Influence of management and environment on Australian wheat: information for sustainable intensification and closing yield gaps

NASA Astrophysics Data System (ADS)

Bryan, B. A.; King, D.; Zhao, G.

2014-04-01

In the future, agriculture will need to produce more, from less land, more sustainably. But currently, in many places, actual crop yields are below those attainable. We quantified the ability for agricultural management to increase wheat yields across 179 Mha of potentially arable land in Australia. Using the Agricultural Production Systems Simulator (APSIM), we simulated the impact on wheat yield of 225 fertilization and residue management scenarios at a high spatial, temporal, and agronomic resolution from 1900 to 2010. The influence of management and environmental variables on wheat yield was then assessed using Spearman’s non-parametric correlation test with bootstrapping. While residue management showed little correlation, fertilization strongly increased wheat yield up to around 100 kg N ha-1 yr-1. However, this effect was highly dependent on the key environment variables of rainfall, temperature, and soil water holding capacity. The influence of fertilization on yield was stronger in cooler, wetter climates, and in soils with greater water holding capacity. We conclude that the effectiveness of management intensification to increase wheat yield is highly dependent upon local climate and soil conditions. We provide context-specific information on the yield benefits of fertilization to support adaptive agronomic decision-making and contribute to the closure of yield gaps. We also suggest that future assessments consider the economic and environmental sustainability of management intensification for closing yield gaps.

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.

Connecting Groundwater, Crop Price, and Crop Production Variability in India

NASA Astrophysics Data System (ADS)

Pollack, A.; Lobell, D. B.; Jain, M.

2015-12-01

Farmers in India rely on groundwater resources for irrigation and production of staple crops that provide over half of the calories consumed domestically each year. While this has been a productive strategy in increasing agricultural production and maintaining high yields, groundwater resources are depleting at a quicker rate than natural resources can replace. This issue gains relevance as climate variability concurrently adds to yearly fluctuations in farmer demand for irrigation each year, which can create high risk for farmers that depend on consistent yields, but do not have access to dwindling water resources. This study investigates variability in groundwater levels from 2005 to 2013 in relation to crop prices and production by analyzing district-level datasets made available through India's government. Through this analysis, we show the impact of groundwater variability on price variability, crop yield, and production during these years. By examining this nine-year timescale, we extend our analysis to forthcoming years to demonstrate the increasing importance of groundwater resources in irrigation, and suggest strategies to reduce the impact of groundwater shortages on crop production and prices.

Variability of arginine content and yield components in Valencia peanut germplasm.

PubMed

Aninbon, Chorkaew; Jogloy, Sanun; Vorasoot, Nimitr; Nuchadomrong, Suporn; Holbrook, C Corley; Kvien, Craig; Puppala, Naveen; Patanothai, Aran

2017-06-01

Peanut seeds are rich in arginine, an amino acid that has several positive effects on human health. Establishing the genetic variability of arginine content in peanut will be useful for breeding programs that have high arginine as one of their goals. The objective of this study was to evaluate the variation of arginine content, pods/plant, seeds/pod, seed weight, and yield in Valencia peanut germplasm. One hundred and thirty peanut genotypes were grown under field condition for two years. A randomized complete block design with three replications was used for this study. Arginine content was analyzed in peanut seeds at harvest using spectrophotometry. Yield and yield components were recorded for each genotype. Significant differences in arginine content and yield components were found in the tested Valencia peanut germplasm. Arginine content ranged from 8.68-23.35 μg/g seed. Kremena was the best overall genotype of high arginine content, number of pods/plant, 100 seed weight and pod yield.

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.

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.

Logging effects on streamflow: water yields and summer flows at Caspar Creek in northwestern California

Treesearch

Elizabeth T. Keppeler; Robert R. Ziemer

1990-01-01

Streamflow data for a 21-year period were analyzed to determine the effects of selective tractor harvesting of second-growth Douglas fir and redwood forest on the volume, timing, and duration of low flows and annual water yield in northwestern California. The flow response to logging was highly variable. Some of this variability was correlated with antecedent...

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

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

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

Leng, Guoyong

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

Analysis of Biomass Feedstock Availability and Variability for the Peace River Region of Alberta, Canada

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

Stephen, Jamie; Sokhansanj, Shahabaddine; Bi, X.T.

2009-11-01

Biorefineries or other biomass-dependent facilities require a predictable, dependable feedstock supplied over many years to justify capital investments. Determining inter-year variability in biomass availability is essential to quantifying the feedstock supply risk. Using a geographic information system (GIS) and historic crop yield data, average production was estimated for 10 sites in the Peace River region of Alberta, Canada. Four high-yielding potential sites were investigated for variability over a 20 year time-frame (1980 2000). The range of availability was large, from double the average in maximum years to nothing in minimum years. Biomass availability is a function of grain yield, themore » biomass to grain ratio, the cropping frequency, and residue retention rate to ensure future crop productivity. Storage strategies must be implemented and alternate feedstock sources identified to supply biomass processing facilities in low-yield years.« less

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.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin

PubMed Central

Villamor, Grace B.; Nyarko, Benjamin Kofi; Wala, Kperkouma; Akpagana, Koffi

2018-01-01

Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield. PMID:29346406

Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin.

PubMed

Aleza, Koutchoukalo; Villamor, Grace B; Nyarko, Benjamin Kofi; Wala, Kperkouma; Akpagana, Koffi

2018-01-01

Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield.

Efficient SRAM yield optimization with mixture surrogate modeling

NASA Astrophysics Data System (ADS)

Zhongjian, Jiang; Zuochang, Ye; Yan, Wang

2016-12-01

Largely repeated cells such as SRAM cells usually require extremely low failure-rate to ensure a moderate chi yield. Though fast Monte Carlo methods such as importance sampling and its variants can be used for yield estimation, they are still very expensive if one needs to perform optimization based on such estimations. Typically the process of yield calculation requires a lot of SPICE simulation. The circuit SPICE simulation analysis accounted for the largest proportion of time in the process yield calculation. In the paper, a new method is proposed to address this issue. The key idea is to establish an efficient mixture surrogate model. The surrogate model is based on the design variables and process variables. This model construction method is based on the SPICE simulation to get a certain amount of sample points, these points are trained for mixture surrogate model by the lasso algorithm. Experimental results show that the proposed model is able to calculate accurate yield successfully and it brings significant speed ups to the calculation of failure rate. Based on the model, we made a further accelerated algorithm to further enhance the speed of the yield calculation. It is suitable for high-dimensional process variables and multi-performance applications.

Post-heading heat stress and yield impact in winter wheat of China.

PubMed

Liu, Bing; Liu, Leilei; Tian, Liying; Cao, Weixing; Zhu, Yan; Asseng, Senthold

2014-02-01

Wheat is sensitive to high temperatures, but the spatial and temporal variability of high temperature and its impact on yield are often not known. An analysis of historical climate and yield data was undertaken to characterize the spatial and temporal variability of heat stress between heading and maturity and its impact on wheat grain yield in China. Several heat stress indices were developed to quantify heat intensity, frequency, and duration between heading and maturity based on measured maximum temperature records of the last 50 years from 166 stations in the main wheat-growing region of China. Surprisingly, heat stress between heading and maturity was more severe in the generally cooler northern wheat-growing regions than the generally warmer southern regions of China, because of the delayed time of heading with low temperatures during the earlier growing season and the exposure of the post-heading phase into the warmer part of the year. Heat stress between heading and maturity has increased in the last decades in most of the main winter wheat production areas of China, but the rate was higher in the south than in the north. The correlation between measured grain yields and post-heading heat stress and average temperature were statistically significant in the entire wheat-producing region, and explained about 29% of the observed spatial and temporal yield variability. A heat stress index considering the duration and intensity of heat between heading and maturity was required to describe the correlation of heat stress and yield variability. Because heat stress is a major cause of yield loss and the number of heat events is projected to increase in the future, quantifying the future impact of heat stress on wheat production and developing appropriate adaptation and mitigation strategies are critical for developing food security policies in China and elsewhere. © 2013 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

High precision and high yield fabrication of dense nanoparticle arrays onto DNA origami at statistically independent binding sites

NASA Astrophysics Data System (ADS)

Takabayashi, Sadao; Klein, William P.; Onodera, Craig; Rapp, Blake; Flores-Estrada, Juan; Lindau, Elias; Snowball, Lejmarc; Sam, Joseph T.; Padilla, Jennifer E.; Lee, Jeunghoon; Knowlton, William B.; Graugnard, Elton; Yurke, Bernard; Kuang, Wan; Hughes, William L.

2014-10-01

High precision, high yield, and high density self-assembly of nanoparticles into arrays is essential for nanophotonics. Spatial deviations as small as a few nanometers can alter the properties of near-field coupled optical nanostructures. Several studies have reported assemblies of few nanoparticle structures with controlled spacing using DNA nanostructures with variable yield. Here, we report multi-tether design strategies and attachment yields for homo- and hetero-nanoparticle arrays templated by DNA origami nanotubes. Nanoparticle attachment yield via DNA hybridization is comparable with streptavidin-biotin binding. Independent of the number of binding sites, >97% site-occupation was achieved with four tethers and 99.2% site-occupation is theoretically possible with five tethers. The interparticle distance was within 2 nm of all design specifications and the nanoparticle spatial deviations decreased with interparticle spacing. Modified geometric, binomial, and trinomial distributions indicate that site-bridging, steric hindrance, and electrostatic repulsion were not dominant barriers to self-assembly and both tethers and binding sites were statistically independent at high particle densities.High precision, high yield, and high density self-assembly of nanoparticles into arrays is essential for nanophotonics. Spatial deviations as small as a few nanometers can alter the properties of near-field coupled optical nanostructures. Several studies have reported assemblies of few nanoparticle structures with controlled spacing using DNA nanostructures with variable yield. Here, we report multi-tether design strategies and attachment yields for homo- and hetero-nanoparticle arrays templated by DNA origami nanotubes. Nanoparticle attachment yield via DNA hybridization is comparable with streptavidin-biotin binding. Independent of the number of binding sites, >97% site-occupation was achieved with four tethers and 99.2% site-occupation is theoretically possible with five tethers. The interparticle distance was within 2 nm of all design specifications and the nanoparticle spatial deviations decreased with interparticle spacing. Modified geometric, binomial, and trinomial distributions indicate that site-bridging, steric hindrance, and electrostatic repulsion were not dominant barriers to self-assembly and both tethers and binding sites were statistically independent at high particle densities. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03069a

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Effects of lakes and reservoirs on annual river nitrogen, phosphorus, and sediment export in agricultural and forested landscapes

USGS Publications Warehouse

Powers, Stephen M.; Robertson, Dale M.; Stanley, Emily H.

2014-01-01

Recently, effects of lakes and reservoirs on river nutrient export have been incorporated into landscape biogeochemical models. Because annual export varies with precipitation, there is a need to examine the biogeochemical role of lakes and reservoirs over time frames that incorporate interannual variability in precipitation. We examined long-term (~20 years) time series of river export (annual mass yield, Y, and flow-weighted mean annual concentration, C) for total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) from 54 catchments in Wisconsin, USA. Catchments were classified as small agricultural, large agricultural, and forested by use of a cluster analysis, and these varied in lentic coverage (percentage of catchment lake or reservoir water that was connected to river network). Mean annual export and interannual variability (CV) of export (for both Y and C) were higher in agricultural catchments relative to forested catchments for TP, TN, and TSS. In both agricultural and forested settings, mean and maximum annual TN yields were lower in the presence of lakes and reservoirs, suggesting lentic denitrification or N burial. There was also evidence of long-term lentic TP and TSS retention, especially when viewed in terms of maximum annual yield, suggesting sedimentation during high loading years. Lentic catchments had lower interannual variability in export. For TP and TSS, interannual variability in mass yield was often >50% higher than interannual variability in water yield, whereas TN variability more closely followed water (discharge) variability. Our results indicate that long-term mass export through rivers depends on interacting terrestrial, aquatic, and meteorological factors in which the presence of lakes and reservoirs can reduce the magnitude of export, stabilize interannual variability in export, as well as introduce export time lags.

Study on Analysis of Variance on the indigenous wild and cultivated rice species of Manipur Valley

NASA Astrophysics Data System (ADS)

Medhabati, K.; Rohinikumar, M.; Rajiv Das, K.; Henary, Ch.; Dikash, Th.

2012-10-01

The analysis of variance revealed considerable variation among the cultivars and the wild species for yield and other quantitative characters in both the years of investigation. The highly significant differences among the cultivars in year wise and pooled analysis of variance for all the 12 characters reveal that there are enough genetic variabilities for all the characters studied. The existence of genetic variability is of paramount importance for starting a judicious plant breeding programme. Since introduced high yielding rice cultivars usually do not perform well. Improvement of indigenous cultivars is a clear choice for increase of rice production. The genetic variability of 37 rice germplasms in 12 agronomic characters estimated in the present study can be used in breeding programme

A Regional Modeling Framework of Phosphorus Sources and Transport in Streams of the Southeastern United States

USGS Publications Warehouse

Garcia, A.M.; Hoos, A.B.; Terziotti, S.

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. ?? 2011 American Water Resources Association. This article is a US Government work and is in the public domain in the USA.

Water and Temperature Stresses Impact Canola (Brassica napus L.) Fatty Acid, Protein, and Yield over Nitrogen and Sulfur.

PubMed

Hammac, W Ashley; Maaz, Tai M; Koenig, Richard T; Burke, Ian C; Pan, William L

2017-12-06

Interactive effects of weather and soil nutrient status often control crop productivity. An experiment was conducted to determine effects of nitrogen (N) and sulfur (S) fertilizer rate, soil water, and atmospheric temperature on canola (Brassica napus L.) fatty acid (FA), total oil, protein, and grain yield. Nitrogen and sulfur were assessed in a 4-yr study with two locations, five N rates (0, 45, 90, 135, and 180 kg ha -1 ), and two S rates (0 and 17 kg ha -1 ). Water and temperature were assessed using variability across 12 site-years of dryland canola production. Effects of N and S were inconsistent. Unsaturated FA, oleic acid, grain oil, protein, and theoretical maximum grain yield were highly related to water and temperature variability across the site-years. A nonlinear model identified water and temperature conditions that enabled production of maximum unsaturated FA content, oleic acid content, total oil, protein, and theoretical maximum grain yield. Water and temperature variability played a larger role than soil nutrient status on canola grain constituents and yield.

Small-scale spatial variation in population dynamics and fishermen response in a coastal marine fishery.

PubMed

Wilson, Jono R; Kay, Matthew C; Colgate, John; Qi, Roy; Lenihan, Hunter S

2012-01-01

A major challenge for small-scale fisheries management is high spatial variability in the demography and life history characteristics of target species. Implementation of local management actions that can reduce overfishing and maximize yields requires quantifying ecological heterogeneity at small spatial scales and is therefore limited by available resources and data. Collaborative fisheries research (CFR) is an effective means to collect essential fishery information at local scales, and to develop the social, technical, and logistical framework for fisheries management innovation. We used a CFR approach with fishing partners to collect and analyze geographically precise demographic information for grass rockfish (Sebastes rastrelliger), a sedentary, nearshore species harvested in the live fish fishery on the West Coast of the USA. Data were used to estimate geographically distinct growth rates, ages, mortality, and length frequency distributions in two environmental subregions of the Santa Barbara Channel, CA, USA. Results indicated the existence of two subpopulations; one located in the relatively cold, high productivity western Channel, and another in the relatively warm, low productivity eastern Channel. We parameterized yield per recruit models, the results of which suggested nearly twice as much yield per recruit in the high productivity subregion relative to the low productivity subregion. The spatial distribution of fishing in the two environmental subregions demonstrated a similar pattern to the yield per recruit outputs with greater landings, effort, and catch per unit effort in the high productivity subregion relative to the low productivity subregion. Understanding how spatial variability in stock dynamics translates to variability in fishery yield and distribution of effort is important to developing management plans that maximize fishing opportunities and conservation benefits at local scales.

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

NASA Astrophysics Data System (ADS)

Cai, Y.

2017-12-01

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

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.

The Safe Yield and Climatic Variability: Implications for Groundwater Management.

PubMed

Loáiciga, Hugo A

2017-05-01

Methods for calculating the safe yield are evaluated in this paper using a high-quality and long historical data set of groundwater recharge, discharge, extraction, and precipitation in a karst aquifer. Consideration is given to the role that climatic variability has on the determination of a climatically representative period with which to evaluate the safe yield. The methods employed to estimate the safe yield are consistent with its definition as a long-term average extraction rate that avoids adverse impacts on groundwater. The safe yield is a useful baseline for groundwater planning; yet, it is herein shown that it is not an operational rule that works well under all climatic conditions. This paper shows that due to the nature of dynamic groundwater processes it may be most appropriate to use an adaptive groundwater management strategy that links groundwater extraction rates to groundwater discharge rates, thus achieving a safe yield that represents an estimated long-term sustainable yield. An example of the calculation of the safe yield of the Edwards Aquifer (Texas) demonstrates that it is about one-half of the average annual recharge. © 2016, National Ground Water Association.

Vine vigor components and its variability - relationship to wine composition

NASA Astrophysics Data System (ADS)

Lafontaine, Magali; Tittmann, Susanne; Stoll, Manfred

2015-04-01

It was pointed out that a high spatial variability for canopy size and yield would exist within a vineyard but a high temporal stability over the years was observed. Furthermore, a greater variability in grape phenolics than in sugars and pH was detected within a vineyard. But the link between remote sensing indices and quality parameters of grapes is still unclear. Indeed, though in red grape varieties anthocyanins content was spatially negatively correlated to vigor parameters, it seemed that yield, Normalized Difference Vegetation Index (NDVI) and Plant Cell Density (PCD) indices were poorly correlated. Moreover, the link to quality parameters of wines remains uncertain. It was shown that more vigorous vines would lead to wines with less tannins while anthocyanins in wines would be highest when the vines were balanced but the question is if vine size or architecture, yield or nitrogen assimilation would play major contribution to those differences. The general scope of our project was to provide further knowledge on the relationship between vigor parameters and wine composition and relate these to the information gained by remote sensing. Variability in a 0.15 ha vineyard of Pinot noir planted in 2003 and grafted on SO4 rootstock at Geisenheim (Germany) was followed. Vine vigor was assessed manually for each of the 400 vines (cane number, pruning weight, trunk diameter) together with yield parameters (number of bunches per vine, crop yield). Leaf composition was assessed with a hand-held optical sensor (Multiplex3® [Mx3] (Force-A, Orsay, France) based on chlorophyll fluorescence screening providing information on leaf chlorophyll (SFR_G) and nitrogen (NBI_G) content. A micro-scale winemaking of single vines with a 3 factorial design on yield (L low, M middle, H high), SFRG (L, M, H) and canopy size (pruning weight, trunk diameter) (L, M, H) was performed for 2013 and 2014 to completely reflect variability. Wine tannin concentration represented the highest variability with a 11 fold concentration range (50-550 mg CE L-1) while variability of anthocyanins was lower with a 3 fold concentration range (90-250 mg M3OG L-1). The results showed that differences in leaf chlorophyll (SFR_G) would represent the most important factor influencing wine phenolic composition. Measurements of soil resistivity based on ARP technique (Geocarta, Paris, France), leaf composition with a mounted Multiplex providing information on porosity (NFI), biomass (BIOMASS) and chlorophyll (BISFR) together with NDVI assessed by geo-X8000 (geo-konzept-Gesellschaft für Umweltplanungssysteme mbH, Adelschlag, Germany) were performed. Grapes and berry composition was also assessed with Mx3 providing information on anthocyanins (ANTH, FERARI) and sugar (SFR_R) variability. In a second step, vines similar in size (trunk diameter and cane number) and similar yield (number of bunches per vines) were divided in 3 groups differing in leaf SFR_G. A larger scale winemaking (150kg) showed that with increasing SFR_G, Pinot noir wine typicity decreased together with anthocyanin concentration while tannin concentration increased. A better understanding of vineyard variability for targeted management or harvest would allow better understanding to produce and select fruit to a favored wine style.

Spatial variability of sugarcane yields in relation to soil salinity in Louisiana

USDA-ARS?s Scientific Manuscript database

High soil salinity levels have been documented to negatively impact sugarcane yields. Tests were conducted in commercial sugarcane fields in South Louisiana in 2009-2010 to determine if elevated soil salinity levels resulting from salt water intrusion from several recent hurricanes was having a neg...

Assessing the seasonal variability of ephemeral gully erosion using high-frequency monitoring: case study in a fully cultivated catchment (The Pommeroye, Northern France)

NASA Astrophysics Data System (ADS)

Patault, E.; Alary, C.; Franke, C.; Gauthier, A.; Abriak, N. E.

2017-12-01

Gully erosion results in on-site and off-site problems including the loss of cultivated soils, the silting of riverbeds and dams as well as infrastructure and property damage by muddy floods. Regions of intensive agricultural production situated on the European loess belt are particularly affected. Recently a growing interest has focused on ephemeral gullies since there have been recognized as a major contributor to the sediment yield in small agricultural catchment in this area. The aims of this case study are (i) to quantify the sediment yield transported by ephemeral gullies, (ii) to identify parameters that control the function of the hydro-sedimentary response and (iii) to evaluate the influence of seasonal variability on the ephemeral gully erosion. For this study a high-frequency monitoring station was implemented. For each flood event, 8 variables related to hydro-sedimentary and rainfall dynamics are calculated and the relationships between these variables are analyzed using the Pearson correlation matrix and Principal Component Analysis. During the first year of monitoring (03/2016-03/2017), 22 flood events were recorded of which 75% occurred in spring and winter. The specific sediment yield was evaluated to 30 t km-2 yr-1 which is conventional for the study region but the results show a highly variable seasonal distribution; 90% of the sedimentary transfer occurred in winter and autumn. The main reasons were a high cumulative rainfall and a long duration for the events. The maximum suspended sediment concentration at the catchment outlet was observed in spring, likely due to maximum rainfall intensities in that season. Also, a huge variability between the events is observed; e.g. one exceptional rain storm in 11/2016 represents 45% of the total sediment yield of the study period. For the monitored 22 events, 2 different types of hysteresis behavior were observed: (i) clockwise and (ii) complex. In winter, only clockwise hysteresis was observed. These results suggest that other factors have to be considered to better explain the variability of gully erosion, such as the soil surface characteristics (crop cover, crusting stage, roughness). A monitoring of these parameters on experimental plots is in progress.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Assessment on induced genetic variability and divergence in the mutagenized lentil populations of microsperma and macrosperma cultivars developed using physical and chemical mutagenesis

PubMed Central

2017-01-01

Induced mutagenesis was employed to create genetic variation in the lentil cultivars for yield improvement. The assessments were made on genetic variability, character association, and genetic divergence among the twelve mutagenized populations and one parent population of each of the two lentil cultivars, developed by single and combination treatments with gamma rays and hydrazine hydrates. Analysis of variance revealed significant inter-population differences for the observed quantitative phenotypic traits. The sample mean of six treatment populations in each of the cultivar exhibited highly superior quantitative phenotypic traits compared to their parent cultivars. The higher values of heritability and genetic advance with a high genotypic coefficient of variation for most of the yield attributing traits confirmed the possibilities of lentil yield improvement through phenotypic selection. The number of pods and seeds per plant appeared to be priority traits in selection for higher yield due to their strong direct association with yield. The cluster analysis divided the total populations into three divergent groups in each lentil cultivar with parent genotypes in an independent group showing the high efficacy of the mutagens. Considering the highest contribution of yield trait to the genetic divergence among the clustered population, it was confirmed that the mutagenic treatments created a wide heritable variation for the trait in the mutant populations. The selection of high yielding mutants from the mutant populations of DPL 62 (100 Gy) and Pant L 406 (100Gy + 0.1% HZ) in the subsequent generation is expected to give elite lentil cultivars. Also, hybridization between members of the divergent group would produce diverse segregants for crop improvement. Apart from this, the induced mutations at loci controlling economically important traits in the selected high yielding mutants have successfully contributed in diversifying the accessible lentil genetic base and will definitely be of immense value to the future lentil breeding programmes in India. PMID:28922405

Agricultural Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Tam, A.; Jain, M.

2016-12-01

This research includes two projects pertaining to agricultural systems' adaption to climate change. The first research project focuses on the wheat yielding regions of India. Wheat is a major staple crop and many rural households and smallholder farmers rely on crop yields for survival. We examine the impacts of weather variability and groundwater depletion on agricultural systems, using geospatial analysis and satellite-based analysis and household-based and census data sets. We use these methods to estimate the crop yields and identify what factors are associated with low versus high yielding regions. This can help identify strategies that should be further promoted to increase crop yields. The second research project is a literature review. We conduct a meta-analysis and synthetic review on literature about agricultural adaptation to climate change. We sort through numerous articles to identify and examine articles that associate socio-economic, biophysical, and perceptional factors to farmers' adaption to climate change. Our preliminary results show that researchers tend to associate few factors to a farmers' vulnerability and adaptive capacity, and most of the research conducted is concentrated in North America, whereas tropical regions that are highly vulnerable to weather variability are underrepresented by literature. There are no conclusive results in both research projects as of so far.

Assessment of impact of climate change and adaptation strategies on maize production in Uganda

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.

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.

Predawn respiration rates during flowering are highly predictive of yield response in Gossypium hirsutum when yield variability is water-induced

USDA-ARS?s Scientific Manuscript database

Respiratory carbon evolution by leaves under abiotic stress is implicated as a major limitation to crop productivity; however, respiration rates of fully expanded leaves are positively associated with plant growth rates. Given the substantial sensitivity of plant growth to drought, it was hypothesiz...

Calibrating SALT: a sampling scheme to improve estimates of suspended sediment yield

Treesearch

Robert B. Thomas

1986-01-01

Abstract - SALT (Selection At List Time) is a variable probability sampling scheme that provides unbiased estimates of suspended sediment yield and its variance. SALT performs better than standard schemes which are estimate variance. Sampling probabilities are based on a sediment rating function which promotes greater sampling intensity during periods of high...

Temperature, Sowing and Harvest Dates, and Yield of Maize in the Southwestern US

NASA Astrophysics Data System (ADS)

Kafatos, M.; Stack, D.; Myoung, B.; Kim, S. H.; Kim, J.

2014-12-01

Since sowing date of maize is sensitive to climate variability and changes, it is of a practical importance to examine how sowing dates affect maize yields in various temperature regimes in the southwestern US. A 21-year (1991-2011) simulation of maize yield using Agricultural Production Systems sIMulator (APSIM) with observed meteorological forcing, shows that earlier sowing dates are favorable for higher yields primarily by increasing the length of growing season in cold mountaineous regions. In these regions, warmer conditions in the sowing period tend to advance the sowing date and then enhance yield. Over low-elevation warm regions, yields are less correlated with sowing dates and the length of growing season, perhaps because growing season temperatures are high enough for fast growth. Instead, in the warm regions, maize yields are sensitive to temperature variations during the late growing season due to adverse effects of extreme high temperature events on maize development.

The effects of temperature and frequencies in ultrasound assisted extraction of phycocyanin from microalgae Spirulina sp

NASA Astrophysics Data System (ADS)

Hadiyanto, Suttrisnorhadi, Sutanto, Heri; Suzery, Meiny; Soetrisnanto, Danny; Azizah, Nur

2015-12-01

Microalgae Spirulina sp has been identified as source of protein and other high added value compounds. One of the compounds is phycocyanin as also known for antioxidant use. The extraction of this compound by using conventional method (soxhlet extraction) resulted low yield and longer processing time. This research was aimed to extract phycocyanin by using an extraction assisted by ultrasound irradiation. The extraction was performed by using variable of ultrasound frequency and extraction temperature and ethanol was used as a solvent. The result showed that yield of phycocyanin extracted by conventional method was 11.13% while the ultrasound irradiation could increase the yield up to 15.61% at constant frequency of 42 kHz, while the optimum temperature was obtained at 45°C. The analysis of variable interactions showed that both temperature and time has an interaction and temperature was the highest variable in increasing the yield. The conclusion of this research was the ultrasound could improve significantly the efficiency of extraction as well as activity of phycocyanin extracted from microalgae.

The effects of temperature and frequencies in ultrasound assisted extraction of phycocyanin from microalgae Spirulina sp

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

Hadiyanto,, E-mail: hadiyanto@live.undip.ac.id; Suttrisnorhadi,; Soetrisnanto, Danny

Microalgae Spirulina sp has been identified as source of protein and other high added value compounds. One of the compounds is phycocyanin as also known for antioxidant use. The extraction of this compound by using conventional method (soxhlet extraction) resulted low yield and longer processing time. This research was aimed to extract phycocyanin by using an extraction assisted by ultrasound irradiation. The extraction was performed by using variable of ultrasound frequency and extraction temperature and ethanol was used as a solvent. The result showed that yield of phycocyanin extracted by conventional method was 11.13% while the ultrasound irradiation could increasemore » the yield up to 15.61% at constant frequency of 42 kHz, while the optimum temperature was obtained at 45°C. The analysis of variable interactions showed that both temperature and time has an interaction and temperature was the highest variable in increasing the yield. The conclusion of this research was the ultrasound could improve significantly the efficiency of extraction as well as activity of phycocyanin extracted from microalgae.« less

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

NASA Astrophysics Data System (ADS)

Parkes, Ben; Defrance, Dimitri; Sultan, Benjamin; Ciais, Philippe; Wang, Xuhui

2018-02-01

The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes? An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986-2005) and a near-term future when global temperatures are 1.5 K above pre-industrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates. Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively. The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

Future Warming Increases Global Maize Yield Variability with Implications for Food Markets

NASA Astrophysics Data System (ADS)

Tigchelaar, M.; Battisti, D. S.; Naylor, R. L.; Ray, D. K.

2017-12-01

If current trends in population growth and dietary shifts continue, the world will need to produce about 70% more food by 2050, while earth's climate is rapidly changing. Rising temperatures in particular are projected to negatively impact agricultural production, as the world's staple crops perform poorly in extreme heat. Theoretical models suggest that as temperatures rise above plants' optimal temperature for performance, not only will mean yields decline rapidly, but the variability of yields will increase, even as interannual variations in climate remain unchanged. Here we use global datasets of maize production and climate variability combined with CMIP5 temperature projections to quantify how yield variability will change in major maize producing countries under 2°C and 4°C of global warming. Maize is the world's most produced crop, and is linked to other staple crops through substitution in consumption and production. We find that in warmer climates - absent any breeding gains in heat tolerance - the Coefficient of Variation (CV) of maize yields increases almost everywhere, to values much larger than present-day. This increase in CV is due both to an increase in the standard deviation of yields, and a decrease in mean yields. In locations where crop failures become the norm under high (4°C) warming (mostly in tropical, low-yield environments), the standard deviation of yields ultimately decreases. The probability that in any given year the most productive areas in the top three maize producing countries (United States, China, Brazil) have simultaneous production losses greater than 10% is virtually zero under present-day climate conditions, but increases to 12% under 2°C warming, and 89% under 4°C warming. This has major implications for global food markets and staple crop prices, affecting especially the 2.5 billion people that comprise the world's poor, who already spend the majority of their disposable income on food and are particularly vulnerable to agricultural price spikes.

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.

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.

Control of growth of juvenile leaves of Eucalyptus globulus: effects of leaf age.

PubMed

Metcalfe, J C; Davies, W J; Pereira, J S

1991-12-01

Biophysical variables influencing the expansion of plant cells (yield threshold, cell wall extensibility and turgor) were measured in individual Eucalyptus globulus leaves from the time of emergence until cessation of growth. Leaf water relations variables and growth rates were determined as relative humidity was changed on an hourly basis. Yield threshold and cell wall extensibility were estimated from plots of leaf growth rate versus turgor. Cell wall extensibility was also measured by the Instron technique, and yield threshold was determined experimentally both by stress relaxation in a psychrometer chamber and by incubation in a range of polyethylene glycol solutions. Once emerging leaves reached approximately 5 cm(2) in size, increases in leaf area were rapid throughout the expansive phase and varied little between light and dark periods. Both leaf growth rate and turgor were sensitive to changes in humidity, and in the longer term, both yield threshold and cell wall extensibility changed as the leaf aged. Rapidly expanding leaves had a very low yield threshold and high cell wall extensibility, whereas mature leaves had low cell wall extensibility. Yield threshold increased with leaf age.

Early lactation production, health, and welfare characteristics of cows selected for extended lactation.

PubMed

Lehmann, J O; Mogensen, L; Kristensen, T

2017-02-01

Some cows are able to achieve relatively high milk yields during extended lactations beyond 305 d in milk, and farmers may be able to use this potential by selecting the most suitable cows for an extended lactation. However, the decision to postpone insemination has to rely on information available in early lactation. The main objectives of this study were, therefore, to assess the association between the information available in early lactation and the relative milk production of cows on extended lactation, and to investigate if this information can be used to differentiate time of first insemination between cows. Data came from 4 Danish private herds practicing extended lactation in which some cows are selected to have a delayed time of planned first insemination. Average herd size varied from 93 to 157 cows, and milk yield varied from 7,842 to 12,315 kg of energy-corrected milk (ECM) per cow per year across herds. The analysis was based on 422 completed extended lactations (427 ± 87 d), and each lactation was assigned to 1 of 3 (low, medium, and high) milk performance groups (MPG) within parity group within herd based on a standardized lactation yield. For cows in the high MPG, peak ECM yield, and ECM yield at dry off were significantly greater, the relative reduction in milk yield between 60 and 305 d in milk was significantly smaller, and a smaller proportion had a body condition score (scale: 1-5) at dry off of 3.5 or greater compared with cows in low MPG. Previous lactation days in milk at peak ECM yield and ECM yield at dry off were higher, the relative reduction in milk yield between 60 and 305 d in milk was smaller, and the number of inseminations per conception was higher for multiparous cows in high MPG compared with low. Current lactation ECM yield at second and third milk recording were greater for cows in high MPG compared with low. A principal component analysis indicated that variables related to fertility, diseases, and milk yield explained most of the total variation between primiparous cows, whereas variables related to milk yield, fertility, and days in milk at peak yield were the most dominating for multiparous cows. Our study indicated that milk yields in previous lactation and at second and third milk recording correlate well with milk production potential, and therefore, may be promising indicators when selecting the most suitable cows for extended lactation. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Variable sensitivity of US maize yield to high temperatures across developmental stages

NASA Astrophysics Data System (ADS)

Butler, E. E.; Huybers, P. J.

2013-12-01

The sensitivity of maize to high temperatures has been widely demonstrated. Furthermore, field work has indicated that reproductive development stages are particularly sensitive to stress, but this relationship has not been quantified across a wide geographic region. Here, the relationship between maize yield and temperature variations is examined as a function of developmental stage. US state-level data from the National Agriculture Statistics Service provide dates for six growing stages: planting, silking, doughing, dented, mature, and harvested. Temperatures that correspond to each developmental stage are then inferred from a network of weather station observations interpolated to the county level, and a multiple linear regression technique is employed to estimate the sensitivity of county yield outcomes to variations in growing-degree days and an analogous measure of high temperatures referred to as killing-degree days. Uncertainties in the transition times between county-level growth stages are accounted for. Results indicate that the silking and dented stages are generally the most sensitive to killing degree days, with silking the most sensitive stage in the US South and dented the most sensitive in the US North. These variable patterns of sensitivity aid in interpreting which weather events are of greatest significance to maize yields and provide some insight into how shifts in planting time or changes in developmental timing would influence the risks associated with exposure to high temperatures.

Estimating historical groundwater levels based on relations with hydrologic and meteorological variables in the U.S. glacial aquifer system

NASA Astrophysics Data System (ADS)

Dudley, R. W.; Hodgkins, G. A.; Nielsen, M. G.; Qi, S. L.

2018-07-01

A number of previous studies have examined relations between groundwater levels and hydrologic and meteorological variables over parts of the glacial aquifer system, but systematic analyses across the entire U.S. glacial aquifer system are lacking. We tested correlations between monthly groundwater levels measured at 1043 wells in the U.S. glacial aquifer system considered to be minimally influenced by human disturbance and selected hydrologic and meteorological variables with the goal of extending historical groundwater records where there were strong correlations. Groundwater levels in the East region correlated most strongly with short-term (1 and 3 month) averages of hydrologic and meteorological variables, while those in the Central and West Central regions yielded stronger correlations with hydrologic and meteorological variables averaged over longer time intervals (6-12 months). Variables strongly correlated with high and low annual groundwater levels were identified as candidate records for use in statistical linear models as a means to fill in and extend historical high and low groundwater levels respectively. Overall, 37.4% of study wells meeting data criteria had successful models for high and (or) low groundwater levels; these wells shared characteristics of relatively higher local precipitation, higher local land-surface slope, lower amounts of clay within the surficial sediments, and higher base-flow index. Streamflow and base flow served as explanatory variables in about two thirds of both high- and low-groundwater-level models in all three regions, and generally yielded more and better models compared to precipitation and Palmer Drought Severity Index. The use of variables such as streamflow with substantially longer and more complete records than those of groundwater wells provide a means for placing contemporary groundwater levels in a longer historical context and can support site-specific analyses such as groundwater modeling.

Variability in arginine content and yield components in Valencia peanut germplasm

USDA-ARS?s Scientific Manuscript database

Peanut seeds are rich in arginine, an amino acid that has several positive effects on human health. Establishing the genetic variability of arginine content in peanut will be useful for breeding programs that have high arginine as one of their goals. The objective of this study was to evaluate the...

Defining process design space for a hydrophobic interaction chromatography (HIC) purification step: application of quality by design (QbD) principles.

PubMed

Jiang, Canping; Flansburg, Lisa; Ghose, Sanchayita; Jorjorian, Paul; Shukla, Abhinav A

2010-12-15

The concept of design space has been taking root under the quality by design paradigm as a foundation of in-process control strategies for biopharmaceutical manufacturing processes. This paper outlines the development of a design space for a hydrophobic interaction chromatography (HIC) process step. The design space included the impact of raw material lot-to-lot variability and variations in the feed stream from cell culture. A failure modes and effects analysis was employed as the basis for the process characterization exercise. During mapping of the process design space, the multi-dimensional combination of operational variables were studied to quantify the impact on process performance in terms of yield and product quality. Variability in resin hydrophobicity was found to have a significant influence on step yield and high-molecular weight aggregate clearance through the HIC step. A robust operating window was identified for this process step that enabled a higher step yield while ensuring acceptable product quality. © 2010 Wiley Periodicals, Inc.

28nm node process optimization: a lithography centric view

NASA Astrophysics Data System (ADS)

Seltmann, Rolf

2014-10-01

Many experts claim that the 28nm technology node will be the most cost effective technology node forever. This results from primarily from the cost of manufacturing due to the fact that 28nm is the last true Single Patterning (SP) node. It is also affected by the dramatic increase of design costs and the limited shrink factor of the next following nodes. Thus, it is assumed that this technology still will be alive still for many years. To be cost competitive, high yields are mandatory. Meanwhile, leading edge foundries have optimized the yield of the 28nm node to such a level that that it is nearly exclusively defined by random defectivity. However, it was a long way to go to come to that level. In my talk I will concentrate on the contribution of lithography to this yield learning curve. I will choose a critical metal patterning application. I will show what was needed to optimize the process window to a level beyond the usual OPC model work that was common on previous nodes. Reducing the process (in particular focus) variability is a complementary need. It will be shown which improvements were needed in tooling, process control and design-mask-wafer interaction to remove all systematic yield detractors. Over the last couple of years new scanner platforms were introduced that were targeted for both better productivity and better parametric performance. But this was not a clear run-path. It needed some extra affords of the tool suppliers together with the Fab to bring the tool variability down to the necessary level. Another important topic to reduce variability is the interaction of wafer none-planarity and lithography optimization. Having an accurate knowledge of within die topography is essential for optimum patterning. By completing both the variability reduction work and the process window enhancement work we were able to transfer the original marginal process budget to a robust positive budget and thus ensuring high yield and low costs.

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.

Temporal changes in climatic variables and their impact on crop yields in southwestern China

NASA Astrophysics Data System (ADS)

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P < 0.05). Increased sunshine hours were observed during the oilseed rape growth period ( P < 0.05). Rainy days decreased slightly in annual and oilseed rape growth time series ( P < 0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall ( P < 0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity ( P < 0.01). Tobacco yield increased with mean temperature ( P < 0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Temporal changes in climatic variables and their impact on crop yields in southwestern China.

PubMed

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P<0.05). Increased sunshine hours were observed during the oilseed rape growth period (P<0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P<0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P<0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P<0.01). Tobacco yield increased with mean temperature (P<0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Selection Index in the Study of Adaptability and Stability in Maize

PubMed Central

Lunezzo de Oliveira, Rogério; Garcia Von Pinho, Renzo; Furtado Ferreira, Daniel; Costa Melo, Wagner Mateus

2014-01-01

This paper proposes an alternative method for evaluating the stability and adaptability of maize hybrids using a genotype-ideotype distance index (GIDI) for selection. Data from seven variables were used, obtained through evaluation of 25 maize hybrids at six sites in southern Brazil. The GIDI was estimated by means of the generalized Mahalanobis distance for each plot of the test. We then proceeded to GGE biplot analysis in order to compare the predictive accuracy of the GGE models and the grouping of environments and to select the best five hybrids. The G × E interaction was significant for both variables assessed. The GGE model with two principal components obtained a predictive accuracy (PRECORR) of 0.8913 for the GIDI and 0.8709 for yield (t ha−1). Two groups of environments were obtained upon analyzing the GIDI, whereas all the environments remained in the same group upon analyzing yield. Coincidence occurred in only two hybrids considering evaluation of the two features. The GIDI assessment provided for selection of hybrids that combine adaptability and stability in most of the variables assessed, making its use more highly recommended than analyzing each variable separately. Not all the higher-yielding hybrids were the best in the other variables assessed. PMID:24696641

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

A Fast Track approach to deal with the temporal dimension of crop water footprint

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2017-07-01

Population growth, socio-economic development and climate changes are placing increasing pressure on water resources. Crop water footprint is a key indicator in the quantification of such pressure. It is determined by crop evapotranspiration and crop yield, which can be highly variable in space and time. While the spatial variability of crop water footprint has been the objective of several investigations, the temporal variability remains poorly studied. In particular, some studies approached this issue by associating the time variability of crop water footprint only to yield changes, while considering evapotranspiration patterns as marginal. Validation of this Fast Track approach has yet to be provided. In this Letter we demonstrate its feasibility through a comprehensive validation, an assessment of its uncertainty, and an example of application. Our results show that the water footprint changes are mainly driven by yield trends, while evapotranspiration plays a minor role. The error due to considering constant evapotranspiration is three times smaller than the uncertainty of the model used to compute the crop water footprint. These results confirm the suitability of the Fast Track approach and enable a simple, yet appropriate, evaluation of time-varying crop water footprint.

Optimizing cropland cover for stable food production in Sub-Saharan Africa using simulated yield and Modern Portfolio Theory

NASA Astrophysics Data System (ADS)

Bodin, P.; Olin, S.; Pugh, T. A. M.; Arneth, A.

2014-12-01

Food security can be defined as stable access to food of good nutritional quality. In Sub Saharan Africa access to food is strongly linked to local food production and the capacity to generate enough calories to sustain the local population. Therefore it is important in these regions to generate not only sufficiently high yields but also to reduce interannual variability in food production. Traditionally, climate impact simulation studies have focused on factors that underlie maximum productivity ignoring the variability in yield. By using Modern Portfolio Theory, a method stemming from economics, we here calculate optimum current and future crop selection that maintain current yield while minimizing variance, vs. maintaining variance while maximizing yield. Based on simulated yield using the LPJ-GUESS dynamic vegetation model, the results show that current cropland distribution for many crops is close to these optimum distributions. Even so, the optimizations displayed substantial potential to either increase food production and/or to decrease its variance regionally. Our approach can also be seen as a method to create future scenarios for the sown areas of crops in regions where local food production is important for food security.

Assessment of different gridded weather data for soybean yield simulations in Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Bender, F. D.; Sentelhas, P. C.

2018-01-01

A high-density, well-distributed, and consistent historical weather data series is of major importance for agricultural planning and climatic risk evaluation. A possible option for regions where weather station network is irregular is the use of gridded weather data (GWD), which can be downloaded online from different sources. Based on that, the aim of this study was to assess the suitability of two GWD, AgMERRA and XAVIER, by comparing them with measured weather data (MWD) for estimating soybean yield in Brazil. The GWD and MWD were obtained for 24 locations across Brazil, considering the period between 1980 and 2010. These data were used to estimate soybean yield with DSSAT-CROPGRO-Soybean model. The comparison of MWD with GWD resulted in a good agreement between climate variables, except for solar radiation. The crop simulations with GWD and MWD resulted in a good agreement for vegetative and reproductive phases. Soybean potential yield (Yp) simulated with AgMERRA and XAVIER had a high correlation (r > 0.88) when compared to the estimates with MWD, with the RMSE of about 400 kg ha-1. For attainable yield (Ya), estimates with XAVIER resulted in a RMSE of 700 kg ha-1 against 864 kg ha-1 from AgMERRA, both compared to the simulations using MWD. Even with these differences in Ya simulations, both GWD can be considered suitable for simulating soybean growth, development, and yield in Brazil; however, with XAVIER GWD presenting a better performance for weather and crop variables assessed.

Change in the magnitude and mechanisms of global temperature variability with warming.

PubMed

Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming

NASA Astrophysics Data System (ADS)

Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.

2017-12-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

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

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

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

Impacts of variability in cellulosic biomass yields on energy security.

PubMed

Mullins, Kimberley A; Matthews, H Scott; Griffin, W Michael; Anex, Robert

2014-07-01

The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.

[Body condition and metabolic stability as the basis for high milk yield and undisturbed fertility in dairy cows--a contribution for deduction of reference values].

PubMed

Staufenbiel, R; Arndt, G; Schröder, U; Gelfert, C C

2004-05-01

The target of this study was to describe the interactions between body condition and various descriptors of yield and fertility. It was aimed to identify an optimal conditional range to be used in herd management which combines high milk yield with acceptable fertility traits and general health. For this purpose, backfat thickness was measured by ultrasound at 46111 dairy cows on 78 different farms and was subsequently related to production variables. Negative energy balance is getting more intense and prolonged with increasing milk yield. However a conditional nadir below 10 mm leads to decreased milk production. To reach a high production level without an increasing incidence of health disorders, conditional nadir should not decline below 13 mm backfat thickness on herd average. Lower value only lead to negligibly higher milk yield but cause a distinctively higher risk of fertility problems and culling. High herd yields do not have to be at expense of reproduction performance and can be achieved without extreme body condition losses. An efficient herd management can offset depression in fertility, which commonly is combined with increasing milk yield. A standard curve for backfat thickness throughout lactation is suggested to be used in dairy herd management.

[Winter wheat yield gap between field blocks based on comparative performance analysis].

PubMed

Chen, Jian; Wang, Zhong-Yi; Li, Liang-Tao; Zhang, Ke-Feng; Yu, Zhen-Rong

2008-09-01

Based on a two-year household survey data, the yield gap of winter wheat in Quzhou County of Hebei Province, China in 2003-2004 was studied through comparative performance analysis (CPA). The results showed that there was a greater yield gap (from 4.2 to 7.9 t x hm(-2)) between field blocks, with a variation coefficient of 0.14. Through stepwise forward linear multiple regression, it was found that the yield model with 8 selected variables could explain 63% variability of winter wheat yield. Among the variables selected, soil salinity, soil fertility, and irrigation water quality were the most important limiting factors, accounting for 52% of the total yield gap. Crop variety was another important limiting factor, accounting for 14%; while planting date, fertilizer type, disease and pest, and water press accounted for 7%, 14%, 10%, and 3%, respectively. Therefore, besides soil and climate conditions, management practices occupied the majority of yield variability in Quzhou County, suggesting that the yield gap could be reduced significantly through optimum field management.

Sediment Concentration and Its Relation to Catchment Characteristics in Forested Headwater Streams of the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Wagenbrenner, J.; Safeeq, M.; Hunsaker, C. T.

2017-12-01

Sediment yields are highly variable and controlled by multiple topographic, geomorphic, and hydrologic factors that make its generalization or prediction challenging. We examined the characteristics of sediment concentration across ten headwater catchments located in the Kings River Experimental Watersheds, Sierra Nevada, California. Study catchments ranged from 50 to 475 ha and spanned from 1,782 to 2,373 m in elevation in the rain-snow transition zone. Mean annual streamflow ranged from 281 to 408 mm in the low elevation Providence and 436 to 656 mm in the high elevation Bull catchments. We measured suspended sediment concentration (SSC) and bedload sediment yield from 2004-2016. We related these outputs to catchment mean elevation, relief, slope, and drainage density as natural controls and runoff ratio, baseflow index, recession constant, and slope of the flow duration curve as hydrologic controls. The SSC were higher in the high elevation Bull catchments (64 ± 34 mg L-1) as compared to low elevation Providence catchments (30 ± 17 mg L-1). Measured SSC in both Bull and Providence declined with increasing catchment mean elevation (R > - 0.5). We found slope of the flow duration curve (R = 0.85) and recession constant (R = -0.91) as the two of best predictors of SSC in Providence. In Bull, drainage area (R = 0.87) and baseflow index (R = -0.78) were the two best predictors of SSC. The intercept and slope of the suspended sediment yield - discharge rating curve (SSY-Q) in Providence was positively related to catchment relief. In contrast, the SSY-Q intercept increased and SSY-Q slope declined with increasing relief in Bull. The mean annual bedload sediment yield varied between 0.4 Mg km-2 and 4.2 Mg km-2 across the ten watersheds, and bedload contributed a relatively small fraction to the total sediment load. Mean bedload sediment yields across the catchments were most associated with catchment slope and relief. These preliminary results provide insight on the dynamics of sediment yield and the natural range of variability in small headwater Sierra Nevada streams. These results can guide selection of appropriate predictor variables for catchment-scale sediment yield models that inform forest management.

