SPME/GC-MS法结合电子鼻技术测定茶叶中的香气成分
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摘要
采用固相微萃取与气相色谱-质谱联用(SPME/GC-MS)技术,对茶叶的特征香气成分进行分析研究。5种不同种类的茶叶共检测出42种香气成分,相对含量较高的主要成分有肉豆蔻酸异丙酯、β-紫罗兰酮、(E,E)-3,5辛二烯-2-酮,香气成分含量的差异造成了不同茶叶品种的风味特征。利用带有10个不同金属氧化物传感器的电子鼻对5种茶叶进行品种分类,采用主成分分析(PCA)、线性判别分析(LDA)和负荷加载分析(Loading analysis)对样品进行分析。PCA和LDA分析得到了较好的结果,识别率分别为97.99%和97.69%。测量响应值表明,传感器S1(W1C,芳香族化合物,苯类)、S3(W3C,芳香族化合物,氨)、S6(W1S,甲烷)对5种不同茶叶的区分有较好的贡献率。本研究结果表明,SPME/GCMS结合电子鼻技术能有效分析茶叶的主要香气成分。
The aromatic components of five kinds of tea were analyzed by solid-phase microextraction(SPME) and gas chromatography-mass spectroscopy(GC-MS). 42 kinds of aromatic components were detected and the relatively high content were isopropyl myristate, β-ionone, and(E,E)-3,5-octadien-2-one.The difference in the contents of these aromatic components forms the flavor characteristics of different tea varieties. An investigation was made to evaluate the capacity of an electronic nose to classify five different kinds of tea, using a specific electronic nose device with 10 different metal oxide sensors.Principal component analysis(PCA), linear discriminant analysis(LDA) and loadings analysis were used to identify the classification ability of electronic nose. Good classification results were obtained by PCA and LDA analysis. The recognition rates were 97.99% and 97.69%, respectively. The response values showed that the sensors S1(W1C, aromatic compounds, benzene), S3(W3C, aromatic compounds, ammonia) and S6(W1S, methane) had a good contribution to the differentiation of five different tea leaves. The results of this research indicate that SPME/GC-MS combined with electronic nose technology can effectively analyze the main aromatic components of tea.
The aromatic components of five kinds of tea were analyzed by solid-phase microextraction(SPME) and gas chromatography-mass spectroscopy(GC-MS). 42 kinds of aromatic components were detected and the relatively high content were isopropyl myristate, β-ionone, and(E,E)-3,5-octadien-2-one.The difference in the contents of these aromatic components forms the flavor characteristics of different tea varieties. An investigation was made to evaluate the capacity of an electronic nose to classify five different kinds of tea, using a specific electronic nose device with 10 different metal oxide sensors.Principal component analysis(PCA), linear discriminant analysis(LDA) and loadings analysis were used to identify the classification ability of electronic nose. Good classification results were obtained by PCA and LDA analysis. The recognition rates were 97.99% and 97.69%, respectively. The response values showed that the sensors S1(W1C, aromatic compounds, benzene), S3(W3C, aromatic compounds, ammonia) and S6(W1S, methane) had a good contribution to the differentiation of five different tea leaves. The results of this research indicate that SPME/GC-MS combined with electronic nose technology can effectively analyze the main aromatic components of tea.
引文
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[18]王霞,黄健,侯云丹,等.电子鼻结合气相色谱-质谱联用技术分析黄鳍金枪鱼肉的挥发性成分[J].食品科学,2012,33(12):268-272.
[19]郭嘉懿,雷雨,郑鹏程,等.茶树新品系80-53-34制作工夫红茶香气分析[J].茶叶学报,2016,57(1):42-48.
[20]孙慕芳,郭桂义.著名信阳毛尖产地茶叶香气成分的GC-MS分析[J].江苏农业科学,2014,42(7):319-321.
[21]龙立梅,宋沙沙,李柰,等.3种名优绿茶特征香气成分的比较及种类判别分析[J].食品科学,2015,36(2):114-119.
[22]史文青,薛雅琳,何东平.花生挥发性香味识别的研究[J].中国粮油学报,2012,27(7):58-62.
[2]马军辉.HS-SPME-GC-MS检测茶叶内挥发性组分方法的建立及应用[D].杭州:浙江大学,2008.
[3]陈梅春,陈峥,史怀,等.陈年普洱茶特征风味成分分析[J].茶叶科学,2014,34(1):45-54.
[4]孙彦,陈倩,郭雯飞.龙井茶的香气成分分析与比较[J].浙江大学学报(理学版),2013,40(2):186-190.
[5]刘晓慧,张丽霞,王日为,等.顶空固相微萃取-气相色谱-质谱联用法分析黄茶香气成分[J].食品科学,2010,31(16):239-243.
[6]兰欣,汪东风,张莉,等.HS-SPME法结合GC-MS分析崂山绿茶的香气成分[J].食品与机械,2012,28(5):96-101.
[7]叶红,周春宏,王克其.直接进样气相色谱/质谱法对茶叶香气的分析[J].食品研究与开发,2007,28(12):138-140.
[8]肖丹.顶空固相微萃取技术的应用与展望[J].中国卫生工程学,2015,14(1):88-92.
[9]道平,甘秀海,梁志远,等.固相微萃取法与同时蒸馏萃取法提取茶叶香气成分[J].西南农业学报,2013,26(1):131-135.
[10]俞慧红,崔晓红,刘平.电子鼻在酱油气味识别中的应用[J].中国调味品,2016,41(2):121-125.
[11]刘莎莎,张宝善,孙肖园,等.红枣香味物质的主成分分析[J].食品工业科技,2015,36(20):72-76.
[12]于慧春,王俊,张红梅,等.龙井茶叶品质的电子鼻检测方法[J].农业机械学报,2007,38(7):103-106.
[13]陈婷,蒋明忠,彭文,等.基于电子鼻技术对云南普洱熟茶的香气品质判别[J].西南农业学报,2017,30(2):339-344.
[14]史波林,赵镭,支瑞聪,等.应用电子鼻判别西湖龙井茶香气品质[J].农业工程学报,2011,27(12):302-306.
[15]张红梅,王俊,余泳昌,等.基于电子鼻技术的信阳毛尖茶咖啡碱检测方法[J].传感技术学报,2011,24(8):1223-1227.
[16] Huichun Yu, Jun Wang, Hong Xiao,et al. Quality Grade Identi-fication of Green Tea Using the Eigenvalues of PCA Based on the E-Nose Signals[J].Sensors and Actuators B:Chemical,2009,140(2):378-382.
[17] Liu Ming, Han Xiaomin, Tu Kang, et al. Application of Electronic Nose in Chinese Spirits Quality Control and Flavour Assessm-ent[J].Food Control,2012,26(2):564-570.
[18]王霞,黄健,侯云丹,等.电子鼻结合气相色谱-质谱联用技术分析黄鳍金枪鱼肉的挥发性成分[J].食品科学,2012,33(12):268-272.
[19]郭嘉懿,雷雨,郑鹏程,等.茶树新品系80-53-34制作工夫红茶香气分析[J].茶叶学报,2016,57(1):42-48.
[20]孙慕芳,郭桂义.著名信阳毛尖产地茶叶香气成分的GC-MS分析[J].江苏农业科学,2014,42(7):319-321.
[21]龙立梅,宋沙沙,李柰,等.3种名优绿茶特征香气成分的比较及种类判别分析[J].食品科学,2015,36(2):114-119.
[22]史文青,薛雅琳,何东平.花生挥发性香味识别的研究[J].中国粮油学报,2012,27(7):58-62.