Compound Microbial Agent Improves Soil Redox Status to Reduce Methane Emissions from Paddy Fields

doi:10.1016/j.rsci.2024.05.002

摘要/Abstract

. [J]. Rice Science, 2024, 31(6): 740-750.

Fig. 1. Dynamics of dissolved oxygen in paddy flooded layer (Experiment 1). M2 and M4 denote the treatments without or with the application of the microbial compound agent under deep water irrigation, respectively. ** indicates significant differences between treatments at P < 0.01.

Fig. 2. Dynamics of redox potential in paddy soil. M1 and M3 denote the treatments without or with the application of the microbial compound agent under alternate wetting and drying, respectively, in Experiment 1. M2 and M4 denote the treatments without or with the application of the microbial compound agent under deep water irrigation, respectively, in Experiment 1. O1 and O2 denote the control and the application of the microbial compound agent, respectively, in Experiment 2.* and ** indicate significant differences between treatments at P < 0.05 and P < 0.01, respectively, and ‘ns’ indicates no significance.

Fig. 3. Methane (CH4) flux of paddy soil under alternate wetting and drying (A) and deep water irrigation (B) conditions, as well as CH4 accumulation emissions (C) after microbial compound agent application (Experiment 1). M1 and M3 denote the treatments without or with the application of the microbial compound agent under alternate wetting and drying, respectively. M2 and M4 denote the treatments without or with the application of the microbial compound agent under deep water irrigation, respectively.** indicates significant differences between treatments at P < 0.01.

Fig. 4. Methane (CH4) flux of paddy soil (A and C) and CH4 accumulation emissions (B and D) after microbial compound agent application in Experiment 2 (A and B) and Experiment 3 (C and D). O1 and O2 denote the control and the application of the microbial compound agent, respectively, in Experiment 2. T1, T2, and T3 denote the control, the application of the microbial compound agent at a rate of 45 and 75 kg/hm2, respectively. TS, BS, and GF represent the tillering, booting, and grain- filling stages, respectively.** indicates significant differences between treatments at P < 0.01. ns, Not significant.

Fig. 5. Abundance of mcrA gene (A), pmoA gene (B), and mcrA/pmoA ratio (C) under conventional fertilizer application and paired with microbial agents. O1 and O2 denote the control and the application of the microbial compound agent, respectively, in Experiment 2. ** indicates significant differences between treatments at P < 0.01. ns, Not significant.

Fig. 6. Correlations of methane (CH4) flux with dissolved oxygen (A), redox potential under alternate wetting and drying (B), and redox potential under deep water irrigation (C).

Fig. 7. Correlation analysis (A) and structural equation model (SEM, B) for methane (CH4) flux from paddy soils. The blue and red arrows in the SEM indicate positive and negative relationships, respectively. Continuous and dashed arrows indicate significant and non-significant relationships, respectively. Numbers at the arrows are standardized path coefficients. Correlation coefficients marked with ‘**’ and ‘*’ are significant at P < 0.01 and P < 0.05 levels, respectively. The width of the arrows is proportional to the effect size of the relationship. R2 values denote the proportion of variance explained for each variable. Eh, Redox potential; mcrA, Methanogens; pmoA, Methanotrophs.

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