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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AmeriFlux FLUXNET-1F US-DS2 Staten Corn 2

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-DS2 Staten Corn 2. This is the FLUXNET version of the carbon flux data for the site US-DS2 Staten Corn 2 produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in a corn field in the California Delta on Staten Island. The tower is positioned within several hundred hectares of homogenous agricultural (corn) fields.

Deverel, Steve [Hydrofocus, Inc]↗
DOE OSTI2018

Corn Stover Harvest, Tillage, and Cover Crop Effects on Soil Health Indicators

Monitoring soil health indicators (SHI) will help ensure that corn (Zea mays L.) stover harvest is sustainable. This study examines SHI changes after 5 yr of growing continuous corn with either chisel plow or no-tillage practices and harvesting 0, ~35, or ~60% of the stover. Two no-tillage treatments with a cereal rye (Secale cereale L.) cover crop and stover harvest rates of ~35 or ~60% were evaluated. All eight treatments were replicated four times in a randomized complete block design at an 11-ha site in Boone County, IA. Soil samples were collected following grain and stover harvest from 0- to 5- and 5- to 15-cm depth increments. Particulate organic matter C (POM-C) decreased when stover was removed or the soil was chisel plowed. No-till with 0% stover removal had 10 mg g –1 POM-C in the 0- to 5-cm soil layer, which was 1.9-fold higher than in other treatments. Potentially mineralizable N (PMN) was greater under cover crop treatments. Average PMN values were 56.9 and 45.5 µg g –1 PMN for no-till with cereal rye at 0- to 5- and 5- to 15-cm depths, respectively, compared with 17.5 and -3.7 µg g –1 PMN for the same no-till treatments without cereal rye. Other soil properties did not respond to increasing levels of stover removal. At this location and at the studied removal rates, 5 yr of harvesting corn stover did not decrease soil health, but POM-C data suggest that changes may be occurring. Long-term monitoring should continue to assess corn stover harvest sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Do Cover Crops and Corn Residue Removal Affect Soil Thermal Properties?

Soil thermal properties govern the transport and storage of heat in the soil. How management practices such as crop residue removal and cover crop (CC) use affect these soil properties is not well understood. For example, CCs could provide physical cover and improve soil properties after main crop residue removal and thus ameliorate the negative effects of residue removal on soil thermal properties. We measured changes in soil thermal properties including soil thermal conductivity, thermal diffusivity, volumetric heat capacity, and related properties under corn (Zea mays L.) residue removal with and without winter cereal rye (Secale cereale L.) under a 6-yr irrigated no-till continuous corn experiment on a silt loam in south central Nebraska. Cover crops did not affect thermal properties, but corn residue removal reduced field thermal conductivity by 12 to 41% and volumetric heat capacity by 6 to 49% during the growing season for the 0- to 5-cm depth. Residue removal also reduced laboratory thermal conductivity by 19% at –0.03-MPa and by 28% at –1.5-MPa matric potential. Residue removal also reduced volumetric heat capacity in the laboratory by 23% at both matric potentials in the 0- to 10-cm depth. Neither residue removal nor CC affected thermal diffusivity. Thermal conductivity was more strongly correlated with soil water content than with bulk density and soil organic C. Altogether, CC had no effect on thermal properties, but corn residue removal could reduce the soil’s ability to conduct heat relative to no removal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enzyme-assisted liquefaction for different fractions of corn stover pellets

With an increase in population, the world will depend on renewable sources to meet the increasing energy needs. The use of lignocellulosic biomass as a renewable source has been proven efficient for conversion to cellulosic ethanol and capable of contributing to thresholds for energy demand while reducing greenhouse gases by 90% when compared with fossil fuels. However, limitations in feeding and flow within biorefineries are encountered when system plugging occurs due to biomass compaction and a high yield stress for slurries formed during its processing. Furthermore, differences in the biomass source present a challenge to the continuity of operations and reliability in the process. This work explores enzyme-assisted liquefaction for solid loadings up to 30% as an alternative for the creation of slurry from two different types of biomass (pelleted corn stover and cobs) that were liquefied in a fed-batch process using commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU/g or 3 FPU/g of dry solids in a 10 mM sodium citrate buffer solution (pH 4.8). Pellets were fed into a 1 L stirred bioreactor according to a predefined fed-batch protocol during the first 5 hours until 30% solid loading was reached. After 6, 24 and 96 hours, samples were taken and characterized with respect to their composition, rheology, and water absorption. Successful slurry creation with dramatically reduced yield stress was achieved for corn stover for both enzymes assessed. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3 FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme. Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours. A profile for 6, 24 and 96h of yield stress measurements and sugar conversion is presented.

