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GENETIC PARAMETERS FOR BODY WEIGHT OF SOUTH AFRICAN ANGORA KIDS AND YOUNG GOATS

 

M.A. Snyman

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

E-mail: Gretha Snyman

 

 

INTRODUCTION

Body weight is one of the most important selection criteria in almost any sheep and goat breeding program. In many sheep breeds, continuous selection for increased body weight has led to a situation where a further increase in body weight is contra-indicated. This is, however, not the case in Angora goats, where there is still a positive relationship between ewe body weight and reproductive performance (Snyman, 2010a). Many of the problems encountered in Angora goats, such as high kid mortality rates (Snyman, 2010b), poor post weaning growth rates (Snyman, 2007) and low reproductive rate of young ewes (Snyman, 2010a) could be linked to body weight. Body weight should therefore be one of the most important criteria in the selection program of Angora goats.

There is a dearth of information on genetic parameters of body weight and growth traits in goats in general (Bosso et al., 2007; Boujenane & Hazzab, 2008; Zhang et al., 2008; Gowane et al., 2011; Rashidi et al., 2011) and in Angora goats specifically, particularly with regard to the influence of maternal effects on these traits (Snyman & Olivier, 1996). The objectives of this study were, firstly, to determine the most appropriate models of analysis for body weight of Angora goat kids at different ages, and secondly, to estimate genetic parameters for these traits. Information generated by this study will be applied for the estimation of breeding values for growth performance of animals in the South African Angora goat industry.

 

MATERIALS AND METHODS

The data were collected on the 2000- to 2009-born kids of 11 different Angora goat studs. The data file comprised of 27485 records after editing. Traits analysed were birth weight (BW), weaning weight (WW) and body weight at 8, 12 and 16 months of age (W8, W12 and W16). Birth weight, weaning weight and 8-month body weights were recorded on both male and female kids, while 12- and 16-month body weights were only recorded for the female kids, with the exception of two studs where male kids were also recorded.

The data were initially analysed by least-squares means methods to identify the non-genetic effects, which contributed significantly to variation, using the General Linear Model procedure of the SAS computer package (SAS, 2009). The fixed effects included in the final model for BW were herd-year of birth (HY), sex (male and female), birth status of the kid (1, 2 or 3) and age of dam (1 to 10 years of age). For WW, W8, W12 and W16, fixed effects for herd-year-rearing group (HYGR), sex, rearing status of the kid (11, 21, 22, 31, 32, 33), age of dam and a linear covariate for age of the kid at weighing (age in days), were included.  The reason for including the combined HYGR-effect is that different rearing strategies were followed in the different studs from birth till weaning and after weaning and the rearing groups in the different studs were not the same (Gerstmayr & Horst, 1995). No sire by herd interaction was included, as the structure of the data set did not facilitate the inclusion of such an interaction due to limited sire links among the studs.

(Co)variance components were estimated using the ASReml program of Gilmour et al. (2009). Single-trait animal models were fitted for all traits. Direct additive and maternal additive genetic effects, with or without a covariance between them, and maternal permanent environmental effects were tested in different combinations to yield six models, which were fitted for all traits. Subsequently, multi-trait analyses were done to estimate covariance components and correlations among BW, WW, W8, W12 and W16, using the most suitable model for each trait, as determined under single-trait analyses.

 

RESULTS AND DISCUSSION

The number of records analysed for each trait, as well as the average and coefficient of variation for each trait, are summarised in Table 1. The reason why it seems as if the ram kids lost body weight from 8 to 12 months of age, is that in those studs where body weight of the ram kids were recorded after 8 months of age, the rams were not supplemented after weaning. The estimated genetic parameters for the traits analysed are summarised in Table 2.

 

Table 1. Description of the final data set on body weight of Angora kids

Trait

Rams

Ewes

CV (%)

Rams (n)

Ewes (n)

Birth weight (kg)

3.06 ± 0.02

2.84 ± 0.02

18.61

11015

10627

Weaning weight (kg)

16.41 ± 0.24

15.11 ± 0.18

25.41

11903

11718

8-month body weight (kg)

25.39 ± 0.55

17.34 ± 0.30

30.34

5787

6517

12-month body weight (kg)

24.02 ± 0.30

19.64 ± 0.29

25.50

1890

4786

16-month body weight (kg)

29.15 ± 0.46

22.79 ± 0.45

26.31

1440

4787

 

 

Table 2. Genetic parameter estimates for body weight from birth to 16 months of age

Parameter

Birth weight

Weaning weight

8-month body weight

12-month body weight

16-month body weight

h2

0.22 ± 0.02

0.20 ± 0.02

0.12 ± 0.02

0.34 ± 0.04

0.58 ± 0.03

m2

0.10 ± 0.03

0.09 ± 0.02

0.03 ± 0.02

0.06 ± 0.03

 

p2

0.13 ± 0.02

0.11 ± 0.02

0.06 ± 0.02

0.04 ± 0.03

 

ram

-0.38 ± 0.10

 

 

 

 

Direct heritability (h2), maternal heritability (m2), maternal permanent environmental effect (p2), direct-maternal correlation (ram)

 

For birth weight, the best model included direct additive and maternal additive genetic effects, with a covariance between them, as well as a maternal permanent environmental effect. The model including a direct additive and maternal additive genetic effect, without a covariance between them, as well as a maternal permanent environmental effect, was the most appropriate model for WW, W8 and W12. For W16, only direct additive genetic effects were included in the best model.

