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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
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 NTRS1985

Application of Thematic Mapper data to corn and soybean development stage estimation

A model, utilizing direct relationship between remotely sensed spectral data and the development stage of both corn and soybeans has been proposed and published previously (Badhwar and Henderson, 1981; and Henderson and Badhwar, 1984). This model was developed using data acquired by instruments mounted on trucks over field plots of corn and soybeans as well as satellite data from Landsat. In all cases, the data was analyzed in the spectral bands equivalent to the four bands of Landsat multispectral scanner (MSS). In this study the same model has been applied to corn and soybeans using Landsat-4 Thematic Mapper (TM) data combined with simulated TM data to provide a multitemporal data set in TM band intervals. All data (five total acquisitions) were acquired over a test site in Webster County, Iowa from June to October 1982. The use of TM data for determining development state is as accurate as with Landsat MSS and field plot data in MSS bands. The maximum deviation of 0.6 development stage for corn and 0.8 development stage for soybeans is well within the uncertainty with which a field can be estimated with procedures used by observers on the ground in 1982.

Badhwar, G. D.↗
NASA NTRS2001

Nutrient Stress Detection in Corn, Using Neural Networks and AVIRIS Hyperspectral Imagery

The US Department of Agriculture (USDA) Agricultural Research Service (ARS) Variable Rate (VRAT) Nitrogen Application site in Shelton, Nebraska, represents a well-documented, corn-growing quarter section. The USDA VRAT site is used to systematically study nutrient stress in corn by varying sub-plot application of fertilizer. The field has four replicates of five blocks that vary by nitrogen treatment from 0-kg/ha to 200-kg/ha in 50-kg/ha increments. The treatment blocks are set out in a randomized, complete block design. Typically, the VRAT is planted in a ridge till, monoculture corn and is watered by a central pivot irrigation system on a three-day period. Since water stress can increase spectral reflectance from corn leaves, it is important that the N-application plots be adequately watered so that only nutrient-related stress will predominate. A figure shows imagery of the USDA VRAT site with the fertilizer amounts for each block shown. Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery was acquired over the Shelton, Nebraska, VRAT site on July 22, 1999. The overflight produced 3-meter pixels with 224 spectral bands. Ground personnel supported the mission with measurements at the time of the overflight. The image data was pre-processed at JPL before being sent out to an investigator. The data arrived radiometrically corrected, allowing ready application of an atmospheric correction procedure. The Atmosphere Removal Program (ATREM) was used to perform an atmospheric correction. The AVIRIS imagery after ATREM correction was output as relative reflectance. This relative reflectance file was scaled by an empirical line procedure to provide reflectances that matched closely those measured in the field.

Estep, Lee↗
NASA NTRS2008

Temporal Stability of Surface Roughness Effects on Radar Based Soil Moisture Retrieval During the Corn Growth Cycle

A representative soil surface roughness parameterization needed for the retrieval of soil moisture from active microwave satellite observation is difficult to obtain through either in-situ measurements or remote sensing-based inversion techniques. Typically, for the retrieval of soil moisture, temporal variations in surface roughness are assumed to be negligible. Although previous investigations have suggested that this assumption might be reasonable for natural vegetation covers (Moran et al. 2002, Thoma et al. 2006), insitu measurements over plowed agricultural fields (Callens et al. 2006) have shown that the soil surface roughness can change considerably over time. This paper reports on the temporal stability of surface roughness effects on radar observations and soil moisture retrieved from these radar observations collected once a week during a corn growth cycle (May 10th - October 2002). The data set employed was collected during the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) field campaign covering this 2002 corn growth cycle and consists of dual-polarized (HH and VV) L-band (1.6 GHz) acquired at view angles of 15, 35, and 55 degrees. Cross-polarized L baud radar data were also collected as part of this experiment, but are not used in the analysis reported on here. After accounting for vegetation effects on radar observations, time-invariant optimum roughness parameters were determined using the Integral Equation Method (IEM) and radar observations acquired over bare soil and cropped conditions (the complete radar data set includes entire corn growth cycle). The optimum roughness parameters, soil moisture retrieval uncertainty, temporal distribution of retrieval errors and its relationship with the weather conditions (e.g. rainfall and wind speed) have been analyzed. It is shown that over the corn growth cycle, temporal roughness variations due to weathering by rain are responsible for almost 50% of soil moisture retrieval uncertainty depending on the sensing configuration. The effects of surface roughness variations are found to be smallest for observations acquired at a view angle of 55 degrees and HH polarization. A possible explanation for this result is that at 55 degrees and HH polarization the effect of vertical surface height changes on the observed radar response are limited because the microwaves travel parallel to the incident plane and as a result will not interact directly with vertically oriented soil structures.

