Genetic and phenotypic parameter estimates for feed intake and other traits in growing beef cattle, and opportunities for selection123

2011 ◽  
Vol 89 (11) ◽  
pp. 3452-3459 ◽  
Author(s):  
K. M. Rolfe ◽  
W. M. Snelling ◽  
M. K. Nielsen ◽  
H. C. Freetly ◽  
C. L. Ferrell ◽  
...  
2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. 1655-1657
Author(s):  
Emma A Briggs ◽  
R Mark Enns ◽  
Milton G Thomas ◽  
Scott E Speidel

2019 ◽  
Vol 97 (5) ◽  
pp. 2181-2187
Author(s):  
Ahmed A Elolimy ◽  
Emad Abdel-Hamied ◽  
Liangyu Hu ◽  
Joshua C McCann ◽  
Daniel W Shike ◽  
...  

Abstract Residual feed intake (RFI) is a widely used measure of feed efficiency in cattle. Although the precise biologic mechanisms associated with improved feed efficiency are not well-known, most-efficient steers (i.e., with low RFI coefficient) downregulate abundance of proteins controlling protein degradation in skeletal muscle. Whether cellular mechanisms controlling protein turnover in ruminal tissue differ by RFI classification is unknown. The aim was to investigate associations between RFI and signaling through the mechanistic target of rapamycin (MTOR) and ubiquitin-proteasome pathways in ruminal epithelium. One hundred and forty-nine Red Angus cattle were allocated to 3 contemporary groups according to sex and herd origin. Animals were offered a finishing diet for 70 d to calculate the RFI coefficient for each. Within each group, the 2 most-efficient (n = 6) and least-efficient animals (n = 6) were selected. Compared with least-efficient animals, the most-efficient animals consumed less feed (P < 0.05; 18.36 vs. 23.39 kg/d DMI). At day 70, plasma samples were collected for insulin concentration analysis. Ruminal epithelium was collected immediately after slaughter to determine abundance and phosphorylation status of 29 proteins associated with MTOR, ubiquitin-proteasome, insulin signaling, and glucose and amino acid transport. Among the proteins involved in cellular protein synthesis, most-efficient animals had lower (P ≤ 0.05) abundance of MTOR, p-MTOR, RPS6KB1, EIF2A, EEF2K, AKT1, and RPS6KB1, whereas MAPK3 tended (P = 0.07) to be lower. In contrast, abundance of p-EEF2K, p-EEF2K:EEF2K, and p-EIF2A:EIF2A in most-efficient animals was greater (P ≤ 0.05). Among proteins catalyzing steps required for protein degradation, the abundance of UBA1, NEDD4, and STUB1 was lower (P ≤ 0.05) and MDM2 tended (P = 0.06) to be lower in most-efficient cattle. Plasma insulin and ruminal epithelium insulin signaling proteins did not differ (P > 0.05) between RFI groups. However, abundance of the insulin-responsive glucose transporter SLC2A4 and the amino acid transporters SLC1A3 and SLC1A5 also was lower (P ≤ 0.05) in most-efficient cattle. Overall, the data indicate that differences in signaling mechanisms controlling protein turnover and nutrient transport in ruminal epithelium are components of feed efficiency in beef cattle.


1990 ◽  
Vol 73 (3) ◽  
pp. 826-834 ◽  
Author(s):  
R.K. Moore ◽  
B.W. Kennedy ◽  
L.R. Schaeffer ◽  
J.E. Moxley

1987 ◽  
Vol 28 (5) ◽  
pp. 547-555 ◽  
Author(s):  
T.A. Gipson ◽  
D.W. Vogt ◽  
M.R. Ellersieck ◽  
J.W. Massey

2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 58-58
Author(s):  
Megan A Gross ◽  
Claire Andresen ◽  
Amanda Holder ◽  
Alexi Moehlenpah ◽  
Carla Goad ◽  
...  

