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Aiming at the problem that in the automatic root cutting process of factory bottle-planted enokis, the stroke of the clamping end was fixed due to the structural design, which affected the gripping effect and even the quality of root cutting, an improved enoki-pick_region-YOLO v8 based on the you only look once (YOLO v8) was constructed, realized accurate positioning and contour extraction of the whole bottle-planted enoki as well as the optimal stress area (the key picking region). The accurate localization and contour extraction of the whole bottle-planted enoki and the best stress region guaranteed the reliability of the grasping parameters. On the basis of network optimization, a mask attribution and judgment model based on the minimum Euclidean distance (ED) was constructed, the parentchild relationship between the enoki body mask and the key region mask was clarified, and they were merged for optimization. By analyzing the relative position encoding of the key region before and after the merger, the grasping parameters were determined and converted into coordinates, which provided the basis for establishing the end control mapping model to realize the precise control of the end manipulator’s motion stroke. The experimental results showed that the algorithm achieved a mask recognition rate of up to 99.3% for the enoki body and 99.6% for the key picking region. At the same time, it was found that the quality of the mask was improved, and the error between the width of the picking area and the actual width of the acquired parameters was only 0.7%, and the grasping parameters basically satisfied the conditions of grasping, which effectively realized the accurate identification and localization of the optimal grasping position.