Non-destructive prediction and visualization of chemical composition in lamb meat using NIR hyperspectral imaging and multivariate regression

Innovative Food Science and Emerging Technologies

Volumn 16, Issue , 2012, Pages 218-226

  Kamruzzaman, Mohammed ^a   Elmasry, Gamal ^a   Sun, Da Wen ^a   Allen, Paul ^b  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b ASHTOWN FOOD RESEARCH CENTRE   (Ireland)

Author keywords

Fat and protein; Lamb; Near infrared hyperspectral imaging; Partial least squares regression; Water

Indexed keywords

CHEMICAL COMPOSITIONS; CHEMICAL CONSTITUENTS; CHEMICAL IMAGES; COMPOSITIONAL GRADIENTS; DETERMINATION COEFFICIENTS; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGING; LAMB; MEAT INDUSTRY; MULTIVARIATE CALIBRATION; MULTIVARIATE REGRESSION; NEAR-INFRARED HYPERSPECTRAL IMAGING; NEAR-INFRARED RANGE; NON-DESTRUCTIVE PREDICTION; PARTIAL LEAST SQUARES REGRESSION; PROTEIN CONTENTS; REGRESSION COEFFICIENT; REGRESSION EQUATION; SPECTRAL IMAGES; STANDARD ERROR OF PREDICTION;

FORECASTING; INFRARED DEVICES; MEATS; MUSCLE; REGRESSION ANALYSIS; WATER;

SPECTROSCOPY;

EID: 84870535960     PISSN: 14668564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ifset.2012.06.003     Document Type: Article

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