Literature DB >> 23658333

Predicting carcass and body fat composition using biometric measurements of grazing beef cattle.

N F De Paula1, L O Tedeschi, M F Paulino, H J Fernandes, M A Fonseca.   

Abstract

This study was conducted to develop equations to predict carcass and body fat compositions using biometric measures (BM) and body postmortem measurements and to determine the relationships between BM and carcass fat and empty body fat compositions of 44 crossbred bulls under tropical grazing conditions. The bulls were serially slaughtered in 4 groups at approximately 0 d (n = 4), 84 d (n = 4), 168 d (n = 8), 235 d (n = 8), and 310 d (n = 20) of growth. The day before each slaughter, bulls were weighed, and BM were taken, including hook bone width, pin bone width, abdomen width, body length, rump height, height at withers, pelvic girdle length, rib depth, girth circumference, rump depth, body diagonal length, and thorax width. Others measurements included were total body surface (TBS), body volume (BV), subcutaneous fat (SF), internal fat (InF), intermuscular fat, carcass physical fat (CFp), empty body physical fat (EBFp), carcass chemical fat (CFch), empty body chemical fat (EBFch), fat thickness in the 12th rib (FT), and 9th- to 11th-rib section fat (HHF). The stepwise procedure was used to select the variables included in the model. The r(2) and the root-mean-square error (RMSE) were used to account for precision and variability. Our results indicated that lower rates of fat deposition can be attributed to young cattle and low concentration of dietary energy under grazing conditions. The BM improved estimates of TBS (r(2) = 0.999) and BV (r(2) = 0.997). The adequacy evaluation of the models developed to predict TBS and BV using theoretical equations indicated precision, but lower and intermediate accuracy (bias correction = 0.138 and 0.79), respectively, were observed. The data indicated that BM in association with shrunk BW (SBW) were precise in accounting for variability of SF (r(2) = 0.967 and RMSE = 0.94 kg), InF (r(2) = 0.984 and RMSE = 1.26 kg), CFp (r(2) = 0.981 and RMSE = 2.98 kg), EBFp (r(2) = 0.985 and RMSE = 3.99 kg), CFch (r(2) = 0.940 and RMSE = 2.34 kg), and EBFch (r(2) = 0.934 and RMSE = 3.91 kg). Results also suggested that approximately 70% of body fat was deposited as CFp and 30% as InF. Furthermore, the development of an equation using HHF as a predictor, in combination with SBW, was a better predictor of CFp and EBFp than using HHF by itself. We concluded that the prediction of physical and chemical CF and EBF composition of grazing cattle can be improved using BM as a predictor.

Entities:  

Mesh:

Year:  2013        PMID: 23658333     DOI: 10.2527/jas.2012-5233

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


  7 in total

1.  Evaluation of active dried yeast in the diets of feedlot steers-I: Effects on feeding performance traits, the composition of growth, and carcass characteristics1.

Authors:  Whitney L Crossland; Jillian T Jobe; Flavio R B Ribeiro; Jason E Sawyer; Todd R Callaway; Luis O Tedeschi
Journal:  J Anim Sci       Date:  2019-03-01       Impact factor: 3.159

Review 2.  Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part I: Cattle and swine.

Authors:  Zhoumeng Lin; Miao Li; Yu-Shin Wang; Lisa A Tell; Ronald E Baynes; Jennifer L Davis; Thomas W Vickroy; Jim E Riviere
Journal:  J Vet Pharmacol Ther       Date:  2020-04-08       Impact factor: 1.786

3.  In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle.

Authors:  A M Castilhos; C L Francisco; R H Branco; S F M Bonilha; M E Z Mercadante; P R L Meirelles; C M Pariz; A M Jorge
Journal:  J Anim Sci       Date:  2018-05-04       Impact factor: 3.159

4.  Assessment of body fat composition in crossbred Angus × Nellore using biometric measurements.

Authors:  M A Fonseca; L O Tedeschi; S C Valadares Filho; N F De Paula; F A C Villadiego; J M Silva Junior; D C Abreu; M L Chizzotti
Journal:  J Anim Sci       Date:  2017-12       Impact factor: 3.159

5.  Effect of using banana by-products and other agricultural residues for beef cattle in southern China.

Authors:  Zhulin Xue; Lan Mu; Ming Cai; Yingjun Zhang; Metha Wanapat; Bizhi Huang
Journal:  Trop Anim Health Prod       Date:  2019-08-08       Impact factor: 1.559

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

Authors:  Flavia Adriane de Sales Silva; Sebastião de Campos Valadares Filho; Luiz Fernando Costa E Silva; Jaqueline Gonçalves Fernandes; Bruno Corrêa Lage; Mario Luiz Chizzotti; Tara Louise Felix
Journal:  Anim Biosci       Date:  2020-06-24

7.  Effects of lipid and starch supplementation as water intake mitigation techniques on performance and efficiency of nursing Holstein calves.

Authors:  A Macias Franco; A E M da Silva; F H de Moura; A B Norris; K Van Den Broek; M Valcheck; A de Mello; M Fonseca
Journal:  Transl Anim Sci       Date:  2021-06-21
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.