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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Responsiveness of miscanthus and switchgrass yields to stand age and nitrogen fertilization: A meta‐regression analysis

Abstract Optimal management of the perennial bioenergy crops, miscanthus and switchgrass, requires an understanding of their responsiveness to nitrogen (N) fertilizer at different maturity stages across locations and growing conditions. Earlier studies that have examined the yield response of these crops to N and stand age using field experiments or meta‐analysis techniques provide mixed evidence. We extend earlier studies by applying a multi‐level mixed‐effects (MLME) meta‐regression model to conduct a more extensive multivariate regression of yield response of these crops to N and stand age, while controlling for climate and location conditions and unobserved factors related to study design. Our findings are based on 1403 and 2811 yield observations for miscanthus and switchgrass, respectively, from experiments conducted between 2002 and 2019 across the rainfed region in the United States. We find statistically significant evidence that an additional year of maturity increases miscanthus and switchgrass yields but at a decreasing rate; yields peak at the 7th and 6th year respectively, for the observed range of applied N rates and stands. We also find that an increase in N application increases yield by a statistically significant level, but at a declining rate; the magnitude of the yield response to N is, however, small and varies with the age of the crop. The impact of N is larger on older compared to younger and middle‐aged stands of miscanthus. In contrast, the impact of N on switchgrass is larger on middle‐aged compared to younger and older stands of switchgrass. We do not find a statistically significant effect of soil productivity on yield for either crop. This analysis provides a basis for developing N application recommendations and optimal rotation age for miscanthus and switchgrass and shows that these energy crops can grow just as productively on low productivity land as on high productivity land.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identifying the Best High‐Biomass Sorghum Hybrids Based on Biomass Yield Potential and Feedstock Quality Affected by Nitrogen Fertility Management Under Various Environments

The growing interest in high-biomass sorghum ( Sorghum bicolor L. Moench), hereafter referred to as sorghum, as a bioenergy feedstock in the United States requires an understanding of geographical adaptation to identify the most suitable hybrids for the Midwest. In this study, 13 sorghum hybrids (H1–H13) were evaluated for biomass yield potential in central and southern IL over two growing seasons (2022 and 2023). In addition to biomass yield, the effects of nitrogen (N) fertilization on yield, nutrient removal (N, P, and K), and feedstock composition (cellulose, hemicellulose, lignin, and soluble fractions) were determined to identify the best-performing sorghum hybrid across environmental gradients. The experimental design was a split-plot arrangement within a randomized complete block design with four replications at each of two locations: N rates (0 and 112 kg-N ha −1 ) as a whole plot factor and 13 sorghum hybrids as a subplot factor. As a result, complex genotypes (13 hybrids) by environment (2 sites and 2 years) and management (2 N rates) interactions were observed in biomass yield. The best hybrids at both sites were H1 (ATx2932/F10702_PSL) and H13 (TX08001), which were very photoperiod sensitive (PS). These hybrids produced superior biomass yield, and they also exhibited less nutrient removal and high energy-rich feedstock compositions (cellulose, hemicellulose, and lignin). Biomass yield potential was associated with morphological and phenological traits according to environmental conditions. Low-yielding hybrids were short-stature (H5 and H6) with pollinators (F10801_PSL-3dw and F10805_PSL-3dw) that are recessive at the Dw3 locus. Moderate PS hybrids (H7, H8, H11, and H12) that produced grain panicles at harvest showed high biomass yield plasticity and excessive nutrient removal as they accumulated high K concentrations in biomass tissues and high N and P in grain panicles.

09 BIOMASS FUELS↗
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 OSTI2019

Capturing Maize Stand Heterogeneity Across Yield-Stability Zones Using Unmanned Aerial Vehicles (UAV)

Despite the new equipment capabilities, uneven crop stands are still common occurrences in crop fields, mainly due to spatial heterogeneity in soil conditions, seedling mortality due to herbivore predation and disease, or human error. Non-uniform plant stands may reduce grain yield in crops like maize. Thus, detecting signs of variability in crop stand density early in the season provides critical information for management decisions and crop yield forecasts. Processing techniques applied on images captured by unmanned aerial vehicles (UAVs) has been used successfully to identify crop rows and estimate stand density and, most recently, to estimate plant-to-plant interval distance. Here, we further test and apply an image processing algorithm on UAV images collected from yield-stability zones in a commercial crop field. Our objective was to implement the algorithm to compare variation of plant-spacing intervals to test whether yield differences within these zones are related to differences in crop stand characteristics. Our analysis indicates that the algorithm can be reliably used to estimate plant counts (precision >95% and recall >97%) and plant distance interval (R2 ~0.9 and relative error <10%). Analysis of the collected data indicated that plant spacing variability differences were small among plots with large yield differences, suggesting that it was not a major cause of yield variability across zones with distinct yield history. This analysis provides an example of how plant-detection algorithms can be applied to improve the understanding of patterns of spatial and temporal yield variability.

