Literature DB >> 23345557

Cell Biology Symposium: genetics of feed efficiency in dairy and beef cattle.

D P Berry1, J J Crowley.   

Abstract

Increasing food production for the growing human population off a constraining land base will require greater efficiency of production. Genetic improvement of feed efficiency in cattle, which is cumulative and permanent, is one likely vehicle to achieving efficiency gains. The objective of this review is to summarize genetic parameters for feed efficiency traits in dairy and beef cattle and also to address some of the misconceptions associated with feed efficiency in these sectors, as well as discuss the potential use of feed efficiency in breeding programs. A meta-analysis of up to 39 scientific publications in growing cattle clearly showed that genetic variation in feed efficiency exists with a pooled heritability for residual feed intake (RFI) and feed conversion efficiency of 0.33 ± 0.01 (range of 0.07 to 0.62) and 0.23 ± 0.01 (range of 0.06 to 0.46), respectively. Heritability estimates for feed efficiency in cows were lower; a meta-analysis of up to 11 estimates revealed heritability estimates for gross feed efficiency and RFI of 0.06 ± 0.010 and 0.04 ± 0.008, respectively. Meta-analysis of genetic correlations between feed intake, feed efficiency and other performance traits are presented, and selection index theory is used to calculate the proportion of genetic variation in feed intake that can be explained by easy to measure, and often already collected, data. A large proportion of the genetic variation in feed intake could be explained in both growing animals and lactating animals using up to 5 predictor traits, including BW, growth rate, milk yield, body composition, and linear type traits reflecting body size and muscularity. Knowledge of genetic merit for feed intake can be used, along with estimates of genetic merit for energy sinks, to calculate genetic merit for feed efficiency. Therefore, the marginal benefit of collecting actual feed intake data, using the genetic parameters used in this study, appears to be low. There is now sufficient information available to develop a road map on how best to direct research to ensure long-term food security for a growing human population. Gaps in knowledge are identified here, and possibilities to address these gaps are discussed.

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Year:  2013        PMID: 23345557     DOI: 10.2527/jas.2012-5862

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  50 in total

1.  Genetic parameters and genome-wide association study regarding feed efficiency and slaughter traits in Charolais cows.

Authors:  Pauline Martin; Sébastien Taussat; Aurélie Vinet; Daniel Krauss; David Maupetit; Gilles Renand
Journal:  J Anim Sci       Date:  2019-09-03       Impact factor: 3.159

2.  Relationship between feed efficiency and slaughter traits of French Charolais bulls.

Authors:  Sébastien Taussat; Romain Saintilan; Daniel Krauss; David Maupetit; Marie-Noëlle Fouilloux; Gilles Renand
Journal:  J Anim Sci       Date:  2019-05-30       Impact factor: 3.159

3.  Genetic trends for live weight traits reflect breeding strategies in registered Charolais Farms in Mexico.

Authors:  G M Parra-Bracamonte; N Lopez-Villalobos; S T Morris; A M Sifuentes-Rincón; L A Lopez-Bustamante
Journal:  Trop Anim Health Prod       Date:  2016-09-30       Impact factor: 1.559

4.  Genetic and phenotypic associations of feed efficiency with growth and carcass traits in Australian Angus cattle.

Authors:  José Antonio Torres-Vázquez; Julius H J van der Werf; Samuel A Clark
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

5.  Relationships among carbon dioxide, feed intake, and feed efficiency traits in ad libitum fed beef cattle.

Authors:  Paul F Arthur; Tracie Bird-Gardiner; Idris M Barchia; Kath A Donoghue; Robert M Herd
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

6.  Non-genetic sources of variation and temporal variability in growth and feed efficiency traits among phylogenetically distinct clusters of indigenous chicken in Kenya.

Authors:  Sophie Miyumo; Alexander K Kahi; Chrilukovian B Wasike
Journal:  Trop Anim Health Prod       Date:  2016-08-25       Impact factor: 1.559

7.  Variability in residual feed intake and nutrient utilization in Murrah buffalo heifers.

Authors:  Tegene Negesse; Chander Datt; S S Kundu
Journal:  Trop Anim Health Prod       Date:  2016-09-12       Impact factor: 1.559

8.  A dynamic model as a tool to describe the variability of lifetime body weight trajectories in livestock females.

Authors:  L Puillet; O Martin
Journal:  J Anim Sci       Date:  2017-11       Impact factor: 3.159

9.  Evaluation of feed efficiency traits for genetic improvement in Japanese Black cattle.

Authors:  Masayuki Takeda; Yoshinobu Uemoto; Keiichi Inoue; Atsushi Ogino; Takayoshi Nozaki; Kazuhito Kurogi; Takanori Yasumori; Masahiro Satoh
Journal:  J Anim Sci       Date:  2018-04-03       Impact factor: 3.159

10.  Feed and production efficiency of young crossbred beef cattle stratified on a terminal total merit index.

Authors:  David N Kelly; Stephen B Conroy; Craig P Murphy; Roy D Sleator; Donagh P Berry
Journal:  Transl Anim Sci       Date:  2020-07-01
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