TY  - DATA
AU  - Ristivojević, Petar
AU  - Trifković, Jelena
AU  - Vovk, Irena
AU  - Milojković-Opsenica, Dušanka
PY  - 2017
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3065
PB  - Elsevier Science Bv, Amsterdam
T2  - Talanta
T1  - Supplementary data for article:          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. Talanta 2017, 162, 72–79. https://doi.org/10.1016/j.talanta.2016.10.023
DO  - 10.1016/j.talanta.2016.10.023
ER  - 

@misc{
author = "Ristivojević, Petar and Trifković, Jelena and Vovk, Irena and Milojković-Opsenica, Dušanka",
year = "2017",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Talanta",
title = "Supplementary data for article:          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. Talanta 2017, 162, 72–79. https://doi.org/10.1016/j.talanta.2016.10.023",
doi = "10.1016/j.talanta.2016.10.023"
}

Ristivojević, P., Trifković, J., Vovk, I.,& Milojković-Opsenica, D.. (2017). Supplementary data for article:          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. Talanta 2017, 162, 72–79. https://doi.org/10.1016/j.talanta.2016.10.023. in Talanta
Elsevier Science Bv, Amsterdam..
https://doi.org/10.1016/j.talanta.2016.10.023

Ristivojević P, Trifković J, Vovk I, Milojković-Opsenica D. Supplementary data for article:          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. Talanta 2017, 162, 72–79. https://doi.org/10.1016/j.talanta.2016.10.023. in Talanta. 2017;.
doi:10.1016/j.talanta.2016.10.023 .

Ristivojević, Petar, Trifković, Jelena, Vovk, Irena, Milojković-Opsenica, Dušanka, "Supplementary data for article:          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. Talanta 2017, 162, 72–79. https://doi.org/10.1016/j.talanta.2016.10.023" in Talanta (2017),
https://doi.org/10.1016/j.talanta.2016.10.023 . .

TY  - 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 . .

TY  - JOUR
AU  - Milojković-Opsenica, Dušanka
AU  - Ristivojević, Petar
AU  - Trifković, Jelena
AU  - Vovk, Irena
AU  - Lušić, Dražen
AU  - Tešić, Živoslav Lj.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2360
AB  - Propolis is a "natural" remedy with prominent biological activity, which is used as dietary supplement. In the absence of clinical studies that would substantiate these claims, information on the biological activity of propolis is valuable. This study comprises chromatographic, image processing and chemometric approach for phenolic profiling of Serbian, Croatian and Slovenian propolis test solutions. Modern thin-layer chromatography equipment in combination with software for image processing was applied for fingerprinting and data acquisition, whereas the principal component analysis was used as pattern recognition method. Characterization of phenolic profile was performed along with the determination of the botanical and geographical origin of propolis. High-performance thin-layer chromatograms reveal that Central and Southeastern European propolis samples are rich in flavonoids. In addition, phenolic compounds proved to be suitable markers for the determination of European propolis authenticity.
PB  - Oxford Univ Press Inc, Cary
T2  - Journal of Chromatographic Science
T1  - TLC Fingerprinting and Pattern Recognition Methods in the Assessment of Authenticity of Poplar-Type Propolis
VL  - 54
IS  - 7
SP  - 1077
EP  - 1083
DO  - 10.1093/chromsci/bmw024
ER  - 

@article{
author = "Milojković-Opsenica, Dušanka and Ristivojević, Petar and Trifković, Jelena and Vovk, Irena and Lušić, Dražen and Tešić, Živoslav Lj.",
year = "2016",
abstract = "Propolis is a "natural" remedy with prominent biological activity, which is used as dietary supplement. In the absence of clinical studies that would substantiate these claims, information on the biological activity of propolis is valuable. This study comprises chromatographic, image processing and chemometric approach for phenolic profiling of Serbian, Croatian and Slovenian propolis test solutions. Modern thin-layer chromatography equipment in combination with software for image processing was applied for fingerprinting and data acquisition, whereas the principal component analysis was used as pattern recognition method. Characterization of phenolic profile was performed along with the determination of the botanical and geographical origin of propolis. High-performance thin-layer chromatograms reveal that Central and Southeastern European propolis samples are rich in flavonoids. In addition, phenolic compounds proved to be suitable markers for the determination of European propolis authenticity.",
publisher = "Oxford Univ Press Inc, Cary",
journal = "Journal of Chromatographic Science",
title = "TLC Fingerprinting and Pattern Recognition Methods in the Assessment of Authenticity of Poplar-Type Propolis",
volume = "54",
number = "7",
pages = "1077-1083",
doi = "10.1093/chromsci/bmw024"
}

Milojković-Opsenica, D., Ristivojević, P., Trifković, J., Vovk, I., Lušić, D.,& Tešić, Ž. Lj.. (2016). TLC Fingerprinting and Pattern Recognition Methods in the Assessment of Authenticity of Poplar-Type Propolis. in Journal of Chromatographic Science
Oxford Univ Press Inc, Cary., 54(7), 1077-1083.
https://doi.org/10.1093/chromsci/bmw024

Milojković-Opsenica D, Ristivojević P, Trifković J, Vovk I, Lušić D, Tešić ŽL. TLC Fingerprinting and Pattern Recognition Methods in the Assessment of Authenticity of Poplar-Type Propolis. in Journal of Chromatographic Science. 2016;54(7):1077-1083.
doi:10.1093/chromsci/bmw024 .

