MétaCan
Menu
Back to cohort

Evaluation of The Potential of Amaranth Flour for Lactic Acid Fermentation

2016· article· en· W2283245852 on OpenAlexvenueno aff
Zuzana Matejčeková, Denisa Liptáková, Ľubomí­r Valí­k

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2016
Typearticle
Languageen
FieldNursing
TopicMicrobial Metabolites in Food Biotechnology
Canadian institutionsnot available
FundersVedecká Grantová Agentúra MŠVVaŠ SR a SAV
KeywordsAmaranthFood scienceFermentationLactobacillus rhamnosusLactic acidChemistryProbioticWater activityBiologyLactobacillusBacteriaWater content

Abstract

fetched live from OpenAlex

Although cereals and pseudocereals are deficient in some basic components, fermentation process is the most economical and simple way, how to improve nutritional value, functional qualities and sensory properties of the final products. In our study, we focused on the evaluation of amaranth flour for preparation of new probiotic functional foods suitable for celiac patients. That is why the growth dynamics of several Lactobacillus sp. in amaranth mashes were evaluated. All the monitored strains showed sufficient growth in mashes (growth rates of lactobacilli ranged from 0.73 to 1.52 h-1). Based on the rates, only Lb. rhamnosus VT1 was able to grow with the values higher than 1.38 h-1 in both milk and water based mashes.In the second part of our study, we described behaviour of Lb. rhamnosus GG in amaranth water- or milk- based mashes after 8 h of co-cultivation with Fresco DVS 1010 culture (37 ± 1 °C, 5 % CO2). Final counts after the fermentation reached values 108 CFU.ml-1 and no decrease was recorded during 2-week storage period at 6 ± 1 °C. Thus we may conclude that densities of lactobacilli were able to maintain above the limit of >106 CFU.ml-1 essential from the legislation point of view.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.067
GPT teacher head0.390
Teacher spread0.324 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy and Nutrition SciencesSame topicMicrobial Metabolites in Food BiotechnologyFrench-language works237,207