During difficult economic times, Indian agriculture has proven to be one of the most robust sectors. Despite the pandemic, the sector has seen tremendous activity driven by tech-led agricultural Industry. According to a Bain Company report, the Indian agritech Industry has the potential to reach $35 billion by 2025. This expected increase is heavily influenced by the pandemic, which caused several employees from rural areas to lose employment and return to their hometowns to pursue agriculture, followed by food processing and other agriculture-related jobs to optimize farming operations and supply chain.
Agriculture is the primary source of all development efforts and provides a living for 58% of the Indian people. In FY20, it earned Rs 19.48 lakh crore in gross income, including the subsidiary businesses. It provides:
- 17.8% of Indian GVA and $3,320.4 billion to the world economy.
- Making it around 11.9%.
- Placing 18th, slightly behind China.
The current agricultural landscape in India
There is little doubt that the agricultural industry faces numerous worrisome global challenges. However, the situation in India is unique. As a result, solutions developed for the Indian agrarian landscape are conventional and tailored to specific circumstances. New Age agriculture technologies are also strengthening Indian agriculture’s position in the global arena, signaling a watershed moment for the Indian economy.
Agriculture, which roughly includes farming and forestry, livestock (milk, eggs, and meat), and fisheries, is on the edge of a tremendous revolution, with a higher emphasis on technology integration. Given the sector’s scope, agriculture faces problems across the value chain and requires better operational optimization. As a result, farmers embrace sustainable practices while controlling soil degradation, gaining access to technology, inputs, credit, and markets, and lowering product costs and waste.
Agriculture AI development in India
AI adoption has become critical to enhancing farmer productivity to digitize the agriculture sector. Agricultural robotics, soil and crop monitoring, and predictive analysis are all becoming incredibly valuable in realizing agriculture’s full potential.
Farmers use artificial intelligence, such as robotics, sensors, and soil sampling, to collect data from farm management systems for better processing and analysis. These techniques reduce water waste, eliminate pesticides and herbicides, retain soil fertility, aid in the efficient use of labour, boost production, and improve product quality. The availability of such agricultural data is fueling the rise of artificial intelligence in agriculture.
Advanced analytics combines statistical modelling, data mining techniques, and machine learning to forecast future events based on specific historical data. In agriculture, predictive analytics is no longer a buzzword; instead, it has become a reality as farmers employ actionable data to make the best choices for practical farming. Farmers may optimize agronomic output, control inputs, and plan for production by market and weather circumstances by learning from that data and using real-time weather analysis and soil health monitoring.
Predictive modelling in agriculture, in addition to weather analysis or rainfall variability, optimizes fertilizer applications and assists farmers in choosing the best time for planting and harvesting. The incorporation of AI also gives farmers timely warnings to adjust their plans in the event of an unexpected change in the market or environmental conditions.
AI offers precision farming among its many uses. It has taken the top spot for farmers and other players in the food industry. By identifying plant illnesses, pests, and inadequate nutrient levels on farms, the AI integration aids farmers in increasing the quality and accuracy of their yield. AI sensors, for instance, can identify and target weeds, assisting farmers in deciding which pesticide should be used in the area. As a result, it increases the production of the maximum output from the available resources while decreasing resource and money waste.
The service segment
Though technology integration in agriculture is not new in India, it has advanced to enable more intelligent resource allocation in light of ongoing efforts to lessen the amount of labour-intensive work in farming. The fastest-growing area of AI’s use in agriculture relates to farmers’ needs for effective installation, training, and maintenance services. A quick move to AI in agriculture necessitates translating farmers’ knowledge into AI training, which also requires technological and educational investments in the industry.
Given the potential for AI to be used in farming, it is foreseeable that this will bring in the long-awaited technological revolution. Farmers are no longer as concerned about the financial burden of losses they experienced before technology integration since they have better access to crops with improved yields and more effective agricultural techniques. Additionally, by providing farmers with effective farming techniques, AI leverages the opportunity to lessen their burden of feeding a growing population.
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