Content
- India’s Mission for Aatmanirbharta in Pulses
- Transforming India with AI
India’s Mission for Aatmanirbharta in Pulses
Why in News
- Launched by PM Narendra Modi on October 11, 2025, at IARI, New Delhi.
- Outlay: ₹11,440 crore (2025–26 to 2030–31).
- Goal: Achieve complete self-reliance in pulses by 2030–31 and eliminate import dependence by December 2027.
Relevance : GS 3 – Agriculture, Inclusive Growth, Food Security, Nutritional Security, MSP Reforms, Sustainable Farming
Background and Context
- India is theWorld’s largest producer (≈25%), consumer (≈27%), and importer (≈14%) of global pulses.
- Current production (2024–25): 252.38 lakh tonnes (↑31% since 2013–14).
- Imports (2023–24): 47.38 lakh tonnes; exports: 5.94 lakh tonnes.
- Despite progress, domestic production lags behind demand, necessitating a self-reliance mission.
- Aligned with Vision 2047 and Aatmanirbhar Bharat Abhiyan.
Significance of Pulses
- Contribute 20–25% of total protein intake in Indian diets (NIN data).
- Crucial for nutritional security, soil nitrogen fixation, and farm income diversification.
- Per capita consumption below recommended 85 g/day — linked to protein deficiency.
- Environmental benefits: low water footprint, improves soil fertility and sustainability.
Mission Objectives
- Achieve Aatmanirbharta (self-sufficiency) in pulses by 2030–31.
- Expand pulses area to 310 lakh ha (↑35 lakh ha from 2024–25 baseline).
- Increase production to 350 lakh tonnes; improve yield to 1,130 kg/ha.
- Reduce imports to zero and ensure 100% MSP procurement for Tur, Urad, and Masoor for four years.
- Empower 2 crore farmers via quality seeds, procurement assurance, and market linkage.
Key Components and Interventions
- Seed Revolution:
- 126 lakh quintals of certified seeds distributed.
- 88 lakh free seed kits to farmers.
- Use of SATHI (seedtrace.gov.in) for seed authentication and traceability.
- Development of high-yielding, pest-resistant, and climate-resilient varieties.
- Procurement Security:
- 100% MSP procurement of Tur, Urad, and Masoor under PM-AASHA.
- NAFED and NCCF to manage procurement.
- Value Chain & Infrastructure:
- Establish 1,000 processing and packaging units, with subsidies up to ₹25 lakh/unit.
- Focus on cluster-based approach (as per NITI Aayog recommendations).
- Soil & Climate Sustainability:
- Promotion of balanced fertilizer use, intercropping, crop diversification, and mechanization.
- Integration with ICAR and KVKs for field demonstrations and technology dissemination.
Technological & Institutional Innovations
- SATHI Portal (Seed Authentication, Traceability & Holistic Inventory):
- Tracks the full seed life cycle — from breeder seed to sale.
- Ensures quality assurance, transparency, and accountability in seed supply.
- Digital Monitoring:
- Data-driven decision-making via SAATHI and ICAR monitoring systems.
- Breeder & Foundation Seed Plans:
- State-wise rolling five-year seed production plans supervised by ICAR.
PM-AASHA Integration
- Launched: 2018, continued in 2024.
- Components: Price Support Scheme (PSS), Price Deficiency Payment Scheme (PDPS), Market Intervention Scheme (MIS).
- Objective: Protect farmers from distress sales, ensure price stability, and promote pulses and oilseeds cultivation.
NITI Aayog’s Recommendations (Sept 2025 Report)
- Based on survey of 885 farmers from Rajasthan, MP, Gujarat, Andhra Pradesh, and Karnataka.
- Key Suggestions:
- Expand pulses into rice fallows and diversify cropping patterns.
- Develop “One Block–One Seed Village” model for seed self-sufficiency.
- Strengthen FPO-based seed hubs for localized production.
- Promote mechanization, efficient irrigation, and bio-fertilizers.
- Introduce climate-resilient and short-duration varieties.
- Establish local procurement centers and processing units to minimize middlemen.
- Integrate pulses into PDS, Mid-Day Meal, and Poshan Abhiyan to boost demand and nutrition.
