An integrated approach utilising chemometrics and GC/MS for classification of chamomile flowers, essential oils and commercial products

•Three types of chamomile flowers, commercial products and oils were analysed.•A sample class prediction (SCP) model was constructed based on chemometrics.•Commercial products and oils containing chamomile were predicted by the SCP model.•Identification of markers correlated with different chamomiles was explored. As part of an ongoing research program on authentication, safety and biological evaluation of phytochemicals and dietary supplements, an in-depth chemical investigation of different types of chamomile was performed. A collection of chamomile samples including authenticated plants, commercial products and essential oils was analysed by GC/MS. Twenty-seven authenticated plant samples representing three types of chamomile, viz. German chamomile, Roman chamomile and Juhua were analysed. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model was cross-validated with samples including authenticated plants and commercial products. The model demonstrated 100.0% accuracy for both recognition and prediction abilities. In addition, 35 commercial products and 11 essential oils purported to contain chamomile were subsequently predicted by the validated PLS-DA model. Furthermore, tentative identification of the marker compounds correlated with different types of chamomile was explored.