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Técnicas de procesamiento digital de imágenes para detección de plagas y enfermedades en cultivos: una revisión

dc.contributor.authorGómez Camperos, July Andrea
dc.contributor.authorJaramillo, Haidee Yulady
dc.coverage.spatialColombiaen_US
dc.date.accessioned2025-10-21T19:58:30Z
dc.date.available2025-10-21T19:58:30Z
dc.date.issued2022-01-15
dc.identifier.issn0123-3033en_US
dc.identifier.urihttps://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/5851
dc.description.abstractLa detección adecuada de plagas y enfermedades en la producción de cultivos es fundamental para aumentar la producción agrícola de forma sostenible. Es por esta razón, que se incorpora el término Agricultura 4.0, la cual integra un conjunto de tecnologías, dispositivos, protocolos y paradigmas computacionales para mejorar los procesos agrícolas. La información sobre las condiciones climáticas, suelos, enfermedades, insectos, semillas, fertilizantes, constituye una importante contribución al desarrollo económico y sostenible de este sector. Las técnicas de procesamiento digital de imágenes son una herramienta que permite la identificación temprana de las plagas o enfermedades en los cultivos como: cereales, frutales, raíces, hojas y tubérculos; y de esta forma, mitigar pérdidas económicas en el sector agrícola. A nivel mundial, alrededor del 40% de los cultivos son desechados por diversas ISSN: 0123-3033 –ISSN-e: 2027-8284 enfermedades y plagas. En la mayoría de los casos, las enfermedades de los cultivos producen síntomas y características visibles durante el crecimiento de las plantas. Debido a la escasez de tecnologías utilizadas en los cultivos, el diagnóstico de las enfermedades y plagas se soporta en gran parte en la inspección humana, generando errores ocasionados por la subjetividad de los individuos. La presente revisión de literatura se llevó a cabo con la finalidad de identificar diferentes técnicas de procesamiento digital de imágenes para la prevención de plagas y enfermedades en cultivos de los diferentes sectores agrícolas. Los resultados demostraron que el sistema de diagnóstico está compuesto de la adquisición de imágenes, preprocesamiento de imágenes, la segmentación, la extracción de características, la selección de características y la posterior clasificación de las plagas o enfermedades; asimismo, se presentan las tendencias y desafíos actuales en la temática.en_US
dc.language.isoengen_US
dc.relationhttps://revistaingenieria.univalle.edu.co/index.php/ingenieria_y_competitividad/article/view/10973en_US
dc.titleTécnicas de procesamiento digital de imágenes para detección de plagas y enfermedades en cultivos: una revisiónen_US
dc.title.translatedDigital image processing techniques for detecting pests and diseases in crops: a reviewen_US
dc.contributor.cvlacJuly Andrea Gómez Camperos [0001164287]en_US
dc.contributor.cvlacHaidee Yulady Jaramillo [0001604237]en_US
dc.contributor.cvlacGustavo Guerrero Gómez [0001413037]en_US
dc.contributor.googlescholarGustavo Guerrero Gómez [La8nZsAAAAAJ]en_US
dc.contributor.orcidJuly Andrea Gómez Camperos [0000-0003-3894-144X]en_US
dc.contributor.orcidHaidee Yulady Jaramillo [0000-0002-4185-119X]en_US
dc.contributor.orcidGustavo Guerrero Gómez [0000-0002-4316-7113]en_US
dc.contributor.scopusJuly Andrea Gómez Camperos [57220550902]en_US
dc.contributor.scopusHaidee Yulady Jaramillo [57205118794]en_US
dc.contributor.scopusGustavo Guerrero Gómez [57205119123]en_US
dc.description.abstractenglishProper detection of pests and diseases in crop production is essential to increase agricultural production in a sustainable way. For this reason, the term Agriculture 4.0 is incorporated, which integrates a set of technologies, devices, protocols, and computational paradigms to improve agricultural processes. Information on climatic conditions, soils, diseases, insects, seeds, fertilizers. It constitutes an essential contribution to the economic and sustainable development of this sector. Digital image processing techniques are a tool that allows early identification of pests or diseases in crops such as cereals, fruit trees, roots, leaves, and tubers mainly. In this way, mitigate economic losses in the agricultural sector. Globally, about 40% of crops are discarded by various diseases and pests. In most cases, crop diseases produce visible symptoms and characteristics during plant growth. Due to the scarcity of technologies used in crops, the diagnosis of diseases and pests is supported mainly by human inspection, generating errors caused by the subjectivity of individuals.This literature review was carried out to identify different digital image processing techniques for pests and disease prevention in crops from different agricultural sectors. The results showed that the diagnostic system is composed of the acquisition of images, pre-image processing, segmentation, characteristics extraction, characteristics selection, and the subsequent classification of pests or diseases. Likewise, current trends and challenges on the subject are presented.en_US
dc.subject.proposalagriculturaen_US
dc.subject.proposalcultivoen_US
dc.subject.proposalenfermedaden_US
dc.subject.proposalprocesamiento de imágenesen_US
dc.subject.proposalplagaen_US
dc.subject.keywordsagricultureen_US
dc.subject.keywordscropen_US
dc.subject.keywordsdiseaseen_US
dc.subject.keywordsimage processingen_US
dc.subject.keywordsplagueen_US
dc.publisher.facultyFacultad ingenieríasen_US
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTen_US
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dc.identifier.DOIhttps://doi.org/10.25100/iyc.v24i1.10973en_US


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