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EVALUATION OF EWE PRODUCTIVITY MEASURES

by

Willem Johannes Olivier

Thesis submitted to the faculty of Agriculture,

Department of Animal Science,

University of the Orange Free State.

In partial fulfilment of the requirements for the degree

MAGISTER SCIENTIAE AGRICULTURAE

 

Supervisor       :      Dr. M.A. Snyman

Co-supervisor   :      Prof. J.B. van Wyk

Bloemfontein, December 1997

 

TABLE OF CONTENTS

PREFACE

1.   INTRODUCTION

2.   DESCRIPTION OF THE GROOTFONTEIN MERINO STUD  AND THE CARNARVON MERINO FLOCK

2.1   History, management and selection procedure of the Grootfontein Merino stud

2.2   History, management and selection procedure of the Carnarvon Merino flock

2.3   Data description

3.   GENETIC PARAMETER ESTIMATES FOR FITNESS TRAITS

3.1   Introduction

3.2   Material and methods

3.2.1   Data

3.2.2   Sources of non-genetic variation

3.2.3   Threshold model analysis

3.3   Results and discussion

3.3.1   Thresholds and solutions for Afixed@ effects

3.3.2   Heritabilities

3.3.3   Sire breeding values

3.4   Conclusions

4.   DIRECT AND CORRELATED SELECTION RESPONSE PER GENERATION IN TOTAL WEIGHT OF LAMB WEANED

4.1   Introduction

4.2   Material and methods

4.2.1   Data

4.2.2   Statistical analysis

4.3   Results and discussion

4.4   Conclusion

5.   GENERAL CONCLUSIONS

ABSTRACT

OPSOMMING

REFERENCES

 

PREFACE

This dissertation is presented in the form of two separate scientific publications (Olivier et al., 1998a; Olivier et al., 1998b) augmented by a general introduction, a chapter on the history of the Grootfontein Merino stud and the Carnarvon Merino flock and general conclusions in an effort to eventually create a single unit.

The author wishes to express his sincere appreciation and gratitude to the following persons and institutions:

 

CHAPTER 1

INTRODUCTION

Selection objectives and criteria in sheep farming enterprises differ from breed to breed, country to country, and even from farm to farm. Reproduction and survival rate, however, are the only traits that are universally important, regardless of whether the sheep enterprise is based on the production of wool, mutton, milk or pelts. These two traits are also the most important factors determining the efficiency of lamb production (Large, 1970;  Snyman et al., 1997c). There is more potential for increasing both biological and economic efficiency of lamb production through genetic improvement in reproduction than in either growth rate or body composition (Dickerson, 1978). Genetic improvement of reproduction rate in sheep is being sought in many countries, by means of both selection and crossbreeding (Turner, 1978).

The efficiency of lamb production can be improved through an increase in the number of lambs marketed per ewe per year (Shelton, 1971). Clarke (1972) and Turner (1978) reported that selection for litter size was successful, but genetic gains were limited because reproduction traits are only observable in females of reproductive age. Increased accuracy of selection, and therefore increased response from selection, for litter size in sheep can be obtained by using information from correlated traits (Waldron & Thomas, 1992a). This method of selection could lead to an increased improvement of 155% in litter size, compared to selection on an individual=s litter size record alone (Waldron & Thomas, 1992b).

Although reproductive performance of a ewe flock is one of the main factors contributing to the monetary value of a flock, reproduction traits have in the past largely been ignored in selection programmes. This is especially the case for Merino sheep, as they are pre-eminently wool producers. The accurate measurement of reproductive performance at an early age and the lack of suitable computer software, were some of the main difficulties, resulting in reproduction traits being ignored in selection programmes. The availability of modern statistical software, and compatible computer hardware, has made it possible to obtain more accurate estimates of genetic parameters and breeding values for reproduction traits. Sheep in South Africa is to a large extent kept under extensive farming conditions in harsh, arid environments. It is therefore a difficult and time consuming practise to record reproductive performance under these extensive farming conditions accurately.

