Application of GC/Q-ToF combined with advanced data mining and chemometric tools in the characterization and quality control of bay leaves

Authors: WANG, MEI - University Of Mississippi; RAMAN, VIJAYASANKAR - University Of Mississippi; ZHAO, JIANPING - University Of Mississippi; AVULA, BHARATHI - University Of Mississippi; WANG, YAN-HONG - University Of Mississippi; WYLIE, PHILIP - Agilent Technologies, Inc; KHAN, IKHLAS - University Of Mississippi

Submitted to: Planta Medica
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/26/2018
Publication Date: 2/26/2018
Citation: Wang, M., Raman, V., Zhao, J., Avula, B., Wang, Y., Wylie, P.L., Khan, I.A. 2018. Application of GC/Q-ToF combined with advanced data mining and chemometric tools in the characterization and quality control of bay leaves. Planta Medica. https://doi.org/10.1055/a-0585-5987.
DOI: https://doi.org/10.1055/a-0585-5987

Interpretive Summary: Laurus nobilis, the true bay leaf, is a common household spice used in flavoring a wide varity of foods. However, leaves from several other species are also traded as “bay leaves” and are often substituted or confused with the true bay leaves due to their similar usage and resemblances in aroma and leaf morphology. The aroma and flavor of these leaves are however not the same as the true bay leaf, and for that reason they should not be used in cooking as a substitute for L. nobilis. Some of the bay leaf surrogates, for example Umbellularia californica, can cause potential health problems. Therefore, correct identification of the true bay leaf is important. The present work is the first study to analyze various bay leaf samples using GC/Q-ToF with accurate mass and retention time locking data for non-targeted compound analysis. The sample class prediction model (PLS-DA) constructed for the analyzed samples was successfully applied to classify and predict commercial bay leaf products from different species. In addition, an in-house developed personal compound database and library (PCDL) was used for the compound identification.

Technical Abstract: Correct identification of the true bay leaf and its substitutes is of great importance not only for the quality control of the bay leaf products sold in U.S. market, but also for the safety concerns of consumers. In this study, the potential of gas chromatography combined with quadrupole time-of-flight mass spectrometry (GC/Q-ToF MS) for the profiling of bay leaf samples were evaluated. Thirty-nine authenticated bay leaf samples representing the true bay leaf (Laurus nobilis) and four common substitute species (Cinnamomum tamala, Pimenta racemosa, Syzygium polyanthum and Umbellularia californica) were analyzed. GC/Q-ToF with retention time locking offered the advantage of combining retention-time matching with accurate-mass matching, resulting in high confidence of compound identification. An automatic feature extraction algorithm was applied for data mining and pretreatment in order to identify the most characteristic marker compounds representing different bay leaf groups. This set of data was employed to construct a sample class prediction (SCP) model based on stepwise reduction of data dimensionality followed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The model, with demonstrated excellent accuracies in recognition and prediction abilities, enabled correct classification of 10 commercial samples. In addition, the tentative identification of major and marker compounds were carried out using accurate mass measurement of full single MS spectra and a custom personal compound database and library (PCDL).