Slow Pyrolysis of Vomitoxin-Contaminated Corn in a Batch Reactor
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».