Literature DB >> 16478969

Identifying differences in feed efficiency among group-fed cattle.

L O Tedeschi1, D G Fox, M J Baker, D P Kirschten.   

Abstract

Identification of efficient animals in the postweaning growth phase for use in selection for improved feed efficiency is important to improve the economic and environmental sustainability of the beef cattle industry. Progeny testing using group-fed animals in commercial feedlots is the most common and practical method used to evaluate postweaning growth on large numbers of animals. We developed the Cornell Value Discovery System (CVDS) to dynamically predict growth rate, accumulated weight, days required to reach target body composition, carcass weight, and composition of individual beef cattle fed in group pens. Observed BW, ADG, BW at 28% empty body fat (EBF), breed type, environmental conditions, and dietary ME concentration are used by the CVDS to predict, for each animal in a pen, the feed DM required for maintenance (FFM), the feed DM required for gain, and the total DM required for maintenance and gain (DMR). The CVDS then computes DMR-to-ADG ratio (DMR:ADG), which is a feed conversion measure, and ADG-to-DMR ratio (ADG:DMR), which is a feed efficiency measure, for each animal. This study used the observed F:G ratio of 362 individually fed steers to evaluate CVDS-predicted indicators of feed efficiency and the Kleiber ratio. A subset of 37 data points was used to evaluate residual feed intake (RFI) as an indicator of feed efficiency. The database included 4 published studies, each with detailed individual animal description, environment, diet, and body composition information. The CVDS-predicted DMR:ADG accounted for 84% of the variation in the actual F:G ratio with a mean bias of 1.94% (P = 0.20). The predicted FFM to actual DMI ratio had a high correlation with actual ADG (R2 = 0.76), and indicated a decay-type nonlinear dilution of FFM as ADG increased. The CVDS-predicted ADG:DMR and the Kleiber ratio had a significant (R2 = 0.88) logarithmic relationship. In an analysis of a contemporary group within the database, RFI was highly correlated with the F:G ratio (r = 0.71). There was a positive relationship between RFI and EBF. The RFIM (DMI - DMR) was moderately correlated with DMI and ADG (0.37 and -0.38; respectively), suggesting that selecting for low RFI(M) would decrease DMI and increase ADG in this database. We conclude that the CVDS model can be used to identify differences in the F:G and G:F ratios by predicting DMR for individual growing cattle fed in groups.

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Year:  2006        PMID: 16478969     DOI: 10.2527/2006.843767x

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


  6 in total

1.  Consistency of feed efficiency ranking and mechanisms associated with inter-animal variation among growing calves.

Authors:  A Asher; A Shabtay; M Cohen-Zinder; Y Aharoni; J Miron; R Agmon; I Halachmi; A Orlov; A Haim; L O Tedeschi; G E Carstens; K A Johnson; A Brosh
Journal:  J Anim Sci       Date:  2018-04-03       Impact factor: 3.159

2.  A mathematical nutrition model adequately predicts beef and dairy cow intake and biological efficiency.

Authors:  Phillip A Lancaster; Michael E Davis; Luis O Tedeschi; Jack J Rutledge; Larry V Cundiff
Journal:  Transl Anim Sci       Date:  2021-12-20

3.  Genomic Regions Associated with Feed Efficiency Indicator Traits in an Experimental Nellore Cattle Population.

Authors:  Bianca Ferreira Olivieri; Maria Eugênia Zerlotti Mercadante; Joslaine Noely Dos Santos Gonçalves Cyrillo; Renata Helena Branco; Sarah Figueiredo Martins Bonilha; Lucia Galvão de Albuquerque; Rafael Medeiros de Oliveira Silva; Fernando Baldi
Journal:  PLoS One       Date:  2016-10-19       Impact factor: 3.240

4.  Impact of supplemental protein source offered to primiparous heifers during gestation on II. Progeny performance and carcass characteristics.

Authors:  A F Summers; A D Blair; R N Funston
Journal:  J Anim Sci       Date:  2015-04       Impact factor: 3.159

5.  Animals selected for postweaning weight gain rate have similar maintenance energy requirements regardless of their residual feed intake classification.

Authors:  Camila Delveaux Araujo Batalha; Luís Orlindo Tedeschi; Fabiana Lana de Araújo; Renata Helena Branco; Joslaine Noely Dos Santos Gonçalves Cyrillo; Sarah Figueiredo Martins Bonilha
Journal:  J Anim Sci       Date:  2021-03-01       Impact factor: 3.159

6.  Integrating Genomics with Nutrition Models to Improve the Prediction of Cattle Performance and Carcass Composition under Feedlot Conditions.

Authors:  Luis O Tedeschi
Journal:  PLoS One       Date:  2015-11-24       Impact factor: 3.240

  6 in total

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