Abstract: Saline-alkali tolerant rice often grows in saline-alkali land with salt (alkali) concentration above 0.3%, mainly in Inner Mongolia and Ningxia semi-desert inland areas. The growth environment has posed a serious threat to the yield of saline-alkali-tolerant rice. Traditional wireless sensor network (WSN) has been widely used for energy consumption, transmission delay and throughput in data collection and transmission. However, the current environmental monitoring cannot fully meet the requirement of large-scale production in recent years, due to the complex environmental data under the condition of low communication coverage. In this study, the medium access layer saline-alkali tolerant rice environmental data perception strategy (MAC-SREP) was proposed in the WSN network, in order to comprehensively optimize the MAC layer and multiple unmanned aerial vehicles (UAV) route planning in the multiple unmanned aerial vehicles-wireless sensor network (mUAVs-WSN) system. The monitoring region was first divided into some subregions using the concave and convex polygon division. Multi-UAVs collaborative search region model was utilized to map into a single UAV search subregion model. Voronoi diagram was also modified using the communication distance of cluster head nodes and the communication coverage radius of the UAV to the ground. The modified Voronoi diagram was then divided into some clusters to optimize the flight path of the UAV. Then, the MAC layer mechanism was used to prioritize the packet types of UAVs for the effective allocation of time slots and network resources. The competition window size was adjusted under the different network loads. The adaptive retreat mechanism was used to reduce the channel conflict. The environment data was collected from the saline-alkali tolerant rice growth in real time and then uploaded into the server of the management center. The data was also processed and then published on the website. The functions of remote monitoring were realized for the historical record query and visualization of the growth environment information of saline-alkali tolerant rice. The field test was carried out in the large-scale continuous planting area at the saline-alkali tolerant rice experimental base of Guangdong Ocean University, Buchao Village, Jianxin Town, Suixi County, Zhanjiang City, Guangdong Province, China. A monitoring area was about 53 hm². A simulation test was also performed on Matlab software. The results show that: 1) The life cycle of information perception in the mUAVs-WSN network was about 1.25 times that of the single unmanned aerial vehicle-wireless sensor network (sUAV-WSN). The network throughput increased by 15%, whereas, the end-to-end average delay was reduced by 26.60%. 2) In the actual engineering test, the packet loss rate of the mUAVs-WSN network was less than 2% with the data error less than 5%, both of which fully met the monitoring requirements of saline-alkali tolerant rice growing environment area information. 3) The mUAVs-WSN was more suitable for the monitoring areas with a large number of nodes and coverage, especially for the agricultural environments, such as the saline-alkali tolerant rice. The naturally harsh environment limited the formation of a complete monitoring network (often divided into multiple independent networks). Therefore, the improved strategy can be expected to realize the stable real-time acquisition and transmission of saline-alkali tolerant rice remote data. The data packet loss rate and delay were effectively reduced to improve the overall performance of the network. The finding can fully meet the needs of long-term, stable, and efficient growth environment data with the large coverages in the saline-alkali tolerant rice.