A comparison of artificial neural networks and partial least squares modelling for the rapid detection of the microbial spoilage of beef fillets based on Fourier transform infrared spectral fingerprints

Food Microbiology

Volumn 28, Issue 4, 2011, Pages 782-790

  Panagou, Efstathios Z ^a   Mohareb, Fady R ^b   Argyri, Anthoula A ^a,b   Bessant, Conrad M ^b   Nychas, George John E ^a  

^a AGRICULTURAL UNIVERSITY OF ATHENS   (Greece)

^b CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Aerobic storage; Artificial neural networks; Beef fillets; FTIR; Machine learning; Meat spoilage; Partial least squares regression; Pattern recognition

Indexed keywords

ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACTERIAL COUNT; BIOLOGICAL MODEL; CATTLE; COMPARATIVE STUDY; FOOD CONTROL; INFRARED SPECTROSCOPY; MEAT; METHODOLOGY; MICROBIOLOGY; REGRESSION ANALYSIS;

ANIMALS; CATTLE; COLONY COUNT, MICROBIAL; FOOD MICROBIOLOGY; LEAST-SQUARES ANALYSIS; MEAT; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); REGRESSION ANALYSIS; SPECTROSCOPY, FOURIER TRANSFORM INFRARED;

EID: 79954575819     PISSN: 07400020     EISSN: 10959998     Source Type: Journal    
DOI: 10.1016/j.fm.2010.05.014     Document Type: Article

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