the agrocycle as a framework for sustainable robotic farming

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.

Authors

Publication Details

Journal
DiRROS repository (University of Maribor)
Published
2026-04-25
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

the agrocycle as a framework for sustainable robotic farming

Михаил Косткин, Sabri Öz, Blaž Germšek, Žiga Vavpotič et al.
DiRROS repository (University of Maribor)
Smart Agriculture and AI
article

the agrocycle as a framework for sustainable robotic farming

Михаил Косткин, Sabri Öz, Blaž Germšek, Žiga Vavpotič, M. Fethi Agalar
article en

Abstract

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.

DiRROS repository (University of Maribor)
Zero hunger
Openalex Percentile: Top 6%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

the agrocycle as a framework for sustainable robotic farming — Михаил Косткин, Sabri Öz, et al. · DiRROS repository (University of Maribor) (2026) | TGRS Research Map | TGRS