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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://dirros.openscience.si/IzpisGradiva.php?id=29164"><dc:title>From mechanization to autonomy:</dc:title><dc:creator>Kostkin,	Mikhail	(Avtor)
	</dc:creator><dc:creator>Vavpotič,	Žiga	(Avtor)
	</dc:creator><dc:creator>Agalar,	M. Fethi	(Avtor)
	</dc:creator><dc:creator>Germšek,	Blaž	(Avtor)
	</dc:creator><dc:creator>Öz,	Sabri	(Avtor)
	</dc:creator><dc:subject>autonomous agriculture</dc:subject><dc:subject>agrocycle</dc:subject><dc:subject>agricultural robotics</dc:subject><dc:subject>digital twin farming</dc:subject><dc:subject>sustainable farming systems</dc:subject><dc:subject>precision agriculture</dc:subject><dc:subject>soil compaction</dc:subject><dc:subject>energy efficiency</dc:subject><dc:subject>robotic field operations</dc:subject><dc:description>This study examines the transition from conventional agricultural mechanization to autonomous robotic farming through the conceptual lens of the agrocycle, a holistic framework that integrates all agricultural operations across the full production year into a continuous, data-driven system. Rather than evaluating isolated field tasks, the agrocycle treats soil preparation, crop management, plant protection, pruning, and harvesting as interdependent components of a single adaptive operational loop. Within this framework, the performance of the PeK Automotive autonomous robotic platform (Slopehelper agrosystem) is empirically compared with a conventional tractor–implement system under comparable field conditions. Field experiments were conducted in temperate Central European vineyard and orchard systems, combining quantitative indicators—such as energy consumption, operational time, positional precision, soil compaction, and CO₂ emissions—with system-level indices including Operational Efficiency, Continuity, and System Resilience. Results demonstrate that the autonomous system achieved up to a 96% reduction in energy consumption per hectare, a 72% decrease in soil compaction, and the complete elimination of local CO₂ emissions. Despite slightly longer task durations in some operations, overall agrocycle feasibility and cost efficiency improved by more than threefold due to the absence of labor costs, optimized energy use, and uninterrupted autonomous operation. Beyond performance gains, the findings highlight a fundamental shift in agricultural systems logic. Autonomy, when embedded within the agrocycle framework, transforms farming from task-based mechanization toward a cyber-physical, self-optimizing production system aligned with the principles of Agriculture 5.0. The study concludes that the agrocycle represents both a practical and conceptual pathway toward resilient, subsidy-independent, and climate-resilient agricultural production, demonstrating that the move from mechanization to autonomy is not merely a technological substitution but a systemic transformation of modern agriculture.</dc:description><dc:date>2026</dc:date><dc:date>2026-04-22 14:06:29</dc:date><dc:type>Neznano</dc:type><dc:identifier>29164</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
