A leafspot susceptible peanut cultivar (cv JL 24) was sown during kharif season of 2005 in rainfed region of Andhra
Pradesh, India. Five disease levels (scale 0-4) were created in the field by differential fungicidal spray schedule, and each
treatment was replicated four times. Spectral data was recorded at 2 nm intervals using a portable spectroradiometer
within a spectral range of 300-1100 nm. The loss of leaf pigments (Chlorophyll a and b) due to diseases was quantified
using spectrophotometer. The red and infrared reflectance values between 620- 680 and 770-860 nm, respectively were
used for calculating Normalized Difference Vegetation Index (NDVI). Significant reduction in chlorophyll content was
observed only when the disease reached a stage of scale 2 and above. The ratio of chlorophyll a to b showed a declining
trend as the number of spots per leaf increased. From the spectral reflectance studies typical chlorophyll absorption
bands (350 - 500 and 620-690 nm) of healthy and diseased plants could not be differentiated. However, the difference
was evident in the chlorophyll reflection bands (522- 600 nm). The infrared spectral region between 700-850 nm was
found to be sensitive to canopy disease stress. The reflectance (%) in this part of spectrum was higher for healthy plants
compared to diseased plants. But, the low level of disease intensity (scale 1) was not differentiated by the spectral
reflectance. The NDVI value for 82 days old healthy crop was in the range of 0.45 to 0.50, while the same for diseased
plants was between 0.34 and 0.45. This study finds potential application of remote sensing techniques in detection of
plant diseases.
This study investigated the relationship between sorghum grain yield over range of soil depth with seasonal crop water stress index based on relative evapotranspiration deficits and spectral vegetation indices. A root zone soil moisture model has been used to evaluate the seasonal soil moisture fluctuation and actual evapotranspiration within a toposequence having varying soil depth of 30 to 75 cm as well as different available water capacity ranging from 6.9% to 12.6% (V/V%). The higher r2 values between modeled and observed values of soil water (r2> 0.69 significant at <0.001) and runoff (r2 = 0.95, significant at P<0.001) indicated good agreement between model output and observed values. The spectral vegetation indices like simple ratio, normalized difference vegetation index (NDVI), green NDVI, perpendicular vegetation index, soil adjusted vegetation index (SAVI) and modified SAVI (MSAVI) was recorded through out the growth period of sorghum. The vegetation indices except perpendicular vegetation index measured during booting to anthesis stages were positively correlated (P<0.05) with leaf area index and yield. The MSAVI measured during booting to milk-grain stage have the highest positive correlation with yield. Variation was noticed when additive and multiplicative forms of water-production functions calculated from water budget model were used to predict crop yield. But the yield estimation was improved when spectral vegetation indices measured during booting to milk-grain is incorporated along with water production functions. The water budget model along with spectral vegetation indices gave satisfactory estimates of sorghum grain yields and appears to be a useful tool to estimate yield as a function of soil depth and available soil water.
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