Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin
Samo za registrovane korisnike
2017
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Considering the introduction of phytochemical fingerprint analysis, as a method of screening the complex natural products for the presence of most bioactive compounds, use of chemometric classification methods, application of powerful scanning and image capturing and processing devices and algorithms, advancement in development of novel stationary phases as well as various separation modalities, high-performance thin-layer chromatography (HPTLC) fingerprinting is becoming attractive and fruitful field of separation science. Multivariate image analysis is crucial in the light of proper data acquisition. In a current study, different image processing procedures were studied and compared in detail on the example of HPTLC chromatograms of plant resins. In that sense, obtained variables such as gray intensities of pixels along the solvent front, peak area and mean values of peak were used as input data and compared to obtained best classification models. Important steps in image analysis, b...aseline removal, denoising, target peak alignment and normalization were pointed out. Numerical data set based on mean value of selected bands and intensities of pixels along the solvent front proved to be the most convenient for planar-chromatographic profiling, although required at least the basic knowledge on image processing methodology, and could be proposed for further investigation in HPLTC fingerprinting.
Ključne reči:
High-performance thin-layer chromatography / Image analysis / Pattern recognition technique / Phenolics profile / Plant resinsIzvor:
Talanta, 2017, 162, 72-79Izdavač:
- Elsevier Science Bv, Amsterdam
Finansiranje / projekti:
- Korelacija strukture i osobina prirodnih i sintetičkih molekula i njihovih kompleksa sa metalima (RS-172017)
- Slovenian Research Agency [P1-0005]
Napomena:
- Supplementary material: http://cherry.chem.bg.ac.rs/handle/123456789/3065
DOI: 10.1016/j.talanta.2016.10.023
ISSN: 0039-9140
PubMed: 27837887
WoS: 000389088700011
Scopus: 2-s2.0-84991088912
Institucija/grupa
Hemijski fakultet / Faculty of ChemistryTY - JOUR AU - Ristivojević, Petar AU - Trifković, Jelena AU - Vovk, Irena AU - Milojković-Opsenica, Dušanka PY - 2017 UR - https://cherry.chem.bg.ac.rs/handle/123456789/2359 AB - Considering the introduction of phytochemical fingerprint analysis, as a method of screening the complex natural products for the presence of most bioactive compounds, use of chemometric classification methods, application of powerful scanning and image capturing and processing devices and algorithms, advancement in development of novel stationary phases as well as various separation modalities, high-performance thin-layer chromatography (HPTLC) fingerprinting is becoming attractive and fruitful field of separation science. Multivariate image analysis is crucial in the light of proper data acquisition. In a current study, different image processing procedures were studied and compared in detail on the example of HPTLC chromatograms of plant resins. In that sense, obtained variables such as gray intensities of pixels along the solvent front, peak area and mean values of peak were used as input data and compared to obtained best classification models. Important steps in image analysis, baseline removal, denoising, target peak alignment and normalization were pointed out. Numerical data set based on mean value of selected bands and intensities of pixels along the solvent front proved to be the most convenient for planar-chromatographic profiling, although required at least the basic knowledge on image processing methodology, and could be proposed for further investigation in HPLTC fingerprinting. PB - Elsevier Science Bv, Amsterdam T2 - Talanta T1 - Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin VL - 162 SP - 72 EP - 79 DO - 10.1016/j.talanta.2016.10.023 ER -
@article{ author = "Ristivojević, Petar and Trifković, Jelena and Vovk, Irena and Milojković-Opsenica, Dušanka", year = "2017", abstract = "Considering the introduction of phytochemical fingerprint analysis, as a method of screening the complex natural products for the presence of most bioactive compounds, use of chemometric classification methods, application of powerful scanning and image capturing and processing devices and algorithms, advancement in development of novel stationary phases as well as various separation modalities, high-performance thin-layer chromatography (HPTLC) fingerprinting is becoming attractive and fruitful field of separation science. Multivariate image analysis is crucial in the light of proper data acquisition. In a current study, different image processing procedures were studied and compared in detail on the example of HPTLC chromatograms of plant resins. In that sense, obtained variables such as gray intensities of pixels along the solvent front, peak area and mean values of peak were used as input data and compared to obtained best classification models. Important steps in image analysis, baseline removal, denoising, target peak alignment and normalization were pointed out. Numerical data set based on mean value of selected bands and intensities of pixels along the solvent front proved to be the most convenient for planar-chromatographic profiling, although required at least the basic knowledge on image processing methodology, and could be proposed for further investigation in HPLTC fingerprinting.", publisher = "Elsevier Science Bv, Amsterdam", journal = "Talanta", title = "Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin", volume = "162", pages = "72-79", doi = "10.1016/j.talanta.2016.10.023" }
Ristivojević, P., Trifković, J., Vovk, I.,& Milojković-Opsenica, D.. (2017). Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin. in Talanta Elsevier Science Bv, Amsterdam., 162, 72-79. https://doi.org/10.1016/j.talanta.2016.10.023
Ristivojević P, Trifković J, Vovk I, Milojković-Opsenica D. Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin. in Talanta. 2017;162:72-79. doi:10.1016/j.talanta.2016.10.023 .
Ristivojević, Petar, Trifković, Jelena, Vovk, Irena, Milojković-Opsenica, Dušanka, "Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin" in Talanta, 162 (2017):72-79, https://doi.org/10.1016/j.talanta.2016.10.023 . .