摘要
[目的]提高牛奶掺假检测的准确率。[方法]提出一种结合拉曼光谱和时空注意力网络的牛奶掺假检测方法,通过拉曼光谱提取分子特征,利用拉曼光谱和时空注意力网络模型提取时序和空间特征,并通过自注意力机制加权重要信息。[结果]与现有方法相比,试验方法的牛奶掺假检测准确率平均提升了4.5%,精确度平均提升了约5.8%,召回率平均提升了4.9%,F1分数平均提升了5.4%。[结论]试验方法对牛奶掺假检测具有高精度、高鲁棒性、实时检测潜力和可推广性,能够应用于牛奶生产及监管过程中的在线质量监控,并可拓展至其他食品的掺假检测中。
[Objective]To enhance the milk adulteration detection accuracy.[Methods]This study proposes a milk adulteration detection method by integrating Raman spectroscopy with a spatiotemporal attention network(STAN).In the method,Raman spectroscopy is employed to extract molecular features,while STAN is applied to capture both temporal and spatial features,with a self-attention mechanism for further emphasizing critical information.[Results]Compared with existing methods,the experimental method increases milk adulteration detection accuracy by an average of 4.5%,precision by about 5.8%,recall by 4.9%,and F1 score by 5.4%.[Conclusion]The experimental method achieves high accuracy and robustness in milk adulteration detection,with strong potential for real-time detection and broad applicability.It can be utilized for online quality monitoring in milk production and regulatory processes and extended to adulteration detection in other foods.
作者
刘延梅
赵宝峰
马慧莲
LIU Yanmei;ZHAO Baofeng;MA Huilian(Shanxi Police Vocational College,Taiyuan,Shanxi 030006,China;Taiyuan University of Technology,Taiyuan,Shanxi 030024,China;Taiyuan Institute of Technology,Taiyuan,Shanxi 030008,China)
出处
《食品与机械》
北大核心
2025年第5期71-76,共6页
Food and Machinery
基金
山西省教育科学规划课题(编号:ZJ-07130)
山西省教育教学改革与实践研究项目(编号:202403069)。
关键词
牛奶掺假
拉曼光谱
时空注意力网络
在线检测
食品安全
milk adulteration
Raman spectroscopy
spatiotemporal attention network
online detection
food safety
