Syllabus: GS-III: Agriculture 

Why in the news?

A recent report by The Associated Chambers of Commerce and Industry of India (ASSOCHAM) warns that around 86 % of India’s farmers remain beyond the reach of mainstream agricultural-technology solutions. The report calls for a radical redesign of how agri-tech is validated, commercialised and delivered to smallholder farmers.

What’s broken: The fragmentation

• India’s agriculture technology landscape is highly fragmented. 
• There are over 90 institutes under ICAR, 60 State Agricultural Universities (SAUs), and more than 700 Krishi Vigyan Kendras (KVKs) — yet a unified system to test and scale emerging technologies is missing.
• Agricultural data is locked in silos: research data with ICAR/SAUs; market data with State marketing boards; farm-level adoption data with private agri-tech startups. 
  • This limits the development of innovation that depends on verified, shared data.
• Many agri-tech startups still follow product-centric models, not always aligned with small farmers’ affordability, local context, and capability. 
  • The report says there must be a shift to “context-fit” models.

What the report recommends

• State-level agri-tech sandboxes
  • These are collaborative testbeds where government agencies, startups and research institutions pilot technologies under real-world conditions before full-scale roll-out.
  • Anchored at the State agriculture departments, with participation from allied departments, ICAR institutions, SAUs & development banks (e.g., NABARD).
• Unified data framework – Agricultural Data Commons
  • Built on FAIR principles (Findable, Accessible, Interoperable, Reusable) as recommended by the Food and Agriculture Organization (FAO).
  • For example, the ADeX – Agricultural Data Exchange in Telangana, developed in partnership with the World Economic Forum, is cited as a model.
• Business and financing innovation
  • For low-cost technologies: direct-to-farmer retail models.
  • For complex or capital-intensive tech: collaborative ownership models, access-based services, and outcome-linked commercialisation.
  • Policy measures: innovative financing (credit-linked adoption loans, crop-cycle repayments), tax incentives for agri-tech investment, and strengthening last-mile infrastructure (cold chains, storage, logistics).
• Upskilling and inclusion
  • Farmers and Farmer Producer Organisations (FPOs) need digital literacy and advisory tools (including AI-enabled) so that technology adoption becomes meaningful.

Why this matters for India

• Agriculture supports nearly half of India’s population, yet productivity and profitability remain constrained by inefficient technology adoption and uneven access.
• Technology alone is insufficient: if small farmers cannot access, trust or afford innovations, the potential of India’s agri-tech revolution remains untapped.
• A unified ecosystem would help: bring together research, startups, government and data; enable validation of solutions; ensure scalability; and reduce duplication and waste.
• It also ties into broader goals such as doubling farmers’ income, making agriculture climate-resilient and sustainable (for which the Pradhan Mantri Krishi Sinchayee Yojana, PM-KISAN, and other digital agriculture initiatives play supportive roles). 
  • The report focuses more on the systems of innovation, validation and delivery rather than schemes per se.

Key terms explained

• Agri-tech sandbox: A controlled environment where new agricultural technologies are trialled under real-world conditions, with stakeholder involvement and monitoring, before full deployment.
• Data silos: Situations where data is held separately by different organisations, preventing sharing and integration — hindering unified analytics and decision-making.
• FAIR principles: A set of guidelines for data management and stewardship ensuring that data is Findable, Accessible, Interoperable and Reusable.
• Context-fit model: A technology or business approach tailored to the local conditions of the farmer (costs, scale, language, capability), rather than a one-size-fits-all product.
• Outcome-linked commercialisation: Business models where payment or adoption of a technology is tied to achieving specific results (for example yield improvements), thus aligning incentives of farmers, providers and investors.
  

Way Ahead

• State governments should launch pilot sandboxes urgently, integrate them with State agriculture departments, research institutions and development banks.
• The central government (via the Ministry of Agriculture & Farmers Welfare and NITI Aayog) should set up a national steering committee to oversee governance and funding of the sandbox ecosystem, as the report suggests.
• Build the Agricultural Data Commons, adopt open-data standards, and break down silos between research, market and operational data.
• Encourage agri-tech startups and service providers to adopt business models aligned with small and marginal farmers — low cost, high relevance, and local language support.
• Strengthen last-mile delivery: infrastructure, logistics, extension services, and digital literacy — so innovations don’t just stay in labs but reach the farmer’s field.

Key Take-aways (Exam Hook)

• India’s agri-tech ecosystem today is fragmented and unequal; about 86% of farmers are yet to benefit from innovations.
• A unified, systemic approach — combining state-level testing sandboxes, data commons, context-fit business models and capacity building — is crucial to scale impact.

Mains Question: 

“Examine the key barriers to agri-technology adoption for smallholders in India and evaluate the institutional reforms needed to build a unified agri-tech ecosystem.”

SOURCE