TY  - JOUR
AU  - Krstić, Đurđa D.
AU  - Ristivojević, Petar
AU  - Gašić, Uroš M.
AU  - Lazović, Mila
AU  - Fotirić-Akšić, Milica M.
AU  - Milivojević, Jasminka
AU  - Morlock, Gertrud E.
AU  - Milojković-Opsenica, Dušanka
AU  - Trifković, Jelena
PY  - 2023
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/5633
AB  - Considering the health-benefits of berry fruits consumption and increased market demands for food authenticity
as one of the most important quality assurances, phenolic profiling by high-performance thin layer chroma-
tography and ultra-high-performance liquid chromatography hyphenated with mass spectrometry was combined
with multivariate analysis for phytochemical characterization and intercultivar discrimination of cultivated
berry seeds. The phenolic profiles of 45 berry seeds from nine genuine Serbian cultivated fruit species (straw-
berry, raspberry, blackberry, black currant, blueberry, gooseberry, cape gooseberry, chokeberry, and goji berry)
revealed a good differentiation according to botanical origin. In order to determine biomarkers responsible for
the classification, a total of 103 phenolic compounds were identified, including 53 phenolic acids and their
derivatives, 26 flavonoids and 24 glycosides. Biomarkers derived from the phenolic profile of berry seeds proved
to be a powerful tool in the authentication of botanical origin, and may be useful in detection of frauds in berry-
based seed-containing product.
PB  - Elsevier
T2  - Food Chemistry
T1  - Authenticity assessment of cultivated berries via phenolic profiles of seeds
VL  - 402
SP  - 134184
DO  - 10.1016/j.foodchem.2022.134184
ER  - 

@article{
author = "Krstić, Đurđa D. and Ristivojević, Petar and Gašić, Uroš M. and Lazović, Mila and Fotirić-Akšić, Milica M. and Milivojević, Jasminka and Morlock, Gertrud E. and Milojković-Opsenica, Dušanka and Trifković, Jelena",
year = "2023",
abstract = "Considering the health-benefits of berry fruits consumption and increased market demands for food authenticity
as one of the most important quality assurances, phenolic profiling by high-performance thin layer chroma-
tography and ultra-high-performance liquid chromatography hyphenated with mass spectrometry was combined
with multivariate analysis for phytochemical characterization and intercultivar discrimination of cultivated
berry seeds. The phenolic profiles of 45 berry seeds from nine genuine Serbian cultivated fruit species (straw-
berry, raspberry, blackberry, black currant, blueberry, gooseberry, cape gooseberry, chokeberry, and goji berry)
revealed a good differentiation according to botanical origin. In order to determine biomarkers responsible for
the classification, a total of 103 phenolic compounds were identified, including 53 phenolic acids and their
derivatives, 26 flavonoids and 24 glycosides. Biomarkers derived from the phenolic profile of berry seeds proved
to be a powerful tool in the authentication of botanical origin, and may be useful in detection of frauds in berry-
based seed-containing product.",
publisher = "Elsevier",
journal = "Food Chemistry",
title = "Authenticity assessment of cultivated berries via phenolic profiles of seeds",
volume = "402",
pages = "134184",
doi = "10.1016/j.foodchem.2022.134184"
}

Krstić, Đ. D., Ristivojević, P., Gašić, U. M., Lazović, M., Fotirić-Akšić, M. M., Milivojević, J., Morlock, G. E., Milojković-Opsenica, D.,& Trifković, J.. (2023). Authenticity assessment of cultivated berries via phenolic profiles of seeds. in Food Chemistry
Elsevier., 402, 134184.
https://doi.org/10.1016/j.foodchem.2022.134184

Krstić ĐD, Ristivojević P, Gašić UM, Lazović M, Fotirić-Akšić MM, Milivojević J, Morlock GE, Milojković-Opsenica D, Trifković J. Authenticity assessment of cultivated berries via phenolic profiles of seeds. in Food Chemistry. 2023;402:134184.
doi:10.1016/j.foodchem.2022.134184 .

Krstić, Đurđa D., Ristivojević, Petar, Gašić, Uroš M., Lazović, Mila, Fotirić-Akšić, Milica M., Milivojević, Jasminka, Morlock, Gertrud E., Milojković-Opsenica, Dušanka, Trifković, Jelena, "Authenticity assessment of cultivated berries via phenolic profiles of seeds" in Food Chemistry, 402 (2023):134184,
https://doi.org/10.1016/j.foodchem.2022.134184 . .

TY  - DATA
AU  - Ristivojević, Petar
AU  - Andrić, Filip
AU  - Vasić, Vesna
AU  - Milojković-Opsenica, Dušanka
AU  - Morlock, Gertrud E.
PY  - 2022
UR  - http://cherry.chem.bg.ac.rs/handle/123456789/5001
PB  - Elsevier
T2  - Food Chemistry
T1  - Supplementary data for the article: Ristivojević, P.; Andrić, F.; Vasić, V.; Milojković Opsenica, D.; Morlock, G. Fast Detection of Apricot Product Frauds by Added Pumpkin via Planar Chromatography and Chemometrics: Greenness Assessment by Analytical Eco-Scale. Food Chemistry 2022, 374 (131714). https://doi.org/10.1016/j.foodchem.2021.131714.
UR  - https://hdl.handle.net/21.15107/rcub_cherry_5001
ER  - 

@misc{
author = "Ristivojević, Petar and Andrić, Filip and Vasić, Vesna and Milojković-Opsenica, Dušanka and Morlock, Gertrud E.",
year = "2022",
publisher = "Elsevier",
journal = "Food Chemistry",
title = "Supplementary data for the article: Ristivojević, P.; Andrić, F.; Vasić, V.; Milojković Opsenica, D.; Morlock, G. Fast Detection of Apricot Product Frauds by Added Pumpkin via Planar Chromatography and Chemometrics: Greenness Assessment by Analytical Eco-Scale. Food Chemistry 2022, 374 (131714). https://doi.org/10.1016/j.foodchem.2021.131714.",
url = "https://hdl.handle.net/21.15107/rcub_cherry_5001"
}

Ristivojević, P., Andrić, F., Vasić, V., Milojković-Opsenica, D.,& Morlock, G. E.. (2022). Supplementary data for the article: Ristivojević, P.; Andrić, F.; Vasić, V.; Milojković Opsenica, D.; Morlock, G. Fast Detection of Apricot Product Frauds by Added Pumpkin via Planar Chromatography and Chemometrics: Greenness Assessment by Analytical Eco-Scale. Food Chemistry 2022, 374 (131714). https://doi.org/10.1016/j.foodchem.2021.131714.. in Food Chemistry
Elsevier..
https://hdl.handle.net/21.15107/rcub_cherry_5001

Ristivojević P, Andrić F, Vasić V, Milojković-Opsenica D, Morlock GE. Supplementary data for the article: Ristivojević, P.; Andrić, F.; Vasić, V.; Milojković Opsenica, D.; Morlock, G. Fast Detection of Apricot Product Frauds by Added Pumpkin via Planar Chromatography and Chemometrics: Greenness Assessment by Analytical Eco-Scale. Food Chemistry 2022, 374 (131714). https://doi.org/10.1016/j.foodchem.2021.131714.. in Food Chemistry. 2022;.
https://hdl.handle.net/21.15107/rcub_cherry_5001 .

