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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

land-use patterns↗
NASA NTRS2002

Light, plants, and power for life support on Mars

Regardless of how well other growing conditions are optimized, crop yields will be limited by the available light up to saturation irradiances. Considering the various factors of clouds on Earth, dust storms on Mars, thickness of atmosphere, and relative orbits, there is roughly 2/3 as much light averaged annually on Mars as on Earth. On Mars, however, crops must be grown under controlled conditions (greenhouse or growth rooms). Because there presently exists no material that can safely be pressurized, insulated, and resist hazards of puncture and deterioration to create life support systems on Mars while allowing for sufficient natural light penetration as well, artificial light will have to be supplied. If high irradiance is provided for long daily photoperiods, the growing area can be reduced by a factor of 3-4 relative to the most efficient irradiance for cereal crops such as wheat and rice, and perhaps for some other crops. Only a small penalty in required energy will be incurred by such optimization. To obtain maximum yields, crops must be chosen that can utilize high irradiances. Factors that increase ability to convert high light into increased productivity include canopy architecture, high-yield index (harvest index), and long-day or day-neutral flowering and tuberization responses. Prototype life support systems such as Bios-3 in Siberia or the Mars on Earth Project need to be undertaken to test and further refine systems and parameters.

Non-NASA Center↗
NASA NTRS2015

Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information

Wheat is themost important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop typemasks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel (area within the CMG pixel occupied by wheat), and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: the Unites States (US), Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest), while conserving an accuracy of 10% in the production forecast.

Production↗
NASA NTRS2016

Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

MODIS↗
NASA NTRS2024

Improved alternate wetting and drying irrigation increases global water productivity

Rice is the staple food for half of the world’s population but also has the largest water footprint among cereal crops. Alternate wetting and drying (AWD) is a promising irrigation strategy to improve paddy rice’s water productivity—defined as the ratio of rice yield to irrigation water use. However, its global adoption has been limited due to concerns about potential yield losses and uncertainties regarding water productivity improvements. Here, using 1,187 paired field observations of rice yield under AWD and continuous flooding to quantify AWD effects (ΔY), we found that variation in ΔY is predominantly explained by the lowest soil water potential during the drying period. We estimate that implementing a soil water potential-based AWD scheme could increase water productivity across 37% of the global irrigated rice area, particularly in India, Bangladesh and central China. These findings highlight the potential of AWD to promote more sustainable rice production systems and provide a pathway toward the sustainable intensification of rice cultivation worldwide.

Irrigation↗
NASA NTRS2015

Integrated Assessment of Climate Change Impacts on Maize Farms and Farm Household Incomes in South India: A Case Study from Tamil Nadu: Chapter - 9

South India is characterized by a wide variety of landscapes, soils and climatic zones. It is comprised of tropical, semi-arid, humid-moist, and high-altitude environments, which support a diversity of agricultural systems. Our study focused on the state of Tamil Nadu, which is characterized by a generally tropical climate, and receive rainfall during both the southwest monsoon season (SWM, June to September) and the northeast monsoon (NEM, September to December). Agriculture continues to be an important sector in the state economy, as more than 56 of the people depend on agriculture and allied sectors for their livelihood. Analysis of land-use patterns in Tamil Nadu reveals that in the past decade there has been a reduction in net sown area and current fallow, while the share of cultivable wastelands has increased. The area under cereals, pulses, and oilseeds had marginally declined, although area under commercial crops like turmeric, sugar-cane, banana, fruits, and vegetables has shown an increasing trend. The production performance of major crops like cereals, pulses, and oilseeds has not shown any significant increase. Demand and supply gap of important crops in Tamil Nadu for the year 2010 indicates that the state is lagging far behind in the production of various crops.

agriculture↗
NASA NTRS1990

Cloning crops in a CELSS via tissue culture: Prospects and problems

Micropropagation is currently used to clone fruits, nuts, and vegetables and involves controlling the outgrowth in vitro of basal, axillary, or adventitious buds. Following clonal multiplication, shoots are divided and rooted. This process has greatly reduced space and energy requirements in greenhouses and field nurseries and has increased multiplication rates by greater than 20 fold for some vegetatively propagated crops and breeding lines. Cereal and legume crops can also be cloned by tissue culture through somatic embryogenesis. Somatic embryos can be used to produce 'synthetic seed', which can tolerate desiccation and germinate upon rehydration. Synthetic seed of hybrid wheat, rice, soybean and other crops could be produced in a controlled ecological life support system. Thus, yield advantages of hybreds over inbreds (10 to 20 percent) could be exploited without having to provide additional facilities and energy for parental-line and hybrid seed nurseries.

Carman, John G.↗
NASA NTRS2018

Global Patterns of Crop Yield Stability Under Additional Nutrient and Water Inputs

Agricultural production must increase to feed a growing and wealthier population, as well as to satisfy increasing demands for biomaterials and biomass-based energy. At the same time, deforestation and land-use change need to be minimized in order to preserve biodiversity and maintain carbon stores in vegetation and soils. Consequently, agricultural land use needs to be intensified in order to increase food production per unit area of land. Here we use simulations of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 to assess implications of input-driven intensification (water, nutrients) on crop yield and yield stability, which is an important aspect in food security. We find region- and crop-specific responses for the simulated period 1980+/-2009 with broadly increasing yield variability under additional nitrogen inputs and stabilizing yields under additional water inputs (irrigation), reflecting current patterns of water and nutrient limitation. The different models of the GGCMI ensemble show similar response patterns, but model differences warrant further research on management assumptions, such as variety selection and soil management, and inputs as well as on model implementation of different soil and plant processes, such as on heat stress, and parameters. Higher variability in crop productivity under higher fertilizer input will require adequate buffer mechanisms in trade and distribution/storage networks to avoid food price volatility.

