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Organic and Inorganic Amendments Shape Bacterial Indicator Communities That Can, In Turn, Promote Rice Yield
The dynamic patterns of the belowground microbial communities and their corresponding metabolic functions, when exposed to various environmental disturbances, are important for the understanding and development of sustainable agricultural systems. In this study, a two-year field experiment with soil...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880095/ https://www.ncbi.nlm.nih.gov/pubmed/35208936 http://dx.doi.org/10.3390/microorganisms10020482 |
Sumario: | The dynamic patterns of the belowground microbial communities and their corresponding metabolic functions, when exposed to various environmental disturbances, are important for the understanding and development of sustainable agricultural systems. In this study, a two-year field experiment with soils subjected to: chemical fertilization (F), mushroom residues (MR), combined application of chemical fertilizers and mushroom residues (MRF), and no-fertilization (CK) was conducted to evaluate the effect of fertilization on the soil bacterial taxonomic and functional compositions as well as on the rice yield. The highest rice yield was obtained under MRF. Soil microbial properties (microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), urease, invertase, acid phosphatase, and soil dehydrogenase activities) reflected the rice yield better than soil chemical characteristics (soil organic matter (SOM), total N (TN), total K (TK), available P (AP), available K (AK), and pH). Although the dominant bacterial phyla were not significantly different among fertilizations, 10 bacterial indicator taxa that mainly belonged to Actinobacteria (Nocardioides, Marmoricola, Tetrasphaera, and unclassified Intrasporangiaceae) with functions of xenobiotic biodegradation and metabolism and amino acid and nucleotide metabolism were found to strongly respond to MRF. Random Forest (RF) modeling further revealed that these 10 bacterial indicator taxa act as drivers for soil dehydrogenase, acid phosphatase, pH, TK, and C/N cycling, which directly and/or indirectly determine the rice yield. Our study demonstrated the explicit links between bacterial indicator communities, community function, soil nutrient cycling, and crop yield under organic and inorganic amendments, and highlighted the advantages of the combined chemical and organic fertilization in agroecosystems. |
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