Raman spectroscopic‐based chemometric modeling in assessment of red pepper ripening phases and carotenoids accumulation

The main goal of the present study is validation of different chemometric models in Raman spectroscopic monitoring of different maturity phases of the red pepper fruit. Successive ripening stages commonly corresponding with different fruit coloration (green, green‐brown, brown‐red, and deep red) were assessed. The fruit maturation process in red pepper is related to alteration in composition and content of different primary and secondary metabolites, including the most represented carotenoid, the capsanthin. Raman microspectroscopy with wavelength of 532 nm was used to obtain the spectra of the pericarp of different maturation phases. Several multivariate classification methods, such as Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA), Partial Least Squares‐Discriminant Analysis (PLS‐DA), and Soft Independent Modeling of Class Analogy (SIMCA) were tested to determine the model which best fits the target ripening phases related to composition and the content of the most represented carotenoids. Concerning different fruit ripening phases, several characteristic bands were obtained, including those at 1514–1517, 1151, and 1003 cm−1, all assigned to carotenoids with nine conjugated double bonds in the main polyene chain (e.g., lutein, beta carotene, beta cryptoxanthin, zeaxanthin, capsorubin, and capsanthin). All tested classification chemometric models had a high rate of prediction accuracy (between 95% and 100%). The SIMCA showed the best result, probably because of using a different algorithm compared with the other tested models. Raman spectra shows an increase in intensity of bands assigned to carotenoids, primarily the capsanthim, and decrease of bands intensity assigned to phenolic compounds during fruit ripening. Soft Independent Modeling of Class Analogy (SIMCA), Partial Least Squares‐Discriminant Analysis (PLS‐DA), and Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) showed very good accuracy in classification of Raman spectra of four distinct ripening phases and were especially favorable in case of very similar spectra, that is, in final phases of fruit maturation.