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Selection for Adaptation to Dietary Shifts: Towards Sustainable Breeding of Carnivorous Fish

Overview of attention for article published in PLOS ONE, September 2012
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Title
Selection for Adaptation to Dietary Shifts: Towards Sustainable Breeding of Carnivorous Fish
Published in
PLOS ONE, September 2012
DOI 10.1371/journal.pone.0044898
Pubmed ID
Authors

Richard Le Boucher, Mathilde Dupont-Nivet, Marc Vandeputte, Thierry Kerneïs, Lionel Goardon, Laurent Labbé, Béatrice Chatain, Marie Josée Bothaire, Laurence Larroquet, Françoise Médale, Edwige Quillet

Abstract

Genetic adaptation to dietary environments is a key process in the evolution of natural populations and is of great interest in animal breeding. In fish farming, the use of fish meal and fish oil has been widely challenged, leading to the rapidly increasing use of plant-based products in feed. However, high substitution rates impair fish health and growth in carnivorous species. We demonstrated that survival rate, mean body weight and biomass can be improved in rainbow trout (Oncorhynchus mykiss) after a single generation of selection for the ability to adapt to a totally plant-based diet (15.1%, 35.3% and 54.4%, respectively). Individual variability in the ability to adapt to major diet changes can be effectively used to promote fish welfare and a more sustainable aquaculture.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Australia 1 <1%
Unknown 109 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 25%
Student > Ph. D. Student 20 18%
Student > Master 16 14%
Professor > Associate Professor 7 6%
Student > Doctoral Student 6 5%
Other 15 13%
Unknown 21 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 50%
Environmental Science 8 7%
Biochemistry, Genetics and Molecular Biology 7 6%
Medicine and Dentistry 6 5%
Engineering 2 2%
Other 6 5%
Unknown 28 25%