PIB Summary - 11th October 2025 | PIB (Press Information Bureau) Summary - UPSC PDF Download

Minimum Support Prices: From Safety Net to Self-Sufficiency

Basic Concept

• Minimum Support Price (MSP) is the price set by the government at which it buys crops from farmers. This acts as a safety net for farmers, protecting them from sudden price drops.
• Objective of MSP is to safeguard farmers from having to sell their produce at very low prices, ensure they receive a fair income, encourage them to grow more crops, and support national food security.
• Coverage MSP is announced for 22 main crops, and it has also been extended to include Toria and de-husked coconut.

Policy Framework

• Recommending Body. The Commission for Agricultural Costs and Prices (CACP) recommends the MSP.
• Approval. The Cabinet approves the MSP after consulting with State Governments and Central Ministries.
• Determinants. The MSP is determined based on various factors including:
• Cost of production (A2+FL basis)
• Domestic and international price trends
• Inter-crop price parity
• Terms of trade between agriculture and non-agriculture sectors
• Impact on the economy and inflation
• Formula since 2018-19. MSP is set at 1.5 times the cost of production, ensuring a 50% profit margin for farmers.

Cost Computation

• Cost Computation for MSP Includes: Paid-out costs (A2) and Imputed family labour (FL).
• Components of Cost. Seeds, fertilizers, irrigation, rent for leased land, depreciation, interest, labour, diesel/electricity, and other expenses.
• Uniform Formula. The cost computation formula is applied uniformly across 22 crops and all states.

Rabi Crops (MSP 2026–27)

• Highest MSP margin.
• Wheat — 109% over cost (₹2,585 per quintal).
• Rapeseed & Mustard — 93%.
• Lentil — 89%.
• Highest absolute increase. Safflower — ₹600 per quintal.
• Procurement target. 297 Lakh Metric Tonnes (MT); farmers to receive approximately ₹84,263 crore.

Kharif Crops (MSP 2025–26)

• Highest increase. Nigerseed (+₹820), Ragi (+₹596), Cotton (+₹589).
• Highest margin. Bajra (63%), Maize & Tur (59%).
• Focus. Pulses, oilseeds, and nutri-cereals to encourage diversification beyond traditional cereals.

Procurement Mechanisms

• Lead Agencies for Procurement.
• Food Corporation of India (FCI) for cereals and coarse grains.
• National Agricultural Cooperative Marketing Federation of India (NAFED) and National Cooperative Consumers' Federation of India (NCCF) for pulses, oilseeds, and copra under the PM-AASHA scheme.
• Cotton Corporation of India (CCI) and Jute Corporation of India (JCI) for cotton and jute.
• Estimation Basis for Procurement. Production estimates, surplus availability, and state-level inputs.
• Procurement Limits. No quantitative limits on procurement for cotton and jute.

PM-AASHA (Pradhan Mantri Annadata Aay Sanrakshan Abhiyan)

• Objective of PM-AASHA. To ensure farmers receive remunerative prices for their produce.
• Key Component. Price Support Scheme (PSS) is activated when market prices fall below MSP.
• Procurement Mode under PM-AASHA. Direct procurement from pre-registered farmers with mandatory Aadhaar and land record verification. Through NAFED and NCCF for procurement.
• Financial Provision. PM-AASHA guarantee increased from ₹45,000 crore to ₹60,000 crore in Budget 2025.
• Extension of PM-AASHA. Continued up to FY 2025–26.

From MSP to Atmanirbharta (Self-Sufficiency)

• Goal. To achieve self-reliance in pulses by December 2027.
• Government Commitment. 100% procurement of tur, urad, and masoor pulses up to 2028–29, supported by Budget 2025 announcements.
• Progress. By March 2025, 2.46 LMT of tur procured across 5 states, benefiting over 1.71 lakh farmers.

