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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for Immediate Impacts of Soybean Cover Crop on Bacterial Community Composition and Diversity in Soil Under Long-Term Saccharum Monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Field Data↗
DOE OSTI2026

Data for Promoter Deletion in the Soybean Compact Mutant Leads to Overexpression of a Gene with Homology to the C20-Gibberellin 2-Oxidase Family

Height is a critical component of plant architecture, significantly affecting crop yield. The genetic basis of this trait in soybean remains unclear. In this study, we report the characterization of the Compact mutant of soybean, which has short internodes. The candidate gene was mapped to chromosome 17, and the interval containing the causative mutation was further delineated using biparental mapping. Whole-genome sequencing of the mutant revealed an 8.7 kb deletion in the promoter of the Glyma.17g145200 gene, which encodes a member of the class III gibberellin (GA) 2-oxidases. The mutation has a dominant effect, likely via increased expression of the GA 2-oxidase transcript observed in green tissue, as a result of the deletion in the promoter of Glyma.17g145200. We further demonstrate that levels of GA precursors are altered in the Compact mutant, supporting a role in GA metabolism, and that the mutant phenotype can be rescued with exogenous GA3. We also determined that overexpression of Glyma.17g145200 in Arabidopsis results in dwarfed plants. Thus, gain of promoter activity in the Compact mutant leads to a short internode phenotype in soybean through altered metabolism of gibberellin precursors. These results provide an example of how structural variation can control an important crop trait and a role for Glyma.17g145200 in soybean architecture, with potential implications for increasing crop yield.

Biomass Analytics↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
NASA NTRS2005

Influence of Hydroponically Grown Hoyt Soybeans and Radiation Encountered on Mars Missions on the Yield and Quality of Soymilk and Tofu

Soybeans were chosen for hmar and planetary missions due to their nutritive value and ability to produce oil and protein for further food applications. However, soybeans must be processed into foods prior to crew consumption. Wilson et al. (2003) raised questions about (1) the influence of radiation (on germination and functional properties) that the soybeans would be exposed to during bulk storage for a Mars mission, and (2) the impact of using hydroponically grown versus field grown soybeans on the yield and quality of soyfoods. The influence of radiation can be broken down into two components: (A) affect of surface pasteurization to ensure the astronauts safety from food-borne illnesses (a Hazard Analysis Critical Control Point), and (B) affect of the amount of radiation the soybeans receive during a Mars mission. Decreases in the amount of natural antioxidants and free radical formation and oxidation induced changes in the soybean (lipid, protein, etc.) will influence the nutritional value, texture, quality, and safety of soyfoods made from them. The objectives of this project are to (1) evaluate the influence of gamma and electron beam radiation on bulk soybeans (HACCP, CCP) on the microbial load, germination, ease of processing, and quality of soymilk and tofu; (2) provide scale up and mass balance data for Advanced Life Support subsystems including Biomass, Solid Waste Processing, and Water Recovery Systems; and (3) to compare Hoyt field grown to hydroponically grown Hoyt soybeans for soymilk and tofu production. The soybean cultivar Hoyt, a small standing, high protein cultivar that could grow hydroponically in the AIMS facility on Mars) was evaluated for the production of soymilk and tofu. The quality and yield of the soymilk and tofu from hydroponic Hoyt, was compared to Vinton 81 (a soyfood industry standard), field Hoyt, IA 2032LS (lipoxygenase-free), and Proto (high protein and antioxidant potential). Soymilk and tofu were produced using the Japanese method. The soymilk was coagulated with calcium sulfate dihydrate. Soybeans and tofu were evaluated using chemical, microbial, and instrumental sensory methods. The surface radiation of whole dry soybeans using electron beam or gamma rays at 10 or 30 kGy did provide microbial safety for the astronauts. However, these doses caused oxidative changes that resulted in tofu with rancid aroma, darkening of the tofu, lower tofu yields, more solid waste, and loss of the ability of the seeds to germinate. While lower doses may reduce these problems, we lose the ability to insure microbial safety (cross-contamination) of bulk soybeans for the astronauts. Counter measures could include vacuum packaging, radiating under freezing conditions. A No Effect Dose for food quality, below 10 kGy needs to be determined. Better estimates of the radiation that the food will be exposed to need to determined and shared. Appropriate shielding for the food as well as the astronauts needs to be developed. The Hoyt soybean did not provide a high yielding, high quality tofu. A new small scale system for evaluating soybeans was developed using 50 g quantities of soybeans.

