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中国精品科技期刊2020
邓云, 胡荣锁, 陆敏泉, 杨晓曼, 徐树良, 董文江. 德宏州生咖啡风味组分与海拔相关性研究[J]. 华体会体育, 2017, (02): 166-169. DOI: 10.13386/j.issn1002-0306.2017.02.023
引用本文: 邓云, 胡荣锁, 陆敏泉, 杨晓曼, 徐树良, 董文江. 德宏州生咖啡风味组分与海拔相关性研究[J]. 华体会体育, 2017, (02): 166-169. DOI: 10.13386/j.issn1002-0306.2017.02.023
DENG Yun, HU Rong-suo, LU Min-quan, YANG Xiao-man, XU Shu-liang, DONG Wen-jiang. The correlative analysis of altitude and flavor components of Dehong State green coffee beans[J]. Science and Technology of Food Industry, 2017, (02): 166-169. DOI: 10.13386/j.issn1002-0306.2017.02.023
Citation: DENG Yun, HU Rong-suo, LU Min-quan, YANG Xiao-man, XU Shu-liang, DONG Wen-jiang. The correlative analysis of altitude and flavor components of Dehong State green coffee beans[J]. Science and Technology of Food Industry, 2017, (02): 166-169. DOI: 10.13386/j.issn1002-0306.2017.02.023

德宏州生咖啡风味组分与海拔相关性研究

The correlative analysis of altitude and flavor components of Dehong State green coffee beans

  • 摘要: 为了探讨生咖啡风味组分与海拔之间的关系,采用HS-SPME-GC/MS对德宏州13个不同海拔地区的咖啡豆风味组分进行分析,同时利用聚类分析及Pearson相关分析法对相关性进行分析。实验结果表明:德宏州咖啡含量最高5种风味物质分别为异戊醛、异戊醇、正己醇、2,3-丁二醇和异戊酸;按不同海拔咖啡区分,第一主成分累计贡献率为46.572%,第一第二主成分的累计贡献率为74.224%;通过聚类分析可知除样品11外,其它样品分为2大类(900 m以上和900 m以下),但差异不显著;通过Pearson相关性系数分析可知样品间不存在显著性差异,相关性随着海拔差距而增大。综上可知,海拔是造成风味差异的因素之一,但两者的相关性不强,不存在显著性差异。 

     

    Abstract: To explore the relationship of dehong state green coffee flavor component and altitude. The flavor components of Dehong State green coffee beans in 13 different altitudes were analyzed by HS- SPME- GC / MS,while the correlative analysis was executed by cluster analysis and pearson analysis. The experimental results showed that the highest levels of five kinds of flavor substances in Dehong State were 3- methyl- butanal,isoamyl alcohol,hexanol,2,3- butanediol and isovaleric acid.Principal component analysis could distinguish the different elevations coffee,the first principal component cumulative contribution rate was 46.572%,the first and second principal component cumulative contribution rates were 74.224%. The samples were divided into 2 major categories by clustering analysis( 900 m above and 900 m below) excepting sample 11,but the difference was not significant,there was no significant difference between samples via Pearson correlation analysis,but the correlation had increased along with the elevation increasing.All known elevation was one of the factors of flavor differences,but the correlation was not strong,no significant difference.

     

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