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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Future impacts of ozone driven damages on agricultural systems

Current ozone (O 3 ) concentration levels entail significant damages in crop yields around the world. The reaction of the emitted precursors (mostly methane and nitrogen oxides) with solar radiation contribute to O 3 levels that exceed established thresholds for crop damage. This paper shows current and projected (up to 2080) relative yield losses (RYLs) driven by O 3 exposure for different crops and the associated economic damages applying dynamic crop production and prices that are calculated per region and period. We adjust future crop yields in the Global Change Assessment Model (GCAM) to reflect the RYLs and analyze the effects on agricultural markets. We find that the changes (generally reductions) in O 3 precursor emissions in a reference scenario would reduce the agricultural damages, compared to present, for most of the regions, with a few exceptions including India, where higher future O3 concentrations have large negative impacts on crop yields. The annual economic impact of O3 driven losses from 2010-2080 are, in billion US dollars at 2015 prices ($B), 5.0-6.0, 9.8-18.8, 6.7-10.6 and 10.4-12.5 for corn, soybeans, rice and wheat, respectively, with the large losses for wheat and soybeans driven by their comparatively high responses to O 3 . When O 3 effects are explicitly modelled as exogenous yield shocks in future periods, there is a direct impact in future agricultural markets. Therefore, the aggregated net present value (NPV) of crop production would be reduced around by $90.8B at a global level. However, these changes are not distributed evenly across regions, and the net present market value of the crops would increase by up to $118.2B (India) or decrease by up to $59.2B (China).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interactions Between Climate Mean and Variability Drive Future Agroecosystem Vulnerability

ABSTRACT Agriculture is crucial for global food supply and dominates the Earth's land surface. It is unknown, however, how slow but relentless changes in climate mean state, versus random extreme conditions arising from changing variability , will affect agroecosystems' carbon fluxes, energy fluxes, and crop production. We used an advanced weather generator to partition changes in mean climate state versus variability for both temperature and precipitation, producing forcing data to drive factorial‐design simulations of US Midwest agricultural regions in the Energy Exascale Earth System Model. We found that an increase in temperature mean lowers stored carbon, plant productivity, and crop yield, and tends to convert agroecosystems from a carbon sink to a source, as expected; it also can cause local to regional cooling in the earth system model through its effects on the Bowen Ratio. The combined effect of mean and variability changes on carbon fluxes and pools was nonlinear, that is, greater than each individual case. For instance, gross primary production reduces by 9%, 1%, and 13% due to change in mean temperature, change in temperature variability, and change in both temperature mean and variability, respectively. Overall, the scenario with change in both temperature and precipitation means leads to the largest reduction in carbon fluxes (−16% gross primary production), carbon pools (−35% vegetation carbon), and crop yields (−33% and −22% median reduction in yield for corn and soybean, respectively). By unambiguously parsing the effects of changing climate mean versus variability and quantifying their nonadditive impacts, this study lays a foundation for more robust understanding and prediction of agroecosystems' vulnerability to 21st‐century climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Managing Plant Microbiomes for Sustainable Biofuel Production

The development of environmentally sustainable, economical, and reliable sources of energy is one of the great challenges of the 21st century. Large-scale cultivation of cellulosic feedstock crops (henceforth, bioenergy crops) is considered one of the most promising renewable sources for liquid transportation fuels. However, the mandate to develop a viable cellulosic bioenergy industry is accompanied by an equally urgent mandate to deliver not only cheap reliable biomass but also ecosystem benefits, including efficient use of water, nitrogen, and phosphorous; restored soil health; and net negative carbon emissions. Thus, sustainable bioenergy crop production may involve new agricultural practices or feedstocks and should be reliable, cost effective, and minimal input, without displacing crops currently grown for food production on fertile land. In this editorial perspective for the Phytobiomes Journal Focus Issue on Phytobiomes of Bioenergy Crops and Agroecosystems, we consider the microbiomes associated with bioenergy crops, the effects beneficial microbes have on their hosts, and potential ecosystem impacts of these interactions. We also address outstanding questions, major advances, and emerging biotechnological strategies to design and manipulate bioenergy crop microbiomes. This approach could simultaneously increase crop yields and provide important ecosystem services for a sustainable energy future.

