The relationship between soil microbial diversity and angelica planting based on network big data

Angelica sinensis is a kind of traditional Chinese medicine with very good blood nourishing effect, and it is cultivated in many regions of China. But with the increasingly severe climate, angelica cultivation has become a big problem. Therefore, this paper starts from the soil microorganisms of angelica planting, and studies the influence of soil biodiversity and angelica planting in the context of big data. This paper proposes a Hadoop system for big data analysis, combining the biocommunity characteristics and metagenomes of soil microorganisms. It then calculates the distance between samples and generates a dissimilarity matrix. Finally, this paper proposes a soil optimization method for angelica planting based on big data analysis of soil microorganisms. In order to optimize the Angelica planting soil designed in this paper, a soil microbial genome comparison experiment and a big data concurrent control test experiment were designed in this paper. It then analyzes the data obtained from the experiment, and the results of the analysis are used to optimize the soil for angelica planting. It finally compares the soil method of Angelica planting designed in this paper with the traditional Angelica planting method. The experimental results show that the survival rate of Angelica sinensis planted by the soil optimization method based on big data analysis of soil microorganisms has increased by 16.09% compared with the traditional Angelica sinensis planting site. The growth rate of Angelica sinensis planted by the soil optimization method based on big data analysis of soil microorganisms increased by 9.64% compared with the traditional Angelica sinensis planting area.