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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Use of microwaves to improve nutritional value of soybeans for future space inhabitants

Whole soybeans from four different varieties at different moisture contents were microwaved for varying times to determine the conditions for maximum destruction of trypsin inhibitor and lipoxygenase activities, and optimal growth of chicks. Microwaving 150 gm samples of soybeans (at 14 to 28% moisture) for 1.5 min was found optimal for reduction of trypsin inhibitor and lipoxygenase activities. Microwaving 1 kgm samples of soybeans for 9 minutes destroyed 82% of the trypsin inhibitor activity and gave optimal chick growth. It should be pointed out that the microwaving time would vary according to the weight of the sample and the power of the microwave oven. The microwave oven used in the above experiments was rated at 650 watts 2450 MHz.

Singh, G.↗
NASA NTRS1982

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

Batista, G. T.↗
NASA NTRS1982

An initial model for estimating soybean development stages from spectral data

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.

Henderson, K. E.↗
NASA NTRS1984

Automatic corn-soybean classification using Landsat MSS data. I - Near-harvest crop proportion estimation. II - Early season crop proportion estimation

The techniques used initially for the identification of cultivated crops from Landsat imagery depended greatly on the iterpretation of film products by a human analyst. This approach was not very effective and objective. Since 1978, new methods for crop identification are being developed. Badhwar et al. (1982) showed that multitemporal-multispectral data could be reduced to a simple feature space of alpha and beta and that these features would separate corn and soybean very well. However, there are disadvantages related to the use of alpha and beta parameters. The present investigation is concerned with a suitable method for extracting the required features. Attention is given to a profile model for crop discrimination, corn-soybean separation using profile parameters, and an automatic labeling (target recognition) method. The developed technique is extended to obtain a procedure which makes it possible to estimate the crop proportion of corn and soybean from Landsat data early in the growing season.

Badhwar, G. D.↗
NASA NTRS1984

Soybean canopy reflectance modeling data sets

Numerous mathematical models of the interaction of radiation with vegetation canopies have been developed over the last two decades. However, data with which to exercise and validate these models are scarce. During three days in the summer of 1980, experiments are conducted with the objective of gaining insight about the effects of solar illumination and view angles on soybean canopy reflectance. In concert with these experiment, extensive measurements of the soybean canopies are obtained. This document is a compilation of the bidirectional reflectance factors, agronomic, characteristics, canopy geometry, and leaf, stem, and pod optical properties of the soybean canopies. These data sets should be suitable for use with most vegetation canopy reflectance models.

Ranson, K. J.↗
NASA NTRS2001

Effect of spaceflight on isoflavonoid accumulation in etiolated soybean seedlings

In order to explore the potential impact of microgravity on flavonoid biosynthesis, we examined isoflavonoid levels in soybean (Glycine max) tissues generated under both spaceflight and clinorotation conditions. A 6-day Space Shuttle-based microgravity exposure resulted in enhanced accumulation of isoflavone glycosides (daidzin, 6"-O-malonyl-7-O-glucosyl daidzein, genistin, 6"-O-malonyl-7-O-glucosyl genistein) in hypocotyl and root tissues, but reduced levels in cotyledons (relative to 1g controls on Earth). Soybean seedlings grown on a horizontally rotating clinostat for 3, 4 and 5 days exhibited (relative to a vertical clinorotation control) an isoflavonoid accumulation pattern similar to the space-grown tissues. Elevated isoflavonoid levels attributable to the clinorotation treatment were transient, with the greatest increase observed in the three-day-treated tissues and smaller increases in the four- and five-day-treated tissues. Differences between stresses presented by spaceflight and clinorotation and the resulting biochemical adaptations are discussed, as is whether the increase in isoflavonoid concentrations were due to differential rates of development under the "gravity" treatments employed. Results suggest that spaceflight exposure does not impair isoflavonoid accumulation in developing soybean tissues and that isoflavonoids respond positively to microgravity as a biochemical strategy of adaptation.

Flight Experiment↗
NASA NTRS1999

Electron-cytochemical study of Ca2+ in cotyledon cells of soybean seedlings grown in microgravity

Microgravity and horizontal clinorotation are known to cause the rearrangement of the structural-functional organization of plant cells, leading to accelerated aging. Altered gravity conditions resulted in an increase in the droplets volume in cells and the destruction of chloroplast structure in Arabidopsis thaliana plants, an enhancement of cytosolic autophagaous processes, an increase in the respiration rate and a greater number of multimolecular forms of succinate- and malate dehydrogenases in cells of the Funaria hygrometrica protonema and Chlorella vulgaris, and changes in calcium balance of cells. Because ethylene is known to be involved in cell aging and microgravity appears to speed the process, and because soybean seedlings grown in space produce higher ethylene levels we asked: 1) does an acceleration of soybean cotyledon cell development and aging occur in microgravity? 2) what roles do Ca2+ ions and the enhanced ethylene level play in these events? Therefore, the goal of our investigation was to examine of the interaction of microgravity and ethylene on the localization of Ca2+ in cotyledon mesophyll of soybean seedlings.