Wilson, Lester A.↗
NASA NTRS2006

Irradiating of Bulk Soybeans: Influence on Their Functional and Sensory Properties for Soyfood Processing

Soybeans were chosen for lunar and planetary missions, where soybeans will be supplied in bulk or grown locally, due to their nutritive value and ability to produce oil and protein for further food applications. However, soybeans must be processed into foods prior to consumption. Radiation that soybeans would be exposed to during bulk storage prior to and during a Mars mission may influence their germination and functional properties. The influence of radiation includes the affect of surface pasteurization to ensure the astronauts safety from food-borne illnesses (HACCP, CCP), and the affect of the amount of radiation the soybeans receive during a Mars mission. Decreases in the amount of natural antioxidants free radical formation, and oxidation-induced changes in the soybean will influence the nutritional value, texture, color, and aroma of soyfoods. The objective of this study was to determine the influence of pasteurization and sterilization surface radiation on whole soybeans using gamma and electron beam radiation. The influence of 0, 1, 5, 10, and 30kGy on microbial load, germination rate, ease of processing, and quality of soymilk and tofu were determined. Surface radiation of whole dry soybeans using electron beam or gamma rays from 1-30kGy did provide microbial safety for the astronauts. However, the lower dose levels had surviving yeasts and molds. These doses caused oxidative changes that resulted in soymilk and tofu with rancid aromas. GC-MS of the aroma compounds using SPME Headspace confirmed the presence of lipid oxidation compounds. Soybean germination ability was reduced as radiation dosage increased. While lower doses may reduce these problems, the ability to insure microbial safety of bulk soybeans will be lost. Counter measures could include vacuum packaging, nitrogen flushing, added antioxidants, and radiating under freezing conditions. Doses below 1kGy need to be investigated further to determine the influence of the radiation encountered during Mars missions.

Chia, Chiew-Ling↗
DOE OSTI2025

Soybean rust‐resistant and tolerant varieties identified through the Pan‐African Trial Network

Abstract BACKGROUND The global demand for soybeans is increasing rapidly, with projections indicating an escalation of 70–80 million metric tons over the next decade. Sub‐Saharan Africa (SSA) contributes significantly to this growth, with soybean production increasing by 6.8% per year, outpacing the global average increase of 4.7%. Despite the expansion, soybean productivity in Africa remains less than half of the global average. This yield gap is largely due to diseases and pests, such as soybean rust, which can be particularly severe. Effective management of soybean rust depends on several factors, including resistant cultivars. However, there has been limited information on the rust‐resistance levels of African cultivars. To address this gap, the Pan‐African Trial network conducted soybean varietal trials across diverse locations. RESULT Analyzing data from 370 individual trials conducted between 2015–2022, the network identified 81 cultivars with sufficient rust‐resistance data. Six cultivars including, Black Hawk, Dundee, Egret, Heron, Ibis, and Peka 06 were found to be resistant, and 12 were classified as tolerant. CONCLUSION This research is a significant step forward in improving soybean productivity in Africa, and further assessments are being undertaken to address other crop production challenges in the region. © 2025 Society of Chemical Industry.

Favoretto, Vitor Rampazzo [Cenex Harvest States (C↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-Ne2 Mead - irrigated maize-soybean rotation site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ne2 Mead - irrigated maize-soybean rotation site. This is the FLUXNET version of the carbon flux data for the site US-Ne2 Mead - irrigated maize-soybean rotation site produced by applying the standard ONEFlux (1F) software. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Eastern Nebraska Research, Extension and Education Center near Mead, Nebraska. This site is irrigated with a center pivot system. Prior to the initiation of the study, the irrigated site had a 10-yr history of maize-soybean rotation under no-till management. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since this tillage operation, the site has been under no-till management in a maize-soybean rotation (maize odd years and soybean even years). There was a brief period due to an intercomparison study from 2010 to 2013 when fall conservation tillage was performed and maize (not soybean) was planted in 2010 and 2012. The management reverted to a strictly no-till maize-soybean crop rotation after 2014.

