Insight into N2O emission and denitrifier communities under different aeration intensities in composting of cattle manure from perspective of multi-factor interaction analysis.

Nitrous oxide (N2O) emission from composting is a significant contributor to greenhouse effect and ozone depletion, which poses a threat to environment. To address the challenge of mitigating N2O emission during composting, this study investigated the response of N2O emission and denitrifier communities (detected by metagenome sequencing) to aeration intensities of 6 L/min (C6), 12 L/min (C12), and 18 L/min (C18) in cattle manure composting using multi-factor interaction analysis. Results showed that N2O emission occurred mainly at mesophilic phase. Cumulative N2O emission (QN2O, 9.79 mg·kg-1 DW) and total nitrogen loss (TN loss, 16.40 %) in C12 composting treatment were significantly lower than those in the other two treatments. The lower activity of denitrifying enzymes and the more complex and balanced network of denitrifiers and environmental factors might be responsible for the lower N2O emission. Denitrification was confirmed to be the major pathway for N2O production. Moisture content (MC) and Luteimonas were the key factors affecting N2O emission, and nosZ-carrying denitrifier played a significant role in reducing N2O emission. Although relative abundance of nirS was lower than that of nirK significantly (P < 0.05), nirS was the key gene influencing N2O emission. Community composition of denitrifier varied significantly with different aeration treatments (R2 = 0.931, P = 0.001), and Achromobacter was unique to C12 at mesophilic phase. Physicochemical factors had higher effect on QN2O, whereas denitrifying genes, enzymes and NOX- had lower effect on QN2O in C12. The complex relationship between N2O emission and the related factors could be explained by multi-factor interaction analysis more comprehensively. This study provided a novel understanding of mechanism of N2O emission regulated by aeration intensity in composting.

Improving prediction of N2O emissions during composting using model-agnostic meta-learning.

Nitrous oxide (N2O) represents a significant environmental challenge as a harmful, long-lived greenhouse gas that contributes to the depletion of stratospheric ozone and exacerbates global anthropogenic greenhouse warming. Composting is considered a promising and economically feasible strategy for the treatment of organic waste. However, recent research indicates that composting is a source of N2O, contributing to atmospheric pollution and greenhouse effect. Consequently, there is a need for the development of effective, cost-efficient methodologies to quantify N2O emissions accurately. In this study, we employed the model-agnostic meta-learning (MAML) method to improve the performance of N2O emissions prediction during manure composting. The highest R2 and lowest root mean squared error (RMSE) values achieved were 0.939 and 18.42 mg d-1, respectively. Five machine learning methods including the backpropagation neural network, extreme learning machine, integrated machine learning method based on ELM and random forest, gradient boosting decision tree, and extreme gradient boosting were adopted for comparison to further demonstrate the effectiveness of the MAML prediction model. Feature analysis showed that moisture content of structure material and ammonium concentration during composting process were the two most significant features affecting N2O emissions. This study serves as proof of the application of MAML during N2O emissions prediction, further giving new insights into the effects of manure material properties and composting process data on N2O emissions. This approach helps determining the strategies for mitigating N2O emissions.

Deciphering biochar compost co-application impact on microbial communities mediating carbon and nitrogen transformation across different stages of corn development.