Joseph, A.T.↗
DOE OSTI2021

Technical and economic feasibility of an integrated ethanol and anthocyanin coproduction process using purple corn stover

The coproduction of high-value anthocyanin extract in the cellulosic ethanol process would diversify the co-product market, increase revenue, and potentially improve the economics of the process. The high anthocyanin concentration in the cob and structural carbohydrates in residual stover make purple corn stover an attractive source for anthocyanin and ethanol coproduction. In this study, we aimed to develop simulation models for processes integrating ethanol production and anthocyanin extraction using purple corn stover, to evaluate their techno-economic feasibility, and to compare their performance with the conventional ethanol production process using corn stover. The annual ethanol production for plants processing 2000 MT dry feedstock / day was 148.6 million L/year for the integrated processes compared with 222.6 million L/year for the conventional process. Anthocyanin production in the modified processes using dilute acid-based and water-based anthocyanin extraction processes was 1779 and 1099 MT/year, respectively. Capital investments for the integrated processes ($\$448.1$ to $\$443.8$ million) were higher than the conventional process ($\$371.9$ million). Due to high revenue from anthocyanin extract, the ethanol production cost for the integrated process using acid-based anthocyanin extraction ($\$0.36$/L) was 34.5% lower than conventional ethanol production ($\$0.55$/L). The ethanol production cost for the integrated process using water-based anthocyanin extraction ($\$0.68$/L) was higher than conventional ethanol production due to low ethanol and anthocyanin yields. The minimum ethanol selling price for the integrated process using acid-based anthocyanin extraction ($\$0.65$/L) was also lower than the conventional process ($\$0.72$/L), indicating an improvement in economic performance.

09 BIOMASS FUELS↗
DOE OSTI2025

Cradle-to-Gate greenhouse gas emissions of the production of ethylene from U.S. Corn ethanol and comparison to fossil-derived ethylene production

Conventional ethylene production heavily depends on fossil-derived feedstocks via steam cracking, a very energy- and emission-intensive process. Researchers have been exploring alternatives to reduce CO 2 emissions including producing ethylene from biobased feedstocks. This paper evaluates the cradle-to-gate greenhouse gas (GHG) emissions of bioethylene produced from U.S. corn ethanol. The analysis includes different pathways for the dehydration of corn ethanol to ethylene and co-processing routes via fluid catalytic cracking (FCC) processes. For the FCC co-processing route carbon-14 analysis is used to determine bioethanol yields. A 127% reduction in life cycle GHG emissions of bioethylene is estimated compared to fossil-derived ethylene for the base case. Additional case studies are also discussed to understand the reduction of GHG emissions due to sustainable corn farming and renewable power use, biogenic carbon capture, and fuel switch with biofuels at the ethanol plant, and its impact on bioethylene GHG emissions.

carbon footprint↗
DOE OSTI2025

Unveiling Feedstock Variability: Insights into Corn Stover Conversion - Part I: Physicochemical Properties and Self-Degradation

Transforming agricultural waste into biofuels and bioproducts is crucial to advancing a low-carbon bioeconomy. However, the inherent variability in the composition and quality introduces uncertainties in the conversion efficiency and poses challenges in process development. Through integrating a high-throughput conversion system, material characterization techniques, and advanced data analysis tools, this study investigates the variability of corn stover and its subsequent impacts on carbohydrate conversion. The findings reveal that indoor storage substantially reduces the moisture and ash content and soil contamination, while other properties remain largely unchanged. Self-degradation due to microbial activity during storage decreases the carbohydrate content of corn stover but enhances glucose and xylose yields. A negative correlation is observed between sugar yields and lignin content across samples with varying ash and moisture content. The inhibitory effect of lignin diminishes in self-degraded samples likely due to the disrupted cell wall structure. Although self-degradation slightly increases cellulose crystallinity, no strong correlation was observed between the crystallinity and sugar yield. Hot water pretreatment under mild conditions effectively mitigates inherent variability, consistently improving the sugar yield from corn stover by up to 50%. By elucidating the feedstock variability and its impact on convertibility, these findings offer valuable insights into appropriate feedstock handling and management, highlighting potential strategies to address variability challenges.

