Exploration and classification of chromatographic fingerprints as additional tool for identification and quality control of several Artemisia species.

The World Health Organization accepts chromatographic fingerprints as a tool for identification and quality control of herbal medicines. This is the first study in which the distinction, identification and quality control of four different Artemisia species, i.e. Artemisia vulgaris, A. absinthium, A. annua and A. capillaris samples, is performed based on the evaluation of entire chromatographic fingerprint profiles developed with identical experimental conditions. High-Performance Liquid Chromatography (HPLC) with Diode Array Detection (DAD) was used to develop the fingerprints. Application of factorial designs leads to methanol/water (80:20 (v/v)) as the best extraction solvent for the pulverised plant material and to a shaking bath for 30 min as extraction method. Further, so-called screening, optimisation and fine-tuning phases were performed during fingerprint development. Most information about the different Artemisia species, i.e. the highest number of separated peaks in the fingerprint, was acquired on four coupled Chromolith columns (100 mm × 4.6 mm I.D.). Trifluoroacetic acid 0.05% (v/v) was used as mobile-phase additive in a stepwise linear methanol/water gradient, i.e. 5, 34, 41, 72 and 95% (v/v) methanol at 0, 9, 30, 44 and 51 min, where the last mobile phase composition was kept isocratic till 60 min. One detection wavelength was selected to perform data analysis. The lowest similarity between the fingerprints of the four species was present at 214 nm. The HPLC/DAD method was applied on 199 herbal samples of the four Artemisia species, resulting in 357 fingerprints. The within- and between-day variation of the entire method, as well as the quality control fingerprints obtained during routine analysis, were found acceptable. The distinction of these Artemisia species was evaluated based on the entire chromatographic profiles, developed by a shared method, and visualised in score plots by means of the Principal Component Analysis (PCA) exploratory data-analysis technique. Samples of different quality could be indicated on the score plots. No multi-component analysis was required to reach the goal. Furthermore, differences related to the origin of some of the not-certified samples were shown. The importance of the specific herbal part used for its identification was also presented. In addition, no differences were observed among fingerprints of lyophilised or conditioned-air dried samples. Finally, a classification technique, Soft Independent Modelling by Class Analogy (SIMCA), was successfully evaluated as identification technique for unknown samples. Six additional Artemisia species (29 herbal samples) were identified as not belonging to any of the four modelled classes. The developed chromatographic fingerprints and the evaluation of the entire profiles provide an added value to the distinction, identification and quality control of the simultaneously investigated Artemisia species.

Recent developments in chromatographic fingerprints from herbal products: set-up and data analysis.

The use of chromatographic fingerprints from herbal products where the whole chromatographic profile is applied to evaluate the quality of the investigated product. In this paper, recent developments in the set-up and data analysis of chromatographic fingerprints for herbal products are discussed. First different set-ups for fingerprint development are reviewed. Prior to fingerprint development, a suitable sample preparation, e.g. extraction, should be considered. In a second instance, this review focuses on the data analysis with regards to the different applications of fingerprints. Usually, chemometric data pretreatment is necessary. This is discussed first, followed by a short overview of the data handling techniques used in the two main application areas of herbal fingerprints, i.e. quality assurance and classification or calibration. The quality assurance, which involves the identification and quality control of the herbal products, is reviewed, followed by the use of fingerprints in classification or modelling. The different application areas are illustrated and discussed with several case studies.

Broad-spectrum separations in metabolomics using enhanced polar LC stationary phases: a dedicated evaluation using plant metabolites.

In metabolomics, major efforts are invested in the development of suitable analytical approaches. A tendency towards the use of LC-MS is nowadays very obvious. A great majority of the metabolites of interest are polar to highly polar in nature. We focus on the so-called 'extended polarity' reversed LC phases, developed specifically to allow better retention characteristics for polar compounds. Several of these phases (Atlantis dC18, Inertsil ODS-3, Zorbax XDB, Alltima HP C18) are tested for different column dimension variations (0.5, 1.0, 2.1 mm id) in a specific LC-MS metabolomics setting. Important chromatographic and mass spectrometric quality parameters such as capacity factor, separation efficiency, peak symmetry, sensitivity, and mass accuracy are taken into account. All phases show adequate retention of polar compounds and also perform well with highly aqueous mobile phase compositions. On comparing 1.0 and 2.1 mm id columns, it is clear that the potential gain in sensitivity is not achieved. Using a Lockspray device, accurate mass measurement with a Q-TOF micro is feasible within a mass range of 12 ppm if signal intensities of compound and lockmass are equated. Finally, the extended polarity RP approach in metabolomics experiments is endorsed using real plant extracts.

Sequential uniform designs for fingerprints development of Ginkgo biloba extracts by capillary electrophoresis.

A sequential procedure for the method of development of fingerprints based on a uniform design approach has been described in this paper. The sequential uniform design is used to reach the global optimum for a separation. The procedure is illustrated through developing the fingerprint of a Ginkgo biloba extract by capillary electrophoresis (CE) with diode array detection (DAD). The local overlap index (LOVI) is proposed as a criterion to evaluate the separation quality of two-dimensional hyphenated data in the optimization process. The successful application of the described techniques, including a sequential procedure, the CE-DAD hyphenated method and the LOVI criterion, shows their practicality in the fingerprint development of herbal medicines. However, some critical remarks on their use can also be made.