The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

Author:

Zhang Longlong12ORCID,Yang Qiuping23,Zhu Zhiyuan2

Affiliation:

1. Key Laboratory of Intelligent Manufacturing Technology (Shantou University), Ministry of Education, Shantou 515063, China

2. College of Electronic Engineering, Southwest University, Chongqing 400715, China

3. Hubei Key Laboratory of Food Nutrition and Safety, Huazhong University of Science and Technology, Wuhan 430030, China

Abstract

Against the backdrop of continuous socio-economic development, there is a growing concern among people about food quality and safety. Individuals are increasingly realizing the critical importance of healthy eating for bodily health; hence the continuous rise in demand for detecting food pollution. Simultaneously, the rapid expansion of global food trade has made people’s pursuit of high-quality food more urgent. However, traditional methods of food analysis have certain limitations, mainly manifested in the high degree of reliance on personal subjective judgment for assessing food quality. In this context, the emergence of artificial intelligence and biosensors has provided new possibilities for the evaluation of food quality. This paper proposes a comprehensive approach that involves aggregating data relevant to food quality indices and developing corresponding evaluation models to highlight the effectiveness and comprehensiveness of artificial intelligence and biosensors in food quality evaluation. The potential prospects and challenges of this method in the field of food safety are comprehensively discussed, aiming to provide valuable references for future research and practice.

Funder

Key Laboratory of Intelligent Manufacturing Technology

Ministry of Education

Hubei Key Laboratory of Food Nutrition and Safety

Publisher

MDPI AG

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