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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Economic Benefits of Improved Information on Worldwide Crop Production: An Optimal Decision Model of Production and Distribution with Application to Wheat, Corn, and Soybeans

An optimal decision model of crop production, trade, and storage was developed for use in estimating the economic consequences of improved forecasts and estimates of worldwide crop production. The model extends earlier distribution benefits models to include production effects as well. Application to improved information systems meeting the goals set in the large area crop inventory experiment (LACIE) indicates annual benefits to the United States of $200 to $250 million for wheat, $50 to $100 million for corn, and $6 to $11 million for soybeans, using conservative assumptions on expected LANDSAT system performance.

Andrews, J.↗
NASA NTRS1979

Temporal spectral measurements of corn and soybean crops

A ground-based, hand-held radiometer, configured to measure red and photographic infrared spectral radiances, was successfully used to collect in situ temporal spectral measurements of corn and soybean crops. Significant relationships were found between the radiance data and the biomass, plant height, percentage crop cover, percentage crop chlorosis, and percentage leaf loss. The results of this experiment show conclusively that hand-held radiometers can be used to collect spectral data that are highly correlated to several agronomic variables. These findings suggest approaches for agronomic research, and confirm the value of remote sensing of agricultural targets.

Tucker, C. J.↗
NASA NTRS1978

Advances in the Dow Corning process for solar-grade silicon

The Dow Corning process consists of the carbothermic reduction of silica to produce silicon that is then purified by unidirectional solidification. The process has produced silicon of semiconductor quality with respect to all elements except boron and phosphorus at about 10 ppma and aluminum at 0.1 ppma. Solar cells produced from this silicon gave AM0 conversion efficiencies of 11%. A process cost analysis is presented.

Hunt, L. P.↗
NASA NTRS1979

Progress on the Dow Corning process for solar-grade silicon

The Dow Corning approach to increasing the resistivity of solar-grade silicon from about 0.04 ohm-cm (40 ppma B) to greater than 0.1 ohm-cm (10 ppma B) involves the use of high-purity raw materials carbothermically reduced in a specially designed electric arc furnace. Final purification occurs during Czochralski crystal growth of a polycrystalline ingot. This small-scale purification technology has resulted in silicon that has been fabricated into solar cells with a maximum AM1 conversion efficiency of 13.4%.

Hunt, L. P.↗
NASA NTRS1981

A project to evaluate moisture stress and phenological factors in corn and soybean areas of southwestern and south-central Minnesota

The capability of aerial color infrared photography for identifying and locating soilscapes most susceptible to drought development or those having different soil drainages was evaluated. Although west central and southwestern Minnesota had a significant precipitation deficit during the 1980 crop season, indications of plant stress were not observed either from ground observation or through interpretation of imagery at the selected sampling sites. Well-drained soil was more depleted during the "maximium green peak" period than the poorly drained soil. The recharge was more evident on the poorly drained site in the fall. Measurements of leaf water potential and leaf temperature for corn and soybean leaves were made by multispectral band scanner and recorded for analysis.

Rust, R. H.↗
NASA NTRS1981

Recommended data sets, corn segments and spring wheat segments, for use in program development

The sets of Large Area Crop Inventory Experiment sites, crop year 1978, which are recommended for use in the development and evaluation of classification techniques based on LANDSAT spectral data are presented. For each site, the following exists: (1) accuracy assessment digitized ground truth; (2) a minimum of 5 percent of the scene ground truth identified as corn or spring wheat; and (3) at least four acquisitions of acceptable data quality during the growing season of the crop of interest. The recommended data sets consist of 41 corn/soybean sites and 17 spring wheat sites.

Austin, W. W.↗
NASA NTRS1981

Effects of nitrogen nutrition on the growth, yield and reflectance characteristics of corn canopies

Spectral and agronomic measurements were collected from corn (Zea mays L.) canopies under four nitrogen treatment levels (0, 67, 134, and 202 kg/ha) on 11 dates during 1978 and 12 dates during 1979. Data were analyzed to determine the relationship between the spectral responses of canopies and their argonomic characteristics as well as the spectral separability of the four treatments. Red reflectance was increased, while the near infrared reflectance was decreased for canopies under nitrogen deprivation. Spectral differences between treatments were seen throughout each growing season. The near infrared/red reflectance ratio increased spectral treatment differences over those shown by single band reflectance measures. Of the spectral variables examined, the near infrared/red reflectance ratio most effectively separated the treatments. Differences in spectral response between treatments were attributed to varying soil cover, leaf area index, and leaf pigmentation values, all of which changed with N treatment.

