Anna Pinna

Dr. Anna Pinna

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 August 2025 in Foods
Verified
Journal Article
Open access
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PFPaolo Ferrari
Paolo Ferrari
ABAndrea Bertolini
Andrea Bertolini
AGAnna Garavaldi
Anna Garavaldi
VFValerio Faeti
Valerio Faeti
MBMonica Bergamaschi
Monica Bergamaschi
RVRoberta Virgili
Roberta Virgili
Consumer demand for high-quality products, combined with expectations for more sustainable production systems and animal welfare, is driving major changes in livestock farming practices. It is known that space allowance plays a central role in pig welfare, promoting resting and reducing the incidence of injuries and stress-related behaviors; however, there is little scientific evidence on the effect that available space has on the carcass and meat quality. In this study, space allowances were compared, in both an indoor conventional system (1.15, 1.9 and 3 m2/pig) and an indoor organic system with outdoor access (1.4 + 1, 2.6 + 2 and 3.9 + 3 m2/pig). The increase in space available for pigs had no effect on pig performance, carcass and meat quality characteristics, such as pH, drip and cooking loss. However, lowering stocking density in the conventional indoor housing system improved meat tenderness, as assessed by the Slice Shear Force test, while no difference was found between meat tenderness in organic pigs raised with three different stocking densities. Increased space allowance per pig reduced n-3 fatty acids in pig loins from both housing systems and n-6 fatty acids and PUFAs in loins from pigs reared in the organic housing system with both indoor and outdoor space.

10 April 2026 in Foods
Verified
Journal Article
Open access
PDF file
Anna PinnaAnna Pinna
Anna Pinna
RFRosaria Fragni
Rosaria Fragni
RVRoberta Virgili
Roberta Virgili
CLCecilia Loffi
Cecilia Loffi
IRIsabel Revilla
Isabel Revilla
PFPaolo Ferrari
Paolo Ferrari
European pork production pursues traceability and authenticity to ensure animal welfare, food safety, and support products with geographical indications. This study reports a European survey integrating stable isotope ratios (δ13C, δ15N, δ34S, δ18O, δ2H) and multi-element profiling using IRMS and ICP-MS, on 612 samples collected across Denmark, Poland, Italy, and Spain, with diverse production systems, breeds, feeding, and slaughter ages. Geographical and climatic gradients influenced δ2H and δ18O, which ranged from −111‰ to −89‰ in samples from Denmark and Spain and from 13.3‰ to 16.0‰ in samples from Italy and Spain, respectively. In selected farms, δ13C ranged from −22.7‰ to −17.0‰ depending on diet composition based on C3 and C4 plants. The wide variability in pig management practices suggested that δ15N (2.50 ÷ 4.96‰) increased with slaughter age and was positively correlated with Fe (3.38 ÷ 8.39 mg/kg) and Zn (9.39 ÷ 23.6 mg/kg). Most mineral components were mainly driven by feed formulation and supplementation. Principal component analysis (PCA) showed that samples were grouped based on their origin and husbandry system, confirming the key role of isotopic and elemental markers for the development of a database supporting the pork supply chains across Europe.

5 September 2026 in SSRN Electronic Journal
Verified
Preprint
Open access
ZFZuzanna Fendor
Zuzanna Fendor
ACAndrea Jr. Carnoli
Andrea Jr. Carnoli
RHRosan Hobé
Rosan Hobé
WHWouter Hoenderdaal
Wouter Hoenderdaal
MCMathilde Coutant
Mathilde Coutant
EAEsther van Asselt
Esther van Asselt
Consumer demands and EU policies on animal welfare have resulted in the extensification of animal husbandry systems reflected in increased space, different breeds, feed adaptations and enrichment options. Apart from impacting animal welfare, such changes may impact the quality of the meat. However, since extensive farming comprises a range of husbandry systems and factors, it is difficult to draw generalized conclusions on husbandry-meat quality relations. The complex nature asks for a data-driven approach. Therefore, the aim of this study was to use machine learning models to establish relations between pork quality characteristics and husbandry extensification factors grouped into: space, genetics, feed, and enrichment. The models were trained to distinguish the different levels of the four extensification factors using the physicochemical properties of the meat and the country of origin. The highest performance of the model was achieved by the model for the genetics factor, followed by the diet factor, the space allowance and the quality of space. The model performance used as a proxy for the strength of the relation revealed the most pronounced differences between indigenous and conventional breeds. Further analysis of the genetics factor model using model-agnostic explainable artificial intelligence uncovered that its predictions were mostly based on the country of origin, moisture, L*, and EZ-DripLoss. These results provide insights into likely links between the physicochemical properties of pork and the extensification factors for which the causal relations can be tested in future research.