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Volume 14
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10.3390/foods14030386
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Review

Advances in Computer Vision and Spectroscopy Techniques for Non-Destructive Quality Assessment of Citrus Fruits: A Comprehensive Review

by
Kai Yu
1,
Mingming Zhong
1,
Wenjing Zhu
2,*,
Arif Rashid
1,
Rongwei Han
3,
Muhammad Safiullah Virk
1,
Kaiwen Duan
2,
Yongjun Zhao
1 and
Xiaofeng Ren
1,4,*
1
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China
2
School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
3
College of Food Science and Engineering, Qingdao Agricultural University, Qingdao 266109, China
4
Institute of Food Physical Processing, Jiangsu University, Zhenjiang 212013, China
*
Authors to whom correspondence should be addressed.
Foods 2025, 14(3), 386; https://doi.org/10.3390/foods14030386
Submission received: 4 January 2025 / Revised: 18 January 2025 / Accepted: 22 January 2025 / Published: 24 January 2025
(This article belongs to the Special Issue Non-Destructive Quality Evaluation Methods for Foods)
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Abstract

Citrus fruits, classified under the Rutaceae family and Citrus genus, are valued for their high nutritional content, attributed to their rich array of natural bioactive compounds. To ensure both quality and nutritional value, precise non-destructive testing methods are crucial. Among these, computer vision and spectroscopy technologies have emerged as key tools. This review examines the principles and applications of computer vision technologies—including traditional computer vision, hyperspectral, and multispectral imaging—as well as various spectroscopy techniques, such as infrared, Raman, fluorescence, terahertz, and nuclear magnetic resonance spectroscopy. Additionally, data fusion methods that integrate these technologies are discussed. The review explores innovative uses of these approaches in Citrus quality inspection and grading, damage detection, adulteration identification, and traceability assessment. Each technology offers distinct characteristics and advantages tailored to the specific testing requirements in Citrus production. Through data fusion, these technologies can be synergistically combined, enhancing the accuracy and depth of Citrus quality assessments. Future advancements in this field will likely focus on optimizing data fusion algorithms, selecting effective preprocessing and feature extraction techniques, and developing portable, on-site detection devices. These innovations will drive the Citrus industry toward increased intelligence and precision in quality control.
Keywords: Citrus fruit; computer vision; spectroscopy; data fusion; non-destructive quality assessment Citrus fruit; computer vision; spectroscopy; data fusion; non-destructive quality assessment
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MDPI and ACS Style

Yu, K.; Zhong, M.; Zhu, W.; Rashid, A.; Han, R.; Virk, M.S.; Duan, K.; Zhao, Y.; Ren, X. Advances in Computer Vision and Spectroscopy Techniques for Non-Destructive Quality Assessment of Citrus Fruits: A Comprehensive Review. Foods 2025, 14, 386. https://doi.org/10.3390/foods14030386

AMA Style

Yu K, Zhong M, Zhu W, Rashid A, Han R, Virk MS, Duan K, Zhao Y, Ren X. Advances in Computer Vision and Spectroscopy Techniques for Non-Destructive Quality Assessment of Citrus Fruits: A Comprehensive Review. Foods. 2025; 14(3):386. https://doi.org/10.3390/foods14030386

Chicago/Turabian Style

Yu, Kai, Mingming Zhong, Wenjing Zhu, Arif Rashid, Rongwei Han, Muhammad Safiullah Virk, Kaiwen Duan, Yongjun Zhao, and Xiaofeng Ren. 2025. "Advances in Computer Vision and Spectroscopy Techniques for Non-Destructive Quality Assessment of Citrus Fruits: A Comprehensive Review" Foods 14, no. 3: 386. https://doi.org/10.3390/foods14030386

APA Style

Yu, K., Zhong, M., Zhu, W., Rashid, A., Han, R., Virk, M. S., Duan, K., Zhao, Y., & Ren, X. (2025). Advances in Computer Vision and Spectroscopy Techniques for Non-Destructive Quality Assessment of Citrus Fruits: A Comprehensive Review. Foods, 14(3), 386. https://doi.org/10.3390/foods14030386

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