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| Artificial Intelligence in Indian Agriculture: The Dawn of a Second Green Revolution | | A New Direction for Farmers’ Income, Productivity, and Sustainability | | PROF. (DR.) PARSHANT BAKSHI
The Soul of India and the Future of Its Fields
The soul of India lives in its villages, and the soul of its villages resides in agriculture. Even today, more than 50 percent of the country’s population is directly or indirectly connected with farming. Agriculture is not merely an occupation in India; it is the foundation of our economy, food security, rural employment, culture, and social stability. From the wheat fields of Punjab to the orchards of Jammu & Kashmir, from the cotton belts of Maharashtra to the paddy fields of Tamil Nadu, agriculture shapes India’s identity and sustains its people.
Yet Indian agriculture stands at a critical crossroads. Climate change, shrinking landholdings, soil degradation, rising input costs, labour shortages, water scarcity, and volatile markets are creating unprecedented challenges. Traditional farming methods, though valuable and time-tested, are no longer sufficient to ensure stable income and long-term sustainability.
In this context, the recent AI Summit organized in India in New Delhi sent a powerful message: Artificial Intelligence (AI) will not remain confined to IT parks and corporate offices; it will transform farms and villages. Policymakers, scientists, startups, agri-entrepreneurs, and farmer representatives collectively emphasized that India’s next development story will remain incomplete without “AI for Agriculture.” AI is emerging as the foundation of what many are calling the Second Green Revolution-technology-driven, climate-smart, data-powered, and farmer-centric.
The Need for AI in Indian Agriculture
India has over 140 million hectares of net sown area, yet nearly 80 percent of farmers are small and marginal, owning less than 2 hectares of land. These farmers operate under severe constraints:
• Limited capital
• Inadequate irrigation facilities
• Poor access to quality inputs
• Weak market linkages
• High exposure to climate risks
In a country with a population exceeding 1.4 billion, ensuring food and nutritional security while conserving natural resources is an enormous challenge. Production must increase but without degrading soil, water, and biodiversity.
Artificial Intelligence offers a powerful solution.
AI refers to computer systems capable of learning from data, recognizing patterns, making predictions, and supporting decision-making. When applied to agriculture, AI can guide farmers on:
• When to sow crops
• How much irrigation is required
• The precise quantity of fertilizers
• Early detection of pests and diseases
• Market price trends and optimal selling time
This shift from guesswork to data-driven precision marks a revolutionary transformation.
AI as the Foundation of the Second Green Revolution
The First Green Revolution of the 1960s, led by improved varieties, irrigation, and fertilizers, helped India achieve self-sufficiency in food grains. The visionary scientists like Dr. M.S. Swaminathan and policy support transformed India from a food-deficit to a food-surplus nation.
However, the first revolution also led to:
• Overuse of fertilizers
• Groundwater depletion
• Soil health decline
• Environmental stress
The Second Green Revolution must correct these imbalances. AI enables:
• Precision input application
• Resource-use efficiency
• Climate adaptation
• Reduced environmental footprint
• Income optimization
This revolution is not merely about producing more, it is about producing smarter.
Major Applications of AI in Indian Agriculture
i. Precision Agriculture
Precision agriculture uses data from soil sensors, satellites, drones, and weather stations to optimize farm operations.
Applications include:
• Fertilizer recommendation based on soil testing
• Irrigation scheduling using moisture sensors
• Crop health monitoring through satellite imagery
• Variable rate application technologies
Benefits:
• Reduced input cost
• Increased yield
• Higher nutrient-use efficiency
• Improved soil health
In water-scarce regions such as Rajasthan and parts of Haryana, AI-based irrigation scheduling can save up to 30–40% water.
ii. Crop Monitoring and Disease Detection
Drones equipped with multispectral cameras can detect crop stress before it becomes visible to the human eye. AI models analyze leaf images captured via smartphones to diagnose diseases.
For example:
• Early detection of apple scab in Jammu & Kashmir
• Identification of blast disease in paddy
• Detection of nutrient deficiencies in horticultural crops
Benefits:
• Reduced crop loss
• Lower pesticide use
• Timely intervention
• Improved quality produce
iii. Weather Forecasting and Climate Advisory
AI enhances hyper-local weather prediction. Instead of district-level forecasts, farmers can receive village-level advisories.
