食品科学 ›› 2018, Vol. 39 ›› Issue (14): 268-275.doi: 10.7506/spkx1002-6630-201814040

• 成分分析 • 上一篇    下一篇

不同季节绿茶香气成分的判别与聚类分析

Kang Suyoung1,朱荫1,郑新强2,梁月荣2,*,林智1,*   

  1. (1.中国农业科学院茶叶研究所,农业部茶树生物学与资源利用重点实验室,浙江?杭州 310008;2.浙江大学茶叶研究所,浙江?杭州 310058)
  • 出版日期:2018-07-25 发布日期:2018-07-16
  • 基金资助:
    浙江省自然科学基金项目(LQ15C160007);中央级公益性科研院所基本科研业务费专项(1610212016014); 现代农业产业技术体系建设专项(CARS-19);中国农业科学院创新工程项目(CAAS-ASTIP-2014-TRICAAS)

Multivariate Statistical Analysis of Volatiles Compounds in Green Teas from Different Harvesting Seasons

KANG Suyoung1, ZHU Yin1, ZHENG Xinqiang2, LIANG Yuerong2,*, LIN Zhi1,*   

  1. (1. Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China; 2. Tea Research Institute, Zhejiang University, Hangzhou 310058, China)
  • Online:2018-07-25 Published:2018-07-16

摘要: 采用顶空固相微萃取法结合气相色谱-质谱联用技术对春、夏及秋季绿茶的香气成分进行定性定量分析,进一步结合多元统计分析手段对不同季节绿茶香气成分进行判别和聚类分析,得到不同季节绿茶的关键差异性香气成分。结果表明:共鉴定出不同季节绿茶中的32 种挥发性物质,可分为醇类、醛类、酮类、酯类、烷类、杂环类及其他化合物;基于不同季节绿茶香气成分的含量建立的偏最小二乘判别分析模型(拟合参数为R2Y=0.903,Q2=0.570)可有效区分春、夏及秋季的绿茶样品,其中12 种香气物质为不同季节绿茶间的关键差异性化合物,分别是顺-茉莉酮、苯甲醇、反-2-辛烯醛、β-环柠檬醛、1-己醇、5,6-环氧-β-紫罗兰酮、(反,反)-2,4-庚二烯醛、壬醛、脱氢芳樟醇、2,2,6-三甲基环己酮、3-甲基呋喃及1-庚醇。对关键差异性化合物的聚类分析结果表明,顺-茉莉酮、脂肪醇及苯甲醇在春茶中含量显著高于夏季和秋季,它们的香气特征普遍为草本的清香及花果香;夏茶中甜香及脂肪香的醛酮化合物含量较高,其中(反,反)-2,4-庚二烯醛含量最高;秋茶中的关键香气成分种类最为单一,仅清香、花香及木香型的脱氢芳樟醇含量在大部分秋茶中相对较高。

关键词: 绿茶, 季节, 香气成分, 顶空固相微萃取(HS-SPME), 多元统计分析

Abstract: The aroma quality of tea is closely related to the harvesting seasons. It is important to identify the difference in volatile compounds of green teas from different harvesting seasons. In our present study, headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was used to qualitatively and quantitatively analyze the volatiles compounds of green tea samples harvested in spring, summer and autumn. Subsequently, discriminant and cluster analyses of the volatile compounds in these green teas were carried out by using multivariate statistical analysis. The results showed that a total of 32 volatile components were identified, including alcohols, aldehydes, ketones, esters, alkanes, heterocyclic compounds and other substances. A model of partial least squares-discriminate analysis (PLS-DA) based on the relative contents of the identified compounds could effectively differentiate among the green tea samples from spring, summer and autumn seasons (fitting parameters R2Y = 0.903, Q2 = 0.570). A total of 12 key components, including cis-jasmone, benzyl alcohol, (E)-2-octenal, β-cyclocitral, 1-hexanol, 5,6-epoxy-β-ionone, (E,E)-2,4-heptadienal, nonanal, hotrienol, 2,2,6-trimethyl-cyclohexanone, 3-methyl-furan and 1-heptanol were identified. Furthermore, the results of cluster analysis based on the contents of the key components showed that cis-jasmone, aliphatic alcohol and benzyl alcohol in spring green tea, which generally have the characteristic aroma of grass as well as fruits and flowers, were remarkably higher than those in summer and autumn teas. The contents of aldehydes and ketones with sweet and fatty aromas were higher in green tea harvested in summer than those harvested in spring and autumn, among which (E,E)-2,4-heptadienal was the most abundant. Autumn tea contained the fewest number of key volatiles, and only hotrienol with grass, floral and woody scents was higher in most autumn green tea samples than in spring and summer green teas.

Key words: green tea, harvesting seasons, aroma compounds, headspace-solid phase microextraction (HS-SPME), multivariate statistical analysis

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