Revista UIS Ingenierías

Vol. 24 Núm. 3 (2025): Revista UIS Ingenierías
Artículos

Evaluación de la madurez del banano usando aprendizaje de máquinas basado en reconocimiento de imágenes – Revisión

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  • Cristhian David López- Jiménez,
  • Luis Octavio González- Salcedo,
  • Luis Eduardo Ordóñez-Santos
Cristhian David López- Jiménez
Universidad Nacional de Colombia
Luis Octavio González- Salcedo
Universidad Nacional de Colombia
Luis Eduardo Ordóñez-Santos
Universidad Nacional de Colombia
DOI: https://doi.org/10.18273/revuin.v24n3-2025003

Publicado 2025-08-22

Palabras clave

  • color,
  • inteligencia artificial,
  • aprendizaje automático,
  • visión computacional,
  • red neuronal artificial

Cómo citar

López- Jiménez, C. D., González- Salcedo, L. O., & Ordóñez-Santos, L. E. (2025). Evaluación de la madurez del banano usando aprendizaje de máquinas basado en reconocimiento de imágenes – Revisión. Revista UIS Ingenierías, 24(3), 29–42. https://doi.org/10.18273/revuin.v24n3-2025003

Derechos de autor 2025 Revista UIS Ingenierías

Creative Commons License

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Resumen

En este trabajo se realiza una revisión sistemática de la literatura sobre las diferentes técnicas de aprendizaje de máquinas utilizadas para la evaluación de la madurez de las frutas, específicamente del banano (Musa spp.), mediante el reconocimiento de imágenes. Los resultados muestran que existen diversas técnicas de aprendizaje de máquinas, como máquinas de soporte vectorial, redes neuronales artificiales, y árboles de decisiones, entre otras. Se encontró que estas técnicas son capaces de analizar imágenes digitales de las frutas, extraer características y patrones relevantes, y realizar la clasificación y regresión para la determinación de la madurez de las mismas. Se concluye que las técnicas de aprendizaje de máquinas basadas en reconocimiento de imágenes, son una herramienta efectiva no invasiva, rápida y precisa. Su implementación en la cadena agroindustrial del banano permitiría optimizar la cosecha, clasificación y distribución del fruto, mejorando la eficiencia del proceso productivo, reduciendo pérdidas postcosecha y garantizando una mayor calidad y uniformidad del producto para su comercialización, especialmente en mercados de exportación.

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