiving significant attention in scientific and policy circles. SRM schemes aim to reduce global warming despite increasing atmospheric CO2 concentrations by diminishing the amount of solar insolation absorbed by the Earth, for example, by injecting scattering aerosols into the atmosphere. Climate models predict that SRM could fully compensate warming at the global mean in a high-CO2 world. While reduction of global warming may offset a part of the predicted negative effects of future climate change on crop yields, SRM schemes are expected to alter regional climate and to have substantial effects on climate variables other than temperature, such as precipitation. It has therefore been warned that, overall, SRM may pose a risk to food security. Assessments of benefits and risks of geoengineering are imperative, yet such assessments are only beginning to emerge; in particular, effects on global food security have not previously been assessed. Here, for the first time, we combine climate model simulations with models of crop yield responses to climate to assess large-scale changes in yields and food production under SRM. In most crop-growing regions, we find that yield losses caused by climate changes are substantially reduced under SRM as compared with a non-geoengineered doubling of atmospheric CO2. Substantial yield losses with SRM are only found for rice in high latitudes, where the limits of low temperatures are no longer alleviated. At the same time, the beneficial effect of CO2-fertilization on plant productivity remains active. Overall therefore, SRM in our models causes global crop yields to increase. We estimate the direct effects of climate and CO2 changes on crop production, and do not quantify effects of market dynamics and management changes. We note, however, that an SRM deployment would be unlikely to maintain the economic status quo, as market shares of agricultural output may change with the different spatial pattern of climate change. More importantly, geoengineering by SRM does not address a range of other detrimental consequences of climate change, such as ocean acidification, which could also affect food security via effects on marine food webs. Finally, SRM poses substantial anticipated and unanticipated risks by interfering with complex, not fully understood systems. Therefore, despite potential positive effects of SRM on crop yields, the most certain way to reduce climate risks to global food security is to reduce emissions of greenhouse gases.

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.

Contributions of atmospheric nitrogen deposition to U.S. estuaries: Summary and conclusions: Chapter 8

USGS Publications Warehouse

Stacey, Paul E.; Greening, Holly; Kremer, James N.; Peterson, David; Tomasko, David A.; Valigura, Richard A.; Alexander, Richard B.; Castro, Mark S.; Meyers, Tilden P.; Paerl, Hans W.; Stacey, Paul E.; Turner, R. Eugene

2001-01-01

A NOAA project was initiated in 1998, with support from the U.S. EPA, to develop state-of-the-art estimates of atmospheric N deposition to estuarine watersheds and water surfaces and its delivery to the estuaries. Work groups were formed to address N deposition rates, indirect (from the watershed) yields from atmospheric and other anthropogenic sources, and direct deposition on the estuarine waterbodies, and to evaluate the levels of uncertainty within the estimates. Watershed N yields were estimated using both a land-use based process approach and a national (SPARROW) model, compared to each other, and compared to estimates of N yield from the literature. The total N yields predicted by the national model were similar to values found in the literature and the land-use derived estimates were consistently higher. Atmospheric N yield estimates were within a similar range for the two approaches, but tended to be higher in the land-use based estimates and were not wellcorrelated. Median atmospheric N yields were around 15% of the total N yield for both groups, but ranged as high as 60% when both direct and indirect deposition were considered. Although not the dominant source of anthropogenic N, atmospheric N is, and will undoubtedly continue to be, an important factor in culturally eutrophied estuarine systems, warranting additional research and management attention.

Towards systematic evaluation of crop model outputs for global land-use models

NASA Astrophysics Data System (ADS)

Leclere, David; Azevedo, Ligia B.; Skalský, Rastislav; Balkovič, Juraj; Havlík, Petr

2016-04-01

Land provides vital socioeconomic resources to the society, however at the cost of large environmental degradations. Global integrated models combining high resolution global gridded crop models (GGCMs) and global economic models (GEMs) are increasingly being used to inform sustainable solution for agricultural land-use. However, little effort has yet been done to evaluate and compare the accuracy of GGCM outputs. In addition, GGCM datasets require a large amount of parameters whose values and their variability across space are weakly constrained: increasing the accuracy of such dataset has a very high computing cost. Innovative evaluation methods are required both to ground credibility to the global integrated models, and to allow efficient parameter specification of GGCMs. We propose an evaluation strategy for GGCM datasets in the perspective of use in GEMs, illustrated with preliminary results from a novel dataset (the Hypercube) generated by the EPIC GGCM and used in the GLOBIOM land use GEM to inform on present-day crop yield, water and nutrient input needs for 16 crops x 15 management intensities, at a spatial resolution of 5 arc-minutes. We adopt the following principle: evaluation should provide a transparent diagnosis of model adequacy for its intended use. We briefly describe how the Hypercube data is generated and how it articulates with GLOBIOM in order to transparently identify the performances to be evaluated, as well as the main assumptions and data processing involved. Expected performances include adequately representing the sub-national heterogeneity in crop yield and input needs: i) in space, ii) across crop species, and iii) across management intensities. We will present and discuss measures of these expected performances and weight the relative contribution of crop model, input data and data processing steps in performances. We will also compare obtained yield gaps and main yield-limiting factors against the M3 dataset. Next steps include iterative improvement of parameter assumptions and evaluation of implications of GGCM performances for intended use in the IIASA EPIC-GLOBIOM model cluster. Our approach helps targeting future efforts at improving GGCM accuracy and would achieve highest efficiency if combined with traditional field-scale evaluation and sensitivity analysis.

A Structural Evaluation of a Large-Scale Quasi-Experimental Microfinance Initiative

PubMed Central

Kaboski, Joseph P.; Townsend, Robert M.

2010-01-01

This paper uses a structural model to understand, predict, and evaluate the impact of an exogenous microcredit intervention program, the Thai Million Baht Village Fund program. We model household decisions in the face of borrowing constraints, income uncertainty, and high-yield indivisible investment opportunities. After estimation of parameters using pre-program data, we evaluate the model’s ability to predict and interpret the impact of the village fund intervention. Simulations from the model mirror the data in yielding a greater increase in consumption than credit, which is interpreted as evidence of credit constraints. A cost-benefit analysis using the model indicates that some households value the program much more than its per household cost, but overall the program costs 20 percent more than the sum of these benefits. PMID:22162594

Macromod: Computer Simulation For Introductory Economics

ERIC Educational Resources Information Center

Ross, Thomas

1977-01-01

The Macroeconomic model (Macromod) is a computer assisted instruction simulation model designed for introductory economics courses. An evaluation of its utilization at a community college indicates that it yielded a 10 percent to 13 percent greater economic comprehension than lecture classes and that it met with high student approval. (DC)

Do increases in cigarette prices lead to increases in sales of cigarettes with high tar and nicotine yields?

PubMed

Farrelly, Matthew C; Loomis, Brett R; Mann, Nathan H

2007-10-01

We used scanner data on cigarette prices and sales collected from supermarkets across the United States from 1994 to 2004 to test the hypothesis that cigarette prices are positively correlated with sales of cigarettes with higher tar and nicotine content. During this period the average inflation-adjusted price for menthol cigarettes increased 55.8%. Price elasticities from multivariate regression models suggest that this price increase led to an increase of 1.73% in sales-weighted average tar yields and a 1.28% increase in sales-weighted average nicotine yields for menthol cigarettes. The 50.5% price increase of nonmenthol varieties over the same period yielded an estimated increase of 1% in tar per cigarette but no statistically significant increase in nicotine yields. An ordered probit model of the impact of cigarette prices on cigarette strength (ultra-light, light, full flavor, unfiltered) offers an explanation: As cigarette prices increase, the probability that stronger cigarette types will be sold increases. This effect is larger for menthol than for nonmenthol cigarettes. Our results are consistent with earlier population-based cross-sectional and longitudinal studies showing that higher cigarette prices and taxes are associated with increasing consumption of higher-yield cigarettes by smokers.

Biofilms promote altruism.

PubMed

Kreft, Jan-Ulrich

2004-08-01

The origin of altruism is a fundamental problem in evolution, and the maintenance of biodiversity is a fundamental problem in ecology. These two problems combine with the fundamental microbiological question of whether it is always advantageous for a unicellular organism to grow as fast as possible. The common basis for these three themes is a trade-off between growth rate and growth yield, which in turn is based on irreversible thermodynamics. The trade-off creates an evolutionary alternative between two strategies: high growth yield at low growth rate versus high growth rate at low growth yield. High growth yield at low growth rate is a case of an altruistic strategy because it increases the fitness of the group by using resources economically at the cost of decreased fitness, or growth rate, of the individual. The group-beneficial behaviour is advantageous in the long term, whereas the high growth rate strategy is advantageous in the short term. Coexistence of species requires differences between their niches, and niche space is typically divided into four 'axes' (time, space, resources, predators). This neglects survival strategies based on cooperation, which extend the possibilities of coexistence, arguing for the inclusion of cooperation as the fifth 'axis'. Here, individual-based model simulations show that spatial structure, as in, for example, biofilms, is necessary for the origin and maintenance of this 'primitive' altruistic strategy and that the common belief that growth rate but not yield decides the outcome of competition is based on chemostat models and experiments. This evolutionary perspective on life in biofilms can explain long-known biofilm characteristics, such as the structural organization into microcolonies, the often-observed lack of mixing among microcolonies, and the shedding of single cells, as promoting the origin and maintenance of the altruistic strategy. Whereas biofilms enrich altruists, enrichment cultures, microbiology's paradigm for isolating bacteria into pure culture, select for highest growth rate.

Root Traits Enhancing Rice Grain Yield under Alternate Wetting and Drying Condition

PubMed Central

Sandhu, Nitika; Subedi, Sushil R.; Yadaw, Ram B.; Chaudhary, Bedanand; Prasai, Hari; Iftekharuddaula, Khandakar; Thanak, Tho; Thun, Vathany; Battan, Khushi R.; Ram, Mangat; Venkateshwarlu, Challa; Lopena, Vitaliano; Pablico, Paquito; Maturan, Paul C.; Cruz, Ma. Teresa Sta.; Raman, K. Anitha; Collard, Bertrand; Kumar, Arvind

2017-01-01

Reducing water requirements and lowering environmental footprints require attention to minimize risks to food security. The present study was conducted with the aim to identify appropriate root traits enhancing rice grain yield under alternate wetting and drying conditions (AWD) and identify stable, high-yielding genotypes better suited to the AWD across variable ecosystems. Advanced breeding lines, popular rice varieties and drought-tolerant lines were evaluated in a series of 23 experiments conducted in the Philippines, India, Bangladesh, Nepal and Cambodia in 2015 and 2016. A large variation in grain yield under AWD conditions enabled the selection of high-yielding and stable genotypes across locations, seasons and years. Water savings of 5.7–23.4% were achieved without significant yield penalty across different ecosystems. The mean grain yield of genotypes across locations ranged from 3.5 to 5.6 t/ha and the mean environment grain yields ranged from 3.7 (Cambodia) to 6.6 (India) t/ha. The best-fitting Finlay-Wilkinson regression model identified eight stable genotypes with mean grain yield of more than 5.0 t/ha across locations. Multidimensional preference analysis represented the strong association of root traits (nodal root number, root dry weight at 22 and 30 days after transplanting) with grain yield. The genotype IR14L253 outperformed in terms of root traits and high mean grain yield across seasons and six locations. The 1.0 t/ha yield advantage of IR14L253 over the popular cultivar IR64 under AWD shall encourage farmers to cultivate IR14L253 and also adopt AWD. The results suggest an important role of root architectural traits in term of more number of nodal roots and root dry weight at 10–20 cm depth on 22–30 days after transplanting (DAT) in providing yield stability and preventing yield reduction under AWD compared to continuous flooded conditions. Genotypes possessing increased number of nodal roots provided higher yield over IR64 as well as no yield reduction under AWD compared to flooded irrigation. The identification of appropriate root architecture traits at specific depth and specific growth stage shall help breeding programs develop better rice varieties for AWD conditions. PMID:29163604

Drought Tolerance during Reproductive Development is Important for Increasing wheat yield Potential under Climate change in Europe.

PubMed

Senapati, Nimai; Stratonovitch, Pierre; Paul, Matthew J; Semenov, Mikhail A

2018-06-12

Drought stress during reproductive development could drastically reduce grain number and wheat yield, but quantitative evaluation of such effect is unknown under climate change. The objectives of this study were to a) evaluate potential yield benefits of drought tolerance during reproductive development for wheat ideotypes under climate change in Europe, and b) identify potential cultivar parameters for improvement. We used the Sirius wheat model to optimise drought tolerant (DT) and drought sensitive (DS) wheat ideotypes under future 2050 climate scenario at 13 contrasting sites, representing major wheat growing regions in Europe. Averaged over the sites, DT ideotypes achieved 13.4% greater yield compared to DS, with the double yield stability for DT. However, the performances of the ideotypes were site dependent. Mean yield of DT was 28-37% greater compared to DS in southern Europe. In contrast, no yield difference (≤ 1%) between ideotypes was found in north-western Europe. An intermediate yield benefit of 10-23% was found due to drought tolerance in central and eastern Europe. We conclude that tolerance to drought stress during reproductive development is important for high yield potentials and greater yield stability of wheat under climate change in Europe.

Climate Change Impacts on Agriculture and Food Security in 2050 under a Range of Plausible Socioeconomic and Emissions Scenarios

NASA Astrophysics Data System (ADS)

Wiebe, K.; Lotze-Campen, H.; Bodirsky, B.; Kavallari, A.; Mason-d'Croz, D.; van der Mensbrugghe, D.; Robinson, S.; Sands, R.; Tabeau, A.; Willenbockel, D.; Islam, S.; van Meijl, H.; Mueller, C.; Robertson, R.

2014-12-01

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. New work extends that analysis to cover a range of plausible socioeconomic scenarios and emission pathways. Results from three general circulation models are combined with one crop model and five global economic models to examine the global and regional impacts of climate change on yields, area, production, prices and trade for coarse grains, rice, wheat, oilseeds and sugar to 2050. Results show that yield impacts vary with changes in population, income and technology as well as emissions, but are reduced in all cases by endogenous changes in prices and other variables.

Regional Magnitude Research Supporting Broad-Area Monitoring of Small Seismic Events

DTIC Science & Technology

2007-09-01

detonated at the Nevada Test Site (NTS) and the Semipalatinsk Test Site (STS). Observations for both test sites show that Pn amplitudes yield scale 10...identification procedures, and yield, via direct comparison to test site results for high frequencies (>1 Hz). Coda techniques are known to be effective...2006). Source spectral modeling of regional P/S discriminants at nuclear test sites in China and the former Soviet Union, Bull. Seismol. Soc. Am

Research in Energetic Compounds.

DTIC Science & Technology

1985-01-01

CH 2 2 2 I R It has been reported, however, that the hydrolysis of dihalo hexane diepoxides yields the isomeric bicyclo[3.3.0]-2,6-dioxaoctanes 4...as model compounds. Hexitols, such as D-mannitol, give high yields of 4,8-dihydroxybi- cyclor3.3.0]-2,6-dioxaoctane 4 by dehydration with...C (0.1 mm). Continued distillation resulted in violent exothermic decomposition . The distilled sample also decomposed within one day. This material

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.

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.

Assessing and modelling ecohydrologic processes at the agricultural field scale

NASA Astrophysics Data System (ADS)

Basso, Bruno

2015-04-01

One of the primary goals of agricultural management is to increase the amount of crop produced per unit of fertilizer and water used. World record corn yields demonstrated that water use efficiency can increase fourfold with improved agronomic management and cultivars able to tolerate high densities. Planting crops with higher plant density can lead to significant yield increases, and increase plant transpiration vs. soil water evaporation. Precision agriculture technologies have been adopted for the last twenty years but seldom have the data collected been converted to information that led farmers to different agronomic management. These methods are intuitively appealing, but yield maps and other spatial layers of data need to be properly analyzed and interpreted to truly become valuable. Current agro-mechanic and geospatial technologies allow us to implement a spatially variable plan for agronomic inputs including seeding rate, cultivars, pesticides, herbicides, fertilizers, and water. Crop models are valuable tools to evaluate the impact of management strategies (e.g., cover crops, tile drains, and genetically-improved cultivars) on yield, soil carbon sequestration, leaching and greenhouse gas emissions. They can help farmers identify adaptation strategies to current and future climate conditions. In this paper I illustrate the key role that precision agriculture technologies (yield mapping technologies, within season soil and crop sensing), crop modeling and weather can play in dealing with the impact of climate variability on soil ecohydrologic processes. Case studies are presented to illustrate this concept.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations.

PubMed

Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng

2017-03-15

With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Observation of isoprene hydroxynitrates in the southeastern United States and implications for the fate of NOx

NASA Astrophysics Data System (ADS)

Xiong, F.; McAvey, K. M.; Pratt, K. A.; Groff, C. J.; Hostetler, M. A.; Lipton, M. A.; Starn, T. K.; Seeley, J. V.; Bertman, S. B.; Teng, A. P.; Crounse, J. D.; Nguyen, T. B.; Wennberg, P. O.; Misztal, P. K.; Goldstein, A. H.; Guenther, A. B.; Koss, A. R.; Olson, K. F.; de Gouw, J. A.; Baumann, K.; Edgerton, E. S.; Feiner, P. A.; Zhang, L.; Miller, D. O.; Brune, W. H.; Shepson, P. B.

2015-10-01

Isoprene hydroxynitrates (IN) are tracers of the photochemical oxidation of isoprene in high NOx environments. Production and loss of IN have a significant influence on the NOx cycle and tropospheric O3 chemistry. To better understand IN chemistry, a series of photochemical reaction chamber experiments was conducted to determine the IN yield from isoprene photooxidation at high NO concentrations (> 100 ppt). By combining experimental data and calculated isomer distributions, a total IN yield of 9(+4/-3) % was derived. The result was applied in a zero-dimensional model to simulate production and loss of ambient IN observed in a temperate forest atmosphere, during the Southern Oxidant and Aerosol Study (SOAS) field campaign, from 27 May to 11 July 2013. The 9 % yield was consistent with the observed IN/(MVK+MACR) ratios observed during SOAS. By comparing field observations with model simulations, we identified NO as the limiting factor for ambient IN production during SOAS, but vertical mixing at dawn might also contribute (~ 27 %) to IN dynamics. A close examination of isoprene's oxidation products indicates that its oxidation transitioned from a high-NO dominant chemical regime in the morning into a low-NO dominant regime in the afternoon. A significant amount of IN produced in the morning high NO regime could be oxidized in the low NO regime, and a possible reaction scheme was proposed.

Prebiotic Synthesis of Diaminopyrimidine and Thiocytosine

NASA Technical Reports Server (NTRS)

Robertson, Michael P.; Levy, Matthew; Miller, Stanley L.

1996-01-01

The reaction of guanidine hydrochloride with cyanoacetaldehyde gives high yields (40-85%) of 2,4-diaminopyrimidine under the concentrated conditions of a drying lagoon model of prebiotic synthesis, in contrast to the low yields previously obtained under more dilute conditions. The prebiotic source of cyanoacetaldehyde, cyanoacetylene, is produced from electric discharges under reducing conditions. The effect of pH and concentration of guanidine hydrochloride on the rate of synthesis and yield of diaminopyrimidine were investigated, as well as the hydrolysis of diaminopyrimidine to cytosine, isocytosine, and uracil. Thiourea also reacts with cyanoacetaldehyde to give 2-thiocytosine, but the pyrimidine yields are much lower than with guanidine hydrochloride or urea. Thiocytosine hydrolyzes to thiouracil and cytosine and then to uracil. This synthesis would have been a significant prebiotic source of 2-thiopyrimidines and 5-substituted derivatives of thiouracil, many of which occur in tRNA. The applicability of these results to the drying lagoon model of prebiotic synthesis was tested by dry-down experiments where dilute solutions of cyanoacetaldehyde, guanidine hydrochloride, and 0.5 M NaCl were evaporated over varying periods of time. The yields of diaminopyrimidine varied from 1 to 7%. These results show that drying lagoons and beaches may have been major sites of prebiotic syntheses.

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV)], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

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

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

USGS Publications Warehouse

Waldron, Marcus C.; Archfield, Stacey A.

2006-01-01

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the historical record is not valid. For multiple-reservoir systems, the firm-yield estimate was dependent on the reservoir system's configuration. The firm yield of a system is sensitive to how the water is transferred from one reservoir to another, the capacity of the connection between the reservoirs, and how seasonal variations in demand are represented in the FYE model. Firm yields for 25 (14 single-reservoir systems and 11 multiple-reservoir systems) reservoir systems were determined by using the historical records of streamflow and precipitation. Current water-use data indicate that, on average, 20 of the 25 reservoir systems in the study were operating below their estimated firm yield; during months with peak demands, withdrawals exceeded the firm yield for 8 reservoir systems.

Water yield issues in the jarrah forest of south-western Australia

NASA Astrophysics Data System (ADS)

Ruprecht, J. K.; Stoneman, G. L.

1993-10-01

The jarrah forest of south-western Australia produces little streamflow from moderate rainfall. Water yield from water supply catchments for Perth, Western Australia, are low, averaging 71 mm (7% of annual rainfall). The low water yields are attributed to the large soil water storage available for continuous use by the forest vegetation. A number of water yield studies in south-western Australia have examined the impact on water yield of land use practices including clearing for agricultural development, forest harvesting and regeneration, forest thinning and bauxite mining. A permanent reduction in forest cover by clearing for agriculture led to permanent increases of water yield of approximately 28% of annual rainfall in a high rainfall catchment. Thinning of a high rainfall catchment led to an increase in water yield of 20% of annual rainfall. However, it is not clear for how long the increased water yield will persist. Forest harvesting and regeneration have led to water yield increases of 16% of annual rainfall. The subsequent recovery of vegetation cover has led to water yields returning to pre-disturbance levels after an estimated 12-15 years. Bauxite mining of a high rainfall catchment led to a water yield increase of 8% of annual rainfall, followed by a return to pre-disturbance water yield after 12 years. The magnitude of specific streamflow generation mechanisms in small catchments subject to forest disturbance vary considerably, typically in a number of distinct stages. The presence of a permanent groundwater discharge area was shown to be instrumental in determining the magnitude of the streamflow response after forest disturbance. The long-term prognosis for water yield from areas subject to forest thinning, harvesting and regeneration, and bauxite mining are uncertain, owing to the complex interrelationship between vegetation cover, tree height and age, and catchment evapotranspiration. Management of the forest for water yield needs to acknowledge this complexity and evaluate forest management strategies both at the large catchment scale and at long time-scales. The extensive network of small catchment experiments, regional studies, process studies and catchment modelling at both the small and large scale, which are carried out in the jarrah forest, are all considered as integral components of the research to develop these management strategies to optimise water yield from the jarrah forest, without forfeiting other forest values.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Modeling the Propagation of Shock Waves in Metals

NASA Astrophysics Data System (ADS)

Howard, W. Michael

2005-07-01

We present modeling results for the propagation of strong shock waves in metals. In particular, we use an arbitrary Lagrange Eulerian (ALE3D) code to model the propagation of strong pressure waves (P ˜300 to 400 kbars) generated with high explosives in contact with aluminum cylinders. The aluminum cylinders are assumed to be both flat-topped and have large-amplitude curved surfaces. We use 3D Lagrange mechanics. For the aluminum we use a rate-independent Steinberg-Guinan model, where the yield strength and bulk modulus depends on pressure, density and temperature. The calculation of the melt temperature is based on the Lindermann law. At melt the yield strength and bulk modulus is set to zero. The pressure is represented as a seven-term polynomial as a function of density. For the HMX-based high explosive, we use a JWL, with a program burn model that gives the correct detonation velocity and C-J pressure (P ˜ 390 kbars). For the case of the large-amplitude curved surface, we discuss the evolving shock structure in terms of the early shock propagation experiments by Sakharov. We also discuss the dependence of our results upon our material model for aluminum.

Water Ice Radiolytic O2, H2, and H2O2 Yields for Any Projectile Species, Energy, or Temperature: A Model for Icy Astrophysical Bodies

NASA Astrophysics Data System (ADS)

Teolis, B. D.; Plainaki, C.; Cassidy, T. A.; Raut, U.