Ristivojević, Petar, Andrić, Filip, Vasić, Vesna, Milojković-Opsenica, Dušanka, Morlock, Gertrud E., "Supplementary data for the article: Ristivojević, P.; Andrić, F.; Vasić, V.; Milojković Opsenica, D.; Morlock, G. Fast Detection of Apricot Product Frauds by Added Pumpkin via Planar Chromatography and Chemometrics: Greenness Assessment by Analytical Eco-Scale. Food Chemistry 2022, 374 (131714). https://doi.org/10.1016/j.foodchem.2021.131714." in Food Chemistry (2022),
https://hdl.handle.net/21.15107/rcub_cherry_5001 .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Andrić, Filip
AU  - Vasić, Vesna
AU  - Milojković-Opsenica, Dušanka
AU  - Morlock, Gertrud E.
PY  - 2022
UR  - http://cherry.chem.bg.ac.rs/handle/123456789/5000
AB  - The European Commission requires that fruit products distributed on the market meet standards of high quality and authenticity. For the quality assessment of apricot products susceptible to food fraud, an environmentally friendly, simple and cost-effective analytical profiling was developed by high-performance thin-layer chromatography multi-imaging (HPTLC-FLD/Vis). The new phytochemical profiling was applied for analysis of authentic samples (7 apricot and 5 pumpkin samples) and simulated adulterated products (11 mixture samples prepared by addition of 2.5–53% pooled pumpkin to pooled apricot). Based on the analytical eco-scale assessment, the HPTLC-FLD/Vis method was proven as an excellent green analytical method with low energy and solvent consumption. Chemometric data analysis confirmed the difference between apricot and apricot-pumpkin mixtures based on the phytochemical profile. Chemical markers responsible for their differentiation were identified. The results indicated that frauds by adding pumpkin to apricot products can be detected at added contents as low as 2.5%.
PB  - Elsevier
T2  - Food Chemistry
T1  - Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale
VL  - 374
IS  - 131714
DO  - 10.1016/j.foodchem.2021.131714
ER  - 

@article{
author = "Ristivojević, Petar and Andrić, Filip and Vasić, Vesna and Milojković-Opsenica, Dušanka and Morlock, Gertrud E.",
year = "2022",
abstract = "The European Commission requires that fruit products distributed on the market meet standards of high quality and authenticity. For the quality assessment of apricot products susceptible to food fraud, an environmentally friendly, simple and cost-effective analytical profiling was developed by high-performance thin-layer chromatography multi-imaging (HPTLC-FLD/Vis). The new phytochemical profiling was applied for analysis of authentic samples (7 apricot and 5 pumpkin samples) and simulated adulterated products (11 mixture samples prepared by addition of 2.5–53% pooled pumpkin to pooled apricot). Based on the analytical eco-scale assessment, the HPTLC-FLD/Vis method was proven as an excellent green analytical method with low energy and solvent consumption. Chemometric data analysis confirmed the difference between apricot and apricot-pumpkin mixtures based on the phytochemical profile. Chemical markers responsible for their differentiation were identified. The results indicated that frauds by adding pumpkin to apricot products can be detected at added contents as low as 2.5%.",
publisher = "Elsevier",
journal = "Food Chemistry",
title = "Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale",
volume = "374",
number = "131714",
doi = "10.1016/j.foodchem.2021.131714"
}

Ristivojević, P., Andrić, F., Vasić, V., Milojković-Opsenica, D.,& Morlock, G. E.. (2022). Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale. in Food Chemistry
Elsevier., 374(131714).
https://doi.org/10.1016/j.foodchem.2021.131714

Ristivojević P, Andrić F, Vasić V, Milojković-Opsenica D, Morlock GE. Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale. in Food Chemistry. 2022;374(131714).
doi:10.1016/j.foodchem.2021.131714 .

Ristivojević, Petar, Andrić, Filip, Vasić, Vesna, Milojković-Opsenica, Dušanka, Morlock, Gertrud E., "Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale" in Food Chemistry, 374, no. 131714 (2022),
https://doi.org/10.1016/j.foodchem.2021.131714 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2019
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3939
AB  - The quality of three types of beer (dark, light and non-alcoholic) was assessed using high-performance thin-layer chromatography (HPTLC) combined with high-resolution mass spectrometry and chemometrics. An HPTLC separation of the polar beer components in the ethyl acetate extract was developed. The polar components were detec ted either by the in situ 2, 2 -d iphenyl -1-picrylhydrazyl (DPPH*) assay or by derivatization with the Neu’s reagent, followed by the PEG solution. This directly allowed the visual comparison and evaluation of the phenolic/flavonoid or radical scavenging (antioxidative) beer profile. Although the three types of beer showed a very similar chemical HPTLC pattern, the signal intensities were different. Detected by the Neu’s reagent, the dark beer extracts contained a high amount of phenolic compounds, and the light beer extracts showed a moderate content, while the non-alcoholic beer extracts had the lowest phenolic content. The HPTLC—DPPH* assay confirmed the higher radical scavenging activity of dark beer extracts, if compared to light and non-alcoholic beer extracts. The most active bands with regard to the radical scavenging property were identified to be desdimethyl-octahydro-iso-cohumulone and iso-n/ad-humulone. The use of pattern recognition techniques showed a clear differentiation between dark and non-alcoholic beer extracts, while light beer extracts did overlap with both beer types. This HPTLC screening allowed the (1) direct comparison of beer samples/types via classification and pattern recognition, (2) the assessment of the beer quality with regard to its antioxidative potential, and (3) the reference to single components.
PB  - Akadémiai Kiadó
T2  - JPC - Journal of Planar Chromatography - Modern TLC
T1  - Phenolic fingerprints and quality assessment of three types of beer
VL  - 32
SP  - 191
EP  - 196
DO  - 10.1556/1006.2019.32.3.3
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2019",
abstract = "The quality of three types of beer (dark, light and non-alcoholic) was assessed using high-performance thin-layer chromatography (HPTLC) combined with high-resolution mass spectrometry and chemometrics. An HPTLC separation of the polar beer components in the ethyl acetate extract was developed. The polar components were detec ted either by the in situ 2, 2 -d iphenyl -1-picrylhydrazyl (DPPH*) assay or by derivatization with the Neu’s reagent, followed by the PEG solution. This directly allowed the visual comparison and evaluation of the phenolic/flavonoid or radical scavenging (antioxidative) beer profile. Although the three types of beer showed a very similar chemical HPTLC pattern, the signal intensities were different. Detected by the Neu’s reagent, the dark beer extracts contained a high amount of phenolic compounds, and the light beer extracts showed a moderate content, while the non-alcoholic beer extracts had the lowest phenolic content. The HPTLC—DPPH* assay confirmed the higher radical scavenging activity of dark beer extracts, if compared to light and non-alcoholic beer extracts. The most active bands with regard to the radical scavenging property were identified to be desdimethyl-octahydro-iso-cohumulone and iso-n/ad-humulone. The use of pattern recognition techniques showed a clear differentiation between dark and non-alcoholic beer extracts, while light beer extracts did overlap with both beer types. This HPTLC screening allowed the (1) direct comparison of beer samples/types via classification and pattern recognition, (2) the assessment of the beer quality with regard to its antioxidative potential, and (3) the reference to single components.",
publisher = "Akadémiai Kiadó",
journal = "JPC - Journal of Planar Chromatography - Modern TLC",
title = "Phenolic fingerprints and quality assessment of three types of beer",
volume = "32",
pages = "191-196",
doi = "10.1556/1006.2019.32.3.3"
}

Ristivojević, P.,& Morlock, G. E.. (2019). Phenolic fingerprints and quality assessment of three types of beer. in JPC - Journal of Planar Chromatography - Modern TLC
Akadémiai Kiadó., 32, 191-196.
https://doi.org/10.1556/1006.2019.32.3.3

Ristivojević P, Morlock GE. Phenolic fingerprints and quality assessment of three types of beer. in JPC - Journal of Planar Chromatography - Modern TLC. 2019;32:191-196.
doi:10.1556/1006.2019.32.3.3 .

