Preliminary construction of a microecological evaluation model for uranium-contaminated soil.

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.

Combined forage grass-microbial for remediation of strontium-contaminated soil.

Enrichment plants were screened from six forage grasses in this study to establish a complete combined forage grass-microbial remediation system of strontium-contaminated soil, and microbial groups were added to the screened dominant forage grasses. The occurrence states of strontium in forage grasses were explored by the BCR sequential extraction method. The results showed that the annual removal rate of Sudan grass (Sorghum sudanense (Piper) Stapf.) reached 23.05% in soil with a strontium concentration of 500 mg·kg-1. Three dominant microbial groups: E, G and H, have shown good facilitation effects in co-remediation with Sudan grass and Gaodan grass (Sorghum bicolor × sudanense), respectively. When compared to the control, the strontium accumulation of forage grasses in kg of soil with microbial groups was increased by 0.5-4 fold. The optimal forage grass-microbial combination can theoretically repair contaminated soil in three years. The microbial group E was found to promote the transfer of the exchangeable state and the reducible state of strontium to the overground part of the forage grass. Metagenomic sequencing results showed that the addition of microbial groups increased Bacillus spp. in rhizosphere soil, enhanced the disease resistance and tolerance of forage grasses, and improved the remediation ability of forage grass-microbial combinations.