Combining portable nir spectroscopy and multivariate calibration for the determination of ethanol in fermented alcoholic beverages by a multi-product model

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dc.creatorAna Carolina da Costa Fulgêncio
dc.creatorGlaucimar Alex Passos Resende
dc.creatorMarden Claret Fontoura Teixeira
dc.creatorBruno Gonçalves Botelho
dc.creatorMarcelo Martins de Sena
dc.date.accessioned2025-09-04T20:07:31Z
dc.date.accessioned2025-09-08T23:56:38Z
dc.date.available2025-09-04T20:07:31Z
dc.date.issued2023-08
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.format.mimetypepdf
dc.identifier.doi10.1016/j.talo.2023.100180
dc.identifier.issn26668319
dc.identifier.urihttps://hdl.handle.net/1843/84889
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Aberto
dc.subjectBebida alcoólica
dc.subject.otherTeor alcoólico
dc.subject.otherSensor NIR portátil
dc.subject.otherPortabilidade
dc.subject.otherQuimioterapia
dc.subject.otherMiniaturização
dc.subject.otherAnálise direta
dc.titleCombining portable nir spectroscopy and multivariate calibration for the determination of ethanol in fermented alcoholic beverages by a multi-product model
dc.typeArtigo de periódico
local.citation.epage10
local.citation.spage1
local.citation.volume7
local.description.resumoIn this study, a multivariate calibration multi-product model was built by combining partial least square regression (PLS) and portable near infrared (NIR) spectroscopy for the determination of ethanol content in fermented alcoholic beverages. Reference values were obtained by gas chromatography with flame ionization detection (GC-FID). Aiming at building a robust model, a great variety of beers, ciders, meads, and wines were incorporated into the model. NIR spectra were recorded between 908 and 1676 nm for 153 alcoholic beverage samples, corresponding to a range from 4.3 to 15.3% (v/v) of alcohol content. PLS model provided accurate results with root mean square errors of calibration (RMSEC) and prediction (RMSEP) of 0.8% and 0.9%, respectively. The developed method was validated through the estimate of proper figures of merit, such as linearity, trueness, precision, analytical sensitivity, bias, and residual prediction deviation (RPD). This method was simple, direct, rapid, of low-cost and environmentally friendly, not consuming reagents or solvents nor generating chemical waste. It could be incorporated in analytical platforms for quality inspection, contributing to provide better transparency in the food supply chain.
local.publisher.countryBrasil
local.publisher.departmentFAR - DEPARTAMENTO DE ALIMENTOS
local.publisher.departmentICX - DEPARTAMENTO DE QUÍMICA
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S2666831923000012

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