Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique
Mozambique faces challenges in staple food crop production, which makes crop yield prediction vital for effective policy-making on food security. The analytic framework that integrates satellite data and crop growth simulations to forecast regional crop yield can aid policy makers. The objectives of...
| Main Authors: | , , |
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| Format: | Informe técnico |
| Language: | Inglés |
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International Food Policy Research Institute
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/178003 |
| _version_ | 1855536381813587968 |
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| author | Kim, Kwang Soo Hyun, Shinwoo Lee, Seok Ho |
| author_browse | Hyun, Shinwoo Kim, Kwang Soo Lee, Seok Ho |
| author_facet | Kim, Kwang Soo Hyun, Shinwoo Lee, Seok Ho |
| author_sort | Kim, Kwang Soo |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Mozambique faces challenges in staple food crop production, which makes crop yield prediction vital for effective policy-making on food security. The analytic framework that integrates satellite data and crop growth simulations to forecast regional crop yield can aid policy makers. The objectives of this study were to apply the analytic framework to three major crop production regions in Mozambique including Gaza, Manica, and Nampula provinces for maize, soybean, and rice. The gridded crop growth simulations were performed using Decision Support System for Agrotechnology Transfer (DSSAT). A set of crop management scenarios were applied to the crop growth simulations. One of these simulations were identified to obtain crop yield hindcasts by cell comparing leaf area index data derived from the simulations and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Crop yield hindcasts were obtained using a percentile of crop yield distribution using three preceding growing seasons. It was found that the percentile used for crop yield hindcasts differed by crop and province. The accuracy of maize and soybean yield hindcasts was within an acceptable range, e.g., < 20% of crop yield in growing seasons, whereas that of rice yield hindcasts was considerably high. Crop yield predictions were limited by the use of crop management scenarios such as cultivars and fertilizer application. Despite biases and limitations in representing real farming conditions, the framework provided insights into improving staple food crop production. It was also highlighted that detailed knowledge on crop management practices such as cultivar and fertilizer applications would improve the reliability of the analytic framework to predict crop yield in the major production regions in Mozambique. |
| format | Informe técnico |
| id | CGSpace178003 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1780032025-12-03T20:01:03Z Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique Kim, Kwang Soo Hyun, Shinwoo Lee, Seok Ho frameworks crop yield farmland crop production models decision-support systems forecasting food security Mozambique faces challenges in staple food crop production, which makes crop yield prediction vital for effective policy-making on food security. The analytic framework that integrates satellite data and crop growth simulations to forecast regional crop yield can aid policy makers. The objectives of this study were to apply the analytic framework to three major crop production regions in Mozambique including Gaza, Manica, and Nampula provinces for maize, soybean, and rice. The gridded crop growth simulations were performed using Decision Support System for Agrotechnology Transfer (DSSAT). A set of crop management scenarios were applied to the crop growth simulations. One of these simulations were identified to obtain crop yield hindcasts by cell comparing leaf area index data derived from the simulations and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Crop yield hindcasts were obtained using a percentile of crop yield distribution using three preceding growing seasons. It was found that the percentile used for crop yield hindcasts differed by crop and province. The accuracy of maize and soybean yield hindcasts was within an acceptable range, e.g., < 20% of crop yield in growing seasons, whereas that of rice yield hindcasts was considerably high. Crop yield predictions were limited by the use of crop management scenarios such as cultivars and fertilizer application. Despite biases and limitations in representing real farming conditions, the framework provided insights into improving staple food crop production. It was also highlighted that detailed knowledge on crop management practices such as cultivar and fertilizer applications would improve the reliability of the analytic framework to predict crop yield in the major production regions in Mozambique. 2025-11-18 2025-11-18T18:32:58Z 2025-11-18T18:32:58Z Report https://hdl.handle.net/10568/178003 en Open Access application/pdf International Food Policy Research Institute Kim, Kwang Soo; Hyun, Shinwoo; and Lee, Seok Ho. 2025. Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/178003 |
| spellingShingle | frameworks crop yield farmland crop production models decision-support systems forecasting food security Kim, Kwang Soo Hyun, Shinwoo Lee, Seok Ho Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title | Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title_full | Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title_fullStr | Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title_full_unstemmed | Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title_short | Application of an analytical framework to hindcast crop yield in major crop production regions in Mozambique |
| title_sort | application of an analytical framework to hindcast crop yield in major crop production regions in mozambique |
| topic | frameworks crop yield farmland crop production models decision-support systems forecasting food security |
| url | https://hdl.handle.net/10568/178003 |
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