India’s food requirement is likely to go up from the present level of 330 million tonne (mt) to more than 500 mt by 2050, even as supply is expected to fall 16 per cent due to water and heat stress. Hence, in order to meet the growing demand for food amidst shrinking land size, there’s a need to focus on precision farming.

This involves leveraging digital tools such as artificial intelligence, machine learning, and the Internet of Things to optimise crop yield and quality while minimising costs and resources. Quality estimation of the seeds to be cropped along with well-prepared soil and precise seeding advisory are needed to increase the efficiency of the input resources.

Based on the soil health analytics, the amount and type or micro/macro nutrients can be decided and added to the soil. IoT enabled soil sensors combined with remotely sensed data through drones/satellites and fast processing can determine what is needed by the soil. And this can either send a notification to the farmer’s phone or through a central server.

Crop surveillance

Crop surveillance is the only way that a farmer can ensure a timely harvest, especially when dealing with seasonal crops. Any errors at this stage can result in crop failure. It also helps in understanding and planning for the next farming season. Through effective inspection of the field with infrared cameras and based on their real-time information, farmers can take active measures to improve the condition of plants in the field.

PEAT, a tech start-up, has developed an AI-based application called Plantix that can identify the nutrient deficiencies in soil including plant pests and diseases by which farmers can also get an idea of the precise quantity of fertiliser to use, which will help improve the harvest quality. This app uses image-recognition-based technology. The farmer can capture images of plants using smartphones.

Data-based harvesting decisions are the next important step that can increase the efficiency of farming decisions. IoT and analytical tools can identify the parameters for harvesting in real-time and allow the farmer to decide whether the crop is ready to be harvested. Presently, this is done based on physical attributes of the crop, such as colour, size, and shape.

Through digital tools, farmers can estimate when the nutritional content is highest in the crop and determine the correct time of harvesting. For example, the harvesting of sugarcane crop can be done based on sugar content in the plant and not by its size. Post the harvesting stage, digital tools can enable farmers with price, storage, transportation and logistics information, which is of utmost importance to the farmer. Traceability in supply chain, particularly in exports, is gaining importance where the precision technology can play a useful role .

Digital agriculture

The primary factor behind the slow uptake of digital agriculture is the prominence of segregated smallholder farms in the country, which makes data gathering a complicated activity. Additionally, data of different geographical locations, markets, weather, soil types, crop types, and of many other parameters are needed to make a viable advanced technology-based model. At present, there isn’t a centralised repository of different varieties of data stacks to be used in agriculture.

An efficient analytical model requires high quality weather, soil, cadastral, and several other data types. While satellite data is available to a certain extent, finding matching levels of other data sets is an issue. Cadastral data with administrative boundaries and geo-coded soil data must be made available through public sources to improve the analytics and insight generation capabilities. At present, only few States have GIS maps of cadastral boundaries, which limits the potential of wide scale implementations of digital solutions.

There are several disparate sets of rich data that exist across various parameters. For instance, Soil Land and Use Survey of India captures data on soil and land characteristics that are made available for watershed-based soil and water conservation and soil health management. The soil health card database is another rich source of data on micronutrient status of soil. These data sets are again disparate and not interoperable, limiting analytics and value creation.

Way forward

The solution towards scaling up of digital agriculture in India is partnerships. Learnings can be drawn from several successful examples of partnerships between stakeholders within India and internationally to bring digitisation to the farm and impact the sector.

In the recent Budget, the government had announced development of digital public infrastructure for farmers covering all areas from input to output. While one is not still aware of the type of infrastructure expected, it is a great initiative as it might help several start-ups in the country not to replicate their efforts and focus more in connecting the farmers to the market.

The farmers in our country cannot afford to pay for the technological interventions. They need the government to subsidise the cost of technology or to help through the custom hiring route to enable them move towards digital technology, which would significantly enhance farm productivity and, in addition, improve the environment.

There’s also the need to ensure creation of carbon credits for the farmers which would give a boost to the adoption of precision agriculture.

The writer is Director & Group President (Finance & Investment), TAFE Ltd. The views are personal

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