The traits that natural selection favours are survival and reproduction, collectively called fitness. The fitness of an individual is the contribution of genes that it makes to the next generation, or the number of its progeny represented in the next generation (Falconer & Mackay, 1996).  Subsequently, animals who have more off-spring are fitter in the Darwinian sense (Lerner, 1961). The goal of natural selection cannot be defined in any way except by saying that natural selection favours the fitter animals. It was noted by Crow & Kimura (1956) that fitness may decrease under natural selection in the presence of particular circumstances involving change in the degree of inbreeding and in the selection coefficient.

 

Fig.  1.1. Some components of the lifetime reproduction of an ewe, to show the variation hierarchy of causes of variation. Variation of each of these metric traits is associated, to a greater or lesser degree, with variation of lifetime reproduction. This figure was adapted from Falconer & Mackay (1996).

 

Fig 1.1 illustrates the hierarchy of the traits contributing to the lifetime reproduction of ewes. The reproductive performance of a ewe can be divided into two main components, namely, the total number of lambs born and the quality of these lambs. The latter may be measured as the individual weaning weight of the lambs. The variation in these two components, if measured properly, would account for all the variation in the reproductive performance of a ewe. The variation in these two components can in turn be attributed to other traits, some of which are shown in Fig.1.1. Some of these traits would again be influenced by other traits. The best measurement of a ewe=s reproductive performance is therefore the composite trait ewe productivity, which can be defined as the total weight of lamb weaned per ewe mated.

Individual components that influence the productivity of a ewe could be included in a selection programme as selection criteria. Each of these components has a direct impact on ewe productivity, as illustrated by Fig.1.1. In any sheep enterprise, wool or mutton production, it is important to maintain the quality-quantity equilibrium, especially in the harsh and arid environments of South Africa. In light of the fact that the Merino is pre-eminently a wool producer, it is important for a breeding ewe to produce a substantial amount of good quality wool, while at the same time rearing viable lambs with a good quality carcass. In areas where the lambing percentages are already high, an increase in the number of lambs born would be undesirable, as it may lead to less and poorer quality wool produced by the ewe (Kennedy, 1967; Shelton & Menzies, 1968), as well as the weaning of inferior lambs.

In animal production many of the important traits, such as fertility, fecundity, litter size and survival rate in sheep, display a discontinuous distribution of phenotypes. Breeding tests show in these instances features that cannot be readily explained by simple strict Mendelian inheritance (Gianola, 1982). The understanding of the inheritance of such traits lies in the idea that the trait has an underlying continuity with a threshold which imposes a discontinuity on the visible expression of the trait (Falconer & Mackay, 1996). The relationship between polygenes and the expression of discontinuous traits comes about through the establishment of thresholds. That is, those polygenically determined genotypes that have values below the threshold show no expression of the trait (Strickberger, 1990). Traits that exhibit such categorical phenotypes are known as  threshold traits (Wright, 1934).

In the past general linear model theory was the most frequently used for analysis of both continuous and discontinuous animal production data (Harvey, 1975; Henderson, 1953; Henderson, 1973). The problem when analysing discontinuous data with linear procedures, is that the method of analysis is based on continuous phenotypic distribution and does not take the discontinuity of threshold traits into consideration. It was argued by Thompson (1979) and Gianola (1980) that, at least in theory, methodology for continuous data is not suitable in the discrete case. Nonlinear approaches for analyses of categorical traits have been proposed by Gianola &Foulley (1983), Gilmour (1983), Harville & Mee (1984), Foulley et al. (1987) and Tempelman (1993) to obtain more accurate estimates of genetic parameters and better predictors of genetic merit of candidates for selection. This nonlinear approach is based on the threshold concept (Wright, 1934; Dempster & Lerner, 1950; Bulmer, 1980; Gianola, 1982).

Estimates obtained utilizing threshold models may lead to increased responses from selection for reproduction traits in sheep, compared to linear model estimates (Matos et al., 1997). The advantage of using threshold over linear methodology in breeding programmes increases as the heritability of the trait decreases (Matos et al., 1997). Olesen et al. (1994) found that the threshold model seemed more valuable for genetic analysis of litter size in sheep than a linear model. Gianola (1982) argued that the main theoretical reason for not using BLUP (Best Linear Unbiased Prediction) with categorical data is that breeding values and residuals are not independent of each other. Threshold procedures should therefore be more suitable when analysing reproduction data, as threshold model sire breeding values are expressed in units of residual standard deviation of the underlying scale.

