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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

ERTS-1 data collection systems used to predict wheat disease severities

The author has identified the following significant results. The feasibility of using the data collection system on ERTS-1 to predict wheat leaf rust severity and resulting yield loss was tested. Ground-based data collection platforms (DCP'S), placed in two commercial wheat fields in Riley County, Kansas, transmitted to the satellite such meteorological information as maximum and minimum temperature, relative humidity, and hours of free moisture. Meteorological data received from the two DCP'S from April 23 to 29 were used to estimate the disease progress curve. Values from the curve were used to predict the percentage decrease in wheat yields resulting from leaf rust. Actual decrease in yield was obtained by applying a zinc and maneb spray (5.6 kg/ha) to control leaf rust, then comparing yields of the controlled (healthy) and the noncontrolled (rusted) areas. In each field a 9% decrease in yield was predicted by the DCP-derived data; actual decreases were 12% and 9%.

Kanemasu, E. T.↗
NASA NTRS1974

ERTS-1 data collection systems used to predict wheat disease severities

The feasibility of using the data collection system on Earth Technology Satellite-1 to predict wheat leaf rust severity and resulting yield loss was tested. Ground-based data-collection platforms (DCPs), placed in two commercial wheat fields, transmitted to the satellite such meteorological information as maximum and minimum temperature, relative humidity, and hours of free moisture. Meteorological data received from the two DCPs from April 23 to 29 were used to estimate the disease progress curve. Values from the curve were used to predict the percentage decrease in wheat yields resulting from leaf rust. Actual decrease in yield obtained by applying a zinc and maneb spray to control leaf rust, and then comparing yields of the controlled (healthy) and the noncontrolled (rusted) areas. In each field, a 9% decrease in yield was predicted by the DCP-derived data; actual decreases were 12% and 9%.

Kanemasu, E. T.↗
NASA NTRS1975

Proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference

The proceedings of the 1974 Lyndon B. Johnson Space Center Wheat-Yield Conference are presented. The state of art of wheat-yield forecasting and the feasibility of incorporating remote sensing into this forecasting were discussed with emphasis on formulating common approach to wheat-yield forecasting, primarily using conventional meteorological measurements, which can later include the various applications of remote sensing. Papers are presented which deal with developments in the field of crop modelling.

Pitts, D. E.↗
NASA NTRS1975

Remotely sensing wheat maturation with radar

The scattering properties of wheat were studied in the 8-18 GHz band as a function of frequency, polarization, incidence angle, and crop maturity. Supporting ground truth was collected at the time of measurement. The data indicate that the radar backscattering coefficient is sensitive to both radar system parameters and crop characteristics particularly at incidence angles near nadir. Linear regression analyses of the radar backscattering coefficient on both time and plant moisture content result in rather good correlation. Furthermore, by calculating the average time rate of change of the radar backscattering coefficient it is found that it undergoes rapid variations shortly before and after the wheat is harvested. Both of these analyses suggest methods for estimating wheat maturity and for monitoring the progress of harvest.

Bush, T. F.↗
NASA NTRS1976

Monitoring wheat growth with radar

The scattering properties of wheat in the 8-18 GHz band were studied as a function of frequency, polarization, incidence angle, and crop maturity. Supporting ground truth was collected at the time of measurement. The data indicate the radar backscattering coefficient is sensitive to both radar system parameters and crop characteristics, particularly at incidence angles near nadir. Linear regression analysis of the backscattering coefficient (dB) on both time and plant moisture content result in rather good correlation, as high as 0.9, with the slope of these regression lines being 0.55 dB/day and -0.275 dB% plant moisture at 9.4 GHz at nadir. It is found that the coefficient undergoes rapid variations shortly before and after the wheat is harvested. Both of these analyses suggest methods for estimating wheat maturity and for monitoring the progress of harvest.

Bush, T. F.↗
NASA NTRS1976

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Objective measurements of percent green wheat cover on May 21 were significantly correlated with yield, as were measurements of green LAI and LANDSAT data. Three data sets from the Finney test site were analyzed from LANDSAT passes on 22 November 1974, 15 April 1975, and 21 May 1975. After mean signal values in each band were computed for each sufficiently large wheat field, the mean values were correlated with the farmer estimates of wheat grain yield in order to assess relative information content. It is clear that the single best spectral temporal band for predicting yield is the 15 April red band (0.6-0.7 microns, band 5), with the 15 April green band (0.5-0.6 microns, band 4) a close second.

