食品安全中的人工智能:第三级研究
Marina Arribas Lopez1, Yamine Bouzembrak1, Bedir Tekinerdogan1
1Information Technology Group, Wageningen University & Research, Wageningen, the Netherlands.
Comprehensive reviews in food science and food safety
|March 14, 2026
概括
人工智能 (AI) 通过分析庞大的数据集来提高食品安全. 本研究综合了人工智能在食品安全方面的应用,发现神经网络普遍用于化学危害检测,特别是在乳制品中.
科学领域:
- 食品科学 食品科学 食品科学
- 计算机科学 计算机科学
- 数据科学数据科学数据科学
背景情况:
- 食品安全对公共健康至关重要,防止消费者接触危险产品.
- 人工智能 (AI) 提供了分析食品安全大数据集的先进功能.
- 现有的研究突出了AI应用,但缺乏系统性审查的综合概述.
研究的目的:
- 为食品安全领域的人工智能应用提供全面的三级分析.
- 确定人工智能驱动的食品安全研究的趋势,包括数据源,危险和算法.
- 突出在食品安全领域对人工智能的挑战和未来方向.
主要方法:
- 对中学研究进行系统的三级分析.
- 识别和综合现有的对食品安全人工智能系统审查的趋势.
- 根据食品类型,数据源,危害和算法对AI应用进行分类.
主要成果:
- 乳制品是研究最多的食品类别,传感数据是主要来源.
- 神经网络是最常用的AI算法.
- 应用主要集中在化学危险检测上,仅限于使用非结构化数据.
结论:
- 人工智能,特别是神经网络,在检测化学食品安全危害方面显示出重大前景.
- 需要探索AI应用,利用非结构化数据进行全面的食品安全监测.
- 大型语言模型 (LLM) 为推进食品安全和监管合规性提供了未来的途径.
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