09 BIOMASS FUELS↗
DOE OSTI2022

Process-based modeling of soil nitrous oxide emissions from United States corn fields under different management and climate scenarios coupled with evaluation using regional estimates

Direct emissions of soil nitrous oxide during a growing season (N 2 O gs ) can be quantified with process-based models considering interactions between management, climate, and soil moisture when key data are available. We used an adapted “parameterized CENTURY/DAYCENT-model” ( p CENTURY) calibrated with crop growth and soil organic matter decay coefficients at the county-level for the estimation of N 2 O gs in the United States Corn Belt. Model estimated N 2 O-emissions from corn-based biofuels scenarios considering crop rotation, fertilizer inputs, tillage, and weather were compared against meta-summary of field observations from 55 studies. Both model and meta-summary ranked N 2 O gs -emissions to be corn > wheat > soybean phase while model likely underestimated cover crop N 2 O gs -emissions. The N 2 O gs -emissions and the associated emission factors (EFs) were modeled and summarized to be greater after anhydrous ammonia than urea application and from conventional tilled than non-tilled fields. Modeled and observed N 2 O gs -emissions after organic and inorganic fertilizer amendment did not differ due to high variability associated with the treatments. However, the organic fertilizer associated EFs were greater according to meta-summary data because of N input rates. Regionalized weather scenarios indicate hotspots for N 2 O gs -emissions can occur where crop N uptake is limited during dry years and in eastern states also during normal or wet seasons. The p CENTURY-derived N 2 O gs EFs (0.91 ± 0.19%) for counties investigated were only slightly lower than literature (1.07 ± 0.57%) or Tier-1 (1%) values. Our preliminary evaluation of regional soil moisture estimates showed reasonable agreement between monthly soil moisture estimates and the North American Soil Moisture Dataset during the growing season, but overestimation of soil moisture in winter-spring can influence the estimates of annual N 2 O emissions so future work is needed to calibrate soil moisture-associated model parameters. Our work provided scenario-based estimates of climate and management impacts on soil N 2 O gs -emissions together with valuable spatial insights into EFs that will be improved by more accurate information of fertilizer inputs and more temporally refined model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Techno‐economic assessment of single‐stream feedstock logistics supply chain for corn stover and grain

Abstract The state‐of‐technology for corn stover harvest is a multi‐pass system that collects the stover after grain harvest. An alternative is a single‐stream system where the grain and stover are harvested as a bulk material co‐stored and preserved by anerobic fermentation, and finally, co‐transported to a biorefinery. In the present work, four single‐pass whole‐plant bulk systems were compared with a conventional multi‐pass bale system. The single‐stream systems consisted of the harvest of corn grain and a portion of the stover fraction. Four machine configurations were simulated. This work predicted that a multi‐pass bale system would result in a material cost of 111.80 $2021 Mg –1 stover DM delivered to the biorefinery gate. Alternatively, the lowest cost single‐stream system was the self‐propelled forage harvester (SPFH) configured with the whole‐plant header, which delivered feedstock for 74.76 $2021 Mg stover DM –1 . In addition to machine configuration, a sensitivity analysis was performed to understand important drivers of feedstock cost. These analyses revealed that feedstock cost increased with moisture content, fertilizer price, and biorefinery size, and decreased with harvest season length, crop yield, and grower participation. This work demonstrated that single‐stream systems could reduce corn stover feedstock costs in comparison with state‐of‐technology systems. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2025

Understanding the Effects of Ash Content on Various Pretreatment Technologies for the Bioconversion of Corn Stover

Here, the study aimed to examine the effects of adding biomass ash on the biochemical processes involved in fermentable sugar production. Corn stover was pretreated using several methods—hot water, dilute acid, alkaline, γ-valerolactone, and ionic liquid methods, each examined with ash loadings of 7.18% and 21.07%. The findings demonstrated that increased ash content adversely affected both pretreatment and enzymatic hydrolysis. Specifically, the total sugar yield was 3 to 16% lower at the higher ash content across all pretreatment methods, and up to 4.01% lower during enzymatic hydrolysis. For acidic pretreatment, the sugar yield decreased as ash content increased. In contrast, ash content had a lesser impact on alkaline pretreatment compared to acidic pretreatment. For example, using corn stover with an ash content as high as 22.65% resulted in only a 2.90% decrease in total sugar yield compared to corn stover without added ash. Further, the primary reasons for the reduced sugar yield in higher ash biomass during acidic pretreatments were likely the neutralizing effect of the ash and decreased acid access to the substrates. During enzymatic hydrolysis, ash reduced the sugar yield by limiting enzyme access to cellulose.

