Abstract: Gender sorting silkworm pupae is a highly labor-intensive step in the agricultural industry nowadays. The existing sorting machine also suffers small applicable variety, low accuracy and low efficiency. Furthermore, gender sorting can depend mainly on the reliable difference in the gonad characteristics of male and female silkworm pupa. In this study, an online gonad image acquisition and automatic gender classification device was designed for silkworm pupae. The silkworm pupae were automatically flipped to capture the gonad feature image. Firstly, the vibration feeding, conveyor slide and rotation structures were analyzed using the physical parameters of silkworm pupae. The key influencing factors were determined in the automatic identification and sorting of male and female silkworm pupa: the spiral obliquity of vibration feeding, slideway obliquity and rotational speed. Then, the spiral obliquity of vibration feeding, slideway obliquity and rotational speed of silkworm pupae were optimized to improve the sorting speed under the same recognition and computer hardware conditions. Finally, an information fusion control system was designed using a laser and photoelectric sensor with SIEMENS-S7-200SMART-ST30 as the controller. The automatic opening and closing of the anti-congestion device were accurately controlled to realize the automatic moving and reset of the silkworm pupae pushing and receiving device, the automatic collection of image information, the automatic start and stop vibrating feeding system. The Box-Behnken test was carried out to improve the performance of the sorting device. The three-factor and three-level orthogonal experiments were conducted, in which the spiral obliquity, slideway obliquity, and rotational speed were taken as influencing factors, whereas, the average sorting time, sorting accuracy, and breakage rate of single silkworm pupa were as the response indexes. The results of variance and response surface showed that the best parameters were the spiral obliquity of 15.62°, slideway obliquity of 31.77° and rotational speed of 21.09 r/min, single silkworm pupae average sorting time of 5.13 s, sorting accuracy rate of 95.97%, and breakage rate of 0.07%. Under such optimal parameters, the prototype test showed that the sorting time, sorting accuracy, and breakage rate were 5.03 s, 96.47%, and 0.09%, respectively, which fully met the practical application requirements of the gender sorting for silkworm pupae. The developed device was achieved in the automatic feeding, online gonad image acquisition, automatic recognition and sorting of silkworm pupae, indicating the higher efficiency and accuracy of gender classification. Therefore, the finding can provide the theoretical basis and technical support to the automatic gender sorting device of silkworm pupae. It is of great significance in the automated breeding of the silkworm industry.