Content

1. Minimum Support Prices: From Safety Net to Self-Sufficiency
2. India Accelerates AI Self-Reliance: From Compute Power to Foundation Models

Minimum Support Prices: From Safety Net to Self-Sufficiency

Basic Concept

• Minimum Support Price (MSP): The pre-announced price at which the government purchases crops from farmers, acting as a safety net against price fluctuations.
• Objective:
  • Protect farmers from distress sales.
  • Ensure fair income and incentivize production.
  • Promote crop diversification and national food security.
• Coverage: Announced for 22 mandated crops; also extended to Toria and de-husked coconut.

Relevance : GS 3 – Agriculture, Inclusive Growth, Government Policies, Food Security, MSP Reforms

Policy Framework

• Recommending Body: Commission for Agricultural Costs and Prices (CACP).
• Approval: By the Cabinet, after consulting State Governments and Central Ministries.
• Determinants:
  • Cost of production (A2+FL basis).
  • Domestic & international price trends.
  • Inter-crop price parity.
  • Terms of trade (agriculture vs non-agriculture).
  • Effect on economy & inflation.
• Formula since 2018-19: MSP = 1.5 × cost of production (ensuring 50% profit margin).

Cost Computation

• Includes: Paid-out costs (A2) + Imputed family labour (FL).
• Components: Seeds, fertilizers, irrigation, rent for leased land, depreciation, interest, labour, diesel/electricity, etc.
• Uniform Formula: Applied across 22 crops and all states.

Rabi Crops (MSP 2026–27)

• Highest MSP margin:
  • Wheat — 109% over cost (₹2,585/qtl).
  • Rapeseed & Mustard — 93%.
  • Lentil — 89%.
• Highest absolute increase:
  • Safflower — ₹600/qtl.
• Procurement target: 297 Lakh MT; farmers to receive ~₹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 — incentivizing diversification beyond cereals.

Procurement Mechanisms

• Lead Agencies:
  • FCI — Cereals & coarse grains.
  • NAFED & NCCF — Pulses, oilseeds, copra (under PM-AASHA).
  • CCI & JCI — Cotton and jute.
• Estimation Basis: Production, surplus, and state-level inputs.
• No quantitative limit on procurement for cotton & jute.

PM-AASHA (Pradhan Mantri Annadata Aay Sanrakshan Abhiyan)

• Objective: Ensure remunerative prices for farmers.
• Key Component: Price Support Scheme (PSS) — activated when market prices < MSP.
• Procurement Mode:
  • Direct from pre-registered farmers (Aadhaar, land records mandatory).
  • Through NAFED and NCCF.
• Financial Provision: PM-AASHA guarantee raised from ₹45,000 crore to ₹60,000 crore (Budget 2025).
• Extension: Continued up to FY 2025–26.

From MSP to Atmanirbharta (Self-Sufficiency)

• Goal: India to become self-reliant in pulses by December 2027.
• Government Commitment:
  • 100% procurement of tur, urad, and masoor up to 2028–29.
  • Supported by Budget 2025 announcements.
• Progress:
  • By March 2025, 2.46 LMT tur procured across 5 states.
  • 1.71 lakh+ farmers benefitted.

Impact Analysis (2014–2025)

a. Foodgrains Overall

• Procurement: ↑ from 761 LMT (2014–15) to 1,175 LMT (2024–25).
• Value disbursed: ↑ from ₹1.06 lakh crore → ₹3.33 lakh crore.
• Farmers benefitted: ↑ from 1.63 crore (2021–22) → 1.84 crore (2024–25).

b. Paddy & Kharif Crops

• Procurement: ↑ from 4,590 LMT (2004–14) → 7,608 LMT (2014–25).
• MSP payout: ↑ from ₹4.44 lakh crore → ₹14.16 lakh crore (paddy).
• For all 14 Kharif crops: ↑ from ₹4.75 lakh crore → ₹16.35 lakh crore.

c. Pulses & Oilseeds

• Pulses procurement: ↑ 7,350%, from 1.52 LMT (2009–14) → 82.98 LMT (2020–25).
• Oilseeds procurement: ↑ over 1,500% (2014–25).
• Marked decline in import dependence and price volatility.

d. Wheat

• RMS 2024–25 procurement: 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:
  • e-Samriddhi (NAFED): End-to-end digital procurement for pulses & oilseeds.
  • e-Samyukti (NCCF): Tracks farmer registration, scheduling, payments.
  • Kapas Kisan App (CCI): For cotton — self-registration, quality check updates, multilingual interface.
• Benefits: Eliminates middlemen, ensures timely MSP payments, improves data traceability.

Overall Outcomes

• Economic Security: Tripling of MSP payouts in a decade.
• Wider Inclusion: 20 lakh+ additional farmers benefitted since 2021–22.
• Diversification: Strong push toward pulses, oilseeds, and millets.
• Digital Governance: Transparent, cashless procurement ecosystem.
• National Self-Reliance: Policy shift from safety net → productivity & import substitution.

Challenges Ahead

• Regional skew in procurement (Punjab-Haryana dominance).
• Storage and logistics limitations for expanded MSP crops.
• Balancing fiscal burden and inflation management.
• Ensuring private market participation without price distortion.

