Soramitsu CBDC and Ryobi Systems Selected for Tokyo's 'Global South GX Promotion Project' for AWD Farming and Digital Currency Environmental Value Return Model

Soramitsu CBDC Co., Ltd. and Ryobi Systems Co., Ltd. announced that their 'Feasibility and Demonstration Project for Decarbonization through AWD Farming Promotion and Environmental Value Return Model using Digital Currency in Bangladesh' has been selected for the Tokyo Metropolitan Government's 'Global South GX Promotion Project.'

In 2025, Ryobi Systems demonstrated AWD farming in Bangladesh, achieving over 20% productivity improvement and approximately 30% methane emission reduction. They are currently scaling this initiative to reduce greenhouse gas emissions in the country's rice production. This new project aims to enhance water management efficiency, reduce MRV (Measurement, Reporting, and Verification) burden, and establish a framework to return environmental value using digital currency.

●Background Bangladesh is one of the world's leading rice-producing nations. However, due to outdated agricultural technology and financial constraints for farmers, improving productivity and stabilizing income remain challenges. While AWD farming is effective in reducing greenhouse gas emissions by managing water levels in paddies, widespread adoption faces challenges in streamlining water management, verifying emission reductions, and designing economic incentives for farmers.

Soramitsu CBDC has successfully tackled social issues including geopolitical concerns and economic security across six countries, including Cambodia and Laos. Promoting AWD farming and introducing digital currency will contribute not only to decarbonization but also to the country's economic development.

●Project Scope - Duration: Until March 31, 2028. - Scope: Starting with feasibility studies to consider moving to full-scale demonstration and commercialization phases. 1. Demonstration of labor-saving, high-precision water management By combining Japanese automated sluice gates and water level sensors with AI image analysis, the project will notify farmers to operate gates based on detected water levels, aiming to balance reduced workload with precise water management.