09 BIOMASS FUELS↗
DOE OSTI2025

Unveiling the drivers contributing to global wheat yield shocks through quantile regression

Sudden reductions in crop yield (i.e., yield shocks) severely disrupt the food supply, intensify food insecurity, depress farmers' welfare, and worsen a country's economic conditions. Here, we study the spatiotemporal patterns of wheat yield shocks, quantified by the lower quantiles of yield fluctuations, in 86 countries over 30 years. Furthermore, we assess the relationships between shocks and their key ecological and socioeconomic drivers using quantile regression based on statistical (linear quantile mixed model) and machine learning (quantile random forest) models. Using a panel dataset that captures spatiotemporal patterns of yield shocks and possible drivers in 86 countries, we find that the severity of yield shocks has been increasing globally since 1997. Moreover, our cross-validation exercise shows that quantile random forest outperforms the linear quantile regression model. Despite this performance difference, both models consistently reveal that the severity of shocks is associated with higher weather stress, nitrogen fertilizer application rate, and gross domestic product (GDP) per capita (a typical indicator for economic and technological advancement in a country). While the unexpected negative association between more severe wheat yield shocks and higher fertilizer application rate and GDP per capita does not imply a direct causal effect, they indicate that the advancement in wheat production has been primarily on achieving higher yields and less on lowering the possibility and magnitude of sharp yield reductions. Hence, in the context of growing extreme weather stress, there is a critical need to enhance the technology and management practices that mitigate yield shocks to improve the resilience of the world food systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Detection of the Metabolic Response to Drought Stress Using Hyperspectral Reflectance

Drought is the most important limitation on crop yield. Understanding and detecting drought stress in crops is vital for improving water use efficiency through effective breeding and management. Leaf reflectance spectroscopy offers a rapid, non-destructive alternative to traditional techniques for measuring plant traits involved in a drought response. We measured drought stress in six glasshouse-grown agronomic species using physiological, biochemical and spectral data. In contrast to physiological traits, leaf metabolite concentrations revealed drought stress before it was visible to the naked eye. We used full-spectrum leaf reflectance data to predict metabolite concentrations using partial least-squares regression, with validation R2 values of 0.49 to 0.87. We show for the first time that spectroscopy may be used for the quantitative estimation of proline and abscisic acid, demonstrating the first use of hyperspectral data to detect a phytohormone. We used linear discriminant analysis and partial least squares discriminant analysis to differentiate between droughted and watered plants based on measured traits (accuracy: 71%) and raw spectral data (66%). Finally, we validated our glasshouse-developed models in an independent field trial. We demonstrate that spectroscopy can detect drought stress via underlying biochemical changes, before visual differences occur, representing a powerful advance for measuring limitations on yield.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantifying cover crop effects on soil health and productivity

The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Increasing thermostability of the key photorespiratory enzyme glycerate 3‐kinase by structure‐based recombination

As global temperatures rise, improving crop yields will require enhancing the thermotolerance of crops. One approach for improving thermotolerance is using bioengineering to increase the thermostability of enzymes catalysing essential biological processes. Photorespiration is an essential recycling process in plants that is integral to photosynthesis and crop growth. The enzymes of photorespiration are targets for enhancing plant thermotolerance as this pathway limits carbon fixation at elevated temperatures. We explored the effects of temperature on the activity of the photorespiratory enzyme glycerate kinase (GLYK) from various organisms and the homologue from the thermophilic alga Cyanidioschyzon merolae was more thermotolerant than those from mesophilic plants, including Arabidopsis thaliana. To understand enzyme features underlying the thermotolerance of C. merolae GLYK (CmGLYK), we performed molecular dynamics simulations using AlphaFold-predicted structures, which revealed greater movement of loop regions of mesophilic plant GLYKs at higher temperatures compared to CmGLYK. Based on these simulations, hybrid proteins were produced and analysed. These hybrid enzymes contained loop regions from CmGLYK replacing the most mobile corresponding loops of AtGLYK. Two of these hybrid enzymes had enhanced thermostability, with melting temperatures increased by 6 °C. One hybrid with three grafted loops maintained higher activity at elevated temperatures. Whilst this hybrid enzyme exhibited enhanced thermostability and a similar Km for ATP compared to AtGLYK, its Km for glycerate increased threefold. This study demonstrates that molecular dynamics simulation-guided structure-based recombination offers a promising strategy for enhancing the thermostability of other plant enzymes with possible application to increasing the thermotolerance of plants under warming climates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Expression of dicarboxylate transporter from setaria italica in transgenic plants to increase yield

Compositions and methods for increasing plant growth for higher crop yield are provided. The methods involve the expression in a plant of interest of at least one C4 transporter coding sequence. Plants showing increased expression of one or more C4 transporter coding sequence of interest are encompassed by the invention. It is recognized that any method for increasing the expression of the C4 transporter coding sequences in a plant of interest can be used in the practice of the methods disclosed herein. Such methods include transformation, breeding and the like. Increased expression of the C4 transporter coding sequences in the plant of interest results in yield gains. Expression cassettes and vectors comprising the C4 transporter sequences disclosed herein are also provided herein. Methods for identifying genes under positive selection in plants that use C4 photosynthesis are disclosed and provided herein.