2017-10-01

O2, H2, and H2O2 radiolysis from water ice is pervasive on icy astrophysical bodies, but the lack of a self-consistent, quantitative model of the yields of these water products versus irradiation projectile species and energy has been an obstacle to estimating the radiolytic oxidant sources to the surfaces and exospheres of these objects. A major challenge is the wide variation of O2 radiolysis yields between laboratory experiments, ranging over 4 orders of magnitude from 5 × 10-7 to 5 × 10-3 molecules/eV for different particles and energies. We revisit decades of laboratory data to solve this long-standing puzzle, finding an inverse projectile range dependence in the O2 yields, due to preferential O2 formation from an 30 Å thick oxygenated surface layer. Highly penetrating projectile ions and electrons with ranges ≳30 Å are therefore less efficient at producing O2 than slow/heavy ions and low-energy electrons (≲ 400 eV) which deposit most energy near the surface. Unlike O2, the H2O2 yields from penetrating projectiles fall within a comparatively narrow range of (0.1-6) × 10-3 molecules/eV and do not depend on range, suggesting that H2O2 forms deep in the ice uniformly along the projectile track, e.g., by reactions of OH radicals. We develop an analytical model for O2, H2, and H2O2 yields from pure water ice for electrons and singly charged ions of any mass and energy and apply the model to estimate possible O2 source rates on several icy satellites. The yields are upper limits for icy bodies on which surface impurities may be present.

Cropping system diversification for food production in Mindanao rubber plantations: a rice cultivar mixture and rice intercropped with mungbean

PubMed Central

Elazegui, Francisco; Duque, Jo-Anne Lynne Joy E.; Mundt, Christopher C.; Vera Cruz, Casiana M.

2017-01-01

Including food production in non-food systems, such as rubber plantations and biofuel or bioenergy crops, may contribute to household food security. We evaluated the potential for planting rice, mungbean, rice cultivar mixtures, and rice intercropped with mungbean in young rubber plantations in experiments in the Arakan Valley of Mindanao in the Philippines. Rice mixtures consisted of two- or three-row strips of cultivar Dinorado, a cultivar with higher value but lower yield, and high-yielding cultivar UPL Ri-5. Rice and mungbean intercropping treatments consisted of different combinations of two- or three-row strips of rice and mungbean. We used generalized linear mixed models to evaluate the yield of each crop alone and in the mixture or intercropping treatments. We also evaluated a land equivalent ratio for yield, along with weed biomass (where Ageratum conyzoides was particularly abundant), the severity of disease caused by Magnaporthe oryzae and Cochliobolus miyabeanus, and rice bug (Leptocorisa acuta) abundance. We analyzed the yield ranking of each cropping system across site-year combinations to determine mean relative performance and yield stability. When weighted by their relative economic value, UPL Ri-5 had the highest mean performance, but with decreasing performance in low-yielding environments. A rice and mungbean intercropping system had the second highest performance, tied with high-value Dinorado but without decreasing relative performance in low-yielding environments. Rice and mungbean intercropped with rubber have been adopted by farmers in the Arakan Valley. PMID:28194318

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

DOE PAGES

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...

2016-11-12

Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA)more » census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

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

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi

Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA)more » census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.« less

Factors related to well yield in the fractured-bedrock aquifer of New Hampshire

USGS Publications Warehouse

Moore, Richard Bridge; Schwartz, Gregory E.; Clark, Stewart F.; Walsh, Gregory J.; Degnan, James R.

2002-01-01

The New Hampshire Bedrock Aquifer Assessment was designed to provide information that can be used by communities, industry, professional consultants, and other interests to evaluate the ground-water development potential of the fractured-bedrock aquifer in the State. The assessment was done at statewide, regional, and well field scales to identify relations that potentially could increase the success in locating high-yield water supplies in the fractured-bedrock aquifer. statewide, data were collected for well construction and yield information, bedrock lithology, surficial geology, lineaments, topography, and various derivatives of these basic data sets. Regionally, geologic, fracture, and lineament data were collected for the Pinardville and Windham quadrangles in New Hampshire. The regional scale of the study examined the degree to which predictive well-yield relations, developed as part of the statewide reconnaissance investigation, could be improved by use of quadrangle-scale geologic mapping. Beginning in 1984, water-well contractors in the State were required to report detailed information on newly constructed wells to the New Hampshire Department of Environmental Services (NHDES). The reports contain basic data on well construction, including six characteristics used in this study?well yield, well depth, well use, method of construction, date drilled, and depth to bedrock (or length of casing). The NHDES has determined accurate georeferenced locations for more than 20,000 wells reported since 1984. The availability of this large data set provided an opportunity for a statistical analysis of bedrock-well yields. Well yields in the database ranged from zero to greater than 500 gallons per minute (gal/min). Multivariate regression was used as the primary statistical method of analysis because it is the most efficient tool for predicting a single variable with many potentially independent variables. The dependent variable that was explored in this study was the natural logarithm (ln) of the reported well yield. One complication with using well yield as a dependent variable is that yield also is a function of demand. An innovative statistical technique that involves the use of instrumental variables was implemented to compensate for the effect of demand on well yield. Results of the multivariate-regression model show that a variety of factors are either positively or negatively related to well yields. Using instrumental variables, well depth is positively related to total well yield. Other factors that were found to be positively related to well yield include (1) distance to the nearest waterbody; (2) size of the drainage area upgradient of a well; (3) well location in swales or valley bottoms in the Massabesic Gneiss Complex and Breakfast Hill Granite; (4) well proximity to lineaments, identified using high-altitude (1:80,000-scale) aerial photography, which are correlated with the primary fracture direction (regional analysis); (5) use of a cable tool rig for well drilling; and (6) wells drilled for commercial or public supply. Factors negatively related to well yields include sites underlain by foliated plutons, sites on steep slopes sites at high elevations, and sites on hilltops. Additionally, seven detailed geologic map units, identified during the detailed geologic mapping of the Pinardville and Windham quadrangles, were found to be positively or negatively related to well yields. Twenty-four geologic map units, depicted on the Bedrock Geologic Map of New Hampshire, also were found to be positively or negatively related to well yields. Maps or geographic information system (GIS) data sets identifying areas of various yield probabilities clearly display model results. Probability criteria developed in this investigation can be used to select areas where other techniques, such as geophysical techniques, can be applied to more closely identify potential drilling sites for high-yielding

The Effects of Temperature and Precipitation on the Yield of Zea Mays L. I the Southeastern United States

NASA Astrophysics Data System (ADS)

Stooksbury, David Emory

Three families of straightforward maize (Zea mays L.) yield/climate models using monthly temperature and precipitation terms are produced. One family of models uses USDA's Crop Reporting Districts (CRD) as its scale of aggregation. The other two families of models use three different district aggregates based on climate or yield patterns. The climate and yield districts are determined by using a two-stage cluster analysis. The CRD-based family of models perform as well as the climate and yield based models. All models explain between 80% and 90% of the variance in maize yield. The most important climate term affecting maize yield in the South is the daily maximum temperature at pollination time. The higher the maximum temperature, the lower the yield. Above normal minimum temperature during pollination increases yield in the Middle South. Weather that favors early planting and rapid vegetative growth increases yield. Ideal maize yield weather includes a dry period during planting followed by a warm period during vegetative growth. Moisture variables are important only during the planting and harvest periods when above normal precipitation delays field work and thereby reduces yield. The model results indicate that the dire predictions about the fate of Southern agriculture in a trace gas warmed world may not be true. This is due to the overwhelming influence of the daily maximum temperature on yield. An optimum aggregate for climate impact studies was not found. I postulate that this is due to the dynamic nature of the American maize production system. For most climate impact studies on a dynamic agricultural system, there does not need to be a concern about the model aggregation.

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

NASA Technical Reports Server (NTRS)

French, V. (Principal Investigator)

1982-01-01

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

Effect of Pellet Boiler Exhaust on Secondary Organic Aerosol Formation from α-Pinene.

PubMed

Kari, Eetu; Hao, Liqing; Yli-Pirilä, Pasi; Leskinen, Ari; Kortelainen, Miika; Grigonyte, Julija; Worsnop, Douglas R; Jokiniemi, Jorma; Sippula, Olli; Faiola, Celia L; Virtanen, Annele

2017-02-07

Interactions between anthropogenic and biogenic emissions, and implications for aerosol production, have raised particular scientific interest. Despite active research in this area, real anthropogenic emission sources have not been exploited for anthropogenic-biogenic interaction studies until now. This work examines these interactions using α-pinene and pellet boiler emissions as a model test system. The impact of pellet boiler emissions on secondary organic aerosol (SOA) formation from α-pinene photo-oxidation was studied under atmospherically relevant conditions in an environmental chamber. The aim of this study was to identify which of the major pellet exhaust components (including high nitrogen oxide (NO x ), primary particles, or a combination of the two) affected SOA formation from α-pinene. Results demonstrated that high NO x concentrations emitted by the pellet boiler reduced SOA yields from α-pinene, whereas the chemical properties of the primary particles emitted by the pellet boiler had no effect on observed SOA yields. The maximum SOA yield of α-pinene in the presence of pellet boiler exhaust (under high-NO x conditions) was 18.7% and in the absence of pellet boiler exhaust (under low-NO x conditions) was 34.1%. The reduced SOA yield under high-NO x conditions was caused by changes in gas-phase chemistry that led to the formation of organonitrate compounds.

[Predicting the impact of climate change in the next 40 years on the yield of maize in China].

PubMed

Ma, Yu-ping; Sun, Lin-li; E, You-hao; Wu, Wei

2015-01-01

Climate change will significantly affect agricultural production in China. The combination of the integral regression model and the latest climate projection may well assess the impact of future climate change on crop yield. In this paper, the correlation model of maize yield and meteorological factors was firstly established for different provinces in China by using the integral regression method, then the impact of climate change in the next 40 years on China's maize production was evaluated combined the latest climate prediction with the reason be ing analyzed. The results showed that if the current speeds of maize variety improvement and science and technology development were constant, maize yield in China would be mainly in an increasing trend of reduction with time in the next 40 years in a range generally within 5%. Under A2 climate change scenario, the region with the most reduction of maize yield would be the Northeast except during 2021-2030, and the reduction would be generally in the range of 2.3%-4.2%. Maize yield reduction would be also high in the Northwest, Southwest and middle and lower reaches of Yangtze River after 2031. Under B2 scenario, the reduction of 5.3% in the Northeast in 2031-2040 would be the greatest across all regions. Other regions with considerable maize yield reduction would be mainly in the Northwest and the Southwest. Reduction in maize yield in North China would be small, generally within 2%, under any scenarios, and that in South China would be almost unchanged. The reduction of maize yield in most regions would be greater under A2 scenario than under B2 scenario except for the period of 2021-2030. The effect of the ten day precipitation on maize yield in northern China would be almost positive. However, the effect of ten day average temperature on yield of maize in all regions would be generally negative. The main reason of maize yield reduction was temperature increase in most provinces but precipitation decrease in a few provinces. Assessments of the future change of maize yield in China based on the different methods were not consistent. Further evaluation needs to consider the change of maize variety and scientific and technological progress, and to enhance the reliability of evaluation models.

Modeling water yield response to forest cover changes in northern Minnesota

Treesearch

S.C. Bernath; E.S. Verry; K.N. Brooks; P.F. Ffolliott

1982-01-01

A water yield model (TIMWAT) has been developed to predict changes in water yield following changes in forest cover in northern Minnesota. Two versions of the model exist; one predicts changes in water yield as a function of gross precipitation and time after clearcutting. The second version predicts changes in water yield due to changes in above-ground biomass...

Skiff-based Sonar/LiDAR Survey to Calibrate Reservoir Volumes for Watershed Sediment Yield Studies: Carmel River Example

NASA Astrophysics Data System (ADS)

Smith, D. P.; Kvitek, R.; Quan, S.; Iampietro, P.; Paddock, E.; Richmond, S. F.; Gomez, K.; Aiello, I. W.; Consulo, P.

2009-12-01

Models of watershed sediment yield are complicated by spatial and temporal variability of geologic substrate, land cover, and precipitation parameters. Episodic events such as ENSO cycles and severe wildfire are frequent enough to matter in the long-term average yield, and they can produce short-lived, extreme geomorphic responses. The sediment yield from extreme events is difficult to accurately capture because of the obvious dangers associated with field measurements during flood conditions, but it is critical to include extreme values for developing realistic models of rainfall-sediment yield relations, and for calculating long term average denudation rates. Dammed rivers provide a time-honored natural laboratory for quantifying average annual sediment yield and extreme-event sediment yield. While lead-line surveys of the past provided crude estimates of reservoir sediment trapping, recent advances in geospatial technology now provide unprecedented opportunities to improve volume change measurements. High-precision digital elevation models surveyed on an annual basis, or before-and-after specific rainfall-runoff events can be used to quantify relations between rainfall and sediment yield as a function of landscape parameters, including spatially explicit fire intensity. The Basin-Complex Fire of June and July 2008 resulted in moderate to severe burns in the 114 km^2 portion of the Carmel River watershed above Los Padres Dam. The US Geological Survey produced a debris flow probability/volume model for the region indicating that the reservoir could lose considerable capacity if intense enough precipitation occurred in the 2009-10 winter. Loss of Los Padres reservoir capacity has implications for endangered steelhead and red-legged frogs, and groundwater on municipal water supply. In anticipation of potentially catastrophic erosion, we produced an accurate volume calculation of the Los Padres reservoir in fall 2009, and locally monitored hillslope and fluvial processes during winter months. The pre-runoff reservoir volume was developed by collecting and merging sonar and LiDAR data from a small research skiff equipped with a high-precision positioning and attitude-correcting system. The terrestrial LiDAR data were augmented with shore-based total station positioning. Watershed monitoring included benchmarked serial stream surveys and semi-quantitative assessment of a variety of near-channel colluvial processes. Rainfall in the 2009-10 water year was not intense enough to trigger widespread debris flows of slope failure in the burned watershed, but dry ravel was apparently accelerated. The geomorphic analysis showed that sediment yield was not significantly higher during this low-rainfall year, despite the wide-spread presence of very steep, fire-impacted slopes. Because there was little to no increase in sediment yield this year, we have postponed our second reservoir survey. A predicted ENSO event that might bring very intense rains to the watershed is currently predicted for winter 2009-10.

Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

PubMed

Brügemann, K; Gernand, E; von Borstel, U U; König, S

2011-08-01

Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression model tended to be slightly higher in the THI range corresponding to cows' comfort zone. Selecting such superior environments for progeny testing can contribute to an accurate genetic differentiation among selection candidates. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

B{yields}X{sub s{gamma}} rate and CP asymmetry within the aligned two-Higgs-doublet model

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

Jung, Martin; Pich, Antonio; Tuzon, Paula

In the two-Higgs-doublet model the alignment of the Yukawa matrices in flavor space guarantees the absence of flavor-changing neutral currents at tree level, while introducing new sources for CP violation parametrized in a very economical way [Antonio Pich and Paula Tuzon, Phys. Rev. D 80, 091702 (2009)]. This implies a potentially large influence in a number of processes, b{yields}s{gamma} being a prominent example where rather high experimental and theoretical precision meet. We analyze the CP rate asymmetry in this inclusive decay and determine the resulting constraints on the model parameters. We demonstrate the compatibility with previously obtained limits [Martin Jung,more » Antonio Pich, and Paula Tuzon, J. High Energy Phys. 11 (2010) 003]. Moreover, we extend the phenomenological analysis of the branching ratio, and examine the influence of resulting correlations on the like-sign dimuon charge asymmetry in B decays.« less

Multi-phase SPH model for simulation of erosion and scouring by means of the shields and Drucker-Prager criteria.

NASA Astrophysics Data System (ADS)

Zubeldia, Elizabeth H.; Fourtakas, Georgios; Rogers, Benedict D.; Farias, Márcio M.

2018-07-01

A two-phase numerical model using Smoothed Particle Hydrodynamics (SPH) is developed to model the scouring of two-phase liquid-sediments flows with large deformation. The rheology of sediment scouring due to flows with slow kinematics and high shear forces presents a challenge in terms of spurious numerical fluctuations. This paper bridges the gap between the non-Newtonian and Newtonian flows by proposing a model that combines the yielding, shear and suspension layer mechanics which are needed to predict accurately the local erosion phenomena. A critical bed-mobility condition based on the Shields criterion is imposed to the particles located at the sediment surface. Thus, the onset of the erosion process is independent on the pressure field and eliminates the numerical problem of pressure dependant erosion at the interface. This is combined with the Drucker-Prager yield criterion to predict the onset of yielding of the sediment surface and a concentration suspension model. The multi-phase model has been implemented in the open-source DualSPHysics code accelerated with a graphics processing unit (GPU). The multi-phase model has been compared with 2-D reference numerical models and new experimental data for scour with convergent results. Numerical results for a dry-bed dam break over an erodible bed shows improved agreement with experimental scour and water surface profiles compared to well-known SPH multi-phase models.

Atomistic basis for the plastic yield criterion of metallic glass.

PubMed

Schuh, Christopher A; Lund, Alan C

2003-07-01

Because of their disordered atomic structure, amorphous metals (termed metallic glasses) have fundamentally different deformation mechanisms compared with polycrystalline metals. These different mechanisms give metallic glasses high strength, but the extent to which they affect other macroscopic deformation properties is uncertain. For example, the nature of the plastic-yield criterion is a point of contention, with some studies reporting yield behaviour roughly in line with that of polycrystalline metals, and others indicating strong fundamental differences. In particular, it is unclear whether pressure- or normal stress-dependence needs to be included in the plastic-yield criterion of metallic glasses, and how such a dependence could arise from their disordered structure. In this work we provide an atomic-level explanation for pressure-dependent yield in amorphous metals, based on an elementary unit of deformation. This simple model compares favourably with new atomistic simulations of metallic glasses, as well as existing experimental data.

Propagation of nuclear data uncertainties for fusion power measurements

NASA Astrophysics Data System (ADS)

Sjöstrand, Henrik; Conroy, Sean; Helgesson, Petter; Hernandez, Solis Augusto; Koning, Arjan; Pomp, Stephan; Rochman, Dimitri

2017-09-01

Neutron measurements using neutron activation systems are an essential part of the diagnostic system at large fusion machines such as JET and ITER. Nuclear data is used to infer the neutron yield. Consequently, high-quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are not fully taken into account in uncertainty analysis for neutron yield calibrations using activation foils. This paper investigates the neutron yield uncertainty due to nuclear data using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of the JET fusion machine; the uncertainties due to the cross-sections and angular distributions in JET structural materials, as well as the activation cross-sections in the activation foils, are analysed. It is found that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.

Excitonic Emission of Monolayer Semiconductors Near-Field Coupled to High-Q Microresonators

NASA Astrophysics Data System (ADS)

Javerzac-Galy, Clément; Kumar, Anshuman; Schilling, Ryan D.; Piro, Nicolas; Khorasani, Sina; Barbone, Matteo; Goykhman, Ilya; Khurgin, Jacob B.; Ferrari, Andrea C.; Kippenberg, Tobias J.

2018-05-01

We present quantum yield measurements of single layer $\\textrm{WSe}_2$ (1L-$\\textrm{WSe}_2$) integrated with high-Q ($Q>10^6$) optical microdisk cavities, using an efficient ($\\eta>$90%) near-field coupling scheme based on a tapered optical fiber. Coupling of the excitonic emission is achieved by placing 1L-WSe$_2$ to the evanescent cavity field. This preserves the microresonator high intrinsic quality factor ($Q>10^6$) below the bandgap of 1L-WSe$_2$. The nonlinear excitation power dependence of the cavity quantum yield is in agreement with an exciton-exciton annihilation model. The cavity quantum yield is $\\textrm{QY}_\\textrm{c}\\sim10^{-3}$, consistent with operation in the \\textit{broad emitter} regime (i.e. the emission lifetime of 1L-WSe$_2$ is significantly shorter than the bare cavity decay time). This scheme can serve as a precise measurement tool for the excitonic emission of layered materials into cavity modes, for both in plane and out of plane excitation.

Photooxidation of mixed aryl and biarylphosphines.

PubMed

Zhang, Dong; Celaje, Jeff A; Agua, Alon; Doan, Chad; Stewart, Timothy; Bau, Robert; Selke, Matthias

2010-07-02

Arylphosphines and dialkylbiarylphosphines react with singlet oxygen to form phosphine oxides and phosphinate esters. For mixed arylphosphines, the most electron-rich aryl group migrates to form the phosphinate, while for dialkylbiarylphosphines migration of the alkyl group occurs. Dialkylbiarylphosphines also yield arene epoxides, especially in electron-rich systems. Phosphinate ester formation is increased at high temperature, while protic solvents increase the yield of epoxide. The product distribution provides evidence for Buchwald's recent conformational model for the aerobic oxidation of dialkylbiarylphosphines.

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.

Multicriteria evaluation of simulated logging scenarios in a tropical rain forest.

PubMed

Huth, Andreas; Drechsler, Martin; Köhler, Peter

2004-07-01

Forest growth models are useful tools for investigating the long-term impacts of logging. In this paper, the results of the rain forest growth model FORMIND were assessed by a multicriteria decision analysis. The main processes covered by FORMIND include tree growth, mortality, regeneration and competition. Tree growth is calculated based on a carbon balance approach. Trees compete for light and space; dying large trees fall down and create gaps in the forest. Sixty-four different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated. The scenarios differ regarding the logging cycle, logging method, cutting limit and logging intensity. We characterise the impacts with four criteria describing the yield, canopy opening and changes in species composition. Multicriteria decision analysis was used for the first time to evaluate the scenarios and identify the efficient ones. Our results plainly show that reduced-impact logging scenarios are more 'efficient' than the others, since in these scenarios forest damage is minimised without significantly reducing yield. Nevertheless, there is a trade-off between yield and achieving a desired ecological state of logged forest; the ecological state of the logged forests can only be improved by reducing yields and enlarging the logging cycles. Our study also demonstrates that high cutting limits or low logging intensities cannot compensate for the high level of damage caused by conventional logging techniques.

ANSYS Modeling of Hydrostatic Stress Effects

NASA Technical Reports Server (NTRS)

Allen, Phillip A.

1999-01-01

Classical metal plasticity theory assumes that hydrostatic pressure has no effect on the yield and postyield behavior of metals. Plasticity textbooks, from the earliest to the most modem, infer that there is no hydrostatic effect on the yielding of metals, and even modem finite element programs direct the user to assume the same. The object of this study is to use the von Mises and Drucker-Prager failure theory constitutive models in the finite element program ANSYS to see how well they model conditions of varying hydrostatic pressure. Data is presented for notched round bar (NRB) and "L" shaped tensile specimens. Similar results from finite element models in ABAQUS are shown for comparison. It is shown that when dealing with geometries having a high hydrostatic stress influence, constitutive models that have a functional dependence on hydrostatic stress are more accurate in predicting material behavior than those that are independent of hydrostatic stress.

Ecosystem Services Provided by Agricultural Land as Modeled by Broad Scale Geospatial Analysis

NASA Astrophysics Data System (ADS)

Kokkinidis, Ioannis

Agricultural ecosystems provide multiple services including food and fiber provision, nutrient cycling, soil retention and water regulation. Objectives of the study were to identify and quantify a selection of ecosystem services provided by agricultural land, using existing geospatial tools and preferably free and open source data, such as the Virginia Land Use Evaluation System (VALUES), the North Carolina Realistic Yield Expectations (RYE) database, and the land cover datasets NLCD and CDL. Furthermore I sought to model tradeoffs between provisioning and other services. First I assessed the accuracy of agricultural land in NLCD and CDL over a four county area in eastern Virginia using cadastral parcels. I uncovered issues concerning the definition of agricultural land. The area and location of agriculture saw little change in the 19 years studied. Furthermore all datasets have significant errors of omission (11.3 to 95.1%) and commission (0 to 71.3%). Location of agriculture was used with spatial crop yield databases I created and combined with models I adapted to calculate baseline values for plant biomass, nutrient composition and requirements, land suitability for and potential production of biofuels and the economic impact of agriculture for the four counties. The study area was then broadened to cover 97 counties in eastern Virginia and North Carolina, investigating the potential for increased regional grain production through intensification and extensification of agriculture. Predicted yield from geospatial crop models was compared with produced yield from the NASS Survey of Agriculture. Area of most crops in CDL was similar to that in the Survey of Agriculture, but a yield gap is present for most years, partially due to weather, thus indicating potential for yield increase through intensification. Using simple criteria I quantified the potential to extend agriculture in high yield land in other uses and modeled the changes in erosion and runoff should conversion take place. While the quantity of wheat produced though extensification is equal to 4.2 times 2012 production, conversion will lead to large increases in runoff (4.1 to 39.4%) and erosion (6 times). This study advances the state of geospatial tools for quantification of ecosystem services.

