Simulation of an Automated Tahitian Lemon Grading System Based on Computer Vision

• Autores: Valenzuela Lino, Yadhira Samhira, Ortiz Zacarias, Jhon Rodrigo, Sullca Mendoza, Yordan Cesar, Del Carpio Ramirez, Sliver Ivan, Moggiano Aburto, Nabilt Jill, Coaquira Rojo, Carlos Alberto
• Formato: tesis de grado
• Fecha de Publicación: 2024
• Institución: Universidad Continental
• Repositorio: CONTINENTAL-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.continental.edu.pe:20.500.12394/14442
• Enlace del recurso: https://hdl.handle.net/20.500.12394/14442; https://doi.org/10.1109/UEMCON54665.2022.9965667
• Nivel de acceso: acceso abierto
• Materia: Simulación; Control de procesos; Automatización industrial; https://purl.org/pe-repo/ocde/ford#2.03.00

Lemon exports are of great influence in Peru, since there is a great demand from countries such as the USA, Belgium and Holland. For this reason, the agricultural sector is one of the essential factors for the economic development of the country, since it generates S/29,553 million annually throughout the national territory. On the other hand, Peru offers two types of lemons, for example: the Tahitian lemon and the subtle lemon; however, due to its characteristics, the Tahitian lemon is the one that is sent as an export product worldwide. Currently, the selection process of this fruit is done manually, since there are not enough industrial optimizations in its process. Therefore, the present study aims to carry out the simulation of an automated grading system for Tahitian lemon based on computer vision. The selection parameters for the image processing were established as the levels of ripeness of the lemon: early ripening, medium ripening, ripe and stale. This selection was implemented due to the need to comply with the quality standards required by the Free Trade Agreements (FTA). As a result, the selection simulation was obtained through a conveyor belt, where the fruit passed through the computer vision, which determined the route of the fruit. Finally, it was concluded that through automation it is possible to optimize the selection time of food products.