Slow Pyrolysis of Vomitoxin-Contaminated Corn in a Batch Reactor
Why this work is in the frame
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Bibliographic record
Abstract
Maize is one of the most important agricultural products in terms of production, consumption, and economic importance. However, its contamination with mycotoxins, particularly deoxynivalenol (DON), frequently occurs around the world due to high humidity. This mycotoxin appears predominantly in grains associated primarily with pathogens such as Fusarium graminearum (Gibberella zeae) or Fusarium culmorum. This phenomenon, threatening both human and animal health, also affects the economy due to the disposal of large amounts of contaminated corn. The overall objectives of this study were to use thermochemical conversions (i.e. pyrolysis) for managing this seasonal waste by converting it into value-added industrial solid (bio-char), liquid (bio-oil) and gaseous products. The pyrolysis of vomitoxin-corn grains was carried out in a bench-scale batch reactor at temperatures between 450 to 650 °C with 15 to 20 °C/min heating rates and without carrier gas.\nPyrolysis resulted in the deterioration of deoxynivalenol (DON) from 5-7 ppm in raw corn grains to zero ppm in the treated biochar, making thermochemical conversion a promising method for industrial applications.\nThe effect of pyrolysis conditions, including temperature and heating rate, on the conversion of toxic corn grains, was investigated. The results showed the maximum bio-oil yield was achieved at 650 °C (47 wt.%). Bio-char and non-condensable gases were two other products with 28.6 wt.% and 24.5 wt.% yields, respectively.\nFurther, the chemical composition of the bio-oil was identified using Gas Chromatography-Mass Spectrometry (GC-MS) and quantified by High-Performance Liquid Chromatography (HPLC). The results showed that acetic acid and levoglucosan are the two major components in the bio-oil, which were measured to be 26 g/kg, and 13 g/kg of bio-oil, respectively. Both acetic acid and levoglucosan have potential applications in various industries, such as for the synthesis of polymers, solvents, and pharmaceuticals.\nThe bio-chars were analyzed using TGA for proximate analysis, FTIR for identification of significant functional groups, BET for surface area, SEM for measuring the development of the pores, and elemental analysis for CHNS content. Bio-char was upgraded by physical activation using a CO2 at 900 °C. Activation significantly increased the BET surface area of the bio-char from 3 to 419 m2g-1. The significant development of the pore structure was verified through SEM images. The performance of activated bio-char has been tested by utilizing three different model molecules, i.e. methylene blue, methyl orange, and ibuprofen. The results showed that adsorption capacity of the activated bio-char was similar to that of commercial activated carbons (CAC).\nThe gas composition from pyrolysis of corn was analyzed via micro-GC to investigate the potential use of gases as a renewable energy resource for combustion in engines or as for process energy recovery.\nIn this study, we demonstrated a successful process for eliminating DON from contaminated corn via pyrolysis, while producing value-added products.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it