The beef livestock system in Sardinia is based on suckler cows, often belonging to autochthonous breeds, such as the Sarda breed, and they often graze silvopastoral areas. Besides beef meat, silvopastoral systems (SPSs) provide several Ecosystem Services (ESs), such as timber provision, harvested as wood, and watershed protection. Livestock distribution is a critical factor for the sustainable use of SPSs (e.g., to avoid uneven grazing patterns) and information on patterns of spatial use are required. A study was conducted to determine: (i) the spatial distribution and (ii) the habitat selection of Sarda cattle grazing in a Mediterranean silvopastoral area. Over different seasons, 12 free-roaming adult Sarda cows were fitted with Global Positioning System (GPS) Knight tracking collars to calculate an index mapping of the incidence of livestock in the landscape (LRI) and a preference index (PI) for different areas. Since the PI data were not normally distributed, the Aligned Rank Transform (ART) procedure was used for the analysis. LRI was able to represent the spatial variability in resource utilization by livestock as a LRI map. Overall, the areas where the animals drank and received supplementation were strongly preferred by the cows, reaching PI values in the summer of 19.3 ± 4.9 (median ± interquartile range), whereas areas with predominantly rocks were strongly avoided (the worst PI value in the spring was 0.2 ± 0.6). Grasslands were, in general, used in proportion to their presence in the area, with slightly increased use in the spring (PI 1.1 ± 0.5). Forest area was avoided by cows, except in the spring when it was used in proportion to their presence in the area.

This work evaluated the reliability of the multivariate statistical analysis to discriminate the feeding system and the species of ruminants using their intramuscular fatty acids (FA) profile. FA composition of 53 meat samples (longissimus dorsi muscle) from animals of different species (sheep and cattle) raised with different feeding systems (pasture and stall-fed) (4 groups overall) was determined and expressed as % fatty acid methyl ester (FAME). A stepwise discriminant analysis (SDA) was applied to the full set of FA to select the variables that best discriminated between feeding systems and animal species. The selected variables were then submitted to a canonical discriminant analysis (CDA) to test the ability of those variables in discriminating against the four groups. Discriminant analysis (DA) was then exploited to classify meat samples. From the 62 initial variables detected in the FA profile, 24 were retained in the SDA. The subsequent CDA developed by using the selected variables, significantly discriminated the four groups (Hotelling's test p < 0.0001) by extracting three canonical functions. Heptadecenoic acid C17:1 c10, seemed to play a pivotal role both in discriminating species and feeding system while some 18:1 isomers (C18:1 c12, C18:1 c13 C18:1 t13/t14) together with CLA c9, t11 and ω-3 were important in discriminating feeding systems. Multivariate statistical analysis of FA was able to track both the species and the feeding system of source animals with good accuracy.

Context: Recent heightened interest of consumers in the origins of their food, together with broader general awareness of environmental matters, has led to an increase in the demand for meat obtained from grazing systems. The importance of local breeds adapted to medium- and low-input production is fully recognised as a means of guaranteeing the sustainability of these farming methods. A finishing system based on pastures and the use of local breeds could both meet the demands of consumers and increase economic returns for Sardinian farmers. Aims: The work evaluated the effects of different finishing treatments (pasture PAS-0C vs hay–concentrate-based diets HAY-C) on the quality of meat from young Sarda bulls and the usefulness of meat chemicals as markers to discriminate between finishing systems. Methods: Twenty-eight young Sarda bulls were assigned randomly to the following two treatments: finished on natural pasture (PAS-0C group, n = 7), and fed on natural pasture hay ad libitum and concentrate (HAY-C group, n = 21). The latter group comprised three levels characterised by an increasing daily dose of concentrates, as follows: 2.5 kg/animal (HAY-2.5C), 3.3 kg/animal (HAY-3.3C), and ad libitum (HAY-ALC). After slaughter at a fixed age (416 ± 25 days), carcass yield, pH of the Longissimus thoracis (LT) muscle, colour parameters, cooking loss, proximate analysis, α-tocopherol and cholesterol concentration, and fatty acid composition of intramuscular fat of LT were all determined. The discriminating power of the meat chemicals between the two main finishing systems (PAS-0C vs HAY-C) and among the three groups receiving concentrates and hay (HAY-2.5C, HAY-3.3C and HAY-ALC) was assessed using linear discriminant analysis. Key results: Pasture-based treatment decreased the intramuscular fat and increased the α-tocopherol concentration of meat and the proportion of some desirable fatty acids (α-linolenic acid and its derivatives eicosapentaenoic acid, docosapentaenoic acid), and improved the value of the ratio of n-6:n-3, without affecting the ultimate pH, colour parameters, and cooking loss. The discriminant procedure was able to discriminate accurately between the two main finishing systems and among the three groups receiving concentrate and hay (P < 0.0001 and P < 0.005 of the Hotelling’s T-squared test respectively). The concentration of α-tocopherol was key to the discrimination of the two main finishing systems, whereas the content of C17:0 and C18:0i were particularly effective in discriminating among the three groups fed with hay concentrate. Conclusions: Grazing improves some of the meat traits of young Sarda bulls compared with the effects of a hay-concentrate-based finishing diet. The concentration of α-tocopherol in meat is an effective marker for discriminating the effects of pasture from those of a concentrate-based finishing diet Implications: The results highlight the role of pasture-based diet in finishing young Sarda bulls, and could provide a wealth of knowledge for Sardinian beef farmers for delivering meat produce that stands out in the market and meets the demand of consumers more concerned about food origin and its healthiness.

Knowledge of how grazing cattle utilize heterogeneous landscapes in Mediterranean silvopastoral areas is scarce. Global positioning systems (GPS) to track animals, together with geographic information systems (GIS), can relate animal distribution to landscape features. With the aim to develop a general spatial model that provides accurate prediction of cattle resource selection patterns within a Mediterranean mountainous silvopastoral area, free-roaming Sarda cows were fitted with GPS collars to track their spatial behaviors. Resource selection function models (RSF) were developed to estimate the probability of resource use as a function of environmental variables. A set of over 500 candidate RSF models, composed of up to five environmental predictor variables, were fitted to data. To identify a final model providing a robust prediction of cattle resource selection pattern across the different seasons, the 10 best models (ranked on the basis of the AIC score) were fitted to seasonal data. Prediction performance of the models was evaluated with a Spearman correlation analysis using the GPS position data sets previously reserved for model validation. The final model emphasized that watering point, elevation, and distance to fences were important factors affecting cattle resource-selection patterns. The prediction performances (as Spearman rank correlation scores) of the final model, when fitted to each season, ranged between 0.7 and 0.94. The cows were more likely to select areas lower in elevation and farther from the watering point in winter than in summer (693 ± 1 m and 847 ± 13 m vs. 707 ± 1 m and 635 ± 21 m, respectively), and in spring opted for the areas furthest from the water (963 ± 12). Although caution should be exercised in generalizing to other silvopastoral areas, the satisfactory Spearman correlations scores from the final RSF model applied to different seasons indicate resource selection function is a powerful predictive model. The relative importance of the individual predictors within the model varied among the different seasons, demonstrating the RSF model’s ability to interpret changes in animal behavior at different times of the year. The RSF model has proven to be a useful tool to interpret the spatial behaviors of cows grazing in Mediterranean silvopastoral areas and could therefore be helpful in managing and preserving ecosystem services of these areas.