Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 61-70 |
| Number of pages | 10 |
| Journal | Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences |
| Volume | 910 |
| DOIs | |
| State | Published - Jun 4 2012 |
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Keywords
- Correlation and distance matrix
- Fingerprint chromatography
- Green tea
- Quality control
- Sample identification
- Similarity analysis
ASJC Scopus subject areas
- Analytical Chemistry
- Biochemistry
- Clinical Biochemistry
- Cell Biology
Cite this
Similarity analyses of chromatographic fingerprints as tools for identification and quality control of green tea. / Alaerts, G.; Van Erps, J.; Pieters, S.; Dumarey, M.; van Nederkassel, A. M.; Goodarzi, M.; Smeyers-Verbeke, J.; Vander Heyden, Y.
In: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, Vol. 910, 04.06.2012, p. 61-70.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Similarity analyses of chromatographic fingerprints as tools for identification and quality control of green tea
AU - Alaerts, G.
AU - Van Erps, J.
AU - Pieters, S.
AU - Dumarey, M.
AU - van Nederkassel, A. M.
AU - Goodarzi, M.
AU - Smeyers-Verbeke, J.
AU - Vander Heyden, Y.
PY - 2012/6/4
Y1 - 2012/6/4
N2 - 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.
AB - 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.
KW - Correlation and distance matrix
KW - Fingerprint chromatography
KW - Green tea
KW - Quality control
KW - Sample identification
KW - Similarity analysis
UR - http://www.scopus.com/inward/record.url?scp=84870238366&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870238366&partnerID=8YFLogxK
U2 - 10.1016/j.jchromb.2012.04.031
DO - 10.1016/j.jchromb.2012.04.031
M3 - Article
C2 - 22672846
AN - SCOPUS:84870238366
VL - 910
SP - 61
EP - 70
JO - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
JF - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
SN - 1570-0232
ER -