Aflatoxin detection in whole corn kernels using hyperspectral methods

David Casasent; Xue-Wen Chen

doi:10.1117/12.516135

30 March 2004 Aflatoxin detection in whole corn kernels using hyperspectral methods

David Casasent, Xue-Wen Chen

Author Affiliations +

Proceedings Volume 5271, Monitoring Food Safety, Agriculture, and Plant Health; (2004) https://doi.org/10.1117/12.516135
Event: Optical Technologies for Industrial, Environmental, and Biological Sensing, 2003, Providence, RI, United States

Abstract

Hyperspectral (HS) data for the inspection of whole corn kernels for aflatoxin is considered. The high-dimensionality of HS data requires feature extraction or selection for good classifier generalization. For fast and inexpensive data collection, only several features (λ responses) can be used. These are obtained by feature selection from the full HS response. A new high dimensionality branch and bound (HDBB) feature selection algorithm is used; it is found to be optimum, fast and very efficient. Initial results indicate that HS data is very promising for aflatoxin detection in whole kernel corn.

Citation Download Citation

David Casasent and Xue-Wen Chen "Aflatoxin detection in whole corn kernels using hyperspectral methods", Proc. SPIE 5271, Monitoring Food Safety, Agriculture, and Plant Health, (30 March 2004); https://doi.org/10.1117/12.516135

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