dc.contributor
Universitat Ramon Llull. IQS
dc.contributor.author
Cano-Lara, Miroslava
dc.contributor.author
López, Adolfo R.
dc.contributor.author
Rostro Gonzalez, Horacio
dc.contributor.author
Padilla-Medina, José Alfredo
dc.contributor.author
Barranco-Gutiérrez, Alejandro Israel
dc.date.accessioned
2025-05-14T11:40:13Z
dc.date.available
2025-05-14T11:40:13Z
dc.date.issued
2024-07-08
dc.identifier.issn
2076-3417
dc.identifier.uri
http://hdl.handle.net/20.500.14342/4587
dc.description.abstract
The orange (Citrus sinensis) is a fruit of the Citrus genus, which is part of the Rutaceae family. The orange has gained considerable importance due to its extensive range of applications, including the production of juices, jams, sweets, and extracts. The consumption of oranges confers several nutritional benefits, including flavonoids, vitamin C, potassium, beta-carotene, and dietary fiber. It is crucial to acknowledge that the primary quality criterion employed by consumers and producers is maturity, which is correlated with the visual quality associated with the color of the epicarp. This study proposes the implementation of a computer vision system that estimates the degree of ripeness of oranges Valencia using fuzzy logic (FL); the soluble solids content was determined by refractometry, while the firmness of the fruit was evaluated through the fruit firmness test. The proposed method was divided into five distinct steps. The initial stage involved the acquisition of RGB images. The second stage presents the segmentation of the fruit, which entails the removal of extraneous noise and backgrounds. The third and fourth steps involve determining the centroid of the fruit, and five regions of interest were obtained in the centroid of the fruit of the Citrus Color Index (CII), ranging from 3 × 3 to 11 × 11 pixels. Finally, in the fifth step, a model was created to estimate maturity, °Brix, and firmness using Matlab 2024 and the Fuzzy Logic Designer and Neuro-Fuzzy Designer applications. Consequently, a statistically significant correlation was established between maturity, degree Brix, and firmness, with a value greater than 0.9, using the Citrus Color Index (CII), which reflects the physical–chemical changes that occur in the orange.
dc.relation.ispartof
Applied Sciences. 2024;14(13):5953-5971
dc.rights
Attribution 4.0 International
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Citrus Color Index (CII)
dc.subject
fuzzy logic (FL)
dc.title
Fuzzy Classification of the Maturity of the Orange (Citrus × sinensis) Using the Citrus Color Index (CCI)
dc.type
info:eu-repo/semantics/article
dc.description.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
https://doi.org/10.3390/app14135953
dc.rights.accessLevel
info:eu-repo/semantics/openAccess