刘雅婧,袁建,鞠兴荣,邢常瑞,何荣,陈尚兵.电子舌快速检测食用植物油掺伪[J].食品安全质量检测学报,2018,9(10):2339-2344
电子舌快速检测食用植物油掺伪
Rapid detection of adulteration in vegetable oil using electronic tongue
投稿时间:2018-03-05  修订日期:2018-05-16
DOI:
中文关键词:  电子舌  食用油掺伪  主成分分析  判别因子分析
英文关键词:electronic tongue  edible oil adulteration  principal component analysis  discriminant factor analysis
基金项目:现代粮仓绿色储粮科技示范工程(2016YFD0401603)、江苏省高校优势学科建设工程资助项目
作者单位
刘雅婧 南京财经大学食品科学与工程学院 
袁建 南京财经大学食品科学与工程学院;江苏省现代粮食流通与安全协同创新中心;江苏高校粮油质量安全控制及深加工重点实验室 
鞠兴荣 南京财经大学食品科学与工程学院;江苏省现代粮食流通与安全协同创新中心;江苏高校粮油质量安全控制及深加工重点实验室 
邢常瑞 南京财经大学食品科学与工程学院;江苏省现代粮食流通与安全协同创新中心;江苏高校粮油质量安全控制及深加工重点实验室 
何荣 南京财经大学食品科学与工程学院;江苏省现代粮食流通与安全协同创新中心 
陈尚兵 南京财经大学食品科学与工程学院;江苏省现代粮食流通与安全协同创新中心;江苏高校粮油质量安全控制及深加工重点实验室 
AuthorInstitution
LIU Ya-Jing College of Food Science and Engineering, Nanjing University of Finance and Economics 
YUAN Jian College of Food Science and Engineering, Nanjing University of Finance and Economics 
JU Xing-Rong College of Food Science and Engineering, Nanjing University of Finance and Economics 
XING Chang-Rui College of Food Science and Engineering, Nanjing University of Finance and Economics 
HE Rong College of Food Science and Engineering, Nanjing University of Finance and Economics 
CHEN Shang-Bing College of Food Science and Engineering, Nanjing University of Finance and Economics 
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中文摘要:
      目的 应用法国Alpha M.O.S公司生产的传感器型味觉电子舌系统对3组不同程度掺伪的食用植物油进行掺伪检测。方法 选取6种不同类型植物油, 用20%的乙醇浸泡后超声, 静置隔夜, 将油脂中的味觉信息提取出来, 由电子舌自动进样系统采集原始数据, 所得样品数据用主成分分析法、判别因子法进行分析。 结果 2种方法均能较好地检测区分不同的食用植物油样品, 大部分的指纹分辨指数高于95分。此方法可以区分不同榨取工艺或不同产地的同种类油脂, 可鉴别的掺伪检测限为0.1%。结论 本实验鉴别精确度远大于常规的油脂检测方法, 且具有较高的灵敏度, 能够快速有效地鉴别不同种类食用植物油并区分不同掺杂比例的油脂样品。
英文摘要:
      Objective To detect 3 groups of different levels of adulterated edible vegetable oils by electronic tongue of Alpha M.O.S.(France). Methods Six different types of vegetable oils were selected, and soaked in 20% ethanol and left overnight, and the odor information was extracted from the oil. The raw data were collected by the electronic tongue automatic sampling system. The sample data were analyzed by principal component analysis (PCA) and discriminant factor analysis (DFA). Results Both of the 2 data analysis methods could distinguish edible vegetable oils well, and most of the identification indexes were over 95. This method could be used to distinguish different kinds of oils extracted from different extraction processes or from different producing areas, and the limit of detection was 0.1%. Conclusion The accuracy of this experiment is far greater than that of conventional oil detection methods, and it has high sensitivity, which can quickly and effectively identify different kinds of edible vegetable oils and differentiate the oil samples with different doping ratios.
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