Abstract: 【Objective】 Variable spray system can reduce the waste of liquid medicine and reduce the pollution of liquid medicine to land and water. The acquisition of plant geometric parameter information is an important prerequisite for implementing variable spray. R-Fans-32 three-dimensional laser radar (LiDAR) was used to explore the relationship between plant 3D laser point cloud and plant leaf area, providing data support for variable spray machine. 【Methods】 It was assumed that there was a linear relationship between the number of laser point cloud and leaf area. The target detection based on 3 d laser point cloud of the test system was set to measure the height of the target plant to explore the accuracy of laser radar, laser radar with 10 Hz scanning frequency and 1m of the detection range of 10 strains of tomato three-dimensional point cloud data acquisition of laser radar PC software Ctrlview implementation of 3 d laser point cloud data storage. Cloud Compare software was used to process the stored point cloud data, and LiDAR360 software was used to measure the height of plants and obtain the number of point Cloud. The quantity of collected plant point cloud was counted, and the leaf area of picked target plant leaves was measured by CL-202 plant leaf area meter to verify the relationship between plant point cloud and leaf area. 【Results】 The experimental results showed that the maximum relative error between the height of tomato plants detected by lidar and manual measurement was 7.92%. The linear function was used to fit the number of plant point cloud and leaf area, with a fitting degree of 0.7805 and a maximum relative error of 5.64%. 【Conclusion】 An experimental system was designed to explore the feasibility of variable spray system based on laser point cloud. The accuracy of plant leaf area prediction based on 3d laser point cloud was good, and 3D LIDAR R-FAN-32 could be used as the component of variable spray system for crop detection.