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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 L of cinnamon EO (CIN-03) in a sealed system for 14 days at room temperature.Sachets containing 50 L or higher levels of CIN-03 showed fungicidal effect.Active packaging combined with 500 L to 1000 L 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 L to 1000 L 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

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)0.000
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 score0.183
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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