Precision feeding as a tool to reduce the environmental footprint of pig production systems: a life-cycle assessment
Notice bibliographique
Résumé
Nitrogen and phosphorus excretion are major sources of environmental contamination in growing-finishing pig operations. Nutrient excretion can be reduced by feeding pigs daily-tailored diets to their estimated nutrient requirements using individual precision feeding (IPF) techniques. This study modeled and evaluated the environmental impact of moving from conventional group 3-phase feeding (CGF) to IPF systems in Quebec, Canada, using life-cycle assessment with SimaPro software. The cradle-to-farm model included inputs and outputs of each subphase: raw materials/feedstuffs production, feed mill processing, transport, animal rearing, and manure management. The model was identical for both treatments in all aspects except for the production of feeds and barn and manure emissions in the growing-finishing phases. All feed ingredients originated from Quebec, simulating agricultural practices using real management data from an average farm in Quebec. Based on observed pig growth data, the CGF and IPF systems were compared in the growing-finishing phase. IPF diets were modeled as the blend of 2 feeds (i.e., A and B), while CGF diets were stablished according to the industry. The evaluated impact categories were global warming potential (GWP), eutrophication potential (EP), and acidification potential (AP). The functional unit was 1 t of feed at the feed mill gate and 1 t of finished pig live weight at the farm gate. A Monte Carlo analysis determined the uncertainty of the growth performance results. Feeding programs were compared using analysis of variance. Corn was associated with elevated GWP and AP impacts, leading to higher impacts for diets with higher corn content. Feed B, which contained 83% corn, resulted in impacts of 645 kg of CO2-eq., 8.53 kg SO2-eq., and 4.89 kg PO4-eq. Diets with higher EP impact had a higher percentage of soybean meal. Feed A contained 25% of this ingredient and had an impact of 608 kg CO2-eq., 6.98 kg SO2-eq., and 5.57 kg PO4-eq. CGF diets had environmental impacts between those of feeds A and B. Compared to CGF, applying IPF programs during the growing-finishing phase decreased GWP by 7.6%, AP by 16.2% and EP by 13.0%. IPF significantly reduced the environmental impact in all categories through the more efficient use of nutritional resources by pigs. IPF could help to improve the sustainability of growing-finishing pig operations in Quebec and likely other regions using corn and soybean-based diets.
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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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 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 ».