Students at the National Center for Artificial Intelligence (NCAI) at the NED University, in collaboration with Rice Lab Pakistan, have successfully developed Pakistan’s first AI-based software that analyzes the quality of rice grains.
Named “Rice Quality Analyzer,” the software uses Machine Learning to determine 7 important features of rice grains including length, thickness, average weight, and percentage of broken grains in less than 60 seconds.
Rice Quality Analyzer has 99% accuracy and is on par with two modern Japanese and American softwares. However, the Pakistani version of the software is more efficient in comparison to the Japanese version and is more cost-effective compared to the American version.
More importantly, Rice Quality Analyzer has been developed keeping in view the atmospheric conditions of Pakistan and is in accordance with the requirements of the national rice industry.
Pakistan is the 10th biggest producer of rice in the world and the crop is an important source of foreign exchange for the country. The price of rice is based on its quality worldwide, meaning the better the quality of the product the higher its price.
For decades, the quality of rice grains in Pakistan has been determined manually through the human eye and other instruments. The traditional process involves analyzing the 8kg sample taken out of the 2.5-ton rice lot. Not only is this method time consuming and ineffective but costs thousands of rupees as well.
Rice Quality Analyzer, on the other hand, will increase the testing capacity of the local rice industry by enabling it to ascertain the quality of maximum rice samples in minimum time and cost.
A research associate at the NCAI and member of the Rice Quality Analyzer software development team, Hafiz Ahsan-ur-Rehman, has declared the achievement as a major milestone for the Pakistani rice sector.
He added that the advertising campaign of the Rice Quality Analyzer is well underway and has received encouraging feedback from major rice-producing nations including China, India, Indonesia, and Bangladesh.