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Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques

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Abstract

Non-destructive detection methods to identify food foreign contaminants meet the development of the food industry. Near infrared (NIR) spectroscopy and computer vision (CV) have been considerably intriguing due to the advantages of safety and rapidity. In this study, foreign contaminants, including metallic iron, polypropylene plastic, and hair in bread, were identified based on these two techniques. In NIR spectroscopy, the effectiveness of distance match and discriminant analysis methods combined with different spectral pretreatments was compared. It showed that the accuracy was 98%, 94%, 91%, and F-score was 0.97, 0.93, and 0.91 in the validation set for detecting foreign contaminants aforementioned when discriminant analysis combined with Savitzky-Golay smoothing was used. In CV, deep learning based on the modified U-net has applied to segment these contaminants on the surface of the bread; the accuracy of the test set was 95%, 93%, and 92%, respectively. Based on the results, it can be concluded that NIR spectroscopy and CV are both an operational way to detect foreign contaminants in bread. And these two techniques could be combined to apply in on-line detection further.

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Acknowledgements

This work was supported by the National Key R&D Program of China (2017YFC1600805).

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Authors and Affiliations

  1. College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, People’s Republic of China

    Jifan Yin, Saima Hameed, Lijuan Xie & Yibin Ying

  2. Key Laboratory of On-Site Processing Equipment for Agricultural Products, Ministry of Agriculture and Rural Affairs, Zhejiang University, Hangzhou, 310058, People’s Republic of China

    Jifan Yin, Saima Hameed, Lijuan Xie & Yibin Ying

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  1. Jifan Yin
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  2. Saima Hameed
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  3. Lijuan Xie
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  4. Yibin Ying
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Correspondence to Lijuan Xie.

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Yin, J., Hameed, S., Xie, L. et al. Non-destructive detection of foreign contaminants in toast bread with near infrared spectroscopy and computer vision techniques. Food Measure 15, 189–198 (2021). https://doi.org/10.1007/s11694-020-00627-6

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  • DOI: https://doi.org/10.1007/s11694-020-00627-6

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