A U-net based method for extracting the phenotypes of shiitake mushrooms was proposed to solve the problems of the low level of informatization and the time-consuming and laborious manual measurement of phenotypes in shiitake mushroom. U-net based segmentation of caps， stipes， and left and right gills in shiitake mushroom was achieved by collecting the cross-sectional images of shiitake mushrooms and establishing a dataset. The results showed that the average intersection to union ratio and average pixel accuracy of the model was 85.00% and 91.25%， respectively. The automatic measurement of five parameters for phenotypes in shiitake mushrooms including the cap diameter， cap thickness， stipe length， stipe diameter， and gill width was achieved by combining the centroid method with the minimum bounding rectangle method. The method proposed had mean absolute percentage error （MAPE）of 1.57%， 5.01%， 2.57%， 5.47%， and 2.74% in measuring the cap diameter， cap thickness， stem length， stem diameter， and gill width， with the root mean square error（RMSE） of 0.12 cm， 0.08 cm， 0.09 cm， 0.10 cm， 0.06 cm and all determination coefficients（R2） exceeding 0.90 compared with manual measurements. It is indicated that the U-net based method for extracting the phenotypes in shiitake mushrooms is suitable for measuring phenotypes in shiitake mushrooms with a high accuracy of segmentation. It will provide strong technical support for the sorting and grading of shiitake mushrooms.