Czech Journal of Animal Science - In Press
Effects of manganese supplementation to diets containing flaxseed oil on performance, antioxidant status, serum lipids, and egg fatty acid profile in aged laying hensOriginal Paper
Israa Saddam Mohammed Al-Moussawi, Seyyed Ali Mirghelenj, Mohsen Daneshyar, Hamed Khalilvandi Behrouzyar, Hamzeh Ghaderi Chaparabad, Motaleb Ebrahimi
The present study was conducted to investigate the effect of manganese (Mn) methionine supplementation in diets containing different levels of flaxseed oil (FO) on performance, blood and liver antioxidant parameters, serum lipid parameters, and egg fatty acid profile in laying hens. For this purpose, 288 laying hens were used in a completely randomised design with a 2×3 factorial arrangement, comprising six replications with eight birds in each. The experimental treatments included diets containing three levels of FO (0, 1.5, and 3% of the diet) and two levels of Mn–methionine (0 and 80 mg/kg of the diet). The results showed that hens treated with 3% FO, with or without Mn, had the highest egg production and egg weight, which were significantly greater than those of hens fed diets without FO (P < 0.05). The synergistic effects of FO and Mn indicated that FO at concentrations of 1.5% and 3%, in combination with Mn, significantly reduced triglyceride and LDL levels (P < 0.05). Diets containing 1.5 and 3% FO decreased the total antioxidant capacity of the liver and serum, while the use of 80 mg Mn increased the aforementioned parameters. The percentage of polyunsaturated fatty acids (PUFA), the ratio of PUFA to saturated fatty acids, and the percentage of ω-3 fatty acids increased significantly with the higher inclusion levels of FO in the diet (P < 0.05). In general, the inclusion of 3% FO in the diet of laying hens is recommended to improve performance while reducing serum lipid parameters and enhancing the fatty acid profile of eggs; however, the supplementation of Mn as an antioxidant is necessary to prevent lipid peroxidation.
Decision Support Systems in Dairy Cows Farming: A 20-Year Scoping Review of Characteristics, Applications, and Future ChallengesReview
Jan Saro, Jaromír Ducháček, Luděk Stádník, Helena Brožová
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 analyzes 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 specialized 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 specialized 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 optimize dairy farming.