Abstract

This research aims to investigate the feasibility to rapidly and simultaneously determine the quality characteristics of Chinese ‘Dangshan’ pear by using near infrared (NIR) spectroscopy. A total of 151 ‘Dangshan’ pears with various ripen stages were used in this study. The NIR spectrum from each fresh intact sample was calibrated against four major physiological properties: soluble solid content (SSC), pH, firmness and density. The calibration models for these parameters were developed using the partial least square (PLS) based on the original and the four preprocessed spectra, respectively. The optimum spectral regions, the best pretreatment method and the fewest number of regression factors in the PLS-models were decided according to the minimum standard error in cross-validation (SECV). Finally, the proposed calibration models were validated using an independent sample set to evaluate their predicting ability. The best models for SSC, pH and firmness showed good predictability with the lowest standard error of prediction (SEP) of 0.3490Brix, 0.081 and 0.310N, and corresponding correlation coefficients of 0.985, 0.910 and 0.905, respectively, indicating that it is possible to simultaneously measure SSC, pH and firmness of Chinese ‘Dangshan’ pear by using NIR spectroscopy with the satisfactory accuracy. However, validation results also showed that no satisfactory NIR calibration equation for the density could be obtained.

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