CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone

Accurate prediction of phenology is the most critical aspect for the development of models aimed at estimating seed yield, particularly in species that exhibit variable sensitivity to environmental factors throughout the cycle and among genotypes. With this purpose, we evaluated the phenology of 34...

Descripción completa

Detalles Bibliográficos
Autores principales: Severini, Alan David, Álvarez-Prado, Santiago, Otegui, María Elena, Kavanová, Monika, Vega, Claudia Rosa Cecilia, Zuil, Sebastian, Ceretta, Sergio, Acreche, Martin Moises, Amarilla, Fidencia, Cicchino, Mariano Andres, Fernández-Long, María E., Crespo, Aníbal, Serrago, Román, Miralles, Daniel Julio
Formato: Artículo
Lenguaje:Inglés
Publicado: Oxford University Press 2025
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/21690
https://academic.oup.com/insilicoplants/article/6/1/diae005/7667638
https://doi.org/10.1093/insilicoplants/diae005
_version_ 1855486803531792384
author Severini, Alan David
Álvarez-Prado, Santiago
Otegui, María Elena
Kavanová, Monika
Vega, Claudia Rosa Cecilia
Zuil, Sebastian
Ceretta, Sergio
Acreche, Martin Moises
Amarilla, Fidencia
Cicchino, Mariano Andres
Fernández-Long, María E.
Crespo, Aníbal
Serrago, Román
Miralles, Daniel Julio
author_browse Acreche, Martin Moises
Amarilla, Fidencia
Ceretta, Sergio
Cicchino, Mariano Andres
Crespo, Aníbal
Fernández-Long, María E.
Kavanová, Monika
Miralles, Daniel Julio
Otegui, María Elena
Serrago, Román
Severini, Alan David
Vega, Claudia Rosa Cecilia
Zuil, Sebastian
Álvarez-Prado, Santiago
author_facet Severini, Alan David
Álvarez-Prado, Santiago
Otegui, María Elena
Kavanová, Monika
Vega, Claudia Rosa Cecilia
Zuil, Sebastian
Ceretta, Sergio
Acreche, Martin Moises
Amarilla, Fidencia
Cicchino, Mariano Andres
Fernández-Long, María E.
Crespo, Aníbal
Serrago, Román
Miralles, Daniel Julio
author_sort Severini, Alan David
collection INTA Digital
description Accurate prediction of phenology is the most critical aspect for the development of models aimed at estimating seed yield, particularly in species that exhibit variable sensitivity to environmental factors throughout the cycle and among genotypes. With this purpose, we evaluated the phenology of 34 soybean varieties in field experiments located in Argentina, Uruguay and Paraguay. Experiments covered a broad range of maturity group (MG)s (2.2–6.8), sowing dates (SDs) (from spring to summer) and latitude range (24.9–35.6 °S), thus ensuring a wide range of thermo-photoperiodic conditions during the growing season. Based on the observed data, daily time-step models were developed and tested, first for each genotype, and then across MGs. We identified base temperatures specific for different developmental phases and an extra parameter for calculating the photoperiod effect after the R1 stage (flowering). Also, an optimum photoperiod length for each MG was found. Model selection showed that the determinants of phenology across MGs were mainly affecting the duration of vegetative and early reproductive phases. Even so, early phases of development were better predicted than later ones, particularly in locations with cool growing seasons, where the model tended to overestimate their duration. In summary, we have constructed a soybean phenology model that simulates phenology accurately across various geographic locations and sowing dates. The model’s process-based approach has resulted in root mean square errors ranging from 5.8 to 9.5 days for different developmental stages.
format Artículo
id INTA21690
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher Oxford University Press
publisherStr Oxford University Press
record_format dspace
spelling INTA216902025-03-18T11:22:46Z CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone Severini, Alan David Álvarez-Prado, Santiago Otegui, María Elena Kavanová, Monika Vega, Claudia Rosa Cecilia Zuil, Sebastian Ceretta, Sergio Acreche, Martin Moises Amarilla, Fidencia Cicchino, Mariano Andres Fernández-Long, María E. Crespo, Aníbal Serrago, Román Miralles, Daniel Julio Soja Fenología Toma de Decisiones Modelo Dinámico Desarrollo de la Semilla Soybeans Phenology Decision Making Dynamic Models Seed Development Bayesian Model Model Development Accurate prediction of phenology is the most critical aspect for the development of models aimed at estimating seed yield, particularly in species that exhibit variable sensitivity to environmental factors throughout the cycle and among genotypes. With this purpose, we evaluated the phenology of 34 soybean varieties in field experiments located in Argentina, Uruguay and Paraguay. Experiments covered a broad range of maturity group (MG)s (2.2–6.8), sowing dates (SDs) (from spring to summer) and latitude range (24.9–35.6 °S), thus ensuring a wide range of thermo-photoperiodic conditions during the growing season. Based on the observed data, daily time-step models were developed and tested, first for each genotype, and then across MGs. We identified base temperatures specific for different developmental phases and an extra parameter for calculating the photoperiod effect after the R1 stage (flowering). Also, an optimum photoperiod length for each MG was found. Model selection showed that the determinants of phenology across MGs were mainly affecting the duration of vegetative and early reproductive phases. Even so, early phases of development were better predicted than later ones, particularly in locations with cool growing seasons, where the model tended to overestimate their duration. In summary, we have constructed a soybean phenology model that simulates phenology accurately across various geographic locations and sowing dates. The model’s process-based approach has resulted in root mean square errors ranging from 5.8 to 9.5 days for different developmental stages. EEA Pergamino Fil: Severini, Alan D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina Fil: Álvarez Prado, Santiago. