In accordance with cotton planting areas in different regions and of different maturity levels in Xinjiang, as determined using the agricultural big data platform of Xinjiang Production Corp., the microbial group database and big data visualization analysis process of a typical cotton field ecosystem in China were established. Using LEfse and an RDA analysis, the soil microbial diversity and community structure in Xinjiang cotton fields from 2017 to 2019 were analyzed, and the effective integration of cotton field soil microbial resources and multiple heterogeneous agricultural resources data was realized by modeling.

The Xinjiang cotton field soil microbial resources database and the visualization analysis of soil microbial diversity, which provided approximately 1.7 GB of soil microbial information and 5–6 GB of environmental information, were preliminarily established. Using the platform, soil bacterial community structures in the Exceptional Early Maturing Cotton Areas (Bole, Shihezi, and Fukang), Early Maturing Cotton Area (Kuitun), and Early–Middle Maturing Cotton Area (Hami) were found to have changed greatly at the phylum level, with Proteobacteria accounting for 20.9% to 29.8%, Acidobacteria accounting for 16.1% to 30.6%, Verrucomicrobia accounting for 7.0% to 28.9%, and Chloroflexi accounting for 6.6% to 21.2%. The LEfse revealed that there were 255 different species, with Sphingomonasdales, Desulfobacterales, and Geobacter being the main species having different microbial community structures in Northern Xinjiang.

The collection, management, and analysis of soil microbial diversity data in the Xinjiang cotton area plays an important supporting role in the construction and application of a big data platform for cotton production and agriculture from the Xinjiang Production Corp., which will lay a scientific foundation for the protection and utilization of soil microbial diversity resources in China.