Genetic variation in heat tolerance-related traits in a population of wheat multiple synthetic derivatives

PubMed Central

Elbashir, Awad A. E.; Gorafi, Yasir S. A.; Tahir, Izzat S. A.; Elhashimi, Ashraf. M. A.; Abdalla, Modather G. A.; Tsujimoto, Hisashi

2017-01-01

In wheat (Triticum aestivum L.) high temperature (≥30°C) during grain filling leads to considerable reduction in grain yield. We studied 400 multiple synthetic derivatives (MSD) lines to examine the genetic variability of heat stress–adaptive traits and to identify new sources of heat tolerance to be used in wheat breeding programs. The experiment was arranged in an augmented randomized complete block design in four environments in Sudan. A wide range of genetic variability was found in most of the traits in all environments. For all traits examined, we found MSD lines that showed better performance than their parent ‘Norin 61’ and two adapted Sudanese cultivars. Using the heat tolerance efficiency, we identified 13 highly heat-tolerant lines and several lines with intermediate heat tolerance and good yield potential. We also identified lines with alleles that can be used to increase wheat yield potential. Our study revealed that the use of the MSD population is an efficient way to explore the genetic variation in Ae. tauschii for wheat breeding and improvement. PMID:29398942

Identification of potentially high yielding irradiated cassava ‘Gajah’ genotype with different geographic coordinates

NASA Astrophysics Data System (ADS)

Subekti, I.; Khumaida, N.; Ardie, SW

2017-01-01

Cassava is one of the main and important carbohydrate producing crops in Indonesia. Thus cassava production and its tuber quality need to be improved. ‘Gajah’ genotype is a local genotypes cassava from East Kalimantan, has high potential yield (> 60 ton Ha-1). However, the harvest time of this genotype is quite long (>= 12 months). The objective of this research was to identify the high yielding cassava mutants from the gamma rays irradiated ‘Gajah’ genotype at M1V3 population and potential yield at different location. Several putative cassava mutants (12 mutants) were planted in Cikabayan Experimental Field, IPB from March 2015 to March 2016 and the yields compared with the same genotype grown at different location by seeing its coordinates to observe the potential yield. Our result showed that the fresh tuber weight per plant of some putative mutants could reach more than 8 kg (yield potential of 64 ton Ha-1). The harvested tubers also had sweet flavor, although the tubers of some putative mutants were bitter. Based on previous research study, the different geographic coordinate has resulted variability on fresh tuber yield. It seems that it needs to observe the stability of ‘Gajah’- irradiated mutants in several location in Java Island.

Soil Water Holding Capacity Mitigates Downside Risk and Volatility in US Rainfed Maize: Time to Invest in Soil Organic Matter?

PubMed Central

Williams, Alwyn; Hunter, Mitchell C.; Kammerer, Melanie; Kane, Daniel A.; Jordan, Nicholas R.; Mortensen, David A.; Smith, Richard G.; Snapp, Sieglinde

2016-01-01

Yield stability is fundamental to global food security in the face of climate change, and better strategies are needed for buffering crop yields against increased weather variability. Regional- scale analyses of yield stability can support robust inferences about buffering strategies for widely-grown staple crops, but have not been accomplished. We present a novel analytical approach, synthesizing 2000–2014 data on weather and soil factors to quantify their impact on county-level maize yield stability in four US states that vary widely in these factors (Illinois, Michigan, Minnesota and Pennsylvania). Yield stability is quantified as both ‘downside risk’ (minimum yield potential, MYP) and ‘volatility’ (temporal yield variability). We show that excessive heat and drought decreased mean yields and yield stability, while higher precipitation increased stability. Soil water holding capacity strongly affected yield volatility in all four states, either directly (Minnesota and Pennsylvania) or indirectly, via its effects on MYP (Illinois and Michigan). We infer that factors contributing to soil water holding capacity can help buffer maize yields against variable weather. Given that soil water holding capacity responds (within limits) to agronomic management, our analysis highlights broadly relevant management strategies for buffering crop yields against climate variability, and informs region-specific strategies. PMID:27560666

Breeding high-yielding drought-tolerant rice: genetic variations and conventional and molecular approaches

PubMed Central

Kumar, Arvind; Dixit, Shalabh; Ram, T.; Yadaw, R. B.; Mishra, K. K.; Mandal, N. P.

2014-01-01

The increased occurrence and severity of drought stress have led to a high yield decline in rice in recent years in drought-affected areas. Drought research at the International Rice Research Institute (IRRI) over the past decade has concentrated on direct selection for grain yield under drought. This approach has led to the successful development and release of 17 high-yielding drought-tolerant rice varieties in South Asia, Southeast Asia, and Africa. In addition to this, 14 quantitative trait loci (QTLs) showing a large effect against high-yielding drought-susceptible popular varieties were identified using grain yield as a selection criterion. Six of these (qDTY 1.1, qDTY 2.2, qDTY 3.1, qDTY 3.2, qDTY 6.1, and qDTY 12.1) showed an effect against two or more high-yielding genetic backgrounds in both the lowland and upland ecosystem, indicating their usefulness in increasing the grain yield of rice under drought. The yield of popular rice varieties IR64 and Vandana has been successfully improved through a well-planned marker-assisted backcross breeding approach, and QTL introgression in several other popular varieties is in progress. The identification of large-effect QTLs for grain yield under drought and the higher yield increase under drought obtained through the use of these QTLs (which has not been reported in other cereals) indicate that rice, because of its continuous cultivation in two diverse ecosystems (upland, drought tolerant, and lowland, drought susceptible), has benefited from the existence of larger genetic variability than in other cereals. This can be successfully exploited using marker-assisted breeding. PMID:25205576

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

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.

Closing the Yield Gap of Sugar Beet in the Netherlands-A Joint Effort.

PubMed

Hanse, Bram; Tijink, Frans G J; Maassen, Jurgen; van Swaaij, Noud

2018-01-01

The reform of the European Union's sugar regime caused potential decreasing beet prices. Therefore, the Speeding Up Sugar Yield (SUSY) project was initiated. At the start, a 3 × 15 target was formulated: in 2015 the national average sugar yield in the Netherlands equals 15 t/ha (60% of the sugar beet potential) and the total variable costs 15 euro/t sugar beet, aspiring a saving on total variable costs and a strong increase in sugar yield. Based on their average sugar yield in 2000-2004, 26 pairs of "type top" (high yielding) and "type average" (average yielding) growers were selected from all sugar beet growing regions in the Netherlands. On the fields of those farmers, all measures of sugar beet cultivation were investigated, including cost calculation and recording phytopathological, agronomical and soil characteristics in 2006 and 2007. Although there was no significant difference in total variable costs, the "type top" growers yielded significantly 20% more sugar in each year compared to the "type average" growers. Therefore, the most profitable strategy for the growers is maximizing sugar yield and optimizing costs. The difference in sugar yield between growers could be explained by pests and diseases (50%), weed control (30%), soil structure (25%) and sowing date (14%), all interacting with each other. The SUSY-project revealed the effect of the grower's management on sugar yield. As a follow up for the SUSY-project, a growers' guide "Suikerbietsignalen" was published, Best Practice study groups of growers were formed and trainings and workshops were given and field days organized. Further, the benchmarking and feedback on the crop management recordings and the extension on variety choice, sowing performance, foliar fungi control and harvest losses were intensified. On the research part, a resistance breaking strain of the Beet Necrotic Yellow Vein Virus (BNYVV) and a new foliar fungus, Stemphylium beticola , were identified and options for control were tested, and implemented in growers practices. The joint efforts of sugar industry, sugar beet research and growers resulted in a raise in sugar yield from 10.6 t/ha in 2002-2006 to 13.8 t/ha in 2012-2016.

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

Assessment of diesel-contaminated domestic wastewater treated by constructed wetlands for irrigation of chillies grown in a greenhouse.

PubMed

Al-Isawi, Rawaa H K; Scholz, Miklas; Al-Faraj, Furat A M

2016-12-01

In order to avoid environmental pollution and eliminate the need for using fertiliser, this study assessed for the first time the optimum performance of mature (in operation since 2011) vertical flow constructed wetlands in treating domestic wastewater (with and without hydrocarbon) and the subsequent recycling of the outflow to irrigate chillies (De Cayenne; Capsicum annuum (Linnaeus) Longum Group 'De Cayenne') grown in a greenhouse. Various variables were investigated to assess the treatment performance. Concerning chilli fruit numbers, findings showed that the highest fruit yields for all wetland filters were associated with those that received inflow wastewater with a high loading rate, reflecting the high nutrient availability in treated wastewater, which is of obvious importance for yield production. Findings also indicated that wetlands without hydrocarbon, small aggregate size, low contact time and low inflow loading rate provided high marketable yields (expressed in economic return). In comparison, chillies irrigated by filters with hydrocarbon contamination, small aggregate size, high contact time and high loading rate also resulted in high marketable yields of chillies, which pointed out the role of high contact time and high inflow load for better diesel degradation rates.

Yield impact for wafer shape misregistration-based binning for overlay APC diagnostic enhancement

NASA Astrophysics Data System (ADS)

Jayez, David; Jock, Kevin; Zhou, Yue; Govindarajulu, Venugopal; Zhang, Zhen; Anis, Fatima; Tijiwa-Birk, Felipe; Agarwal, Shivam

2018-03-01

The importance of traditionally acceptable sources of variation has started to become more critical as semiconductor technologies continue to push into smaller technology nodes. New metrology techniques are needed to pursue the process uniformity requirements needed for controllable lithography. Process control for lithography has the advantage of being able to adjust for cross-wafer variability, but this requires that all processes are close in matching between process tools/chambers for each process. When this is not the case, the cumulative line variability creates identifiable groups of wafers1 . This cumulative shape based effect is described as impacting overlay measurements and alignment by creating misregistration of the overlay marks. It is necessary to understand what requirements might go into developing a high volume manufacturing approach which leverages this grouping methodology, the key inputs and outputs, and what can be extracted from such an approach. It will be shown that this line variability can be quantified into a loss of electrical yield primarily at the edge of the wafer and proposes a methodology for root cause identification and improvement. This paper will cover the concept of wafer shape based grouping as a diagnostic tool for overlay control and containment, the challenges in implementing this in a manufacturing setting, and the limitations of this approach. This will be accomplished by showing that there are identifiable wafer shape based signatures. These shape based wafer signatures will be shown to be correlated to overlay misregistration, primarily at the edge. It will also be shown that by adjusting for this wafer shape signal, improvements can be made to both overlay as well as electrical yield. These improvements show an increase in edge yield, and a reduction in yield variability.

Sensitivity of barley varieties to weather in Finland.

PubMed

Hakala, K; Jauhiainen, L; Himanen, S J; Rötter, R; Salo, T; Kahiluoto, H

2012-04-01

Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather parameters critical for yield formation. To determine the scale of such 'weather response diversity' within barley (Hordeum vulgare L.), an important crop in northern conditions, the yield responses of a wide range of modern and historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in the season, delayed sowing, rain 3-7 weeks after sowing, a temperature change 3-4 weeks after sowing, a high temperature sum accumulation rate from heading to yellow ripeness and high temperatures (⩾25°C) at around heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present study. However, new technology and novel genetic material are needed to enable crops to withstand periods of excessive rain or drought early in the season and to enhance performance under increased temperature sum accumulation rates prior to heading.

Implementation of high slurry concentration and sonication to pack high-efficiency, meter-long capillary ultrahigh pressure liquid chromatography columns.

PubMed

Godinho, Justin M; Reising, Arved E; Tallarek, Ulrich; Jorgenson, James W

2016-09-02

Slurry packing capillary columns for ultrahigh pressure liquid chromatography is complicated by many interdependent experimental variables. Previous results have suggested that combination of high slurry concentration and sonication during packing would create homogeneous bed microstructures and yield highly efficient capillary columns. Herein, the effect of sonication while packing very high slurry concentrations is presented. A series of six, 1m×75μm internal diameter columns were packed with 200mg/mL slurries of 2.02μm bridged-ethyl hybrid silica particles. Three of the columns underwent sonication during packing and yielded highly efficient separations with reduced plate heights as low as 1.05. Copyright © 2016 Elsevier B.V. All rights reserved.

Genetic variability for stomatal conductance in Pima cotton and its relation to improvements of heat adaptation.

PubMed Central

Radin, J W; Lu, Z; Percy, R G; Zeiger, E

1994-01-01

Responses of stomata to environment have been intensively studied, but little is known of genetic effects on stomatal conductance or their consequences. In Pima cotton (Gossypium barbadense L.), a crop that is bred for irrigated production in very hot environments, stomatal conductance varies genetically over a wide range and has increased with each release of new higher-yielding cultivars. A cross between heat-adapted (high-yielding) and unadapted genotypes produced F2 progeny cosegregating for stomatal conductance and leaf temperature. Within segregating populations in the field, conductance was negatively correlated with foliar temperature because of evaporative cooling. Plants were selected from the F2 generation specifically and solely for differing stomatal conductance. Among F3 and F4 populations derived from these selections, conductance and leaf cooling were significantly correlated with fruiting prolificacy during the hottest period of the year and with yield. Conductance was not associated with other factors that might have affected yield potential (single-leaf photosynthetic rate, leaf water potential). As breeders have increased the yield of this crop, genetic variability for conductance has allowed inadvertent selection for "heat avoidance" (evaporative cooling) in a hot environment. PMID:11607487

Temporal variability of green and blue water footprint worldwide

NASA Astrophysics Data System (ADS)

Tamea, Stefania; Lomurno, Marianna; Tuninetti, Marta; Laio, Francesco; Ridolfi, Luca

2016-04-01

Water footprint assessment is becoming widely used in the scientific literature and it is proving useful in a number of multidisciplinary contexts. Given this increasing popularity, measures of green and blue water footprint (or virtual water content, VWC) require evaluations of uncertainty and variability to quantify the reliability of proposed analyses. As of today, no studies are known to assess the temporal variability of crop VWC at the global scale; the present contribution aims at filling this gap. We use a global high-resolution distributed model to compute the VWC of staple crops (wheat and maize), basing on the soil water balance, forced by hydroclimatic imputs, and on the total crop evapotranspiration in multiple growing seasons. Crop actual yield is estimated using country-based yield data, adjusted to account for spatial variability, allowing for the analysis of the different role played by climatic and management factors in the definition of crop yield. The model is then run using hydroclimatic data, i.e., precipitation and potential evapotranspiration, for the period 1961-2013 as taken from the CRU database (CRU TS v. 3.23) and using the corresponding country-based yield data from FAOSTAT. Results provide the time series of total evapotranspiration, actual yield and VWC, with separation between green and blue VWC, and the overall volume of water used for crop production, both at the cell scale (5x5 arc-min) and aggregated at the country scale. Preliminary results indicate that total (green+blue) VWC is, in general, weekly dependent on hydroclimatic forcings if water for irrigation is unlimited, because irrigated agriculture allows to compensate temporary water shortage. Conversely, most part of the VWC variability is found to be determined by the temporal evolution of crop yield. At the country scale, the total water used by countries for agricultural production has seen a limited change in time, but the marked increase in the water-use efficiency expressed by VWC has determined an increase of production. Such increase has helped to meet the increasing global food demand in the past 50 years.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

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

2016-01-01

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

Epidemiology and impact of Fasciola hepatica exposure in high-yielding dairy herds

PubMed Central

Howell, Alison; Baylis, Matthew; Smith, Rob; Pinchbeck, Gina; Williams, Diana

2015-01-01

The liver fluke Fasciola hepatica is a trematode parasite with a worldwide distribution and is the cause of important production losses in the dairy industry. The aim of this observational study was to assess the prevalence of exposure to F. hepatica in a group of high yielding dairy herds, to determine the risk factors and investigate their associations with production and fertility parameters. Bulk milk tank samples from 606 herds that supply a single retailer with liquid milk were tested with an antibody ELISA for F. hepatica. Multivariable linear regression was used to investigate the effect of farm management and environmental risk factors on F. hepatica exposure. Higher rainfall, grazing boggy pasture, presence of beef cattle on farm, access to a stream or pond and smaller herd size were associated with an increased risk of exposure. Univariable regression was used to look for associations between fluke exposure and production-related variables including milk yield, composition, somatic cell count and calving index. Although causation cannot be assumed, a significant (p < 0.001) negative association was seen between F. hepatica exposure and estimated milk yield at the herd level, representing a 15% decrease in yield for an increase in F. hepatica exposure from the 25th to the 75th percentile. This remained significant when fertility, farm management and environmental factors were controlled for. No associations were found between F. hepatica exposure and any of the other production, disease or fertility variables. PMID:26093971

Change in the magnitude and mechanisms of global temperature variability with warming

PubMed Central

Brown, Patrick T.; Ming, Yi; Li, Wenhong; Hill, Spencer A.

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future. PMID:29391875

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE PAGES

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; ...

2017-02-21

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

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

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Coapplication of Chicken Litter Biochar and Urea Only to Improve Nutrients Use Efficiency and Yield of Oryza sativa L. Cultivation on a Tropical Acid Soil

PubMed Central

Maru, Ali; Haruna, Osumanu Ahmed; Charles Primus, Walter

2015-01-01

The excessive use of nitrogen (N) fertilizers in sustaining high rice yields due to N dynamics in tropical acid soils not only is economically unsustainable but also causes environmental pollution. The objective of this study was to coapply biochar and urea to improve soil chemical properties and productivity of rice. Biochar (5 t ha−1) and different rates of urea (100%, 75%, 50%, 25%, and 0% of recommended N application) were evaluated in both pot and field trials. Selected soil chemical properties, rice plants growth variables, nutrient use efficiency, and yield were determined using standard procedures. Coapplication of biochar with 100% and 75% urea recommendation rates significantly increased nutrients availability (especially P and K) and their use efficiency in both pot and field trials. These treatments also significantly increased rice growth variables and grain yield. Coapplication of biochar and urea application at 75% of the recommended rate can be used to improve soil chemical properties and productivity and reduce urea use by 25%. PMID:26273698

Relationship of grapevine yield and growth to nematode densities.

PubMed

Ferris, H; McKenry, M V

1975-07-01

Yield, growth, and vigor of individual grape vines were correlated with nematode population densities in a series of California vineyards. In a Hanford sandy loam soil, Xiphinema americanum densities showed negative correlations with yield, growth, and vigor of vines. When vines were categorized according to vigor, X. americanurn densities had little relationship to yield of high-vigor vines, but were negatively correlated with yield of low-vigor vines. Densities of Paratylenchus harnatus were positively correlated with yield, growth, and vigor of vines. Correlations between Meloidogyne spp. densities and vine performance were variable, even when the vines were separated according to soil type and plant vigor. Densities of Meloidogyne spp. populations were generally higher on coarser-textured, sandy soils and the vines were less vigorous there. Densities of P. hamatus were greater in fine-textured soils.

Inferring genetic parameters on latent variables underlying milk yield and quality, protein composition, curd firmness and cheese-making traits in dairy cattle.

PubMed

Dadousis, C; Cipolat-Gotet, C; Bittante, G; Cecchinato, A

2018-02-01

We studied the genetics of cheese-related latent variables (factors; Fs) for application in dairy cattle breeding. In total, 26 traits, recorded in 1264 Brown Swiss cows, were analyzed through multivariate factor analysis (MFA). Traits analyzed were descriptors of milk quality and yield (including protein fractions) and measures of coagulation, curd firmness (CF), cheese yields (%CY) and nutrient recoveries in the curd (REC). A total of 10 Fs (mutual orthogonal with a varimax rotation) were obtained. To assess the practical use of the Fs into breeding, we inferred their genetic parameters using single and bivariate animal models under a Bayesian framework. Heritability estimates (intra-herd) varied between 0.11 and 0.72 (F3: Yield and F7: κ-β-CN, respectively). The Fs underlined basic characteristics of the cheese-making process, milk components and udder health, while retaining 74% of the original variability. The first two Fs were indicators of the CY percentage (F1: %CY) and the CF process (F2: CF t ), and presented similar heritability estimates: 0.268 and 0.295, respectively. The third factor was associated with the yield of milk and solids (F3: Yield) characterized by a low heritability (0.108) and the fourth with the cheese nitrogen (N) (F4: Cheese N) that conversely appeared to be characterized by a high heritability (0.618). Three Fs were associated with the proportion of the basic milk caseins on total milk protein (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN), also highly heritable (0.565, 0.723 and 0.397, respectively) and 1 factor with the phosphorylated form of the as1-CN (F9: as1-CN-Ph; 0.318). Moreover, 1 factor was linked to the whey protein α-LA (F10: α-LA; 0.147). An indicator factor of a cow's udder health (F6: Udder health) was also obtained and showed a moderate heritability (0.204). Although the Fs were phenotypically uncorrelated, considerable additive genetic correlations existed among them, with highest values observed between F10: α-LA and F6: Udder health (-0.67) as well as between F9: as1-CN-Ph and F3: Yield (-0.60). Our results show the usefulness of MFA in dairy cattle breeding. The ability to replace a large number of variables with a few latent indicators of the same biological meaning marks MFA as a valuable tool for developing breeding strategies to improve cow's cheese-related traits.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Recent climate variability and its impacts on soybean yields in Southern Brazil

NASA Astrophysics Data System (ADS)

Ferreira, Danielle Barros; Rao, V. Brahmananda

2011-08-01

Recent climate variability in rainfall, temperatures (maximum and minimum), and the diurnal temperature range is studied with emphasis on its influence over soybean yields in southern Brazil, during 1969 to 2002. The results showed that the soybean ( Glycine max L. Merril) yields are more affected by changes in temperature during summer, while changes in rainfall are more important during the beginning of plantation and at its peak of development. Furthermore, soybean yields in Paraná are more sensitive to rainfall variations, while soybean yields in the Rio Grande do Sul are more sensitive to variations in temperature. Effects of interannual climatic variability on soybean yields are evaluated through three agro-meteorological models: additive Stewart, multiplicative Rao, and multiplicative Jensen. The Jensen model is able to reproduce the interannual behavior of soybean yield reasonably well.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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 ...

Strengths and Limitations of Operational Use of 1 Km EO Biophysical Products for Regional Prediction of Grain Yelds in Europe (wheat, barley and maize)

NASA Astrophysics Data System (ADS)

Meroni, M.; LEO, O.; Lopez-Lozano, R.; Baruth, B.; Duveiller, G.; Garcia-Condado, S.; Hooker, J.; Seguini, L.

2014-12-01

The site-specific relationship between EO indicators and actual crop yields has been explored in many different studies, describing semi-empirical regression models between spatially aggregated biophysical parameters or vegetation indices and observed yields (from field measurements or official statistics). However, when considering larger extensions -from countries to continents- agro-climatic conditions and crop management may differ substantially among regions, and these differences may greatly influence the relationship between biophysical indicators and the observed yields, which may be also driven by limiting factors other than green biomass formation. The present study aims to better assess the contribution of EO indicators within an operational crop yield forecasting system in Europe and neighbouring countries, by evaluating how these above mentioned geographic differences influence the relationship between biophysical indicators and crop yield. We therefore explore, as a first step, the correspondence between fAPAR time-series (1999-2013) and the inter-annual yield variability of wheat, barley and grain maize, at sub-national level across Europe (270-450 Administrative Units, depending on crop). In a second step, we map the agro-climatic contexts in which EO indicators better explain the observed yield inter-annual variability, identify the influence of some meteorological events on the fAPAR -yield relationship and provide some recommendations for further investigation. The results indicate that in water-limited environments (e.g. Mediterranean and Black Sea areas), fAPAR is highly correlated with yields whereas in northern Europe, crop yield appears much less limited by leaf area expansion along the season, and the relationship between yield and EO products becomes more difficult to interpret.

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

NASA Astrophysics Data System (ADS)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields and thus has potential to be used for yield prediction, or for ingestion into a crop simulation model as a crop-specific moisture stress function.

Relationship between cotton yield and soil electrical conductivity, topography, and landsat imagery

USDA-ARS?s Scientific Manuscript database

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this stu...

Tightly-Coupled Plant-Soil Nitrogen Cycling: Comparison of Organic Farms across an Agricultural Landscape

PubMed Central

Bowles, Timothy M.; Hollander, Allan D.; Steenwerth, Kerri; Jackson, Louise E.

2015-01-01

How farming systems supply sufficient nitrogen (N) for high yields but with reduced N losses is a central challenge for reducing the tradeoffs often associated with N cycling in agriculture. Variability in soil organic matter and management of organic farms across an agricultural landscape may yield insights for improving N cycling and for evaluating novel indicators of N availability. We assessed yields, plant-soil N cycling, and root expression of N metabolism genes across a representative set of organic fields growing Roma-type tomatoes (Solanum lycopersicum L.) in an intensively-managed agricultural landscape in California, USA. The fields spanned a three-fold range of soil carbon (C) and N but had similar soil types, texture, and pH. Organic tomato yields ranged from 22.9 to 120.1 Mg ha-1 with a mean similar to the county average (86.1 Mg ha-1), which included mostly conventionally-grown tomatoes. Substantial variability in soil inorganic N concentrations, tomato N, and root gene expression indicated a range of possible tradeoffs between yields and potential for N losses across the fields. Fields showing evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which high crop yields are supported by adequate N availability but low potential for N loss, had the highest total and labile soil C and N and received organic matter inputs with a range of N availability. In these fields, elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, confirmed that plant N assimilation was high even when inorganic N pools were low. Thus tightly-coupled N cycling occurred on several working organic farms. Novel combinations of N cycling indicators (i.e. inorganic N along with soil microbial activity and root gene expression for N assimilation) would support adaptive management for improved N cycling on organic as well as conventional farms, especially when plant-soil N cycling is rapid. PMID:26121264

Tightly-Coupled Plant-Soil Nitrogen Cycling: Comparison of Organic Farms across an Agricultural Landscape.

PubMed

Bowles, Timothy M; Hollander, Allan D; Steenwerth, Kerri; Jackson, Louise E

2015-01-01

How farming systems supply sufficient nitrogen (N) for high yields but with reduced N losses is a central challenge for reducing the tradeoffs often associated with N cycling in agriculture. Variability in soil organic matter and management of organic farms across an agricultural landscape may yield insights for improving N cycling and for evaluating novel indicators of N availability. We assessed yields, plant-soil N cycling, and root expression of N metabolism genes across a representative set of organic fields growing Roma-type tomatoes (Solanum lycopersicum L.) in an intensively-managed agricultural landscape in California, USA. The fields spanned a three-fold range of soil carbon (C) and N but had similar soil types, texture, and pH. Organic tomato yields ranged from 22.9 to 120.1 Mg ha-1 with a mean similar to the county average (86.1 Mg ha-1), which included mostly conventionally-grown tomatoes. Substantial variability in soil inorganic N concentrations, tomato N, and root gene expression indicated a range of possible tradeoffs between yields and potential for N losses across the fields. Fields showing evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which high crop yields are supported by adequate N availability but low potential for N loss, had the highest total and labile soil C and N and received organic matter inputs with a range of N availability. In these fields, elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, confirmed that plant N assimilation was high even when inorganic N pools were low. Thus tightly-coupled N cycling occurred on several working organic farms. Novel combinations of N cycling indicators (i.e. inorganic N along with soil microbial activity and root gene expression for N assimilation) would support adaptive management for improved N cycling on organic as well as conventional farms, especially when plant-soil N cycling is rapid.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

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

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled futuremore » climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.« less

Genetic variability in Jatropha curcas L. from diallel crossing.

PubMed

Ribeiro, D O; Silva-Mann, R; Alvares-Carvalho, S V; Souza, E M S; Vasconcelos, M C; Blank, A F

2017-05-18

Physic nut (Jatropha curcas L.) presents high oilseed yield and low production cost. However, technical-scientific knowledge on this crop is still limited. This study aimed to evaluate and estimate the genetic variability of hybrids obtained from dialell crossing. Genetic variability was carried out using ISSR molecular markers. For genetic variability, nine primers were used, and six were selected with 80.7% polymorphism. Genetic similarity was obtained using the NTSYS pc. 2.1 software, and cluster analysis was obtained by the UPGMA method. Mean genetic similarity was 58.4% among hybrids; the most divergent pair was H1 and H10 and the most similar pair was H9 and H10. ISSR PCR markers provided a quick and highly informative system for DNA fingerprinting, and also allowed establishing genetic relationships of Jatropha hybrids.

Variability of Precipitation and Evapotranspiration across an Andean Paramo

NASA Astrophysics Data System (ADS)

Jaimes, J. C.; Riveros-Iregui, D.; Avery, W. A.; Gaviria, S.; Peña-Quemba, C.; Herran, G.

2012-12-01

Paramos are alpine grasslands that occur mostly in the Andes Mountains of South America. Typically soils in the paramo have a volcanic origin, which leads to high permeability and high water yield and makes the paramo a reliable drinking water supply for many highland cities. Because hydrological measurements in these humid systems are rare, current understanding of the hydrologic behavior of paramos relies on modeling studies with little validation against ground observations. We present measurements of evapotranspiration (ET) and precipitation (P) across Chingaza Paramo, near Bogotá, Colombia. This paramo supplies water for ~80% of Bogotá's population (a total of 8 million people). Meteorological variables such us air temperature, relative humidity, wind speed, precipitation, and solar radiation were monitored using five weather stations located at various elevations from 3000m to 3600m. Our results show that ET varies from 500 to 700 mm y-1 as a function of elevation, whereas precipitation commonly exceeds ET, ranging between 1500 and 1800 mm y-1. These spatial differences between P and ET make water yield highly variable across this mountainous environment. Our results demonstrate that while paramos play an important role in the hydrologic cycle of tropical environments, understanding their hydrologic behavior requires characterization and monitoring of the pronounced spatial gradients of precipitation and evapotranspiration.

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

Evidence for divergence of response in Indica, Japonica, and wild rice to high CO2 x temperature interaction

USDA-ARS?s Scientific Manuscript database

Previous studies suggest that the intraspecific variability of rice yield response to rising carbon dioxide concentration, [CO2], could serve as a basis of selection to improve genotypes for future high CO2 conditions. However, assessment of responses to elevated [CO2] must consider air temperature,...

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.

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

Rice Root Architectural Plasticity Traits and Genetic Regions for Adaptability to Variable Cultivation and Stress Conditions1[OPEN

PubMed Central

Sandhu, Nitika; Raman, K. Anitha; Torres, Rolando O.; Audebert, Alain; Dardou, Audrey; Kumar, Arvind; Henry, Amelia

2016-01-01

Future rice (Oryza sativa) crops will likely experience a range of growth conditions, and root architectural plasticity will be an important characteristic to confer adaptability across variable environments. In this study, the relationship between root architectural plasticity and adaptability (i.e. yield stability) was evaluated in two traditional × improved rice populations (Aus 276 × MTU1010 and Kali Aus × MTU1010). Forty contrasting genotypes were grown in direct-seeded upland and transplanted lowland conditions with drought and drought + rewatered stress treatments in lysimeter and field studies and a low-phosphorus stress treatment in a Rhizoscope study. Relationships among root architectural plasticity for root dry weight, root length density, and percentage lateral roots with yield stability were identified. Selected genotypes that showed high yield stability also showed a high degree of root plasticity in response to both drought and low phosphorus. The two populations varied in the soil depth effect on root architectural plasticity traits, none of which resulted in reduced grain yield. Root architectural plasticity traits were related to 13 (Aus 276 population) and 21 (Kali Aus population) genetic loci, which were contributed by both the traditional donor parents and MTU1010. Three genomic loci were identified as hot spots with multiple root architectural plasticity traits in both populations, and one locus for both root architectural plasticity and grain yield was detected. These results suggest an important role of root architectural plasticity across future rice crop conditions and provide a starting point for marker-assisted selection for plasticity. PMID:27342311

Large Variability of Proanthocyanidin Content and Composition in Sainfoin (Onobrychis viciifolia)

PubMed Central

2015-01-01

Proanthocyanidins (PAs) in sainfoin (Onobrychis viciifolia Scop.) are of interest to ameliorate the sustainability of livestock production. However, sainfoin forage yield and PA concentrations, as well as their composition, require optimization. Individual plants of 27 sainfoin accessions from four continents were analyzed with LC-ESI-QqQ-MS/MS for PA concentrations and simple phenolic compounds. Large variability existed in PA concentrations (23.0–47.5 mg g–1 leaf dry matter (DM)), share of prodelphinidins (79–96%), and mean degree of polymerization (11–14) among, but also within, accessions. PAs were mainly located in leaves (26.8 mg g–1 DM), whereas stems had less PAs (7.8 mg g–1 DM). Overall, high-yielding plants had lower PA leaf concentrations (R2 = 0.16, P < 0.001) and fewer leaves (R2 = 0.66, P < 0.001). However, the results show that these two trade-offs between yield and bioactive PAs can be overcome. PMID:26551032

Limited and time-delayed internal resource allocation generates oscillations and chaos in the dynamics of citrus crops

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

Ye, Xujun, E-mail: yexujun@cc.hirosaki-u.ac.jp; Faculty of Agriculture and Life Sciences, Hirosaki University, Aomori 036-8561; Sakai, Kenshi, E-mail: ken@cc.tuat.ac.jp

Alternate bearing or masting is a yield variability phenomenon in perennial crops. The complex dynamics in this phenomenon have stimulated much ecological research. Motivated by data from an eight-year experiment with forty-eight individual trees, we explored the mechanism inherent to these dynamics in Satsuma mandarin (Citrus unshiu Marc.). By integrating high-resolution imaging technology, we found that the canopy structure and reproduction output of individual citrus crops are mutually dependent on each other. Furthermore, it was revealed that the mature leaves in early season contribute their energy to the fruiting of the current growing season, whereas the younger leaves show amore » delayed contribution to the next growing season. We thus hypothesized that the annual yield variability might be caused by the limited and time-delayed resource allocation in individual plants. A novel lattice model based on this hypothesis demonstrates that this pattern of resource allocation will generate oscillations and chaos in citrus yield.« less

Genotypic character relationship and phenotypic path coefficient analysis in chili pepper genotypes grown under tropical condition.

PubMed

Usman, Magaji G; Rafii, Mohd Y; Martini, Mohammad Y; Oladosu, Yusuff; Kashiani, Pedram

2017-03-01

Studies on genotypic and phenotypic correlations among characters of crop plants are useful in planning, evaluating and setting selection criteria for the desired characters in a breeding program. The present study aimed to estimate the phenotypic correlation coefficients among yield and yield attributed characters and to work out the direct and indirect effects of yield-related characters on yield per plant using path coefficient analysis. Twenty-six genotypes of chili pepper were laid out in a randomized complete block design with three replications. Yield per plant showed positive and highly significant (P ≤ 0.01) correlations with most of the characters studied at both the phenotypic and genotypic levels. By contrast, disease incidence and days to flowering showed a significant negative association with yield. Fruit weight and number of fruits exerted positive direct effect on yield and also had a positive and significant (P ≤ 0.01) correlation with yield per plant. However, fruit length showed a low negative direct effect with a strong and positive indirect effect through fruit weight on yield and had a positive and significant association with yield. Longer fruits, heavy fruits and a high number of fruits are variables that are related to higher yields of chili pepper under tropical conditions and hence could be used as a reliable indicator in indirect selection for yield. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

The Role of Climate Covariability on Crop Yields in the Conterminous United States

DOE PAGES

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

2016-09-12

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R,more » an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.« less

Correlated Metrics Yield Multimetric Indices with Inferior Performance

EPA Science Inventory

Multimetric indices (MMIs) are widely used to assess the ecological health of freshwater ecosystems. An MMI is a sum of 5-15 standardized, numeric variables (or “metrics”), each representing a different attribute of a biological assemblage. Many researchers believe that highly co...

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Variability in cotton fiber yield, fiber quality, and soil properties in a southeastern coastal plain

USDA-ARS?s Scientific Manuscript database

To maximize profitability, cotton (GossypiumhirsutumL.) producers must attempt to control the quality of the crop while maximizing yield. The objective of this research was to measure the intrinsic variability present in cotton fiber yield and quality. The 0.5-ha experimental site was located in a...

Electrical resistivity tomography to delineate greenhouse soil variability

NASA Astrophysics Data System (ADS)

Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.

2013-03-01

Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

Yield response to variable rate irrigation in corn

USDA-ARS?s Scientific Manuscript database

To investigate the impact of variable rate irrigation on corn yield, twenty plots of corn were laid out under a center pivot variable rate irrigation (VRI) system in an experimental field near Stoneville, MS. The VRI system is equipped with five VRI zone control units, a global positioning system (G...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Genetic divergence in northern Benin sorghum (Sorghum bicolor L. Moench) landraces as revealed by agromorphological traits and selection of candidate genotypes.

PubMed

Dossou-Aminon, Innocent; Loko, Laura Yêyinou; Adjatin, Arlette; Ewédjè, Eben-Ezer B K; Dansi, Alexandre; Rakshit, Sujay; Cissé, Ndiaga; Patil, Jagannath Vishnu; Agbangla, Clément; Sanni, Ambaliou; Akoègninou, Akpovi; Akpagana, Koffi

2015-01-01

Sorghum [Sorghum bicolor (L.) Moench] is an important staple food crop in northern Benin. In order to assess its diversity in Benin, 142 accessions of landraces collected from Northern Benin were grown in Central Benin and characterised using 10 qualitative and 14 quantitative agromorphological traits. High variability among both qualitative and quantitative traits was observed. Grain yield (0.72-10.57 tons/ha), panicle weight (15-215.95 g), days to 50% flowering (57-200 days), and plant height (153.27-636.5 cm) were among traits that exhibited broader variability. Correlations between quantitative traits were determined. Grain yield for instance exhibited highly positive association with panicle weight (r = 0.901, P = 0.000) and 100 seed weight (r = 0.247, P = 0.000). UPGMA cluster analysis classified the 142 accessions into 89 morphotypes. Based on multivariate analysis, twenty promising sorghum genotypes were selected. Among them, AT41, AT14, and AT29 showed early maturity (57 to 66 days to 50% flowering), high grain yields (4.85 to 7.85 tons/ha), and shorter plant height (153.27 to 180.37 cm). The results obtained will help enhancing sorghum production and diversity and developing new varieties that will be better adapted to the current soil and climate conditions in Benin.

Societal resilience to hydroclimatic change in the Roman World

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Bierkens, Marc; Dekker, Stefan

2016-04-01

The Romans were masters of water resource management. They employed sophisticated irrigation techniques alongside a highly integrated food redistribution system that provided stable food supplies under the variable hydroclimatic regime within the Roman World. However, a number of paleoclimate studies have demonstrated hydroclimatic changes during the Roman Period that exceeded the amplitude and persistence of normal climate variability. In particular, there was a shift from warmer and more stable hydroclimatic conditions in the Roman Warm Period (c.250 BC - 250 AD) to cooler and more variable conditions in Late Roman Period (after c.250 AD). In this study we use a socio-hydrological model of the Roman world to explore the impact of hydroclimatic changes between the Roman Warm Period and Late Roman Period on the Roman food production and redistribution system. We calculate crop yields based on temperature and water resource availability using PC Raster Global Water Balance model (PCR-GLOBWB). PCR-GLOBWB is forced with reanalysis climate fields reflecting reconstructions of Roman Warm Period to the Late Roman climate patterns. Cropland areas and settlement patterns are derived from a database of 14,700 Roman settlement sites and crop suitability maps. We simulate food redistribution using a multi-agent food redistribution network with link weights based on Orbis: The Stanford Geospatial Network of the Roman World. Our analysis indicates a reduction in crop yields during the Late Roman Period compared with the Roman Warm Period owing to cooler temperatures. In addition, our simulations indicate that increased hydroclimatic variability decreased the stability of yields in the Late Roman period. Crop yields in the Western Empire are simulated to have been impacted most by the change in climate owing to cooler average temperatures and greater hydroclimatic variability compared with the Eastern part of the Empire. The food redistribution network was essential to buffer against lower and less stable yields in the Late Roman Period. However, the Late Roman Period coincided with a breakdown in the food redistribution network, making the Western Roman Empire particularly vulnerable to changing climate conditions. Our analysis demonstrates a number of important processes that have general implications for water resource management in food production and redistribution systems.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Optimizing Phosphoric Acid plus Hydrogen Peroxide (PHP) Pretreatment on Wheat Straw by Response Surface Method for Enzymatic Saccharification.

PubMed

Qiu, Jingwen; Wang, Qing; Shen, Fei; Yang, Gang; Zhang, Yanzong; Deng, Shihuai; Zhang, Jing; Zeng, Yongmei; Song, Chun

2017-03-01

Wheat straw was pretreated by phosphoric acid plus hydrogen peroxide (PHP), in which temperature, time, and H 3 PO 4 proportion for pretreatment were investigated by using response surface method. Results indicated that hemicellulose and lignin removal positively responded to the increase of pretreatment temperature, H 3 PO 4 proportion, and time. H 3 PO 4 proportion was the most important variable to control cellulose recovery, followed by pretreatment temperature and time. Moreover, these three variables all negatively related to cellulose recovery. Increasing H 3 PO 4 proportion can improve enzymatic hydrolysis; however, reduction on cellulose recovery results in decrease of glucose yield. Extra high temperature or long time for pretreatment was not beneficial to enzymatic hydrolysis and glucose yield. Based on the criterion for minimizing H 3 PO 4 usage and maximizing glucose yield, the optimized pretreatment conditions was 40 °C, 2.0 h, and H 3 PO 4 proportion of 70.2 % (H 2 O 2 proportion of 5.2 %), by which glucose yielded 299 mg/g wheat straw (946.2 mg/g cellulose) after 72-h enzymatic hydrolysis.

Biodegradability study of high-erucic-acid-rapeseed-oil-based lubricant additives

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

Zhou, E.; Crawford, R.L.; Shanahan, A.

1995-12-31

A variety of high-erucic-acid-rapeseed (HEAR)-oil-based lubricants, lubricant additives, and greases were examined for biodegradability at the University of Idaho Center for Hazardous Waste Remediation Research. Two standard biodegradability tests were employed, a currently accepted US Environmental Protection Agency (EPA) protocol and the Sturm Test. As is normal for tests that employ variable inocula such as sewage as a source of microorganisms, these procedures yielded variable results from one repetition to another. However, a general trend of rapid and complete biodegradability of the HEAR-oil-based materials was observed.

Interannual variability of crop water footprint

NASA Astrophysics Data System (ADS)

Tuninetti, M.; Tamea, S.; Laio, F.; Ridolfi, L.

2016-12-01

The crop water footprint, CWF, is a useful tool to investigate the water-food nexus, since it measures the water requirement for crop production. Heterogeneous spatial patterns of climatic conditions and agricultural practices have inspired a flourishing literature on the geographic assessment of CWF, mostly referred to a fixed (time-averaged) period. However, given that both climatic conditions and crop yield may vary substantially over time, also the CWF temporal dynamics need to be addressed. As other studies have done, we base the CWF variability on yield, while keeping the crop evapotranspiration constant over time. As a new contribution, we prove the feasibility of this approach by comparing these CWF estimates with the results obtained with a full model considering variations of crop evapotranspiration: overall, the estimates compare well showing high coefficients of determination that read 0.98 for wheat, 0.97 for rice, 0.97 for maize, and 0.91 for soybean. From this comparison, we derive also the precision of the method, which is around ±10% that is higher than the precision of the model used to evaluate the crop evapotranspiration (i.e., ±30%). Over the period between 1961 and 2013, the CWF of the most cultivated grains has sharply decreased on a global basis (i.e., -68% for wheat, -62% for rice, -66% for maize, and -52% for soybean), mainly driven by enhanced yield values. The higher water use efficiency in crop production implies a reduced virtual displacement of embedded water per ton of traded crop and as a result, the temporal variability of virtual water trade is different if considering constant or time-varying CWF. The proposed yield-based approach to estimate the CWF variability implies low computational costs and requires limited input data, thus, it represents a promising tool for time-dependent water footprint assessments.

Precipitation Storage Efficiency During Fallow in Wheat-Fallow Systems

USDA-ARS?s Scientific Manuscript database

Wheat-fallow production systems arose in order to stabilize widely ranging wheat yields that resulted from highly variable precipitation in the Great Plains. Historically, precipitation storage efficiency (PSE) over the fallow period increased over time as inversion tillage systems used for weed con...

Process Development in the Teaching Laboratory

NASA Astrophysics Data System (ADS)

Klein, Leonard C.; Dana, Susanne M.

1998-06-01

Many experiences in high school and undergraduate laboratories are well-tested cookbook recipes that have already been designed to yield optimal results; the well-known synthesis of aspirin is such an example. In this project for advanced placement or second-year high school chemistry students, students mimic the process development in industrial laboratories by investigating the effect of varying conditions in the synthesis of aspirin. The class decides on criteria that should be explored (quantity of catalyst, temperature of reaction, etc.). The class is then divided into several teams with each team assigned a variable to study. Each team must submit a proposal describing how they will explore the variable before they start their study. After data on yield and purity has been gathered and evaluated, students discuss which method is most desirable, based on their agreed-upon criteria. This exercise provides an opportunity for students to review many topics from the course (rate of reaction, limiting reagents, Beer's Law) while participating in a cooperative exercise designed to imitate industrial process development.

Variable screening via quantile partial correlation

PubMed Central

Ma, Shujie; Tsai, Chih-Ling

2016-01-01

In quantile linear regression with ultra-high dimensional data, we propose an algorithm for screening all candidate variables and subsequently selecting relevant predictors. Specifically, we first employ quantile partial correlation for screening, and then we apply the extended Bayesian information criterion (EBIC) for best subset selection. Our proposed method can successfully select predictors when the variables are highly correlated, and it can also identify variables that make a contribution to the conditional quantiles but are marginally uncorrelated or weakly correlated with the response. Theoretical results show that the proposed algorithm can yield the sure screening set. By controlling the false selection rate, model selection consistency can be achieved theoretically. In practice, we proposed using EBIC for best subset selection so that the resulting model is screening consistent. Simulation studies demonstrate that the proposed algorithm performs well, and an empirical example is presented. PMID:28943683

Bottom Pressure Tides Along a Line in the Southeast Atlantic Ocean and Comparisons with Satellite Altimetry

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Byrne, Deidre A.

2010-01-01

Seafloor pressure records, collected at 11 stations aligned along a single ground track of the Topex/Poseidon and Jason satellites, are analyzed for their tidal content. With very low background noise levels and approximately 27 months of high-quality records, tidal constituents can be estimated with unusually high precision. This includes many high-frequency lines up through the seventh-diurnal band. The station deployment provides a unique opportunity to compare with tides estimated from satellite altimetry, point by point along the satellite track, in a region of moderately high mesoscale variability. That variability can significantly corrupt altimeter-based tide estimates, even with 17 years of data. A method to improve the along-track altimeter estimates by correcting the data for nontidal variability is found to yield much better agreement with the bottom-pressure data. The technique should prove useful in certain demanding applications, such as altimetric studies of internal tides.

Model-assisted forest yield estimation with light detection and ranging

Treesearch

Jacob L. Strunk; Stephen E. Reutebuch; Hans-Erik Andersen; Peter J. Gould; Robert J. McGaughey

2012-01-01

Previous studies have demonstrated that light detection and ranging (LiDAR)-derived variables can be used to model forest yield variables, such as biomass, volume, and number of stems. However, the next step is underrepresented in the literature: estimation of forest yield with appropriate confidence intervals. It is of great importance that the procedures required for...

Isolation of fish skin and bone gelatin from tilapia (Oreochromis niloticus): Response surface approach

NASA Astrophysics Data System (ADS)

Arpi, N.; Fahrizal; Novita, M.

2018-03-01

In this study, gelatin from fish collagen, as one of halal sources, was extracted from tilapia (Oreochromis niloticus) skin and bone, by using Response Surface Methodology to optimize gelatin extraction conditions. Concentrations of alkaline NaOH and acid HCl, in the pretreatment process, and temperatures in extraction process were chosen as independent variables, while dependent variables were yield, gel strength, and emulsion activity index (EAI). The result of investigation showed that lower NaOH pretreatment concentrations provided proper pH extraction conditions which combine with higher extraction temperatures resulted in high gelatin yield. However, gelatin emulsion activity index increased proportionally to the decreased in NaOH concentrations and extraction temperatures. No significant effect of the three independent variables on the gelatin gel strength. RSM optimization process resulted in optimum gelatin extraction process conditions using alkaline NaOH concentration of 0.77 N, acid HCl of 0.59 N, and extraction temperature of 66.80 °C. The optimal solution formula had optimization targets of 94.38%.

Relationship between mozzarella yield and milk composition, processing factors, and recovery of whey constituents.

PubMed

Sales, D C; Rangel, A H N; Urbano, S A; Freitas, Alfredo R; Tonhati, Humberto; Novaes, L P; Pereira, M I B; Borba, L H F

2017-06-01

Our aim was to identify the relationship between mozzarella cheese yield and buffalo milk composition, processing factors, and recovery of whey constituents. A production of 30 batches of mozzarella cheese at a dairy industry in northeast Brazil (Rio Grande do Norte) was monitored between March and November 2015. Mozzarella yield and 32 other variables were observed for each batch, and divided into 3 groups: milk composition variables (12); variables involved in the cheesemaking process (14); and variables for recovery of whey constituents (6). Data were analyzed using descriptive statistics, Pearson correlation, and principal component analysis. Most of the correlations between milk composition variables and between the variables of the manufacturing processes were not significant. Significant correlations were mostly observed between variables for recovery of whey constituents. Yield only showed significant correlation with time elapsed between curd cuttings and age of the starter culture, and it showed greater association with age of the starter culture, time elapsed between curd cuttings, and during stretching, as well as with milk pH and density. Thus, processing factors and milk characteristics are closely related to dairy efficiency in mozzarella manufacturing. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

Modified Lipid Extraction Methods for Deep Subsurface Shale

PubMed Central

Akondi, Rawlings N.; Trexler, Ryan V.; Pfiffner, Susan M.; Mouser, Paula J.; Sharma, Shikha

2017-01-01

Growing interest in the utilization of black shales for hydrocarbon development and environmental applications has spurred investigations of microbial functional diversity in the deep subsurface shale ecosystem. Lipid biomarker analyses including phospholipid fatty acids (PLFAs) and diglyceride fatty acids (DGFAs) represent sensitive tools for estimating biomass and characterizing the diversity of microbial communities. However, complex shale matrix properties create immense challenges for microbial lipid extraction procedures. Here, we test three different lipid extraction methods: modified Bligh and Dyer (mBD), Folch (FOL), and microwave assisted extraction (MAE), to examine their ability in the recovery and reproducibility of lipid biomarkers in deeply buried shales. The lipid biomarkers were analyzed as fatty acid methyl esters (FAMEs) with the GC-MS, and the average PL-FAME yield ranged from 67 to 400 pmol/g, while the average DG-FAME yield ranged from 600 to 3,000 pmol/g. The biomarker yields in the intact phospholipid Bligh and Dyer treatment (mBD + Phos + POPC), the Folch, the Bligh and Dyer citrate buffer (mBD-Cit), and the MAE treatments were all relatively higher and statistically similar compared to the other extraction treatments for both PLFAs and DGFAs. The biomarker yields were however highly variable within replicates for most extraction treatments, although the mBD + Phos + POPC treatment had relatively better reproducibility in the consistent fatty acid profiles. This variability across treatments which is associated with the highly complex nature of deeply buried shale matrix, further necessitates customized methodological developments for the improvement of lipid biomarker recovery. PMID:28790998

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

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.

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.

Bioreactor process parameter screening utilizing a Plackett-Burman design for a model monoclonal antibody.

