Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics

IF 5.6 1区农林科学 Q1 FOOD SCIENCE & TECHNOLOGY

Food Control Pub Date : 2024-11-16 DOI:10.1016/j.foodcont.2024.111033

Ting Shi , Tenghui Dai , Gangcheng Wu , Qingzhe Jin , Xingguo Wang

{"title":"Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics","authors":"Ting Shi , Tenghui Dai , Gangcheng Wu , Qingzhe Jin , Xingguo Wang","doi":"10.1016/j.foodcont.2024.111033","DOIUrl":null,"url":null,"abstract":"<div><div>The volatile compounds combined with chemometrics, were used for different grade camellia oil adulterated detection. Using unsupervised models with fatty acids or triglycerides as input variables, the first-grade camellia oils (CAO Ⅰ) and second-grade camellia oils (CAO Ⅱ) occurred severely overlay in principle component analysis (PCA), for their almost quite identical compositions. While based on volatile components, hierarchical clustering analysis (HCA) presented a clear boundary between CAO Ⅰ and CAO Ⅱ samples. Subsequently, using our selected 15 volatile components by the variable importance in projection (VIP), both orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and support vector machines (SVM), could be utilized as complementary models for camellia oil grade authentication with good classification rate (≥91.67%). In addition, according to those above characteristic variables with auto-scaling pretreatment, the optimized OPLS model could be recommended for adulterated level prediction (5%–100%, w/w).</div></div>","PeriodicalId":319,"journal":{"name":"Food Control","volume":"169 ","pages":"Article 111033"},"PeriodicalIF":5.6000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Control","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0956713524007503","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

The volatile compounds combined with chemometrics, were used for different grade camellia oil adulterated detection. Using unsupervised models with fatty acids or triglycerides as input variables, the first-grade camellia oils (CAO Ⅰ) and second-grade camellia oils (CAO Ⅱ) occurred severely overlay in principle component analysis (PCA), for their almost quite identical compositions. While based on volatile components, hierarchical clustering analysis (HCA) presented a clear boundary between CAO Ⅰ and CAO Ⅱ samples. Subsequently, using our selected 15 volatile components by the variable importance in projection (VIP), both orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and support vector machines (SVM), could be utilized as complementary models for camellia oil grade authentication with good classification rate (≥91.67%). In addition, according to those above characteristic variables with auto-scaling pretreatment, the optimized OPLS model could be recommended for adulterated level prediction (5%–100%, w/w).

查看原文本刊更多论文

利用特征挥发性成分 GC-MS 指纹结合化学计量学检测山茶油分级掺假情况

将挥发性化合物与化学计量学相结合，用于不同等级山茶油的掺假检测。使用以脂肪酸或甘油三酯为输入变量的无监督模型，一级山茶油（CAO Ⅰ）和二级山茶油（CAO Ⅱ）在原理成分分析（PCA）中出现严重重叠，因为它们的成分几乎完全相同。而基于挥发性成分的层次聚类分析（HCA）则在 CAO Ⅰ 和 CAO Ⅱ 样品之间显示出明显的界限。随后，利用所选的 15 个挥发性成分的投影重要性变量（VIP），将正交投影潜结构判别分析（OPLS-DA）和支持向量机（SVM）作为山茶油等级鉴定的补充模型，分类率良好（≥91.67%）。此外，根据上述特征变量并进行自动缩放预处理，优化后的 OPLS 模型可推荐用于掺假水平预测（5%-100%，w/w）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Food Control 工程技术-食品科技

CiteScore

12.20

自引率

6.70%

发文量

758

审稿时长

33 days

期刊介绍： Food Control is an international journal that provides essential information for those involved in food safety and process control. Food Control covers the below areas that relate to food process control or to food safety of human foods: • Microbial food safety and antimicrobial systems • Mycotoxins • Hazard analysis, HACCP and food safety objectives • Risk assessment, including microbial and chemical hazards • Quality assurance • Good manufacturing practices • Food process systems design and control • Food Packaging technology and materials in contact with foods • Rapid methods of analysis and detection, including sensor technology • Codes of practice, legislation and international harmonization • Consumer issues • Education, training and research needs. The scope of Food Control is comprehensive and includes original research papers, authoritative reviews, short communications, comment articles that report on new developments in food control, and position papers.