Search NASA⌕ Search

SEARCH · Search NASA

Results for “Crop yield”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Using LANDSAT to provide potato production estimates to Columbia Basin farmers and processors

The estimation of potato yields in the Columbia basin is described. The fundamental objective is to provide CROPIX with working models of potato production. A two-pronged approach was used to yield estimation: (1) using simulation models, and (2) using purely empirical models. The simulation modeling approach used satellite observations to determine certain key dates in the development of the crop for each field identified as potatoes. In particular, these include planting dates, emergence dates, and harvest dates. These critical dates are fed into simulation models of crop growth and development to derive yield forecasts. Purely empirical models were developed to relate yield to some spectrally derived measure of crop development. Two empirical approaches are presented: one relates tuber yield to estimates of cumulative intercepted solar radiation, the other relates tuber yield to the integral under GVI (Global Vegetation Index) curve.

Source record↗
NASA NTRS2016

Safety and Certification Considerations for Expanding the Use of UAS in Precision Agriculture

The agricultural community is actively engaged in adopting new technologies such as unmanned aircraft systems (UAS) to help assess the condition of crops and develop appropriate treatment plans. In the United States, agricultural use of UAS has largely been limited to small UAS, generally weighing less than 55 lb and operating within the line of sight of a remote pilot. A variety of small UAS are being used to monitor and map crops, while only a few are being used to apply agricultural inputs based on the results of remote sensing. Larger UAS with substantial payload capacity could provide an option for site-specific application of agricultural inputs in a timely fashion, without substantive damage to the crops or soil. A recent study by the National Aeronautics and Space Administration (NASA) investigated certification requirements needed to enable the use of larger UAS to support the precision agriculture industry. This paper provides a brief introduction to aircraft certification relevant to agricultural UAS, an overview of and results from the NASA study, and a discussion of how those results might affect the precision agriculture community. Specific topics of interest include business model considerations for unmanned aerial applicators and a comparison with current means of variable rate application. The intent of the paper is to inform the precision agriculture community of evolving technologies that will enable broader use of unmanned vehicles to reduce costs, reduce environmental impacts, and enhance yield, especially for specialty crops that are grown on small to medium size farms.

Hayhurst, Kelly J.↗
NASA NTRS1973

Results of the 1971 Corn Blight Watch experiment.

The objective of the experiment was to evaluate the use of advanced remote sensing techniques to detect the development and spread of southern corn leaf blight during the growing season across the Corn Belt region. The sampling plan involved the selection of the study area, the determination of the flightline, and the determination of a field sample design. Aspects of data acquisition are discussed, giving attention to ground data collection and aerial data collection. Details of data flow are considered along with data analysis procedures and corn blight records. The experiment results are examined, taking into account photointerpretation results, the machine analysis of multispectral scanner data results, the influence of blight on yields, and questions of crop identification.

Macdonald, R. B.↗
NASA NTRS1975

Policy issues and data communications for NASA earth observation missions until 1985

The series of LANDSAT sensors with the highest potential data rates of the missions were examined. An examination of LANDSAT imagery uses shows that relatively few require transmission of the full resolution data on a repetitive quasi real time basis. Accuracy of global crop size forecasting can possibly be improved through information derived from LANDSAT imagery. A current forecasting experiment uses the imagery for crop area estimation only, yield being derived from other data sources.

Corte, A. B.↗
NASA NTRS1978

Crop water-stress assessment using an airborne thermal scanner

An airborne thermal scanner was used to measure the temperature of a wheat crop canopy in Phoenix, Arizona. The results indicate that canopy temperatures acquired about an hour and a half past solar noon were well correlated with presunrise plant water tension, a parameter directly related to plant growth and development. Pseudo-colored thermal images reading directly in stress degree days, a unit indicative of crop irrigation needs and yield potential, were produced. The aircraft data showed significant within-field canopy temperature variability, indicating the superiority of the synoptic view provided by aircraft over localized ground measurements. The standard deviation between airborne and ground-acquired canopy temperatures was 2 C or less.

Millard, J. P.↗
NASA NTRS1978

Proceedings of Plenary Session: The LACIE Symposium

A technology assessment of the LACIE data processing and information systems was discussed during the Large Area Crop Inventory Experiment Symposium. Crop inventories of wheat yield in the United States as well as several other nations (such as the U.S.S.R., Canada, etc.) were discussed, along with the methodology involved in acquiring this data.

