Identification of green tea origins by near-infrared (NIR) spectroscopy and different regression tools

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• 作者：XinGang Zhuang ; LiLi Wang ; Qi Chen ; XueYuan Wu…
• 关键词：near ; infrared spectroscopy (NIRS) ; green tea ; origin ; regression tool
• 刊名：Science China Technological Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：60
• 期：1
• 页码：84-90
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Engineering, general;
• 出版者：Science China Press
• ISSN：1869-1900
• 卷排序：60

文摘

In this study, near-infrared (NIR) spectroscopy was applied to efficiently and non-destructively identify Shandong green tea origins coupled with three different regression tools. Analysis results indicated that partial least squares (PLS) had better performance than back propagation artificial neural network (BP-ANN) and support vector machine (SVM). For PLS, the accuracies of identification were up to 100% for both training and testing. The results sufficiently demonstrate that NIR spectroscopy can be efficiently utilized for the non-destructive identification of green tea origins.