Context: Millions of farmers in India, who often rely on luck or favorable weather for a decent harvest, could be benefitted with access to better technologies which are affordable.

Key Points

• The technology aids farmers in three key areas: farm management with personalized agronomic intelligence, access to inputs, and post-harvest commerce.

Challenges

• Among the largest consortium of farmer producer firms in the country. “Their reach is limited and they are only targeting the progressive farmers".
• Ultimately, the adoption of technology in agriculture will depend on the criticality of the service offering.
• Many of these startups which claim to help growers undertake intelligent farming are only solving about 5% of the (farm-level) problem.
• It is also not easy to convince farmers to invest in tech solutions without overwhelming evidence of an adequate return. 
• Innovative financial arrangements and micro-loans might be required to increase adoption, which is currently absent.

Solutions

• Digitizing farm operations through a business-to-business (B2B) model, where the firm does not directly deal with farmers and instead works with agri-businesses.
• Provide farmers with agronomy intelligence required to manage the crops right from land preparation to harvest.
• Provide access to inputs based on (the) farmer’s needs across the cropping cycle.

The solution sends out SMS advisories to farmers to alert them about likely future events. This makes the farmer future-ready for pest and disease control and the timely SMS alerts have shown a significant increase in yields for the farmers.

• Even Farmers associated with the agri startup say they were able to reduce input costs by 10-15% and increase crop yields by 30-40%.

Role of Technology in agriculture 

1. Crop and Soil Monitoring: using censors or Internet of Things,  for example Understanding the level of soil moisture and predicting the right time to start sowing 
2. Predictive agriculture analytics: Predicting the amount of fertilizers needed to maximize the farm yield using Artificial Intelligence and Machine learning Tools
3. Real time Data Analytics: to build an efficient and smart supply chain
4. Weather based advisories: using data analytics to provide accurate advice to the farmers.
5. Pest and disease management: through use of Drone technology along with sensors enabled with AI
6. Water Management: to use the water resources optimally technology is used to link irrigation facility with soil sensors
7. Smart Supply Chain: Applications are developed  to solve the crop marketing and logistical issues, reducing the intervention of middle men, addressing price volatility, wastage, and unfair trade practices. Ex- eNAM
8. Quality Assessment: Use of computer vision and deep learning tool can be used to provide monitoring and grading solutions which adds value to product. 

Road Ahead

• Globally, the supply chain in agriculture got disrupted due to the impact of covid-19. Food is now recognized as the top-most item in terms of criticality. Therefore, there is a general uptick in investor interest in agriculture since the covid outbreak. Agritech is one of the ways to unlock the full potential of agriculture in India.