title: Rapid discrimination of Apiaceae plants by electronic nose coupled with multivariate statistical analyses.
abstract: Since many Apiaceae plants, with antimicrobial activities, have similar characteristics, it is difficult to separate them from one another. The aim of this study is to distinguish different kinds of Apiaceae plants by an electronic nose (EN) and multivariate statistical analyses. The dynamic response of a metal oxide sensor array to Apiaceae plants showed that the response values and different kinds of Apiaceae plants were positively related. Atractylodis Macrocephalae Rhizoma (as the reference sample) and other nine different kinds of Apiaceae plants were measured. Multivariate statistical analyses, including linear discrimination analysis (LDA), principal component analysis (PCA), hierarchical clustering analysis (HCA) and artificial neural network (ANN), were employed. The result showed that these samples could be classified correctly by this method, which suggested that the EN system could be used as a simple and rapid technique for the discrimination of Apiaceae plants.
authors.affiliation: School of Chinese Materia Medica, Beijing University of Chinese Medicine, No. 6 Wangjing Zhonghuan South Road, Beijing 100102, PR China.
authors.forename: Hui
authors.initials: H
authors.lastname: Lin
authors.forename: Yonghong
authors.initials: Y
authors.lastname: Yan
authors.forename: Ting
authors.initials: T
authors.lastname: Zhao
authors.forename: Lian
authors.initials: L
authors.lastname: Peng
authors.forename: Huiqin
authors.initials: H
authors.lastname: Zou
authors.forename: Jian
authors.initials: J
authors.lastname: Li
authors.forename: Xiaoyun
authors.initials: X
authors.lastname: Yang
authors.forename: Yin
authors.initials: Y
authors.lastname: Xiong
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.forename: Haozhong
authors.initials: H
authors.lastname: Wu
mesh_terms: D019661:Apiaceae / Q000737:chemistry* / Q000145:classification*; D016000:Cluster Analysis; D016002:Discriminant Analysis; D062609:Electronic Nose; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D010946:Plants, Medicinal / Q000737:chemistry* / Q000145:classification*; D025341:Principal Component Analysis / Q000379:methods; D027343:Rhizome / Q000737:chemistry
keywords: Apiaceae; Electronic nose; Medicinal plants; Statistical analysis