Agricultura guiada por datos para maíz en Chiapas, México y altiplano occidental de Guatemala
| cg.authorship.types | CGIAR multi-centre | |
| cg.contributor.affiliation | International Maize and Wheat Improvement Center | |
| cg.contributor.affiliation | Bioversity International and International Center for Tropical Agriculture | |
| cg.contributor.donor | International Center for Tropical Agriculture | |
| cg.contributor.donor | International Maize and Wheat Improvement Center | |
| cg.contributor.programAccelerator | Climate Action | |
| cg.contributor.programAccelerator | Digital Transformation | |
| cg.contributor.programAccelerator | Scaling for Impact | |
| cg.coverage.country | Guatemala | |
| cg.coverage.country | Mexico | |
| cg.coverage.iso3166-alpha2 | GT | |
| cg.coverage.iso3166-alpha2 | MX | |
| cg.coverage.region | Americas | |
| cg.coverage.region | Central America | |
| cg.coverage.region | Latin America and the Caribbean | |
| cg.creator.identifier | Carlos Eduardo Navarro-Racines: 0000-0002-8692-6431 | |
| cg.creator.identifier | Lizeth Llanos-Herrera: 0000-0003-3540-7348 | |
| cg.creator.identifier | Oscar Hernan Estrada Vargas: 0009-0000-9536-5317 | |
| cg.creator.identifier | Camilo Barrios-Perez: 0000-0001-8332-8746 | |
| cg.creator.identifier | Daniel Jiménez: 0000-0003-4218-4306 | |
| cg.creator.identifier | Hugo Andres Dorado: 0000-0002-0103-7505 | |
| cg.creator.identifier | Julian Ramirez-Villegas: 0000-0002-8044-583X | |
| cg.subject.actionArea | Resilient Agrifood Systems | |
| cg.subject.alliancebiovciat | AGRICULTURE | |
| cg.subject.alliancebiovciat | CLIMATE CHANGE ADAPTATION | |
| cg.subject.alliancebiovciat | FOOD SYSTEMS | |
| cg.subject.alliancebiovciat | MODELING | |
| cg.subject.impactArea | Climate adaptation and mitigation | |
| cg.subject.impactArea | Nutrition, health and food security | |
| cg.subject.sdg | SDG 2 - Zero hunger | |
| cg.subject.sdg | SDG 13 - Climate action | |
| cg.subject.sdg | SDG 17 - Partnerships for the goals | |
| dc.contributor.author | Navarro Racines, Carlos | |
| dc.contributor.author | Jaimes, Diana | |
| dc.contributor.author | Llanos, Lizeth | |
| dc.contributor.author | Estrada, Oscar | |
| dc.contributor.author | Barrios, Camilo | |
| dc.contributor.author | Agudelo, Diego | |
| dc.contributor.author | Jimenez, Daniel | |
| dc.contributor.author | Gardeazabal, Andrea | |
| dc.contributor.author | Dorado, Hugo | |
| dc.contributor.author | Ramirez Villegas, Julian | |
| dc.date.accessioned | 2026-01-23T15:48:32Z | |
| dc.date.available | 2026-01-23T15:48:32Z | |
| dc.identifier.uri | https://hdl.handle.net/10568/180542 | |
| dc.title | Agricultura guiada por datos para maíz en Chiapas, México y altiplano occidental de Guatemala | es |
| dcterms.abstract | La limitada cobertura y pertinencia de la asistencia técnica agrícola en Mesoamérica ha restringido la adopción de prácticas de manejo adaptadas a la variabilidad climática y a las condiciones biofísicas locales. Esta presentación expone un enfoque de agricultura guiada por datos para el cultivo de maíz, basado en el análisis integrado de información climática, edáfica y de manejo agronómico mediante técnicas de minería de datos y aprendizaje automático. A partir de más de 4,500 registros productivos en Chiapas, México, y 6,500 observaciones en parcelas de pequeños productores del altiplano occidental de Guatemala, se aplicaron modelos Random Forest para identificar factores determinantes del rendimiento y sus interacciones. Los resultados explican entre el 70 % y 74 % de la variabilidad del rendimiento, evidenciando la influencia de variables como densidad de siembra, fertilización nitrogenada, pendiente del terreno y patrones de precipitación. Asimismo, se integraron pronósticos climáticos estacionales para generar recomendaciones agronómicas sitio-específicas, orientadas a la adaptación y mitigación frente al cambio climático. El enfoque demuestra el potencial de los sistemas de información agroclimática para fortalecer y modernizar los servicios de extensión agrícola, mejorando la toma de decisiones en campo y la resiliencia de los sistemas productivos de maíz. Limited coverage and relevance of agricultural extension services in Mesoamerica have constrained the adoption of management practices adapted to climate variability and local biophysical conditions. This presentation introduces a data-driven agriculture approach for maize production, integrating climatic, soil, and agronomic management data through data mining and machine learning techniques. Using more than 4,500 production records from Chiapas, Mexico, and 6,500 observations from smallholder maize plots in the western highlands of Guatemala, Random Forest models were applied to identify key yield-determining factors and their interactions. The models explained between 70% and 74% of yield variability, highlighting the influence of planting density, nitrogen fertilization, slope, and precipitation patterns. Seasonal climate forecasts were further incorporated to generate site-specific agronomic recommendations aimed at climate change adaptation and mitigation. The results demonstrate the potential of agroclimatic information services to strengthen and modernize agricultural extension systems, enhance on-farm decision-making, and improve the resilience of maize-based production systems. | es |
| dcterms.accessRights | Open Access | |
| dcterms.bibliographicCitation | Navarro-Racines, C.; Jaimes, D.; Llanos, L.; Estrada, O.; Barrios, C.; Agudelo, D.; Jimenez, D.; Gardeazabal, A.; Dorado, H.; Ramirez Villegas, J. (2025) Agricultura guiada por datos para maíz en Chiapas, México y altiplano occidental de Guatemala. Presented at LXVII Reunión Anual Programa Cooperativo Centroamericano para el Mejoramiento de Cultivos y Animales, Mayo 1, 2025 – San Salvador. 23 sl. | es |
| dcterms.extent | 23 sl. | |
| dcterms.issued | 2025-05 | |
| dcterms.language | es | |
| dcterms.license | CC-BY-4.0 | |
| dcterms.subject | evaluation | es |
| dcterms.subject | adaptation | es |
| dcterms.subject | agriculture | es |
| dcterms.subject | cambio climático | es |
| dcterms.subject | climate change | es |
| dcterms.subject | maize | es |
| dcterms.subject | models | es |
| dcterms.subject | modelo | es |
| dcterms.subject | agricultura | es |
| dcterms.subject | mitigación | es |
| dcterms.subject | mitigation | es |
| dcterms.subject | adaptación | es |
| dcterms.subject | maíz | es |
| dcterms.type | Presentation |