Literature DB >> 6728761

Genetic variation of abdominal fat, body weight, and carcass weight in a female broiler line.

W A Becker, J V Spencer, L W Mirosh, J A Verstrate.   

Abstract

Pedigreed matings in a commercial purebred female broiler selection line produced 311 males and 341 females, which were slaughtered at 50 days of age. Coefficients of variation of abdominal fat weights were higher than live and carcass weights. The coefficient of variation was reduced when abdominal fat was regressed on live weight or when percentage of live or carcass weight was used. Leaf fat was approximately two-thirds and gizzard fat was approximately one-third of the total abdominal fat. Heritabilities for abdominal fat were high, and the genetic correlations between the fat and live or carcass weights ranged from .43 to .50 in males and .32 to .40 in females. The phenotypic correlations between fat and live weight were reduced when abdominal fat weight was subtracted from live weight, showing that the part-whole relationship between abdominal fat included in live body weight increased the correlations. The heritabilities indicate that it should be possible to reduce abdominal fat by selection, and the genetic correlations signify that a method has to be devised to increase body weight while simultaneously reducing abdominal fat weight.

Entities:  

Mesh:

Year:  1984        PMID: 6728761     DOI: 10.3382/ps.0630607

Source DB:  PubMed          Journal:  Poult Sci        ISSN: 0032-5791            Impact factor:   3.352


  2 in total

1.  Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping.

Authors:  Beatriz do Nascimento Nunes; Salvador Boccaletti Ramos; Rodrigo Pelicioni Savegnago; Mônica Corrêa Ledur; Kátia Nones; Claudete Hara Klein; Danísio Prado Munari
Journal:  Genet Mol Biol       Date:  2011-07-01       Impact factor: 1.771

2.  Differentially Expressed lncRNAs Related to the Development of Abdominal Fat in Gushi Chickens and Their Interaction Regulatory Network.

Authors:  Bin Zhai; Yinli Zhao; Shengxin Fan; Pengtao Yuan; Hongtai Li; Shuaihao Li; Yuanfang Li; Yanhua Zhang; Hetian Huang; Hong Li; Xiangtao Kang; Guoxi Li
Journal:  Front Genet       Date:  2021-12-24       Impact factor: 4.599

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.