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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Response of winter and spring wheat grain yields to meteorological variation

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.

Feyerherm, A. M.↗
NASA NTRS1997

Photomorphogenesis, photosynthesis, and seed yield of wheat plants grown under red light-emitting diodes (LEDs) with and without supplemental blue lighting

Red light-emitting diodes (LEDs) are a potential light source for growing plants in spaceflight systems because of their safety, small mass and volume, wavelength specificity, and longevity. Despite these attractive features, red LEDs must satisfy requirements for plant photosynthesis and photomorphogenesis for successful growth and seed yield. To determine the influence of gallium aluminium arsenide (GaAlAs) red LEDs on wheat photomorphogenesis, photosynthesis, and seed yield, wheat (Triticum aestivum L., cv. 'USU-Super Dwarf') plants were grown under red LEDs and compared to plants grown under daylight fluorescent (white) lamps and red LEDs supplemented with either 1% or 10% blue light from blue fluorescent (BF) lamps. Compared to white light-grown plants, wheat grown under red LEDs alone demonstrated less main culm development during vegetative growth through preanthesis, while showing a longer flag leaf at 40 DAP and greater main culm length at final harvest (70 DAP). As supplemental BF light was increased with red LEDs, shoot dry matter and net leaf photosynthesis rate increased. At final harvest, wheat grown under red LEDs alone displayed fewer subtillers and a lower seed yield compared to plants grown under white light. Wheat grown under red LEDs+10% BF light had comparable shoot dry matter accumulation and seed yield relative to wheat grown under white light. These results indicate that wheat can complete its life cycle under red LEDs alone, but larger plants and greater amounts of seed are produced in the presence of red LEDs supplemented with a quantity of blue light.

NASA Discipline Life Support Systems↗
DOE OSTI2022

Site-specific field management adaptation is key to feeding the world in the 21st century

Rapid climate change and growing population threaten global food security across the globe. Several studies have proposed early planting, increased irrigation, and increased fertilizer applications as climate adaptation strategies, yet none have considered combined and site-specific field management strategies as a comprehensive solution. Here, we analyzed non-irrigated wheat yield responses to climate change and field management adaptation using a mechanistic crop model evaluated against observed global non-irrigated wheat-yield over 3-year intervals spanning 13 years at 3749 sites (RMSE = 36 gC m -2 ). Early planting with later-maturing varieties provided the most benefit to future yields among the proposed field management adaptation strategies. Improved water use efficiency from increased CO 2 led to relatively low benefits of additional irrigation. Here we estimated that spatially heterogeneous adaption strategies had the potential to improve global wheat yields by 91% by 2100 compared to the present day. The yield improvements from combined field adaptation strategies were larger than the sum of improvements from the individual strategies. These synergistic benefits were shown to result from complementary processes regulating nutrient and water uptake, physiological tolerance to heat stress, and internal carbon and nutrient cycling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Crop status evaluations and yield predictions

One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

Haun, J. R.↗
NASA NTRS2016

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.

upscaling↗
NASA NTRS1997

Very high CO2 reduces photosynthesis, dark respiration and yield in wheat

Although terrestrial CO2 concentrations, [CO2] are not expected to reach 1000 micromoles mol-1 for many decades, CO2 levels in closed systems such as growth chambers and glasshouses, can easily exceed this concentration. CO2 levels in life support systems in space can exceed 10000 micromoles mol-1 (1%). Here we studied the effect of six CO2 concentrations, from ambient up to 10000 micromoles mol-1, on seed yield, growth and gas exchange of two wheat cultivars (USU-Apogee and Veery-l0). Elevating [CO2] from 350 to 1000 micromoles mol-1 increased seed yield (by 33%), vegetative biomass (by 25%) and number of heads m-2 (by 34%) of wheat plants. Elevation of [CO2] from 1000 to 10000 micromoles mol-1 decreased seed yield (by 37%), harvest index (by 14%), mass per seed (by 9%) and number of seeds per head (by 29%). This very high [CO2] had a negligible, non-significant effect on vegetative biomass, number of heads m-2 and seed mass per head. A sharp decrease in seed yield, harvest index and seeds per head occurred by elevating [CO2] from 1000 to 2600 micromoles mol-1. Further elevation of [CO2] from 2600 to 10000 micromoles mol-1 caused a further but smaller decrease. The effect of CO2 on both wheat cultivars was similar for all growth parameters. Similarly there were no differences in the response to high [CO2] between wheat grown hydroponically in growth chambers under fluorescent lights and those grown in soilless media in a glasshouse under sunlight and high pressure sodium lamps. There was no correlation between high [CO2] and ethylene production by flag leaves or by wheat heads. Therefore, the reduction in seed set in wheat plants is not mediated by ethylene. The photosynthetic rate of whole wheat plants was 8% lower and dark respiration of the wheat heads 25% lower when exposed to 2600 micromoles mol-1 CO2 compared to ambient [CO2]. It is concluded that the reduction in the seed set can be mainly explained by the reduction in the dark respiration in wheat heads, when most of the respiration is functional and is needed for seed development.

