高效液相色谱全轮廓指纹图谱结合化学计量学区分不同地区的紫苏叶  

Discrimination of Perilla frutescens(L.) Britt. from Different Geographical Origins by High Performance Liquid Chromatography Fingerprints Combined with Chemometrics

作　　者：董文江[1,2] 倪永年[1,2] 

机构地区：[1]南昌大学食品科学与技术国家重点实验室,江西南昌330047 [2]南昌大学化学系,江西南昌330031

出　　处：《分析测试学报》2014年第5期506-511,共6页Journal of Instrumental Analysis

基　　金：国家自然科学基金项目(21065007)

摘　　要：利用高效液相色谱全轮廓指纹图谱结合化学计量学方法对不同栽培地区的紫苏叶样品(共84个)进行区分。全轮廓色谱数据经自适应迭代加权最小二乘法(airPLS)和相关优化翘曲法(COW)校正后,基线和保留时间漂移现象均得到明显改善。经预处理后的色谱数据采用主成分分析(PCA)进行解析,结果表明不同来源的样品能按其特性各自聚为一类;而分段间隔压缩变量后的色谱数据经主成分分析处理可得到与全轮廓色谱数据为输入变量时相一致的结果。此外,偏最小二乘判别分析(PLS-DA)对于紫苏叶样品分类的识别能力和预报能力分别为92.8%和89.6%。A total of 84 Perilla frutescens （L.） Britt. samples from three main geographical origins inChina were collected and investigated by using high performance liquid chromatography （HPLC） in-corporated with chemometrics method. Prior to investigation, the measured liquid chromatographicdata were subjected to pretreatments, including baseline correction and retention time alignment.Principal component analysis （PCA） was then applied in the aligned and compressed data sets, re-spectively, to evaluate the data quality, and three sample groups were observed in the PCA scoreplots. Moreover, partial least squares - discriminant analysis （ PLS - DA） was applied to classifythese herbal samples, providing better abilities of recognition（92. 896 ） and prediction（89. 6% ）.

关 键 词：紫苏叶 高效液相色谱 指纹图谱 化学计量学 产地区分 

分 类 号：O657.72[理学—分析化学]