Classification of aflatoxin contaminated chili pepper using hyperspectral imaging and artificial neural networks

Date

2010-04-24

Author

ATAŞ, MUSA
Temizel, Alptekin
ÇETİN, YASEMİN

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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

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Graduate School of Informatics, Conference / Seminar

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Citation Formats

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.