Search NASA⌕ Search

SEARCH · Search NASA

Results for “corn and soybean”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

194 records · Page 11

Variability of reflectance measurements with sensor altitude and canopy type

Data were acquired on canopies of mature corn planted in 76 cm rows, mature soybeans planted in 96 cm rows with 71 percent soil cover, and mature soybeans planed in 76 cm rows with 100 percent soil cover. A LANDSAT band radiometer with a 15 degree field of view was used at ten altitudes ranging from 0.2 m to 10 m above the canopy. At each altitude, measurements were taken at 15 cm intervals also a 2.0 m transect perpendicular to the crop row direction. Reflectance data were plotted as a function of altitude and horizontal position to verify that the variance of measurements at low altitudes was attributable to row effects which disappear at higher altitudes where the sensor integrate across several rows. The coefficient of variation of reflectance decreased exponentially as the sensor was elevated. Systematic sampling (at odd multiples of 0.5 times the row spacing interval) required fewer measurements than simple random sampling over row crop canopies.

Daughtry, C. S. T.↗

USA Crop Yield Estimation with MODIS NDVI: Are Remotely Sensed Models Better Than Simple Trend Analyses?

Crop yield forecasting is performed monthly during the growing season by the United States Department of Agriculture’s National Agricultural Statistics Service. The underpinnings are long-established probability surveys reliant on farmers’ feedback in parallel with biophysical measurements. Over the last decade though, satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to corroborate the survey information. This is facilitated through the Global Inventory Modeling and Mapping Studies/Global Agricultural Monitoring system, which provides open access to pertinent real-time normalized difference vegetation index (NDVI) data. Hence, two relatively straightforward MODIS-based modeling methods are employed operationally. The first model constitutes mid-season timing based on the maximum peak NDVI value, while the second is reflective of late-season timing by integrating accumulated NDVI over a threshold value. Corn model results nationally show the peak NDVI method provides a R^(2) of 0.88 and a coefficient of variation (CV) of 3.5%. The accumulated method, using an optimally derived 0.58 NDVI threshold, improves the performance to 0.93 and 2.7%, respectively. Both these models outperform simple trend analysis, which is 0.48 and 7.4%, correspondingly. For soybeans the R^(2) results of the peak NDVI model are 0.62, and 0.73 for the accumulated using a 0.56 threshold. CVs are 6.8% and 5.7%, respectively. Spring wheat’s R2performance with the accumulated NDVI model is 0.60 but just 0.40 with peak NDVI. The soybean and spring wheat models perform similarly to trend analysis. Winter wheat and upland cotton show poor model performance, regardless of method. Ultimately, corn yield forecasting derived from MODIS imagery is robust, and there are circumstances when forecasts for soybeans and spring wheat have merit too.

crop yield↗

Future Climate Change Impacts on U.S. Agricultural Yields, Production, and Market

This study provides estimates of climate change impacts on U.S. agricultural yields and the agricultural economy through the end of the 21st century, utilizing multiple climate scenarios. Results from a process-based crop model project future increases in wheat, grassland, and soybean yield due to climate change and atmospheric CO2 change; corn and sorghum show more muted responses. Results using yields from econometric models show less positive results. Both the econometric and process-based models tend to show more positive yields by the end of the century than several other similar studies. Using the process-based model to provide future yield estimates to an integrated agricultural sector model, the welfare gain is roughly $16B/year (2019 USD) for domestic producers and $6.2B/year for international trade, but domestic consumers lose $10.6B/year, resulting in a total welfare gain of $11.7B/year. When yield projections for major crops are drawn instead from econometric models, total welfare losses of more than $28B/year arise. Simulations using the process-based model as input to the agricultural sector model show large future production increases for soybean, wheat, and sorghum and large price reductions for corn and wheat. The most important factors are those about economic growth, flooding, international trade, and the type of yield model used. Somewhat less, but not insignificant factors include adaptation, livestock productivity, and damages from surface ozone, waterlogging, and pests and diseases.

Agricultural sector↗

Estimation of canopy parameters for inhomogeneous vegetation canopies from reflectance data. II - Estimation of leaf area index and percentage of ground cover for row canopies

The canopy reflectance (CR) model for row-planted vegetation proposed earlier has been tested for soybean canopies in three different stages of growth and for corn canopies at early and full growth stages. The model fits the field-measured bidirectional CR data quite well. It is shown that, by inverting this model, one could estimate the leaf area index as well as the percentage of ground cover quite accurately from measured canopy reflectances.