Predicting Greenhouse Gas Emissions and Soil Carbon from Changing Pasture to an Energy Crop

PubMed Central

Duval, Benjamin D.; Anderson-Teixeira, Kristina J.; Davis, Sarah C.; Keogh, Cindy; Long, Stephen P.; Parton, William J.; DeLucia, Evan H.

2013-01-01

Bioenergy related land use change would likely alter biogeochemical cycles and global greenhouse gas budgets. Energy cane (Saccharum officinarum L.) is a sugarcane variety and an emerging biofuel feedstock for cellulosic bio-ethanol production. It has potential for high yields and can be grown on marginal land, which minimizes competition with grain and vegetable production. The DayCent biogeochemical model was parameterized to infer potential yields of energy cane and how changing land from grazed pasture to energy cane would affect greenhouse gas (CO2, CH4 and N2O) fluxes and soil C pools. The model was used to simulate energy cane production on two soil types in central Florida, nutrient poor Spodosols and organic Histosols. Energy cane was productive on both soil types (yielding 46–76 Mg dry mass⋅ha−1). Yields were maintained through three annual cropping cycles on Histosols but declined with each harvest on Spodosols. Overall, converting pasture to energy cane created a sink for GHGs on Spodosols and reduced the size of the GHG source on Histosols. This change was driven on both soil types by eliminating CH4 emissions from cattle and by the large increase in C uptake by greater biomass production in energy cane relative to pasture. However, the change from pasture to energy cane caused Histosols to lose 4493 g CO2 eq⋅m−2 over 15 years of energy cane production. Cultivation of energy cane on former pasture on Spodosol soils in the southeast US has the potential for high biomass yield and the mitigation of GHG emissions. PMID:23991028

Gaussian functional regression for output prediction: Model assimilation and experimental design

NASA Astrophysics Data System (ADS)

Nguyen, N. C.; Peraire, J.

2016-03-01

In this paper, we introduce a Gaussian functional regression (GFR) technique that integrates multi-fidelity models with model reduction to efficiently predict the input-output relationship of a high-fidelity model. The GFR method combines the high-fidelity model with a low-fidelity model to provide an estimate of the output of the high-fidelity model in the form of a posterior distribution that can characterize uncertainty in the prediction. A reduced basis approximation is constructed upon the low-fidelity model and incorporated into the GFR method to yield an inexpensive posterior distribution of the output estimate. As this posterior distribution depends crucially on a set of training inputs at which the high-fidelity models are simulated, we develop a greedy sampling algorithm to select the training inputs. Our approach results in an output prediction model that inherits the fidelity of the high-fidelity model and has the computational complexity of the reduced basis approximation. Numerical results are presented to demonstrate the proposed approach.

Substitution of carcinogenic solvent dichloromethane for the extraction of volatile compounds in a fat-free model food system.

PubMed

Cayot, Nathalie; Lafarge, Céline; Bou-Maroun, Elias; Cayot, Philippe

2016-07-22

Dichloromethane is known as a very efficient solvent, but, as other halogenated solvents, is recognized as a hazardous product (CMR substance). The objective of the present work is to propose substitution solvent for the extraction of volatile compounds. The most important physico-chemical parameters in the choice of an appropriate extraction solvent of volatile compounds are reviewed. Various solvents are selected on this basis and on their hazard characteristics. The selected solvents, safer than dichloromethane, are compared using the extraction efficiency of volatile compounds from a model food product able to interact with volatile compounds. Volatile compounds with different hydrophobicity are used. High extraction yields were positively correlated with high boiling points and high Log Kow values of volatile compounds. Mixtures of solvents such as azeotrope propan-2-one/cyclopentane, azeotrope ethyl acetate/ethanol, and mixture ethyl acetate/ethanol (3:1, v/v) gave higher extraction yields than those obtained with dichloromethane. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Biofuels on the landscape: Is "land sharing" preferable to "land sparing"?

NASA Astrophysics Data System (ADS)

DeLucia, E. H.; Anderson-Teixeira, K. J.; Duval, B. D.; Long, S. P.

2012-12-01

Widespread land use changes—and ensuing effects on biodiversity and ecosystem services—are expected as a result of expanding bioenergy production. Although almost all US production of ethanol today is from corn, it is envisaged that future ethanol production will also draw from cellulosic sources such as perennial grasses. In selecting optimal bioenergy crops, there is debate as to whether it is preferable from an environmental standpoint to cultivate bioenergy crops with high ecosystem services (a "land sharing" strategy) or to grow crops with lower ecosystem services but higher yield, thereby requiring less land to meet bioenergy demand (a "land sparing" strategy). Here, we develop a simple model to address this question. Assuming that bioenergy crops are competing with uncultivated land, our model calculates land requirements to meet a given bioenergy demand intensity based upon the yields of bioenergy crops and combines fractional land cover of each ecosystem type with its associated ecosystem services to determine whether land sharing or land sparing strategies maximize ecosystem services at the landscape level. We apply this model to a case in which climate protection through GHG regulation—an ecosystem's greenhouse gas value (GHGV)—is the ecosystem service of interest. We consider five bioenergy crops competing for land area with five unfarmed ecosystem types in the central and eastern US. Our results show that the relative advantages of land sparing and land sharing depend upon the type of ecosystem with which the bioenergy crop is competing for land; as the GHGV value of the unfarmed land increases, the preferable strategy shifts from land sharing to land sparing. This implies that, while it may be preferable to replace ecologically degraded land with high-GHGV, lower yielding bioenergy crops, average landscape GHGV will most often be maximized through high yielding bioenergy crops that leave more land for uncultivated, high-GHGV ecosystems. While our case study focuses on GHGV, the same principles will be generally applicable to any ecosystem service whose value does not depend upon the spatial configuration of the landscape. Whenever bioenergy crops have substantially lower ecosystem services than the ecosystems with which they are competing for land, the most effective strategy for meeting bioenergy demand while maximizing ecosystem services on a landscape level is one of land sparing—that is, focusing simultaneously on maximizing the yield of bioenergy crops while preserving or restoring natural ecosystems.

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.

Application of wheat yield model to United States and India. [Great Plains

NASA Technical Reports Server (NTRS)

Feyerherm, A. M. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The wheat yield model was applied to the major wheat-growing areas of the US and India. In the US Great Plains, estimates from the winter and spring wheat models agreed closely with USDA-SRS values in years with the lowest yields, but underestimated in years with the highest yields. Application to the Eastern Plains and Northwest indicated the importance of cultural factors, as well as meteorological ones in the model. It also demonstrated that the model could be used, in conjunction with USDA-SRRS estimates, to estimate yield losses due to factors not included in the model, particularly diseases and freezes. A fixed crop calendar for India was built from a limited amount of available plot data from that country. Application of the yield model gave measurable evidence that yield variation from state to state was due to different mixes of levels of meteorological and cultural factors.

Carbon export and cycling by the Yukon, Tanana, and Porcupine rivers, Alaska, 2001-2005

USGS Publications Warehouse

Striegl, Robert G.; Dornblaser, Mark M.; Aiken, George R.; Wickland, Kimberly P.; Raymond, Peter A.

2007-01-01

Loads and yields of dissolved and particulate organic and inorganic carbon (DOC, POC, DIC, PIC) were measured and modeled at three locations on the Yukon River (YR) and on the Tanana and Porcupine rivers (TR, PR) in Alaska during 2001–2005. Total YR carbon export averaged 7.8 Tg C yr−1, 30% as OC and 70% as IC. Total C yields (0.39–1.03 mol C m−2 yr−1) were proportional to water yields (139–356 mm yr−1; r2 = 0.84) at all locations. Summer DOC had an aged component (fraction modern (FM) = 0.94–0.97), except in the permafrost wetland‐dominated PR, where DOC was modern. POC had FM = 0.63–0.70. DOC had high concentration, high aromaticity, and high hydrophobic content in spring and low concentration, low aromaticity, and high hydrophilic content in winter. About half of annual DOC export occurred during spring. DIC concentration and isotopic composition were strongly affected by dissolution of suspended carbonates in glacial meltwater during summer.

Co-solvent pretreatment reduces costly enzyme requirements for high sugar and ethanol yields from lignocellulosic biomass.

PubMed

Nguyen, Thanh Yen; Cai, Charles M; Kumar, Rajeev; Wyman, Charles E

2015-05-22

We introduce a new pretreatment called co-solvent-enhanced lignocellulosic fractionation (CELF) to reduce enzyme costs dramatically for high sugar yields from hemicellulose and cellulose, which is essential for the low-cost conversion of biomass to fuels. CELF employs THF miscible with aqueous dilute acid to obtain up to 95 % theoretical yield of glucose, xylose, and arabinose from corn stover even if coupled with enzymatic hydrolysis at only 2 mgenzyme  gglucan (-1) . The unusually high saccharification with such low enzyme loadings can be attributed to a very high lignin removal, which is supported by compositional analysis, fractal kinetic modeling, and SEM imaging. Subsequently, nearly pure lignin product can be precipitated by the evaporation of volatile THF for recovery and recycling. Simultaneous saccharification and fermentation of CELF-pretreated solids with low enzyme loadings and Saccharomyces cerevisiae produced twice as much ethanol as that from dilute-acid-pretreated solids if both were optimized for corn stover. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data

NASA Astrophysics Data System (ADS)

Kouadio, Louis; Duveiller, Grégory; Djaby, Bakary; El Jarroudi, Moussa; Defourny, Pierre; Tychon, Bernard

2012-08-01

Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence rate and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha-1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.

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

Towards a Solid Foundation of Using Remotely Sensed Solar-Induced Chlorophyll Fluorescence for Crop Monitoring and Yield Forecast

NASA Astrophysics Data System (ADS)

Chen, Y.; Sun, Y.; You, L.; Liu, Y.

2017-12-01

The growing demand for food production due to population increase coupled with high vulnerability to volatile environmental changes poses a paramount challenge for mankind in the coming century. Real-time crop monitoring and yield forecasting must be a key part of any solution to this challenge as these activities provide vital information needed for effective and efficient crop management and for decision making. However, traditional methods of crop growth monitoring (e.g., remotely sensed vegetation indices) do not directly relate to the most important function of plants - photosynthesis and therefore crop yield. The recent advance in the satellite remote sensing of Solar-Induced chlorophyll Fluorescence (SIF), an integrative photosynthetic signal from molecular origin and a direct measure of plant functions holds great promise for real-time monitoring of crop growth conditions and forecasting yields. In this study, we use satellite measurements of SIF from both the Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A and the Orbiting Carbon Observatory-2 (OCO-2) satellites to estimate crop yield using both process-based and statistical models. We find that SIF-based crop yield well correlates with the global yield product Spatial Production Allocation Model (SPAM) derived from ground surveys for all major crops including maize, soybean, wheat, sorghum, and rice. The potential and challenges of using upcoming SIF satellite missions for crop monitoring and prediction will also be discussed.

Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

NASA Astrophysics Data System (ADS)

Huber, I.; Archontoulis, S.

2017-12-01

In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar application rate.

Low-high junction theory applied to solar cells

NASA Technical Reports Server (NTRS)

Godlewski, M. P.; Baraona, C. R.; Brandhorst, H. W., Jr.

1973-01-01

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open circuit voltage and improved radiation resistance. Several analytical models for open circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero SRV case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells. Detailed descriptions and derivations for the models are included. The correspondences between them are discussed. This modeling suggests that the meaning of minority carrier diffusion length measured in BSF cells be reexamined.

Impact of plastic mulching on nitrous oxide emissions in China's arid agricultural region under climate change conditions

NASA Astrophysics Data System (ADS)

Yu, Yongxiang; Tao, Hui; Jia, Hongtao; Zhao, Chengyi

2017-06-01

The denitrification-decomposition (DNDC) model is a useful tool for integrating the effects of agricultural practices and climate change on soil nitrous oxide (N2O) emissions from agricultural ecosystems. In this study, the DNDC model was evaluated against observations and used to simulate the effect of plastic mulching on soil N2O emissions and crop growth. The DNDC model performed well in simulating temporal variations in N2O emissions and plant growth during the observation period, although it slightly underestimated the cumulative N2O emissions, and was able to simulate the effects of plastic mulching on N2O emissions and crop yield. Both the observations and simulations demonstrated that the application of plastic film increased cumulative N2O emissions and cotton lint yield compared with the non-mulched treatment. The sensitivity test showed that the N2O emissions and lint yield were sensitive to changes in climate and management practices, and the application of plastic film made the N2O emissions and lint yield less sensitive to changes in temperature and irrigation. Although the simulations showed that the beneficial impacts of plastic mulching on N2O emissions were not gained under high fertilizer and irrigation scenarios, our simulations suggest that the application of plastic film effectively reduced soil N2O emissions while promoting yields under suitable fertilizer rates and irrigation. Compared with the baseline scenario, future climate change significantly increased N2O emissions by 15-17% without significantly influencing the lint yields in the non-mulched treatment; in the mulched treatment, climate change significantly promoted the lint yield by 5-6% and significantly reduced N2O emissions by 14% in the RCP4.5 and RCP8.5 scenarios. Overall, our results demonstrate that the application of plastic film is an efficient way to address increased N2O emissions and simultaneously enhance crop yield in the future.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

DOE PAGES

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.; ...

2018-04-17

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

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

Schiro, Kathleen A.; Ahmed, Fiaz; Giangrande, Scott E.

Representations of strongly precipitating deep-convective systems in climate models are among the most important factors in their simulation. Parameterizations of these motions face the dual challenge of unclear pathways to including mesoscale organization and high sensitivity of convection to approximations of turbulent entrainment of environmental air. Ill-constrained entrainment processes can even affect global average climate sensitivity under global warming. Multiinstrument observations from the Department of Energy GoAmazon2014/5 field campaign suggest that an alternative formulation from radar-derived dominant updraft structure yields a strong relationship of precipitation to buoyancy in both mesoscale and smaller-scale convective systems. This simultaneously provides a key stepmore » toward representing the influence of mesoscale convection in climate models and sidesteps a problematic dependence on traditional entrainment rates. A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Lastly, deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.« less

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

PubMed

Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David

2018-05-01

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

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.

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

Why the Particle-in-a-Box Model Works Well for Cyanine Dyes but Not for Conjugated Polyenes

ERIC Educational Resources Information Center

Autschbach, Jochen

2007-01-01

We investigate why the particle-in-a-box (PB) model works well for calculating the absorption wavelengths of cyanine dyes and why it does not work for conjugated polyenes. The PB model is immensely useful in the classroom, but owing to its highly approximate character there is little reason to expect that it can yield quantitative agreement with…

Assessment of municipal solid waste settlement models based on field-scale data analysis.

PubMed

Bareither, Christopher A; Kwak, Seungbok

2015-08-01

An evaluation of municipal solid waste (MSW) settlement model performance and applicability was conducted based on analysis of two field-scale datasets: (1) Yolo and (2) Deer Track Bioreactor Experiment (DTBE). Twelve MSW settlement models were considered that included a range of compression behavior (i.e., immediate compression, mechanical creep, and biocompression) and range of total (2-22) and optimized (2-7) model parameters. A multi-layer immediate settlement analysis developed for Yolo provides a framework to estimate initial waste thickness and waste thickness at the end-of-immediate compression. Model application to the Yolo test cells (conventional and bioreactor landfills) via least squares optimization yielded high coefficient of determinations for all settlement models (R(2)>0.83). However, empirical models (i.e., power creep, logarithmic, and hyperbolic models) are not recommended for use in MSW settlement modeling due to potential non-representative long-term MSW behavior, limited physical significance of model parameters, and required settlement data for model parameterization. Settlement models that combine mechanical creep and biocompression into a single mathematical function constrain time-dependent settlement to a single process with finite magnitude, which limits model applicability. Overall, all models evaluated that couple multiple compression processes (immediate, creep, and biocompression) provided accurate representations of both Yolo and DTBE datasets. A model presented in Gourc et al. (2010) included the lowest number of total and optimized model parameters and yielded high statistical performance for all model applications (R(2)⩾0.97). Copyright © 2015 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

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;

Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts ...

Simulating future climate change impacts on seed cotton yield in the Texas high plains using the CSM-CROPGRO cotton model

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) region contributes to about 25% of the US cotton production. Dwindling groundwater resources in the underlying Ogallala aquifer, future climate variability and frequent occurrences of droughts are major concerns for cotton production in this region. Assessing the impacts ...

Spray combustion modeling

NASA Technical Reports Server (NTRS)

Bellan, J.

1997-01-01

Concern over the future availability of high quality liquid fuels or use in furnaces and boilers prompted the U. S. Department of Energy (DOE) to consider alternate fuels as replacements for the high grade liquid fuels used in the 1970's and 1980's. Alternate fuels were defined to be combinations of a large percentage of viscous, low volatility fuels resulting from the low end of distillation mixed with a small percentage of relatively low viscosity, high volatility fuels yielded by the high end of distillation. The addition of high volatility fuels was meant to promote desirable characteristics to a fuel that would otherwise be difficult to atomize and burn and whose combustion would yield a high amount of pollutants. Several questions thus needed to be answered before alternate fuels became commercially viable. These questions were related to fuel atomization, evaporation, ignition, combustion and pollutant formation. This final report describes the results of the most significant studies on ignition and combustion of alternative fuels.

Power law behavior of the isotope yield distributions in the multifragmentation regime of heavy ion reactions

NASA Astrophysics Data System (ADS)

Huang, M.; Wada, R.; Chen, Z.; Keutgen, T.; Kowalski, S.; Hagel, K.; Barbui, M.; Bonasera, A.; Bottosso, C.; Materna, T.; Natowitz, J. B.; Qin, L.; Rodrigues, M. R. D.; Sahu, P. K.; Schmidt, K. J.; Wang, J.

2010-11-01

Isotope yield distributions in the multifragmentation regime were studied with high-quality isotope identification, focusing on the intermediate mass fragments (IMFs) produced in semiviolent collisions. The yields were analyzed within the framework of a modified Fisher model. Using the ratio of the mass-dependent symmetry energy coefficient relative to the temperature, asym/T, extracted in previous work and that of the pairing term, ap/T, extracted from this work, and assuming that both reflect secondary decay processes, the experimentally observed isotope yields were corrected for these effects. For a given I=N-Z value, the corrected yields of isotopes relative to the yield of C12 show a power law distribution Y(N,Z)/Y(12C)~A-τ in the mass range 1⩽A⩽30, and the distributions are almost identical for the different reactions studied. The observed power law distributions change systematically when I of the isotopes changes and the extracted τ value decreases from 3.9 to 1.0 as I increases from -1 to 3. These observations are well reproduced by a simple deexcitation model, with which the power law distribution of the primary isotopes is determined to be τprim=2.4±0.2, suggesting that the disassembling system at the time of the fragment formation is indeed at, or very near, the critical point.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle.

PubMed

Pereira, R J; Bignardi, A B; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

2013-01-01

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Estimated effects of temperature on secondary organic aerosol concentrations.

PubMed

Sheehan, P E; Bowman, F M

2001-06-01

The temperature-dependence of secondary organic aerosol (SOA) concentrations is explored using an absorptive-partitioning model under a variety of simplified atmospheric conditions. Experimentally determined partitioning parameters for high yield aromatics are used. Variation of vapor pressures with temperature is assumed to be the main source of temperature effects. Known semivolatile products are used to define a modeling range of vaporization enthalpy of 10-25 kcal/mol-1. The effect of diurnal temperature variations on model predictions for various assumed vaporization enthalpies, precursor emission rates, and primary organic concentrations is explored. Results show that temperature is likely to have a significant influence on SOA partitioning and resulting SOA concentrations. A 10 degrees C decrease in temperature is estimated to increase SOA yields by 20-150%, depending on the assumed vaporization enthalpy. In model simulations, high daytime temperatures tend to reduce SOA concentrations by 16-24%, while cooler nighttime temperatures lead to a 22-34% increase, compared to constant temperature conditions. Results suggest that currently available constant temperature partitioning coefficients do not adequately represent atmospheric SOA partitioning behavior. Air quality models neglecting the temperature dependence of partitioning are expected to underpredict peak SOA concentrations as well as mistime their occurrence.

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.

Operational modelling: the mechanisms influencing TB diagnostic yield in an Xpert® MTB/RIF-based algorithm.

PubMed

Dunbar, R; Naidoo, P; Beyers, N; Langley, I

2017-04-01

Cape Town, South Africa. To compare the diagnostic yield for smear/culture and Xpert® MTB/RIF algorithms and to investigate the mechanisms influencing tuberculosis (TB) yield. We developed and validated an operational model of the TB diagnostic process, first with the smear/culture algorithm and then with the Xpert algorithm. We modelled scenarios by varying TB prevalence, adherence to diagnostic algorithms and human immunodeficiency virus (HIV) status. This enabled direct comparisons of diagnostic yield in the two algorithms to be made. Routine data showed that diagnostic yield had decreased over the period of the Xpert algorithm roll-out compared to the yield when the smear/culture algorithm was in place. However, modelling yield under identical conditions indicated a 13.3% increase in diagnostic yield from the Xpert algorithm compared to smear/culture. The model demonstrated that the extensive use of culture in the smear/culture algorithm and the decline in TB prevalence are the main factors contributing to not finding an increase in diagnostic yield in the routine data. We demonstrate the benefits of an operational model to determine the effect of scale-up of a new diagnostic algorithm, and recommend that policy makers use operational modelling to make appropriate decisions before new diagnostic algorithms are scaled up.

High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling.

PubMed

Rollin, Joseph A; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K; Wu, Chang-Hao; Adams, Michael W W; Senger, Ryan S; Zhang, Y-H Percival

2015-04-21

The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L(-1)⋅h(-1). The productivity was further enhanced to 54 mmol H2⋅L(-1)⋅h(-1) by increasing reaction temperature, substrate, and enzyme concentrations--an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

PubMed Central

Rollin, Joseph A.; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K.; Wu, Chang-Hao; Adams, Michael W. W.; Senger, Ryan S.; Zhang, Y.-H. Percival

2015-01-01

The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L−1⋅h−1. The productivity was further enhanced to 54 mmol H2⋅L−1⋅h−1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production. PMID:25848015

High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

DOE PAGES

Rollin, Joseph A.; Martin del Campo, Julia; Myung, Suwan; ...

2015-04-06

The use of hydrogen (H 2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H 2 and CO 2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H 2 with a yield of two H 2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and amore » global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H 2 productivity was increased 3-fold to 32 mmol H 2∙L ₋1∙h ₋1. The productivity was further enhanced to 54 mmol H 2∙L ₋1∙h ₋1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.« less

End-to-End Assessment of a Large Aperture Segmented Ultraviolet Optical Infrared (UVOIR) Telescope Architecture

NASA Technical Reports Server (NTRS)

Feinberg, Lee; Rioux, Norman; Bolcar, Matthew; Liu, Alice; Guyon, Oliver; Stark, Chris; Arenberg, Jon

2016-01-01

Key challenges of a future large aperture, segmented Ultraviolet Optical Infrared (UVOIR) Telescope capable of performing a spectroscopic survey of hundreds of Exoplanets will be sufficient stability to achieve 10^-10 contrast measurements and sufficient throughput and sensitivity for high yield Exo-Earth spectroscopic detection. Our team has collectively assessed an optimized end to end architecture including a high throughput coronagraph capable of working with a segmented telescope, a cost-effective and heritage based stable segmented telescope, a control architecture that minimizes the amount of new technologies, and an Exo-Earth yield assessment to evaluate potential performance. These efforts are combined through integrated modeling, coronagraph evaluations, and Exo-Earth yield calculations to assess the potential performance of the selected architecture. In addition, we discusses the scalability of this architecture to larger apertures and the technological tall poles to enabling it.

Model-Based Nutrient Feeding Strategies for the Increased Production of Polyhydroxybutyrate (PHB) by Alcaligenes latus.

