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作 者:王雪萍[1] 高士伟[1] 郑鹏程[1] 叶飞[1] 王胜鹏[1] 龚自明[1] WANG Xueping;GAO Shiwei;ZHENG Pengcheng;YE Fei;WANG Shengpeng;GONG Ziming(Institute of Fruit&Tea,Hubei Academy of Agricultural Sciences,Fruit and Tea Subcenter,Hubei Innovation Center of Agricultural Science and Technology,Hubei Tea Engineering and Technology Research Centre,Wuhan 430064)
机构地区:[1]湖北省农业科学院果树茶叶研究所,湖北省农业科技创新中心果茶分中心,湖北省茶叶工程技术研究中心,武汉430064
出 处:《食品工业》2020年第2期322-325,共4页The Food Industry
基 金:国家茶叶产业技术体系项目(CARS-19);湖北省农业科技创新中心创新团队项目(2019-620-000-001-24);中央引导地方科技发展专项“茶叶学科科研条件改善和创新能力提升”(2018ZYYD009).
摘 要:通过对氨基酸组分和矿物元素测定分析,结合统计学方法对来自湖北不同产区名优绿茶进行产地区分。以17种氨基酸及7种矿物元素含量为变量,利用SPSS软件进行逐步判别分析。结果表明,钾、镁、组氨酸、钙和铁先后被引入判别模型中,所建立的判别模型正确判别率为94.44%,交叉验证判别率为86.12%。基于氨基酸组分和矿物元素的统计学分析为绿茶产地判断提供了重要依据。The origin of famous green tea from different producing areas in Hubei Province was differentiated by amino acid composition and mineral elements combined with statistics analysis. Taking the contents of 17 amino acids and 7 mineral elements as variables, the stepwise discriminant analysis was carried out with SPSS software. The results showed that potassium, magnesium, histidine, calcium and iron were introduced into the discrimination model. The correct rate of the established discrimination model was 94.44%, and the correct rate of cross-validation was 86.12%. The statistical analysis of amino acid components and mineral elements provided an important basis for determining the origin of green tea.
分 类 号:TS272.51[农业科学—茶叶生产加工]
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