Decision Support Systems in dairy cows farming: A 20-year scoping review of characteristics, applications, and future challenges

Decision Support Systems (DSS) streamline dairy farm management by addressing challenges in productivity, animal welfare, sustainability, and economics. Yet, their precise impact on dairy cattle farm operations remains unclear. This scoping review systematically analyses DSS applications in dairy farming using studies from Scopus and Web of Science published between 2005 and June 2025, following PRISMA-ScR guidelines. From 1 112 identified records, 84 studies were included, after deduplication and screening, and classified into four mutually exclusive primary categories, namely data-, model- and knowledge-driven and other specialised DSS. The findings revealed that DSS complexity increased over time, with model-driven systems dominating (40.5%), followed by data- (38.1%) and knowledge-driven (15.5%) DSS, while other specialised systems accounted for the remaining 6.0%. Temporal multi-label analysis also highlighted trends towards integrated methodologies, with 20 DSS combining data- and model-driven approaches. DSS are mainly applied in Animal Health and Welfare (48% model- and 32% data-driven) and in Farm Business and Management (54.5% model- and 22.7% data-driven). Consequently, the top data inputs are Animal Health & Performance (28.0%), Farm & Business (22.4%), and Environmental & Spatial Data (21.3%). The most commonly applied models are Mathematical/Deterministic (22.7%) and Simulation (13.6%) models, increasingly alongside ML techniques. Key challenges include data integration, real-farm validation, model interpretability, bias reduction, and practical usability. Bridging these gaps will enhance DSS effectiveness and strengthen their potential to optimise dairy farming.