Predicting salinity in tomato using soil reflectance spectra

Abstract

Soil salinity is one of the most common soil degradation processes, found particularly in both arid and semi-arid areas. Salt (Cl)- and sodium (Na)-affected soils impact vegetation and plant communities. Under these conditions, soil salinity can serve as an indicator of vegetation salinity. In this study, we explored whether spectroscopy could quantitatively assess foliar Cl and Na concentration as indicators to assess salinity in tomato plants. Reflectance spectra of soil samples were obtained in the 400–2500 nm region using a hyperspectral radiometer. The relationship between the Na and Cl contents of tomato plants growing in various saline environments and soil spectral reflectance was determined using partial least squares regression. The Cl-content model was more accurate for determining leaf salinity (R 2 = 0.92, root mean square error of prediction (RMSEP) = 0.2%) than the Na-content model (R 2 = 0.87, RMSEP = 0.6%). We conclude that reflectance spectroscopy is potentially useful for characterizing the key properties of salinity in growing vegetation and assessing its salt quality. The results of this study can serve as a starting point in precision agriculture for salinity measurements in tomato fields and could be further upgraded for use by airborne/satellite remote-sensing modes.