In the peach packinghouses, the postharvest handling and packaging of peaches has been extensively automated, with the exception of the sorting operation, which continues to be a manual effort Consepuently, automation of the peach defect sorting has potential for improving product quality, in addition to reducing packinghouse labor costs.
This paper dealt with the spectral reflectance characteristics of peachsurface defects in order to the development of a machine vision sorting system for peach defects. And the types of peach defects were bruises, cuts, brown rots, compressed and impacted damages.
The detection of peach defects in the visible wavelength region(290～780nm) was complicated by the variation in color over the surface of the peach. But blush and ground color curves had about same values of spectral reflectance in the near infrared region. And the spectral reflectance drew the clear distinction between normal and damage of peach surface.
Since near infrared region was not affected by peach color variations．It was preperred for finding defects in the near infrared region.