Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data
Cassava (Manihot esculenta Crantz) is a critical food security crop for sub- Saharan Africa. Efforts to improve cassava through breeding have expanded over the past decade. Crop growth models (CGM) are becoming common place in breeding efforts to expand the inference of evaluations of breeding germp...
| Autores principales: | , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Frontiers Media
2025
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| Acceso en línea: | https://hdl.handle.net/10568/175352 |
| _version_ | 1855521949338304512 |
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| author | Okoma, P.M. Kayondo, S.I. Rabbi, I.Y. Moreno-Cadena, L.P. Hoogenboom, G. Jannink, J. |
| author_browse | Hoogenboom, G. Jannink, J. Kayondo, S.I. Moreno-Cadena, L.P. Okoma, P.M. Rabbi, I.Y. |
| author_facet | Okoma, P.M. Kayondo, S.I. Rabbi, I.Y. Moreno-Cadena, L.P. Hoogenboom, G. Jannink, J. |
| author_sort | Okoma, P.M. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Cassava (Manihot esculenta Crantz) is a critical food security crop for sub- Saharan Africa. Efforts to improve cassava through breeding have expanded over the past decade. Crop growth models (CGM) are becoming common place in breeding efforts to expand the inference of evaluations of breeding germplasm to environments that have not been tested and to prepare for breeding for
adaptation to future climates. We parameterized a CGM, the CROPGROMANIHOT- Cassava model in the DSSAT family of models, using data on 67 clones from the International Institute of Tropical Agriculture cassava breeding program evaluated from 2017 to 2020 and over eight locations in Nigeria using trial and error parameter adjustments and the General Likelihood Uncertainty Estimation method. Our objectives were to assess the feasibility of this largescale
calibration in the context of a cassava breeding program and to identify systematic biases of the model. For each cultivar we calculated the Pearson correlation between model prediction and observation across the environments, as well as root mean squared error and d statistics. As a result of calibration, the correlation coefficient increased from –0.03 to +0.08, the RMSE dropped from 21 t ha-1 to 5 t ha-1 while d increased from 0.23 to 0.44. We found that the model
underestimated root yield in dry environments (low precipitation and high temperature) and overestimated root yield in wet environments (high precipitation and low temperature). Our experience suggests both that CGM calibration could become a routine component of the cassava breeding data analysis cycle and that there are opportunities for model improvement. |
| format | Journal Article |
| id | CGSpace175352 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1753522025-12-08T10:29:22Z Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data Okoma, P.M. Kayondo, S.I. Rabbi, I.Y. Moreno-Cadena, L.P. Hoogenboom, G. Jannink, J. cassava crop growth calibration nigeria food security Cassava (Manihot esculenta Crantz) is a critical food security crop for sub- Saharan Africa. Efforts to improve cassava through breeding have expanded over the past decade. Crop growth models (CGM) are becoming common place in breeding efforts to expand the inference of evaluations of breeding germplasm to environments that have not been tested and to prepare for breeding for adaptation to future climates. We parameterized a CGM, the CROPGROMANIHOT- Cassava model in the DSSAT family of models, using data on 67 clones from the International Institute of Tropical Agriculture cassava breeding program evaluated from 2017 to 2020 and over eight locations in Nigeria using trial and error parameter adjustments and the General Likelihood Uncertainty Estimation method. Our objectives were to assess the feasibility of this largescale calibration in the context of a cassava breeding program and to identify systematic biases of the model. For each cultivar we calculated the Pearson correlation between model prediction and observation across the environments, as well as root mean squared error and d statistics. As a result of calibration, the correlation coefficient increased from –0.03 to +0.08, the RMSE dropped from 21 t ha-1 to 5 t ha-1 while d increased from 0.23 to 0.44. We found that the model underestimated root yield in dry environments (low precipitation and high temperature) and overestimated root yield in wet environments (high precipitation and low temperature). Our experience suggests both that CGM calibration could become a routine component of the cassava breeding data analysis cycle and that there are opportunities for model improvement. 2025 2025-06-27T14:23:06Z 2025-06-27T14:23:06Z Journal Article https://hdl.handle.net/10568/175352 en Open Access application/pdf Frontiers Media Okoma, P.M., Kayondo, S.I., Rabbi, I.Y., Moreno-Cadena, L.P., Hoogenboom, G. & Jannink, J. (2025). Evaluating a cassava crop growth model by optimizing genotypic-specific parameters using multi-environment trial breeding data. Frontiers in Plant Science, 16: 1535058, 1-15. |
| spellingShingle | cassava crop growth calibration nigeria food security Okoma, P.M. Kayondo, S.I. Rabbi, I.Y. Moreno-Cadena, L.P. Hoogenboom, G. Jannink, J. Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title | Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title_full | Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title_fullStr | Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title_full_unstemmed | Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title_short | Evaluating a cassava crop growth model by optimizing genotype-specifc parameters using multienvironment trial breeding data |
| title_sort | evaluating a cassava crop growth model by optimizing genotype specifc parameters using multienvironment trial breeding data |
| topic | cassava crop growth calibration nigeria food security |
| url | https://hdl.handle.net/10568/175352 |
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