ARCJMCH2

2589

28 octobre 2020 12:38

28 octobre 2020 12:38

Cette étude a évalué la spectroscopie visible et proche infrarouge (Vis-NIRS) pour authentifier le bœuf orge fini en utilisant différentes approches de discrimination. La source de céréales alimentaires (orge, maïs ou mélange 50% orge / 50% maïs) n'a pas affecté (P> 0,05) la qualité de la viande mais a influencé (P< 0.05) fatty acid profiles. The longissimus thoracis (LT) from barley-fed steers had lower n-6 fatty acid content and n-6/n-3 ratio compared to LT from corn and blended grain-fed steers. Vis-NIRS coupled with partial least square discriminant analysis (PLS-DA) and support vector machine in the linear (L-SVM) kernel classified with approximately 70% overall accuracy subcutaneous fat and intact LT samples, respectively, from barley, corn, and blended-fed cattle. When only barley and corn samples were considered, fat and intact LT samples were correctly classified with overall accuracy >94% avec PLS-DA et radial / L-SVM, et environ 90% avec PLS-DA et L-SVM, respectivement. Les échantillons de LT haché ont été classés avec une précision globale ≤ 70%. Les mesures Vis-NIRS sur la graisse et la LT intacte ont le potentiel de faire la distinction entre le maïs et le bœuf nourri à l'orge.

This study evaluated visible and near-infrared spectroscopy (Vis-NIRS) to authenticate barley-finished beef using different discrimination approaches. Dietary grain source (barley, corn, or blend-50% barley/50% corn) did not affect (P > 0.05) meat quality but influenced (P < 0.05) fatty acid profiles. The longissimus thoracis (LT) from barley-fed steers had lower n-6 fatty acid content and n-6/n-3 ratio compared to LT from corn and blended grain-fed steers. Vis-NIRS coupled with partial least square discriminant analysis (PLS-DA) and support vector machine in the linear (L-SVM) kernel classified with approximately 70% overall accuracy subcutaneous fat and intact LT samples, respectively, from barley, corn, and blended-fed cattle. When only barley and corn samples were considered, fat and intact LT samples were correctly classified with overall accuracy >94% with PLS-DA and radial/L-SVM, and approximately 90% with PLS-DA and L-SVM, respectively. Ground LT samples were classified with ≤70% overall accuracy. Vis-NIRS measurements on fat and intact LT have potential to discriminate between corn and barley-fed beef.

None

• AB - Utile à l'AB
• FREDO alimentation animale
• FREDO qualité des produits
• SPECIES barley
• beef
• élevage

• NIRS
• PLS-DA
• support vector machine

Meat Science

172

108342

February 1, 2021

1 février 2021

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