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ICRISAT West and Central Africa Highlights 2018: Systems analysis

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ICRISAT West and Central Africa Highlights 2018: Systems analysis

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The Research Program on Innovation systems for the drylands aims to improve farm productivity by recognizing the importance of conditions needed to create demand for technologies, and how knowledge produced through systems thinking may be used to bring about such changes. To support its research, ICRISAT focuses on the systemic analysis of conditions that trigger agricultural intensification, and how to support inclusive market−oriented development through digital agriculture and associated technologies. Specifically, automated, remote sensing−based methods to scale up attainable yield gap quantification for locally dominant crops are used and IT platforms developed to include smallholders into networks through enhanced access to credit and financial services, insurance, quality inputs at affordable prices and next generation agricultural advisory services. The research also focuses on improvement of field−scale seasonal yield prediction with satellite data assimilation in smallholder production systems.

The Research Program on Innovation systems for the drylands aims to improve farm productivity by recognizing the importance of conditions needed to create demand for technologies, and how knowledge produced through systems thinking may be used to bring about such changes. To support its research, ICRISAT focuses on the systemic analysis of conditions that trigger agricultural intensification, and how to support inclusive market−oriented development through digital agriculture and associated technologies. Specifically, automated, remote sensing−based methods to scale up attainable yield gap quantification for locally dominant crops are used and IT platforms developed to include smallholders into networks through enhanced access to credit and financial services, insurance, quality inputs at affordable prices and next generation agricultural advisory services. The research also focuses on improvement of field−scale seasonal yield prediction with satellite data assimilation in smallholder production systems.

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