Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/29577
Título: QSPR modeling is able to predict retention times of fatty acids using simple molecular descriptors
Palavras-chave: Chromatographic retention
Multiple linear regression
QSPR Modeling
Retenção cromatográfica
Regressão linear múltipla
Modelagem QSPR
Data do documento: 2017
Editor: Igi Global
Citação: DUARTE, M. H.; NUNES, C. QSPR modeling is able to predict retention times of fatty acids using simple molecular descriptors. International Journal of Quantitative Structure-Property Relationships, [S. l.], v. 2, n. 1, 2017. 9 p. doi: 10.4018/IJQSPR.2017010103.
Resumo: A QSPR modeling was carried out to predict the chromatographic retention times of a series of fatty acid methyl esters (FAME) widely used as standard in the characterization of lipids from agricultural and food products. Number of carbons, total double bonds, position of double bonds and geometric isomerism were used as descriptors to generate a Multiple Linear Regression (MLR) model. The best model yielded an RMSE = 0.167 and R2 = 0.999 for the calibration set, and RMSE = 0.151 and R2 = 1.000 for the test set. Number of carbons and total double bonds were the most important descriptors, according to the regression coefficients, but position of double bonds and isomerism cannot be neglected as they provide relevant information to improve the accuracy of the predicted property.
URI: https://www.igi-global.com/article/qspr-modeling-is-able-to-predict-retention-times-of-fatty-acids-using-simple-molecular-descriptors/171144
http://repositorio.ufla.br/jspui/handle/1/29577
Aparece nas coleções:DCA - Artigos publicados em periódicos

Arquivos associados a este item:
Não existem arquivos associados a este item.


Os itens no repositório estão protegidos por copyright, com todos os direitos reservados, salvo quando é indicado o contrário.