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Enregistrement W1989147834 · doi:10.1111/jbg.12098

North American animal breeding and production: meeting the needs of a changing landscape

2014· editorial· en· W1989147834 sur OpenAlexaffabout
Harvey D. Blackburn, Y. Plante

Notice bibliographique

RevueJournal of Animal Breeding and Genetics · 2014
Typeeditorial
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetic and phenotypic traits in livestock
Établissements canadiensAgriculture and Agri-Food Canada
Organismes subventionnairesnon disponible
Mots-clésLivestockPopulationProduction (economics)Profitability indexBusinessAgricultural economicsExportationProduct (mathematics)Agricultural scienceNatural resource economicsEconomicsGeographyBiology

Résumé

récupéré en direct d'OpenAlex

The North American livestock sector is economically mature; much of the increased demand for livestock products is driven by modest increases in human population and substitution of one species for another in response to commodity prices and consumer trends. Depending on the price of production inputs and farm gate prices, the population of national herds can be cyclical. Major weather events or disease outbreaks can cause subregional fluctuations in population sizes. Accordingly, exportation of animal products is in part based upon the cyclical nature of markets. The vast majority of livestock entering the food chain do so through highly efficient production, processing and retailing systems, although the ‘slow food’ movement and niche markets are gaining traction and developing at relatively fast rates (primarily due to their small initial size). While these niche markets provide interesting opportunities for livestock producers, or producer groups, their robustness to changes in price and product supply is unknown. Due to the mature market structure for livestock products, producers focus attention on approaches that can improve their production efficiency. It is recognized that early adoption of new technology can improve profitability. This drive for efficient animal production has had the net result of decreasing the number of livestock. Regionally from the 1970s to the present the inventory of dairy cattle has decreased while total milk production has increased largely due to genetic improvement. This same trend has been observed with beef cattle for both Canada and the USA, which experienced a 13% and 32% decrease in cow numbers, with little change in total production levels over recent decades. The increased cow productivity has been made possible by selection for increased weaning and yearling weights, which have been translated into increased dressed steer weights. Similar types of production efficiency gains have also been achieved with traits with lower heritability. For example, during the last decade the number of piglets, born per litter has increased by about 10% for the region. While breeding programmes have increased productivity, there has been a contraction in the number of breeders across species. That said, across ruminants and purebred swine, there are still substantial numbers of breeders controlling livestock breeding programmes. As might be expected with a wide range of actors with varying resources, all breeders do not act in unison when implementing selection programmes. As a result, there have always been breeders who tend to be counter-cyclical in their breeding decisions. In general, the rational behaviour of breeders has served the industry well by providing a pool of genetic resources to be drawn upon if current popular trends result in negative impacts on productivity or marketability of their stock. Furthermore, and as a failsafe, both countries have developed substantial cryopreserved germplasm collections, which can be utilized to increase genetic variability and to facilitate adaptation to shifting market demands or environments. Across livestock species, breeders have adapted breeding technologies. In several instances, consortiums of public and private sector stakeholders have been developed to facilitate the access to and implementation of various tools to accelerate genetic gains. The estimation of breeding values for a wide variety of traits is common place across all species. Breed associations have tended to work on a contractual basis with the public sector to develop breeding value estimates for new traits. Larger breed associations and corporate breeding firms have also been among the first to genotype animals and to use this information in developing genomic breeding values that combine molecular information and quantitative data. Smaller associations have started to genotype animals and develop training datasets so that molecular breeding values can be developed. Even though breeders may be armed with access to such technologies, it is a private business level decision to use such tools and the amount of selection pressure to apply. A number of important factors will impact breeding and selection programmes. The trend towards higher meat quality will likely continue to influence breeding decisions across species. But in addition, and particularly for ruminants, there is a growing awareness of a need to better match genotypes to the diverse production environments found in North America. For example, it has been discussed in several fora, the need to optimize cow size, especially in the more arid and subtropical environments. Such a driver will force breeders to explore alternatives – to increase selection pressure on traits for adaptability (e.g. high altitude) while scaling back selection intensity on other traits in an effort to better balance livestock to their environment. There is now interest in increasing productivity and profitability through selecting for better animal health and decreased residual feed intake, both efforts contribute to environmental sustainability by reducing the environmental footprint of livestock production. Certainly, genomic tools will have a role to play in developing solutions for the above issues. To better identify optimal production and breeding strategies, reinitiating deterministic modelling approaches would provide effective insights for breeders to base the direction of their selection programmes and the economic impact of such firm level decisions. Generally, climate change will have a larger negative impact on the US livestock sector when compared to Canada. The breeding and animal science community has started to address those potential stressors. For example, research has been initiated into the role of heat-shock proteins (Collier et al. 2008, J. Dairy Sci. 91, 445), SNPs associated with embryonic survival (Cochran et al. 2013, BMC Genetics 14, 49) and the ‘slick-haired’ gene in cattle (Olson et al. 2003, J. Anim. Sci. 81, 80) – all of which improve our understanding of and ability to manipulate populations for greater climate adaptability. In addition, given the relatively long time frame (2050) before the projected full impact of climate change, as identified by the Intergovernmental Panel on Climate Change, modifications in animal genetic composition can be made to meet this challenge. The potential for diseases increases as climate change progresses. Inquiry into the genetic basis of disease resistance is under investigation in North America and globally. Additional efforts among the monogastric species selection have begun to maintain performance levels while altering diets and implementing production systems which are perceived as more animal welfare friendly. North America has a broad array of genetic resources which have been used to develop populations capable of performing in diverse production settings. For example, of the top 10 international (or transboundary) cattle breeds identified by FAO, all are found in North America along with active breeder associations. The underlying success in using these resources has been the willingness of producers/breeders to incorporate new technologies that aid selection and to develop and evaluate new breed types, composites or synthetics to match their performance under different agro-ecosystems and to meet specific market niches. As a result, North American genetics have been widely exported through individual breeders or corporate breeding firms. As a 2009 report found, over 50% of the globally exported bovine semen was from North America (Gollin et al. 2009, Livestock Sci. 120, 248). Particularly, among the monogastric species, we note with interest that while developing countries have imported intensively bred and produced livestock, it has been the subject of criticism by some. But these imported populations and associated production systems may be solely responsible for the increased monogastric per animal productivity observed in the least developed countries during the last decade (based upon FAOSTAT). The use of productive genetic resources has been called for by the ‘High Level Panel of Experts on Food Security and Nutrition’ convened by FAO. While the panel recognizes the need for genetic resources exchange, as does the CBD, neither has acknowledged that mechanisms are already in place in the livestock sector to facilitate genetic resource exchange. Principally, as livestock and their genetic resources are private property (affirmed in the Interlaken Declaration), owners/breeders have and continue to practice genetic resource exchange, which benefits the global community. Close association between the property rights of breeders and their selection decisions has contributed to the genetic progress achieved during the past 20–30 years and suggests Darwin's observation about livestock breeders, and particularly in the North American context, is still relevant today: ‘breeders habitually speak of an animal's organization as something plastic, which they model as they please’ – long live the breeder.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,226
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,234
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2014
Routes d'admission2
Résumé présentoui

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