RGB color imaging to detect Aspergillus flavus infection in dates

M. Teena, A. Manickavasagan*, A. M. Al-Sadi, R. Al-Yahyai, M. L. Deadman, A. Al-Ismaili

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)683-688
Number of pages6
JournalEmirates Journal of Food and Agriculture
Issue number10
Publication statusPublished - 2016


  • Aspergillus flavus
  • Dates
  • RGB color images

ASJC Scopus subject areas

  • Food Science
  • Applied Microbiology and Biotechnology
  • Animal Science and Zoology
  • Agronomy and Crop Science


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