NASA Discipline Life Support Systems↗
NASA NTRS1973

Kansas environmental and resource study: A Great Plains model

The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

Haralick, R. M.↗
NASA NTRS1989

Current and potential productivity of wheat for a controlled environment life support system

Several determinants of crop growth are analyzed to determine theoretical and potentially achievable productivity. These include: incident photosynthetic photon flux (PPF); percent absorption of the incident PPF by photo synthetic tissue; photosynthetic efficiency; respiratory carbon use efficiency; and harvest index. The effects of optimal environmental and cultural factors on each of these determinants are also investigated. Results indicate that an increase in the percentage of absorbed photons is responsible for most of the improvement in wheat yields in an optimal controlled environment. An integrated PPF of 150 mol/sq m per d has produced 60 g/sq m per d of grain. There is almost a linear increase in wheat yields with increasing PPF. At intermediate and equal integrated daily PPF levels, photoperiod had little effect on yield per day or energy efficiency. Decreasing temperature from 23 to 17 deg increased yield per day by 20 percent but increased the life cycle from 62 to 89 days.

Bugbee, B. G.↗
NASA NTRS1986

Studies on maximum yield of wheat for the controlled environments of space

The economic feasibility of using food-producing crop plants in a closed ecological Life-Support System (CELSS) will ultimately depend on the energy and area (or volume) required to provide the nutritional requirements for each person. Energy and area requirements are, to some extent, inversely related; that is, an increased energy input results in a decreased area requirement and vice versa. A major goal of the research effort was to determine the controlled-environment good-production efficiency of wheat per unit area, per unit time, and per unit energy input.

Bugbee, B. G.↗
NASA NTRS2018

Climate Change Impact and Adaptation for Wheat Protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

grain protein↗
NASA NTRS2023

The Extreme 2016 Wheat Failure in France

France suffered in 2016 the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.

Extreme weather↗
NASA NTRS2017

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

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models.

Wheat; Field Experimental Data; Heat Stress; Simul↗
NASA NTRS1988

Plant productivity in controlled environments

To assess the cost and area/volume requirements of a farm in a space station or Lunar or Martian base, a few laboratories in the United States, the Soviet Union, France, and Japan are studying optimum controlled environments for the production of selected crops. Temperature, light, photoperiod, CO2, humidity, the root-zone environment, and cultivars are the primary factors being manipulated to increase yields and harvest index. Our best wheat yields on a time basis (24 g m-2 day-1 of edible biomass) are five times good field yields and twice the world record. Similar yields have been obtained in other laboratories with potatoes and lettuce; soybeans are also promising. These figures suggest that approximately 30 m2 under continuous production could support an astronaut with sufficient protein and about 2800 kcal day-1. Scientists under Iosif Gitelzon in Krasnoyarsk, Siberia, have lived in a closed system for up to 5 months, producing 80% of their own food. Thirty square meters for crops were allotted to each of the two men taking part in the experiment. A functional controlled-environment life-support system (CELSS) will require the refined application of several disciplines: controlled-environment agriculture, food preparation, waste disposal, and control-systems technology, to list only the broadest categories. It has seemed intuitively evident that ways could be found to prepare food, regenerate plant nutrients from wastes, and even control and integrate several subsystems of a CELSS. But could sufficient food be produced in the limited areas and with the limited energy that might be available? Clearly, detailed studies of food production were necessary.

NASA Discipline Life Support Systems↗
NASA NTRS2023

Wheat Crop Traits Conferring High Yield Potential May Also Improve Yield Stability Under Climate Change

Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability.

Climate change↗
NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗
NASA NTRS1983

A meteorologically-driven yield reduction model for spring and winter wheat

A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.

Ravet, F. W.↗