Goedele Alaerts

Similarity analyses of chromatographic fingerprints as tools for identification and quality control of green tea.

Similarity assessment of complex chromatographic profiles of herbal medicinal products is important as a potential tool for their identification. Mathematical similarity parameters have the advantage to be more reliable than visual similarity evaluations of often subtle differences between the fingerprint profiles. In this paper, different similarity analysis (SA) parameters are applied on green-tea chromatographic fingerprint profiles in order to test their ability to identify (dis)similar tea samples. These parameters are either based on correlation or distance measurements. They are visualised in colour maps and evaluation plots. Correlation (r) and congruence (c) coefficients are shown to provide the same information about the similarity of samples. The standardised Euclidean distance (ds) reveals less information than the Euclidean distance (de), while Mahalanobis distances (dm) are unsuitable for the similarity assessment of chromatographic fingerprints. The adapted similarity score (ss*) combines the advantages of r (or c) and de. Similarity analysis based on correlation is useful if concentration differences between samples are not important, whereas SA based on distances also detects concentration differences well. The evaluation plots including statistical confidence limits for the plotted parameter are found suitable for the evaluation of new suspected samples during quality assurance. The ss* colour maps and evaluation plots are found to be the best tools (in comparison to the other studied parameters) for the distinction between deviating and genuine fingerprints. For all studied data sets it is confirmed that adequate data pre-treatment, such as aligning the chromatograms, prior to the similarity assessment, is essential. Furthermore, green-tea samples chromatographed on two dissimilar High-Performance Liquid Chromatography (HPLC) columns provided the same similarity assessment. Combining these complementary fingerprints did not improve the similarity analysis of the studied data set.

Exploratory analysis of chromatographic fingerprints to distinguish rhizoma Chuanxiong and rhizoma Ligustici.

Identification and quality control of products of natural origin, used for preventive and therapeutical goals, is required by regulating authorities, as the World Health Organization. This study focuses on the identification and distinction of the rhizomes from two Chinese herbs, rhizoma Chuanxiong (from Ligusticum chuanxiong Hort.) and rhizoma Ligustici (from Ligusticum jeholense Nakai et Kitag), by chromatographic fingerprints. A second goal is using the fingerprints to assay ferulic acid, as its concentration provides an additional differentiation feature. Several extraction methods were tested, to obtain the highest number of peaks in the fingerprints. The best results were found using 76:19:5 (v/v/v) methanol/water/formic acid as solvent and extracting the pulverized material on a shaking bath for 15 min. Then fingerprint optimization was done. Most information about the herbs, i.e. the highest number of peaks, was observed on a Hypersil ODS column (250 mm × 4.6 mm ID, 5 μm), 1.0% acetic acid in the mobile phase and employing within 50 min linear gradient elution from 5:95 (v/v) to 95:5 (v/v) acetonitrile/water. The final fingerprints were able to distinguish rhizoma Chuanxiong and Ligustici, based on correlation coefficients combined with exploratory data analysis. The distinction was visualized using Principal Component Analysis, Projection Pursuit and Hierarchical Clustering Analysis techniques. Quantification of ferulic acid was possible in the fingerprints of both rhizomes. The time-different intermediate precisions of the fingerprints and of the ferulic acid quantification were shown to be acceptable.

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.

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.

Pressurized capillary electrochromatography in a screening for possible antioxidant molecules in Mallotus fingerprints: challenges, potentials and prospects.

Because of its eminent high resolution potential and minimal solvent consumption, pressurized capillary electrochromatography (pCEC) may offer an interesting alternative to HPLC for screening applications that need to resolve complex samples. In this paper, its potential was assessed in a screening of plant extracts from Mallotus species to indicate compounds with possible antioxidant activities by means of a PLS model built from their pCEC fingerprints. The main aim of this research was to find out whether pCEC can have an added value for this application. To get a complete overview of the techniques potential for this application, it was also assessed whether the technique can meet the requirements in terms of precision, sensitivity and column robustness. Encountered benefits and downsides were reported. Fingerprints with satisfactory sensitivity and precision could be obtained by concentrating the sample 5-fold and using optimized rinsing procedures, respectively. From the generated pCEC fingerprints of 39 Mallotus samples and their respective DPPH radical scavenging activity test results, a three-component PLS model was being built. The model proved good predictive abilities and easily allowed the indication of possible antioxidant compounds in the fingerprints. Despite its much higher peak capacity, the performance of pCEC to fingerprint the majority of the Mallotus extracts did not surpass that of a custom HPLC method. This was also reflected in its comparable power to indicate possible antioxidant compounds in the fingerprints after modeling. Because of its low detection sensitivity and modest column robustness, the benefit of the lower solvent consumption was partly paid-off by the current need for more system maintenance, also limiting the sample throughput. For the considered screening application, pCEC may suit as a viable but no preferred alternative technique.