分析与检测

基于zNoseTM电子鼻的新产原酒品质检测

  • 张君生 ,
  • 李臻峰 ,
  • 宋飞虎 ,
  • 李静 ,
  • 朱冠宇 ,
  • 张鑫 ,
  • 吕丙
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  • 1(江南大学 机械工程学院,江苏 无锡,214122)
    2(江苏省食品先进制造装备技术重点实验室,江苏 无锡,214122)
    3(山西杏花村汾酒厂股份有限公司 技术中心,山西 汾阳,032200)
硕士研究生(李臻峰教授为通讯作者,E-mail:1475753851@qq.com)。

收稿日期: 2018-06-26

  网络出版日期: 2019-01-22

基金资助

国家自然科学基金(515082290);江苏省产学研联合创新资金(BY20140023-32);江南大学基本科研青年基金项目(1072050205134580);江苏省食品先进制造装备技术重点实验室开放课题(BM2013001);江苏省食品先进制造装备技术重点实验室开放课题(FM-201406)

Quality inspection of original liquor based on electronic nose detection

  • ZHANG Jun-sheng ,
  • LI Zhen-feng ,
  • SONG Fei-hu ,
  • LI Jing ,
  • ZHU Guan-yu ,
  • ZHANG Xin ,
  • LYU Bing
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  • 1(School of Mechanical Engineering Jiangnan University, Wuxi 214122, China)
    2(Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China)
    3(Technology Center of Shanxi Xinghuacun Fenjiu factory Co. Ltd, Fenyang 032200, China)

Received date: 2018-06-26

  Online published: 2019-01-22

摘要

新产原酒等级的准确评判是白酒分级储存的重要依据,也是白酒质量控制中至关重要一环。针对目前新产原酒等级评定依靠品酒师感官品评结合化学检测繁琐费时的缺点,采用zNoseTM电子鼻对3个等级新产原酒挥发性物质进行检测分析,从等级判定和总酸、总酯含量预测2方面对新产原酒品质预测方法进行研究。在等级判定中,采用主成分分析与费舍尔判别分析。结果表明,费舍尔判别分析效果优于主成分分析,判别正确率为85.11%。在酸酯含量预测中,采用偏最小二乘法对变量进行提取,并建立偏最小二乘回归模型对总酸、总酯指标含量进行预测,预测集模型拟合决定系数R2分别为0.8361、0.8522。实验表明zNoseTM电子鼻在新产原酒等级鉴别与酸酯含量预测方面具有较好应用前景。

本文引用格式

张君生 , 李臻峰 , 宋飞虎 , 李静 , 朱冠宇 , 张鑫 , 吕丙 . 基于zNoseTM电子鼻的新产原酒品质检测[J]. 食品与发酵工业, 2018 , 44(12) : 216 -220 . DOI: 10.13995/j.cnki.11-1802/ts.018132

Abstract

Accurate grade evaluation of young liquor is essential for subsequent liquor-graded storage and a crucial part of quality control. Currently, the grade evaluation of the products mainly depends on the taster's sensory evaluation and chemical analysis, which is time-consuming and of cumbersome . The detection and analysis of the volatiles in three grades of young liquors was carried out by using an electronic nose and the quality prediction methods were studied in terms of grade determination, total acids and total ester contents. 1) The principal component analysis and Fischer discriminant analysis were used to determine the grades, resulted in that Fisher's discriminant analysis was superior to the principal component analysis and the correct rate of discrimination reached 85.11%. 2) In the prediction of acid and ester contents, a partial least-squares regression model was established that predicted the total acid and total ester index contents, which fit determination coefficient R2 of 0.836 1 and 0.852 2. These results suggest that electronic nose is a useful and powerful tool in identification and prediction of acid ester contents in different grade liquors.

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