Ultraviolet fluorescence to identify navel oranges with poor peel quality and decay.

摘要

Navel oranges were sorted into 4 groups under UV illumination in commercial packinghouse black light rooms based upon the amount of fluorescence visible on each fruit to determine if fluorescence was predictive of peel quality. The groups corresponded to fruit with: little or no fluorescence (group 0); low fluorescence (group 1); moderate fluorescence (group 2); and large fluorescent areas (group 3) that were indicative of developing decay lesions. Identification and elimination of group 3 fruit in black light rooms is a common practice now, but the other groups pass through these rooms. 6 tests were conducted over a 2-yr period during different times in the mid to late navel orange season. Fruit were visually evaluated for peel quality within 24 hours of their initial segregation into fluorescence groups and again following 3 wk of storage at 15 degrees C. Peel quality assessment was based upon commercial grading practices, and the fruit were placed into fancy, choice, juice, or decay classes. Fruit with low to no peel fluorescence (groups 0 and 1) had numerous fancy-grade fruit and few juice- and decay-grade fruit in comparison with the other 2 groups. In contrast, fruit with moderate fluorescence (group 2) were of poor peel quality. In the initial evaluation, this group had 28% fewer fancy fruit and 19% more juice fruit than did group 0. During storage, group 2 fruit declined markedly in quality and numerous fruit of group 2 in the choice and juice classes decayed; percentage of decayed fruit increased from 1% initially to 29% after 3 wk of storage. Navel oranges in group 3, with numerous and obvious fluorescent decay lesions, mainly consisted of either juice grade or decayed fruit; 70% of group 3 decayed after 3 wk. In addition to removing fluorescing fruit that have obvious indications of decay (group 3), it would be advantageous to remove or otherwise recognize that fruit with moderate levels of fluorescence (group 2) are also of lower quality and that they should not be selected for long storage or distant transport. Their identification may be most practical with an automated system using machine vision and UV illumination.