PubMed

Agarabi, Cyrus D; Schiel, John E; Lute, Scott C; Chavez, Brittany K; Boyne, Michael T; Brorson, Kurt A; Khan, Mansoora; Read, Erik K

2015-06-01

Consistent high-quality antibody yield is a key goal for cell culture bioprocessing. This endpoint is typically achieved in commercial settings through product and process engineering of bioreactor parameters during development. When the process is complex and not optimized, small changes in composition and control may yield a finished product of less desirable quality. Therefore, changes proposed to currently validated processes usually require justification and are reported to the US FDA for approval. Recently, design-of-experiments-based approaches have been explored to rapidly and efficiently achieve this goal of optimized yield with a better understanding of product and process variables that affect a product's critical quality attributes. Here, we present a laboratory-scale model culture where we apply a Plackett-Burman screening design to parallel cultures to study the main effects of 11 process variables. This exercise allowed us to determine the relative importance of these variables and identify the most important factors to be further optimized in order to control both desirable and undesirable glycan profiles. We found engineering changes relating to culture temperature and nonessential amino acid supplementation significantly impacted glycan profiles associated with fucosylation, β-galactosylation, and sialylation. All of these are important for monoclonal antibody product quality. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

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

Development of heat and drought related extreme weather events and their effect on winter wheat yields in Germany

NASA Astrophysics Data System (ADS)

Lüttger, Andrea B.; Feike, Til

2018-04-01

Climate change constitutes a major challenge for high productivity in wheat, the most widely grown crop in Germany. Extreme weather events including dry spells and heat waves, which negatively affect wheat yields, are expected to aggravate in the future. It is crucial to improve the understanding of the spatiotemporal development of such extreme weather events and the respective crop-climate relationships in Germany. Thus, the present study is a first attempt to evaluate the historic development of relevant drought and heat-related extreme weather events from 1901 to 2010 on county level (NUTS-3) in Germany. Three simple drought indices and two simple heat stress indices were used in the analysis. A continuous increase in dry spells over time was observed over the investigated periods from 1901-1930, 1931-1960, 1961-1990 to 2001-2010. Short and medium dry spells, i.e., precipitation-free periods longer than 5 and 8 days, respectively, increased more strongly compared to longer dry spells (longer than 11 days). The heat-related stress indices with maximum temperatures above 25 and 28 °C during critical wheat growth phases showed no significant increase over the first three periods but an especially sharp increase in the final 1991-2010 period with the increases being particularly pronounced in parts of Southwestern Germany. Trend analysis over the entire 110-year period using Mann-Kendall test revealed a significant positive trend for all investigated indices except for heat stress above 25 °C during flowering period. The analysis of county-level yield data from 1981 to 2010 revealed declining spatial yield variability and rather constant temporal yield variability over the three investigated (1981-1990, 1991-2000, and 2001-2010) decades. A clear spatial gradient manifested over time with variability in the West being much smaller than in the east of Germany. Correlating yield variability with the previously analyzed extreme weather indices revealed strong spatiotemporal fluctuations in explanatory power of the different indices over all German counties and the three time periods. Over the 30 years, yield deviations were increasingly well correlated with heat and drought-related indices, with the number of days with maximum temperature above 25 °C during anthesis showing a sharp increase in explanatory power over entire Germany in the final 2001-2010 period.

Population pressure and agricultural productivity in Bangladesh.

PubMed

Chaudhury, R H

1983-01-01

The relationship between population pressure or density and agricultural productivity is examined by analyzing the changes in the land-man ratio and the changes in the level of land yield in the 17 districts of Bangladesh from 1961-64 and 1974-77. The earlier years were pre-Green Revolution, whereas in the later years new technology had been introduced in some parts of the country. Net sown area, value of total agricultural output, and number of male agricultural workers were the main variables. For the country as a whole, agricultural output grew by 1.2%/year during 1961-64 to 1974-77, while the number of male agricultural workers grew at 1.5%/year. The major source of agricultural growth during the 1960s was found to be increased land-yield associated with a higher ratio of labor to land. The findings imply that a more intensified pattern of land use, resulting in both higher yield and higher labor input/unit of land, is the main source of growth of output and employment in agriculture. There is very little scope for extending the arable area in Bangladesh; increased production must come from multiple cropping, especially through expansion of irrigation and drainage, and from increases in per acre yields, principly through adoption of high yield variants, which explained 87% of the variation in output per acre during the 1970s. Regional variation in output was also associated with variation in cropping intensity and proportion of land given to high yield variants. There is considerable room for modernizing agricultural technology in Bangladesh: in 1975-76 less than 9% of total crop land was irrigated and only 12% of total acreage was under high yield variants. The adoption of new food-grain technology and increased use of high yield variants in Bangladesh's predominantly subsistence-based agriculture would require far-reaching institutional and organizational changes and more capital. Without effective population control, expansion of area under high yield variants would not improve the employment situation in the foreseeable future.

Identification of saline soils with multi-year remote sensing of crop yields

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

Lobell, D; Ortiz-Monasterio, I; Gurrola, F C

2006-10-17

Soil salinity is an important constraint to agricultural sustainability, but accurate information on its variation across agricultural regions or its impact on regional crop productivity remains sparse. We evaluated the relationships between remotely sensed wheat yields and salinity in an irrigation district in the Colorado River Delta Region. The goals of this study were to (1) document the relative importance of salinity as a constraint to regional wheat production and (2) develop techniques to accurately identify saline fields. Estimates of wheat yield from six years of Landsat data agreed well with ground-based records on individual fields (R{sup 2} = 0.65).more » Salinity measurements on 122 randomly selected fields revealed that average 0-60 cm salinity levels > 4 dS m{sup -1} reduced wheat yields, but the relative scarcity of such fields resulted in less than 1% regional yield loss attributable to salinity. Moreover, low yield was not a reliable indicator of high salinity, because many other factors contributed to yield variability in individual years. However, temporal analysis of yield images showed a significant fraction of fields exhibited consistently low yields over the six year period. A subsequent survey of 60 additional fields, half of which were consistently low yielding, revealed that this targeted subset had significantly higher salinity at 30-60 cm depth than the control group (p = 0.02). These results suggest that high subsurface salinity is associated with consistently low yields in this region, and that multi-year yield maps derived from remote sensing therefore provide an opportunity to map salinity across agricultural regions.« less

Reliability of reservoir firm yield determined from the historical drought of record

USGS Publications Warehouse

Archfield, S.A.; Vogel, R.M.

2005-01-01

The firm yield of a reservoir is typically defined as the maximum yield that could have been delivered without failure during the historical drought of record. In the future, reservoirs will experience droughts that are either more or less severe than the historical drought of record. The question addressed here is what the reliability of such systems will be when operated at the firm yield. To address this question, we examine the reliability of 25 hypothetical reservoirs sited across five locations in the central and western United States. These locations provided a continuous 756-month streamflow record spanning the same time interval. The firm yield of each reservoir was estimated from the historical drought of record at each location. To determine the steady-state monthly reliability of each firm-yield estimate, 12,000-month synthetic records were generated using the moving-blocks bootstrap method. Bootstrapping was repeated 100 times for each reservoir to obtain an average steady-state monthly reliability R, the number of months the reservoir did not fail divided by the total months. Values of R were greater than 0.99 for 60 percent of the study reservoirs; the other 40 percent ranged from 0.95 to 0.98. Estimates of R were highly correlated with both the level of development (ratio of firm yield to average streamflow) and average lag-1 monthly autocorrelation. Together these two predictors explained 92 percent of the variability in R, with the level of development alone explaining 85 percent of the variability. Copyright ASCE 2005.

Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures

PubMed Central

Welch, Jarrod R.; Vincent, Jeffrey R.; Auffhammer, Maximilian; Moya, Piedad F.; Dobermann, Achim; Dawe, David

2010-01-01

Data from farmer-managed fields have not been used previously to disentangle the impacts of daily minimum and maximum temperatures and solar radiation on rice yields in tropical/subtropical Asia. We used a multiple regression model to analyze data from 227 intensively managed irrigated rice farms in six important rice-producing countries. The farm-level detail, observed over multiple growing seasons, enabled us to construct farm-specific weather variables, control for unobserved factors that either were unique to each farm but did not vary over time or were common to all farms at a given site but varied by season and year, and obtain more precise estimates by including farm- and site-specific economic variables. Temperature and radiation had statistically significant impacts during both the vegetative and ripening phases of the rice plant. Higher minimum temperature reduced yield, whereas higher maximum temperature raised it; radiation impact varied by growth phase. Combined, these effects imply that yield at most sites would have grown more rapidly during the high-yielding season but less rapidly during the low-yielding season if observed temperature and radiation trends at the end of the 20th century had not occurred, with temperature trends being more influential. Looking ahead, they imply a net negative impact on yield from moderate warming in coming decades. Beyond that, the impact would likely become more negative, because prior research indicates that the impact of maximum temperature becomes negative at higher levels. Diurnal temperature variation must be considered when investigating the impacts of climate change on irrigated rice in Asia. PMID:20696908

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

PubMed

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

2013-12-01

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

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.

Climatic variability effects on summer cropping systems of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Capa-Morocho, M.; Rodríguez-Fonseca, B.; Ruiz-Ramos, M.

2012-04-01

Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004). This paper analyses the evolution of the yield anomalies of irrigated maize in several representative agricultural locations in Spain with contrasting temperature and precipitation regimes and compare it to the evolution of different patterns of climate variability, extending the methodology of Porter and Semenov (2005). To simulate maize yields observed daily data of radiation, maximum and minimum temperature and precipitation were used. These data were obtained from the State Meteorological Agency of Spain (AEMET). Time series of simulated maize yields were computed with CERES-maize model for periods ranging from 22 to 49 years, depending on the observed climate data available for each location. The computed standardized anomalies yields were projected on different oceanic and atmospheric anomalous fields and the resulting patterns were compared with a set of documented patterns from the National Oceanic and Atmospheric Administration (NOAA). The results can be useful also for climate change impact assessment, providing a scientific basis for selection of climate change scenarios where combined natural and forced variability represent a hazard for agricultural production. Interpretation of impact projections would also be enhanced.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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.

Using artificial neural network and satellite data to predict rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-09-01

Rice production in Bangladesh is a crucial part of the national economy and providing about 70 percent of an average citizen's total calorie intake. The demand for rice is constantly rising as the new populations are added in every year in Bangladesh. Due to the increase in population, the cultivation land decreases. In addition, Bangladesh is faced with production constraints such as drought, flooding, salinity, lack of irrigation facilities and lack of modern technology. To maintain self sufficiency in rice, Bangladesh will have to continue to expand rice production by increasing yield at a rate that is at least equal to the population growth until the demand of rice has stabilized. Accurate rice yield prediction is one of the most important challenges in managing supply and demand of rice as well as decision making processes. Artificial Neural Network (ANN) is used to construct a model to predict Aus rice yield in Bangladesh. Advanced Very High Resolution Radiometer (AVHRR)-based remote sensing satellite data vegetation health (VH) indices (Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) are used as input variables and official statistics of Aus rice yield is used as target variable for ANN prediction model. The result obtained with ANN method is encouraging and the error of prediction is less than 10%. Therefore, prediction can play an important role in planning and storing of sufficient rice to face in any future uncertainty.

Investment risk in bioenergy crops

DOE PAGES

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia; ...

2015-11-18

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Investment risk in bioenergy crops

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

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Contemporary suspended sediment dynamics within two partly glacierized mountain drainage basins in western Norway (Erdalen and Bødalen, inner Nordfjord)

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Laute, Katja; Storms, Joep E. A.

2017-06-01

This paper focuses on environmental controls, spatiotemporal variability and rates of contemporary fluvial suspended sediment transport in the neighboring, partly glacierized and steep Erdalen (79.5 km2) and Bødalen (60.1 km2) drainage basins in the fjord landscape of the inner Nordfjord in western Norway. Field work, including extended samplings and measurements, was conducted since 2004 in Erdalen and since 2008 in Bødalen. The distinct intra- and inter-annual temporal variability of suspended sediment transport found is mostly controlled by meteorological events, with most suspended sediment transport occurring during pluvial events in autumn (September-November), followed by mostly thermally determined glacier melt in summer (July-August), and by mostly thermally determined snowmelt in spring (April-June). Extreme rainfall events (> 70 mm d- 1) in autumn can trigger significant debris-flow activity that can cause significant transfers of suspended sediments from ice-free surface areas with sedimentary covers into main stream channels and is particularly important for fluvial suspended sediment transport. In years with occurring relevant debris-flow activity the total annual drainage-basin wide suspended sediment yields are strongly determined by these single extreme events. The proportion of glacier coverage, followed by steepness of slopes, and degree of vegetation cover in ice-free surface areas with sedimentary covers are the main controls for the detected spatial variability of suspended sediment yields. The contemporary sediment supply from glacierized surface areas and the Jostedalsbreen ice cap through different defined outlet glaciers shows a high spatial variability. The fact that the mean annual suspended sediment yield of Bødalen is with 31.3 t km- 2 yr- 1 almost twice as high as the mean annual suspended sediment yield of Erdalen (16.4 t km- 2 yr- 1) is to a large extent explained by the higher proportion of glacier coverage in Bødalen (38% of the drainage basin surface area) as compared to Erdalen (18% of the drainage basin surface area) and by a significantly higher sediment yield from the glacierized area of the Bødalen drainage basin compared to the glacierized surface area in Erdalen. When looking at the total annual mass of suspended sediments being fluvially exported from both entire drainage basin systems, the total amount of suspended sediments coming from the ice-free drainage basin surface areas altogether dominates over the total amount of suspended sediments coming from the glacierized surface area of both drainage basins. Drainage-basin wide annual suspended sediment yields are rather low when compared with yields of other partly glacierized drainage basin systems in Norway and in other cold climate environments worldwide, which is mainly due to the high resistance of the predominant gneisses towards glacial erosion and weathering, the altogether only small amounts of sediments being available within the entire drainage basin systems, the stable and nearly closed vegetation cover in the ice-free surface areas with sedimentary covers, and the efficiency of proglacial lakes in trapping sediments supplied by defined outlet glaciers. Both contemporary and long-term suspended sediment yields are altogether supply-limited. Contemporary suspended sediment transport accounts for nearly two-thirds of the total fluvial transport and, accordingly, plays an important role within the sedimentary budgets of the entire Erdalen and Bødalen drainage basins.

Forage yield, weed suppression and fertilizer nitrogen replacement value (FNRV) of alfalfa-tall fescue mixtures

USDA-ARS?s Scientific Manuscript database

Adding plant diversity to forage systems may help growers deal with increasing fertilizer costs and a more variable climate. Maintaining highly diverse forage mixtures in forage-livestock production is difficult and may warrant a closer reexamination of simpler grass-legume mixtures to achieve simi...

Evaluating variable rate fungicide applications for control of Sclerotinia

USDA-ARS?s Scientific Manuscript database

Oklahoma peanut growers continue to try to increase yields and reduce input costs. Perhaps the largest input in a peanut crop is fungicide applications. This is especially true for areas in the state that have high disease pressure from Sclerotinia. On average, a single fungicide application cost...

Variability associated with screening for common scab and verticillium wilt in potato

USDA-ARS?s Scientific Manuscript database

Common Scab (CS) and Verticillium Wilt (VW) are caused by the soilborne bacteria Streptomyces scabies, and fungi, Verticillium dahliae and V. albo-atrum, respectively, in potato (Solanum tuberosum). Both diseases result in biological and/or marketable yield loss and are tested in fields with high di...

Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes

NASA Astrophysics Data System (ADS)

Zipper, Samuel C.; Qiu, Jiangxiao; Kucharik, Christopher J.

2016-09-01

Maximizing agricultural production on existing cropland is one pillar of meeting future global food security needs. To close crop yield gaps, it is critical to understand how climate extremes such as drought impact yield. Here, we use gridded, daily meteorological data and county-level annual yield data to quantify meteorological drought sensitivity of US maize and soybean production from 1958 to 2007. Meteorological drought negatively affects crop yield over most US crop-producing areas, and yield is most sensitive to short-term (1-3 month) droughts during critical development periods from July to August. While meteorological drought is associated with 13% of overall yield variability, substantial spatial variability in drought effects and sensitivity exists, with central and southeastern US becoming increasingly sensitive to drought over time. Our study illustrates fine-scale spatiotemporal patterns of drought effects, highlighting where variability in crop production is most strongly associated with drought, and suggests that management strategies that buffer against short-term water stress may be most effective at sustaining long-term crop productivity.

Efficient heterologous expression and secretion in Aspergillus oryzae of a llama variable heavy-chain antibody fragment V(HH) against EGFR.

PubMed

Okazaki, Fumiyoshi; Aoki, Jun-ichi; Tabuchi, Soichiro; Tanaka, Tsutomu; Ogino, Chiaki; Kondo, Akihiko

2012-10-01

We have constructed a filamentous fungus Aspergillus oryzae that secretes a llama variable heavy-chain antibody fragment (V(HH)) that binds specifically to epidermal growth factor receptor (EGFR) in a culture medium. A major improvement in yield was achieved by fusing the V(HH) with a Taka-amylase A signal sequence (sTAA) and a segment of 28 amino acids from the N-terminal region of Rhizopus oryzae lipase (N28). The yields of secreted, immunologically active anti-EGFR V(HH) reached 73.8 mg/1 in a Sakaguchi flask. The V(HH) fragments were released from the sTAA or N28 proteins by an indigenous A. oryzae protease during cultivation. The purified recombinant V(HH) fragment was specifically recognized and could bind to the EGFR with a high affinity.

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.

Seasonal and latitudinal acclimatization of cardiac transcriptome responses to thermal stress in porcelain crabs, Petrolisthes cinctipes.

PubMed

Stillman, Jonathon H; Tagmount, Abderrahmane

2009-10-01

Central predictions of climate warming models include increased climate variability and increased severity of heat waves. Physiological acclimatization in populations across large-scale ecological gradients in habitat temperature fluctuation is an important factor to consider in detecting responses to climate change related increases in thermal fluctuation. We measured in vivo cardiac thermal maxima and used microarrays to profile transcriptome heat and cold stress responses in cardiac tissue of intertidal zone porcelain crabs across biogeographic and seasonal gradients in habitat temperature fluctuation. We observed acclimatization dependent induction of heat shock proteins, as well as unknown genes with heat shock protein-like expression profiles. Thermal acclimatization had the largest effect on heat stress responses of extensin-like, beta tubulin, and unknown genes. For these genes, crabs acclimatized to thermally variable sites had higher constitutive expression than specimens from low variability sites, but heat stress dramatically induced expression in specimens from low variability sites and repressed expression in specimens from highly variable sites. Our application of ecological transcriptomics has yielded new biomarkers that may represent sensitive indicators of acclimatization to habitat temperature fluctuation. Our study also has identified novel genes whose further description may yield novel understanding of cellular responses to thermal acclimatization or thermal stress.

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

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.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Pancreatic islet isolation variables in non-human primates (rhesus macaques).

PubMed

Andrades, P; Asiedu, C K; Gansuvd, B; Inusah, S; Goodwin, K J; Deckard, L A; Jargal, U; Thomas, J M

2008-07-01

Non-human primates (NHPs) are important preclinical models for pancreatic islet transplantation (PIT) because of their close phylogenetic and immunological relationship with humans. However, low availability of NHP tissue, long learning curves and prohibitive expenses constrain the consistency of isolated NHP islets for PIT studies. To advance preclinical studies, we attempted to identify key variables that consistently influence the quantity and quality of NHP islets. Seventy-two consecutive pancreatic islet isolations from rhesus macaques were reviewed retrospectively. A scaled down, semi-automated islet isolation method was used, and monkeys with streptozotocin-induced diabetes, weighing 3-7 kg, served as recipients for allotransplantation. We analysed the effects of 22 independent variables grouped as donor factors, surgical factors and isolation technique factors. Islet yields, success of isolation and transplantation results were used as quantitative and qualitative outcomes. In the multivariate analysis, variables that significantly affected islet yield were the type of monkey, pancreas preservation, enzyme lot and volume of enzyme delivered. The variables associated with successful isolation were the enzyme lot and volume delivered. The transplant result was correlated with pancreas preservation, enzyme lot, endotoxin levels and COBE collection method. Islet quantity and quality are highly variable between isolations. The data reviewed suggest that future NHP isolations should use bilayer preservation, infuse more than 80 ml of Liberase into the pancreas, collect non-fractioned tissue from the COBE, and strictly monitor for infection.

Assessment of chemical and genetic variability in Tanacetum gracile accessions collected from cold desert of Western Himalaya.

PubMed

Mahajan, Vidushi; Chouhan, Rekha; Kitchlu, Surinder; Bindu, Kushal; Koul, Sushma; Singh, Bikarma; Bedi, Yashbir S; Gandhi, Sumit G

2018-06-01

Genetic diversity is essential for survival and adaptation of high altitude plants such as those of Tanacetum genus, which are constantly exposed to environmental stress. We collected flowering shoots of ten accessions of Tanacetum gracile Hook.f. & Thomson (Asteraceae) (Tg 1-Tg 10), from different regions of cold desert of Western Himalaya. Chemical profile of the constituents, as inferred from GC-MS, exhibited considerable variability. Percentage yield of essential oil ranged from 0.2 to 0.75% (dry-weight basis) amongst different accessions. Tg 1 and Tg 6 were found to produce high yields of camphor (46%) and lavandulol (41%), respectively. Alpha -phellendrene, alpha -bisabool, p -cymene and chamazulene were the main oil components in other accessions. Genetic variability among the accessions was studied using RAPD markers as well as by sequencing and analyzing nuclear 18S rDNA, and plastid rbcL and matK loci. The polymorphic information content (PIC) of RAPD markers ranged from 0.18 to 0.5 and the analysis clustered the accessions into two major clades. The present study emphasized the importance of survey, collection, and conservation of naturally existing chemotypes of medicinal and aromatic plants, considering their potential use in aroma and pharmaceutical industry.

An analysis of yield stability in a conservation agriculture system

USDA-ARS?s Scientific Manuscript database

Climate models predict increasing growing-season weather variability, with negative consequences for crop production. Maintaining agricultural productivity despite variability in weather (i.e., crop yield stability) will be critical to meeting growing global demand. Conservation agriculture is an ...

Temporal variability in chlorophyll fluorescence of back-reef corals in Ofu, American Samoa

USGS Publications Warehouse

Piniak, G.A.; Brown, E.K.

2009-01-01

Change in the yield of chlorophyll a fluorescence is a common indicator of thermal stress in corals. The present study reports temporal variability in quantum yield measurements for 10 coral species in Ofu, American Samoa - a place known to experience elevated and variable seawater temperatures. In winter, the zooxanthellae generally had higher dark-adapted maximum quantum yield (F v/Fm), higher light- adapted effective quantum yield (??F/F'm), and lower relative electron transport rates (rETR) than in the summer. Temporal changes appeared unrelated to the expected bleaching sensitivity of corals. All species surveyed, with the exception of Montipora grisea, demonstrated significant temporal changes in the three fluorescence parameters. Fluorescence responses were influenced by the microhabitat - temporal differences in fluorescence parameters were usually observed in the habitat with a more variable temperature regime (pool 300), while differences in Fv/Fm between species were observed only in the more environmentally stable habitat (pool 400). Such species-specific responses and microhabitat variability should be considered when attempting to determine whether observed in situ changes are normal seasonal changes or early signs of bleaching. ?? 2009 Marine Biological Laboratory.

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.

Contribution of morphoagronomic traits to grain yield and earliness in grain sorghum.

PubMed

da Silva, K J; Teodoro, P E; de Menezes, C B; Júlio, M P M; de Souza, V F; da Silva, M J; Pimentel, L D; Borém, A

2017-05-04

Given the importance of selecting lines to obtain hybrids, we aimed to verify the relationship between morphological traits that can be used as the criteria for the selection of sorghum lines with high grain yield and earliness. A total of 18 traits were evaluated in 160 sorghum elite lines, in an incomplete block design with two replicates. A correlation network was used to graphically express the estimates of phenotypic and genotypic correlations between the traits. Two path analyses were processed, the first considering grain yield and the second considering flowering as the principle dependent variable. In general, most of the variation in the grain yield and flowering of sorghum lines was explained by the traits evaluated. Selecting sorghum lines with greater width of the third leaf blade from flag leaf, panicle weight, and panicle harvest index might lead to increased grain yield, and selecting sorghum genotypes with higher plant height might lead to reduced earliness and increased grain yield. Thus, the results suggest the establishment of selection indices aiming at simultaneously increasing the grain yield and earliness in sorghum genotypes.

Enzymatic extraction of pectin from artichoke (Cynara scolymus L.) by-products using Celluclast®1.5L.

PubMed

Sabater, Carlos; Corzo, Nieves; Olano, Agustín; Montilla, Antonia

2018-06-15

The aim of this study was to optimise pectin extraction from artichoke by-products with Celluclast ® 1.5L using an experimental design analysed by response-surface methodology (RSM). The variables optimised were artichoke by-product powder concentration (2-7%, X 1 ), enzyme dose (2.2-13.3 U g -1 , X 2 ) and extraction time (6-24 h, X 3 ). The variables studied were galacturonic acid (GalA) (R 2 93.9) and pectic neutral sugars (R 2 92.8) content and pectin yield (R 2 88.6). In the optimum extraction conditions (X 1  = 6.5%; X 2  = 10.1 U g -1 ; X 3  = 27.2 h), pectin yield was 176 mgg -1 dry matter (DM). Considering 27.2 h of treatment as the +α value given by the design, the extraction time was increased up to 48 h obtaining a yield of 221 mg g -1 DM. The enzymatic method optimised allows obtaining artichoke pectin with good yield, high GalA (720 mg g -1 DM) and arabinose (127.6mgg -1 DM) contents and degree of methylation of 19.5%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Yield and quality attributes of faba bean inbred lines grown under marginal environmental conditions of Sudan.

PubMed

Gasim, Seif; Hamad, Solafa A A; Abdelmula, Awadalla; Mohamed Ahmed, Isam A

2015-11-01

Faba beans (Vicia faba L.) represent an essential source of food protein for many people in Sudan, especially those who cannot afford to buy animal meat. The demand for faba bean seeds is greatly increased in recent years, and consequently its production area was extended southward where the climate is marginally suitable. Therefore, this study was aimed to evaluate seed yield and nutritional quality of five faba bean inbred lines grown under marginal environmental conditions of Sudan. The inbred lines have considerable (P ≤ 0.05) variability in yield and yield components, and seed chemical composition. The mean carbohydrate content was very high (501.1 g kg(-1)) and negatively correlated with seed yield, whereas the average protein content was relatively high (253.1 g kg(-1)) and positively correlated with seed yield. Globulin was the significant fraction (613.5 g kg(-1)protein) followed by albumin (200.2 g kg(-1)protein). Biplot analysis indicates that inbred lines Hudeiba/93-S5 and Ed-damar-S5 outscore other lines in terms of seed yield and nutritional quality. This study demonstrates that Hudeiba/93-S5 and Ed-damar-S5 are useful candidates in faba bean breeding program to terminate the protein deficiency malnutrition and provide healthy and nutritious meal for people living in subtropical areas.

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

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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.

Framework for making better predictions by directly estimating variables' predictivity.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2016-12-13

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the [Formula: see text]-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the [Formula: see text]-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the [Formula: see text]-score on real data to demonstrate the statistic's predictive performance on sample data. We conjecture that using the partition retention and [Formula: see text]-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired.

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain

NASA Astrophysics Data System (ADS)

Chen, Chao; Baethgen, Walter E.; Wang, Enli; Yu, Qiang

2011-12-01

Grain yields of wheat and maize were obtained from national statistics and simulated with an agricultural system model to investigate the effects of historical climate variability and irrigation on crop yield in the North China Plain (NCP). Both observed and simulated yields showed large temporal and spatial variability due to variations in climate and irrigation supply. Wheat yield under full irrigation (FI) was 8 t ha-1 or higher in 80% of seasons in the north, it ranged from 7 to 10 t ha-1 in 90% of seasons in central NCP, and less than 9 t ha-1 in 85% of seasons in the south. Reduced irrigation resulted in increased crop yield variability. Wheat yield under supplemental irrigation, i.e., to meet only 50% of irrigation water requirement [supplemental irrigation (SI)] ranged from 2.7 to 8.8 t ha-1 with the maximum frequency of seasons having the range of 4-6 t ha-1 in the north, 4-7 t ha-1 in central NCP, and 5-8 t ha-1 in the south. Wheat yield under no irrigation (NI) was lower than 1 t ha-1 in about 50% of seasons. Considering the NCP as a whole, simulated maize yield under FI ranged from 3.9 to 11.8 t ha-1 with similar frequency distribution in the range of 6-11.8 t ha-1 with the interval of 2 t ha-1. It ranged from 0 to 11.8 t ha-1, uniformly distributed into the range of 4-10 t ha-1 under SI, and NI. The results give an insight into the levels of regional crop production affected by climate and water management strategies.

Sputtering by the Solar Wind: Effects of Variable Composition

NASA Technical Reports Server (NTRS)

Killen, R. M.; Arrell, W. M.; Sarantos, M.; Delory, G. T.

2011-01-01

It has long been recognized that solar wind bombardment onto exposed surfaces in the solar system will produce an energetic component to the exospheres about those bodies. Laboratory experiments have shown that there is no increase in the sputtering yield caused by highly charged heavy ions for metallic and for semiconducting surfaces, but the sputter yield can be noticeably increased in the case of a good insulating surface. Recently measurements of the solar wind composition have become available. It is now known that the solar wind composition is highly dependent on the origin of the particular plasma. Using the measured composition of the slow wind, fast wind, solar energetic particle (SEP) population, and coronal mass ejection (CME), broken down into its various components, we have estimated the total sputter yield for each type of solar wind. Whereas many previous calculations of sputtering were limited to the effects of proton bombardment. we show that the heavy ion component. especially the He++ component. can greatly enhance the total sputter yield during times when the heavy ion population is enhanced. We will discuss sputtering of both neutrals and ions.

Behavior of Three Metallic Alloys Under Combined Axial-Shear Stress at 650 C

NASA Technical Reports Server (NTRS)

Colaiuta, Jason F.; Lerch, Bradley (Technical Monitor)

2001-01-01

Three materials, Inconel 718, Haynes 188, and 316 stainless steel, were tested under an axial-torsional stress state at 650 C. The objective of this study was to quantify the evolution of the material while in the viscoplastic domain. Initial and subsequent yield surfaces were experimentally determined to quantify hardening. Subsequent yield surfaces (yield surfaces taken after a preload) had a well-defined front side, in the prestrain direction, but a poorly defined back side, opposite the prestrain direction. Subsequent yield surfaces exhibited isotropic hardening by expansion of the yield surface, kinematic hardening by translation of the yield surface, and distortional hardening by flattening of the yield surface in the direction opposite to the last prestrain. An existing yield function capable of representing isotropic, kinematic, and distortional hardening was used to fit each yield surface. Four variables are used to describe each surface. These variables evolve as the material state changes and have been regressed to the yield surface data.

Calculations Supporting Management Zones

USDA-ARS?s Scientific Manuscript database

Since the early 1990’s the tools of precision farming (GPS, yield monitors, soil sensors, etc.) have documented how spatial and temporal variability are important factors impacting crop yield response. For precision farming, variability can be measured then used to divide up a field so that manageme...

Lean Principles and Defense Information Technology Acquisition: An Investigation of the Determinants of Successful Application

ERIC Educational Resources Information Center

Haley, M.

2013-01-01

The purpose of this study was to investigate whether or not there have been successful applications of lean manufacturing principles in highly variable defense IT environments. Specifically, the study assessed if implementation of the lean philosophies by a defense organization yielded repeatable, predictable results in software release schedules…

Stability Criteria for Differential Equations with Variable Time Delays

ERIC Educational Resources Information Center

Schley, D.; Shail, R.; Gourley, S. A.

2002-01-01

Time delays are an important aspect of mathematical modelling, but often result in highly complicated equations which are difficult to treat analytically. In this paper it is shown how careful application of certain undergraduate tools such as the Method of Steps and the Principle of the Argument can yield significant results. Certain delay…

Skip-row Planting Patterns Stabilize Corn Grain Yields in the Central Great Plains

USDA-ARS?s Scientific Manuscript database

The highly variable climate of the Central Great Plains makes dryland corn (Zea mays) production a risky enterprise. Twenty-three field trials were conducted across the Central Great Plains from 2004 through 2006 to quantify the effect of various skip-row planting patterns and plant populations on g...

Demonstrating the Financial Benefit of Human Resource Development: Status and Update on the Theory and Practice.

ERIC Educational Resources Information Center

Swanson, Richard A.

1998-01-01

A research review identified findings about the financial analysis method, forecasting of the financial benefits of human resource development (HRD), and recent financial analysis research: (1) HRD embedded in a performance improvement framework yielded high return on investment; and (2) HRD interventions focused on performance variables forecast…

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Associations of Self-Presentation on Facebook with Mental Health and Personality Variables: A Systematic Review.

PubMed

Twomey, Conal; O'Reilly, Gary

2017-10-01

Many investigations of the associations of self-presentation on Facebook with mental health and personality variables exist, but their findings have not yet been synthetized. We therefore carried out a narrative synthesis of 21 observational studies (combined N = 7,573) obtained from a systematic search of four academic databases. Significant self-presentation associations were yielded for self-esteem, perceived social support, social anxiety, well-being, depression, bipolar/mania, stress, self-consciousness, and insecure attachment. Significant associations were also yielded for all of the big five personality variables and narcissism. The clearest trends-based on the number of times significant associations were yielded across included studies-were as follows: (1) inauthentic self-presentation was consistently associated with low self-esteem and elevated levels of social anxiety; (2) inauthentic self-presentation was consistently more likely to occur in people high in neuroticism and narcissism; and (3) authentic/positive self-presentation was consistently associated with increased levels of self-esteem and perceived social support. The assessment of online self-presentation may offer clinicians important insights into how clients are functioning in relation to various domains of mental health and personality. For example, clients who present inauthentic versions of themselves on Facebook could be experiencing social anxiety or have maladaptive personality traits such as neuroticism and narcissism, all of which could be targeted in intervention.

Rainfall Variability, Adaptation through Irrigation, and Sustainable Management of Water Resources in India

NASA Astrophysics Data System (ADS)

Fishman, R.

2013-12-01

Most studies of the impact of climate change on agriculture account for shifts in temperature and total seasonal (or monthly) precipitation. However, climate change is also projected to increase intra-seasonal precipitation variability in many parts of the world. To provide first estimates of the potential impact, I paired daily rainfall and rice yield data during the period 1970-2004, from across India, where about a fifth of the world's rice is produced, and yields have always been highly dependent on the erratic monsoon rainfall. Multivariate regression models revealed that the number of rainless days during the wet season has a statistically robust negative impact on rice yields that exceeds that of total seasonal rainfall. Moreover, a simulation of climate change impacts found that the negative impact of the projected increase in the number of rainless days will trump the positive impact of the projected increase in total precipitation, and reverse the net precipitation effect on rice production from positive (+3%) to negative (-10%). The results also indicate that higher irrigation coverage is correlated with reduced sensitivity to rainfall variability, suggesting the expansion of irrigation can effectively adapt agriculture to these climate change impacts. However, taking into account limitations on water resource availability in India, I calculate that under current irrigation practices, sustainable use of water can mitigate less than a tenth of the impact.

The value of seasonal forecasting and crop mix adaptation to climate variability for agriculture under climate change

NASA Astrophysics Data System (ADS)

Choi, H. S.; Schneider, U.; Schmid, E.; Held, H.

2012-04-01

Changes to climate variability and frequency of extreme weather events are expected to impose damages to the agricultural sector. Seasonal forecasting and long range prediction skills have received attention as an option to adapt to climate change because seasonal climate and yield predictions could improve farmers' management decisions. The value of seasonal forecasting skill is assessed with a crop mix adaptation option in Spain where drought conditions are prevalent. Yield impacts of climate are simulated for six crops (wheat, barely, cotton, potato, corn and rice) with the EPIC (Environmental Policy Integrated Climate) model. Daily weather data over the period 1961 to 1990 are used and are generated by the regional climate model REMO as reference period for climate projection. Climate information and its consequent yield variability information are given to the stochastic agricultural sector model to calculate the value of climate information in the agricultural market. Expected consumers' market surplus and producers' revenue is compared with and without employing climate forecast information. We find that seasonal forecasting benefits not only consumers but also producers if the latter adopt a strategic crop mix. This mix differs from historical crop mixes by having higher shares of crops which fare relatively well under climate change. The corresponding value of information is highly sensitive to farmers' crop mix choices.

Precalving and early lactation factors that predict milk casein and fertility in the transition dairy cow.

PubMed

Rodney, Rachael M; Hall, Jenianne K; Westwood, Charlotte T; Celi, Pietro; Lean, Ian J

2016-09-01

Multiparous Holstein cows (n=82) of either high or low genetic merit (GM) (for milk fat + protein yield) were allocated to 1 of 2 diets in a 2×2 factorial design. Diets differed in the ratio of rumen-undegradable protein (RUP) to rumen-degradable protein (37% RUP vs. 15% RUP) and were fed from 21 d precalving to 150 days in milk. This study evaluated the effects of these diets and GM on concentrations of milk casein (CN) variants and aimed to identify precalving and early lactation variables that predict milk CN and protein yield and composition and fertility of dairy cows. It explored the hypothesis that low milk protein content is associated with lower fertility and extended this hypothesis to also evaluate the association of CN contents with fertility. Yields (kg/d) for CN variants were 0.49 and 0.45 of α-CN, 0.38 and 0.34 of β-CN, 0.07 and 0.06 for κ-CN, and 0.10 and 0.09 of γ-CN for high- and low-RUP diets, respectively. Increased RUP increased milk, CN, and milk protein yields. Increased GM increased milk protein and γ-CN yields and tended to increase milk CN yield. The effects of indicator variables on CN variant yields and concentrations were largely consistent, with higher body weight and α-amino nitrogen resulting in higher yields, but lower concentrations. An increase in cholesterol was associated with decreased CN variant concentrations, and disease lowered CN variant yield. A diet high in RUP increased proportion of first services that resulted in pregnancy from 41 to 58%. Increased precalving metabolizable protein (MP) balance decreased the proportion of first services that resulted in pregnancy when evaluated in a model containing CN percentage, milk protein yield, diet, and GM. This finding suggests that the positive effects of increasing dietary RUP on fertility may be curvilinear because cows with a very positive MP balance before calving were less fertile than those with a lower, but positive, MP balance. Prepartum MP balance was important to production and reproductive outcomes, but surprisingly, metabolizable energy balance was not. The hazard of pregnancy in the first 150 d of lactation was 28% lower in cows producing milk with the lowest quartile of protein percentage compared with cows with milk in the upper 3 quartiles. Milk CN percentage was positively associated with improved pregnancy at first service. This study demonstrates the importance of protein metabolism to reproductive performance of the dairy cow. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity.

PubMed

Van Hertem, T; Maltz, E; Antler, A; Romanini, C E B; Viazzi, S; Bahr, C; Schlageter-Tello, A; Lokhorst, C; Berckmans, D; Halachmi, I

2013-07-01

The objective of this study was to develop and validate a mathematical model to detect clinical lameness based on existing sensor data that relate to the behavior and performance of cows in a commercial dairy farm. Identification of lame (44) and not lame (74) cows in the database was done based on the farm's daily herd health reports. All cows were equipped with a behavior sensor that measured neck activity and ruminating time. The cow's performance was measured with a milk yield meter in the milking parlor. In total, 38 model input variables were constructed from the sensor data comprising absolute values, relative values, daily standard deviations, slope coefficients, daytime and nighttime periods, variables related to individual temperament, and milk session-related variables. A lame group, cows recognized and treated for lameness, to not lame group comparison of daily data was done. Correlations between the dichotomous output variable (lame or not lame) and the model input variables were made. The highest correlation coefficient was obtained for the milk yield variable (rMY=0.45). In addition, a logistic regression model was developed based on the 7 highest correlated model input variables (the daily milk yield 4d before diagnosis; the slope coefficient of the daily milk yield 4d before diagnosis; the nighttime to daytime neck activity ratio 6d before diagnosis; the milk yield week difference ratio 4d before diagnosis; the milk yield week difference 4d before diagnosis; the neck activity level during the daytime 7d before diagnosis; the ruminating time during nighttime 6d before diagnosis). After a 10-fold cross-validation, the model obtained a sensitivity of 0.89 and a specificity of 0.85, with a correct classification rate of 0.86 when based on the averaged 10-fold model coefficients. This study demonstrates that existing farm data initially used for other purposes, such as heat detection, can be exploited for the automated detection of clinically lame animals on a daily basis as well. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Effects of ecological and conventional agricultural intensification practices on maize yields in sub-Saharan Africa under potential climate change

NASA Astrophysics Data System (ADS)

Folberth, Christian; Yang, Hong; Gaiser, Thomas; Liu, Junguo; Wang, Xiuying; Williams, Jimmy; Schulin, Rainer

2014-04-01

Much of Africa is among the world’s regions with lowest yields in staple food crops, and climate change is expected to make it more difficult to catch up in crop production in particular in the long run. Various agronomic measures have been proposed for lifting agricultural production in Africa and to adapt it to climate change. Here, we present a projection of potential climate change impacts on maize yields under different intensification options in Sub-Saharan Africa (SSA) using an agronomic model, GIS-based EPIC (GEPIC). Fallow and nutrient management options taken into account are (a) conventional intensification with high mineral N supply and a bare fallow, (b) moderate mineral N supply and cowpea rotation, and (c) moderate mineral N supply and rotation with a fast growing N fixing tree Sesbania sesban. The simulations suggest that until the 2040s rotation with Sesbania will lead to an increase in yields due to increasing N supply besides improving water infiltration and soils’ water holding capacity. Intensive cultivation with a bare fallow or an herbaceous crop like cowpea in the rotation is predicted to result in lower yields and increased soil erosion during the same time span. However, yields are projected to decrease in all management scenarios towards the end of the century, should temperature increase beyond critical thresholds. The results suggest that the effect of eco-intensification as a sole means of adapting agriculture to climate change is limited in Sub-Saharan Africa. Highly adverse temperatures would rather have to be faced by improved heat tolerant cultivars, while strongly adverse decreases in precipitation would have to be faced by expanding irrigation where feasible. While the evaluation of changes in agro-environmental variables like soil organic carbon, erosion, and soil humidity hints that these are major factors influencing climate change resilience of the field crop, no direct relationship between these factors, crop yields, and changes in climate variables could be identified. This will need further detailed studies at the field and regional scale.

Relationships between surface solar radiation and wheat yield in Spain

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, Sara; Rodriguez-Puebla, Concepción

2017-04-01

Here we examine the role of solar radiation to describe wheat-yield variability in Spain. We used Partial Least Square regression to capture the modes of surface solar radiation that drive wheat-yield variability. We will show that surface solar radiation introduces the effects of teleconnection patterns on wheat yield and also it is associated with drought and diurnal temperature range. We highlight the importance of surface solar radiation to obtain models for wheat-yield projections because it could reduce uncertainty with respect to the projections based on temperatures and precipitation variables. In addition, the significance of the model based on surface solar radiation is greater than the previous one based on drought and diurnal temperature range (Hernandez-Barrera et al., 2016). According to our results, the increase of solar radiation over Spain for 21st century could force a wheat-yield decrease (Hernandez-Barrera et al., 2017). Hernandez-Barrera S., Rodríguez-Puebla C. and Challinor A.J. 2016 Effects of diurnal temperature range and drought on wheat yield in Spain. Theoretical and Applied Climatology. DOI: 10.1007/s00704-016-1779-9 Hernandez-Barrera S., Rodríguez-Puebla C. 2017 Wheat yield in Spain and associated solar radiation patterns. International Journal of Climatology. DOI: 10.1002/joc.4975

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

PubMed Central

Hawkins, Ed; Fricker, Thomas E; Challinor, Andrew J; Ferro, Christopher A T; Kit Ho, Chun; Osborne, Tom M

2013-01-01

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target. PMID:23504849

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

PubMed

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

2010-12-01

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

Yielding physically-interpretable emulators - A Sparse PCA approach

NASA Astrophysics Data System (ADS)

Galelli, S.; Alsahaf, A.; Giuliani, M.; Castelletti, A.

2015-12-01

Projection-based techniques, such as Principal Orthogonal Decomposition (POD), are a common approach to surrogate high-fidelity process-based models by lower order dynamic emulators. With POD, the dimensionality reduction is achieved by using observations, or 'snapshots' - generated with the high-fidelity model -, to project the entire set of input and state variables of this model onto a smaller set of basis functions that account for most of the variability in the data. While reduction efficiency and variance control of POD techniques are usually very high, the resulting emulators are structurally highly complex and can hardly be given a physically meaningful interpretation as each basis is a projection of the entire set of inputs and states. In this work, we propose a novel approach based on Sparse Principal Component Analysis (SPCA) that combines the several assets of POD methods with the potential for ex-post interpretation of the emulator structure. SPCA reduces the number of non-zero coefficients in the basis functions by identifying a sparse matrix of coefficients. While the resulting set of basis functions may retain less variance of the snapshots, the presence of a few non-zero coefficients assists in the interpretation of the underlying physical processes. The SPCA approach is tested on the reduction of a 1D hydro-ecological model (DYRESM-CAEDYM) used to describe the main ecological and hydrodynamic processes in Tono Dam, Japan. An experimental comparison against a standard POD approach shows that SPCA achieves the same accuracy in emulating a given output variable - for the same level of dimensionality reduction - while yielding better insights of the main process dynamics.

Genetic architecture, inter-relationship and selection criteria for yield improvement in rice (Oryza sativa L.).

PubMed

Yadav, S K; Pandey, P; Kumar, B; Suresh, B G

2011-05-01

This study has been conducted to determine the extent of genetic association between yield of Rice (Oryza sativa L.) and its components. The present experiment was carried out with 40 Rice (Oryza sativa L.) genotypes which were evaluated in a randomized block design with 3 replications during wet season of 2007 and 2008. Results showed that sufficient amount of variability was found in the entire gene pool for all traits studied. Higher magnitude of genotypic and phenotypic coefficients of variation was recorded for seed yield, harvest index, biological yield, number of spikelets per panicle, flag leaf length, plant height and number of tillers indicates that these characters are least influence by environment. High heritability coupled with high genetic advance as percent of mean was registered for seed yield, harvest index, number of spikelets per panicle, biological yield and flag leaf length, suggesting preponderance of additive gene action in the expression of these characters. Grain yield was significantly and positively associated with harvest index, number of tillers per hill, number of panicle per plant, panicle length, number of spikelet's per panicle and test weight at both genotypic and phenotypic levels. Path coefficient analysis revealed that harvest index, biological yield, number of tillers per hill, panicle length, number of spikelets per panicle, plant height and test weight had direct positive effect on seed yield, indicating these are the main contributors to yield. From this study it may be concluded that harvest index, number of tillers per hill, panicle length and number of spikelet per panicle and test weight are the most important characters that contributed directly to yield. Thus, these characters may serve selection criteria for improving genetic potential of rice.

Variation in nutrients formulated and nutrients supplied on 5 California dairies.

PubMed

Rossow, H A; Aly, S S

2013-01-01

Computer models used in ration formulation assume that nutrients supplied by a ration formulation are the same as the nutrients presented in front of the cow in the final ration. Deviations in nutrients due to feed management effects such as dry matter changes (i.e., rain), loading, mixing, and delivery errors are assumed to not affect delivery of nutrients to the cow and her resulting milk production. To estimate how feed management affects nutrients supplied to the cow and milk production, and determine if nutrients can serve as indexes of feed management practices, weekly total mixed ration samples were collected and analyzed for 4 pens (close-up cows, fresh cows, high-milk-producing, and low-milk-producing cows, if available) for 7 to 12 wk on 5 commercial California dairies. Differences among nutrient analyses from these samples and nutrients from the formulated rations were analyzed by PROC MIXED of SAS (SAS Institute Inc., Cary, NC). Milk fat and milk protein percentages did not vary as much [coefficient of variation (CV) = 18 to 33%] as milk yield (kg; CV = 16 to 47 %) across all dairies and pens. Variability in nutrients delivered were highest for macronutrient fat (CV = 22%), lignin (CV = 15%), and ash (CV = 11%) percentages and micronutrients Fe (mg/kg; CV = 48%), Na (%; CV = 42%), and Zn (mg/kg; CV = 38%) for the milking pens across all dairies. Partitioning of the variability in random effects of nutrients delivered and intraclass correlation coefficients showed that variability in lignin percentage of TMR had the highest correlation with variability in milk yield and milk fat percentage, followed by fat and crude protein percentages. But, variability in ash, fat, and lignin percentages of total mixed ration had the highest correlation with variability in milk protein percentage. Therefore, lignin, fat, and ash may be the best indices of feed management to include effects of variability in nutrients on variability in milk yield, milk fat, and milk protein percentages in ration formulation models. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Navigation bronchoscopy for diagnosis and small nodule location

PubMed Central

Muñoz-Largacha, Juan A.; Litle, Virginia R.

2017-01-01

Lung cancer continues to be the most common cause of cancer death. Screening programs for high risk patients with the use of low-dose computed tomography (CT) has led to the identification of small lung lesions that were difficult to identify using previous imaging modalities. Electromagnetic navigational bronchoscopy (ENB) is a novel technique that has shown to be of great utility during the evaluation of small, peripheral lesions, that would otherwise be challenging to evaluate with conventional bronchoscopy. The diagnostic yield of navigational bronchoscopy however is highly variable, with reports ranging from 59% to 94%. This variability suggests that well-defined selection criteria and standardized protocols for the use of ENB are lacking. Despite this variability, we believe that this technique is a useful tool evaluating small peripheral lung lesions when patients are properly selected. PMID:28446971

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.

A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

NASA Astrophysics Data System (ADS)

Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

2012-12-01

Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter crop, however, has a moderately strong correlation with wet season start date (ρ = .577). In addition, winter crop yield (ton/ha) has a moderate correlation with wet season end date (ρ = .624), number of rainy days during the wet season (ρ = .492), and during the dry season (ρ = .410). Future work will assess which other factors influence cropping intensity (e.g. access to irrigation among many other), since a complex interplay of bio-physical and socio-economic factors governs the decision-making at the farm-level, ultimately leading to inter-annual variability in cropping intensity and/or yield.

Exploring Niches for Short-Season Grain Legumes in Semi-Arid Eastern Kenya - Coping with the Impacts of Climate Variability.

PubMed

Sennhenn, Anne; Njarui, Donald M G; Maass, Brigitte L; Whitbread, Anthony M

2017-01-01

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean ( Phaseolus vulgaris L.), cowpea ( Vigna unguiculata (L.) Walp.] and lablab [ Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha -1 . An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter production, reaching very high grain yields at high potential sites (3,000 kg ha -1 ) but being highly susceptible to in-season drought. Lablab seemed to be best adapted to dry environments. Its canopy architecture appeared to be best in compromising between the investment in biomass as a prerequisite to accumulate grain yield by minimizing water loss through soil evaporation and crop transpiration. This lead to grain yields of up to 2,000 kg ha -1 at high potential sites and >1,000 kg ha -1 at low potential sites. The variance of observed and simulated WUE was high and no clear dependency on total rainfall alone was observed for all three short-season grain legumes, highlighting that pattern of water use is also important in determining final WUE biomass and WUE grain . Mean WUE grain was lowest for cowpea (1.5-3.5 kg grain ha -1 mm -1 ) and highest for lablab (5-7 kg grain ha -1 mm -1 ) reflecting the high susceptibility to drought of cowpea and the good adaptation to dry environments of lablab. Results highlight that, based on specific morphological, phonological, and physiological characteristics, the three short-season grain legumes follow different strategies to cope with climate variability. The climate-smart site-specific utilization of the three legumes offers promising options to design more resilient and productive farming systems in semi-arid Eastern Kenya.

