As one of the representative industries of agricultural production，the wine industry mainly includes two main parts：grape planting and wine making. featuring long production cycles，difficulty in collecting process data，and complicated biochemical principles. These factors have brought difficulties to those who engaged in the cultivation and production of agricultural products in the production analysis and process optimization. To solve this difficulty，it is necessary to use new information technology to construct the process data set. However，the collection，transmission and storage of complex data put forward higher requirements for network throughput，delay，jitter，and packet loss rate. This requires a new type of industrial interconnection network and connection platform to support it. With the help of high-quality external networks，comprehensive utilization，and real-time monitoring of data in the process of grape planting and wine production are carried out，and data identification is established；based on this，data cleaning and conversion are completed，data warehouses are built，mechanism models are set up and virtual comparison experiments are conducted. The small-scale mechanism experiment of this method is completed offline，which relieves the user’s concern about leakage of the production process. The massive parallel comparison data can greatly reduce the number of biochemical experiments and provide guiding opinions for the researcher to choose the research direction. The core advantage of the method is that it makes full use of high-quality external networks and big data to perform virtual logic comparisons，thereby completing the mechanism restoration test that cannot be reproduced on a small scale. At the same time，the core process landing experiment is completed offline，which relieves users from concerns.