title: Detection of aflatoxin and surface mould contaminated figs by using Fourier transform near-infrared reflectance spectroscopy.
abstract: BACKGROUND
  Aflatoxins are toxic metabolites that are mainly produced by members of the Aspergillus section Flavi on many agricultural products. Certain agricultural products such as figs are known to be high risk products for aflatoxin contamination. Aflatoxin contaminated figs may show a bright greenish yellow fluorescence (BGYF) under ultraviolet (UV) light at a wavelength of 365 nm. Traditionally, BGYF positive figs are manually selected by workers. However, manual selection depends on the expertise level of the workers and it may cause them skin-related health problems due to UV radiation.
  
  
  RESULTS
  In this study, we propose a non-invasive approach to detect aflatoxin and surface mould contaminated figs by using Fourier transform near-infrared (FT-NIR) reflectance spectroscopy. A classification accuracy of 100% is achieved for classifying the figs into aflatoxin contaminated/uncontaminated and surface mould contaminated/uncontaminated categories. In addition, a strong correlation has been found between aflatoxin and surface mould.
  
  
  CONCLUSIONS
  Combined with pattern classification methods, the NIR spectroscopy can be used to detect aflatoxin contaminated figs non-invasively. Furthermore, a positive correlation between surface mould and aflatoxin contamination leads to a promising alternative indicator for the detection of aflatoxin-contaminated figs. © 2016 Society of Chemical Industry.
authors.affiliation: Vision, Image Processing and Pattern Recognition Laboratory (VIPLAB), Süleyman Demirel University, Department of Computer Engineering, Isparta, 32260, Turkey.
authors.forename: Efkan
authors.initials: E
authors.lastname: Durmuş
authors.affiliation: Vision, Image Processing and Pattern Recognition Laboratory (VIPLAB), Süleyman Demirel University, Department of Computer Engineering, Isparta, 32260, Turkey.
authors.forename: Ali
authors.initials: A
authors.lastname: Güneş
authors.affiliation: Vision, Image Processing and Pattern Recognition Laboratory (VIPLAB), Süleyman Demirel University, Department of Computer Engineering, Isparta, 32260, Turkey.
authors.forename: Habil
authors.initials: H
authors.lastname: Kalkan
mesh_terms: D000348:Aflatoxins / Q000032:analysis*; D001231:Aspergillus flavus / Q000737:chemistry / Q000302:isolation & purification; D030681:Ficus; D005453:Fluorescence; D005516:Food Microbiology / Q000379:methods*; D005638:Fruit / Q000737:chemistry / Q000145:classification / Q000382:microbiology*; D017550:Spectroscopy, Fourier Transform Infrared
chemical_list: D000348:Aflatoxins
keywords: aflatoxin; near-infrared spectroscopy; non-invasive inspection; surface mould