The main objective in practice is to improve the reproduction performance of a flock and  the best measure of the reproduction performance of a flock is probably total weight of lamb weaned per ewe over her lifetime (Snyman et al., 1997c). Reproductive performance could be increased by accelerated lambing, artificial rearing, hormonal treatment, etc. (Littlejohn, 1977), but this would lead to higher overhead costs, extra labour needs and the requirement of more specialised facilities ( Nugent III & Jenkins, 1991). Some of the factors determining total weight of lamb weaned per ewe are ovulation rate, mothering ability and milk production of the ewe and growth rate and viability of the lamb. Each of these factors could be included in a selection programme as a selection criterion. This objective could be reached by either direct or indirect selection for reproduction traits. Indirect selection on, for instance, number of lambs born will increase the ovulation rate of a ewe, but mothering ability and milk production of the ewe or the growth rate and viability of the lamb would not necessarily be increased. The same applies for indirect selection on number of lambs weaned or weaning weight. However, direct selection on the composite trait total weight of lamb weaned per ewe per year addresses all of the above mentioned factors (Snyman et al., 1997c). The genetic merit of an animal is usually the function of several interrelated traits. This relationship may be positively or negatively correlated genetically, phenotypically and environmentally (Lax & Jackson, 1987). The importance of genetic correlations are  enhanced by the fact that stud breeders and commercial farmers must improve their stock for several traits simultaneously. Knowledge of genetic and phenotypic covariances is therefore important to evaluate animals for multiple traits (Hazel, 1943; Henderson & Quaas, 1976) and to predict the correlated responses to selection (Falconer & Mackay, 1996).

The purpose of this study was to evaluate different ewe productivity measures and to determine the most efficient selection criterion to improve total weight of lamb weaned per ewe mated in the Grootfontein Merino stud and the Carnarvon Merino flock.

Due to the fact that several of the component traits of total weight of lamb weaned are categorical traits, it was decided to evaluate these traits with threshold procedures, as it is the method of choice for discontinuous data. The main objective of the first part of this study were therefore to estimate heritabilities and determine the range of sire breeding values for these component traits. The traits included were fertility (whether a ewe lambed or not), fecundity (number of lambs born to a ewe that lambed), litter size at birth (number of lambs born to a ewe mated), litter size at weaning (number of lambs weaned to a ewe mated) and survival rate (whether a lamb born alive, was dead or alive at weaning).

As previously discussed, the best measurement of a ewe=s lifetime reproduction appears to be the composite trait total weight of lamb weaned per ewe mated. For the purpose of the second part of this study, TWW (total weight of lamb weaned per ewe mated), NLB (number of lambs born per ewe mated) and NLW (number of lambs weaned per ewe mated) over the first three lambing opportunities of a ewe were taken as an indication of lifetime reproduction efficiency. The traits NLB and NLW were treated as continuous traits for this part of the study, as these traits are a combination of three separate lambing opportunities, which extended the number of categories and resulted in a near normal distribution. The main objective in this part of the study was to calculate the direct and correlated selection response per generation in total weight of lamb weaned per ewe mated (TWW), number of lambs born (NLB) and number of lambs weaned (NLW) over three lambing opportunities and individual weaning weight (WW) of each lamb for selection based on any of these four traits. For this purpose, genetic and phenotypic correlations among these traits were estimated.

 

CHAPTER 2

DESCRIPTION OF THE GROOTFONTEIN MERINO STUD AND THE CARNARVON MERINO FLOCK

The data collected on the Grootfontein Merino stud and the Carnarvon Merino flock were used in this study. These two Merino flocks are unique in the sense that they are the only flocks in South Africa for which such data sets are available. Further important points to note is that the data sets of these two flocks used in the analysis, are not genetically link and they were kept under widely differing environments, and were subjected to different selection objectives and management systems.

