Indirect Nuclear Magnetic Resonance (NMR) Spectroscopic Determination of Acrylamide in Coffee Using Partial Least Squares (PLS) Regression
| Autor: | Elke Richling, Carmen M. Breitling-Utzmann, Katrin Krumbügel, Simone Stegmüller, Stephan G. Walch, Dirk W. Lachenmeier, Vera Rief, Christina Felske, Andreas Scharinger |
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| Rok vydání: | 2021 |
| Předmět: |
Coffea arabica
analytical_chemistry multivariate data analysis spectroscopy RC620-627 Coffee roasting 01 natural sciences chemistry.chemical_compound 0404 agricultural biotechnology LC–MS/MS 2-propenamide coffee roasting Partial least squares regression media_common.cataloged_instance TX341-641 European union Nutritional diseases. Deficiency diseases Roasting media_common Chromatography Nutrition. Foods and food supply 010401 analytical chemistry 04 agricultural and veterinary sciences Nuclear magnetic resonance spectroscopy 040401 food science 0104 chemical sciences NMR spectra database chemistry Acrylamide Proton NMR Food Science |
| Zdroj: | Beverages; Volume 7; Issue 2; Pages: 31 Beverages, Vol 7, Iss 31, p 31 (2021) |
| DOI: | 10.20944/preprints202103.0446.v1 |
| Popis: | Acrylamide is probably carcinogenic to humans (International Agency for Research on Cancer, group 2A) with major occurrence in heated, mainly carbohydrate-rich foods. For roasted coffee, a European Union benchmark level of 400 µg/kg acrylamide is of importance. Regularly, the acrylamide contents are controlled using liquid chromatography combined with tandem mass spectrometry (LC-MS/MS). This reference method is reliable and precise but laborious because of the necessary sample clean-up procedure and instrument requirements. This research investigates the possibility of predicting the acrylamide content from proton nuclear magnetic resonance (NMR) spectra that are already recorded for other purposes of coffee control. In the NMR spectrum acrylamide is not directly quantifiable, so that the aim was to establish a correlation between the reference value and the corresponding NMR spectrum by means of a partial least squares (PLS) regression. Therefore, 40 commercially available coffee samples with already available LC-MS/MS data and NMR spectra were used as calibration data. To test the accuracy and robustness of the model and its limitations, 50 coffee samples with extreme roasting degrees and blends were additionally prepared as test set. The PLS model shows an applicability for the varieties C. arabica and C. canephora, which were medium to very dark roasted using drum or infrared roasters. The root mean square error of prediction (RMSEP) is 79 µg/kg acrylamide (n=32). The PLS model is judged as suitable to predict the acrylamide values of commercially available coffee samples. On the other hand, very light roasts containing more than 1000 µg/kg acrylamide are currently not suitable for PLS prediction. |
| Databáze: | OpenAIRE |
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