Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia
Wheat productivity in Ethiopia is low compared to countries potential yield. This is due to lack of context-specific good crop management practices. Using machine learning techniques, Alliance of Bioversity International and CIAT (ABC) and its partners, developed season-smart and site-specific ferti...
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/135013 |
| _version_ | 1855540615409827840 |
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| author | Liben, Feyera Abera, Wuletawu Ebrahim, Mohammed Mesfin, Tewodros Tesfu, Daniel Gashaw, Getachew Bekele, Hawinet Tilaye, Asmalu Erkossa, Teklu Ayele, Kebede Adimassu, Zenebe Tamene, Lulseged D. |
| author_browse | Abera, Wuletawu Adimassu, Zenebe Ayele, Kebede Bekele, Hawinet Ebrahim, Mohammed Erkossa, Teklu Gashaw, Getachew Liben, Feyera Mesfin, Tewodros Tamene, Lulseged D. Tesfu, Daniel Tilaye, Asmalu |
| author_facet | Liben, Feyera Abera, Wuletawu Ebrahim, Mohammed Mesfin, Tewodros Tesfu, Daniel Gashaw, Getachew Bekele, Hawinet Tilaye, Asmalu Erkossa, Teklu Ayele, Kebede Adimassu, Zenebe Tamene, Lulseged D. |
| author_sort | Liben, Feyera |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Wheat productivity in Ethiopia is low compared to countries potential yield. This is due to lack of context-specific good crop management practices. Using machine learning techniques, Alliance of Bioversity International and CIAT (ABC) and its partners, developed season-smart and site-specific fertilizer recommendation (SSFR) that can be used to improve wheat productivity in Ethiopia. ABC and Digital Green co-piloted to assess the performance of the SSFR on farmers field in 2022/23 main crop season in Amhara, Oromia and SSNP regions in Ethiopia. ‘Add-on’ survey was conducted to characterize farms and households to provide tailored advisory to fill specific yield gaps, address specific household groups, and gender as well as youth categories. The technical capacity of national and regional research staff from research institutions and universities was enhanced via training on add-on surveys. The survey data collected through the add-on survey was submitted to ONA website and available for use in future initiative. Result from the on-farm pilot scaling on farmers field showed, SSFR significantly improved wheat grain and straw yields for smallholder farmers in the country. We suggest wider pilot scaling of the SSFR innovation to reach more smallholder wheat farmers in Ethiopia. |
| format | Informe técnico |
| id | CGSpace135013 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| record_format | dspace |
| spelling | CGSpace1350132025-11-05T12:12:31Z Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia Liben, Feyera Abera, Wuletawu Ebrahim, Mohammed Mesfin, Tewodros Tesfu, Daniel Gashaw, Getachew Bekele, Hawinet Tilaye, Asmalu Erkossa, Teklu Ayele, Kebede Adimassu, Zenebe Tamene, Lulseged D. machine learning fertilizer application wheat Wheat productivity in Ethiopia is low compared to countries potential yield. This is due to lack of context-specific good crop management practices. Using machine learning techniques, Alliance of Bioversity International and CIAT (ABC) and its partners, developed season-smart and site-specific fertilizer recommendation (SSFR) that can be used to improve wheat productivity in Ethiopia. ABC and Digital Green co-piloted to assess the performance of the SSFR on farmers field in 2022/23 main crop season in Amhara, Oromia and SSNP regions in Ethiopia. ‘Add-on’ survey was conducted to characterize farms and households to provide tailored advisory to fill specific yield gaps, address specific household groups, and gender as well as youth categories. The technical capacity of national and regional research staff from research institutions and universities was enhanced via training on add-on surveys. The survey data collected through the add-on survey was submitted to ONA website and available for use in future initiative. Result from the on-farm pilot scaling on farmers field showed, SSFR significantly improved wheat grain and straw yields for smallholder farmers in the country. We suggest wider pilot scaling of the SSFR innovation to reach more smallholder wheat farmers in Ethiopia. 2023-11-30 2023-12-05T08:32:36Z 2023-12-05T08:32:36Z Report https://hdl.handle.net/10568/135013 en Open Access application/pdf Liben, F.; Abera, W.; Ebrahim, M.; Mesfin, T.; Tesfu, D.; Gashaw, G.; Bekele, H.; Tilaye, A.; Erkossa, T.; Ayele, K.; Adimassu, Z.; Tamene, L.(2023) Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia. 9 p. |
| spellingShingle | machine learning fertilizer application wheat Liben, Feyera Abera, Wuletawu Ebrahim, Mohammed Mesfin, Tewodros Tesfu, Daniel Gashaw, Getachew Bekele, Hawinet Tilaye, Asmalu Erkossa, Teklu Ayele, Kebede Adimassu, Zenebe Tamene, Lulseged D. Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title | Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title_full | Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title_fullStr | Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title_full_unstemmed | Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title_short | Assessing the performance of the NextGen agroadvisory on wheat yields in Ethiopia |
| title_sort | assessing the performance of the nextgen agroadvisory on wheat yields in ethiopia |
| topic | machine learning fertilizer application wheat |
| url | https://hdl.handle.net/10568/135013 |
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