UPSC MainsGeneral Studies Paper IIIAgriculturePractice question

Last Mile Technology in Agricultural Productivity

"Technology can be a great equalizer only if it reaches the last mile." Analyse the challenges in implementing technological interventions aimed at enhancing farmers' productivity. Suggest suitable strategies to overcome these challenges.

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How to approach

Begin by contextualizing how technological interventions can bridge yield gaps and eliminate information asymmetries, highlighting the structural reality of Indian agriculture dominated by smallholders. Analyse the core economic, infrastructural, social, and institutional bottlenecks that impede last-mile technological adoption. Conclude with actionable strategies such as Farming-as-a-Service, FPO aggregation, vernacular AI, and phygital extension models.

Model answer

402 words

Introduction

Technological interventions—ranging from precision irrigation and IoT-driven soil monitoring to AI-powered advisories—possess transformative potential to bridge farm yield gaps and eliminate informational asymmetries. However, their equalizing power falters at the last mile, where small and marginal farmers operate 86.2% of Indian landholdings with an average size of just 1.08 hectares, limiting access to high-cost and infrastructure-dependent innovations.

Challenges in Implementing Last-Mile Agricultural Technology

  • Economic and Scale Barriers: High capital expenditure for precision tools such as drones, laser land levelers, and IoT sensors yields a low return on investment on fragmented, sub-hectare landholdings.
  • The Digital-Physical Divide: Uneven rural broadband coverage, erratic three-phase rural power supply, and low digital literacy constrain the real-time functionality of automated irrigation, sensor networks, and smartphone-based advisory apps.
  • Informal Tenancy and Land Record Deficits: Outdated land records and unrecorded tenancy exclude millions of sharecroppers and tenant cultivators from digital farmer registries like AgriStack, denying them access to tech-driven credit and input subsidies.
  • Algorithmic Disconnect and Lack of Localization: Top-down, generic mobile advisories often lack vernacular accessibility and hyper-local micro-climatic precision, driving smallholders back to trusted, informal input-dealer networks.
  • Deficits in Supporting Physical Infrastructure: Digital price-discovery platforms such as e-NAM cannot deliver full benefits without village-level assaying labs, cold chain networks, and seamless multi-modal logistics.

Strategies to Overcome Adoption Challenges

  • Farming-as-a-Service (FaaS) via Custom Hiring Centres: Democratise expensive technology by expanding Custom Hiring Centres (CHCs) under the Sub-Mission on Agricultural Mechanization (SMAM), providing affordable, pay-per-use drone spraying and mechanisation services.
  • Aggregated Adoption through FPOs: Leverage Farmer Producer Organisations (FPOs) to pool landholdings, reduce capital overheads for collective tech deployment, and connect producers directly to e-commerce and digital mandis.
  • Vernacular and Voice-Based AI Systems: Integrate the Digital Agriculture Mission with national AI initiatives like Bhashini to deploy local-language, voice-based chatbots (such as Kisan e-Mitra) that overcome literacy barriers.
  • Phygital Extension Delivery: Combine digital tools with human intermediaries by deploying Krishi Sakhis, Community Resource Persons, and Krishi Vigyan Kendras (KVKs) to ground-truth data and build farmer trust.
  • Institutional and Tenancy Reforms: Adopt the Model Agricultural Land Leasing Act across states to formalise tenant cultivators, enabling their onboarding onto Digital Public Infrastructure (DPI) and institutional credit channels.

Conclusion

Bridging the last-mile adoption gap transforms agricultural technology from an elitist efficiency tool into an instrument of social and economic equity. Ensuring that modern agronomic tools are affordable, localized, and inclusive is critical for building climate-resilient agriculture and achieving inclusive rural prosperity under Viksit Bharat 2047.

Key facts to remember

statistic

Small and marginal farmers account for 86.2% of all operational landholdings in India, operating an average parcel size of only 1.08 hectares.

Agriculture Census 2015-16
scheme
Digital Agriculture Mission

An initiative launched with an outlay of ₹2,817 crore to build foundational Digital Public Infrastructure (DPI) for agriculture, including AgriStack and the Krishi Decision Support System.

example
Kisan e-Mitra AI Chatbot

An AI-powered voice chatbot integrated with PM-KISAN that delivers real-time scheme updates and advisories in multiple regional languages to overcome literacy barriers.

definition
Farming-as-a-Service (FaaS)

A business model that delivers pay-per-use mechanisation, precision agriculture, and equipment access to farmers without requiring upfront capital ownership.

Frequently asked questions

Why do precision agriculture technologies face poor adoption among small farmers in India?

High capital costs, land fragmentation, lack of digital literacy, and irregular rural power supply make direct individual ownership economically unviable for smallholders without collective models like Custom Hiring Centres.