 

2.1 History, management and selection procedures of the Grootfontein Merino stud

The Grootfontein Merino stud (GMS) is kept at the Grootfontein Agricultural Development Institute near Middelburg (31°28'S,25°1'E) in the North-western Karoo region of South Africa. The average annual rainfall at Middelburg is 360mm. Acocks (1988) described the veld type as False Karroid Broken Veld. The GMS is run under relatively favourable nutritional conditions, which includes irrigated pastures and supplementary feeding.

The basis of the Grootfontein Merino stud were formed in 1955 by 227 ewes bought from local breeders, 63 ewes donated by local breeders and 105 ewes from the three selections lines situated at Grootfontein at the time. In the same year four rams were imported from Australia for use in the newly founded Grootfontein Merino stud (stud no. 888)(Olivier, 1989). In 1962 and 1964 a further two rams and 11 ewes were bought from local breeders. Since 1966 only nine rams were brought into the stud, namely:

1966         -           Trumps Merino stud (stud no. 1600)

1979         -           Komarsekraal stud (stud no. 801)

1980         -           Trumps Merino stud (stud no. 1600)

1987         -           Korenhof Merino stud (stud no. 952) 2 Rams

1992         -           Patryskraal Merino stud (stud no. 518)

1992         -           Trumps Merino stud (stud no. 1600)

1992         -           Efpeno Merino stud (stud no. 1759)

1992         -           Eenboom Merino stud (stud no. 836)

 

From 1956 to 1972, 300 ewes were mated in the autumn and 200 ewes in the spring. These ewes were hand mated with eight to 15 rams. Since 1973 only 300 ewes were mated with five to 10 rams in the autumn. The ewes were hand mated from 1956 to 1986 and since 1987 artificial insemination was practised. Teaser rams were used to identify ewes that were in heat and these ewes were then inseminated twice within 12 hours. No hormonal treatment were used with the artificial insemination. The average conception rate, lambing percentage (lambs born per ewe mated) and weaning percentage (lambs weaned per ewe mated) were 91%, 138% and 123% respectively over the last ten years. The ewes were kept on natural veld until a month before the onset of the lambing season, when they were transferred to irrigated pastures. At first the ewes were kept on these pastures until their lambs were weaned, but have recently only been kept on the irrigated pastures for approximately 60 days after lambing. The young ewe and ram lambs were raised separately on natural veld up to selection age (15 to 16 months). Supplementation in the form of lucern and maize was provided.

The main selection objectives from 1956 to 1983 were to obtain a sheep with good conformation and wool traits. Animals with conformation and wool faults, as well as animals with low 120 day weight were culled. According to Olivier et al. (1995) further selection was based on overall excellence, with body size, wool quality (definition of crimps and softness) and quality being the most important criteria. Apparently, some attention was given to measured performance, but the extent there of is difficult to quantify. Since 1985 animals with definite conformation and wool faults were still culled, but final selection was done on animal model BLUP (best linear unbiased prediction) of breeding values. The main selection objectives were to increase body weight, maintain clean fleece weight and decrease mean fibre diameter and pleat score. Due to the role of GMS in the stud industry, the maintenance or improvement of visually assessed traits are regarded as important. Olivier (1989) and Olivier et al. (1995) described the selection procedures followed in the GMS more fully.

 

2.2   History, management and selection procedures of the Carnarvon Merino flock

The Carnarvon Merino flock (CMF) was kept on the Klerefontein experimental station near Carnarvon (30°59'S,20°9'E) in the North-western Karoo region from 1964 to 1983. The veld type is described by Acocks (1988) as False desert. The annual rainfall averages 209mm and occurs mainly during the autumn months. The temperature varies between -9°C to 39°C, which is typical of a semi-desert climate. The vegetation consists of mixed grasses and karoo shrub, with an estimated grazing capacity of 5.5 hectare per small stock unit (1.1 small stock unit = 1 Merino ewe with a lamb).

In 1962, 500 Merino ewes were visually selected from the 700 available ewes of the Grootfontein Merino flock. These ewes were randomly divided into two selection lines (200 ewes each) and a control line (100 ewes). The control line was gradually increased to 200 ewes. The selection procedures followed in each of these lines were described by Erasmus (1988).