Suyker, Andy [University of Nebraska - Lincoln]↗
NASA NTRS1987

Oxidative processes in soybean and pea seeds: effect of light, temperature, and water content

Oxidative processes are probable determinants of longevity of seeds in storage. Measurements of actual oxygen uptake rates were made for soybean and pea seeds as a comparison of short and long lived seeds when light, temperature, and moisture contents were varied. In both peas and soybeans, the oxygen uptake was depressed at low temperatures (<16 degrees C) and low water contents (< 0.25 gram H2O per gram dry weight). Apparent activation energies under these conditions are very high, while apparent activation energies of seeds at higher water contents and at temperatures greater than 22 degrees C are much less. Light enhances the level of oxygen uptake in pea, but reduces the level of oxygen uptake in soybean. The complexities of the interactions of oxygen uptake with environmental conditions in soybean compared to pea suggest that oxidative processes occur in soybean at low water contents, but are essentially absent in pea. It is suggested that the additional oxidative processes in soybean with moisture contents between 0.10 and 0.24 gram per gram may contribute to the poorer longevity of soybean seed compared to pea seed.

NASA Program Space Biology↗
NASA NTRSDate not supplied

Active/Passive Remote Sensing of a Mature Soybean Canopy at L-band

This paper reports on development of a scattering model of a soybean canopies at L-band. The scattering model will be used for active and passive remote sensing of soybean plants with an emphasis on mature soybeans where the presence of pods is important to the observed microwave signal. The active problem is treated using the Distorted Born Approximation (DBA) and the passive problem is analyzed using Peake's method. These results are compared with field measurements made in 2012 by the truck-mounted ComRAD system, which is a combined radar and radiometer instrument operating at L-band. Investigation of backscatter from the soybean canopy shows good agreement between the radar measurement data and modeling results. The results also indicate that the L-band radar backscatter can be used to monitor both the soil moisture and the growth of the soybean pods. Past passive modeling efforts have not considered soybeans late in the growing season when pods are important. A new passive radiation model of soybean canopy will be developed based on the backscatter model.

Yiwen Zhou↗
NASA NTRS2020

The Backscattering Contribution of Soybean Pods at L-band

L-band (1.25 GHz) radar measurements of a soybean canopy indicate that the emergence of seed pods is a significant contributor to the backscatter during the late stages of the growing season. In order to validate the measured data, a realistic scattering model of the soybean canopy is developed. The parameters of the soybean canopy and underlying soil used in the model vary over the growing season based on in situ measurements. Scattering amplitudes for soybean leaves are modeled analytically by using a thin disk approximation; stem and pods are jointly modeled using a numerical electromagnetic field solver. These scattering amplitudes are together incorporated into a coherent scattering model to obtain the backscattering coefficient for VV- and HH-polarizations. The modeling results show good agreement with the radar field measurements, having RMSEs of 0.51 dB for VV-pol and 1.1 dB for HH-pol. Both measured data and modeled results show that the change of soil moisture can be accurately monitored by L-band backscatter. It is also found that the difference between HH- and VV-polarized backscatter increases as the size of the soybean pods becomes larger. A method is developed here to estimate the number of pods in a soybean canopy based on polarimetric radar backscatter at L-band.

Radar backscatter↗
DOE OSTI2024

Soybean genomics research community strategic plan: A vision for 2024–2028

Abstract This strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [Glycine max(L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024–2028). This work is the result of deliberations among over 50 soybean researchers during a 2‐day workshop in St Louis, MO, USA, at the end of 2022. The plan is divided into seven traditional areas/disciplines: Breeding, Biotic Interactions, Physiology and Abiotic Stress, Functional Genomics, Biotechnology, Genomic Resources and Datasets, and Computational Resources. One additional section was added, Training the Next Generation of Soybean Researchers, when it was identified as a pressing issue during the workshop. This installment of the soybean genomics strategic plan provides a snapshot of recent progress while looking at future goals that will improve resources and enable innovation among the community of basic and applied soybean researchers. We hope that this work will inform our community and increase support for soybean research.

