Abstract

Rind biochemical properties play major roles in defence mechanisms against the incidence of rind physiological disorders of citrus fruit during cold storage. Hence, multivariate calibration models were developed to rapidly and non-destructively determine rind biochemical properties of citrus fruit from visible to near-infrared (Vis/NIR) spectra acquired by Vis/NIR spectroscopy using partial least square regression algorithm. To achieve optimum models for determination of each rind biochemical property, several mathematical pre-processing methods were explored, including no pre-treatment. However, special emphases were given to the best model statistics in terms of coefficient of determination (R2) and residual predictive deviation (RPD). Models were performed by critical examination of different wavelength ranges (visible, near-infrared and full regions) and combinations of fruit harvested from different production regions and acquired before (week 0) and after (week 9) cold storage. Results obtained showed excellent models for determining parameters such as sucrose (R2 = 0.99 and RPD = 11.42), total flavonoids (R2 = 0.99 and RPD = 12.37), and chlorophyll b (R2 = 0.97 and RPD = 5.67). This study reported the first application of Vis/NIR and chemometrics in determining the rind biochemical properties of 'Marsh' grapefruit rapidly and non-destructively.

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