In this study, the potential of RGB color imaging to detect fungal contamination in three varieties (Khalas, Fard and Naghal) of dates was investigated. The samples were treated as three groups: UC (untreated control), SC (surface sterilized, rinsed and air-dried) and IS (surface sterilized, rinsed, air-dried and fungal inoculated). Color images of control samples and A. flavus inoculated date fruits after every 48 h of inoculation for 10 days were acquired using an RGB color imaging system (n=3150). The classification accuracies for IS were compared with UC and SC separately using a two-class model (control vs. infected (all stages of infection together)), six-class model (control, infected day 2, day 4, day 6, day 8 and day 10) and pair-wise model (control vs. each stage of infection). In the two-class model, the highest accuracy obtained by Fard, Khalas and Naghal dates were 97, 100 and 99%, respectively. The developed algorithm was also tested on pooled dates (all three varieties were combined together: control vs infected), and 98% and 99% of infested samples were correctly classified from untreated control and sterile control, respectively in two class models. In six class models, highest classification accuracies of 99-100% were obtained for IS Day 10 in all three date varieties.
Key words: RGB color images, Aspergillus flavus, dates
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