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Sistemas de Cultivos Extensivos—GIMUCE. Campo Experimental Villarino; Argentina Fil: Álvarez Prado, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Otegui, María Elena. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino; Argentina Fil: Otegui, María E. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina Fil: Otegui, María E. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Kavanová, Monika. Instituto Nacional de Investigación Agropecuaria (INIA). Programa de Investigación en Cultivos de Secano. La Estanzuela; Uruguay Fil: Vega, C. R. C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina Fil: Zuil, Sebastián. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina Fil: Ceretta, Sergio. Instituto Nacional de Investigación Agropecuaria (INIA). Programa de Investigación en Cultivos de Secano. La Estanzuela; Uruguay Fil: Acreche, Martin Moises. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina Fil: Acreche, Martin Moises. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Amarilla, Fidencia. Instituto Paraguayo de Tecnología Agraria. Centro de Investigación Capitán Miranda; Paraguay Fil: Cicchino, Mariano. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cuenca del Salado; Argentina Fil: Fernández-Long, María E. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Crespo, Aníbal. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Serrago, Román. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Serrago, Román. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Miralles, Daniel J. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Miralles, Daniel J. Universidad de Buenos Aires. Facultad de Agronomía; Argentina 2025-03-18T11:13:21Z 2025-03-18T11:13:21Z 2024-05 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/21690 https://academic.oup.com/insilicoplants/article/6/1/diae005/7667638 2517-5025 (online) https://doi.org/10.1093/insilicoplants/diae005 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Oxford University Press In silico Plants 6 (1) : diae005. (2024)
spellingShingle Soja
Fenología
Toma de Decisiones
Modelo Dinámico
Desarrollo de la Semilla
Soybeans
Phenology
Decision Making
Dynamic Models
Seed Development
Bayesian Model
Model Development
Severini, Alan David
Álvarez-Prado, Santiago
Otegui, María Elena
Kavanová, Monika
Vega, Claudia Rosa Cecilia
Zuil, Sebastian
Ceretta, Sergio
Acreche, Martin Moises
Amarilla, Fidencia
Cicchino, Mariano Andres
Fernández-Long, María E.
Crespo, Aníbal
Serrago, Román
Miralles, Daniel Julio
CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title_full CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title_fullStr CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title_full_unstemmed CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title_short CRONOSOJA : a daily time-step hierarchical model predicting soybean development across maturity groups in the Southern Cone
title_sort cronosoja a daily time step hierarchical model predicting soybean development across maturity groups in the southern cone
topic Soja
Fenología
Toma de Decisiones
Modelo Dinámico
Desarrollo de la Semilla
Soybeans
Phenology
Decision Making
Dynamic Models
Seed Development
Bayesian Model
Model Development
url http://hdl.handle.net/20.500.12123/21690
https://academic.oup.com/insilicoplants/article/6/1/diae005/7667638
https://doi.org/10.1093/insilicoplants/diae005
work_keys_str_mv AT severinialandavid cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT alvarezpradosantiago cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT oteguimariaelena cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT kavanovamonika cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT vegaclaudiarosacecilia cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT zuilsebastian cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT cerettasergio cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT acrechemartinmoises cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT amarillafidencia cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT cicchinomarianoandres cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT fernandezlongmariae cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT crespoanibal cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT serragoroman cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone
AT mirallesdanieljulio cronosojaadailytimestephierarchicalmodelpredictingsoybeandevelopmentacrossmaturitygroupsinthesoutherncone