Cleaning system, batch sorting and traceability between field-industry in the mechanical harvesting of table olives

• DOI: 10.1016/j.postharvbio.2023.112278
• Publication Date: 2023-02-03T23:26:55Z
• Authors: Sergio Bayano-Tejero; Diego Martínez-Gila; Gregorio Blanco-R...; Rafael R. Sola-Gu...
• Keywords: 330; Sorting machine; Batches Quality; Traceability; Post-harvesting; 04 agricultural and veterinary sciences; Batches; 0405 other agricultural sciences; Quality

The table olive sector, there is no cleaning and fruit sorting by quality in the field of the harvested olive batches, nor is there an exhaustive recording of traceability. As a result, the batches are stored and shipped dry, dirty and with fruit of different qualities. When they arrive at the industry, they are cleaned and sorted according to their quality, maturity index and size into fruit suitable for green or black processing and unsuitable for olive oil processing. Overall, all fruits are mixed regardless of their origin leading to loss or interruption of traceability, so that there are also inefficiencies in the logistical process. To offer a possible solution, this paper proposes a methodology and presents a prototype that enables cleaning and sorting based on quality at the field level, incorporating a liquid transport system to stop or reduce bruising and an application for recording traceability throughout the production cycle. This prototype has been tested in the laboratory with artificial olives to study the sorting algorithm and, subsequently, in field conditions in a harvesting campaign with real fruit. The algorithm reported a mean relative error of 9.02 ± 6.66%, 11.63 ± 9.61% and 10.31 ± 8.85% in the test with 3 predefined sizes and 3 different ripening stages evaluated. In the evaluation test of the fruit bruising with 2% and 10% of controlled damage, results of 2.67 ± 1.74% and 10.09 ± 4.55% respectively were obtained. In the field, the grading machine for small size olives removed 98% of small diameter fruit and the cleaning system worked efficiently. The percentage of correct sorting based on the maturity index reported 89.3% for ’A’ or suitable quality and 76.7% for ’B’ or unsuitable quality. The fruit bruising sorting reported acceptable results influenced by the randomness in the bruising and its positioning with respect to the artificial vision system. The application recorded the previous operations, the batches generated and their characteristics as well as transport to the industry with its associated variables. The methodology and prototype developed may represent an advance in the management of the quality and traceability of table olives from the field level, making the logistics function more efficient and supporting the industry.