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Publishing Language: Chinese

Application and Prospect of Integrated Food Testing Technology Based on Artificial Intelligence

Haohan DING1,2, Zhenqi XIE2, Song SHEN2, Xiaohui CUI1,3(), Zhenyu WANG4, Ou FU1, Jun WAN2
Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
Jiaxing Institute of Future Food, Jiaxing 314005, China
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Abstract

The integration of artificial intelligence (AI) and rapid detection technologies has brought significant transformations to the field of food testing, driving advancements in food safety, quality, and authenticity identification capabilities. The current status of the application of integrated rapid detection technologies in food testing technology based on AI was introduced. In chemical and biological contamination testing, the combination of AI and rapid testing technologies effectively enhances the efficiency and accuracy of food safety testing. In terms of food quality testing, AI combined with rapid testing technologies is widely used for quality assessment of fruits, meat products, aquatic products, and other foods, achieving precise measurement through efficient data analysis and intelligent recognition. Moreover, AI is applied in food authenticity identification, including adulteration detection and geographic traceability, ensuring the authenticity and reliability of food products. Especially when blockchain technology is integrated with AI, blockchain-based traceability systems ensure full traceability of food through transparent and tamper-proof records, while AI algorithms can analyze data from the food supply chain in real-time to identify potential risks and anomalies. The integration of these technologies could not only enhance the overall level of food testing, but also lay the foundation for the construction of future intelligent food testing systems.

Keywords

artificial intelligencefood testingtechnology integrationmachine learningdeep learning
CLC number: TS207;TP18 Document code: A Article ID: 2095-6002(2024)05-0013-11

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Journal of Food Science and Technology
Volume 42 Issue 5,
September 2024
Pages 13-23,32
DOI: 10.12301/spxb202400408
Cite this article:
DING H, XIE Z, SHEN S, et al. Application and Prospect of Integrated Food Testing Technology Based on Artificial Intelligence. Journal of Food Science and Technology, 2024, 42(5): 13-23,32. https://doi.org/10.12301/spxb202400408
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