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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Investigation of the chemical interface in the soybean–aphid and rice–bacteria interactions using MALDI-mass spectrometry imaging

Mass spectrometry imaging (MSI) is an emerging technology for high-resolution plant biology. It has been utilized to study plant–pest interactions, but limited to the surface interfaces. Here we expand the technology to explore the chemical interactions occurring inside the plant tissues. Two sample preparation methods, imprinting and fracturing, were developed and applied, for the first time, to visualize internal metabolites of leaves in matrix-assisted laser desorption ionization (MALDI)-MSI. This is also the first time nanoparticle-based ionization was implemented to ionize diterpenoid phytochemicals that were difficult to analyze with traditional organic matrices. The interactions between rice–bacterium and soybean–aphid were investigated as two model systems to demonstrate the capability of high-resolution MSI based on MALDI. Localized molecular information on various plant- or pest-derived chemicals provided valuable insight for the molecular processes occurring during the plant–pest interactions. Basically, salicylic acid and isoflavone based resistance was visualized in the soybean–aphid system and antibiotic diterpenoids in rice–bacterium interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Biorenewable tough blends of polylactide and acrylated epoxidized soybean oil compatibilized by a polylactide star polymer

Polylactide (PLA), a commercially available thermoplastic derived from plant sugars, finds applications in consumer products, disposable packaging, and textiles, among others. The widespread application of this material is limited by its brittleness, as evidenced by low tensile elongation at break, impact strength, and fracture toughness. Herein, a multifunctional vegetable oil, acrylated epoxidized soybean oil (AESO), was investigated as a biodegradable, renewable additive to improve the toughness of PLA. AESO was found to be a highly reactive oil, providing a dispersed phase with tunable properties in which the acrylate groups underwent cross-linking at the elevated temperatures required for processing the blends. Additionally, the presence of hydroxyl groups on AESO provided two routes for compatibilization of PLA/AESO blends: (1) reactive compatibilization through the transesterification of AESO and PLA and (2) synthesis of a PLA star polymer with an AESO core. The morphological, thermal, and mechanical behaviors of PLA/oil blends were investigated, in which the dispersed oil phase consisted of AESO, soybean oil (SYBO), or a 50/50 mixture of AESO/SYBO. The oil additives were found to toughen the PLA matrix, with significant enhancements in the elongation at break and tensile toughness values, while maintaining the glass transition temperature of neat PLA. Specifically, the blend containing PLA, AESO, SYBO, and the PLA star polymer was found to exhibit a uniform oil droplet size distribution with small average droplet size and interparticle distance, resulting in the greatest enhancements of PLA tensile properties with no observable plasticization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Potassium and Calcium Isotopic Fractionation by Plants (Soybean [Glycine max], Rice [Oryza sativa], and Wheat [Triticum aestivum])

Here, we conducted hydroponic experiments growing soybean (Glycine max), rice (Oryza sativa), and wheat (Triticum aestivum) under K and Ca replete conditions to establish the degree of K isotopic fractionation by plants, and compare the isotopic fractionation of Ca and K. Each of the test plants displays fractionation relative to the growth solution favoring the light isotopes of K and Ca. The average δ 41 K values of the roots from the three plant species were similar, and have an overall average of -0.55 ± 0.24‰ 2s, while the overall average δ 44 Ca for roots is -0.67 ± 0.44. For leaves, the overall average of δ 41 K is -0.97 ± 0.4‰, compared to an overall average leaf δ 44 Ca of -0.83 ± 0.09‰. In the case of the soybean plants, the lightest K and Ca occurs in the stems with average δ 41 K of -1.31 ± 0.40‰ 2s and average δ 44 Ca of -1.20 ± 0.19 ‰ 2s. We present a simple box model involving the relative fluxes of K and its isotopic fractionation that reproduces our K isotopic observations and suggests a fractionation of ~0.8‰ with K uptake from solution by roots. Finally, directly comparing the per amu fractionation of K and Ca reveals an average factor of 2.05 ± 0.50 2s greater fractionation of K isotopes which may reflect their different roles and behaviors in plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Observed metabolic asymmetry within soybean root nodules reflects unexpected complexity in rhizobacteria-legume metabolite exchange