09 BIOMASS FUELS↗
DOE OSTI2021

New strategy for liquefying corn stover pellets

The movement of solid material into and between unit operations within a biorefinery is a bottleneck in reaching design capacity, with formation of biomass slurries needed to introduce feedstock. Corn stover slurries have been achieved from dilute acid, pretreated materials resulting in slurry concentrations of up to about 150 g/L, above which flowability is compromised. We report a new strategy to liquefy corn stover at higher solids concentration (300 g/L) by initially cooking it with the enzyme mimetic maleic acid at 40 mM and 150°C. This is followed by 6 h of enzymatic modification at 1 FPU (2.2 mg protein)/g solids, resulting in a yield stress of 171 Pa after 6 h and 58 Pa in 48 h compared to 6806 Pa for untreated stover. Mimetic treatment of corn stover pellets minimizes the inhibitory effect of xylo-oligomers on hydrolytic enzymes. Furthermore, this strategy allows for the delivery of solid lignocellulosic slurry into a pretreatment reactor by pumping, improving operability of a biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2020

Production of levulinic acid and biocarbon electrode material from corn stover through an integrated biorefinery process

To overcome the inefficient biomass conversion, waste generation, and lack of co-production in biorefineries, an integrated process was proposed for the conversion of corn stover into levulinic acid and biocarbon electrode material. Corn stover was pretreated through hydrothermal process using 0.45 wt% K 2 CO 3 which removed 76 wt% lignin and 85 wt% xylan while preserving 83 wt% glucan. This was followed by acid hydrolysis to produce levulinic acid at varying H 2 SO 4 concentrations and reaction time in a batch reactor at 190 °C. At a reaction time of 5 min in 2 wt% H 2 SO 4 , 35.8 wt% and 30 wt% glucan in raw and pretreated corn stover was converted to levulinic acid, respectively. The residue from acid hydrolysis was converted into biocarbon for supercapacitor electrodes via a two-step thermal activation process which showed a specific capacitance of 120 F g -1 . The proposed integrated biorefinery concept provides multiple value-added products for a greater financial and environmental sustainability.

09 BIOMASS FUELS↗
DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗
NASA NTRS2017

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

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

evapotranspiration↗
NASA NTRS2020

Adaptation in U.S. Corn Belt Increases Resistance to Soil Carbon Loss With Climate Change

Increasing the amount of soil organic carbon (SOC) has agronomic benefits and the potential to mitigate climate change. Previous regional predictions of SOC trends under climate change often ignore or do not explicitly consider the effect of crop adaptation (i.e., changing planting dates and varieties). We used the DayCent biogeochemical model to examine the effect of adaptation on SOC for corn and soybean production in the U.S. Corn Belt using climate data from three models. Without adaptation, yields of both corn and soybean tended to decrease and the decomposition of SOC tended to increase leading to a loss of SOC with climate change compared to a baseline scenario with no climate change. With adaptation, the model predicted a substantially higher crop yield. The increase in yields and associated carbon input to the SOC pool counteracted the increased decomposition in the adaptation scenarios, leading to similar SOC stocks under different climate change scenarios. Consequently, we found that crop management adaptation to changing climatic conditions strengthen agroecosystem resistance to SOC loss. However, there are differences spatially in SOC trends. The northern part of the region is likely to gain SOC while the southern part of the region is predicted to lose SOC.

Soil Organic Carbon (SOC)↗
DOE OSTI2022

Corn Stover Fractions from Different Harvest Conditions

There is a lot of variability in biomass. This variability can make it difficult to process the biomass into a consistent format for handling and conversion. As a result, bioenergy feedstocks are often under- or over-converted. Corn stover in particular can be harvested in different ways, baled in different ways, and has significant intrinsic variability due to its very different anatomies. These factors could cause variability in the fractions of corn stover. The fractions of corn stover are leaf, husk, cob, and stalk.

09 BIOMASS FUELS↗
DOE OSTI2023

A global meta‐analysis of cover crop response on soil carbon storage within a corn production system

Abstract By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn ( Zea mays L.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates.

60 APPLIED LIFE SCIENCES↗