基于低场核磁弛豫特性的油茶籽油支持向量机掺伪鉴别模型的建立与评价  

Establishment and Evaluation of Support Vector Machine Model for Adulteration Discrimination of Camellia Oil Based on Low-Field Nuclear Magnetic Resonance Relaxation Characteristics

作　　者：林晓浪 傅利斌 王欣[1] LIN Xiaoang;FU Libin;WANG Xin(School of Health Science and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Hongkou District Market Supervision and Administration,Shanghai 200081,China)

机构地区：[1]上海理工大学健康科学与工程学院,上海200093 [2]上海市虹口区市场监督管理局,上海200081

出　　处：《食品科学》2024年第10期19-27,共9页Food Science

基　　金：“十四五”国家重点研发计划重点专项(2022YFF1101100)。

摘　　要：油茶籽油商业价值高,有必要开发快速准确的油茶籽油掺伪鉴别方法。本实验研究低场核磁共振(low-field nuclear magnetic resonance,LF-NMR)弛豫特性结合支持向量机(support vector machine,SVM)鉴别油茶籽油掺伪的可行性。在比较了油茶籽油、3种其他种类的正常/氧化的食用油及多种二元掺兑油样的LF-NMR弛豫特性的基础上进行主成分分析,设计了具有二叉树结构的SVM多分类器,采用ReliefF算法进行特征筛选,建立并验证了油茶籽油掺伪的SVM鉴别模型。研究表明,油脂种类、氧化程度及掺兑比例均会影响油样的LF-NMR弛豫特性。当特征数为9时,SVM多分类模型性能最佳,准确率可达90.77%,对油茶籽油、掺兑类型及比例的平均召回率为90.87%、精确率为90.83%、F1分数为0.90。这表明基于LF-NMR弛豫特性的SVM模型可用于油茶籽油的掺伪鉴别。The high commercial value of camellia oil entails the development of a rapid and accurate method for identifying camellia oil adulteration.In this study,the feasibility of using low-field nuclear magnetic resonance(LF-NMR)relaxation characteristics and support vector machine(SVM)to detect adulteration in camellia oil was investigated.The LF-NMR relaxation characteristics of raw and oxidized oils of camellia and three other species and their binary blends were compared.Furthermore,principal component analysis was carried out and then an SVM multi-classifier with a binary tree structure was designed.After feature screening by the ReliefF algorithm,an SVM model for identifying adulteration in camellia oil was established and evaluated.The results showed that the LF-NMR relaxation characteristics of oil samples were affected by oil type,oxidation degree and blending ratio.The SVM multi-classification model with 9 features exhibited the best performance,with an accuracy of 90.77%.Additionally,the average recall,precision and F1 score for camellia oil,blending type and ratio were 90.87%,90.83%and 0.90,respectively.This study indicated that the SVM model based on LF-NMR relaxation characteristics could be employed for identifying adulteration in camellia oil.

关 键 词：油茶籽油 掺伪鉴别 低场核磁共振 支持向量机 主成分分析 RELIEFF算法 

分 类 号：TS227[轻工技术与工程—粮食、油脂及植物蛋白工程]