Monitoring of Chlorophylls during the Maturation Stage of Plums by Multivariate Calibration of RGB Data from Digital Images

The methodology developed in this study was based on digital imaging processing of plums harvested eight different weeks during their ripening process. Mean RGB data, histograms, and matrices data were used to characterise the stage plums, both qualitative quantitative approaches, by using classification quantification chemometric methods. An exploratory analysis performed principal component (PCA) parallel factor (PARAFAC) histograms respectively, showing differences colour features since fourth week harvesting. In case approach, high correlation achieved between histogram partial least squares (PLS), total chlorophyll content. addition, three-way matrixes content, good correlations obtained applying unfolded-PLS (U-PLS) N-way-PLS (N-PLS). most accurate results green channel. Analytical parameters good, with determination coefficients (R2) higher than 0.91 for all models first second-order multivariate analysis. relative errors prediction (REPs) lower 12% Therefore, proposed method a satisfactory alternative destructive physiological biochemical methods chlorophylls plum samples. routine analysis, first-order calibration PLS is option due simplicity processing.