Comparative Analysis of Milk Urea Nitrogen and FCR in Indigenous Goats under Silvopastoral Systems

Abstract

Efficient nutrient utilization and feed management are critical for improving productivity in small ruminant systems, particularly under sustainable land-use practices such as silvopastoral systems. This study presents a comparative analysis of milk urea nitrogen (MUN) and feed conversion ratio (FCR) in indigenous goats reared under silvopastoral systems to evaluate their nutritional efficiency and production performance. The proposed methodology involves controlled field observations across different silvopastoral setups, integrating measurements of feed intake, milk yield, body weight changes, and forage composition. Key indicators such as MUN levels are analyzed to assess protein metabolism efficiency, while FCR is calculated to determine feed utilization effectiveness. Additional parameters, including forage quality, soil fertility, and environmental conditions, are monitored to understand system-level interactions. The collected data are preprocessed through cleaning, normalization, and statistical validation to ensure consistency and reliability. Advanced analytical and machine learning models, including regression analysis, Random Forest, and Artificial Neural Networks, are employed to evaluate the relationships between feeding strategies, metabolic indicators, and production efficiency. Experimental results indicate that silvopastoral systems enhance feed quality and nutrient availability, leading to optimal MUN levels that reflect efficient protein utilization. Improved FCR values are observed compared to conventional grazing systems, indicating better conversion of feed into milk and body mass. The study also highlights the role of diversified forage species in stabilizing nutrient intake and improving overall animal performance. The findings demonstrate that silvopastoral systems provide a sustainable and efficient approach for optimizing goat productivity. The study concludes that integrating advanced analytical methods with sustainable grazing systems offers a scalable solution for improving nutrient efficiency, animal health, and farm profitability.