PubMed

Gahlawat, Geeta; Srivastava, Ashok K

2017-10-01

Polyhydroxyalkanoates (PHAs) are biodegradable polymers which are considered as an effective alternative for conventional plastics due to their mechanical properties similar to the latter. However, the widespread use of these polymers is still hampered due to their higher cost of production as compared to plastics. The production cost could be overcome by obtaining high yields and productivity. The goal of the present research was to enhance the yield of polyhydroxybutyrate (PHB) with the help of two simple fed-batch cultivation strategies. In the present study, average batch kinetic and substrate limitation/inhibition study data of Alcaligenes latus was used for the development of PHB model which was then adopted for designing various off-line nutrient feeding strategies to enhance PHB accumulation. The predictive ability of the model was validated by experimental implementation of two fed-batch strategies. One such dynamic strategy of fed-batch cultivation under pseudo-steady state with respect to nitrogen and simultaneous carbon feeding strategy resulted in significantly high biomass and PHB concentration of 39.17 g/L and 29.64 g/L, respectively. This feeding strategy demonstrated a high PHB productivity and PHB content of 0.6 g/L h and 75%, respectively, which were remarkably high in comparison to batch cultivation. The mathematical model can also be employed for designing various other nutrient feeding strategies.

Carrier Multiplication in Quantum Dots within the Framework of Two Competing Energy Relaxation Mechanisms.

PubMed

Stewart, John T; Padilha, Lazaro A; Bae, Wan Ki; Koh, Weon-Kyu; Pietryga, Jeffrey M; Klimov, Victor I

2013-06-20

The realization of high-yield, low-threshold carrier multiplication (CM) in semiconductor quantum dots (QDs) is a promising step toward third-generation photovoltaics (PV). Recent studies of QD solar cells have shown that CM can indeed produce greater-than-unity quantum efficiencies in photon-to-charge-carrier conversion, establishing the relevance of this process to practical PV technologies. While being appreciable, the reported CM yields are still not high enough for a significant increase in the power conversion efficiency over traditional bulk materials. At present, the design of nanomaterials with improved CM is hindered by a poor understanding of the mechanism underlying this process. Here, we present a possible solution to this problem by introducing a model that treats CM as a competition between impact-ionization-like scattering and non-CM energy losses. Importantly, it allows for evaluation of expected CM yields from fairly straightforward measurements of Auger recombination (inverse of CM) and near-band-edge carrier cooling. The validation of this model via a comparative CM study of PbTe, PbSe, and PbS QDs suggests that it indeed represents a predictive capability, which might help in the development of nanomaterials with improved CM performance.

Accelerated high-yield generation of limb-innervating motor neurons from human stem cells

PubMed Central

Amoroso, Mackenzie W.; Croft, Gist F.; Williams, Damian J.; O’Keeffe, Sean; Carrasco, Monica A.; Davis, Anne R.; Roybon, Laurent; Oakley, Derek H.; Maniatis, Tom; Henderson, Christopher E.; Wichterle, Hynek

2013-01-01

Human pluripotent stem cells are a promising source of differentiated cells for developmental studies, cell transplantation, disease modeling, and drug testing. However, their widespread use even for intensely studied cell types like spinal motor neurons is hindered by the long duration and low yields of existing protocols for in vitro differentiation and by the molecular heterogeneity of the populations generated. We report a combination of small molecules that within 3 weeks induce motor neurons at up to 50% abundance and with defined subtype identities of relevance to neurodegenerative disease. Despite their accelerated differentiation, motor neurons expressed combinations of HB9, ISL1 and column-specific markers that mirror those observed in vivo in human fetal spinal cord. They also exhibited spontaneous and induced activity, and projected axons towards muscles when grafted into developing chick spinal cord. Strikingly, this novel protocol preferentially generates motor neurons expressing markers of limb-innervating lateral motor column motor neurons (FOXP1+/LHX3−). Access to high-yield cultures of human limb-innervating motor neuron subtypes will facilitate in-depth study of motor neuron subtype-specific properties, disease modeling, and development of large-scale cell-based screening assays. PMID:23303937

Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale.

PubMed

Sommerlot, Andrew R; Nejadhashemi, A Pouyan; Woznicki, Sean A; Giri, Subhasis; Prohaska, Michael D

2013-09-30

Many watershed model interfaces have been developed in recent years for predicting field-scale sediment loads. They share the goal of providing data for decisions aimed at improving watershed health and the effectiveness of water quality conservation efforts. The objectives of this study were to: 1) compare three watershed-scale models (Soil and Water Assessment Tool (SWAT), Field_SWAT, and the High Impact Targeting (HIT) model) against calibrated field-scale model (RUSLE2) in estimating sediment yield from 41 randomly selected agricultural fields within the River Raisin watershed; 2) evaluate the statistical significance among models; 3) assess the watershed models' capabilities in identifying areas of concern at the field level; 4) evaluate the reliability of the watershed-scale models for field-scale analysis. The SWAT model produced the most similar estimates to RUSLE2 by providing the closest median and the lowest absolute error in sediment yield predictions, while the HIT model estimates were the worst. Concerning statistically significant differences between models, SWAT was the only model found to be not significantly different from the calibrated RUSLE2 at α = 0.05. Meanwhile, all models were incapable of identifying priorities areas similar to the RUSLE2 model. Overall, SWAT provided the most correct estimates (51%) within the uncertainty bounds of RUSLE2 and is the most reliable among the studied models, while HIT is the least reliable. The results of this study suggest caution should be exercised when using watershed-scale models for field level decision-making, while field specific data is of paramount importance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparative study of transient hydraulic tomography with varying parameterizations and zonations: Laboratory sandbox investigation

NASA Astrophysics Data System (ADS)

Luo, Ning; Zhao, Zhanfeng; Illman, Walter A.; Berg, Steven J.

2017-11-01

Transient hydraulic tomography (THT) is a robust method of aquifer characterization to estimate the spatial distributions (or tomograms) of both hydraulic conductivity (K) and specific storage (Ss). However, the highly-parameterized nature of the geostatistical inversion approach renders it computationally intensive for large-scale investigations. In addition, geostatistics-based THT may produce overly smooth tomograms when head data used to constrain the inversion is limited. Therefore, alternative model conceptualizations for THT need to be examined. To investigate this, we simultaneously calibrated different groundwater models with varying parameterizations and zonations using two cases of different pumping and monitoring data densities from a laboratory sandbox. Specifically, one effective parameter model, four geology-based zonation models with varying accuracy and resolution, and five geostatistical models with different prior information are calibrated. Model performance is quantitatively assessed by examining the calibration and validation results. Our study reveals that highly parameterized geostatistical models perform the best among the models compared, while the zonation model with excellent knowledge of stratigraphy also yields comparable results. When few pumping tests with sparse monitoring intervals are available, the incorporation of accurate or simplified geological information into geostatistical models reveals more details in heterogeneity and yields more robust validation results. However, results deteriorate when inaccurate geological information are incorporated. Finally, our study reveals that transient inversions are necessary to obtain reliable K and Ss estimates for making accurate predictions of transient drawdown events.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Influence of declining mean annual rainfall on the behavior and yield of sediment and particulate organic carbon from tropical watersheds

NASA Astrophysics Data System (ADS)

Strauch, Ayron M.; MacKenzie, Richard A.; Giardina, Christian P.; Bruland, Gregory L.

2018-04-01

The capacity to forecast climate and land-use driven changes to runoff, soil erosion and sediment transport in the tropics is hindered by a lack of long-term data sets and model study systems. To address these issues we utilized three watersheds characterized by similar shape, geology, soils, vegetation cover, and land use arranged across a 900 mm gradient in mean annual rainfall (MAR). Using this space-for-time design, we quantified suspended sediment (SS) and particulate organic carbon (POC) export over 18 months to examine how large-scale climate trends (MAR) affect sediment supply and delivery patterns (hysteresis) in tropical watersheds. Average daily SS yield ranged from 0.128 to 0.618 t km- 2 while average daily POC ranged from 0.002 to 0.018 t km- 2. For the largest storm events, we found that sediment delivery exhibited similar clockwise hysteresis patterns among the watersheds, with no significant differences in the similarity function between watershed pairs, indicating that: (1) in-stream and near-stream sediment sources drive sediment flux; and (2) the shape and timing of hysteresis is not affected by MAR. With declining MAR, the ratio of runoff to baseflow and inter-storm length between pulse events both increased. Despite increases in daily rainfall and the number of days with large rainfall events increasing with MAR, there was a decline in daily SS yield possibly due to the exhaustion of sediment supply by frequent runoff events in high MAR watersheds. By contrast, mean daily POC yield increased with increasing MAR, possibly as a result of increased soil organic matter decomposition, greater biomass, or increased carbon availability in higher MAR watersheds. We compared results to modeled values using the Load Estimator (LOADEST) FORTRAN model, confirming the negative relationship between MAR and sediment yield. However, because of its dependency on mean daily flow, LOADEST tended to under predict sediment yield, a result of its poor ability to capture the high variability in tropical streamflow. Taken together, results indicate that declines in MAR can have contrasting effects on hydrological processes in tropical watersheds, with consequences for instream ecology, downstream water users, and nearshore habitat.

Influence of conduit flow mechanics on magma rheology and the growth style of lava domes

NASA Astrophysics Data System (ADS)

Husain, Taha; Elsworth, Derek; Voight, Barry; Mattioli, Glen; Jansma, Pamela

2018-06-01

We develop a 2-D particle-mechanics model to explore different lava-dome growth styles. These range from endogenous lava dome growth comprising expansion of a ductile dome core to the exogenous extrusion of a degassed lava plug resulting in generation of a lava spine. We couple conduit flow dynamics with surface growth of the evolving lava dome, fuelled by an open-system magma chamber undergoing continuous replenishment. The conduit flow model accounts for the variation in rheology of ascending magma that results from degassing-induced crystallization. A period of reduced effusive flow rates promote enhanced degassing-induced crystallization. A degassed lava plug extrudes exogenously for magmas with crystal contents (ϕ) of 78 per cent, yield strength >1.62 MPa, and at flow rates of <0.5 m3 s-1, while endogenous dome growth is predicted at higher flow rates (Qout > 3 m3 s-1) for magma with lower relative yield strengths (<1 MPa). At moderately high flow rates (Qout = 4 m3 s-1), the extrusion of magma with lower crystal content (62 per cent) and low interparticulate yield strength (0.6 MPa) results in the development of endogenous shear lobes. Our simulations model the periodic extrusion history at Mount St. Helens (1980-1983). Endogenous growth initiates in the simulated lava dome with the extrusion of low yield strength magma (ϕ = 0.63 and τp = 0.76 MPa) after the crystallized viscous plug (ϕ = 0.87 and τp = 3 MPa) at the conduit exit is forced out by the high discharge rate pulse (2 < Qout < 12 m3 s-1). The size of the endogenous viscous plug and the occurrence of exogenous growth depend on magma yield strength and the magma chamber volume, which control the periodicity of the effusion. Our simulations generate dome morphologies similar to those observed at Mount St Helens, and demonstrate the degree to which domes can sag and spread during and following extrusion pulses. This process, which has been observed at Mount St. Helens and other locations, largely reflects gravitational loading of dome with a viscous core, with retardation by yield strength and talus friction.

A combined approach to investigate the toxicity of an industrial landfill's leachate: Chemical analyses, risk assessment and in vitro assays

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

Baderna, D., E-mail: diego.baderna@marionegri.it; Maggioni, S.; Boriani, E.

2011-05-15

Solid wastes constitute an important and emerging problem. Landfills are still one of the most common ways to manage waste disposal. The risk assessment of pollutants from landfills is becoming a major environmental issue in Europe, due to the large number of sites and to the importance of groundwater protection. Furthermore, there is lack of knowledge for the environmental, ecotoxicological and toxicological characteristics of most contaminants contained into landfill leacheates. Understanding leachate composition and creating an integrated strategy for risk assessment are currently needed to correctly face the landfill issues and to make projections on the long-term impacts of amore » landfill, with particular attention to the estimation of possible adverse effects on human health and ecosystem. In the present study, we propose an integrated strategy to evaluate the toxicity of the leachate using chemical analyses, risk assessment guidelines and in vitro assays using the hepatoma HepG2 cells as a model. The approach was applied on a real case study: an industrial waste landfill in northern Italy for which data on the presence of leachate contaminants are available from the last 11 years. Results from our ecological risk models suggest important toxic effects on freshwater fish and small rodents, mainly due to ammonia and inorganic constituents. Our results from in vitro data show an inhibition of cell proliferation by leachate at low doses and cytotoxic effect at high doses after 48 h of exposure. - Research highlights: {yields} We study the toxicity of leachate from a non-hazardous industrial waste landfill. {yields} We perform chemical analyses, risk assessments and in vitro assays on HepG2 cells. {yields} Risk models suggest toxic effects due to ammonia and inorganic constituents. {yields} In vitro assays show that leachate inhibits cell proliferation at low doses. {yields} Leachate can induce cytotoxic effects on HepG2 cells at high doses.« less

Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status

NASA Astrophysics Data System (ADS)

Kvakić, Marko; Pellerin, Sylvain; Ciais, Philippe; Achat, David L.; Augusto, Laurent; Denoroy, Pascal; Gerber, James S.; Goll, Daniel; Mollier, Alain; Mueller, Nathaniel D.; Wang, Xuhui; Ringeval, Bruno

2018-01-01

Phosphorus (P) is an essential element for plant growth. Low P availability in soils is likely to limit crop yields in many parts of the world, but this effect has never been quantified at the global scale by process-based models. Here we attempt to estimate P limitation in three major cereals worldwide for the year 2000 by combining information on soil P distribution in croplands and a generic crop model, while accounting for the nature of soil-plant P transport. As a global average, the diffusion-limited soil P supply meets the crop's P demand corresponding to the climatic yield potential, due to the legacy soil P in highly fertilized areas. However, when focusing on the spatial distribution of P supply versus demand, we found strong limitation in regions like North and South America, Africa, and Eastern Europe. Averaged over grid cells where P supply is lower than demand, the global yield gap due to soil P is estimated at 22, 55, and 26% in winter wheat, maize, and rice. Assuming that a fraction (20%) of the annual P applied in fertilizers is directly available to the plant, the global P yield gap lowers by only 5-10%, underlying the importance of the existing soil P supply in sustaining crop yields. The study offers a base for exploring P limitation in crops worldwide but with certain limitations remaining. These could be better accounted for by describing the agricultural P cycle with a fully coupled and mechanistic soil-crop model.

Negative impacts of climate change on cereal yields: statistical evidence from France

NASA Astrophysics Data System (ADS)

Gammans, Matthew; Mérel, Pierre; Ortiz-Bobea, Ariel

2017-05-01

In several world regions, climate change is predicted to negatively affect crop productivity. The recent statistical yield literature emphasizes the importance of flexibly accounting for the distribution of growing-season temperature to better represent the effects of warming on crop yields. We estimate a flexible statistical yield model using a long panel from France to investigate the impacts of temperature and precipitation changes on wheat and barley yields. Winter varieties appear sensitive to extreme cold after planting. All yields respond negatively to an increase in spring-summer temperatures and are a decreasing function of precipitation about historical precipitation levels. Crop yields are predicted to be negatively affected by climate change under a wide range of climate models and emissions scenarios. Under warming scenario RCP8.5 and holding growing areas and technology constant, our model ensemble predicts a 21.0% decline in winter wheat yield, a 17.3% decline in winter barley yield, and a 33.6% decline in spring barley yield by the end of the century. Uncertainty from climate projections dominates uncertainty from the statistical model. Finally, our model predicts that continuing technology trends would counterbalance most of the effects of climate change.

The impact exploration of agricultural drought on winter wheat yield in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui

2017-04-01

Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive correlation (p<0.01), which may provide a way to quantitatively evaluate the winter wheat yield losses caused by drought. Key words: drought, winter wheat yield, SPEI, EPIC, the North China Plain

Baryonic contributions to the dilepton spectra in relativistic heavy ion collisions

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

Bleicher, M.; Dutt-mazumder, A. K.; Gale, C.

2017-05-09

We investigate the baryonic contributions to the dilepton yield in high energy heavy ion collisions within the context of a transport model. The relative contribution of the baryonic and mesonic sources are examined. It is observed that most dominant among the baryonic channels is the decay of N*(1520) and mostly confined in the region below the rho peak. In a transport theory implementation we find the baryonic contribution to the lepton pair yield to be small.

Photooxidation of Mixed Aryl and Biarylphosphines

PubMed Central

Zhang, Dong; Celaje, Jeff A.; Agua, Alon; Doan, Chad; Stewart, Timothy; Bau, Robert; Selke, Matthias

2010-01-01

Aryl phosphines and dialkylbiaryl phosphines react with singlet oxygen to form phosphinate esters. For mixed arylphosphines, the most electron-rich aryl group migrates to form the phosphinate, while for dialkylbiaryl phosphines migration of the alkyl group occurs. Dialkylbiaryl phosphines also yield arene epoxides, especially in electron rich systems. Phosphinate ester formation is increased at high temperature while protic solvents increase the yield of epoxide. The product distribution provides evidence for Buchwald’s recent conformational model for the aerobic oxidation of dialkylbiaryl phosphines. PMID:20527907

Assessing the impacts of crop-rotation and tillage on crop yields and sediment yield using a modeling approach

Treesearch

B.P. Parajuli; P. Jayakody; G.F. Sassenrath; Y. Ouyang; J.W. Pote

2013-01-01

This study was conducted in the Big Sunflower River Watershed (BSRW), north-west, Mississippi. The watershed has been identified as “impaired waters” under Section 303(d) of the Federal Clean Water Act due to high levels of sediment and total phosphorus. This excess is then transported to the Gulf of Mexico via the Yazoo River, further damaging the nation’s water...

A novel approach: high resolution inspection with wafer plane defect detection

NASA Astrophysics Data System (ADS)

Hess, Carl; Wihl, Mark; Shi, Rui-fang; Xiong, Yalin; Pang, Song

2008-05-01

High Resolution reticle inspection is well-established as a proven, effective, and efficient means of detecting yield-limiting mask defects as well as defects which are not immediately yield-limiting yet can enable manufacturing process improvements. Historically, RAPID products have enabled detection of both classes of these defects. The newly-developed Wafer Plane Inspection (WPI) detector technology meets the needs of some advanced mask manufacturers to identify the lithographically-significant defects while ignoring the other non-lithographically-significant defects. Wafer Plane Inspection accomplishes this goal by performing defect detection based on a modeled image of how the mask features would actually print in the photoresist. This has the effect of reducing sensitivity to non-printing defects while enabling higher sensitivity focused in high MEEF areas where small reticle defects still yield significant printing defects on wafers. WPI is a new inspection mode that has been developed by KLA-Tencor and is currently under test with multiple customers. It employs the same transmitted and reflected-light high-resolution images as the industry-standard high-resolution inspections, but with much more sophisticated processing involved. A rigorous mask pattern recovery algorithm is used to convert the transmitted and reflected light images into a modeled representation of the reticle. Lithographic modeling of the scanner is then used to generate an aerial image of the mask. This is followed by resist modeling to determine the exposure of the photoresist. The defect detectors are then applied on this photoresist plane so that only printing defects are detected. Note that no hardware modifications to the inspection system are required to enable this detector. The same tool will be able to perform both our standard High Resolution inspections and the Wafer Plane Inspection detector. This approach has several important features. The ability to ignore non-printing defects and to apply additional effective sensitivity in high MEEF areas enables advanced node development. In addition, the modeling allows the inclusion of important polarization effects that occur in the resist for high NA operation. This allows for the results to better match wafer print results compared to alternate approaches. Finally, the simulation easily allows for the application of arbitrary illumination profiles. With this approach, users of WPI can make use of unique or custom scanner illumination profiles. This allows the more precise modeling of profiles without inspection system hardware modification or loss of company intellectual property. This paper examines WPI in Die:Die mode. Future work includes a review of Die:Database WPI capability.

Remote sensing and modelling of vegetation dynamics for early estimation and spatial analysis of grain yields in semiarid context in central Tunisia

NASA Astrophysics Data System (ADS)

Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra

2016-04-01

In arid and semi-arid areas, population growth, urbanization, food security and climate change have an impact on agriculture in general and particular on the cereal production. Therefore to improve food security in arid countries, crop canopy monitoring and yield forecasting cereals are needed. Many models, based on the use of remote sensing or agro-meteorological models, have been developed to estimate the biomass and grain yield of cereals. Through the use of a rich database, acquired over a period of two years for more than 80 test fields, and from optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two yield prediction approaches. The first approach is based on the application of the semi-empirical growth model SAFY, developed to simulate the dynamics of the LAI and the grain yield, at the field scale. The model is able to reproduce the time evolution of the leaf area index of all fields with acceptable error. However, an inter-comparison between ground yield measurements and SAFY model simulations reveals that the yields are under-estimated by this model. We can explain the limits of the semi-empirical model SAFY by its simplicity and also by various factors that were not considered (fertilization, irrigation,...). To improve the yield estimation, a new approach is proposed: the grain yield is estimated in function of the LAI in the growth period between 25 March and 5 April. The LAI of this period is estimated by SAFY model. A linear relationship is developed between the measured grain yield and the LAI area of the maximum growth period.This approach is robust, the measured and estimated grain yields are well correlated. Following the validation of this approach, yield estimations are proposed for the entire studied site using the SPOT/HRV images.

Characterization and modeling of the rheology of cement paste: With applications toward self-flowing materials

NASA Astrophysics Data System (ADS)

Saak, Aaron Wilbur

The objective of this research is to better understand the important mechanisms that control the rheology of cement paste. In order to understand these mechanisms, new experimental techniques are developed. The insights gained through these studies are then applied toward designing self-flowing materials, particularly self-compacting concrete (SCC). A new testing program is developed where both the peak and equilibrium stress flow curves of cement paste are obtained by testing only one sample. Additionally, the influence of wall slip on yield stress and viscoelastic measurements is determined using a vane. The results indicate that a slip layer develops when the shear stress approaches the yield point. A three-dimensional model relating slump to yield stress is derived as a function of cone geometry. The results indicate that the model fits experimental data for cylindrical slumps over a wide range of yield stress values for a variety of materials. When compared to other published models, the results suggest that a fundamental relationship exists between yield stress and slump that is material independent and largely independent of cone geometry. The affect of various mixing techniques on the rheology of cement paste is investigated using a rheometer as a highly controlled mixer. The results suggest that there is a characteristic shear rate where the viscosity of cement paste is minimized. The influence of particle packing density, morphology and surface area on the viscosity of cement paste is quantified. The data suggest that even though packing density increases with the addition of fine particles, the benefits are largely overshadowed by a dramatic increase in surface area. Finally, a new methodology is introduced for designing self-compacting concrete. This approach incorporates a "self-flow zone" where the rheology of the paste matrix provides high workability, yet segregation resistance. The flow properties of fresh concrete are measured using a U-tube apparatus to test the general applicability of the proposed methodology. Using the new design approach, concrete with a slump of 29 cm (11 inches) and slump flow diameter of 60.9 cm (24 inches) is produced.

Quantifying potential yield and water-limited yield of summer maize in the North China Plain

NASA Astrophysics Data System (ADS)

Jiang, Mingnuo; Liu, Chaoshun; Chen, Maosi

2017-09-01

The North China Plain is a major food producing region in China, and climate change could pose a threat to food production in the region. Based on China Meteorological Forcing Dataset, simulating the growth of summer maize in North China Plain from 1979 to 2015 with the regional implementation of crop growth model WOFOST. The results showed that the model can reflect the potential yield and water-limited yield of Summer Maize in North China Plain through the calibration and validation of WOFOST model. After the regional implementation of model, combined with the reanalysis data, the model can better reproduce the regional history of summer maize yield in the North China Plain. The yield gap in Southeastern Beijing, southern Tianjin, southern Hebei province, Northwestern Shandong province is significant, these means the water condition is the main factor to summer maize yield in these regions.

Impacts of drought on grape yields in Western Cape, South Africa

NASA Astrophysics Data System (ADS)

Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on how to reduce the impacts of drought on food security in South Africa.