Ristivojević, Petar, Morlock, Gertrud E., "Phenolic fingerprints and quality assessment of three types of beer" in JPC - Journal of Planar Chromatography - Modern TLC, 32 (2019):191-196,
https://doi.org/10.1556/1006.2019.32.3.3 . .

TY  - JOUR
AU  - Jamshidi-Aidji, Maryam
AU  - Dimkić, Ivica
AU  - Ristivojević, Petar
AU  - Stanković, Slaviša
AU  - Morlock, Gertrud E.
PY  - 2019
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3941
AB  - Bacillus species produce a wide array of biologically active metabolites, including nonribosomaly synthesized lipopeptides (LPs). The high-performance thin-layer chromatography (HPTLC) technique hyphenated with different bioassays and mass spectrometry was demonstrated as a valuable tool for effect-directed analysis of iturins, surfactins, fengycins and kurstakins homologues from complex mixtures of LPs. As proof of this straightforward strategy, the found surfactin and iturin A homologues were characterized and compared with reference substances. This study considered two different extraction methods for LPs produced by five Bacillus strains. The ethyl acetate extraction (Ex-1), and the acidic precipitation followed by methanol extraction (Ex-2) were investigated. Diverse enzyme inhibitions and antimicrobial potentials of LPs were analyzed, and in parallel, high-resolution mass spectra (HRMS) were online recorded from the HPTLC zones of interest. No antimicrobial effect against Gram-positive B. subtilis was evident for iturin, whereas a response was detected for surfactin. The nonpolar kurstakin compounds showed a pronounced B. subtilis antimicrobial activity in Ex-1 of almost all strains, whereas the fengycin homologues were detected in Ex-2 of SS-10.7 and SS-27.2. Iturin had also no activity against Gram-negative Aliivibrio fischeri, while again surfactin showed an enhancing luminescent activity. Contrary, kurstakin compounds caused a decrease in the luminescence in Ex-1 of all strains, particularly for SS-13.1. Both, iturin and surfactin showed a strong acetylcholinesterase (AChE) and α-glucosidase inhibition, but surfactin caused a much stronger inhibition. This was evident in all bacterial strains, except for SS-13.1 in Ex-1 and for SS-38.4 in Ex-2. Although, iturin and surfactin exhibited no DPPH˙ scavenging activity, Ex-1 of all strains contained more intense DPPH˙ scavenging compounds compared to Ex-2, and surfactin methyl esters showed a pronounced DPPH˙ activity, particularly in SS-12.6 in Ex-1. This study pointed to active metabolites of strains that can be used as therapeutics and biocontrol agents with beneficial effects on human health. The straightforward HPTLC profiling served as an excellent bioanalytical tool to control the formed bioactive metabolites. As the fermentation process is very sensitive to external influences, it could be a helpful control tool for standardization of the biotechnological processing.
PB  - Elsevier
T2  - Journal of Chromatography A
T1  - Effect-directed screening of Bacillus lipopeptide extracts via hyphenated high-performance thin-layer chromatography
VL  - 1605
SP  - 460366
DO  - 10.1016/j.chroma.2019.460366
ER  - 

@article{
author = "Jamshidi-Aidji, Maryam and Dimkić, Ivica and Ristivojević, Petar and Stanković, Slaviša and Morlock, Gertrud E.",
year = "2019",
abstract = "Bacillus species produce a wide array of biologically active metabolites, including nonribosomaly synthesized lipopeptides (LPs). The high-performance thin-layer chromatography (HPTLC) technique hyphenated with different bioassays and mass spectrometry was demonstrated as a valuable tool for effect-directed analysis of iturins, surfactins, fengycins and kurstakins homologues from complex mixtures of LPs. As proof of this straightforward strategy, the found surfactin and iturin A homologues were characterized and compared with reference substances. This study considered two different extraction methods for LPs produced by five Bacillus strains. The ethyl acetate extraction (Ex-1), and the acidic precipitation followed by methanol extraction (Ex-2) were investigated. Diverse enzyme inhibitions and antimicrobial potentials of LPs were analyzed, and in parallel, high-resolution mass spectra (HRMS) were online recorded from the HPTLC zones of interest. No antimicrobial effect against Gram-positive B. subtilis was evident for iturin, whereas a response was detected for surfactin. The nonpolar kurstakin compounds showed a pronounced B. subtilis antimicrobial activity in Ex-1 of almost all strains, whereas the fengycin homologues were detected in Ex-2 of SS-10.7 and SS-27.2. Iturin had also no activity against Gram-negative Aliivibrio fischeri, while again surfactin showed an enhancing luminescent activity. Contrary, kurstakin compounds caused a decrease in the luminescence in Ex-1 of all strains, particularly for SS-13.1. Both, iturin and surfactin showed a strong acetylcholinesterase (AChE) and α-glucosidase inhibition, but surfactin caused a much stronger inhibition. This was evident in all bacterial strains, except for SS-13.1 in Ex-1 and for SS-38.4 in Ex-2. Although, iturin and surfactin exhibited no DPPH˙ scavenging activity, Ex-1 of all strains contained more intense DPPH˙ scavenging compounds compared to Ex-2, and surfactin methyl esters showed a pronounced DPPH˙ activity, particularly in SS-12.6 in Ex-1. This study pointed to active metabolites of strains that can be used as therapeutics and biocontrol agents with beneficial effects on human health. The straightforward HPTLC profiling served as an excellent bioanalytical tool to control the formed bioactive metabolites. As the fermentation process is very sensitive to external influences, it could be a helpful control tool for standardization of the biotechnological processing.",
publisher = "Elsevier",
journal = "Journal of Chromatography A",
title = "Effect-directed screening of Bacillus lipopeptide extracts via hyphenated high-performance thin-layer chromatography",
volume = "1605",
pages = "460366",
doi = "10.1016/j.chroma.2019.460366"
}

Jamshidi-Aidji, M., Dimkić, I., Ristivojević, P., Stanković, S.,& Morlock, G. E.. (2019). Effect-directed screening of Bacillus lipopeptide extracts via hyphenated high-performance thin-layer chromatography. in Journal of Chromatography A
Elsevier., 1605, 460366.
https://doi.org/10.1016/j.chroma.2019.460366

Jamshidi-Aidji M, Dimkić I, Ristivojević P, Stanković S, Morlock GE. Effect-directed screening of Bacillus lipopeptide extracts via hyphenated high-performance thin-layer chromatography. in Journal of Chromatography A. 2019;1605:460366.
doi:10.1016/j.chroma.2019.460366 .

