Prediction model for crop productivity in India

Climate change is predicted to result in a 4%-26% loss in net farm income. Operating in highly resource constrained environment, Indian policy makers and insurance companies often ask which geographies, agriculture seasons, crops and communities are more vulnerable to climate change? To answer this, I have developed a prediction model for crop productivity of top-10 crops in India, at district level--using historical crop-yield data, irrigation, climate, soil, socioeconomic data during 1997-2014. Used machine learning methods random forests, gradient boosting machine, and neural networks for modeling. Finally, predicted crop-yields in near-future using climate forecasts of Global Climate Models.

https://researchday.yale.edu/entityform/186

National implementation: India

Planned for future from 01/02/2018 to 25/05/2018

Yale University, Ministry of Rural Development

* The role of governments and all stakeholders in the promotion of ICTs for development
      * Partnerships
* Enabling environment
* ICT applications: benefits in all aspects of life
      * E-environment
         * Ensure sustainable ICTs
         * Monitor/prevent disasters
      * E-agriculture

• Goal 2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture
• Goal 13: Take urgent action to combat climate change and its impacts
• Goal 15: Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss
• Goal 17: Revitalize the global partnership for sustainable development

• Programme
• Tool-kit
• Database
• Decision Support System/ Data-Driven Policy Making