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Classification of aflatoxin contaminated chili pepper using hyperspectral imaging and artificial neural networks
Date
2010-04-24
Author
ATAŞ, MUSA
Temizel, Alptekin
ÇETİN, YASEMİN
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Many foods (such as hazelnut, pistachio nut, almond, corn, wheat, dried fig, and chili pepper) may include carcinogenic aflatoxins that threatens human health. Chili pepper is also prone to aflatoxin contamination during harvesting, production and storage periods. Although Turkey is the third largest chili pepper producer in the world, it has less than three percent international market share due to the high level of aflatoxin contamination in the chili pepper. Various chemical methods are used for detection of aflatoxin. Chemical methods used for detection of aflatoxin contamination give accurate results, but they are slow, expensive and destructive. In this study, intensity histograms of hyper spectral images of chili peppers are extracted under halogen illumination source and aflatoxin detection is made by artificial neural networks.
Subject Keywords
Chemical engineering
,
Contamination
,
Food products
,
Halogens
,
Health hazards
,
International trade
,
Lighting
,
Neural nets
,
Pattern classification
,
Production engineering computing
URI
https://hdl.handle.net/11511/31568
DOI
https://doi.org/10.1109/siu.2010.5650935
Collections
Graduate School of Informatics, Conference / Seminar
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M. ATAŞ, A. Temizel, and Y. ÇETİN, “Classification of aflatoxin contaminated chili pepper using hyperspectral imaging and artificial neural networks,” 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31568.