Monitoring cotton (Gossypium hirsutum L.) leaf ion content and leaf water content in saline soil with hyperspectral reflectance

The objectives of this study were to establish quantitative models for monitoring the leaf ion and water content under saline conditions. The best spectral indices for estimating leaf ion content and leaf water content were found to be normalized difference spectral indices (NDSI (R-1340, R-2306)), ratio spectral indices (RSI (R-2306, R-1347)) for K+, NDSI (R-1346, R-2276), RSI (R-2276, R-1343) for Na+, NDSI (R-1380, R-2307), RSI (R-2306, R-1350) for Ca2+; NDSI (R-1200, R-2211), RSI (R-2202, R-1361) for Mg2+; NDSI (R-1300, R-2250), RSI (R-2264, R-1335) for Cl-; NDSI (R-1154, R-2317), RSI (R-2317, R-1154) for SO42- and NDSI (R-1222, R-2264), RSI (R-2264, R-1321) for RWC, respectively. The regression models based on the above spectral indices were formulated with R-2 greater than 0.46. The high fit between the measured and estimated values indicate that the present models based on RSI could be used to estimate leaf ion and water content feasibly under saline conditions.