47 OTHER INSTRUMENTATION↗
NASA NTRS2017

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗
NASA NTRS2024

Global Nitrogen Needs to Improve Wheat Yield Under Climate Change

Increasing global food demand will require more food production without further exceeding the planetary boundaries, while at the same time adapting to climate change. We used an ensemble of wheat simulation models, with improved yield traits from the highest-yielding wheat genotypes to quantify potential yield gains and associated N requirements. This was explored for current and climate change scenarios across representative sites of major world wheat producing regions. The improved yield traits increased yield by 16% with current N fertilizer applications under both current climate and mid-century climate change scenarios. To achieve the full yield potential, a 52% increase in global average yield under a mid-century high warming climate scenario (RCP8.5), fertilizer use would need to increase fourfold over current use, which would unavoidably lead to higher environmental impacts from wheat production. Our results show the need to improve soil N availability and N use efficiency, along with yield potential.

Nitrogen↗
DOE OSTI2020

Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects

Hydroxymethylfurfural (HMF) is one of the important renewable platform compounds that can be obtained from biomass feedstocks through glucose conversion catalyzed by Brønsted and Lewis acids. However, it is challenging to enhance the HMF yield due to side reactions. In this study, a systematic approach combining theory and experiment was performed to investigate the influence of Lewis acids and organic solvents on the HMF yield. For the Lewis acid effect, a relationship between chemical hardness and experimental HMF yields was found in the rate-limiting step of glucose-to-fructose isomerization for six metal chlorides; HMF production was promoted when the metal chloride and a substrate had a similar chemical hardness. To study the organic solvent effect, a multivariate model was developed based on the insights gained from the mechanistic study of fructose dehydration, to predict HMF yields in a given water-organic cosolvent system. It showed a reliable accuracy in evaluating HMF yields with a mean absolute error (MAE) of 3.0% with respect to experimental HMF yields for 13 solvents, and also predicted HMF yields with a MAE of 10.7% for four new solvents. Chemical interpretation of the model revealed that it is desirable to use a solvent capable of stabilizing the carbocation intermediates with low proton transfer activity and high hydrogen bond basicity, to maximize the HMF yield. This multivariate model informs experimentalists about rational selection of solvents with very low computational costs needed to calculate only six variables for each solvent. It can be expanded to other catalytic systems such as heterogeneous Brønsted–Lewis bifunctional catalysts and enables optimization of reaction conditions to obtain other useful platform molecules through biomass conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Inferring neutron yields using indium activation samples for small fractions of tritium added to deuterium fuel in inertial confinement fusion (ICF) experiments

In inertial confinement fusion experiments, the neutron yield is an important metric for thermonuclear fusion performance. Neutron activation diagnostics can be used to infer neutron yields. The material used for neutron activation diagnostic undergoes a threshold reaction so that only neutrons having energies above the threshold energy are observed. For thermonuclear experiments using deuterium (D) and tritium (T) fuel constituents, neutrons arising from D + D reactions (DD-neutrons) and neutrons resulting from D + T reactions (DT-neutrons) are of primary interest. Indium has two neutron activation reactions that can be used to infer yields of DD-neutrons and DT-neutrons. One threshold is high enough that only DT-neutrons can induce activation, the second reaction can be activated by both DD-neutrons and DT-neutrons. Thus, to obtain the DD-neutron yield, the contribution made by DT-neutrons to the total induced activity must be extracted. In DD-fuel experiments, DT-neutrons arise from secondary reactions, which are significantly lower in number than primary DD-neutrons, and their contribution to the inferred DD-neutron yield can be ignored. When the DD- and DT-neutron yields become comparable, such as when low tritium fractions are added to DD-fuel, the contribution of DT-neutrons must be extracted to obtain accurate yields. A general method is described for this correction to DD-neutron yields.

