槠叶种新鲜茶树叶的拉曼光谱检测

摘要/Abstract

摘要： 基于激光拉曼光谱技术对新鲜茶叶原叶品质鉴定及产地区分进行了研究，对祁门县六个村庄槠叶种新鲜茶树叶（简称原叶）进行了检测。结果表明不同产地原叶在748,831，1005,1158,1328,1527,1609 cm-1等处均有较强拉曼峰，但每组峰强度存在差异。采用主成分分析法（PCA）及线性判别分析法（LDA）对原叶的拉曼光谱进行了分析，得到不同产地原叶的区分度为70.7%。

关键词: 光谱学, 激光拉曼光谱, 主成分分析, 线性判别分析, 槠叶种新鲜茶树叶

Abstract: Based on laser Raman spectroscopy technology, the quality identification of fresh tea leaves and growing region discrimination are investigated. Fresh leaves of Zhuye (the original leaves) of six villages in Qimen County are detected. Results show that there are strong Raman peaks at 748,831,1005,1158,1328,1527,1609 cm in the original leaves from different regions, but the intensity of peaks are different in each group．Principal component analysis (PCA) and linear discriminant analysis (LDA) are used to analyze Raman spectra of the original leaves, and it’s found that the discrimination index of original leaves from different regions is 70.7%.

Key words: spectroscopy, laser Raman spectroscopy, principal component analysis, linear discriminant analysis, fresh tea leaves of Zhuye

陈长水, 师星哲, 李谦, 刘兆伟. 槠叶种新鲜茶树叶的拉曼光谱检测[J]. 量子电子学报.

CHEN Changshui, SHI Xingzhe, LI Qian, LIU Zhaowei. Detection of fresh tea leaves of Zhuye by Raman spectroscopy[J]. Chinese Journal of Quantum Electronics.

参考文献

[1] Ma Guicen，Zhang Yingbin，Zhang Jianyang,et el. Determining the geographical origin of Chinese green tea by linear discriminant analysis of trace metals and rare earth elements: Taking Dongting Biluochun as an example[J].Food Control，2016，59: 714-720. [2] Zhang Long，Pan Jiarong，Zhu Cheng. Determination of the geographical origin of Chinese teas based on stable carbon and nitrogen isotope ratios[J].Journal of Zhejiang University，2012，13（10）：824-830. [3 ] Ana Marcos，Andrew Fisher，Gerry Rea，et el. Preliminary study using trace element concentrations and a chemometrics approach to determine the geographical origin of tea[J].Journal of Managerial Psychology，1998，13(6)：521-525. [4] Zhou Jian,Cheng Hao,He Wei,et el. Identification of geographical indication tea with Fisher's discriminant classification and principal components analysis[J].Journal of near infrared spectroscopy，2009，17(3): 159-164. [5] Liang Qifeng,Hou Hongna. Identification of Tea Varieties by Fourier Transform Infrared Spectroscopy [J].Guangzhou Chemical Industry（广州化工），2016,44（1）: 119-120，189（in Chinese）. [6] Yuan Yuwei， Hu Guixian ,Shao Shengzhi，et el. Progress in Analytical Methods for the Detection of Geographical Origin and Authenticity of Tea ( Camellia sinensis)[J].Journal of Nuclear Agricultural Sciences(核农学报)，2013，27(4) : 0452-0457（in Chinese）. [7] Liu Hailong，Wu Xijun，Tian Guangjun.Three-Dimensional Fluorescence Spectroscopy Combined with Parallerl Factor Analysis as a Complementary Technique for Green Tea Charactorization [J].Chinese J Lasers(中国激光)，2008,35（5）: 685-689（in Chinese）. [8] Zhang Zhimin，Chen Shan，Liang Yizeng，et el. An intelligent background-correction algorithm for highly fluorescent samples in Raman spectroscopy[J].Journal of Raman Spectroscopy，2010，41（6）: 659-669. [9] Luo Shuwen，Chen Changshui，Chen Weidong. Early Diagnosis of Colon Cancer Using Raman Spectroscopy and Multivariate Statistical Analysis Techniques[J].Chinese Journal of Luminescence(发光学报)，2013, 34(11): 1544-1549（in Chinese）. [10] Jiang Yuling，Liu Junxian，Chen Yue，et el. Screening of Caratenoid High-Producing Mutants from Rhodotorula Glutinis Using Raman Spectroscopy in Situ Quantitative Detection Technology[J].Chinese J Lasers(中国激光)，2014,41（2）: 341-346（in Chinese）. [11] Chen Yongjian,Feng Shangyuan,Guo Xiaolin,et el. Preliminary Study on the Surface Enhanced Raman Spectrum of Tea[J].Spectroscopy And Spectral Analysis(光谱学与光谱分析), 2012, 32（10）：2702-2705（in Chinese）. [12] Zhengling，Zhao Yanping，Feng Yadong. Identification of Pu’er Ripe Teas with Different Origins and Fermantation Years by Surface-Enhanced Raman Spectroscopy[J].Spectroscopy And Spectral Analysis(光谱学与光谱分析), 2013, 33（6）：1575-1580（in Chinese）. [13] Lu Meihong,Lei Haiying,Wang Zhijun,et el. Fluorescence spectra and Raman spectra of several synthetic food colors[J].Chinese Journal of Quantum Electronics(量子电子学报),2014，31（1）：12-17（in Chinese）. [14] Yu Cuirong,Wang Xinquan,Qi Minjun,et el. Application of spectral and spectral imaging technology in biomedicine[J].Chinese Journal of Quantum Electronics(量子电子学报),2015，32（6）：641-647（in Chinese）. [15] Abdullah Chandra Sekhar Talart，Zanyar Movasaghi，Shazza Rehman，et el. Raman Spectroscopy of Biological Tissues[J]. Applied Spectroscopy Reviews，2015, 50(1): 46-111. [16] Ding Yong, Xu Yiding, Wang Yejun，et el. Study on Withering and First Drying Technology at Primary Processing of Keemun Black Tea[J].Chinese Agricultural Science Bulletin(中国农学通报)，2010, 26(9): 110-114（in Chinese）. [17] Wang Chen. Study on the influence of processing technology and varity on the chemical compositions of tea(加工工艺和品种对茶叶化学成分的影响研究)[D]. Master Thesis of Kunming University of Science and Technology, 2016（in Chinese）. [18] Kang Suyoung. Effects of tea cultivar,growing season and processing method on volatitles of tea leaves(不同茶树品种、生产季节和加工方法对茶叶挥发性化合物的影响)[D]. Doctorate dissertation of Zhejiang University, 2016（in Chinese）. [19] Chen Tao. Terahertz spectra identification of biomolecules based on principal component analysis and fuzzy recognition[J].Chinese Journal of Quantum Electronics(量子电子学报), 2016, 33(4): 392-398（in Chinese）. [20] Teh Seng Khoon , Zheng Wei, Ho Khek Yu,et al. Near-infrared Raman spectroscopy for optical diagnosis in the stomach: Identification of Helicobacter-pylori infection and intestinal metaplasia ［J］.Int. J. Cancer，2010，126(8): 1920-1927．

