Predicting Beef Fatty Acid Composition from Diet and Plasma Profiles Using Multivariate Models
Articolo
Data di Pubblicazione:
2025
Citazione:
Predicting Beef Fatty Acid Composition from Diet and Plasma Profiles Using Multivariate Models / Acciaro, Marco; Sulas, Leonardo; Carta, Gianfranca; Banni, Sebastiano; Murru, Elisabetta; Manca, Claudia; Dimauro, Corrado; Fiori, Myriam; Cabiddu, Andrea; Re, Giovanni Antonio; Molinu, Maria Giovanna; Piluzza, Giovanna; Giovanetti, Valeria. - In: ANIMALS. - ISSN 2076-2615. - 15:20(2025). [10.3390/ani15202969]
Abstract:
The nutritional quality of beef depends largely on the fats it contains, which is strongly
influenced by the animals’ diet. Traditionally, evaluating these traits requires slaughtering,
but this study tested a less invasive approach based on blood analysis. Young cattle were
raised either on natural pastures or with hay- and concentrate-based diets. The results
showed that key dietary components, especially natural antioxidants found in pasture
plants and the fat fraction of the feed, play an important role in determining the meat
composition. Diets richer in antioxidants were associated with higher levels of healthpromoting
fats, such as omega-3 fatty acids and conjugated linoleic acid, known for their
benefits to human health. Blood plasma analysis proved to be a reliable predictor of these
traits, allowing the meat quality to be monitored without killing the animal. This innovative
strategy could help farmers improve sustainability, increase product value, and provide
consumers with healthier beef.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
pasture; stall; phenolic compounds; fatty acids; partial least square regression; canonical correlation; plasma; meat
Elenco autori:
Acciaro, Marco; Sulas, Leonardo; Carta, Gianfranca; Banni, Sebastiano; Murru, Elisabetta; Manca, Claudia; Dimauro, Corrado; Fiori, Myriam; Cabiddu, Andrea; Re, Giovanni Antonio; Molinu, Maria Giovanna; Piluzza, Giovanna; Giovanetti, Valeria
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