Inactivation of Fungi Associated with Barley Grain by Gaseous Ozone
Bibliographic record
Abstract
The use of gaseous ozone as a fungicide to preserve stored barley was studied. The effects of the following operating parameters on the fungicidal efficacy of ozone were examined: 1) the applied ozone dose, 2) ozonation time, 3) water activity of barley, and 4) temperature of barley. The effect of ozonation on germination of barley was also investigated. The experimental results showed that ozone was very effective in inactivation of fungi associated with the barley regardless of whether the fungi were in the forms of spores or mycelia. However, the mycelia were less resistant to ozone. With 5 minutes of ozonation, 96% of inactivation were achieved for spores as well as for mixtures of spores and small amount of mycelia by applying 0.16 and 0.10 mg of ozone/(g barley) x min, respectively. In addition, for sealed storage silos, inactivation of fungi continued when the ozone-containing gas was held inside the silos following a continuous ozone supply. The experimental results also revealed that increases in water activity and temperature of barley enhanced the fungicidal efficacy of ozone. Results of this study also indicated that the inactivation processes could be controlled by simply monitoring the exit ozone from the reactor instead of performing the time-consuming microbial examination. This finding would make the application of ozone in the preservation of cereal grains easier, simpler, and more practically applicable. The experimental results demonstrated that although ozonation above certain strength may reduce barley germination, inactivation of fungi was achieved with ozonation strengths far below the critical point.
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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) | 0.000 | 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".