Modeling the impact of conservation agriculture on crop production and soil properties in Mediterranean climate

NASA Astrophysics Data System (ADS)

Moussadek, Rachid; Mrabet, Rachid; Dahan, Rachid; Laghrour, Malika; Lembiad, Ibtissam; ElMourid, Mohamed

2015-04-01

In Morocco, rainfed agriculture is practiced in the majority of agricultural land. However, the intensive land use coupled to the irregular rainfall constitutes a serious threat that affect country's food security. Conservation agriculture (CA) represents a promising alternative to produce more and sustainably. In fact, the direct seeding showed high yield in arid regions of Morocco but its extending to other more humid agro-ecological zones (rainfall > 350mm) remains scarce. In order to promote CA in Morocco, differents trials have been installed in central plateau of Morocco, to compare CA to conventional tillage (CT). The yields of the main practiced crops (wheat, lentil and checkpea) under CA and CT were analyzed and compared in the 3 soils types (Vertisol, Cambisol and Calcisol). Also, we studied the effect of CA on soil organic matter (SOM) and soil losses (SL) in the 3 different sites. The APSIM model was used to model the long term impact of CA compared to CT. The results obtained in this research have shown favorable effects of CA on crop production, SOM and soil erosion. Key words: Conservation agriculture, yield, soil properties, modeling, APSIM, Morocco.

A regional modeling framework of phosphorus sources and transport in streams of the southeastern United States

USGS Publications Warehouse

Garcia, Ana Maria.; Hoos, Anne B.; Terziotti, Silvia

2011-01-01

We applied the SPARROW model to estimate phosphorus transport from catchments to stream reaches and subsequent delivery to major receiving water bodies in the Southeastern United States (U.S.). We show that six source variables and five land-to-water transport variables are significant (p < 0.05) in explaining 67% of the variability in long-term log-transformed mean annual phosphorus yields. Three land-to-water variables are a subset of landscape characteristics that have been used as transport factors in phosphorus indices developed by state agencies and are identified through experimental research as influencing land-to-water phosphorus transport at field and plot scales. Two land-to-water variables – soil organic matter and soil pH – are associated with phosphorus sorption, a significant finding given that most state-developed phosphorus indices do not explicitly contain variables for sorption processes. Our findings for Southeastern U.S. streams emphasize the importance of accounting for phosphorus present in the soil profile to predict attainable instream water quality. Regional estimates of phosphorus associated with soil-parent rock were highly significant in explaining instream phosphorus yield variability. Model predictions associate 31% of phosphorus delivered to receiving water bodies to geology and the highest total phosphorus yields in the Southeast were catchments with already high background levels that have been impacted by human activity.

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%.

Effects of different biomass drying and lipid extraction methods on algal lipid yield, fatty acid profile, and biodiesel quality.

PubMed

Hussain, Javid; Liu, Yan; Lopes, Wilson A; Druzian, Janice I; Souza, Carolina O; Carvalho, Gilson C; Nascimento, Iracema A; Liao, Wei

2015-03-01

Three lipid extraction methods of hexane Soxhlet (Sox-Hex), Halim (HIP), and Bligh and Dyer (BD) were applied on freeze-dried (FD) and oven-dried (OD) Chlorella vulgaris biomass to evaluate their effects on lipid yield, fatty acid profile, and algal biodiesel quality. Among these three methods, HIP was the preferred one for C. vulgaris lipid recovery considering both extraction efficiency and solvent toxicity. It had the highest lipid yields of 20.0 and 22.0% on FD and OD biomass, respectively, with corresponding neutral lipid yields of 14.8 and 12.7%. The lipid profiling analysis showed that palmitic, oleic, linoleic, and α-linolenic acids were the major fatty acids in the algal lipids, and there were no significant differences on the amount of these acids between different drying and extraction methods. Correlative models applied to the fatty acid profiles concluded that high contents of palmitic and oleic acids in algal lipids contributed to balancing the ratio of saturated and unsaturated fatty acids and led to a high-quality algal biodiesel.

Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models

USGS Publications Warehouse

Linard, Joshua I.

2013-01-01

Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.

CFD modelling of a membrane reactor for hydrogen production from ammonia

NASA Astrophysics Data System (ADS)

Shwe Hla, San; Dolan, Michael D.

2018-01-01

Despite the growing use of hydrogen (H2) as a transport fuel, one of the major barriers still remaining is efficient and inexpensive fuel distribution and storage. Current approaches, such as compression, liquefaction or metal hydride formation, incur a significant energy penalty. Ammonia (NH3) has long been considered a prospective H2 medium, exhibiting a higher volumetric H2 density than liquid H2, through liquid-phase storage at mild pressure. Decomposition of NH3 into H2 and N2 can be achieved via use of catalytic reactors and fuel-cell-grade H2 can be produced using metal membranes at H2 distribution sites.In this study, a 3-Dimensional (3D) Computational Fluid Dynamics (CFD) model has been developed to understand the performance of the H2 separation process in gas mixtures derived from an NH3-cracking reaction. The reactor consists of 19 tubular membrane tubes, each 470 mm long, inside a tubular shell with an inner diameter of 130 mm. Standard transport and energy equations governing a 3D, pressure-based, steady-state model were derived from the laws of conservation of mass, momentum and energy. The governing equations were solved using commercial CFD software ANSYS Fluent 18.0. Gas flow and mixing were modelled by the two-equation standard k-epsilon model for closure. Coupled solver was used for pressure-velocity coupling, enabling a pseudo-transient option with pseudo time steps of 0.01 s. To estimate H2 permeation through the metal membrane, a constant H2 permeability of 3.0E-07 mol.m-1 s-1 Pa-0.5 derived from series of experiments tested under a range of industrial conditions, was used. Model simulations were conducted for an adiabatic temperature of 300 °C, a feed-side pressure of 7.8 bara and a permeate side pressure of 0.1 bara. A parametric analysis was carried out to explore the effects of variation in total feed-gas flow and effects of changes in NH3-cracking efficiency on H2 production rates and H2 yields. The model estimated that 4.6-11.6 kg H2/day can be produced from a 30-70 L min-1 NH3 inlet flow with 80-90% NH3-cracking efficiency. At lower NH3 inlet flow rates, higher H2 yields can be obtained within a shorter distance of the membrane tubes due to relatively slower velocities and longer residence times. At high inlet flow rates, H2 yields were significantly lower due to their faster velocities and shorter resident times, but high yields (>95%) were still observed at the membrane reactor outlet. A sensitivity analysis of the model showed that even if metal membranes functioned at only 50% of the maximum permeability, a high H2 yield similar to that estimated using 100% permeability can still be achieved at the H2 outlets.

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.

Evaluation of the CEAS trend and monthly weather data models for soybean yields in Iowa, Illinois, and Indiana

NASA Technical Reports Server (NTRS)

French, V. (Principal Investigator)

1982-01-01

The CEAS models evaluated use historic trend and meteorological and agroclimatic variables to forecast soybean yields in Iowa, Illinois, and Indiana. Indicators of yield reliability and current measures of modeled yield reliability were obtained from bootstrap tests on the end of season models. Indicators of yield reliability show that the state models are consistently better than the crop reporting district (CRD) models. One CRD model is especially poor. At the state level, the bias of each model is less than one half quintal/hectare. The standard deviation is between one and two quintals/hectare. The models are adequate in terms of coverage and are to a certain extent consistent with scientific knowledge. Timely yield estimates can be made during the growing season using truncated models. The models are easy to understand and use and are not costly to operate. Other than the specification of values used to determine evapotranspiration, the models are objective. Because the method of variable selection used in the model development is adequately documented, no evaluation can be made of the objectivity and cost of redevelopment of the model.

Observation of isoprene hydroxynitrates in the southeastern United States and implications for the fate of NO x

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

Xiong, F.; McAvey, Kevin; Pratt, Kerri A.

2015-10-09

Isoprene hydroxynitrates (IN) are tracers of the photochemical oxidation of isoprene in high NO x environ-ments. Production and loss of IN have a significant influ-ence on the NO x cycle and tropospheric O 3 chemistry. To better understand IN chemistry, a series of photochemical re-action chamber experiments was conducted to determine the IN yield from isoprene photooxidation at high NO concentra-tions (> 100 ppt). By combining experimental data and cal-culated isomer distributions, a total IN yield of 9(+4/-3) %was derived. The result was applied in a zero-dimensional model to simulate production and loss of ambient IN ob-served in a temperatemore » forest atmosphere, during the Southern Oxidant and Aerosol Study (SOAS) field campaign, from 27 May to 11 July 2013. The 9 % yield was consistent with the observed IN/(MVK+MACR) ratios observed during SOAS. By comparing field observations with model simulations, we identified NO as the limiting factor for ambient IN produc-tion during SOAS, but vertical mixing at dawn might also contribute (~ 27 %) to IN dynamics. A close examination of isoprene’s oxidation products indicates that its oxidation transitioned from a high-NO dominant chemical regime in the morning into a low-NO dominant regime in the after-noon. A significant amount of IN produced in the morning high NO regime could be oxidized in the low NO regime, and a possible reaction scheme was proposed.« less

Singlet Delta oxygen generation for chemical oxygen-iodine lasers

NASA Astrophysics Data System (ADS)

Georges, E.; Mouthon, A.; Barraud, R.

To improve the overall efficiency of chemical oxygen-iodine lasers, it is necessary to increase the generator production and yield of singlet delta oxygen at low and high pressure, respectively, for subsonic and supersonic lasers. The water vapor content must also be as low as possible. A generator model based on gas-liquid reaction and liquid-vapor equilibrium theories is presented. From model predictions, operating conditions have been drawn to attain the following experimental results in a bubble-column: by increasing the superficial gas velocity, the production of singlet delta oxygen is largely improved at low pressure; by mixing chlorine with an inert gas before injection in the reactor, this yield is maintained constant up to higher pressure.

Structural investigation of porcine stomach mucin by X-ray fiber diffraction and homology modeling

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

Veluraja, K., E-mail: veluraja@msuniv.ac.in; Vennila, K.N.; Umamakeshvari, K.

Research highlights: {yields} Techniques to get oriented mucin fibre. {yields} X-ray fibre diffraction pattern for mucin. {yields} Molecular modeling of mucin based on X-ray fibre diffraction pattern. -- Abstract: The basic understanding of the three dimensional structure of mucin is essential to understand its physiological function. Technology has been developed to achieve orientated porcine stomach mucin molecules. X-ray fiber diffraction of partially orientated porcine stomach mucin molecules show d-spacing signals at 2.99, 4.06, 4.22, 4.7, 5.37 and 6.5 A. The high intense d-spacing signal at 4.22 A is attributed to the antiparallel {beta}-sheet structure identified in the fraction of themore » homology modeled mucin molecule (amino acid residues 800-980) using Nidogen-Laminin complex structure as a template. The X-ray fiber diffraction signal at 6.5 A reveals partial organization of oligosaccharides in porcine stomach mucin. This partial structure of mucin will be helpful in establishing a three dimensional structure for the whole mucin molecule.« less

Climate Based Predictability of Oil Palm Tree Yield in Malaysia.

PubMed

Oettli, Pascal; Behera, Swadhin K; Yamagata, Toshio

2018-02-02

The influence of local conditions and remote climate modes on the interannual variability of oil palm fresh fruit bunches (FFB) total yields in Malaysia and two major regions (Peninsular Malaysia and Sabah/Sarawak) is explored. On a country scale, the state of sea-surface temperatures (SST) in the tropical Pacific Ocean during the previous boreal winter is found to influence the regional climate. When El Niño occurs in the Pacific Ocean, rainfall in Malaysia reduces but air temperature increases, generating a high level of water stress for palm trees. As a result, the yearly production of FFB becomes lower than that of a normal year since the water stress during the boreal spring has an important impact on the total annual yields of FFB. Conversely, La Niña sets favorable conditions for palm trees to produce more FFB by reducing chances of water stress risk. The region of the Leeuwin current also seems to play a secondary role through the Ningaloo Niño/ Niña in the interannual variability of FFB yields. Based on these findings, a linear model is constructed and its ability to reproduce the interannual signal is assessed. This model has shown some skills in predicting the total FFB yield.

Modelling climate change impact: A case of bambara groundnut (Vigna subterranea)

NASA Astrophysics Data System (ADS)

Mabhaudhi, Tafadzwanashe; Chibarabada, Tendai Polite; Chimonyo, Vimbayi Grace Petrova; Modi, Albert Thembinkosi

2018-06-01

Climate change projections for southern Africa indicate low and erratic rainfall as well as increasing frequency and intensity of rainfall extremes such as drought. The 2015/16 drought devastated large parts of southern Africa and highlighted the need for drought tolerant crops. Bambara groundnut is an African indigenous crop, commonly cultivated in southern Africa, with a higher potential for drought tolerance compared to other staple legumes. AquaCrop model was used to evaluate the impacts of climate change on yield, water use (ET) and water productivity (WP) of bambara groundnut using climate change data representative of the past (1961-1991), present (1995-2025), mid-century (2030-2060) and late century (2065-2095) obtained from five global circulation models (GCMs). The carbon dioxide (CO2) file selected was for the A2 scenario. The model was run at a sub-catchment level. Model simulations showed that yield and WP of bambara groundnut will increase over time. The mean values of yield at the different time scales across the GCMs showed that yield of bambara groundnut increased by ∼9% from the past to the present, will increase by ∼15% from the present to mid-century and will increase by 6% from mid-to late-century. The simulated results of ET showed seasonal ranges of 703-796 mm. Of this, 45% was lost to soil evaporation, suggesting the need for developing bambara groundnut varieties with faster establishment and high canopy cover. Model simulations showed an increase in WP by ∼13% from the past to present and ∼15% from the present to mid-century and ∼11% from mid-century to late century. While the results of these simulations are preliminary, they confirm the view that bambara groundnut is a potential future crop suitable for cultivation in marginal agricultural production areas. Future research should focus on crop improvement to improve current yield of bambara groundnut.

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

PubMed

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

2017-01-01

To our knowledge, yield strength testing in human nasal septal cartilage has not been reported to date. An understanding of the basic mechanics of the nasal septum may help surgeons decide how much of an L-strut to preserve and how much grafting is needed. To determine the factors correlated with yield strength of the cartilaginous nasal septum and to explore the association between L-strut width and thickness in determining yield strength. In an anatomy laboratory, yield strength of rectangular pieces of fresh cadaver nasal septal cartilage was measured, and regression was performed to identify the factors correlated with yield strength. To measure yield strength in L-shaped models, 4 bonded paper L-struts models were constructed for every possible combination of the width and thickness, for a total of 240 models. Mathematical modeling using the resultant data with trend lines and surface fitting was performed to quantify the associations among L-strut width, thickness, and yield strength. The study dates were November 1, 2015, to April 1, 2016. The factors correlated with nasal cartilage yield strength and the associations among L-strut width, thickness, and yield strength in L-shaped models. Among 95 cartilage pieces from 12 human cadavers (mean [SD] age, 67.7 [12.6] years) and 240 constructed L-strut models, L-strut thickness was the only factor correlated with nasal septal cartilage yield strength (coefficient for thickness, 5.54; 95% CI, 4.08-7.00; P < .001), with an adjusted R2 correlation coefficient of 0.37. The mean (SD) yield strength R2 varied with L-strut thickness exponentially (0.93 [0.06]) for set widths, and it varied with L-strut width linearly (0.82 [0.11]) or logarithmically (0.85 [0.17]) for set thicknesses. A 3-dimensional surface model of yield strength with L-strut width and thickness as variables was created using a 2-dimensional gaussian function (adjusted R2 = 0.94). Estimated yield strengths were generated from the model to allow determination of the desired yield strength with different permutations of L-strut width and thickness. In this study of human cadaver nasal septal cartilage, L-strut thickness was significantly associated with yield strength. In a bonded paper L-strut model, L-strut thickness had a more important role in determining yield strength than L-strut width. Surgeons should consider the thickness of potential L-struts when determining the amount of cartilaginous septum to harvest and graft. NA.

An adapted yield criterion for the evolution of subsequent yield surfaces

NASA Astrophysics Data System (ADS)

Küsters, N.; Brosius, A.

2017-09-01

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

Projecting crop yield in northern high latitude area.

PubMed

Matsumura, Kanichiro

2014-01-01

Changing climatic conditions on seasonal and longer time scales influence agricultural production. Improvement of soil and fertilizer is a strong factor in agricultural production, but agricultural production is influenced by climate conditions even in highly developed countries. It is valuable if fewer predictors make it possible to conduct future projections. Monthly temperature and precipitation, wintertime 500hPa geopotential height, and the previous year's yield are used as predictors to forecast spring wheat yield in advance. Canadian small agricultural divisions (SAD) are used for analysis. Each SAD is composed of a collection of Canadian Agricultural Regions (CAR) of similar weather and growing conditions. Spring wheat yields in each CAR are forecast from the following variables: (a) the previous year's yield, (b) earlier stages of the growing season's climate conditions and, (c) the previous year's wintertime northern hemisphere 500hPa geopotential height field. Arctic outflow events in the Okanagan Valley in Canada are associated with episodes of extremely low temperatures during wintertime. Principal component analysis (PCA) is applied for wintertime northern hemisphere 500hPa geopotential height anomalies. The spatial PCA mode1 is defined as Arctic Oscillation and it influences prevailing westerlies. The prevailing westerlies meanders and influences climatic conditions. The spatial similarity between wintertime top 5 Arctic outflow event year's composites of 500hPa geopotential height anomalies and mode 3's spatial pattern is found. Mode 3's spatial pattern looks like the Pacific/North American (PNA) pattern which describes the variation of atmospheric circulation pattern over the Pacific Ocean and North America. Climate conditions from April to June, May to July, mode 3's time coefficients, and previous year's yield are used for forecasting spring wheat yield in each SAD. Cross-validation procedure which generates eight sets of models for the eight validation periods is used. To show the reproducing projection between observed and calculated values, the root mean squared error for skill score (RMSE SS) with the persistence model serving as the reference model is used. The persistence model is used as a benchmark. The results show that SADs near USA border show better RMSE SS values and mode 3's time coefficients can be a useful predictor especially for inland province such as Manitoba. Among 27 Canadian Prairie's SADs with perfect yield data, 67% of Alberta's SADs, 86% of Manitoba's SADs, and 77% of Saskatchewan's SADs can get positive skill scores. In each SAD, future yield projection is calculated applying predictors in 2013 for the obtained eight sets of models and eight sets of forecasted values in 2013 are averaged and a near future projection result is obtained. Series of outputs including calculated forecasted yield value in each SAD is provided by smart phone application. A system for providing climatic condition for a point with a permission of Climatic Research Unit - University of East Anglia and for obtaining patent is proposed. There are several patented systems similar to the system proposed in this paper. However, these patents are different in essence. The system proposed in this paper consists of two parts. First part is to estimate equations using time series data. The second part is to acquire and apply latest climatic conditions for obtained equations and calculate future projection. If the procedure is refined and devices are originally developed, series of idea can be patented. For future work, crop index, Hokkaido is also introduced.

Effect of natural biostimulants on yield and nutritional quality: an example of sweet yellow pepper (Capsicum annuum L.) plants.

PubMed

Parađiković, Nada; Vinković, Tomislav; Vinković Vrček, Ivana; Žuntar, Irena; Bojić, Mirza; Medić-Šarić, Marica

2011-09-01

Modifications in growing techniques can affect the yield and nutritional quality of various cultivated plant species. Owing to its high nutritional value, pepper (Capsicum annuum L.) was used in this study as a model plant to investigate the effect of natural biostimulants on yield and fruit quality parameters under conditions of reduced fertilisation. A positive influence of biostimulant treatment on yield parameters was observed. The overall increase in the pigment content of leaves after biostimulant application agreed well with the higher total and commercial yields of treated pepper cultivars compared with their controls. The results showed that natural biostimulants had a positive effect on the vitamin C and total phenolic contents in pepper fruits during the hot summer season. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) antioxidant activities were also significantly higher (P < 0.05) in treated plants and correlated strongly with all measured quality parameters except total phenolic content. Generally, biostimulants improved the antioxidant activity, vitamin C and phenolic contents in fruits as well as the pigment content in leaves of treated compared with non-treated pepper plants grown hydroponically. Thus the application of biostimulants could be considered as a good production strategy for obtaining high yields of nutritionally valuable vegetables with lower impact on the environment. Copyright © 2011 Society of Chemical Industry.

Formation temperatures of thermogenic and biogenic methane

USGS Publications Warehouse

Stolper, D.A.; Lawson, M.; Davis, C.L.; Ferreira, A.A.; Santos Neto, E. V.; Ellis, G.S.; Lewan, M.D.; Martini, Anna M.; Tang, Y.; Schoell, M.; Sessions, A.L.; Eiler, J.M.

2014-01-01

Methane is an important greenhouse gas and energy resource generated dominantly by methanogens at low temperatures and through the breakdown of organic molecules at high temperatures. However, methane-formation temperatures in nature are often poorly constrained. We measured formation temperatures of thermogenic and biogenic methane using a “clumped isotope” technique. Thermogenic gases yield formation temperatures between 157° and 221°C, within the nominal gas window, and biogenic gases yield formation temperatures consistent with their comparatively lower-temperature formational environments (<50°C). In systems where gases have migrated and other proxies for gas-generation temperature yield ambiguous results, methane clumped-isotope temperatures distinguish among and allow for independent tests of possible gas-formation models.

Estimation of regional material yield from coastal landslides based on historical digital terrain modelling

USGS Publications Warehouse

Hapke, C.J.

2005-01-01

High-resolution historical (1942) and recent (1994) digital terrain models were derived from aerial photographs along the Big Sur coastline in central California to measure the long-term volume of material that enters the nearshore environment. During the 52-year measurement time period, an average of 21 000 ?? 3100 m3 km-1 a-1 of material was eroded from nine study sections distributed along the coast, with a low yield of 1000 ?? 240 m3 km-1 a-1 and a high of 46 700 ?? 7300 m3 km-1 a-1. The results compare well with known volumes from several deep-seated landslides in the area and suggest that the processes by which material is delivered to the coast are episodic in nature. In addition, a number of parameters are investigated to determine what influences the substantial variation in yield along the coast. It is found that the magnitude of regional coastal landslide sediment yield is primarily related to the physical strength of the slope-forming material. Coastal Highway 1 runs along the lower portion of the slope along this stretch of coastline, and winter storms frequently damage the highway. The California Department of Transportation is responsible for maintaining this scenic highway while minimizing the impacts to the coastal ecosystems that are part of the Monterey Bay National Marine Sanctuary. This study provides environmental managers with critical background data on the volumes of material that historically enter the nearshore from landslides, as well as demonstrating the application of deriving historical digital terrain data to model landscape evolution. Published in 2005 by John Wiley & Sons, Ltd.

Characterization and protective efficacy in an animal model of a novel truncated rotavirus VP8 subunit parenteral vaccine candidate.

PubMed

Xue, Miaoge; Yu, Linqi; Che, Yaojian; Lin, Haijun; Zeng, Yuanjun; Fang, Mujin; Li, Tingdong; Ge, Shengxiang; Xia, Ningshao

2015-05-21

The cell-attachment protein VP8* of rotavirus is a potential candidate parenteral vaccine. However, the yield of full-length VP8 protein (VP8*, residues 1-231) expressed in Escherichia coli was low, and a truncated VP8 protein (ΔVP8*, residues 65-231) cannot elicit efficient protective immunity in a mouse model. In this study, tow novel truncated VP8 proteins, VP8-1 (residues 26-231) and VP8-2 (residues 51-231), were expressed in E. coli and evaluated for immunogenicity and protective efficacy, compared with VP8* and ΔVP8*. As well as ΔVP8*, the protein VP8-1 and VP8-2 were successfully expressed in high yield and purified in homogeneous dimeric forms, while the protein VP8* was expressed with lower yield and prone to aggregation and degradation in solution. Although the immunogenicity of the protein VP8*, VP8-1, VP8-2 and ΔVP8* was comparable, immunization of VP8* and VP8-1 elicited significantly higher neutralizing antibody titers than that of VP8-2 and ΔVP8* in mice. Furthermore, when assessed using a mouse maternal antibody model, the efficacy of VP8-1 to protect against rotavirus-induced diarrhea in pups was comparable to that of VP8*, both were dramatically higher than that of VP8-2 and ΔVP8*. Taken together, the novel truncated protein VP8-1, with increased yield, improved homogeneity and high protective efficacy, is a viable candidate for further development of a parenterally administrated prophylactic vaccine against rotavirus infection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Modeling and prediction of extraction profile for microwave-assisted extraction based on absorbed microwave energy.

PubMed

Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng

2013-09-01

A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.

Catalytic conversion of lignin pyrolysis model compound- guaiacol and its kinetic model including coke formation.