Abstract In this study, the three-dimensional spatial distributions of a number of metabolites involved in regulating symbiosis and biological nitrogen fixation (BNF) within soybean root nodules were revealed using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). While many metabolites exhibited distinct spatial compartmentalization, some metabolites were asymmetrically distributed throughout the nodule (e.g., S-adenosylmethionine). These results establish a more complex metabolic view of plant–bacteria symbiosis (and BNF) within soybean nodules than previously hypothesized. Collectively these findings suggest that spatial perspectives in metabolic regulation should be considered to unravel the overall complexity of interacting organisms, like those relating to associations of nitrogen-fixing bacteria with host plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility

Abstract The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m 2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Radiance-based NIR v as a proxy for GPP of corn and soybean

Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIR v,Rad ), defined as the product of observed NIR radiance and normalized difference vegetation index (NDVI), can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIR v,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIR v,Ref ), enhanced vegetation index (EVI), and far-red solar-induced fluorescence (SIF760). The strong linear relationship between NIR v,Rad and absorbed photosynthetically active radiation by green leaves (APAR green ), and that between APAR green and GPP, explain the good NIR v,Rad -GPP relationship. The NIR v,Rad -GPP relationship is robust and consistent across sites. The scalability and simplicity of NIR v,Rad indicate a great potential to estimate daily or sub-daily GPP from high-resolution and/or long-term satellite remote sensing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Expression of cyanobacterial FBP/SBPase in soybean prevents yield depression under future climate conditions

Predictions suggest that current crop production needs to double by 2050 to meet global food and energy demands. Based on theory and experimental studies, overexpression of the photosynthetic enzyme sedoheptulose-1,7-bisphosphatase (SBPase) is expected to enhance C3 crop photosynthesis and yields. Here we test how expression of the cyanobacterial, bifunctional fructose-1,6/sedoheptulose-1,7-bisphosphatase (FBP/SBPase) affects carbon assimilation and seed yield (SY) in a major crop (soybean, Glycine max). For three growing seasons, wild-type (WT) and FBP/SBPase-expressing (FS) plants were grown in the field under ambient (400 μmol mol-1) and elevated (600 μmol mol-1) CO2 concentrations [CO2] and under ambient and elevated temperatures (+2.7 °C during daytime, +3.4 °C at night) at the SoyFACE research site. Across treatments, FS plants had significantly higher carbon assimilation (4–14%), Vc,max (5–8%), and Jmax (4–8%). Under ambient [CO2], elevated temperature led to significant reductions of SY of both genotypes by 19–31%. However, under elevated [CO2] and elevated temperature, FS plants maintained SY levels, while the WT showed significant reductions between 11% and 22% compared with plants under elevated [CO2] alone. These results show that the manipulation of the photosynthetic carbon reduction cycle can mitigate the effects of future high CO2 and high temperature environments on soybean yield.

Plant Sciences↗
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↗
DOE OSTI2022

Spatial mapping of plant N-glycosylation cellular heterogeneity inside soybean root nodules provided insights into legume-rhizobia symbiosis

Although ubiquitously present, information on the function of complex N-glycan posttranslational modification in plants is very limited and it is often neglected. In this work, we adopted an enzyme-assisted matrix-assisted laser desorption/ionization mass spectrometry imaging strategy to visualize the distribution and identity of N-glycans in soybean root nodules at a cellular resolution. We additionally performed proteomics analysis to probe the potential correlation to proteome changes during symbiotic rhizobia-legume interactions. Our ion images reveal that intense N-glycosylation occurs in the sclerenchyma layer, and inside the infected cells within the infection zone, while morphological structures such as the cortex, uninfected cells, and cells that form the attachment with the root are less N-glycosylated. Notably, we observed different N-glycan profiles between soybean root nodules infected with wild type rhizobia and those infected with mutant rhizobia incapable of efficiently fixing atmospheric nitrogen. The majority of complex N-glycan structures, particularly those with characteristic Lewis-a epitopes, are overexpressed in the mutant nodules. Our proteomic results revealed that these glycans likely originated from proteins that maintain the redox balance crucial for proper nitrogen fixation, but also from enzymes involved in N-glycan and phenylpropanoid biosynthesis. These findings indicate possible involvement of Lewis-a glycans in these critical pathways during legume-rhizobia symbiosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Assessment of canopy chlorophyll content retrieval in maize and soybean: Implications of hysteresis on the development of generic algorithms

