Loquat Bruise Detection Using Optical Coherence Tomography Based on Microstructural Parameters
- 193 Downloads
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.
KeywordsOCT Microstructure Bruise Detection Loquat
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.
Compliance with Ethical Standards
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.
- Chen XP, Jiang JM, Xu XD, Zheng SQ (2006) Fruit tissue structure of loquat cultivars. In: II International Symposium on Loquat 750, pp 253–258Google Scholar
- Egea I, Bian W, Barsan C, Jauneau A, Pech JC, Latché A et al (2011) Chloroplast to chromoplast transition in tomato fruit: spectral confocal microscopy analyses of carotenoids and chlorophylls in isolated plastids and time-lapse recording on intact live tissue. Ann Bot 108(2):291–297CrossRefPubMedPubMedCentralGoogle Scholar
- Ford HD, Tatam RP, Landahl S, Terry LA (2011) Investigation of disease in stored onions using optical coherence tomography. In: IV International Conference Postharvest Unlimited 2011 945, pp 247–254Google Scholar
- Hernández-Sánchez N, Moreda GP, Herre-ro-Langreo A, Melado-Herreros Á (2016) Assessment of internal and external quality of fruits and vegetables. In Imaging Technologies and Data Processing for Food Engineers (pp 269–309). Springer International PublishingGoogle Scholar
- Landahl S, Terry LA, Ford HD (2012) Investigation of diseased onion bulbs using data processing of optical coherence tomography images. In VI International Symposium on Edible Alliaceae 969, pp 261–270Google Scholar
- Li M, East AR, Heyes JA, Verboven P, Nicolaї B, Buchsbaum A (2014) Development of an optical coherence tomography image analysis method to characterise cellular structure of kiwifruit. In XXIX International Horticultural Congress on Horticulture: Sustaining Lives, Livelihoods and Landscapes (IHC2014): 1119, pp 127–134Google Scholar
- Testoni A, Grassi A (1995) Aspetti qualitativi e conservabilità di alcune cultivar di nespolo del GiapponeGoogle Scholar
- Tian S, Li B, Ding Z (2007) Physiological properties and storage technologies of loquat fruit. Fresh Produce 1(1):76–81Google Scholar
- Wijesinghe R, Lee SY, Ravichandran NK, Shirazi MF, Kim P, Jung HY et al (2016) Optical screening of venturianashicola caused pyruspyrifolia (asian pear) scab using optical coherence tomography. Int J Appl Eng Res 11(12):7728–7731Google Scholar
- Yamanaka M, Kawagoe H, Nishizawa N (2015) Non-destructive cross-sectional imaging of tomato using ultra-high resolution optical coherence tomography. In Society of Instrument and Control Engineers of Japan (SICE), 2015 54th Annual Conference of the (pp 95–96). IEEEGoogle Scholar