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Record W3026419196 · doi:10.1021/acsomega.0c01352

Production of α-Glycerylphosphorylcholine and Other Compounds from Wheat Fermentation

2020· article· en· W3026419196 on OpenAlexafffundabout
Adebimpe Oyeneye, Jianheng Shen, Youn Young Shim, Timothy J. Tse, Martin J. T. Reaney

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsGenome PrairieUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsFermentationLactic acidChemistryAcetic acidEthanolSuccinic acidFood scienceGlycerolEthanol fermentationLactic acid fermentationIndustrial fermentationAlcoholEthanol fuelBiochemistryBacteriaBiology

Abstract

fetched live from OpenAlex

The liquified mash of milled grains from the Canadian wheat cultivar, AC Andrew, was fermented to determine whether α-glycerylphosphorylcholine (α-GPC) accumulated and whether the accumulation was dependent on fermentation-related factors. Fermentation was conducted at a temperature of 37 °C for 7 days (168 h) with samples collected every 24 h. The samples were analyzed using a proton nuclear magnetic resonance water suppression pulse sequence to allow the quantitation of ethanol, acetic acid, lactic acid, succinic acid, glycerol, phenethyl alcohol, betaine, and α-GPC. A Gompertz model was used to interpret fermentation kinetics for each analyte, and during fermentation, ethanol accumulated to a concentration of 72.1 g/L while α-GPC accumulated to a concentration of 1.68 g/L over 72 h. There were significant and positive correlations between the accumulation of α-GPC, ethanol, lactic acid, and glycerol and acetic acid production. Furthermore, there were no significant negative correlations between the productions of these compounds; hence, all the compounds accumulated during fermentation were produced simultaneously with no observed decrease measured in any compound. This indicates that α-GPC can be successfully produced industrially without any negative impact on ethanol or other useful compounds.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.118

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)0.0000.000

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 head0.037
GPT teacher head0.239
Teacher spread0.203 · 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 teacher head, 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
Published2020
Admission routes3
Has abstractyes

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