Jamshidi-Aidji, Maryam, Dimkić, Ivica, Ristivojević, Petar, Stanković, Slaviša, Morlock, Gertrud E., "Effect-directed screening of Bacillus lipopeptide extracts via hyphenated high-performance thin-layer chromatography" in Journal of Chromatography A, 1605 (2019):460366,
https://doi.org/10.1016/j.chroma.2019.460366 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2018
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/331
AB  - Biological and biochemical fingerprints were investigated for the first time for the feasibility of effect-directed classification, and thus, to allow the choice of a distinct beer with regard to beneficial health effects. A high-performance thin-layer chromatography method was newly developed and combined with in situ effect-directed analysis for profiling 50 German beers for multipotent active compounds, and thus, their health-related potential. Discovered multipotent active zones were online eluted and characterized by high resolution mass spectrometry. For example, isoxanthohumol, iso-α-ad/n-humulone or its isomers, desdimethyl-octahydro-isocohumulone and ad/n-humulone were proven as antimicrobial compounds, isoxanthohumol as an acetylcholinesterase inhibitor, and isoxanthohumol and iso-α-ad/n-humulone or its isomers as radical scavengers. Investigating multivariate data analysis of effect-directed fingerprints for the first time, the pattern recognition and classification results showed the power of clustering non-alcoholic beers from other types of beer, or it showed the differentiation of dark and non-alcoholic beers. © 2018 Elsevier Ltd
T2  - Food Chemistry
T1  - Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers
VL  - 260
SP  - 344
EP  - 353
DO  - 10.1016/j.foodchem.2018.03.127
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2018",
abstract = "Biological and biochemical fingerprints were investigated for the first time for the feasibility of effect-directed classification, and thus, to allow the choice of a distinct beer with regard to beneficial health effects. A high-performance thin-layer chromatography method was newly developed and combined with in situ effect-directed analysis for profiling 50 German beers for multipotent active compounds, and thus, their health-related potential. Discovered multipotent active zones were online eluted and characterized by high resolution mass spectrometry. For example, isoxanthohumol, iso-α-ad/n-humulone or its isomers, desdimethyl-octahydro-isocohumulone and ad/n-humulone were proven as antimicrobial compounds, isoxanthohumol as an acetylcholinesterase inhibitor, and isoxanthohumol and iso-α-ad/n-humulone or its isomers as radical scavengers. Investigating multivariate data analysis of effect-directed fingerprints for the first time, the pattern recognition and classification results showed the power of clustering non-alcoholic beers from other types of beer, or it showed the differentiation of dark and non-alcoholic beers. © 2018 Elsevier Ltd",
journal = "Food Chemistry",
title = "Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers",
volume = "260",
pages = "344-353",
doi = "10.1016/j.foodchem.2018.03.127"
}

Ristivojević, P.,& Morlock, G. E.. (2018). Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers. in Food Chemistry, 260, 344-353.
https://doi.org/10.1016/j.foodchem.2018.03.127

Ristivojević P, Morlock GE. Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers. in Food Chemistry. 2018;260:344-353.
doi:10.1016/j.foodchem.2018.03.127 .

Ristivojević, Petar, Morlock, Gertrud E., "Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers" in Food Chemistry, 260 (2018):344-353,
https://doi.org/10.1016/j.foodchem.2018.03.127 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2018
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2914
AB  - Biological and biochemical fingerprints were investigated for the first time for the feasibility of effect-directed classification, and thus, to allow the choice of a distinct beer with regard to beneficial health effects. A high-performance thin-layer chromatography method was newly developed and combined with in situ effect-directed analysis for profiling 50 German beers for multipotent active compounds, and thus, their health-related potential. Discovered multipotent active zones were online eluted and characterized by high resolution mass spectrometry. For example, isoxanthohumol, iso-α-ad/n-humulone or its isomers, desdimethyl-octahydro-isocohumulone and ad/n-humulone were proven as antimicrobial compounds, isoxanthohumol as an acetylcholinesterase inhibitor, and isoxanthohumol and iso-α-ad/n-humulone or its isomers as radical scavengers. Investigating multivariate data analysis of effect-directed fingerprints for the first time, the pattern recognition and classification results showed the power of clustering non-alcoholic beers from other types of beer, or it showed the differentiation of dark and non-alcoholic beers. © 2018 Elsevier Ltd
T2  - Food Chemistry
T1  - Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers
VL  - 260
SP  - 344
EP  - 353
DO  - 10.1016/j.foodchem.2018.03.127
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2018",
abstract = "Biological and biochemical fingerprints were investigated for the first time for the feasibility of effect-directed classification, and thus, to allow the choice of a distinct beer with regard to beneficial health effects. A high-performance thin-layer chromatography method was newly developed and combined with in situ effect-directed analysis for profiling 50 German beers for multipotent active compounds, and thus, their health-related potential. Discovered multipotent active zones were online eluted and characterized by high resolution mass spectrometry. For example, isoxanthohumol, iso-α-ad/n-humulone or its isomers, desdimethyl-octahydro-isocohumulone and ad/n-humulone were proven as antimicrobial compounds, isoxanthohumol as an acetylcholinesterase inhibitor, and isoxanthohumol and iso-α-ad/n-humulone or its isomers as radical scavengers. Investigating multivariate data analysis of effect-directed fingerprints for the first time, the pattern recognition and classification results showed the power of clustering non-alcoholic beers from other types of beer, or it showed the differentiation of dark and non-alcoholic beers. © 2018 Elsevier Ltd",
journal = "Food Chemistry",
title = "Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers",
volume = "260",
pages = "344-353",
doi = "10.1016/j.foodchem.2018.03.127"
}

Ristivojević, P.,& Morlock, G. E.. (2018). Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers. in Food Chemistry, 260, 344-353.
https://doi.org/10.1016/j.foodchem.2018.03.127

Ristivojević P, Morlock GE. Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers. in Food Chemistry. 2018;260:344-353.
doi:10.1016/j.foodchem.2018.03.127 .

Ristivojević, Petar, Morlock, Gertrud E., "Effect-directed classification of biological, biochemical and chemical profiles of 50 German beers" in Food Chemistry, 260 (2018):344-353,
https://doi.org/10.1016/j.foodchem.2018.03.127 . .

TY  - DATA
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2018
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2915
T2  - Food Chemistry
T1  - Supplementary data for the article: Ristivojević, P. M.; Morlock, G. E. Effect-Directed Classification of Biological, Biochemical and Chemical Profiles of 50 German Beers. Food Chemistry 2018, 260, 344–353. https://doi.org/10.1016/j.foodchem.2018.03.127
UR  - https://hdl.handle.net/21.15107/rcub_cherry_2915
ER  - 

@misc{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2018",
journal = "Food Chemistry",
title = "Supplementary data for the article: Ristivojević, P. M.; Morlock, G. E. Effect-Directed Classification of Biological, Biochemical and Chemical Profiles of 50 German Beers. Food Chemistry 2018, 260, 344–353. https://doi.org/10.1016/j.foodchem.2018.03.127",
url = "https://hdl.handle.net/21.15107/rcub_cherry_2915"
}

Ristivojević, P.,& Morlock, G. E.. (2018). Supplementary data for the article: Ristivojević, P. M.; Morlock, G. E. Effect-Directed Classification of Biological, Biochemical and Chemical Profiles of 50 German Beers. Food Chemistry 2018, 260, 344–353. https://doi.org/10.1016/j.foodchem.2018.03.127. in Food Chemistry.
https://hdl.handle.net/21.15107/rcub_cherry_2915

Ristivojević P, Morlock GE. Supplementary data for the article: Ristivojević, P. M.; Morlock, G. E. Effect-Directed Classification of Biological, Biochemical and Chemical Profiles of 50 German Beers. Food Chemistry 2018, 260, 344–353. https://doi.org/10.1016/j.foodchem.2018.03.127. in Food Chemistry. 2018;.
https://hdl.handle.net/21.15107/rcub_cherry_2915 .