PubMed

Zhang, Huiyan; Wang, Yun; Shao, Shanshan; Xiao, Rui

2016-11-21

Lignin is the most difficult to be converted and most easy coking component in biomass catalytic pyrolysis to high-value liquid fuels and chemicals. Catalytic conversion of guaiacol as a lignin model compound was conducted in a fixed-bed reactor over ZSM-5 to investigate its conversion and coking behaviors. The effects of temperature, weight hourly space velocity (WHSV) and partial pressure on product distribution were studied. The results show the maximum aromatic carbon yield of 28.55% was obtained at temperature of 650 °C, WHSV of 8 h -1 and partial pressure of 2.38 kPa, while the coke carbon yield was 19.55%. The reaction pathway was speculated to be removing methoxy group to form phenols with further aromatization to form aromatics. The amount of coke increased with increasing reaction time. The surface area and acidity of catalysts declined as coke formed on the acid sites and blocked the pore channels, which led to the decrease of aromatic yields. Finally, a kinetic model of guaiacol catalytic conversion considering coke deposition was built based on the above reaction pathway to properly predict product distribution. The experimental and model predicting data agreed well. The correlation coefficient of all equations were all higher than 0.90.

Catalytic conversion of lignin pyrolysis model compound- guaiacol and its kinetic model including coke formation

PubMed Central

Zhang, Huiyan; Wang, Yun; Shao, Shanshan; Xiao, Rui

2016-01-01

Lignin is the most difficult to be converted and most easy coking component in biomass catalytic pyrolysis to high-value liquid fuels and chemicals. Catalytic conversion of guaiacol as a lignin model compound was conducted in a fixed-bed reactor over ZSM-5 to investigate its conversion and coking behaviors. The effects of temperature, weight hourly space velocity (WHSV) and partial pressure on product distribution were studied. The results show the maximum aromatic carbon yield of 28.55% was obtained at temperature of 650 °C, WHSV of 8 h−1 and partial pressure of 2.38 kPa, while the coke carbon yield was 19.55%. The reaction pathway was speculated to be removing methoxy group to form phenols with further aromatization to form aromatics. The amount of coke increased with increasing reaction time. The surface area and acidity of catalysts declined as coke formed on the acid sites and blocked the pore channels, which led to the decrease of aromatic yields. Finally, a kinetic model of guaiacol catalytic conversion considering coke deposition was built based on the above reaction pathway to properly predict product distribution. The experimental and model predicting data agreed well. The correlation coefficient of all equations were all higher than 0.90. PMID:27869228

Role of high-spin hyperon resonances in the reaction of {gamma}p{yields}K{sup +}K{sup +}{Xi}{sup -}

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

Man, J. Ka Shing; Oh, Yongseok; Excited Baryon Analysis Center, Thomas Jefferson National Accelerator Facility, Newport News, Virginia 23606

The recent data taken by the CLAS Collaboration at the Thomas Jefferson National Accelerator Facility for the reaction of {gamma}p{yields}K{sup +}K{sup +}{Xi}{sup -} are reanalyzed within a relativistic meson-exchange model of hadronic interactions. The present model is an extension of the one developed in an earlier work by Nakayama, Oh, and Haberzettl [Phys. Rev. C 74, 035205 (2006)]. In particular, the role of the spin-5/2 and -7/2 hyperon resonances, which were not included in the previous model, is investigated in the present study. It is shown that the contribution of the {Sigma}(2030) hyperon having spin-7/2 and positive parity has amore » key role to bring the model predictions into a fair agreement with the measured data for the K{sup +}{Xi}{sup -} invariant mass distribution.« less

Study of High Lift Configurations

NASA Technical Reports Server (NTRS)

Edward, Jack R.; Hassan, Hassan A.

2000-01-01

This project focus on the implementation of the Warren-Hassan transition / turbulence model (Journal of Aircraft, Vol. 35, No. 5) into the NASA code CFL3D and its testing for multi-element airfoils in landing configuration at different angles of attack. The Warren-Hassan transition model solves an evolution equation for a kinetic energy characteristic of non-turbulent fluctuations. This is combined with an empirical estimate of the frequency of the most amplified first-mode disturbance to yield an expression for an eddy viscosity characteristic of non-turbulent fluctuations. This is combined with the k - zeta model for fully turbulent flow to yield a unified approach capable of predicting both transition onset and extent. Blending of the non-turbulent and turbulent components of the model is accomplished by an intermittency function based on the work of Dhawan and Narasimha (Journal of Fluid Mechanics, Vol. 3, No. 4).

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Climate change and potato cropping in the Peruvian Altiplano

NASA Astrophysics Data System (ADS)

Sanabria, J.; Lhomme, J. P.

2013-05-01

The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071-2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO2 concentration (A2) and moderate CO2 concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato ( Solanum tuberosum) and the bitter potato ( Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO2 on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.

Risk factors for displaced abomasum or ketosis in Swedish dairy herds.

PubMed

Stengärde, L; Hultgren, J; Tråvén, M; Holtenius, K; Emanuelson, U

2012-03-01

Risk factors associated with high or low long-term incidence of displaced abomasum (DA) or clinical ketosis were studied in 60 Swedish dairy herds, using multivariable logistic regression modelling. Forty high-incidence herds were included as cases and 20 low-incidence herds as controls. Incidence rates were calculated based on veterinary records of clinical diagnoses. During the 3-year period preceding the herd classification, herds with a high incidence had a disease incidence of DA or clinical ketosis above the 3rd quartile in a national database for disease recordings. Control herds had no cows with DA or clinical ketosis. All herds were visited during the housing period and herdsmen were interviewed about management routines, housing, feeding, milk yield, and herd health. Target groups were heifers in late gestation, dry cows, and cows in early lactation. Univariable logistic regression was used to screen for factors associated with being a high-incidence herd. A multivariable logistic regression model was built using stepwise regression. A higher maximum daily milk yield in multiparous cows and a large herd size (p=0.054 and p=0.066, respectively) tended to be associated with being a high-incidence herd. Not cleaning the heifer feeding platform daily increased the odds of having a high-incidence herd twelvefold (p<0.01). Keeping cows in only one group in the dry period increased the odds of having a high incidence herd eightfold (p=0.03). Herd size was confounded with housing system. Housing system was therefore added to the final logistic regression model. In conclusion, a large herd size, a high maximum daily milk yield, keeping dry cows in one group, and not cleaning the feeding platform daily appear to be important risk factors for a high incidence of DA or clinical ketosis in Swedish dairy herds. These results confirm the importance of housing, management and feeding in the prevention of metabolic disorders in dairy cows around parturition and in early lactation. Copyright © 2011 Elsevier B.V. All rights reserved.

The Role of Trabecular Microarchitecture in the Formation, Accumulation, and Morphology of Microdamage in Human Cancellous Bone

PubMed Central

Karim, Lamya; Vashishth, Deepak

2011-01-01

Alterations in microdamage morphology and accumulation are typically attributed to impaired remodeling, but may also result from changes in microdamage initiation and propagation. Such alterations are relevant for cancellous bone with high metabolic activity and numerous bone quality changes. This study investigates the role of trabecular microarchitecture on morphology and accumulation of microdamage in human cancellous bone. Trabecular bone cores from donors of varying ages and bone volume fraction (BV/TV) were separated into high and low BV/TV groups. Samples were subjected to no load or uniaxial compression to 0.6% (pre-yield) or 1.1% (post-yield) strain. Microdamage was stained with lead uranyl acetate and specimens were imaged via microcomputed tomography to quantify microdamage and determine its morphology in three-dimensions (3D). Donors with high BV/TV had greater post yield strain and were tougher than low BV/TV donors. High BV/TV bone had less microdamage than low BV/TV bone under post- but not pre-yield loading. Microdamage under both loading conditions showed significant correlations with microarchitecture and BV/TV, but the key predictor was structure model index (SMI). As SMI increased (more trabecular rods), microdamage morphology became crack-like. Thus, low BV/TV and increased SMI have strong influences on microdamage accumulation in bone through altered initiation. PMID:21538510

Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

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

Using LANDSAT to provide potato production estimates to Columbia Basin farmers and processors

NASA Technical Reports Server (NTRS)

1991-01-01

The estimation of potato yields in the Columbia basin is described. The fundamental objective is to provide CROPIX with working models of potato production. A two-pronged approach was used to yield estimation: (1) using simulation models, and (2) using purely empirical models. The simulation modeling approach used satellite observations to determine certain key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Purely empirical models were developed to relate yield to some spectrally derived measure of crop development. Two empirical approaches are presented: one relates tuber yield to estimates of cumulative intercepted solar radiation, the other relates tuber yield to the integral under GVI (Global Vegetation Index) curve.

Identification of Critical Erosion Prone Areas and Computation of Sediment Yield Using Remote Sensing and GIS: A Case Study on Sarada River Basin

NASA Astrophysics Data System (ADS)

Sundara Kumar, P.; Venkata Praveen, T.; Anjanaya Prasad, M.; Santha Rao, P.

2018-06-01

The two most important resources blessed by nature to the mankind are land and water. Undoubtedly, these gifts have to be conserved and maintained with unflinching efforts from every one of us for an effective environmental and ecological balance. The efforts and energy of water resources engineers and conservationists are going in this direction to conserve these precious resources of nature. The present study is an attempt to develop suitable methodology to facilitate decision makers to conserve the resources and also reflects the cause mentioned above has been presented here. The main focus of this study is to identify the critical prone areas for soil erosion and computation of sediment yield in a small basin using Universal Soil Loss Equation and Modified Universal Soil Loss Equation (MUSLE) respectively. The developed model has been applied on Sarada river basin which has a drainage area of 1252.99 km2. This river is located in Andhra Pradesh State (AP), India. The basin has been divided into micro basins for effective estimation and also for precise identification of the areas that are prone to soil erosion. Remote Sensing and Geographic Information Systems tools were used to generate and spatially organize the data that is required for soil erosion modeling. It was found that the micro basins with very severe soil erosion are consisting of hilly areas with high topographic factor and 38.01% of the study area has the rate erosion more than 20 t/ha/year and hence requires an immediate attention from the soil conservation point of view. In this study region, though there is one discharge measuring gauge station available at Anakapalli but there is no sediment yield gauging means available to compute the sediment yield. Therefore, to arrive at the suspended-sediment concentration was a challenge task. In the present study the sediment measurement has been carried out with an instrument (DH-48), sediment sampling equipment as per IS: 4890-1968, has been used. Suspended-sediment samples were collected and sediment yield was arrived at the site by using this instrument. The sediment yield was also computed using MUSLE. Data for this model study has been generated from the samples collected from 28 storm events spread over a time span of 1 year, at the outlet of the basin at Anakapalli for computation of sediment yield. The sediment yield as estimated by MUSLE model has been successfully compared with the sediment yield measured at the outlet of the basin by sediment yield measuring unit and found fairly good correlation between them. Hence the developed methodology will be useful to estimate the sediment yield in the hydrologically similar basins that are not gauged for sediment yield.

Seismic Source Scaling and Characteristics of Six North Korean Underground Nuclear Explosions

NASA Astrophysics Data System (ADS)

Park, J.; Stump, B. W.; Che, I. Y.; Hayward, C.

2017-12-01

We estimate the range of yields and source depths for the six North Korean underground nuclear explosions in 2006, 2009, 2013, 2016 (January and September), and 2017, based on regional seismic observations in South Korea and China. Seismic data used in this study are from three seismo-acoustic stations, BRDAR, CHNAR, and KSGAR, cooperatively operated by SMU and KIGAM, the KSRS seismic array operated by the Comprehensive Nuclear Test Ban Treaty Organization, and MDJ, a station in the Global Seismographic Network. We calculate spectral ratios for event pairs using seismograms from the six explosions observed along the same paths and at the same receivers. These relative seismic source scaling spectra for Pn, Pg, Sn, and surface wave windows provide a basis for a grid search source solution that estimates source yield and depth for each event based on both the modified Mueller and Murphy (1971; MM71) and Denny and Johnson (1991; DJ91) source models. The grid search is used to identify the best-fit empirical spectral ratios subject to the source models by minimizing the goodness-of-fit (GOF) in the frequency range of 0.5-15 Hz. For all cases, the DJ91 model produces higher ratios of depth and yield than MM71. These initial results include significant trade-offs between depth and yield in all cases. In order to better take the effect of source depth into account, a modified grid search was implemented that includes the propagation effects for different source depths by including reflectivity Greens functions in the grid search procedure. This revision reduces the trade-offs between depth and yield, results in better model fits to frequencies as high as 15 Hz, and GOF values smaller than those where the depth effects on the Greens functions were ignored. The depth and yield estimates for all six explosions using this new procedure will be presented.

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.

Synthesis of Enantiomerically Pure Lignin Dimer Models for Catalytic Selectivity Studies

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

Njiojob, Costyl N.; Rhinehart, Jennifer L.; Bozell, Joseph J.

2015-02-06

A series of highly enantioselective transformations, such as the Sharpless asymmetric epoxidation and Jacobsen hydrolytic kinetic resolution, were utilized to achieve the complete stereoselective synthesis of β-O-4 lignin dimer models containing the S, G, and H subunits with excellent ee (>99%) and moderate to high yields. This unprecedented synthetic method can be exploited for enzymatic, microbial, and chemical investigations into lignin’s degradation and depolymerization as related to its stereochemical constitution. Preliminary degradation studies using enantiopure Co(salen) catalysts are also reported.

The Processing and Mechanical Properties of High Temperature/High Performance Composites. Book 3. Constituent Properties and Macroscopic Performance: MMCs

DTIC Science & Technology

1993-04-01

re - expressed as, v .= hCSw (C3) Combining Eqns. (C2) and C3) yields, Se = - ’. S (C4...of vi( s ) or v ’( s ). Substituting eq. (B10) into eq. (25), one finds the finite element method expression for functional Ud [ v ] which is U, d [] = v , K...Measurements 1- D 2- D S ,_DL 4 Constitutive W Constitutive Laws Laws Matrix Cracking Labor Models Models Stress Redistribution Numerical Calculations

Acoustic vibrations of metal nanoparticles: high order radial mode detection

NASA Astrophysics Data System (ADS)

Nelet, A.; Crut, A.; Arbouet, A.; Del Fatti, N.; Vallée, F.; Portalès, H.; Saviot, L.; Duval, E.

2004-03-01

The vibrational radial modes of silver nanospheres embedded in a glass matrix are investigated using a high sensitivity femtosecond pump-probe technique. The results yield evidence for coherent launching of the fundamental and higher order radial modes in agreement with a sphere dilation mediated excitation model. The results are consistent with low-frequency Raman scattering experiments.

Phenotypic effects of subclinical paratuberculosis (Johne's disease) in dairy cattle.

PubMed

Pritchard, Tracey C; Coffey, Mike P; Bond, Karen S; Hutchings, Mike R; Wall, Eileen

2017-01-01

The effect of subclinical paratuberculosis (or Johne's disease) risk status on performance, health, and fertility was studied in 58,096 UK Holstein-Friesian cows with 156,837 lactations across lactations 1 to 3. Low-, medium-, and high-risk group categories were allocated to cows determined by a minimum of 4 ELISA milk tests taken at any time during their lactating life. Lactation curves of daily milk, protein, and fat yields and protein and fat percentage, together with log e -transformed somatic cell count, were estimated using a random regression model to quantify differences between risk groups. The effect of subclinical paratuberculosis risk groups on fertility, lactation-average somatic cell count, and mastitis were analyzed using linear regression fitting risk group as a fixed effect. Milk yield losses associated with high-risk cows compared with low-risk cows in lactations 1, 2, and 3 for mean daily yield were 0.34, 1.05, and 1.61kg; likewise, accumulated 305-d yields were 103, 316, and 485kg, respectively. The total loss was 904kg over the first 3 lactations. Protein and fat yield losses associated with high-risk cows were significant, but primarily a feature of decreasing milk yield. Similar trends were observed for both test-day and lactation-average somatic cell count measures with higher somatic cell counts from medium- and high-risk cows compared with low-risk cows, and differences were in almost all cases significant. Likewise, mastitis incidence was significantly higher in high-risk cows compared with low-risk cows in lactations 2 and 3. Whereas the few significant differences between risk groups among fertility traits were inconsistent with no clear trend. These results are expected to be conservative, as some animals that were considered negative may become positive after the timeframe of this study, particularly if the animal was tested when relatively young. However, the magnitude of milk yield losses together with higher somatic cell counts and an increase in mastitis incidence should motivate farmers to implement the appropriate control measures to reduce the spread of the disease. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Metabolite and transcript markers for the prediction of potato drought tolerance.

PubMed

Sprenger, Heike; Erban, Alexander; Seddig, Sylvia; Rudack, Katharina; Thalhammer, Anja; Le, Mai Q; Walther, Dirk; Zuther, Ellen; Köhl, Karin I; Kopka, Joachim; Hincha, Dirk K

2018-04-01

Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

First-Order Model Management With Variable-Fidelity Physics Applied to Multi-Element Airfoil Optimization

NASA Technical Reports Server (NTRS)

Alexandrov, N. M.; Nielsen, E. J.; Lewis, R. M.; Anderson, W. K.

2000-01-01

First-order approximation and model management is a methodology for a systematic use of variable-fidelity models or approximations in optimization. The intent of model management is to attain convergence to high-fidelity solutions with minimal expense in high-fidelity computations. The savings in terms of computationally intensive evaluations depends on the ability of the available lower-fidelity model or a suite of models to predict the improvement trends for the high-fidelity problem, Variable-fidelity models can be represented by data-fitting approximations, variable-resolution models. variable-convergence models. or variable physical fidelity models. The present work considers the use of variable-fidelity physics models. We demonstrate the performance of model management on an aerodynamic optimization of a multi-element airfoil designed to operate in the transonic regime. Reynolds-averaged Navier-Stokes equations represent the high-fidelity model, while the Euler equations represent the low-fidelity model. An unstructured mesh-based analysis code FUN2D evaluates functions and sensitivity derivatives for both models. Model management for the present demonstration problem yields fivefold savings in terms of high-fidelity evaluations compared to optimization done with high-fidelity computations alone.

Synergistic effect of microbubble emulsion and sonic or ultrasonic agitation on endodontic biofilm in vitro.

PubMed

Halford, Andrew; Ohl, Claus-Dieter; Azarpazhooh, Amir; Basrani, Bettina; Friedman, Shimon; Kishen, Anil

2012-11-01

Irrigation dynamics and antibacterial activity determine the efficacy of root canal disinfection. Sonic or ultrasonic agitation of irrigants is expected to improve irrigation dynamics. This study examined the effects of microbubble emulsion (ME) combined with sonic or ultrasonic agitation on irrigation dynamics and reduction of biofilm bacteria within root canal models. Two experiments were conducted. First, high-speed imaging was used to characterize the bubble dynamics generated in ME by sonic or ultrasonic agitation within canals of polymer tooth models. Second, 5.25% NaOCl irrigation or ME was sonically or ultrasonically agitated in canals of extracted teeth with 7-day-grown Enterococcus faecalis biofilms. Dentinal shavings from canal walls were sampled at 1 mm and 3 mm from the apical terminus, and colony-forming units (CFUs) were enumerated. Mean log CFU/mL values were analyzed with analysis of variance and post hoc tests. High-speed imaging demonstrated strongly oscillating and vaporizing bubbles generated within ME during ultrasonic but not sonic agitation. Compared with CFU counts in controls, NaOCl-sonic and NaOCl-ultrasonic yielded significantly lower counts (P < .05) at both measurement levels. ME-sonic yielded significantly lower counts (P = .002) at 3 mm, whereas ME-ultrasonic yielded highly significantly lower counts (P = .000) at both measurement levels. At 3 mm, ME-ultrasonic yielded significantly lower CFU counts (P = .000) than ME-sonic, NaOCl-sonic, and NaOCl-ultrasonic. Enhanced bubble dynamics and reduced E. faecalis biofilm bacteria beyond the level achieved by sonic or ultrasonic agitation of NaOCl suggested a synergistic effect of ME combined with ultrasonic agitation. Copyright © 2012 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

The production of formaldehyde and hydroxyacetone in methacrolein photooxidation: New insights into mechanism and effects of water vapor.

PubMed

Xing, Yanan; Li, Huan; Huang, Liubin; Wu, Huihui; Shen, Hengqing; Chen, Zhongming

2018-04-01

Methacrolein (MACR) is an abundant multifunctional carbonyl compound with high reactivity in the atmosphere. In this study, we investigated the hydroxyl radical initiated oxidation of MACR at various NO/MACR ratios (0 to 4.04) and relative humidities (<3% to 80%) using a flow tube. Meanwhile, a box model based on the Master Chemical Mechanism was performed to test our current understanding of the mechanism. In contrast to the reasonable predictions for hydroxyacetone production, the modeled yields of formaldehyde (HCHO) were twice higher than the experimental results. The discrepancy was ascribed to the existence of unconsidered non-HCHO forming channels in the chemistry of CH 3 C(CH 2 )OO, which account for approx. 50%. In addition, the production of hydroxyacetone and HCHO were affected by water vapor as well as the initial NO/MACR ratio. The yields of HCHO were higher under humid conditions than that under dry condition. The yields of hydroxyacetone were higher under humid conditions at low-NO x level, while lower at high-NO x level. The reasonable explanation for the lower hydroxyacetone yield under humid conditions at high-NO x level is that water vapor promotes the production of methacrolein nitrate in the reaction of HOCH 2 C(CH 3 )(OO)CHO with NO due to the peroxy radical-water complex formation, which was evidenced by calculational results. And the minimum equilibrium constant of this water complex formation was estimated to be 1.89×10 -18 cm 3 /molecule. These results provide new insights into the MACR oxidation mechanism and the effects of water vapor. Copyright © 2017. Published by Elsevier B.V.

Applicability of the polynomial chaos expansion method for personalization of a cardiovascular pulse wave propagation model.

PubMed

Huberts, W; Donders, W P; Delhaas, T; van de Vosse, F N

2014-12-01

Patient-specific modeling requires model personalization, which can be achieved in an efficient manner by parameter fixing and parameter prioritization. An efficient variance-based method is using generalized polynomial chaos expansion (gPCE), but it has not been applied in the context of model personalization, nor has it ever been compared with standard variance-based methods for models with many parameters. In this work, we apply the gPCE method to a previously reported pulse wave propagation model and compare the conclusions for model personalization with that of a reference analysis performed with Saltelli's efficient Monte Carlo method. We furthermore differentiate two approaches for obtaining the expansion coefficients: one based on spectral projection (gPCE-P) and one based on least squares regression (gPCE-R). It was found that in general the gPCE yields similar conclusions as the reference analysis but at much lower cost, as long as the polynomial metamodel does not contain unnecessary high order terms. Furthermore, the gPCE-R approach generally yielded better results than gPCE-P. The weak performance of the gPCE-P can be attributed to the assessment of the expansion coefficients using the Smolyak algorithm, which might be hampered by the high number of model parameters and/or by possible non-smoothness in the output space. Copyright © 2014 John Wiley & Sons, Ltd.

Optimising the Encapsulation of an Aqueous Bitter Melon Extract by Spray-Drying

PubMed Central

Tan, Sing Pei; Kha, Tuyen Chan; Parks, Sophie; Stathopoulos, Costas; Roach, Paul D.

2015-01-01

Our aim was to optimise the encapsulation of an aqueous bitter melon extract by spray-drying with maltodextrin (MD) and gum Arabic (GA). The response surface methodology models accurately predicted the process yield and retentions of bioactive concentrations and activity (R2 > 0.87). The optimal formulation was predicted and validated as 35% (w/w) stock solution (MD:GA, 1:1) and a ratio of 1.5:1 g/g of the extract to the stock solution. The spray-dried powder had a high process yield (66.2% ± 9.4%) and high retention (>79.5% ± 8.4%) and the quality of the powder was high. Therefore, the bitter melon extract was well encapsulated into a powder using MD/GA and spray-drying. PMID:28231214

Transverse momentum and centrality dependence of high-pT nonphotonic electron suppression in Au+Au collisions at sqrt[s NN]=200 GeV.

