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THE GENETIC RELATIONSHIP AMONG LAMB SURVIVAL, BIRTH COAT TYPE, BIRTH WEIGHT

AND 42-DAY BODY WEIGHT IN A SOUTH AFRICAN FINE WOOL MERINO STUD

 

W.J. Olivier1, S.W.P. Cloete2 & A.C. Greyling3


1Grootfontein Agricultural Development Institute, Private Bag X529, Middelburg (EC), 5900

2Institute for Animal Production: Elsenburg, Private Bag X1, Elsenburg, 7607

3Cradock Experimental Station, PO Box 284, Cradock, 5880

E-mail: Willem Olivier

 


INTRODUCTION

The production of slaughter lambs is the most important source of income for South African Merino farmers. An increase in slaughter lamb production can be obtained through selection for increased growth rate or through an increase in the number of lambs that survived until weaning and slaughter age. Increasing the number of lambs that survive until weaning can have a quick and immediate effect on efficiency of the enterprise.

 

The survival of a Merino lamb is linked directly to its genetic makeup and management factors. Most of the management problems can be rectified with immediate effect, while changing the genetic makeup of lambs is a medium to long term objective and of utmost importance. Changing the genetic makeup of the lambs will lead to more viable lambs being born.

 

Three traits can possibly be linked to the survival of Merino lambs and can therefore be included in selection programs, namely birth coat type, birth weight and 42-day body weight. Before these traits can be included in selection programs, the genetic relationship among these traits and lamb survival must be quantified. The aim of this study is therefore to quantify the genetic relationship among lamb survival, birth coat type, birth weight and 42-day body weight through deriving genetic parameters for these traits in a South African fine wool Merino stud.

 

MATERIALS AND METHODS

The Cradock Fine Wool Merino Stud was established in 1988 as described by Olivier et al. (2006). Ewes were bought from Merino farmers with the finest clips throughout South Africa and four fine wool rams were imported from Australia. Data collected on 5769 ram and ewe lambs that were born alive within this stud from 1988 to 2003 were used for the analyses.

 

The traits included in the analysis were birth weight, birth coat type, 42-day body weight and lamb survival. Lamb survival was defined as the number of lambs born alive that survived until weaning. This trait was coded as a binary trait with two categories, namely lambs born alive that died before weaning (coded as 1) and lambs that survived until weaning (coded as 2).

 

Birth coat types were recorded since 1992 and assessed on a scale from 1 to 4 with 1 being woolly and 4 being hairy. Records from lambs without a birth weight were discarded from the data set. All birth weights were recorded within 24 h of birth. The 42-day body weight was measured at an average age (± s.d.) of 47 ± 6 days.

 

The number of records, means, standard deviations, coefficient of variations, minimums and maximums of the respective traits are summarised in Table 1.

 

Table 1. Descriptive statistics for birth weight, birth coat type, 42-day body weight and lamb survival

 

Birth weight

(kg)

Birth coat types

42-day body weight (kg)

Lamb survival

Number of records

5769

4456

5352

5769

Mean

4.47

1.92

16.09

1.91

Standard deviation

0.87

0.81

3.69

0.29

Coefficient of variation

19.50

42.12

22.94

15.01

Minimum

1.10

1

4.40

1

Maximum

8.00

4

30.20

2

Birth coat types: 1 – woolly; 2 – more woolly than hairy; 3 – more hairy than woolly; 4 – hairy

Lamb survival (lambs born alive): 1 – dead at weaning; 2 – alive at weaning

 

The means, standard deviations, coefficient of variations, minimums and maximums for the respective traits were obtained with the PROC MEANS procedure of SAS, and significance levels for the fixed effects were obtained with the PDIFF option under the PROC GLM procedure of SAS (Littell et al., 2002). The effects tested included year of birth, sex, age of dam in years and birth status. The age of the animals (linear regression) at 42 days of age was also tested for significance. Only effects that had a significant effect were included in the final model for each trait.

