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Unlocking the potential of AI in the growth of the agriculture sector

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Unlocking the potential of AI in the growth of the agriculture sector

 

Indian agriculture has proved to be one of the most robust sectors during challenging economic situations. Even on the outbreak of the pandemic, the sector has shown a remarkable amount of activity driven by tech-led agriculture startups. According to a study by Bain Company, the potential of the Indian agritech market is projected to reach $35 billion by 2025. This projected growth is highly driven by the pandemic when a number of workers from rural areas lost their job and went back to their hometowns to pursue cultivation, followed by food processing and other agriculture-related jobs to optimize farming processes and supply chain.

Agriculture is indeed a primary source of all development activities and acts as a livelihood source for 58% of the Indian population. It recorded a gross income of Rs 19.48 lakh crore, including the subsidiary sectors in FY20. Along with associated sectors, it contributes 17.8% of the Indian GVA and $3,320.4 billion to the global economy making it about 11.9%, ranking 18, just next to China.

India’s current agricultural landscape

There is little doubt that the agricultural industry encounters many troubling difficulties globally. The circumstances in India are unique, though. Therefore, solutions created for the Indian agrarian landscape are customary and based on specialised needs. New Age agriculture technologies are also boosting the position of Indian agriculture in the global arena, marking a turning moment for the Indian economy.

Being a high-priority sector for the Indian economy, agriculture, broadly comprising farming and forestry, livestock (milk, eggs and meat) and fisheries, is on the verge of massive transformation with a greater focus on technology integration. Considering the spectrum of the sector, agriculture is still mired with challenges spread across the value chain and needs better optimisation of operations. As a result, it helps farmers adopt sustainable farming practices with a sense of control over soil degradation, access to technology, inputs, credit and market and while reducing the cost and wastage of products.

AI development in Indian agriculture

With a key focus on digitizing the agriculture sector, the adoption of AI has become imperative towards improving the productivity of farmers. Agricultural robotics, soil and crop monitoring and predictive analysis are increasingly becoming significant in unlocking the full agriculture potential.

Artificial intelligence, including robotics, sensors, and soil sampling, is being used by farmers to gather data based on farm management systems for better processing and analysis. These technologies reduce the overuse of water, put an end to pesticides and herbicides, preserve soil fertility, assist in the effective use of labour, increase output, and enhance product quality. The availability of such agricultural data is leading to the emergence of AI in agriculture.

Predictive analytics

Predictive analytics is no longer a buzzword in agriculture, however, it is the reality as actionable insights are used to make the right decisions for efficient farming. Advanced analytics that incorporates statistical modelling, data mining methods, and machine learning predict future events based on specific historical data. By learning from that data, farmers get real-time weather analysis and soil health detection to improve agronomic performance, manage inputs and plan for production according to the market and weather conditions.
Apart from weather analysis or rainfall variability, predictive modelling in farming optimises fertilizer applications and also helps farmers to decide the optimal time for sowing and harvesting. The integration of AI also provides timely alerts to farmers to make changes to their schedule in case of a sudden shift in the environmental or market condition.

Precision farming

With the various applications, AI also provides precision farming. It has become the top-most priority for farmers and any other stakeholders within the food industry. The AI integration is helping farmers to improve the harvest quality and accuracy by detecting plant diseases, pests and poor nutrition on farms. For instance, the sensors of AI can detect and target weeds and help farmers to decide which herbicide needs to be applied in the region. As a result, it increases the optimum yield production from the available resources while reducing the wastage of cost and resources.

The service segment

The fastest growing spectrum of the AI application in agriculture deals with the requirement of efficient installation, training, and maintenance services among farmers. Though technology integration is not new in the history of Indian agriculture, considering the consistent efforts in reducing the amount of labour-intensive work in farming, it has evolved to make resource allocation smarter. With a sudden shift to AI in agriculture, the farmers’ knowledge needs to be translated into AI training which also calls for technical and educational investments within the sector.

Considering the potential of AI integration in farming, it can be predicted that it is going to bring a much-awaited technological revolution to the industry. With better access to improved crop yields and efficient farming methods, farmers are now less concerned about the burden of losses they suffered before technology integration. In addition, AI takes advantage of lowering the burden of farmers for producing food for the increasing population by equipping them with methods of efficient farming.

 

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