Agri Business

An AI-based app from SLCM to assess crop quality in a jiffy

Rutam Vora Ahmedabad | Updated on January 20, 2021

A representative image   -  Getty Images/iStockphoto

Agtech player and post-harvest crop management solutions provider, Sohan Lal Commodity Management Pvt Ltd (SLCM), has developed an AI-based mobile app to provide quality assessment of a crop within a minute with upto 90 per cent accuracy.

Speaking to BusinessLine, Sandeep Sabharwal, CEO, SLCM Group, informed that the new service will be launched in the second quarter of next fiscal.

“The trader or farmer would just need to scan the seeds through our mobile app. It can check multiple quality parameters for a variety of agri produces within a minute with 85-90% accuracy as compared with lab test. It compares with pre-fed data in our back-end system, which also keeps updating itself with machine learning. This is the on-ground utilisation of the technology for agri trade,” said Sabharwal.

The app aims at improving fidelity of commodity quality checks and bringing transparency by reducing turnaround time for quality check.

Currently, SLCM is conducting trials for wheat and chana. It intends to cover rice, guar, moong, tur and other pulses.

“The current quality testing methods of physical verification by holding the grains in the hands, is arbitrary and does not necessarily match the standard quality parameters. So there are possibilities of exploitation on both sides, buyers and the farmers,” said Kamlesh Bhalodiya, a trader at Rajkot APMC.

The app will be based on Machine Learning with Python. Once the picture is uploaded on the app, the system will read the image and create a database based on the physical parameters such as height, length, grid, colour, specific pattern.

However, it will still not replace the lab immediately for other-than physical feature assessment of the crops to assess moisture, etc. “We are working on it and in future we plan to include these features as well,” said Sabharwal.

Published on January 20, 2021

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