Source record↗
NASA NTRSDate not supplied

Sustained Veggie: A Continuous Food Production Comparison

The International Space Station’s Veggie system intermittently supplies the crew with fresh produce. To assess the potential for continuous crop production in Veggie and develop a baseline for future space crop production systems, a 120-day study was conducted to determine methodology for inputs, optimal yield, and crew involvement. ‘Amara’ mustard and ‘Red Russian’ kale were grown as initial crops, followed by ‘Extra Dwarf’ pak choi and shungiku as final crops. Previous grow-outs in Veggie have included harvests at 28-35days after initiation. In this study, a 56-day grow-out with multiple harvests from the same plants was compared to the conventional, single harvest Veggie schedule. Unlike previous Veggie studies which grew all plants simultaneously, this test staggered initiation and harvest, aiming for consistent and increased production. Plant pillows were initiated in pairs weekly and positioned to reduce shading. Completed pillows were immediately replaced with fresh ones. The multi-harvest scheme used fewer pillows, totaling 46% less pillow mass than the single harvest method. Scaled to 56-day increments, yield varied by crop and harvest scheme. ‘Red Russian’ kale yielded similarly across harvest schemes. In the multiple-harvest schedule, ‘Amara’ mustard and shungiku yielded 23% to 25% higher, respectively, while ‘Extra Dwarf’ pak choi had43% lower yield. Microbial analysis of the plants indicated no culturable human pathogens. Microbial load of a given plant appears to depend more on system age than plant age. Across harvest methods, aerobic plate counts from final crops were higher than those of initial crops. This project also considered the complexity of crew involvement in a continuous production scenario. New crew procedures that periodically remove plant material from the Veggie root mat are needed under continuous production to prevent potential pathogens and unpleasant odors. This study supports future space crop production scenarios and was funded by NASA’s Human Research Program.

Jess M Bunchek↗
NASA NTRS2021

Extreme Lows of Wheat Production in Brazil

Wheat production in Brazil is insufficient to meet domestic demand and falls drastically in response to adverse climate events. Multiple, agro-climate-specific regression models, quantifying regional production variability, were combined to estimate national production based on past climate, cropping area, trend-corrected yield, and national commodity prices. Projections with five CMIP6 climate change models suggest extremes of low wheat production historically occurring once every 20 years would become up to 90% frequent by the end of this century, depending on representative concentration pathway, magnified by wheat and in some cases by maize price fluctuations. Similar impacts can be expected for other crops and in other countries. This drastic increase in frequency in extreme low crop production with climate change will threaten Brazil's and many other countries progress toward food security and abolishing hunger.

Brazil↗
NASA NTRS1980

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Cate, R. B.↗
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 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 NTRS2015

Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario.

climate change impact↗
NASA NTRSDate not supplied

Exploring Sustained Food Production in the Veggie Vegetable Production System

Since 2014, the Veggie vegetable production system on the International Space Station has intermittently supplied astronaut crews with fresh produce. To assess the potential for continuous crop production in Veggie and develop a baseline for future space crop production systems, a 120-day study was conducted to determine methodology for inputs, optimal yield, food safety standards, and crew involvement. ‘Amara’ mustard and ‘Red Russian’ kale were grown as initial crops, followed by ‘Extra Dwarf’ pakchoi and shungiku as final crops. Previous grow-outs in Veggie have included harvests at 28-35 days after initiation. In this study, a 56-day grow-out with multiple harvests from the same plants was compared to the conventional, single harvest Veggie schedule. Unlike previous Veggie studies which grew all plants simultaneously, this test staggered initiation and harvest, aiming for consistent and increased production. Plant pillows were initiated in pairs weekly and positioned to reduce shading. Completed pillows were immediately replaced with fresh ones. The multi-harvest scheme used fewer pillows, totaling 46% less pillow mass than the single harvest method. Yield varied by crop and harvest scheme, when compared as fresh edible biomass production across 56-day time increments. ‘Red Russian’ kale yielded similarly across harvest schemes. In the multiple-harvest schedule, ‘Amara’ mustard and shungiku yielded 23% to 25% higher, respectively, while ‘Extra Dwarf’ pakchoi had 43% lower yield. Microbial analysis of the plants indicated no culturable human pathogens. Microbial load of a given plant appeared to depend more on system age than plant age; across harvest methods, aerobic plate counts from final crops were higher than those of initial crops. This project also considered the complexity of crew involvement in a continuous production scenario. New crew procedures that periodically remove plant material from the Veggie root mat would be needed under continuous production to prevent potential pathogens and unpleasant odors. This study supports future space crop production scenarios and was funded by NASA’s Human Research Program.

