Machine learning innovations to improve maize nutrient management recommendations in the eastern IndoGangetic Plains
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...
| Autor principal: | |
|---|---|
| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2019
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/123554 |
Ejemplares similares: Machine learning innovations to improve maize nutrient management recommendations in the eastern IndoGangetic Plains
- Assessment of climate adaptation options for cereal-based systems in the eastern Indo-Gangetic Plains, South Asia
- Machine learning innovations for rapid assessments in wheat and rice systems in South Asia.
- Reducing Poverty in South Asia by accelerating irrigation Intensification by influencing groundwater pricing policy in Bangladesh, East India and Nepal
- Climate change and agriculture in South Asia: adaptation options in smallholder production systems
- Array sites established in multiple locations in India, Southeast Asia, Latin America, and Africa
- Factors driving large-scale adoption of sustainable intensification practices in the Indo-Gangetic Plain (Cereal Systems Initiative for South Asia - CSISA)