AI-based systems analyze:
• Historical weather data
• Satellite observations
• Wind patterns
• Rainfall distribution
This helps farmers plan:
• Sowing dates
• Irrigation schedules
• Harvest timing
In climate-sensitive horticulture crops, accurate weather prediction can prevent major economic losses.
iv. Automated Machinery and Robotics
AI-driven farm machinery is transforming labour-intensive tasks:
• Autonomous tractors
• Robotic weeders
• Smart harvesters
• AI-based grading machines
In high-value crops like fruits and vegetables, robotic harvesting ensures uniform quality and reduces labour dependency.
v. Supply Chain Optimization
Post-harvest losses in India range between 5–25%, depending on the commodity. AI can:
• Track produce from farm to market
• Optimize cold chain logistics
• Reduce spoilage
• Forecast demand
Digital platforms can connect farmers directly to buyers, reducing the role of intermediaries.
vi. Price Forecasting and Market Intelligence
AI models analyze:
• Historical mandi prices
• Demand-supply trends
• Export-import data
• Seasonal fluctuations
Farmers can then decide:
When to sell, Where to sell, Whether to store
Such predictive insights improve bargaining power and income realization.
vii. Digital Advisory Services
Mobile apps and AI chatbots provide real-time advice in local languages. Voice-based systems are especially helpful for farmers with limited literacy.
These tools can answer queries on:
• Crop management
• Government schemes
• Pest control
• Fertilizer application
Digital advisories are bridging the knowledge gap.
Government Initiatives Supporting AI in Agriculture
India has launched several landmark initiatives to integrate AI into agriculture.
i. Digital Agriculture Mission
The Government of India has expanded the Digital Agriculture Mission with a long-term vision up to financial year 2030. With a proposed budget exceeding Rs 7,500 crore, it aims to build digital public infrastructure for agriculture, including:
• AgriStack
• Krishi Decision Support System (KDSS)
• Soil and weather data integration
This ecosystem strengthens AI-based decision-making at scale.
ii. AI Centres of Excellence
The Government has established AI Centres of Excellence in agriculture to promote research, innovation, and AI solution development tailored to Indian conditions.
iii. IndiaAI Mission
Under the IndiaAI Mission, with an allocation of over Rs 10,000 crore, AI development across sectors—including agriculture—is being accelerated. This initiative supports startups, research institutions, and AI ecosystem development.
iv. Bharat-VISTAAR
Bharat-VISTAAR is an AI-powered multilingual digital advisory platform designed to deliver localized farming recommendations. It ensures that language barriers do not prevent farmers from accessing technology.
v. Kisan e-Mitra and National Pest Surveillance System
Kisan e-Mitra, an AI chatbot, assists farmers in understanding government schemes and resolving agricultural queries.
The National Pest Surveillance System uses AI and machine learning to monitor pest outbreaks across multiple crops, enabling early warning systems.
vi. State-Level Initiatives
States like Maharashtra have launched AI-focused agricultural policies such as MahaAgri-AI Policy 2025–29 to promote AI-based agri-solutions.
Benefits of AI for Farmers
• Increased Productivity
• Reduced Cost of Cultivation
• Improved Decision-Making
• Risk Mitigation
• Environmental Sustainability
• Empowerment of Small Farmers
• Direct Market Linkages
In horticulture, especially fruit crops, AI can enhance quality, grading accuracy, and export competitiveness.
Challenges in AI Adoption
Despite immense potential, several barriers exist:
• Poor internet connectivity in rural areas
• Limited digital literacy
• High initial cost of technology
• Data privacy concerns
• Fragmented landholdings
• Inadequate quality datasets
Addressing these challenges requires:
• Capacity building
• Strengthened extension systems
• Public-private partnerships
• Affordable technology models
• Farmer producer organizations (FPOs)
Future Possibilities
The coming decade may witness:
• AI-powered village-level weather stations
• Drone-based crop insurance assessment
• AI-based agricultural credit scoring
• Robotic fruit harvesting in orchards
• Climate-resilient crop modeling
• Integration of AI with organic and natural farming systems
AI-driven credit systems may enable small farmers to access loans without traditional collateral, based on crop data and predictive analytics.
AI in Horticulture: A Special Opportunity
As a fruit scientist, I see tremendous scope of AI in horticulture:
• Yield estimation in apple, mango, citrus, walnut orchards
• Quality grading through computer vision
• Smart fertigation in high-density orchards
• Disease forecasting in perennial crops
• Precision pruning advisory systems
AI can significantly benefit temperate and subtropical fruit production systems, particularly in regions like Jammu & Kashmir.
A Farmer-Centric Approach to AI
Technology must not replace farmers, it must empower them.
AI solutions should be:
Affordable, User-friendly, Language-accessible, Scalable and Inclusive
Women farmers, tribal communities, and youth must be central to digital transformation.
Conclusion: The Intelligent Green Revolution
Artificial Intelligence is not merely a technological innovation it is a transformative force for Indian agriculture. It offers farmers the power of information, prediction, and precision. If policymakers, scientists, startups, extension workers, and farmers collaborate effectively, AI can usher in a Second Green Revolution—intelligent, inclusive, sustainable, and climate-resilient. The future of Indian agriculture will not depend solely on seeds and fertilizers—but on data, algorithms, and informed decision-making.
The field of tomorrow will be smart.
The farmer of tomorrow will be empowered.
And at the heart of this transformation will be Artificial Intelligence.
The author of this article is Professor & Head, Division of Fruit Science, SKUAST-Jammu. For more information you can write at [email protected] |
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