Durbin-Watson partial least-squares regression applied to MIR data on adulteration with edible oils of different origins

Food Chemistry

Volumn 213, Issue , 2016, Pages 791-798

  Jović, Ozren ^a  

^a UNIVERSITY OF ZAGREB   (Croatia)

Author keywords

Binary mixtures; Durbin Watson statistic; MIR; Oil adulteration; PLS; Variable selection

Indexed keywords

BINARY MIXTURES; OILS AND FATS; OILSEEDS; REGRESSION ANALYSIS; SUNFLOWER OIL; VEGETABLE OILS;

COLD PRESSED LINSEED OIL; DURBIN-WATSON STATISTIC; OIL ADULTERATIONS; PARTIAL LEAST SQUARES REGRESSION; QUANTITATIVE DETERMINATIONS; QUANTITATIVE PREDICTION; REGRESSION COEFFICIENT; VARIABLE SELECTION;

LEAST SQUARES APPROXIMATIONS;

EDIBLE OIL; LINSEED OIL; RAPESEED OIL; SESAME SEED OIL; SUNFLOWER OIL; CANOLA OIL; VEGETABLE OIL;

ARTICLE; DISCRIMINANT ANALYSIS; DURBIN WATSON PARTIAL LEAST SQUARES REGRESSION; GEOGRAPHIC ORIGIN; PARTIAL LEAST SQUARES REGRESSION; ANALYSIS; FOOD ANALYSIS; FOOD CONTAMINATION; LEAST SQUARE ANALYSIS; MULTIVARIATE ANALYSIS;

FOOD ANALYSIS; FOOD CONTAMINATION; LEAST-SQUARES ANALYSIS; LINSEED OIL; MULTIVARIATE ANALYSIS; PLANT OILS; SESAME OIL;

EID: 84978105204     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2016.07.016     Document Type: Article

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