The three lines were kept on natural veld where they were managed as one flock, except at mating when the ewes were kept separate and hand mated to the respective rams. Ten rams and 5 reserve rams were selected for each line, the rams being replaced annually except in 1980 and 1981 when only 50% of the rams were replaced (Erasmus, 1988). Ewes with twins did not receive special attention and were kept with the flock. In a time of drought an energy-lick consisting of 70% maize meal and 30% salt was provided. The lambs were weaned at approximately 120 days and the sexes were separated two months later after shearing. Due to the fact that the ewes of CMF were used in 1969 for the development of the Afrino breed, no progeny were available in that year. Olivier (1980) reported that selection line and the two way interactions of selection line with year, sex, rearing status and age of dam had no significant (P<0.01) effect on 120 day weight. Due to this and the fact that the three selection lines were selected from the same genetic base (Erasmus, 1988), selection line was not included as a fixed effect in the analyses for this study.

 

2.3   Data description

In both flocks the full pedigree, birth weight, birth date, sex and birth status were recorded at the birth of each lamb. At weaning, the weaning weight, weaning date and weaning status were recorded. In GMS the 15 to 16 month body weight, greasy fleece weight, clean fleece weight and mean fibre diameter were recorded for ram and ewe lambs. In CMF six month greasy fleece weight and body weight were recorded. For both ram and ewe lambs 18 month body weight, greasy fleece weight, clean fleece weight and mean fibre diameter were also recorded. The total number of records available before editing were 11335 and 10079  for the GMS and CMF respectively.

The number of lambs born (NLB) and weaned (NLW) and the total weight of lamb weaned (TWW) per ewe mated for each lambing opportunity were calculated from the information collected on both flocks. The TWW was calculated as described by Snyman et al. (1997c): the weaning weight for all the lambs was adjusted to 120 days in both flocks, followed by least-squares adjustments for sex of lamb. No adjustments were made for birth status. The total weight of lamb weaned per ewe mated for each lambing opportunity (TWW/EJ) was calculated by adding the adjusted weaning weights of all the lambs weaned by a ewe in a specific lambing season. Subsequently, total weight of lamb weaned by each ewe over n lambing opportunities (TWWn; n = 1...7), was calculated. For example, total weight of lamb weaned over three lambing opportunities (TWW3) was calculated as the sum of TWW/EJ for the first, second and third lambing opportunities (Snyman et al., 1997c). The total weight of lamb weaned for the first (TWW1), second (TWW2), third (TWW3), fourth (TWW4), fifth (TWW5), sixth (TWW6) and seventh (TWW7) lambing opportunities were calculated, depending upon the number of lambing opportunities each ewe had over her lifetime in a specific flock. NLBn and NLWn were calculated by adding the respective NLB and NLW for each lambing opportunity.

The total number of ewe records available for NLB, NLW and TWW for n number of lambing opportunities and the mean and coefficient of variation (CV) are summarised in Table 2.1 and 2.2 for GMS and CMF respectively.

It is evident from Table 2.1 and 2.2 that the GMS had higher means for all traits, compared to that of the CMF. This is due to the harsh conditions under which the CMF were kept. These conditions resulted in a large number of ewes in CMF (85 ewes) which failed to mate successfully during their first lambing opportunity, compared to the 17 ewes of the GMS which failed to mate successfully. Furthermore, the ewes of the GMS produced almost twice as many lambs at birth compared to the ewes of the CMF. While at weaning the average ewe in the GMS weaned about three lambs more than the ewes of the CMF over their lifetime. The large difference between TWW7 of the GMS (211.02 kg) and the CMF (90.54 kg) are a further reflection of the differences in the number of lambs born and weaned, as well as the different environments.

