Literature DB >> 19820067

Effect of divergence in residual feed intake on feeding behavior, blood metabolic variables, and body composition traits in growing beef heifers.

A K Kelly1, M McGee, D H Crews, A G Fahey, A R Wylie, D A Kenny.   

Abstract

This study examined the relationship of feed efficiency and performance with feeding behavior, blood metabolic variables, and various body composition measurements in growing beef heifers. Individual DMI and growth were measured in yearling Limousin x Holstein-Friesian heifers [n = 86; initial BW = 191.8 (SD = 37) kg] fed a TMR diet comprising 70:30 concentrate:corn silage on a DM basis (ME of 2.65 Mcal/kg of DM; DM of 580 g/kg) for 82 d. Meal duration (min/d) and meal frequency (events/d) were calculated for each animal on a daily basis using an Insentec computerized feeding system. Physical measurements as well as ultrasonic fat and muscle depths were recorded on 3 equally spaced occasions during the experimental period. Blood samples were collected by jugular venipuncture on 4 equally spaced occasions and analyzed for plasma concentrations of IGF-I, insulin, leptin, and various metabolites. Phenotypic residual feed intake (RFI) was calculated for all animals as the residuals from a multiple regression model regressing DMI on ADG and midtest BW(0.75). Overall, ADG, DMI, feed conversion ratio (FCR), and RFI were 1.51 (SD = 0.13), 6.74 (SD = 0.99), 4.48 (SD = 0.65), and 0.00 (SD = 0.48) kg/d, respectively. Residual feed intake was positively correlated with DMI (r = 0.47) and FCR (r = 0.46), but not with ADG or midtest BW. Positive correlations (ranging from r = 0.27 to r = 0.63) were estimated between ultrasonic measures of final lumbar fat and lumbar fat accretion over the test period and DMI, FCR, and RFI. The inclusion of gain in lumbar fat to the base RFI model increased R(2) (0.77 vs. 0.80) value for the degree of variation in DMI not explained by midtest BW and ADG alone. The Pearson rank correlation between RFI and carcass-adjusted RFI (RFI(c)) was high (r = 0.93). From the plasma analytes measured, NEFA (r = -0.21; P < 0.05) and beta-hydroxybutyrate (r = 0.37; P < 0.05) concentrations were correlated with RFI. Plasma leptin (r = 0.48), glucose:insulin (r = -0.23), NEFA (r = -0.32), and beta-hydroxybutyrate (r = 0.25) were associated with FCR. However, systemic IGF-I and insulin were unrelated (P > 0.05) to any measure of feed efficiency. The feeding behavior traits of eating rate, daily feeding events, and nonfeeding events were positively correlated (P < 0.05) with RFI and RFI(c). This multifactorial study provides new information on some of the biological processes responsible for variation in feed efficiency in beef cattle.

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Year:  2009        PMID: 19820067     DOI: 10.2527/jas.2009-2196

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


  33 in total

1.  Impact of feed efficiency and diet on adaptive variations in the bacterial community in the rumen fluid of cattle.

Authors:  Emma Hernandez-Sanabria; Laksiri A Goonewardene; Zhiquan Wang; Obioha N Durunna; Stephen S Moore; Le Luo Guan
Journal:  Appl Environ Microbiol       Date:  2011-12-09       Impact factor: 4.792

Review 2.  Residual feed intake: a nutritional tool for genetic improvement.

Authors:  Leilson Rocha Bezerra; José Lindenberg Rocha Sarmento; Severino Gonzaga Neto; Ney Rômulo Oliveira de Paula; Ronaldo Lopes Oliveira; Wagner Martins Fontes do Rêgo
Journal:  Trop Anim Health Prod       Date:  2013-10-31       Impact factor: 1.559

3.  Feed efficiency, blood parameters, and ingestive behavior of young Nellore males and females.

Authors:  Sarah Figueiredo Martins Bonilha; Joslaine Noely dos Santos Gonçalves Cyrillo; Guilherme Pinheiro dos Santos; Renata Helena Branco; Enilson Geraldo Ribeiro; Maria Eugênia Zerlotti Mercadante
Journal:  Trop Anim Health Prod       Date:  2015-07-04       Impact factor: 1.559

4.  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

5.  Association analysis between feed efficiency and expression of key genes of the avTOR signaling pathway in meat-type ducks.

Authors:  Lei Yang; Tingting He; Yuan Xu; He Zang; Jiafa Wang; Zhiqiang Lin; Sihua Jin; Zhaoyu Geng
Journal:  Mol Biol Rep       Date:  2019-05-28       Impact factor: 2.316

6.  Characterization of feeding behavior traits in steers with divergent residual feed intake consuming a high-concentrate diet.

Authors:  Ira L Parsons; Jocelyn R Johnson; William C Kayser; Luis O Tedeschi; Gordon E Carstens
Journal:  J Anim Sci       Date:  2020-07-01       Impact factor: 3.159

7.  Relationships between feed efficiency and puberty in Bos taurus and Bos indicus-influenced replacement beef heifers.

Authors:  Luara B Canal; Pedro L P Fontes; Carla D Sanford; Vitor R G Mercadante; Nicolas DiLorenzo; G Cliff Lamb; Nicola Oosthuizen
Journal:  J Anim Sci       Date:  2020-10-01       Impact factor: 3.159

8.  Digestion and metabolism of low and high residual feed intake Nellore bulls.

Authors:  Sarah Figueiredo Martins Bonilha; Renata Helena Branco; Maria Eugênia Zerlotti Mercadante; Joslaine Noely Dos Santos Gonçalves Cyrillo; Fábio Morato Monteiro; Enilson Geraldo Ribeiro
Journal:  Trop Anim Health Prod       Date:  2017-01-26       Impact factor: 1.559

9.  Rumen methanogenic genotypes differ in abundance according to host residual feed intake phenotype and diet type.

Authors:  Ciara A Carberry; Sinéad M Waters; Sinead M Waters; David A Kenny; Christopher J Creevey
Journal:  Appl Environ Microbiol       Date:  2013-11-08       Impact factor: 4.792

10.  Effect of phenotypic residual feed intake and dietary forage content on the rumen microbial community of beef cattle.

Authors:  Ciara A Carberry; David A Kenny; Sukkyan Han; Matthew S McCabe; Sinead M Waters
Journal:  Appl Environ Microbiol       Date:  2012-05-04       Impact factor: 4.792

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