Gutierrez, Diana↗
DOE OSTI2023

Liquefaction of different corn stover fractions assisted by enzyme-biomass deconstruction

Recalcitrant properties of different sources of lignocellulosic biomass represent challenges in materials processing within a biorefinery, as well as enzyme efficient deconstruction to fermentable sugars. Limitations include lignin derived enzyme inhibitors, enzyme inhibition by hydrolysis products, and resistance to mixing due to rheological properties of lignocellulosic particulates at high solids loadings. Consequently, we examined conditions that might be used to achieve liquid slurries (i.e., liquefaction) at solids loadings of 300 g/L before the material enters the biorefinery through a pretreatment step. This work explores enzyme-assisted liquefaction in a fed-batch process using the commercial enzymes Celluclast 1.5L or Ctec-2 at 1FPU/g or 3 FPU/g of dry solids, basis. Corn stover pellets were fed into a 1 L stirred bioreactor containing enzyme solution over a 5-hour period until reaching 30% solids loading (dry wgt / vol basis). After 6, 24 and 96 hours from the start of the run, samples were taken and characterized with respect to their sugar composition, rheology, water absorption and enzyme activity. Slurries with dramatically reduced yield stresses were achieved for corn stover. Yield stresses of 178±7 Pa (3 FPU, Celluclast 1.5L) and 79±6 Pa (3FPU, Ctec-2) were measured for corn stover at 24 hours, compared to 6,000 Pa for samples without enzyme.Yield stress was 155± 29 Pa (3FPU, Ctec-2) and 257 ± 72 Pa (1 FPU, Celluclast 1.5L) for corn cobs at 24 hours.A profile based on 6, 24 and 96h of yield stress measurements and sugar conversion is presented. Enzyme activity is measured and the impact of liquefaction on an integrated processing in a biorefinery operation is discussed.

Gutierrez, Diana↗
NASA NTRS1972

The 1971 corn blight watch experiment

The successful fulfillment of the objectives for the 1971 corn blight watch experiment is reported. The objectives were: (1) detect the development and spread of corn blight during the growing season across the Corn Belt; (2) assess different levels of infection in the Corn Belt; (3) amplify data acquired by ground observations to better appraise current blight status and the probable impact on crop production; and (4) estimate through extrapolation the applicability of these techniques to similar situations occurring in the future.

Clifton, J. W.↗
NASA NTRS1974

Statistical separability of spectral classes of blighted corn

A study was conducted to determine the statistical separability of multispectral measurements from corn having varying levels of southern corn leaf blight severity. Multispectral scanner data in twelve spectral channels in the wavelength range 0.4 to 11.7 microns were analyzed for ten selected flightlines of the 1971 Corn Blight Watch Experiment. A total of 168 corn fields having 18,804 sample points were analyzed. The blight rating information for these fields was available from ground observations. Maximum average transformed divergence between spectral classes of all possible pairs of blight levels, maximized over a subset of channels, was computed in each of one, two, three, and four spectral channels for each of ten flightlines. From the statistical analysis of the values of average transformed divergence, it was concluded that the greater the difference between the blight levels, the more statistically separable they are.

Kumar, R.↗
NASA NTRS1981

Fiscal year 1981 US corn and soybeans pilot preliminary experiment plan, phase 1

A draft of the preliminary experiment plan for the foreign commodity production forecasting project fiscal year 1981 is presented. This draft plan includes: definition of the phase 1 and 2 U.S. pilot objectives; the proposed experiment design to evaluate crop calendar, area estimation, and area aggregation components for corn and soybean technologies using 1978/1979 crop-year data; a description of individual sensitivity evaluations of the baseline corn and soybean segment classification procedure; and technology and data assessment in support of the corn and soybean estimation technology for use in the U.S. central corn belt.

Livingston, G. P.↗
NASA NTRS1981

Temporal spectral response of a corn canopy

Techniques developed for the prediction of winter wheat yields from remotely sensed data indicating crop status over the growing season are tested for their applicability to corn. Ground-based spectral measurements in the Landsat Thematic Mapper bands 3 (0.62-0.69 microns), 4 (0.76-0.90 microns) and 5 (1.55-1.75 microns) were performed at one-week intervals throughout the growing season for 24 plots of corn, and analyzed to derive spectral ratios and normalized spectral differences of the IR and shortwave IR bands with the red. The ratios of the near IR and shortwave IR bands are found to provide the highest and most consistent correlations with corn yield and dry matter accumulation, however the value of band 5 could not be tested due to the absence of water stress conditions. Integration of spectral ratios over several dates improved the correlations over those of any single date by achieving a seasonal, rather than instantaneous, estimate of crop status. Results point to the desirability of further tests under other growth conditions to determine whether satellite-derived data will be useful in providing corn yield information.

Markham, B. L.↗
NASA NTRS1982

Analysis of the profile characteristics of corn and soybeans using field reflectance data

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗
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↗