湖北农业科学2024,Vol.63Issue(12) :171-177.DOI:10.14088/j.cnki.issn0439-8114.2024.12.031

基于快速蒸发电离质谱技术鉴别咖啡掺伪

Identification of coffee adulteration based on rapid evaporation ionization mass spectrometry technology

吴婉琴 江丰 范小龙 黎星 朱松松 汪薇 张莉 张亚珍 朱晓玲 冯猛
湖北农业科学2024,Vol.63Issue(12) :171-177.DOI:10.14088/j.cnki.issn0439-8114.2024.12.031

基于快速蒸发电离质谱技术鉴别咖啡掺伪

Identification of coffee adulteration based on rapid evaporation ionization mass spectrometry technology

吴婉琴 1江丰 1范小龙 1黎星 1朱松松 1汪薇 1张莉 1张亚珍 1朱晓玲 1冯猛2
扫码查看

作者信息

  • 1. 湖北省食品质量安全监督检验研究院国家市场监管重点实验室(动物源性食品中重点化学危害物检测技术)/国家卫生健康委员会食品安全风险评估与标准研制特色实验室,武汉 430075;湖北时珍实验室,武汉 430065
  • 2. 沃特世科技(上海)有限公司,上海 201206
  • 折叠

摘要

对咖啡及其掺伪物黑豆、黑玉米以及不同比例掺伪咖啡样品进行评估,采用快速蒸发电离质谱(REIMS)采集各样品一级全扫质谱数据,构建样品主成分分析-线性判别分析(PCA-LDA)模型,并进行leave-20%-out模式验证.结果表明,咖啡粉、黑豆粉及黑玉米粉样品的识别正确率为100.00%,咖啡粉、黑豆粉及不同比例黑豆粉掺伪咖啡粉样品的识别正确率为97.07%,咖啡粉、黑玉米粉及不同比例黑玉米粉掺伪咖啡粉样品的识别正确率为96.60%,可以较好地区分咖啡、黑豆、黑玉米以及不同比例掺伪咖啡样品,构建的模型可实现样品的瞬时实时识别.采用Live ID软件对随机的原料样品和不同比例(5%、10%、20%、30%、40%、50%)掺伪咖啡样品进行实时识别,结果表明各样品均被正确识别,掺伪比例检出限最低可达5%.该方法可高效、快速、准确地监测咖啡掺伪情况,有效满足咖啡样品中掺伪黑豆和黑玉米的鉴别需求.

Abstract

Coffee and its adulterated black soybean,black corn,and coffee samples with different proportions of adulteration were evaluated,rapid evaporation ionization mass spectrometry(REIMS)to was used collect primary full scan mass spectrometry data of each sample,a sample principal component analysis linear discriminant analysis(PCA-LDA)model was constructed,and the leave-20%-out mode was validated.The results showed that the correct recognition rate of coffee powder,black soybean powder and black corn powder samples was 100.00%,the correct recognition rate of coffee powder,black soybean powder and different proportion of black soybean powder adulterated with coffee powder samples was 97.07%,and the correct recognition rate of coffee powder,black corn powder and different proportion of black corn powder adulterated with coffee powder samples was 96.60%.Coffee,black soy-bean,black corn and different proportion of adulterated coffee samples could be better distinguished.The model constructed could achieve instantaneous real-time recognition of samples.Real time identification of random raw material samples and coffee samples with different proportions(5%,10%,20%,30%,40%,and 50%)of adulteration was carried out using Live ID software.The results showed that all samples were correctly identified,and the detection limit of adulteration proportion could reach as low as 5%.This method could efficiently,quickly,and accurately monitor coffee adulteration,effectively meeting the identification needs of adulterat-ed black soybean and black corn in coffee samples.

关键词

快速蒸发电离质谱/咖啡/掺伪/PCA-LDA模型

Key words

rapid evaporation ionization mass spectrometry/coffee/adulteration/PCA-LDA model

引用本文复制引用

出版年

2024
湖北农业科学
湖北省农业科学院 华中农业大学 长江大学 黄冈师范学院

湖北农业科学

CSTPCD
影响因子:0.442
ISSN:0439-8114
段落导航相关论文