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Loquat Bruise Detection Using Optical Coherence Tomography Based on Microstructural Parameters

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Abstract

Slight postharvest bruises of loquats remarkably affect the quality and shelf life of the fruits, but they are difficult to identify using visual inspection. Sub-surface structural changes in cells caused by mechanical injury or impact can be detected using spectroscopy-based methods from different angles. Optical coherence tomography (OCT), a non-destructive technology, can acquire cross-sectional images to analyze sub-surface structures of loquats, thus offering the potential to identify fruit bruises. This study proposes an automated OCT image processing method for extracting large cells from loquat images, which involves a series of steps including image denoising, boundary detection, filtering, binarization, segmentation, and region selection. Parenchyma cells in loquat tissue were visualized and characterized, and the five-cell morphological parameters, including total cell surface area, average cell surface area, average cell Feret diameter, equivalent diameter, and cell amount were measured. The bruised and non-bruised loquat groups showed significant differences in the total cell surface area and cell amount, suggesting that these two parameters might be used as indictors for bruise identification. No significant differences in other parameters were observed between the two groups. The microcosm approach proposed in this study sheds some light on ways to improve fruit quality evaluation. Overall, combined with appropriate image processing, OCT is an efficient and non-destructive tool for loquat bruise detection. The proposed strategy might also be expanded to other agricultural applications.

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Acknowledgements

This research is financially supported by National Natural Science Foundation of China (No. U1709212, No. 61605173, No. 61403346, No. 61502429), Scientific Research Project of Zhejiang Province (No. 2017C31010, No. GG18F030012), National Key Research and Development Program of China (2016YFF0201904, 2017YFF0207804), Natural Science Foundation of Zhejiang Province (Project No. LY16C130003), Open Foundation of Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing and Zhejiang Provincial Key Lab. for Chem. & Bio. Processing Technology of Farm Products, No. 2016KF0035, and China Scholarship Council No.201608330413. We would like to express our gratitude to Dr. Hui Nie, who helped us in improving the language of the manuscript.

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Authors and Affiliations

  1. School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, 310023, China

    Yang Zhou, Wujie Zhou, Yun Zhao, Zhengwei Chen & Fangni Chen

  2. Zhejiang Province Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou, 310023, China

    Yang Zhou, Jianwei Mao, Tiebing Liu & Zhengwei Chen

  3. Zhejiang Provincial Key Lab. for Chem. & Bio. Processing Technology of Farm Products, Liuhe Road 318#, Xihu District, Hangzhou City, 310023, Zhejiang Province, China

    Yang Zhou, Jianwei Mao, Tiebing Liu & Zhengwei Chen

  4. College of Agriculture & Biotechnology, Zhejiang University, Hangzhou, 310058, China

    Di Wu

  5. School of Information Engineering, Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province, Zhejiang A & F University, Linan, 311300, China

    Guohua Hui

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  1. Yang Zhou
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Correspondence to Yang Zhou or Guohua Hui.

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This article does not contain any studies with human or animal subjects.

Conflict of Interest

Yang Zhou declares that he has no conflict of interest. Di Wu declares that he has no conflict of interest. Guohua Hui declares that he has no conflict of interest. Jianwei Mao declares that he has no conflict of interest. Tiebing Liu declares that he has no conflict of interest. Wujie Zhou declares that he has no conflict of interest. Yun Zhao declares that she has no conflict of interest. Zhengwei Chen declares that he has no conflict of interest. Fangni Chen declares that she has no conflict of interest.

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Zhou, Y., Wu, D., Hui, G. et al. Loquat Bruise Detection Using Optical Coherence Tomography Based on Microstructural Parameters. Food Anal. Methods 11, 2692–2698 (2018). https://doi.org/10.1007/s12161-018-1246-6

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  • DOI: https://doi.org/10.1007/s12161-018-1246-6

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