Monitoring Plant and Canopy Leaf Water Contents Based On Canopy Hyperspectra In Rice.

Plant water status is a key index for evaluating crop growth and irrigation management. The purpose of this study were to find out the relationship of canopy reflectance to plant water status in rice (Oryza sativa L.), and to develop key hyperspectral parameters for accurate prediction of plant and canopy leaf water content. Three experiments were conducted with different soil water conditions and rice cultivars across three growing seasons, and time-course measurements were taken on canopy hyperspectral reflectance, plant and canopy leaf water content over growth stages. Ratio spectral indices (RSI) and normalized difference spectral indices (NDSI) with all combinations of two wavebands between 350 and 2500 nm were calculated, and their relationships to plant and canopy leaf water content were analyzed. The results indicated that plant water content, canopy leaf water content in rice and spectral reflectance varied distinctly with soil water conditions. The sensitivity bands mostly occured within visible light region and near infrared region. The RSI(773, 1287) were the most effective approach for predicting plant and canopy leaf water content, giving the determination coefficient of linear regression (S-R2) of 0.811and 0.747. The predicted R2 (P-R2) based on the testing performance with independent datasets were 0.895 and 0.825 respectively. It is concluded that the RSI(773, 1287) can be used to monitor plant and canopy leaf water content.