Mangan, M. A. (ORCID:000000034583700X)↗
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

Quorum-sensing molecules increase ethanol yield from Saccharomyces cerevisiae

ABSTRACT One strategy to increase the yield of desired fermentation products is to redirect substrate carbon from biomass synthesis. Nongenetic approaches to alter metabolism may have advantages of general applicability and simple control. The goal of this study was to identify and evaluate chemicals for their ability to inhibit the growth of Saccharomyces cerevisiae while allowing ethanol production with higher yields. Eight potential growth-inhibitory chemicals were screened for their ability to reduce cell growth in 24-well plates. Effective chemicals were then evaluated in cultivations to identify those that simultaneously reduced biomass yield and increased ethanol yield. The yeast quorum-sensing molecules 2-phenylethanol, tryptophol and tyrosol were found to increase the ethanol yield of S. cerevisiae JAY 270. These molecules were tested with seven other yeast strains and ethanol yields of up to 15% higher were observed. The effects of 2-phenylethanol and tryptophol were also studied in bioreactor fermentations. These findings demonstrate for the first time that the ethanol yield can be improved by adding yeast quorum-sensing molecules to reduce the cell growth of S. cerevisiae, suggesting a strategy to improve the yield of ethanol and other yeast fermentation products by manipulating native biological control systems.

Huang, Xing-Feng (ORCID:0000000251165177)↗
DOE OSTI2018

Poplar and shrub willow energy crops in the United States: field trial results from the multiyear regional feedstock partnership and yield potential maps based on the PRISM‐ELM model

Abstract To increase the understanding of poplar and willow perennial woody crops and facilitate their deployment for the production of biofuels, bioproducts, and bioenergy, there is a need for broadscale yield maps. For national analysis of woody and herbaceous crops production potential, biomass feedstock yield maps should be developed using a common framework. This study developed willow and poplar potential yield maps by combining data from a network of willow and poplar field trials and the modeling power of PRISM‐ELM. Yields of the top three willow cultivars across 17 sites ranged from 3.60 to 14.6 Mg ha −1 yr −1 dry weight, while the yields from 17 poplar trials ranged from 7.5 to 15.2 Mg ha −1 yr −1 . Relationships between the environmental suitability estimates from the PRISM‐ELM model and results from field trials had an R 2 of 0.60 for poplar and 0.81 for willow. The resulting potential yield maps reflected the range of poplar and willow yields that have been reported in the literature. Poplar covered a larger geographic range than willow, which likely reflects the poplar breeding efforts that have occurred for many more decades using genotypes from a broader range of environments than willow. While the field trial data sets used to develop these models represent the most complete information at the time, there is a need to expand and improve the model by monitoring trials over multiple cutting cycles and across a broader range of environmental gradients. Despite some limitations, the results of these models represent a dramatic improvement in projections of potential yield of poplar and willow crops across the United States.

09 BIOMASS FUELS↗
DOE OSTI2020

Global Market and Economic Welfare Implications of Changes in Agricultural Yields Due to Climate Change

The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and economic processes. For a given emissions scenario, these include: (1) the response of the climate system to anthropogenic forcing, (2) the response of crop yields to climate system and carbon dioxide changes, given baseline improvements in crop yields, (3) the response of agricultural markets to crop yield changes, and (4) the economic welfare implications of such market responses. In this paper, we use information about the first two processes from available climate-crop model comparison studies to analyze implications for the third and fourth processes. Applying the range of crop yield changes in a Global Integrated Assessment Model (GCAM) highlights several important economic relationships. First, we find a consistent relationship between global cropland area and yield change that is approximately orthogonal to the relationship between regional cropland area and yield change. Second, we find that the change in economic welfare, expressed as total surplus change per unit economic output, peaks during the 21st century. Third, we find that, at the global level, changes in yield affect both producer surplus and consumer surplus. Specifically, surplus changes to producers and consumers are always opposite in sign, although which economic actors gain or lose varies with the sign of yield change for any given commodity. Taken together, these results contribute to a growing body of research on climate-induced changes on agriculture by highlighting several economic relationships that are robust to differences in the underlying biophysical responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Theoretical Yields for 188 W Production in the High Flux Isotope Reactor

Accurately predicting the production yield of 188 W and 191 Os from enriched 186W metal rings irradiated in HFIR is not straightforward. Two key factors can lead to significant uncertainty or inaccuracy in yield predictions: The effect of neutron flux depression in the dense tungsten metal target. Inaccuracy of the currently published 187 W thermal neutron absorption cross section. This manuscript reports the calculated yields for 188 W, 191 Os, and total osmium mass for the NM-888 target that was irradiated in High Flux Isotope Reactor (HFIR) Cycles 487 and 488. Three different yield calculation methods were used and are described herein. The results are presented in terms of total yield and in terms of yield per target mass. This allows for an approximate estimation of yields for future targets of varying mass loading but with similar irradiation profiles. For more accurate prediction yields, target-specific models that account for target loading, target positioning within HFIR, and accurate HFIR cycle data are required.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Long-term integrated soil-crop management improves soil microbial community structure to reduce GHG emission and increase yield