Impact Analysis (2014–2025)

• Foodgrains Overall.
  • Procurement increased from 761 LMT in 2014–15 to 1,175 LMT in 2024–25.
  • Value disbursed rose from ₹1.06 lakh crore to ₹3.33 lakh crore.
  • Farmers benefitting increased from 1.63 crore in 2021–22 to 1.84 crore in 2024–25.
• Paddy & Kharif Crops.
  • Procurement of paddy increased from 4,590 LMT (2004–14) to 7,608 LMT (2014–25).
  • MSP payout for paddy increased from ₹4.44 lakh crore to ₹14.16 lakh crore.
  • For all 14 Kharif crops, payout increased from ₹4.75 lakh crore to ₹16.35 lakh crore.
• Pulses & Oilseeds.
  • Pulses procurement increased by 7,350%, from 1.52 LMT (2009–14) to 82.98 LMT (2020–25).
  • Oilseeds procurement increased by over 1,500% between 2014 and 2025.
  • Significant decline in import dependence and price volatility for pulses and oilseeds.
• Wheat.
  • RMS 2024–25 procurement target set at 266 LMT, up from 262 LMT (2023–24).
  • ₹0.61 lakh crore credited directly to 22 lakh farmers’ bank accounts.

Technology & Transparency Reforms

• Digital Portals for Procurement.
• e-Samriddhi (by NAFED) for digital end-to-end procurement of pulses and oilseeds.
• e-Samyukti (by NCCF) to track farmer registration, scheduling, and payments.
• Kapas Kisan App (by CCI) for cotton procurement — features self-registration, quality check updates, and multilingual support.
• Benefits of Digital Reforms. Eliminates middlemen, ensures timely payments of MSP, and improves data traceability in the procurement process.

Overall Outcomes

• Economic Security. Tripling of MSP payouts over a decade.
• Wider Inclusion. Over 20 lakh additional farmers benefitted since 2021–22.
• Diversification. Strong emphasis on promoting pulses, oilseeds, and millets.
• Digital Governance. Establishment of a transparent and cashless procurement ecosystem.
• National Self-Reliance. Shift in policy focus from merely providing a safety net to enhancing productivity and substituting imports.

Challenges Ahead

• Regional Skew. Dominance of Punjab and Haryana in procurement, leading to regional imbalances.
• Storage and Logistics. Limitations in storage and logistics for expanded MSP crops, hindering effective distribution.
• Fiscal Burden. Balancing the fiscal burden of increased MSPs with inflation management.
• Private Market Participation. Ensuring private market participation without distorting prices, maintaining a fair market environment.

Conclusion

• MSP has transformed from a basic price guarantee into a vital tool for agricultural self-sufficiency.
• With robust procurement, enhanced digital transparency, and a strong focus on pulses and oilseeds, India is making significant strides towards Atmanirbhar Krishi (self-reliant agriculture).
• The impressive 109% margin on wheat and the commitment to 100% procurement of key pulses reflect a new era of inclusive and technology-driven agricultural governance.

India Accelerates AI Self-Reliance: From Compute Power to Foundation Models

Introduction

• The Ministry of Electronics and Information Technology (MeitY) organized pre-summit events for the India-AI Impact Summit 2026 during the India Mobile Congress 2025 in New Delhi. During this event, it was announced that 12 Indian companies are working on developing AI foundation models using 38,000 GPUs, with a compute cost of ₹65 per GPU per hour, which is among the lowest in the world. 
• This cost-effective infrastructure is expected to facilitate affordable AI model training and innovation.
• A National Large Language Model (LLM) is also set to be launched by the end of 2025. The core objective of these initiatives is to strengthen AI self-reliance and digital sovereignty under the IndiaAI Mission, aiming to build a frugal, inclusive, and globally replicable model for AI development.

 Institutional Framework 

The nodal ministry for this initiative is MeitY, with the IndiaAI under the Digital India Corporation executing the mission. The framework focuses on several pillars, including:

• Affordable Compute Infrastructure: The availability of 38,000 GPUs at a competitive rate of ₹65 per hour, along with a national AI compute grid that ensures parity between the public and private sectors.
• National Data Platform: This component involves the creation of curated, secure, and anonymized datasets to support AI research and development.
• Foundation Model Development: Encouraging the development of indigenous large language models (LLMs) and multimodal models by various companies.
• AI Skilling and Workforce: Initiatives aimed at enhancing AI literacy, reskilling the workforce, and promoting inclusion in the AI sector.
• Safe and Trustworthy AI: Establishing frameworks to ensure the responsible use of AI, mitigate bias, and enhance transparency in AI systems.