Exploring Niches for Short-Season Grain Legumes in Semi-Arid Eastern Kenya — Coping with the Impacts of Climate Variability

PubMed Central

Sennhenn, Anne; Njarui, Donald M. G.; Maass, Brigitte L.; Whitbread, Anthony M.

2017-01-01

Climate variability is the major risk to agricultural production in semi-arid agroecosystems and the key challenge to sustain farm livelihoods for the 500 million people who inhabit these areas worldwide. Short-season grain legumes have great potential to address this challenge and help to design more resilient and productive farming systems. However, grain legumes display a great diversity and differ widely in growth, development, and resource use efficiency. Three contrasting short season grain legumes common bean (Phaseolus vulgaris L.), cowpea (Vigna unguiculata (L.) Walp.] and lablab [Lablab purpureus (L.) Sweet] were selected to assess their agricultural potential with respect to climate variability and change along the Machakos-Makueni transect in semi-arid Eastern Kenya. This was undertaken using measured data [a water response trial conducted during 2012/13 and 2013/14 in Machakos, Kenya] and simulated data using the Agricultural Production System sIMulator (APSIM). The APSIM crop model was calibrated and validated to simulate growth and development of short-season grain legumes in semi-arid environments. Water use efficiency (WUE) was used as indicator to quantify the production potential. The major traits of adaptation include early flowering and pod and seed set before the onset of terminal drought. Early phenology together with adapted canopy architecture allowed more optimal water use and greater partitioning of dry matter into seed (higher harvest index). While common bean followed a comparatively conservative strategy of minimizing water loss through crop transpiration, the very short development time and compact growth habit limited grain yield to rarely exceed 1,000 kg ha−1. An advantage of this strategy was relatively stable yields independent of in-crop rainfall or season length across the Machakos-Makueni transect. The growth habit of cowpea in contrast minimized water loss through soil evaporation with rapid ground cover and dry matter production, reaching very high grain yields at high potential sites (3,000 kg ha−1) but being highly susceptible to in-season drought. Lablab seemed to be best adapted to dry environments. Its canopy architecture appeared to be best in compromising between the investment in biomass as a prerequisite to accumulate grain yield by minimizing water loss through soil evaporation and crop transpiration. This lead to grain yields of up to 2,000 kg ha−1 at high potential sites and >1,000 kg ha−1 at low potential sites. The variance of observed and simulated WUE was high and no clear dependency on total rainfall alone was observed for all three short-season grain legumes, highlighting that pattern of water use is also important in determining final WUEbiomass and WUEgrain. Mean WUEgrain was lowest for cowpea (1.5–3.5 kggrain ha−1 mm−1) and highest for lablab (5–7 kggrain ha−1 mm−1) reflecting the high susceptibility to drought of cowpea and the good adaptation to dry environments of lablab. Results highlight that, based on specific morphological, phonological, and physiological characteristics, the three short-season grain legumes follow different strategies to cope with climate variability. The climate-smart site-specific utilization of the three legumes offers promising options to design more resilient and productive farming systems in semi-arid Eastern Kenya. PMID:28536585

Vertical distributions and diel migrations of Euthecosomata in the northwest Sargasso Sea

NASA Astrophysics Data System (ADS)

Wormuth, John H.

1981-12-01

Vertical distributions and seasonal variations in abundance of nine abundant or frequent pteropod species or subspecies in the northwest Sargasso Sea are described. Factor analyses yielded two groups, diel migrators and non-migrators. In terms of water column abundances, tows taken in August and November are similar, as are tows in December and April. Most species show significant within-species agreement in depth distribution over the year but high variability in abundance. Regression analyses using environmental parameters as independent variables show significant correlations of species abundances with temperature.

Spatio-temporal Variability of Stemflow Volume in a Beech-Yellow Poplar Forest in Relation to Tree Species and Size

NASA Astrophysics Data System (ADS)

Levia, D. F.; van Stan, J. T.; Mage, S.; Hauske, P. W.

2009-05-01

Stemflow is a localized point input at the base of trees that can account for more than 10% of the incident gross precipitation in deciduous forests. Despite the fact that stemflow has been documented to be of hydropedological importance, affecting soil moisture patterns, soil erosion, soil chemistry, and the distribution of understory vegetation, our current understanding of the temporal variability of stemflow yield is poor. The aim of the present study, conducted in a beech-yellow poplar forest in northeastern Maryland (39°42'N, 75°50'W), was to better understand the temporal and variability of stemflow production from Fagus grandifolia Ehrh. (American beech) and Liriodendron tulipifera L. (yellow poplar) in relation to meteorological conditions and season in order to better assess its importance to canopy-soil interactions. The experimental plot had a stand density of 225 trees/ha, a stand basal area of 36.8 sq. m/ha, a mean dbh of 40.8 cm, and a mean tree height of 27.8 m. The stand leaf area index (LAI) is 5.3. Yellow poplar and beech constitute three- quarters of the stand basal area. Using a high resolution (5 min) sequential stemflow sampling network, consisting of tipping-bucket gauges interfaced with a Campbell CR1000 datalogger, the temporal variability of stemflow yield was examined. Beech produced significantly larger stemflow amounts than yellow poplar. The amount of stemflow produced by individual beech trees in 5 minute intervals reached three liters. Stemflow yield and funneling ratios decreased with increasing rain intensity. Temporal variability of stemflow inputs were affected by the nature of incident gross rainfall, season, tree species, tree size, and bark water storage capacity. Stemflow was greater during the leafless period than full leaf period. Stemflow yield was greater for larger beech trees and smaller yellow poplar trees, owing to differences in bark water storage capacity. The findings of this study indicate that stemflow has a detectable affect on soil moisture patterning and the hydraulic conductivity of forest soils.

Spatio-temporal response of maize yield to edaphic and meteorological conditions in a saline farmland

USDA-ARS?s Scientific Manuscript database

Spatio-temporal variability of crop production strongly depends on soil heterogeneity, meteorological conditions, and their interaction. Canopy reflectance can be used to describe crop status and yield spatial variability. The objectives of this work were to understand the spatio-temporal variabilit...

Yield response to landscape position under variable N for irrigated corn

USDA-ARS?s Scientific Manuscript database

Variable nutrient and water supply can result in spatial and temporal variation in crop yield within a given agricultural field. For the western Corn Belt, irrigated corn accounts for 58% of total annual corn production with the majority grown in Nebraska. Although irrigation decreases temporal yi...

Encapsulation Processing and Manufacturing Yield Analysis

NASA Technical Reports Server (NTRS)

Willis, P. B.

1984-01-01

The development of encapsulation processing and a manufacturing productivity analysis for photovoltaic cells are discussed. The goals were: (1) to understand the relationships between both formulation variables and process variables; (2) to define conditions required for optimum performance; (3) to predict manufacturing yield; and (4) to provide documentation to industry.

Variable Rate Application of Nematicides on Cotton Fields: A Promising Site-Specific Management Strategy

USDA-ARS?s Scientific Manuscript database

Cotton (Gossypium hirsutum L.) lint yield losses associated with southern root-knot nematode [Meloidogyne incognita] (RKN) parasitism have increased during the last 20 years. The hypothesis that variable rate application of nematicides can reduce yield losses and reduce the risk for under- and over-...

Encapsulation processing and manufacturing yield analysis

NASA Astrophysics Data System (ADS)

Willis, P. B.

1984-10-01

The development of encapsulation processing and a manufacturing productivity analysis for photovoltaic cells are discussed. The goals were: (1) to understand the relationships between both formulation variables and process variables; (2) to define conditions required for optimum performance; (3) to predict manufacturing yield; and (4) to provide documentation to industry.

Argentina wheat yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.

Argentina corn yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.

Selection and Clonal Propagation of High Artemisinin Genotypes of Artemisia annua

PubMed Central

Wetzstein, Hazel Y.; Porter, Justin A.; Janick, Jules; Ferreira, Jorge F. S.; Mutui, Theophilus M.

2018-01-01

Artemisinin, produced in the glandular trichomes of Artemisia annua L. is a vital antimalarial drug effective against Plasmodium falciparum resistant to quinine-derived medicines. Although work has progressed on the semi-synthetic production of artemisinin, field production of A. annua remains the principal commercial source of the compound. Crop production of artemisia must be increased to meet the growing worldwide demand for artemisinin combination therapies (ACTs) to treat malaria. Grower artemisinin yields rely on plants generated from seeds from open-pollinated parents. Although selection has considerably increased plant artemisinin concentration in the past 15 years, seed-generated plants have highly variable artemisinin content that lowers artemisinin yield per hectare. Breeding efforts to produce improved F1 hybrids have been hampered by the inability to produce inbred lines due to self-incompatibility. An approach combining conventional hybridization and selection with clonal propagation of superior genotypes is proposed as a means to enhance crop yield and artemisinin production. Typical seed-propagated artemisia plants produce less than 1% (dry weight) artemisinin with yields below 25 kg/ha. Genotypes were identified producing high artemisinin levels of over 2% and possessing improved agronomic characteristics such as high leaf area and shoot biomass production. Field studies of clonally-propagated high-artemisinin plants verified enhanced plant uniformity and an estimated gross primary productivity of up to 70 kg/ha artemisinin, with a crop density of one plant m-2. Tissue culture and cutting protocols for the mass clonal propagation of A. annua were developed for shoot regeneration, rooting, acclimatization, and field cultivation. Proof of concept studies showed that both tissue culture-regenerated plants and rooted cutting performed better than plants derived from seed in terms of uniformity, yield, and consistently high artemisinin content. Use of this technology to produce plants with homogeneously-high artemisinin can help farmers markedly increase the artemisinin yield per cultivated area. This would lead to increased profit to farmers and decreased prices of ACT. PMID:29636758

Alterations to Functional Analysis Methodology to Clarify the Functions of Low Rate, High Intensity Problem Behavior

PubMed Central

Davis, Barbara J; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results. PMID:23326628

Alterations to functional analysis methodology to clarify the functions of low rate, high intensity problem behavior.

PubMed

Davis, Barbara J; Kahng, Sungwoo; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results.

Framework for making better predictions by directly estimating variables’ predictivity

PubMed Central

Chernoff, Herman; Lo, Shaw-Hwa

2016-01-01

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the I-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the I-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data. We conjecture that using the partition retention and I-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired. PMID:27911830

Supporting Climatic Trends of Corn and Soybean Production in the USA

NASA Astrophysics Data System (ADS)

Mishra, V.; Cherkauer, K. A.; Verdin, J. P.

2010-12-01

The United States of America (USA) is a major source of corn and soybeans, producing about 39 percent of the world’s corn and 50 percent of world’s soybean supply. The north central states, including parts of the Midwestern US and the Great Plains form what is commonly described as the “Corn Belt” and consist of the most productive grain growing region in the United States. Changes in climate, including precipitation and temperature, are being observed throughout the world, and the Corn Belt region of the US is not immune posing a potential threat to global food security. We conducted a retrospective analysis of observed climate variables and crop production statistics to evaluate if observed climatic trends are having a positive or negative effect on corn and soybean production in the US. We selected climate indices based on gridded daily precipitation, maximum and minimum air temperature data from the National Climatic Data Center (NCDC) for the period of 1920-2009 and for 13 states in the Corn Belt region. We used the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for different periods overlapping the important seasons for crop growths, such as the planting (April-May), grain-filling (June-August), and harvesting (September -October) seasons. We estimated the seasonal average of maximum and minimum daily temperatures to identify the historic trends and variability in air temperature during the key crop-growth seasons. Extreme warm temperatures can affect crop growth and yields adversely; therefore, cumulative maximum air temperature above the 90th percentiles (e.g. Cumulative Heat Index) was estimated for each growing period. We evaluated historic trends and variability of areal extents of severe or extreme droughts along with the areal extents facing the high cumulative heat stress. Our results showed that climatic extremes (e.g. droughts and heat stress) that occurred during the period of June - August (JJA), affected the yields of corn and soybeans most severely. High moisture and low heat stress during the JJA period favored crop yields, while low moisture and high heat conditions during the planting season (April-May) increased yields. Results also indicated that this part of the US is trending towards lower heat stress and drought extents, and higher moisture conditions during the JJA period. Therefore, in future, if the present trends persist, we expect the climate will more supportive of increased corn and soybean yields.

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.

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

PubMed Central

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

2014-01-01

Climate warming is projected to affect forest water yields but the effects are expected to vary. We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long-term experimental catchments across Canada and the United States over 5-year cool and warm periods. Using the theoretical framework of the Budyko curve, we calculated the effects of climate warming on the annual partitioning of precipitation (P) into evapotranspiration (ET) and water yield. Deviation (d) was defined as a catchment's change in actual ET divided by P [AET/P; evaporative index (EI)] coincident with a shift from a cool to a warm period – a positive d indicates an upward shift in EI and smaller than expected water yields, and a negative d indicates a downward shift in EI and larger than expected water yields. Elasticity was defined as the ratio of interannual variation in potential ET divided by P (PET/P; dryness index) to interannual variation in the EI – high elasticity indicates low d despite large range in drying index (i.e., resilient water yields), low elasticity indicates high d despite small range in drying index (i.e., nonresilient water yields). Although the data needed to fully evaluate ecosystems based on these metrics are limited, we were able to identify some characteristics of response among forest types. Alpine sites showed the greatest sensitivity to climate warming with any warming leading to increased water yields. Conifer forests included catchments with lowest elasticity and stable to larger water yields. Deciduous forests included catchments with intermediate elasticity and stable to smaller water yields. Mixed coniferous/deciduous forests included catchments with highest elasticity and stable water yields. Forest type appeared to influence the resilience of catchment water yields to climate warming, with conifer and deciduous catchments more susceptible to climate warming than the more diverse mixed forest catchments. PMID:24757012

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

Xiong, Wei; Balkovic, Juraj; van der Velde, M.

Crop models are increasingly used to assess impacts of climate change/variability and management practices on productivity and environmental performance of alternative cropping systems. Calibration is an important procedure to improve reliability of model simulations, especially for large area applications. However, global-scale crop model calibration has rarely been exercised due to limited data availability and expensive computing cost. Here we present a simple approach to calibrate Environmental Policy Integrated Climate (EPIC) model for a global implementation of rice. We identify four parameters (potential heat unit – PHU, planting density – PD, harvest index – HI, and biomass energy ratio – BER)more » and calibrate them regionally to capture the spatial pattern of reported rice yield in 2000. Model performance is assessed by comparing simulated outputs with independent FAO national data. The comparison demonstrates that the global calibration scheme performs satisfactorily in reproducing the spatial pattern of rice yield, particularly in main rice production areas. Spatial agreement increases substantially when more parameters are selected and calibrated, but with varying efficiencies. Among the parameters, PHU and HI exhibit the highest efficiencies in increasing the spatial agreement. Simulations with different calibration strategies generate a pronounced discrepancy of 5–35% in mean yields across latitude bands, and a small to moderate difference in estimated yield variability and yield changing trend for the period of 1981–2000. Present calibration has little effects in improving simulated yield variability and trends at both regional and global levels, suggesting further works are needed to reproduce temporal variability of reported yields. This study highlights the importance of crop models’ calibration, and presents the possibility of a transparent and consistent up scaling approach for global crop simulations given current availability of global databases of weather, soil, crop calendar, fertilizer and irrigation management information, and reported yield.« less

Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

2017-09-01

Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

Use of multi-temporal UAV-derived imagery for estimating individual tree growth in Pinus pinea stands

Treesearch

Juan Guerra-Hernández; Eduardo González-Ferreiro; Vicente Monleon; Sonia Faias; Margarida Tomé; Ramón Díaz-Varela

2017-01-01

High spatial resolution imagery provided by unmanned aerial vehicles (UAVs) can yield accurate and efficient estimation of tree dimensions and canopy structural variables at the local scale. We flew a low-cost, lightweight UAV over an experimental Pinus pinea L. plantation (290 trees distributed over 16 ha with different fertirrigation treatments)...

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.

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.

Selecting AGN through Variability in SN Datasets

NASA Astrophysics Data System (ADS)

Boutsia, K.; Leibundgut, B.; Trevese, D.; Vagnetti, F.

2010-07-01

Variability is a main property of Active Galactic Nuclei (AGN) and it was adopted as a selection criterion using multi epoch surveys conducted for the detection of supernovae (SNe). We have used two SN datasets. First we selected the AXAF field of the STRESS project, centered in the Chandra Deep Field South where, besides the deep X-ray surveys also various optical catalogs exist. Our method yielded 132 variable AGN candidates. We then extended our method including the dataset of the ESSENCE project that has been active for 6 years, producing high quality light curves in the R and I bands. We obtained a sample of ˜4800 variable sources, down to R=22, in the whole 12 deg2 ESSENCE field. Among them, a subsample of ˜500 high priority AGN candidates was created using as secondary criterion the shape of the structure function. In a pilot spectroscopic run we have confirmed the AGN nature for nearly all of our candidates.

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2017-10-01

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

State-specific enhancement of Cl+ and Cl- desorption for SiCl4 adsorbed on a Si(100) surface following Cl 2 p and Si 2 p core-level excitations.

PubMed

Chen, J M; Lu, K T

2001-04-02

State-specific desorption for SiCl4 adsorbed on a Si(100) surface at approximately 90 K with variable coverage following the Cl 2p and Si 2p core-level excitations has been investigated using synchrotron radiation. The Cl+ yields show a significant enhancement following the Cl 2p-->8a*1 excitation. The Cl- yields are notably enhanced at the 8a*1 resonance at both Cl 2p and Si 2p edges. The enhancement of the Cl- yield occurs through the formation of highly excited states of the adsorbed molecules. These results provide some new dissociation processes from adsorbates on surfaces via core-level excitation.

High-Volume Production of Lightweight Multijunction Solar Cells

NASA Technical Reports Server (NTRS)

Youtsey, Christopher

2015-01-01

MicroLink Devices, Inc., has transitioned its 6-inch epitaxial lift-off (ELO) solar cell fabrication process into a manufacturing platform capable of sustaining large-volume production. This Phase II project improves the ELO process by reducing cycle time and increasing the yield of large-area devices. In addition, all critical device fabrication processes have transitioned to 6-inch production tool sets designed for volume production. An emphasis on automated cassette-to-cassette and batch processes minimizes operator dependence and cell performance variability. MicroLink Devices established a pilot production line capable of at least 1,500 6-inch wafers per month at greater than 80 percent yield. The company also increased the yield and manufacturability of the 6-inch reclaim process, which is crucial to reducing the cost of the cells.

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

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Optimization of ultrasound-assisted extraction of charantin from Momordica charantia fruits using response surface methodology.

PubMed

Ahamad, Javed; Amin, Saima; Mir, Showkat R

2015-01-01

Momordica charantia Linn. (Cucurbitaceae) fruits are well known for their beneficial effects in diabetes that are often attributed to its bioactive component charantin. The aim of the present study is to develop and optimize an efficient protocol for the extraction of charantin from M. charantia fruits. Response surface methodology (RSM) was used for the optimization of ultrasound-assisted extraction (UAE) conditions. RSM was based on a three-level, three-variable Box-Behnken design (BBD), and the studied variables included solid to solvent ratio, extraction temperature, and extraction time. The optimal conditions predicted by the BBD were: UAE with methanol: Water (80:20, v/v) at 46°C for 120 min with solid to solvent ratio of 1:26 w/v, under which the yield of charantin was 3.18 mg/g. Confirmation trials under slightly adjusted conditions yielded 3.12 ± 0.14 mg/g of charantin on dry weight basis of fruits. The result of UAE was also compared with Soxhlet extraction method and UAE was found 2.74-fold more efficient than the Soxhlet extraction for extracting charantin. A facile UAE protocol for a high extraction yield of charantin was developed and validated.

Identification of Quantitative Trait Loci Conditioning the Main Biomass Yield Components and Resistance to Melampsora spp. in Salix viminalis × Salix schwerinii Hybrids

PubMed Central

Sulima, Paweł; Przyborowski, Jerzy A.; Kuszewska, Anna; Załuski, Dariusz; Jędryczka, Małgorzata; Irzykowski, Witold

2017-01-01

The biomass of Salix viminalis is the most highly valued source of green energy, followed by S. schwerinii, S. dasyclados and other species. Significant variability in productivity and leaf rust resistance are noted both within and among willow species, which creates new opportunities for improving willow yield parameters through selection of desirable recombinants supported with molecular markers. The aim of this study was to identify quantitative trait loci (QTLs) linked with biomass yield-related traits and the resistance/susceptibility of Salix mapping population to leaf rust. The experimental material comprised a mapping population developed based on S. viminalis × S. schwerinii hybrids. Phenotyping was performed on plants grown in a field experiment that had a balanced incomplete block design with 10 replications. Based on a genetic map, 11 QTLs were identified for plant height, 9 for shoot diameter, 3 for number of shoots and 11 for resistance/susceptibility to leaf rust. The QTLs identified in our study explained 3%–16% of variability in the analyzed traits. Our findings make significant contributions to the development of willow breeding programs and research into shrubby willow crops grown for energy. PMID:28327519

[Flag leaf photosynthetic characteristics, change in chlorophyll fluorescence parameters, and their relationships with yield of winter wheat sowed in spring].

PubMed

Xu, Lan; Gao, Zhi-qang; An, Wei; Li, Yan-liang; Jiao, Xiong-fei; Wang, Chuang-yun

2016-01-01

With five good winter wheat cultivars selected from the middle and lower reaches of Yangtze River and Southwest China as test materials, a field experiment in Xinding basin area of Shanxi Province was conducted to study the photosynthetic characteristics, chlorophyll content, and chlorophyll fluorescence parameters of flag leaf at different sowing dates, as well as the correlations between these indices and yield for two years (2013-2014). The results showed that the difference in most fluorescence parameters except chlorophyll content among cultivars was significant. The correlations between these fluorescence parameters and yield were significant. The variation coefficient of chlorophyll (Chl) content was low (0.12-0.17), and that of performance index based on absorption (PIabs) was high (0.32-0.39), with the partial correlation coefficients of them with grain yield from 2013 to 2014 ranged in 0.70-0.81. Under the early sowing condition, the grain yield positively correlated with PIabs at flowering and filling stages and chlorophyll content at grain filling stage, but negatively correlated with the relative variable fluorescence at I point (Vi) at grain filling stage. About 81.1%-82.8% of grain yield were determined by the variations of PIabs, Chl, and Vi. Wheat cultivars had various performances in the treatments with different sowing dates and a consistent trend was observed in the two experimental years. Among these 5 cultivars, Yangmai 13 was suitable for early sowing, with the flag leaf photosynthetic rate (Pn), Chl, most fluorescence parame-ters, and grain yield showed obviously high levels. In conclusion, under early sowing condition chlorophyll content at grain filling stages, PIabs at flowering and filling stages, and Pn were important indices for selecting wheat cultivars with high photosynthetic efficiency.

Vergence variability: a key to understanding oculomotor adaptability?

PubMed

Petrock, Annie Marie; Reisman, S; Alvarez, T

2006-01-01

Vergence eye movements were recorded from three different populations: healthy young (ages 18-35 years), adaptive presbyopic and non-adaptive presbyopic(the presbyopic groups aged above 45 years) to determine how the variability of the eye movements made by the populations differs. The variability was determined using Shannon Entropy calculations of Wavelet transform coefficients, to yield a non-linear analysis of the vergence movement variability. The data were then fed through a k-means clustering algorithm to classify each subject, with no a priori knowledge of true subject classification. The results indicate a highly significant difference in the total entropy values between the three groups, indicating a difference in the level of information content, and thus hypothetically the oculomotor adaptability, between the three groups.Further, the frequency distribution of the entropy varied across groups.

Athletics, Applications, & Yields: The Relationship between Successful College Football and Institutional Attractiveness

ERIC Educational Resources Information Center

Jones, Willis A.

2009-01-01

This study examines the impact of fielding a successful college football team on institutional popularity using a dependent variable (admissions yield) and an independent variable (bowl game television rating) which have been unexamined in previous research on this topic. The findings suggest that college football success is correlated with a…

Microwave Energy Increases Fatty Acid Methyl Ester Yield in Human Whole Blood Due to Increased Sphingomyelin Transesterification.

PubMed

Metherel, Adam H; Aristizabal Henao, Juan J; Ciobanu, Flaviu; Taha, Ameer Y; Stark, Ken D

2015-09-01

Dried blood spots (DBS) by fingertip prick collection for fatty acid profiling are becoming increasingly popular due to ease of collection, minimal invasiveness and its amenability to high-throughput analyses. Herein, we assess a microwave-assisted direct transesterification method for the production of fatty acid methyl esters (FAME) from DBS. Technical replicates of human whole blood were collected and 25-μL aliquots were applied to chromatography strips prior to analysis by a standard 3-h transesterification method or microwave-assisted direct transesterification method under various power (variable vs constant), time (1-5 min) and reagent (1-10% H2SO4 in methanol) conditions. In addition, a standard method was compared to a 5-min, 30-W power microwave in 1% H2SO4 method for FAME yield from whole blood sphingomyelin, and sphingomyelin standards alone and spiked in whole blood. Microwave-assisted direct transesterification yielded no significant differences in both quantitative (nmol/100 µL) and qualitative (mol%) fatty acid assessments after as little as 1.5- and 1-min reaction times, respectively, using the variable power method and 5% H2SO4 in methanol. However, 30-W power for 5 min increased total FAME yield of the technical replicates by 14%. This increase appears largely due to higher sphingomyelin-derived FAME yield of up to 109 and 399% compared to the standard method when determined from whole blood or pure standards, respectively. In conclusion, microwave-assisted direct transesterification of DBS achieved in as little as 1-min, and 5-min reaction times increase total fatty acids primarily by significantly improving sphingomyelin-derived fatty acid yield.

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and good analytical procedures needed to generate this data. As a result, when combined with a robust QA/QC oversight protocol, these empirical methods can be relied upon to generate high-quality data over a long period of time.« less

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

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

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and good analytical procedures needed to generate this data. As a result, when combined with a robust QA/QC oversight protocol, these empirical methods can be relied upon to generate high-quality data over a long period of time.« less

Narrowing the agronomic yield gap with improved nitrogen use efficiency: a modeling approach.

PubMed

Ahrens, T D; Lobell, D B; Ortiz-Monasterio, J I; Li, Y; Matson, P A

2010-01-01

Improving nitrogen use efficiency (NUE) in the major cereals is critical for more sustainable nitrogen use in high-input agriculture, but our understanding of the potential for NUE improvement is limited by a paucity of reliable on-farm measurements. Limited on-farm data suggest that agronomic NUE (AE(N)) is lower and more variable than data from trials conducted at research stations, on which much of our understanding of AE(N) has been built. The purpose of this study was to determine the magnitude and causes of variability in AE(N) across an agricultural region, which we refer to as the achievement distribution of AE(N). The distribution of simulated AE(N) in 80 farmers' fields in an irrigated wheat system in the Yaqui Valley, Mexico, was compared with trials at a local research center (International Wheat and Maize Improvement Center; CIMMYT). An agroecosystem simulation model WNMM was used to understand factors controlling yield, AE(N), gaseous N emissions, and nitrate leaching in the region. Simulated AE(N) in the Yaqui Valley was highly variable, and mean on-farm AE(N) was 44% lower than trials with similar fertilization rates at CIMMYT. Variability in residual N supply was the most important factor determining simulated AE(N). Better split applications of N fertilizer led to almost a doubling of AE(N), increased profit, and reduced N pollution, and even larger improvements were possible with technologies that allow for direct measurement of soil N supply and plant N demand, such as site-specific nitrogen management.

Development of LACIE CCEA-1 weather/wheat yield models. [regression analysis

NASA Technical Reports Server (NTRS)

Strommen, N. D.; Sakamoto, C. M.; Leduc, S. K.; Umberger, D. E. (Principal Investigator)

1979-01-01

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Physical and chemical properties of pomegranate fruit accessions from Croatia.

PubMed

Radunić, Mira; Jukić Špika, Maja; Goreta Ban, Smiljana; Gadže, Jelena; Díaz-Pérez, Juan Carlos; MacLean, Dan

2015-06-15

The objective was to evaluate physical and chemical properties of eight pomegranate accessions (seven cultivars and one wild genotype) collected from the Mediterranean region of Croatia. Accessions showed high variability in fruit weight and size, calyx and peel properties, number of arils per fruit, total aril weight, and aril and juice yield. Variables that define sweet taste, such as low total acidity (TA; 0.37-0.59%), high total soluble solids content (TSS; 12.5-15.0%) and their ratio (TSS/TA) were evaluated, and results generally aligned with sweetness classifications of the fruit. Pomegranate fruit had a high variability in total phenolic content (1985.6-2948.7 mg/L). HPLC-MALDI-TOF/MS analysis showed that accessions with dark red arils had the highest total anthocyanin content, with cyanidin 3-glucoside as the most abundant compound. Principal component analysis revealed great differences in fruit physical characteristics and chemical composition among pomegranate accessions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Anthropometry as a predictor of high speed performance.

PubMed

Caruso, J F; Ramey, E; Hastings, L P; Monda, J K; Coday, M A; McLagan, J; Drummond, J

2009-07-01

To assess anthropometry as a predictor of high-speed performance, subjects performed four seated knee- and hip-extension workouts with their left leg on an inertial exercise trainer (Impulse Technologies, Newnan GA). Workouts, done exclusively in either the tonic or phasic contractile mode, entailed two one-minute sets separated by a 90-second rest period and yielded three performance variables: peak force, average force and work. Subjects provided the following anthropometric data: height, weight, body mass index, as well as total, upper and lower left leg lengths. Via multiple regression, anthropometry attempted to predict the variance per performance variable. Anthropometry explained a modest (R2=0.27-0.43) yet significant degree of variance from inertial exercise trainer workouts. Anthropometry was a better predictor of peak force variance from phasic workouts, while it accounted for a significant degree of average force and work variance solely from tonic workouts. Future research should identify variables that account for the unexplained variance from high-speed exercise performance.

Simultaneous Optimization of Multiple Response Variables for the Gelatin-chitosan Microcapsules Containing Angelica Essential Oil.

PubMed

Li, Qiang; Sun, Li-Jian; Gong, Xian-Feng; Wang, Yang; Zhao, Xue-Ling

2017-01-01

Angelica essential oil (AO), a major pharmacologically active component of Angelica sinensis (Oliv.) Diels, possesses hemogenesis, analgesic activities, and sedative effect. The application of AO in pharmaceutical systems had been limited because of its low oxidative stability. The AO-loaded gelatin-chitosan microcapsules with prevention from oxidation were developed and optimized using response surface methodology. The effects of formulation variables (pH at complex coacervation, gelatin concentration, and core/wall ratio) on multiple response variables (yield, encapsulation efficiency, antioxidation rate, percent of drug released in 1 h, and time to 85% drug release) were systemically investigated. A desirability function that combined these five response variables was constructed. All response variables investigated were found to be highly dependent on the formulation variables, with strong interactions observed between the formulation variables. It was found that optimum overall desirability of AO microcapsules could be obtained at pH 6.20, gelatin concentration 25.00%, and core/wall ratio 40.40%. The experimental values of the response variables highly agreed with the predicted values. The antioxidation rate of optimum formulation was approximately 8 times higher than that of AO. The in-vitro drug release from microcapsules was followed Higuchi model with super case-II transport mechanism.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

Variable-rate nitrogen application algorithm based on canopy reflected spectrum and its influence on wheat

NASA Astrophysics Data System (ADS)

Liang, Hongxia; Zhao, Chunjiang; Huang, Wenjiang; Liu, Liangyun; Wang, Jihua; Ma, Youhua

2005-01-01

This study was to develop the time-specific and time-critical method to overcome the limitations of traditional field sampling methods for variable rate fertilization. Farmers, agricultural managers and grain processing enterprises are interested in measuring and assessing soil and crop status in order to apply adequate fertilizer quantities to crop growth. This paper focused on studying the relationship between vegetation index (OSAVI) and nitrogen content to determine the amount of nitrogen fertilizer recommended for variable rate management in precision agriculture. The traditional even rate fertilizer management was chosen as the CK. The grain yield, ear numbers, 1000-grain weight and grain protein content were measured among the CK, uniform treatments and variable rate fertilizer treatments. It indicated that variable rate fertilization reduced the variability of wheat yield, ear numbers and dry biomass, but it didn't increased crop yield and grain protein content significantly and did not decrease the variety of 1000-grain weight, compared to traditional rate application. The nitrogen fertilizer use efficiency was improved, for this purpose, the variable rate technology based on vegetation index could be used to prevent under ground water pollution and environmental deterioration.

Low-Dimensional Statistics of Anatomical Variability via Compact Representation of Image Deformations.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2016-10-01

Using image-based descriptors to investigate clinical hypotheses and therapeutic implications is challenging due to the notorious "curse of dimensionality" coupled with a small sample size. In this paper, we present a low-dimensional analysis of anatomical shape variability in the space of diffeomorphisms and demonstrate its benefits for clinical studies. To combat the high dimensionality of the deformation descriptors, we develop a probabilistic model of principal geodesic analysis in a bandlimited low-dimensional space that still captures the underlying variability of image data. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than models based on the high-dimensional state-of-the-art approaches such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA).

The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2016-09-01

Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05 t ha-1 and 5.03 t C ha-1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57 t ha-1 and 09.29 t C ha-1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30 t ha-1 and 13.65 t C ha-1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems.

A SPECTROPOLARIMETRIC TEST OF THE STRUCTURE OF THE INTRINSIC ABSORBERS IN THE QUASAR HS 1603+3820

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

Misawa, Toru; Kawabata, Koji S.; Eracleous, Michael

We report the results of a spectropolarimetric observation of the C VI 'mini-broad' absorption line (mini-BAL) in the quasar HS 1603+3820 (z {sub em} = 2.542). The observations were carried out with the FOCAS instrument on the Subaru Telescope and yielded an extremely high polarization sensitivity of {delta}p{approx} 0.1%, at a resolving power of R {approx} 1500. HS 1603+3820 has been the target of a high-resolution spectroscopic monitoring campaign for more than four years, aimed at studying its highly variable C VI mini-BAL profile. Using the monitoring observations in an earlier paper, we were able to narrow down the causesmore » of the variability to the following two scenarios: (1) scattering material of variable optical depth redirecting photons around the absorber and (2) a variable, highly ionized screen between the continuum source and the absorber which modulates the UV continuum incident on the absorber. The observations presented here provide a crucial test of the scattering scenario and lead us to disfavor it because (1) the polarization level is very small (p {approx} 0.6%) throughout the spectrum and (2) the polarization level does not increase across the mini-BAL trough. Thus, the variable screen scenario emerges as our favored explanation of the C VI mini-BAL variability. Our conclusion is bolstered by recent X-ray observations of nearby mini-BAL quasars, which show a rapidly variable soft X-ray continuum that appears to be the result of transmission through an ionized absorber of variable ionization parameter and optical depth.« less

Variation of inulin content, inulin yield and water use efficiency for inulin yield in Jerusalem artichoke genotypes under different water regimes

USDA-ARS?s Scientific Manuscript database

The information on genotypic variation for inulin content, inulin yield and water use efficiency of inulin yield (WUEi) in response to drought is limited. This study was to investigate the genetic variability in inulin content, inulin yield and WUEi of Jerusalem artichoke (Helianthus tuberosus L.) ...

Proteomic analysis of duck fatty liver during post-mortem storage related to the variability of fat loss during cooking of "foie gras".

PubMed

Theron, Laetitia; Fernandez, Xavier; Marty-Gasset, Nathalie; Chambon, Christophe; Viala, Didier; Pichereaux, Carole; Rossignol, Michel; Astruc, Thierry; Molette, Caroline

2013-01-30

Fat loss during cooking of duck "foie gras" is the main problem for both manufacturers and consumers. Despite the efforts of the processing industry to control fat loss, the variability of fatty liver cooking yields remains high and uncontrolled. To understand the biochemical effects of postslaughter processing on fat loss during cooking, this study characterizes for the first time the protein expression of fatty liver during chilling using a proteomic approach. For this purpose the proteins were separated according to their solubility: the protein fraction soluble in a buffer of low ionic strength (S) and the protein fraction insoluble in the same buffer (IS). Two-dimensional electrophoresis was used to analyze the S fraction and mass spectrometry for the identification of spots of interest. This analysis revealed 36 (21 identified proteins) and 34 (26 identified proteins) spots of interests in the low-fat-loss and high-fat-loss groups, respectively. The expression of proteins was lower after chilling, which revealed a suppressive effect of chilling on biological processes. The shot-gun strategy was used to analyze the IS fraction, with the identification of all the proteins by mass spectrometry. This allowed identification of 554 and 562 proteins in the low-fat-loss and high-fat-loss groups, respectively. Among these proteins, only the proteins that were up-regulated in the high-fat-loss group were significant (p value = 3.17 × 10(-3)) and corresponded to protein from the cytoskeleton and its associated proteins. Taken together, these results suggest that the variability of technological yield observed in processing plants could be explained by different aging states of fatty livers during chilling, most likely associated with different proteolytic patterns.

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.

Total suspended solids concentrations and yields for water-quality monitoring stations in Gwinnett County, Georgia, 1996-2009

USGS Publications Warehouse

Landers, Mark N.

2013-01-01

The U.S. Geological Survey, in cooperation with the Gwinnett County Department of Water Resources, established a water-quality monitoring program during late 1996 to collect comprehensive, consistent, high-quality data for use by watershed managers. As of 2009, continuous streamflow and water-quality data as well as discrete water-quality samples were being collected for 14 watershed monitoring stations in Gwinnett County. This report provides statistical summaries of total suspended solids (TSS) concentrations for 730 stormflow and 710 base-flow water-quality samples collected between 1996 and 2009 for 14 watershed monitoring stations in Gwinnett County. Annual yields of TSS were estimated for each of the 14 watersheds using methods described in previous studies. TSS yield was estimated using linear, ordinary least-squares regression of TSS and explanatory variables of discharge, turbidity, season, date, and flow condition. The error of prediction for estimated yields ranged from 1 to 42 percent for the stations in this report; however, the actual overall uncertainty of the estimated yields cannot be less than that of the observed yields (± 15 to 20 percent). These watershed yields provide a basis for evaluation of how watershed characteristics, climate, and watershed management practices affect suspended sediment yield.

Effect of condensed tannins in rations of lactating dairy cows on production variables and nitrogen use efficiency.

PubMed

Gerlach, K; Pries, M; Tholen, E; Schmithausen, A J; Büscher, W; Südekum, K-H

2018-01-08

The objective of this study was to evaluate the effect of supplemented condensed tannins (CT) from the bark of the Black Wattle tree (Acacia mearnsii) on production variables and N use efficiency in high yielding dairy cows. A feeding trial with 96 lactating German Holstein cows was conducted for a total of 169 days, divided into four periods. The animals were allotted to two groups (control (CON) and experimental (EXP) group) according to milk yield in previous lactation, days in milk (98), number of lactations and BW. The trial started and finished with a period (period 1 and 4) where both groups received the same ration (total-mixed ration based on grass and maize silage, ensiled sugar beet pulp, lucerne hay, mineral premix and concentrate, calculated for 37 kg energy-corrected milk). In between, the ration of EXP cows was supplemented with 1% (CT1, period 2) and 3% of dry matter (DM) (CT3, period 3) of a commercial A. mearnsii extract (containing 0.203 g CT/g DM) which was mixed into the concentrate. In period 3, samples of urine and faeces were collected from 10 cows of each group and analyzed to estimate N excretion. Except for a tendency for a reduced milk urea concentration with CT1, there was no difference between groups in period 2 (CON v. CT1; P>0.05). The CT3 significantly reduced (P<0.05) milk protein yield, the apparent N efficiency (kg milk N/k feed N) and milk urea concentration; but total milk yield and energy-corrected milk yield were not affected by treatment. Furthermore, as estimated from 10 cows per group and using urinary K as a marker to estimate the daily amount of urine voided, CT3 caused a minor shift of N compounds from urine to faeces, as urea-N in urine was reduced, whereas the N concentration in faeces increased. As an improvement in productivity was not achieved and N use efficiency was decreased by adding the CT product it can be concluded that under current circumstances the use in high yielding dairy cows is not advantageous.

Monitoring and assessment of treated river, rain, gully pot and grey waters for irrigation of Capsicum annuum.

PubMed

Al-Isawi, Rawaa H K; Almuktar, Suhad A A A N; Scholz, Miklas

2016-05-01

This study examines the benefits and risks associated with various types of wastewater recycled for vegetable garden irrigation and proposes the best water source in terms of its water quality impact on crop yields. The aim was to evaluate the usability of river, rain, gully pot, real grey and artificial grey waters to water crops. The objectives were to evaluate variables and boundary conditions influencing the growth of chillies (De Cayenne; Capsicum annuum (Linnaeus) Longum Group 'De Cayenne') both in the laboratory and in the greenhouse. A few irrigated chilli plants suffered from excess of some nutrients, which led to a relatively poor harvest. High levels of trace minerals and heavy metals were detected in river water, gully pot effluent and greywater. However, no significant differences in plant yields were observed, if compared with standards and other yields worldwide. The highest yields were associated with river water both in the laboratory and in the greenhouse. Plant productivity was unaffected by water quality due to the high manganese, potassium, cadmium and copper levels of the greywater. These results indicate the potential of river water and gully pot effluent as viable alternatives to potable water for irrigation in agriculture.

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.

Effects of process variables on the yield stress of rheologically modified biomass

Treesearch

Joseph R. Samaniuk; C Tim Scott; Thatcher W. Root; Daniel J. Klingenberg

2015-01-01

Additives that alter the rheology of lignocellulosic biomass suspensions were tested under conditions of variable pH, temperature, and solid concentration. The effects of certain ions, biomass type, after the addition of rheological modifier were also examined. Torque and vane rheometry were used to measure the yield stress of samples. It was found that the...

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.

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

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.

Design and characteristics of MRF-based actuators for torque transmission under influence of high shear rates up to 34,000s-1

NASA Astrophysics Data System (ADS)

Güth, Dirk; Erbis, Vadim; Schamoni, Markus; Maas, Jürgen

2014-04-01

High rotational speeds for brakes and clutches based on magnetorheological fluids represent a remaining challenge for the industrial or automotive application. Beside particle centrifugation effects and rotational speed-depending no-load losses, the torque characteristic is an important property that needs to considered in the design process of actuators. Due to missing experimental data for these operating conditions, in this paper the shear rate and flux depending yield stress behavior of magnetorheological uids is experimentally investigated for high rotational speeds or respectively high shear rates. Therefore a brake actuator with variable shear gap heights up to 4 mm is designed, realized and used for the experimental investigation, which are performed for a maximum shear rate of ƴ= 34; 000 s-1 under large magnetic elds. The measurement results point out a strong dependency between shear rate, magnetic ux density and resulting yield stress. For low shear gap heights, a significant reduction in the yield stress up to 10 % can be determined. Additionally the development of Taylor vortices is determined, which will not only occur in viscous case without an applied magnetic field. The measurement results are important for a reliable actuator design which should be used in application with high rotational speeds.

Echo Mapping of Active Galactic Nuclei

NASA Technical Reports Server (NTRS)

Peterson, B. M.; Horne, K.

2004-01-01

Echo mapping makes use of the intrinsic variability of the continuum source in active galactic nuclei to map out the distribution and kinematics of line-emitting gas from its light travel time-delayed response to continuum changes. Echo mapping experiments have yielded sizes for the broad line-emitting region in about three dozen AGNs. The dynamics of the line-emitting gas seem to be dominated by the gravity of the central black hole, enabling measurement of the black-hole masses in AGNs. We discuss requirements for future echo-mapping experiments that will yield the high quality velocity-delay maps of the broad-line region that are needed to determine its physical nature.

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2005-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. We have formed images in... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2002-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. In this first year of... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2004-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. We have formed images in... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Reanalysis of Water, Land Use, and Production Data for Assessing China's Agricultural Resources

NASA Astrophysics Data System (ADS)

Smith, T.; Pan, J.; McLaughlin, D.

2016-12-01

Quantitative data about water availability, crop evapotranspiration (ET), agricultural land use, and production are needed at high temporal and spatial resolutions to develop sustainable water and agricultural plan and policies. However, large-scale high-resolution measured data can be susceptible to errors, physically inconsistent, or incomplete. Reanalysis provides a way to develop improved physically consistent estimates of both measured and hidden variables. The reanalysis approach described here uses a least-squares technique constrained by water balances and crop water requirements to assimilate many possibly redundant data sources to yield estimates of water, land use, and food production variables that are physically consistent while minimizing differences from measured data. As an example, this methodology is applied in China, where food demand is expected to increase but land and water resources could constrain further increases in food production. Hydrologic fluxes, crop ET, agricultural land use, yields, and food production are characterized at 0.5o by 0.5o resolution for a nominal year around the year 2000 for 22 different crop groups. The reanalysis approach provides useful information for resource management and policy, both in China and around the world.

Ceres model application for increasing preparedness to climate variability in agricultural planning

NASA Astrophysics Data System (ADS)

Popova, Z.; Kercheva, M.

2003-04-01

The paper should demonstrate how knowledge of climate variability and simulation analyses over 30 years could be used to study the vulnerability of maize and wheat ecosystems in the region of Sofia. The procedure of stepwise calibration and validation of agricultural simulation CERES-maize and CERES-wheat models was used at two fields of contrastive soil conditions (Chromic Luvisol and Vertisol). Lysimeters observations under "Chromic Luvisol-maize" combination enabled to test integrally the prediction capacity of CERES-maize, including water and nitrogen fluxes at the boundaries of this vulnerable system over "1.05.1997-1.10.1999" period. The role of soil, crop, climate and irrigation scheduling (under maize only) on drought consequences and groundwater pollution was quantified for four "soil-crop" combinations by CERES models. Four water supply treatments of maize were considered on both soils: one under rainfed conditions and three with varied irrigation application. Water application in initial, development, and mid season growth stages was scheduled by CROPWAT model at any day that soil matrix suction fell to 3.0-3.2 pF with one irrigation scenario and 2.4-2.6 pF with another one. The third drainage-controlling scenario was developed on the basis of 50-75% of the required irrigation depth by satisfying most sensible phases of maize. It was established that "Chromic Luvisol -maize - dry land" combination was associated with the greatest coefficient of variability of yields (Cv=42%) and drought frequency (75% of the years with yield losses more than 20%). Average yield losses in dry vegetation seasons were 60% of the productivity potential under sufficient soil moisture. As a consequence maize cultivation under these conditions was inefficient in 20% of the years when production expenses were greater than losses. Any irrigation practice, even the drainage controlling scenario, mitigated drought consequences on risky soils as Chromic Luvisol by reducing year-to-year variability of yield (CV=5.6-6%). Long-term wheat yields were much more stable (CV=17-23% on Chromic Luvisol) than those of maize. In this case droughts covered 40% of the years when yield losses were 25-30% on the average. Soils of high water holding capacity (as Vertisol) provided additionally 50-150mm-water storage for evapotranspiration and thus reduced frequency of drought under both crops to 20-25% of the years. Agriculture on this soil should be more sustainable (CV=8-8.5% for yield under wheat and CV=14.6% respectively under maize). Reduction of yield during dry vegetation periods was 10-15% under wheat and 22% under maize if compared with productivity under sufficient soil water. Risk assessment of groundwater pollution showed that N-leaching hazards were associated mostly with moderately permeable Chromic Luvisol and high precipitation during the periods of low transpiration rate of both crops. Frequency analyses of seasonal N- losses, proved that half of the wheat and 3% of maize vegetation seasons were susceptible to significant N-leaching (10-45 kg N/ha for "N200" fertilization level) on Chromic Luvisol. Simulated irrigation scenarios did not influence vegetation drainage. Another risky situations occurred in 3% of the years of wet fallow after dry rainfed maize vegetation when up to 30% of fertilization dose might be leached on Chromic Luvisol. Earlier wheat sowing (on the 1st of October) and adjusted fertilization rates and timing to maximum N-uptake under both crops mitigated environmental hazards. Drainage-controlling irrigation scheduling decreased maize fallow state drainage by 30-40 % in half of the years and proved to be economically optimal. Such measure though may tend to increase vulnerability of ecosystem to climate variability by increasing residual soil nitrogen at the end of vegetation.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

Genotypic variability and genotype by environment interactions in oil and fatty acids in high, intermediate, and low oleic acid peanut genotypes.

PubMed

Singkham, Nattawut; Jogloy, Sanun; Kesmala, Thawan; Swatsitang, Prasan; Jaisil, Prasit; Puppala, Naveen

2010-05-26

Variability of genotype and genotype x environment (G x E) interactions for fatty acids are important to develop high-oleic types in peanut varietal improvement programs. The objective of this study was to determine the variation in fatty acid composition among peanut genotypes and G x E interactions of fatty acids in three groups of genotypes with high, intermediate, and low-oleic acid. Twenty-one genotypes were tested in three environments consisting of two rainy seasons and one dry season. The results indicated that G x E interactions were significant for biomass, pod yield, and harvest index and also for oleic, linoleic acids, and O/L ratio. G x E interactions were less important than genotypic main effect. For oleic acid, significant interactions were found in the intermediate and low-oleic groups only. Therefore, selection for high-oleic trait in peanut breeding programs should be effective.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups

PubMed Central

Dar, Manzoor H.; de Janvry, Alain; Emerick, Kyle; Raitzer, David; Sadoulet, Elisabeth

2013-01-01

Approximately 30% of the cultivated rice area in India is prone to crop damage from prolonged flooding. We use a randomized field experiment in 128 villages of Orissa India to show that Swarna-Sub1, a recently released submergence-tolerant rice variety, has significant positive impacts on rice yield when fields are submerged for 7 to 14 days with no yield penalty without flooding. We estimate that Swarna-Sub1 offers an approximate 45% increase in yields over the current popular variety when fields are submerged for 10 days. We show additionally that low-lying areas prone to flooding tend to be more heavily occupied by people belonging to lower caste social groups. Thus, a policy relevant implication of our findings is that flood-tolerant rice can deliver both efficiency gains, through reduced yield variability and higher expected yield, and equity gains in disproportionately benefiting the most marginal group of farmers. PMID:24263095

Response of wheat yield in Spain to large-scale patterns

NASA Astrophysics Data System (ADS)

Hernandez-Barrera, Sara; Rodriguez-Puebla, Concepcion

2016-04-01

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

Framework for the rapid optimization of soluble protein expression in Escherichia coli combining microscale experiments and statistical experimental design.

PubMed

Islam, R S; Tisi, D; Levy, M S; Lye, G J

2007-01-01

A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g.L-1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production.

