Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods

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dc.creatorCarolina Sheng Whei Miaw
dc.creatorCamila Assis
dc.creatorAlessandro Rangel Carolino Sales Silva
dc.creatorMaria Luísa Cunha
dc.creatorMarcelo Martins Sena
dc.creatorScheilla Vitorino Carvalho de Souza
dc.date.accessioned2022-05-16T21:43:32Z
dc.date.accessioned2025-09-08T23:47:11Z
dc.date.available2022-05-16T21:43:32Z
dc.date.issued2018-07-15
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.description.sponsorshipOutra Agência
dc.identifier.doi10.1016/j.foodchem.2018.02.015
dc.identifier.issn0308-8146
dc.identifier.urihttps://hdl.handle.net/1843/41728
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofFood Chemistry
dc.rightsAcesso Restrito
dc.subjectTecnologia de alimentos
dc.subjectFrutas
dc.subjectEspectroscopia de infravermelho médio
dc.subject.otherfood fraud
dc.subject.otherMid-infrared spectroscopy
dc.subject.otherMultivariate analysis
dc.subject.otherChemometrics
dc.subject.otherVariable selection
dc.subject.otherMultivariate validation
dc.titleDetermination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods
dc.typeArtigo de periódico
local.citation.epage280
local.citation.spage272
local.citation.volume254
local.description.resumoGrape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated.
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/S0308814618302401?via%3Dihub

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