Non-Destructive Quality Evaluation of Tropical Fruit (Mango and Mangosteen) Purée Using Near-Infrared Spectroscopy Combined with Partial Least Squares Regression

Abstract

Mango and mangosteen are commercially important tropical fruits with a short shelf life. Fruit processing is one of the alternatives to extend the shelf life of these fruits. Purée is one of the processed products of fresh fruit. In this research, the quality of mango and mangosteen purée was analyzed. Titratable acidity (TA) and total soluble solids (TSS) were predicted using non-destructive near-infrared (NIR) spectroscopy. A partial least squares regression (PLSR) model was developed based on the NIR spectra with a wavelength ranging from 800 to 2500 nm. The PLSR model returned a coefficient of determination (r2) and a ratio of prediction to deviation (RPD) of 0.955 and 4.7 for TSS, and 0.784 and 2.2 for TA, in the mango purée. Similarly, the best model was selected for the TSS prediction in the mangosteen purée through PLSR, with an r2, a root mean square error of cross-validation (RMSECV), and RPD of 0.799, 0.3% malic acid, and 2.2, respectively. The results show the possible application of NIR spectroscopy in the product processing line, although a larger number of samples with wide variation in future studies are needed as an input to update the model, in order to obtain a more robust model.