Abstract
The estimation of plant water status is an essential component of precision crop management, and is directly related to plant physiological processes and ultimately crop yield. Hyperspectral models developed to estimate plant water content have met with limited success and have not been rigorously validated. A spectrum matching technique was applied to the hyperspectral data to directly calculate the canopy equivalent water thickness (EWT) using a look-up table approach. The objective of this study was to test the validity of this algorithm using crop water status information collected on the ground. Data were acquired over an experimental test site near Indian Head, Saskatchewan using the Probe-1 airborne hyperspectral sensor. Plant biomass samples were collected simultaneously from 96 plots spanning eight fields of various crop types (wheat, canola, and peas). The model was validated against EWT estimated from biomass samples as well as more conventional measures of crop water status. Results indicate that the liquid water retrieval technique can be used to estimate crop water status for broad-leafed crops such as peas and canola, but is not a reliable estimator of wheat this early stage of vegetative growth. This may be related to the low level of water in the crop and the contribution of soil to the reflectance signal.
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