Soil colour was expressed in terms of chromaticity coordinates instead of traditional Munsell notations which facilitated correlation with the moisture content of soils. Spectral reflectance of twenty‐one soil samples was measured in the visible region from saturation to air‐dryness from which the colour coordinates for each soil at various moisture levels were calculated. The data were transformed to metric lightness, metric chroma and Munsell values using the tables of Wyszecki and Stiles (1982). All the colour coordinates, metric lightness, metric chroma and Munsell value were negatively correlated with the moisture content. For dark soils, the rate of change of colour parameters with moisture is less compared to red and light coloured alluvial soils. An interesting feature of the study is that all the colour parameters converged to a characteric value for a group of soils at zero moisture level (intercept), which will be useful to assess the moisture status of a soil in that group from the regression equations, if the colour of soil is estimated in terms of spectral parameters.
The productivity of cereal crops is mainly related to their nitrogen status. It is hypothesized that the spectral reflectance data could be used to predict wheat nitrogen status with spectral indices and that their performance depends on the nature of the interaction of the solar radiation with the crop canopy. A wheat crop was raised with 12 levels of nitrogen treatments: 0, 15, 30, 40, 50, 60, 70, 80, 90, 100, 110, and 120 kg ha(1 , with uniform phosphorous and potassium nutrition and uniform water and management practice. The spectral reflectance measurements of the crop canopy were taken at 5 nm intervals, throughout the crop growth period. Different spectral indices, both broadband (ratio as well as orthogonal) and hyperspectral indices were computed throughout the growing season. Canopy Colour Difference ( D E), an index developed from the entire visible region and hence broader than the spectral indices developed hitherto, was also estimated from the reflectance data. Simple linear relationships developed between spectral indices versus applied nitrogen levels as well as the plant nitrogen content revealed that the hyperspectral indices are less sensitive in comparison to broadband indices. The result was reinforced by a higher correlation between the colour difference, NDVI and Greenness Index with plant nitrogen level/content, as opposed to hyperspectral indices.
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