Measuring fig quality using near-infrared spectroscopy

Sorting of dried figs prior to inspection is labor-intensive and somewhat c omplex. We examined the potential of using near-infrared spectroscopy (NIRS ) to automate sorting of dried figs. Calimyrna and Adriatic types were insp ected by hand using established criteria. For both varieties, approximately 100 passable figs and 100 figs each for the infested, rotten, sour, and di rty defect categories were examined using NIRS and partial least-squares re gression (PLS). Correct classifications for these varieties ranged from 83 to 100%. About twenty PLS factors were used to make the predictions. These results indicate that the use of NIRS to help automate inspection for dried fig processing is feasible. However, the large number of wavelengths neede d for prediction, as indicated by PLS beta coefficients, indicates that imp lementing NIRS in fig sorting may require an instrument capable of reading numerous wavelengths rather than a more economical filter-based instrument. Published by Elsevier Science Ltd.