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Based on in situ measurements of incident and reflected solar irradiation over a wheat field, daily values of the surface reflectance, a scene signature, were determined for a crop year. Diagnoses of these data reveal the character of the signature, and its changes with time, crop stage, and the magnitude of incident irradiance. The latter varies inversely with cloud cover.
The Robertson phenology was used to provide growth stage information to a wheat stress indicator mode. A stress indicator model demands two acurate predictions from a crop calendar: date of spring growth initiation; and crop calendar stage at growth initiation. Several approaches for restarting the Robertson phenology model at spring growth initiation were studied. Although best results were obtained with a solar thermal unit method, an alternate approach which indicates soil temperature as the controlling parameter for spring growth initiation was selected and tested. The modified model (Doraiswamy-Thompson) is compared to LACIE-Robertson model predictions.
A 3 x 3 pixel spatial filter for postclassification was used for wheat classification to evaluate the effects of this procedure on the accuracy of area estimation using LANDSAT digital data obtained from a single pass. Quantitative analyses were carried out in five test sites (approx 40 sq km each) and t tests showed that filtering with threshold values significantly decreased errors of commission and omission. In area estimation filtering improved the overestimate of 4.5% to 2.7% and the root-mean-square error decreased from 126.18 ha to 107.02 ha. Extrapolating the same procedure of automatic classification using spatial filtering for postclassification to the whole study area, the accuracy in area estimate was improved from the overestimate of 10.9% to 9.7%. It is concluded that when single pass LANDSAT data is used for crop identification and area estimation the postclassification procedure using a spatial filter provides a more accurate area estimate by reducing classification errors.
Results on environmental and genotypic factors influencing preharvest sprouting of wheat are summarized. Other possible areas where additional research is needed is suggested.
Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the LANDSAT satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and LANDSAT-2 calibration data, the reflectance were used to simulate LANDSAT digital counts (not quantized) for the four LANDSAT bands for each day of the growing season, through a clear (approximately 100 km meteorological range) and a turbid (approximately 10 km meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results show that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.
The Williams type model, developed similarly to previous models of C.V.D. Williams, uses monthly temperature and precipitation data as well as soil and topological variables to predict the yield of the spring wheat crop. The models are statistically developed using the regression technique. Eight model characteristics are examined in the evaluation of the model. Evaluation is at the crop reporting district level, the state level and for the entire region. A ten year bootstrap test was the basis of the statistical evaluation. The accuracy and current indication of modeled yield reliability could show improvement. There is great variability in the bias measured over the districts, but there is a slight overall positive bias. The model estimates for the east central crop reporting district in Minnesota are not accurate. The estimate of yield for 1974 were inaccurate for all of the models.
Spectral reflectances of Produra wheat were measured at 13 different times of the day at Phoenix, Arizona, during April 1979 using a nadir-oriented hand-held 4-band radiometer which had bandpass characteristics similar to those on LANDSAT satellites. Different Sun altitude and azimuth angles caused significant diurnal changes in radiant return in both visible and near-IR regions of the spectrum and in several vegetation indices derived from them. The magnitude of these changes were related to different canopy architecture, percent cover and green leaf area conditions. Spectral measurements taken at each time period were well correlated with green leaf area index but the nature of the relationship changed significantly with time of day. Thus, a significant bias in the estimation of the green leaf area index from remotely sensed spectral data could occur if sun angles are not properly accounted for.
Models based on multiple regression were developed to estimate barley yield and spring wheat yield from weather data for Agrophysical units(APU) in North Dakota. 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 models show sight improvements in some of the statistics of the models, e.g., explained variation. These models are to be independently evaluated and compared to the previously evaluated CRD models. The comparison will indicate the preferred model area for this application, i.e., APU or CRD.
The relationships between crop canopy variables such as leaf area index (LAI) and their multispectral reflectance properties were investigated along with the potential for estimating canopy variables from remotely sensed reflectance measurements. Reflectance spectra over the 0.4 to 2.5 micron wavelength range were acquired during each of the major development stages of spring wheat canopies at Williston, North Dakota, during three seasons. Treatments included planting date, N fertilization, cultivar, and soil moisture. Agronomic measurements included development stage, biomass, LAI, and percent soil cover. High correlations were found between reflectance and percent cover, LAI, and biomass. A near infrared wavelength band, 0.76 to 0.90 microns, was most important in explaining variation in LAI and percent cover, while a middle infrared band, 2.08 to 2.35 microns, explained the most variation in biomass and plant water content. Transformations, including the near infrared/red reflectance ratio and greenness index, were also highly correlated to canopy variables. The relationship of canopy variables to reflectance decreased as the crop began to ripen. the canopy variables could be accurately predicted using measurements from three to five wavelength bands. The wavelength bands proposed for the thematic mapper sensor were more strongly related to the canopy variables than the LANDSAT MSS bands.
A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.
