The Ministry of Agriculture signed five memorandums of understanding (MoUs) with five tech giants. Under the collaborations, the private players will conduct pilot projects to integrate digital technology and other best practices in the agricultural sector.
According to a news report, these MoUs are a part of the digital agriculture mission that was initiated for 2021-25 by the government to integrate emerging technology such as artificial intelligence (AI), blockchain, remote sensing and GIS technology and the use of drones and robots, etc. Establishing a digital ecosystem of agriculture needs to take a long-term view of aspects like interoperability, data governance, data quality, data standards, security, and privacy, besides promoting innovation. A significant requirement is the adoption of a decentralised, federated architecture that assures autonomy to the service providers and all other actors and ensures interoperability at the same time.
To support these projects, the ministry is creating a federated farmers database that will be linked to farmers’ land records from across the country and a unique farmer ID will be created. These technologies will support farmers to make informed decisions on suitable crops to grow, types of seeds to use, and the best practices for maximum yields. The agriculture supply chain players can plan their procurement and logistics on precise and timely information. Farmers can make informed decisions about whether to sell or store their produce and when and where and what price to sell, the report said.
Further, under the unified database for all farmers, users can access the information of all benefits and supports of various schemes of the central and state governments. So far, the database is ready with details of around 55 million farmers. Any attempt to transform the agriculture sector needs to imbibe an ecosystem thinking and a digital ecosystem. The agriculture value chain extends from crop selection to crop management and the market; it involves public and private players in agricultural inputs and services and also logistics.
The country has been using technology to improve crop yield and double farmer incomes. In July, researchers at the Indian Institute of Technology in Mandi (IIT-Mandi) and the Central Potato Research Institute (CPRI) in Shimla developed an AI solution that can detect diseased parts of potato crop using photographs of its leaves. As OpenGov Asia had reported, blight is a common disease of the potato plant. It leads to the rotting of the plant. If left undetected and unchecked, blight could destroy the entire crop within a week under conducive conditions.
IIT-Mandi’s computational tool can detect blight in potato leaf images. The model is built using an AI tool called mask region-based convolutional neural network architecture and can accurately highlight the diseased portions of the leaf amid a complex background of plant and soil matter. In India, as with most developing countries, the detection and identification of blight are performed manually by trained personnel who scout the field and visually inspect potato foliage. This process, as expected, is tedious and often impractical, especially for remote areas, because it requires the expertise of a horticultural specialist who may not be physically accessible.
Automated disease detection can help in this regard and given the extensive proliferation of mobile phones across the country, the smartphone could be a useful tool, according to a researcher on the team. The advanced HD cameras, better computing power, and communication avenues offered by smartphones offer a promising platform for automated disease detection in crops.