 

Table 2.1. The number of records available for NLBn, NLWn and TWWn for n number of lambing opportunities, the mean and CV% of each trait in Grootfontein Merino stud

No. of lambing opportunities

No. of ewe records

NLBa

NLWb

TWWc

Mean

CV%

Mean

CV%

Mean (kg)

CV%

1

2705

1.15

54.3

0.92

70.7

24.99

67.0

2

2204

2.55

37.5

2.09

48.2

57.22

45.7

3

1777

4.06

30.1

3.35

38.4

91.44

36.8

4

1271

5.54

27.6

4.61

34.3

124.38

33.2

5

672

7.03

25.5

5.82

30.8

154.26

29.5

6

238

8.50

22.6

7.00

28.4

183.33

27.2

7

27

10.11

12.6

7.96

18.7

211.02

21.0

a - Number of lambs born

b - Number of lambs weaned

c - Total weight of lamb weaned per ewe mated

The high CV of the reproductive traits was expected, as it included records from ewes which failed to lamb in their lifetime, as well as ewes which produced up to 14 lambs.

From Table 2.1 and 2.2 it can be seen that the total number of ewes mated at least once in GMS and CMF were 2705 and 2510 respectively. In total, these ewes were available for 8887 and 9759 lambing opportunities, averaging 3.18 and 3.50 for GMS and CMF respectively. From these matings a total of 11335 and 10079 lambs were born in GMS and CMF. The total number of lambs weaned were 10793 in GMS and 8480 in CMF with an average weaning weight of 26.5kg and 20.75kg respectively. It is interesting to note that the average ewe in the CMF (3.50) had more lambing opportunities than the ewes of the GMS (3.18). But contrary to this, CMF ewes had lower means for NLB, NLW and TWW.

Due to the fact that about half of the ewes mated had at least three lambing opportunities, NLB3, NLW3 and TWW3 were used as indications of lifetime reproduction for the analysis in Chapter 4.

 

Table 2.2. The number of records available for NLBn, NLWn and TWWn for n number of lambing opportunities, the mean and CV% of each trait in Carnarvon Merino flock

No. of lambing opportunities

No. of ewe records

NLBa

NLWb

TWWc

Mean

CV%

Mean

CV%

Mean (kg)

CV%

1

2510

0.55

91.5

0.44

110.8

8.77

114.4

2

2237

1.34

56.1

1.16

69.5

22.58

72.6

3

1991

2.22

45.1

1.88

54.8

37.77

55.9

4

1711

3.15

38.3

2.70

46.3

54.38

48.3

5

1322

4.59

35.2

3.97

41.5

79.61

43.3

6

663

5.06

33.9

4.36

40.1

86.95

41.7

7

75

5.60

31.9

4.57

42.5

90.54

43.9

a - Number of lambs born

b - Number of lambs weaned

c - Total weight of lamb weaned per ewe mated

Several of the component traits that have a large influence on TWW are categorical traits by definition, and were therefore analysed by means of threshold procedures. The traits included for analysis (Chapter 3) were fertility, fecundity, litter size at birth (LSB), litter size at weaning (LSW) and survival rate. Fertility (whether a ewe lambed or not; coded as 0 or 1), fecundity (number of lambs born to a ewe lambed; 1, 2 or 3), LSB (number of lambs born to a ewe mated; 0, 1, 2 or 3) and LSW (number of lambs weaned to a ewe mated; 0, 1, 2 or 3) were calculated by handling each ewe=s different lambing opportunities as a separate record. For survival rate (whether a lamb born alive, was dead or alive at weaning; 0 or 1) each lamb born alive was handled as a separate record. The number of records available for fertility, fecundity, LSB, LSW and survival rate in the GMS and the CMF are given in Table 2.3.

 

Table 2.3. The number of records available for fertility, fecundity, LSB, LSW and survival rate in Grootfontein Merino stud (GMS) and Carnarvon Merino flock (CMF).

 

No. of records

GMS

CMF

Fertility

8887

9759

Fecundity

7745

8837

LSBa

8887

9759

LSWb

8887

9759

Survival rate

11335

10079

a - Litter size at birth

b - Litter size at weaning

The average litter size at birth over the experimental period was 1.03 for CMF and 1.28 for GMS. The corresponding litter size at weaning was 0.87 and 1.21, while fecundity for the two flocks was 1.14 and 1.46 respectively.

