Evidence map›Paper›PMID 42404797›Full record

ArticleFrontiers in microbiology2026

Microbial-enzymatic coupling drives nitrogen stabilization during static pile composting of rice straw amended with contrasting nitrogen sources.

Qingran Guo, Jiawei Li, Yutao Peng, Jing Li, Hongzhao Li, Xiao Chen, Baige Zhang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Qingran GuoKey Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Jiawei Li *Key Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Yutao Peng *School of Agriculture and Biotechnology, Sun Yat-sen University, Shenzhen, China.
Jing LiKey Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Hongzhao LiKey Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Xiao ChenKey Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
Baige ZhangKey Laboratory for New Technology Research of Vegetable, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nitrogen loss during straw composting substantially undermines nutrient recycling efficiency and the agronomic value of finished compost products. Clarifying how different nitrogen sources mediate nitrogen transformation and nitrogen retention in organic fractions is therefore essential for improving compost maturity and nitrogen retention. This study evaluated how three nitrogen-rich amendments with divergent chemical characteristics (chicken manure, fish meal, and soybean powder) influenced nitrogen transformation, organic nitrogen fractionation, enzyme dynamics, and microbial succession during static pile composting of rice straw. Compost maturity varied significantly among treatments (

Indexed as

enzyme activitymicrobial communitynitrogen transformationorganic amendmentsstraw composting

Identifiers

PMID42404797
PMCPMC13328361

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.