Soon all farmers, traders, exporters and government will have information about crops at the time of harvesting as machine learning (ML) and artificial intelligence (AI) will give nearly accurate predictions of crop production.
Junagadh Agriculture University (JAU) is developing a model using remote sensing which was selected at national level by Indian Council of Agricultural Research (ICAR) and a grant of Rs 75 lakh was approved for this project under National Agriculture Science Fund.
The three-year project will be done at the remote sensing and GIS (Geographical Information System) lab at Research Training and Testing Centre (RTTC) on JAU campus.
Project is being executed jointly by JAU, Agri Engineering College at Godhra affiliated with Anand Agriculture University, and Soil and Water Conservation Research Centre, Vasad.
Initially, prediction for three districts of Saurashtra — Junagadh, Amreli, and Rajkot — and three districts of central Gujarat including Ahmedabad, Dahod and Panchmahal will be done. Groundnut and cotton crops from Saurashtra and millets and rice from central Gujarat will be taken up for the study.
The project in-charge Parthsarthi said: “We will collect the data of sowing using two satellites — Landsat and Sentinel — and prepare a vegetation index and will generate the data for Kharif crop in the initial stage. We will also feed the meteorological indication, weather prediction including rain and temperature prediction provided by metrological department. We will feed last 30 to 40 years data for sowing, crop yield, meteorological condition (drought, over raining) etc, and based on all these inputs this model will provide us with the prediction of the crop at the time of harvesting.”
This crop yield prediction will be available on a web portal for all the stake holders.
RB Madariya, director of research at JAU said, “The current system of generating data of production is manual, and it takes a lot of time. It the govt wants to decide on importing any agro-product or allowing export looking to the local supply, they would be able to take early based on this data. The farmers will be able to see how much price they would get in the market, based on the expected crop yield. The traders and exporters will also be able to make informed decisions.”
AAU has also collaborated with the Indian Space Research Organization (ISRO) for price forecasting of crops. “SAC, Ahmedabad is one of the collaborating agencies through which satellite data is being utilized along with ML and AI for developing the model which would help increase the accuracy of price forecast keeping multiple parameters in consideration,” said AAU vice-chancellor KB Kathiria.
“We have collaborated with SAC, ISRO to develop a model for price forecasting of selected agri-commodities like wheat, rice, maize among others,” he said. He also added that satellite images are being used for weather forecasts, weather-based crop estimation, knowing the geographical spread of crops, yield estimation and disease surveillance.
“Once we know the total area under sowing and harvesting and the estimated yield of crops, we can estimate the total production in any season. This, in turn, provides us an understanding of price patterns which is the main concern of farmers,” he said.
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