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 in eight different weeks during their ripening process. Mean RGB data, histograms, and matrices of RGB data were used to characterise the ripening stage of the plums, in both qualitative and quantitative approaches, by using classification and quantification chemometric methods. An exploratory analysis of data was performed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) in RGB histograms and matrices data, respectively, showing differences in the colour features since the fourth week of harvesting. In the case of the quantitative approach, high correlation was achieved between the histogram data, using partial least squares (PLS), and total chlorophyll content. In addition, between three-way matrixes and total chlorophyll content, good correlations were obtained applying unfolded-PLS (U-PLS) and N-way-PLS (N-PLS). The most accurate results were obtained on the green channel. Analytical parameters obtained were good, with determination coefficients (R-2) higher than 0.91 for all models in the first and second-order multivariate analysis. In addition, relative errors of prediction (REPs) were lower than 12% in all models for the green channel. Therefore, the proposed method was a satisfactory alternative to destructive physiological and biochemical methods in the determination of total chlorophylls in plum samples. In the routine analysis, first-order multivariate calibration with PLS analysis is a good option due to the simplicity of data processing.

Automated summary

The study used digital imaging processing to characterize the ripening stage of plums by analyzing mean RGB data, histograms, and matrices. The results showed differences in color features since the fourth week of harvesting. The quantitative approach achieved high correlation between histogram data and total chlorophyll content, as well as good correlations between three-way matrices and total chlorophyll content.