Goel, N. S.↗

Relating polarization phase difference of SAR signals to scene properties

This paper examines the statistical behavior of the phase difference Delta-phi between the HH-polarized and VV-polarized backscattered signals recorded by an L-band SAR over an agricultural test site in Illinois. Polarization-phase difference distributions were generated for about 200 agricultural fields for which ground information had been acquired in conjunction with the SAR mission. For the overwhelming majority of cases, the Delta-phi distribution is symmetric and has a single major lobe centered at the mean value of the distribution Delta-phi. Whereas the mean Delta-phi was found to be close to zero degrees for bare soil, cut vegetation, alfalfa, soybeans, and clover, a different pattern was observed for the corn fields; the mean Delta-phi increased with increasing incidence angle Theta = 35 deg. The explanation proposed for this variation is that the corn canopy, most of whose mass is contained in its vertical stalks, acts like a uniaxial crystal characterized by different velocities of propagation for waves with horizontal and vertical polarization. Thus, it is hypothesized that the observed backscatter is contributed by a combination of propagation delay, forward scatter by the soil surface, and specular bistatic reflection by the stalks. Model calculations based on this assumption were found to be in general agreement with the phase observations.

Ulaby, Fawwaz T.↗

Preliminary evaluation of the SIR-B response to soil moisture, surface roughness, and crop canopy cover

Two predawn ascending data-takes by the Shuttle Imaging Radar-B (SIR-B) were used to evaluate the effects of surface roughness, crop canopy, and soil moisture on radar backscatter. The two images, separated by three days, were both obtained at 30-deg local angle of incidence, but with opposite azimuth viewing directions. The imagery was externally calibrated with respect to the radar backscattering coefficient sigma(0) via response to arrays of point and area-extended targets of known radar cross section. Three land-cover classes: (1) corn, (2) corn stubble and plowed bare soil, and (3) disked bare soil, soybeans, soybean stubble, alfalfa, and clover could be readily separated for either observation date on the basis of image tone alone. The dependence of sigma(0) on the surface roughness and canopy brightness inhibits the capability of SIR to globally estimate the near-surface soil moisture from the value of sigma(0) for single date observations, unless the surface roughness or canopy cover conditions are accounted for. However, within given ranges of these conditions, the sigma(0) was found to be highly correlated with the soil moisture.

Dobson, M. C.↗

Developing processing techniques for Skylab data

The author has identified the following significant results. The effects of misregistration and the scan-line-straightening algorithm on multispectral data were found to be: (1) there is greatly increased misregistration in scan-line-straightening data over conic data; (2) scanner caused misregistration between any pairs of channels may not be corrected for in scan-line-straightened data; and (3) this data will have few pure field center pixels than will conic data. A program SIMSIG was developed implementing the signature simulation model. Data processing stages of the experiment were carried out, and an analysis was made of the effects of spatial misregistration on field center classification accuracy. Fifteen signatures originally used for classifying the data were analyzed, showing the following breakdown: corn (4 signatures), trees (2), brush (1), grasses, weeds, etc. (5), bare soil (1), soybeans (1), and alfalfa (1).

Nalepka, R. F.↗

Molecular and biochemical evidence for the involvement of calcium/calmodulin in auxin action

