Literature DB >> 32819069

Nutrient requirements and evaluation of equations to predict chemical body composition of dairy crossbred steers.

Flavia Adriane de Sales Silva1, Sebastião de Campos Valadares Filho1, Luiz Fernando Costa E Silva2, Jaqueline Gonçalves Fernandes3, Bruno Corrêa Lage1, Mario Luiz Chizzotti1, Tara Louise Felix4.   

Abstract

OBJECTIVE: Objectives were to estimate energy and protein requirements of dairy crossbred steers, as well as to evaluate equations previously described in the literature (HH46 and CS16) to predict the carcass and empty body chemical composition of crossbred dairy cattle.
METHODS: Thirty-three Holstein × Zebu steers, aged 19 ± 1 months old, with an initial shrunk body weight of 324 ± 7.7 kg, were randomly divided into three groups: reference group (n = 5), maintenance level (1.17% BW; n = 4), and the remaining 24 steers were randomly allocated to 1 of 4 treatments. Treatments were: intake restricted to 85% of ad libitum feed intake for either 0, 28, 42, or 84 d of an 84-d finishing period.
RESULTS: The net energy and the metabolizable protein requirements for maintenance were 0.083 Mcal/EBW0.75/d and 4.40 g/EBW0.75, respectively. The net energy (NEG) and protein (NPG) requirements for growth can be estimated with the following equations: NEG (Mcal/kg EBG) = 0.2973(± 0.1212) × EBW0.4336(± 0.1002) and NPG (g/d) = 183.6(± 22.5333) × EBG - 2.0693(± 4.7254) × RE, where EBW = empty body weight, EBG = empty body gain, and RE = retained energy. Crude protein (CP) and ether extract (EE) chemical contents in carcass, and all the chemical components in the empty body were precisely and accurately estimated by CS16 equations. However, water content in carcass was better predicted by HH46 equation.
CONCLUSION: The equations proposed in this study can be used for estimating the energy and protein requirements of crossbred dairy steers. The CS16 equations were the best estimator for CP and EE chemical contents in carcass, and all chemical components in the empty body of crossbred dairy steers, whereas water in carcass was better estimated using the HH46 equations.

Entities:  

Keywords:  Body Composition; Carcass Composition; Cattle

Year:  2020        PMID: 32819069      PMCID: PMC7961289          DOI: 10.5713/ajas.19.0829

Source DB:  PubMed          Journal:  Anim Biosci        ISSN: 2765-0189


  8 in total

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2.  Prediction of physical and chemical body compositions of purebred and crossbred Nellore cattle using the composition of a rib section.

Authors:  M I Marcondes; L O Tedeschi; S C Valadares Filho; M L Chizzotti
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3.  Body composition of cattle. II. Determination of fat and water content from measurement of body specific gravity.

Authors:  H F KRAYBILL; H L BITTER; O G HANKINS
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4.  Predicting carcass and body fat composition using biometric measurements of grazing beef cattle.

Authors:  N F De Paula; L O Tedeschi; M F Paulino; H J Fernandes; M A Fonseca
Journal:  J Anim Sci       Date:  2013-05-08       Impact factor: 3.159

5.  Nutritional recommendations of feedlot consulting nutritionists: The 2015 New Mexico State and Texas Tech University survey.

Authors:  K L Samuelson; M E Hubbert; M L Galyean; C A Löest
Journal:  J Anim Sci       Date:  2016-06       Impact factor: 3.159

6.  Technical note: chemical composition of Angus and Holstein carcasses predicted from rib section composition.

Authors:  A Y Nour; M L Thonney
Journal:  J Anim Sci       Date:  1994-05       Impact factor: 3.159

7.  Effect of level of energy intake and influence of breed and sex on the chemical composition of cattle.

Authors:  A Fortin; S Simpfendorfer; J T Reid; H J Ayala; R Anrique; A F Kertz
Journal:  J Anim Sci       Date:  1980-09       Impact factor: 3.159

8.  Macrominerals and Trace Element Requirements for Beef Cattle.

Authors:  Luiz Fernando Costa e Silva; Sebastião de Campos Valadares Filho; Terry Eugene Engle; Polyana Pizzi Rotta; Marcos Inácio Marcondes; Flávia Adriane Sales Silva; Edilane Costa Martins; Arnaldo Taishi Tokunaga
Journal:  PLoS One       Date:  2015-12-14       Impact factor: 3.240

  8 in total

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