Integrated soil-crop management (ISCM) has been shown as an effective strategy to increase efficiency and yield while its soil microbial community structure and function remain unclear. We evaluated changes in soil physicochemical factors, bacterial community structure responses, and the contributions of soil properties and bacterial communities to summer maize-winter wheat yield and GHG emissions through an ISCM experiment [T1 (local smallholder farmers practice system), T2 (improved management system), T3 (high–yield production system), and T4 (optimized management system)], which could provide scientific guidance for sustainable development of soil in summer maize-winter wheat rotation system. The results showed that the optimized ISCM could improve the soil quality, which significantly changed the soil bacterial community structure to reduce GHG emissions and increase yield. The co-occurrence network density of T3 was increased significantly. The Acidobacteria (class) and OM190 (class) were enriched in T2 and T4. The Frankiales (order) and Gaiellales (order) were enriched in T3. However, the changes in different crop growth stages were different. At the wheat jointing stage and maize mature stage, T4 could enhance carbon-related functional groups, such as aromatic hydrocarbon degradation and hydrocarbon degradation, to increase the soil organic carbon content. And at the maize tasseling stage, T4 could enhance nitrogen-related functional groups. And soil bacteria structure and function indirectly affected annual yield and GHG emission. T2 and T4 exhibited a similar soil microbial community. However, the yield and nitrogen use efficiency of T2 were reduced compared to those of T4. The yield of T3 was the highest, but the GHG emission increased and soil pH and nitrogen use efficiency decreased significantly. Therefore, T4 was a suitable management system to improve soil quality and soil bacterial community structure and function to decrease GHG emissions and increase the yield of the summer maize-winter wheat rotation system.

Yu, Ningning↗
DOE OSTI2019

A crop yield change emulator for use in GCAM and similar models: Persephone v1.0

Abstract. Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multi-sector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model's results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.

58 GEOSCIENCES↗
NASA NTRS1990

Yield estimation of sugarcane based on agrometeorological-spectral models

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

Rudorff, Bernardo Friedrich Theodor↗
NASA NTRS1992

Secondary electron yields of solar system ices

The secondary electron yields of H2O, CO2, NH3, and CH3OH ices have been measured as a function of electron beam energy in the 2- to 30-keV energy range. The ices were produced on a liquid-nitrogen-cooled cold finger and transferred under vacuum to a SEM where the yield measurements were made. The imaging capabilities of the SEM provide a means of correlating the yield measurements with the morphology of the ices and are also used to monitor charging effects. The yields were determined by measuring the amplified current from a secondary electron detector and calibrating this current signal with the amplified current signal from samples of metals with known secondary electron yields. Each of the measured yields is found to decrease with an increase in energy in the 2- to 30-keV range. Estimates are given for the maximum secondary electron yield Y(max) of each ice and the energy at which this maximum yield occurs. Implications for the charging of solar system ice grains are discussed.

Suszcynsky, David M.↗
NASA NTRS2003

Xenon Sputter Yield Measurements for Ion Thruster Materials

In this paper, we describe a technique that was used to measure total and differential sputter yields of materials important to high specific impulse ion thrusters. The heart of the technique is a quartz crystal monitor that is swept at constant radial distance from a small target region where a high current density xenon ion beam is aimed. Differential sputtering yields were generally measured over a full 180 deg arc in a plane that included the beam centerline and the normal vector to the target surface. Sputter yield results are presented for a xenon ion energy range from 0.5 to 10 keV and an angle of incidence range from 0 deg to 70 deg from the target surface normal direction for targets consisting of molybdenum, titanium, solid (Poco) graphite, and flexible graphite (grafoil). Total sputter yields are calculated using a simple integration procedure and comparisons are made to sputter yields obtained from the literature. In general, the agreement between the available data is good. As expected for heavy xenon ions, the differential and total sputter yields are found to be strong functions of angle of incidence. Significant under- and over-cosine behavior is observed at low- and high-ion energies, respectively. In addition, strong differences in differential yield behavior are observed between low-Z targets (C and Ti) and high-Z targets (Mo). Curve fits to the differential sputter yield data are provided. They should prove useful to analysts interested in predicting the erosion profiles of ion thruster components and determining where the erosion products re-deposit.

Williams, John D.↗