In-depth analysis of volatolomic and odorous profiles of novel craft beer by permutation test features selection and multivariate correlation analysis.

Craft beer formulation Multivariate statistics, permutation test Odour sensory profile Volatile compounds

Journal

Food chemistry
ISSN: 1873-7072
Titre abrégé: Food Chem
Pays: England
ID NLM: 7702639

Informations de publication

Date de publication:
17 May 2024
Historique:
received: 04 01 2024
revised: 05 04 2024
accepted: 14 05 2024
medline: 22 5 2024
pubmed: 22 5 2024
entrez: 21 5 2024
Statut: aheadofprint

Résumé

This research explored the impact of binary cereal blends [barley with durum wheat (DW) and soft wheat (CW)], four autochthonous yeast strains (9502, 9518, 14061 and 17290) and two refermentation sugar concentrations (6-9 g/L), on volatolomics (VOCs) and odour profiles of craft beers using unsupervised statistics. For the first time, we applied permutation test to select volatiles with higher significance in explaining variance among samples. The unsupervised approach on the 19 selected VOCs revealed cereal-yeast interaction to be the main source of variability and DW-9502-6/9, DW-17290-6, CW-17290-6 and CW-9518-6 being the best technological strategies. In particular, in samples DW-9502-6/9, concentrations of some of the selected volatiles were observed to be approximately three to more than seven times higher than the average. PLS-correlation between VOCs and odour profiles proved to be very useful in assessing the weight of each of the selected VOCs on the perception of odour notes.

Identifiants

pubmed: 38772309
pii: S0308-8146(24)01352-9
doi: 10.1016/j.foodchem.2024.139702
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

139702

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Maria Tufariello (M)

Institute of Sciences of Food Production, National Research Council, Prov.le, Lecce-Monteroni, 73100 Lecce, Italy.

Lorenzo Palombi (L)

Institute of Applied Physic "Nello Carrara", National Research Council, Via Madonna del Piano 10, Sesto Fiorentino, Firenze 50019, Italy. Electronic address: l.palombi@ifac.cnr.it.

Antonietta Baiano (A)

Department of Agricultural Sciences, Food, Natural Resources and Engineering, University of Foggia, Via Napoli, 25, 71122 Foggia, Italy.

Francesco Grieco (F)

Institute of Sciences of Food Production, National Research Council, Prov.le, Lecce-Monteroni, 73100 Lecce, Italy.

Classifications MeSH