Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/97762
標題: 建立駝峰指紋圖譜及以多變量統計分析方式鑑別成茶之茶種
Identification of Tea Breeds by Means of Establishment Hump Fingerprint and Multivariate Statistical Analysis
作者: 陳晴雯
Ching-Wen Chen
關鍵字: 茶;駝峰;指紋圖譜;液相層析;串聯質譜儀;Camellia sinensis;humps;fingerprint;HPLC;LC-MS/MS
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摘要: 
茶(Camellia sinensis)為山茶科山茶屬,若以亞種做分類,可依葉形大小分為大葉種(var. assamica)以及小葉種(var. sinensis);又可依製程氧化程度分為不發酵茶、半發酵茶及全發酵茶。在茶葉加工程序中之烘焙和發酵步驟促使其成分經多酚氧化酶、過氧化物酶及熱之轉化,導致液相層析圖譜中呈現不易分離之訊號叢,被稱為駝峰(humps)。茶種為決定價格重要因素之一,現行茶種鑑定須使用高技術成本之DNA分子標記,並對於經劇烈熱處理或重度發酵後之成茶無法鑑別。本實驗蒐集台灣各地63個成茶樣品,透過分液萃取及液相層析法分析不同品種經不同製程所作之成茶的特定駝峰指紋圖譜。結果顯示小葉種茶種皆具有P2、P3及P4訊號,且四季春、武夷、臺茶12號、臺茶13號及青心大冇另具P1訊號;而大葉種之茶種皆具有P5、P6及P7訊號,其中臺茶8號和山茶具額外訊號叢Pex。進一步透過質譜儀分析,推測駝峰中指標化合物分別為P1(Q-GaRhG)、P2(Q-GRhG)、P3(K-GaRhG)、P4(K-GRhG)、P5(Q-GRh)、P6(K-GaRh)及P7(K-GRh)。接著利用多變量統計分析之主成分分析(principal component analysis;PCA)及階層式匯聚型集群分析(hierarchical agglomerative clustering;HAC)作為驗證。綜合上述,大小葉種各具有特定之指標化合物,並繪製一Hump model,建立茶駝峰之指紋圖譜輔以乙酸乙酯層之分光值,用作茶種之判定。

Tea is produced from the leaves of Camellia sinensis which is generally classified as var. assamica and var. sinensis according to the shape of leaves. On the other hand, it can also be classified into non-fermented, semi-fermented and fully fermented tea by the degree of oxidation caused by oxidase in the tea processing. The baking and fermentation processes used in tea processing promote the conversions of their components by the activity of polyphenol oxidase and peroxidase, external heating and oxidation, resulting in a signal clusters that is not easily separated in the liquid chromatogram known as humps. Tea breed is one of the important factors in deciding commercial price. Compared with the current identification of tea breeds, high-tech and high-cost DNA molecular marker methods are used but it cannot be applied to teas which had been intense heat treatment. I aimed to analyze 63 tea samples (including different breeds of tea made by different processes) from all over places in Taiwan by using the construction of their specific hump fingerprints via liquid chromatography analysis. The results showed that (i) there are signals P2, P3 and P4 in var. sinensis, and additional signal P1 in Shy Jih Chuen, Wuu Yi, Chin Shin Dah Pan, Ttes No.12 and Ttes No.13, (ii) P5, P6, and P7 are in var. assamica, and extra signal cluster (Pex) is in Ttes No.8 and Sun Cha. Furthermore, the compounds for these signals were preliminarily identified by LC-MS/MS as P1 (Q-GaRhG), P2 (Q-GRhG), P3 (K-GaRhG), P4 (K-GRhG), P5 (Q-GRh), P6 (K-GaRh) and P7 (K-GRh) respectively. The principal component analysis (PCA) and hierarchical cluster analysis (HAC) were used to verify the results of hump fingerprints. Overall, each of var. assamica and var. sinensis has specific indicator compounds, and I establish the humps fingerprint model for the identification of the tea breeds.
URI: http://hdl.handle.net/11455/97762
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