PubMed

Rincent, R; Nicolas, S; Bouchet, S; Altmann, T; Brunel, D; Revilla, P; Malvar, R A; Moreno-Gonzalez, J; Campo, L; Melchinger, A E; Schipprack, W; Bauer, E; Schoen, C-C; Meyer, N; Ouzunova, M; Dubreuil, P; Giauffret, C; Madur, D; Combes, V; Dumas, F; Bauland, C; Jamin, P; Laborde, J; Flament, P; Moreau, L; Charcosset, A

2014-11-01

Genetic and phenotypic analysis of two complementary maize panels revealed an important variation for biomass yield. Flowering and biomass QTL were discovered by association mapping in both panels. The high whole plant biomass productivity of maize makes it a potential source of energy in animal feeding and biofuel production. The variability and the genetic determinism of traits related to biomass are poorly known. We analyzed two highly diverse panels of Dent and Flint lines representing complementary heterotic groups for Northern Europe. They were genotyped with the 50 k SNP-array and phenotyped as hybrids (crossed to a tester of the complementary pool) in a western European field trial network for traits related to flowering time, plant height, and biomass. The molecular information revealed to be a powerful tool for discovering different levels of structure and relatedness in both panels. This study revealed important variation and potential genetic progress for biomass production, even at constant precocity. Association mapping was run by combining genotypes and phenotypes in a mixed model with a random polygenic effect. This permitted the detection of significant associations, confirming height and flowering time quantitative trait loci (QTL) found in literature. Biomass yield QTL were detected in both panels but were unstable across the environments. Alternative kinship estimator only based on markers unlinked to the tested SNP increased the number of significant associations by around 40% with a satisfying control of the false positive rate. This study gave insights into the variability and the genetic architectures of biomass-related traits in Flint and Dent lines and suggests important potential of these two pools for breeding high biomass yielding hybrid varieties.

Coupled Effects of non-Newtonian Rheology and Aperture Variability on Flow in a Single Fracture

NASA Astrophysics Data System (ADS)

Di Federico, V.; Felisa, G.; Lauriola, I.; Longo, S.

2017-12-01

Modeling of non-Newtonian flow in fractured media is essential in hydraulic fracturing and drilling operations, EOR, environmental remediation, and to understand magma intrusions. An important step in the modeling effort is a detailed understanding of flow in a single fracture, as the fracture aperture is spatially variable. A large bibliography exists on Newtonian and non-Newtonian flow in variable aperture fractures. Ultimately, stochastic or deterministic modeling leads to the flowrate under a given pressure gradient as a function of the parameters describing the aperture variability and the fluid rheology. Typically, analytical or numerical studies are performed adopting a power-law (Oswald-de Waele) model. Yet the power-law model, routinely used e.g. for hydro-fracturing modeling, does not characterize real fluids at low and high shear rates. A more appropriate rheological model is provided by e.g. the four-parameter Carreau constitutive equation, which is in turn approximated by the more tractable truncated power-law model. Moreover, fluids of interest may exhibit yield stress, which requires the Bingham or Herschel-Bulkely model. This study employs different rheological models in the context of flow in variable aperture fractures, with the aim of understanding the coupled effect of rheology and aperture spatial variability with a simplified model. The aperture variation, modeled within a stochastic or deterministic framework, is taken to be one-dimensional and i) perpendicular; ii) parallel to the flow direction; for stochastic modeling, the influence of different distribution functions is examined. Results for the different rheological models are compared with those obtained for the pure power-law. The adoption of the latter model leads to overestimation of the flowrate, more so for large aperture variability. The presence of yield stress also induces significant changes in the resulting flowrate for assigned external pressure gradient.

Computer optimization of cutting yield from multiple ripped boards

Treesearch

A.R. Stern; K.A. McDonald

1978-01-01

RIPYLD is a computer program that optimizes the cutting yield from multiple-ripped boards. Decisions are based on automatically collected defect information, cutting bill requirements, and sawing variables. The yield of clear cuttings from a board is calculated for every possible permutation of specified rip widths and both the maximum and minimum percent yield...

Commercially sterilized mussel meats (Mytilus chilensis): a study on process yield.

PubMed

Almonacid, S; Bustamante, J; Simpson, R; Urtubia, A; Pinto, M; Teixeira, A

2012-06-01

The processing steps most responsible for yield loss in the manufacture of canned mussel meats are the thermal treatments of precooking to remove meats from shells, and thermal processing (retorting) to render the final canned product commercially sterile for long-term shelf stability. The objective of this study was to investigate and evaluate the impact of different combinations of process variables on the ultimate drained weight in the final mussel product (Mytilu chilensis), while verifying that any differences found were statistically and economically significant. The process variables selected for this study were precooking time, brine salt concentration, and retort temperature. Results indicated 2 combinations of process variables producing the widest difference in final drained weight, designated best combination and worst combination with 35% and 29% yield, respectively. Significance of this difference was determined by employing a Bootstrap methodology, which assumes an empirical distribution of statistical error. A difference of nearly 6 percentage points in total yield was found. This represents a 20% increase in annual sales from the same quantity of raw material, in addition to increase in yield, the conditions for the best process included a retort process time 65% shorter than that for the worst process, this difference in yield could have significant economic impact, important to the mussel canning industry. © 2012 Institute of Food Technologists®

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Theory of nonlinear elasticity, stress-induced relaxation, and dynamic yielding in dense fluids of hard nonspherical colloids

NASA Astrophysics Data System (ADS)

Zhang, Rui; Schweizer, Kenneth S.

2012-04-01

We generalize the microscopic naïve mode coupling and nonlinear Langevin equation theories of the coupled translation-rotation dynamics of dense suspensions of uniaxial colloids to treat the effect of applied stress on shear elasticity, cooperative cage escape, structural relaxation, and dynamic and static yielding. The key concept is a stress-dependent dynamic free energy surface that quantifies the center-of-mass force and torque on a moving colloid. The consequences of variable particle aspect ratio and volume fraction, and the role of plastic versus double glasses, are established in the context of dense, glass-forming suspensions of hard-core dicolloids. For low aspect ratios, the theory provides a microscopic basis for the recently observed phenomenon of double yielding as a consequence of stress-driven sequential unlocking of caging constraints via reduction of the distinct entropic barriers associated with the rotational and translational degrees of freedom. The existence, and breadth in volume fraction, of the double yielding phenomena is predicted to generally depend on both the degree of particle anisotropy and experimental probing frequency, and as a consequence typically occurs only over a window of (high) volume fractions where there is strong decoupling of rotational and translational activated relaxation. At high enough concentrations, a return to single yielding is predicted. For large aspect ratio dicolloids, rotation and translation are always strongly coupled in the activated barrier hopping event, and hence for all stresses only a single yielding process is predicted.

High Variability in Outcome Reporting Patterns in High-Impact ACL Literature.

PubMed

Makhni, Eric C; Padaki, Ajay S; Petridis, Petros D; Steinhaus, Michael E; Ahmad, Christopher S; Cole, Brian J; Bach, Bernard R

2015-09-16

ACL (anterior cruciate ligament) reconstruction is one of the most commonly performed and studied procedures in modern sports medicine. A multitude of objective and subjective patient outcome measures exists; however, nonstandardized reporting patterns of these metrics may create challenges in objectively analyzing pooled results from different studies. The goal of this study was to document the variability in outcome reporting patterns in high-impact orthopaedic studies of ACL reconstruction. All clinical studies pertaining to ACL reconstruction in four high-impact-factor orthopaedic journals over a five-year period were reviewed. Biomechanical, basic science, and imaging studies were excluded, as were studies with fewer than fifty patients, yielding 119 studies for review. Incorporation of various objective and subjective outcomes was noted for each study. Substantial variability in reporting of both objective and subjective measures was noted in the study cohort. Although a majority of studies reported instrumented laxity findings, there was substantial variability in the type and method of laxity reporting. Most other objective outcomes, including range of motion, strength, and complications, were reported in <50% of all studies. Return to pre-injury level of activity was infrequently reported (24% of studies), as were patient satisfaction and pain assessment following surgery (8% and 13%, respectively). Of the patient-reported outcomes, the International Knee Documentation Committee (IKDC), Lysholm, and Tegner scores were most often reported (71%, 63%, and 42%, respectively). Substantial variability in outcome reporting patterns exists among high-impact studies of ACL reconstruction. Such variability may create challenges in interpreting results and pooling them across different studies. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

The evolution of the disc variability along the hard state of the black hole transient GX 339-4

NASA Astrophysics Data System (ADS)

De Marco, B.; Ponti, G.; Muñoz-Darias, T.; Nandra, K.

2015-12-01

We report on the analysis of hard-state power spectral density function (PSD) of GX 339-4 down to the soft X-ray band, where the disc significantly contributes to the total emission. At any luminosity probed, the disc in the hard state is intrinsically more variable than in the soft state. However, the fast decrease of disc variability as a function of luminosity, combined with the increase of disc intensity, causes a net drop of fractional variability at high luminosities and low energies, which reminds the well-known behaviour of disc-dominated energy bands in the soft state. The peak frequency of the high-frequency Lorentzian (likely corresponding to the high-frequency break seen in active galactic nuclei, AGN) scales with luminosity, but we do not find evidence for a linear scaling. In addition, we observe that this characteristic frequency is energy dependent. We find that the normalization of the PSD at the peak of the high-frequency Lorentzian decreases with luminosity at all energies, though in the soft band this trend is steeper. Together with the frequency shift, this yields quasi-constant high-frequency (5-20 Hz) fractional rms at high energies, with less than 10 per cent scatter. This reinforces previous claims suggesting that the high-frequency PSD solely scales with black hole mass. On the other hand, this constancy breaks down in the soft band (where the scatter increases to ˜30 per cent). This is a consequence of the additional contribution from the disc component, and resembles the behaviour of optical variability in AGN.

Processing of electronic waste in a counter current teeter-bed separator.

PubMed

Dey, Sujit Kumar; Ari, Vidyadhar; Das, Avimanyu

2012-09-30

Advanced gravity separation of ground electronic waste (e-waste) in a teeter-bed separator was investigated. It was established that the Floatex Density Seprator (FDS) is a promising device for wet processing of e-waste to recover metal values physically. It was possible to enrich the metal content from 23% in the feed to 37% in the product in a single stage operation using the FDS with over 95% recovery of the metals. A two-stage processing scheme was developed that enriched the metal content further to 48.2%. The influence of the operating variables, namely, teeter water flow rate, bed pressure and feed rate were quantified. Low bed pressures and low teeter water rates produced higher mass yields with poorer product grades. On the contrary, a high bed pressure and high teeter water rate combination led to a lower mass yield but better product quality. A high feed rate introduced en-masse settling leading to higher yield but at a poorer product grade. For an FDS with 230 mm × 230 mm cross section and a height of 530 mm, the process condition with 6.6l pm teeter water rate, 5.27 kPa bed pressure and 82 kg/hr feed rate maximized the yield for a target product grade of 37% metal in a single pass. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Spectropolarimetric Test of the Structure of the Intrinsic Absorbers in the Quasar HS 1603+3820

NASA Astrophysics Data System (ADS)

Misawa, Toru; Kawabata, Koji S.; Eracleous, Michael; Charlton, Jane C.; Kashikawa, Nobunari

2010-08-01

We report the results of a spectropolarimetric observation of the C VI "mini-broad" absorption line (mini-BAL) in the quasar HS 1603+3820 (z em = 2.542). The observations were carried out with the FOCAS instrument on the Subaru Telescope and yielded an extremely high polarization sensitivity of δp~ 0.1%, at a resolving power of R ~ 1500. HS 1603+3820 has been the target of a high-resolution spectroscopic monitoring campaign for more than four years, aimed at studying its highly variable C VI mini-BAL profile. Using the monitoring observations in an earlier paper, we were able to narrow down the causes of the variability to the following two scenarios: (1) scattering material of variable optical depth redirecting photons around the absorber and (2) a variable, highly ionized screen between the continuum source and the absorber which modulates the UV continuum incident on the absorber. The observations presented here provide a crucial test of the scattering scenario and lead us to disfavor it because (1) the polarization level is very small (p ~ 0.6%) throughout the spectrum and (2) the polarization level does not increase across the mini-BAL trough. Thus, the variable screen scenario emerges as our favored explanation of the C VI mini-BAL variability. Our conclusion is bolstered by recent X-ray observations of nearby mini-BAL quasars, which show a rapidly variable soft X-ray continuum that appears to be the result of transmission through an ionized absorber of variable ionization parameter and optical depth. Based on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan.

Biometry and diversity of Arabica coffee genotypes cultivated in a high density plant system.

PubMed

Rodrigues, W N; Tomaz, M A; Ferrão, M A G; Martins, L D; Colodetti, T V; Brinate, S V B; Amaral, J F T; Sobreira, F M; Apostólico, M A

2016-02-11

The present study was developed to respond to the need for an increase in crop yield in the mountain region of Caparaó (southern Espírito Santo State, Brazil), an area of traditional coffee production. This study aimed to analyze the diversity and characterize the crop yield of genotypes of Coffea arabica L. with potential for cultivation in high plant density systems. In addition, it also aimed to quantify the expression of agronomic traits in this cultivation system and provide information on the genotypes with the highest cultivation potential in the studied region. The experiment followed a randomized block design with 16 genotypes, four repetitions, and six plants per experimental plot. Plant spacing was 2.00 x 0.60 m, with a total of 8333 plants per hectare, representing a high-density cultivation system. Coffee plants were cultivated until the start of their reproductive phenological cycles and were evaluated along four complete reproductive cycles. Genotypes with high crop yield and beverage quality, short canopy, and rust resistance were selected. C. arabica genotypes showed variability in almost all characteristics. It was possible to identify different responses among genotypes grown in a high plant density cultivation system. Although the chlorophyll a content was similar among genotypes, the genotypes Acauã, Araponga MG1, Sacramento MG1, Tupi, and Catuaí IAC 44 showed a higher chlorophyll b content than the other genotypes. Among these, Sacramento MG1 also showed high leafiness and growth of vegetative structures, whereas Araponga MG1, Pau-Brasil MG1, and Tupi showed high fruit production. In addition, Araponga MG1 had also a higher and more stable crop yield over the years.

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

PubMed

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

2014-10-01

Climate warming is projected to affect forest water yields but the effects are expected to vary. We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long-term experimental catchments across Canada and the United States over 5-year cool and warm periods. Using the theoretical framework of the Budyko curve, we calculated the effects of climate warming on the annual partitioning of precipitation (P) into evapotranspiration (ET) and water yield. Deviation (d) was defined as a catchment's change in actual ET divided by P [AET/P; evaporative index (EI)] coincident with a shift from a cool to a warm period - a positive d indicates an upward shift in EI and smaller than expected water yields, and a negative d indicates a downward shift in EI and larger than expected water yields. Elasticity was defined as the ratio of interannual variation in potential ET divided by P (PET/P; dryness index) to interannual variation in the EI - high elasticity indicates low d despite large range in drying index (i.e., resilient water yields), low elasticity indicates high d despite small range in drying index (i.e., nonresilient water yields). Although the data needed to fully evaluate ecosystems based on these metrics are limited, we were able to identify some characteristics of response among forest types. Alpine sites showed the greatest sensitivity to climate warming with any warming leading to increased water yields. Conifer forests included catchments with lowest elasticity and stable to larger water yields. Deciduous forests included catchments with intermediate elasticity and stable to smaller water yields. Mixed coniferous/deciduous forests included catchments with highest elasticity and stable water yields. Forest type appeared to influence the resilience of catchment water yields to climate warming, with conifer and deciduous catchments more susceptible to climate warming than the more diverse mixed forest catchments. © 2014 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies.

PubMed

Calus, M P L; de Haas, Y; Veerkamp, R F

2013-10-01

Genomic selection holds the promise to be particularly beneficial for traits that are difficult or expensive to measure, such that access to phenotypes on large daughter groups of bulls is limited. Instead, cow reference populations can be generated, potentially supplemented with existing information from the same or (highly) correlated traits available on bull reference populations. The objective of this study, therefore, was to develop a model to perform genomic predictions and genome-wide association studies based on a combined cow and bull reference data set, with the accuracy of the phenotypes differing between the cow and bull genomic selection reference populations. The developed bivariate Bayesian stochastic search variable selection model allowed for an unbalanced design by imputing residuals in the residual updating scheme for all missing records. The performance of this model is demonstrated on a real data example, where the analyzed trait, being milk fat or protein yield, was either measured only on a cow or a bull reference population, or recorded on both. Our results were that the developed bivariate Bayesian stochastic search variable selection model was able to analyze 2 traits, even though animals had measurements on only 1 of 2 traits. The Bayesian stochastic search variable selection model yielded consistently higher accuracy for fat yield compared with a model without variable selection, both for the univariate and bivariate analyses, whereas the accuracy of both models was very similar for protein yield. The bivariate model identified several additional quantitative trait loci peaks compared with the single-trait models on either trait. In addition, the bivariate models showed a marginal increase in accuracy of genomic predictions for the cow traits (0.01-0.05), although a greater increase in accuracy is expected as the size of the bull population increases. Our results emphasize that the chosen value of priors in Bayesian genomic prediction models are especially important in small data sets. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Hyperspectral imagery for mapping crop yield for precision agriculture

USDA-ARS?s Scientific Manuscript database

Crop yield is perhaps the most important piece of information for crop management in precision agriculture. It integrates the effects of various spatial variables such as soil properties, topographic attributes, tillage, plant population, fertilization, irrigation, and pest infestations. A yield map...

Managing Potato Biodiversity to Cope with Frost Risk in the High Andes: A Modeling Perspective

PubMed Central

Condori, Bruno; Hijmans, Robert J.; Ledent, Jean Francois; Quiroz, Roberto

2014-01-01

Austral summer frosts in the Andean highlands are ubiquitous throughout the crop cycle, causing yield losses. In spite of the existing warming trend, climate change models forecast high variability, including freezing temperatures. As the potato center of origin, the region has a rich biodiversity which includes a set of frost resistant genotypes. Four contrasting potato genotypes –representing genetic variability- were considered in the present study: two species of frost resistant native potatoes (the bitter Solanum juzepczukii, var. Luki, and the non-bitter Solanum ajanhuiri, var. Ajanhuiri) and two commercial frost susceptible genotypes (Solanum tuberosum ssp. tuberosum var. Alpha and Solanum tuberosum ssp. andigenum var. Gendarme). The objective of the study was to conduct a comparative growth analysis of four genotypes and modeling their agronomic response under frost events. It included assessing their performance under Andean contrasting agroecological conditions. Independent subsets of data from four field experiments were used to parameterize, calibrate and validate a potato growth model. The validated model was used to ascertain the importance of biodiversity, represented by the four genotypes tested, as constituents of germplasm mixtures in single plots used by local farmers, a coping strategy in the face of climate variability. Also scenarios with a frost routine incorporated in the model were constructed. Luki and Ajanhuiri were the most frost resistant varieties whereas Alpha was the most susceptible. Luki and Ajanhuiri, as monoculture, outperformed the yield obtained with the mixtures under severe frosts. These results highlight the role played by local frost tolerant varieties, and featured the management importance –e.g. clean seed, strategic watering- to attain the yields reported in our experiments. The mixtures of local and introduced potatoes can thus not only provide the products demanded by the markets but also reduce the impact of frosts and thus the vulnerability of the system to abiotic stressors. PMID:24497912

Managing potato biodiversity to cope with frost risk in the high Andes: a modeling perspective.

PubMed

Condori, Bruno; Hijmans, Robert J; Ledent, Jean Francois; Quiroz, Roberto

2014-01-01

Austral summer frosts in the Andean highlands are ubiquitous throughout the crop cycle, causing yield losses. In spite of the existing warming trend, climate change models forecast high variability, including freezing temperatures. As the potato center of origin, the region has a rich biodiversity which includes a set of frost resistant genotypes. Four contrasting potato genotypes--representing genetic variability--were considered in the present study: two species of frost resistant native potatoes (the bitter Solanum juzepczukii, var. Luki, and the non-bitter Solanum ajanhuiri, var. Ajanhuiri) and two commercial frost susceptible genotypes (Solanum tuberosum ssp. tuberosum var. Alpha and Solanum tuberosum ssp. andigenum var. Gendarme). The objective of the study was to conduct a comparative growth analysis of four genotypes and modeling their agronomic response under frost events. It included assessing their performance under Andean contrasting agroecological conditions. Independent subsets of data from four field experiments were used to parameterize, calibrate and validate a potato growth model. The validated model was used to ascertain the importance of biodiversity, represented by the four genotypes tested, as constituents of germplasm mixtures in single plots used by local farmers, a coping strategy in the face of climate variability. Also scenarios with a frost routine incorporated in the model were constructed. Luki and Ajanhuiri were the most frost resistant varieties whereas Alpha was the most susceptible. Luki and Ajanhuiri, as monoculture, outperformed the yield obtained with the mixtures under severe frosts. These results highlight the role played by local frost tolerant varieties, and featured the management importance--e.g. clean seed, strategic watering--to attain the yields reported in our experiments. The mixtures of local and introduced potatoes can thus not only provide the products demanded by the markets but also reduce the impact of frosts and thus the vulnerability of the system to abiotic stressors.

Variable helium diffusion characteristics in fluorite

NASA Astrophysics Data System (ADS)

Wolff, R.; Dunkl, I.; Kempe, U.; Stockli, D.; Wiedenbeck, M.; von Eynatten, H.

2016-09-01

Precise analysis of the diffusion characteristics of helium in fluorite is crucial for establishing the new fluorite (U-Th-Sm)/He thermochronometer (FHe), which potentially provides a powerful tool for dating ore deposits unsuitable for the application of conventional geochronometers. Incremental helium outgassing experiments performed on fluorites derived from a spectrum of geological environments suggest a thermally activated volume diffusion mechanism. The diffusion behaviour is highly variable and the parameters range between log D0/a2 = 0.30 ± 0.27-7.27 ± 0.46 s-1 and Ea = 96 ± 3.5-182 ± 3.8 kJ/mol. Despite the fact that the CaF2 content of natural fluorites in most cases exceeds 99 weight percent, the closure temperature (Tc) of the fluorite (U-Th-Sm)/He thermochronometer as calculated from these diffusion parameters varies between 46 ± 14 °C and 169 ± 9 °C, considering a 125 μm fragment size. Here we establish that minor substitutions of calcium by rare earth elements and yttrium (REE + Y) and related charge compensation by sodium, fluorine, oxygen and/or vacancies in the fluorite crystal lattice have a significant impact on the diffusivity of helium in the mineral. With increasing REE + Y concentrations F vacancies are reduced and key diffusion pathways are narrowed. Consequently, a higher closure temperature is to be expected. An empirical case study confirms this variability: two fluorite samples from the same deposit (Horni Krupka, Czech Republic) with ca. 170 °C and ca. 43 °C Tc yield highly different (U-Th-Sm)/He ages of 290 ± 10 Ma and 79 ± 10 Ma, respectively. Accordingly, the fluorite sample with the high Tc could have quantitatively retained helium since the formation of the fluorite-bearing ores in the Permian, despite subsequent Mesozoic burial and associated regional hydrothermal heating. In contrast, the fluorite with the low Tc yields a Late Cretaceous age close to the apatite fission track (AFT) and apatite (U-Th)/He ages (AHe) from the same locality. Remarkably, thermal modelling of FHe yields comparable results to the well-established modelling based on AFT and AHe.

Optimization of ultrasound-assisted extraction of charantin from Momordica charantia fruits using response surface methodology

PubMed Central

Ahamad, Javed; Amin, Saima; Mir, Showkat R.

2015-01-01

Background: Momordica charantia Linn. (Cucurbitaceae) fruits are well known for their beneficial effects in diabetes that are often attributed to its bioactive component charantin. Objective: The aim of the present study is to develop and optimize an efficient protocol for the extraction of charantin from M. charantia fruits. Materials and Methods: Response surface methodology (RSM) was used for the optimization of ultrasound-assisted extraction (UAE) conditions. RSM was based on a three-level, three-variable Box-Behnken design (BBD), and the studied variables included solid to solvent ratio, extraction temperature, and extraction time. Results: The optimal conditions predicted by the BBD were: UAE with methanol: Water (80:20, v/v) at 46°C for 120 min with solid to solvent ratio of 1:26 w/v, under which the yield of charantin was 3.18 mg/g. Confirmation trials under slightly adjusted conditions yielded 3.12 ± 0.14 mg/g of charantin on dry weight basis of fruits. The result of UAE was also compared with Soxhlet extraction method and UAE was found 2.74-fold more efficient than the Soxhlet extraction for extracting charantin. Conclusions: A facile UAE protocol for a high extraction yield of charantin was developed and validated. PMID:26681889

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).

Generalized structural equations improve sexual-selection analyses

PubMed Central

Santini, Giacomo; Marchetti, Giovanni Maria; Focardi, Stefano

2017-01-01

Sexual selection is an intense evolutionary force, which operates through competition for the access to breeding resources. There are many cases where male copulatory success is highly asymmetric, and few males are able to sire most females. Two main hypotheses were proposed to explain this asymmetry: “female choice” and “male dominance”. The literature reports contrasting results. This variability may reflect actual differences among studied populations, but it may also be generated by methodological differences and statistical shortcomings in data analysis. A review of the statistical methods used so far in lek studies, shows a prevalence of Linear Models (LM) and Generalized Linear Models (GLM) which may be affected by problems in inferring cause-effect relationships; multi-collinearity among explanatory variables and erroneous handling of non-normal and non-continuous distributions of the response variable. In lek breeding, selective pressure is maximal, because large numbers of males and females congregate in small arenas. We used a dataset on lekking fallow deer (Dama dama), to contrast the methods and procedures employed so far, and we propose a novel approach based on Generalized Structural Equations Models (GSEMs). GSEMs combine the power and flexibility of both SEM and GLM in a unified modeling framework. We showed that LMs fail to identify several important predictors of male copulatory success and yields very imprecise parameter estimates. Minor variations in data transformation yield wide changes in results and the method appears unreliable. GLMs improved the analysis, but GSEMs provided better results, because the use of latent variables decreases the impact of measurement errors. Using GSEMs, we were able to test contrasting hypotheses and calculate both direct and indirect effects, and we reached a high precision of the estimates, which implies a high predictive ability. In synthesis, we recommend the use of GSEMs in studies on lekking behaviour, and we provide guidelines to implement these models. PMID:28809923

Bounds on internal state variables in viscoplasticity

NASA Technical Reports Server (NTRS)

Freed, Alan D.

1993-01-01

A typical viscoplastic model will introduce up to three types of internal state variables in order to properly describe transient material behavior; they are as follows: the back stress, the yield stress, and the drag strength. Different models employ different combinations of these internal variables--their selection and description of evolution being largely dependent on application and material selection. Under steady-state conditions, the internal variables cease to evolve and therefore become related to the external variables (stress and temperature) through simple functional relationships. A physically motivated hypothesis is presented that links the kinetic equation of viscoplasticity with that of creep under steady-state conditions. From this hypothesis one determines how the internal variables relate to one another at steady state, but most importantly, one obtains bounds on the magnitudes of stress and back stress, and on the yield stress and drag strength.

Production of biodiesel from Jatropha curcas L. oil catalyzed by SO₄²⁻/ZrO₂ catalyst: effect of interaction between process variables.

PubMed

Yee, Kian Fei; Lee, Keat Teong; Ceccato, Riccardo; Abdullah, Ahmad Zuhairi

2011-03-01

This study reports the conversion of Jatrophacurcas L. oil to biodiesel catalyzed by sulfated zirconia loaded on alumina catalyst using response surface methodology (RSM), specifically to study the effect of interaction between process variables on the yield of biodiesel. The transesterification process variables studied were reaction temperature, reaction duration, molar ratio of methanol to oil and catalyst loading. Results from this study revealed that individual as well as interaction between variables significantly affect the yield of biodiesel. With this information, it was found that 4h of reaction at 150°C, methanol to oil molar ratio of 9.88 mol/mol and 7.61 wt.% for catalyst loading gave an optimum biodiesel yield of 90.32 wt.%. The fuel properties of Jatropha biodiesel were characterized and it indeed met the specification for biodiesel according to ASTM D6751. Copyright © 2010 Elsevier Ltd. All rights reserved.

Predicted stand volume for Eucalyptus plantations by spatial analysis

NASA Astrophysics Data System (ADS)

Latifah, Siti; Teodoro, RV; Myrna, GC; Nathaniel, CB; Leonardo, M. F.

2018-03-01

The main objective of the present study was to assess nonlinear models generated by integrating the stand volume growth rate to estimate the growth and yield of Eucalyptus. The primary data was done for point of interest (POI) of permanent sample plots (PSPs) and inventory sample plots, in Aek Nauli sector, Simalungun regency,North Sumatera Province,Indonesia. from December 2008- March 2009. Today,the demand for forestry information has continued to grow over recent years. Because many forest managers and decision makers face complex decisions, reliable information has become the necessity. In the assessment of natural resources including plantation forests have been widely used geospatial technology.The yield of Eucalyptus plantations represented by merchantable volume as dependent variable while factors affecting yield namely stands variables and the geographic variables as independent variables. The majority of the areas in the study site has stand volume class 0 - 50 m3/ha with 16.59 ha or 65.85 % of the total study site.

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

Root carboxylate exudation capacity under phosphorus stress does not improve grain yield in green gram.

PubMed

Pandey, Renu; Meena, Surendra Kumar; Krishnapriya, Vengavasi; Ahmad, Altaf; Kishora, Naval

2014-06-01

Genetic variability in carboxylate exudation capacity along with improved root traits was a key mechanism for P-efficient green gram genotype to cope with P-stress but it did not increase grain yield. This study evaluates genotypic variability in green gram for total root carbon exudation under low phosphorus (P) using (14)C and its relationship with root exuded carboxylates, growth and yield potential in contrasting genotypes. Forty-four genotypes grown hydroponically with low (2 μM) and sufficient (100 μM) P concentrations were exposed to (14)CO2 to screen for total root carbon exudation. Contrasting genotypes were employed to study carboxylate exudation and their performance in soil at two P levels. Based on relative (14)C exudation and biomass, genotypes were categorized. Carboxylic acids were measured in exudates and root apices of contrasting genotypes belonging to efficient and inefficient categories. Oxalic and citric acids were released into the medium under low-P. PDM-139 (efficient) was highly efficient in carboxylate exudation as compared to ML-818 (inefficient). In low soil P, the reduction in biomass was higher in ML-818 as compared to PDM-139. Total leaf area and photosynthetic rate averaged for genotypes increased by 71 and 41 %, respectively, with P fertilization. Significantly, higher root surface area and volume were observed in PDM-139 under low soil P. Though the grain yield was higher in ML-818, the total plant biomass was significantly higher in PDM-139 indicating improved P uptake and its efficient translation into biomass. The higher carboxylate exudation capacity and improved root traits in the later genotype might be the possible adaptive mechanisms to cope with P-stress. However, it is not necessary that higher root exudation would result in higher grain yield.

Changes in rainfed and irrigated crop yield response to climate in the western US

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

As the global population increases and the climate changes, ensuring a secure food supply is increasingly important. One strategy is irrigation, which allows for crops to be grown outside their optimal climate growing regions and which buffers against climate variability. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources as it can lead to groundwater depletion and diminished surface water supplies. This study quantifies how crop yields are affected by climate variability and extremes and the impact of irrigation on crop yield increases under various growing-season climate conditions. To do this, we use historical climate data and county-level rainfed and irrigated crop yields for maize, soybean, winter and spring wheat over the US to analyze the relationship between climate, crop yields, and irrigation. We find that there are optimal climates, specific to each crop, where irrigation provides a benefit and other conditions where irrigation proves to have marginal, if any, benefits. Furthermore, the relationship between crop yields and climate has changed over the last decades, with a changing sensitivity in the relationship of soybean and winter wheat yields to certain climate variables, like crop reference evapotranspiration. These two conclusions have important implications for agricultural and water resource system planning, as it implies there are more optimal climate conditions where irrigation is particularly productive and regions where irrigation should be reconsidered as there is not a significant agricultural benefit and the water could be used more productively.

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.

Development and validation of equations utilizing lamb vision system output to predict lamb carcass fabrication yields.

PubMed

Cunha, B C N; Belk, K E; Scanga, J A; LeValley, S B; Tatum, J D; Smith, G C

2004-07-01

This study was performed to validate previous equations and to develop and evaluate new regression equations for predicting lamb carcass fabrication yields using outputs from a lamb vision system-hot carcass component (LVS-HCC) and the lamb vision system-chilled carcass LM imaging component (LVS-CCC). Lamb carcasses (n = 149) were selected after slaughter, imaged hot using the LVS-HCC, and chilled for 24 to 48 h at -3 to 1 degrees C. Chilled carcasses yield grades (YG) were assigned on-line by USDA graders and by expert USDA grading supervisors with unlimited time and access to the carcasses. Before fabrication, carcasses were ribbed between the 12th and 13th ribs and imaged using the LVS-CCC. Carcasses were fabricated into bone-in subprimal/primal cuts. Yields calculated included 1) saleable meat yield (SMY); 2) subprimal yield (SPY); and 3) fat yield (FY). On-line (whole-number) USDA YG accounted for 59, 58, and 64%; expert (whole-number) USDA YG explained 59, 59, and 65%; and expert (nearest-tenth) USDA YG accounted for 60, 60, and 67% of the observed variation in SMY, SPY, and FY, respectively. The best prediction equation developed in this trial using LVS-HCC output and hot carcass weight as independent variables explained 68, 62, and 74% of the variation in SMY, SPY, and FY, respectively. Addition of output from LVS-CCC improved predictive accuracy of the equations; the combined output equations explained 72 and 66% of the variability in SMY and SPY, respectively. Accuracy and repeatability of measurement of LM area made with the LVS-CCC also was assessed, and results suggested that use of LVS-CCC provided reasonably accurate (R2 = 0.59) and highly repeatable (repeatability = 0.98) measurements of LM area. Compared with USDA YG, use of the dual-component lamb vision system to predict cut yields of lamb carcasses improved accuracy and precision, suggesting that this system could have an application as an objective means for pricing carcasses in a value-based marketing system.

Essential climatic variables estimation with satellite imagery

NASA Astrophysics Data System (ADS)

Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

2016-12-01

According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms

PubMed Central

Dube, Timothy; Mutanga, Onisimo; Adam, Elhadi; Ismail, Riyad

2014-01-01

The quantification of aboveground biomass using remote sensing is critical for better understanding the role of forests in carbon sequestration and for informed sustainable management. Although remote sensing techniques have been proven useful in assessing forest biomass in general, more is required to investigate their capabilities in predicting intra-and-inter species biomass which are mainly characterised by non-linear relationships. In this study, we tested two machine learning algorithms, Stochastic Gradient Boosting (SGB) and Random Forest (RF) regression trees to predict intra-and-inter species biomass using high resolution RapidEye reflectance bands as well as the derived vegetation indices in a commercial plantation. The results showed that the SGB algorithm yielded the best performance for intra-and-inter species biomass prediction; using all the predictor variables as well as based on the most important selected variables. For example using the most important variables the algorithm produced an R2 of 0.80 and RMSE of 16.93 t·ha−1 for E. grandis; R2 of 0.79, RMSE of 17.27 t·ha−1 for P. taeda and R2 of 0.61, RMSE of 43.39 t·ha−1 for the combined species data sets. Comparatively, RF yielded plausible results only for E. dunii (R2 of 0.79; RMSE of 7.18 t·ha−1). We demonstrated that although the two statistical methods were able to predict biomass accurately, RF produced weaker results as compared to SGB when applied to combined species dataset. The result underscores the relevance of stochastic models in predicting biomass drawn from different species and genera using the new generation high resolution RapidEye sensor with strategically positioned bands. PMID:25140631

Diversity pattern in Sesamum mutants selected for a semi-arid cropping system.

PubMed

Murty, B R; Oropeza, F

1989-02-01

Due to the complex requirements of moisture stress, substantial genetic diversity with a wide array of character combinations and effective simultaneous selection for several variables is necessary for improving the productivity and adaptation of a component crop in order for it to fit into a cropping system under semi-arid tropical conditions. Sesamum indicum L. is grown in Venezuela after rice/sorghum/or maize under such conditions. A mutation breeding program was undertaken using six locally adapted varieties to develop genotypes suitable for the above system. The diversity pattern for nine variables was assessed by multivariate analysis in 301 M4 progenies. Analysis of the characteristic roots and principal components in three methods of selection, i.e., M2 bulks (A), individual plant selection throughout (B), and selection in M3 for single variable (C), revealed differences in the pattern of variation between varieties, selection methods, and varieties x methods interactions. Method B was superior to the others and gave 17 of the 21 best M5 progenies. 'Piritu' and 'CF' varieties yielded the most productive progenies in M5 and M6. Diversity was large and selection was effective for such developmental traits as earliness and synchrony, combined with multiple disease resistance, which could be related to their importance by multivariate analyses. Considerable differences in the variety of character combinations among the high yielding. M5 progenies of 'CF' and 'Piritu' suggested possible further yield improvement. The superior response of 'Piritu' and 'CF' over other varieties in yield and adaptation was due to major changes in plant type and character associations. Multilocation testing of M5 generations revealed that the mutant progenies had a 40%-100% yield superiority over the parents; this was combined with earliness, synchrony, and multiple disease resistance, and was confirmed in the M6 generation grown on a commercial scale. This study showed that multivariate analysis is an effective tool for assessing diversity patterns, choice of appropriate variety, and selection methodology in order to make rapid progress in meeting the complex requirements of semi-arid cropping systems.

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

NASA Technical Reports Server (NTRS)

Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

2011-01-01

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Stability Performance of Inductively Coupled Plasma Mass Spectrometry-Phenotyped Kernel Minerals Concentration and Grain Yield in Maize in Different Agro-Climatic Zones

PubMed Central

Mallikarjuna, Mallana Gowdra; Thirunavukkarasu, Nepolean; Hossain, Firoz; Bhat, Jayant S.; Jha, Shailendra K.; Rathore, Abhishek; Agrawal, Pawan Kumar; Pattanayak, Arunava; Reddy, Sokka S.; Gularia, Satish Kumar; Singh, Anju Mahendru; Manjaiah, Kanchikeri Math; Gupta, Hari Shanker

2015-01-01

Deficiency of iron and zinc causes micronutrient malnutrition or hidden hunger, which severely affects ~25% of global population. Genetic biofortification of maize has emerged as cost effective and sustainable approach in addressing malnourishment of iron and zinc deficiency. Therefore, understanding the genetic variation and stability of kernel micronutrients and grain yield of the maize inbreds is a prerequisite in breeding micronutrient-rich high yielding hybrids to alleviate micronutrient malnutrition. We report here, the genetic variability and stability of the kernel micronutrients concentration and grain yield in a set of 50 maize inbred panel selected from the national and the international centres that were raised at six different maize growing regions of India. Phenotyping of kernels using inductively coupled plasma mass spectrometry (ICP-MS) revealed considerable variability for kernel minerals concentration (iron: 18.88 to 47.65 mg kg–1; zinc: 5.41 to 30.85 mg kg–1; manganese: 3.30 to17.73 mg kg–1; copper: 0.53 to 5.48 mg kg–1) and grain yield (826.6 to 5413 kg ha–1). Significant positive correlation was observed between kernel iron and zinc within (r = 0.37 to r = 0.52, p < 0.05) and across locations (r = 0.44, p < 0.01). Variance components of the additive main effects and multiplicative interactions (AMMI) model showed significant genotype and genotype × environment interaction for kernel minerals concentration and grain yield. Most of the variation was contributed by genotype main effect for kernel iron (39.6%), manganese (41.34%) and copper (41.12%), and environment main effects for both kernel zinc (40.5%) and grain yield (37.0%). Genotype main effect plus genotype-by-environment interaction (GGE) biplot identified several mega environments for kernel minerals and grain yield. Comparison of stability parameters revealed AMMI stability value (ASV) as the better representative of the AMMI stability parameters. Dynamic stability parameter GGE distance (GGED) showed strong and positive correlation with both mean kernel concentrations and grain yield. Inbreds (CM-501, SKV-775, HUZM-185) identified from the present investigation will be useful in developing micronutrient-rich as well as stable maize hybrids without compromising grain yield. PMID:26406470

Stability Performance of Inductively Coupled Plasma Mass Spectrometry-Phenotyped Kernel Minerals Concentration and Grain Yield in Maize in Different Agro-Climatic Zones.

PubMed

Mallikarjuna, Mallana Gowdra; Thirunavukkarasu, Nepolean; Hossain, Firoz; Bhat, Jayant S; Jha, Shailendra K; Rathore, Abhishek; Agrawal, Pawan Kumar; Pattanayak, Arunava; Reddy, Sokka S; Gularia, Satish Kumar; Singh, Anju Mahendru; Manjaiah, Kanchikeri Math; Gupta, Hari Shanker

2015-01-01

Deficiency of iron and zinc causes micronutrient malnutrition or hidden hunger, which severely affects ~25% of global population. Genetic biofortification of maize has emerged as cost effective and sustainable approach in addressing malnourishment of iron and zinc deficiency. Therefore, understanding the genetic variation and stability of kernel micronutrients and grain yield of the maize inbreds is a prerequisite in breeding micronutrient-rich high yielding hybrids to alleviate micronutrient malnutrition. We report here, the genetic variability and stability of the kernel micronutrients concentration and grain yield in a set of 50 maize inbred panel selected from the national and the international centres that were raised at six different maize growing regions of India. Phenotyping of kernels using inductively coupled plasma mass spectrometry (ICP-MS) revealed considerable variability for kernel minerals concentration (iron: 18.88 to 47.65 mg kg(-1); zinc: 5.41 to 30.85 mg kg(-1); manganese: 3.30 to 17.73 mg kg(-1); copper: 0.53 to 5.48 mg kg(-1)) and grain yield (826.6 to 5413 kg ha(-1)). Significant positive correlation was observed between kernel iron and zinc within (r = 0.37 to r = 0.52, p < 0.05) and across locations (r = 0.44, p < 0.01). Variance components of the additive main effects and multiplicative interactions (AMMI) model showed significant genotype and genotype × environment interaction for kernel minerals concentration and grain yield. Most of the variation was contributed by genotype main effect for kernel iron (39.6%), manganese (41.34%) and copper (41.12%), and environment main effects for both kernel zinc (40.5%) and grain yield (37.0%). Genotype main effect plus genotype-by-environment interaction (GGE) biplot identified several mega environments for kernel minerals and grain yield. Comparison of stability parameters revealed AMMI stability value (ASV) as the better representative of the AMMI stability parameters. Dynamic stability parameter GGE distance (GGED) showed strong and positive correlation with both mean kernel concentrations and grain yield. Inbreds (CM-501, SKV-775, HUZM-185) identified from the present investigation will be useful in developing micronutrient-rich as well as stable maize hybrids without compromising grain yield.

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.

The Source of the PB1 Gene in Influenza Vaccine Reassortants Selectively Alters the Hemagglutinin Content of the Resulting Seed Virus

PubMed Central

Cobbin, Joanna C. A.; Verity, Erin E.; Gilbertson, Brad P.; Rockman, Steven P.

2013-01-01

The yields of egg-grown influenza vaccines are maximized by the production of a seed strain using a reassortment of the seasonal influenza virus isolate with a highly egg-adapted strain. The seed virus is selected based on high yields of viral hemagglutinin (HA) and expression of the surface antigens from the seasonal isolate. The remaining proteins are usually derived from the high-growth parent. However, a retrospective analysis of vaccine seeds revealed that the seasonal PB1 gene was selected in more than 50% of reassortment events. Using the model seasonal H3N2 virus A/Udorn/307/72 (Udorn) virus and the high-growth A/Puerto Rico/8/34 (PR8) virus, we assessed the influence of the source of the PB1 gene on virus growth and vaccine yield. Classical reassortment of these two strains led to the selection of viruses that predominantly had the Udorn PB1 gene. The presence of Udorn PB1 in the seed virus, however, did not result in higher yields of virus or HA compared to the yields in the corresponding seed virus with PR8 PB1. The 8-fold-fewer virions produced with the seed virus containing the Udorn PB1 were somewhat compensated for by a 4-fold increase in HA per virion. A higher HA/nucleoprotein (NP) ratio was found in past vaccine preparations when the seasonal PB1 was present, also indicative of a higher HA density in these vaccine viruses. As the HA viral RNA (vRNA) and mRNA levels in infected cells were similar, we propose that PB1 selectively alters the translation of viral mRNA. This study helps to explain the variability of vaccine seeds with respect to HA yield. PMID:23468502

Real-time fuzzy inference based robot path planning

NASA Technical Reports Server (NTRS)

Pacini, Peter J.; Teichrow, Jon S.

1990-01-01

This project addresses the problem of adaptive trajectory generation for a robot arm. Conventional trajectory generation involves computing a path in real time to minimize a performance measure such as expended energy. This method can be computationally intensive, and it may yield poor results if the trajectory is weakly constrained. Typically some implicit constraints are known, but cannot be encoded analytically. The alternative approach used here is to formulate domain-specific knowledge, including implicit and ill-defined constraints, in terms of fuzzy rules. These rules utilize linguistic terms to relate input variables to output variables. Since the fuzzy rulebase is determined off-line, only high-level, computationally light processing is required in real time. Potential applications for adaptive trajectory generation include missile guidance and various sophisticated robot control tasks, such as automotive assembly, high speed electrical parts insertion, stepper alignment, and motion control for high speed parcel transfer systems.

VizieR Online Data Catalog: RR Lyrae in SDSS Stripe 82 (Suveges+, 2012)

NASA Astrophysics Data System (ADS)

Suveges, M.; Sesar, B.; Varadi, M.; Mowlavi, N.; Becker, A. C.; Ivezic, Z.; Beck, M.; Nienartowicz, K.; Rimoldini, L.; Dubath, P.; Bartholdi, P.; Eyer, L.

2013-05-01

We propose a robust principal component analysis framework for the exploitation of multiband photometric measurements in large surveys. Period search results are improved using the time-series of the first principal component due to its optimized signal-to-noise ratio. The presence of correlated excess variations in the multivariate time-series enables the detection of weaker variability. Furthermore, the direction of the largest variance differs for certain types of variable stars. This can be used as an efficient attribute for classification. The application of the method to a subsample of Sloan Digital Sky Survey Stripe 82 data yielded 132 high-amplitude delta Scuti variables. We also found 129 new RR Lyrae variables, complementary to the catalogue of Sesar et al., extending the halo area mapped by Stripe 82 RR Lyrae stars towards the Galactic bulge. The sample also comprises 25 multiperiodic or Blazhko RR Lyrae stars. (8 data files).

Reequilibration of fluid inclusions in low-temperature calcium-carbonate cement

NASA Astrophysics Data System (ADS)

Goldstein, Robert H.

1986-09-01

Calcium-carbonate cements precipitated in low-temperature, near-surface, vadose environments contain fluid inclusions of variable vapor-to-liquid ratios that yield variable homogenization temperatures. Cements precipitated in low-temperature, phreatic environments contain one-phase, all-liquid fluid inclusions. Neomorphism of unstable calcium-carbonate phases may cause reequilibration of fluid inclusions. Stable calcium-carbonate cements of low-temperature origin, which have been deeply buried, contain fluid inclusions of variable homogenization temperature and variable salt composition. Most inclusion fluids are not representative of the fluids present during cement growth and are more indicative of burial pore fluids. Therefore, low-temperature fluid inclusions probably reequilibrate with burial fluids during progressive burial. Reequilibration is likely caused by high internal pressures in inclusions which result in hydrofracturing. The resulting fluid-inclusion population could contain a nearly complete record of burial fluids in which a particular rock has been bathed. *Present address: Department of Geology, University of Kansas, Lawrence, Kansas 66045

Sahelian rangeland response to changes in rainfall over two decades in the Gourma region, Mali

NASA Astrophysics Data System (ADS)

Hiernaux, Pierre; Mougin, Eric; Diarra, Lassine; Soumaguel, Nogmana; Lavenu, François; Tracol, Yann; Diawara, Mamadou

2009-08-01

SummaryTwenty-five rangeland sites were monitored over two decades (1984-2006) first to assess the impact of the 1983-1984 droughts on fodder resources, then to better understand ecosystem functioning and dynamics. Sites are sampled along the south-north bioclimatic gradient in Gourma (Mali), within three main edaphic situations: sandy, loamy-clay and shallow soils. In addition, three levels of grazing pressure where systematically sampled within sandy soils. Located at the northern edge of the area reached by the West African monsoon, the Gourma gradient has recorded extremes in inter-annual variations of rainfall and resulting variations in vegetation growth. Following rainfall variability, inter-annual variability of herbaceous yield increases as climate gets dryer with latitudes at least on the sandy soils sites. Local redistribution of rainfall explains the high patchiness of herbaceous vegetation, especially on shallow soils. Yet spatial heterogeneity of the vegetation does not buffer between year yield variability that increases with spatial heterogeneity. At short term, livestock grazing during the wet season affects plant growth and thus yield in direction and proportions that vary with the timing and intensity of grazing. In the longer term, grazing also impinges upon species composition in many ways. Hence, long histories of heavy grazing promote either long cycle annuals refused by livestock or else short cycle good quality feed species. Primary production is maintained or even increased in the case of refusal such as Sida cordifolia, and is lessened in the case of short cycle species such as Zornia glochidiata. These behaviours explain that the yield anomalies calculated for the rangelands on sandy soils relative to the yield of site less grazed under similar climate tend to be negative in northern Sahel where the scenario of short cycle species dominates, while yield anomalies are close to nil in centre Sahel and slightly positive in South Sahel where the refusal scenario is more frequent. Because grazing promotes short cycle species, grazed rangelands respond faster to droughts. Year to year changes in species composition are abrupt as expected from the transient soil seed stock. However, some decadal trends in species composition are identified, with a wave of pioneer species following the 1983-1984 droughts, and a more progressive diversification and return to typical Sahel flora from 1992 onwards.

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.;

Comparison of various RNA extraction methods, cDNA preparation and isolation of calmodulin gene from a highly melanized isolate of apple leaf blotch fungus Marssonina coronaria.

PubMed

Chauhan, Arjun; Sharma, J N; Modgil, Manju; Siddappa, Sundaresha

2018-05-29

Marssonina coronaria causes apple blotch disease resulting in severe premature defoliation, and is distributed in many leading apple-growing areas in the world. Effective, reliable and high-quality RNA extraction is an indispensable procedure in any molecular biology study. No method currently exists for RNA extraction from M. coronaria that produces a high quantity of melanin-free RNA. Therefore, we evaluated eight RNA extraction methods including manual and commercial kits, to yield a sufficient quantity of high-quality and melanin-free RNA. Manual methods used here resulted in low quality and black colored RNA pellets showing the presence of melanin, despite all the modifications employed to original procedures. However, these methods when coupled with clean up resulted in melanin-free RNA. On the other hand, all commercial kits used were able to yield high-quality melanin-free RNA having variable yields. TRIzol™ Reagent + RNA Clean & Concentrator™-5 and Ambion-PureLink® RNA Mini Kit were found to be the best methods as the RNA extracted with these methods from 15 day old fungal culture grown on solid medium were free of melanin with good yield. RNA extracted by this improved methodology was applied for RT-PCR, subsequent PCR amplification, and isolation of calmodulin gene sequences from M. coronaria and infected apple leaf pieces. These methods are more time effective than traditional methods and take only an hour to complete. To our knowledge, this is the first report on the method of isolation of high-quality RNA for cDNA synthesis as well as isolation of the calmodulin gene sequence from this fungus. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

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.

