Evidence map›Paper›PMID 30814601›Full record

ArticleScientific reports2019

A novel, nature-based alternative for photobioreactor decontaminations.

Lisa Krug, Armin Erlacher, Gabriele Berg, Tomislav Cernava

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Lisa KrugACIB GmbH, Petersgasse 14, 8010, Graz, Austria.
Armin ErlacherInstitute of Environmental Biotechnology, Graz University of Technology, Petersgasse 12, 8010, Graz, Austria.
Gabriele BergInstitute of Environmental Biotechnology, Graz University of Technology, Petersgasse 12, 8010, Graz, Austria.ORCID 0000-0001-9423-3101
Tomislav CernavaInstitute of Environmental Biotechnology, Graz University of Technology, Petersgasse 12, 8010, Graz, Austria. tomislav.cernava@tugraz.at.ORCID 0000-0001-7772-4080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale microalgae cultivations are increasingly used for the production of animal feed, nutritional supplements and various high-value bioproducts. Due to the process size and other limitations, contaminations of microalgae fermentations with other photoautotrophic microorganism are frequently observed. In the present study, we explored the applicability of 5-isobutyl-2,3-dimethylpyrazine for the removal of contaminating microalgae from industrial photobioreactors. In order to select a representative microbial population for susceptibility experiments, reactor samples were obtained from a multi-stage cultivation process. Assignments of 18S rRNA gene fragment amplicons indicated that Haematococcus, Chlorella, and Scenedesmus were the three most frequently occurring microalgae genera in the selected reactors. Following the isolation of representative algae cultures, susceptibility tests were conducted with the antimicrobial pyrazine. It was demonstrated that all isolated contaminants are highly susceptible to the bioactive compound. The highest tolerance towards the alkylpyrazine was observed with Scenedesmus vacuolatus; solutions with 1.66% (v/v) of the active compound were required for its deactivation. Further tests with the vaporized pyrazine showed consistent reductions in the viability of treated microalgae. This pilot study provides evidence for the applicability of a novel, nature-based alternative for bioreactor decontaminations.

Indexed as

BioreactorsDecontaminationMicroalgaePyrazinesPyrazines

Identifiers

PMID30814601
PMCPMC6393562

What OpenQuestion holds

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Registered trials

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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.