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Intercomparación de modelos ecofisiológicos para el análisis de la productividad del cultivo de arroz en Colombia

dc.rights.licenseAtribución-NoComercial 4.0 Internacional
dc.contributor.advisorRamirez Villegas, Julian Armando
dc.contributor.advisorMejía de Tafur, Maria Sara
dc.contributor.authorRodriguez Espinoza, Jeferson
dc.date.accessioned2024-02-08T16:37:41Z
dc.date.available2024-02-08T16:37:41Z
dc.date.issued2024
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/85667
dc.descriptionIlustraciones, gráficas, tablas
dc.description.abstractEste estudio aborda la intercomparación de tres modelos ecofisiológicos del cultivo de arroz (ORYZA v3, DSSAT-CERES-Rice y Aquacrop), evaluados en tres ambientes de producción en Colombia: Zona Centro, Llanos Orientales y Bajo Cauca. Se implementó un Algoritmo Genético para la optimización de parámetros y se evaluaron las predicciones de los modelos en variables como fenología, biomasa aérea, área foliar y rendimiento en grano. Además, se analizó la respuesta de los modelos a las condiciones de variabilidad climática ENSO utilizando el conjunto de datos del cultivar Fedearroz 2000, sembrado en todas las regiones. Los resultados mostraron variaciones en las predicciones de los modelos, indicando una interacción significativa entre las variaciones climáticas y el sistema de cultivo. La intercomparación proporcionó conocimientos valiosos sobre las fortalezas y debilidades de cada modelo, esencial para futuras aplicaciones en la planificación agronómica y la adaptación al cambio climático. (Texto tomado de la fuente)
dc.description.abstractThis study addresses the intercomparison of three ecophysiological models of rice cultivation (ORYZA v3, DSSAT-CERES-Rice, and Aquacrop), evaluated with three cultivars in three production environments in Colombia: Central Zone, Eastern Plains, and Lower Cauca. A Genetic Algorithm was implemented for parameter optimization, and the models' predictions were evaluated in variables such as phenology, aerial biomass, leaf area, and grain yield. Additionally, the models' response to ENSO climatic variability conditions was analyzed using the dataset of the Fedearroz 2000 cultivar, planted in all regions. The results showed variations in the models' predictions, indicating a significant interaction between climatic variations and the cultivation system. In conclusion, the intercomparison provided valuable insights into the strengths and weaknesses of each model, essential for future applications in agronomic planning and adaptation to climate change.
dc.description.sponsorshipMADR
dc.description.sponsorshipFEDEARROZ-FNA
dc.description.sponsorshipGobernacion del Valle del Cauca-FAN
dc.format.extentxii, 85 páginas
dc.format.mimetypeapplication/pdf
dc.language.isospa
dc.publisherUniversidad Nacional de Colombia
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject.ddc630 - Agricultura y tecnologías relacionadas
dc.titleIntercomparación de modelos ecofisiológicos para el análisis de la productividad del cultivo de arroz en Colombia
dc.typeTrabajo de grado - Maestría
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.publisher.programPalmira - Ciencias Agropecuarias - Maestría en Ciencias Agrarias
dc.coverage.countryColombia
dc.description.degreelevelMaestría
dc.description.methodsSe implementó un Algoritmo Genético para la optimización de parámetros y se evaluaron las predicciones de los modelos en variables como fenología, biomasa aérea, área foliar y rendimiento en grano. Además, se analizó la respuesta de los modelos a las condiciones de variabilidad climática ENSO utilizando el conjunto de datos del cultivar Fedearroz 2000, sembrado en todas las regiones
dc.description.researchareaFisiologia de Cultivos
dc.description.researchareaModelacion de Cultivos
dc.description.researchareaCiencia de Datos
dc.description.technicalinfoLos desarrollos derivados de esta investigación, se encuentran alojados en los repositorios de Github (https://github.com/jrodriguez88/agroclimR, https://jrodriguez88.github.io/agroclimR/), siendo de libre acceso para los investigadores que busquen replicar las metodologías y flujos de datos.
dc.identifier.instnameUniversidad Nacional de Colombia
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourlhttps://repositorio.unal.edu.co/
dc.publisher.facultyFacultad de Ciencias Agropecuarias
dc.publisher.placePalmira, Valle del Cauca, Colombia
dc.publisher.branchUniversidad Nacional de Colombia - Sede Palmira
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.agrovocArroz
dc.subject.agrovocRice
dc.subject.agrovocEcofisiología
dc.subject.agrovocEcophysiology
dc.subject.agrovocModelos vegetales
dc.subject.agrovocPlant models
dc.subject.agrovocProductividad agrícola
dc.subject.agrovocAgricultural productivity
dc.subject.agrovocModelos de simulación
dc.subject.agrovocSimulation models
dc.subject.proposalModelos de Cultivo
dc.subject.proposalORYZA
dc.subject.proposalDSSAT
dc.subject.proposalAquacrop
dc.subject.proposalAlgoritmo genetico
dc.subject.proposalagroclimR
dc.subject.proposalVariabilidad climática
dc.subject.proposalCrop Modeling
dc.subject.proposalClimate Variability
dc.subject.proposalGenetic Algorithm
dc.title.translatedIntercomparison of ecophysiological models for the analysis of rice crop productivity in Colombia
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2
oaire.fundernameAllianza CIAT-Bioversity
dcterms.audience.professionaldevelopmentInvestigadores
dc.description.curricularareaCiencias Agropecuarias.Sede Palmira
dc.contributor.orcid0000-0001-5914-6571
dc.contributor.scopus57217764588


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