At present, in the task of detecting grain quality indicators in China, incomplete grain detection mainly relies on manual detection, with strong subjectivity and low detection efficiency in the detection results. In response to the pain point issue of incomplete grain testing in the industry, the company has developed and launched a series of grain quality analyzer products. This product is equipped with a wheat incomplete grain detection algorithm based on deep learning and machine vision technology, achieving automated and rapid detection of incomplete grain, and deeply promoting the practical application of artificial intelligence technology in the field of grain quality inspection.