Genetics & Heredity↗
NASA NTRS1999

Safety Analysis of Soybean Processing for Advanced Life Support

Soybeans (cv. Hoyt) is one of the crops planned for food production within the Advanced Life Support System Integration Testbed (ALSSIT), a proposed habitat simulation for long duration lunar/Mars missions. Soybeans may be processed into a variety of food products, including soymilk, tofu, and tempeh. Due to the closed environmental system and importance of crew health maintenance, food safety is a primary concern on long duration space missions. Identification of the food safety hazards and critical control points associated with the closed ALSSIT system is essential for the development of safe food processing techniques and equipment. A Hazard Analysis Critical Control Point (HACCP) model was developed to reflect proposed production and processing protocols for ALSSIT soybeans. Soybean processing was placed in the type III risk category. During the processing of ALSSIT-grown soybeans, critical control points were identified to control microbiological hazards, particularly mycotoxins, and chemical hazards from antinutrients. Critical limits were suggested at each CCP. Food safety recommendations regarding the hazards and risks associated with growing, harvesting, and processing soybeans; biomass management; and use of multifunctional equipment were made in consideration of the limitations and restraints of the closed ALSSIT.

Hentges, Dawn L.↗
NASA NTRS1990

Photomorphogenesis and photoassimilation in soybean and sorghum grown under broad spectrum or blue-deficient light sources

The role of blue light in plant growth and development was investigated in soybean (Glycine max [L.] Merr. cv Williams) and sorghum (Sorghum bicolor [L.] Moench. cv Rio) grown under equal photosynthetic photon fluxes (approximately 500 micromoles per square meter per second) from broad spectrum daylight fluorescent or blue-deficient, narrow-band (589 nanometers) low pressure sodium (LPS) lamps. Between 14 and 18 days after sowing, it was possible to relate adaptations in photosynthesis and leaf growth to dry matter accumulation. Soybean development under LPS light was similar in several respects to that of shaded plants, consistent with an important role for blue light photoreceptors in regulation of growth response to irradiance. Thus, soybeans from LPS conditions partitioned relatively more growth to leaves and maintained higher average leaf area ratios (mean LAR) that compensated lower net assimilation rates (mean NAR). Relative growth rates were therefore comparable to plants from daylight fluorescent lamps. Reductions in mean NAR were matched by lower rates of net photosynthesis (A) on an area basis in the major photosynthetic source (first trifoliolate) leaf. Lower A in soybean resulted from reduced leaf dry matter per unit leaf area, but lower A under LPS conditions in sorghum correlated with leaf chlorosis and reduced total nitrogen (not observed in soybean). In spite of a lower A, mean NAR was larger in sorghum from LPS conditions, resulting in significantly greater relative growth rates (mean LAR was approximately equal for both light conditions). Leaf starch accumulation rate was higher for both species and starch content at the end of the dark period was elevated two- and three-fold for sorghum and soybean, respectively, under LPS conditions. Possible relations between starch accumulation, leaf export, and plant growth in response to spectral quality were considered.

NASA Discipline Life Support Systems↗
NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗
DOE OSTI2025

Unlocking soybean meal pectin recalcitrance using a multi-enzyme cocktail approach

Pectin is a complex plant heteropolysaccharide whose structure and function differ depending on its source. In animal feed, breaking down pectin is essential, as its presence increases feed viscosity and reduces nutrient absorption. Soybean meal, a protein-rich poultry feed ingredient, contains significant amounts of pectin, the structure of which remains unclear. Consequently, the enzyme activities required to degrade soybean meal pectin and how they interact are still open questions. In this study, we produced 15 recombinant fungal carbohydrate-active enzymes (CAZymes) identified from fungal secretomes acting on pectin. After observing that these enzymes were not active on soybean meal pectin when used alone, we developed a semi-miniaturized method to evaluate their effect as multi-activity cocktails. We designed and tested 12 enzyme pools, containing up to 15 different CAZymes, using several hydrolysis markers. Thanks to our multiactivity enzymatic approach combined with a Pearson correlation matrix, we identified 10 fungal CAZymes efficient on soybean meal pectin, 9 of which originate from Talaromyces versatilis. Based on enzyme specificity and linkage analysis, we propose a structural model for soybean meal pectin. Our findings underscore the importance of combining CAZymes to improve the degradation of agricultural co-products.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Transfer learning-based soybean LAI estimations by integrating PROSAIL, UAV, and PlanetScope imagery

