Multivariate modeling for detecting adulteration of extra virgin olive oil with soybean oil using fluorescence and UV–Vis spectroscopies: A preliminary approach

LWT

Volumn 85, Issue , 2017, Pages 9-15

  Milanez, Karla Danielle Tavares Melo ^a   Nóbrega, Thiago César Araújo ^a   Nascimento, Danielle Silva ^b   Insausti, Matías ^b   Band, Beatriz Susana Fernández ^b   Pontes, Márcio José Coelho ^a  

^a FEDERAL UNIVERSITY OF PARAÍBA   (Brazil)

^b UNIVERSIDAD NACIONAL DEL SUR   (Argentina)

Author keywords

Authenticity; Multiple linear regression; Partial least squares regression; Variable selection

Indexed keywords

FLUORESCENCE; FLUORESCENCE SPECTROSCOPY; GENETIC ALGORITHMS; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; MEAN SQUARE ERROR; OLIVE OIL;

AUTHENTICITY; MULTIPLE LINEAR REGRESSIONS; PARTIAL LEAST SQUARE (PLS); PARTIAL LEAST SQUARES REGRESSION; ROOT-MEAN-SQUARE ERROR OF PREDICTIONS; SATISFACTORY PREDICTIONS; SUCCESSIVE PROJECTIONS ALGORITHM; VARIABLE SELECTION;

SOYBEAN OIL;

EID: 85021769717     PISSN: 00236438     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.lwt.2017.06.060     Document Type: Article

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