Calibration of artificial neural network and partial least squares regression models for the prediction of secoisolariciresinol diglucoside contents in microwave-assisted extracts of various flaxseed (Linum usitatissimum L.) samples

Food Chemistry

Volumn 133, Issue 4, 2012, Pages 1588-1595

  Nemes, Simona M ^a   Orsat, Valérie ^a   Vijaya Raghavan, G S ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

ANN; Calibration; Nutraceutical; PLS; Polyphenol; SDG; Spectrophotometric; UV Vis

Indexed keywords

ANN; NUTRACEUTICALS; PLS; POLYPHENOLS; SDG; SPECTROPHOTOMETRIC; UV-VIS;

CALIBRATION; FORECASTING; LIGHT ABSORPTION; NEURAL NETWORKS; OILSEEDS; PLANTS (BOTANY); REGRESSION ANALYSIS;

FLAX;

GLUCOSIDE; SECOISOLARICIRESINOL;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALIBRATION; CHEMICAL COMPOSITION; CULTIVAR; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; LIGHT ABSORPTION; LINSEED; MICROWAVE RADIATION; NONBIOLOGICAL MODEL; PARTIAL LEAST SQUARES REGRESSION; PREDICTIVE VALUE;

LINUM USITATISSIMUM;

EID: 84859792993     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2012.02.053     Document Type: Article

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