Optimizing mating schemes in fish breeding

The optimal contribution selection method and the simulated annealing algorithm were used to maximize the genetic gain and reduce inbreeding in fish breeding populations. This study considered the following mating designs: full factorial (3 x 3); full factorial (6 x 6) and nested (6 males x 18 femal...
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Autor*in:	D. Lanari [verfasserIn] C. S. Haley [verfasserIn] J. A. Woolliams [verfasserIn] E. D'Agaro [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Simulation, Fish, optimum contribution, Annealing algorithm.

Übergeordnetes Werk:	In: Italian Journal of Animal Science - Taylor & Francis Group, 2007, 6(2010), 1s, Seite 795-796
Übergeordnetes Werk:	volume:6 ; year:2010 ; number:1s ; pages:795-796

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.4081/ijas.2007.1s.795

Katalog-ID:	DOAJ020532229

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callnumber-first	S - Agriculture
author	D. Lanari
spellingShingle	D. Lanari misc SF1-1100 misc Simulation, Fish, optimum contribution, Annealing algorithm. misc Animal culture Optimizing mating schemes in fish breeding
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topic_title	SF1-1100 Optimizing mating schemes in fish breeding Simulation, Fish, optimum contribution, Annealing algorithm
topic	misc SF1-1100 misc Simulation, Fish, optimum contribution, Annealing algorithm. misc Animal culture
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title	Optimizing mating schemes in fish breeding
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title_full	Optimizing mating schemes in fish breeding
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title_sort	optimizing mating schemes in fish breeding
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title_auth	Optimizing mating schemes in fish breeding
abstract	The optimal contribution selection method and the simulated annealing algorithm were used to maximize the genetic gain and reduce inbreeding in fish breeding populations. This study considered the following mating designs: full factorial (3 x 3); full factorial (6 x 6) and nested (6 males x 18 females). A quantitative trait based on a strictly additive and polygenic model was simulated. Two levels for the number of genotyped offspring (360 or 720) and three levels of heritability (0.1; 0.3; 0.5) were assumed. The best results in terms of DF and DG were obtained with the full factorial design (6 x 6) and considering a trait with a high heritability. The optimal family size was found at 20 fish per mating.
abstractGer	The optimal contribution selection method and the simulated annealing algorithm were used to maximize the genetic gain and reduce inbreeding in fish breeding populations. This study considered the following mating designs: full factorial (3 x 3); full factorial (6 x 6) and nested (6 males x 18 females). A quantitative trait based on a strictly additive and polygenic model was simulated. Two levels for the number of genotyped offspring (360 or 720) and three levels of heritability (0.1; 0.3; 0.5) were assumed. The best results in terms of DF and DG were obtained with the full factorial design (6 x 6) and considering a trait with a high heritability. The optimal family size was found at 20 fish per mating.
abstract_unstemmed	The optimal contribution selection method and the simulated annealing algorithm were used to maximize the genetic gain and reduce inbreeding in fish breeding populations. This study considered the following mating designs: full factorial (3 x 3); full factorial (6 x 6) and nested (6 males x 18 females). A quantitative trait based on a strictly additive and polygenic model was simulated. Two levels for the number of genotyped offspring (360 or 720) and three levels of heritability (0.1; 0.3; 0.5) were assumed. The best results in terms of DF and DG were obtained with the full factorial design (6 x 6) and considering a trait with a high heritability. The optimal family size was found at 20 fish per mating.
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title_short	Optimizing mating schemes in fish breeding
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