Abstract In 1996, the NASEM beef cattle committee developed and published an equation to estimate cow feed intake using results from studies conducted or published between 1979 and 1993 (Nutrient Requirements of Beef Cattle). The same equation was recommended for use in the most recent version of this publication (2016). The equation is sensitive to cow weight, diet digestibility and milk yield. Our objective was to validate the accuracy of this equation using more recent published and unpublished data. Criteria for inclusion in the validation data set included projects conducted or published within the last ten years, direct measurement of forage intake, adequate protein supply, and pen feeding (no tie stall or metabolism crate data). The validation data set included 29 treatment means for gestating cows and 26 treatment means for lactating cows. Means for the gestating cow data set was 11.4 ± 1.9 kg DMI, 599 ± 77 kg BW, 1.24 ± 0.14 Mcal/kg NEm per kg of feed and lactating cow data set was 14.5 ± 2.0 kg DMI, 532 ± 116.3 kg BW, and 1.26 ± 0.24 Mcal NEm per kg feed, respectively. Non intercept models were used to determine equation accuracy in predicting validation data set DMI. The slope for linear bias in the NASEM gestation equation did not differ from 1 (P = 0.07) with a 3.5% positive bias. However, when the NASEM equation was used to predict DMI in lactating cows, the slope for linear bias significantly differed from 1 (P < 0.001) with a downward bias of 13.7%. Therefore, a new multiple regression equation was developed from the validation data set: DMI= (-4.336 + (0.086427 (BW^.75) + 0.3 (Milk yield)+6.005785(NEm)), (R-squared=0.84). The NASEM equation for gestating beef cows was reasonably accurate while the lactation equation underestimated feed intake.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 98-99
Author(s):  
Timothy DelCurto ◽  
Sam Wyffels

Abstract Designing research for beef cattle production in rangeland environments is an ongoing challenge for researchers worldwide. Specifically, creating study designs that mirror actual production environments yet have enough observations for statistical inference is a challenge that often hinders researchers in efforts to publish their observations. Numerous journals will accept “case study” or observational results that lack valid statistical inference. However, these journals are limited in number and often lack impact. Approaches are available to gain statistical inference by creating multiple observations within a common group of animals. Approaches to increasing statistical observations will be discussed in this presentation. Modeling animal behavior and performance on extensive rangeland landscapes is commonly practiced in wildlife ecology and, more recently, has been published in Animal Science journals. Additionally, new technology has made it possible to apply treatments (e.g., supplementation studies) to individual animals on extensive environments where large, diverse herds/flocks of cattle/sheep are managed as a single group. Use of individual animal identification (EID) and feed intake technology has opened a wide range of research possibilities for beef cattle production systems research in rangeland environments. Likewise, global positioning system (GPS) collars and activity monitors have created the opportunity to evaluate animal grazing behavior in remote and extensive landscapes. The use of multiple regression models to evaluate resource use in extensive environments will, in turn, help managers optimize beef cattle production and the sustainable use of forage/rangeland resources. Embracing new technologies such as GPS, activity monitors, EID tags, and feed intake monitors combined with multiple regression modeling tools will aid in designing and publishing beef cattle production research in extensive rangeland environments.


1997 ◽  
Vol 1997 ◽  
pp. 31-31
Author(s):  
A.D. Hall ◽  
W.G. Hill ◽  
P.R. Bampton ◽  
A.J. Webb

Until recently, to enable accurate recording of feed intake, pigs were kept in individual pens. The advent of electronic feeders has allowed accurate records of feed intake and feeding patterns in group housing which is more similar to that found in the production environment. The objectives of this study were to estimate genetic parameters for these feeding pattern traits and their correlations with production traits to show potential benefits in selection.


2021 ◽  
Vol 30 (2) ◽  
pp. 149-156
Author(s):  
O. O Mgbere ◽  
O. Olutogun

Genetic parameters for Absolute Growth Rate (AGR), Relative Growth Rate (RGR) and Absolute Maturing Rate (AMR) at various age interval from birth to maturity in N 'Dama beef cattle raised in the humid Tropics of Nigeria were estimated. Performance data used were accumulated between 1948 and 1964 at Fasola cattle ranch in Oyo, Nigeria and the number of records analysed ranged from 44 to 678. prewering (B - W) growth and maturing rates in N’Dama calves were 0.377 ± 0.009 kg/day (AGR), 0.643 ± 0.006 %/day (RGR) and 0.120 ± 0.003% A/day (AMR) and fluctuated subsequently, following the animals' state of development and certain physiological stress conditions.  At post weaning (W-12), these rates decreased to 0.249 ± 0.049 kg/day, 0.204 ± 0.029 %/day and 0.075 ± 0.014 % A/day for AGR, RGR and AMR respectively. Estimates of heritability at the various age intervals were considered low in these growth traits with values obtained ranging from 0.03 to 0.24 for AGR, 0.03 to 0.21 for RGR and 0.02 to 0.42 for AMR, with high standard errors. The low estimates though, consistent with literature reports were attributed to the poor standard of animal management and production environment at Fasola. It was evident from this study that selection of N'Dama calves based on post weaning (W-12) growth or maturing rates would yield substantial genetic progress. However, improved animal management and production environment on the ranch would not only improve precision of the genetic parameter estimates but would also enhance N 'Dama growth performance generally.


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