Milojković-Opsenica, Dušanka, Ristivojević, Petar, Trifković, Jelena, Vovk, Irena, Lušić, Dražen, Tešić, Živoslav Lj., "TLC Fingerprinting and Pattern Recognition Methods in the Assessment of Authenticity of Poplar-Type Propolis" in Journal of Chromatographic Science, 54, no. 7 (2016):1077-1083,
https://doi.org/10.1093/chromsci/bmw024 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Andrić, Filip
AU  - Trifković, Jelena
AU  - Vovk, Irena
AU  - Stanisavljević, Ljubiša
AU  - Tešić, Živoslav Lj.
AU  - Milojković-Opsenica, Dušanka
PY  - 2014
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/1521
AB  - High-performance thin-layer chromatography (HPTLC) combined with image analysis and pattern recognition methods were used for fingerprinting and classification of 52 propolis samples collected from Serbia and one sample from Croatia. Modern thin-layer chromatography equipment in combination with software for image processing and warping was applied for fingerprinting and data acquisition. The three mostly used chemometric techniques for classification, principal component analysis, cluster analysis and partial least square-discriminant analysis, in combination with simple and fast HPTLC method for fingerprint analysis of propolis, were performed in order to favor and encourage their use in planar chromatography. HPTLC fingerprint analysis of propolis was for the first time performed on amino silica plates. All studied propolis samples have been classified in two major types, orange and blue, supporting the idea of existence of two types of European propolis. Signals at specific R-F values responsible for classification of studied extracts have also been isolated and underlying compounds targeted for further investigation. Copyright (c) 2014 John Wiley & Sons, Ltd. High-performance thin-layer chromatography combined with image analysis and pattern recognition methods were used for fingerprinting and classification of 53 propolis samples. High-performance thin-layer chromatography analysis of propolis was for the first time performed on amino silica plates. All studied propolis samples have been classified in two major types, orange and blue, supporting the idea of existence of two varieties of European propolis. Signals at specific R-F values responsible for classification of studied extracts have also been isolated and underlying compounds targeted for further investigation.
PB  - Wiley-Blackwell, Hoboken
T2  - Journal of Chemometrics
T1  - Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts
VL  - 28
IS  - 4
SP  - 301
EP  - 310
DO  - 10.1002/cem.2592
ER  - 

@article{
author = "Ristivojević, Petar and Andrić, Filip and Trifković, Jelena and Vovk, Irena and Stanisavljević, Ljubiša and Tešić, Živoslav Lj. and Milojković-Opsenica, Dušanka",
year = "2014",
abstract = "High-performance thin-layer chromatography (HPTLC) combined with image analysis and pattern recognition methods were used for fingerprinting and classification of 52 propolis samples collected from Serbia and one sample from Croatia. Modern thin-layer chromatography equipment in combination with software for image processing and warping was applied for fingerprinting and data acquisition. The three mostly used chemometric techniques for classification, principal component analysis, cluster analysis and partial least square-discriminant analysis, in combination with simple and fast HPTLC method for fingerprint analysis of propolis, were performed in order to favor and encourage their use in planar chromatography. HPTLC fingerprint analysis of propolis was for the first time performed on amino silica plates. All studied propolis samples have been classified in two major types, orange and blue, supporting the idea of existence of two types of European propolis. Signals at specific R-F values responsible for classification of studied extracts have also been isolated and underlying compounds targeted for further investigation. Copyright (c) 2014 John Wiley & Sons, Ltd. High-performance thin-layer chromatography combined with image analysis and pattern recognition methods were used for fingerprinting and classification of 53 propolis samples. High-performance thin-layer chromatography analysis of propolis was for the first time performed on amino silica plates. All studied propolis samples have been classified in two major types, orange and blue, supporting the idea of existence of two varieties of European propolis. Signals at specific R-F values responsible for classification of studied extracts have also been isolated and underlying compounds targeted for further investigation.",
publisher = "Wiley-Blackwell, Hoboken",
journal = "Journal of Chemometrics",
title = "Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts",
volume = "28",
number = "4",
pages = "301-310",
doi = "10.1002/cem.2592"
}

Ristivojević, P., Andrić, F., Trifković, J., Vovk, I., Stanisavljević, L., Tešić, Ž. Lj.,& Milojković-Opsenica, D.. (2014). Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts. in Journal of Chemometrics
Wiley-Blackwell, Hoboken., 28(4), 301-310.
https://doi.org/10.1002/cem.2592

Ristivojević P, Andrić F, Trifković J, Vovk I, Stanisavljević L, Tešić ŽL, Milojković-Opsenica D. Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts. in Journal of Chemometrics. 2014;28(4):301-310.
doi:10.1002/cem.2592 .

Ristivojević, Petar, Andrić, Filip, Trifković, Jelena, Vovk, Irena, Stanisavljević, Ljubiša, Tešić, Živoslav Lj., Milojković-Opsenica, Dušanka, "Pattern recognition methods and multivariate image analysis in HPTLC fingerprinting of propolis extracts" in Journal of Chemometrics, 28, no. 4 (2014):301-310,
https://doi.org/10.1002/cem.2592 . .