<p>Volume is an important attribute of agricultural products. Accurately obtaining the volume is vital for monitoring growth status, evaluating nutritional value, post-harvest grading and packaging of them. Different from spherical agricultural products, columnar agricultural products have irregular shape and poor symmetry. This makes it difficult to apply traditional volume measurement methods. In this paper, we proposed a novel pipeline for columnar agricultural products volume measurement, named CSVM. The CSVM method employed mobile phone as data acquisition device due to its cost performance, and the NeRF technology was utilized to get the point cloud of the object. To overcome the information loss caused by sparse point clouds during traditional filtering, the quadratic vector filter was designed, which can effectively preserve correct point clouds while filtering out the noise, even if they are highly similar. Finally, the volume measurement results are acquired by improved point cloud slicing method. This study selected four typical columnar agricultural products (king trumpet mushroom, green pepper, carrot, and balsam pear) as experimental samples. The mean absolute percentage error(MAPE) for volume estimation was 3.98%, 3.16%, 2.22%, and 3.36%, respectively. These results demonstrate the excellent performance of CSVM method, which is comparable or superior to existing methods. This pipeline can accurately measure the volume of columnar agricultural products, furthermore, it can lay the foundation for industrial application.</p>