［［Objective ］］ Improve the accuracy and robustness of maturity detection of pitaya fruit.［［Methods ］］ Combining the YOLOv 8 object detection model with the PSP -Ellipse segmentation algorithm,an efficient and accurate automatic identification method for pitaya fruit maturity was proposed.First,the real -time target detection function of YOLOv 8 was used to locate and identify the pitaya fruit initially.Then the shape recognition capability of PSP -Ellipse was used to further fine classify the shape and maturity of the pitaya fruit.［［Results］］ The accuracy rate of maturity classification of pitaya fruit was 97.6%,and the robustness was strong.［［Conclusion ］］ This method can significantly improve the automatic classification efficiency of pitaya fruit under complex backgrounds and various lighting conditions.