Technology will now aid farmers in calculating weather conditions and pest threats to ensure more crop yield
A few dozen villages in the states of Karnataka, Andhra Pradesh, Madhya Pradesh, Maharashtra, and Telangana have now made use of Artificial Intelligence (AI) to help farmers. Microsoft India has collaborated with ICRISAT (International Crop Research Institute for the Semi-Arid Tropics) to develop guiding systems for farmers in these states.
ICRISAT is a non-profit organisation which conducts agricultural research for development in Asia and sub-Saharan Africa.
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Technologies like Cloud Machine Learning, Satellite Imagery, and Advanced Analytics will guide the farmers in getting a higher crop yield and better price control. These technologies are optimized by Microsoft Cortana Intelligence Suite including machine Learning and Power BI.
A model inclusive of a variety of agricultural products will forecast arrival of these commodities and their corresponding prices.
The model calculates crop yields, updating itself through each stage of farming by using data from geostationary satellite images.
These systems will also help the government in Karnataka to plan the Minimum Support Price (MSP) according to the price forecasts offered by the AI on tur (or split red gram) three months in advance. Karnataka is the second largest producer of tur.
Suhas P. Wani, the director of Asia Region in ICRISAT said, “Sowing date as such is very critical to ensure that farmers harvest a good crop. And if it fails, it results in [a] loss as a lot of costs are incurred for seeds, as well as the fertiliser applications.”
The AI will also notify the farmers in case there’s a pest threat to their crops and price forecasts. These calculations are based on the weather conditions and crop stage.
Keeping in mind the lifestyles of Indian farmers, this system does not need them to install any sensors in their fields or spend heavily.
ICRISAT says, “the app sends sowing advisories to participating farmers on the optimal date to sow. The best part is that the farmers don’t need to install any sensors in their fields or incur any capital expenditure. All they need is a feature phone capable of receiving text messages.”
The system gathers data spanning over three decades to analyse and calculate price predictions or pest threats. For example, they collected climate data for the Devanakonda area in Andhra Pradesh, between 1986 to 2015, to predict the crop-sowing period.
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Moisture Adequate Index (MAI) is the standard measure used to assess the adequacy of rainfall and soil moisture. It calculates the water requirement of crops and was used to analyse the optimal sowing period.
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Around 4000 farmers in Andhra Pradesh and Karnataka have used the swing insights by ICRISAT for the Kharif crop cycle (rainy season) this year.
Featured image source: Flickr.
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