AI-based decision support system for improving rice crop yield and quality in Uganda 2023

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dc.contributor.author Arinda, Sophie
dc.contributor.author Otim, Natham Petum
dc.contributor.author Ambangira, Mark Mwesigwa
dc.contributor.author Abitegeka, Bridget
dc.date.accessioned 2024-01-08T09:28:34Z
dc.date.available 2024-01-08T09:28:34Z
dc.date.issued 2023-05
dc.description Research Report submitted to the School of Computing and Informatics Technology For the Study Leading to a Project Proposal in Partial Fulfilment of the Requirements for the Award of the Degree of Bachelor of Science in Computer Science Of Makerere University en_US
dc.description.abstract The Ugandan government has identified rice as a strategic crop to combat food insecurity and boost economic standards. A study will focus on the Ugandan rice sector, collecting data from historical records and focusing on rice farmers across the country. The data will include socioeconomic, agronomic, and environmental data. Socioeconomic data will include farm size, ownership, and management structure, while agronomic data will focus on crop management practices and environmental factors. The study will use deep learning techniques and consider yearly rice crop yields, regardless of the two major growing seasons. The data collection will be conducted across all commercial rice growing districts in Uganda. en_US
dc.identifier.citation Arinda, S. et al. (2023). AI-based decision support system for improving rice crop yield and quality in Uganda 2023 (Unpublished undergraduate dissertation). Kampala: Makerere University. en_US
dc.identifier.uri http://hdl.handle.net/20.500.12281/18102
dc.language.iso en en_US
dc.publisher Makerere University en_US
dc.subject Crop yield prediction en_US
dc.subject Decision Support Systems en_US
dc.title AI-based decision support system for improving rice crop yield and quality in Uganda 2023 en_US
dc.type Thesis en_US
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