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Record W3203663875 · doi:10.21065/advfoodnutrsci.4.13

EFFECT OF INDIGENOUS VARIETY OF ALOE VERA ON BACTERIOCIN PRODUCTION BY PROBIOTICS CULTURE

2020· article· en· W3203663875 on OpenAlexvenueno aff
Abdul Momin

Bibliographic record

VenueAdvanced Food and Nutritional Sciences · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and biological activity of medicinal plants
Canadian institutionsnot available
Fundersnot available
KeywordsAloe veraProbioticFood scienceBiologyTraditional medicineLactobacillus acidophilusLactobacillusMicrobiologyBacteriaFermentationMedicine

Abstract

fetched live from OpenAlex

Background: Aloe vera has long been used as a medicinal plant in the preparation of various gels, lotions and ointments besides its use in various food products.Methodology: The present study was carried out at the Plants Genetics Research Institute, National Agricultural Research Centre, Islamabad. For the purpose of this study, an indigenous variety of Aloe vera was taken along with probiotics culture of Lactobacillus acidophilus, Lactococcus lactis and Lactobacillus helveticus. Aloe vera gel matrix was separated from outer cortex of leaves and media were prepared for the growth of respective probiotics cultures. Aloe vera was used in each probiotic culture against two pathogenic strains, i.e E. coli and S. aureus. In one plate, tryptone was replaced by 1% Aloe vera extract, while 0.5% and 1% Aloe vera extracts were added to other two plates. All the three probiotic cultures were separately inoculated in test tubes, which were incubated at 370C for 24 hours.Results: After incubation of 24 hours, plates were observed on the next day for the measurement of inhibition zones. Strong to medium zones of inhibition were formed against E. coli and S. aureus for all three probiotic cultures when 1% Aloe vera extract was used.Conclusions: This study revealed that the indigenous variety of Aloe vera exhibited significant anti microbial properties.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.130

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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