ArticleJournal of industrial microbiology & biotechnology2026
Dynamics of contaminant microbes in bioethanol production from sugarcane.
Article in Journal of industrial microbiology & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The dynamics and impact of microbial contaminants in industrial sugarcane bioethanol production in Brazil were investigated through a 2-year metagenomic study across two biorefineries. Shotgun metagenomic sequencing revealed that temporal shifts in the contaminant microbiome dynamics within production seasons were more pronounced than inter-annual or inter-mill variations. While Saccharomyces spp. dominated, bacterial communities, primarily within the Firmicutes phylum and dominated by the genera Lactobacillus, Limosilactobacillus, and Bacillus, exhibited dynamic changes. Correlation analyses with industrial process parameters revealed a complex interplay: lower Lactobacillus levels in one mill were associated with increased ethanol yield, whereas higher levels in another mill correlated with reduced yeast viability and increased flocculation. The presence of Limosilactobacillus was linked to decreased yeast viability, whereas Bacillus showed potential for inhibiting both Lactobacillus and Limosilactobacillus. These findings highlight the nuanced and species-specific impacts of bacterial contaminants on bioethanol production, underscoring the need for strain-level functional studies and targeted interventions to optimize fermentation efficiency and stability in industrial settings. One-Sentence Summary The dynamics of contaminant bacterial populations during fuel ethanol production from sugarcane was unrevealed in two biorefineries and in two consecutive production years using shotgun metagenomics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.