To realize the efficient, accurate and rapid automatic picking of brown mushroom, the identification, size measurement and positioning of mushroom are the key to the robot selective picking operation. An integrated method for in situ identification, measurement and location of brown mushroom was proposed based on YOLO v5 transfer learning (YOLO v5-TL) and dynamic diameter estimation based on 3D edge information. Firstly, YOLO v5-TL algorithm was used to realize rapid identification of brown mushroom under complex mycelia background. Then, the image enhancement algorithm, denoising, adaptive binarization algorithm, morphological processing and contour fitting algorithm were used to locate the edge of the mushroom image in the anchor frame area, meanwhile, the pixel coordinates of the edge point and the center point were extracted. Finally, the dynamic diameter estimation method based on 3D edge information was used to accurately measure the size and locate the center point of the mushroom. The experimental results showed that the average processing time of single frame image was 50ms. The average success rate of picking object recognition under low, medium and high light intensity was 91.67%, and the recognition rate reached 100% under high light intensity. The average measurement accuracy of mushroom cover was 97.28%. The results showed that the proposed YOLO v5-TL method combined with 3D edge information diameter dynamic estimation method can realize the integration of identification, measurement and location of brown mushroom under factory planting, which met the demand of automatic picking of brown mushroom by robot.