Nalepka, R. F.↗
NASA NTRS1976

Wheat signature modeling and analysis for improved training statistics

The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important.

Nalepka, R. F.↗
NASA NTRS1977

LACIE: Wheat yield models for the USSR

A quantitative model determining the relationship between weather conditions and wheat yield in the U.S.S.R. was studied to provide early reliable forecasts on the size of the U.S.S.R. wheat harvest. Separate models are developed for spring wheat and for winter. Differences in yield potential and responses to stress conditions and cultural improvements necessitate models for each class.

Sakamoto, C. M.↗
NASA NTRS1977

Two phase sampling for wheat acreage estimation

A two phase LANDSAT-based sample allocation and wheat proportion estimation method was developed. This technique employs manual, LANDSAT full frame-based wheat or cultivated land proportion estimates from a large number of segments comprising a first sample phase to optimally allocate a smaller phase two sample of computer or manually processed segments. Application to the Kansas Southwest CRD for 1974 produced a wheat acreage estimate for that CRD within 2.42 percent of the USDA SRS-based estimate using a lower CRD inventory budget than for a simulated reference LACIE system. Factor of 2 or greater cost or precision improvements relative to the reference system were obtained.

Thomas, R. W.↗
NASA NTRS1977

Application of wheat yield model to United States and India

The author has identified the following significant results. The wheat yield model was applied to the major wheat-growing areas of the US and India. In the US Great Plains, estimates from the winter and spring wheat models agreed closely with USDA-SRS values in years with the lowest yields, but underestimated in years with the highest yields. Application to the Eastern Plains and Northwest indicated the importance of cultural factors, as well as meteorological ones in the model. It also demonstrated that the model could be used, in conjunction with USDA-SRRS estimates, to estimate yield losses due to factors not included in the model, particularly diseases and freezes. A fixed crop calendar for India was built from a limited amount of available plot data from that country. Application of the yield model gave measurable evidence that yield variation from state to state was due to different mixes of levels of meteorological and cultural factors.

Feyerherm, A. M.↗
NASA NTRS1977

Two phase sampling for wheat acreage estimation

A two phase Landsat-based sample allocation and wheat proportion estimation method was developed. This technique employs manual, Landsat full frame-based wheat or cultivated land proportion estimates from a large number of segments comprising a first sample phase to optimally allocate a smaller phase two sample of computer or manually processed segments. Application to the Kansas Southwest CRD for 1974 produced a wheat acreage estimate for that CRD within 2.42 percent of the USDA SRS-based estimate using a lower CRD inventory budget than for a simulated reference LACIE system. Factor of 2 or greater cost or precision improvements relative to the reference system were obtained

Thomas, R. W.↗
NASA NTRS1978

Plant canopy light absorption model with application to wheat

A light absorption model (LAM) for vegetative plant canopies has been derived from the Suits reflectance model. From the LAM the absorption of light in the photosynthetically active region of the spectrum (400-700 nm) has been calculated for a Penjamo wheat crop for several situations including (a) the percent absorption of the incident radiation by a canopy of LAI 3.1 having a four-layer structure, (b) the percent absorption of light by the individual layers within a four-layer canopy and by the underlying soil, (c) the percent absorption of light by each vegetative canopy layer for variable sun angle, and (d) the cumulative solar energy absorbed by the developing wheat canopy as it progresses from a single layer through its growth stages to a three-layer canopy. This calculation is also presented as a function of the leaf area index and is shown to be in agreement with experimental data reported by Kanemasu on Plainsman V wheat.

Chance, J. E.↗
NASA NTRS1979

The Relationship of Red and Photographic Infrared Spectral Data to Grain Yield Variation Within a Winter Wheat Field

Two band hand-held radiometer data from a winter wheat field, collected on 21 dates during the spring growing season, were correlated within field final grain yield. Significant linear relationships were found between various combinations of the red and photographic infrared radiance data collected and the grain yield. The spectral data explained approximately 64 percent of the within field grain yield variation. This variation in grain yield could not be explained using meteorological data as these were similar for all areas of the wheat field. Most importantly, data collected early in the spring were highly correlated with grain yield, a five week time window existed from stem elongation through antheses in which the spectral data were most highly correlated with grain yield, and manifestations of wheat canopy water stress were readily apparent in the spectral data.

