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Record W3149289552 · doi:10.3390/catal11040456

Multi-Scale Biosurfactant Production by Bacillus subtilis Using Tuna Fish Waste as Substrate

2021· article· en· W3149289552 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCatalysts · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsMemorial University of Newfoundland
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUnited Nations Development Programme
KeywordsSurfactinBacillus subtilisFood scienceSubstrate (aquarium)ChemistryTunaPulp and paper industryFish <Actinopterygii>BiotechnologyBiologyBacteriaFisheryEcologyEngineering

Abstract

fetched live from OpenAlex

As one of the most effective biosurfactants reported to date, lipopeptides exhibit attractive surface and biological activities and have the great potential to serve as biocatalysts. Low yield, high cost of production, and purification hinder the large-scale applications of lipopeptides. Utilization of waste materials as low-cost substrates for the growth of biosurfactant producers has emerged as a feasible solution for economical biosurfactant production. In this study, fish peptone was generated through enzyme hydrolyzation of smashed tuna (Katsuwonus pelamis). Biosurfactant (mainly surfactin) production by Bacillus subtilis ATCC 21332 was further evaluated and optimized using the generated fish peptone as a comprehensive substrate. The optimized production conduction was continuously assessed in a 7 L batch-scale and 100 L pilot-scale fermenter, exploring the possibility for a large-scale surfactin production. The results showed that Bacillus subtilis ATCC 21332 could effectively use the fish waste peptones for surfactin production. The highest surfactin productivity achieved in the pilot-scale experiments was 274 mg/L. The experimental results shed light on the further production of surfactins at scales using fish wastes as an economical substrate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.234
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it