Mumbai: Dr Ashish Kumar Bhutani, CEO, PMFBY and Joint Secretary (Credit), Ministry of Agriculture and Farmers Welfare, has said that the government is putting up a common data infrastructure of all the farmers in the country. “PMFBY, PM-Kisan, the Soil health Card, are all being integrated through a common database along with land record details over the period of time. This will act as a one stop shop for data, including access to finance by farmers, start-ups, and researchers for developing new apps, so that the benefits reach the grassroots,” he added. 

Addressing a webinar on AI & Digital Applications in Agriculture, organized by FICCI, jointly with the German Agribusiness Alliance, Dr Bhutani said that the data will be reliable, and that the government is targeting to launch this soon. “The government acting as an enabler is a critical factor in faster adoption of AI,” he said. 

Dr Bhutani further stated that developing standards for sharing and improving the quality of data will be monitored closely by the government. “The government is working to provide an enabling environment where the private players and government can work together to bring the benefit of AI to all the farmers and the consumers. This will also help in bringing down the price for the consumers as well as getting the best price for the farmers,” he emphasized. 

Dr Bhutani added that India has about 145 million farmlands with very small holding size, which is around one hectare per holder. The target of doubling farmers’ income is a massive task to be achieved. “Artificial Intelligence would play a major role in ensuring that targets are met. There is a need for digitalization in the agriculture sector,” he added. 

Elaborating on the PMFBY (Pradhan Mantri Fasal Bima Yojna), he said that since its launch, the scheme has been a radical shift in the way crop insurance is implemented in the country. It is the third biggest program in the world after the US and China’s programs. “Technology is the way forward for implementation of the program.

 Dr Bhutani said that the biggest challenge is to increase the production by 50 percent over the next 20-30 years with limited scope of increase in the farming area. “The entire focus has shifted to using technology for managing the food security and other aspects of agriculture. AI can be effectively used in soil monitoring, predictive data analytics and improving supply chain inefficiencies. The National e-Governance project on agriculture, which has been revisited this year, has given focus on using information technology, AI, Machine Learning etc.,” he noted.  He further stated that the use of AI and digital technologies for smart crop cutting experiments will further improve the accuracy of forecasts and lead to effective implementation of the PMFBY. 

FICCI-PwC Report ‘Ushering in new growth wave: From Artificial Intelligence to Agricultural Intelligence’

Key highlights of the report:

  1. Globally, the market size of AI in agriculture stood at USD 0.85 billion in 2019, and it is expected to reach USD 8.4 billion by 2030, with a CAGR of 24.8%.
  2. Precision agriculture and farm management is the largest category within the AI (Artificial Intelligence) and related technology segment, wherein predictive analysis is the fastest growing subcategory.
  3. Mobile connection penetration in India  will increase to 85% by 2025 from the current level of 78%, while smartphone adoption is forecasted to reach to 84% by 2025 from its current level of 67% –  a strong AI & Tech enabler.
  4. Important AI & Tech solutions for Agri-value chain issues: 
  • Predictive Analytics & Machine learning for volatility in input prices & suboptimal input usages
  • Imaging and AI to monitor input as well as output quality and traceability
  • Data platforms for price transparency
  • Agbots and drones for Operational challenges during farm operations

5. Strategic interventions to catalyse AI adoption scenario in India:  FICCI PwC Ten-point Agenda

  1. Development of country-specific platform to address asymmetry in information:  It will ensure that multiple data points or knowledge portals are aggregated into a single integrated agriculture platform.
  2. Improving digital literacy among farmers: This will help to bring more imaginative in designing solutions and interfaces that are socially embedded and localised in relation to socio-cultural and agronomic contextualities.
  3. Identifying & Developing effective channels for dissemination of AI solutions among farming communities: Business to farmers channels is suited for disruptive technologies, Digital Agripreneurs- suited for progressive technologies, FPOs – suited for capacity building and Start up- tech companies- Govt collaboration: suited for diffusion tech.
  4. Promoting ultimate use of AI data for effective, accessible and affordable solutions: Information sources, such as satellites, drones and weather-related data can be combined with the results of crop-cutting experiments to improve the accuracy of forecasts and many related solutions.
  5. Establishment of skill development centres for training on AI tools: Establishment of Skill Development Centres (SDCs) would support the creation of reliable AI-extension experts in the market. A last mile delivery approach.
  6. Fostering sustainable linkages among private players and PPP: This will help to cross pollinate ideas amongst private platforms of varied scale and emerge PPP.
  7. Promoting linkages between private players and state agriculture universities: This will help the AI tech to customize the IT tech with Agri tech and hence make more meaningful offerings.
  8. Categorisation for effective dissemination of digital technologies: Identification of two broad categories of innovation, i.e. social embeddedness-led innovation and transfer and diffusion-led innovation. This will lead to reduce the adoption lag time and enhance faster technology infusion.
  9. Artificial intelligence (AI) can be applied to predict current sowing time and provide advisories on pest and input control. This can help in ensuring increased yield and also reduce effective input costs thereby enhancing farm income.
  10. AI will immensely help in reducing wastage and losses. It will ensure judicious use of resources, therefore promoting precision farming and enabling sustainable farming systems.