Researchers at Bangladesh Agricultural University (BAU) have developed an automated potato grading machine designed to slash the substantial post‑harvest losses that trouble the country’s potato sector.

Bangladesh loses roughly 20 percent of its potato yield after lifting, according to Department of Agricultural Extension data, as inadequate sorting and storage rot produce and erode export potential. The new device sorts more than 500 kg of potatoes per hour at a cost of just 12 poisha (BDT 0.12) per kilogram, making it roughly 70 times cheaper than manual grading, according to the research team’s calculations.

The machine uses computer vision to assess potatoes’ external characteristics in real time, replacing labour‑intensive conventional methods that the team described as slow, expensive and inconsistent.

Professor Anisur Rahman of the university’s farm power and machinery department, who led the project, said the technology was built to overcome the shortcomings of traditional sorting. “Current grading is done using conventional methods. It’s time‑consuming, labour‑intensive, and produces inconsistent quality,” he said.

The third iteration of the prototype marks a significant leap in speed and accuracy. An earlier version, reliant on pixel‑based analysis, could process only 14 images a minute. The latest model incorporates an industrial CCD camera capturing 539 frames per second, which the team says has dramatically improved throughput and precision. The device is built from locally sourced components and has now completed laboratory trials, with field‑level testing due to begin shortly.

Co‑researcher Professor Rostom Ali cited Bangladesh Bureau of Statistics figures showing the country produced roughly 11.5 million tonnes of potatoes last year against domestic demand of 9 million tonnes, leaving an exportable surplus of around 2.5 million tonnes. The automated grader, he said, could reduce storage‑related rot, raise the share of export‑quality produce, and supply processing industries with consistently graded stock. Ali added that output‑based grading would also help farmers secure fairer prices.