[1]	陈珂马凤翔赵跃李辰溪安冉朱峰杭忱. 基于光纤光声传感的油中溶解气体分析系统[J]. 量子电子学报, 2023, 40(4): 597-605.
[2]	曹冬梅, 李永放 . 领结状金纳米二聚体耦合共振特性研究[J]. 量子电子学报, 2023, 40(4): 606-613.
[3]	费晔, 孙仲谋, 田东鹏, 刘骁源, 刘玉柱, . 基于激光诱导击穿光谱的果木炭燃烧对空气成分影响的研究[J]. 量子电子学报, 2023, 40(4): 436-446.
[4]	王海青 , 施卫 . THz-ATR 技术检测生物医学样品的研究进展[J]. 量子电子学报, 2023, 40(3): 319-332.
[5]	曾子威 , 李宏光 , 郭宇烽 , 廖文焘 . 隐匿危险品高准确度太赫兹光谱识别方法[J]. 量子电子学报, 2023, 40(3): 340-348.
[6]	白岩冰, 张梦圆, 朱梦琪, 李旭, 闫佳玉, 张存林, 左剑, . α-乳糖一水合物太赫兹动力学研究[J]. 量子电子学报, 2023, 40(3): 349-359.
[7]	葛宏义 , 王飞 , 蒋玉英 , 李丽 , 张元 , 贾柯柯 , . 基于宽度学习的太赫兹光谱图像小麦霉变识别研究[J]. 量子电子学报, 2023, 40(3): 360-368.
[8]	张冉冉 , 应璐娜 , 周卫东. 相关向量机结合主成分分析应用于 LIBS 技术定量分析[J]. 量子电子学报, 2023, 40(3): 376-382.
[9]	杨金, , 王云峰, , 储玲巧 , 蒋华超 , 苏付海 ∗. 少层 PtSe2 中光生载流子超快动力学研究[J]. 量子电子学报, 2023, 40(2): 282-292.
[10]	王庆乐, , 薛雪 , 李元诚∗. 量子典型相关分析算法[J]. 量子电子学报, 2023, 40(1): 120-126.
[11]	王泽育, 崔琪, 和小虎, 卢丹华, 邱选兵何秋生, 赖云忠, 李传亮∗. I₂⁺离子低能电子态的计算和光谱研究[J]. 量子电子学报, 2022, 39(4): 477-484.
[12]	徐鹏, 贾韧, 姚关心, 秦正波, 郑贤锋, 杨新艳, 崔执凤, . 混合水溶液中金属元素的偏最小二乘法激光诱导击穿光谱[J]. 量子电子学报, 2022, 39(4): 485-493.
[13]	于玮, 周卓彦, 孙仲谋, 张兴龙, 刘玉柱, . 激光诱导击穿光谱技术实时检测蔷薇属植物[J]. 量子电子学报, 2022, 39(4): 494-501.
[14]	丁伯坤, 邵李刚, 王坤阳, 陈家金, 王贵师, 刘锟, 梅教旭, 谈图, 高晓明, ∗. 基于离轴积分腔的海水溶解气体实时检测技术研究[J]. 量子电子学报, 2022, 39(4): 502-510.
[15]	马凤翔, 赵跃, 崔方晓∗, 李大成. 基于支持向量回归的光声光谱信号温度和湿度校正方法[J]. 量子电子学报, 2022, 39(4): 511-518.