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Record W1574025144

CARBON DIOXIDE GENERATION, TRANSPORT AND RELEASE DURING THE FERMENTATION OF BARLEY MALT

2013· article· en· W1574025144 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon dioxideFermentationEnvironmental scienceChemistryEnvironmental chemistryFood science
DOInot available

Abstract

fetched live from OpenAlex

Carbon Dioxide (CO2) is a major fermentation product generated during the production of beer, the subsequent release of this gas within the fermentor results in agitation that is necessary for sustained industrial fermentation. CO2 is sometimes monitored allowing brewers to stoichiometrically relate CO2 released to other products. In this manner the rate of gas release from the fermentor may be used to assess, control and predict other aspects of fermentation. The dynamics of CO2 generation, transport and release are explored throughout this thesis over several studies. The tools used to examine CO2 production were scrutinized including a miniature assay using various modeling techniques. \nA miniature scale fermentation assay included in the methods of the American Society of Brewing Chemists was compared to industrial scale fermentations. It was found that discrepancies were possibly due (at least in part) to fermentor geometry. Following this study, a literature review of CO2 solubility in aqueous sugar, and ethanol solutions was conducted. This study exposed previously undescribed inaccuracies in literature, i.e., it was found that several gas solubility tables were empirical derived and are therefore unlikely to accurately reflect all styles of beer. The next study scrutinized the consumption of sugars during barley fermentation and found that these fermentations often exhibit asymmetric sigmoidal attenuation. A five parameter logistic model was introduced to model this sugar consumption more accurately than previously described techniques. Using methods refined during the aforementioned studies, a fermentation was conducted where a mass balance was used to track all major fermentation parameters (the consumption of individual sugars, and the production of ethanol, carbon dioxide, yeast biomass and glycerol). This allowed an assessment of Balling’s theorem as compared to modern theory. It was shown that while accurate in predicting original extract, Balling’s theorem incorrectly quantified other fermentation parameters. This has large ramifications for both industry and research as the estimation of fermentation parameters (such as ethanol and fermentation time) is now better understood.\nFrom these studies, the production of beer becomes less of a “black box” operation, and CO2 saturation, transport and release can be better explained. Of the many fermentation aspects monitored during these studies, most were predicted by theory, however, there were notable exceptions. For instance, it was found that both the inhibition of maltose consumption and yeast sugar consumption dynamics (which remained relatively constant throughout the fermentation at ~ 50 pg·h-1 for cells with an average mass of ~ 40 pg). were found to deviate from previously described reports. These, and other findings improve our understanding of brewing fermentations allowing for additional applications of theory and recommendations in industrial operations.

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 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 score0.418
Threshold uncertainty score0.538

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 head0.002
GPT teacher head0.120
Teacher spread0.118 · 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