Revista UIS Ingenierías

Vol. 23 Núm. 4 (2024): Revista UIS Ingenierías
Artículos

Integración de la inteligencia artificial y la agricultura de precisión en cultivos de café

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  • Cristian Andrés Hernández-Salazar,
  • Octavio Andrés González-Estrada,
  • Germán González-Silva
Cristian Andrés Hernández-Salazar
Universidad Industrial de Santander
Octavio Andrés González-Estrada
Universidad Industrial de Santander
Germán González-Silva
Universidad Industrial de Santander
DOI: https://doi.org/10.18273/revuin.v23n4-2024012

Publicado 2024-12-01

Palabras clave

  • Aprendizaje profundo,
  • FarmBot,
  • coffea arabica,
  • redes neuronales convolucional,
  • agricultura inteligente

Cómo citar

Hernández-Salazar, C. A. ., González-Estrada, O. A., & González-Silva, G. (2024). Integración de la inteligencia artificial y la agricultura de precisión en cultivos de café. Revista UIS Ingenierías, 23(4), 145–158. https://doi.org/10.18273/revuin.v23n4-2024012

Derechos de autor 2024 Revista UIS Ingenierías

Creative Commons License

Esta obra está bajo una licencia internacional Creative Commons Atribución-SinDerivadas 4.0.

Resumen

La inteligencia artificial (IA) está transformando el sector agroindustrial al facilitar tareas como la predicción del clima, la detección de plagas y enfermedades, y la optimización del uso de agua y fertilizantes. Estas aplicaciones no solo aumentan la eficiencia y sostenibilidad de los sistemas agrícolas, sino que también mejoran la productividad y la resiliencia frente al cambio climático. Este trabajo realiza una revisión sistemática sobre el uso de IA en la producción de café, analizando estudios encontrados en bases de datos reconocidas como Scopus, Web of Science, IEEE Xplore y Google Scholar. La búsqueda incluyó combinaciones de palabras como, "café" AND "machine learning", "inteligencia artificial" AND "agricultura de precisión", "detección de plagas" OR "redes neuronales", AND "sostenibilidad". Inicialmente se identificaron 452 artículos, de los cuales 85 cumplieron con los criterios de inclusión tras un riguroso proceso de selección y exclusión. La revisión identificó que las aplicaciones de IA en la producción cafetera se enfocan principalmente en la detección temprana de enfermedades como la roya del café mediante visión por computadora y redes neuronales convolucionales, la optimización de sistemas de riego inteligentes que integran sensores y algoritmos para reducir el consumo de agua hasta en un 20%, y el uso de robótica agrícola para mejorar la eficiencia operativa y disminuir la dependencia de mano de obra. Las tecnologías, además, fomentan prácticas más sostenibles y mejoran la trazabilidad en la cadena de suministro del café. Los resultados de esta revisión arrojan luces sobre cómo las técnicas de IA pueden optimizar la producción cafetera y contribuir al desarrollo de sistemas agrícolas más eficientes y sostenibles. Este trabajo ofrece un marco de referencia que puede ser útil para orientar investigaciones futuras y guiar a los productores hacia prácticas resilientes frente al cambio climático y las crecientes demandas de sostenibilidad.

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