Monitoring the leaf water content and specific leaf weight of cotton (Gossypium hirsutum L.) in saline soil using leaf spectral reflectance

Abstract The objectives of the present study are to determine the relationships of equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf weight (SLW) of cotton leaves with leaf spectra reflectance, and to find sensitive spectral bands and best spectral indices to establish quantitative models for the quick and accurate estimation of EWT, FMC and SLW in cotton plants under different salinity levels. Plot experiments were conducted at different levels of salinity and cotton cultivars during three consecutive growing seasons. Time-course measurements of the leaf spectral reflectance, leaf fresh weight, leaf dry weight, leaf area, and leaf ion content of cotton were recorded under various treatments. Then, the normalized difference spectral indices (NDSI) and ratio spectral indices (RSI) based on the leaf spectrum were obtained within 350–2500 nm, and their correlation with EWT, FMC and SLW were quantified. The results show that the EWT, FMC and SLW of cotton leaves increased with increasing soil salinity levels and that the changes in leaf spectral reflectance under varied salinity levels are highly significant, with consistent patterns across the two cultivars tested. As the soil salinity levels increased, the Na + , Cl − , and SO 4 2− content in the cotton leaves increased, whereas K + and Ca 2+ decreased at the same growth stage. In addition, the relationships among ion content, EWT, FMC and SLW were significant ( P R 1347 , R 2307 ), RSI ( R 2307 , R 1347 ); NDSI ( R 1650 , R 1801 ), RSI ( R 1801 , R 1650 ); NDSI ( R 1300 , R 2308 ), RSI ( R 2307 , R 1347 ) and 1650/2220 nm ratio, and the regression models based on the above spectral indices were identified as the best equations for the effective estimation of EWT and SLW in cotton. After testing these derived equations, the models for EWT and SLW estimation based on NDSI and RSI yielded an R 2 of over 0.73, with more satisfactory performance under different ecological conditions, but the estimated accuracies of FMC models were very low and may not be suitable for estimating vegetation water content in saline conditions from leaf-level reflectance. The high fit between the measured and estimated values indicates that the EWT and SLW models based on new spectral indices from leaf-level reflectance could be used for the indirect estimation of plant salinity status by monitoring the changes in EWT and SLW caused by soil salinity in cotton plants.

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