Model-based Assessment of Manual Raspberry Harvesting Efficiency Using the CIOSTA Methodology in Tunnel-Grown Production Systems

Abstract The aim of this study was to assess how raspberry cultivar and work organization influence the efficiency of manual harvesting under intensive tunnel-grown production. The research was carried out in July and August 2022 on a 20-hectare plantation and included four cultivars: Kwanza, Malling Bella, Enrosadira, and Diamond Jubilee. The CIOSTA methodology was applied, combining detailed time measurements and full-day work observations, which enabled an indepth analysis of effective time, auxiliary time, transport time, and work losses. In July, the average total harvest time was 240.7 rbh·ha⁻¹, while in August it decreased to 153.2 rbh·ha⁻¹. The highest efficiency was recorded for the Diamond Jubilee cultivar (K 07 = 0.82), whereas the lowest values were observed for Malling Bella in July and Enrosadira in August. Transport-related activities accounted for the largest share of time losses, which is reflected in the transport utilization coefficient K t (0.43-0.44). The results indicate that harvest efficiency depends not only on the cultivar and its yield potential but also on work organization and internal logistics. The findings confirm that the structure of the harvesting proces-particularly transport Logistics-plays a key role in determining overall efficiency. The presented analysis provides valuable input data for developing simulation and optimization models that support the design of improved work organization solutions in horticultural farms. The study aligns with current research trends in organizational and logistical analysis within horticultural production and forms a basis for creating model approaches to soft-fruit harvesting systems.