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

Chavas, Daniel R.; Izaurralde, Roberto C.; Thomson, Allison M.

Increasing atmospheric greenhouse gas concentrations are expected to induce significant climate change over the next century and beyond, but the impacts on society remain highly uncertain. This work examines potential climate change impacts on the productivity of five major crops in northeastern China: canola, corn, potato, rice, and winter wheat. In addition to determining domain-wide trends, the objective is to identify vulnerable and emergent regions under future climate conditions, defined as having a greater than 10% decrease and increase in productivity, respectively. Data from the ICTP RegCM3 regional climate model for baseline (1961-1990) and future (2071-2100) periods under A2 scenariomore » conditions are used as input in the EPIC agro-ecosystem simulation model in the domain [30ºN, 108ºE] to [42ºN, 123ºE]. Simulations are performed with and without the enhanced CO2 fertilization effect. Results indicate that aggregate potential productivity (i.e. if the crop is grown everywhere) increases 6.5% for rice, 8.3% for canola, 18.6% for corn, 22.9% for potato, and 24.9% for winter wheat, although with significant spatial variability for each crop. However, absent the enhanced CO2 fertilization effect, potential productivity declines in all cases ranging from 2.5-12%. Interannual yield variability remains constant or declines in all cases except rice. Climate variables are found to be more significant drivers of simulated yield changes than changes in soil properties, except in the case of potato production in the northwest where the effects of wind erosion are more significant. Overall, in the future period corn and winter wheat benefit significantly in the North China Plain, rice remains dominant in the southeast and emerges in the northeast, potato and corn yields become viable in the northwest, and potato yields suffer in the southwest with no other crop emerging as a clear beneficiary from among those simulated in this study.« less

Future consequences of decreasing marginal production efficiency in the high-yielding dairy cow.

PubMed

Moallem, U

2016-04-01

The objectives were to examine the gross and marginal production efficiencies in high-yielding dairy cows and the future consequences on dairy industry profitability. Data from 2 experiments were used in across-treatments analysis (n=82 mid-lactation multiparous Israeli-Holstein dairy cows). Milk yields, body weights (BW), and dry matter intakes (DMI) were recorded daily. In both experiments, cows were fed a diet containing 16.5 to 16.6% crude protein and net energy for lactation (NEL) at 1.61 Mcal/kg of dry matter (DM). The means of milk yield, BW, DMI, NEL intake, and energy required for maintenance were calculated individually over the whole study, and used to calculate gross and marginal efficiencies. Data were analyzed in 2 ways: (1) simple correlation between variables; and (2) cows were divided into 3 subgroups, designated low, moderate, and high DMI (LDMI, MDMI, and HDMI), according to actual DMI per day: ≤ 26 kg (n=27); >26 through 28.2 kg (n=28); and >28.2 kg (n=27). The phenotypic Pearson correlations among variables were analyzed, and the GLM procedure was used to test differences between subgroups. The relationships between milk and fat-corrected milk yields and the corresponding gross efficiencies were positive, whereas BW and gross production efficiency were negatively correlated. The marginal production efficiency from DM and energy consumed decreased with increasing DMI. The difference between BW gain as predicted by the National Research Council model (2001) and the present measurements increased with increasing DMI (r=0.68). The average calculated energy balances were 1.38, 2.28, and 4.20 Mcal/d (standard error of the mean=0.64) in the LDMI, MDMI, and HDMI groups, respectively. The marginal efficiency for milk yields from DMI or energy consumed was highest in LDMI, intermediate in MDMI, and lowest in HDMI. The predicted BW gains for the whole study period were 22.9, 37.9, and 75.8 kg for the LDMI, MDMI, and HDMI groups, respectively. The present study demonstrated that marginal production efficiency decreased with increasing feed intake. Because of the close association between production and intake, the principle of diminishing marginal productivity may explain why increasing milk production (and consequently increasing intake) does not always enhance profitability. To maintain high production efficiency in the future, more attention should be given to optimizing rather than maximizing feed intake, a goal that could be achieved by nutritional manipulations that would increase digestibility or by using a diet of denser nutrients that would provide all nutritional requirements from lower intake. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Rice yield in response to climate trends and drought index in the Mun River Basin, Thailand.

PubMed

Prabnakorn, Saowanit; Maskey, Shreedhar; Suryadi, F X; de Fraiture, Charlotte

2018-04-15

Rice yields in Thailand are among the lowest in Asia. In northeast Thailand where about 90% of rice cultivation is rain-fed, climate variability and change affect rice yields. Understanding climate characteristics and their impacts on the rice yield is important for establishing proper adaptation and mitigation measures to enhance productivity. In this paper, we investigate climatic conditions of the past 30years (1984-2013) and assess the impacts of the recent climate trends on rice yields in the Mun River Basin in northeast Thailand. We also analyze the relationship between rice yield and a drought indicator (Standardized Precipitation and Evapotranspiration Index, SPEI), and the impact of SPEI trends on the yield. Our results indicate that the total yield losses due to past climate trends are rather low, in the range of <50kg/ha per decade (3% of actual average yields). In general, increasing trends in minimum and maximum temperatures lead to modest yield losses. In contrast, precipitation and SPEI-1, i.e. SPEI based on one monthly data, show positive correlations with yields in all months, except in the wettest month (September). If increasing trends of temperatures during the growing season persist, a likely climate change scenario, there is high possibility that the yield losses will become more serious in future. In this paper, we show that the drought index SPEI-1 detects soil moisture deficiency and crop stress in rice better than precipitation or precipitation based indicators. Further, our results emphasize the importance of spatial and temporal resolutions in detecting climate trends and impacts on yields. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

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

Production of single cell protein from cellulose wastes

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

Humphrey, A.E.; Moreira, A.; Armiger, W.

1977-01-01

Experiments made with a thermophilic Actinomyces that utilizes cellulose for growth are summarized. The organism, identified as a Thermoactinomyces sp., is a highly filamentous fungi. Although initial work was done with feedlot wastes, the variability of the data made it necessary to work on a uniform cellulose substrate Avicel. A probable mechanism of cellulose degradation by this fungi is suggested. Preliminary results are encouraging, but high growth rate must be maintained if a high cell yield is to be achieved. Both glucose and oxygen-limited growth were encountered; it is not known if these were coincidental or not. (JSR)

Quantitative Genetic Analysis Reveals Potential to Genetically Improve Fruit Yield and Drought Resistance Simultaneously in Coriander

PubMed Central

Khodadadi, Mostafa; Dehghani, Hamid; Jalali Javaran, Mokhtar

2017-01-01

Enhancing water use efficiency of coriander (Coriandrum sativum L.) is a major focus for coriander breeding to cope with drought stress. The purpose of this study was; (a) to identify the predominant mechanism(s) of drought resistance in coriander and (b) to evaluate the genetic control mechanism(s) of traits associated with drought resistance and higher fruit yield. To reach this purpose, 15 half-diallel hybrids of coriander and their six parents were evaluated under well-watered and water deficit stressed (WDS) in both glasshouse lysimetric and field conditions. The parents were selected for their different response to water deficit stress following preliminary experiments. Results revealed that the genetic control mechanism of fruit yield is complex, variable and highly affected by environment. The mode of inheritance and nature of gene action for percent assimilate partitioned to fruits were similar to those for flowering time in both well-watered and WDS conditions. A significant negative genetic linkage was found between fruit yield and percent assimilate partitioned to root, percent assimilate partitioned to shoot, root number, root diameter, root dry mass, root volume, and early flowering. Thus, to improve fruit yield under water deficit stress, selection of low values of these traits could be used. In contrast, a significant positive genetic linkage between fruit yield and percent assimilate partitioned to fruits, leaf relative water content and chlorophyll content indicate selection for high values of these traits. These secondary or surrogate traits could be selected during early segregating generations. The early ripening parent (P1; TN-59-230) contained effective genes involved in preferred percent assimilate partitioning to fruit and drought stress resistance. In conclusion, genetic improvement of fruit yield and drought resistance could be simultaneously gained in coriander when breeding for drought resistance. PMID:28473836

Advanced reliability methods for structural evaluation

NASA Technical Reports Server (NTRS)

Wirsching, P. H.; Wu, Y.-T.

1985-01-01

Fast probability integration (FPI) methods, which can yield approximate solutions to such general structural reliability problems as the computation of the probabilities of complicated functions of random variables, are known to require one-tenth the computer time of Monte Carlo methods for a probability level of 0.001; lower probabilities yield even more dramatic differences. A strategy is presented in which a computer routine is run k times with selected perturbed values of the variables to obtain k solutions for a response variable Y. An approximating polynomial is fit to the k 'data' sets, and FPI methods are employed for this explicit form.

Climate risks on potato yield in Europe

NASA Astrophysics Data System (ADS)

Sun, Xun; Lall, Upmanu

2016-04-01

The yield of potatoes is affected by water and temperature during the growing season. We study the impact of a suite of climate variables on potato yield at country level. More than ten climate variables related to the growth of potato are considered, including the seasonal rainfall and temperature, but also extreme conditions at different averaging periods from daily to monthly. A Bayesian hierarchical model is developed to jointly consider the risk of heat stress, cold stress, wet and drought. Future climate risks are investigated through the projection of future climate data. This study contributes to assess the risks of present and future climate risks on potatoes yield, especially the risks of extreme events, which could be used to guide better sourcing strategy and ensure food security in the future.

Precision of coherence analysis to detect cerebral autoregulation by near-infrared spectroscopy in preterm infants

NASA Astrophysics Data System (ADS)

Hahn, Gitte Holst; Christensen, Karl Bang; Leung, Terence S.; Greisen, Gorm

2010-05-01

Coherence between spontaneous fluctuations in arterial blood pressure (ABP) and the cerebral near-infrared spectroscopy signal can detect cerebral autoregulation. Because reliable measurement depends on signals with high signal-to-noise ratio, we hypothesized that coherence is more precisely determined when fluctuations in ABP are large rather than small. Therefore, we investigated whether adjusting for variability in ABP (variabilityABP) improves precision. We examined the impact of variabilityABP within the power spectrum in each measurement and between repeated measurements in preterm infants. We also examined total monitoring time required to discriminate among infants with a simulation study. We studied 22 preterm infants (GA<30) yielding 215 10-min measurements. Surprisingly, adjusting for variabilityABP within the power spectrum did not improve the precision. However, adjusting for the variabilityABP among repeated measurements (i.e., weighting measurements with high variabilityABP in favor of those with low) improved the precision. The evidence of drift in individual infants was weak. Minimum monitoring time needed to discriminate among infants was 1.3-3.7 h. Coherence analysis in low frequencies (0.04-0.1 Hz) had higher precision and statistically more power than in very low frequencies (0.003-0.04 Hz). In conclusion, a reliable detection of cerebral autoregulation takes hours and the precision is improved by adjusting for variabilityABP between repeated measurements.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

PubMed Central

Jiménez, Daniel; Dorado, Hugo; Cock, James; Prager, Steven D.; Delerce, Sylvain; Grillon, Alexandre; Andrade Bejarano, Mercedes; Benavides, Hector; Jarvis, Andy

2016-01-01

Agriculture research uses “recommendation domains” to develop and transfer crop management practices adapted to specific contexts. The scale of recommendation domains is large when compared to individual production sites and often encompasses less environmental variation than farmers manage. Farmers constantly observe crop response to management practices at a field scale. These observations are of little use for other farms if the site and the weather are not described. The value of information obtained from farmers’ experiences and controlled experiments is enhanced when the circumstances under which it was generated are characterized within the conceptual framework of a recommendation domain, this latter defined by Non-Controllable Factors (NCFs). Controllable Factors (CFs) refer to those which farmers manage. Using a combination of expert guidance and a multi-stage analytic process, we evaluated the interplay of CFs and NCFs on plantain productivity in farmers’ fields. Data were obtained from multiple sources, including farmers. Experts identified candidate variables likely to influence yields. The influence of the candidate variables on yields was tested through conditional forests analysis. Factor analysis then clustered harvests produced under similar NCFs, into Homologous Events (HEs). The relationship between NCFs, CFs and productivity in intercropped plantain were analyzed with mixed models. Inclusion of HEs increased the explanatory power of models. Low median yields in monocropping coupled with the occasional high yields within most HEs indicated that most of these farmers were not using practices that exploited the yield potential of those HEs. Varieties grown by farmers were associated with particular HEs. This indicates that farmers do adapt their management to the particular conditions of their HEs. Our observations confirm that the definition of HEs as recommendation domains at a small-scale is valid, and that the effectiveness of distinct management practices for specific micro-recommendation domains can be identified with the methodologies developed. PMID:26930552

On locally and nonlocally related potential systems

NASA Astrophysics Data System (ADS)

Cheviakov, Alexei F.; Bluman, George W.

2010-07-01

For any partial differential equation (PDE) system, a local conservation law yields potential equations in terms of some potential variable, which normally is a nonlocal variable. The current paper examines situations when such a potential variable is a local variable, i.e., is a function of the independent and dependent variables of a given PDE system, and their derivatives. In the case of two independent variables, a simple necessary and sufficient condition is presented for the locality of such a potential variable, and this is illustrated by several examples. As a particular example, two-dimensional reductions of equilibrium equations for fluid and plasma dynamics are considered. It is shown that such reductions with respect to helical, axial, and translational symmetries have conservation laws which yield local potential variables. This leads to showing that the well-known Johnson-Frieman-Kruskal-Oberman (JFKO) and Bragg-Hawthorne (Grad-Shafranov) equations are locally related to the corresponding helically and axially symmetric PDE systems of fluid/plasma dynamics. For the axially symmetric case, local symmetry classifications and arising invariant solutions are compared for the original PDE system and the Bragg-Hawthorne (potential) equation. The potential equation is shown to have additional symmetries, denoted as restricted symmetries. Restricted symmetries leave invariant a family of solutions of a given PDE system but not the whole solution manifold, and hence are not symmetries of the given PDE system. Corresponding reductions are shown to yield solutions, which are not obtained as invariant solutions from local symmetry reduction.

Relationship of goat milk flow emission variables with milking routine, milking parameters, milking machine characteristics and goat physiology.

PubMed

Romero, G; Panzalis, R; Ruegg, P

2017-11-01

The aim of this paper was to study the relationship between milk flow emission variables recorded during milking of dairy goats with variables related to milking routine, goat physiology, milking parameters and milking machine characteristics, to determine the variables affecting milking performance and help the goat industry pinpoint farm and milking practices that improve milking performance. In total, 19 farms were visited once during the evening milking. Milking parameters (vacuum level (VL), pulsation ratio and pulsation rate, vacuum drop), milk emission flow variables (milking time, milk yield, maximum milk flow (MMF), average milk flow (AVMF), time until 500 g/min milk flow is established (TS500)), doe characteristics of 8 to 10 goats/farm (breed, days in milk and parity), milking practices (overmilking, overstripping, pre-lag time) and milking machine characteristics (line height, presence of claw) were recorded on every farm. The relationships between recorded variables and farm were analysed by a one-way ANOVA analysis. The relationships of milk yield, MMF, milking time and TS500 with goat physiology, milking routine, milking parameters and milking machine design were analysed using a linear mixed model, considering the farm as the random effect. Farm was significant (P<0.05) in all the studied variables. Milk emission flow variables were similar to those recommended in scientific studies. Milking parameters were adequate in most of the farms, being similar to those recommended in scientific studies. Few milking parameters and milking machine characteristics affected the tested variables: average vacuum level only showed tendency on MMF, and milk pipeline height on TS500. Milk yield (MY) was mainly affected by parity, as the interaction of days in milk with parity was also significant. Milking time was mainly affected by milk yield and breed. Also significant were parity, the interaction of days in milk with parity and overstripping, whereas overmilking showed a slight tendency. We concluded that most of the studied variables were mainly related to goat physiology characteristics, as the effects of milking parameters and milking machine characteristics were scarce.

Bioactive compounds and antioxidant activity exhibit high intraspecific variability in Pleurotus ostreatus mushrooms and correlate well with cultivation performance parameters.

PubMed

Koutrotsios, Georgios; Kalogeropoulos, Nick; Stathopoulos, Pantelis; Kaliora, Andriana C; Zervakis, Georgios I

2017-05-01

Experimental data related with oyster mushroom production and nutritional properties usually derive from the examination of only one strain, and hence their representativeness/usefulness is questionable. This work aims at assessing intraspecific variability in Pleurotus ostreatus by studying 16 strains, under the same conditions, in respect to essential cultivation and mushroom quality aspects, and by defining the impact of intrinsic/genetic factors on such parameters. Hence, mushroom yield, earliness, crop length, biological efficiency, productivity, and their content in selected macro and microconstituents (e.g. fatty acids, sterols, individual phenolic compounds, terpenic acids, glucans) as well as their antioxidant properties (i.e., antiradical activity, ferric reducing potential, inhibition of serum oxidation) were assayed. The effect of intrinsic/genetic factors was evident, especially as regards earliness, yield of each production flush and mushroom weight, whereas biological efficiency was not particularly influenced by the cultivated strain. Moreover, phenolics, ergosterol and antiradical activity demonstrated significant variability among strains in contrast to what was observed for fatty acids, β-glucans and ferric reducing potential. The observed heterogeneity reveals the limitations of using a low number of strains for evaluating mushroom production and/or their content in bioactive compounds, and as evidenced, it is valuable for breeding and commercial purposes.

Variability of High-Resolution Sea Surface Heights on a Broad, Shallow Continental Shelf

NASA Astrophysics Data System (ADS)

Crout, R. L.; Rice, A. E.

2017-12-01

Recent satellite altimeter technologies and processing methodologies are allowing investigation of the dynamics of the continental shelf as never before. The region seaward of 20 km from the coast is a region where winds, tides, currents, river discharge, and bathymetry interact. All of these are important parameters to understand when applying coastal altimetry to coastal sea level monitoring. Processing of 8 years (July 2008 to July 2016) of Jason-2 altimeter 20 Hz data from the L2 AVISO-PISTACH experimental products yields nearly 300 crossings of the broad continental shelf to the southeast of Delaware Bay from Cape May, NJ. Removal of a mean surface yields individual crossings that, plotted together, form an envelope that shows high water level variability near the coast. Water level changes near the coast begin at a hinge point that occurs approximately 50 km from shore in less than 30 meters of water. Comparison of individual Jason-2 passes with regional weather patterns, cold front passages, local winds, tides, surface currents, river discharge, and regional oceanography provides information regarding the forcing factors for these regional water levels. The water levels farther than 20 km from shore show similar patterns to the low pass filtered tide data at Cape May, NJ and respond primarily to regional forcing.

Meteorological fluctuations define long-term crop yield patterns in conventional and organic production systems

USDA-ARS?s Scientific Manuscript database

Periodic variability in meteorological patterns presents significant challenges to crop production consistency and yield stability. Meteorological influences on corn and soybean grain yields were analyzed over an 18-year period at a long-term experiment in Beltsville, Maryland, U.S.A., comparing c...

A Geostatistical Approach to the Trickle Irrigation Design in a Heterogeneous Soil 2. A Field Test

NASA Astrophysics Data System (ADS)

Russo, David

1984-05-01

In a heterogeneous field in which the soil water properties vary under a "deterministic" uniform trickle irrigation system, the midway soil-water pressure head hc and the yield of a crop also differ from place to place. These differences may, in turn, reduce the average (over the field) yield relative to the yield that would be obtained if the soil was uniform throughout the field. A field experiment was conducted to test the hypothesis that this yield reduction may be eliminated by using a spatially variable trickle irrigation system. Twenty-five plots (200 m2 each) were established on a 30-m2 grid. Half of each plot was equipped with a standard trickle irrigation system with constant spacing between emitters of d = 50 cm (control plots), and the other half was equipped with a trickle irrigation system for which the spacing between the emitters was selected by using the pertinent hydraulic properties (the saturated hydraulic conductivity Ks and the soil parameter α) according to the procedure of Bresler (1978) as described in paper 1 (Russo, 1983b). Values of hc measured at different times, as well as the total fruit yield Y of bell pepper (Capsicum frutescens var. "Maor"), were used to estimate the seasonal and the spatial distributions of hc and the spatial distribution of Y and their moments. The variograms of hc and Y were calculated and used to estimate their integral scales. It was found that the use of a spatially variable d relative to the use of a uniform d did not change the seasonal behavior of hc but reduced the spatial variability in hc and Y by 35% and 11%, respectively, and increased the integral scale of hc and Y by 30% and 10%, respectively, but increased the average total fruit yield by only 1.9%. The use of a spatially variable d reduced the dependence of Y on hc. This indicates that when the emitters are properly spaced, it is not the water but other factors that most influence yield. When a constant d was used, the dependence of Y of hc decreased with time. This and the relatively good agreement between the values of hc measured at the initial stages of the growing season and those calculated in paper 1 demonstrate that the concept of hc is important in the early stages of the plant's growth, when the root system is not fully developed. Both the theoretical (paper 1) and the experimental results showed that although Ks and α, as well as hc, varied considerably in the field the spatial variability of the crop yield was relatively small. This explains why the use of a spatially variable d essentially was not an improvement over the fixed d. It is suggested that this study will be considered as a methodological one, which can be adapted to solve practical problems associated with field spatial variability.

Towards a high yield recovery of polyphenols from olive mill wastewater on activated carbon coated with milk proteins: Experimental design and antioxidant activity.

PubMed

Yangui, Asma; Abderrabba, Manef

2018-10-01

Activated carbon coated with milk proteins was used for the removal and recovery of phenolic compounds from actual olive mill wastewater (OMW). The extraction of polyphenols using the new adsorbent based on natural coating agent has significant potential compared with traditional extraction methods, as it significantly increases the extraction yield (80%) and overall efficiencies of the process for total phenols (75.4%) and hydroxytyrosol (90.6%) which is the most valuable compound. Complete discussions on the adsorption isotherms, kinetic and thermodynamic were performed and the optimum adsorption variables were investigated using the response surface methodology and the central composite experimental design. The extracted polyphenols exhibited a high antioxidant activity and a fast scavenging effect on DPPH free radical. The strategy devised in this work for polyphenol extraction using modified activated carbon with biological coating agent is of simple design, very effective and ensure the recovery of highly antioxidant extract. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Increased yield stability of field-grown winter barley (Hordeum vulgare L.) varietal mixtures through ecological processes

PubMed Central

Creissen, Henry E.; Jorgensen, Tove H.; Brown, James K.M.

2016-01-01

Crop variety mixtures have the potential to increase yield stability in highly variable and unpredictable environments, yet knowledge of the specific mechanisms underlying enhanced yield stability has been limited. Ecological processes in genetically diverse crops were investigated by conducting field trials with winter barley varieties (Hordeum vulgare), grown as monocultures or as three-way mixtures in fungicide treated and untreated plots at three sites. Mixtures achieved yields comparable to the best performing monocultures whilst enhancing yield stability despite being subject to multiple predicted and unpredicted abiotic and biotic stresses including brown rust (Puccinia hordei) and lodging. There was compensation through competitive release because the most competitive variety overyielded in mixtures thereby compensating for less competitive varieties. Facilitation was also identified as an important ecological process within mixtures by reducing lodging. This study indicates that crop varietal mixtures have the capacity to stabilise productivity even when environmental conditions and stresses are not predicted in advance. Varietal mixtures provide a means of increasing crop genetic diversity without the need for extensive breeding efforts. They may confer enhanced resilience to environmental stresses and thus be a desirable component of future cropping systems for sustainable arable farming. PMID:27375312

Managment oriented analysis of sediment yield time compression

NASA Astrophysics Data System (ADS)

Smetanova, Anna; Le Bissonnais, Yves; Raclot, Damien; Nunes, João P.; Licciardello, Feliciana; Le Bouteiller, Caroline; Latron, Jérôme; Rodríguez Caballero, Emilio; Mathys, Nicolle; Klotz, Sébastien; Mekki, Insaf; Gallart, Francesc; Solé Benet, Albert; Pérez Gallego, Nuria; Andrieux, Patrick; Moussa, Roger; Planchon, Olivier; Marisa Santos, Juliana; Alshihabi, Omran; Chikhaoui, Mohamed

2016-04-01

The understanding of inter- and intra-annual variability of sediment yield is important for the land use planning and management decisions for sustainable landscapes. It is of particular importance in the regions where the annual sediment yield is often highly dependent on the occurrence of few large events which produce the majority of sediments, such as in the Mediterranean. This phenomenon is referred as time compression, and relevance of its consideration growths with the increase in magnitude and frequency of extreme events due to climate change in many other regions. So far, time compression has ben studied mainly on events datasets, providing high resolution, but (in terms of data amount, required data precision and methods), demanding analysis. In order to provide an alternative simplified approach, the monthly and yearly time compressions were evaluated in eight Mediterranean catchments (of the R-OSMed network), representing a wide range of Mediterranean landscapes. The annual sediment yield varied between 0 to ~27100 Mg•km-2•a-1, and the monthly sediment yield between 0 to ~11600 Mg•km-2•month-1. The catchment's sediment yield was un-equally distributed at inter- and intra-annual scale, and large differences were observed between the catchments. Two types of time compression were distinguished - (i) the inter-annual (based on annual values) and intra- annual (based on monthly values). Four different rainfall-runoff-sediment yield time compression patterns were observed: (i) no time-compression of rainfall, runoff, nor sediment yield, (ii) low time compression of rainfall and runoff, but high compression of sediment yield, (iii) low compression of rainfall and high of runoff and sediment yield, and (iv) low, medium and high compression of rainfall, runoff and sediment yield. All four patterns were present at inter-annual scale, while at intra-annual scale only the two latter were present. This implies that high sediment yields occurred in particular months, even in catchment with low or no inter-annual time compression. The analysis of seasonality of time compression showed that in most of the catchments large sediment yields were more likely to occur between October and January, while in two catchments it was in summer (June and July). The appropriate sediment yield management measure: enhancement of soil properties, (dis)connectivity measures or vegetation cover, should therefore be selected with regard to the type of inter-annual time compression, to the properties of the individual catchments, and to the magnitudes of sediment yield. To increase the effectivity and lower the costs of the applied measures, the management in the months or periods when large sediment yields are most likely to occur should be prioritized. The analysis of the monthly time compression might be used for their identification in areas where no event datasets are available. The R-OSMed network of Mediterranean erosion research catchments was funded by "SicMed-Mistrals" grants from 2011 to 2014. Anna Smetanová has received the support of the European Union, in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills' fellowship (under grant agreement n° 267196). João Pedro Nunes has received support from the European Union (in the framework of the European Social Fund) and the Portuguese Government under a post-doctoral fellowship (SFRH/BPD/87571/2012).

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

Crop-ecology and nutritional variability influence growth and secondary metabolites of Stevia rebaudiana Bertoni.

PubMed

Pal, Probir Kumar; Kumar, Rajender; Guleria, Vipan; Mahajan, Mitali; Prasad, Ramdeen; Pathania, Vijaylata; Gill, Baljinder Singh; Singh, Devinder; Chand, Gopi; Singh, Bikram; Singh, Rakesh Deosharan; Ahuja, Paramvir Singh

2015-02-27

Plant nutrition and climatic conditions play important roles on the growth and secondary metabolites of stevia (Stevia rebaudiana Bertoni); however, the nutritional dose is strongly governed by the soil properties and climatic conditions of the growing region. In northern India, the interactive effects of crop ecology and plant nutrition on yield and secondary metabolites of stevia are not yet properly understood. Thus, a field experiment comprising three levels of nitrogen, two levels of phosphorus and three levels of potassium was conducted at three locations to ascertain whether the spatial and nutritional variability would dominate the leaf yield and secondary metabolites profile of stevia. Principal component analysis (PCA) indicates that the applications of 90 kg N, 40 kg P2O5 and 40 kg K2O ha-1 are the best nutritional conditions in terms of dry leaf yield for CSIR-IHBT (Council of Scientific and Industrial Research- Institute Himalayan Bioresource Technology) and RHRS (Regional Horticultural Research Station) conditions. The spatial variability also exerted considerable effect on the leaf yield and stevioside content in leaves. Among the three locations, CSIR-IHBT was found most suitable in case of dry leaf yield and secondary metabolites accumulation in leaves. The results suggest that dry leaf yield and accumulation of stevioside are controlled by the environmental factors and agronomic management; however, the accumulation of rebaudioside-A (Reb-A) is not much influenced by these two factors. Thus, leaf yield and secondary metabolite profiles of stevia can be improved through the selection of appropriate growing locations and proper nutrient management.

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

USGS Publications Warehouse

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

2015-01-01

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

Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?

USDA-ARS?s Scientific Manuscript database

Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...

A provisional effective evaluation when errors are present in independent variables

NASA Technical Reports Server (NTRS)

Gurin, L. S.

1983-01-01

Algorithms are examined for evaluating the parameters of a regression model when there are errors in the independent variables. The algorithms are fast and the estimates they yield are stable with respect to the correlation of errors and measurements of both the dependent variable and the independent variables.

Evaluation of Street Sweeping as a Stormwater-Quality-Management Tool in Three Residential Basins in Madison, Wisconsin

USGS Publications Warehouse

Selbig, William R.; Bannerman, Roger T.

2007-01-01

Recent technological improvements have increased the ability of street sweepers to remove sediment and other debris from street surfaces; the effect of these technological advancements on stormwater quality is largely unknown. The U.S. Geological Survey, in cooperation with the City of Madison and the Wisconsin Department of Natural Resources, evaluated three street-sweeper technologies from 2002 through 2006. Regenerative-air, vacuum-assist, and mechanical-broom street sweepers were operated on a frequency of once per week (high frequency) in separate residential basins in Madison, Wis., to measure each sweeper's ability to not only reduce street-dirt yield but also improve the quality of stormwater runoff. A second mechanical-broom sweeper operating on a frequency of once per month (low frequency) was also evaluated to measure reductions in street-dirt yield only. A paired-basin study design was used to compare street-dirt and stormwater-quality samples during a calibration (no sweeping) and a treatment period (weekly sweeping). The basis of this paired-basin approach is that the relation between paired street-dirt and stormwater-quality loads for the control and tests basins is constant until a major change is made at one of the basins. At that time, a new relation will develop. Changes in either street-dirt and/or stormwater quality as a result of street sweeping could then be quantified by use of statistical tests. Street-dirt samples collected weekly during the calibration period and twice per week during the treatment period, once before and once after sweeping, were dried and separated into seven particle-size fractions ranging from less than 63 micrometers to greater than 2 millimeters. Street-dirt yield evaluation was based on a computed mass per unit length of pounds per curb-mile. An analysis of covariance was used to measure the significance of the effect of street sweeping at the end of the treatment period and to quantify any reduction in street-dirt yield. Both the regenerative-air and vacuum-assist sweepers produced reductions in street-dirt yield at the 5-percent significance level. Street-dirt yield was reduced by an average of 76, 63, and 20 percent in the regenerative-air, vacuum-assist, and high-frequency broom basins, respectively. The low-frequency broom basin showed no significant reductions in street-dirt yield. Sand-size particles (greater than 63 micrometers) recorded the greatest overall reduction. Street-sweeper pickup efficiency was determined by computing the difference between weekly street-dirt yields before and after sweeping cleaning. The regenerative-air and vacuum-assist sweepers had similar pickup efficiencies of 25 and 30 percent, respectively. The mechanical broom sweeper operating at high frequency was considerably less efficient, removing an average of 5 percent of street-dirt yield. The effects of street sweeping on stormwater quality were evaluated by use of statistical tests to compare event mean concentrations and loads computed for individual storms at the control and test basins. Loads were computed by multiplying the event mean concentrations by storm-runoff volumes. Only ammonia-nitrogen for the test basin with the vacuum-assist sweeper showed significant load increases over the control basin, at the 10-percent significance level, of 63 percent. Difficulty in detecting significant changes in constituent stormwater-quality loads could be due, in part, to the large amount of variability in the data. Coefficients of variation for the majority of constituent loads were greater than 1, indicating substantial variability. The ability to detect changes in constituent stormwater-quality loads was likely hampered by an inadequate number of samples in the data set. However, sediment transport in the storm-sewer pipe, sediment washing onto the street from other source areas, winter sand application, and sampling challenges were additional sources of variability within each study ba

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1975-01-01

A model was developed for predicting the day 50 percent of the wheat crop is planted in North Dakota. This model incorporates location as an independent variable. The Julian date when 50 percent of the crop was planted for the nine divisions of North Dakota for seven years was regressed on the 49 variables through the step-down multiple regression procedure. This procedure begins with all of the independent variables and sequentially removes variables that are below a predetermined level of significance after each step. The prediction equation was tested on daily data. The accuracy of the model is considered satisfactory for finding the historic dates on which to initiate yield prediction model. Growth prediction models were also developed for spring wheat.

Harvesting Atlantic Cod under Climate Variability

NASA Astrophysics Data System (ADS)

Oremus, K. L.

2016-12-01

Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

Time-resolved High Spectral Resolution Observation of 2MASSW J0746425+200032AB

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

Wang, Ji; Mawet, Dimitri; Prato, Lisa, E-mail: ji.wang@caltech.edu

Many brown dwarfs (BDs) exhibit photometric variability at levels from tenths to tens of percents. The photometric variability is related to magnetic activity or patchy cloud coverage, characteristic of BDs near the L–T transition. Time-resolved spectral monitoring of BDs provides diagnostics of cloud distribution and condensate properties. However, current time-resolved spectral studies of BDs are limited to low spectral resolution ( R ∼ 100) with the exception of the study of Luhman 16 AB at a resolution of 100,000 using the VLT+CRIRES. This work yielded the first map of BD surface inhomogeneity, highlighting the importance and unique contribution of highmore » spectral resolution observations. Here, we report on the time-resolved high spectral resolution observations of a nearby BD binary, 2MASSW J0746425+200032AB. We find no coherent spectral variability that is modulated with rotation. Based on simulations, we conclude that the coverage of a single spot on 2MASSW J0746425+200032AB is smaller than 1% or 6.25% if spot contrast is 50% or 80% of its surrounding flux, respectively. Future high spectral resolution observations aided by adaptive optics systems can put tighter constraints on the spectral variability of 2MASSW J0746425+200032AB and other nearby BDs.« less

Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment.

PubMed

Tuset, J; Vericat, D; Batalla, R J

2016-01-01

The relation between rainfall, runoff, erosion and sediment transport is highly variable in Mediterranean catchments. Their relation can be modified by land use changes and climate oscillations that, ultimately, will control water and sediment yields. This paper analyses rainfall, runoff and sediment transport relations in a meso-scale Mediterranean mountain catchment, the Ribera Salada (NE Iberian Peninsula). A total of 73 floods recorded between November 2005 and November 2008 at the Inglabaga Sediment Transport Station (114.5 km(2)) have been analysed. Suspended sediment transport and flow discharge were measured continuously. Rainfall data was obtained by means of direct rain gauges and daily rainfall reconstructions from radar information. Results indicate that the annual sediment yield (2.3 t km(-1) y(-1) on average) and the flood-based runoff coefficients (4.1% on average) are low. The Ribera Salada presents a low geomorphological and hydrological activity compared with other Mediterranean mountain catchments. Pearson correlations between rainfall, runoff and sediment transport variables were obtained. The hydrological response of the catchment is controlled by the base flows. The magnitude of suspended sediment concentrations is largely correlated with flood magnitude, while sediment load is correlated with the amount of direct runoff. Multivariate analysis shows that total suspended load can be predicted by integrating rainfall and runoff variables. The total direct runoff is the variable with more weight in the equation. Finally, three main hydro-sedimentary phases within the hydrological year are defined in this catchment: (a) Winter, where the catchment produces only water and very little sediment; (b) Spring, where the majority of water and sediment is produced; and (c) Summer-Autumn, when little runoff is produced but significant amount of sediments is exported out of the catchment. Results show as land use and climate change may have an important role in modifying the cycles of water and sediment yields in Mediterranean mountain catchments. Copyright © 2015 Elsevier B.V. All rights reserved.

Alternate wetting and drying practice for reducing greenhouse gas emissions in flooded rice agroecosystems

NASA Astrophysics Data System (ADS)

Adviento-Borbe, A.; Anders, M. M.; Runkle, B.; Reba, M. L.; Suvocarev, K.; Massey, J. H.; Linquist, B.

2017-12-01

Alternate wetting and drying management (AWD) practices which minimize flooding times have been shown to reduce both CH4 emissions and water use but effects on N2O emissions and grain yields are variable. Grain yield and seasonal CH4 and N2O emissions were measured from AWD treatments with various soil water thresholds and conventionally flooded water treatment in two commercial farms in Arkansas and in an experimental field in Biggs, CA during 2015 and 2016 crop seasons. Methane and N2O emissions were measured using vented flux chamber and gas chromatography methods. Grain yields ( 10 Mg ha-1) were similar in AWD and conventional water treatments. Total CH4 emissions ranged from 21 to 338 kg CH4-C ha-1 season-1. The AWD practice reduced growing season CH4 emissions by 44-73% while N2O emissions remained low and represented only <2% of the total seasonal global warming potential in all treatments. The long aerobic periods and proper implementation of AWD drain events showed greatest CH4 reduction. However, N2O emissions can increase if soil inorganic N levels are potentially high prior to initiating the dry cycle. Our results showed that AWD can reduce CH4 and N2O emissions while maintaining optimal grain yields. However, adoption of AWD to mitigate greenhouse gas emissions (GHG) in commercial farms requires proper implementation of AWD to avoid risk of yield loss and high GHG emissions.

Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production

NASA Astrophysics Data System (ADS)

Lipiec, Jerzy; Usowicz, Boguslaw

2017-04-01

Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).

The effect of soil moisture anomalies on maize yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

2018-03-01

Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

Preparation and characterization of ibuprofen-cetyl alcohol beads by melt solidification technique: effect of variables.

PubMed

Maheshwari, Manish; Ketkar, Anant R; Chauhan, Bhaskar; Patil, Vinay B; Paradkar, Anant R

2003-08-11

Ibuprofen (IBU) exhibits short half-life, poor compressibility, flowability and caking tendency. IBU melt has sufficiently low viscosity and exhibits interfacial tension sufficient to form droplet even at low temperature. A single step novel melt solidification technique (MST) was developed to produce IBU beads with lower amounts of excipient. Effect of variables was studied using a 3(2) factorial approach with speed of agitation and amount of cetyl alcohol (CA) as variables. The beads were evaluated using DSC, FT-IR and scanning electron microscope (SEM). Yield, micromeritic properties, crushing strength and release kinetics were also studied. Spherical beads with a method yield of above 90% were obtained. The data was analyzed by response surface methodology. The variables showed curvilinear relationship with yield in desired particle size range, crushing strength and, bulk and tap density. The drug release followed non-Fickian case II transport and the release rate decreased linearly with respect to amount of CA in the initial stages followed by curvilinearity at later stages of elution. The effect of changing porosity and tortuosity was well correlated.

Water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; van Beek, Rens L. P. H.; Meeks, Elijah; Klein Goldewijk, Kees; Bierkens, Marc F. P.; Scheidel, Walter; Wassen, Martin J.; van der Velde, Ype; Dekker, Stefan C.

2014-05-01

Climate variability can have extreme impacts on societies in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or redistributing water resources through trade in food. Here, we explore how such water management strategies affected the resilience of the Roman Empire to climate variability in the water-limited region of the Mediterranean. Using the large-scale hydrological model PCR-GLOBWB and estimates of landcover based on the Historical Database of the Global Environment (HYDE) we generate potential agricultural yield maps under variable climate. HYDE maps of population density in conjunction with potential yield estimates are used to develop maps of agricultural surplus and deficit. The surplus and deficit regions are abstracted to nodes on a water redistribution network based on the Stanford Geospatial Network Model of the Roman World (ORBIS). This demand-driven, water redistribution network allows us to quantitatively explore how water management strategies such as irrigation and food trade improved the resilience of the Roman Empire to climate variability.

Transparent ceramic garnet scintillator optimization via composition and co-doping for high-energy resolution gamma spectrometers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cherepy, Nerine J.; Payne, Stephen A.; Seeley, Zachary M.; Beck, Patrick R.; Swanberg, Erik L.; Hunter, Steven L.

2016-09-01

Breakthrough energy resolution, R(662keV) <4%, has been achieved with an oxide scintillator, Cerium-doped Gadolinium Yttrium Gallium Aluminum Garnet, or GYGAG(Ce), by optimizing fabrication conditions. Here we describe the dependence of scintillation light yield and energy resolution on several variables: (1) Stoichiometry, in particular Gd/Y and Ga/Al ratios which modify the bandgap energy, (2) Processing methods, including vacuum vs. oxygen sintering, and (3) Trace co-dopants that influence the formation of Ce4+ and modify the intra-bandgap trap distribution. To learn about how chemical composition influences the scintillation properties of transparent ceramic garnet scintillators, we have measured: scintillation decay component amplitudes; intensity and duration of afterglow; thermoluminescence glow curve peak positions and amplitudes; integrated light yield; light yield non-proportionality, as measured in the Scintillator Light Yield Non-Proportionality Characterization Instrument (SLYNCI); and energy resolution for gamma spectroscopy. Optimized GYGAG(Ce) provides R(662 keV) =3.0%, for 0.05 cm3 size ceramics with Silicon photodiode readout, and R(662 keV) =4.6%, at 2 in3 size with PMT readout.

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed Central

Carpenter, C E

1992-01-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection. PMID:1464540

Determinants of hospital tax-exempt debt yields: corrections for selection and simultaneous equation bias.

PubMed

Carpenter, C E

1992-12-01

The cost of capital for hospitals is a topic of continuing interest as Medicare's new capital payment policy is implemented. This study examines the determinants of tax-exempt revenue bond yields, the primary source of long-term capital for hospitals. Two important methodological issues are addressed. A probit analysis estimates the probability that a hospital or system will be observed in the tax-exempt market. A selection-corrected two-stage least squares analysis allows for the simultaneous determination of bond yield and bond size. The study is based on a sample of hospitals that issued tax-exempt revenue bonds in 1982-1984, the years immediately surrounding implementation of Medicare's new payment system based on diagnosis-related groups, and an equal number of hospitals not in the market during the study period. Results suggest that hospital systems and hospitals with high occupancy rates are most likely to enter the tax-exempt revenue bond market. The yield equation suggests that hospital-specific variables may not be good predictors of the cost of capital once estimates are corrected for selection.

Extending the applicability of pressurized hot water extraction to compounds exhibiting limited water solubility by pH control: curcumin from the turmeric rhizome.

PubMed

Euterpio, Maria Anna; Cavaliere, Chiara; Capriotti, Anna Laura; Crescenzi, Carlo

2011-11-01

Pressurized hot water extraction (PHWE, also known as subcritical water extraction) is commonly considered to be an environmentally friendly extraction technique that could potentially replace traditional methods that use organic solvents. Unfortunately, the applicability of this technique is often limited by the very low water solubility of the target compounds, even at high temperatures. In this paper, the scope for broadening the applicability of PHWE by adjusting the pH of the water used in the extraction is demonstrated in the extraction of curcumin (which exhibits very limited water solubility) from untreated turmeric (Curcuma longa L.) rhizomes. Although poor extraction yields were obtained, even at high temperatures when using degassed water or neutral phosphate buffer as the extraction medium, yields exceeding those obtained by Soxhlet extraction were achieved using highly acidic pH buffers due to curcumin protonation. The influence of the temperature, pH, and buffer concentration on the extraction yield were investigated in detail by means of a series of designed experiments. Optimized conditions for the extraction of curcumin from turmeric by PHWE were estimated at 197 °C using 62 g/L buffer concentration at pH 1.6. The relationships between these variables were subjected to statistical analysis using response surface methodology.

Experimental Assessment of Recycled Diesel Spill-Contaminated Domestic Wastewater Treated by Reed Beds for Irrigation of Sweet Peppers

PubMed Central

Almuktar, Suhad A.A.A.N.; Scholz, Miklas

2016-01-01

The aim of this experimental study is to assess if urban wastewater treated by ten different greenhouse-based sustainable wetland systems can be recycled to irrigate Capsicum annuum L. (Sweet Pepper; California Wonder) commercially grown either in compost or sand within a laboratory environment. The design variables were aggregate diameter, contact time, resting time and chemical oxygen demand. The key objectives were to assess: (i) the suitability of different treated (recycled) wastewaters for irrigation; (ii) response of peppers in terms of growth when using recycled wastewater subject to different growth media and hydrocarbon contamination; and (iii) the economic viability of different experimental set-ups in terms of marketable yield. Ortho-phosphate-phosphorus, ammonia-nitrogen, potassium and manganese concentrations in the irrigation water considerably exceeded the corresponding water quality thresholds. A high yield in terms of economic return (marketable yield expressed in monetary value) was linked to raw wastewater and an organic growth medium, while the plants grown in organic medium and wetlands of large aggregate size, high contact and resting times, diesel-spill contamination and low inflow loading rate produced the best fruits in terms of their dimensions and fresh weights, indicating the role of diesel in reducing too high nitrogen concentrations. PMID:26861370

Association between home posture habits and neck pain in High School adolescents.

PubMed

Meziat-Filho, Ney; Azevedo E Silva, Gulnar; Coutinho, Evandro Silva; Mendonça, Roberta; Santos, Vivian

2017-01-01

Neck pain (NP) in adolescence is as frequent as in adulthood. However, the relationship between home posture habits and neck pain is still unknown. To investigate the prevalence of NP and the association with home posture habits (HPH) in adolescents. Cross-sectional study with High School adolescents. Students answered questions regarding sociodemographic variables, lifestyle, HPH (illustration in the questionnaire), time (TV, computer, video-game) and the presence of NP. Multivariate logistic regression was used to investigate the association between HPH and NP. The prevalence of NP was 48.9%. The ones who watched TV lying supine in bed for 2 hours or more a day yielded an odds ratio (OR) of 6.21 (1.45-26.52) for acute neck pain (ANP). Who watched TV and used the desktop in the slump posture yielded, respectively, an OR of 4.0 (1.63-9.85), and 2.03 (1.23-3.34) for chronic neck pain (CNP). The ones who frequently changed their positions while using the desktop and used it for 2 hours or more a day yielded an OR of 0.34 (0.14-0.85) for ANP. Our findings support the high prevalence of NP in adolescence and raise the association between some HPH and neck pain.

A methodology for probabilistic assessment of solar thermal power plants yield

NASA Astrophysics Data System (ADS)

Fernández-Peruchena, Carlos M.; Lara-Faneho, Vicente; Ramírez, Lourdes; Zarzalejo, Luis F.; Silva, Manuel; Bermejo, Diego; Gastón, Martín; Moreno, Sara; Pulgar, Jesús; Pavon, Manuel; Macías, Sergio; Valenzuela, Rita X.

2017-06-01

A detailed knowledge of the solar resource is a critical point to perform an economic feasibility analysis of Concentrating Solar Power (CSP) plants. This knowledge must include its magnitude (how much solar energy is available at an area of interest over a long time period), and its variability over time. In particular, DNI inter-annual variations may be large, increasing the return of investment risk in CSP plant projects. This risk is typically evaluated by means of the simulation of the energy delivered by the CSP plant during years with low solar irradiation, which are typically characterized by annual solar radiation datasets with high probability of exceedance of their annual DNI values. In this context, this paper proposes the use meteorological years representative of a given probability of exceedance of annual DNI in order to realistically assess the inter-annual variability of energy yields. The performance of this approach is evaluated in the location of Burns station (University of Oregon Solar Radiation Monitoring Laboratory), where a 34-year (from 1980 to 2013) measured data set of solar irradiance and temperature is available.

Relationship between the Fluorescence Lifetime of Chlorophyll 'a' and Primary Productivity within the Mississippi River Plume and Adjacent Shelf Region

NASA Technical Reports Server (NTRS)

Hall, Callie; Miller, Richard L.; Fernandez, Salvador M.; McKee, Brent A.

2000-01-01

In situ measurements of chlorophyll fluorescence intensity have been widely used to estimate phytoplankton biomass. However, because the fluorescence quantum yield of chlorophyll a in vivo can be highly variable, measurements of chlorophyll fluorescence intensity cannot be directly correlated with phytoplankton biomass and do not provide information on the physiological state of the phytoplankton under study. Conversely, lifetime-based measurements of chlorophyll fluorescence provide a framework in which photosynthetic rates of phytoplankton can be analyzed according to phytoplankton physiology. Along with the measurement of primary production and ambient nutrient concentrations within the Mississippi River plume in the northern Gulf of Mexico, phytoplankton fluorescence lifetimes were measured using a Fluorescence Lifetime Phytoplankton Analyzer (developed under a NASA Small Business Innovative Research contract to Ciencia, Inc.). Variability of fluorescence lifetimes within the plume can be used as a background from which to interpret variations in the maximum quantum yield of photochemistry. The extent to which nutrient and effluent loading in this dynamic coastal area affect the photosynthetic performance of phytoplankton will be presented as a function of phytoplankton fluorescence lifetimes.

Development and Validation of a High-Quality Composite Real-World Mortality Endpoint.

PubMed

Curtis, Melissa D; Griffith, Sandra D; Tucker, Melisa; Taylor, Michael D; Capra, William B; Carrigan, Gillis; Holzman, Ben; Torres, Aracelis Z; You, Paul; Arnieri, Brandon; Abernethy, Amy P

2018-05-14

To create a high-quality electronic health record (EHR)-derived mortality dataset for retrospective and prospective real-world evidence generation. Oncology EHR data, supplemented with external commercial and US Social Security Death Index data, benchmarked to the National Death Index (NDI). We developed a recent, linkable, high-quality mortality variable amalgamated from multiple data sources to supplement EHR data, benchmarked against the highest completeness U.S. mortality data, the NDI. Data quality of the mortality variable version 2.0 is reported here. For advanced non-small-cell lung cancer, sensitivity of mortality information improved from 66 percent in EHR structured data to 91 percent in the composite dataset, with high date agreement compared to the NDI. For advanced melanoma, metastatic colorectal cancer, and metastatic breast cancer, sensitivity of the final variable was 85 to 88 percent. Kaplan-Meier survival analyses showed that improving mortality data completeness minimized overestimation of survival relative to NDI-based estimates. For EHR-derived data to yield reliable real-world evidence, it needs to be of known and sufficiently high quality. Considering the impact of mortality data completeness on survival endpoints, we highlight the importance of data quality assessment and advocate benchmarking to the NDI. © 2018 The Authors. Health Services Research published by Wiley Periodicals, Inc. on behalf of Health Research and Educational Trust.