Conclusion

• MSP has evolved from a price safety mechanism into a strategic tool for self-sufficiency.
• With strong procurement, digital transparency, and focus on pulses & oilseeds, India is progressing toward Atmanirbhar Krishi.
• The 109% margin on wheat and 100% procurement guarantee for pulses mark a new phase of inclusive, data-driven, and technology-enabled agricultural governance.

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

Why in News

• MeitY hosted Pre-Summit events for the India–AI Impact Summit 2026 during India Mobile Congress 2025 in New Delhi.
• Announced:
  • 12 Indian companies developing AI foundation models using 38,000 GPUs.
  • Compute Cost: ₹65 per GPU per hour — among the lowest globally, ensuring affordable AI model training and innovation access.
  • National Large Language Model (LLM) to be launched by end of 2025.

Relevance : GS 3 – Science & Technology, IT and Computers, Indigenization of Technology, Digital Economy

Core Objective

• Strengthen AI self-reliance and digital sovereignty under the IndiaAI Mission.
• Build a frugal, inclusive, and globally replicable model for AI development — leveraging affordability, public-private collaboration, and equitable access.

Institutional Framework

• Nodal Ministry: Ministry of Electronics and Information Technology (MeitY)
• Mission Executing Body: IndiaAI under Digital India Corporation

IndiaAI Mission: Pillars of AI Self-Reliance

• Affordable Compute Infrastructure:
  • 38,000 GPUs available at ₹65/hour (among the world’s lowest).
  • National AI compute grid enabling public and private sector parity.
• National Data Platform:
  • Curated, secure, and anonymized datasets for AI R&D.
• Foundation Model Development:
  • 12 companies developing indigenous LLMs and multimodal models.
• AI Skilling and Workforce:
  • Initiatives for AI literacy, reskilling, and inclusion.
• Safe and Trustworthy AI:
  • Frameworks for responsible use, bias mitigation, and transparency.

Strategic Context: From Dependence to Digital Atmanirbharta

• Reducing dependency on foreign AI models and compute infrastructure (like OpenAI, Google, or Nvidia clouds).
• India aims to emerge as a “compute-rich, cost-efficient hub” for the Global South.
• Alignment with Digital India, Make in India, and Viksit Bharat @2047 goals.

India-AI Impact Summit 2026: Vision and Themes

• Date & Venue: 19–20 February 2026, Bharat Mandapam, New Delhi.
• Theme: “From Action to Impact.”
• Guiding Sutras:
  • People: Inclusive, human-centric AI respecting diversity.
  • Planet: Sustainable, resource-efficient AI aligned with climate goals.
  • Progress: Equitable access to AI benefits, compute, and models.

Seven Chakras: Operational Pillars of AI Diplomacy

1. Human Capital: Global AI literacy, upskilling, and equitable workforce transition.
2. Inclusion for Social Empowerment: Multilingual, gender-neutral, accessible AI systems.
3. Safe and Trusted AI: Common safety-testing, auditing, and governance tools.
4. Resilience, Innovation & Efficiency: Lightweight, resource-optimized AI for real-world use.
5. Science: Open and responsible AI research collaborations across the Global South.
6. Democratizing AI Resources: Shared access to compute, datasets, and models.
7. AI for Economic Development & Social Good: AI deployment in healthcare, education, governance, and agriculture.

Key Areas of AI Application in Telecom

• AI in Telecom for Social & Economic Impact: Improved connectivity, smart infrastructure.
• Trustworthy AI in Telecom: Frameworks for safety, transparency, and ethics.
• AI Workforce Development: Training engineers and professionals for telecom-AI integration.
• AI for Inclusive Growth: Bridging digital divides in rural and underserved areas.

Institutional Participants

• Government: MeitY, NIC, IndiaAI, C-DOT.
• Industry: Reliance Jio, Airtel, TCS, AWS, AMD, Google, Netweb Technologies, Tanla Platforms.
• Academia: BITS Pilani.
• International Agencies: UNESCO and other global AI stakeholders.

Outcomes and Global Relevance

• India’s AI model recognized by international agencies for:
  • Cost-effective scalability.
  • Public–private inclusivity.
  • Replicability for Global South nations.
• Reinforces India’s leadership in responsible AI diplomacy, linking digital access with social empowerment.

Achievements & Recognition

• MeitY Pavilion awarded Best Government Exhibitor at IMC 2025.
• Acknowledged for interactive showcase of India’s AI ecosystem and digital innovation.

Broader Implications

• Economic: Boosts domestic AI industry, startups, and export potential.
• Strategic: Reduces reliance on foreign AI tech, enhancing data sovereignty.
• Social: Promotes inclusive digital growth, AI accessibility for marginalized groups.
• Environmental: Encourages low-energy, sustainable AI design principles.

Conclusion

India’s AI strategy exemplifies frugal innovation and inclusive modernization, blending affordability with ambition.
With national foundation models, accessible compute infrastructure, and global partnerships, India is positioning itself as the AI hub of the Global South—ensuring that the power of Artificial Intelligence serves People, Planet, and Progress.