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Effect of Selected Oligosaccharides on the Viability and Fermentation Kinetics of Lactobacillus acidophilus and Lactobacillus casei in Cultured Milk

2014· article· en· W2024429265 on OpenAlexvenueno aff
Seah Young Ng, Loo Wee Chia, Birdie Scott Padam, Fook Yee Chye

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2014
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsnot available
FundersUniversiti Malaysia Sabah
KeywordsLactobacillus caseiLactobacillus acidophilusFermentationFood scienceChemistryLactic acidProbioticLactobacillaceaeLactobacillusBacteriaBiology

Abstract

fetched live from OpenAlex

The study aimed to investigate the effect of fructo-oligosaccharides (FOS) on the growth and fermentation kinetics of Lactobacillus casei LC-01 (LC) and Lactobacillus acidophilus LA5 (LA) in cultured milk. Two commercially available FOS with different degree of polymerization (DP), namely Fibrulose F97 (DP, 2-20) and Fibruline Instant (DP, 3-60) were used at 4% (w/v) and 8% (w/v) respectively during fermentation and storage of cultured milk. Physicochemical properties and acidification kinetic of milk were measured throughout the fermentation. The concentration and DP values of the FOS do not seem to affect the growth of both probiotics during fermentation. Nevertheless, the pH and total soluble solid of milk fermented by both probiotics supplemented with FOS decreased tremendously during fermentation. It is noted that the percentage of lactic acid produced in L. acidophilus is higher than L. casei owing to the metabolic characteristic of the strain. The kinetic of maximum acidification rate Vmax of cultured milk was significantly higher with the addition of FOSs at 4%. However, FOS with lower DP seemed to enhance (p

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.314
Teacher spread0.294 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

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