Integrating Field Experiments and Multi-Criteria Decision Modelling for Sustainable Mechanisation: A Comprehensive Assessment of Olive Harvesting Technologies

Articles in Press

Document Type : Research Article- En

Authors

A. Bozorgi ¹

N. Banaeian ¹

M. Zangeneh ¹

Z. Yousefi ²

¹ Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Guilan, Iran

² Agricultural and Natural Resources Research and Education Center of Guilan, Province, Guilan, Iran

https://doi.org/10.22067/jam.2026.98934.1494

Abstract

Olive harvesting is one of the most labour-intensive operations in olive production, particularly in high-density orchards, where technology selection strongly affects productivity and sustainability. This study combines quantitative field experiments with a sustainability-oriented multi-criteria decision-making framework to evaluate three harvesting methods including hand rake, branch shaker, and over-the-row combine harvester, for Arbequina and Koroneiki cultivars in Iran. A factorial RCBD was implemented to measure harvesting loss, harvesting efficiency, harvesting rate, oil content, and chemical quality indices. Results showed significant differences among methods in harvesting loss, efficiency, and rate (P < 0.01). Hand rake achieved the highest harvesting percentage (100%) but also the highest fruit loss (3.33%). Branch shaker recorded the lowest fruit loss (1.12%) but only 53.8% efficiency. Combine harvester provided the highest harvesting rate (4429–5158 kg h⁻¹) and the greatest economic return, with benefit–cost ratios of 1.297 for Arbequina and 1.375 for Koroneiki. To integrate technical, economic, social, and environmental indicators, fuzzy AHP was used to compute criterion weights, and Grey Relational Analysis (GRA) was applied to rank alternatives. Combine harvester obtained the highest GRA score (0.812), followed by the shaker (0.774) and the hand rake (0.682). A comprehensive sensitivity analysis was conducted using ten weighting scenarios and four multi-criteria decision-making methods (GRA, TOPSIS, VIKOR, and ELECTRE), which confirmed the robustness of the rankings across different policy priorities. Also, scenario-based sensitivity analysis demonstrated that combine harvesters consistently ranked first under economic and technical priorities, while shakers became the preferred option in sustainability-oriented scenarios emphasising employment and reduced non-renewable energy use. These results confirm that no single harvesting method dominates across all performance dimensions. Proposed integrated framework provides a robust, evidence-based decision support tool for selecting olive harvesting technologies that balance operational efficiency, profitability, and long-term sustainability.

Keywords

Harvest performance indicators

Mechanisation of olive production

Multi-criteria decision-making

Scenario-based sensitivity analysis

Subjects

• Sustainability and Circular Bioeconomy, and Environmental Resilience

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Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

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