Ristivojević, Petar, Morlock, Gertrud E., "Supplementary data for the article: Ristivojević, P. M.; Morlock, G. E. Effect-Directed Classification of Biological, Biochemical and Chemical Profiles of 50 German Beers. Food Chemistry 2018, 260, 344–353. https://doi.org/10.1016/j.foodchem.2018.03.127" in Food Chemistry (2018),
https://hdl.handle.net/21.15107/rcub_cherry_2915 .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2017
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2371
AB  - A simple, rapid, and accurate high-performance thin-layer chromatography (HPTLC) method was applied in combination with powerful pattern recognition techniques for differentiating thickening agents, which are mainly based on polysaccharides or biopolymers. After methanolysis, the monomeric units of the thickeners were separated by HPTLC and detected using derivatization with the aniline diphenylamine o-phosphoric acid reagent. According to their resulting fingerprint and chemical pattern, the thickening agents studied have been classified by principal component analysis and by hierarchic cluster analysis in several groups. This newly combined approach using HPTLC fingerprints and pattern recognition techniques differentiated high similarity thickeners. Monomeric units responsible for the classification of the investigated thickener have been identified. The results showed that the HPTLC technique in combination with chemometrics can be a very reliable technique for authentication of high similarity thickening agents and can be used for a quick screening of additives in foodstuffs.
PB  - Elsevier Sci Ltd, Oxford
T2  - Food Hydrocolloids
T1  - High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents
VL  - 64
SP  - 78
EP  - 84
DO  - 10.1016/j.foodhyd.2016.10.005
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2017",
abstract = "A simple, rapid, and accurate high-performance thin-layer chromatography (HPTLC) method was applied in combination with powerful pattern recognition techniques for differentiating thickening agents, which are mainly based on polysaccharides or biopolymers. After methanolysis, the monomeric units of the thickeners were separated by HPTLC and detected using derivatization with the aniline diphenylamine o-phosphoric acid reagent. According to their resulting fingerprint and chemical pattern, the thickening agents studied have been classified by principal component analysis and by hierarchic cluster analysis in several groups. This newly combined approach using HPTLC fingerprints and pattern recognition techniques differentiated high similarity thickeners. Monomeric units responsible for the classification of the investigated thickener have been identified. The results showed that the HPTLC technique in combination with chemometrics can be a very reliable technique for authentication of high similarity thickening agents and can be used for a quick screening of additives in foodstuffs.",
publisher = "Elsevier Sci Ltd, Oxford",
journal = "Food Hydrocolloids",
title = "High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents",
volume = "64",
pages = "78-84",
doi = "10.1016/j.foodhyd.2016.10.005"
}

Ristivojević, P.,& Morlock, G. E.. (2017). High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents. in Food Hydrocolloids
Elsevier Sci Ltd, Oxford., 64, 78-84.
https://doi.org/10.1016/j.foodhyd.2016.10.005

Ristivojević P, Morlock GE. High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents. in Food Hydrocolloids. 2017;64:78-84.
doi:10.1016/j.foodhyd.2016.10.005 .

Ristivojević, Petar, Morlock, Gertrud E., "High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents" in Food Hydrocolloids, 64 (2017):78-84,
https://doi.org/10.1016/j.foodhyd.2016.10.005 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2017
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3217
AB  - A simple, rapid, and accurate high-performance thin-layer chromatography (HPTLC) method was applied in combination with powerful pattern recognition techniques for differentiating thickening agents, which are mainly based on polysaccharides or biopolymers. After methanolysis, the monomeric units of the thickeners were separated by HPTLC and detected using derivatization with the aniline diphenylamine o-phosphoric acid reagent. According to their resulting fingerprint and chemical pattern, the thickening agents studied have been classified by principal component analysis and by hierarchic cluster analysis in several groups. This newly combined approach using HPTLC fingerprints and pattern recognition techniques differentiated high similarity thickeners. Monomeric units responsible for the classification of the investigated thickener have been identified. The results showed that the HPTLC technique in combination with chemometrics can be a very reliable technique for authentication of high similarity thickening agents and can be used for a quick screening of additives in foodstuffs.
PB  - Elsevier Sci Ltd, Oxford
T2  - Food Hydrocolloids
T1  - High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents
VL  - 64
SP  - 78
EP  - 84
DO  - 10.1016/j.foodhyd.2016.10.005
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2017",
abstract = "A simple, rapid, and accurate high-performance thin-layer chromatography (HPTLC) method was applied in combination with powerful pattern recognition techniques for differentiating thickening agents, which are mainly based on polysaccharides or biopolymers. After methanolysis, the monomeric units of the thickeners were separated by HPTLC and detected using derivatization with the aniline diphenylamine o-phosphoric acid reagent. According to their resulting fingerprint and chemical pattern, the thickening agents studied have been classified by principal component analysis and by hierarchic cluster analysis in several groups. This newly combined approach using HPTLC fingerprints and pattern recognition techniques differentiated high similarity thickeners. Monomeric units responsible for the classification of the investigated thickener have been identified. The results showed that the HPTLC technique in combination with chemometrics can be a very reliable technique for authentication of high similarity thickening agents and can be used for a quick screening of additives in foodstuffs.",
publisher = "Elsevier Sci Ltd, Oxford",
journal = "Food Hydrocolloids",
title = "High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents",
volume = "64",
pages = "78-84",
doi = "10.1016/j.foodhyd.2016.10.005"
}

Ristivojević, P.,& Morlock, G. E.. (2017). High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents. in Food Hydrocolloids
Elsevier Sci Ltd, Oxford., 64, 78-84.
https://doi.org/10.1016/j.foodhyd.2016.10.005

Ristivojević P, Morlock GE. High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents. in Food Hydrocolloids. 2017;64:78-84.
doi:10.1016/j.foodhyd.2016.10.005 .

Ristivojević, Petar, Morlock, Gertrud E., "High-performance thin-layer chromatography combined with pattern recognition techniques as tool to distinguish thickening agents" in Food Hydrocolloids, 64 (2017):78-84,
https://doi.org/10.1016/j.foodhyd.2016.10.005 . .

TY  - DATA
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2017
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3218
PB  - Elsevier Sci Ltd, Oxford
T2  - Food Hydrocolloids
T1  - Supplementary material for the article: Ristivojević, P.; Morlock, G. E. High-Performance Thin-Layer Chromatography Combined with Pattern Recognition Techniques as Tool to Distinguish Thickening Agents. Food Hydrocolloids 2017, 64, 78–84. https://doi.org/10.1016/j.foodhyd.2016.10.005
UR  - https://hdl.handle.net/21.15107/rcub_cherry_3218
ER  - 

@misc{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2017",
publisher = "Elsevier Sci Ltd, Oxford",
journal = "Food Hydrocolloids",
title = "Supplementary material for the article: Ristivojević, P.; Morlock, G. E. High-Performance Thin-Layer Chromatography Combined with Pattern Recognition Techniques as Tool to Distinguish Thickening Agents. Food Hydrocolloids 2017, 64, 78–84. https://doi.org/10.1016/j.foodhyd.2016.10.005",
url = "https://hdl.handle.net/21.15107/rcub_cherry_3218"
}

Ristivojević, P.,& Morlock, G. E.. (2017). Supplementary material for the article: Ristivojević, P.; Morlock, G. E. High-Performance Thin-Layer Chromatography Combined with Pattern Recognition Techniques as Tool to Distinguish Thickening Agents. Food Hydrocolloids 2017, 64, 78–84. https://doi.org/10.1016/j.foodhyd.2016.10.005. in Food Hydrocolloids
Elsevier Sci Ltd, Oxford..
https://hdl.handle.net/21.15107/rcub_cherry_3218

Ristivojević P, Morlock GE. Supplementary material for the article: Ristivojević, P.; Morlock, G. E. High-Performance Thin-Layer Chromatography Combined with Pattern Recognition Techniques as Tool to Distinguish Thickening Agents. Food Hydrocolloids 2017, 64, 78–84. https://doi.org/10.1016/j.foodhyd.2016.10.005. in Food Hydrocolloids. 2017;.
https://hdl.handle.net/21.15107/rcub_cherry_3218 .

