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Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale

Authorized Users Only
2022
Authors
Ristivojević, Petar
Andrić, Filip
Vasić, Vesna
Milojković-Opsenica, Dušanka
Morlock, Gertrud E.
Article (Published version)
Metadata
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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 fra...uds by adding pumpkin to apricot products can be detected at added contents as low as 2.5%.

Keywords:
Fruit product adulteration / Pumpkin / Apricot / HPTLC−FLD/Vis / Carotenoid profile / Green metrics / Multivariate analysis
Source:
Food Chemistry, 2022, 374, 131714
Publisher:
  • Elsevier
Funding / projects:
  • Ministry of Education, Science and Technological Development, Republic of Serbia, Grant no. 200168 (University of Belgrade, Faculty of Chemistry) (RS-200168)
Note:
  • Supplementary material: https://cherry.chem.bg.ac.rs/handle/123456789/5001
Related info:
  • Referenced by
    https://cherry.chem.bg.ac.rs/handle/123456789/5001

DOI: 10.1016/j.foodchem.2021.131714

ISSN: 0308-8146

WoS: 000734119700007

Scopus: 2-s2.0-85120634855
[ Google Scholar ]
URI
http://cherry.chem.bg.ac.rs/handle/123456789/5000
Collections
  • Publikacije
Institution/Community
Hemijski fakultet
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 . .

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