 

CHAPTER 3

GENETIC PARAMETER ESTIMATES FOR FITNESS TRAITS

 

3.1   Introduction

Reproduction traits are, by definition, threshold traits. Due to the fact that several of the component traits of total weight of lamb weaned are categorical traits, it was decided to evaluate these traits with threshold procedures, as it is the method of choice for discontinuous data. The main objective of the first part of this study was therefore to estimate heritabilities and determine the range of sire breeding values for these component traits. The traits included were fertility (whether a ewe lambed or not), fecundity (number of lambs born to a ewe that lambed), litter size at birth (number of lambs born to a ewe mated), litter size at weaning (number of lambs weaned to a ewe mated) and survival rate (whether a lamb born alive, was dead or alive at weaning).

 

3.2   Material and methods

3.2.1   Data

Data collected on the Grootfontein Merino stud (from 1968 to 1996) and the Carnarvon Merino flock (from 1964 to 1983) were used for this study. These traits were coded and calculated as described in paragraph 2.3. Only sires with more than ten records for each trait were retained for analyses. A description of the data sets is given in Table 3.1. The number of records in GMS ranged from 7432 for fecundity to 10 210 for survival rate (Table 3.1), while in CMF the number of records ranged from 6237 for fecundity to 9174 for survival rate. The number of sires in the data sets range from 185 to 217 for GMS and for CMF from 420 to 493 for fecundity and survival rate respectively.

 

Table 3.1. Description of the data sets for the Grootfontein Merino stud (GMS) and Carnarvon Merino flock (CMF)

 

No. of records

No. of sires

No. of categories

No. of thresholds

 

GMS

CMF

GMS

CMF

Fertility

8590

8777

193

420

2

1

Fecundity

7432

6237

185

420

3

2

LSBa

8590

8777

193

420

4

3

LSWb

8590

8777

193

420

4

3

Survival rate

10210

9174

217

493

2

1

a - Litter size at birth

b - Litter size at weaning

It is common knowledge that there is always one less threshold than the number of categories. As fertility was defined as whether a ewe mated lambed or not and coded accordingly, it has only two categories (Table 3.1). Fecundity has three categories, as it was defined as the number of lambs born per ewe lambed. In both these flocks there were single, twin and triplet births and weanings. LSB and LSW had four categories as it was defined as the number of lambs born or weaned per ewe mated, and the number of lambs born or weaned ranged from zero to three. As for survival rate, it had only two categories as it was defined as whether a lamb born alive, was dead or alive at weaning.

 

3.2.2   Sources of non-genetic variation

The categorical data modelling (CATMOD) procedure of SAS (1989) was used to determine the importance of non-genetic sources of variation. The effects of  year (19 for CMF) / year-season (36 for GMS), age of dam in years (7 for GMS and 6 for CMF) and birth status (3 in both flocks; fitted for survival rate only) were included in the analyses.

 

3.2.3   Threshold model analysis

Heritability estimates and estimated sire breeding values (EBVs) were obtained by means of a GFCAT set of programmes (Konstantinov, 1995). GFCAT is a set of programmes for the analyses of Amixed@ threshold models with support for REML-type variance component estimation based on the methods of Gianola & Foulley (1983). Under these models, the respective traits occur as a result of an underlying unobserved phenotype exceeding a given threshold (Konstantinov et al., 1994). The unobserved continuous phenotypes are assumed to be normally distributed. For each trait a vector, F, of means corresponding to subpopulations determined by combinations of levels of Afixed@ b and Arandom@ s factors, is modelled as:

F = Xb + Zs

where    F is a vector of underlying means,

b is a vector associated with the Afixed@ effects,

s is a vector of sire effects and

X and Z are design matrices.

The sire effects are assumed to be normally distributed, with E(s) = 0 and Var(s) = Aδ2s, where A is the numerator relationship matrix.

The thresholds and the solutions for vectors b and s were computed as described by Konstantinov et al. (1994). The different traits for each of the flocks were analysed separately. The heritability (h2) was estimated by setting the error variance to unity:

h2 =  

(4 X δ2s)


(1 + δ2s)

The thresholds, the solutions for all the effects and the estimated sire breeding values are in units of residual standard deviation of the underlying scale due to the fact that the underlying scale is unknown.