 Strategic Context: From Dependence to Digital Atmanirbharta 

• The strategic context of this initiative involves reducing dependence on foreign AI models and compute infrastructure, such as those provided by OpenAI, Google, or Nvidia clouds. 
• India aims to position itself as a “compute-rich, cost-efficient hub” for the Global South, aligning with broader goals like Digital India, Make in India, and Viksit Bharat @2047.

 India-AI Impact Summit 2026: Vision and Themes 

• Date & Venue: The summit is scheduled for 19–20 February 2026 at Bharat Mandapam, New Delhi.
• Theme: The theme for the summit is “From Action to Impact.”
• Guiding Sutras:
  • People: Focus on inclusive and human-centric AI that respects diversity.
  • Planet: Promote sustainable and resource-efficient AI aligned with climate goals.
  • Progress: Ensure equitable access to AI benefits, compute resources, and models.

 Seven Chakras: Operational Pillars of AI Diplomacy 

• Human Capital: Enhance global AI literacy, upskilling, and ensure equitable workforce transitions.
• Inclusion for Social Empowerment: Develop multilingual, gender-neutral, and accessible AI systems to empower marginalized communities.
• Safe and Trusted AI: Implement common safety-testing, auditing, and governance tools to ensure AI safety and trustworthiness.
• Resilience, Innovation & Efficiency: Promote lightweight and resource-optimized AI solutions for real-world applications.
• Science: Foster open and responsible AI research collaborations, especially across the Global South.
• Democratizing AI Resources: Ensure shared access to compute resources, datasets, and AI models.
• AI for Economic Development & Social Good: Focus on deploying AI in sectors like healthcare, education, governance, and agriculture for economic development and social welfare.

 Key Areas of AI Application in Telecom 

• AI in Telecom for Social & Economic Impact: Utilize AI to improve connectivity and develop smart infrastructure in the telecom sector.
• Trustworthy AI in Telecom: Establish frameworks to ensure safety, transparency, and ethical considerations in AI applications within telecom.
• AI Workforce Development: Focus on training engineers and professionals for the integration of AI in telecom.
• AI for Inclusive Growth: Implement AI solutions to bridge digital divides, particularly in rural and underserved areas.

 Institutional Participants 

• Government: Various bodies under MeitY, including the National Informatics Centre (NIC), IndiaAI, and the Centre for Development of Telematics (C-DOT).
• Industry: Major companies like Reliance Jio, Airtel, Tata Consultancy Services (TCS), Amazon Web Services (AWS), AMD, Google, Netweb Technologies, and Tanla Platforms.
• Academia: Institutions such as BITS Pilani contributing to research and development in AI.
• International Agencies: Collaboration with organizations like UNESCO and other global stakeholders in AI.

 Outcomes and Global Relevance 

• India’s AI model is gaining recognition from international agencies for its:
  • Cost-effective scalability.
  • Public–private inclusivity.
  • Replicability for nations in the Global South.
• This initiative reinforces India’s leadership in responsible AI diplomacy, linking digital access with social empowerment.

 Achievements & Recognition 

• The MeitY Pavilion received the Best Government Exhibitor award at IMC 2025.
• This recognition was for its interactive showcase of India’s AI ecosystem and digital innovation.

 Broader Implications 

• Economic: The initiative is expected to boost the domestic AI industry, foster startups, and enhance export potential in AI technologies.
• Strategic: By developing indigenous AI capabilities, India aims to reduce reliance on foreign AI technology, thereby strengthening data sovereignty and security.
• Social: The focus on inclusive digital growth will ensure that AI technologies are accessible to marginalized and underserved communities, promoting social equity.
• Environmental: Encouraging principles of low-energy and sustainable AI design will contribute to environmental conservation and sustainability goals.

 Conclusion 

•  India’s AI strategy is a model of frugal innovation and inclusive modernization, combining affordability with ambitious goals. 
• With the development of national foundation models, accessible compute infrastructure, and fostering global partnerships, India is positioning itself as the AI hub for the Global South. 
• The aim is to ensure that the benefits of Artificial Intelligence are harnessed for the greater good, serving the interests of People, Planet, and Progress.