Implementation Framework
- Nodal Agency: Ministry of Agriculture & Farmers’ Welfare.
- Collaborating Institutions: ICAR, KVKs, NAFED, NCCF, State Agri Departments, and FPOs.
- Timeline: 2025–26 to 2030–31 (six years).
- Cluster-Based Implementation: Regional specialization for Tur (Deccan plateau), Urad (Central India), and Masoor (Northern plains).
Expected Outcomes
- Self-sufficiency by 2027 for key pulses (Tur, Urad, Masoor).
- Zero import dependence by 2030–31.
- Increase in farmers’ income through assured MSP and value addition.
- Strengthened seed and processing infrastructure across India.
- Foreign exchange savings by cutting import bills.
- Improved soil fertility, climate resilience, and employment generation in rural areas.
Challenges Ahead
- Yield gaps due to climatic variability and pest resistance.
- Low mechanization and poor irrigation coverage in pulse-growing belts.
- Ensuring timely MSP procurement and payments.
- Balancing expansion with ecological sustainability and water management.
- Need for strong coordination among central, state, and cooperative agencies.
Conclusion
- The Mission for Aatmanirbharta in Pulses is a landmark step toward nutritional security, import substitution, and farmer empowerment.
- Integrates science, policy, and market reforms to transform India’s pulses sector.
- By 2030–31, India aims not only to be self-reliant but also a global leader in sustainable pulse production, contributing to Viksit Bharat 2047 through resilient agriculture, healthy citizens, and prosperous farmers.
Value Addition
Major Pulses Grown in India
| Pulse Type | Major Producing States | Sowing Season | Key Growing Conditions |
| Tur (Arhar/Pigeon Pea) | Maharashtra, MP, Karnataka, UP, Gujarat | Kharif (June–July) | Warm climate; 25–35°C; rainfall 600–1000 mm; well-drained loamy soils |
| Urad (Black Gram) | MP, UP, Maharashtra, Rajasthan, Tamil Nadu | Kharif & Rabi | Tolerant to drought; requires 25–30°C; medium black soils |
| Moong (Green Gram) | Rajasthan, MP, Maharashtra, Karnataka, Andhra Pradesh | Kharif & Summer | 25–35°C; short-duration crop (60–70 days); sandy loam soils |
| Masoor (Lentil) | MP, UP, Bihar, West Bengal, Rajasthan | Rabi (Nov–Apr) | Cool temperature; 18–25°C; requires moderate irrigation |
| Gram (Chickpea) | MP, Maharashtra, Rajasthan, UP, Karnataka | Rabi (Oct–Feb) | Semi-arid climate; 20–25°C; loamy to sandy soils |
| Peas (Matar) | UP, Bihar, MP, Punjab, Haryana | Rabi | Cool, temperate climate; 15–20°C; clay-loam soils |
| Cowpea (Lobia) | Rajasthan, Gujarat, Karnataka, Tamil Nadu | Kharif/Summer | Drought-tolerant; sandy soils |
Area and Production (2024–25: 3rd Advance Estimates)
| Parameter | Data |
| Total Area under Pulses | ~275 lakh hectares |
| Production | ~252.38 lakh tonnes |
| Productivity | ~915 kg/ha |
| Top Producer State | Madhya Pradesh (~30% of India’s total) |
| Largest Exported Pulses | Chickpea (mainly to Bangladesh, UAE, and Nepal) |
State-Wise Contribution (Share in Total Production, 2024–25 est.)
| Rank | State | Share (%) | Major Crops |
| 1 | Madhya Pradesh | 30–32 | Gram, Tur, Urad, Masoor |
| 2 | Maharashtra | 15–17 | Tur, Gram, Urad, Moong |
| 3 | Rajasthan | 12–13 | Moong, Gram |
| 4 | Karnataka | 8–9 | Tur, Urad |
| 5 | Uttar Pradesh | 7–8 | Gram, Masoor, Pea |
Agro-Climatic Suitability
- Pulses can be grown in rainfed, marginal, and arid conditions.
- Optimal conditions:
- Temperature: 18–35°C (varies by crop).
- Rainfall: 400–1000 mm.
- Soils: Loamy, sandy loam, or black cotton soils with good drainage.
- Pulses are short-duration crops (60–120 days) ideal for intercropping and crop rotation.
Pulses and Soil Health
- Nitrogen fixation: Pulses host Rhizobium bacteria in root nodules, fixing atmospheric N₂ into soil — reduces fertilizer use.
- Improves soil structure and organic matter, promoting sustainable agriculture.
- Ideal for inclusion in crop rotation systems (e.g., Tur–Wheat, Gram–Maize).
Transforming India with AI
Why in News
- IndiaAI Mission (₹10,371.92 crore) has achieved 38,000 GPUs, marking a major step in AI infrastructure.
- India is positioning itself as a global AI hub, combining inclusive innovation with economic transformation.
Relevance : GS 3 – Science & Technology, IT & Computers, Inclusive Growth, E-Governance, Innovation & Employment Generation
What is Artificial Intelligence (AI)?
- Definition: AI enables machines to perform tasks that require human-like intelligence — learning, reasoning, decision-making, and problem-solving.
- Core Components:
- Machine Learning (ML) – Algorithms that learn from data.
- Deep Learning (DL) – Neural networks mimicking human brain patterns.
- Natural Language Processing (NLP) – Understanding human language.
- Computer Vision – Image and pattern recognition.
- Generative AI – Produces new content (text, image, audio).
- India’s approach: “AI for All” — open, affordable, and accessible.
AI Landscape in India (2025 Snapshot)
- Tech Revenue: Projected to cross $280 billion (2025).
- Employment: 6 million people in tech & AI ecosystem.
- Startups: 1.8 lakh total, with 89% using AI.
- Global Capability Centres (GCCs): 1,800+, with 500+ AI-focused.
- AI Adoption: 87% enterprises use AI; NASSCOM Index score 2.45/4.
- Sectors leading adoption: BFSI, Healthcare, Retail, Manufacturing, and Automotive (≈60% of AI value).
- Global Recognition:
- Top 4 in AI skills and policy ecosystem (Stanford AI Index 2025).
- 2nd largest contributor to AI projects on GitHub.
Economic Impact
- Projected contribution: $1.7 trillion to India’s GDP by 2035 (NITI Aayog estimate).
- Boosts productivity, governance efficiency, and innovation across public and private sectors.
- Aligns with Viksit Bharat 2047 — technology-driven inclusive development.
IndiaAI Mission (Launched 2024)
- Budget: ₹10,371.92 crore (5 years).
- Vision: “Make AI in India and Make AI Work for India.”
- Implementing Agency: IndiaAI Division under MeitY.
- GPU Capacity: Target of 10,000 → achieved 38,000 GPUs (affordable compute at ₹65/hour).
Seven Pillars of the IndiaAI Mission
| Pillar | Focus | Key Outcomes |
| 1. IndiaAI Compute | Affordable high-end GPUs | 38,000 GPUs deployed |
| 2. IndiaAI Application Development | AI for India-specific challenges | 30+ approved apps (cybersecurity, agriculture, climate) |
| 3. AIKosh (Data Platform) | Unified data repository | 3,000 datasets, 243 AI models, 6,000 registered users |
| 4. IndiaAI Foundation Models | Indigenous LLMs | 4 startups selected (Sarvam, Soket, Gnani, Gan AI) |
| 5. IndiaAI FutureSkills | AI talent ecosystem | 13,500 fellowships, 27 AI labs in Tier-2/3 cities |
| 6. IndiaAI Startup Financing | Funding & global expansion | Collaboration with Station F (Paris), 10 startups supported |
| 7. Safe & Trusted AI | Ethics, privacy, bias mitigation | 8 research projects, AI Safety Institute in progress |
Supporting Initiatives
A. Centres of Excellence (CoEs)
- Focus sectors: Healthcare, Agriculture, Sustainable Cities, Education.
- Linked with 5 National Centres for AI Skilling.
B. AI Competency Framework
- Structured AI training for government officials to enhance policy and service design.
C. IndiaAI Startups Global Acceleration Programme
- Collaboration with Station F and HEC Paris to globalize Indian AI innovation.
Key Indian AI Projects
| Initiative | Purpose | Impact |
| Sarvam AI | Building India’s sovereign LLM ecosystem | AI-driven Aadhaar services |
| Bhashini | Multilingual AI platform | 20 languages, 350 models, 1M+ downloads |
| BharatGen AI (2025) | Government-funded multilingual LLM | Supports 22 Indian languages |
| AI Data Labs Network | Foundational AI training | 570 labs nationwide |
| AI Impact Summit 2026 | Showcasing India’s AI leadership | 300 exhibitors, 30+ countries, youth & women innovation challenges |
AI in Key Sectors
(a) Healthcare
- Early diagnosis, telemedicine, image recognition.
- ICMR–IndiaAI–U.K.–Singapore collaborations ensure ethical standards.
- AI models in radiology, pathology, drug discovery.
(b) Agriculture
- AI in crop forecasting, pest detection, irrigation scheduling.
- Kisan e-Mitra: AI chatbot linking farmers to schemes.
- National Pest Surveillance System integrates weather & satellite data.
(c) Education & Skilling
- NEP 2020: AI introduced from Class VI–XII.
- YUVAi Programme: Students build AI solutions for local challenges.
- DIKSHA Platform: AI for accessibility (text-to-speech, keyword search).
(d) Governance & Justice
- e-Courts Project Phase III: AI in translation, scheduling, and filing.
- AI Translation Committees translating judgments into regional languages.
- e-HCR, e-ILR: Digital legal access platforms.
(e) Climate & Weather Forecasting
- IMD uses AI models for rainfall, fog, cyclone intensity.
- MausamGPT (upcoming) to provide real-time weather advice.
Employment & Skilling Impact
- AI Talent Pool: Expected to double from 6.5 lakh (2025) → 12.5 lakh (2027).
- FutureSkills PRIME Programme:
- 18.56 lakh enrolled; 3.37 lakh certified.
- Focus on 10 frontier technologies including AI, Big Data, and IoT.
- AI creating new job categories in data science, robotics, analytics, and governance.
NITI Aayog Report 2025 – AI for Inclusive Societal Development
- Vision: Empower 490 million informal workers through AI, IoT, Blockchain, and Robotics.
- Digital ShramSetu Mission: Frontier technologies for informal sector.
- Phased Implementation (2025–2035):
- Mission Orientation (2025–26) – Define goals and framework.
- Institutional Setup (2026–27) – Governance, regulation, partnerships.
- Pilot Programs (2027–29) – Sectoral implementation, M&E.
- Nationwide Rollout (2029–35) – Full-scale adoption and integration.
- Outcome: Inclusive, voice-first, multilingual, skill-amplifying digital ecosystem.
Ethical and Governance Dimensions
- Safe & Trusted AI Framework:
- Focus on bias mitigation, explainability, privacy, and accountability.
- IndiaAI Safety Institute: Developing national AI governance standards.
- Global Cooperation: Participation in GPAI (Global Partnership on AI) and UNESCO AI Ethics Framework.
Challenges
- Limited domestic chip manufacturing and AI compute capacity.
- Data fragmentation and lack of standardized datasets.
- Shortage of AI researchers and PhDs relative to the U.S./China.
- Need for AI ethics, regulatory clarity, and public trust.
- Risk of digital divide if access and affordability gaps persist.
Way Forward
- Invest in indigenous GPUs and semiconductor fabs.
- Accelerate AI skilling in Tier-2/3 cities.
- Expand AI use in social sectors (health, agri, education).
- Create a National AI Regulatory Authority for ethical oversight.
- Integrate AI into Digital Public Infrastructure (DPI) frameworks — UPI, ONDC, and Ayushman Bharat Digital Mission.
- Encourage global South cooperation on ethical, multilingual AI.
Conclusion
- India’s AI transformation blends computational power, inclusive design, and innovation to build a globally competitive yet socially equitable tech ecosystem.
- With initiatives like IndiaAI Mission, BharatGen, and Digital ShramSetu, India aims to achieve AI sovereignty and inclusive digital empowerment by Viksit Bharat 2047.
