Abstract: 【Objective】 To develop an adaptive slicing method for point cloud volume estimation tailored to pig body segmentation，which could provide technical support for the efficient acquisition of novel pig phenotypic information. 【Method】 A point cloud segmentation technique was employed to divide the pig body into 8 major parts，including the head，torso，and limbs. An adaptive slice distance algorithm was proposed based on the geometric characteristics and point density of each part. The slice distance parameters were adaptively adjusted by calculating the uniformity of point cloud distribution，density uniformity and mesh volume，and the most suitable cutting direction to calculate the volume and the proportion of each part’s volume was selected by using the slicing method. To verify the accuracy of the algorithm，tests were conducted respectively with standard-shaped point clouds（cylinders，cubes，spheres），the Stanford Bunny rabbit model，and the model pig with the volume obtained by the water displacement method. The accuracy of the algorithm was evaluated by comparing with the actual volume. 【Result】 The adaptive slice distance algorithm demonstrated high accuracy and good adaptability on both standard geometric bodies and complex shape models，and showed higher precision and robustness under different densities. The volume of the model piglet was calculated to be 4379.658 cm³ by the method of segmentation first and then volume calculation. The absolute error compared with the actual volume was 157.642 cm³，and the relative error was 3.47%. The data of 371 pig body point cloud samples were divided into 222 training samples and 149 test samples. A weight prediction model was constructed based on volume，and the correlation coefficient（r）between volume and weight was 0.952，indicating that there was extremely strong positive correlation between the calculation result of pig body point cloud volume and the actual weight of pigs. The absolute error and relative error of the estimated weight were 3.244 kg and 2.91% respectively. The point cloud calculation of the volume and proportion of each part of the entire pig bodies showed that the average proportion of the head volume was 6.49%，the average proportion of the limb volume was 10.32%，and the average proportion of the Torso volume was 83.04%. 【Conclusion】 The slice volume calculation method based on adaptive cutting distance is applicable to the calculation of point cloud vo-lume in pig body segmentation. It shows obvious advantages in the calculation of point cloud volume with different densities and complex geometric shapes，effectively solving the problem that the traditional fixed slice method cannot adapt to the uneven densities of point clouds and the continuous change of volume. That is，by measuring the volume of different parts，the proportion of each part of the pig body can be estimated. It provides support for meat density assessment and quantitative breeding，and obtaining new phenotypes information of pigs.