Robust linear and non-linear models of NIR spectroscopy for detection and quantification of adulterants in fresh and frozen-thawed minced beef

Meat Science

Volumn 93, Issue 2, 2013, Pages 292-302

  Morsy, Noha ^a,b   Sun, Da Wen ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b University of Suez Canal   (Egypt)

Author keywords

Adulteration; Authentication; Minced beef; Multivariate analysis; NIRS; Spectroscopy

Indexed keywords

ADULTERATION; CLASSIFICATION ACCURACY; CROSS VALIDATION; DATA SETS; DETERMINATION COEFFICIENTS; DEVELOPED MODEL; EXPONENTIAL REGRESSION; LINEAR DISCRIMINANT ANALYSIS; MINCED BEEF; MULTI VARIATE ANALYSIS; NIR SPECTROSCOPY; NIRS; NON-LINEAR MODEL; NON-LINEAR REGRESSION; NONDESTRUCTIVE TOOLS; PARTIAL LEAST SQUARES-DISCRIMINANT ANALYSIS; PARTIAL LEAST-SQUARES REGRESSION; STANDARD ERROR OF PREDICTION; VIS-NIR SPECTROSCOPY;

AUTHENTICATION; DISCRIMINANT ANALYSIS; INFRARED DEVICES; NEAR INFRARED SPECTROSCOPY; REGRESSION ANALYSIS; SPECTROSCOPY; THAWING;

MEATS;

ANIMAL; ARTICLE; CATTLE; DISCRIMINANT ANALYSIS; FOOD CONTAMINATION; FOOD HANDLING; FREEZING; MEAT; METHODOLOGY; MULTIVARIATE ANALYSIS; NEAR INFRARED SPECTROSCOPY; NONLINEAR SYSTEM; REGRESSION ANALYSIS;

ANIMALS; CATTLE; DISCRIMINANT ANALYSIS; FOOD CONTAMINATION; FOOD HANDLING; FREEZING; LEAST-SQUARES ANALYSIS; MEAT; MULTIVARIATE ANALYSIS; NONLINEAR DYNAMICS; SPECTROSCOPY, NEAR-INFRARED;

EID: 84868618442     PISSN: 03091740     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.meatsci.2012.09.005     Document Type: Article

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