 

The estimation of variance components and genetic parameters was done with THRGIBBSF90 (Misztal et al., 2002). This software can be used to estimate variance components and genetic parameters in threshold animal mixed models for any combination of categorical and continuous traits (Lee et al., 2002). POSTGIBBSF90 was used for Post Gibbs analysis to obtain solutions for the random effects (Misztal et al., 2002). A single chain of 150 000 cycles was run and the first 50 000 cycles used as the burn-in period. Every 10th sample after the burn-in period was stored, giving a total of 10 000 samples for the computation of posterior means and standard deviations.

 

RESULTS AND DISCUSSION

It is evident from Table 1 that the average birth weight of the lambs that were born alive was 4.47 kg ranging from 1.10 kg to 8.00 kg and the average 42-day body weight was 16.09 kg and it ranged from 4.40 kg to 30.20 kg. The average birth coat types (1 being more woolly and 4 being more hairy) and lamb survival (1 for lambs that died before weaning and 2 for lambs that survived until weaning) on the underlying scale were 1.92 and 1.91 respectively. This means that more than 90 % (5247 lambs) of the lambs born alive survived until weaning in the Cradock fine wool Merino stud.

 

The point estimates for direct heritabilities (h2), maternal heritabilities (m2), maternal permanent environment effect (c2) and the correlation between the direct and maternal genetic effects (ram) on the underlying scale for birth coat type and lamb survival, as well as for birth weight and 42-day body weight are presented in Table 2.

 

The heritability for lamb survival estimated in this study falls within the range of the values cited by Safari et al. (2005) that ranged from 0.00 (Olivier et al., 1998 – threshold model) to 0.11 (Hall et al., 1995 – threshold model). However, Cloete et al. (2008) reported a higher heritability of 0.27 for lamb survival obtained with THRGIBBSF90 (Misztal et al., 2002). The maternal heritability estimated in this study is higher than the estimate (0.14) obtained by Cloete et al. (2008), as well as the range of values reported by Safari et al. (2005).

 

Table 2. The direct heritability (h2), maternal heritability (m2), maternal permanent environment effect (c2) and correlation between direct and maternal genetic effects (ram) for the different traits (± s.e.)

 

h2

c2

m2

ram

Birth weight

0.19 ± 0.05

0.06 ± 0.02

0.34 ± 0.08

-0.26 ± 0.12

Birth coat

0.19 ± 0.02

0.03 ± 0.01

0.18 ± 0.07

 

42-day body weight

0.06 ± 0.06

0.02 ± 0.01

0.37 ± 0.13

-0.04 ± 0.06

Lamb survival

0.09 ± 0.05

0.01 ± 0.00

0.26 ± 0.16

-0.14 ± 0.10

 

The genetic correlations among the different traits are summarised in Table 3. It is evident from this table that all the correlations were low to moderate among the respective traits.  Cloete et al. (2008) also reported a low negative genetic correlation between birth weight and lamb survival. Sawalha et al. (2007) also reported an unfavourable genetic correlation between lamb viability (coded as 0 for survivors and 1 for animals that had died) and birth weight of 0.21. The relationship between lamb survival and birth weight is complicated and difficult to explain due the non-linear relationship that exists between these two traits.  This relationship suggest that it would be better to produce lambs with intermediate birth weights, as the extreme to both sides, i.e. too low or too heavy birth weights, will decrease lamb survival. Small and ill thrifty lambs will most probably die due to starvation and hypothermia, whereas dystocia will be the biggest problem in lambs that are too big and heavy.

 

Table 3. The genetic correlations among the different traits (± s.e.)

