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Record W2343854116 · doi:10.1177/1082013216646491

Evaluation of a potentially probiotic non-dairy beverage developed with honey and kefir grains: Fermentation kinetics and storage study

2016· article· en· W2343854116 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.

Bibliographic record

VenueFood Science and Technology International · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsLakehead University
Fundersnot available
KeywordsKefirFood scienceFermentationProbioticLightnessChemistryBioreactorYeastBacteriaBiologyLactic acidBiochemistry

Abstract

fetched live from OpenAlex

The aim of this work was to study the fermentation process of honey with kefir grains through a comprehensive understanding of its rheological properties, probiotic cell viability, instrumental color parameters and kinetic aspects in a batch bioreactor and during storage. The results showed that kefir grains were well adapted to bioreactor conditions, reaching high levels of cell viability (over 10 6 CFU mL −1 for total yeast and bacteria), phenolic compounds content (190 GAE/100 g) and acidification after 24 h of fermentation at 30 ℃. Colorimetric analysis showed that lightness (L*) and redness (a*) remained constant, while yellowness intensities (b*) decreased during fermentation time. After 35 days of storage, honey kefir beverage maintained its chemical characteristics and microbial viability as required to be classified as a probiotic product. The Ostwald-de-Waele (R 2 ≥ 0.98) and Herschel-Bulkley (R 2 ≥ 0.99) models can be used to predict the behavior of honey kefir beverage. The parameters analyzed in this study should be taken into account for industrial production of this novel non-dairy beverage.

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)0.001
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 score0.779
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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