Evidence map›Paper›PMID 41301089›Full record

ArticleBioengineering (Basel, Switzerland)2025

Methane Concentration Prediction in Anaerobic Codigestion Using Multiple Linear Regression with Integrated Microbial and Operational Data.

Iván Ostos, Iván Ruiz, Diego Cruz, Luz Marina Flórez-Pardo

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Iván OstosGrupo de Investigación en Ingeniería Electrónica, Industrial, Ambiental, Metrología GIEIAM, Universidad Santiago de Cali, Cali 760036, Colombia.ORCID 0000-0001-9981-3412
Iván RuizGrupo de Investigación en Ingeniería Electrónica, Industrial, Ambiental, Metrología GIEIAM, Universidad Santiago de Cali, Cali 760036, Colombia.
Diego CruzGrupo de Interacciones Microbianas GIM, Universidad de Salamanca, 37008 Salamanca, Spain.
Luz Marina Flórez-PardoGrupo de Investigación en Modelado, Análisis y Simulación de Procesos Ambientales e Industriales PAI+, Universidad Autónoma de Occidente, Cali 760030, Colombia.

Funding

Dirección General de Investigaciones of Universidad Santiago de Cali No. DGI-01-2025
6 · The paper itself

Abstract

Anaerobic codigestion of organic residues is a proven strategy for enhancing methane recovery. However, the complexity of microbial interactions and variability in operational conditions make it difficult to estimate methane concentration in real time, particularly in rural contexts. This study developed a multiple linear regression model to predict methane concentration using operational data and microbial community profiles derived from 16S rRNA gene sequencing. The system involved the codigestion of cassava by-product and pig manure in a two-phase anaerobic reactor. Predictor variables were selected through a hybrid approach combining statistical correlation with microbial functional relevance. The final model, trained on 70% of the dataset, demonstrated satisfactory generalization capability on the other 30 test set, achieving a coefficient of determination (R

Indexed as

biogascodigestionmetagenomicsMLR

Identifiers

PMID41301089
PMCPMC12649161

What OpenQuestion holds

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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.