Evidence map›Paper›PMID 42236919›Full record

ArticleNature food2026

Machine learning-optimized composting strategies can enhance nutrient recycling and transform food system waste into a net carbon sink.

Lu Zhang, Junyu Yang, Junjie Liu, Qishun Zhou, Xuan Wang, Haodi Zhang, Yazhan Ren, Zhaohai Bai, Lin Ma

Erratum issuedAbstract read
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In one paragraph

Article in Nature food, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

9 authors.

Lu Zhang *State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China.
Junyu Yang *College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.
Junjie Liu *Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China.ORCID http://orcid.org/0009-0003-2795-0081
Qishun ZhouCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.
Xuan WangKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China. wangxuan@sjziam.ac.cn.ORCID http://orcid.org/0009-0000-3368-4857
Haodi ZhangCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. hdzhang@szu.edu.cn.
Yazhan RenKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China.
Zhaohai BaiState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0001-7685-5441
Lin MaState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China. malin1979@nju.edu.cn.ORCID http://orcid.org/0000-0003-1761-0158

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Composting organic waste offers a circular solution to recycle nutrients and restore soil health, but nitrogen (N) and carbon (C) losses during the process undermine its agricultural and climate benefits. Here, using a machine learning approach, we analyse 848 global manure, food waste and sewage sludge composting experiments, identifying 19 key management parameters that drive ammonia (NH

Indexed as

Carbon SequestrationCompostingMachine LearningRecyclingAmmoniaCarbonCarbon DioxideFood Loss and WasteManureMethaneNitrogenNitrous OxideNutrientsSewageSoilAmmoniaCarbonCarbon DioxideFood Loss and WasteManureMethaneNitrogenNitrous OxideSewageSoil

Identifiers

PMID42236919

What OpenQuestion holds

Textmetadata
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.