Table olives are harvested traditionally by hand to maintain a high quality standard for the market. The labor shortage and the rising costs have driven the harvesting process towards its mechanization, despite the lower quality of the fruits harvested with trunk and branch shakers. Impact absorbing materials, such as polymers, can be used to mitigate damages from impacts to the harvesting machine collecting system, which is usually a reversed umbrella. In this work, an energy-based approach for the selection of cushioning materials to be installed on the harvesting machine is proposed exploiting drop testing experiments and image analysis techniques

An Energy-Based Approach to Cushioning Material Selection for Table Olive Mechanical Harvesting / Annessi, Alessandro; Belluccini, Francesco; Medici, Vittoria; Giorgi, Veronica; Lodolini, Enrico Maria; Martarelli, Milena; Castellini, Paolo; Neri, Davide. - (2025), pp. 13-18. (Intervento presentato al convegno 2024 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor tenutosi a Padua, Italy nel 29-31 October 2024) [10.1109/metroagrifor63043.2024.10948869].

An Energy-Based Approach to Cushioning Material Selection for Table Olive Mechanical Harvesting

Annessi, Alessandro
;
Belluccini, Francesco;Medici, Vittoria;Giorgi, Veronica;Lodolini, Enrico Maria;Martarelli, Milena;Castellini, Paolo;Neri, Davide
2025-01-01

Abstract

Table olives are harvested traditionally by hand to maintain a high quality standard for the market. The labor shortage and the rising costs have driven the harvesting process towards its mechanization, despite the lower quality of the fruits harvested with trunk and branch shakers. Impact absorbing materials, such as polymers, can be used to mitigate damages from impacts to the harvesting machine collecting system, which is usually a reversed umbrella. In this work, an energy-based approach for the selection of cushioning materials to be installed on the harvesting machine is proposed exploiting drop testing experiments and image analysis techniques
2025
979-8-3503-5544-4
979-8-3503-5545-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/343944
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