Ristivojević, Petar, Morlock, Gertrud E., "Supplementary material for the article: Ristivojević, P.; Morlock, G. E. High-Performance Thin-Layer Chromatography Combined with Pattern Recognition Techniques as Tool to Distinguish Thickening Agents. Food Hydrocolloids 2017, 64, 78–84. https://doi.org/10.1016/j.foodhyd.2016.10.005" in Food Hydrocolloids (2017),
https://hdl.handle.net/21.15107/rcub_cherry_3218 .

TY  - JOUR
AU  - Fichou, Dimitri
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3601
AB  - High-performance thin-layer chromatography (HPTLC) is an advantageous analytical technique for analysis of complex samples. Combined with multivariate data analysis, it turns out to be a powerful tool for profiling of many samples in parallel. So far, chromatogram analysis has been time-consuming and required the application of at least two software packages to convert HPTLC chromatograms into a numerical data matrix. Hence, this study aimed to develop a powerful, all in one open-source software for user-friendly image processing and multivariate analysis of HPTLC chromatograms. Using the caret package for machine learning, the software was set up in the R programming language with an HTML−user interface created by the shiny package. The newly developed software, called rTLC, is deployed online, and instructions for direct use as a web application and for local installation, if required, are available on GitHub. rTLC was created especially for routine use in planar chromatography. It provides the necessary tools to guide the user in a fast protocol to the statistical data output (e.g., data extraction, preprocessing techniques, variable selection, and data analysis). rTLC offers a standardized procedure and informative visualization tools that allow the user to explore the data in a reproducible and comprehensive way. As proof-of-principle of rTLC, German propolis samples were analyzed using pattern recognition techniques, principal component analysis, hierarchic cluster analysis, and predictive techniques, such as random forest and support vector machines. © 2016 American Chemical Society.
T2  - Analytical Chemistry
T1  - Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms
VL  - 88
IS  - 24
SP  - 12494
EP  - 12501
DO  - 10.1021/acs.analchem.6b04017
ER  - 

@article{
author = "Fichou, Dimitri and Ristivojević, Petar and Morlock, Gertrud E.",
year = "2016",
abstract = "High-performance thin-layer chromatography (HPTLC) is an advantageous analytical technique for analysis of complex samples. Combined with multivariate data analysis, it turns out to be a powerful tool for profiling of many samples in parallel. So far, chromatogram analysis has been time-consuming and required the application of at least two software packages to convert HPTLC chromatograms into a numerical data matrix. Hence, this study aimed to develop a powerful, all in one open-source software for user-friendly image processing and multivariate analysis of HPTLC chromatograms. Using the caret package for machine learning, the software was set up in the R programming language with an HTML−user interface created by the shiny package. The newly developed software, called rTLC, is deployed online, and instructions for direct use as a web application and for local installation, if required, are available on GitHub. rTLC was created especially for routine use in planar chromatography. It provides the necessary tools to guide the user in a fast protocol to the statistical data output (e.g., data extraction, preprocessing techniques, variable selection, and data analysis). rTLC offers a standardized procedure and informative visualization tools that allow the user to explore the data in a reproducible and comprehensive way. As proof-of-principle of rTLC, German propolis samples were analyzed using pattern recognition techniques, principal component analysis, hierarchic cluster analysis, and predictive techniques, such as random forest and support vector machines. © 2016 American Chemical Society.",
journal = "Analytical Chemistry",
title = "Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms",
volume = "88",
number = "24",
pages = "12494-12501",
doi = "10.1021/acs.analchem.6b04017"
}

Fichou, D., Ristivojević, P.,& Morlock, G. E.. (2016). Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms. in Analytical Chemistry, 88(24), 12494-12501.
https://doi.org/10.1021/acs.analchem.6b04017

Fichou D, Ristivojević P, Morlock GE. Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms. in Analytical Chemistry. 2016;88(24):12494-12501.
doi:10.1021/acs.analchem.6b04017 .

Fichou, Dimitri, Ristivojević, Petar, Morlock, Gertrud E., "Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms" in Analytical Chemistry, 88, no. 24 (2016):12494-12501,
https://doi.org/10.1021/acs.analchem.6b04017 . .

TY  - JOUR
AU  - Fichou, Dimitri
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/306
AB  - High-performance thin-layer chromatography (HPTLC) is an advantageous analytical technique for analysis of complex samples. Combined with multivariate data analysis, it turns out to be a powerful tool for profiling of many samples in parallel. So far, chromatogram analysis has been time-consuming and required the application of at least two software packages to convert HPTLC chromatograms into a numerical data matrix. Hence, this study aimed to develop a powerful, all in one open-source software for user-friendly image processing and multivariate analysis of HPTLC chromatograms. Using the caret package for machine learning, the software was set up in the R programming language with an HTML−user interface created by the shiny package. The newly developed software, called rTLC, is deployed online, and instructions for direct use as a web application and for local installation, if required, are available on GitHub. rTLC was created especially for routine use in planar chromatography. It provides the necessary tools to guide the user in a fast protocol to the statistical data output (e.g., data extraction, preprocessing techniques, variable selection, and data analysis). rTLC offers a standardized procedure and informative visualization tools that allow the user to explore the data in a reproducible and comprehensive way. As proof-of-principle of rTLC, German propolis samples were analyzed using pattern recognition techniques, principal component analysis, hierarchic cluster analysis, and predictive techniques, such as random forest and support vector machines. © 2016 American Chemical Society.
T2  - Analytical Chemistry
T1  - Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms
VL  - 88
IS  - 24
SP  - 12494
EP  - 12501
DO  - 10.1021/acs.analchem.6b04017
ER  - 

@article{
author = "Fichou, Dimitri and Ristivojević, Petar and Morlock, Gertrud E.",
year = "2016",
abstract = "High-performance thin-layer chromatography (HPTLC) is an advantageous analytical technique for analysis of complex samples. Combined with multivariate data analysis, it turns out to be a powerful tool for profiling of many samples in parallel. So far, chromatogram analysis has been time-consuming and required the application of at least two software packages to convert HPTLC chromatograms into a numerical data matrix. Hence, this study aimed to develop a powerful, all in one open-source software for user-friendly image processing and multivariate analysis of HPTLC chromatograms. Using the caret package for machine learning, the software was set up in the R programming language with an HTML−user interface created by the shiny package. The newly developed software, called rTLC, is deployed online, and instructions for direct use as a web application and for local installation, if required, are available on GitHub. rTLC was created especially for routine use in planar chromatography. It provides the necessary tools to guide the user in a fast protocol to the statistical data output (e.g., data extraction, preprocessing techniques, variable selection, and data analysis). rTLC offers a standardized procedure and informative visualization tools that allow the user to explore the data in a reproducible and comprehensive way. As proof-of-principle of rTLC, German propolis samples were analyzed using pattern recognition techniques, principal component analysis, hierarchic cluster analysis, and predictive techniques, such as random forest and support vector machines. © 2016 American Chemical Society.",
journal = "Analytical Chemistry",
title = "Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms",
volume = "88",
number = "24",
pages = "12494-12501",
doi = "10.1021/acs.analchem.6b04017"
}

Fichou, D., Ristivojević, P.,& Morlock, G. E.. (2016). Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms. in Analytical Chemistry, 88(24), 12494-12501.
https://doi.org/10.1021/acs.analchem.6b04017

Fichou D, Ristivojević P, Morlock GE. Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms. in Analytical Chemistry. 2016;88(24):12494-12501.
doi:10.1021/acs.analchem.6b04017 .

