Transformación digital: Evolución de las aplicaciones de inteligencia artificial en la industria del café

Esteban Largo Avila; Carlos Hernán Suárez Rodríguez; Edwin Arango Espinal

doi:10.14482/inde.43.01.445.864

Autores/as

Esteban Largo Avila Universidad del Valle (Colombia) https://orcid.org/0000-0001-6047-1523
Carlos Hernán Suárez Rodríguez Universidad del Valle (Colombia) https://orcid.org/0000-0002-1304-3646
Edwin Arango Espinal Universidad del Valle (Colombia) https://orcid.org/0000-0002-2231-3513

DOI:

https://doi.org/10.14482/inde.43.01.445.864

Palabras clave:

café, calidad sensorial, indicadores bibliométricos, inteligencia artificial, mapeo bibliográfico

Resumen

La evolución de la Inteligencia Artifical (IA) en café es crucial para transformar esta agroindustria. Colombia produce anualmente 12.6 millones de sacos y desarrolla investigación sobre IA aplicada al sector; desde la detección de defectos en granos hasta la optimización del tueste para mejorar la calidad del café. Sin embargo, se carece de publicaciones que aborden líneas de investigación e indicadores de manera completa. En este contexto, este trabajo de investigación se fundamentó en un análisis estadístico multivariado de clúster jerárquico usado bajo la metodología de análisis bibliométrico. Este permitió inferir la tendencia actual de investigación en IA aplicada a la industria del café. Además, mediante técnicas bibliométricas de búsqueda de información se obtuvieron 208 documentos de la base de datos Scopus que fueron analizados con estadísticos descriptivos. Los resultados arrojaron que investigadores colombianos impactan significativamente la producción de conocimiento en IA aplicada al café, en comparación con Brasil, mayor productor de café. También, se identificaron líneas de investigación en análisis de mercado mediante Aprendizaje Automático (AA), tecnologías para detectar enfermedades y mejorar la productividad, métodos algorítmicos para resolver desafíos en esta agroindustria, y uso de teledetección e IA para la gestión ambiental y agrícola en la producción.

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