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...
| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
Oxford University Press
2025
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| 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 |
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| 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 |
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