Measuring fig quality using near-infrared spectroscopy

Sorting of dried figs prior to inspection is labor-intensive and somewhat complex. We examined the potential of using near-infrared spectroscopy (NIRS) to automate sorting of dried figs. Calimyrna and Adriatic types were inspected by hand using established criteria. For both varieties, approximately 100 passable figs and 100 figs each for the infested, rotten, sour, and dirty defect categories were examined using NIRS and partial least-squares regression (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 needed for prediction, as indicated by PLS beta coefficients, indicates that implementing NIRS in fig sorting may require an instrument capable of reading numerous wavelengths rather than a more economical filter-based instrument.