The use of (35)S-labeled calmodulin (CaM) to screen a corn root cDNA expression library has led to the isolation of a CaM-binding protein, encoded by a cDNA with sequence similarity to small auxin up RNAs (SAURs), a class of early auxin-responsive genes. The cDNA designated as ZmSAUR1 (Zea mays SAURs) was expressed in Escherichia coli, and the recombinant protein was purified by CaM affinity chromatography. The CaM binding assay revealed that the recombinant protein binds to CaM in a calcium-dependent manner. Deletion analysis revealed that the CaM binding site was located at the NH(2)-terminal domain. A synthetic peptide of amino acids 20-45, corresponding to the potential CaM binding region, was used for calcium-dependent mobility shift assays. The synthetic peptide formed a stable complex with CaM only in the presence of calcium. The CaM affinity assay indicated that ZmSAUR1 binds to CaM with high affinity (K(d) approximately 15 nM) in a calcium-dependent manner. Comparison of the NH(2)-terminal portions of all of the characterized SAURs revealed that they all contain a stretch of the basic alpha-amphiphilic helix similar to the CaM binding region of ZmSAUR1. CaM binds to the two synthetic peptides from the NH(2)-terminal regions of Arabidopsis SAUR-AC1 and soybean 10A5, suggesting that this is a general phenomenon for all SAURs. Northern analysis was carried out using the total RNA isolated from auxin-treated corn coleoptile segments. ZmSAUR1 gene expression began within 10 min, increased rapidly between 10 and 60 min, and peaked around 60 min after 10 microM alpha-naphthaleneacetic acid treatment. These results indicate that ZmSAUR1 is an early auxin-responsive gene. The CaM antagonist N-(6-aminohexyl)5-chloro-1-naphthalenesulfonamide hydrochloride inhibited the auxin-induced cell elongation but not the auxin-induced expression of ZmSAUR1. This suggests that calcium/CaM do not regulate ZmSAUR1 at the transcriptional level. CaM binding to ZmSAUR1 in a calcium-dependent manner suggests that calcium/CaM regulate ZmSAUR1 at the post-translational level. Our data provide the first direct evidence for the involvement of calcium/CaM-mediated signaling in auxin-mediated signal transduction.

NASA Program Fundamental Space Biology↗

Estimating scattered and absorbed radiation in plant canopies by remote sensing

Several research avenues are summarized. The relationships of canopy characteristics to multispectral reflectance factors of vegetation are reviewed. Several alternative approaches for incorporating spectrally derived information into plant models are discussed, using corn as the main example. A method is described and evaluated whereby a leaf area index is estimated from measurements of radiation transmitted through plant canopies, using soybeans as an example. Albedo of a big bluestem grass canopy is estimated from 60 directional reflectance factor measurements. Effects of estimating albedo with substantially smaller subsets of data are evaluated.

Daughtry, G. S. T.↗

An initial model for estimating soybean development stages from spectral data

A model, utilizing a direct relationship between remotely sensed spectral data and soybean development stage, has been proposed. The model is based upon transforming the spectral data in Landsat bands to greenness values over time and relating the area of this curve to soybean development stage. Soybean development stages were estimated from data acquired in 1978 from research plots at the Purdue University Agronomy Farm as well as Landsat data acquired over sample areas of the U.S. Corn Belt in 1978 and 1979. Analysis of spectral data from research plots revealed that the model works well with reasonable variation in planting date, row spacing, and soil background. The R-squared of calculated U.S. observed development stage exceeded 0.91 for all treatment variables. Using Landsat data the calculated U.S. observed development stage gave an R-squared of 0.89 in 1978 and 0.87 in 1979. No difference in the models performance could be detected between early and late planted fields, small and large fields, or high and low yielding fields.

Henderson, K. E.↗

Inferring spectral reflectances of plant elements by simple inversion of bidirectional reflectance measurements

Inverting previously developed explicit expressions for a vertical architecture, bidirectional reflectances measured over corn viewing from the solar quadrant at azimuths near the principal plane are used to determine the spectral reflectances of plant elements. The leaf reflectance values extracted in three visible bands at viewing zenith angles of 70 deg, 60 deg, and 45 deg agree closely with laboratory-measured reflectances of corn leaves. At viewing zenith angle of 30 deg, the inversion breaks down, inasmuch as the inferred plant element reflectances are too high. Satisfactory results are also achieved when the same approach is applied to bidirectional reflectances measured over potted balsam firs, but when applied to soybeans reflectances, the procedure yields unreasonably high leaf reflectances. The failure in this case is attributed to the nonvertical architecture of the soybean canopy; however, for this canopy, inversion based on horizontal architecture is possible. The bidirectional reflectances measured from the solar quadrant, at viewing angles appreciably far from 'hot spot' viewing, approximately equal in magnitude half of the leaf reflectance. The 0.5 ratio is predicted by a previous analysis of opaque horizontal Lambertian facets, as the asymptotic value for a dense canopy at any viewing angle. For soybeans, this ratio applies very closely at 15 deg viewing zenith angle. The results suggest that inversion based on simple architecture, applying explicit expressions, might be of value, either in itself or as a preliminary step before inversion applying complex models.

