• EI
  • Scopus
  • 中国科技期刊卓越行动计划项目资助期刊
  • 北大核心期刊
  • DOAJ
  • EBSCO
  • 中国核心学术期刊RCCSE A+
  • 中国精品科技期刊
  • JST China
  • FSTA
  • 中国农林核心期刊
  • 中国科技核心期刊CSTPCD
  • CA
  • WJCI
  • 食品科学与工程领域高质量科技期刊分级目录第一方阵T1
中国精品科技期刊2020
张丰, 董文江, 王凯丽, 谷风林, 熊善柏, 赵建平. 云南不同地区烘焙咖啡豆挥发性成分的HS-SPME/GC-MS分析[J]. 华体会体育, 2015, (11): 273-280. DOI: 10.13386/j.issn1002-0306.2015.11.047
引用本文: 张丰, 董文江, 王凯丽, 谷风林, 熊善柏, 赵建平. 云南不同地区烘焙咖啡豆挥发性成分的HS-SPME/GC-MS分析[J]. 华体会体育, 2015, (11): 273-280. DOI: 10.13386/j.issn1002-0306.2015.11.047
ZHANG Feng, DONG Wen-jiang, WANG Kai-li, GU Feng-lin, XIONG Shan-bai, ZHAO Jian-ping. Comparative analysis of aromatic components of roasted coffee beans from different gengraphical origins in Yunnan province by HS- SPME / GC- MS[J]. Science and Technology of Food Industry, 2015, (11): 273-280. DOI: 10.13386/j.issn1002-0306.2015.11.047
Citation: ZHANG Feng, DONG Wen-jiang, WANG Kai-li, GU Feng-lin, XIONG Shan-bai, ZHAO Jian-ping. Comparative analysis of aromatic components of roasted coffee beans from different gengraphical origins in Yunnan province by HS- SPME / GC- MS[J]. Science and Technology of Food Industry, 2015, (11): 273-280. DOI: 10.13386/j.issn1002-0306.2015.11.047

云南不同地区烘焙咖啡豆挥发性成分的HS-SPME/GC-MS分析

Comparative analysis of aromatic components of roasted coffee beans from different gengraphical origins in Yunnan province by HS- SPME / GC- MS

  • 摘要: 采用顶空固相微萃取法(HS-SPME)结合气相色谱-质谱联用(GC-MS)对云南三个地区(普洱、保山、临沧)烘焙咖啡的挥发性物质进行分析,考察不同萃取条件(萃取头、萃取温度、萃取时间、样品量)对挥发性物质萃取效果的影响,利用主成分分析(PCA)和系统聚类分析(HCA)对不同地区样品进行区分。结果表明:在最优的萃取条件下,共鉴定出65种挥发性物质,其中呋喃类物质含量最高,三个地区分别为46.15%、41.45%和41.16%;硫化物和呋喃酮类物质含量较少;不同地区样品在PCA的二维得分投影图上各自聚为一类,HCA的最小二乘树状图分类结果与PCA相一致。 

     

    Abstract: Headspace solid- space microextraction ( HS- SPME) / gas chromatography- mass spectroscopy ( GC-MS) was applied to analyze the aromatic components of coffee beans collented from three areas ( Puer, Baoshan, Lincang) in China. Different extraction conditions ( SPME fibers, sample weight, extraction temperature, extraction time) were applied to test the influence on extraction efficiency.Samples discrimination was achieved by principal component analysis ( PCA) and hierarchical cluster analysis ( HCA) . The results indicated that a total of 65 aroma components were identified in coffee beans under optimum conditions, among them, furans compounds were the most abundant component ( 46.15%, 41.45% and 41.16% respectively) , whereas sulfurs and furanone compounds accounted for less, respectively. PCA and HCA showed that these coffee samples could be clearly differentiated according to geographical origins.

     

/

返回文章
返回