Vis/NIR spectroscopy and chemometrics for non-destructive estimation of water and chlorophyll status in sunflower leaves

Vegetation biochemical and biophysical variables are important for many ecological, agronomic, and meteorological applications. Among the main variables, water and chlorophyll are essentials due to directly affect the plant photosynthetic capacity and crop productivity. The objective of this study was develop and validate models capable of estimating water and chlorophyll status in sunflower leaves under progressive water stress, based on the visible/near-infrared region (Vis/NIR) spectral reflectance and chemometric technique. The water and chlorophyll models were adjusted considering the spectral reflectance from the 500–1039 nm wavelengths by using partial least squares regressions (PLSR). In the external validation, high determination coefficient (0.8386 and 0.8097) and low mean bias error (−0.40 dry basis and 0.09 mg g−1) values for water and chlorophyll, respectively, indicating that their predictive capabilities and accuracies of the models were satisfactory. Results showed that spectrometry has potential to be applied as an alternative method in quantifying water and chlorophyll status in sunflower leaves in a non-destructive, quick, and consistent way.

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