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金秀野生茶树群体的生化特征 被引量:6

Analysis of biochemical components of wild tea colonies in Jinxiu
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摘要 为了深入研究金秀野生茶树的种质资源,对广西金秀瑶族自治县境内的8个野生茶树群体的茶多酚、氨基酸和生物碱等主要生化特征进行了研究鉴定和遗传多样性分析.结果表明,8个野生茶树群体的生化成分具有丰富的多样性,平均变异系数达到28.03%.多变量的主成分分析表明,前4个主成分包含了茶树群体生化成分的94.81%信息.生化成分聚类分析表明,8个野生茶树群体可分为3大类群,第Ⅰ和Ⅲ类群为红、绿茶兼制的资源,第Ⅱ类群为适制绿茶的资源.对种质资源进行氨基酸、茶多酚、生物碱和酚氨比等主要生化成分分析揭示了茶树品种的适制性和品质特征,并从中筛选出的特异资源可作为下一步育种的材料,不同群体的生化特征研究为今后茶叶的加工提供依据. The main biochemical characteristics of tea polyphenols,amino acids and alkaloids,such as tea polyphenols,amino acids and alkaloids in 8 wild tea tree populations in Jinxiu Yao Autonomous County,Guangxi,were studied and identified and the genetic diversity was analyzed. The results showed these populations had rich diversity in their biochemical components,with an average variation coefficient of 28. 03%. Multivariate principal component analysis showed that the first 4 principal components contained 94.81% information of biochemical components of the populations. The cluster analysis of biochemical components showed that 8 wild tea tree populations could be divided into 3 groups,the first and third groups were red and green tea,and the second group was the resources suitable for green tea. Amino acids,tea polyphenols,alkaloids and phenolic ammonia ratios were used to reveal the suitability and quality of tea varieties. The qualitative characteristics,and the specific resources selected from it can be used as the next breeding material. The study of biochemical characteristics of different populations provides the basis for the processing of tea in the future.
作者 莫岚 黄亚辉 赵文芳 曾贞 MO Lan;HUANG Yahui;ZHAO Wenfang;ZENG Zhen(College of Horticulture,South China Agricultural University,Guangzhou,Guangdong 510642,China)
出处 《福建农林大学学报(自然科学版)》 CSCD 北大核心 2018年第4期409-414,共6页 Journal of Fujian Agriculture and Forestry University:Natural Science Edition
基金 广东省科技项目(2015B020202007 2016A020208012) 福建省"2011协同创新中心"中国乌龙茶产业协同创新中心专项(闽教[2015]75号) 广东省产业体系项目(2016LM1117) 金秀野生茶树资源的研究[桂科(AB16380063)]
关键词 茶树 种质资源 生化特征 遗传多样性 金秀 tea gennplasm resources biochemical component diversity analysis Jinxiu
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