Reductive Catalytic Fractionation of Corn Stover Lignin

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

Anderson, Eric M.; Katahira, Rui; Reed, Michelle

Reductive catalytic fractionation (RCF) has emerged as an effective biomass pretreatment strategy to depolymerize lignin into tractable fragments in high yields. We investigate the RCF of corn stover, a highly abundant herbaceous feedstock, using carbon-supported Ru and Ni catalysts at 200 and 250 degrees C in methanol and, in the presence or absence of an acid cocatalyst (H3PO4 or an acidified carbon support). Three key performance variables were studied: (1) the effectiveness of lignin extraction as measured by the yield of lignin oil, (2) the yield of monomers in the lignin oil, and (3) the carbohydrate retention in the residualmore » solids after RCF. The monomers included methyl coumarate/ferulate, propyl guaiacol/syringol, and ethyl guaiacol/syringol. The Ru and Ni catalysts performed similarly in terms of product distribution and monomer yields. The monomer yields increased monotonically as a function of time for both temperatures. At 6 h, monomer yields of 27.2 and 28.3% were obtained at 250 and 200 degrees C, respectively, with Ni/C. The addition of an acid cocatalysts to the Ni/C system increased monomer yields to 32% for acidified carbon and 38% for phosphoric acid at 200 degrees C. The monomer product distribution was dominated by methyl coumarate regardless of the use of the acid cocatalysts. The use of phosphoric acid at 200 degrees C or the high temperature condition without acid resulted in complete lignin extraction and partial sugar solubilization (up to 50%) thereby generating lignin oil yields that exceeded the theoretical limit. In contrast, using either Ni/C or Ni on acidified carbon at 200 degrees C resulted in moderate lignin oil yields of ca. 55%, with sugar retention values >90%. Notably, these sugars were amenable to enzymatic digestion, reaching conversions >90% at 96 h. Characterization studies on the lignin oils using two-dimensional heteronuclear single quantum coherence nuclear magnetic resonance and gel permeation chromatrography revealed that soluble oligomers are formed via solvolysis, followed by further fragmentation on the catalyst surface via hydrogenolysis. Overall, the results show that clear trade-offs exist between the levels of lignin extraction, monomer yields, and carbohydrate retention in the residual solids for different RCF conditions of corn stover.« less

Growth and yield in Eucalyptus globulus

Treesearch

James A. Rinehart; Richard B. Standiford

1983-01-01

A study of the major Eucalyptus globulus stands throughout California conducted by Woodbridge Metcalf in 1924 provides a complete and accurate data set for generating variable site-density yield models. Two models were developed using linear regression techniques. Model I depicts a linear relationship between age and yield best used for stands between five and fifteen...

Optimization of Fermentation Conditions and Rheological Properties of Exopolysaccharide Produced by Deep-Sea Bacterium Zunongwangia profunda SM-A87

PubMed Central

Liu, Sheng-Bo; Qiao, Li-Ping; He, Hai-Lun; Zhang, Qian; Chen, Xiu-Lan; Zhou, Wei-Zhi; Zhou, Bai-Cheng; Zhang, Yu-Zhong

2011-01-01

Zunongwangia profunda SM-A87 isolated from deep-sea sediment can secrete large quantity of exopolysaccharide (EPS). Response surface methodology was applied to optimize the culture conditions for EPS production. Single-factor experiment showed that lactose was the best carbon source. Based on the Plackett–Burman design, lactose, peptone and temperature were selected as significant variables, which were further optimized by the steepest ascent (descent) method and central composite design. The optimal culture conditions for EPS production and broth viscosity were determined as 32.21 g/L lactose, 8.87 g/L peptone and an incubation temperature of 9.8°C. Under these conditions, the maximum EPS yield and broth viscosity were 8.90 g/L and 6551 mPa•s, respectively, which is the first report of such high yield of EPS from a marine bacterium. The aqueous solution of the EPS displayed high viscosity, interesting shearing thinning property and great tolerance to high temperature, a wide range of pH, and high salinity. PMID:22096500

Crystallization using reverse micelles and water-in-oil microemulsion systems: the highly selective tool for the purification of organic compounds from complex mixtures.

PubMed

Kljajic, Alen; Bester-Rogac, Marija; Klobcar, Andrej; Zupet, Rok; Pejovnik, Stane

2013-02-01

The active pharmaceutical ingredient orlistat is usually manufactured using a semi-synthetic procedure, producing crude product and complex mixtures of highly related impurities with minimal side-chain structure variability. It is therefore crucial for the overall success of industrial/pharmaceutical application to develop an effective purification process. In this communication, we present the newly developed water-in-oil reversed micelles and microemulsion system-based crystallization process. Physiochemical properties of the presented crystallization media were varied through surfactants and water composition, and the impact on efficiency was measured through final variation of these two parameters. Using precisely defined properties of the dispersed water phase in crystallization media, a highly efficient separation process in terms of selectivity and yield was developed. Small-angle X-ray scattering, high-performance liquid chromatography, mass spectrometry, and scanning electron microscopy were used to monitor and analyze the separation processes and orlistat products obtained. Typical process characteristics, especially selectivity and yield in regard to reference examples, were compared and discussed. Copyright © 2012 Wiley Periodicals, Inc.

Using FTIR spectroscopy to model alkaline pretreatment and enzymatic saccharification of six lignocellulosic biomasses.

PubMed

Sills, Deborah L; Gossett, James M

2012-04-01

Fourier transform infrared, attenuated total reflectance (FTIR-ATR) spectroscopy, combined with partial least squares (PLS) regression, accurately predicted solubilization of plant cell wall constituents and NaOH consumption through pretreatment, and overall sugar productions from combined pretreatment and enzymatic hydrolysis. PLS regression models were constructed by correlating FTIR spectra of six raw biomasses (two switchgrass cultivars, big bluestem grass, a low-impact, high-diversity mixture of prairie biomasses, mixed hardwood, and corn stover), plus alkali loading in pretreatment, to nine dependent variables: glucose, xylose, lignin, and total solids solubilized in pretreatment; NaOH consumed in pretreatment; and overall glucose and xylose conversions and yields from combined pretreatment and enzymatic hydrolysis. PLS models predicted the dependent variables with the following values of coefficient of determination for cross-validation (Q²): 0.86 for glucose, 0.90 for xylose, 0.79 for lignin, and 0.85 for total solids solubilized in pretreatment; 0.83 for alkali consumption; 0.93 for glucose conversion, 0.94 for xylose conversion, and 0.88 for glucose and xylose yields. The sugar yield models are noteworthy for their ability to predict overall saccharification through combined pretreatment and enzymatic hydrolysis per mass dry untreated solids without a priori knowledge of the composition of solids. All wavenumbers with significant variable-important-for-projection (VIP) scores have been attributed to chemical features of lignocellulose, demonstrating the models were based on real chemical information. These models suggest that PLS regression can be applied to FTIR-ATR spectra of raw biomasses to rapidly predict effects of pretreatment on solids and on subsequent enzymatic hydrolysis. Copyright © 2011 Wiley Periodicals, Inc.

Spatial partitioning of environmental correlates of avian biodiversity in the conterminous United States

USGS Publications Warehouse

O'Connor, R.J.; Jones, M.T.; White, D.; Hunsaker, C.; Loveland, Tom; Jones, Bruce; Preston, E.

1996-01-01

Classification and regression tree (CART) analysis was used to create hierarchically organized models of the distribution of bird species richness across the conterminous United States. Species richness data were taken from the Breeding Bird Survey and were related to climatic and land use data. We used a systematic spatial grid of approximately 12,500 hexagons, each approximately 640 square kilometres in area. Within each hexagon land use was characterized by the Loveland et al. land cover classification based on Advanced Very High Resolution Radiometer (AVHRR) data from NOAA polar orbiting meteorological satellites. These data were aggregated to yield fourteen land classes equivalent to an Anderson level II coverage; urban areas were added from the Digital Chart of the World. Each hexagon was characterized by climate data and landscape pattern metrics calculated from the land cover. A CART model then related the variation in species richness across the 1162 hexagons for which bird species richness data were available to the independent variables, yielding an R2-type goodness of fit metric of 47.5% deviance explained. The resulting model recognized eleven groups of hexagons, with species richness within each group determined by unique sequences of hierarchically constrained independent variables. Within the hierarchy, climate data accounted for more variability in the bird data, followed by land cover proportion, and then pattern metrics. The model was then used to predict species richness in all 12,500 hexagons of the conterminous United States yielding a map of the distribution of these eleven classes of bird species richness as determined by the environmental correlates. The potential for using this technique to interface biogeographic theory with the hierarchy theory of ecology is discussed. ?? 1996 Blackwell Science Ltd.

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

Treesearch

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

2014-01-01

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

Diallel analysis of corn for special use as corn grits: determining the main genetic effects for corn gritting ability.

PubMed

Conrado, T V; Scapim, C A; Bignotto, L S; Pinto, R J B; Freitas, I L J; Amaral, A T; Pinheiro, A C

2014-08-26

Corn grits are used for various purposes such as flakes, snacks, livestock feed, hominy, extruded products, beer, etc. The grit size proportion varies according to the hybrid, and thus, once the use of the grits is linked to the particle size, determining the genetic effects is essential to develop hybrids for any specific use. For this purpose a complete diallel series of crosses, involving eight parents, was performed near Maringá, PR, Brazil. The objective of this study was to evaluate the general (GCA) and specific (SCA) combining abilities of 28 progeny for selection of hybrids for breeding programs and extraction of inbred lines for hybrid development. The response variables, such as plant height, ear insertion height, crop stand, grain yield, and grits, small grits and bran production, were gauged and appraised for each of the 28 progeny. The trait effects and GCA were significant for all response variables, while for SCA, only grain yield and crop stand showed significance (P < 0.05), according to Griffing (1955) analysis. A significant weak negative partial correlation was found between grain yield and grits conversion. In relation to the hybrid selection for breeding programs, the parent IAC Nelore was highly recommended for recurrent selection and the hybrids IPR 119 x HT 392 and IAC Nelore x HD 332 for the extraction of pure lines for hybrid development.

Photoproduction of hydrated electrons from natural organic solutes in aquatic environments

USGS Publications Warehouse

Zepp, R.G.; Braun, A.M.; Hoigne, J.; Leenheer, J.A.

1987-01-01

Laser flash photolysis was used to investigate the transients formed on absorption of 355-nm light by dissolved organic matter (DOM) from natural water bodies and from soil. Absorption spectra and quenching studies of the transients provided confirming evidence that hydrated electrons were formed by all of the DOM that were studied. The DOM from the Suwannee River in Georgia and from the Greifensee, a Swiss lake, exhibited great variability in light-absorbing properties. Despite this high variability in absorption coefficients, the primary quantum yields for electron ejection from the Greifensee and Suwannee DOM fell in a narrow range (0.005-0.008). Steady-state irradiations (355 nm) of the DOM with 2-chloroethanol (0.02 M) present as an electron scavenger produced chloride ions with quantum yields that were about 2 orders of magnitude lower than the primary quantum yields. This result indicates that most of the photoejected electrons recombine with cations before escaping into bulk solution. Irradiations of DOM solutions under sunlight (April, latitude 34?? N) photoproduced electrons at rates falling in the range of 0.2-0.4 ??mol/[(mg of DOC) h]. These results indicate that hydrated electrons can play a significant role in the environmental photoreduction of persistent, electronegative pollutants but may be relatively unimportant in the environmental production of hydrogen peroxide. ?? 1987 American Chemical Society.

A global sensitivity analysis of crop virtual water content

NASA Astrophysics Data System (ADS)

Tamea, S.; Tuninetti, M.; D'Odorico, P.; Laio, F.; Ridolfi, L.

2015-12-01

The concepts of virtual water and water footprint are becoming widely used in the scientific literature and they are proving their usefulness in a number of multidisciplinary contexts. With such growing interest a measure of data reliability (and uncertainty) is becoming pressing but, as of today, assessments of data sensitivity to model parameters, performed at the global scale, are not known. This contribution aims at filling this gap. Starting point of this study is the evaluation of the green and blue virtual water content (VWC) of four staple crops (i.e. wheat, rice, maize, and soybean) at a global high resolution scale. In each grid cell, the crop VWC is given by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield, where evapotranspiration is determined with a detailed daily soil water balance and actual yield is estimated using country-based data, adjusted to account for spatial variability. The model provides estimates of the VWC at a 5x5 arc minutes and it improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The model is then used as the basis for a sensitivity analysis, in order to evaluate the role of model parameters in affecting the VWC and to understand how uncertainties in input data propagate and impact the VWC accounting. In each cell, small changes are exerted to one parameter at a time, and a sensitivity index is determined as the ratio between the relative change of VWC and the relative change of the input parameter with respect to its reference value. At the global scale, VWC is found to be most sensitive to the planting date, with a positive (direct) or negative (inverse) sensitivity index depending on the typical season of crop planting date. VWC is also markedly dependent on the length of the growing period, with an increase in length always producing an increase of VWC, but with higher spatial variability for rice than for other crops. The sensitivity to the reference evapotranspiration is highly variable with the considered crop and ranges from positive values (for soybean), to negative values (for rice and maize) and near-zero values for wheat. This variability reflects the different yield response factors of crops, which expresses their tolerance to water stress.

Effect of pelleting process variables on physical properties and sugar yields of ammonia fiber expansion pretreated corn stover

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

Amber N. Hoover; Jaya Shankar Tumuluru; Farzaneh Teymouri

Pelletization process variables including grind size (4, 6 mm), die speed (40, 50, 60 Hz), and preheating (none, 70 degrees C) were evaluated to understand their effect on pellet quality attributes and sugar yields of ammonia fiber expansion (AFEX) pretreated biomass. The bulk density of the pelletized AFEX corn stover was three to six times greater compared to untreated and AFEX-treated corn stover. Also the durability of the pelletized AFEX corn stover was >97.5% for all pelletization conditions studied except for preheated pellets. Die speed had no effect on enzymatic hydrolysis sugar yields of pellets. Pellets produced with preheating ormore » a larger grind size (6 mm) had similar or lower sugar yields. Pellets generated with 4 mm AFEX-treated corn stover, a 60 Hz die speed, and no preheating resulted in pellets with similar or greater density, durability, and sugar yields compared to other pelletization conditions.« less

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.

The spark discharge synthesis of amino acids from various hydrocarbons

NASA Technical Reports Server (NTRS)

Ring, D.; Miller, S. L.

1984-01-01

The spark discharge synthesis of amino acids using an atmosphere of CH4+N2+H2O+NH3 has been investigated with variable pNH3. The amino acids produced using higher hydrocarbons (ethane, ethylene, acetylene, propane, butane, and isobutane) instead of CH4 were also investigated. There was considerable range in the absolute yields of amino acids, but the yields relative to glycine (or alpha-amino-n-butyric acid) were more uniform. The relative yields of the C3 to C6 aliphatic alpha-amino acids are nearly the same (with a few exceptions) with all the hydrocarbons. The glycine yields are more variable. The precursors to the C3-C6 aliphatic amino acids seem to be produced in the same process, which is separate from the synthesis of glycine precursors. It may be possible to use these relative yields as a signature for a spark discharge synthesis provided corrections can be made for subsequent decomposition events (e.g. in the Murchison meteorite).

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

NASA Astrophysics Data System (ADS)

Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, Katja

2018-05-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.

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

Schmidt, Edward G.; Hemen, Brian; Rogalla, Danielle

We have obtained VR photometry of 282 Cepheid variable star candidates from the northern part of the All Sky Automated Survey (ASAS). These together with data from the ASAS and the Northern Sky Variability Survey (NSVS) were used to redetermine the periods of the stars. We divided the stars into four groups based on location in a plot of mean color, (V-R), versus period. Two of the groups fell within the region of the diagram containing known type II Cepheids and yielded 14 new highly probable type II Cepheids. The properties of the remaining stars in these two groups aremore » discussed but their nature remains uncertain. Unexplained differences exist between the sample of stars studied here and a previous sample drawn from the NSVS by Akerlof et al. This suggests serious biases in the identification of variables in different surveys.« less

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

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

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

Evaluating the applicability of using daily forecasts from seasonal prediction systems (SPSs) for agriculture: a case study of Nepal's Terai with the NCEP CFSv2

NASA Astrophysics Data System (ADS)

Jha, Prakash K.; Athanasiadis, Panos; Gualdi, Silvio; Trabucco, Antonio; Mereu, Valentina; Shelia, Vakhtang; Hoogenboom, Gerrit

2018-03-01

Ensemble forecasts from dynamic seasonal prediction systems (SPSs) have the potential to improve decision-making for crop management to help cope with interannual weather variability. Because the reliability of crop yield predictions based on seasonal weather forecasts depends on the quality of the forecasts, it is essential to evaluate forecasts prior to agricultural applications. This study analyses the potential of Climate Forecast System version 2 (CFSv2) in predicting the Indian summer monsoon (ISM) for producing meteorological variables relevant to crop modeling. The focus area was Nepal's Terai region, and the local hindcasts were compared with weather station and reanalysis data. The results showed that the CFSv2 model accurately predicts monthly anomalies of daily maximum and minimum air temperature (Tmax and Tmin) as well as incoming total surface solar radiation (Srad). However, the daily climatologies of the respective CFSv2 hindcasts exhibit significant systematic biases compared to weather station data. The CFSv2 is less capable of predicting monthly precipitation anomalies and simulating the respective intra-seasonal variability over the growing season. Nevertheless, the observed daily climatologies of precipitation fall within the ensemble spread of the respective daily climatologies of CFSv2 hindcasts. These limitations in the CFSv2 seasonal forecasts, primarily in precipitation, restrict the potential application for predicting the interannual variability of crop yield associated with weather variability. Despite these limitations, ensemble averaging of the simulated yield using all CFSv2 members after applying bias correction may lead to satisfactory yield predictions.

Analogue evaluation of the effects of opportunities to respond and ratios of known items within drill rehearsal of Esperanto words.

PubMed

Szadokierski, Isadora; Burns, Matthew K

2008-10-01

Drill procedures have been used to increase the retention of various types of information, but little is known about the causal mechanisms of these techniques. The current study compared the effect of two key features of drill procedures, a large number of opportunities to respond (OTR) and a drill ratio that maintains a high percentage of known to unknown items (90% known). Using a factorial design, 27 4th graders were taught the pronunciation and meaning of Esperanto words using four versions of incremental rehearsal that varied on two factors, percentage of known words (high - 90% vs. moderate - 50%) and the number of OTR (high vs. low). A within-subject ANOVA revealed a significant main effect for OTR and non-significant effects for drill ratio and the interaction between the two variables. Moreover, it was found that increasing OTR from low to high yielded a large effect size (d=2.46), but increasing the percentage of known material from moderate (50%) to high (90%) yielded a small effect (d=0.16). These results suggest that a high number of OTR may be a key feature of flashcard drill techniques in promoting learning and retention.

Climate Change and ENSO Effects on Southeastern US Climate Patterns and Maize Yield.

PubMed

Mourtzinis, Spyridon; Ortiz, Brenda V; Damianidis, Damianos

2016-07-19

Climate change has a strong influence on weather patterns and significantly affects crop yields globally. El Niño Southern Oscillation (ENSO) has a strong influence on the U.S. climate and is related to agricultural production variability. ENSO effects are location-specific and in southeastern U.S. strongly connect with climate variability. When combined with climate change, the effects on growing season climate patterns and crop yields might be greater than expected. In our study, historical monthly precipitation and temperature data were coupled with non-irrigated maize yield data (33-43 years depending on the location) to show a potential yield suppression of ~15% for one °C increase in southeastern U.S. growing season maximum temperature. Yield suppression ranged between -25 and -2% among locations suppressing the southeastern U.S. average yield trend since 1981 by 17 kg ha(-1)year(-1) (~25%), mainly due to year-to-year June temperature anomalies. Yields varied among ENSO phases from 1971-2013, with greater yields observed during El Niño phase. During La Niña years, maximum June temperatures were higher than Neutral and El Niño, whereas June precipitation was lower than El Niño years. Our data highlight the importance of developing location-specific adaptation strategies quantifying both, climate change and ENSO effects on month-specific growing season climate conditions.

DNA fingerprinting of Brassica juncea cultivars using microsatellite probes.

PubMed

Bhatia, S; Das, S; Jain, A; Lakshmikumaran, M

1995-09-01

The genetic variability in the Brassica juncea cultivars was detected by employing in-gel hybridization of restricted DNA to simple repetitive sequences such as (GATA)4, (GACA)4 and (CAC)5. The most informative probe/enzyme combination was (GATA)4/EcoRI, yielding highly polymorphic fingerprint patterns for the B. juncea cultivars. This technique was found to be dependable for establishing the variety specific patterns for most of the cultivars studied, a prerequisite for germplasm preservation. The results of the present study were compared with those reported in our earlier study in which random amplification of polymorphic DNA (RAPD) was used for assessing the genetic variability in the B. juncea cultivars.

Aerodynamic effects of moveable sidewall nozzle geometry and rotor exit restriction on the performance of a radial turbine

NASA Technical Reports Server (NTRS)

Rogo, C.; Hajek, T.; Roelke, R.

1983-01-01

Attention is given to the experimental results obtained with a high work capacity radial inflow turbine of known performance, whose baseline configuration was modified to accept a variety of movable nozzle sidewall, diffusing or accelerating rotor inlet ramp, and rotor exit restriction ring combinations. The performance of this variable geometry turbine was measured at constant speed and pressure ratio for 31 different test configurations, yielding test data over a nozzle area range from 50 to 100 percent of maximum depending on the movement of the nozzle assembly's forward and rearward sidewalls. Performance comparisons with data for a variable stagger angle vane concept indicate the present system's viability.

Gravitational lensing of active galactic nuclei.

PubMed

Hewitt, J N

1995-12-05

Most of the known cases of strong gravitational lensing involve multiple imaging of an active galactic nucleus. The properties of lensed active galactic nuclei make them promising systems for astrophysical applications of gravitational lensing; in particular, they show structure on scales of milliseconds of arc to tens of seconds of arc, they are variable, and they are polarized. More than 20 cases of strong gravitational lenses are now known, and about half of them are radio sources. High-resolution radio imaging is making possible the development of well-constrained lens models. Variability studies at radio and optical wavelengths are beginning to yield results of astrophysical interest, such as an independent measure of the distance scale and limits on source sizes.

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.

Global growth and stability of agricultural yield decrease with pollinator dependence

PubMed Central

Garibaldi, Lucas A.; Aizen, Marcelo A.; Klein, Alexandra M.; Cunningham, Saul A.; Harder, Lawrence D.

2011-01-01

Human welfare depends on the amount and stability of agricultural production, as determined by crop yield and cultivated area. Yield increases asymptotically with the resources provided by farmers’ inputs and environmentally sensitive ecosystem services. Declining yield growth with increased inputs prompts conversion of more land to cultivation, but at the risk of eroding ecosystem services. To explore the interdependence of agricultural production and its stability on ecosystem services, we present and test a general graphical model, based on Jensen's inequality, of yield–resource relations and consider implications for land conversion. For the case of animal pollination as a resource influencing crop yield, this model predicts that incomplete and variable pollen delivery reduces yield mean and stability (inverse of variability) more for crops with greater dependence on pollinators. Data collected by the Food and Agriculture Organization of the United Nations during 1961–2008 support these predictions. Specifically, crops with greater pollinator dependence had lower mean and stability in relative yield and yield growth, despite global yield increases for most crops. Lower yield growth was compensated by increased land cultivation to enhance production of pollinator-dependent crops. Area stability also decreased with pollinator dependence, as it correlated positively with yield stability among crops. These results reveal that pollen limitation hinders yield growth of pollinator-dependent crops, decreasing temporal stability of global agricultural production, while promoting compensatory land conversion to agriculture. Although we examined crop pollination, our model applies to other ecosystem services for which the benefits to human welfare decelerate as the maximum is approached. PMID:21422295

Do genotypic differences in thermotolerance plasticity correspond with water-induced differences in yield and photosynthetic stability for field-grown upland cotton?

USDA-ARS?s Scientific Manuscript database

To determine if cultivar differences in thermotolerance plasticity of photosystem II promote yield or photosynthetic stability when variability in both parameters is water-induced, the temperature response of maximum quantum yield of photosystem II (Fv/Fm) was evaluated for two cotton cultivars (FM ...

Quantitative genetic studies relating to the domestication of meadowfoam (Limnanthes spp. ) as a new oil crop

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

Abuelgasim, E.H.

1982-01-01

Meadowfoam (Limnanthes spp.) has recently aroused interest as a promising new source of industrial oil that is a good substitute for sperm whale oil. Fourteen natural populations of Limnanthes, involving two species and five taxonomic varieties, were studied for 12 quantitative characters, during two seasons. The objectives were: to evaluate the potential use of the populations for domestication purposes, study the interrelationships among characters, and to obtain heritability estimates for some of the important characters. A great deal of variability among the populations was observed for all the characters studied. Although no single taxon or population had all the desiredmore » characters combined, nevertheless, three populations of L. douglasii var. nivea and one population of L. douglasii var. sulphurea, gave consistently higher values for seed yield, seed number, plant dry weight, harvest index and fertility index, than L. alba or L. douglasii var. douglasii populations. The nivea group was also the earliest to flower, however, this group together with var. sulphurea population, suffer from severe seed shattering at maturity. In both seasons, seed yield was positively and highly significantly correlated with all of the other characters with the exception of days to the first flower and days to flower, which showed a highly significant negative correlation with seed yield. Stepwise multiple regression and path-coefficient analyses showed that seed number was the most important character in contribution to variation in seed yield; it accounted for over 85% of the variation in seed yield. The four characters: seed number, 100-seed weight, plant dry weight and harvest index, in that order, were the most important characters to be included in a multiple regression equation for determination of seed yield.« less

Optimization of Supercritical CO2 Extraction of Fish Oil from Viscera of African Catfish (Clarias gariepinus)

PubMed Central

Sarker, Mohamed Zaidul Islam; Selamat, Jinap; Habib, Abu Sayem Md. Ahsan; Ferdosh, Sahena; Akanda, Mohamed Jahurul Haque; Jaffri, Juliana Mohamed

2012-01-01

Fish oil was extracted from the viscera of African Catfish using supercritical carbon dioxide (SC-CO2). A Central Composite Design of Response Surface methodology (RSM) was employed to optimize the SC-CO2 extraction parameters. The oil yield (Y) as response variable was executed against the four independent variables, namely pressure, temperature, flow rate and soaking time. The oil yield varied with the linear, quadratic and interaction of pressure, temperature, flow rate and soaking time. Optimum points were observed within the variables of temperature from 35 °C to 80 °C, pressure from 10 MPa to 40 MPa, flow rate from 1 mL/min to 3 mL/min and soaking time from 1 h to 4 h. However, the extraction parameters were found to be optimized at temperature 57.5 °C, pressure 40 MPa, flow rate 2.0 mL/min and soaking time 2.5 h. At this optimized condition, the highest oil yields were found to be 67.0% (g oil/100 g sample on dry basis) in the viscera of catfish which was reasonable to the yields of 78.0% extracted using the Soxhlet method. PMID:23109854

Optimization of mucilage extraction from chia seeds (Salvia hispanica L.) using response surface methodology.

PubMed

Orifici, Stefania C; Capitani, Marianela I; Tomás, Mabel C; Nolasco, Susana M

2018-02-25

Chia mucilage has potential application as a functional ingredient; advances on maximizing its extraction yield could represent a significant technological and economic impact for the food industry. Thus, first, the effect of mechanical agitation time (1-3 h) on the exudation of chia mucilage was analyzed. Then, response surface methodology was used to determine the optimal combination of the independent variables temperature (15-85 °C) and seed: water ratio (1: 12-1: 40.8 w/v) for the 2 h exudation that give maximum chia mucilage yield. Experiments were designed according to central composite rotatable design. A second-order polynomial model predicted the variation in extraction mucilage yield with the variables temperature and seed: water ratio. The optimal operating conditions were found to be temperature 85 °C and a seed: water ratio of 1: 31 (w/v), reaching an experimental extraction yield of 116 ± 0.21 g kg -1 (dry basis). The mucilage obtained exhibited good functional properties, mainly in terms of water-holding capacity, emulsifying activity, and emulsion stability. The results obtained show that temperature, seed: water ratio, and exudation time are important variables of the process that affect the extraction yield and the quality of the chia mucilage, determined according to its physicochemical and functional properties. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

[Does the Youth Psychopathic Traits Inventory (YPI) identify a clinically relevant subgroup among young offenders?].

PubMed

Mingers, Daniel; Köhler, Denis; Huchzermeier, Christian; Hinrichs, Günter

2017-01-01

Does the Youth Psychopathic Traits Inventory identify one or more high-risk subgroups among young offenders? Which recommendations for possible courses of action can be derived for individual clinical or forensic cases? Method: Model-based cluster analysis (Raftery, 1995) was conducted on a sample of young offenders (N = 445, age 14–22 years, M = 18.5, SD = 1.65). The resulting model was then tested for differences between clusters with relevant context variables of psychopathy. The variables included measures of intelligence, social competence, drug use, and antisocial behavior. Results: Three clusters were found (Low Trait, Impulsive/Irresponsible, Psychopathy) that differ highly significantly concerning YPI scores and the variables mentioned above. The YPI Scores Δ Low = 4.28 (Low Trait – Impulsive/Irresponsible) and Δ High = 6.86 (Impulsive/Irresponsible – Psychopathy) were determined to be thresholds between the clusters. The allocation of a person to be assessed within the calculated clusters allows for an orientation of consequent tests beyond the diagnosis of psychopathy. We conclude that the YPI is a valuable instrument for the assessment of young offenders, as it yields clinically and forensically relevant information concerning the cause and expected development of psychopathological behavior.

Impact of compost, vermicompost and biochar on soil fertility, maize yield and soil erosion in Northern Vietnam: a three year mesocosm experiment.

PubMed

Doan, Thuy Thu; Henry-des-Tureaux, Thierry; Rumpel, Cornelia; Janeau, Jean-Louis; Jouquet, Pascal

2015-05-01

Compost, vermicompost and biochar amendments are thought to improve soil quality and plant yield. However, little is known about their long-term impact on crop yield and the environment in tropical agro-ecosystems. In this study we investigated the effect of organic amendments (buffalo manure, compost and vermicompost) and biochar (applied alone or with vermicompost) on plant yield, soil fertility, soil erosion and water dynamics in a degraded Acrisol in Vietnam. Maize growth and yield, as well as weed growth, were examined for three years in terrestrial mesocosms under natural rainfall. Maize yield and growth showed high inter-annual variability depending on the organic amendment. Vermicompost improved maize growth and yield but its effect was rather small and was only significant when water availability was limited (year 2). This suggests that vermicompost could be a promising substrate for improving the resistance of agrosystems to water stress. When the vermicompost-biochar mixture was applied, further growth and yield improvements were recorded in some cases. When applied alone, biochar had a positive influence on maize yield and growth, thus confirming its interest for improving long-term soil productivity. All organic amendments reduced water runoff, soil detachment and NH₄(+) and NO₃(-) transfer to water. These effects were more significant with vermicompost than with buffalo manure and compost, highlighting that the beneficial influence of vermicompost is not limited to its influence on plant yield. In addition, this study showed for the first time that the combination of vermicompost and biochar may not only improve plant productivity but also reduce the negative impact of agriculture on water quality. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting meat yields and commercial meat cuts from carcasses of young bulls of Spanish breeds by the SEUROP method and an image analysis system.

PubMed

Oliver, A; Mendizabal, J A; Ripoll, G; Albertí, P; Purroy, A

2010-04-01

The SEUROP system is currently in use for carcass classification in Europe. Image analysis and other new technologies are being developed to enhance and supplement this classification system. After slaughtering, 91 carcasses of local Spanish beef breeds were weighed and classified according to the SEUROP system. Two digital photographs (a side and a dorsal view) were taken of the left carcass sides, and a total of 33 morphometric measurements (lengths, perimeters, areas) were made. Commercial butchering of these carcasses took place 24 h postmortem, and the different cuts were grouped according to four commercial meat cut quality categories: extra, first, second, and third. Multiple regression analysis of carcass weight and the SEUROP conformation score (x variables) on meat yield and the four commercial cut quality category yields (y variables) was performed as a measure of the accuracy of the SEUROP system. Stepwise regression analysis of carcass weight and the 33 morphometric image analysis measurements (x variables) and meat yield and yields of the four commercial cut quality categories (y variables) was carried out. Higher accuracy was achieved using image analysis than using only the current SEUROP conformation score. The regression coefficient values were between R(2)=0.66 and R(2)=0.93 (P<0.001) for the SEUROP system and between R(2)=0.81 and R(2)=0.94 (P<0.001) for the image analysis method. These results suggest that the image analysis method should be helpful as a means of supplementing and enhancing the SEUROP system for grading beef carcasses. 2009 Elsevier Ltd. All rights reserved.

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies (Presentation)

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

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

Downscaling Solar Power Output to 4-Seconds for Use in Integration Studies: Preprint

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

Hummon, M.; Weekley, A.; Searight, K.

2013-10-01

High penetration renewable integration studies require solar power data with high spatial and temporal accuracy to quantify the impact of high frequency solar power ramps on the operation of the system. Our previous work concentrated on downscaling solar power from one hour to one minute by simulation. This method used clearness classifications to categorize temporal and spatial variability, and iterative methods to simulate intra-hour clearness variability. We determined that solar power ramp correlations between sites decrease with distance and the duration of the ramp, starting at around 0.6 for 30-minute ramps between sites that are less than 20 km apart.more » The sub-hour irradiance algorithm we developed has a noise floor that causes the correlations to approach ~0.005. Below one minute, the majority of the correlations of solar power ramps between sites less than 20 km apart are zero, and thus a new method to simulate intra-minute variability is needed. These intra-minute solar power ramps can be simulated using several methods, three of which we evaluate: a cubic spline fit to the one-minute solar power data; projection of the power spectral density toward the higher frequency domain; and average high frequency power spectral density from measured data. Each of these methods either under- or over-estimates the variability of intra-minute solar power ramps. We show that an optimized weighted linear sum of methods, dependent on the classification of temporal variability of the segment of one-minute solar power data, yields time series and ramp distributions similar to measured high-resolution solar irradiance data.« less

An Analysis of the Selected Materials Used in Step Measurements During Pre-Fits of Thermal Protection System Tiles and the Accuracy of Measurements Made Using These Selected Materials

NASA Technical Reports Server (NTRS)

Kranz, David William

2010-01-01

The goal of this research project was be to compare and contrast the selected materials used in step measurements during pre-fits of thermal protection system tiles and to compare and contrast the accuracy of measurements made using these selected materials. The reasoning for conducting this test was to obtain a clearer understanding to which of these materials may yield the highest accuracy rate of exacting measurements in comparison to the completed tile bond. These results in turn will be presented to United Space Alliance and Boeing North America for their own analysis and determination. Aerospace structures operate under extreme thermal environments. Hot external aerothermal environments in high Mach number flights lead to high structural temperatures. The differences between tile heights from one to another are very critical during these high Mach reentries. The Space Shuttle Thermal Protection System is a very delicate and highly calculated system. The thermal tiles on the ship are measured to within an accuracy of .001 of an inch. The accuracy of these tile measurements is critical to a successful reentry of an orbiter. This is why it is necessary to find the most accurate method for measuring the height of each tile in comparison to each of the other tiles. The test results indicated that there were indeed differences in the selected materials used in step measurements during prefits of Thermal Protection System Tiles and that Bees' Wax yielded a higher rate of accuracy when compared to the baseline test. In addition, testing for experience level in accuracy yielded no evidence of difference to be found. Lastly the use of the Trammel tool over the Shim Pack yielded variable difference for those tests.

Genetic parameters and path analysis in cowpea genotypes grown in the Cerrado/Pantanal ecotone.

PubMed

Lopes, K V; Teodoro, P E; Silva, F A; Silva, M T; Fernandes, R L; Rodrigues, T C; Faria, T C; Corrêa, A M

2017-05-18

Estimating genetic parameters in plant breeding allows us to know the population potential for selecting and designing strategies that can maximize the achievement of superior genotypes. The objective of this study was to evaluate the genetic potential of a population of 20 cowpea genotypes by estimating genetic parameters and path analysis among the traits to guide the selection strategies. The trial was conducted in randomized block design with four replications. Its morphophysiological components, components of green grain production and dry grain yield were estimated from genetic use and correlations between the traits. Phenotypic correlations were deployed through path analysis into direct and indirect effects of morphophysiological traits and yield components on dry grain yield. There were significant differences (P < 0.01) between the genotypes for most the traits, indicating the presence of genetic variability in the population and the possibility of practicing selection. The population presents the potential for future genetic breeding studies and is highly promising for the selection of traits dry grain yield, the number of grains per pod, and hundred grains mass. A number of grains per green pod is the main determinant trait of dry grain yield that is also influenced by the cultivar cycle and that the selection for the dry grain yield can be made indirectly by selecting the green pod mass and green pod length.

Spectrally-Based Assessment of Crop Seasonal Performance and Yield

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Borisova, Denitsa; Georgiev, Georgy

The rapid advances of space technologies concern almost all scientific areas from aeronautics to medicine, and a wide range of application fields from communications to crop yield predictions. Agricultural monitoring is among the priorities of remote sensing observations for getting timely information on crop development. Monitoring agricultural fields during the growing season plays an important role in crop health assessment and stress detection provided that reliable data is obtained. Successfully spreading is the implementation of hyperspectral data to precision farming associated with plant growth and phenology monitoring, physiological state assessment, and yield prediction. In this paper, we investigated various spectral-biophysical relationships derived from in-situ reflectance measurements. The performance of spectral data for the assessment of agricultural crops condition and yield prediction was examined. The approach comprisesd development of regression models between plant spectral and state-indicative variables such as biomass, vegetation cover fraction, leaf area index, etc., and development of yield forecasting models from single-date (growth stage) and multitemporal (seasonal) reflectance data. Verification of spectral predictions was performed through comparison with estimations from biophysical relationships between crop growth variables. The study was carried out for spring barley and winter wheat. Visible and near-infrared reflectance data was acquired through the whole growing season accompanied by detailed datasets on plant phenology and canopy structural and biochemical attributes. Empirical relationships were derived relating crop agronomic variables and yield to various spectral predictors. The study findings were tested using airborne remote sensing inputs. A good correspondence was found between predicted and actual (ground-truth) estimates

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

THE MASS-RICHNESS RELATION OF MaxBCG CLUSTERS FROM QUASAR LENSING MAGNIFICATION USING VARIABILITY

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

Bauer, Anne H.; Baltay, Charles; Ellman, Nancy

2012-04-10

Accurate measurement of galaxy cluster masses is an essential component not only in studies of cluster physics but also for probes of cosmology. However, different mass measurement techniques frequently yield discrepant results. The Sloan Digital Sky Survey MaxBCG catalog's mass-richness relation has previously been constrained using weak lensing shear, Sunyaev-Zeldovich (SZ), and X-ray measurements. The mass normalization of the clusters as measured by weak lensing shear is {approx}>25% higher than that measured using SZ and X-ray methods, a difference much larger than the stated measurement errors in the analyses. We constrain the mass-richness relation of the MaxBCG galaxy cluster catalogmore » by measuring the gravitational lensing magnification of type I quasars in the background of the clusters. The magnification is determined using the quasars' variability and the correlation between quasars' variability amplitude and intrinsic luminosity. The mass-richness relation determined through magnification is in agreement with that measured using shear, confirming that the lensing strength of the clusters implies a high mass normalization and that the discrepancy with other methods is not due to a shear-related systematic measurement error. We study the dependence of the measured mass normalization on the cluster halo orientation. As expected, line-of-sight clusters yield a higher normalization; however, this minority of haloes does not significantly bias the average mass-richness relation of the catalog.« less

How can we reduce costs of solid-phase multiplex-bead assays used to determine anti-HLA antibodies?

PubMed

Kamburova, E G; Wisse, B W; Joosten, I; Allebes, W A; van der Meer, A; Hilbrands, L B; Baas, M C; Spierings, E; Hack, C E; van Reekum, F E; van Zuilen, A D; Verhaar, M; Bots, M L; Drop, A C A D; Plaisier, L; Seelen, M A J; Sanders, J S F; Hepkema, B G; Lambeck, A J; Bungener, L B; Roozendaal, C; Tilanus, M G J; Vanderlocht, J; Voorter, C E; Wieten, L; van Duijnhoven, E M; Gelens, M; Christiaans, M H L; van Ittersum, F J; Nurmohamed, A; Lardy, N M; Swelsen, W; van der Pant, K A; van der Weerd, N C; Ten Berge, I J M; Bemelman, F J; Hoitsma, A; van der Boog, P J M; de Fijter, J W; Betjes, M G H; Heidt, S; Roelen, D L; Claas, F H; Otten, H G

2016-09-01

Solid-phase multiplex-bead assays are widely used in transplantation to detect anti-human leukocyte antigen (HLA) antibodies. These assays enable high resolution detection of low levels of HLA antibodies. However, multiplex-bead assays are costly and yield variable measurements that limit the comparison of results between laboratories. In the context of a Dutch national Consortium study we aimed to determine the inter-assay and inter-machine variability of multiplex-bead assays, and we assessed how to reduce the assay reagents costs. Fifteen sera containing a variety of HLA antibodies were used yielding in total 7092 median fluorescence intensities (MFI) values. The inter-assay and inter-machine mean absolute relative differences (MARD) of the screening assay were 12% and 13%, respectively. The single antigen bead (SAB) inter-assay MARD was comparable, but showed a higher lot-to-lot variability. Reduction of screening assay reagents to 50% or 40% of manufacturers' recommendations resulted in MFI values comparable to 100% of the reagents, with an MARD of 12% or 14%, respectively. The MARD of the 50% and 40% SAB assay reagent reductions were 11% and 22%, respectively. From this study, we conclude that the reagents can be reliably reduced at least to 50% of manufacturers' recommendations with virtually no differences in HLA antibody assignments. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Box-Behnken design based statistical modeling for ultrasound-assisted extraction of corn silk polysaccharide.

PubMed

Prakash Maran, J; Manikandan, S; Thirugnanasambandham, K; Vigna Nivetha, C; Dinesh, R

2013-01-30

In this study, ultrasound assisted extraction (UAE) conditions on the yield of polysaccharide from corn silk were studied using three factors, three level Box-Behnken response surface design. Process parameters, which affect the efficiency of UAE such as extraction temperature (40-60 °C), time (10-30 min) and solid-liquid ratio (1:10-1:30 g/ml) were investigated. The results showed that, the extraction conditions have significant effects on extraction yield of polysaccharide. The obtained experimental data were fitted to a second-order polynomial equation using multiple regression analysis with high coefficient of determination value (R(2)) of 0.994. An optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variables (extraction temperature of 56 °C, time of 17 min and solid-liquid ratio of 1:20 g/ml) were determined with maximum polysaccharide yield of 6.06%, which was confirmed through validation experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.

Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

PubMed

Foley, Finbar; Rajagopalan, Srinivasan; Raghunath, Sushravya M; Boland, Jennifer M; Karwoski, Ronald A; Maldonado, Fabien; Bartholmai, Brian J; Peikert, Tobias

2016-01-01

Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Finite element analysis on flexural behavior of high ductility of fiber reinforced concrete beam

NASA Astrophysics Data System (ADS)

Zhou, Mohan; Chi, Cuiping; Pei, Changchun

2017-03-01

In this paper, finite element software is used to simulate and analyze ECC beams. With the ratio of water-binder, fiber content and the content of fly ash as variables, the initial cracking moments, the yield moments, the initial cracking deflections, and the yield deflections of the ECC beams are studied. The results show that the lower the water-binder ratio is, the better the beam performance is; When the fiber content is 13kg/m3, the mechanical properties of the ECC beams are the lowest, and then strengthen; When the content of fly ash increase, the bending moment of the specimen beam becomes smaller and the deflection tends to increase, however the deflection of the fly ash decreases when the content of fly ash is higher than 1300kg/m3 in the initial cracking. According to the formula of ordinary concrete ultimate load capacity, the formula of yield capacity of ECC beam is deduced.

Assessment of bioethanol yield by S. cerevisiae grown on oil palm residues: Monte Carlo simulation and sensitivity analysis.

PubMed

Samsudin, Mohd Dinie Muhaimin; Mat Don, Mashitah

2015-01-01

Oil palm trunk (OPT) sap was utilized for growth and bioethanol production by Saccharomycescerevisiae with addition of palm oil mill effluent (POME) as nutrients supplier. Maximum yield (YP/S) was attained at 0.464g bioethanol/g glucose presence in the OPT sap-POME-based media. However, OPT sap and POME are heterogeneous in properties and fermentation performance might change if it is repeated. Contribution of parametric uncertainty analysis on bioethanol fermentation performance was then assessed using Monte Carlo simulation (stochastic variable) to determine probability distributions due to fluctuation and variation of kinetic model parameters. Results showed that based on 100,000 samples tested, the yield (YP/S) ranged 0.423-0.501g/g. Sensitivity analysis was also done to evaluate the impact of each kinetic parameter on the fermentation performance. It is found that bioethanol fermentation highly depend on growth of the tested yeast. Copyright © 2014 Elsevier Ltd. All rights reserved.

Do heart and respiratory rate variability improve prediction of extubation outcomes in critically ill patients?

PubMed Central

2014-01-01

Introduction Prolonged ventilation and failed extubation are associated with increased harm and cost. The added value of heart and respiratory rate variability (HRV and RRV) during spontaneous breathing trials (SBTs) to predict extubation failure remains unknown. Methods We enrolled 721 patients in a multicenter (12 sites), prospective, observational study, evaluating clinical estimates of risk of extubation failure, physiologic measures recorded during SBTs, HRV and RRV recorded before and during the last SBT prior to extubation, and extubation outcomes. We excluded 287 patients because of protocol or technical violations, or poor data quality. Measures of variability (97 HRV, 82 RRV) were calculated from electrocardiogram and capnography waveforms followed by automated cleaning and variability analysis using Continuous Individualized Multiorgan Variability Analysis (CIMVA™) software. Repeated randomized subsampling with training, validation, and testing were used to derive and compare predictive models. Results Of 434 patients with high-quality data, 51 (12%) failed extubation. Two HRV and eight RRV measures showed statistically significant association with extubation failure (P <0.0041, 5% false discovery rate). An ensemble average of five univariate logistic regression models using RRV during SBT, yielding a probability of extubation failure (called WAVE score), demonstrated optimal predictive capacity. With repeated random subsampling and testing, the model showed mean receiver operating characteristic area under the curve (ROC AUC) of 0.69, higher than heart rate (0.51), rapid shallow breathing index (RBSI; 0.61) and respiratory rate (0.63). After deriving a WAVE model based on all data, training-set performance demonstrated that the model increased its predictive power when applied to patients conventionally considered high risk: a WAVE score >0.5 in patients with RSBI >105 and perceived high risk of failure yielded a fold increase in risk of extubation failure of 3.0 (95% confidence interval (CI) 1.2 to 5.2) and 3.5 (95% CI 1.9 to 5.4), respectively. Conclusions Altered HRV and RRV (during the SBT prior to extubation) are significantly associated with extubation failure. A predictive model using RRV during the last SBT provided optimal accuracy of prediction in all patients, with improved accuracy when combined with clinical impression or RSBI. This model requires a validation cohort to evaluate accuracy and generalizability. Trial registration ClinicalTrials.gov NCT01237886. Registered 13 October 2010. PMID:24713049

An Overview on Measurement-While-Drilling Technique and its Scope in Excavation Industry

NASA Astrophysics Data System (ADS)

Rai, P.; Schunesson, H.; Lindqvist, P.-A.; Kumar, U.

2015-04-01

Measurement-while-drilling (MWD) aims at collecting accurate, speedy and high resolution information from the production blast hole drills with a target of characterization of highly variable rock masses encountered in sub-surface excavations. The essence of the technique rests on combining the physical drill variables in a manner to yield a fairly accurate description of the sub-surface rock mass much ahead of following downstream operations. In this light, the current paper presents an overview of the MWD by explaining the technique and its set-up, the existing drill-rock mass relationships and numerous on-going researches highlighting the real-time applications. Although the paper acknowledges the importance of concepts of specific energy, rock quality index and a couple of other indices and techniques for rock mass characterization, it must be distinctly borne in mind that the technique of MWD is highly site-specific, which entails derivation of site-specific calibration with utmost care.

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

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

PubMed

Bicu, Ioan; Mustata, Fanica

2013-10-15

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

Response of winter and spring wheat grain yields to meteorological variation

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Isolation and characterization of hydrophobic compounds from carbohydrate matrix of Pistacia atlantica.

PubMed

Samavati, Vahid; Adeli, Mostafa

2014-01-30

The present work is focused on the optimization of hydrophobic compounds extraction process from the carbohydrate matrix of Iranian Pistacia atlantica seed at laboratory level using ultrasonic-assisted extraction. Response surface methodology (RSM) was used to optimize oil seed extraction yield. Independent variables were extraction temperature (30, 45, 60, 75 and 90°C), extraction time (10, 15, 20, 25, 30 and 35 min) and power of ultrasonic (20, 40, 60, 80 and 100 W). A second order polynomial equation was used to express the oil extraction yield as a function of independent variables. The responses and variables were fitted well to each other by multiple regressions. The optimum extraction conditions were as follows: extraction temperature of 75°C, extraction time of 25 min, and power of ultrasonic of 80 W. A comparison between seed oil composition extracted by ultrasonic waves under the optimum operating conditions determined by RSM for oil yield and by organic solvent was reported. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2003-08-01

benign and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form images of ultrasonic angular scatter. This method provides a new source of image contrast and should enhance the detectability of MCs and improve the differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. In this first year 0 funding, we have formed images in tissue mimicking phantoms and found that

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Tradeoffs between water requirements and yield stability in annual vs. perennial crops

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel A.

2018-02-01

Population growth and changes in climate and diets will likely further increase the pressure on agriculture and water resources globally. Currently, staple crops are obtained from annuals plants. A shift towards perennial crops may enhance many ecosystem services, but at the cost of higher water requirements and lower yields. It is still unclear when the advantages of perennial crops overcome their disadvantages and perennial crops are thus a sustainable solution. Here we combine a probabilistic description of the soil water balance and crop development with an extensive dataset of traits of congeneric annuals and perennials to identify the conditions for which perennial crops are more viable than annual ones with reference to yield, yield stability, and effective use of water. We show that the larger and more developed roots of perennial crops allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species, but their yields remain lower when considering grain crops. Furthermore, perennial crops have higher and more variable irrigation requirements and lower water productivity. These results are important to understand the potential consequences for yield, its stability, and water resource use of a shift from annual to perennial crops and, more generally, if perennial crops may be more resilient than annual crops in the face of climatic fluctuations.

Identification of heterotic loci associated with yield-related traits in Chinese common wild rice (Oryza rufipogon Griff.).

PubMed

Luo, Xiaojin; Wu, Shuang; Tian, Feng; Xin, Xiaoyun; Zha, Xiaojun; Dong, Xianxin; Fu, Yongcai; Wang, Xiangkun; Yang, Jinshui; Sun, Chuanqing

2011-07-01

Many rice breeding programs have currently reached yield plateaus as a result of limited genetic variability in parental strains. Dongxiang common wild rice (Oryza rufipogon Griff.) is the progenitor of cultivated rice (Oryza sativa L.) and serves as an important gene pool for the genetic improvement of rice cultivars. In this study, heterotic loci (HLs) associated with six yield-related traits were identified in wild and cultivated rice and investigated using a set of 265 introgression lines (ILs) of O. rufipogon Griff. in the background of the Indica high-yielding cultivar Guichao 2 (O. sativa L.). Forty-two HLs were detected by a single point analysis of mid-parent heterosis values from test cross F(1) offspring, and 30 (71.5%) of these HLs showed significantly positive effects, consistent with the superiority shown by the F(1) test cross population in the six yield-related traits under study. Genetic mapping of hsp11, a locus responsible for the number of spikelets per panicle, confirmed the utility of these HLs. The results indicate that favorable HLs capable of improving agronomic traits are available. The identification of HLs between wild rice and cultivated rice could lead to a new strategy for the application of heterosis in rice breeding. Copyright © 2011. Published by Elsevier Ireland Ltd.

