Amazon is developing a computer vision-based grading solution for fruits and vegetables in India. According to Business Standard, the machine learning-based approach analyses produce images to detect defects such as cuts, cracks and pressure damage. It can perform millions of assessments per day at a cost far below any other method, said an Amazon representative.
Speaking at the company’s Smbhav event, Rajeev Rastogi, vice president, machine learning, Amazon India, said:
“Quality is one of the key drivers of fruit and vegetable purchasing decisions and a critical factor in achieving customer satisfaction. Having humans grade the quality of fruits and vegetables by manually examining each individual piece of produce like tomato or onion is not scalable to millions of quality assessments per day.”
Amazon plans to develop a conveyor belt-based automatic grading and packing machine. It would leverage hardware and machine learning to pack produce into predetermined quality grades such as premium-grade A. The gradient pack machine will reduce grading costs by 78% compared to manual grading.
Amazon also plans to use near-infrared sensors to detect attributes such as sweetness and ripeness. These cannot be detected in RGB (red, green, blue) images captured by traditional computer vision algorithms and require destructive methods such as eating the fruit.