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The development of a simple multispectral algorithm for detection of fecal contamination on apples using a hyperspectral line-scan imaging system

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Abstract

Foodborne diseases are of serious concern to public health. It is necessary to develop fast and reliable non-destructive detection methods to improve food product monitoring for the food industry. This research was conducted to investigate hyperspectral fluorescence imaging using violet/blue LED excitation to develop a multispectral algorithm for detection of fecal contamination on Golden Delicious apples. From the hyperspectral image data, four wavebands, 680, 684, 720, and 780 nm, were selected for potential use in a multispectral detection algorithm. The algorithm could detect 96–100% of different dilutions of feces on apples. The highly successfully detection of feces showed that a simple multispectral fluorescence imaging algorithm based on violet/blue LED excitation can be used to detect fecal contamination on apple processing lines.

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Acknowledgments

This work was partially supported by a grant from the BioGreen 21 Program (no. PJ007208), Rural Development Administration, Republic of Korea.

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Authors and Affiliations

  1. Environmental Microbial and Food Safety Laboratory, BARC-East, USDA-ARS, 10300 Baltimore Avenue, Beltsville, MD, 20705, USA

    Chun-Chieh Yang, Moon S. Kim, Kuanglin Chao, Alan M. Lefcourt & Diane E. Chan

  2. National Academy of Agricultural Science, Rural Development Administration, Suwon, 441-100, Korea

    Sukwon Kang

  3. Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA

    Tao Tao

Authors
  1. Chun-Chieh Yang
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  2. Moon S. Kim
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  3. Sukwon Kang
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  4. Tao Tao
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  5. Kuanglin Chao
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  6. Alan M. Lefcourt
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  7. Diane E. Chan
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Correspondence to Moon S. Kim.

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Yang, CC., Kim, M.S., Kang, S. et al. The development of a simple multispectral algorithm for detection of fecal contamination on apples using a hyperspectral line-scan imaging system. Sens. & Instrumen. Food Qual. 5, 10–18 (2011). https://doi.org/10.1007/s11694-010-9105-1

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  • DOI: https://doi.org/10.1007/s11694-010-9105-1

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