Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa

Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve biomass production and soil organic carbon (SOC) sequestration. Within East Africa several studies have been conducted to evaluate models in annual cropping systems, and to quantify the...

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Autores principales: Nyawira, Sylvia Sarah, Korir, Mercy Jebet, Boote, Ken, Ordonez, Leonardo, Notenbaert, An Maria Omer, Hoogenboom, Gerrit
Formato: Póster
Lenguaje:Inglés
Publicado: International Center for Tropical Agriculture 2023
Materias:
Acceso en línea:https://hdl.handle.net/10568/132215
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author Nyawira, Sylvia Sarah
Korir, Mercy Jebet
Boote, Ken
Ordonez, Leonardo
Notenbaert, An Maria Omer
Hoogenboom, Gerrit
author_browse Boote, Ken
Hoogenboom, Gerrit
Korir, Mercy Jebet
Notenbaert, An Maria Omer
Nyawira, Sylvia Sarah
Ordonez, Leonardo
author_facet Nyawira, Sylvia Sarah
Korir, Mercy Jebet
Boote, Ken
Ordonez, Leonardo
Notenbaert, An Maria Omer
Hoogenboom, Gerrit
author_sort Nyawira, Sylvia Sarah
collection Repository of Agricultural Research Outputs (CGSpace)
description Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve biomass production and soil organic carbon (SOC) sequestration. Within East Africa several studies have been conducted to evaluate models in annual cropping systems, and to quantify the impacts of different agronomic management options on soil organic carbon and yields. However, no modelling studies exist on perennial forage grasses, which are important for mixed-crop livestock systems within the region. We evaluate the CROPGRO-Perennial Forage model (CROPGRO-PFM) using harvested biomass and SOC data from several sites across Kenya and Tanzania. The model version initially parametrized for Brachiaria cv. Marandu and Panicum maximum in Brazil is applied to simulate Brachiaria cv. hybrid Cayman and Panicum maximum in the two countries. We modify model parameters to improve d-statistic and root mean square error (RMSE) for biomass and SOC. Our results show that the CROPRO-PFM model can simulate biomass of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. The d-statistic for harvested biomass across the Tanzania sites ranged between 0.78 to 0.97, while the root means square error ranged between 0.6 to 2 t/ha. Sensitivity simulations with increased manure application rates of 5t/ha show an increase in SOC of up 0.833 t/ha/yr. These results suggest that the CROPGRO-PFM can be used to simulate growth of Brachiaria cv. Cayman adequately under rainfed conditions in the East African highlands.
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spelling CGSpace1322152025-11-05T11:56:21Z Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa Nyawira, Sylvia Sarah Korir, Mercy Jebet Boote, Ken Ordonez, Leonardo Notenbaert, An Maria Omer Hoogenboom, Gerrit biomass soil organic matter carbon brachiaria perennials models forage Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve biomass production and soil organic carbon (SOC) sequestration. Within East Africa several studies have been conducted to evaluate models in annual cropping systems, and to quantify the impacts of different agronomic management options on soil organic carbon and yields. However, no modelling studies exist on perennial forage grasses, which are important for mixed-crop livestock systems within the region. We evaluate the CROPGRO-Perennial Forage model (CROPGRO-PFM) using harvested biomass and SOC data from several sites across Kenya and Tanzania. The model version initially parametrized for Brachiaria cv. Marandu and Panicum maximum in Brazil is applied to simulate Brachiaria cv. hybrid Cayman and Panicum maximum in the two countries. We modify model parameters to improve d-statistic and root mean square error (RMSE) for biomass and SOC. Our results show that the CROPRO-PFM model can simulate biomass of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. The d-statistic for harvested biomass across the Tanzania sites ranged between 0.78 to 0.97, while the root means square error ranged between 0.6 to 2 t/ha. Sensitivity simulations with increased manure application rates of 5t/ha show an increase in SOC of up 0.833 t/ha/yr. These results suggest that the CROPGRO-PFM can be used to simulate growth of Brachiaria cv. Cayman adequately under rainfed conditions in the East African highlands. 2023-09-21 2023-10-12T08:30:20Z 2023-10-12T08:30:20Z Poster https://hdl.handle.net/10568/132215 en Open Access application/pdf International Center for Tropical Agriculture Nyawira, S.S.; Korir, M.; Boote, K.; Ordonez, L.; Notenbaert, A.; Hoogenboom, G. (2023) Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa. Poster prepared for Tropentag 2023 - Competing pathways for equitable food systems transformation: trade-offs and synergies. Berlin, Germany, 20-22 September 2023. Cali (Colombia): International Center for Tropical Agriculture. 1 p.
spellingShingle biomass
soil organic matter
carbon
brachiaria
perennials
models
forage
Nyawira, Sylvia Sarah
Korir, Mercy Jebet
Boote, Ken
Ordonez, Leonardo
Notenbaert, An Maria Omer
Hoogenboom, Gerrit
Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title_full Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title_fullStr Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title_full_unstemmed Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title_short Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa
title_sort adapting the cropgro model to simulate biomass production and soil organic carbon of cayman grass in east africa
topic biomass
soil organic matter
carbon
brachiaria
perennials
models
forage
url https://hdl.handle.net/10568/132215
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