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Metabolic pathways for N and inositol P metabolism and other types of metabolism related to organic matter turnover. Metabolic map and relative abundances of each type of metabolism. Blue bars represent the total relative abundances in four treatments and the heatmap indicates the relative abundance in each treatment. In the metabolic map, green blocks indicate carbohydrate metabolism, yellow blocks indicate amino acid metabolism, red blocks indicate energy metabolism, and white blocks indicate other types of metabolism such as lipid metabolism, nucleotide metabolism, metabolism of cofactors and vitamins, and biosynthesis of other secondary metabolites

Metabolic pathways for N and inositol P metabolism and other types of metabolism related to organic matter turnover. Metabolic map and relative abundances of each type of metabolism. Blue bars represent the total relative abundances in four treatments and the heatmap indicates the relative abundance in each treatment. In the metabolic map, green blocks indicate carbohydrate metabolism, yellow blocks indicate amino acid metabolism, red blocks indicate energy metabolism, and white blocks indicate other types of metabolism such as lipid metabolism, nucleotide metabolism, metabolism of cofactors and vitamins, and biosynthesis of other secondary metabolites

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We investigated the types of metabolism and genes involved with N and P reactions, and SOM turnover as well as their interaction was monitored in an apple orchard by metagenome sequencing. The field experiment included plots with and without a cover crop but with weed control, and two subplots with or without chemical fertilizer. The relative abund...

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... The main processes involved in the nitrogen cycle by microorganisms include nitrogen fixation, nitrate assimilation reduction, nitrate allotropic reduction, nitrification and denitrification processes, and biosynthesis and degradation of organic nitrogen 48,49 . The nitrogen cycling processes of returned straw of interest in this study mainly include the nitrogen fixation process, nitrification, assimilative nitrate reduction, allotropic nitrate reduction, and nitrate assimilation, and its functional genes also include regulatory-related functional genes associated with genes encoding related functional proteins. ...
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Straw is an important source of organic fertilizer for soil enrichment, however, the effects of different nitrogen(N) application rates and depths on straw decomposition microorganisms and carbon and nitrogen cycling under full straw return conditions in cool regions of Northeast China are not clear at this stage. In this paper, we applied macro-genome sequencing technology to investigate the effects of different N application rates (110 kg hm⁻², 120 kg hm⁻², 130 kg hm⁻², 140 kg hm⁻², 150 kg hm⁻²) and depths (0–15 cm, 15–30 cm) on straw decomposing microorganisms and N cycling in paddy fields in the cool zone of Northeast China. The results showed that (1) about 150 functional genes are involved in the carbon cycle process of degradation during the degradation of returned straw, of which the largest number of functional genes are involved in the methane production pathway, about 42, the highest abundance of functional genes involved in the citric acid cycle pathway. There are 22 kinds of functional genes involved in the nitrogen cycle degradation process, among which there are more kinds involved in nitrogen fixation, with 4 kinds. (2) High nitrogen application (150 kg hm⁻²) inhibited the carbon and nitrogen conversion processes, and the abundance of straw-degrading microorganisms and nitrogen-cycling functional genes was relatively high at a nitrogen application rate of 130 kg hm⁻². (3) Depth-dependent heterogeneity of the microbial community was reduced throughout the vertical space. At 71 days of straw return, the nitrogen cycling function decreased and some carbon functional genes showed an increasing trend with the increase of straw return depth. The nitrogen cycle function decreased with the increase of straw returning depth. The microbial community structure was best and the abundance of functional genes involved in the nitrogen cycling process was higher under the conditions of 0–15 cm of returning depth and 130 kg hm⁻² of nitrogen application.
... Additionally, functional characteristics in bacterial and fungal communities were predicted using the PIC-RUSt2 tool. In accordance with the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Zheng et al. 2019), the predicted functions were classified. Random forest analysis is appropriate for data from microbial communities with discrete and discontinuous distributions (Hooper et al. 2000;Ren et al. 2020). ...
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... Therefore, improving potato crop productivity and quality can address the nutritional needs of a rising population (Dahal et al., 2018;Muleta and Aga, 2019). Various methods, such as the use of plant residues, chemical fertilizers, soil conditioners and beneficial microbial products, have been utilized to improve potato yield (Paul et al., 2016;Zheng et al., 2019). Using biocontrol agents is of great interest as this approach is eco-friendly and conforms with sustainable agricultural practices (Khan et al., 2019). ...
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Understanding the stoichiometry of extracellular enzymes in soil, particularly in relation to nutrient acquisition (e.g., carbon, nitrogen, phosphorus), provides valuable insights into microorganisms’ resource requirements. This study investigates the metabolic constraints of soil microorganisms in response to different growth stages of apple trees under various soil management practices. A 14-year long-term experiment with a split-plot design was conducted, where the main plots received different cover crop treatments (bare vs. cover crop), and subplots were subjected to four fertilizer treatments (CK, M, NPK, MNPK). The significant main and interactive effects of cover crops, fertilizer treatment, and growth period on soil nutrients were observed (p < 0.001). Both cover crop and fertilizer treatments significantly increased the soil organic matter content, with implications for orchard resilience to drought. However, the cover factor alone did not notably influence soil carbon–nitrogen ratios or microbial communities. Microbial carbon limitations were driven by soil water dynamics and microbial biomass, while microbial phosphorus limitations were closely linked to total nitrogen levels. The results underscore the combination of cover crops and MNPK fertilizer-enhanced soil nutrient levels and enzyme activities, mitigating microbial carbon and phosphorus limitations. These findings suggest practical strategies for optimizing fertilization practices to improve soil fertility and address nutrient constraints in orchard ecosystems.