Research and Application of Soil Health Monitoring and Analysis System for Mulberry Planting based on IoT and WebGIS

As an important economic crop in China, the planting history of mulberry can be traced back to more than 5,000 years ago. Since the 1970s, Yizhou District, Hechi City, Guangxi Province has begun to establish a special mulberry silkworm production service management agency. Now Yizhou District, Hechi City, Guangxi Province has become an important base for mulberry planting. Mulberry leaves are not only the main feed for sericulture, but also widely used in traditional Chinese medicine and daily life. Mulberry planting technology has also been continuously improved with the changes of the times. Nowadays, with the rapid development of agricultural modernization, traditional planting methods in Yizhou area have also begun to face many challenges, including low planting efficiency, unstable yield, and difficult management of large plantations. These problems directly affect the quality and yield of mulberry leaves, and directly affect the healthy development of sericulture and the economic income of mulberry silkworm farmers. To solve the above problems, this study proposed a method based on the Internet of Things (IoT) and Web Geographic Information System (WebGIS). The system monitors the soil and environmental data of mulberry planting areas in real time, and provides farmers with accurate planting suggestions and decision support after system processing. By using WebGIS technology to map planting plots and sensors and other equipment, it is easier for farmers to manage planting areas. After field deployment and verification in Yizhou area, the system has been proven to effectively improve planting efficiency, stabilize yields, and reduce production costs. In addition, the implementation of the system is also of great significance to improving the sustainability of agricultural ecology. It not only improves the scientific and technological level of regional agriculture, but also provides new research directions and data support for agricultural scientific research. It has good development prospects and practical application value.