Bauer, M. E.↗
NASA NTRS1981

Spectral-agronomic relationships of corn, soybean and wheat canopies

During the past six years several thousand reflectance spectra of corn, soybean, and wheat canopies were acquired and analyzed. The relationships of biophysical variables, including leaf area index, percent soil cover, chlorophyll and water content, to the visible and infrared reflectance of canopies are described. The effects on reflectance of cultural, environmental, and stress factors such as planting data, seeding rate, row spacing, cultivar, soil type and nitrogen fertilization are also examined. The conclusions are that several key agronomic variables including leaf area index, development stage and degree of stress are strongly related to spectral reflectance and that it should be possible to estimate these descriptions of crop condition from satellite acquired multispectral data.

Bauer, M. E.↗
NASA NTRS1981

AgRISTARS. Preliminary technical results review of FY81 experiments, volume 2: Fiscal year 1981/1982 "corn and soybeans pilot" experiment

The performance of the technology exhibited significant proportion estimation errors, specifically, high mean error in both corn and soybeans area estimation. The data systems, technical approaches, and data assessment of the pilot experiment were reviewed. Results of proportion estimations procedure performance evaluations, and sensitivity evaluations are presented. The role of the pilot experiment in foreign technology development is discussed.

Source record↗
NASA NTRS1982

Cultural and environmental effects on the spectral development patterns of corn and soybeans: Field data analysis

An overall approach to crop spectral understanding is presented which serves to maintain a strong link between actual plant responses and characteristics and spectral observations from ground based and spaceborne sensors. A specific technique for evaluating field reflectance data, as a part of the overall approach, is also described. Results of the application of this technique to corn and soybeans reflectance data collected by and at Purdue/LARS indicate that a number of common cultural and environmental factors can significantly affect the temporal spectral development patterns of these crops in tasseled cap greenness (a transformed variable of LANDSAT MSS signals).

Crist, E. P.↗
NASA NTRS1981

Coherent optical determination of the leaf angle distribution of corn

A coherent optical technique for the diffraction analysis of an image is presented. Developments in radar remote sensing shows a need to understand plant geometry and its relationship to plant moisture, soil moisture, and the radar backscattering coefficient. A corn plant changes its leaf angle distribution, as a function of time, from a uniform distribution to one that is strongly vertical. It is shown that plant and soil moisture may have an effect on plant geometry.

Ulaby, F. T.↗
NASA NTRS1982

Relating thematic mapper bands TM3, TM4, and TM5 to agronomic variables for corn, cotton, sugarbeet, soybean, sorghum, sunflower and tobacco

Red, photographic infrared, near infrared spectral data of corn, cotton, soybeans, sugar beets, sorghum, sunflowers and tobacco were collected throughout the entire growing season by using a three band handheld radiometer. Different radiance patterns were found among these crops based on their morphology, green biomass duration and leaf size. Results show near infrared radiance is a good indicator of water content in plant tissue under small scale experimental conditions.

Fan, C. J.↗
NASA NTRS1982

Use of Landsat-derived temporal profiles for corn-soybean feature extraction and classification

A physical model is presented, which has been derived from multitemporal-multispectral data acquired by Landsat satellites to describe the behavior and new features that are crop specific. A feasibility study over 40 sites was performed to classify the segment pixels into those of corn, soybeans, and others using the new features and a linear classifier. Results agree well with other existing methods, and it is shown the multitemporal-multispectral scanner data can be transformed into two parameters that are closely related to the target of interest and thus can be used in classification. The approach is less time intensive than other techniques and requires labeling of only pure pixels.

Badhwar, G. D.↗
NASA NTRS1982

Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

Leduc, S.↗
NASA NTRS1982

Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

French, V.↗
NASA NTRS1983

Spatial variation of corn canopy temperature as dependent upon soil texture and crop rooting characteristics

A soil plant atmosphere model for corn (Zea mays L.) together with the scaling theory for soil hydraulic heterogeneity are used to study the sensitivity of spatial variation of canopy temperature to field averaged soil texture and crop rooting characteristics. The soil plant atmosphere model explicitly solves a continuity equation for water flux resulting from root water uptake, changes in plant water storage and transpirational flux. Dynamical equations for root zone soil water potential and the plant water storage models the progressive drying of soil, and day time dehydration and night time hydration of the crop. The statistic of scaling parameter which describes the spatial variation of soil hydraulic conductivity and matric potential is assumed to be independent of soil texture class. The field averaged soil hydraulic characteristics are chosen to be representative of loamy sand and clay loam soils. Two rooting characteristics are chosen, one shallow and the other deep rooted. The simulation shows that the range of canopy temperatures in the clayey soil is less than 1K, but for the sandy soil the range is about 2.5 and 5.0 K, respectively, for the shallow and deep rooted crops.

Choudhury, B. J.↗