Future of Indian Agriculture: Digital Agriculture

Agriculture must resemble manufacturing more if it is to continue providing food for the world, according to Geoffrey Carr of The Economist.

By the year 2050, 9.6 billion people are expected to inhabit the planet. Even if the amount of arable land and freshwater resources is fast declining, this would result in a large increase in the demand for food. It is important to upscale, update, and adapt the agriculture industry as a result.

Digital technology might provide a solution to this issue. The Internet of Things (IoT), Artificial Intelligence (AI), and Nano Technology, among others, are becoming more well-known due to Industry 4.0. It has transformed the industrial process and is fundamentally altering the value chain and farming process. Globally, the agricultural industry is embracing genome editing and smart breeding technologies, as well as combining digital AI-based technologies with microbial soil mapping, in order to improve output quality, create seeds that are resistant to pests and diseases, and other things.

The digitization of the agriculture industry is widely embraced and acknowledged in India. The paper focuses on the use of nanomaterials in agriculture, including, among other cutting-edge applications, the targeted administration of nutrients or pharmacological capsids for the identification and treatment of diseases and delivery of bioactive substances to particular locations to stimulate crop development. In order to speed up the transformation of the food and agriculture industry, it also discusses measures for putting these international and Indian learnings into practise on the ground.

The goal of the paper is to help smallholder farmers by fostering transformative innovation in agriculture and the sector as a whole by fostering the growth of more dependable tech-enabled value chains.

The difficulty is pointed out in the report as it relates to the farmer's decision-making process. Indian farmers choose their crops mostly on their traditional knowledge. In the meanwhile, among other things, the crop's adaptability is determined by the kind and quality of the soil, consumer demand, and weather patterns. The paper suggests using AI-based technology that can take into account all of these factors and recommend the ideal crop to sow.

Herein lies the role of digital technology, which can pinpoint the type of seed, quality of soil preparation, analysis of the health of the soil, estimation of the moisture percentage, real-time crop analysis, and others to give farmers accurate information.

IoT and analytical tools can also be used to improve the third stage of farming, or harvesting. The best time to harvest a crop guarantees that it has the most nutritious content.

Digital tools are not only useful throughout the farming process; they also help the farmer with logistics, pricing, and post-harvest tasks like storage and shipping. These techniques, together with market information, aid in optimizing the value of the produce and guarantee the effective and sustainable use of resources.

The limited adoption of mechanization technologies and frequent natural disasters like floods and droughts have further hindered the use of digital solutions in the industry. The proper operation of the AI/ML technologies is further hampered by the lack of a single repository for the various types of data stacks utilized in agriculture.

The Ministry of Agriculture and Farmer's Welfare collaborated with IBM on a pilot project for farm-level weather forecast and village-level soil moisture data, which is just one example of the PPP models used in India. Another example is MoA-IBM. The state governments have also established a number of alliances and are headed in the right way. The following are some ideas for improving digital adoption in the nation:

• Create a strong digital infrastructure in the nation that includes data on the market, land records, cropping patterns, soil health, satellite imagery, and more.
• Make use of satellite data sources
• By using a digital elevation model, you may improve data efficiency (DEM)

- Topography, digital

- Land Cover and Use

- Soil Chart

- Land Registration

Administrative Limitations

• Create demand side and market management systems.
• Utilize data effectively when creating laws, ordinances, and programmes like the Pradhan Mantri Yojanas. Establish a system for data exchange among various states, government agencies, and other public stakeholders.
• Different collaboration models between the public and private sectors could be investigated for the processing and analytics of the large amount of data.
• Encourage innovation, research, and development, and quicken the process of innovation validation and commercialization.

The 21st century is known for its usage of technology. India has a fantastic potential to benefit from its position as an IT powerhouse and modernize the farming industry as the world moves toward quantum computing, AI, big data, and other emerging technologies. The green revolution increased agricultural output, but the IT revolution in Indian agriculture must be the next significant development.