Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia

Climate variability affects crop production in multiple and often complex ways. The development and use hybrid crops with greater productivity and tolerance to climate shocks is one of the approaches to climate adaptation and agricultural intensification. Since hybrid crops are more expensive for th...

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Autores principales: Ordoñez, Leonardo, Vallejo, Eliana, Amariles, Daniel, Mesa, Jeison, Esquivel, Alejandra, Llanos Herrera, Lizeth, Prager, Steven D., Segura, Cristian, Valencia, Jhon Jairo, Duarte, Carmen Julio, Rojas, Diana Carolina, Obando, Diego, Ramírez Villegas, Julián Armando
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/127886
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author Ordoñez, Leonardo
Vallejo, Eliana
Amariles, Daniel
Mesa, Jeison
Esquivel, Alejandra
Llanos Herrera, Lizeth
Prager, Steven D.
Segura, Cristian
Valencia, Jhon Jairo
Duarte, Carmen Julio
Rojas, Diana Carolina
Obando, Diego
Ramírez Villegas, Julián Armando
author_browse Amariles, Daniel
Duarte, Carmen Julio
Esquivel, Alejandra
Llanos Herrera, Lizeth
Mesa, Jeison
Obando, Diego
Ordoñez, Leonardo
Prager, Steven D.
Ramírez Villegas, Julián Armando
Rojas, Diana Carolina
Segura, Cristian
Valencia, Jhon Jairo
Vallejo, Eliana
author_facet Ordoñez, Leonardo
Vallejo, Eliana
Amariles, Daniel
Mesa, Jeison
Esquivel, Alejandra
Llanos Herrera, Lizeth
Prager, Steven D.
Segura, Cristian
Valencia, Jhon Jairo
Duarte, Carmen Julio
Rojas, Diana Carolina
Obando, Diego
Ramírez Villegas, Julián Armando
author_sort Ordoñez, Leonardo
collection Repository of Agricultural Research Outputs (CGSpace)
description Climate variability affects crop production in multiple and often complex ways. The development and use hybrid crops with greater productivity and tolerance to climate shocks is one of the approaches to climate adaptation and agricultural intensification. Since hybrid crops are more expensive for the producer, risk management is of paramount importance. Here, we pose that there is high potential for the Colombian maize sector to use crop-specific climate services for risk reduction. We used the CERES-Maize crop model connected to seasonal climate forecasts developed via Canonical Correlation Analysis (CCA) across key maize growing areas in Colombia to assess the performance of a maize-specific agroclimatic forecast to inform two key decisions, namely, the choice of sowing dates and genotypes. We find that the agroclimatic models perform well at discriminating yield categories (above, below, and normal) with discrimination capacity of up to 70–80 % for the ‘below normal’ and ‘above + below normal’ categories. Consistent with this, agroclimatic forecasts typically predict the optimal planting date with an error of 3 pentads or less. They also predict the optimal choice of genotype correctly around 50–70 % of the time depending on the site or season of interest. Notably, we identify specific cases in which the agroclimatic forecast is misleading but argue that the overall value of the forecasts outweighs these cases. Future work should focus on expanding the scope of the agroclimatic prediction to include other relevant farming decisions that are influenced by climate, and on the improvement of climate forecast performance.
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spelling CGSpace1278862025-11-11T17:43:43Z Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia Ordoñez, Leonardo Vallejo, Eliana Amariles, Daniel Mesa, Jeison Esquivel, Alejandra Llanos Herrera, Lizeth Prager, Steven D. Segura, Cristian Valencia, Jhon Jairo Duarte, Carmen Julio Rojas, Diana Carolina Obando, Diego Ramírez Villegas, Julián Armando agronomy climate services crop modelling climate variability planting date seasonal forecast Climate variability affects crop production in multiple and often complex ways. The development and use hybrid crops with greater productivity and tolerance to climate shocks is one of the approaches to climate adaptation and agricultural intensification. Since hybrid crops are more expensive for the producer, risk management is of paramount importance. Here, we pose that there is high potential for the Colombian maize sector to use crop-specific climate services for risk reduction. We used the CERES-Maize crop model connected to seasonal climate forecasts developed via Canonical Correlation Analysis (CCA) across key maize growing areas in Colombia to assess the performance of a maize-specific agroclimatic forecast to inform two key decisions, namely, the choice of sowing dates and genotypes. We find that the agroclimatic models perform well at discriminating yield categories (above, below, and normal) with discrimination capacity of up to 70–80 % for the ‘below normal’ and ‘above + below normal’ categories. Consistent with this, agroclimatic forecasts typically predict the optimal planting date with an error of 3 pentads or less. They also predict the optimal choice of genotype correctly around 50–70 % of the time depending on the site or season of interest. Notably, we identify specific cases in which the agroclimatic forecast is misleading but argue that the overall value of the forecasts outweighs these cases. Future work should focus on expanding the scope of the agroclimatic prediction to include other relevant farming decisions that are influenced by climate, and on the improvement of climate forecast performance. 2022-12 2023-01-23T13:01:53Z 2023-01-23T13:01:53Z Journal Article https://hdl.handle.net/10568/127886 en Open Access application/pdf Elsevier Ordoñez, L.; Vallejo, E.; Amariles, D.; Mesa, J.; Esquivel, A.; Llanos-Herrera, L.; Prager, S.D.; Segura, C.; Valencia, J.J.; Duarte, C.J.; Rojas, D.C.; Obando, D.; Ramirez-Villegas, J.(2022) Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia. Climate Services 28: 100333. ISSN: 2405-8807
spellingShingle agronomy
climate services
crop modelling
climate variability
planting date
seasonal forecast
Ordoñez, Leonardo
Vallejo, Eliana
Amariles, Daniel
Mesa, Jeison
Esquivel, Alejandra
Llanos Herrera, Lizeth
Prager, Steven D.
Segura, Cristian
Valencia, Jhon Jairo
Duarte, Carmen Julio
Rojas, Diana Carolina
Obando, Diego
Ramírez Villegas, Julián Armando
Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title_full Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title_fullStr Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title_full_unstemmed Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title_short Applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in Colombia
title_sort applying agroclimatic seasonal forecasts to improve rainfed maize agronomic management in colombia
topic agronomy
climate services
crop modelling
climate variability
planting date
seasonal forecast
url https://hdl.handle.net/10568/127886
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