期刊论文

A Nondestructive Method Identifying Varieties of Green Tea Based on Near Infrared Spectroscopy and Chemometrics

中文

分析测试学报

1004-4957

2020

39

11

1344-1350

10.3969/j.issn.1004-4957.2020.11.005

国家自然科学基金(31601551,31671931) 湖南省自然科学基金(2019JJ50240) 湖南省教育厅科学研究项目优秀青年项目(18B118) 中国博士后科学基金面上项目(2019M650187) 2019年度湖南省大学生创新创业训练计划项目(S201910537048) 湖南农业大学校青年基金(19QN19)。

本校为第一机构

该文利用近红外光谱技术结合化学计量学方法开发了不同品种绿茶的无损鉴别方法。通过近红外光谱技术得到了8个品种绿茶样品的近红外光谱,比较了单一以及优化组合光谱预处理方法对光谱的影响,利用无监督的主成分分析(PCA)与有监督的线性判别分析方法(LDA)分别构建了茶叶品种鉴别模型。结果表明:对比单一预处理方法,优化组合预处理具有更优的鉴别准确性。标准正态变量变换预处理消除了茶叶样品大小不均造成的光谱散射影响,一阶导数预处理实现了变动背景的消除,减少了基线漂移的影响,突出了图谱中的有效信息,采用二者相结合的预处理方式并结合无监督的主成分分析法可实现较为准确的绿茶样品种类鉴别...

In this paper,a nondestructive method was developed for the identification of different varieties of green tea by near infrared spectroscopy with chemometrics. The near infrared spectra of eight varieties of green tea samples were collected. Effects of single and optimized combination preprocessing methods on spectra were compared. The identification models were constructed by unsupervised principal component analysis(PCA) and supervised linear discriminant analysis(LDA). Results showed that the optimized combination preprocessing method achieved higher accuracy. The standard normal variable t...