Here, canopy chlorophyll content (Chl) closely relates to plant photosynthetic capacity, nitrogen status and productivity. The goal of this study is to develop remote sensing techniques for accurate estimation of canopy Chl during the entire growing season without re-parameterization of algorithms for two contrasting crop species, maize and soybean. These two crops represent different biochemical mechanisms of photosynthesis, leaf structure and canopy architecture. The relationships between canopy Chl and reflectance, collected at close range and resampled to bands of the Multi Spectral Instrument (MSI) aboard Sentinel-2, were analyzed in samples taken across the entirety of the growing seasons in three irrigated and rainfed sites located in eastern Nebraska between 2001 and 2005. Crop phenology was a factor strongly influencing the reflectance of both maize and soybean. Substantial hysteresis of the reflectance vs. canopy Chl relationship existed between the vegetative and reproductive stages. The effect of the hysteresis on vegetation indices (VI), applied for canopy Chl estimation, depended on the bands used and their formulation. The hysteresis greatly affected the accuracy of canopy Chl estimation by widely-used VIs with near infrared (NIR) and red reflectance (e.g., normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and simple ratio (SR)). VIs that use red edge and NIR bands (e.g., red edge chlorophyll index (CIred edge), red edge NDVI and the MERIS terrestrial chlorophyll index (MTCI)) were minimally affected by crop phenology (i.e., they exhibited little hysteresis) and were able to accurately estimate canopy Chl in two crops without algorithm re-parameterization and, thus, were found to be the best candidates for generic algorithms to estimate crop Chl using the surface reflectance products of MSI Sentinel-2.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1978

Monitoring corn and soybean crop development by remote sensing techniques

A system for spectrally monitoring the stages of crop development for corn and soybeans based upon red and photographic infrared spectral radiances is proposed. The red and photographic infrared spectral radiance, highly correlated with the green leaf area index or green leaf biomass, enable nondestructive monitoring of the crop canopy throughout the growing season. Five distinct periods are apparent which are related to crop development for corn and soybeans.

Tucker, C. J.↗
NASA NTRS1979

Assessing soybean leaf area and leaf biomass by spectral measurements

Red and photographic infrared spectral radiances were correlated with soybean total leaf area index, green leaf area index, chlorotic leaf area index, green leaf biomass, chlorotic leaf biomass, and total biomass. The most significant correlations were found to exist between the IR/red radiance ratio data and green leaf area index and/or green leaf biomass (r squared equals 0.85 and 0.86, respectively). These findings demonstrate that remote sensing data can supply information basic to soybean canopy growth, development, and status by nondestructive determination of the green leaf area or green leaf biomass.

Holben, B. N.↗
NASA NTRS1980

Spectral assessment of soybean leaf area and leaf biomass

Red and photographic infrared spectral radiance have been correlated with soybean total leaf area index, green leaf area index, chlorotic area index, green leaf biomass, chlorotic leaf biomass, and total biomass. The most significant correlations were found to exist between the spectral data and green leaf area index and/or green leaf biomass. These findings demonstrate that ground based remote sensing data can supply information basic to soybean canopy growth, development, and status by non-destructive determination of the green leaf area or green leaf biomass.

Holben, B. N.↗
NASA NTRS1980

Evaluation of results of US corn and soybeans exploratory experiment: Classification procedures verification test

The classification procedure utilized in making crop proportion estimates for corn and soybeans using remotely sensed data was evaluated. The procedure was derived during the transition year of the Large Area Crop Inventory Experiment. Analysis of variance techniques were applied to classifications performed by 3 groups of analysts who processed 25 segments selected from 4 agrophysical units (APU's). Group and APU effects were assessed to determine factors which affected the quality of the classifications. The classification results were studied to determine the effectiveness of the procedure in producing corn and soybeans proportion estimates.

Carnes, J. G.↗
NASA NTRS1981

Users manual for the US baseline corn and soybean segment classification procedure

A user's manual for the classification component of the FY-81 U.S. Corn and Soybean Pilot Experiment in the Foreign Commodity Production Forecasting Project of AgRISTARS is presented. This experiment is one of several major experiments in AgRISTARS designed to measure and advance the remote sensing technologies for cropland inventory. The classification procedure discussed is designed to produce segment proportion estimates for corn and soybeans in the U.S. Corn Belt (Iowa, Indiana, and Illinois) using LANDSAT data. The estimates are produced by an integrated Analyst/Machine procedure. The Analyst selects acquisitions, participates in stratification, and assigns crop labels to selected samples. In concert with the Analyst, the machine digitally preprocesses LANDSAT data to remove external effects, stratifies the data into field like units and into spectrally similar groups, statistically samples the data for Analyst labeling, and combines the labeled samples into a final estimate.

Horvath, R.↗
NASA NTRS1980

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

Thompson, D. R.↗