Unleashing the potential of AI in the growth of the agricultural sector

Indian agriculture has proven to be one of the most resilient sectors in difficult economic situations. Even at the start of the pandemic, the sector showed remarkable activity driven by tech-focused agricultural startups. According to a study by Bain Company, India’s agritech market potential is expected to reach $35 billion by 2025. This projected growth is heavily boosted by the pandemic when a number of workers in rural areas lost their jobs. and returned to their hometown. to pursue cultivation, followed by food processing and other agriculture-related jobs to optimize agricultural processes and the supply chain.

Agriculture is indeed the main source of all development activities and constitutes a means of subsistence for 58% of the Indian population. It recorded a gross income of Rs 19.48 lakh crore including subsidiary sectors in FY20. Together with associated sectors, it contributes 17.8% of Indian GVA and Rs 3,320.4 billion dollars from the global economy, making it about 11.9%, ranking 18th, right next to China.

India’s current agricultural landscape

There is no doubt that the agriculture industry faces many troubling challenges globally. The circumstances in India, however, are unique. Hence, the solutions created for the Indian agrarian landscape are customary and based on specialized needs. New Age agricultural technologies are also strengthening the position of Indian agriculture on the world stage, marking a turning point for the Indian economy.

Being a high priority sector for the Indian economy, agriculture, which broadly comprises of farming and forestry, livestock (milk, eggs and meat) and fisheries, is about to undergo a massive transformation with a increased emphasis on technology integration. Given the breadth of the sector, agriculture is always plagued with challenges spread across the entire value chain and requires better optimization of operations. As a result, it helps farmers adopt sustainable farming practices with a sense of control over land degradation, access to technology, inputs, credit and market and while reducing the cost and waste of produce .

Development of AI in Indian Agriculture

With a focus on digitalization of the agricultural sector, the adoption of AI has become imperative to improve the productivity of farmers. Agricultural robotics, soil and crop monitoring, and predictive analytics are becoming increasingly important to unlock the full potential of agriculture.

Artificial intelligence, including robotics, sensors and soil sampling, is being used by farmers to collect data based on farm management systems for better processing and analysis. These technologies reduce overuse of water, put an end to pesticides and herbicides, preserve soil fertility, contribute to the efficient use of labor, increase production and improve 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, but it is the reality as actionable insights are used to make the right decisions for efficient farming. Advanced analytics that incorporate statistical modeling, data mining methods, and machine learning predict future events based on specific historical data. By learning from this data, farmers get real-time weather analysis and soil health sensing to improve agronomic performance, manage inputs, and plan production based on market and weather conditions.
Apart from analyzing weather or rainfall variability, predictive modeling in agriculture optimizes fertilizer applications and also helps farmers decide on the optimal time to sow and harvest. The AI ​​integration also provides timely alerts to farmers to modify their schedule if there is a sudden change in environmental or market conditions.

Precision farming

Along with the various applications, AI also provides precision farming. It has become the top priority for farmers and everyone else in the food industry. The integration of AI helps farmers improve harvest quality and accuracy by detecting plant diseases, pests and poor nutrition on farms. For example, AI sensors can detect and target weeds and help farmers decide which herbicide to apply in the area. As a result, it increases the optimum yield of production from the available resources while reducing the waste of costs and resources.

The service segment

The fastest growing spectrum of AI application in agriculture relates to the requirement for efficient installation, training and maintenance services among farmers. Although technological integration is not new in the history of Indian agriculture, given the constant efforts to reduce the amount of labor intensive work in agriculture, it has evolved to make resource allocation smarter. With a sudden shift to AI in agriculture, farmers’ knowledge needs to be translated into AI training, which also requires technical and educational investments in the sector.

Considering the potential for integrating AI into agriculture, it can be predicted that it will bring a much-awaited technological revolution to the industry. With greater access to improved crop yields and efficient farming methods, farmers are now less concerned about the burden of losses they incurred before the integration of technology. Additionally, the AI ​​takes advantage of the reduced burden on farmers to produce food for the growing population by equipping them with efficient farming methods.

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