This paper presents an analysis of tractors used in combination with feed harvesting machines, enhanced by artificial intelligence (AI) technologies. The study explores how AI integration improves the operational efficiency, fuel consumption, and overall performance of tractor-harvester aggregates. By utilizing AI-driven data analytics and predictive maintenance, tractors can optimize their functions to adapt to varying field conditions, reduce downtime, and increase productivity. Additionally, AI-based control systems enable precise coordination between tractors and harvesting machines, resulting in smoother operation and minimized crop loss. The research also highlights the environmental benefits of AI-assisted machinery through better fuel efficiency and reduced emissions. The findings suggest that implementing AI in agricultural machinery significantly enhances the sustainability and effectiveness of feed harvesting operations, offering valuable insights for modern farming practices.

tractor, forage machines, unit, efficiency, operation, technical analysis

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