Advanced oxidative decontamination of flax and its impacts on storage
Bibliographic record
Abstract
Abstract The metabolic actions of storage fungi and other microorganisms can cause spoilage and post-harvest losses in agricultural commodities, including flaxseed. These microbial contaminants are oxidized with hydroxyl radicals that are efficiently generated when ozone, hydrogen peroxide (H2O2), and ultraviolet (UV) light react in an advanced oxidative process (AOP). The present work explores what we believe is the first application of an AOP technology to reduce mould on whole brown and yellow flaxseed. The impact of AOP on storage and quality parameters was assessed by measuring the fatty acid value (FAV), germination rate, moisture content (MC), and visible mould growth after 12 weeks of storage. At 30°C and 75% relative humidity (RH), the yellow decontaminated flaxseed showed a 31% decrease in the number of seeds with visible mould without any adverse effect on germination rate, FAV and MC. In contrast, the same AOP treatment created an insignificant decrease in mould in stored brown flaxseed, at the cost of decreasing the germination rate and increasing FAV. Adverse effects of AOP on brown flaxseed were not readily apparent but became measurable after storage. Moreover, Fourier transform infrared (FTIR) spectroscopy was utilized to explore the rationale behind the different reactions of flaxseed varieties to AOP. The corresponding results indicated that the tolerance of yellow flaxseed to AOP might be related to its richness in olefins. The authors believe that technologies that harness advanced oxidative processes open new horizons in decontamination beyond ozone alone and towards increasing the shelf life of various agri-food products.
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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) | 0.001 | 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".