Machine learning innovations to improve maize nutrient management recommendations in the eastern IndoGangetic Plains

CGIAR Research Program on Maize. 2019. Machine learning innovations to improve maize nutrient management recommendations in the eastern IndoGangetic Plains. Reported in Maize Annual Report 2019. Innovations.

CSISA aims to use ‘sustainable intensification’ technologies and management practices to enhance the productivity of cereal-based cropping systems, increase farm incomes, and reduce agriculture’s environmental footprint. the intersection of a diverse set of partners in the public and private sectors, occupying the crucial middle-ground where research meets development. The project generates data and evidence on improving crop production and identifying more sustainable means of growing crops, and then scales them out to partners in the public and private sector to raise the awareness of farmers and other stakeholders on these options. By engaging with a network of partners as an agricultural innovation systems broker, CSISA is built on the premise that transformative development typically requires not one single change, but the orchestration of several changes. Innovation systems can be understood as networks of business, organizations and people – including farmers, esearchers, extension agents, policy makers and entrepreneurs – that, through the sum of their actions bring new technologies, innovations, products processes or policies into use. Efforts to coordinate these groups and actors can accelerate the rate of uptake of technological innovation that can improve the impact of development interventions. CSISA plays a coordinating and facilitating role in South Asia as an agricultural innovation system broker