Limited information is available regarding heritability of early growth traits in Angora goats. All the available estimates are for body weight at 8 months and older, and most of these are based on sire model analyses (Yalςin, 1982; Nicoll, 1985; Nicoll et al., 1989; Gifford et al., 1991; Snyman & Olivier, 1996; Snyman & Olivier, 1999). The heritabilities estimated in this study with animal models fall within the range (0.10 to 0.47) reported in the above-cited literature for body weight in Angora goats.

Maternal effects and direct additive effects in birth weight and weaning weight were equally important, as is evident from the estimates of 0.22 and 0.20 for direct heritability, 0.10 and 0.09 for maternal heritability and 0.13 and 0.11 for dam permanent environment for birth weight and weaning weight respectively. An unfavourable correlation of –0.38 was estimated between direct and maternal genetic effects. Birth weight was the only trait in the study where ram was significant. No other ram estimates are available in the literature for any traits in Angora goats. Negative correlations were also reported for early body weight in Boer goats (Zhang et al., 2008), Draa goats (Boujenane & Hazzab, 2008), Sirohi goats (Gowane et al., 2011) and Markhoz goats (Rashidi et al., 2011). However, conflicting estimates, pertaining to sign and magnitude, were reported for a wide range of sheep breeds, as summarised by Safari & Fogarty (2003).  Apart from discrepancies caused by different models applied and real differences between populations analysed, differences in data structure and size could play an important role (Robinson, 1996; Meyer, 1992; Gerstmayer, 1991). According to Maniatis & Pollott (2003), the estimation of the correlation between direct and maternal genetic effects is dependent on key pedigree relationships. A high proportion of both dams and maternal grand dams with their own records are essential. As the data set used for the present study was collected over a period of only ten years, it could lack the optimum pedigree structure for the accurate and reliable estimates of direct-maternal covariance components.

Similar genetic parameters were estimated for WW than for BW. Estimates of direct heritability increased from 0.12 for W8, to 0.34 for W12 and 0.58 for W16. This is in accordance with estimates obtained with sheep (Snyman et al., 1995; Safari & Fogarty, 2003). The total maternal component remained constant at approximately 0.10 for W8 and W12.

Direct genetic and phenotypic correlations among body weights at the different ages are presented in Table 3, while maternal genetic correlations between birth weight and the other recorded body weights are given in Table 4.

 

Table 3. Direct genetic (above diagonal) and phenotypic (below diagonal) correlations among body weights at different ages

Trait

Birth weight

Weaning weight

8-month body weight

12-month body weight

16-month body weight

Birth weight

-

0.36 ± 0.07

0.29 ± 0.10

0.35 ± 0.11

0.57 ± 0.09

Weaning weight

0.29 ± 0.01

-

0.93 ± 0.02

0.82 ± 0.02

0.73 ± 0.03

8-month body weight

0.25 ± 0.01

0.60 ± 0.01

-

0.97 ± 0.01

0.94 ± 0.01

12-month body weight

0.24 ± 0.01

0.65 ± 0.01

0.83 ± 0.01

-

0.98 ± 0.01

16-month body weight

0.24 ± 0.01

0.54 ± 0.01

0.76 ± 0.01

0.80 ± 0.01

-

 

 

Table 4. Maternal genetic correlations between birth weight and body weight at different ages

Trait

Weaning weight

8-month body weight

12-month body weight

16-month body weight

Birth weight

0.44 ± 0.04

0.61 ± 0.08

0.64 ± 0.11

0.55 ± 0.19

 

Low to medium positive direct genetic correlations were estimated between birth weight and body weights recorded at a later stage in life. High positive direct genetic correlations were estimated among WW, W8, W12 and W16. Similar correlations were obtained among early body weights for other goat breeds (Bosso et al., 2007; Boujenane & Hazzab, 2008; Zhang et al., 2008; Gowane et al., 2011; Rashidi et al., 2011). The maternal genetic correlations obtained between birth weight and the other body weights were medium to high. Phenotypic correlations among the traits ranged from low to high.

 

CONCLUSIONS

Selection of young replacement ewes takes place at 16 to 18 months of age in the South African Angora goat industry. The high heritability estimated for 16-month body weight indicated that selection for increased body weight at this age should be successful. Furthermore, selection for increased 16-month body weight should also have a positive effect on body weight earlier in life, and could contribute indirectly to improved kid survivability.

As reproduction and body weight should be included in a selection program for Angora goats, it is important that the relationship between the direct and maternal additive effects be clarified. The importance of a sufficiently structured and related pedigree, especially on the part of the dams and maternal grand dams, has again been highlighted in this study. As this is one of the constraints of this data set, it is important that data collection in the Angora goat industry should continue until a suitably structured data set has been built up, which could be used for the estimation of multi-trait breeding values for the industry.  

 

ACKNOWLEDGEMENTS

The author wants to convey her sincere appreciation to the participating Angora goat breeders for their collaboration in this project and to Mohair South Africa for funding of the project.

 

REFERENCES

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Published

Grootfontein Agric 12 (1) : 24