 

Birth coat type

42-day body weight

Lamb survival

Birth weight

0.20 ± 0.26

0.44 ± 0.33

-0.31 ± 0.19

Birth coat type

 

0.35 ± 0.76

0.19 ± 0.38

42-day body weight

 

 

0.11 ± 0.23

 

The low genetic correlation between 42-day body weight and lamb survival suggest the improvement in the growth rate of lambs would not have a huge effect on the number of lambs that survived until weaning.  The effect of the ewe is bigger than the lamb’s own performance at this stage of its life. It might be a more viable option to select ewes with better mothering ability, because lambs are still largely dependant of the milk production of the ewes.

 

The genetic correlation between lamb survival and birth coat type in this study, support findings in the literature that lamb survival of Merino lambs is not highly related to the birth coat types (Cloete et al., 2003).

 

The low heritabilities for lamb survival estimated by Olivier et al. (1998) and Snyman et al. (1998) suggested that it would not be possible to improve lamb survival genetically. However, the present study, as well as Cloete et al. (2008), found that it would be possible to improve lamb survival genetically.

 

CONCLUSIONS

It can be concluded that it would be possible to improve lamb survival genetically. This can be achieved by selection for traits directly related to lamb survival in ewes (i.e. rearing ability or multiple rearing ability) by culling of unproductive ewes that failed to rear lambs.  The scope for indirectly selecting for lamb survival by considering birth weight, birth coat score or 42-days weight appears to be limited.

 

REFERENCES

Cloete, S.W.P., Misztal, I. & Olivier, J.J., 2009. Genetic parameters and trends for lamb survival and birth weight in a Merino flock divergently selected for multiple rearing ability. J. Anim. Sci. (Submitted).

Cloete, S.W.P., Olivier, J.J., Van Wyk, J.B., Erasmus, G.J. & Schoeman, S.J., 2003. Genetic parameters and trends for birth weight, birth coat score and weaning weight in Merino lines divergently selected for ewe multiple rearing ability. S. Afr. J. Anim. Sci. 33, 248-256.

Hall, D.G., Fogarty, N.M. & Gilmour, A.R., 1995. Performance of crossbred progeny of Trangie Fertility Merino and Booroola Merino rams and Poll Dorset ewes. I. Lamb birth weight, survival and growth. Aust. J. Exp. Agric. 35, 63-66.

Lee, D., Misztal, I., Bertrand, J.K. & Rekaya, R., 2002. National evaluation for calving ease, gestation length and birth weight by linear and threshold model methodologies. J. Appl. Gen. 43, 209-216.

Littell, R.C., Freud, R.J. & Struop, W.W., 2002 SAS-system for linear models, 4th Ed. SAS Institute. Inc. Cary, N.C., USA.

Misztal, I., Tsuruta, S., Strabel, T., Auvray, B., Druet, T. & Lee, D.H., 2002. BLUPF90 and related programs (BGF90). Proc. 7th World Congr. Gen. Appl. Livest. Prod., Montpellier, France. CD communication 28-07.

Olivier, W.J., Olivier, J.J., Cloete, S.W.P. & Van Wyk, J.B., 2006. Genetic analysis of the Cradock fine wool Merino stud. Proc. 8th World Congr. Gen. Appl. Livest. Prod. , Belo Horizonte, 13-18 Augustus, 84.

Olivier, W.J., Snyman, M.A., Van Wyk, J.B. & Erasmus, G.J., 1998. Genetic parameter estimates for fitness traits in South African Merino sheep. Livest. Prod. Sci. 56, 71-77.

Safari, E., Fogarty, N.M. & Gilmour, A.R., 2005. A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep. Livest. Prod. Sci. 92, 271-289.

Sawalha, R.M., Conington, J., Brothersone, S. & Villanueva, B., 2007. Analyses of lamb survival of Scottish Blackface sheep. Anim. 1, 151-157.

Snyman, M.A., Erasmus, G.J. & Van Wyk, J.B., 1998. The possible improvement of reproduction and survival rate in Afrino sheep using a threshold model. S. Afr. J. Anim. Sci. 28, 120-124.

 

Published

Grootfontein Agric 9 (1)