Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare
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 soi...
- Autores:
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Universidad Católica de Pereira
- Repositorio:
- Repositorio Institucional - RIBUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.ucp.edu.co:10785/13711
- Acceso en línea:
- https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766
http://hdl.handle.net/10785/13711
- Palabra clave:
- Rights
- openAccess
- License
- Derechos de autor 2023 Entre Ciencia e Ingeniería
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2023-08-29T03:49:43Z2023-08-29T03:49:43Z2022-12-31https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/276610.31908/19098367.2766http://hdl.handle.net/10785/13711This 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.Este artículo presenta la caracterización de variables relacionada con la fertilización precisa de suelos y praderas de ganadería de leche, para la construcción de un sistema inteligente de recomendación de planes de fertilización. La caracterización se realizó mediante un estudio de campo que consideró análisis de suelo y determinación de niveles óptimos de macronutrientes en cinco fincas del norte de Antioquia-Colombia. Como principal resultado se logró establecer los conjuntos difusos de entrada y salida, junto con las reglas de producción, que posteriormente se llevaron a un prototipo funcional. A partir de lo anterior, se concluye que el uso de técnicas de inteligencia artificial tiene gran potencial para su integración con software que apoyen las labores relacionadas con la fertilización.application/pdfapplication/xmlspaUniversidad Católica de Pereirahttps://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2598https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2633Derechos de autor 2023 Entre Ciencia e Ingenieríahttps://creativecommons.org/licenses/by-nc/4.0/deed.es_EShttps://creativecommons.org/licenses/by-nc/4.0/deed.es_ESinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Entre ciencia e ingeniería; Vol 16 No 32 (2022); 35-41Entre Ciencia e Ingeniería; Vol. 16 Núm. 32 (2022); 35-41Entre ciencia e ingeniería; v. 16 n. 32 (2022); 35-412539-41691909-8367Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation SoftwareareCaracterización de Variables de Fertilización Precisa de Suelos y Praderas para el Diseño de un Software de Recomendación InteligenteArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionGiraldo Plaza, Jorge EliécerLondoño Franco, Luis FernandoPérez Buelvas, Carlos AndrésÁlvarez Albanés, Eddie YacirPublication10785/13711oai:repositorio.ucp.edu.co:10785/137112025-01-27 18:58:43.177https://creativecommons.org/licenses/by-nc/4.0/deed.es_ESDerechos de autor 2023 Entre Ciencia e Ingenieríametadata.onlyhttps://repositorio.ucp.edu.coRepositorio Institucional de la Universidad Católica de Pereira - RIBUCbdigital@metabiblioteca.com |
| dc.title.eng.fl_str_mv |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| dc.title.spa.fl_str_mv |
Caracterización de Variables de Fertilización Precisa de Suelos y Praderas para el Diseño de un Software de Recomendación Inteligente |
| title |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| spellingShingle |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| title_short |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| title_full |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| title_fullStr |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| title_full_unstemmed |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| title_sort |
Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare |
| description |
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. |
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2022 |
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2022-12-31 |
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2023-08-29T03:49:43Z |
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2023-08-29T03:49:43Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766 10.31908/19098367.2766 |
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http://hdl.handle.net/10785/13711 |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766 http://hdl.handle.net/10785/13711 |
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10.31908/19098367.2766 |
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2598 https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2633 |
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Derechos de autor 2023 Entre Ciencia e Ingeniería https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES |
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https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES |
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Universidad Católica de Pereira |
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Entre ciencia e ingeniería; Vol 16 No 32 (2022); 35-41 |
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Entre Ciencia e Ingeniería; Vol. 16 Núm. 32 (2022); 35-41 |
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Entre ciencia e ingeniería; v. 16 n. 32 (2022); 35-41 |
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2539-4169 1909-8367 |
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Repositorio Institucional de la Universidad Católica de Pereira - RIBUC |
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