欧亚国际

摘要

总多酚是全饮用茶叶的一个主要质量指标。本文研究了使用近红外反射（NIR）光谱（800-2500nm）以及多光谱成像系统（MSI，405-970nm)预测铁观音茶中总多酚含量（TPC）的方法。结果显示，使用MSI成像系统，利用偏较小二乘法回归方法分析茶叶是无损、快速测定总多酚（TPC）含量的较佳方法。另外，利用MSI基于储存期（年份：2004, 2007, 2011, 2012 和2013）做了茶叶鉴别实验，鉴别精度分别可达95.0% （LS-SVM法）和97.5% （ BPNN发）。全部结果显示利用MSI多光谱成像法、适当选择模型是快速、无损测定总多酚含量（TPC）和鉴别茶叶年份的较具前景的方法。

焦点

使用MSI多光谱和NIR近红外法预测铁观音茶中总多酚含量

对MSI多光谱和NIR近红外法做了比较

开发了MSI检测茶叶的无损和快速预测模型

基于MSI和LS-SVM法以及BPNN法鉴别茶叶储存期。

Abstract

Total polyphenols is a primary quality indicator in tea which is consumed worldwide. The feasibility of using near infrared reflectance (NIR) spectroscopy (800–2500 nm) and multispectral imaging (MSI) system (405–970 nm) for prediction of total polyphenols contents (TPC) of Iron Buddha tea was investigated in this study. 

The results revealed that the predictive model by MSI using partial least squares (PLS) analysis for tea leaves was considered to be the best in non-destructive and rapid determination of TPC. 

Besides, the ability of MSI to classify tea leaves based on storage period (year of 2004, 2007, 2011, 2012 and 2013) was tested and the classification accuracies of 95.0% and 97.5% were achieved using LS-SVM and BPNN models, respectively. These overall results suggested that MSI together with suitable analysis model is a promising technology for rapid and non-destructive determination of TPC and classification of storage periods in tea leaves.

Non-destructive determination of total polyphenols content and classification of storage periods of Iron Buddha tea using multispectral imaging system

Highlights

Used MSI and NIR to predict total polyphenols content in Iron Buddha tea.

Compared the performance of prediction models between MSI and NIR for tea powder.

Develop non-destructive and rapid prediction model by MSI for tea leaves.

Identified different storage periods of tea leaves by MSI based on LS-SVM and BPNN.