Zhang Longlong, Yang Qiuping, Zhu Zhiyuan
Key Laboratory of Intelligent Manufacturing Technology (Shantou University), Ministry of Education, Shantou 515063, China.
College of Electronic Engineering, Southwest University, Chongqing 400715, China.
Foods. 2024 Jun 19;13(12):1936. doi: 10.3390/foods13121936.
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.
在社会经济持续发展的背景下，人们对食品质量和安全的关注度日益提高。个人越来越意识到健康饮食对身体健康的至关重要性；因此，对检测食品污染的需求持续上升。同时，全球食品贸易的迅速扩张使人们对高品质食品的追求更加迫切。然而，传统的食品分析方法存在一定局限性，主要体现在评估食品质量时高度依赖个人主观判断。在这种背景下，人工智能和生物传感器的出现为食品质量评估提供了新的可能性。本文提出了一种综合方法，包括汇总与食品质量指标相关的数据并开发相应的评估模型，以突出人工智能和生物传感器在食品质量评估中的有效性和全面性。全面讨论了该方法在食品安全领域的潜在前景和挑战，旨在为未来的研究和实践提供有价值的参考。
