基于快速蒸发电离质谱技术鉴别咖啡掺伪

doi:10.14088/j.cnki.issn0439-8114.2024.12.031

湖北农业科学 ›› 2024, Vol. 63 ›› Issue (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

吴婉琴^1,2, 江丰^1,2, 范小龙^1,2, 黎星^1,2, 朱松松^1,2, 汪薇^1,2, 张莉^1,2, 张亚珍^1,2, 朱晓玲^1,2, 冯猛³

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;
2.湖北时珍实验室,武汉 430065;
3.沃特世科技（上海）有限公司,上海 201206

收稿日期:2023-10-13 出版日期:2024-12-25 发布日期:2025-01-08
通讯作者: 汪薇（1989-）,女,湖北武汉人,高级工程师,主要从事食品安全检测研究,（电子信箱）291668142@qq.com。
作者简介:吴婉琴（1991-）,女,湖北荆州人,工程师,主要从事食品安全检测研究,（电话）15327117381（电子信箱）429371379@qq.com。
基金资助:
湖北省市场监督管理局科技计划项目（Hbscjg-KJ2021002）; 湖北省自然科学基金项目（2022CFB789）

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

WU Wan-qin^1,2, JIANG Feng^1,2, FAN Xiao-long^1,2, LI Xing^1,2, ZHU Song-song^1,2, WANG Wei^1,2, ZHANG Li^1,2, ZHANG Ya-zhen^1,2, ZHU Xiao-ling^1,2, FENG Meng³

1. Key Laboratory of Detection Technology of Focus Chemical Hazards in Animal-derived Food for State Market Regulation/NHC Specialty Laboratory of Food Safety Risk Assessment and Standard Development,Hubei Provincial Institute for Food Supervision and Test ,Wuhan 430075, China;
2. Hubei Shizhen Laboratory, Wuhan 430065, China;
3. Waters Technology （Shanghai） Co., Ltd., Shanghai 201206, China

Received:2023-10-13 Published:2024-12-25 Online:2025-01-08

摘要/Abstract

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。

关键词: 快速蒸发电离质谱, 咖啡, 掺伪, PCA-LDA模型

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 soybean, 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 adulterated black soybean and black corn in coffee samples.

Key words: rapid evaporation ionization mass spectrometry, coffee, adulteration, PCA-LDA model

中图分类号:

TS255.1

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. 基于快速蒸发电离质谱技术鉴别咖啡掺伪[J]. 湖北农业科学, 2024, 63(12): 171-177.

WU Wan-qin, JIANG Feng, FAN Xiao-long, LI Xing, ZHU Song-song, WANG Wei, ZHANG Li, ZHANG Ya-zhen, ZHU Xiao-ling, FENG Meng. Identification of coffee adulteration based on rapid evaporation ionization mass spectrometry technology[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(12): 171-177.

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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

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