Assessment of Melon Fruit Nutritional Composition Using VIS/NIR/SWIR Spectroscopy Coupled with Chemometrics

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Abstract
The objective of this study was to evaluate the feasibility of using visible, near-infrared and short-wave infrared (VIS/NIR/SWIR) spectroscopy coupled with chemometrics for non-destructive prediction of nutritional components in Galia-type melon fruit. A total of 175 fully ripened melons were analyzed for soluble solids content (SSC), dry matter (DM), pH, and titratable acidity (TA) using partial least squares regression (PLSR), principal components regression (PCR), and multilinear regression (MLR) models. Reflectance spectra were captured at three fruit locations (pedicel, equatorial, blossom end) in the 350–2500 nm range. PLSR models yielded the highest accuracy, particularly for SSC (R= 0.80) and SSC/TA (R= 0.79) using equatorial zone data. Genetic algorithm and variable importance in projection (VIP) analyses identified critical wavelengths around 680–720 nm and 900–1000 nm. The study demonstrates the potential of VIS/NIR/SWIR spectroscopy for rapid, non-destructive melon quality assessment, with implications for commercial postharvest management.

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