Development of spectral indices to monitoring non-destructive of ripeness for water stressed grapevine (Vitis vinifera L.) using contour map optimization

Abstract

Accurate and non-destructive monitoring of grape ripening is essential for optimising harvest decisions, particularly under water stress conditions. This study aims to evaluate the application of the contour map optimisation method for determining spectral indices to non-destructive monitoring of soluble solids (SS), titratable acidity (TA), and pH for grapevines (cv. Cabernet-Sauvignon) under four levels of water application. Hyperspectral reflectance data (350–2500 nm) were acquired from grape berries during two consecutive growing seasons (2019/20 and 2020/21) to identify optimal wavelength combinations using contour maps. Results indicated that the optimal spectral indices were SI_SS = 1600 nm/1412 nm for SS, SI_TA = 1617 nm/1415 nm for TA, and SI_pH = 694 nm/697 nm for pH. In this case, the linear regression based on SI_SS, SI_TA, and SI_pH presented a coefficient of determination of 0.82, 0.83, and 0.95, respectively. Model validation confirmed the stability of these spectral indices across different irrigation regimes, with an index of agreement of 0.94 for SS, 0.90 for TA, and 0.79 for pH. The results demonstrate that contour map optimisation could increase the robustness of spectral indices, improving their reliability across varying conditions of soil water availability. This methodology provides a viable alternative to destructive ripeness assessment techniques, offering a scalable solution for vineyard management and decision-making in precision viticulture.