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Record W2345956199 · doi:10.1007/s10295-016-1779-x

Recycling of lipid-extracted hydrolysate as nitrogen supplementation for production of thraustochytrid biomass

2016· article· en· W2345956199 on OpenAlexafffund
Joshua Lowrey, Roberto E. Armenta, Marianne Su‐Ling Brooks

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2016
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsMara Renewables (Canada)Dalhousie University
FundersMitacs
KeywordsHydrolysateBiomass (ecology)Pulp and paper industryNutrientNitrogenWastewaterFood scienceEnvironmental scienceChemistryExtraction (chemistry)HydrolysisBiologyEnvironmental engineeringBiochemistryEcologyChromatography

Abstract

fetched live from OpenAlex

Efficient resource usage is important for cost-effective microalgae production, where the incorporation of waste streams and recycled water into the process has great potential. This study builds upon emerging research on nutrient recycling in thraustochytrid production, where waste streams are recovered after lipid extraction and recycled into future cultures. This research investigates the nitrogen flux of recycled hydrolysate derived from enzymatic lipid extraction of thraustochytrid biomass. Results indicated the proteinaceous content of the recycled hydrolysate can offset the need to supply fresh nitrogen in a secondary culture, without detrimental impact upon the produced biomass. The treatment employing the recycled hydrolysate with no nitrogen addition accumulated 14.86 g L(-1) of biomass in 141 h with 43.3 % (w/w) lipid content compared to the control which had 9.26 g L(-1) and 46.9 % (w/w), respectively. This improved nutrient efficiency and wastewater recovery represents considerable potential for enhanced resource efficiency of commercial thraustochytrid production.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.267
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2016
Admission routes2
Has abstractyes

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