Abstract
Poultry meat is an important part of the human diet, and the valorisation of autochthonous breeds is a determinant for the sustainability of the rural areas. The increasing demand for niche products demands for better knowledge of the carcass characteristics and meat quality of these local populations. The present study aims to characterise the roosters' meat from the "Branca" (BR), "Amarela" (AM), "Pedrês Portuguesa" (PP), and "Preta Lusitânica" (PL) breeds. A total of 80 birds (n = 20 per breed) between 38 and 42 weeks old were slaughtered. The physicochemical and nutritional composition were determined in the breast and drumstick meat. The meat of the PL breed had a higher (p ≤ 0.05) pH value, the AM meat revealed a water-holding capacity (WHC) of superior value and moisture content (p ≤ 0.05), while the BR breed had the highest (p ≤ 0.05) ash content. On the other hand, it was observed that the PP meat had a higher (p ≤ 0.05) yellowness index (b*). The breast meat exhibited, in all breeds, a lower pH value, WHC, redness (a*), and lipid content and greater (p ≤ 0.05) lightness (L*), b*, moisture, and ash and protein contents compared to the drumstick. Furthermore, it presented higher (p ≤ 0.05) K, P, and Mg contents and a superior proportion of total and sensorial relevant amino acids. Regarding the fatty acid profile, the breed differences were more significant in the drumstick, with the AM breed lipids presenting a higher (p ≤ 0.05) percentage of MUFAs in the fat, a lower atherogenic index, and a higher (p ≤ 0.05) value for the hypocholesterolemic/hypercholesterolemic fatty acids ratio, while the BR breed lipids presented a higher (p ≤ 0.05) percentage of PUFAs and PUFAs/SFAs ratio and a lower n-6/n-3 ratio. Considering the results obtained, it can be concluded that the meat from these breeds is a wholesome dietary option, distinguished by a favourable overall nutritional composition marked by elevated protein content, reduced lipid amounts, and amino and fatty acid profiles with desirable nutritional indices.