Otterman, J.↗

The Design of a Remote Sensing Data Acquisition Campaign for Precision Agriculture and Some Early Results

In the 1970s NASA and the Department of Agriculture attempted to use the new Landsat MSS system for agricultural purposes. The program had relatively little success. With the advent of differential GPS, yield monitors on harvest equipment and higher spatial resolution remote sensing systems it seemed likely the situation should be reexamined. Therefore, a campaign of data acquisition involving remote sensing and other modalities with dependent research was assembled and funded by the Space Grant Consortia in Alabama and Georgia. The design of the remote sensing data acquisition was driven by the biology and physics of the crop system and limited by the available sensor platforms. Major parameters included crop stage, spatial resolution, seasonal and daily weather conditions, and which portion of the EM spectrum would actually capture the most discriminating information. Joint visible and Near IR with Thermal IR would permit use of existing indices, such as greenness, as well as phenomena driven by the plant' s evapotranspiration. Spatial resolution in the 2-5 meter range was chosen, avoiding many complexities caused by aliasing crop row spacing at, higher resolutions yet finer than the harvester's tightest recording rate. This dictates use of an airborne system. Use of an airborne system also makes scheduling around weather much simpler than use of satellite data. Active video calibration was recognized as essential if quantitative measures were ever to be obtained or reproduced. The system would also have to have onboard geoOF1 Based on these elements 3 data acquisitions have been flown. Seven flight lines were flown twice in 1998 and 16 lines flown in 1999. Total raw data is several GBytes. All of the data has now been geometrically corrected and some preliminary analysis accomplished. The thermal bands have an extremely high correlation with yield. For one@test case with corn, correlation in excess of 0.86 was obtained from a data acquisition two months prior to harvest! Soil images show significant within field variation in clay, soil brightness and emissivity. Light wind has been found to effect the reflectance and temperature of broad leaf crops, including soybeans, cotton and peanuts. Clearly, this work has already demonstrated some very important results. With continued development of the remote sensing technology there is good reason to believe this research will soon be able to help the individual farmer.

Rickmanl, D.↗

The microwave propagation and backscattering characteristics of vegetation

A semi-empirical model for microwave backscatter from vegetation was developed and a complete set of canope attenuation measurements as a function of frequency, incidence angle and polarization was acquired. The semi-empirical model was tested on corn and sorghum data over the 8 to 35 GHz range. The model generally provided an excellent fit to the data as measured by the correlation and rms error between observed and predicted data. The model also predicted reasonable values of canopy attenuation. The attenuation data was acquired over the 1.6 to 10.2 GHz range for the linear polarizations at approximately 20 deg and 50 deg incidence angles for wheat and soybeans. An attenuation model is proposed which provides reasonable agreement with the measured data.

Ulaby, F. T.↗

Characterization of photosystem 1 chlorophyll a/b-binding apoprotein accumulation in developing soybean using type-specific antibodies

The structure and supramolecular assembly of the soybean photosystem 1 (PS 1) chlorophyll a/b-binding antenna (LHC 1) was examined. We identified the subunit composition of LHC 1 in soybean and followed the accumulation of individual subunits during light-induced assembly. We observed four LHC 1 subunits, at 23, 22, 21 and 20.5 kDa, obtained partial sequence information by amino-terminal sequence analysis, and classified the 20.5, 22, and 21 kDa subunits as being encoded by type I, II, and IV chlorophyll a/b binding protein genes, respectively. Antisera against LHC 1 subunits were used to follow the accumulation of individual subunits during the light-initiated transition from etioplast to chloroplast. Several points are noteworthy. First, monospecific antibody against the 22 kDa subunit decorated a 25 kDa peptide in etiolated tissue, which declined during maturation. This decline correlated with the light-induced appearance of mature 22 kDa peptide, suggesting a precursor/product relationship. Second, the same antibody identified a 22 kDa protein in mature corn, but not a larger band in etiolated corn, suggesting that LHC 1 accumulation is regulated differently between species before the onset of chlorophyll biosynthesis. Third, the mature 22 kDa subunit appeared somewhat later than the other LHC 1 peptides during greening, implying that this subunit is less intimately associated with the PS1 core than are the subunits appearing earlier in development.

Non-NASA Center↗