Brutnell, Thomas P.↗
DOE OSTI2020

Prospects for Engineering Biophysical CO 2 Concentrating Mechanisms into Land Plants to Enhance Yields

Although cyanobacteria and algae represent a small fraction of the biomass of all primary producers, their photosynthetic activity accounts for roughly half of the daily CO 2 fixation that occurs on Earth. These microorganisms are able to accomplish this feat by enhancing the activity of the CO 2 -fixing enzyme Rubisco using biophysical CO 2 concentrating mechanisms (CCMs). Biophysical CCMs operate by concentrating bicarbonate and converting it into CO 2 in a compartment that houses Rubisco (in contrast with other CCMs that concentrate CO 2 via an organic intermediate, such as malate in the case of C 4 CCMs). This activity provides Rubisco with a high concentration of its substrate, thereby increasing its reaction rate. The genetic engineering of a biophysical CCM into land plants is being pursued as a strategy to increase crop yields. This review focuses on the progress toward understanding the molecular components of cyanobacterial and algal CCMs, as well as recent advances toward engineering these components into land plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Empirical estimation of weather-driven yield shocks using biophysical characteristics for U.S. rainfed and irrigated maize, soybeans, and winter wheat

Agricultural yields are highly susceptible to changes in weather system patterns, including both annual and sub-annual changes in temperature and precipitation. Understanding the impacts of future changes in meteorological variables on crop yields have been widely studied in both empirical and process-based models. This work presents a structural econometric approach that combines historical weather data with information about the biophysical growth cycles of maize, winter wheat, and soy to predict the year-to-year yield responses for rainfed crops. Modeled soil moisture and temperature are taken as key predictors, which allows testing the fitted rainfed model’s ability to predict irrigated yields by assuming irrigation produces the numerically optimal level of soil moisture. This approach is grounded in known biophysical processes, which improves confidence in the model predictions. It produces estimates of interannual variability in yields, which enable study of the effects of extreme events on agricultural productivity. Finally, it enables prediction of the potential impacts of changing weather patterns on irrigated crops in areas that are currently primarily rainfed. We present the results of the empirical model, fitted with rainfed data; out-of-sample validation on irrigated crops; and projections of yield shocks under multiple future climate scenarios. Under a bias-corrected GFDL RCP8.5 scenario, this approach predicts average yield change, relative to 2006-2020 average yields, across U.S. counties in the 2040-2060 period of -16.9% and -13.4% for rainfed and irrigated maize, of -19.1% and -18.4% for rainfed and irrigated soy, and of -4.0% and -2.0% for rainfed and irrigated winter wheat. And in the 2070-2090 period of -30.3% and -28.8 % for rainfed and irrigated maize, of -33.1% and -32.8% for rainfed and irrigated soy, and of -6.5% and -5.2%for rainfed and irrigated winter wheat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies

We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Small-Scale Irrigation: Improving Food Security under Changing Climate and Water Resource Conditions in Ethiopia

We develop a new systems modeling tool that integrates knowledge from hydrology, agriculture, and economics to understand the effect of small-scale irrigation on food security and groundwater sustainability in Ethiopia. Irrigation is an effective tool to mitigate climate impacts and improve agricultural yields. Small-scale irrigation, such as decentralized groundwater irrigation, is well suited for developing countries where smallholder farming communities are widely dispersed and can only afford small infrastructure investment. We study the underlying interdependencies between food and water systems in Ethiopia, where small-holder agriculture is the foundation of the nation’s economy and climate variability has led to great challenges to its food security. Our coupled market and crop model with groundwater module captures the interdependencies of climate, water availability (including irrigation), crop yield, farmland allocation, crop production, transport and consumption based on a system approach across multiple spatial scales. We study the implication of small-scale irrigation to Ethiopia’s food security and water resource conditions as a “what-if” question by comparing an irrigation scenario to the calibrated baseline in 2015, a year of significant drought and crop failure over a large portion of Ethiopia. Our model offers fresh insights into geographic disparities in outcomes that are driven by baseline climate variability, soil fertility, and market conditions. In general, we find that small-scale irrigation can potentially improve food security through increases in food consumption, but it requires policy support to direct the increases of production to domestic consumption while maintaining a sustainable groundwater condition. By using Ethiopia as an example, we show the strength of our model to study how water infrastructure resources support critical functions and service in water and food systems.

