Development and application of a versatile HPLC-PDA method for the simultaneous determination of structurally diverse bioactive metabolites in medicinal and aromatic plants

Numerous plants are rich in secondary metabolites, such as phenols, flavonoids and terpenoids, which are associated with various beneficial properties. Extraction methods reported in literature allow the extraction of such phytochemicals, however, robust analytical methods, capable for the simultaneous determination of multi-class metabolites, applicable to multiple plant matrices, remain essential. This work presents the development, validation and application of a simple, sensitive, multi-residue and versatile High-Performance Liquid Chromatography – Photo-Diode Array detector (HPLC-PDA) method for the simultaneous determination of eleven secondary plant metabolites, exhibiting a wide range of polarities, within a single analytical run. The proposed method demonstrated excellent linearity ( R 2 > 0.99) in a wide range of concentrations for all analytes, high method sensitivity, with limits of quantification (LOQ) ranging from 0.02 to 1.2 μg mL −1 , high precision, with intra-day and inter-day precision values below 5 and 10% respectively and accuracy in the 90–110% for low and 95–105% range for intermediate and high concentrations. The analytes were found to remain stable, with changes within 5% of the initial response, over a 30-day refrigerated-storage. The method was successfully tested on four plant extracts (i.e. Origanum vulgare , Rosmarinus officinalis , Lavandula angustifolia and Camellia sinensis ) and analyte identity was further confirmed with mass spectrometry (MS). Between five and eight metabolites were detected and quantified in each analyzed extract, demonstrating the broad applicability of the method. Overall, the proposed method constitutes a reliable and cost-effective tool for simultaneous separation and determination of chemically diverse secondary plant metabolites, which can facilitate phytochemical profiling for complex plant matrices.