The utilization of binary oxide nanoparticles is geometrically increasing due to their numerous applications. Their intentional or accidental release after usage has led to their omnipresence in the environment. The usage of sludge or fertilizer containing binary oxide nanoparticles is likely to increase the chance of the plants being exposed to these binary oxide nanoparticles. The aim of the present review is to assess the detailed positive and negative impacts of these oxide nanoparticles on the soybean plants and its rhizosphere. In this study, methods of synthesizing binary oxide nanoparticles, as well as the merits and demerits of these methods, are discussed. Furthermore, various methods of characterizing the binary oxide nanoparticles in the tissues of soybean are highlighted. These characterization techniques help to track the nanoparticles inside the soybean plant. In addition, the assessment of rhizosphere microbial communities of soybean that have been exposed to these binary oxide nanoparticles is discussed. The impacts of binary oxide nanoparticles on the leaf, stem, root, seeds, and rhizosphere of soybean plant are comprehensively discussed. The impacts of binary oxides on the bioactive compounds such as phytohormones are also highlighted. Overall, it was observed that the impacts of the oxide nanoparticles on the soybean, rhizosphere, and bioactive compounds were dose-dependent. Lastly, the way forward on research involving the interactions of binary oxide nanoparticles and soybean plants is suggested.

The plant microbiome is involved in enhancing nutrient acquisition, plant growth, stress tolerance, and reducing chemical inputs. The identification of microbial functional diversity offers the chance to evaluate and engineer them for various agricultural processes. Using a shotgun metagenomics technique, this study examined the functional diversity and metabolic potentials of microbial communities in the rhizosphere of soybean genotype link 678. The dominant genera are Geobacter, Nitrobacter, Burkholderia, Candidatus, Bradyrhizobium and Streptomyces. Twenty-one functional categories were present, with fourteen of the functions being dominant in all samples. The dominant functions include carbohydrates, fatty acids, lipids and isoprenoids, amino acids and derivatives, sulfur metabolism, and nitrogen metabolism. A Kruskal–Wallis test was used to test samples’ diversity differences. There was a significant difference in the alpha diversity. ANOSIM was used to analyze the similarities of the samples and there were significant differences between the samples. Phosphorus had the highest contribution of 64.3% and was more prominent among the soil properties that influence the functional diversity of the samples. Given the functional groups reported in this study, soil characteristics impact the functional role of the rhizospheric microbiome of soybean.

Soybean develop a symbiotic relationship with the rhizospheric microbial communities. These organisms are important in maintaining soybean growth and health. Soil samples for this study were collected from Free State, South Africa. We present the microbiome of the soybean rhizosphere and its functional categories at level 1 of the SEED subsystem.

The plant microbiome is involved in enhancing nutrient acquisition, plant growth, stress tolerance and reduces chemical inputs. The identification of microbial functional diversity offers the chance to comprehend and engineer them for various agricultural processes. Using a shotgun metagenomics technique, this study examined the functional diversity and metabolic potentials of microbial communities in the rhizosphere soybean. 18 genera were selected out of which six are prominent in sample AB, the prominent genera are Geobacter, Nitrobacter, Burkholderia, Candidatus, Bradyrhizobium and Streptomyces. Twenty-one functional categories were present with 14 of the functions being dominant. The dominant functions include carbohydrates, fatty acids, lipids and isoprenoids, amino acids and derivatives, sulfur metabolism, and nitrogen metabolism. Kruskal- Wallis test was used to test samples’ diversity differences. There was a significant difference in the diversity with p-value of 0.04. ANOSIM was used to analyse the similarities of the samples, p-values and R-values of the samples were 0.01 and 0.5835 respectively. Phosphorus with p-value of0.718 and 64.3% contribution was more prominent among the soil properties that have influence on functional diversity of the samples. Given the functional groups reported in this study, it is clear that soil characteristics had an impact on on the functions role of the rhizospheric microbiome of soybean