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Integrating the Soil Microbiota and Metabolome Reveals the Mechanism through Which Controlled Release Fertilizer Affects Sugarcane Growth
Summary
Researchers used soil microbial community profiling and metabolomics to investigate how controlled-release fertilizer application rates affect sugarcane growth. The study found that different fertilizer rates significantly influenced root-associated microbial communities and soil metabolite patterns, providing insights into optimizing fertilizer use for improved crop production.
Root-soil underground interactions mediated by soil microorganisms and metabolites are crucial for fertilizer utilization efficiency and crop growth regulation. This study employed a combined approach of soil microbial community profiling and non-targeted metabolomics to investigate the patterns of root-associated microbial aggregation and the mechanisms associated with metabolites under varying controlled-release fertilizer (CRF) application rates. The experimental treatments included five field application rates of CRF (D1: 675 kg/ha; D15: 1012.5 kg/ha; D2: 1350 kg/ha; D25: 1687.5 kg/ha; and D3: 2025 kg/ha) along with traditional fertilizer as a control (CK: 1687.5 kg/ha). The results indicated that the growth of sugarcane in the field was significantly influenced by the CRF application rate (p < 0.05). Compared with CK, the optimal field application of CRF was observed at D25, resulting in a 16.3% to 53.6% increase in sugarcane yield. Under the condition of reducing fertilizer application by 20%, D2 showed a 13.3% increase in stem yield and a 6.7% increase in sugar production. The bacterial ACE index exhibited significant differences between D25 and D1, while the Chao1 index showed significance among the D25, D1, and CK treatments. The dominant bacterial phyla in sugarcane rhizosphere aggregation included Proteobacteria, Actinobacteriota, and Acidobacteriota. Fungal phyla comprised Rozellomycota, Basidiomycota, and Ascomycota. The annotated metabolic pathways encompassed biosynthesis of secondary metabolites, carbohydrate metabolism, and lipid metabolism. Differential analysis and random forest selection identified distinctive biomarkers including Leotiomycetes, Cercospora, Anaeromyxobacter, isoleucyl-proline, and methylmalonic acid. Redundancy analysis unveiled soil pH, soil organic carbon, and available nitrogen as the primary drivers of microbial communities, while the metabolic profiles were notably influenced by the available potassium and phosphorus. The correlation heatmaps illustrated potential microbial-metabolite regulatory mechanisms under CRF application conditions. These findings underscore the significant potential of CRF in sugarcane field production, laying a theoretical foundation for sustainable development in the sugarcane industry.
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