Graphical AbstractFor image description, please refer to the figure legend and surrounding text.
Graphical AbstractFor image description, please refer to the figure legend and surrounding text.
Graphical AbstractFor image description, please refer to the figure legend and surrounding text.
The jejunum is the primary site for digestion, nutrient absorption, and protection from antigens and toxins, making its functional integrity during the post-weaning period a key determinant of growth performance in nursery pigs. Inflammatory and oxidative stress biomarkers in the jejunal mucosa are closely associated with growth performance and can serve as functional indicators of intestinal health under post-weaning conditions. Many biomarkers exhibit threshold responses, suggesting that variation below biologically meaningful breakpoints may have minimal impact on performance, whereas exceeding these thresholds results in performance reduction. Inflammatory and oxidative stress responses in the jejunum tend to impair growth prior to reductions in feed intake, cau-tioning that reliance on in-barn observations alone may underestimate early performance losses. Biomarkers should be interpreted within the appropriate biological context as understanding their relative sensitivity is imperative to early detection and subsequent intervention.
Graphical AbstractA full-scale, commercial model farm that offers opportunities for evaluation and demonstration of innovative practices that integrate the CGE management of Merino sheep with cropping, and the management of natural resources, the environment, and biodiversity. International relevance is ensured by connection to the Global Farm Platform (GFP). Created by E van Lier and GB Martin.For image description, please refer to the figure legend and surrounding text.
The integration of artificial intelligence (AI) into livestock farming represents a systemic transformation rather than a mere technological upgrade. This article examines the infrastructural, organisational, and cultural shifts required to make farms “AI-ready” and capable of harnessing digital innovations effectively. Key challenges include redesigning facilities to optimise sensor coverage and animal welfare, ensuring interoperability across data systems, and building robust technological infrastructures for real-time monitoring and predictive management. The transition demands new professional profiles, such as digital field operators and AI system managers, alongside continuous training to develop both technological skills and critical interpretative capacity. Cybersecurity emerges as a central concern, as digitalisation increases vulnerability to cyber threats, requiring strict governance of data access, device protection, and staff awareness. Moreover, AI adoption reshapes workflows: fixed routines give way to adaptive, data-driven decision-making processes, reducing stress on animals and enabling early detection of health or environmental risks. Collaboration also evolves, with consultants, researchers, and suppliers integrated into digital platforms for continuous, evidencebased support and co-development of AI solutions. The article argues that only a holistic approach-combining infrastructure redesign, workforce transformation, data standardisation, and secure digital ecosystems can ensure that AI delivers tangible benefits in sustainability, productivity, and animal welfare. Ignoring the systemic dimension of this change risks confining innovation to isolated pilot projects, whereas a strategic, inclusive adoption has the potential to position European livestock farming at the forefront of agri-food innovation.
Rangeland grazing systems cover a wide range of the world’s grazing lands, provide primary agricultural products, and are rich in natural and semi-natural vegetation that supports habitats with a high nature value. They are also important for socio-economic reasons. These systems, however, are coming under increasing pressure regarding efficiency and adaptation to climate change. Technological innovations have been recognised as part of the solution needed to address these challenges. This feature paper presents how a research and demonstration farm in Scotland (part of the Global Farm Platform Initiative) is developing a new digital vision for rangeland grazing systems to help tackle these issues. The vision includes ensuring rangeland livestock systems are fit for the 21st century, through monitoring livestock welfare and performance, natural capital and biodiversity metrics.
