Pixel-level aflatoxin detecting in maize based on feature selection and hyperspectral imaging

This publication has 18 references indexed in Scilit:

• Detection of Aspergillus spp. contamination levels in peanuts by near infrared spectroscopy and electronic nose
  Food Control, 2018
• Utilisation of visible/near-infrared hyperspectral images to classify aflatoxin B1 contaminated maize kernels
  Biosystems Engineering, 2018
• Mycotoxin contamination of foods in Southern Africa: A 10-year review (2007–2016)
  Critical Reviews in Food Science and Nutrition, 2017
• Detection of aflatoxin B1 (AFB1) in individual maize kernels using short wave infrared (SWIR) hyperspectral imaging
  Biosystems Engineering, 2017
• Data mining derived from food analyses using non-invasive/non-destructive analytical techniques; determination of food authenticity, quality & safety in tandem with computer science disciplines
  Trends in Food Science & Technology, 2016
• Identification of aflatoxin B1 on maize kernel surfaces using hyperspectral imaging
  Food Control, 2014
• Mid infrared and fluorescence spectroscopies coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems
  Food Chemistry, 2011
• Rapid Detection of Kernel Rots and Mycotoxins in Maize by Near-Infrared Reflectance Spectroscopy
  Journal of Agricultural and Food Chemistry, 2005
• DETECTING AFLATOXIN IN SINGLE CORN KERNELS BY TRANSMITTANCE AND REFLECTANCE SPECTROSCOPY
  Transactions of the ASAE, 2001
• Kernel-PCA algorithms for wide data Part II: Fast cross-validation and application in classification of NIR data
  Chemometrics and Intelligent Laboratory Systems, 1997