Resumen

GIRALDO, J. E.; LONDONO, L. F.; PEREZ, C.A.  y  ALVAREZ, E. Y.. Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Software. Entre Ciencia e Ingenieria [online]. 2022, vol.16, n.32, pp.35-41.  Epub 17-Jul-2023. ISSN 1909-8367.  https://doi.org/10.31908/19098367.2766.

This article presents the characterization of variables related to the precise fertilization of soils and dairy cattle pastures, for the construction of an intelligent system for the recommendation of fertilization plans. The characterization was carried out through a field study that considered soil analysis and determination of optimum levels of macronutrients in five farms in the north of Antioquia-Colombia. The main result was the establishment of the input and output fuzzy sets, together with the production rules, which were later taken to a functional prototype. From the above, it is concluded that the use of artificial intelligence techniques has great potential for integration with software to support fertilization-related tasks.

Palabras clave : Accurate Soil Fertilization; Characterization of Variables; Dairy Cattle; Specialized Analysis of Collected Data; Recommendation Software.

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