The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis
Descripción del Articulo
This study examines the increasing role of artificial intelligence (AI) in Costa Rica’s agricultural sector, emphasizing its potential to enhance sustainability, resource management, and market competitiveness. Using a mixed-methods approach, the research integrates structural equation modeling (SEM...
| Autores: | , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2025 |
| Institución: | Universidad Nacional de Trujillo |
| Repositorio: | Revistas - Universidad Nacional de Trujillo |
| Lenguaje: | español inglés |
| OAI Identifier: | oai:ojs.revistas.unitru.edu.pe:article/6559 |
| Enlace del recurso: | https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559 |
| Nivel de acceso: | acceso abierto |
| Materia: | Artificial Intelligence (AI) competitiveness productivity resource optimization sustainable agriculture |
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The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysisOkot, Tom Pérez, Edward Artificial Intelligence (AI)competitivenessproductivityresource optimizationsustainable agricultureThis study examines the increasing role of artificial intelligence (AI) in Costa Rica’s agricultural sector, emphasizing its potential to enhance sustainability, resource management, and market competitiveness. Using a mixed-methods approach, the research integrates structural equation modeling (SEM), multivariate regression analysis, text mining, and scenario analysis to provide a comprehensive evaluation of AI adoption. AI-driven solutions optimize key agricultural processes, including climate pattern prediction, soil condition monitoring, crop disease detection, and pest management. Quantitative findings indicate a strong correlation between AI adoption and improved productivity, economic benefits, and environmental conservation, particularly through optimized fertilizer and pesticide use and enhanced water management. However, challenges such as high implementation costs, limited digital infrastructure, and farmer resistance remain significant barriers. Text mining analysis reveals widespread concerns over data privacy, technical complexity, and financial investment, highlighting the importance of targeted training programs. Scenario analysis further suggests that government support and technological advancements could significantly accelerate AI adoption over the next decade. The study underscores the need for strategic partnerships among government agencies, educational institutions, and technology providers to bridge the digital divide and encourage AI adoption. These findings not only inform Costa Rican agricultural policy and innovation strategies but also provide a replicable model for other emerging economies aiming to integrate AI sustainably into agricultural systems.Universidad Nacional de Trujillo2025-07-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículo evaluado por parestext/htmlapplication/pdfhttps://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559Scientia Agropecuaria; Vol. 16 Núm. 3 (2025): julio-septiembre; 469-480Scientia Agropecuaria; Vol. 16 No. 3 (2025): julio-septiembre; 469-4802306-67412077-9917reponame:Revistas - Universidad Nacional de Trujilloinstname:Universidad Nacional de Trujilloinstacron:UNITRUspaenghttps://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559/6917https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559/6836Derechos de autor 2025 Scientia Agropecuariahttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessoai:ojs.revistas.unitru.edu.pe:article/65592025-07-07T10:41:57Z |
| dc.title.none.fl_str_mv |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| title |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| spellingShingle |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis Okot, Tom Artificial Intelligence (AI) competitiveness productivity resource optimization sustainable agriculture |
| title_short |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| title_full |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| title_fullStr |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| title_full_unstemmed |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| title_sort |
The role of artificial intelligence in sustainable agriculture in Costa Rica: An integrated evaluation using structural equation modeling, text mining, and scenario analysis |
| dc.creator.none.fl_str_mv |
Okot, Tom Pérez, Edward |
| author |
Okot, Tom |
| author_facet |
Okot, Tom Pérez, Edward |
| author_role |
author |
| author2 |
Pérez, Edward |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Artificial Intelligence (AI) competitiveness productivity resource optimization sustainable agriculture |
| topic |
Artificial Intelligence (AI) competitiveness productivity resource optimization sustainable agriculture |
| description |
This study examines the increasing role of artificial intelligence (AI) in Costa Rica’s agricultural sector, emphasizing its potential to enhance sustainability, resource management, and market competitiveness. Using a mixed-methods approach, the research integrates structural equation modeling (SEM), multivariate regression analysis, text mining, and scenario analysis to provide a comprehensive evaluation of AI adoption. AI-driven solutions optimize key agricultural processes, including climate pattern prediction, soil condition monitoring, crop disease detection, and pest management. Quantitative findings indicate a strong correlation between AI adoption and improved productivity, economic benefits, and environmental conservation, particularly through optimized fertilizer and pesticide use and enhanced water management. However, challenges such as high implementation costs, limited digital infrastructure, and farmer resistance remain significant barriers. Text mining analysis reveals widespread concerns over data privacy, technical complexity, and financial investment, highlighting the importance of targeted training programs. Scenario analysis further suggests that government support and technological advancements could significantly accelerate AI adoption over the next decade. The study underscores the need for strategic partnerships among government agencies, educational institutions, and technology providers to bridge the digital divide and encourage AI adoption. These findings not only inform Costa Rican agricultural policy and innovation strategies but also provide a replicable model for other emerging economies aiming to integrate AI sustainably into agricultural systems. |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025-07-07 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artículo evaluado por pares |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559 |
| url |
https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559 |
| dc.language.none.fl_str_mv |
spa eng |
| language |
spa eng |
| dc.relation.none.fl_str_mv |
https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559/6917 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/6559/6836 |
| dc.rights.none.fl_str_mv |
Derechos de autor 2025 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Derechos de autor 2025 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
text/html application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad Nacional de Trujillo |
| publisher.none.fl_str_mv |
Universidad Nacional de Trujillo |
| dc.source.none.fl_str_mv |
Scientia Agropecuaria; Vol. 16 Núm. 3 (2025): julio-septiembre; 469-480 Scientia Agropecuaria; Vol. 16 No. 3 (2025): julio-septiembre; 469-480 2306-6741 2077-9917 reponame:Revistas - Universidad Nacional de Trujillo instname:Universidad Nacional de Trujillo instacron:UNITRU |
| instname_str |
Universidad Nacional de Trujillo |
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UNITRU |
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UNITRU |
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Revistas - Universidad Nacional de Trujillo |
| collection |
Revistas - Universidad Nacional de Trujillo |
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1852864008739094528 |
| score |
13.058819 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).