Three Essays on Beef Genomics: Economic and Environmental Impacts
Notice bibliographique
Résumé
The successful diffusion of new agricultural biotechnologies depends on widespread producer acceptance and uptake. The assessment of the key factors that can influence producer decision making is fundamental to the understanding of the rate of uptake, the attainable rate of potential benefits and the effectiveness of different measures that can stimulate the diffusion of these innovations. This dissertation examines three related aspects of cow-calf producer decision making with regards to the uptake of genomic selection for feed efficiency in beef cattle production in Canada. Improvements in feed efficiency can have significant economic and environmental impacts on beef cattle production through the reductions in feed costs and greenhouse gas emissions. Specifically, the following objectives are addressed: (i) the evaluation of the factors affecting cow-calf producer willingness to pay (WTP) for genomically improved feed efficient bulls (ii) the assessment of how supply chain linkages can influence cow-calf producer decision making (iii) the assessment of environmental outcomes from different decisions made by cow-calf producers and the extent to which the opportunity to obtain additional revenue from these environmental externalities can influence these decisions. In the first paper, cow-calf producers’ private valuation of genomic information on feed efficiency in their bull purchase decision is assessed. The analysis is situated in a multi-trait context that accounted for both conventional and genomic breeding information and cow-calf producer heterogeneity due to attitudes and farm practices. The results indicated that willingness to pay (WTP) for genomic information is positive; cow-calf producer valuation of conventional breeding technologies is relatively higher. The results further showed evidence of heterogeneity in cow-calf producer preferences according to characteristics such as risk perceptions, calf retention practices and familiarity with genomics. The results of the second paper highlight the potential supply chain issues that can impact the widespread diffusion of the innovation. From the stylized industry framework outlined, the allocation of benefits from the genomic selection for feed efficiency is skewed towards feedlot operators who typically do not incur the cost of bull purchases in fragmented systems. The results suggest that in the absence of a mechanism that rewards cow-calf producers for the additional cost associated with the genomic bull, the diffusion of the innovation is likely to be slow. The results of the third paper show that breeding for feed efficient cattle is associated with positive environmental outcomes across the three agroecological zones considered. The simulation analysis showed that these environmental benefits differ spatially and are highest when the selection for feed efficiency is combined with limits on stocking rates. While the participation in a carbon offset scheme is an additional source of revenue which can possibly change cow-calf producer incentives, the results show that revenue from the offset scheme is inadequate given the low level of emissions per farm and the examined price of carbon. Overall, the empirical results of this study suggest that genomic selection for feed efficiency can improve the economic and environmental performance of the Canadian beef cattle industry. The potential supply chain bottlenecks and the spatial heterogeneity in cow-calf production must however be accounted for in the design of mechanisms to stimulate cow-calf producer uptake.
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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 ».