This paper presents the implementation of the Pure Pursuit control algorithm for path tracking on an agricultural pesticide spraying drone. Precise path tracking ensures accurate pesticide coverage, maximizing crop yield and minimizing environmental impact. Conventional position control architectures used by most agricultural drones can lead to inconsistent pesticide distribution due to variability in drone speed. Position control also causes deceleration and acceleration at corners, resulting in over-spraying in these areas. This lack of uniform spray distribution challenges efficient and sustainable agriculture. The Pure Pursuit algorithm is favored for its simplicity and effectiveness in autonomous navigation. The software architecture, including the flight control stack and ROS2-based PX4 simulation architecture, demonstrates the drone’s accurate trajectory following capabilities. Simulation tests evaluated the path tracking accuracy and overall performance of the system. Comparative results show the Pure Pursuit controller’s superiority over standard position controllers in terms of accuracy, robustness, and adaptability. Additionally, this paper introduces an innovative Coverage Path Planning (CPP) strategy based on grid decomposition. Integrated with the Pure Pursuit control mechanism, this CPP strategy ensures precise path tracking and maximizes coverage uniformity, further enhancing the effectiveness and sustainability of agricultural spraying operations.