Pregled bibliografske jedinice broj: 1279397
Classification models for fragrant compounds based on nmr spectroscopy
Classification models for fragrant compounds based on nmr spectroscopy // 7th Adriatic NMR Conference : Book of Abstracts / Bregović, Nikola ; Namjesnik, Danijel ; Novak, Predrag ; Parlov Vuković, Jelena - Croatian Chemical Society Zagreb, 2023, 48-48 / Bregović, Nikola ; Namjesnik, Danijel ; Novak, Predrag ; Parlov Vuković, Jelena (ur.).
Zagreb: Hrvatsko kemijsko društvo, 2023. str. 48-48 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1279397 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Classification models for fragrant compounds based
on nmr spectroscopy
Autori
Ramić, Alma ; Poljak, Marina ; Borovec, Jakov ; Primožič, Ines ; Hrenar, Tomica
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
7th Adriatic NMR Conference : Book of Abstracts / Bregović, Nikola ; Namjesnik, Danijel ; Novak, Predrag ; Parlov Vuković, Jelena - Croatian Chemical Society Zagreb, 2023, 48-48
/ Bregović, Nikola ; Namjesnik, Danijel ; Novak, Predrag ; Parlov Vuković, Jelena - Zagreb : Hrvatsko kemijsko društvo, 2023, 48-48
Skup
7th Adriatic NMR Conference
Mjesto i datum
Mali Ston, Hrvatska, 01.06.2023. - 04.06.2023
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
NMR spectroscopy ; fragrant compounds ; principal component analysis
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Kemija
POVEZANOST RADA
Ustanove:
Prirodoslovno-matematički fakultet, Zagreb