Fichou, Dimitri, Ristivojević, Petar, Morlock, Gertrud E., "Proof-of-principle of rTLC, an open-source software developed for image evaluation and multivariate analysis of planar chromatograms" in Analytical Chemistry, 88, no. 24 (2016):12494-12501,
https://doi.org/10.1021/acs.analchem.6b04017 . .

TY  - JOUR
AU  - Chasset, Thibaut
AU  - Haebe, Tim T.
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/1945
AB  - Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366 nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types. (C) 2016 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Chromatography A
T1  - Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra
VL  - 1465
SP  - 197
EP  - 204
DO  - 10.1016/j.chroma.2016.08.045
ER  - 

@article{
author = "Chasset, Thibaut and Haebe, Tim T. and Ristivojević, Petar and Morlock, Gertrud E.",
year = "2016",
abstract = "Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366 nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types. (C) 2016 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Chromatography A",
title = "Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra",
volume = "1465",
pages = "197-204",
doi = "10.1016/j.chroma.2016.08.045"
}

Chasset, T., Haebe, T. T., Ristivojević, P.,& Morlock, G. E.. (2016). Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra. in Journal of Chromatography A
Elsevier Science Bv, Amsterdam., 1465, 197-204.
https://doi.org/10.1016/j.chroma.2016.08.045

Chasset T, Haebe TT, Ristivojević P, Morlock GE. Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra. in Journal of Chromatography A. 2016;1465:197-204.
doi:10.1016/j.chroma.2016.08.045 .

Chasset, Thibaut, Haebe, Tim T., Ristivojević, Petar, Morlock, Gertrud E., "Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra" in Journal of Chromatography A, 1465 (2016):197-204,
https://doi.org/10.1016/j.chroma.2016.08.045 . .

TY  - JOUR
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2326
AB  - Planar chromatography is commonly used for the quality control of herbal medicines due to its many advantages. Its combination with chemometrics was proven to be a fast and reliable tool for the extraction of even more analytical information, such as similarity or dissimilarity between samples, and the identification of marker compounds. To date, depending on image processing procedures, different variables have been obtained as input data, and thus, various preprocessing procedures have been applied. In this study, we converted the chromatogram images of high-performance thin-layer chromatography to form a data matrix, by digitization of the chromatograms. Further, principal component analysis was applied on raw data and investigated after different preprocessing techniques. The proposed preprocessing techniques were successfully applied to improve the differentiation between two types of German propolis. The best multivariate models were observed in the case of warping, standard normal variate, and mean centering/autoscaling.
PB  - Akademiai Kiado Rt, Budapest
T2  - Journal of Planar Chromatography: Modern TLC / Thin Layer Chromatography
T1  - The Influence of Preprocessing Methods on Multivariate Image Analysis in High-Performance Thin-Layer Chromatography Fingerprinting
VL  - 29
IS  - 4
SP  - 310
EP  - 317
DO  - 10.1556/1006.2016.29.4.10
ER  - 

@article{
author = "Ristivojević, Petar and Morlock, Gertrud E.",
year = "2016",
abstract = "Planar chromatography is commonly used for the quality control of herbal medicines due to its many advantages. Its combination with chemometrics was proven to be a fast and reliable tool for the extraction of even more analytical information, such as similarity or dissimilarity between samples, and the identification of marker compounds. To date, depending on image processing procedures, different variables have been obtained as input data, and thus, various preprocessing procedures have been applied. In this study, we converted the chromatogram images of high-performance thin-layer chromatography to form a data matrix, by digitization of the chromatograms. Further, principal component analysis was applied on raw data and investigated after different preprocessing techniques. The proposed preprocessing techniques were successfully applied to improve the differentiation between two types of German propolis. The best multivariate models were observed in the case of warping, standard normal variate, and mean centering/autoscaling.",
publisher = "Akademiai Kiado Rt, Budapest",
journal = "Journal of Planar Chromatography: Modern TLC / Thin Layer Chromatography",
title = "The Influence of Preprocessing Methods on Multivariate Image Analysis in High-Performance Thin-Layer Chromatography Fingerprinting",
volume = "29",
number = "4",
pages = "310-317",
doi = "10.1556/1006.2016.29.4.10"
}

Ristivojević, P.,& Morlock, G. E.. (2016). The Influence of Preprocessing Methods on Multivariate Image Analysis in High-Performance Thin-Layer Chromatography Fingerprinting. in Journal of Planar Chromatography: Modern TLC / Thin Layer Chromatography
Akademiai Kiado Rt, Budapest., 29(4), 310-317.
https://doi.org/10.1556/1006.2016.29.4.10

Ristivojević P, Morlock GE. The Influence of Preprocessing Methods on Multivariate Image Analysis in High-Performance Thin-Layer Chromatography Fingerprinting. in Journal of Planar Chromatography: Modern TLC / Thin Layer Chromatography. 2016;29(4):310-317.
doi:10.1556/1006.2016.29.4.10 .

Ristivojević, Petar, Morlock, Gertrud E., "The Influence of Preprocessing Methods on Multivariate Image Analysis in High-Performance Thin-Layer Chromatography Fingerprinting" in Journal of Planar Chromatography: Modern TLC / Thin Layer Chromatography, 29, no. 4 (2016):310-317,
https://doi.org/10.1556/1006.2016.29.4.10 . .

TY  - JOUR
AU  - Chasset, Thibaut
AU  - Haebe, Tim T.
AU  - Ristivojević, Petar
AU  - Morlock, Gertrud E.
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3600
AB  - Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366 nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types. (C) 2016 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Chromatography A
T1  - Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra
VL  - 1465
SP  - 197
EP  - 204
DO  - 10.1016/j.chroma.2016.08.045
ER  - 

@article{
author = "Chasset, Thibaut and Haebe, Tim T. and Ristivojević, Petar and Morlock, Gertrud E.",
year = "2016",
abstract = "Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366 nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types. (C) 2016 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Chromatography A",
title = "Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra",
volume = "1465",
pages = "197-204",
doi = "10.1016/j.chroma.2016.08.045"
}

Chasset, T., Haebe, T. T., Ristivojević, P.,& Morlock, G. E.. (2016). Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra. in Journal of Chromatography A
Elsevier Science Bv, Amsterdam., 1465, 197-204.
https://doi.org/10.1016/j.chroma.2016.08.045

Chasset T, Haebe TT, Ristivojević P, Morlock GE. Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra. in Journal of Chromatography A. 2016;1465:197-204.
doi:10.1016/j.chroma.2016.08.045 .