Flight Experiment↗
NASA NTRS1986

Growth reponses of eggplant and soybean seedlings to mechanical stress in greenhouse and outdoor environments

Eggplant (Solanum melongena L. var. esculentum 'Burpee's Black Beauty') and soybean [Glycine max (L.) Merr. 'Wells II'] seedlings were assigned to a greenhouse or a windless or windy outdoor environment. Plants within each environment received either periodic seismic (shaking) or thigmic (flexing or rubbing) treatment, or were left undisturbed. Productivity (dry weight) and dimensional (leaf area and stem length) growth parameters generally were reduced more by mechanical stress in the greenhouse (soybean) or outdoor-windless environment (eggplant) than in the outdoor windy environment. Outdoor exposure enhanced both stem and leaf specific weights, whereas mechanical stress enhanced only leaf specific weight. Although both forms of controlled mechanical stress tended to reduce node and internode diameters of soybean, outdoor exposure increased stem diameter.

NASA Discipline Number 61-10↗
NASA NTRS1990

The role of wall calcium in the extension of cell walls of soybean hypocotyls

Calcium crosslinks are load-bearing bonds in soybean (Glycine max (L.) Merr.) hypocotyl cell walls, but they are not the same load-bearing bonds that are broken during acid-mediated cell elongation. This conclusion is reached by studying the relationship between wall calcium, pH and the facilitated creep of frozen-thawed soybean hypocotyl sections. Supporting data include the following observations: 1) 2-[(2-bis-[carboxymethyl]amino-5-methylphenoxy)methyl]-6-methoxy-8-bis[car boxymethyl]aminoquinoline (Quin 2) and ethylene glycol-bis(2-aminoethyl ether)-N,N,N',N'-tetraacetic acid (EGTA) caused only limited facilitated creep as compared with acid, despite removal of comparable or larger amounts of wall calcium; 2) the pH-response curves for calcium removal and acid-facilitated creep were different; 3) reversible acid-extension occurred even after removal of almost all wall calcium with Quin 2; and 4) growth of abraded sections did not involve a proportional loss of wall calcium. Removal of wall calcium, however, increased the capacity of the walls to undergo acid-facilitated creep. These data indicate that breakage of calcium crosslinks is not a major mechanism of cell-wall loosening in soybean hypocotyl tissues.

Non-NASA Center↗
NASA NTRS1996

Clinorotation affects morphology and ethylene production in soybean seedlings

The microgravity environment of spaceflight influences growth, morphology and metabolism in etiolated germinating soybean. To determine if clinorotation will similarly impact these processes, we conducted ground-based studies in conjunction with two space experiment opportunities. Soybean (Glycine max [L.] Merr.) seeds were planted within BRIC (Biological Research In Canister) canisters and grown for seven days at 20 degrees C under clinorotation (1 rpm) conditions or in a stationary upright mode. Gas samples were taken daily and plants were harvested after seven days for measurement of growth and morphology. Compared to the stationary upright controls, plants exposed to clinorotation exhibited increased root length (125% greater) and fresh weight (42% greater), whereas shoot length and fresh weight decreased by 33% and 16% respectively. Plants grown under clinorotation produced twice as much ethylene as the stationary controls. Seedlings treated with triiodo benzoic acid (TIBA), an auxin transport inhibitor, under clinorotation produced 50% less ethylene than the untreated control subjected to the same gravity treatment, whereas a treatment with 2,4-D increased ethylene by five-fold in the clinorotated plants. These data suggest that slow clinorotation influences biomass partitioning and ethylene production in etiolated soybean plants.

NASA Discipline Life Support Systems↗
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↗
DOE OSTI2025

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗
DOE OSTI2024

How do drought and heat affect the response of soybean seed yield to elevated O3? An analysis of 15 seasons of free-air O3 concentration enrichment (O3-FACE) studies

Over the past 15 years, soybean seed yield response to season-long elevated O3 concentrations [O3] and to year-to-year weather conditions was studied using free-air O3 concentration enrichment (O3-FACE) in the field at the SoyFACE facility in Central Illinois. Elevated [O3] significantly reduced seed yield across cultivars and years. However, our results quantitatively demonstrate that weather conditions, including soil water availability and air temperature, did not alter yield sensitivity to elevated [O3] in soybean.

drought, elevated O3, heat, O3-FACE, soybean, yiel↗
NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗
DOE OSTI2024

AmeriFlux US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage

This is the AmeriFlux version of the carbon flux data for the site US-MN1 Morris: Corn-Soybean with Cover Crops, Strip Tillage. Site Description - Cropland, 2-year rotation (corn-soybean), strip tillage with winter cover crops (annual rye), nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina↗
DOE OSTI2024

AmeriFlux US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage

This is the AmeriFlux version of the carbon flux data for the site US-MN2 Morris: Corn-Soybean-Wheat with Cover Crops, Minimal Tillage. Site Description - Cropland, 3-year rotation (corn-soybean-wheat), cover crops (winter camelina and pennycress), minimum tillage, nutrient management by soil tests, uniform pest management, tile drainage

Helseth, Christina↗
DOE OSTI2024

AmeriFlux US-MN3 Morris: Corn-Soybean, Conventional Tillage

This is the AmeriFlux version of the carbon flux data for the site US-MN3 Morris: Corn-Soybean, Conventional Tillage. Site Description - Cropland, 2-year rotation (corn-soybean), conventional (deep rip) tillage, uniform nutrient management, uniform pest management, tile drainage

Helseth, Christina↗