PubMed

Abelev, B I; Aggarwal, M M; Ahammed, Z; Anderson, B D; Arkhipkin, D; Averichev, G S; Bai, Y; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Baumgart, S; Belaga, V V; Bellingeri-Laurikainen, A; Bellwied, R; Benedosso, F; Betts, R R; Bhardwaj, S; Bhasin, A; Bhati, A K; Bichsel, H; Bielcik, J; Bielcikova, J; Bland, L C; Blyth, S-L; Bombara, M; Bonner, B E; Botje, M; Bouchet, J; Brandin, A V; Bravar, A; Burton, T P; Bystersky, M; Cadman, R V; Cai, X Z; Caines, H; Calderón de la Barca Sánchez, M; Callner, J; Catu, O; Cebra, D; Chajecki, Z; Chaloupka, P; Chattopadhyay, S; Chen, H F; Chen, J H; Chen, J Y; Cheng, J; Cherney, M; Chikanian, A; Christie, W; Chung, S U; Coffin, J P; Cormier, T M; Cosentino, M R; Cramer, J G; Crawford, H J; Das, D; Dash, S; Daugherity, M; de Moura, M M; Dedovich, T G; Dephillips, M; Derevschikov, A A; Didenko, L; Dietel, T; Djawotho, P; Dogra, S M; Dong, X; Drachenberg, J L; Draper, J E; Du, F; Dunin, V B; Dunlop, J C; Dutta Mazumdar, M R; Eckardt, V; Edwards, W R; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Fatemi, R; Fedorisin, J; Feng, A; Filip, P; Finch, E; Fine, V; Fisyak, Y; Fu, J; Gagliardi, C A; Gaillard, L; Ganti, M S; Garcia-Solis, E; Ghazikhanian, V; Ghosh, P; Gorbunov, Y G; Gos, H; Grebenyuk, O; Grosnick, D; Guertin, S M; Guimaraes, K S F F; Gupta, N; Haag, B; Hallman, T J; Hamed, A; Harris, J W; He, W; Heinz, M; Henry, T W; Heppelmann, S; Hippolyte, B; Hirsch, A; Hjort, E; Hoffman, A M; Hoffmann, G W; Hofman, D; Hollis, R; Horner, M J; Huang, H Z; Hughes, E W; Humanic, T J; Igo, G; Iordanova, A; Jacobs, P; Jacobs, W W; Jakl, P; Jia, F; Jones, P G; Judd, E G; Kabana, S; Kang, K; Kapitan, J; Kaplan, M; Keane, D; Kechechyan, A; Kettler, D; Khodyrev, V Yu; Kim, B C; Kiryluk, J; Kisiel, A; Kislov, E M; Klein, S R; Knospe, A G; Kocoloski, A; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kouchpil, V; Kowalik, K L; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kurnadi, P; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Lapointe, S; Laue, F; Lauret, J; Lebedev, A; Lednicky, R; Lee, C-H; Lehocka, S; LeVine, M J; Li, C; Li, Q; Li, Y; Lin, G; Lin, X; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, H; Liu, J; Liu, L; Ljubicic, T; Llope, W J; Longacre, R S; Love, W A; Lu, Y; Ludlam, T; Lynn, D; Ma, G L; Ma, J G; Ma, Y G; Magestro, D; Mahapatra, D P; Majka, R; Mangotra, L K; Manweiler, R; Margetis, S; Markert, C; Martin, L; Matis, H S; Matulenko, Yu A; McClain, C J; McShane, T S; Melnick, Yu; Meschanin, A; Millane, J; Miller, M L; Minaev, N G; Mioduszewski, S; Mironov, C; Mischke, A; Mitchell, J; Mohanty, B; Morozov, D A; Munhoz, M G; Nandi, B K; Nattrass, C; Nayak, T K; Nelson, J M; Nepali, N S; Netrakanti, P K; Nogach, L V; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Pachr, M; Pal, S K; Panebratsev, Y; Pavlinov, A I; Pawlak, T; Peitzmann, T; Perevoztchikov, V; Perkins, C; Peryt, W; Phatak, S C; Planinic, M; Pluta, J; Poljak, N; Porile, N; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Qattan, I A; Raniwala, R; Raniwala, S; Ray, R L; Relyea, D; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Rose, A; Roy, C; Ruan, L; Russcher, M J; Sahoo, R; Sakrejda, I; Sakuma, T; Salur, S; Sandweiss, J; Sarsour, M; Sazhin, P S; Schambach, J; Scharenberg, R P; Schmitz, N; Seger, J; Selyuzhenkov, I; Seyboth, P; Shabetai, A; Shahaliev, E; Shao, M; Sharma, M; Shen, W Q; Shimanskiy, S S; Sichtermann, E P; Simon, F; Singaraju, R N; Smirnov, N; Snellings, R; Sorensen, P; Sowinski, J; Speltz, J; Spinka, H M; Srivastava, B; Stadnik, A; Stanislaus, T D S; Staszak, D; Stock, R; Strikhanov, M; Stringfellow, B; Suaide, A A P; Suarez, M C; Subba, N L; Sumbera, M; Sun, X M; Sun, Z; Surrow, B; Symons, T J M; Szanto de Toledo, A; Takahashi, J; Tang, A H; Tarnowsky, T; Thomas, J H; Timmins, A R; Timoshenko, S; Tokarev, M; Trainor, T A; Trentalange, S; Tribble, R E; Tsai, O D; Ulery, J; Ullrich, T; Underwood, D G; Van Buren, G; van der Kolk, N; van Leeuwen, M; Vander Molen, A M; Varma, R; Vasilevski, I M; Vasiliev, A N; Vernet, R; Vigdor, S E; Viyogi, Y P; Vokal, S; Voloshin, S A; Waggoner, W T; Wang, F; Wang, G; Wang, J S; Wang, X L; Wang, Y; Watson, J W; Webb, J C; Westfall, G D; Wetzler, A; Whitten, C; Wieman, H; Wissink, S W; Witt, R; Wu, J; Wu, Y; Xu, N; Xu, Q H; Xu, Z; Yepes, P; Yoo, I-K; Yue, Q; Yurevich, V I; Zhan, W; Zhang, H; Zhang, W M; Zhang, Y; Zhang, Z P; Zhao, Y; Zhong, C; Zhou, J; Zoulkarneev, R; Zoulkarneeva, Y; Zubarev, A N; Zuo, J X

2007-05-11

The STAR collaboration at the BNL Relativistic Heavy-Ion Collider (RHIC) reports measurements of the inclusive yield of nonphotonic electrons, which arise dominantly from semileptonic decays of heavy flavor mesons, over a broad range of transverse momenta (1.2

Optimization of an innovative approach involving mechanical activation and acid digestion for the extraction of lithium from lepidolite

NASA Astrophysics Data System (ADS)

Vieceli, Nathália; Nogueira, Carlos A.; Pereira, Manuel F. C.; Durão, Fernando O.; Guimarães, Carlos; Margarido, Fernanda

2018-01-01

The recovery of lithium from hard rock minerals has received increased attention given the high demand for this element. Therefore, this study optimized an innovative process, which does not require a high-temperature calcination step, for lithium extraction from lepidolite. Mechanical activation and acid digestion were suggested as crucial process parameters, and experimental design and response-surface methodology were applied to model and optimize the proposed lithium extraction process. The promoting effect of amorphization and the formation of lithium sulfate hydrate on lithium extraction yield were assessed. Several factor combinations led to extraction yields that exceeded 90%, indicating that the proposed process is an effective approach for lithium recovery.

Satellite-based assessment of grassland yields

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Yibo; Xiao, Jingfeng; Ju, Weimin; Xu, Ke; Zhou, Yanlian; Zhao, Yuntai

2016-09-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China’s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation ‘greening’ and ‘browning’ on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate.

Yield prediction by analysis of multispectral scanner data

NASA Technical Reports Server (NTRS)

Colwell, J. E.; Suits, G. H.

1975-01-01

A preliminary model describing the growth and grain yield of wheat was developed. The modeled growth characteristics of the wheat crop were used to compute wheat canopy reflectance using a model of vegetation canopy reflectance. The modeled reflectance characteristics were compared with the corresponding growth characteristics and grain yield in order to infer their relationships. It appears that periodic wheat canopy reflectance characteristics potentially derivable from earth satellites will be useful in forecasting wheat grain yield.

Predicting paddlefish roe yields using an extension of the Beverton–Holt equilibrium yield-per-recruit model

USGS Publications Warehouse

Colvin, M.E.; Bettoli, Phillip William; Scholten, G.D.

2013-01-01

Equilibrium yield models predict the total biomass removed from an exploited stock; however, traditional yield models must be modified to simulate roe yields because a linear relationship between age (or length) and mature ovary weight does not typically exist. We extended the traditional Beverton-Holt equilibrium yield model to predict roe yields of Paddlefish Polyodon spathula in Kentucky Lake, Tennessee-Kentucky, as a function of varying conditional fishing mortality rates (10-70%), conditional natural mortality rates (cm; 9% and 18%), and four minimum size limits ranging from 864 to 1,016mm eye-to-fork length. These results were then compared to a biomass-based yield assessment. Analysis of roe yields indicated the potential for growth overfishing at lower exploitation rates and smaller minimum length limits than were suggested by the biomass-based assessment. Patterns of biomass and roe yields in relation to exploitation rates were similar regardless of the simulated value of cm, thus indicating that the results were insensitive to changes in cm. Our results also suggested that higher minimum length limits would increase roe yield and reduce the potential for growth overfishing and recruitment overfishing at the simulated cm values. Biomass-based equilibrium yield assessments are commonly used to assess the effects of harvest on other caviar-based fisheries; however, our analysis demonstrates that such assessments likely underestimate the probability and severity of growth overfishing when roe is targeted. Therefore, equilibrium roe yield-per-recruit models should also be considered to guide the management process for caviar-producing fish species.

Strategies for narrowing the maize yield gap of household farms through precision fertigation under irrigated conditions using CERES-Maize model.

PubMed

Liu, Jiangang; Wang, Guangyao; Chu, Qingquan; Chen, Fu

2017-07-01

Nitrogen (N) application significantly increases maize yield; however, the unreasonable use of N fertilizer is common in China. The analysis of crop yield gaps can reveal the limiting factors for yield improvement, but there is a lack of practical strategies for narrowing yield gaps of household farms. The objectives of this study were to assess the yield gap of summer maize using an integrative method and to develop strategies for narrowing the maize yield gap through precise N fertilization. The results indicated that there was a significant difference in maize yield among fields, with a low level of variation. Additionally, significant differences in N application rate were observed among fields, with high variability. Based on long-term simulation results, the optimal N application rate was 193 kg ha -1 , with a corresponding maximum attainable yield (AY max ) of 10 318 kg ha -1 . A considerable difference between farmers' yields and AY max was observed. Low agronomic efficiency of applied N fertilizer (AE N ) in farmers' fields was exhibited. The integrative method lays a foundation for exploring the specific factors constraining crop yield gaps at the field scale and for developing strategies for rapid site-specific N management. Optimization strategies to narrow the maize yield gap include increasing N application rates and adjusting the N application schedule. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize

NASA Astrophysics Data System (ADS)

Carter, Elizabeth K.; Melkonian, Jeff; Riha, Susan J.; Shaw, Stephen B.

2016-09-01

Several recent studies have indicated that high air temperatures are limiting maize (Zea mays L.) yields in the US Corn Belt and project significant yield losses with expected increases in growing season temperatures. Further work has suggested that high air temperatures are indicative of high evaporative demand, and that decreases in maize yields which correlate to high temperatures and vapor pressure deficits (VPD) likely reflect underlying soil moisture limitations. It remains unclear whether direct high temperature impacts on yields, independent of moisture stress, can be observed under current temperature regimes. Given that projected high temperature and moisture may not co-vary the same way as they have historically, quantitative analyzes of direct temperature impacts are critical for accurate yield projections and targeted mitigation strategies under shifting temperature regimes. To evaluate yield response to above optimum temperatures independent of soil moisture stress, we analyzed climate impacts on irrigated maize yields obtained from the National Corn Growers Association (NCGA) corn yield contests for Nebraska, Kansas and Missouri. In irrigated maize, we found no evidence of a direct negative impact on yield by daytime air temperature, calculated canopy temperature, or VPD when analyzed seasonally. Solar radiation was the primary yield-limiting climate variable. Our analyses suggested that elevated night temperature impacted yield by increasing rates of phenological development. High temperatures during grain-fill significantly interacted with yields, but this effect was often beneficial and included evidence of acquired thermo-tolerance. Furthermore, genetics and management—information uniquely available in the NCGA contest data—explained more yield variability than climate, and significantly modified crop response to climate. Thermo-acclimation, improved genetics and changes to management practices have the potential to partially or completely offset temperature-related yield losses in irrigated maize.

N* production from pp and p-barp collisions

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

Wu Jiajun; Cao Xu; Theoretical Physics Center for Science Facilities, CAS, Beijing 100049

2011-10-21

With an effective Lagrangian approach, we give a full analysis on the NN{yields}NN{pi}{pi} and pp{yields}pn{pi}{sup +} reactions for proton beam energy from 1 to 1.5 GeV. The results are very consistent with the experiment data from CELSIUS, KEK, COSY, and so on. Based on these results, we consider the N-barN{yields}N-barN{pi}{pi} and p-barp{yields}p-barn{pi}{sup +} for proton beam energy up to 4 GeV. Compare to the pp collisions, there are many benefits to study N* resonances in these two reactions. And for the high proton beam energy up to 15 GeV, we consider some new resonances with hidden charm which are definitelymore » beyond three constituent quarks model in the p-barp{yields}p-barpJ/{psi} and p-barp{yields}p-barp{eta}{sub c}, where there are very nice places to find these new N{sub cc}-bar*. The predicted results about p-barp collisions can be looked for at the forthcoming PANDA/FAIR experiments.« less

Variability of Suitable Habitat of Western Winter-Spring Cohort for Neon Flying Squid in the Northwest Pacific under Anomalous Environments.

PubMed

Yu, Wei; Chen, Xinjun; Yi, Qian; Chen, Yong; Zhang, Yang

2015-01-01

We developed a habitat suitability index (HSI) model to evaluate the variability of suitable habitat for neon flying squid (Ommastrephes bartramii) under anomalous environments in the Northwest Pacific Ocean. Commercial fisheries data from the Chinese squid-jigging vessels on the traditional fishing ground bounded by 35°-45°N and 150°-175°E from July to November during 1998-2009 were used for analyses, as well as the environmental variables including sea surface temperature (SST), chlorophyll-a (Chl-a) concentration, sea surface height anomaly (SSHA) and sea surface salinity (SSS). Two empirical HSI models (arithmetic mean model, AMM; geometric mean model, GMM) were established according to the frequency distribution of fishing efforts. The AMM model was found to perform better than the GMM model. The AMM-based HSI model was further validated by the fishery and environmental data in 2010. The predicted HSI values in 1998 (high catch), 2008 (average catch) and 2009 (low catch) indicated that the squid habitat quality was strongly associated with the ENSO-induced variability in the oceanic conditions on the fishing ground. The La Niña events in 1998 tended to yield warm SST and favorable range of Chl-a concentration and SSHA, resulting in high-quality habitats for O. bartramii. While the fishing ground in the El Niño year of 2009 experienced anomalous cool waters and unfavorable range of Chl-a concentration and SSHA, leading to relatively low-quality squid habitats. Our findings suggest that the La Niña event in 1998 tended to result in more favorable habitats for O. bartramii in the Northwest Pacific with the gravity centers of fishing efforts falling within the defined suitable habitat and yielding high squid catch; whereas the El Niño event in 2009 yielded less favorable habitat areas with the fishing effort distribution mismatching the suitable habitat and a dramatic decline of the catch of O. bartramii. This study might provide some potentially valuable insights into exploring the relationship between the underlying squid habitat and the inter-annual environmental change.

Variability of Suitable Habitat of Western Winter-Spring Cohort for Neon Flying Squid in the Northwest Pacific under Anomalous Environments

PubMed Central

Yu, Wei; Chen, Xinjun; Yi, Qian; Chen, Yong; Zhang, Yang

2015-01-01

We developed a habitat suitability index (HSI) model to evaluate the variability of suitable habitat for neon flying squid (Ommastrephes bartramii) under anomalous environments in the Northwest Pacific Ocean. Commercial fisheries data from the Chinese squid-jigging vessels on the traditional fishing ground bounded by 35°-45°N and 150°-175°E from July to November during 1998-2009 were used for analyses, as well as the environmental variables including sea surface temperature (SST), chlorophyll-a (Chl-a) concentration, sea surface height anomaly (SSHA) and sea surface salinity (SSS). Two empirical HSI models (arithmetic mean model, AMM; geometric mean model, GMM) were established according to the frequency distribution of fishing efforts. The AMM model was found to perform better than the GMM model. The AMM-based HSI model was further validated by the fishery and environmental data in 2010. The predicted HSI values in 1998 (high catch), 2008 (average catch) and 2009 (low catch) indicated that the squid habitat quality was strongly associated with the ENSO-induced variability in the oceanic conditions on the fishing ground. The La Niña events in 1998 tended to yield warm SST and favorable range of Chl-a concentration and SSHA, resulting in high-quality habitats for O. bartramii. While the fishing ground in the El Niño year of 2009 experienced anomalous cool waters and unfavorable range of Chl-a concentration and SSHA, leading to relatively low-quality squid habitats. Our findings suggest that the La Niña event in 1998 tended to result in more favorable habitats for O. bartramii in the Northwest Pacific with the gravity centers of fishing efforts falling within the defined suitable habitat and yielding high squid catch; whereas the El Niño event in 2009 yielded less favorable habitat areas with the fishing effort distribution mismatching the suitable habitat and a dramatic decline of the catch of O. bartramii. This study might provide some potentially valuable insights into exploring the relationship between the underlying squid habitat and the inter-annual environmental change. PMID:25923519

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

Energy yields for hydrogen cyanide and formaldehyde syntheses - The HCN and amino acid concentrations in the primitive ocean

NASA Technical Reports Server (NTRS)

Stribling, Roscoe; Miller, Stanley L.

1987-01-01

Simulated prebiotic atmospheres containing either CH4, CO, or CO2, in addition to N2, H2O, and variable amounts of H2, were subjected to the spark from a high-frequency Tesla coil, and the energy yields for the syntheses of HCN and H2CO were estimated from periodic (every two days) measurements of the compound concentrations. The mixtures with CH4 were found to yield the highest amounts of HCN, whereas the CO mixtures produced the highest yields of H2CO. These results model atmospheric corona discharges. From the yearly energy yields calculated and the corona discharge available on the earth, the yearly production rate of HCN was estimated; using data on the HCN production rates and the experimental rates of decomposition of amino acids through the submarine vents, the steady state amino acid production rate in the primitive ocean was calculated to be about 10 nmoles/sq cm per year.

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Farming and the fate of wild nature.

PubMed

Green, Rhys E; Cornell, Stephen J; Scharlemann, Jörn P W; Balmford, Andrew

2005-01-28

World food demand is expected to more than double by 2050. Decisions about how to meet this challenge will have profound effects on wild species and habitats. We show that farming is already the greatest extinction threat to birds (the best known taxon), and its adverse impacts look set to increase, especially in developing countries. Two competing solutions have been proposed: wildlife-friendly farming (which boosts densities of wild populations on farmland but may decrease agricultural yields) and land sparing (which minimizes demand for farmland by increasing yield). We present a model that identifies how to resolve the trade-off between these approaches. This shows that the best type of farming for species persistence depends on the demand for agricultural products and on how the population densities of different species on farmland change with agricultural yield. Empirical data on such density-yield functions are sparse, but evidence from a range of taxa in developing countries suggests that high-yield farming may allow more species to persist.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

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

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.

The effect of shear strength on isentropic compression experiments

NASA Astrophysics Data System (ADS)

Thomson, Stuart; Howell, Peter; Ockendon, John; Ockendon, Hilary

2015-06-01

Isentropic compression experiments (ICE) are a novel way of obtaining equation of state information for metals undergoing violent plastic deformation. In a typical experiment, millimetre thick metal samples are subjected to pressures on the order of 10 -102 GPa, while the yield strength of the material can be as low as 10-1GPa. The analysis of such experiments has so far neglected the effect of shear strength, instead treating the highly plasticised metal as an inviscid compressible fluid. However making this approximation belies the basic elastic nature of a solid object. A more accurate method should strive to incorporate the small but measurable effects of shear strength. Here we present a one-dimensional mathematical model for elastoplasticity at high stress which allows for both compressibility and the shear strength of the material. In the limit of zero yield stress this model reproduces the hydrodynamic models currently used to analyse ICEs. We will also show using a systematic asymptotic analysis that entropy changes are universally negligible in the absence of shocks. Numerical solutions of the governing equations will then be presented for problems relevant to ICEs in order to investigate the effects of shear strength over a model based purely on hydrodynamics.

Micro-mechanics of electrostatically stabilized suspensions of cellulose nanofibrils under steady state shear flow.

PubMed

Martoïa, F; Dumont, P J J; Orgéas, L; Belgacem, M N; Putaux, J-L

2016-02-14

In this study, we characterized and modeled the rheology of TEMPO-oxidized cellulose nanofibril (NFC) aqueous suspensions with electrostatically stabilized and unflocculated nanofibrous structures. These colloidal suspensions of slender and wavy nanofibers exhibited a yield stress and a shear thinning behavior at low and high shear rates, respectively. Both the shear yield stress and the consistency of these suspensions were power-law functions of the NFC volume fraction. We developed an original multiscale model for the prediction of the rheology of these suspensions. At the nanoscale, the suspensions were described as concentrated systems where NFCs interacted with the Newtonian suspending fluid through Brownian motion and long range fluid-NFC hydrodynamic interactions, as well as with each other through short range hydrodynamic and repulsive colloidal interaction forces. These forces were estimated using both the experimental results and 3D networks of NFCs that were numerically generated to mimic the nanostructures of NFC suspensions under shear flow. They were in good agreement with theoretical and measured forces for model colloidal systems. The model showed the primary role played by short range hydrodynamic and colloidal interactions on the rheology of NFC suspensions. At low shear rates, the origin of the yield stress of NFC suspensions was attributed to the combined contribution of repulsive colloidal interactions and the topology of the entangled NFC networks in the suspensions. At high shear rates, both concurrent colloidal and short (in some cases long) range hydrodynamic interactions could be at the origin of the shear thinning behavior of NFC suspensions.

Fully kinetic simulations of dense plasma focus Z-pinch devices.

PubMed

Schmidt, A; Tang, V; Welch, D

2012-11-16

Dense plasma focus Z-pinch devices are sources of copious high energy electrons and ions, x rays, and neutrons. The mechanisms through which these physically simple devices generate such high-energy beams in a relatively short distance are not fully understood. We now have, for the first time, demonstrated a capability to model these plasmas fully kinetically, allowing us to simulate the pinch process at the particle scale. We present here the results of the initial kinetic simulations, which reproduce experimental neutron yields (~10(7)) and high-energy (MeV) beams for the first time. We compare our fluid, hybrid (kinetic ions and fluid electrons), and fully kinetic simulations. Fluid simulations predict no neutrons and do not allow for nonthermal ions, while hybrid simulations underpredict neutron yield by ~100x and exhibit an ion tail that does not exceed 200 keV. Only fully kinetic simulations predict MeV-energy ions and experimental neutron yields. A frequency analysis in a fully kinetic simulation shows plasma fluctuations near the lower hybrid frequency, possibly implicating lower hybrid drift instability as a contributor to anomalous resistivity in the plasma.

Measuring B{sup {+-}}{yields}{tau}{sup {+-}}{nu} and B{sub c}{sup {+-}}{yields}{tau}{sup {+-}}{nu} at the Z peak

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

Akeroyd, A. G.; Chen, C.H.; National Center for Theoretical Sciences, Taiwan

2008-06-01

The measurement of B{sup {+-}}{yields}{tau}{sup {+-}}{nu}{sub {tau}} at the B factories provides important constraints on the parameter tan{beta}/m{sub H{sup {+-}}} in the context of models with two Higgs doublets. Limits on this decay from e{sup +}e{sup -} collisions at the Z peak were sensitive to the sum of B{sup {+-}}{yields}{tau}{sup {+-}}{nu}{sub {tau}} and B{sub c}{sup {+-}}{yields}{tau}{sup {+-}}{nu}{sub {tau}}. Because of the possibly sizeable contribution from B{sub c}{sup {+-}}{yields}{tau}{sup {+-}}{nu}{sub {tau}} we suggest that a signal for this combination might be observed if the CERN LEP L3 Collaboration used its total data of {approx}3.6x10{sup 6} hadronic decays of the Z boson.more » Moreover, we point out that a future linear collider operating at the Z peak (Giga Z option) could constrain tan{beta}/m{sub H{sup {+-}}} from the sum of these processes with a precision comparable to that anticipated at proposed high luminosity B factories from B{sup {+-}}{yields}{tau}{sup {+-}}{nu}{sub {tau}} alone.« less

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy.

