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In the task of measuring the phenotypic parameters of Pleurotus eryngii in the mushroom house, due to the limited viewing angle of the scanning equipment, the point cloud of the scanned Pleurotus eryngii is incomplete. Aiming to address this problem, an improved SwinPoinTr was proposed based on adaptive geometry-aware point transformers (AdaPoinTr), achieving accurate completion of the incomplete Pleurotus eryngii point cloud and measurement of its phenotypic parameters. Based on the proposed feature reshaping module, a hierarchical Transformer encoding module was constructed with geometric perception ability, improving the model’s utilization rate of the input point cloud and its ability to capture the detailed features of the point cloud. Then based on the Poisson reconstruction method, the surface reconstruction of the completed point cloud was completed, and the phenotypic parameters of Pleurotus eryngii were measured. The experimental results showed that in the task of completing the incomplete Pleurotus eryngii point cloud, the chamfer distance of the model was 1.316×10-4, the earth mover’s distance was 21.328 2, and the F1-score was 87.87%. In the task of phenotypic parameter estimation, the determination coefficients of the model’s estimation results for the height, volume, and surface area of Pleurotus eryngii were 0.958 2, 0.959 6, and 0.960 5, respectively, and the root mean square errors were 4.421 3 mm, 10.818 5 cm3, and 7.577 8 cm2, respectively. The results confirmed that the method can effectively complete the incomplete Pleurotus eryngii point cloud and provide a basis for the measurement of the phenotypic parameters of Pleurotus eryngii in the mushroom house.