Maize↗
NASA NTRS1972

The usefullness of ERTS-1 and supporting aircraft data for monitoring plant development in rangeland environments

The author has identified the following significant results. Preliminary analysis of ERTS-1 MSS imagery of annual and perennial rangeland in California yields the following observations: (1) Sufficient geomorphological detail can be resolved to differentiate upland and bottomland range sites in the foothill range areas. (2) Dry and green meadowland can be differentiated on MSS band 5. (3) Color composites prepared by NASA-Goddard were useful for locating perennial rangeland with varying amounts of herbaceous ground cover. (4) The ERTS-1 images received and interpreted cover nearly 50% of the state of California and show nearly two-thirds of the annual grassland type. (5) Satellite imagery obtained during the late summer season should be optimum for differentiating grassland from brushland and forested land. (6) The ERTS-1 imagery clearly shows areas which at one time were part of the annual grassland but which are now used for dry land farming (cropping of cereal grains). Similarly, the imagery show areas which have been converted from brushland to grassland.

Carneggie, D. M.↗
NASA NTRS1985

Priorities for worldwide remote sensing of agricultural crops

The world's crops are ranked according to total harvested area, and comparisons are made among major world regions of differences in crops produced. The eight leading world crops are wheat, rice, corn, barley, millet, soybeans, sorghum, and cotton. Regionally, millet and sorghum are most important in Africa, wheat is the most extensively grown crop in north-central America, Europe, USSR, and Oceania; corn is the dominant crop in South America; and rice is the most extensively grown crop in Asia. Agriculture in the USA is considered in more detail to show the national economic impact of variations in value per hectare among crops. On the world scene, the cereals are the most important crops, but locally, such crops as tobacco can play a dominant role.

Bowker, D. E.↗
NASA NTRS1994

Bioregenerative life-support systems

Long-duration future habitation of space involving great distances from Earth and/or large crew sizes (eg, lunar outpost, Mars base) will require a controlled ecological life-support system (CELSS) to simultaneously revitalize atmosphere (liberate oxygen and fix carbon dioxide), purify water (via transpiration), and generate human food (for a vegetarian diet). Photosynthetic higher plants and algae will provide the essential functions of biomass productivity in a CELSS, and a combination of physicochemical and bioregenerative processes will be used to regenerate renewable resources from waste materials. Crop selection criteria for a CELSS include nutritional use characteristics as well as horticultural characteristics. Cereals, legumes, and oilseed crops are used to provide the major macronutrients for the CELSS diet. A National Aeronautics and Space Administration (NASA) Specialized Center of Research and Training (NSCORT) was established at Purdue University to establish proof of the concept of the sustainability of a CELSS. The Biosphere 2 project in Arizona is providing a model for predicted and unpredicted situations that arise as a result of closure in a complex natural ecosystem.

NASA Discipline Life Support Systems↗
NASA NTRS2003

Sensory characterization of a ready-to-eat sweetpotato breakfast cereal by descriptive analysis

The sweetpotato [Ipomoea batatas (L.) Lam], an important industry in the United States, has been selected as a candidate crop to be grown on future long-duration space missions by NASA. Raw sweetpotato roots were processed into flour, which was used to formulate ready-to-eat breakfast cereal (RTEBC). Twelve trained panelists evaluated the sensory attributes of the extruded RTEBC using descriptive analysis. The samples were significantly different (P<0.05) for all attributes. Twelve perceived sensory attributes, which could be used to differentiate the appearance, texture, and flavor of sweetpotato RTEBC, were described. The data could be used to optimize the RTEBC and for designing studies to test its consumer acceptance.

NASA Discipline Life Support Systems↗
NASA NTRS2016

Monitoring Interannual Variation in Global Crop Yield Using Long-Term AVHRR and MODIS Observations

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05deg (approx.5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Crop phenology↗
NASA NTRS2021

Severity of Drought and Heatwave Crop Losses Tripled Over the Last Five Decades in Europe

Extreme weather disasters (EWDs) can jeopardize domestic food supply and disrupt commodity markets. However, historical impacts on European crop production associated with droughts, heatwaves, floods, and cold waves are not well understood—especially in view of potential adverse trends in the severity of impacts due to climate change. Here, we combine observational agricultural data (FAOSTAT) with an extreme weather disaster database (EM-DAT) between 1961 and 2018 to evaluate European crop production responses to EWD. Using a compositing approach (superposed epoch analysis), we show that historical droughts and heatwaves reduced European cereal yields on average by 9% and 7.3%, respectively, associated with a wide range of responses (inter-quartile range +2% to −23%; +2% to −17%). Non-cereal yields declined by 3.8% and 3.1% during the same set of events. Cold waves led to cereal and non-cereal yield declines by 1.3% and 2.6%, while flood impacts were marginal and not statistically significant. Production losses are largely driven by yield declines, with no significant changes in harvested area. While all four event frequencies significantly increased over time, the severity of heatwave and drought impacts on crop production roughly tripled over the last 50 years, from −2.2% (1964–1990) to −7.3% (1991–2015). Drought-related cereal production losses are shown to intensify by more than 3% yr−1. Both the trend in frequency and severity can possibly be explained by changes in the vulnerability of the exposed system and underlying climate change impacts.

Extreme weather disasters↗
NASA NTRS1981

Use of remote sensing for land use policy formulation

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Source record↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