title: HRMAS-NMR spectroscopy and multivariate analysis meat characterisation.
abstract: ¹H-High resolution magic angle spinning-nuclear magnetic resonance spectroscopy was employed to gain the metabolic profile of longissimus dorsi and semitendinosus muscles of four different breeds: Chianina, Holstein Friesian, Maremmana and Buffalo. Principal component analysis, partial least squares projection to latent structure - discriminant analysis and orthogonal partial least squares projection to latent structure - discriminant analysis were used to build models capable of discriminating the muscle type according to the breed. Data analysis led to an excellent classification for Buffalo and Chianina, while for Holstein Friesian the separation was lower. In the case of Maremmana the use of intelligent bucketing was necessary due to some resonances shifting allowed improvement of the discrimination ability. Finally, by using the Variable Importance in Projection values the metabolites relevant for the classification were identified.
authors: Agricultural Research Council-Research Centre for the Soil-Plant System, Instrumental Centre of Tor Mancina Strada della Neve Km 1, 00016 Monterotondo, Rome, Italy.
authors: Mena
authors: M
authors: Ritota
authors: Lorena
authors: L
authors: Casciani
authors: Sebastiana
authors: S
authors: Failla
authors: Massimiliano
authors: M
authors: Valentini
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D002417:Cattle / Q000378:metabolism*; D019295:Computational Biology; D016002:Discriminant Analysis; D005513:Food Inspection / Q000379:methods*; D007558:Italy; D016018:Least-Squares Analysis; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008297:Male; D008460:Meat / Q000032:analysis*; D055442:Metabolome; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000737:chemistry* / Q000378:metabolism; D025341:Principal Component Analysis; D013045:Species Specificity