scholarly journals Impact of selection for residual feed intake on production traits and behavior of mule ducks

2016 ◽  
Vol 95 (9) ◽  
pp. 1999-2010 ◽  
Author(s):  
L. Drouilhet ◽  
R. Monteville ◽  
C. Molette ◽  
M. Lague ◽  
A. Cornuez ◽  
...  
2015 ◽  
Vol 55 (12) ◽  
pp. 1437 ◽  
Author(s):  
S. Hermesch ◽  
L. Li ◽  
A. B. Doeschl-Wilson ◽  
H. Gilbert

Pig breeding programs worldwide continue to focus on both productivity and robustness. This selection emphasis has to be accompanied by provision of better-quality environments to pigs to improve performance and to enhance health and welfare of pigs. Definition of broader breeding objectives that include robustness traits in addition to production traits is the first step in the development of selection strategies for productivity and robustness. An approach has been presented which facilitates extension of breeding objectives. Post-weaning survival, maternal genetic effects for growth as an indicator of health status and sow mature weight are examples of robustness traits. Further, breeding objectives should be defined for commercial environments and selection indexes should account for genotype by environment interactions (GxE). Average performances of groups of pigs have been used to quantify the additive effects of multiple environmental factors on performance of pigs. For growth, GxE existed when environments differed by 60 g/day between groups of pigs. This environmental variation was observed even on well managed farms. Selection for improved health of pigs should focus on disease resistance to indirectly reduce pathogen loads on farms and on disease resilience to improve the ability of pigs to cope with infection challenges. Traits defining disease resilience may be based on performance and immune measures, disease incidence or survival rates of pigs. Residual feed intake is a trait that quantifies feed efficiency. The responses of divergent selection lines for residual feed intake to various environmental challenges were often similar or even favourable for the more efficient, low residual feed intake line. These somewhat unexpected results highlight the need to gain a better understanding of the metabolic differences between more or less productive pigs. These physiological differences lead to interactions between the genetic potential of pigs for productivity and robustness and the prevalence of specific environmental conditions.


2019 ◽  
Vol 99 (1) ◽  
pp. 191-201 ◽  
Author(s):  
C. Callum ◽  
K.H. Ominski ◽  
G. Crow ◽  
F. Zvomuya ◽  
J.A. Basarab

The effect of residual feed intake adjusted for backfat thickness (RFIfat) on heifer pregnancy rate and subsequent lifetime productivity was examined in 867 beef females that were ranked as low, medium, or high RFIfat. Age at first calving, weaning weight of first calf, and most probable producing ability for birth weight (MPPAbw) and weaning weight (MPPAww) were calculated to assess first parity heifer productivity. The effect of heifer RFI adjusted for backfat (RFIfat; n = 532) on subsequent lifetime cow productivity (n = 415) was calculated based on kg of calf weaned per cow bred per year. A total lifetime productivity measure (n = 218) were also calculated as total calf weaning weight (kg) output per cow culled. RFI rank had no significant effect on pregnancy rate, when adjusted for season and site differences (P = 0.33). No significant correlations (P < 0.05) were observed between MPPAww and RFI, RFIfat, RFI adjusted for backfat and feeding event frequency (RFIfat & activity), or age at first calving. A negative trend (P < 0.10) between RFI, RFIfat, and MPPAbw calculated from first parity pregnancy rate and production traits was no longer apparent when adjusted for RFIfat & activity. These results suggest that selection for low RFI replacement heifers has no impact on their first parity pregnancy rate and productivity or on subsequent cow productivity.


2020 ◽  
Vol 98 (Supplement_2) ◽  
pp. 75-76
Author(s):  
Camren l Maierle ◽  
Andrew R Weaver ◽  
Eugene Felton ◽  
Scott P Greiner ◽  
Scott A Bowdridge

Abstract Residual feed intake (RFI) is quickly becoming the preferred measurement of efficiency in many species due to its inherent independence of most other important production traits. Making meaningful improvement in feed efficiency of sheep will require a consistent methodology to accurately identify efficient individuals. Due to difficulty in measuring this trait efforts must be made to incorporate efficiency data in large-scale genetic evaluations. The aim of this study was to evaluate lambs in a feedlot with large-scale genetic evaluations for feed efficiency calculated by residual feed intake (RFI) utilizing a Growsafe™ system. RFI was calculated by subtracting expected intake from actual intake. Expected intake was determined by regressing metabolic body size of mid-test weight. Regression determined ADG on actual intake for individuals in the population. Texel (n = 58) and Katahdin (n = 118) lambs were placed in a feedlot and fed in separate feeding trials, a complete pellet ad libitum as the sole source of nutrition. In this environment Texel and Katahdin lambs had expected ADG values (0.27 kg/day, 0.32 kg/day respectively) and actual intake data (2154.17 g/day, 1909.33 g/day respectively. After a period of adaptation, Texel average intake was determined over a period of 27 consecutive days and used to calculate individual RFI within the test population. Observable ranges of RFI (-0.62 – +0.62) were seen in the Texel lambs. At the start of the Katahdin trial lambs were separated by sex and FEC treatment. After a period of adaptation, Katahdin average intake was determined over a period of 42 consecutive days and used to calculate individual RFI within the test population. Observable ranges of RFI (-0.53 – +0.50) were seen in the Katahdin lambs as well. In both feeding trials RFI appeared to be normally distributed. Use of this technology may be useful in identifying superior individuals for feed efficiency.


2011 ◽  
Vol 89 (1) ◽  
pp. 258-266 ◽  
Author(s):  
L. J. Sadler ◽  
A. K. Johnson ◽  
S. M. Lonergan ◽  
D. Nettleton ◽  
J. C. M. Dekkers

2016 ◽  
Vol 94 (suppl_2) ◽  
pp. 108-109 ◽  
Author(s):  
D. J. Hewitt ◽  
C. F. M. de Lange ◽  
T. Antonick ◽  
J. C. M. Dekkers ◽  
A. R. Pendleton ◽  
...  

2013 ◽  
Vol 91 (6) ◽  
pp. 2542-2554 ◽  
Author(s):  
R. Saintilan ◽  
I. Mérour ◽  
L. Brossard ◽  
T. Tribout ◽  
J. Y. Dourmad ◽  
...  

Meat Science ◽  
2015 ◽  
Vol 101 ◽  
pp. 123
Author(s):  
E.K. Arkfeld ◽  
J.E. Berger ◽  
E.R. Hamman ◽  
J.M. Young ◽  
R.C. Johnson ◽  
...  

2018 ◽  
Vol 96 (suppl_2) ◽  
pp. 256-257
Author(s):  
S A Hershorin ◽  
R Manjarin ◽  
A M Emond ◽  
S Id-Lahoucine ◽  
P Fonseca ◽  
...  

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