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Record W2897195436 · doi:10.1111/1541-4337.12398

Cold Plasma for Effective Fungal and Mycotoxin Control in Foods: Mechanisms, Inactivation Effects, and Applications

2018· article· en· W2897195436 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComprehensive Reviews in Food Science and Food Safety · 2018
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversity of Alberta
FundersAlberta Canola Producers CommissionAlberta Agriculture and Forestry
KeywordsMycotoxinShelf lifeFood scienceFood safetyFood productsChemistry

Abstract

fetched live from OpenAlex

Cold plasma treatment is a promising intervention in food processing to boost product safety and extend the shelf-life. The activated chemical species of cold plasma can act rapidly against micro-organisms at ambient temperatures without leaving any known chemical residues. This review presents an overview of the action of cold plasma against molds and mycotoxins, the underlying mechanisms, and applications for ensuring food safety and quality. The cold plasma species act on multiple sites of a fungal cell resulting in loss of function and structure, and ultimately cell death. Likewise, the species cause chemical breakdown of mycotoxins through various pathways resulting in degradation products that are known to be less toxic. We argue that the preliminary reports from cold plasma research point at good potential of plasma for shelf-life extension and quality retention of foods. Some of the notable food sectors which could benefit from antimycotic and antimycotoxin efficacy of cold plasma include, the fresh produce, food grains, nuts, spices, herbs, dried meat and fish industries.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.298
Teacher spread0.275 · 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