Application of GC/Q-ToF Combined with Advanced Data Mining and Chemometric Tools in the Characterization and Quality Control of Bay Leaves

Abstract

Correct identification of the true bay leaf () and its substitutes is important not only for the quality control of the products, but also for the safety of the consumers. is often substituted or confused with other species, such as, and In the present study, the potential of gas chromatography combined with quadrupole time-of-flight mass spectrometry for the profiling of various bay leaf products was evaluated for the first time. Thirty-nine authenticated samples representing the true bay leaf and the four commonly substituted species were analyzed. An automatic feature extraction algorithm was applied for data mining and pretreatment in order to identify the most characteristic compounds representing different bay leaf groups. This set of data was employed to construct a sample class prediction model based on stepwise reduction of data dimensionality followed by principal component analysis and partial least squares discriminant analysis. The statistical model, with demonstrated excellent accuracies in recognition and prediction abilities, enabled the correct classification of commercial samples including complex mixtures and essential oils. In addition, in-house developed personal compound database and library with retention time locking offered the advantage of combining retention time matching with accurate mass matching, resulting in high confidence of compound identification for each bay leaf subgroup. At least three marker compounds were identified for each bay leaf species that could be used to discriminate among them.

Screening for More than 1,000 Pesticides and Environmental Contaminants in Cannabis by GC/Q-TOF

“…Samples were analyzed on an Agilent 8890 GC equipped with an Agilent 7693 Autosampler, a multimode inlet (MMI), a pneumatic switching device, a Purged Ultimate Union (PUU) for backflushing [23, 24], and two 15 m × 0.25 mm × 0.25 µm Agilent HP-5MS Ultra Inert columns. The mass spectral detector was an Agilent 7250 High Resolution Accurate Mass Q-TOF MS operated in the full spectral acquisition mode.…”

Bay Laurel (Laurus nobilis L.) Essential Oil as a Food Preservative Source: Chemistry, Quality Control, Activity Assessment, and Applications to Olive Industry Products

“…Regarding fingerprinting of bay laurel EO, the first relevant study was published recently [ 41 ] and was about the development of a Principal Component Analysis (PCA) chemometric model for the discrimination of the plant species based on non-destructive NIR, Raman, and Laser-Induced Breakdown Spectroscopy (LIBS) data. In the same period, Wang et al [ 42 ] reported a rather sophisticated procedure to develop a class model for the prediction of commercial products labeled as “laurel leaves” or “laurel EO” using GC/Q-ToF analytical data and a combination of PCA and Partial Least Squares-Discriminant Analysis (PLS-DA) chemometric methods. More recently, Ordoudi and collaborators [ 15 ] presented a less complicated approach to characterize the botanical origin of bay laurel EOs through non-targeted FT-IR fingerprinting and the use of one-class chemometric models (Soft Independent Modeling of Class Analogy, SIMCA).…”