Data/hora: 17/06/2024 15:11:10

Provedor de dados: | 5
País: | France
Título: | Amélioration génétique et utilisation des aliments à base de végétaux en pisciculture
Autores: | Le Boucher, Richard; Dupont-nivet, M.; Laureau, S.; Labbe, Laurent; Geurden, I.; Medale, F.; Chatain, Beatrice; Vandeputte, Marc; Quillet, E.
Data: | 2013
Ano: | 2013
Resumo: | World fish farm production is growing rapidly. However, the supply of fishmeal and fish oil, the major ingredients of fish diets, has reached a limit because of the limits in the exploitation of wild fish stocks that cannot be increased to meet a growing demand. The main response, especially in Europe, has been the progressive replacement of fishmeal and fish oil by plant products. However, the strong reduction of growth and sometimes survival of fish fed highly substituted diets has urged research on the genetic potential for adaptation to plant-based diets. Recent results clearly demonstrate that fish can be selected for their capacity to grow when fed plant-based diets, even though the underlying mechanisms remain unknown. Genotype-diet interactions have been shown, indicating that the best performers differ according to the diet. Such interactions may make the management of breeding programmes difficult, as progeny may be reared with a diet differing from the one used to select the breeders. Simulations of the expected genetic gain according to different scenarios can help manage selection programmes for sea bass and rainbow trout, the main farmed species in France. Using both selective breeding and optimized diets provide the opportunity to increase sustainability of fish farming, whilst maintaining product quality.
Tipo: | Text
Idioma: | Francês
Identificador: | http://archimer.ifremer.fr/doc/00200/31167/29566.pdf
Editor: | Inst Natl Recherche Agronomique
Relação: | http://archimer.ifremer.fr/doc/00200/31167/
Formato: | application/pdf
Fonte: | Inra Productions Animales (0990-0632) (Inst Natl Recherche Agronomique), 2013 , Vol. 26 , N. 4 , P. 317-326
Fonte: | INRA