Satellite based approach for rice yield monitoring and forecasting
Rice yield forecasting is a crucial task for management and planning. A rice yield estimation system (RIICE) was developed based on the crop growth model ORYZA and SAR derived key information such as start of season (SOS) and leaf area growth rate. Results from study sites in Sikasso and Segou regio...
| Main Authors: | , , , , , , , , |
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| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
Accelerating Impacts of CGIAR Climate Research for Africa
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/138045 |
| _version_ | 1855536439173840896 |
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| author | Mathieu, Renaud Murugesan, Deiveegan Maunahan, Aileen Quicho, Emma Sataphaty, Sushree Dossou-Yovo, Elliott Ronald Salif, Doumba Akpoffo, Marius Gatti, Luca |
| author_browse | Akpoffo, Marius Dossou-Yovo, Elliott Ronald Gatti, Luca Mathieu, Renaud Maunahan, Aileen Murugesan, Deiveegan Quicho, Emma Salif, Doumba Sataphaty, Sushree |
| author_facet | Mathieu, Renaud Murugesan, Deiveegan Maunahan, Aileen Quicho, Emma Sataphaty, Sushree Dossou-Yovo, Elliott Ronald Salif, Doumba Akpoffo, Marius Gatti, Luca |
| author_sort | Mathieu, Renaud |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Rice yield forecasting is a crucial task for management and planning. A rice yield estimation system (RIICE) was developed based on the crop growth model ORYZA and SAR derived key information such as start of season (SOS) and leaf area growth rate. Results from study sites in Sikasso and Segou regions suggest that incorporating remote sensing data, specifically Synthetic aperture radar (SAR), into a process-based crop model improves the spatial distribution of yield estimates. From the findings, it was evident that the RIICE tool adequately predicted rice yield in the rice growing environments in Mali and can be used by the Ministry of Agriculture and private sector to plan investment to achieve rice self-sufficiency. Nevertheless, continued enhancement of the processing chain, with a specific focus on optimizing output delivery, is essential. |
| format | Informe técnico |
| id | CGSpace138045 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Accelerating Impacts of CGIAR Climate Research for Africa |
| publisherStr | Accelerating Impacts of CGIAR Climate Research for Africa |
| record_format | dspace |
| spelling | CGSpace1380452025-12-08T09:54:28Z Satellite based approach for rice yield monitoring and forecasting Mathieu, Renaud Murugesan, Deiveegan Maunahan, Aileen Quicho, Emma Sataphaty, Sushree Dossou-Yovo, Elliott Ronald Salif, Doumba Akpoffo, Marius Gatti, Luca rice climate information services climate-smart agriculture Rice yield forecasting is a crucial task for management and planning. A rice yield estimation system (RIICE) was developed based on the crop growth model ORYZA and SAR derived key information such as start of season (SOS) and leaf area growth rate. Results from study sites in Sikasso and Segou regions suggest that incorporating remote sensing data, specifically Synthetic aperture radar (SAR), into a process-based crop model improves the spatial distribution of yield estimates. From the findings, it was evident that the RIICE tool adequately predicted rice yield in the rice growing environments in Mali and can be used by the Ministry of Agriculture and private sector to plan investment to achieve rice self-sufficiency. Nevertheless, continued enhancement of the processing chain, with a specific focus on optimizing output delivery, is essential. 2023-12 2024-01-18T16:55:45Z 2024-01-18T16:55:45Z Report https://hdl.handle.net/10568/138045 en Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Mathieu R, Murugesan D, Maunahan A, Quicho E, Sataphaty S, Dossou-Yovo ER, Salif D, Akpoffo M, Gatti. 2023. Satellite based approach for rice yield monitoring and forecasting. AICCRA Report. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA). |
| spellingShingle | rice climate information services climate-smart agriculture Mathieu, Renaud Murugesan, Deiveegan Maunahan, Aileen Quicho, Emma Sataphaty, Sushree Dossou-Yovo, Elliott Ronald Salif, Doumba Akpoffo, Marius Gatti, Luca Satellite based approach for rice yield monitoring and forecasting |
| title | Satellite based approach for rice yield monitoring and forecasting |
| title_full | Satellite based approach for rice yield monitoring and forecasting |
| title_fullStr | Satellite based approach for rice yield monitoring and forecasting |
| title_full_unstemmed | Satellite based approach for rice yield monitoring and forecasting |
| title_short | Satellite based approach for rice yield monitoring and forecasting |
| title_sort | satellite based approach for rice yield monitoring and forecasting |
| topic | rice climate information services climate-smart agriculture |
| url | https://hdl.handle.net/10568/138045 |
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