香精掺假普洱茶的近红外光谱检测  被引量:14

Detection of Flavor Adulterated Pu'er Tea by Near-Infrared Spectroscopy

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作  者:王淑贤 肖航 杨振发 姜明顺[2] 隋青美[2] 冯德军[1] Wang Shuxian;Xiao Hang;Yang Zhenfa;Jiang Mingshun;Sui Qingmei;Feng Dejun(Schoo of Information Science and Engineering,Shandong University,Qingdao,Shandong 266237,China;School of Control Science and Engineering,Shandong University,Jinan,Shandong 250061,China)

机构地区:[1]山东大学信息科学与工程学院,山东青岛266237 [2]山东大学控制科学与工程学院,山东济南250061

出  处:《激光与光电子学进展》2020年第23期384-389,共6页Laser & Optoelectronics Progress

基  金:国家自然科学基金(61377043);山东大学跨学科人才培养项目(2018JCG06)。

摘  要:建立一种能够快速、定量检测掺假普洱茶中香豆素、香兰素、乙基麦芽酚三种常见香精的方法。利用傅里叶变换近红外光谱技术结合偏最小二乘法对香精掺假普洱茶进行定量分析。分别建立三种掺假香精成分的定量分析模型,并对比基于不同预处理方法和未经光谱预处理的定量分析模型的预测能力。结果表明:结合不同光谱预处理方法实现的针对香豆素、香兰素和乙基麦芽酚三种香精的预测均方根误差分别为0.1461,0.1678,0.1800,预测决定系数分别为0.7989,0.7350,0.6938,三种香精的检测限为0.2 mg/g。近红外光谱技术结合偏最小二乘定量分析方法可以实现掺假普洱茶中三种香精成分的快速检测分析。In this work,a quick and quantitative detection method for three common flavors,i.e.,coumarin,vanillin,and ethyl maltol,in flavor adulterated Pu'er tea is established.The Fourier transform near-infrared spectroscopy combined with the partial least squares method is used to quantitatively analyze the flavor adulterated Pu'er tea.The quantitative analysis models for three adulterated flavor components are established,and the predictive capabilities of the quantitative analysis models built with different pre-processing methods and without spectral pre-processing are compared.The results show that the predicted root mean square errors of the three flavors of coumarin,vanillin,and ethyl maltol by combining different spectral pre-processing methods are 0.1461,0.1678,and 0.1800,respectively,and the prediction determination coefficients are 0.7989,0.7350,and 0.6938,respectively.The detection limit of three flavors is 0.2 mg/g.The near-infrared spectroscopy combined with the partial least squares quantitative analysis can achieve rapid detection and analysis of the three flavors in adulterated Pu'er tea.

关 键 词:光谱学 近红外光谱技术 香精 普洱茶 偏最小二乘 

分 类 号:O657.33[理学—分析化学]

 

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