AI push: Farmers reap better quality and yield, but challenges remain

The Indian govt is also promoting use of AI to help farmers increase their productivity

Farmers must produce 70 per cent more food to feed the predicted 2050 global population of 9.1 billion, a recent World Economic Forum report has said. India’s share in it will be around 1.6 billion by then. Clearly, food production will have to keep pace with the rising numbers.

And with climate change impacting agriculture, technology -- especially artificial intelligence -- will play a crucial role going ahead.

A new and promising crop of agritech startups is bringing technological advancements in the sector. India has now over 3,600 such startups in the agritech space.

An agritech startup is generally referred to a firm that leverages technology to innovate agricultural practices, enhancing productivity, sustainability, and efficiency in farming.

Demand forecast   

Delhi-based Poshn, for instance, is using AI to bolster operations.

“We use AI to forecast demand for various crops and commodities, and suppliers can plan effectively. Our smart logistics solutions optimise delivery routes and track locations efficiently, our systems enhance inventory management in warehouses and cold storage, significantly reducing waste,” said Shashank Singh, CEO and co-founder, Poshn.

The firm offers a tri-party commerce platform where wholesale buyers can purchase from millers and stockists. 

Mumbai-based farm-to-fork fruits and vegetable company Pluckk is investing heavily in artificial intelligence-driven solutions for sorting and grading of food products.

Pluckk has developed custom AI models integrated with machine learning algorithms and computer vision technologies to meet challenges such as food quality, wastage, traceability and consistency.

Fyllo is another agritech startup that has created a precision agriculture platform that helps farmers in achieving better yields. The company’s patented IoT product measures the precise requirements of plants on a real-time basis. Its AI platform provides timely advice to farmers.

Currently, over 8,000 farmers are using Fyllo’s services on more than 50,000 acres and have consistently received 25 per cent more yield, 80 per cent export-quality produce, and 30 per cent more income, said the company.

Loosening purse strings

Venture capitalist firms are also expressing confidence in the AI-led innovative solutions in the space. 

“Emerging agritech startups are increasingly leveraging AI to drive innovation, enhance productivity, and secure funding, positioning themselves as key players in the future of agriculture,” said Anirudh Siddharth, AVP, Portfolio Operations, Inflection Point Ventures (IPV). 

IPV is a large angel investment platform that has made investments in agritech startups like Falca and Agrictools. 

“From precision farming and predictive analytics to supply chain optimisation and automated farm management, AI is being integrated across the value chain,” Siddharth added.

Government’s AI push 

The Indian government is also pushing the use of AI to help farmers and increase their productivity.  

Earlier this week, the Union Ministry of Agriculture launched a mobile app under the National Pest Surveillance System (NPSS), to collect information on pest attacks in crops.

Launching the application, Union Agriculture Minister Shivraj Singh Chouhan said that farmers can download this app and take the photos of their field, if it is infested by pests or insects and upload the photos.

He said the app will help the government to get faster information about the pest attacks on crops and take action accordingly, by helping in identifying the location of pest infestation and its scale very quickly.

Not for profit organisation Wadhwani Institute for AI has developed an advanced AI model for the NPSS, using which the government will be able to provide farmers and agricultural experts with timely, reliable advisories to protect crops.

It has deployed AI for daily analysis of agricultural news from different regional language sources and then providing a summary of it to the officials in the Ministry of Agriculture, through a solution known as Krishi 24x7.

JP Tripathi, Director, Agriculture, Wadhwani Institute for AI said, “Each region has its own language and numerous newspapers, making it difficult to track and analyse all relevant information. To streamline this process, we have developed an integrated agriculture news monitoring solution, now incorporated into ministry systems as Krishi 24x7.” 

“The technology scrapes news articles from across the web, translates them from any language, and provides a summary for administrators - be it any language such as Gujarati, Marathi or anything else, using AI,” Tripathi added.

Further, the firm is also revamping the traditional Kisan call centres with the help of AI.

Tripathi said that the Kisan call centres in India handle 10,000-15,000 daily calls. Tele-advisors face language barriers, and rely on Google searches and pre-created master files for answers, causing delays if unfamiliar questions arise, affecting timely farmer assistance. 

To solve this issue, Wadhwani AI, in collaboration with the government is coming up with a dedicated sectoral large language model (LLM) to provide accurate, timely responses to the farmers on their queries.

Challenges facing agritech space

One of the biggest hurdles for agritech startups, experts highlight, is the low average land holding and financial constraints. 

“Of more than 150 million farmers in India, 80 per cent have landholdings of two acres or less, which makes the adoption of technology financially challenging for them,” said Karan Mehta, Venture Principal, Green Frontier Capital -- a VC firm.

Mehta said that the significant total addressable market (TAM) in this sector has been one of the main reasons why startups have attempted to develop solutions for Indian farmers. 

However, most of the agritech startups in the past have created products and services that only targeted the 20 per cent of farmers who have larger landholdings, which limited the TAM significantly, Mehta said. 

Mehta however sees hope for the sector as AI solutions in the agritech space become more accessible and apparent to a broader range of agricultural stakeholders.