Zhang, Ying↗
DOE OSTI2021

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Jagermeyr, Jonas↗
DOE OSTI2023

Response patterns of simulated corn yield and soil nitrous oxide emission to precipitation change

Abstract Background Precipitation plays an important role in crop production and soil greenhouse gas emissions. However, how crop yield and soil nitrous oxide (N 2 O) emission respond to precipitation change, particularly with different background precipitations (dry, normal, and wet years), has not been well investigated. In this study, we examined the impacts of precipitation changes on corn yield and soil N 2 O emission using a long-term (1981–2020, 40 years) climate dataset as well as seven manipulated precipitation treatments with different background precipitations using the DeNitrification-DeComposition (DNDC) model. Results Results showed large variations of corn yield and precipitation but small variation of soil N 2 O emission among 40 years. Both corn yield and soil N 2 O emission showed near linear relationships with precipitation based on the long-term precipitation data, but with different response patters of corn yield and soil N 2 O emission to precipitation manipulations. Corn yield showed a positive linear response to precipitation manipulations in the dry year, but no response to increases in precipitation in the normal year, and a trend of decrease in the wet year. The extreme drought treatments reduced corn yield sharply in both normal and wet years. In contrast, soil N 2 O emission mostly responded linearly to precipitation manipulations. Decreases in precipitation in the dry year reduced more soil N 2 O emission than those in the normal and wet years, while increases in precipitation increased more soil N 2 O emission in the normal and wet years than in the dry year. Conclusions This study revealed different response patterns of corn yield and soil N 2 O emission to precipitation and highlights that mitigation strategy for soil N 2 O emission reduction should consider different background climate conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Compartment-specific energy requirements of photosynthetic carbon metabolism in Camelina sativa leaves

Abstract Main conclusion The oxidative pentose phosphate pathway provides cytosolic NADPH yet reduces carbon and energy use efficiency. Repressing this pathway and introducing cytosolic NADPH-dependent malate dehydrogenase may increase crop yields by ≈5%. Abstract Detailed knowledge about plant energy metabolism may aid crop improvements. Using published estimates of flux through central carbon metabolism, we phenotype energy metabolism in illuminated Camelina sativa leaves (grown at 22 °C, 500 µmol photons m −2 s −1 ) and report several findings. First, the oxidative pentose phosphate pathway (OPPP) transfers 3.3% of the NADPH consumed in the Calvin–Benson cycle to the cytosol. NADPH supply proceeds at about 10% of the rate of net carbon assimilation. However, concomitantly respired CO 2 accounts for 4.8% of total rubisco activity. Hence, 4.8% of the flux through the Calvin–Benson cycle and photorespiration is spent on supplying cytosolic NADPH, a significant investment. Associated energy requirements exceed the energy output of the OPPP. Thus, autotrophic carbon metabolism is not simply optimised for flux into carbon sinks but sacrifices carbon and energy use efficiency to support cytosolic energy metabolism. To reduce these costs, we suggest bioengineering plants with a repressed cytosolic OPPP, and an inserted cytosolic NADPH-dependent malate dehydrogenase tuned to compensate for the loss in OPPP activity (if required). Second, sucrose cycling is a minor investment in overall leaf energy metabolism but a significant investment in cytosolic energy metabolism. Third, leaf energy balancing strictly requires oxidative phosphorylation, cofactor export from chloroplasts, and peroxisomal NADH import. Fourth, mitochondria are energetically self-sufficient. Fifth, carbon metabolism has an ATP/NADPH demand ratio of 1.52 which is met if ≤ 21.7% of whole electron flux is cyclic. Sixth, electron transport has a photon use efficiency of ≥ 62%. Last, we discuss interactions between the OPPP and the cytosolic oxidation–reduction cycle in supplying leaf cytosolic NADPH.

59 BASIC BIOLOGICAL SCIENCES↗