Pyrolytic Conversion of Vomitoxin-Contaminated Corn into Value-Added Products
Bibliographic record
Abstract
Deoxynivalenol (DON) (also called vomitoxin) is a mycotoxin caused by pathogens that periodically contaminate crops such as maize, wheat, barley, oats, and rye, making them unusable. We explored pyrolysis as a process for the decontamination of vomitoxin-corn grains and their transformation into value-added products. Pyrolysis was carried out in a bench-scale batch reactor at maximum temperatures between 450 and 650 °C. This resulted in the total destruction of DON, from 5–7 ppm in raw corn grains to non-detectable levels in the treated bio-char. The effect of pyrolysis conditions, including temperature and heating rate, on the conversion of toxic corn grains was investigated. The maximum bio-oil yield was achieved at 650 °C (47 wt.%). The co-products were bio-char (29 wt.%) and non-condensable gases (24 wt.%). Acetic acid and levoglucosan were the two major valuable components in the bio-oil, corresponding to 26 g/kg and 13 g/kg of bio-oil, respectively. The bio-chars were analyzed and upgraded by physical activation using CO2 at 900 °C. Activation increased the bio-char surface area to 419 m2g−1 and promoted pore development, which was verified by SEM. Proximate analysis illustrated that stable carbon increased to 88.8% after activation compared to 10.9% in the raw corn. FT-IR results showed that the thermally unstable functional groups had been completely eliminated after activation. All characterization results confirmed that the activated corn bio-char has excellent potential for adsorption processes. The HHV of the non-condensable gas stream was 16.46 MJ/Nm3, showing the potential application of this product as an energy source.
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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".