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Record W6989291343

Antimicrobial activity of essential oils and their application in active packaging to inhibit the growth of molds on bread

2018· dissertation· en· W6989291343 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsMcGill University
Fundersnot available
KeywordsAntimicrobialActive packagingFood packagingFungal growthBacteriaShelf life
DOInot available

Abstract

fetched live from OpenAlex

Bread spoilage caused by molds is a major concern for the bakery industry.Traditionally, bread is preserved by chemical preservatives, such as propionic and sorbic acids.Owing to consumer demand for "natural" foods with extended shelf life, there is an increasing interest in replacing chemical preservatives in bread with essential oils (EOs) as natural preservatives.In this study, a number of EOs were investigated for their antifungal activity against molds isolated from moldy bread.Cinnamon EO exhibited marked antimicrobial activity and its estimated minimum inhibitory concentration (MIC) was in the range of 31-125 ppm.The efficacy of sachets containing cinnamon oil in inhibiting filamentous fungi isolated from moldy bread was investigated in vitro and in situ, while in situ growth of molds was inhibited in the presence of sachets containing 25-1000 µL of cinnamon EO (CIN-03) in a sealed system for 14 days at room temperature.Sachets containing 50 µL or higher levels of CIN-03 showed fungicidal effect.Active packaging combined with 500 µL to 1000 µL of CIN-03 in sachets increased the shelf life of bread slices packaged in plastic bags by more than 14 days.The shelf life of whole wheat bread loaves was extended to 6 days using the sachets containing 250 µL to 1000 µL of CIN-03.The results of this work demonstrated that packaging of sliced bread with sachets containing cinnamon EO provides an innovative and effective means of extending the shelf life of bread products.Ismail.I have learnt a lot from his course and his guidance in lab.I am also very grateful for financial assistance provided to support part of my expensive tuition and the extra help for my offcampus life.Secondly, I would like to convey my special thanks to Dr. Jacqueline Sedman, for being willing to listen to my questions and provide useful suggestions.And importantly, I really appreciate that her time in reading my writings and her dedication in editing the

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.009
GPT teacher head0.217
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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes1
Has abstractyes

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