The government of India's policy think-tank NITI Aayog has partnered with one of the world's largest technology companies IBM to develop a crop yield prediction model using artificial intelligence (AI) to provide real time advisory to farmers in backward states of India.

NITI Aayog has signed a Statement of Intent with IBM, wherein the company will assist the country to use technology to provide insights to farmers to improve crop productivity, soil yield and control agricultural inputs with the overarching goal of improving farmers’ incomes. The agreement was signed in the presence of NITI Aayog CEO Amitabh Kant and Karan Bajwa, Managing Director, IBM India.

Essentially, IBM will help India to develop Precision agriculture or satellite farming, which is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. The goal of precision agriculture research is to define a decision support system (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources.

Precision agriculture, as the name implies, means application of precise and correct amount of inputs like water, fertilizer, pesticides etc.

"Bringing future technologies like AI into practical use will greatly benefit agriculture in the country by improving efficiency in resource-use, crop yields and promoting scientific farming," said NITI Aayog CEO Amitabh Kant.

The first phase of the project will focus on developing a model for 10 backward states, which are termed as as "aspirational districts" by NITI Aayog. The states include Assam, Bihar, Jharkhand, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh.

IBM will be using AI to provide all the relevant data and platform for developing technological models for improving agricultural output and productivity for various crops and soil types, for the identified districts. NITI Aayog, on its part, will facilitate the inclusion of more stakeholders on the ground for effective last mile utilisation and extension, using the insights generated through these models. NITI Aayog has also tied up with Google to foster AI and Machine Learning ecosystem in India.

The project also include involvement of other things, besides IBM's technology, such as deployment of weather advisory, rich satellite and enhanced weather forecast information along with IT and mobile applications.

The purview of this project is to introduce and make available climate-aware cognitive farming techniques and identifying systems of crop monitoring, early warning on pest and disease outbreak based on advanced AI innovations.

Capabilities & Offerings of IBM in Agriculture Tech

In order to understand the capabilities of IBM in agriculture and farming, IBM has its flagship offering in Precision Agriculture, wherein its technology helps farmers use data to make precise decisions from planting, growing, harvesting, to transporting food. According to the company, the ability to monitor and track the route of food delivery can not only save food waste but enable food safety.

Besides, IBM has another farming-related offering called Deep Thunder, which can forecast future conditions based upon the physics of how the atmosphere interacts with the soil, which is needed to understand the impact of weather on farming operations.

As 90% of all crop damage is caused by the weather, the loss of crops can be slashed by up to 25% using predictive weather modeling and that's where IBM's Deep Thunder addresses this issue by incorporating a weather model that utilizes data from many public and private sources and provides hyper-local forecasts of weather and weather impacts up to three days ahead with great precision and accuracy.

Smart agriculture has been identified as the top ranked opportunity in 2016 Global Opportunity Report. The farmers and stakeholders in the ecosystem are encouraged to implement advanced technologies to use the resources efficiently and optimize yield.

News Source - Economic Times | References - Press Information Bureau; Huffington Post

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