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丽水茶园土壤肥力与茶叶品质关系的研究
引用本文:徐丽红,吴全聪,李阳,王建清,王伟,陈栎安.丽水茶园土壤肥力与茶叶品质关系的研究[J].茶叶,2012(3):146-150.
作者姓名:徐丽红  吴全聪  李阳  王建清  王伟  陈栎安
作者单位:[1]浙江省农业科学院农产品质量标准研究所,浙江杭州310021 [2]丽水市农业科学研究院,浙江丽水323000 [3]温州医学院检生系生物技术专业,浙江温州325005
基金项目:丽水市科技合作项目(20100413);浙江省农业科学院院创新项目(2010R19Y01D05)
摘    要:通过检测丽水市名茶及普通茶相应茶园土壤养分指标、茶叶品质指标,并运用dps3.0软件,进行多元线性逐步回归分析。结果表明:影响秋茶品质最关键的土壤养分指标是速效氮含量,它与5个茶叶品质指标存在相关性;其次是土壤有机质含量,它与茶叶中的氨基酸、咖啡碱含量和酚氨比呈线性相关。春茶品质主要受速效氮和速效钾含量的影响。丽水市土壤速效氮和有机质含量较高,这是该地区茶叶具有较高品质的主要原因。应保持有机肥、氮肥适量施用,配施钾磷肥,促进茶叶产量及品质的稳步提高。

关 键 词:春茶  秋茶  茶叶品质  土壤肥力  相关性  多元线性逐步回归

A study on the relationship between tea quality and soil fertility in Lishui city
XU Lihong,WU Quancong,LI Yang,WANG JianQing,WANG Wei,CHEN LiAn.A study on the relationship between tea quality and soil fertility in Lishui city[J].Journal of Tea,2012(3):146-150.
Authors:XU Lihong  WU Quancong  LI Yang  WANG JianQing  WANG Wei  CHEN LiAn
Institution:1. Institute of Quality and Standard for agri-produets, Zhejiang Academy of Agrieultural Sciences, Hangzhou, 310021, China; 2. Lishui Academy of Agricultural Sciences, Lishui, Zhejiang 323000, China; 3. Wenzhou Medical College, Wenzhou, Zhejiang, 325005 ,China)
Abstract:The soil fertility indexes and tea quality indexes for the ten famous Lishui teas, flower tea and Biluochun tea were analyzed using. The dps3.0 software. The results show that it was the content of the available nitrogen that affected the autumn tea quality most and the linear correlation between available N and five tea quality indexes was significant. The content of organic matter in soil was linearly eorreled to the content of Amino acid. Spring tea quality was mainly affected by the contents of the available nitrogen and the available potassium. Lishui tea soil was rich in available nitrogen and organic matter. To promote the quality and production of tea, we should apply organic manure and nitrogen fertilizer in appropriate amount, together with phosphorus and potash fertilizer.
Keywords:Spring tea  Autumn tea  tea quality  soil fertility  relevance  multiple linear stepwise regression
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