Effect of Ozone Application on the Fungal Count and Lipid Quality of Peanut Grains
Bibliographic record
Abstract
Peanut is susceptible to fungal contamination at all stages of its production chain, which can lead to aflatoxin production, which can cause serious health problems for consumers. In this sense, post-harvest ozonation of grains has the potential to reduce contaminant microorganisms, but it may cause oxidative damage, degrading organic constituents. Thus, factors influencing the reduction of fungal contamination by gaseous ozone in peanuts (grains and grains in pods) and changes in lipid and oil quality of grain were investigated. The analyzed variables were total fungi count, electrical conductivity, peroxide index, and 2-thiobarbituric acid test. Ozone concentration (10, 30, and 50 ppm) and ozonation time (30, 45, and 60 minutes) significantly affected fungal count (p < 0.05). The maximum fungal reductions were 75.79% for grains and 82.66% for grains in pods at a concentration of 50 ppm and exposure of 60 minutes. The electrical conductivity of exudates was affected by ozone concentration. There was degradation of lipids at a cellular level, but no differences were observed in the peroxide index of treated grains.
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".