Aflatoxin M <sub>1</sub> degradation using high voltage atmospheric cold plasma (HVACP) technology
Bibliographic record
Abstract
Aflatoxins are one of the highly toxic secondary metabolites with high decomposition temperatures, ranging from 237 °C to 306 °C. Therefore, non-thermal treatments are preferred to ensure safe food while preserving food quality. High voltage atmospheric cold plasma (HVACP) is a novel non-thermal technology with the potential to reduce contaminants (e.g. mycotoxins) owing to reactive species such as ozone. Therefore, the aim of this study was to investigate the efficacy of HVACP to degrade Aflatoxin M1 (AFM1) in pure water. A dielectric barrier discharge HVACP was performed at 90 kV using modified air (MA65: 65% O2, 30% CO2, 5% N2) fill gas for 1, 3, and 5 min in a direct and indirect mode with no post-treatment or 4.0 h post-storage at room temperature. The chemical properties of water were evaluated. Ozone concentration in both gas and liquid phases was also measured. A 77% reduction of AFM1 was observed after 1 min of direct treatment with no post-treatment storage. The nitrate and peroxide contents after 1 min of direct treatment were 4.50 ± 0.70 and 9.5 ± 0.70 mg/L, respectively. Longer treatment time and direct mode of exposure resulted in a higher ozone concentration in either the gas or liquid phase. These results demonstrate the potential of HVACP as a non-thermal treatment for reducing AFM1 concentration. HVACP was capable of significantly degrading AFM1 using a very short treatment time and 4.0-h post-treatment storage.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".