The effects of space flight on the growth of wheat seedlings and their nucleic acid content were studied. It was shown that both space and ground seedlings have almost the same appearance, dry weight and nucleic acid content in the root, coleoptile and leaves. The only difference found is in the RNA and DNA content, which is twice as much in the ground seedling apices as in the space-grown seedlings.
The water use and solar energy conversion efficiencies of two cultivars of winter wheat (Triticum aestivum L., vars, Centurk and Newton) planted at three densities, were examined during a growing season. Water use, based on soil moisture depletion, was the lowest under the light, and the highest under the heavy planting densities of both cultivars. Water use efficiency of medium and heavy planting densities were greater than the light planting densities in both cultivars. The canopy radiation extinction coefficients of both cultivars increased with increases in planting density. Efficiency of operation interception of photosynthetically active radiation by both cultivars improved from the time of jointing until anthesis, and then decreased during senescence. The efficiency of the conversion of intercepted radiation to dry matter (biochemical efficiency) decreased throughout the growing season both cultivars. The interception, biochemical, and photosynthetic efficiencies improved as planting density increased.
The results from the U.S./Canada Wheat and Barley Exploratory Experiment which was completed during FY 1980 are presented. The results indicate that the new crop identification procedures performed well for spring small grains and that they are conductive to automation. The performance of the machine processing techniques shows a significant improvement over previously evaluated technology. However, the crop calendars will require additional development and refinements prior to integration into automated area estimation technology. The evaluation showed the integrated technology to be capable of producing accurate and consistent spring small grains proportion estimates. However, barley proportion estimation technology was not satisfactorily evaluated. The low-density segments examined were judged not to give indicative or unequivocal results. It is concluded that, generally, the spring small grains technology is ready for evaluation in a pilot experiment focusing on sensitivity analyses to a variety of agricultural and meteorological conditions representative of the global environment. It is further concluded that a strong potential exists for establishing a highly efficient technology or spring small grains.
The interception of photosynthetically active radiation (PAR) was evaluated relative to greenness and normalized difference (MSS 7-5/7+5) for five planting dates of wheat for 1978-79 and 1979-80 in Phoenix. Intercepted PAR was calculated from a model driven by leaf area index and stage of growth. Linear relationships were found between greenness and normalized difference with a separate model representing growth and senescence of the crop. Normalized difference was a significantly better model and would be easier to apply than the empirically derived greenness parameter. For the leaf area growth portion of the season the model between PAR interception and normalized difference was the same over years, however, for the leaf senescence the models showed more variability due to the lack of data on measured interception in sparse canopies. Normalized difference could be used to estimate PAR interception directly for crop growth models.
The use of modeling to explore the possibility of discovering new and useful crop condition indicators which might be available from the Thematic Mapper and to connect these symptoms to the biological causes in the crop is discussed. A crop growth model was used to predict the day to day growth features of the crop as it responds biologically to the various environmental factors. A reflectance model was used to predict the character of the interaction of daylight with the predicted growth features. An atmospheric path radiance was added to the reflected daylight to simulate the radiance appearing at the sensor. Finally, the digitized data sent to a ground station were calculated. The crop under investigation is wheat.
Several vegetative indices were analyzed for their sensitivity and stability to green-leaf-area index (LAI) changes over various planting dates and irrigation frequencies of wheat grown at Phoenix, AZ, from 1978 to 1980. Seasonal patterns of greenness showed that values saturated at LAI values above 4.0 did not return to the pre-emergence bare-soil value at senescence, and were not uniquely related to LAI over the various planting dates. Regressions of individual MSS band reflectances against LAI also showed that there was not a unique relation between any of the bands and LAI. However, the near-infrared/red reflectance ratio was stable over all planting dates and could be used successfully over a number of years and locations.
When simulating canopies planted in varied densities, researchers were able to demonstrate that increase of dry matter production by enhancing CO2 quickly becomes independant of increase of leaf area, especially above leaf area index of 2; dry matter gain results mainly from photosynthesis stimulation per unit of surface (primary CO2 effect). When crop density is low (the plants remaining alone a longer time), the effects of increasing leaf surface (tillering, leaf elongation here, branching for other plants etc.) was noticeable and dry matter simulation factor reached 1.65. This area effect decreased when canopy was closed in, as the effect of different surfaces no longer worked. The stimulation of photosynthesis reached to the primary CO2 effect. The accumulation in dry matter which was fast during that phase made the original weight advantage more and more neglectible. Comparison with short term measurements showed that first order long term effect of CO2 in wheat is predictible with short term experiment, from the effect of CO2 on photosynthesis measured on reference sample.
The economic feasibility of using food-producing crop plants in a closed ecological Life-Support System (CELSS) will ultimately depend on the energy and area (or volume) required to provide the nutritional requirements for each person. Energy and area requirements are, to some extent, inversely related; that is, an increased energy input results in a decreased area requirement and vice versa. A major goal of the research effort was to determine the controlled-environment good-production efficiency of wheat per unit area, per unit time, and per unit energy input.