Chasset, Thibaut, Haebe, Tim T., Ristivojević, Petar, Morlock, Gertrud E., "Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra" in Journal of Chromatography A, 1465 (2016):197-204,
https://doi.org/10.1016/j.chroma.2016.08.045 . .

TY  - JOUR
AU  - Morlock, Gertrud E.
AU  - Ristivojević, Petar
AU  - Chernetsova, Elena S.
PY  - 2014
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3749
AB  - Sophisticated statistical tools are required to extract the full analytical power from high-performance thin-layer chromatography (HPTLC). Especially, the combination of HPTLC fingerprints (image) with chemometrics is rarely used so far. Also, the newly developed, instantaneous direct analysis in real time mass spectrometry (DART-MS) method is perspective for sample characterization and differentiation by multivariate data analysis. This is a first novel study on the differentiation of natural products using a combination of fast fingerprint techniques, like HPTLC and DART-MS, for multivariate data analysis. The results obtained by the chemometric evaluation of HPTLC and DART-MS data provided complementary information. The complexity, expense, and analysis time were significantly reduced due to the use of statistical tools for evaluation of fingerprints. The approach allowed categorizing 91 propolis samples from Germany and other locations based on their phenolic compound profile. A high level of confidence was obtained when combining orthogonal approaches (HPTLC and DART-MS) for ultrafast sample characterization. HPTLC with selective post-chromatographic derivatization provided information on polarity, functional groups and spectral properties of marker compounds, while information on possible elemental formulae of principal components (phenolic markers) was obtained by DART-MS. (C) 2013 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Chromatography A
T1  - Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis
VL  - 1328
SP  - 104
EP  - 112
DO  - 10.1016/j.chroma.2013.12.053
ER  - 

@article{
author = "Morlock, Gertrud E. and Ristivojević, Petar and Chernetsova, Elena S.",
year = "2014",
abstract = "Sophisticated statistical tools are required to extract the full analytical power from high-performance thin-layer chromatography (HPTLC). Especially, the combination of HPTLC fingerprints (image) with chemometrics is rarely used so far. Also, the newly developed, instantaneous direct analysis in real time mass spectrometry (DART-MS) method is perspective for sample characterization and differentiation by multivariate data analysis. This is a first novel study on the differentiation of natural products using a combination of fast fingerprint techniques, like HPTLC and DART-MS, for multivariate data analysis. The results obtained by the chemometric evaluation of HPTLC and DART-MS data provided complementary information. The complexity, expense, and analysis time were significantly reduced due to the use of statistical tools for evaluation of fingerprints. The approach allowed categorizing 91 propolis samples from Germany and other locations based on their phenolic compound profile. A high level of confidence was obtained when combining orthogonal approaches (HPTLC and DART-MS) for ultrafast sample characterization. HPTLC with selective post-chromatographic derivatization provided information on polarity, functional groups and spectral properties of marker compounds, while information on possible elemental formulae of principal components (phenolic markers) was obtained by DART-MS. (C) 2013 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Chromatography A",
title = "Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis",
volume = "1328",
pages = "104-112",
doi = "10.1016/j.chroma.2013.12.053"
}

Morlock, G. E., Ristivojević, P.,& Chernetsova, E. S.. (2014). Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis. in Journal of Chromatography A
Elsevier Science Bv, Amsterdam., 1328, 104-112.
https://doi.org/10.1016/j.chroma.2013.12.053

Morlock GE, Ristivojević P, Chernetsova ES. Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis. in Journal of Chromatography A. 2014;1328:104-112.
doi:10.1016/j.chroma.2013.12.053 .

Morlock, Gertrud E., Ristivojević, Petar, Chernetsova, Elena S., "Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis" in Journal of Chromatography A, 1328 (2014):104-112,
https://doi.org/10.1016/j.chroma.2013.12.053 . .

TY  - JOUR
AU  - Morlock, Gertrud E.
AU  - Ristivojević, Petar
AU  - Chernetsova, Elena S.
PY  - 2014
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/1502
AB  - Sophisticated statistical tools are required to extract the full analytical power from high-performance thin-layer chromatography (HPTLC). Especially, the combination of HPTLC fingerprints (image) with chemometrics is rarely used so far. Also, the newly developed, instantaneous direct analysis in real time mass spectrometry (DART-MS) method is perspective for sample characterization and differentiation by multivariate data analysis. This is a first novel study on the differentiation of natural products using a combination of fast fingerprint techniques, like HPTLC and DART-MS, for multivariate data analysis. The results obtained by the chemometric evaluation of HPTLC and DART-MS data provided complementary information. The complexity, expense, and analysis time were significantly reduced due to the use of statistical tools for evaluation of fingerprints. The approach allowed categorizing 91 propolis samples from Germany and other locations based on their phenolic compound profile. A high level of confidence was obtained when combining orthogonal approaches (HPTLC and DART-MS) for ultrafast sample characterization. HPTLC with selective post-chromatographic derivatization provided information on polarity, functional groups and spectral properties of marker compounds, while information on possible elemental formulae of principal components (phenolic markers) was obtained by DART-MS. (C) 2013 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Chromatography A
T1  - Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis
VL  - 1328
SP  - 104
EP  - 112
DO  - 10.1016/j.chroma.2013.12.053
ER  - 

@article{
author = "Morlock, Gertrud E. and Ristivojević, Petar and Chernetsova, Elena S.",
year = "2014",
abstract = "Sophisticated statistical tools are required to extract the full analytical power from high-performance thin-layer chromatography (HPTLC). Especially, the combination of HPTLC fingerprints (image) with chemometrics is rarely used so far. Also, the newly developed, instantaneous direct analysis in real time mass spectrometry (DART-MS) method is perspective for sample characterization and differentiation by multivariate data analysis. This is a first novel study on the differentiation of natural products using a combination of fast fingerprint techniques, like HPTLC and DART-MS, for multivariate data analysis. The results obtained by the chemometric evaluation of HPTLC and DART-MS data provided complementary information. The complexity, expense, and analysis time were significantly reduced due to the use of statistical tools for evaluation of fingerprints. The approach allowed categorizing 91 propolis samples from Germany and other locations based on their phenolic compound profile. A high level of confidence was obtained when combining orthogonal approaches (HPTLC and DART-MS) for ultrafast sample characterization. HPTLC with selective post-chromatographic derivatization provided information on polarity, functional groups and spectral properties of marker compounds, while information on possible elemental formulae of principal components (phenolic markers) was obtained by DART-MS. (C) 2013 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Chromatography A",
title = "Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis",
volume = "1328",
pages = "104-112",
doi = "10.1016/j.chroma.2013.12.053"
}

Morlock, G. E., Ristivojević, P.,& Chernetsova, E. S.. (2014). Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis. in Journal of Chromatography A
Elsevier Science Bv, Amsterdam., 1328, 104-112.
https://doi.org/10.1016/j.chroma.2013.12.053

Morlock GE, Ristivojević P, Chernetsova ES. Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis. in Journal of Chromatography A. 2014;1328:104-112.
doi:10.1016/j.chroma.2013.12.053 .

Morlock, Gertrud E., Ristivojević, Petar, Chernetsova, Elena S., "Combined multivariate data analysis of high-performance thin-layer chromatography fingerprints and direct analysis in real time mass spectra for profiling of natural products like propolis" in Journal of Chromatography A, 1328 (2014):104-112,
https://doi.org/10.1016/j.chroma.2013.12.053 . .