PubMed

Payne, Courtney E; Wolfrum, Edward J

2015-01-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. We present individual model statistics to demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. It is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.

Luminescence of water or ice as a new detection method for magnetic monopoles

NASA Astrophysics Data System (ADS)

Pollmann, Anna Obertacke

2017-12-01

Cosmic ray detectors use air as a radiator for luminescence. In water and ice, Cherenkov light is the dominant light producing mechanism when the particle's velocity exceeds the Cherenkov threshold, approximately three quarters of the speed of light in vacuum. Luminescence is produced by highly ionizing particles passing through matter due to the electronic excitation of the surrounding molecules. The observables of luminescence, such as the wavelength spectrum and decay times, are highly dependent on the properties of the medium, in particular, temperature and purity. The results for the light yield of luminescence of previous measurements vary by two orders of magnitude. It will be shown that even for the lowest measured light yield, luminescence is an important signature of highly ionizing particles below the Cherenkov threshold. These could be magnetic monopoles or other massive and highly ionizing exotic particles. With the highest observed efficiencies, luminescence may even contribute significantly to the light output of standard model particles such as the PeV IceCube neutrinos. We present analysis techniques to use luminescence in neutrino telescopes and discuss experimental setups to measure the light yield of luminescence for the particular conditions in neutrino detectors.

The effects of laser absorption on direct-drive capsule experiments at OMEGA

NASA Astrophysics Data System (ADS)

Dodd, E. S.; Benage, J. F.; Kyrala, G. A.; Wilson, D. C.; Wysocki, F. J.; Seka, W.; Glebov, V. Yu.; Stoeckl, C.; Frenje, J. A.

2012-04-01

The yield of an inertial confinement fusion capsule can be greatly affected by the inclusion of high-Z material in the fuel, either intentionally as a diagnostic or from mixing due to hydrodynamic instabilities. To validate calculations of these conditions, glass shell targets filled with a D2 and 3He fuel mixture were fielded in experiments with controlled amounts of pre-mixed Ar, Kr, or Xe. The experiments were fielded at the OMEGA laser [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)] using 1.0 ns square laser pulses having a total energy 23 kJ and direct drive illumination of shells with an outer diameter of ˜925 μm and a thickness of ˜5 μm. Data were collected and compared to one-dimensional integrated models for yield and burn-temperature measurements. This paper presents a critical examination of the calculational assumptions used in our experimental modeling. A modified treatment of laser-capsule interaction improves the match to the measured scattered laser light and also improves agreement for yields, burn-temperatures, and the fuel compression as measured by the ratio of two yields. Remaining discrepancies between measurement and calculation will also be discussed.

Refining metabolic models and accounting for regulatory effects.

PubMed

Kim, Joonhoon; Reed, Jennifer L

2014-10-01

Advances in genome-scale metabolic modeling allow us to investigate and engineer metabolism at a systems level. Metabolic network reconstructions have been made for many organisms and computational approaches have been developed to convert these reconstructions into predictive models. However, due to incomplete knowledge these reconstructions often have missing or extraneous components and interactions, which can be identified by reconciling model predictions with experimental data. Recent studies have provided methods to further improve metabolic model predictions by incorporating transcriptional regulatory interactions and high-throughput omics data to yield context-specific metabolic models. Here we discuss recent approaches for resolving model-data discrepancies and building context-specific metabolic models. Once developed highly accurate metabolic models can be used in a variety of biotechnology applications. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1982-01-01

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Self-consistent one dimension in space and three dimension in velocity kinetic trajectory simulation model of magnetized plasma-wall transition

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

Chalise, Roshan, E-mail: plasma.roshan@gmail.com; Khanal, Raju

2015-11-15

We have developed a self-consistent 1d3v (one dimension in space and three dimension in velocity) Kinetic Trajectory Simulation (KTS) model, which can be used for modeling various situations of interest and yields results of high accuracy. Exact ion trajectories are followed, to calculate along them the ion distribution function, assuming an arbitrary injection ion distribution. The electrons, on the other hand, are assumed to have a cut-off Maxwellian velocity distribution at injection and their density distribution is obtained analytically. Starting from an initial guess, the potential profile is iterated towards the final time-independent self-consistent state. We have used it tomore » study plasma sheath region formed in presence of an oblique magnetic field. Our results agree well with previous works from other models, and hence, we expect our 1d3v KTS model to provide a basis for the studying of all types of magnetized plasmas, yielding more accurate results.« less

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.

Development of a Computationally Efficient, High Fidelity, Finite Element Based Hall Thruster Model

NASA Technical Reports Server (NTRS)

Jacobson, David (Technical Monitor); Roy, Subrata

2004-01-01

This report documents the development of a two dimensional finite element based numerical model for efficient characterization of the Hall thruster plasma dynamics in the framework of multi-fluid model. Effect of the ionization and the recombination has been included in the present model. Based on the experimental data, a third order polynomial in electron temperature is used to calculate the ionization rate. The neutral dynamics is included only through the neutral continuity equation in the presence of a uniform neutral flow. The electrons are modeled as magnetized and hot, whereas ions are assumed magnetized and cold. The dynamics of Hall thruster is also investigated in the presence of plasma-wall interaction. The plasma-wall interaction is a function of wall potential, which in turn is determined by the secondary electron emission and sputtering yield. The effect of secondary electron emission and sputter yield has been considered simultaneously, Simulation results are interpreted in the light of experimental observations and available numerical solutions in the literature.

Non-cell-autonomous effects yield lower clonal diversity in expanding tumors.

PubMed

Tissot, Tazzio; Thomas, Frédéric; Roche, Benjamin

2017-09-11

Recent cancer research has investigated the possibility that non-cell-autonomous (NCA) driving tumor growth can support clonal diversity (CD). Indeed, mutations can affect the phenotypes not only of their carriers ("cell-autonomous", CA effects), but also sometimes of other cells (NCA effects). However, models that have investigated this phenomenon have only considered a restricted number of clones. Here, we designed an individual-based model of tumor evolution, where clones grow and mutate to yield new clones, among which a given frequency have NCA effects on other clones' growth. Unlike previously observed for smaller assemblages, most of our simulations yield lower CD with high frequency of mutations with NCA effects. Owing to NCA effects increasing competition in the tumor, clones being already dominant are more likely to stay dominant, and emergent clones not to thrive. These results may help personalized medicine to predict intratumor heterogeneity across different cancer types for which frequency of NCA effects could be quantified.

Hydrodynamics of CNT dispersion in high shear dispersion mixers

NASA Astrophysics Data System (ADS)

Park, Young Min; Lee, Dong Hyun; Hwang, Wook Ryol; Lee, Sang Bok; Jung, Seung-Il

2014-11-01

In this work, we investigate the carbon nanotube (CNT) fragmentation mechanism and dispersion in high shear homogenizers as a plausible dispersion technique, correlating with device geometries and processing conditions, for mass production of CNT-aluminum composites for automobile industries. A CNT dispersion model has been established in a turbulent flow regime and an experimental method in characterizing the critical yield stress of CNT flocs are presented. Considering CNT dispersion in ethanol as a model system, we tested two different geometries of high shear mixers — blade-stirrer type and rotor-stator type homogenizers — and reported the particle size distributions in time and the comparison has been made with the modeling approach and partly with the computational results.

Fermiophobia in a Higgs triplet model

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

Akeroyd, A. G.; NExT Institute and School of Physics and Astronomy, University of Southampton, Highfield, Southampton SO17 1BJ; Diaz, Marco A.

2011-05-01

A fermiophobic Higgs boson can arise in models with an extended Higgs sector, such as models with scalars in an isospin triplet representation. In a specific model with a scalar triplet and spontaneous violation of lepton number induced by a scalar singlet field, we show that fermiophobia is not a fine-tuned situation, unlike in two higgs doublet models. We study distinctive signals of fermiophobia which can be probed at the LHC. For the case of a small Higgs mass, a characteristic signal would be a moderate B(H{yields}{gamma}{gamma}) accompanied by a large B(H{yields}JJ) (where J is a Majoron), the latter beingmore » an invisible decay. For the case of a large Higgs mass there is the possibility of dominant H{yields}ZZ, WW and suppressed H{yields}JJ decay modes. In this situation, B(H{yields}ZZ) is larger than B(H{yields}WW), which differs from the SM prediction.« less

The use of Fourier-transform infrared spectroscopy to predict cheese yield and nutrient recovery or whey loss traits from unprocessed bovine milk samples.

PubMed

Ferragina, A; Cipolat-Gotet, C; Cecchinato, A; Bittante, G

2013-01-01

Cheese yield is an important technological trait in the dairy industry in many countries. The aim of this study was to evaluate the effectiveness of Fourier-transform infrared (FTIR) spectral analysis of fresh unprocessed milk samples for predicting cheese yield and nutrient recovery traits. A total of 1,264 model cheeses were obtained from 1,500-mL milk samples collected from individual Brown Swiss cows. Individual measurements of 7 new cheese yield-related traits were obtained from the laboratory cheese-making procedure, including the fresh cheese yield, total solid cheese yield, and the water retained in curd, all as a percentage of the processed milk, and nutrient recovery (fat, protein, total solids, and energy) in the curd as a percentage of the same nutrient contained in the milk. All individual milk samples were analyzed using a MilkoScan FT6000 over the spectral range from 5,000 to 900 wavenumber × cm(-1). Two spectral acquisitions were carried out for each sample and the results were averaged before data analysis. Different chemometric models were fitted and compared with the aim of improving the accuracy of the calibration equations for predicting these traits. The most accurate predictions were obtained for total solid cheese yield and fresh cheese yield, which exhibited coefficients of determination between the predicted and measured values in cross-validation (1-VR) of 0.95 and 0.83, respectively. A less favorable result was obtained for water retained in curd (1-VR=0.65). Promising results were obtained for recovered protein (1-VR=0.81), total solids (1-VR=0.86), and energy (1-VR=0.76), whereas recovered fat exhibited a low accuracy (1-VR=0.41). As FTIR spectroscopy is a rapid, cheap, high-throughput technique that is already used to collect standard milk recording data, these FTIR calibrations for cheese yield and nutrient recovery highlight additional potential applications of the technique in the dairy industry, especially for monitoring cheese-making processes and milk payment systems. In addition, the prediction models can be used to provide breeding organizations with information on new phenotypes for cheese yield and milk nutrient recovery, potentially allowing these traits to be enhanced through selection. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

Alkyl nitrate formation from the reactions of C8-C14 n-alkanes with OH radicals in the presence of NO(x): measured yields with essential corrections for gas-wall partitioning.

PubMed

Yeh, Geoffrey K; Ziemann, Paul J

2014-09-18

In this study, C8-C14 n-alkanes were reacted with OH radicals in the presence of NO(x) in a Teflon film environmental chamber and isomer-specific yields of alkyl nitrates were determined using gas chromatography. Because results indicated significant losses of alkyl nitrates to chamber walls, gas-wall partitioning was investigated by monitoring the concentrations of a suite of synthesized alkyl nitrates added to the chamber. Gas-to-wall partitioning increased with increasing carbon number and with proximity of the nitrooxy group to the terminal carbon, with losses as high as 86%. The results were used to develop a structure-activity model to predict the effects of carbon number and isomer structure on gas-wall partitioning, which was used to correct the measured yields of alkyl nitrate isomers formed in chamber reactions. The resulting branching ratios for formation of secondary alkyl nitrates were similar for all isomers of a particular carbon number, and average values, which were almost identical to alkyl nitrate yields, were 0.219, 0.206, 0.254, 0.291, and 0.315 for reactions of n-octane, n-decane, n-dodecane, n-tridecane, and n-tetradecane, respectively. The increase in average branching ratios and alkyl nitrate yields with increasing carbon number to a plateau value of ∼0.30 at about C13-C14 is consistent with predictions of a previously developed model, indicating that the model is valid for alkane carbon numbers ≥C3.

Using Landsat to provide potato production estimates to Columbia Basin farmers and processors

NASA Technical Reports Server (NTRS)

1990-01-01

A summary of project activities relative to the estimation of potato yields in the Columbia Basin is given. Oregon State University is using a two-pronged approach to yield estimation, one using simulation models and the other using purely empirical models. The simulation modeling approach has used satellite observations to determine key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Two empirical modeling approaches are illustrated. One relates tuber yield to estimates of cumulative intercepted solar radiation; the other relates tuber yield to the integral under the GVI curve.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

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.

Near-vacuum hohlraums for driving fusion implosions with high density carbon ablatorsa)

NASA Astrophysics Data System (ADS)

Berzak Hopkins, L. F.; Le Pape, S.; Divol, L.; Meezan, N. B.; Mackinnon, A. J.; Ho, D. D.; Jones, O. S.; Khan, S.; Milovich, J. L.; Ross, J. S.; Amendt, P.; Casey, D.; Celliers, P. M.; Pak, A.; Peterson, J. L.; Ralph, J.; Rygg, J. R.

2015-05-01

Recent experiments at the National Ignition Facility [M. J. Edwards et al., Phys. Plasmas 20, 070501 (2013)] have explored driving high-density carbon ablators with near-vacuum hohlraums, which use a minimal amount of helium gas fill. These hohlraums show improved efficiency relative to conventional gas-filled hohlraums in terms of minimal backscatter, minimal generation of suprathermal electrons, and increased hohlraum-capsule coupling. Given these advantages, near-vacuum hohlraums are a promising choice for pursuing high neutron yield implosions. Long pulse symmetry control, though, remains a challenge, as the hohlraum volume fills with material. Two mitigation methodologies have been explored, dynamic beam phasing and increased case-to-capsule ratio (larger hohlraum size relative to capsule). Unexpectedly, experiments have demonstrated that the inner laser beam propagation is better than predicted by nominal simulations, and an enhanced beam propagation model is required to match measured hot spot symmetry. Ongoing work is focused on developing a physical model which captures this enhanced propagation and on utilizing the enhanced propagation to drive longer laser pulses than originally predicted in order to reach alpha-heating dominated neutron yields.

Controlling Microbial Safety Challenges of Meat Using High Voltage Atmospheric Cold Plasma

PubMed Central

Han, Lu; Ziuzina, Dana; Heslin, Caitlin; Boehm, Daniela; Patange, Apurva; Sango, David M.; Valdramidis, Vasilis P.; Cullen, Patrick J.; Bourke, Paula

2016-01-01

Atmospheric cold plasma (ACP) is a non-thermal technology, effective against a wide range of pathogenic microorganisms. Inactivation efficacy results from plasma generated reactive species. These may interact with any organic components in a test matrix including the target microorganism, thus food components may exert a protective effect against the antimicrobial mode of action. The effect of an in-package high voltage ACP process applied in conjunction with common meat processing MAP gas compositions as well as bacteria type and meat model media composition have been investigated to determine the applicability of this technology for decontamination of safety challenges associated with meat products. E. coli, L. monocytogenes, and S. aureus in PBS were undetectable after 60 s of treatment at 80 kVRMS in air, while ACP treatment of the contaminated meat model required post-treatment refrigeration to retain antimicrobial effect. The nutritive components in the meat model exerted a protective effect during treatment, where 300 s ACP exposure yielded a maximum reduction of 1.5 log using a high oxygen atmosphere, whilst using air and high nitrogen atmospheres yielded lower antimicrobial efficacy. Furthermore, an ROS assay was performed to understand the protective effects observed using the meat model. This revealed that nutritive components inhibited penetration of ROS into bacterial cells. This knowledge can assist the optimization of meat decontamination using ACP technology where interactions with all components of the food matrix require evaluation. PMID:27446018

Food security in the 21st century: Global yield projections and agricultural expansion

NASA Astrophysics Data System (ADS)

Davis, K. F.; Rulli, M.; D'Odorico, P.

2013-12-01

Global demands on agricultural lands are ever increasing as a result of population growth, changes in diet and increasing biofuel use. By mid-century, the demands for food and fiber are expected to roughly double with the population reaching 9.5 billion. However, earth's finite resource base places a ceiling on the amount of agricultural production that is possible. Several strategies have been widely discussed to meet these rapid increases and to extend the ceiling yet higher, including reducing waste, modifying diets, improving yield and productivity and expanding agriculture and aquaculture. One of the most promising of these is closing the yield gap of currently under-performing agricultural land that has the potential to be much more productive. With high inputs (e.g. irrigation, fertilizers), this strategy has real potential to increase food security, particularly in the developing world where population is expected to sharply increase and where a high potential for yield gap closure exists. Thus it is important to consider whether improvements in global yield can adequately meet global dietary demand during the 21st century. Constructing yield projections to the end of the century, we examine whether global crop production for 154 countries and 16 major food crops under selected agricultural and dietary scenarios can keep pace with estimates of population growth to 2100. By calculating the global production of calories, we are then able to examine how many people can be supported under future scenarios and how closing yield gaps can increase this potential. Our findings agree with previous studies that closing the yield gap alone cannot provide sufficient production by mid-century and that a heavy global dependence on trade will persist throughout the century. Using high-resolution global land suitability maps under a suite of climate models, we find that scenarios incorporating a combination of yield gap closure and agricultural expansion provide the most promise in meeting global demand. However, this must be done with the goal of sustainable agriculture in mind and in a way that minimizes detrimental environmental impacts, particularly to forested areas and rangelands.

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

PubMed

Pervin, Lia; Islam, Md Saiful

2015-02-01

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

Search for the Theta+ in photoproduction on the deuteron

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

K.H. Hicks

2005-07-26

A high-statistics experiment on a deuterium target was performed using a real photon beam with energies up to 3.6 GeV at the CLAS detector of Jefferson Lab. The reaction reported here is for {gamma}d {yields} pK{sup -} K{sup +} n where the neutron was identified using the missing mass technique. No statistically significant narrow peak in the mass region from 1.5-1.6 GeV was found. An upper limit on the elementary process {gamma}n {yields} K{sup -} {Theta}{sup +} was estimated to be about 4-5 nb, using a model-dependent correction for rescattering determined from {Lambda}(1520) production. Other reactions with less model-dependence aremore » being pursued.« less

Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations.

PubMed

Amon, Thomas; Amon, Barbara; Kryvoruchko, Vitaliy; Machmüller, Andrea; Hopfner-Sixt, Katharina; Bodiroza, Vitomir; Hrbek, Regina; Friedel, Jürgen; Pötsch, Erich; Wagentristl, Helmut; Schreiner, Matthias; Zollitsch, Werner

2007-12-01

Biogas production is of major importance for the sustainable use of agrarian biomass as renewable energy source. Economic biogas production depends on high biogas yields. The project aimed at optimising anaerobic digestion of energy crops. The following aspects were investigated: suitability of different crop species and varieties, optimum time of harvesting, specific methane yield and methane yield per hectare. The experiments covered 7 maize, 2 winter wheat, 2 triticale varieties, 1 winter rye, and 2 sunflower varieties and 6 variants with permanent grassland. In the course of the vegetation period, biomass yield and biomass composition were measured. Anaerobic digestion was carried out in eudiometer batch digesters. The highest methane yields of 7500-10200 m(N)(3)ha(-1) were achieved from maize varieties with FAO numbers (value for the maturity of the maize) of 300 to 600 harvested at "wax ripeness". Methane yields of cereals ranged from 3200 to 4500 m(N)(3)ha(-1). Cereals should be harvested at "grain in the milk stage" to "grain in the dough stage". With sunflowers, methane yields between 2600 and 4550 m(N)(3)ha(-1) were achieved. There were distinct differences between the investigated sunflower varieties. Alpine grassland can yield 2700-3500 m(N)(3)CH(4)ha(-1). The methane energy value model (MEVM) was developed for the different energy crops. It estimates the specific methane yield from the nutrient composition of the energy crops. Energy crops for biogas production need to be grown in sustainable crop rotations. The paper outlines possibilities for optimising methane yield from versatile crop rotations that integrate the production of food, feed, raw materials and energy. These integrated crop rotations are highly efficient and can provide up to 320 million t COE which is 96% of the total energy demand of the road traffic of the EU-25 (the 25 Member States of the European Union).

Effect of pH on H2O2 production in the radiolysis of water.

PubMed

Roth, Olivia; LaVerne, Jay A

2011-02-10

The yields of hydrogen peroxide have been measured in the radiolysis of aqueous solutions of acrylamide, bromide, nitrate, and air in the pH range of 1-13. Hydrogen peroxide is the main stable oxidizing species formed in the radiolysis of water, and its long-term yield is found to be very sensitive to the system used in the measurements. Experiments with γ-irradiation combined with model calculations show that the primary yields of hydrogen peroxide are nearly independent of pH in the range of 2-12. Slightly higher primary yields are suggested at very low pH in particular when O(2) is present, while the yields seem to decrease at very high pH. Irradiations were performed with 5 MeV H ions, 5 MeV He ions, and 10 MeV C ions to evaluate the intratrack and homogeneous kinetic contributions to H(2)O(2) formation with different ions. Many of the trends in hydrogen peroxide yields with pH observed with γ-irradiations are observed with irradiation by the heavy ions. The lower yields of radicals in the homogeneous phase with the heavier ions tend to minimize the effects of radicals on the hydrogen peroxide yields at long times.

Ensemble brightening and enhanced quantum yield in size-purified silicon nanocrystals

DOE PAGES

Miller, Joseph B.; Van Sickle, Austin R.; Anthony, Rebecca J.; ...

2012-07-18

Here, we report on the quantum yield, photoluminescence (PL) lifetime and ensemble photoluminescent stability of highly monodisperse plasma-synthesized silicon nanocrystals (SiNCs) prepared though density-gradient ultracentrifugation in mixed organic solvents. Improved size uniformity leads to a reduction in PL line width and the emergence of entropic order in dry nanocrystal films. We find excellent agreement with the anticipated trends of quantum confinement in nanocrystalline silicon, with a solution quantum yield that is independent of nanocrystal size for the larger fractions but decreases dramatically with size for the smaller fractions. We also find a significant PL enhancement in films assembled from themore » fractions, and we use a combination of measurement, simulation and modeling to link this ‘brightening’ to a temporally enhanced quantum yield arising from SiNC interactions in ordered ensembles of monodisperse nanocrystals. Using an appropriate excitation scheme, we exploit this enhancement to achieve photostable emission.« less

Multi-tiered Approach to Development of Increased Throughput Assay Models to Assess Endocrine-Disrupting Activity of Chemicals

EPA Science Inventory

Screening for endocrine-disrupting chemicals (EDCs) requires sensitive, scalable assays. Current high-throughput screening (HTPS) approaches for estrogenic and androgenic activity yield rapid results, but many are not sensitive to physiological hormone concentrations, suggesting ...

Forest Growth and Yield Models Viewed From a Different Perspective

Treesearch

Jeffery C. Goelz

2002-01-01

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

Yield estimation of corn based on multitemporal LANDSAT-TM data as input for an agrometeorological model

NASA Astrophysics Data System (ADS)

Bach, Heike

1998-07-01

In order to test remote sensing data with advanced yield formation models for accuracy and timeliness of yield estimation of corn, a project was conducted for the State Ministry for Rural Environment, Food, and Forestry of Baden-Württemberg (Germany). This project was carried out during the course of the `Special Yield Estimation', a regular procedure conducted for the European Union, to more accurately estimate agricultural yield. The methodology employed uses field-based plant parameter estimation from atmospherically corrected multitemporal/multispectral LANDSAT-TM data. An agrometeorological plant-production-model is used for yield prediction. Based solely on four LANDSAT-derived estimates (between May and August) and daily meteorological data, the grain yield of corn fields was determined for 1995. The modelled yields were compared with results gathered independently within the Special Yield Estimation for 23 test fields in the upper Rhine valley. The agreement between LANDSAT-based estimates (six weeks before harvest) and Special Yield Estimation (at harvest) shows a relative error of 2.3%. The comparison of the results for single fields shows that six weeks before harvest, the grain yield of corn was estimated with a mean relative accuracy of 13% using satellite information. The presented methodology can be transferred to other crops and geographical regions. For future applications hyperspectral sensors show great potential to further enhance the results for yield prediction with remote sensing.

Variation in canopy duration in the perennial biofuel crop Miscanthus reveals complex associations with yield.

PubMed

Robson, Paul R H; Farrar, Kerrie; Gay, Alan P; Jensen, Elaine F; Clifton-Brown, John C; Donnison, Iain S

2013-05-01

Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed.