Content:
- Use of AI in agriculture
- Promotion of Organic Farming
Use of AI in Agriculture
The integration of Artificial Intelligence (AI) in Indian agriculture is a significant step toward improving productivity, mitigating risks, and ensuring better decision-making for farmers. The government’s initiatives, as mentioned in the Rajya Sabha, highlight the increasing role of AI-driven solutions in tackling sector-specific challenges such as pest control, climate resilience, and financial accessibility.
Relevance : GS 3(Agriculture)
1. Kisan e-Mitra: AI-powered Chatbot for Farmer Assistance
- Objective: To provide real-time information to farmers, particularly regarding the PM Kisan Samman Nidhi scheme.
- Features:
- Supports multiple languages, ensuring accessibility for farmers across India.
- Currently focused on PM-KISAN queries but is expected to expand to cover other government schemes.
- Reduces dependence on physical government offices for information, improving efficiency.
- Impact:
- Helps farmers receive instant and accurate responses about financial assistance.
- Enhances government outreach to rural areas with minimal infrastructure.
- Reduces misinformation and bureaucratic delays in accessing benefits.
2. National Pest Surveillance System: AI for Climate-Resilient Agriculture
- Need for the System:
- Climate change has led to erratic weather patterns, increasing the risk of pest infestations.
- Traditional pest detection relies on physical inspections, which can be slow and inefficient.
- How AI is Used:
- AI and Machine Learning (ML) analyze historical data, satellite imagery, and real-time field data.
- Identifies early signs of pest infestations and alerts farmers and agricultural officers.
- Suggests targeted interventions to minimize crop losses.
- Impact:
- Enables proactive pest control, reducing dependency on excessive pesticide use.
- Prevents large-scale crop damage, ensuring food security and farmer income stability.
- Improves agricultural sustainability by promoting data-driven pest management.
3. AI-based Crop Health Monitoring & Yield Prediction
- Use of AI Analytics:
- AI analyzes field photographs to assess crop health, identifying stress factors like nutrient deficiencies, diseases, or water stress.
- Uses satellite data, weather patterns, and soil moisture levels to predict yields and detect anomalies.
- Application on Rice and Wheat Crops:
- These staple crops are crucial for India’s food security, and AI-driven insights help optimize productivity.
- Helps policymakers and farmers make informed decisions on irrigation, fertilization, and harvesting.
- Impact:
- Reduces crop loss due to undiagnosed diseases and poor soil conditions.
- Provides real–time advisories to farmers, improving productivity.
- Aids in crop insurance assessments by providing accurate yield predictions.
Broader Implications of AI in Agriculture
1. Precision Farming & Resource Optimization
- AI helps optimize the use of water, fertilizers, and pesticides, reducing input costs and environmental damage.
- Precision agriculture improves yields and enhances soil health through targeted interventions.
2. Market Linkages & Price Forecasting
- AI-powered models analyze market trends and suggest optimal selling times for farmers.
- Reduces farmer dependency on middlemen, ensuring better price realization.
3. Financial Inclusion & Credit Access
- AI-driven risk assessment models help banks and financial institutions determine the creditworthiness of farmers.
- Enables quicker loan approvals and promotes financial security.
Challenges & the Way Forward
Challenges:
- Digital Divide: Many small and marginal farmers lack access to smartphones and the internet, limiting AI adoption.
- Data Gaps: AI models require large-scale datasets, which may not always be available or accurate.
- Lack of Awareness: Farmers may be reluctant to adopt AI-driven solutions due to unfamiliarity and trust issues.
- Infrastructure Limitations: Poor rural connectivity and electricity shortages hinder AI deployment.
The Way Forward:
- Strengthening Digital Infrastructure: Expanding rural broadband connectivity and promoting smartphone adoption.
- AI Training for Farmers: Conducting awareness programs to familiarize farmers with AI-based tools.
- Public-Private Collaboration: Encouraging partnerships between the government, private tech firms, and agricultural institutions to scale AI solutions.
- Localized AI Solutions: Customizing AI models for regional languages and crop-specific challenges.
Promotion of Organic Farming
The Government of India is promoting organic farming to ensure sustainable agriculture, soil health conservation, and premium market access for farmers.
Relevance : GS 3(Agriculture)
Two key schemes are driving this initiative:
Paramparagat Krishi Vikas Yojana (PKVY)
Scope: Implemented in all States & UTs (except the North-East).
Objectives:
- Encourages cluster-based organic farming with end-to-end support.
- Provides financial aid for production, processing, certification, and marketing.
- Empowers farmers through training & capacity building.
Financial Assistance:
- ₹31,500/ha for 3 years (₹15,000/ha for organic inputs through DBT).
- Additional support for value addition, marketing, and certification (₹4,500/ha, ₹3,000/ha, and ₹7,500/ha respectively).
Mission Organic Value Chain Development for North Eastern Region (MOVCDNER)
Scope: Exclusive to the North-East to develop organic value chains
Objectives:
- Supports organic input production & certification.
- Encourages Farmer Producer Organizations (FPOs) to develop market linkages.
- Provides infrastructure for post-harvest management & processing.
Financial Assistance:
- ₹46,500/ha for 3 years (₹32,500/ha for organic inputs, with ₹15,000 through DBT).
- ₹10,000/ha for training, certification, and capacity building.
Organic Certification Mechanisms
Third-Party Certification (NPOP – Ministry of Commerce & Industry)
- Ensures organic products meet export standards.
- Covers production, processing, trading, and export compliance.
Participatory Guarantee System (PGS-India – Ministry of Agriculture & Farmers Welfare)
- Designed for domestic markets.
- Farmers collectively assess, verify, and certify each other’s produce.
Market Support & Digital Initiatives
States actively organize:
- Workshops, buyer-seller meets, organic trade fairs, & festivals.
- Direct marketing platforms such as farmer cooperatives & organic bazaars.
Jaivik Kheti Portal
- Government-backed online organic market.
- 6.22 lakh registered farmers sell directly to consumers.
Total organic farming area in India: 59.74 lakh hectares (NPOP + PGS)
Top States with highest organic area (NPOP + PGS combined):
- Madhya Pradesh: 12.23 lakh ha
- Maharashtra: 10.67 lakh ha
- Rajasthan: 7.28 lakh ha
- Gujarat: 6.90 lakh ha
- Uttarakhand: 2.42 lakh ha
Conclusion
The government’s organic farming initiatives reduce chemical dependency, improve soil fertility, and enhance farmers’ income by providing financial, technical, and market support. These efforts align with sustainable agricultural goals and bolster India’s global organic export potential.
