
Toward the Genetic Improvement of Feed Conversion Efficiency in Fish
Author(s) -
Doupé Robert G.,
Lymbery Alan J.
Publication year - 2003
Publication title -
journal of the world aquaculture society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.655
H-Index - 60
eISSN - 1749-7345
pISSN - 0893-8849
DOI - 10.1111/j.1749-7345.2003.tb00063.x
Subject(s) - biology , fish <actinopterygii> , fishery , feed conversion ratio , evolutionary biology , body weight , endocrinology
Feed conversion efficiency (FCE) is the effectiveness with which feed is converted to saleable fish product. Feed costs are a major input to aquaculture production systems, and genetic improvement in FCE may therefore have an important influence on profitability. FCE is usually expressed by a composite measure that combines feed intake and growth rate. The two most common measures are feed conversion ratio (feed intake/weight gain over a specified time interval) and its inverse, feed efficiency. Feed conversion ratio and feed efficiency are measures of gross FCE, because they do not distinguish between the separate energy requirements of growth and maintenance. There is abundant evidence of substantial genetic variation in FCE and its component traits in terrestrial livestock species and, although data are few, the same is likely for cultured fish species. The major problems with selecting from this variation to genetically improve FCE in fish species are: It appears impractical to measure feed intake on individual fish, so that family mean data must be used. We do not know the optimal time period over which to test fish for FCE. We do not know the genetic correlations between FCE under apparent satiation or restricted intake conditions, or between FCE at different times in the production cycle. If these problems can be overcome, selection to improve FCE might be best achieved by measuring feed intake of growing animals, and by utilizing genetic correlations that are likely to exist between feed intake and other production traits to develop a weighted selection index.