A high-throughput maize kernel traits scorer based on line-scan imaging

Maize kernel traits such as kernel length, kernel width and kernel number determine kernel weight and, consequently, maize yield. Therefore, the measurement of kernel traits is important for maize breeding and the evaluation of maize yield. The conventional method for measuring kernel traits is still manual, which is time consuming, costly and subjective. In this study, a novel maize kernel traits scorer (MKTS) was developed for the automatic measurement of 12 maize kernel traits based on line-scan imaging, image processing, and automatic control techniques. Here, total of 615 samples were measured to evaluate the system performance. The results showed that the MKTS was capable of evaluating maize kernel traits with the mean absolute percentage error of the manual and automatic measurements less than 5% and the measurement efficiency of approximately 72 s for the measurement of 6 ears. In conclusion, this high-throughput scorer will provide maize scientists with a novel tool to assist in maize functional genetics and maize breeding.