When detection of dairy food fraud fails : An alternative approach through proton nuclear magnetic resonance spectroscopy
The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)..
This paper investigated the limits of the current approach for the determination of the fatty acids profile of milk fats from proton nuclear magnetic resonance data based on the hypothesis that the signal at 0.96 ppm, currently assigned in the literature as a marker for the "short chain fatty acids," is generated only by the butyric moiety (not by all of the short-chain fatty acids, which also include C6:0-caproic acid). The hypothesis was tested and experimentally confirmed. Moreover, the triplet at 0.96 ppm can also be due to n-3 fatty acids such as linolenic acid (C18:3); therefore, a previously reported methodology for the fatty acids profiling of dairy products-considered as general in the literature-cannot be used in fraud-detection approaches because it allows linolenic acid to be mistaken for butyric acid, consequently leading to misclassification of adulterated samples as nonadulterated. To support our opinion, we have applied the current literature approach for the determination of the fatty acids composition of 3 synthetic nondairy fat blends and have obtained fatty acid compositions similar to milk fats, allowing for their misclassification as genuine milk fats. However, in reality, the blends had very different compositions, as confirmed by gas chromatography. Consequently, we have highlighted the weaknesses of the existing methodology for the detection of dairy food adulteration. In return, new proton nuclear magnetic resonance descriptors based on various integral ratios of signals associated with CH2 moiety versus signals associated with butyric and n-3 fatty acids were proposed to detect adulterations.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:104 |
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| Enthalten in: |
Journal of dairy science - 104(2021), 8 vom: 29. Aug., Seite 8454-8466 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hanganu, Anamaria [VerfasserIn] |
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| Links: |
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| Themen: |
Butyric acid |
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| Anmerkungen: |
Date Completed 13.07.2021 Date Revised 13.07.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.3168/jds.2020-19883 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM324879636 |
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| 520 | |a The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | ||
| 520 | |a This paper investigated the limits of the current approach for the determination of the fatty acids profile of milk fats from proton nuclear magnetic resonance data based on the hypothesis that the signal at 0.96 ppm, currently assigned in the literature as a marker for the "short chain fatty acids," is generated only by the butyric moiety (not by all of the short-chain fatty acids, which also include C6:0-caproic acid). The hypothesis was tested and experimentally confirmed. Moreover, the triplet at 0.96 ppm can also be due to n-3 fatty acids such as linolenic acid (C18:3); therefore, a previously reported methodology for the fatty acids profiling of dairy products-considered as general in the literature-cannot be used in fraud-detection approaches because it allows linolenic acid to be mistaken for butyric acid, consequently leading to misclassification of adulterated samples as nonadulterated. To support our opinion, we have applied the current literature approach for the determination of the fatty acids composition of 3 synthetic nondairy fat blends and have obtained fatty acid compositions similar to milk fats, allowing for their misclassification as genuine milk fats. However, in reality, the blends had very different compositions, as confirmed by gas chromatography. Consequently, we have highlighted the weaknesses of the existing methodology for the detection of dairy food adulteration. In return, new proton nuclear magnetic resonance descriptors based on various integral ratios of signals associated with CH2 moiety versus signals associated with butyric and n-3 fatty acids were proposed to detect adulterations | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a butyric acid | |
| 650 | 4 | |a detection of adulteration | |
| 650 | 4 | |a fatty acids profile | |
| 650 | 4 | |a milk fat | |
| 650 | 4 | |a proton nuclear magnetic resonance descriptors | |
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