Version 1
: Received: 10 April 2024 / Approved: 14 April 2024 / Online: 15 April 2024 (08:06:04 CEST)
How to cite:
Lazaridis, D.G.; Kokkosi, E.K.; Mylonaki, E.N.; Karabagias, V.K.; Andritsos, N.D.; Karabagias, I.K. Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning. Preprints2024, 2024040871. https://doi.org/10.20944/preprints202404.0871.v1
Lazaridis, D.G.; Kokkosi, E.K.; Mylonaki, E.N.; Karabagias, V.K.; Andritsos, N.D.; Karabagias, I.K. Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning. Preprints 2024, 2024040871. https://doi.org/10.20944/preprints202404.0871.v1
Lazaridis, D.G.; Kokkosi, E.K.; Mylonaki, E.N.; Karabagias, V.K.; Andritsos, N.D.; Karabagias, I.K. Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning. Preprints2024, 2024040871. https://doi.org/10.20944/preprints202404.0871.v1
APA Style
Lazaridis, D.G., Kokkosi, E.K., Mylonaki, E.N., Karabagias, V.K., Andritsos, N.D., & Karabagias, I.K. (2024). Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning. Preprints. https://doi.org/10.20944/preprints202404.0871.v1
Chicago/Turabian Style
Lazaridis, D.G., Nikolaos D Andritsos and Ioannis K Karabagias. 2024 "Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning" Preprints. https://doi.org/10.20944/preprints202404.0871.v1
Abstract
The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of green coffee, clove, cinnamon/clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning green coffee, clove, cinnamon, cinnamon and clove, and nutmeg fine powders based on multivariate analysis of variance and supervised learning on data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography/mass spectrometry. Results showed that 7 volatile compounds namely ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of green coffee, cinnamon, clove, cinnamon and clove and nutmeg, based on selected volatile compounds, and provides further support to the literature by means of possible adulteration given the statistical models developed.
Keywords
Green coffee; spices; volatile compounds; supervised learning; typification
Subject
Chemistry and Materials Science, Food Chemistry
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
*
