Warehousing management firm SLCM has launched a mobile app, named AgriReach, that seeks to provide technological resolution of high-quality checking of farm commodities in mandis and warehouses. Though the app is not an option to the technique of testing accomplished via accredited labs, it is seen as an improvement from present technique in which traders or their representatives choose high-quality of generate on physical inspection of crops.
“We have started with wheat crop first and will add paddy/rice, maize, chana, moong, tur, soyabean and guar to the app in a phased manner,” SLCM’s CEO Sandeep Sabharwal stated in an interaction with media right after the launch. The app will also be offered in other Indian languages apart from English and Hindi, Sabharwal stated, adding that the business plans to give it in even international languages to make it a worldwide platform of its type.
SLCM had currently applied for patent of the AgriReach app in 2018. The business claims the accuracy level, at the moment at 70-80%, will enhance to 95% by March as it has been working on it right after widening its sample collection. “Already 2.5 lakh photographs of wheat of different varieties at different locations in different time have been compiled,” the CEO stated.
Citing that samples collection is essential to the accuracy of the benefits via the app, he stated the business has future strategy to keep away from human interface by producing photography/videography automatic and continuous when crops are unloaded in mandis and warehouses.
“The test results are agnostic of the total sample weight as they are assessed based on its image. Once photograph is submitted, the user will receive the quality report with the photographic evidence evaluated on specifics like damaged, shrunken, shrivelled or immature grains, foreign matter and a host of other physical parameters like height, length, grid, colour and pattern of the commodity,” stated Rakesh Kumar Rana, SLCM’s chief small business officer (digital initiatives).
The benefits are automatically compared with pre-fed information in the back-finish technique, which will routinely update itself making use of a mixture of Artificial Intelligence (AI) and Machine Learning (ML) with Python programming language, on a actual-time basis, Rana stated.
The business will not charge any charge from farmers when they sell it in mandis or elsewhere if they use the app. However, bulk customers like processors and traders will have to spend particular costs.
Approximately, 82% of the foodgrains produced in the nation are traded inside or outdoors mandis though remaining are employed by farmers for their personal consumption, seeds and feed purposes.