Mitigating Greenhouse Gas and Ammonia Emissions in Litter-Based Pig Farming with Microbial Consortia
Notice bibliographique
Résumé
<b><sc>Abstract.</sc></b> Pig production contributes to greenhouse gas (GHG) and ammonia (NH₃) volatilization, posing significant environmental, social, and health challenges. Litter-based pig farming systems are increasingly considered as an alternative to conventional slatted systems due to their potential to improve animal welfare. However, these systems still face challenges related to air quality, nutrient management, and gaseous emissions. Microbial consortia, which leverage the synergistic interactions of diverse microorganisms, offer a promising solution to enhance nutrient cycling and mitigate pollutant emissions in such systems. This study investigates the potential of microbial consortia to mitigate GHG and NH₃ emissions in litter-based pig farming systems. Two microbial consortia, Effective Microorganisms (EM) and Indigenous Microorganisms (IMO), were selected for their potential in GHG and NH₃ reductions. A five-week pilot experiment was conducted in a controlled laboratory setting at the Research and Development Institute for the Agri-environment (IRDA) in Deschambault, QC, Canada. Twelve hermetically sealed chambers were used, each housing three growing pigs and equipped to monitor environmental parameters and gas emissions continuously. The experimental design included three treatments: a control without microbial inoculation, T-EM (500 mL/day EM culture applied to the litter), and T-IMO (500 mL/day IMO culture applied to the litter). The microbial consortia were diluted at 5% for IMO and 1% for EM before application on the bedding. Each treatment was replicated four times, and litter management mimicked commercial practices, including weekly additions based on NH₃ levels and environmental observations. Gas concentrations (NH₃, CO₂, CH₄, and N₂O) were measured at 15-min intervals using advanced spectroscopic instruments. Emission differences between treatments were calculated using ventilation flow data. In addition, odor intensity test and litter physicochemical characterization were conducted. According to the results, gas emissions were consistently lower in the T-IMO treatment compared to the Control and T-EM treatments, with mean reductions of 16% for CO₂, 21% for CH₄, and 29% for NH₃. In odor intensity tests, T-IMO was associated with the lowest n-butanol concentration (875 ppm), compared to 1219 ppm for T-EM and 1110 ppm for Control. Additionally, T-IMO exhibited higher total Kjeldahl nitrogen (NTK) values than the other treatments, indicating improved nitrogen retention within the bedding system. Future research will focus on scaling up these results and evaluating the long-term feasibility of microbial applications and their potential to mitigate GHG and NH<sub>3</sub> emissions in liquid manure management systems.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».