Correlation of the Grapevine (Vitis vinifera L.) Leaf Chlorophyll Concentration with RGB Color Indices

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Abstract
Spectral investigation of the canopy has an increasing importance in precision viticulture to monitor the effect of biotic and abiotic stress factors. In this study, RGB (color model, red, green, blue)-based vegetation indices were evaluated to find a correlation with grapevine leaf chlorophyll concentration. ‘Hárslevelű’ (Vitis vinifera L.) leaf samples were obtained from a commercial vineyard and digitalized. The chlorophyll concentration of the samples was determined with a portable chlorophyll meter. Image processing and color analyses were performed to determine the RGB average values of the digitized samples. According to the RGB values, 31 vegetation indices were calculated and evaluated with a correlation test and multivariate regression. The Pearson correlation between the chlorophyll concentration and most of the indices was significant (p < 0.01), with some exceptions. The same results were obtained with the Spearman correlation as the relationship had high significance (p < 0.01) for most of the indices. The highest Pearson correlation was obtained with the index PCA2 (Principal Component Analysis 2), while Spearman correlation was the highest for RMB (difference between red and blue) and GMB (difference between green and blue). The multivariate regression model also showed a high correlation with the pigmentation. We consider that our results would be applicable in the future to receive information about the canopy physiological status monitored with on-the-go sensors.

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