Under current climatic conditions, developing eco-friendly and climate-smart fertilizers has become increasingly important.The co-application of biochar and compost on agricultural soils has received considerable attention recently.Unfortunately, little is known about its effects on specific microbial taxa involved in carbon and nitrogen transformation in the soil.Herein, we report the efficacy of applying biochar-based amendments on soil physicochemical indices, enzymatic activity, functional genes, bacterial community, and their network patterns in corn rhizosphere at seedling (SS), flowering (FS), and maturity (MS) stages.The applied treatments were: compost alone (COM), biochar alone (BIOC), composted biochar (CMB), fortified compost (CMWB), and the control (no fertilizer (CNTRL).The non-metric multidimensional scaling (NMDS) indicated total nitrogen (TN), pH, NO3--N, urease, protease, and microbial biomass C (MBC) as the dominant environmental factors driving soil bacteria in this study.The dominant N mediating genes belonged to nitrate reductase (narG) and nitronate monooxygenase (amo), while beta-galactosidase, catalase, and alpha-amylase were the dominant genes observed relating to C cycling.Interestingly, the abundance of these genes was higher in COM, CMWB, and CMB compared with the CNTRL and BIOC treatments.The bacteria network properties of CWMB and CMB indicated robust niche overlap associated with high cross-feeding between bacterial communities compared to other treatments.Path and stepwise regression analyses revealed norank_Reyranellaceae and Sphingopyxis in CMWB as the major bacterial genera and the major predictive indices mediating soil organic C (SOC), NH4+-N, NO3--N, and TN transformation.Overall, biochar with compost amendments improved soil nutrient conditions, regulated the composition of the bacterial community, and benefited C/N cycling in the soil ecosystem.

Exploration of ß-glucosidase-producing microorganisms community structure and key communities driving cellulose degradation during composting of pure corn straw by multi-interaction analysis.

Poor management of crop residues leads to environmental pollution and composting is a sustainable practice for addressing the challenge. However, knowledge about composting with pure crop straw is still limited, which is a novel and feasible composting strategy. In this study, pure corn straw was in-situ composted for better management. Community structure of ß-glucosidase-producing microorganisms during composting was deciphered using high-throughput sequencing. Results showed that the compost was mature with organic matter content of 37.83% and pH value of 7.36 and pure corn straw could be composted successfully. Cooling phase was major period for cellulose degradation with the highest ß-glucosidase activity (476.25 µmol·p-Nitr/kg·dw·min) and microbial diversity (Shannon index, 3.63; Chao1 index, 500.81). Significant compositional succession was observed in the functional communities during composting with Streptomyces (14.32%), Trichoderma (13.85%) and Agromyces (11.68%) as dominant genera. ß-Glucosidase-producing bacteria and fungi worked synergistically as a network to degrade cellulose with Streptomyces (0.3045**) as the key community revealed by multi-interaction analysis. Organic matter (-0.415***) and temperature (-0.327***) were key environmental parameters regulating cellulose degradation via influencing ß-glucosidase-producing communities, and ß-glucosidase played a key role in mediating this process. The above results indicated that responses of ß-glucosidase-producing microorganisms to cellulose degradation were reflected at both network and individual levels and multi-interaction analysis could better explain the relationship between variables concerning composting cellulose degradation. The work is of significance for understanding cellulose degradation microbial communities and process during composting of pure corn straw.

Disentangling the coupling relationships between functional denitrifiers and nitrogen transformation during cattle-manure and biochar composting: A novel perspective.

This study explored the coupling relationships between denitrifiers and N-transformation using multi-level (DNA, RNA and enzyme) and multi-aspect (abundance, diversity, structure, key community, network pattern, and functional module) analyses during cattle-manure (CM) and biochar (CMB) composting. Amino sugar-N (ASN, 0.914) and hydrolysable unknown-N (-0.724) were main organic-N components mediating NH4+-N in CM and CMB, respectively. Biochar lowered nirK, nirS, and nosZ genes copies, up-regulated nir gene transcripts, and inhibited nitrite reductase (NIR) activity. For nirK-denitrifiers, Luteimonas was predominant taxa influencing NO2--N and amino acid-N (AAN). Unclassified_k_norank_d_Bacteria and unclassified_p_Proteobacteria regulated NO3--N and ASN, respectively. These three genera played crucial roles in mediating NIR activity and nosZ/nirK. For nirS-denitrifiers, Paracoccus and Pseudomonas mediated NH4+-N and AAN, respectively, and they were vital genera regulating NO3--N, ASN and NIR activity. Furthermore, nirK-denitrifiers was major contributor to denitrification. Overall, functional denitrifiers might simultaneously participate in multiple N-transformation processes.