Hyperspectral images of intact grapes during ripening were recorded using a near infrared hyperspectral imaging system (900-1700 nm). Spectral data have been correlated with grape skin total phenolic concentration, sugar concentration, titratable acidity and pH by modified partial least squares regression (MPLS) using a number of spectral pre-treatments and different sets of calibration. The obtained results (RSQ and SEP, respectively) for the global model of red and white grape samples were: 0.89 and 1.23 mg g(-1) of grape skin for total phenolic concentration, 0.99 and 1.37 °Brix for sugar concentration, 0.98 and 3.88 g L(-1) for titratable acidity and for pH 0.94 and 0.12. Moreover, separate calibration models for red and white grape samples were also developed. The obtained results present a good potential for a fast and reasonably inexpensive screening of these parameters in intact grapes and therefore, for a fast control of technological and phenolic maturity.
Keywords: Chemometrics; Grapes; H; MPLS; MSC; Mahalanobis distance; NIRS; Near infrared hyperspectral imaging; PC; PCA; PLS; Phenolic maturity; RSQ; SEC; SECV; SEP; SNV; Technological maturity; coefficient of determination; modified partial least squares; multiplicative scatter correction; near infrared spectroscopy; partial least squares; principal component; principal component analysis; standard error of calibration; standard error of cross-validation; standard error of prediction; standard normal variate.
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