A thorough analysis of optimization strategies designed specifically for wireless subterranean sensor networks used in precision agriculture is provided in this research. WUSN provides essential insights regarding soil conditions, moisture levels, and nutrient distribution, allowing farmers to make informed decisions for optimal crop management. The distinct constraints presented by subterranean locations, including signal degradation, restricted power availability, and severe conditions, require tailored optimization solutions. This paper examines many methodologies, including energy-efficient routing protocols, data aggregation methods, sensor location optimization, and machine learning algorithms. We rigorously assess the benefits and drawbacks of each technology, offering significant insights for academics and practitioners in precision agriculture. Additionally, we delineate current trends and highlight open research issues to inform future progress in the optimization of Wireless Underground Sensor Networks for agricultural applications.