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ARS Home » Pacific West Area » Parlier, California » San Joaquin Valley Agricultural Sciences Center » Commodity Protection and Quality Research » Research » Publications at this Location » Publication #257668

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

Author
item Obenland, David - Dave
item Margosan, Dennis
item Smilanick, Joseph
item Mackey, Bruce

Submitted to: HortTechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/29/2010
Publication Date: 12/1/2010
Citation: Obenland, D.M., Margosan, D.A., Smilanick, J.L., Mackey, B.E. 2010. Ultraviolet fluorescence to identify navel oranges with poor peel quality and decay. HortTechnology. 20:991-995.

Interpretive Summary: Navel oranges are commercially sorted for peel quality using both electronic and manual means but fruit with poor peel quality still sometimes reach the consumer due to the inability of the current system to accurately identify substandard fruit. Navel oranges were sorted into four groups under ultraviolet (UV) illumination in commercial packinghouse black light rooms based upon the amount of fluorescence visible on each fruit to determine if UV-induced peel fluorescence was predictive of peel quality. The groups corresponded to fruit with: 1) no fluorescence (group 0); 2) low fluorescence (group 1); 3) moderate fluorescence (group 2), and 4) fluorescent lesions indicative of decay (group 3). Fruit were visually evaluated for peel quality initially and after 3 weeks of cold storage. Fluorescence groups 0 and 1 were similar to each other and had high peel quality, while group 2 was of poor peel quality had had a higher amount of decay following storage than groups 0 and 1. Fluorescence group 3 had very high levels of decay and represents fruit which are currently removed by workers in the black light room. This study demonstrated that peel fluorescence under UV light is predictive of peel quality and offers a means with which to improve sorting efficiency for oranges.

Technical Abstract: Navel oranges were sorted into four groups under ultraviolet (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: 1) no fluorescence (group 0); 2) low fluorescence (group 1); 3) moderate fluorescence (group 2); or 4) large fluorescent areas (group 3) indicative of developing decay lesions. Identification and elimination of group 3 fruit in black light rooms is a common practice now, but the other classes pass through these rooms. Six tests were conducted over a two year period during different times in the mid to late navel orange season. Fruit were visually evaluated for peel quality within 24 h of their initial segregation into fluorescence classes and again following 3 weeks of storage at 15°C. Peel quality assessment was based upon commercial grading practices and the fruit were placed into either fancy, choice, juice, or decay classes. Fruit with little or no peel fluorescence (groups 0 and 1) had numerous fancy grade fruit and few juice and decay grade fruit in comparison to the other two groups. In contrast, fruit with moderate fluorescence (group 2) was of poor peel quality. In the initial evaluation, this class had 28% fewer fancy 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; the percentage of decayed fruit increased from 1% initially to 29% after 3 weeks of storage. 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 three weeks. This study demonstrated that in addition to removing fluorescing fruit that have obvious indications of decay (group 3) that it would be advantageous to the overall peel quality and storability of fruit lots to remove fruit with moderate levels of fluorescence (group 2) as well. This may be most practical with an automated system using machine vision and UV illumination.