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基于地理因素的代谢组学揭示了不同种类绿茶(Camellia sinensis)代谢物的多样性。

Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

机构信息

Korean Alcoholic Beverage Research Center, Divisions of Convergence Technology, Korea Food Research Institute, Baekhyun, Sungnam, Kyungki 463-746, Republic of Korea.

Food Research Institute, AMOREPACIFIC R&D Center, Yongin-si, Gyeonggi-do 446-729, Republic of Korea.

出版信息

Food Chem. 2015 May 1;174:452-9. doi: 10.1016/j.foodchem.2014.11.086. Epub 2014 Nov 22.

Abstract

Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach.

摘要

许多因素,如地理起源、品种、气候、文化习俗和制造工艺,都会影响茶叶的化学成分,就像生长条件和葡萄品种影响葡萄酒的质量一样。然而,这些因素与茶叶化学成分之间的关系还不是很清楚。在这项研究中,我们采用了一种新的非靶向或全局分析方法,即代谢组学,该方法在分析多种化合物时具有高度的重现性和统计学有效性,用于更好地了解茶树的代谢组,并确定包括地理、气候和文化习俗在内的环境因素对制茶的影响。我们发现,中国、日本和韩国的绿茶、白茶和乌龙茶的环境因素与代谢组之间存在很强的相关性。特别是,多元统计分析揭示了绿茶和白茶中茶氨酸和儿茶素衍生物水平的强烈的国家间和城市间关系。这些信息可能有助于评估茶叶的质量或在不同地区生产不同的茶叶产品,并通过基于 NMR 的代谢组学方法强调同时鉴定不同的茶叶代谢物。

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