Tucker, C. J.↗
NASA NTRS1980

Effects of management practices on reflectance of spring wheat canopies

The effects of available soil moisture, planting date, nitrogen fertilization, and cultivar on reflectance of spring wheat (Triticum aestivum L.) canopies were investigated. Spectral measurements were acquired on eight dates throughout the growing season, along with measurements of crop maturity stage, leaf area index, biomass, plant height, percent soil cover, and soil moisture. Planting date and available soil moisture were the primary agronomic factors which affected reflectance of spring wheat canopies from tillering to maturity. Comparisons of treatments indicated that during the seedling and tillering stages planting date was associated with 36 percent and 85 percent of variation in red and near infrared reflectances, respectively. As the wheat headed and matured, less of the variation in reflectance was associated with planting date and more with available soil moisture. By mid July, soil moisture accounted for 73 percent and 69 percent of the variation in reflectance in red and near infrared bands, respectively. Differences in spectral reflectance among treatments were attributed to changes in leaf area index, biomass, and percent soil cover. Cultivar and N fertilization rate were associated with very little of the variation in the reflectance of these canopies.

Daughtry, C. S. T.↗
NASA NTRS1980

Illustration of year-to-year variation in wheat spectral profile crop growth curves

Data previously compiled on the year to year variability of spectral profile crop growth parameters for spring and winter wheat in Kansas, Oklahoma, and the Dakotas were used with a profile model to develop graphs illustrating spectral profile crop growth curves for a number of years and a number of spring and winter wheat segments. These curves show the apparent variability in spectral profiles for wheat from one year to another within the same segment and from one segment to another within the same year.

Gonzalez, P.↗
NASA NTRS1981

Evaluation of spring wheat and barley crop calender models for the 1979 crop year

During the Large Area Crop Inventory Experiment, spring wheat planting date and crop development stage estimates based on historical normals were improved by the use of the Feyerherm planting date and Robertson spring wheat crop calendar models. The Supporting Research Crop Calendar Project element modified the Robertson model to reduce bias at cardinal growth stages within the growing season. These models were tested in 1980 along with a state-of-the-art barley model (Williams) against a ground-truth data set from 49 calendar year 1979 segments in the U.S. Great Plains spring wheat and barley region.

Nazare, C. V.↗
NASA NTRS1980

Sonora exploratory study for the detection of wheat-leaf rust

The applicability of LANDSAT remote sensing technology to the detection of a wheat-leaf-rust epidemic in Sonora, Mexico, during 1977 was investigated. LANDSAT data acquired during crop years 1975-76 and 1976-77 were clustered, classified, and analyzed in order to detect agricultural changes. Analysis of 1977 data indicates a significant proportion of the identified wheat is stressed (potentially rust-infected). Additional analyses show a significant increase in fallowing during the year, as well as a substantial decrease in reservoir levels in the Sonora agricultural region. Ground observations are required to substantiate these analyses. The possibility exists that heat-rust is not LANDSAT detectable and that the clusters identified as containing stressed signatures represent different varieties of wheat or perhaps nonwheat crops.

Payne, R. W.↗
NASA NTRS1981

Linear polarization of light by two wheat canopies measured at many view angles

The linear polarization and reflection of visible light by wheat as a function of sun-view directions, crop development stage, and wavelength were examined. Two-hundred spectra were taken continuously in wave-lengths from 0.45 to 0.72 Micron in 33 view directions using an Exotech model 20C spectroradiometer six meters above two wheat canopies in the boot and fully headed maturity stages. The analysis results show that the amount of linearly polarized light from the wheat canopies is greatest in the blue spectral region and decreases gradually with increasing wavelength. The results also show that the linearly polarized light from the canopies is generally greatest in the azimuth direction of the Sun and tends toward zero as the view direction tends toward the direction of the hot spot or anti-solar point. It is demonstrated that the single, angle of incidence of sunlight on the leaf, explains almost all of the variation of the amount of polarized light with Sun-view direction.

Bauer, M. E.↗