Optimization of dilute acid pretreatment of water hyacinth biomass for enzymatic hydrolysis and ethanol production

PubMed Central

Idrees, Muhammad; Adnan, Ahmad; Sheikh, Shahzad; Qureshic, Fahim Ashraf

2013-01-01

The present study was conducted for the optimization of pretreatment process that was used for enzymatic hydrolysis of lignocellulosic biomass (Water Hyacinth, WH), which is a renewable resource for the production of bioethanol with decentralized availability. Response surface methodology has been employed for the optimization of temperature (oC), time (hr) and different concentrations of maleic acid (MA), sulfuric acid (SA) and phosphoric acid (PA) that seemed to be significant variables with P < 0.05. High F and R2 values and low P-value for hydrolysis yield indicated the model predictability. The pretreated biomass producing 39.96 g/l, 39.86 g/l and 37.9 g/l of reducing sugars during enzymatic hydrolysis with yield 79.93, 78.71 and 75.9 % from PA, MA and SA treated respectively. The order of catalytic effectiveness for hydrolysis yield was found to be phosphoric acid > maleic acid > sulfuric acid. Mixture of sugars was obtained during dilute acid pretreatment with glucose being the most prominent sugar while pure glucose was obtained during enzymatic hydrolysis. The resulting sugars, obtained during enzymatic hydrolysis were finally fermented to ethanol, with yield 0.484 g/g of reducing sugars which is 95 % of theoretical yield (0.51 g/g glucose) by using commercial baker's yeast (Sacchromyces cerveasiae). PMID:26417215

Bee pollination increases yield quantity and quality of cash crops in Burkina Faso, West Africa.

PubMed

Stein, Katharina; Coulibaly, Drissa; Stenchly, Kathrin; Goetze, Dethardt; Porembski, Stefan; Lindner, André; Konaté, Souleymane; Linsenmair, Eduard K

2017-12-18

Mutualistic biotic interactions as among flowering plants and their animal pollinators are a key component of biodiversity. Pollination, especially by insects, is a key element in ecosystem functioning, and hence constitutes an ecosystem service of global importance. Not only sexual reproduction of plants is ensured, but also yields are stabilized and genetic variability of crops is maintained, counteracting inbreeding depression and facilitating system resilience. While experiencing rapid environmental change, there is an increased demand for food and income security, especially in sub-Saharan communities, which are highly dependent on small scale agriculture. By combining exclusion experiments, pollinator surveys and field manipulations, this study for the first time quantifies the contribution of bee pollinators to smallholders' production of the major cash crops, cotton and sesame, in Burkina Faso. Pollination by honeybees and wild bees significantly increased yield quantity and quality on average up to 62%, while exclusion of pollinators caused an average yield gap of 37% in cotton and 59% in sesame. Self-pollination revealed inbreeding depression effects on fruit set and low germination rates in the F1-generation. Our results highlight potential negative consequences of any pollinator decline, provoking risks to agriculture and compromising crop yields in sub-Saharan West Africa.

Stability measures in arid ecosystems

NASA Astrophysics Data System (ADS)

Nosshi, M. I.; Brunsell, N. A.; Koerner, S.

2015-12-01

Stability, the capacity of ecosystems to persist in the face of change, has proven its relevance as a fundamental component of ecological theory. Here, we would like to explore meaningful and quantifiable metrics to define stability, with a focus on highly variable arid and semi-arid savanna ecosystems. Recognizing the importance of a characteristic timescale to any definition of stability, our metrics will be focused scales from annual to multi-annual, capturing different aspects of stability. Our three measures of stability, in increasing order of temporal scale, are: (1) Ecosystem resistance, quantified as the degree to which the system maintains its mean state in response to a perturbation (drought), based on inter-annual variability in Normalized Difference Vegetation Index (NDVI). (2) An optimization approach, relevant to arid systems with pulse dynamics, that models vegetation structure and function based on a trade off between the ability to respond to resource availability and avoid stress. (3) Community resilience, measured as species turnover rate (β diversity). Understanding the nature of stability in structurally-diverse arid ecosystems, which are highly variable, yields theoretical insight which has practical implications.

Spray-drying nanocapsules in presence of colloidal silica as drying auxiliary agent: formulation and process variables optimization using experimental designs.

PubMed

Tewa-Tagne, Patrice; Degobert, Ghania; Briançon, Stéphanie; Bordes, Claire; Gauvrit, Jean-Yves; Lanteri, Pierre; Fessi, Hatem

2007-04-01

Spray-drying process was used for the development of dried polymeric nanocapsules. The purpose of this research was to investigate the effects of formulation and process variables on the resulting powder characteristics in order to optimize them. Experimental designs were used in order to estimate the influence of formulation parameters (nanocapsules and silica concentrations) and process variables (inlet temperature, spray-flow air, feed flow rate and drying air flow rate) on spray-dried nanocapsules when using silica as drying auxiliary agent. The interactions among the formulation parameters and process variables were also studied. Responses analyzed for computing these effects and interactions were outlet temperature, moisture content, operation yield, particles size, and particulate density. Additional qualitative responses (particles morphology, powder behavior) were also considered. Nanocapsules and silica concentrations were the main factors influencing the yield, particulate density and particle size. In addition, they were concerned for the only significant interactions occurring among two different variables. None of the studied variables had major effect on the moisture content while the interaction between nanocapsules and silica in the feed was of first interest and determinant for both the qualitative and quantitative responses. The particles morphology depended on the feed formulation but was unaffected by the process conditions. This study demonstrated that drying nanocapsules using silica as auxiliary agent by spray drying process enables the obtaining of dried micronic particle size. The optimization of the process and the formulation variables resulted in a considerable improvement of product yield while minimizing the moisture content.

NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso.

PubMed

Sorgho, Raissa; Franke, Jonas; Simboro, Seraphin; Phalkey, Revati; Saeurborn, Rainer

Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3-4 °C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variables through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons.

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

Sinistore, Julie C.; Reinemann, D. J.; Izaurralde, Roberto C.

Spatial variability in yields and greenhouse gas emissions from soils has been identified as a key source of variability in life cycle assessments (LCAs) of agricultural products such as cellulosic ethanol. This study aims to conduct an LCA of cellulosic ethanol production from switchgrass in a way that captures this spatial variability and tests results for sensitivity to using spatially averaged results. The Environment Policy Integrated Climate (EPIC) model was used to calculate switchgrass yields, greenhouse gas (GHG) emissions, and nitrogen and phosphorus emissions from crop production in southern Wisconsin and Michigan at the watershed scale. These data were combinedmore » with cellulosic ethanol production data via ammonia fiber expansion and dilute acid pretreatment methods and region-specific electricity production data into an LCA model of eight ethanol production scenarios. Standard deviations from the spatial mean yields and soil emissions were used to test the sensitivity of net energy ratio, global warming potential intensity, and eutrophication and acidification potential metrics to spatial variability. Substantial variation in the eutrophication potential was also observed when nitrogen and phosphorus emissions from soils were varied. This work illustrates the need for spatially explicit agricultural production data in the LCA of biofuels and other agricultural products.« less

A biologically inspired variable-pH strategy for enhancing short-chain fatty acids (SCFAs) accumulation in maize straw fermentation.

PubMed

Meng, Yao; Mumme, Jan; Xu, Heng; Wang, Kaijun

2016-02-01

This study investigates the feasibility of varying the pH to enhance the accumulation of short-chain fatty acids (SCFAs) in the in vitro fermentation of maize straw. The corresponding hydrolysis rate and the net SCFA yield increased as inoculum ratio (VSinoculum/VSsubstrate) increased from 0.09 to 0.79. The pH were maintained at 5.3, 5.8, 6.3, 6.8, 7.3, and 7.8, respectively. A neutral pH of approximately 6.8 was optimal for hydrolysis. The net SCFA yield decreased by 34.9% for a pH of less than 5.8, but remained constant at approximately 721±5mg/gvs for a pH between 5.8 and 7.8. In addition, results were obtained for variable and constant pH levels at initial substrate concentrations of 10, 30 and 50g/L. A variable pH increased the net SCFA yield by 23.6%, 29.0%, and 36.6% for concentrations of 10, 30 and 50g/L. Therefore, a variable pH enhanced SCFA accumulation in maize straw fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

ENSO and PDO-related climate variability impacts on Midwestern United States crop yields.

PubMed

Henson, Chasity; Market, Patrick; Lupo, Anthony; Guinan, Patrick

2017-05-01

An analysis of crop yields for the state of Missouri was completed to determine if an interannual or multidecadal variability existed as a result of the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Corn and soybean yields were recorded in kilograms per hectare for each of the six climate regions of Missouri. An analysis using the Mokhov "method of cycles" demonstrated interannual, interdecadal, and multidecadal variations in crop yields. Cross-spectral analysis was used to determine which region was most impacted by ENSO and PDO influenced seasonal (April-September) temperature and precipitation. Interannual (multidecadal) variations found in the spectral analysis represent a relationship to ENSO (PDO) phase, while interdecadal variations represent a possible interaction between ENSO and PDO. Average crop yields were then calculated for each combination of ENSO and PDO phase, displaying a pronounced increase in corn and soybean yields when ENSO is warm and PDO is positive. Climate regions 1, 2, 4, and 6 displayed significant differences (p value of 0.10 or less) in yields between El Niño and La Niña years, representing 55-70 % of Missouri soybean and corn productivity, respectively. Final results give the opportunity to produce seasonal predictions of corn and soybean yields, specific to each climate region in Missouri, based on the combination of ENSO and PDO phases.

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

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.

Productivity limits and potentials of the principles of conservation agriculture.

PubMed

Pittelkow, Cameron M; Liang, Xinqiang; Linquist, Bruce A; van Groenigen, Kees Jan; Lee, Juhwan; Lundy, Mark E; van Gestel, Natasja; Six, Johan; Venterea, Rodney T; van Kessel, Chris

2015-01-15

One of the primary challenges of our time is to feed a growing and more demanding world population with reduced external inputs and minimal environmental impacts, all under more variable and extreme climate conditions in the future. Conservation agriculture represents a set of three crop management principles that has received strong international support to help address this challenge, with recent conservation agriculture efforts focusing on smallholder farming systems in sub-Saharan Africa and South Asia. However, conservation agriculture is highly debated, with respect to both its effects on crop yields and its applicability in different farming contexts. Here we conduct a global meta-analysis using 5,463 paired yield observations from 610 studies to compare no-till, the original and central concept of conservation agriculture, with conventional tillage practices across 48 crops and 63 countries. Overall, our results show that no-till reduces yields, yet this response is variable and under certain conditions no-till can produce equivalent or greater yields than conventional tillage. Importantly, when no-till is combined with the other two conservation agriculture principles of residue retention and crop rotation, its negative impacts are minimized. Moreover, no-till in combination with the other two principles significantly increases rainfed crop productivity in dry climates, suggesting that it may become an important climate-change adaptation strategy for ever-drier regions of the world. However, any expansion of conservation agriculture should be done with caution in these areas, as implementation of the other two principles is often challenging in resource-poor and vulnerable smallholder farming systems, thereby increasing the likelihood of yield losses rather than gains. Although farming systems are multifunctional, and environmental and socio-economic factors need to be considered, our analysis indicates that the potential contribution of no-till to the sustainable intensification of agriculture is more limited than often assumed.

Ozone and sulfur dioxide effects on three tall fescue cultivars

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

Flagler, R.B.; Youngner, V.B.

Although many reports have been published concerning differential susceptibility of various crops and/or cultivars to air pollutants, most have used foliar injury instead of the marketable yield as the factor that determined susceptibility for the crop. In an examination of screening in terms of marketable yield, three cultivars of tall fescue (Festuca arundinacea Schreb.), 'Alta,' 'Fawn,' and 'Kentucky 31,' were exposed to 0-0.40 ppm O/sub 3/ or 0-0.50 ppm SO/sub 2/ 6 h/d, once a week, for 7 and 9 weeks, respectively. Experimental design was a randomized complete block with three replications. Statistical analysis was by standard analysis of variancemore » and regression techniques. Three variables were analyzed: top dry weight (yield), tiller number, and weight per tiller. Ozone had a significant effect on all three variables. Significant linear decreases in yield and weight per tiller occurred with increasing O/sub 3/ concentrations. Linear regressions of these variables on O/sub 3/ concentration produced significantly different regression coefficients. The coefficient for Kentucky 31 was significantly greater than Alta or Fawn, which did not differ from each other. This indicated that Kentucky 31 was more susceptible to O/sub 3/ than either of the other cultivars. Percent reductions in dry weight for the three cultivars at highest O/sub 3/ level were 35, 44, and 53%, respectively, for Fawn, Alta, and Kentucky 31. For weight per tiller, Kentucky 31 had a higher percent reduction than the other cultivars (59 vs. 46 and 44%). Tiller number was generally increased by O/sub 3/, but this variable was not useful for determining differential susceptibility to the pollutant. Sulfur dioxide treatments produced no significant effects on any of the variables analyzed.« less

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

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

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

Long-term lightcurves from combined unified very high energy γ-ray data

NASA Astrophysics Data System (ADS)

Tluczykont, M.; Bernardini, E.; Satalecka, K.; Clavero, R.; Shayduk, M.; Kalekin, O.

2010-12-01

Context. Very high-energy (VHE, E > 100 GeV) γ-ray data are a valuable input for multi-wavelength and multi-messenger (e.g. combination with neutrino data) studies. Aims: We aim at the conservation and homogenization of historical, current, and future VHE γ-ray-data on active galactic nuclei (AGN). Methods: We have collected lightcurve data taken by major VHE experiments since 1991 and combined them into long-term lightcurves for several AGN, and now provide our collected datasets for further use. Due to the lack of common data formats in VHE γ-ray astronomy, we have defined relevant datafields to be stored in standard data formats. The time variability of the combined VHE lightcurve data was investigated, and correlation with archival X-ray data collected by RXTE/ASM tested. Results: The combination of data on the prominent blazar Mrk 421 from different experiments yields a lightcurve spanning more than a decade. From this combined dataset we derive an integral baseline flux from Mrk 421 that must be lower than 33% of the Crab Nebula flux above 1 TeV. The analysis of the time variability yields log-normal flux variations in the VHE-data on Mrk 421. Conclusions: Existing VHE data contain valuable information concerning the variability of AGN and can be an important ingredient for multi-wavelength or multi-messenger studies. In the future, upcoming and planned experiments will provide more data from many transient objects, and the interaction of VHE astronomy with classical astronomy will intensify. In this context a unified and exchangeable data format will become increasingly important. Our data collection is available at the url: http://nuastro-zeuthen.desy.de/magic_experiment/projects/light_curve_archive/index_eng.html

Sustainability analysis of bioenergy based land use change under climate change and variability

NASA Astrophysics Data System (ADS)

Raj, C.; Chaubey, I.; Brouder, S. M.; Bowling, L. C.; Cherkauer, K. A.; Frankenberger, J.; Goforth, R. R.; Gramig, B. M.; Volenec, J. J.

2014-12-01

Sustainability analyses of futuristic plausible land use and climate change scenarios are critical in making watershed-scale decisions for simultaneous improvement of food, energy and water management. Bioenergy production targets for the US are anticipated to impact farming practices through the introduction of fast growing and high yielding perennial grasses/trees, and use of crop residues as bioenergy feedstocks. These land use/land management changes raise concern over potential environmental impacts of bioenergy crop production scenarios, both in terms of water availability and water quality; impacts that may be exacerbated by climate variability and change. The objective of the study was to assess environmental, economic and biodiversity sustainability of plausible bioenergy scenarios for two watersheds in Midwest US under changing climate scenarios. The study considers fourteen sustainability indicators under nine climate change scenarios from World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The distributed hydrological model SWAT (Soil and Water Assessment Tool) was used to simulate perennial bioenergy crops such as Miscanthus and switchgrass, and corn stover removal at various removal rates and their impacts on hydrology and water quality. Species Distribution Models (SDMs) developed to evaluate stream fish response to hydrology and water quality changes associated with land use change were used to quantify biodiversity sustainability of various bioenergy scenarios. The watershed-scale sustainability analysis was done in the St. Joseph River watershed located in Indiana, Michigan, and Ohio; and the Wildcat Creek watershed, located in Indiana. The results indicate streamflow reduction at watershed outlet with increased evapotranspiration demands for high-yielding perennial grasses. Bioenergy crops in general improved in-stream water quality compared to conventional cropping systems (maize-soybean). Water quality benefits due to land use change were generally greater than the effects of climate change variability.

A strategy for high-level expression of a single-chain variable fragment against TNFα by subcloning antibody variable regions from the phage display vector pCANTAB 5E into pBV220.

PubMed

Yang, Tao; Yang, Lijun; Chai, Weiran; Li, Renke; Xie, Jun; Niu, Bo

2011-03-01

A phage display single-chain variable fragment (scFv) library against TNFα was constructed using a recombinant phage antibody system (RPAS). The cloned scFv gene was introduced into the phage display vector pCANTAB 5E and expressed in Escherichia coli (E. coli) with a yield of up to 0.15 mg/l of total protein. With the attempt to improve the expression level of TNF-scFv, a strategy was established for subcloning the scFv gene from pCANTAB 5E into the plasmid pBV220. Under the control of a highly efficient tandem P(R)P(L) promoter system, scFv production was increased to 30% of total protein as inclusion bodies. After extraction from the cell pellet by sonication, the inclusion bodies were solubilized and denatured in the presence of 8M urea. Purification of denatured scFv was performed using nickel column chromatography followed by renaturation. The purity and activity of the refolded scFv were confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), Western blotting and by an enzyme-linked immunoabsorbent assay (ELISA). The results reveal that the overall yield of bioactive TNF-scFv from E. coli flask cultures was more than 45 mg/l culture medium and 15 mg/g wet weight cells. The renatured scFv exhibited binding activity similarly to soluble scFv. In conclusion we developed a method to over-express TNF-scFv, which have biological function after purification and renaturation. Copyright © 2010 Elsevier Inc. All rights reserved.

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

USDA-ARS?s Scientific Manuscript database

Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

NASA Technical Reports Server (NTRS)

Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

2017-01-01

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

Impact of clonal variability in Vitis vinifera Cabernet franc on grape composition, wine quality, leaf blade stilbene content, and downy mildew resistance.

PubMed

van Leeuwen, Cornelis; Roby, Jean-Philippe; Alonso-Villaverde, Virginia; Gindro, Katia

2013-01-09

In this study, 10 clones of Vitis vinifera Cabernet franc (not yet commercial) have been phenotyped on precocity, grape composition, and assessment of wine quality made by microvinification in 2008-2010. Additionally, two original criteria have been considered: concentration of 3-isobutyl-2-methoxypyrazine (IBMP) in grapes and wines (the green bell pepper flavor) and resistance of grapevines to downy mildew ( Plasmopara viticola ) by stilbene quantification upon infection. Precocity of veraison varied up to four days at veraison. Berry size and yield were highly variable among clones. However, these variables were not correlated. Tanins and anthocyanins varied among clones in grapes and wines. Variations in grape and wine IBMP were not significant. Some clones showed lower susceptibility for downy mildew on leaves. Lower susceptibility was linked to a higher production of stilbenic phytoalexins involved in downy mildew resistance mechanisms.

Optimization of L-asparaginase production from novel Enterobacter sp., by submerged fermentation using response surface methodology.

PubMed

Erva, Rajeswara Reddy; Goswami, Ajgebi Nath; Suman, Priyanka; Vedanabhatla, Ravali; Rajulapati, Satish Babu

2017-03-16

The culture conditions and nutritional rations influencing the production of extra cellular antileukemic enzyme by novel Enterobacter aerogenes KCTC2190/MTCC111 were optimized in shake-flask culture. Process variables like pH, temperature, incubation time, carbon and nitrogen sources, inducer concentration, and inoculum size were taken into account. In the present study, finest enzyme activity achieved by traditional one variable at a time method was 7.6 IU/mL which was a 2.6-fold increase compared to the initial value. Further, the L-asparaginase production was optimized using response surface methodology, and validated experimental result at optimized process variables gave 18.35 IU/mL of L-asparaginase activity, which is 2.4-times higher than the traditional optimization approach. The study explored the E. aerogenes MTCC111 as a potent and potential bacterial source for high yield of antileukemic drug.

EUV local CDU healing performance and modeling capability towards 5nm node

NASA Astrophysics Data System (ADS)

Jee, Tae Kwon; Timoshkov, Vadim; Choi, Peter; Rio, David; Tsai, Yu-Cheng; Yaegashi, Hidetami; Koike, Kyohei; Fonseca, Carlos; Schoofs, Stijn

2017-10-01

Both local variability and optical proximity correction (OPC) errors are big contributors to the edge placement error (EPE) budget which is closely related to the device yield. The post-litho contact hole healing will be demonstrated to meet after-etch local variability specifications using a low dose, 30mJ/cm2 dose-to-size, positive tone developed (PTD) resist with relevant throughput in high volume manufacturing (HVM). The total local variability of the node 5nm (N5) contact holes will be characterized in terms of local CD uniformity (LCDU), local placement error (LPE), and contact edge roughness (CER) using a statistical methodology. The CD healing process has complex etch proximity effects, so the OPC prediction accuracy is challenging to meet EPE requirements for the N5. Thus, the prediction accuracy of an after-etch model will be investigated and discussed using ASML Tachyon OPC model.

Bromide's effect on DBP formation, speciation, and control; Part 1: Ozonation

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

Shukairy, H.M.; Summers, R.S.; Miltner, R.J.

1994-06-01

The effect of variable ozone dosage and bromide concentration on the formation of organic disinfection by-products (DBPs) and bromate were evaluated. Low ozone dosages resulted in oxidation of organic precursors, yielding decreases in the formation potential for total trihalomethanes (THMs), six haloacetic acids (HAAs), and total organic halide (TOX). Increasing the ozone dosage oxidized bromide to bromate, decreasing the bromide for incorporation into DBPs. Bromate concentrations were linearly correlated with ozone residuals. Changes in the bromine incorporation factors n and n[prime] reflected differences in the resulting speciation of THMs and HAAs, respectively. Because TOX measurements based on chloride equivalence maymore » underestimate the halogenated DBP yield for high-bromide waters, a procedure is described whereby bromide and bromate concentrations were used to correct the TOX measurement.« less

Precision Viticulture : is it relevant to manage the vineyard according to the within field spatial variability of the environment ?

NASA Astrophysics Data System (ADS)

Tisseyre, Bruno

2015-04-01

For more than 15 years, research projects are conducted in the precision viticulture (PV) area around the world. These research projects have provided new insights into the within-field variability in viticulture. Indeed, access to high spatial resolution data (remote sensing, embedded sensors, etc.) changes the knowledge we have of the fields in viticulture. In particular, the field which was until now considered as a homogeneous management unit, presents actually a high spatial variability in terms of yield, vigour an quality. This knowledge will lead (and is already causing) changes on how to manage the vineyard and the quality of the harvest at the within field scale. From the experimental results obtained in various countries of the world, the goal of the presentation is to provide figures on: - the spatial variability of the main parameters (yield, vigor, quality), and how this variability is organized spatially, - the temporal stability of the observed spatial variability and the potential link with environmental parameters like soil, topography, soil water availability, etc. - information sources available at a high spatial resolution conventionally used in precision agriculture likely to highlight this spatial variability (multi-spectral images, soil electrical conductivity, etc.) and the limitations that these information sources are likely to present in viticulture. Several strategies are currently being developed to take into account the within field variability in viticulture. They are based on the development of specific equipments, sensors, actuators and site specific strategies with the aim of adapting the vineyard operations at the within-field level. These strategies will be presented briefly in two ways : - Site specific operations (fertilization, pruning, thinning, irrigation, etc.) in order to counteract the effects of the environment and to obtain a final product with a controlled and consistent wine quality, - Differential harvesting with the objective to take advantage of the observed spatial variability to produce different quality of wines. These later approach tends to produce very different quality wines which will be blended to control the final quality and/or marketed differently. These applications show that the environment and its spatial variability can be valued with the goal of controlling the final quality of the wine produced. Technologies to characterize the spatial variability of vine fields are currently in rapid evolution. They will significantly impact production methods and management strategies of the vineyard. In its last part, the presentation will summarize the technologies likely to impact the knowledge and the vineyard management either at the field level, at the vineyard level or at the regional level. A brief overview of the needs in terms of information processing will be also performed. A reflection on the difficulties that might limit the adoption of precision viticulture technologies (PV) will be done. Indeed, although very informative, PV entails high costs of information acquisition and data processing. Cost is one of the major obstacles to the dissemination of these tools and services to the majority of wine producers. In this context, the pooling of investments is a choke point to make the VP accessible to the highest number of growers. Thus, to be adopted, the VP will necessarily satisfy the operational requirements at the field level, but also throughout the whole production area (at the regional level). This working scale raises new scientific questions to be addressed.

Fast Synthesis of Gibbsite Nanoplates and Process Optimization using Box-Behnken Experimental Design

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

Zhang, Xin; Zhang, Xianwen; Graham, Trent R.

Developing the ability to synthesize compositionally and morphologically well-defined gibbsite particles at the nanoscale with high yield is an ongoing need that has not yet achieved the level of rational design. Here we report optimization of a clean inorganic synthesis route based on statistical experimental design examining the influence of Al(OH)3 gel precursor concentration, pH, and aging time at temperature. At 80 oC, the optimum synthesis conditions of gel concentration at 0.5 M, pH at 9.2, and time at 72 h maximized the reaction yield up to ~87%. The resulting gibbsite product is composed of highly uniform euhedral hexagonal nanoplatesmore » within a basal plane diameter range of 200-400 nm. The independent roles of key system variables in the growth mechanism are considered. On the basis of these optimized experimental conditions, the synthesis procedure, which is both cost-effective and environmentally friendly, has the potential for mass production scale-up of high quality gibbsite material for various fundamental research and industrial applications.« less

Biochar from commercially cultivated seaweed for soil amelioration

PubMed Central

Roberts, David A.; Paul, Nicholas A.; Dworjanyn, Symon A.; Bird, Michael I.; de Nys, Rocky

2015-01-01

Seaweed cultivation is a high growth industry that is primarily targeted at human food and hydrocolloid markets. However, seaweed biomass also offers a feedstock for the production of nutrient-rich biochar for soil amelioration. We provide the first data of biochar yield and characteristics from intensively cultivated seaweeds (Saccharina, Undaria and Sargassum – brown seaweeds, and Gracilaria, Kappaphycus and Eucheuma – red seaweeds). While there is some variability in biochar properties as a function of the origin of seaweed, there are several defining and consistent characteristics of seaweed biochar, in particular a relatively low C content and surface area but high yield, essential trace elements (N, P and K) and exchangeable cations (particularly K). The pH of seaweed biochar ranges from neutral (7) to alkaline (11), allowing for broad-spectrum applications in diverse soil types. We find that seaweed biochar is a unique material for soil amelioration that is consistently different to biochar derived from ligno-cellulosic feedstock. Blending of seaweed and ligno-cellulosic biochar could provide a soil ameliorant that combines a high fixed C content with a mineral-rich substrate to enhance crop productivity. PMID:25856799

Biochar from commercially cultivated seaweed for soil amelioration.

PubMed

Roberts, David A; Paul, Nicholas A; Dworjanyn, Symon A; Bird, Michael I; de Nys, Rocky

2015-04-09

Seaweed cultivation is a high growth industry that is primarily targeted at human food and hydrocolloid markets. However, seaweed biomass also offers a feedstock for the production of nutrient-rich biochar for soil amelioration. We provide the first data of biochar yield and characteristics from intensively cultivated seaweeds (Saccharina, Undaria and Sargassum--brown seaweeds, and Gracilaria, Kappaphycus and Eucheuma--red seaweeds). While there is some variability in biochar properties as a function of the origin of seaweed, there are several defining and consistent characteristics of seaweed biochar, in particular a relatively low C content and surface area but high yield, essential trace elements (N, P and K) and exchangeable cations (particularly K). The pH of seaweed biochar ranges from neutral (7) to alkaline (11), allowing for broad-spectrum applications in diverse soil types. We find that seaweed biochar is a unique material for soil amelioration that is consistently different to biochar derived from ligno-cellulosic feedstock. Blending of seaweed and ligno-cellulosic biochar could provide a soil ameliorant that combines a high fixed C content with a mineral-rich substrate to enhance crop productivity.

Biochar from commercially cultivated seaweed for soil amelioration

NASA Astrophysics Data System (ADS)

Roberts, David A.; Paul, Nicholas A.; Dworjanyn, Symon A.; Bird, Michael I.; de Nys, Rocky

2015-04-01

Seaweed cultivation is a high growth industry that is primarily targeted at human food and hydrocolloid markets. However, seaweed biomass also offers a feedstock for the production of nutrient-rich biochar for soil amelioration. We provide the first data of biochar yield and characteristics from intensively cultivated seaweeds (Saccharina, Undaria and Sargassum - brown seaweeds, and Gracilaria, Kappaphycus and Eucheuma - red seaweeds). While there is some variability in biochar properties as a function of the origin of seaweed, there are several defining and consistent characteristics of seaweed biochar, in particular a relatively low C content and surface area but high yield, essential trace elements (N, P and K) and exchangeable cations (particularly K). The pH of seaweed biochar ranges from neutral (7) to alkaline (11), allowing for broad-spectrum applications in diverse soil types. We find that seaweed biochar is a unique material for soil amelioration that is consistently different to biochar derived from ligno-cellulosic feedstock. Blending of seaweed and ligno-cellulosic biochar could provide a soil ameliorant that combines a high fixed C content with a mineral-rich substrate to enhance crop productivity.

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

PubMed

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

2017-05-01

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

Climate change impacts on crop yield in the Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Toreti, Andrea; Ceglar, Andrej; Dentener, Frank; Niemeyer, Stefan; Dosio, Alessandro; Fumagalli, Davide

2017-04-01

Agriculture is strongly influenced by climate variability, climate extremes and climate changes. Recent studies on past decades have identified and analysed the effects of climate variability and extremes on crop yields in the Euro-Mediterranean region. As these effects could be amplified in a changing climate context, it is essential to analyse available climate projections and investigate the possible impacts on European agriculture in terms of crop yield. In this study, five model runs from the Euro-CORDEX initiative under two scenarios (RCP4.5 and RCP8.5) have been used. Climate model data have been bias corrected and then used to feed a mechanistic crop growth model. The crop model has been run under different settings to better sample the intrinsic uncertainties. Among the main results, it is worth to report a weak but significant and spatially homogeneous increase in potential wheat yield at mid-century (under a CO2 fertilisation effect scenario). While more complex changes seem to characterise potential maize yield, with large areas in the region showing a weak-to-moderate decrease.

Improving Seasonal Crop Monitoring and Forecasting for Soybean and Corn in Iowa

NASA Astrophysics Data System (ADS)

Togliatti, K.; Archontoulis, S.; Dietzel, R.; VanLoocke, A.

2016-12-01

Accurately forecasting crop yield in advance of harvest could greatly benefit farmers, however few evaluations have been conducted to determine the effectiveness of forecasting methods. We tested one such method that used a combination of short-term weather forecasting from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation and radiation at 4 different forecast lengths (2 weeks, 1 week, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data from the Iowa Environmental Mesonet was combined to drive Agricultural Production Systems sIMulator (APSIM) simulations to forecast soybean and corn yields in 2015 and 2016. The goal of this study is to find the forecast length that reduces the variability of simulated yield predictions while also increasing the accuracy of those predictions. APSIM simulations of crop variables were evaluated against bi-weekly field measurements of phenology, biomass, and leaf area index from early and late planted soybean plots located at the Agricultural Engineering and Agronomy Research Farm in central Iowa as well as the Northwest Research Farm in northwestern Iowa. WRF model predictions were evaluated against observed weather data collected at the experimental fields. Maximum temperature was the most accurately predicted variable, followed by minimum temperature and radiation, and precipitation was least accurate according to RMSE values and the number of days that were forecasted within a 20% error of the observed weather. Our analysis indicated that for the majority of months in the growing season the 3 day forecast performed the best. The 1 week forecast came in second and the 2 week forecast was the least accurate for the majority of months. Preliminary results for yield indicate that the 2 week forecast is the least variable of the forecast lengths, however it also is the least accurate. The 3 day and 1 week forecast have a better accuracy, with an increase in variability.

Large Area Crop Inventory Experiment (LACIE). Feasibility of assessing crop condition and yield from LANDSAT data

NASA Technical Reports Server (NTRS)

1978-01-01

The author has identified the following significant results. Yield modelling for crop production estimation derived a means of predicting the within-a-year yield and the year-to-year variability of yield over some fixed or randomly located unit of area. Preliminary studies indicated that the requirements for interpreting LANDSAT data for yield may be sufficiently similar to those of signature extension that it is feasible to investigate the automated estimation of production. The concept of an advanced yield model consisting of both spectral and meteorological components was endorsed. Rationale for using meteorological parameters originated from known between season and near harvest dynamics in crop environmental-condition-yield relationships.

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.

Technology of compact MAb and its application for medicinal plant breeding named as missile type molecular breeding.

PubMed

Putalun, Waraporn

2011-03-01

Single chain fragment-variable (scFv) enhanced solasodine glycoside accumulation in Solanum khasianum hairy root cultures transformed by the ScFv solamargine (As)-scFv gene. The scFv protein was expressed at a high level in inclusion bodies of E. coli. After being renatured, the scFv protein was purified in a one-step manner by metal chelate affinity chromatography. The yield of refolded and purified scFv was 12.5 mg per 100 ml of cell culture. The characteristics of the As-scFv expressed in E. coli and transgenic hairy roots were similar to those of the parent monoclonal antibody (MAb). The expression of scFv protein provides a low cost and a high yield of functional scFv antibody against solamargine. The full linear range of the ELISA assay using scFv was extended from 1.5-10 µg/ml. The expressed anti-solamargine scFv protein could be useful for determination of total solasodine glycoside content in plant samples by ELISA. Solasodine glycoside levels in the transgenic hairy root were 2.3-fold higher than that in the wild-type hairy root based on the soluble protein level and binding activities. The As-scFv expressed in S. khasianum hairy roots enhanced solasodine glycosides accumulation and provide a novel medicinal plant breeding methodology that can produce a high yield of secondary metabolites.

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

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

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

PubMed Central

2011-01-01

Background The robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability. Results Based on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0); 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value < 0.1); 3. Addition of notable amount of intermediate precursors or nutrients improved product yield by over five folds (P-value < 0.05); 4. Performing the cultivation in a well-controlled bioreactor enhanced the yield of product by three folds (P-value < 0.05); 5. Contribution of oxygen to product yield was not statistically significant. Yield calculations for various chemicals using the linear model were in fairly good agreement with the experimental values. The model generally underestimated the ethanol production as compared to other chemicals, which supported the notion that the metabolism of Saccharomyces cerevisiae has historically evolved for robust alcohol fermentation. Conclusions We generated simple mathematical models for first-order approximation of chemical production yield from S. cerevisiae. These linear models provide empirical insights to the effects of strain engineering and cultivation conditions toward biosynthetic efficiency. These models may not only provide guidelines for metabolic engineers to synthesize desired products, but also be useful to compare the biosynthesis performance among different research papers. PMID:21689458

Observations of V420 Aur (HD 34921) needed to support spectroscopy

NASA Astrophysics Data System (ADS)

Waagen, Elizabeth O.

2016-10-01

Marcella Wijngaarden and Kelly Gourdji (graduate students at the University of Amsterdam/Anton Pannekoek Institute for Astronomy) have requested AAVSO observers' assistance in providing optical photometry of V420 Aur in support of their high-resolution spectroscopy with the Mercator telescope + Hermes spectrograph in La Palma 2016 October 7 through 17. They write: "[V420 Aur (HD 34921) is] the optical Be star that is part of a peculiar High Mass X-ray Binary...[that exhibits highly] complex and variable spectra...it is difficult to construct a physical model of this HMXB system, though based on these observations, the system is thought to contain a B[e] star with a dense plasma region, an accretion disk around a neutron star, a shell and circumstellar regions of cold dust. It has been over a decade since the last spectra were taken, and, given the highly variable nature of this star, we expect new observations to yield new information that will contribute to a better understanding of this system." Observations in BVRI (preferred over other bands) are requested beginning immediately and continuing through October 24. In all cases, timeseries in a few bands (i.e. BVRI) are preferred over single/a few observations in the other bands as it is the variability on relatively short timescales that is most important. "The target is bright so exposures should be long enough to reach good signal to noise in order to see the small variability amplitude but without saturating the target/comparison stars. We will study the variability on several timescales, so observations starting from a few per night to high cadence timeseries are useful." Finder charts with sequence may be created using the AAVSO Variable Star Plotter (https://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. See full Alert Notice for more details.

Investigation of effect of particle size and rumen fluid addition on specific methane yields of high lignocellulose grass silage.

PubMed

Wall, D M; Straccialini, B; Allen, E; Nolan, P; Herrmann, C; O'Kiely, P; Murphy, J D

2015-09-01

This work examines the digestion of advanced growth stage grass silage. Two variables were investigated: particle size (greater than 3 cm and less than 1cm) and rumen fluid addition. Batch studies indicated particle size and rumen fluid addition had little effect on specific methane yields (SMYs). In continuous digestion of 3 cm silage the SMY was 342 and 343 L CH4 kg(-1)VS, respectively, with and without rumen fluid addition. However, digester operation was significantly affected through silage floating on the liquor surface and its entanglement in the mixing system. Digestion of 1cm silage with no rumen fluid addition struggled; volatile fatty acid concentrations rose and SMYs dropped. The best case was 1cm silage with rumen fluid addition, offering higher SMYs of 371 L CH4 kg(-1)VS and stable operation throughout. Thus, physical and biological treatments benefited continuous digestion of high fibre grass silage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preparation of High Surface Area Activated Carbon from Spent Phenolic Resin by Microwave Heating and KOH Activation

NASA Astrophysics Data System (ADS)

Cheng, Song; Zhang, Libo; Zhang, Shengzhou; Xia, Hongying; Peng, Jinhui

2018-01-01

The spent phenolic resin is as raw material for preparing high surface area activated carbon (HSAAC) by microwave-assisted KOH activation. The effects of microwave power, activation duration and impregnation ratio (IR) on the iodine adsorption capability and yield of HSAAC were investigated. The surface characteristics of HSAAC were characterized by nitrogen adsorption isotherms, FTIR, SEM and TEM. The operating variables were optimized utilizing the response surface methodology (RSM) and were identified to be microwave power of 700 W, activation duration of 15 min and IR of 4, corresponding to a yield of 51.25 % and an iodine number of 2,384 mg/g. The pore structure parameters of the HSAAC, i. e., Brunauer-Emmett-Teller (BET) surface area, total pore volume, and average pore diameter were estimated to be 4,269 m2/g, 2.396 ml/g and 2.25 nm, respectively, under optimum conditions. The findings strongly support the feasibility of microwave-assisted KOH activation for preparation of HSAAC from spent phenolic resin.

A Review on Current Status and Future Prospects of Winged Bean (Psophocarpus tetragonolobus) in Tropical Agriculture.

PubMed

Lepcha, Patrush; Egan, Ashley N; Doyle, Jeff J; Sathyanarayana, N

2017-09-01

Winged bean, Psophocarpus tetragonolobus (L.) DC., is analogous to soybean in yield and nutritional quality, proving a valuable alternative to soybean in tropical regions of the world. The presence of anti-nutritional factors and high costs associated with indeterminate plant habit have been major concerns in this crop. But occurrence of good genetic variability in germplasm collections offers precious resources for winged bean breeding. However, lack of germplasm characterization is hindering such efforts. From a genomic standpoint, winged bean has been little studied despite rapid advancement in legume genomics in the last decade. Exploiting modern genomics/breeding approaches for genetic resource characterization and the breeding of early maturing, high yielding, determinate varieties which are disease resistant and free of anti-nutritional factors along with developing consumer friendly value-added products of local significance are great challenges and opportunities in the future that would boost cultivation of winged bean in the tropics. We review past efforts and future prospects towards winged bean improvement.

Response surface methodology applied to the study of the microwave-assisted synthesis of quaternized chitosan.

PubMed

dos Santos, Danilo Martins; Bukzem, Andrea de Lacerda; Campana-Filho, Sérgio Paulo

2016-03-15

A quaternized derivative of chitosan, namely N-(2-hydroxy)-propyl-3-trimethylammonium chitosan chloride (QCh), was synthesized by reacting glycidyltrimethylammonium chloride (GTMAC) and chitosan (Ch) in acid medium under microwave irradiation. Full-factorial 2(3) central composite design and response surface methodology (RSM) were applied to evaluate the effects of molar ratio GTMAC/Ch, reaction time and temperature on the reaction yield, average degree of quaternization (DQ) and intrinsic viscosity ([η]) of QCh. The molar ratio GTMAC/Ch was the most important factor affecting the response variables and RSM results showed that highly substituted QCh (DQ = 71.1%) was produced at high yield (164%) when the reaction was carried out for 30min. at 85°C by using molar ratio GTMAC/Ch 6/1. Results showed that microwave-assisted synthesis is much faster (≤30min.) as compared to conventional reaction procedures (>4h) carried out in similar conditions except for the use of microwave irradiation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impact of industrial hammer mill rotor speed on extraction efficiency and quality of extra virgin olive oil.

PubMed

Polari, Juan J; Garcí-Aguirre, David; Olmo-García, Lucía; Carrasco-Pancorbo, Alegría; Wang, Selina C

2018-03-01

Crushing is a key step during olive oil extraction. Among commercial crushers, the hammer mill is the most widely used due to its robustness and high throughput. In the present work, the impact of hammer mill rotor speed on extraction yield and overall quality of super-high-density Arbosana olive oils were assessed in an industrial facility. Our results show that increasing the rotor speed from 2400rpm to 3600rpm led to a rise in oil yield of 1.2%, while conserving quality parameters. Sensory analysis showed more pungency with increased rotation speed, while others attributes were unaffected. Volatile compounds showed little variation with the differences in crusher speed; however, total phenols content, two relevant secoiridoids, and triterpenoids levels increased with rotor speed. Hammer mill rotor speed is a processing variable that can be tuned to increase the extraction efficiency and modulate the chemical composition of extra virgin olive oil. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fluctuations in coral health of four common inshore reef corals in response to seasonal and anthropogenic changes in water quality.

PubMed

Browne, Nicola K; Tay, Jason K L; Low, Jeffrey; Larson, Ole; Todd, Peter A

2015-04-01

Environmental drivers of coral condition (maximum quantum yield, symbiont density, chlorophyll a content and coral skeletal growth rates) were assessed in the equatorial inshore coastal waters of Singapore, where the amplitude of seasonal variation is low, but anthropogenic influence is relatively high. Water quality variables (sediments, nutrients, trace metals, temperature, light) explained between 52 and 83% of the variation in coral condition, with sediments and light availability as key drivers of foliose corals (Merulina ampliata, Pachyseris speciosa), and temperature exerting a greater influence on a branching coral (Pocillopora damicornis). Seasonal reductions in water quality led to high chlorophyll a concentrations and maximum quantum yields in corals, but low growth rates. These marginal coral communities are potentially vulnerable to climate change, hence, we propose water quality thresholds for coral growth with the aim of mitigating both local and global environmental impacts. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gravitational lensing of active galactic nuclei.

PubMed Central

Hewitt, J N

1995-01-01

Most of the known cases of strong gravitational lensing involve multiple imaging of an active galactic nucleus. The properties of lensed active galactic nuclei make them promising systems for astrophysical applications of gravitational lensing; in particular, they show structure on scales of milliseconds of arc to tens of seconds of arc, they are variable, and they are polarized. More than 20 cases of strong gravitational lenses are now known, and about half of them are radio sources. High-resolution radio imaging is making possible the development of well-constrained lens models. Variability studies at radio and optical wavelengths are beginning to yield results of astrophysical interest, such as an independent measure of the distance scale and limits on source sizes. PMID:11607613

Cryobiopsy: should this be used in place of endobronchial forceps biopsies?

PubMed

Rubio, Edmundo R; le, Susanti R; Whatley, Ralph E; Boyd, Michael B

2013-01-01

Forceps biopsies of airway lesions have variable yields. The yield increases when combining techniques in order to collect more material. With the use of cryotherapy probes (cryobiopsy) larger specimens can be obtained, resulting in an increase in the diagnostic yield. However, the utility and safety of cryobiopsy with all types of lesions, including flat mucosal lesions, is not established. Demonstrate the utility/safety of cryobiopsy versus forceps biopsy to sample exophytic and flat airway lesions. Teaching hospital-based retrospective analysis. Retrospective analysis of patients undergoing cryobiopsies (singly or combined with forceps biopsies) from August 2008 through August 2010. Statistical Analysis. Wilcoxon signed-rank test. The comparative analysis of 22 patients with cryobiopsy and forceps biopsy of the same lesion showed the mean volumes of material obtained with cryobiopsy were significantly larger (0.696 cm(3) versus 0.0373 cm(3), P = 0.0014). Of 31 cryobiopsies performed, one had minor bleeding. Cryopbiopsy allowed sampling of exophytic and flat lesions that were located centrally or distally. Cryobiopsies were shown to be safe, free of artifact, and provided a diagnostic yield of 96.77%. Cryobiopsy allows safe sampling of exophytic and flat airway lesions, with larger specimens, excellent tissue preservation and high diagnostic accuracy.

Performance of some Ethiopian fenugreek (Trigonella foenum-graecum L.) germplasm collections as compared with the commercial variety Challa.

PubMed

Fikreselassie, Million

2012-05-01

Systematic breeding efforts on fenugreek have so far been neglected in Ethiopia. For this, 143 random samples of fenugreek accessions along with a commercial variety were used in this study to evaluate the potential of the land races. The field experiment was conducted at Haramaya University research station during 2011 main cropping season. Treatments were arranged in a 12x12 simple lattice design. The highest biomass and seed yielding accessions were generally concentrated more in the categories of yellow and green seed colors. When compared with the commercial variety, above 27% of the tested accessions performed significantly better in terms of seed yield indicating that significant yield gains could be secured by simple selection. However, further evaluation over wider environments is necessary to arrive at conclusive points for such quantitative traits. Green and yellow seeded accessions are widely distributed over all the country and over half of the accessions (63%) had green seed color. High seed yield bearing accessions were those collected from northwest and central part of Ethiopia, while accessions collected from eastern and northwestern Ethiopia were strikingly bold seed size. This variability would provide a basis for improving the crop in breeding program.

Concentrations, loads, and yields of select constituents from major tributaries of the Mississippi and Missouri Rivers in Iowa, water years 2004-2008

USGS Publications Warehouse

Garrett, Jessica D.

2012-01-01

Excess nutrients, suspended-sediment loads, and the presence of pesticides in Iowa rivers can have deleterious effects on water quality in State streams, downstream major rivers, and the Gulf of Mexico. Fertilizer and pesticides are used to support crop growth on Iowa's highly productive agricultural landscape and for household and commercial lawns and gardens. Water quality was characterized near the mouths of 10 major Iowa tributaries to the Mississippi and Missouri Rivers from March 2004 through September 2008. Stream loads were calculated for select ions, nutrients, and sediment using approximately monthly samples, and samples from storm and snowmelt events. Water-quality samples collected using standard streamflow-integrated protocols were analyzed for major ions, nutrients, carbon, pesticides, and suspended sediment. Statistical data summaries of sample data used parametric and nonparametric techniques to address potential bias related to censored data and multiple levels of censoring of data below analytical detection limits. Constituent stream loads were computed using standard pre-defined models in S-LOADEST that include streamflow and time terms plus additional terms for streamflow variability and streamflow anomalies. Streamflow variability terms describe the difference in streamflow from recent average conditions, whereas streamflow anomaly terms account for deviations from average conditions from long- to short-term sequentially. Streamflow variability or anomaly terms were included in 44 of 80 site/constituent individual models, demonstrating the usefulness of these terms in increasing accuracy of the load estimates. Constituent concentrations in Iowa streams exhibit streamflow, seasonal, and spatial patterns related to the landform and climate gradients across the studied basins. The streamflow-concentration relation indicated dilution for ions such as chloride and sulfate. Other constituent concentrations, such as dissolved organic carbon and suspended sediment, increased with streamflow. Nitrogen concentrations (total nitrogen and nitrate plus nitrite) increased with low and moderate streamflows, but decreased with high streamflows. Seasonal patterns observed in constituent concentrations were affected by streamflow, algae blooms, and pesticide application. The various landform regions produced different water-quality responses across the study basins; for example, total phosphorus, suspended sediment, and turbidity were greatest from the steep, loess-dominated southwestern Iowa basins. Nutrient concentrations, though not regulated for drinking water at the study sites, were high compared to drinking-water limits and criteria for protection of aquatic life proposed for other Midwestern states (Iowa criteria for aquatic life have not been proposed). Nitrate plus nitrite concentrations exceeded the drinking-water limit [10 milligrams per liter (mg/L)] in 11 percent of all samples at the 10 sites, and exceeded Minnesota's proposed aquatic life criteria (4.9 mg/L) in 68 percent of samples. The Wisconsin standard for total phosphorus (0.1 mg/L) was exceeded in 92 percent of samples. Ammonia standards, current during sample collection and at publication of this report, for protection of aquatic life were met for all samples, but draft criteria proposed in 2009 to protect more sensitive species like mussels, were exceeded at three sites. Loads and yields also differed among sites and years. The Big Sioux, Little Sioux, and Des Moines Rivers produced the greatest sulfate yields. Mississippi River tributaries had greater chloride yields than Missouri River tributaries. The Big Sioux River also had the lowest silica yields and total nitrogen and nitrate yields, whereas nitrogen yields were greater in the northeastern rivers. The Boyer and Nishnabotna River total phosphorus yields were the greatest in the study. The Boyer River orthophosphate yields were greatest except in 2008, when the Maquoketa River produced the greatest yield. Rivers in southwestern Iowa's Western Loess Hills and Steeply Rolling Loess Prairie ecoregions had the greatest suspended-sediment yields, whereas the smallest yields were in the Big Sioux and Wapsipinicon Rivers. In the 10 Iowa rivers studied, combined annual total nitrogen stream transport ranged from 3.68 to 9.95 tons per square mile per year, and total phosphorus transport ranged from 0.138 to 0.570 tons per square mile per year. Six-month loads relative to fertilizer use ranged from 8 to 56 percent for nitrogen, and 1.0 to 11.1 percent for phosphorus. The smallest loads relative to fertilizer use for both nitrogen and phosphorus occurred in July-December of dry years, and the largest nitrogen and phosphorus loads relative to use were in wet years from January-June.