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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
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 OSTI2019

Preparation of Chitooligosaccharide by Hydrogen Peroxide Degradation of Chitosan and Its Effect on Soybean Seed Germination

Chitooligosaccharides (COS) were prepared by hydrogen peroxide (1%) degradation of chitosan solution (3%) in dilute lactic acid at ambient temperature. The molecular weights of degraded chitosan were measured by gel permeation chromatography, and the chemical structure of resultant COS were characterized by Fourier transform infrared spectra. The decrease of chitosan Mw followed the first-order kinetics with the rate constant of 5.71 × 10{sup −7} mol/g/h. As a result, the COS with Mw of 4500 g/mol was obtained at 360 h of the reaction time and its chemical structure almost remained the same as initial chitosan. Germination ability of soybean seeds pre-soaking in COS (4500 g/mol) solution with different concentrations, particularly 0 (control), 50, 100 and 200 mg/L was investigated. Results indicated that germination rate increased significantly for all soybean seeds treated with COS compared to the control. Thus, COS prepared by this method can be potentially applied to large-scale production with reasonably low cost and used as an effective biostimulant for sustainable agriculture.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2020

Spatially and Temporally Explicit Life Cycle Environmental Impacts of Soybean Production in the U.S. Midwest

Quantifying the spatially and temporally explicit life cycle environmental impacts of crop production is critical for designing sustainable supply chains for biofuel and animal sectors. This study assessed life cycle environmental impacts of soybean production in around 1000 Midwest counties over 9 years. A combination of Environmental Policy Integrated Climate model and process-based life cycle assessment model was used to estimate the spatially and temporally explicit life cycle global warming (GW), eutrophication (EU) and acidification (AD) impacts. Sequentially, a machine learning approach was applied to identify the top influential factors among soil, climate and farming practices for spatially and temporally explicit life cycle environmental impacts. The results indicated that significant variations existed in life cycle environmental impacts among counties and across years. Life cycle GW impacts ranged from -11.4 to 22.0 kg CO2-eq. kg soybean-1, whereas life cycle EU and AD impacts varied by a factor of 302 and 44, respectively. Nitrogen application rates, temperature in March and soil texture were the top influencing factors for the spatial-temporal variations in life cycle GW impacts. In contrast, soil organic content and nitrogen application rate were the top influencing factors for the spatial-temporal variations in life cycle EU and AD impacts.

Soybean, life cycle analysis, sustainability, spat↗
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↗
DOE OSTI2023

Chlorophyll fluorescence is a potential indicator to measure photochemical efficiency in early to late soybean maturity groups under changing day lengths and temperatures

In this study, we employed chlorophyll a fluorescence technique, to indicate plant health and status in response to changing day lengths (photoperiods) and temperatures in soybean early and late maturity groups. Chlorophyll a fluorescence study indicates changes in light reactions in photosystem II. Experiments were performed for 3-day lengths (12.5, 13.5, and 14.5 h) and five temperatures (22/14°C, 26/18°C, 30/22°C, 34/26°C, and 40/32°C), respectively. The I-P phase declined for changing day lengths. Active reaction centers decreased at long day length for maturity group III. We observed that low temperatures impacted the acceptor side of photosystem II and partially impacted electron transport toward the photosystem I end electron acceptor. Results emphasized that higher temperatures (40/32°C) triggered damage at the oxygen-evolving complex and decreased electron transport and photosynthesis. We studied specific leaf areas and aboveground mass. Aboveground parameters were consistent with the fluorescence study. Chlorophyll a fluorescence can be used as a potential technique for high-throughput phenotyping methods. The traits selected in the study proved to be possible indicators to provide information on the health status of various maturity groups under changing temperatures and day lengths. These traits can also be deciding criteria for breeding programs to develop inbreed soybean lines for stress tolerance and sensitivity based on latitudinal variations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

GmMPK6 Positively Regulates Salt Tolerance through Induction of GmRbohI1 in Soybean

Salt stress is a critical environmental stress that impairs plant growth and development, especially in crop productivity; therefore, understanding the salt response in plants is the basis for their development of salt tolerance. Under salinity, soybean mitogen-activated protein kinase 6 (GmMPK6) is activated and positively regulates reactive oxygen species (ROS) generation. However, it is not yet elucidated how GmMPK6 regulates ROS generation and its role in salt tolerance. Here, we show that GmMPK6, solely activated in NaCl treatment, and gene expression of GmRbohI1 was not only reduced by MPK inhibitor SB202190 in NaCl treatment, but also increased in a GMKK1-expressing protoplast. Furthermore, SB202190 and the NADPH-oxidase inhibitor, diphenyleneiodonium chloride, increased susceptibility to salt stress. The expression of GmRD19A was induced by NaCl treatment, but this expression was compromised by SB202190. Consequently, we revealed that GmMPK6 induces ROS generation through the transcriptional regulation of GmRbohI1 and increases salt tolerance in soybean.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2021

Soybean fallow and nitrification inhibitors: Strategies to reduce N 2 O emission intensities and N losses in Australian sugarcane cropping systems

The Australian sugar industry is facing mounting pressure to reduce the nitrogen (N) losses and nitrous oxide (N 2 O) emissions associated with N fertiliser use. Research has shown that N 2 O emissions from sugarcane (Saccharum officinarum L.) cropping systems can be reduced with the use of fertilisers coated with nitrification inhibitors, or by sowing legume crops in the fallows between sugarcane crop cycles. However, the efficacy of these two N management strategies across different climatic zones is still unclear, as results from field studies have been contradictory. The objectives of this study were therefore to use the DayCent model to assess the long-term effects of the two strategies (separately or in combination) on N 2 O emissions, N losses and yields. The model was parameterised using data from eight field experiments (39 treatments) conducted across four of the five main districts of the Australian sugarcane industry. A series of long-term scenarios embracing a range of N fertiliser rates (0- 160 kg N ha -1 applied as urea), climatic regions (Tropics and Subtropics), soil textures (fine- and coarse-textured soils) and N-loss risk scenarios (crop fertilised well before or close to the on-set of the wet season) were tested for both N management strategies. Simulations identified that the combined use of soybean (Glycine max L.) fallows and N fertiliser coated with the 3,4-dimethylpyrazole phosphate (DMPP) nitrification inhibitor was the most effective strategy to maintain or even increase current yields while significantly reducing N 2 O and cumulative N (mainly due to nitrate) losses. When used alone, the soybean fallow strategy on average reduced N losses over the entire crop cycle by 29 % compared with current industry best practice. However, this strategy showed a limited capacity to reduce N 2 O emissions over the entire cane crop cycle (median: -3% compared with current industry best practice), or even increased them in scenarios at high-risk of N losses in the Tropics. The use of urea coated with DMPP alone allowed current fertiliser N rates to be reduced by 30 % without any substantial yield penalty. In environments prone to high N losses, DMPP urea abated overall N losses and N 2 O emissions by 41 % and 30 %, respectively. This was the first study to use such an extensive dataset to parameterise a biogeochemical model for yields, N 2 O emissions and N losses in sugarcane cropping systems. Finally, the findings will be instrumental in guiding future research and policies designed to improve the profitability and environmental sustainability of this industry.

54 ENVIRONMENTAL SCIENCES↗