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...

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Fecha de publicación:
2022
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Universidad Católica de Pereira
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Repositorio Institucional - RIBUC
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spa
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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
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openAccess
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Derechos de autor 2023 Entre Ciencia e Ingeniería
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oai_identifier_str oai:repositorio.ucp.edu.co:10785/13711
network_acronym_str RepoRIBUC
network_name_str Repositorio Institucional - RIBUC
repository_id_str
spelling Characterization 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 InteligenteThis 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.Universidad Católica de Pereira2023-08-29T03:49:43Z2023-08-29T03:49:43Z2022-12-31Artículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1application/pdfapplication/xmlhttps://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/276610.31908/19098367.2766http://hdl.handle.net/10785/13711Entre 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); 35-412539-41691909-8367spahttps://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_abf2Giraldo Plaza, Jorge EliécerLondoño Franco, Luis FernandoPérez Buelvas, Carlos AndrésÁlvarez Albanés, Eddie Yaciroai:repositorio.ucp.edu.co:10785/137112025-01-27T23:58:43Z
dc.title.none.fl_str_mv Characterization of Accurate Soil and Grassland Fertilization Variables for the Design of Intelligent Recommendation Softwareare
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.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-31
2023-08-29T03:49:43Z
2023-08-29T03:49:43Z
dc.type.none.fl_str_mv Artículo de revista
http://purl.org/coar/resource_type/c_6501
http://purl.org/coar/version/c_970fb48d4fbd8a85
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766
10.31908/19098367.2766
http://hdl.handle.net/10785/13711
url https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766
http://hdl.handle.net/10785/13711
identifier_str_mv 10.31908/19098367.2766
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2598
https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/2766/2633
dc.rights.none.fl_str_mv Derechos de autor 2023 Entre Ciencia e Ingeniería
https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Derechos de autor 2023 Entre Ciencia e Ingeniería
https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/xml
dc.publisher.none.fl_str_mv Universidad Católica de Pereira
publisher.none.fl_str_mv Universidad Católica de Pereira
dc.source.none.fl_str_mv Entre ciencia e ingeniería; Vol 16 No 32 (2022); 35-41
Entre Ciencia e Ingeniería; Vol. 16 Núm. 32 (2022); 35-41
Entre ciencia e ingeniería; v. 16 n. 32 (2022); 35-41
2539-4169
1909-8367
institution Universidad Católica de Pereira
repository.name.fl_str_mv
repository.mail.fl_str_mv
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