Accurate Leaf Area Index (LAI) estimations at the soybean plot scale is achievable using high-resolution Unmanned Aerial Vehicle (UAV) imagery and field measurement samples. However, the limited coverage of UAV flights restricts large-scale remote sensing monitoring in expansive soybean fields. This study leverages the broad coverage and 3-m resolution of PlanetScope satellite imagery to extend LAI prediction from UAV to satellite scales through transfer learning, using UAV-scale LAI estimates as a benchmark to validate cross-scale consistency. To address this challenge, this study proposed the LAI-TransNet, a two-stage transfer learning framework designed for precise and scalable soybean LAI prediction across large areas, demonstrating its effectiveness in cross-scale monitoring. In Stage 1, a UAV-scale benchmark is established using PROSAIL-simulated UAV reflectance data (UAV-Sim) and field-measured soybean LAI. Traditional machine learning, deep learning, and transfer learning models are trained on a hybrid UAV-Sim and field-measured dataset (UAV-Sim_Measured), with the transfer learning model CNN-TL, fine-tuned using pre-trained weights derived from UAV-Sim, achieving the highest accuracy (R 2 = 0.81, RMSE = 0.64 m 2 /m 2 , rRMSE = 11.5 %). In Stage 2, LAI-TransNet is developed by fine-tuning the CNN-TL model on PlanetScope simulated data (PS-Sim), preprocessed via cross-domain mapping to align UAV and satellite spectral features. Real PlanetScope imagery is corrected for reflectance consistency with reference to UAV imagery spectral profiles. LAI-TransNet outperforms other deep learning models trained directly on PS-Sim (R 2 = 0.69 vs. 0.60–0.63), ensuring robust cross-scale consistency. In conclusion, by bridging UAV and satellite scales, LAI-TransNet enables large-scale soybean LAI monitoring, enhancing precision agriculture management through improved monitoring with the PlanetScope imagery.

Leaf area index (LAI)↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-Ne3 Mead - rainfed maize-soybean rotation site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site. This is the FLUXNET version of the carbon flux data for the site US-Ne3 Mead - rainfed maize-soybean rotation site produced by applying the standard ONEFlux (1F) software. Site Description - The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center near Mead, Nebraska. While the other two sites are equipped with irrigation systems, this site relies on rainfall. A tillage operation (disking) was done just prior to the 2001 planting to homogenize the top 0.1 m of soil, incorporate P and K fertilizers, as well as previously accumulated surface residues. Since initiation of the study in 2001, this site has been under a strictly no-till, maize-soybean rotation (maize odd years and soybean even years).

Suyker, Andy [University of Nebraska - Lincoln]↗
NASA NTRS1975

Radar backscatter properties of milo and soybeans

The radar backscatter from fields of milo and soybeans was measured with a ground based radar as a function of frequency (8-18 GHz), polarization (HH and VV) and angle of incidence (0 deg-70 deg) during the summer of 1974. Supporting ground truth was gathered contemporaneously with the backscatter data. At nadir sigma deg of milo correlated highly, r = 0.96, with soil moisture in the milo field at 8.6 GHz but decreased to a value of r = 0.78 at a frequency of 17.0 GHz. Correlation studies of the variations of sigma deg with soil moisture in the soybean fields were not possible due to a lack of a meaningful soil moisture dynamic range. At the larger angles of incidence, however, sigma deg of soybeans did appear to be dependent on precipitation. It is suggested this phenomenon was caused by the rain altering plant geometry. In general sigma deg of both milo and soybeans had a relatively small dynamic range at the higher angles of incidence and showed no significant dependence on the measured crop parameters.

Bush, T. F.↗