Indian civilization is one of the world's oldest civilisations, and Indian agriculture is also of similar age. Because agriculture was the most accomplished and prestigious occupation at the time, ancient Indian farmers were immensely wealthy. Agriculture and agricultural-related occupations continue to employ 50% of the population.
Agriculture is one of India's most important industries and a pillar of the Indian economy. Launching a second green revolution is necessary, which can only be accomplished by transferring technology from the lab to the field. Agriculture knowledge generation and application are becoming increasingly crucial, particularly for small and marginal farmers who need relevant information to enhance, sustain, and diversify their farm enterprises.
Today, India is the leading producer of cereals, milk, sugar, fruits, vegetables, spices, eggs, and so on. The proportion of rice, beef, and sea foods to overall export is 52%. Although India accounts for only 2.4% of the world's geographical area, we have more cultivable land than any other country that can meet our food grain needs.
Furthermore, we may export food products all over the world. Information technology enables new methods and concepts for precise and healthy agriculture, such as computerised farming, weather forecasting, pesticide and fertiliser use, and crop variety.
Traditional Agricultural Issues
While much has been done to improve cultivation, Indian agriculture still relies on traditional farming techniques, natural water irrigation, and development approaches. Farmers rely on groundwater, rivers, and rainfall. Over-pumping of water has resulted in a drop in groundwater levels in some areas, where water-logging has resulted in salty soil. Soil disintegration and flooding are major threats to Indian farmers in rain-fed areas.
Low Agricultural Productivity
Indian agriculture has the potential to improve farm production and yield. Hybrid and genetically modified crops, seed quality, irrigation techniques, crop diversification, and value chains have all seen steady acceptance. However, the use of technologies based on sensors and GIS-based soil, climate prediction, water assets information, mobile-based farming, broad market data information and data services, and farming automation employing robots appears to be unattainable.
Inadequate Knowledge
Other issues confront the agricultural community as well. The main issue is that farmers do not receive fair market value for their produce. This is primarily due to the presence of several intermediaries. Lower returns lead them to take on debts they cannot afford, pushing them deeper into poverty.
They lack access to more potent and high-quality insecticides to protect their crops from bugs, illnesses, weeds, and mites. Furthermore, Indian farmers lack access to improved agricultural yields and information about soil health.
Indian farmers also lack the knowledge and technology to use contemporary irrigation technologies seen in countries such as China, the United States, and others.
What Can The Solutions Be?
1. Exact Predictions
Big data can provide farmers with the information they need to grow high-quality, desirable crops. They can use data to determine the best seeds and other agri-items to employ in order to achieve the most significant results. Artificial intelligence can help them predict weather patterns and plan accordingly. They can also use cutting-edge e-platforms to bypass middlemen and legitimately approach merchants and demand the correct price for their goods.
2. Artificial Intelligence (AI)
The availability of precision data is accelerating the application and development of AI in agriculture. Modern and cutting-edge artificial intelligence-based techniques can assist in bringing precision to large-scale farming. Farm machinery may plant varied densities of seeds and apply different amounts of fertiliser in different parts of a field.
While AI has become a backbone of the technology network, a substantial number of big agriculture input businesses do not appear to be actively seeking AI applications in farming. Agricultural productivity may be successfully displayed using remote sensing and GIS applications.
3. Nanotechnology and Geo-Spatial Farming
Nano Science is a technology that provides farmers with data about whether plants are absorbing water and other necessary inputs in enough quantities by utilising smart delivery systems and nanosensors. It also provides information on the quality of food harvested. Agricultural productivity can be expanded on a vast scale by using geospatial farming. Higher production can be achieved based on elements such as weeds, the type of soil and its moisture content, production (ripeness), and rate of production.
4. Deep Learning
Deep learning, for example, can play an important role in providing significant data to farmers on a variety of topics, such as soil health, genetic engineering of seeds, best practices for planting and picking crops, checking the health of the animals, obtaining guidelines and approaches, obtaining appropriate financial aid, and leveraging appropriate government schemes.
5. Drones
They contribute to increased output by lowering expenses and losses in agricultural production through supervision work. With the support of drones, advanced sensors, digital imaging capability, soil inquiry, crop spraying, crop monitoring, yield health inspection, and fungus infection are all possible.
Written By- Greeshma Chowdary
Edited By- Nidhi Jha
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