title: The relevance of different near infrared technologies and sample treatments for predicting meat quality traits in commercial beef cuts.
abstract: Visible and near infrared reflectance (Vis-NIR, 350 to 1800 nm), and near infrared transmittance (NIT, 850 to 1050 nm) spectroscopy were used to predict beef quality traits of intact and ground meat samples. Calibration equations were developed from reference data (n = 312) of pH, color traits (L*, a*, and b*), ageing loss (%), cooking loss (%), and Warner-Bratzler shear force (WBSF, N) using partial least squares regressions. Predictive ability of the models was assessed by coefficient of determination of cross-validation (R(2)(CV)) and root mean square error of cross-validation. Quality traits were better predicted on intact than on ground samples, and the best results were obtained using Vis-NIR spectroscopy. Predictions were good (R(2)(CV) = 0.62 to 0.73) for pH, L*, and a*, hardly sufficient (R(2)(CV) = 0.34 to 0.60) for b*, cooking loss, and WBSF, and unsatisfactory for ageing loss (R(2)(CV) = 0.15). Vis-NIR spectroscopy might be used to predict some physical beef quality traits on intact meat samples.
authors.affiliation: Department of Agronomy, University of Padova, Viale dell'Università 16, 35020 Legnaro, PD, Italy.
authors.forename: M
authors.initials: M
authors.lastname: De Marchi
authors.forename: M
authors.initials: M
authors.lastname: Penasa
authors.forename: A
authors.initials: A
authors.lastname: Cecchinato
authors.forename: G
authors.initials: G
authors.lastname: Bittante
mesh_terms: D000818:Animals; D001947:Breeding; D002417:Cattle; D005240:Feasibility Studies; D005511:Food Handling / Q000379:methods*; D063427:Food Quality; D016018:Least-Squares Analysis; D008460:Meat / Q000032:analysis*; D018482:Muscle, Skeletal / Q000737:chemistry; D010641:Phenotype; D012016:Reference Values; D019265:Spectroscopy, Near-Infrared / Q000379:methods*