Jess M Bunchek↗
NASA NTRS2022

Economic incentives modify agricultural impacts of nuclear war

A nuclear war using less than 1% of the current global nuclear arsenal, which would inject 5 Tg of soot into the stratosphere, could produce climate change unprecedented in recorded human history and significant impacts on agricultural productivity and the economy. These effects would be most severe for the first five years after the nuclear war and may last for more than a decade. This paper calculates how food availability would change by employing the Environmental Impact and Sustainability Applied General Equilibrium model. Under a robust world trading system, global food availability would drop by a few percentage points. If the war would destabilize trade, it would magnify by several times the negative ramifications of land productivity shocks on food availability. If exporting countries redirect production to domestic consumption at the expense of importing countries, it would lead to the destabilization of international trade. The analysis suggests that economic models aiming to inform policymakers require both economic behavior analysis and biophysical drivers. Policy lessons derived from a crop model can be significantly nuanced when coupled with economic feedback derived from economic models. Through the impact on yield, farmers could shift production among crops and reallocate land use to maximize profits, showing the importance of general equilibrium effects such as product and input substitution and international trade. Although the global impact on corn and soybean production would be significant when just considering crop production, it could be considerably smaller under the economic model. However, this would be at the expense of other sectors, including livestock. In addition, the costs borne from disruptions to climate would vary significantly across regions, with significant adverse effects in high latitude regions. The severity of the shocks in the high-latitude areas would marginalize the farmers' product and input substitution ability.

Nuclear war↗
NASA NTRS1977

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.

Nalepka, R. F.↗
NASA NTRS1995

Photoperiod shift effects on yield characteristics of rice

Edible yield must be maximized for each crop species selected for inclusion in the Controlled Ecological Life-Support System (CELSS) proposed by NASA to support long-term manned space missions. In a greenhouse study aimed at increasing biomass partitioning to rice (Oryza sativa L.) grain, plants of the high yielding semi-dwarf rice cultivar Ai-Nan-Tsao were started in pots under 8-h photoperiods at a density of 212 plants m-2. After different periods of time under 8-h photoperiods, pots were switched to continuous light for the remainder of the cropping cycle. Continuous light did not delay time to first panicle emergence (60 d) or time to harvest (83 d). There was a positive correlation between the length of continuous light treatments and nongrain biomass. Grain yield (1.6 +/- 0.2 g plant-1) did not increase in continuous light. Yield-efficiency rate (grain weight per length of cropping cycle, canopy volume, and weight of nongrain shoot biomass) was used to compare treatments. Small Ai-Nan-Tsao rice canopies grown under 8-h photoperiods were more efficient producers of grain than canopies grown under continuous light for a portion of the rice cropping cycle.

Non-NASA Center↗
NASA NTRS2023

Future Climate Change Impacts on U.S. Agricultural Yields, Production, and Market

This study provides estimates of climate change impacts on U.S. agricultural yields and the agricultural economy through the end of the 21st century, utilizing multiple climate scenarios. Results from a process-based crop model project future increases in wheat, grassland, and soybean yield due to climate change and atmospheric CO2 change; corn and sorghum show more muted responses. Results using yields from econometric models show less positive results. Both the econometric and process-based models tend to show more positive yields by the end of the century than several other similar studies. Using the process-based model to provide future yield estimates to an integrated agricultural sector model, the welfare gain is roughly $16B/year (2019 USD) for domestic producers and $6.2B/year for international trade, but domestic consumers lose $10.6B/year, resulting in a total welfare gain of $11.7B/year. When yield projections for major crops are drawn instead from econometric models, total welfare losses of more than $28B/year arise. Simulations using the process-based model as input to the agricultural sector model show large future production increases for soybean, wheat, and sorghum and large price reductions for corn and wheat. The most important factors are those about economic growth, flooding, international trade, and the type of yield model used. Somewhat less, but not insignificant factors include adaptation, livestock productivity, and damages from surface ozone, waterlogging, and pests and diseases.

Agricultural sector↗
NASA NTRS2008

The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

Cacas, Joseph↗