基于表面解吸常压化学电离质谱法快速评价咖啡种子活力  

Rapid Evaluation of Seed Vigor of Coffee by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry

作　　者：殷勤[1] 罗火林[1] 刘星星[1] 黄学勇[1] 罗丽萍[1] 

机构地区：[1]南昌大学生命科学学院,南昌330031

出　　处：《分析化学》2016年第2期198-204,共7页Chinese Journal of Analytical Chemistry

基　　金："十二五"国家科技支撑计划(No.2012BDA29B01);国家自然科学基金(No.31370384);江西省科技厅项目(No.20123BCB22004);江西省教育厅项目(No.KJLD12051)资助~~

摘　　要：为快速、无损地区分不同活力的咖啡种子,采用自行研制的表面解吸常压化学电离质谱(DAPCIMS),在无需样品预处理的前提下,获得咖啡种子表面的化学指纹图谱,并分别进行了主成分分析(PCA)、聚类分析(CA)和判别分析(DA),获得不同活力的咖啡种子样品的质谱信息特征。结果表明,在正离子模式下,DAPCI-MS结合多变量分析方法能有效区分不同活力的咖啡种子。PCA提取了3个主成分,累计贡献率达到92.2%;CA可以将相同活力的咖啡种子聚在一起,准确率为100%;DA对训练样本的回判正确率为100%,交叉验证分析成功率为100%,对外部验证样本进行DA,正确率95.7%。本方法具有无需样品预处理,分析速度快,灵敏度高,对种子无损伤等优点,能为其它种子活力测定提供参考。To determine the seed vigor of coffee quickly and non-destructively, surface desorption atmospheric pressure chemical ionization mass spectrometry （DAPCI-MS） was used to obtain chemical fingerprints directly from the surface of the coffee seed, without any sample pretreatment. The mass spectral raw data were analyzed by multivariate analysis, including principal component analysis （PCA）, cluster analysis （CA） and discriminant analysis （DA）, to differentiate efficaciously the coffee seeds with different vigor. The experimental results demonstrated that in the positive ion mode, DAPCI-MS combined with multivariate analysis could effectively distinguish different seed vigor for coffee seed. Three principal components were extracted by PCA, and their cumulative contribution rate was 92.2%. Coffee seeds with the same vigor was packed closely together in CA analysis, and its accuracy was 100%. In DA analysis, the return discriminant ratio for the training muster was as high as 100% , while the cross validation analysis success rate was 100%. Thus, it was concluded that the coffee seeds with different vigor could be differentiated by DAPCI-MS, and the results orovided a basis for establishin~ a fast, non-destructive and sensitive detection method of seed vigor.

关 键 词：表面解吸常压化学电离质谱 咖啡 种子活力 多变量分析 

分 类 号：S571.2[农业科学—作物学] O657.63[理学—分析化学]