| Autor: |
Ramić, Alma, Poljak, Marina, Borovec, Jakov, Primožič, Ines, Hrenar, Tomica |
| Přispěvatelé: |
Bregović, Nikola, Namjesnik, Danijel, Novak, Predrag, Parlov Vuković, Jelena |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Popis: |
Spectroscopic measurements of 82 selected odorants were performed using 1H NMR spectroscopy. This set includes 6 main types of perfumery odor notes[1] and the NMR spectral data will subsequently be used to build an accurate classification model. 2nd- order tensor decomposition tool principal component analysis (PCA) was applied to a set of obtained NMR spectra, as well as on their first and second derivatives. The quality of PCA models was evaluated by determining the optimal number of principal components for the representation in the reduced space.[2] In each case, the first principal component accounted for most of the total variance among the samples. The results were additionally improved using spectral derivatives. Classification of these odorants was established and underlying hidden spectral differences among compounds were determined by investigating the principal component loadings.[3] These differences are directly caused by changes in the chemical composition. It was found that NMR spectroscopy coupled with PCA can distinguish between various fragrant compounds. Odorants subjected to the chemometric analyses can be divided into several major groups (clusters). Investigation of the principal component loadings determined the major differences among the NMR spectra regarding structural patterns present in the chemical structures. These differences are associated with the total number of aromatic and/or aliphatic functional groups and their structure, reflecting variations in the composition of different odor notes. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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