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色谱质谱技术结合主成分分析鉴别庐山云雾茶真伪 被引量:5

Identification of Clouds-Mist Tea from Lu Mountain by Chromatography Mass Spectrometry and Principal Component Analysis
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摘要 利用高效液相色谱检测庐山云雾茶水溶性成分,建立庐山云雾茶水溶性成分指纹图谱,并对共有峰相对峰面积进行主成分分析。其中庐山云雾茶液相指纹图谱有38个共有峰,样品与对照指纹图谱相似度均在0.93以上,经主成分分析得到3个主成分,累计方差贡献率达到81.7%。该方法的庐山云雾茶真伪判别率达100%。利用气相色谱-质谱联用技术检测庐山云雾茶挥发性成分,共鉴定出38种挥发性成分,并对共有峰相对峰面积进行主成分分析。经主成分分析得到3个主成分,累计方差贡献率达到83.8%。该方法庐山云雾茶真伪判别率达100%。本试验为庐山云雾茶真伪识别提供一种新思路。 Analysis water soluble components of Lu Mountain Clouds-Mist Tea with high performance liquid chromatography. To establish the fingerprint of Lu Mountain Clouds-Mist Tea, the common peaks were identified by principal component analysis. There were 38 common peaks in the fingerprints of 20 batches of Lu Mountain Clouds-Mist Tea samples, the similarity of samples was above 0.93 with their characteristic fingerprint. Through principal component analysis, three principal components were obtained and make up 81.7% of the total variance. Results the Lu Mountain Clouds-Mist Tea can be authenticity identified from the samples and could be 100% correctly discriminated. Analysis volatile components of Lu Mountain Clouds-Mist Tea with Gas chromatography-mass spectrometry. 38 kinds of volatile components were extracted and through principal component analysis, three principal components were obtained and make up 83.8% of the total variance. Results the Lu Mountain Clouds-Mist Tea can be authenticity identified and could be 100% correctly discriminated. This experiment provides a new idea to identify the authenticity of Lu Mountain Clouds-Mist Tea.
作者 刘晔 徐春晖 王远兴 Liu Ye;Xu Chunhui;Wang Yuanxing(State Key Laboratory of Food Science and Technology,Nanchang University,Nanchang 330047)
出处 《中国食品学报》 EI CAS CSCD 北大核心 2019年第7期262-274,共13页 Journal of Chinese Institute Of Food Science and Technology
基金 国家自然科学基金项目(31560478,31160321)
关键词 庐山云雾茶 高效液相色谱技术(HPLC) 气-质联用技术(GC-MS) 主成分分析 真伪识别 Lu Mountain Clouds-Mist Tea high performance liquid chromatography gas chromatography-mass spectrometry principal component analysis authenticity discrimination
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