The objective of this study was to evaluate the potential of a new handheld ultra-compact near infrared (NIR) spectrometer, based on the linear-variable filter (LVF) technology for rapid and non-destructive quality control analysis of the 'Tommy Atkins' mango. Multivariate calibration models were built using the Partial Least Squares (PLS) regression method to determine soluble solids (SS), dry matter (DM), titratable acidity (TA) and pulp firmness (PF). Different spectral pre-processing techniques were tested. Coefficient of determination and root mean square errors of prediction (RMSEP) values were, respectively: 0.92 and 0.55°Brix for SS, 0.67 and 0.51% for DM, 0.50 and 0.17% citric acid for TA, 0.72 and 12.2N for PF. The predictive models allowed monitoring physico-chemical changes in each fruit during ripening. The results show the feasibility of using the new NIR handheld spectrometer to determine quality parameters in the 'Tommy Atkins' mango.
Keywords: Fruit quality; Mango; NIR spectroscopy; Non-destructive analysis; PLS regression.
Copyright © 2015 Elsevier Ltd. All rights reserved.