Agricultural information technology is an emerging technology based on the cross-fertilization of information technology and agricultural science, which has caused the rapid development of digital agriculture and smart agriculture. Crop growth models, as one of their core components, can dynamically simulate the crop growth and development process and its relationship with climate factors, soil properties, and management techniques, thus effectively overcoming the strong spatial and temporal limitations in traditional agricultural production management research and providing quantitative tools for early warning and effect assessment of crop productivity prediction under different conditions. This study focuses on the general technical approach, the latest research progress, and future development thinking developed by the authors in the construction and application of the tea mushroom growth model. Based on the fitting method of the data model curve of the Internet laboratory, this study is proposed to use network programming technology to digitally fit the growth curve of cap diameter and stalk diameter of the fruiting body in the process of Agrocybe cylindracea growth. The fitting system adopted the development mode of PHP + MYSQL and took the MYSQL database as the core, which made the curve fitting of the final experimental data fast, convenient, and more intelligent. This study laid a preliminary foundation for the effective establishment and improvement of laboratory Agrocybe cylindracea, fruiting body growth data statistics and analysis, and graphical output network sharing.
Research Progress and Prospect of Blockchain + Agricultural Science Data Management
