Partial least squares analysis of near-infrared hyperspectral images for beef tenderness prediction

Sensing and Instrumentation for Food Quality and Safety

Volumn 2, Issue 3, 2008, Pages 178-188

  Naganathan, Govindarajan Konda ^a   Grimes, Lauren M ^a   Subbiah, Jeyamkondan ^a   Calkins, Chris R ^a   Samal, Ashok ^b   Meyer, George E ^a  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Beef tenderness; Instrument grading; Near infrared hyperspectral imaging

Indexed keywords

ABSORPTION BANDS; BEEF TENDERNESS; CO-OCCURRENCE MATRICES; COOKED BEEF; FLOOD LIGHTING; FOOD QUALITY; GRAY LEVELS; HYPER-SPECTRAL; HYPER-SPECTRAL IMAGES; HYPER-SPECTRAL IMAGING; HYPERSPECTRAL IMAGING SYSTEMS; INSTRUMENT GRADING; LONGISSIMUS; MULTI-SPECTRAL IMAGING; NEAR INFRA-RED; NEAR-INFRARED HYPERSPECTRAL IMAGING; PARTIAL LEAST SQUARES ANALYSIS; PARTIAL LEAST-SQUARES REGRESSION; PUSHBROOM; QUANTIZATION LEVELS; REGION -OF-INTEREST; SECOND ORDERS; SHEAR FORCE; TEXTURAL FEATURES; WAVELENGTH RANGES;

ABSORPTION; ATMOSPHERICS; CANNING; CURVE FITTING; CUSTOMER SATISFACTION; FEATURE EXTRACTION; FOOD PRESERVATION; FOOD PROCESSING; FORECASTING; GEODESY; IMAGE ENHANCEMENT; IMAGING SYSTEMS; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; NEURAL NETWORKS; OPTOELECTRONIC DEVICES; QUALITY FUNCTION DEPLOYMENT; WATER ABSORPTION;

IMAGING TECHNIQUES;

EID: 77957727090     PISSN: 19327587     EISSN: 19329954     Source Type: Journal    
DOI: 10.1007/s11694-008-9051-3     Document Type: Article

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