Study on Identification and Traceability of Tea Material Cultivar by Combined Analysis of Multi-Partial Least Squares Models Based on Near Infrared Spectroscopy
ZHOU Jian1, CHENG Hao1*, ZENG Jian-ming1, WANG Li-yuan1，WEI Kang2, HE Wei2，WANG Wei-feng2, LIU Xu2
1. National Center for Tea Improvement, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China 2. Department of Tea Science, Nanjing Agricultural University，Nanjing 210095, China
Abstract：The present study attempted to achieve the identification and traceability of tea material cultivar through combination of multi-partial least squares models and Euclidean distance, etc. The results indicate that with the samples manufactured with tea fresh leaves of cultivar Longjing 43, Qunti, Yingshuang and Wuniuzao as the analysis objects, 4 models were established in this study so as to identify the tea with material cultivar being tea fresh leaves of cultivar Longjing 43, Qunti,Yingshuang and Wuniuzao separately by PLS. Their accuracy rate of identification of samples in the calibration set were 89.8%, 90.9%, 96.1% and 99.5%, respectively, while those in test set were 87.1%, 84.2%, 96.1% and 97.5%, respectively. After the “first identification” through the combined analysis of the four models for identification of tea material cultivar and the “second identification” adopting the Euclidean distance, the accuracy rate of material cultivar recognition for the tea samples was 90.3% (calibration set) and 83.5% (test set), respectively. This study provided a reference method for the identification of tea manufactured with a specific material cultivar and the material cultivar traceability of the manufactured tea.
Key words：Tea;material cultivar;Traceability;Near infrared;Partial least squares;Euclidean Distance
周 健1，成 浩1*，曾建明1，王丽鸳1，韦 康1，贺 巍2，王伟峰1，刘 栩1 . 基于近红外的多相偏最小二乘模型组合分析实现茶叶原料品种鉴定与溯源的研究 [J]. 光谱学与光谱分析, 2010, 30(10): 2650-2653.
ZHOU Jian1, CHENG Hao1*, ZENG Jian-ming1, WANG Li-yuan1，WEI Kang2, HE Wei2，WANG Wei-feng2, LIU Xu2 . Study on Identification and Traceability of Tea Material Cultivar by Combined Analysis of Multi-Partial Least Squares Models Based on Near Infrared Spectroscopy . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2010, 30(10): 2650-2653.
