Non-destructive freeze damage detection in oranges using machine vision and ultraviolet fluorescence

Abstract

A non-contact, non-destructive, and rapid method of detecting freeze-damaged oranges based on ultraviolet (UV) fluorescence of the peel oil constituents visible on the peel surface was investigated. The visual appearance is different from oleocellosis in that freeze-damaged oranges exhibit a fine pattern of 1–2 mm bright yellow dots on the peel when viewed under longwave UV light. Visual and machine vision-based methods were evaluated to determine their ability to detect freeze damage in Californian navel oranges ( Citrus sinensis L. Osbeck) subjected to laboratory simulated freeze conditions of −7 °C for 0, 8, or 16 h periods. The study focused on the period within the first few days (i.e., prior to fruit dehydration) after a freeze event has occurred because there are currently no rapid, objective, and non-destructive methods of freeze damage detection available for use during that time period. Using the USDA segment cut method to determine the presence of internal freeze damage, the classification rates for both UV fluorescence methods varied with the level of freeze damage. Using machine vision, a classification accuracy of 87.9% was obtained for unfrozen and moderately or severely frozen fruit, dropping to 64.4% for fruit with low levels of freeze damage. UV fluorescence shows promise for both visual inspection using existing black light inspection rooms or for automation using on-line machine vision techniques for separating freeze-damaged fruit subjected to moderate or severe freeze conditions.