 

3.3    Results and discussion

3.3.1   Thresholds and the solutions for Afixed@ effects

The thresholds and the solutions for age of dam and birth status for each flock are given in Tables 3.3 and 3.4 for GMS and CMF respectively.

It is evident from Table 3.3 that there was a distinct pattern for the solutions of age of dam in GMS. There was an increase in fertility, fecundity, LSB and LSW with an increase in age of dam until four or five years of age. In CMF (Table 3.4) a similar pattern existed for all traits until five or six years of age. As expected, the youngest ewes had the lowest fertility, fecundity and litter size in both flocks. The decrease in survival rate with an increase in birth status in GMS, as well as the higher survival rate of single born animals compared to that of multiple born animals in CMF, was expected.

 

Table 3.3. Thresholds and solutions for age of dam and birth status for the Grootfontein Merino stud

 

Fertility

Fecundity

Litter size at birth

Litter size at weaning

Survival rate

Thresholds

1

0.0000

0.0000

0.0000

0.0000

0.0000

2

 

2.1871

1.3460

1.3194

 

3

 

 

3.3808

3.3109

 

 

 

 

 

 

 

Age of dam

1

-0.0187

-1.1606

0.0956

-0.3385

 

2

1.1229

-0.2335

1.0519

0.5720

 

3

1.2180

0.2403

1.3572

0.8784

 

4

1.3045

0.4681

1.5431

0.9520

 

5

1.2343

0.5274

1.5510

0.9451

 

6

1.0105

0.4770

1.3973

0.7922

 

7

0.7880

0.4845

1.2499

0.6540

 

 

 

 

 

 

 

Birth status

1

 

 

 

 

1.8735

2

 

 

 

 

1.0933

3

 

 

 

 

0.7718

 


Table 3.4. Thresholds and solutions for the age of dam and birth status for the Carnarvon Merino flock

 

Fertility

Fecundity

Litter size at birth

Litter size at weaning

Survival rate

Thresholds

1

0.0000

0.0000

0.0000

0.0000

0.0000

2

 

2.0875

2.0842

1.9422

 

3

 

 

3.9910

4.0342

 

 

 

 

 

 

 

Age of dam

2

0.0026

-2.7390

-0.1911

-0.3546

 

3

0.4767

-2.1466

0.2747

0.0795

 

4

0.6493

-1.8521

0.4960

0.3081

 

5

0.7551

-1.6821

0.6318

0.4318

 

6

0.7469

-1.4906

0.7111

0.5090

 

7

0.5766

-1.4684

0.5917

0.3567

 

 

 

 

 

 

 

Birth status

1

 

 

 

 

1.5382

2

 

 

 

 

1.1588

3

 

 

 

 

1.1635

 

3.3.2   Heritabilities

Estimates of sire variances and heritabilities for the different traits in each flock are given in Table 3.5.

 

Table 3.5. Sire variance and heritabilities for fitness traits in the Grootfontein Merino stud (GMS) and Carnarvon Merino flock (CMF)

 

GMS

CMF

Trait

Sire Variance

Heritability

Sire Variance

Heritability

Fertility

0.01836

0.072

0.05334

0.203

Fecundity

0.04527

0.173

0.08416

0.311

LSBa

0.03374

0.131

0.05276

0.201

LSWb

0.02373

0.092

0.04780

0.183

Survival rate

0.00000

0.000

0.00000

0.000

a - Litter size at birth

b - Litter size at weaning

The highest heritability estimates in both flocks were obtained for fecundity, which was 10% higher than that estimated for fertility in the respective flocks. This supports claims (Turner & Young, 1969) that selection for reproduction rate should be based on fecundity and not fertility. Furthermore,  heritability estimates for litter size at birth were also lower than those estimated for fecundity. This could be expected, as records from ewes that failed to lamb were also included for the estimation of heritability for  litter size at birth. Heritability estimates obtained for  litter size at weaning were lower than those estimated for fecundity, but similar to the estimates obtained for fertility in both flocks. The heritability estimates for survival rate were zero in both the GMS and CMF.

Estimated heritabilities for the reproductive traits in the CMF were higher than the corresponding heritabilities obtained in the GMS. This may be due to the more natural conditions under which the Carnarvon flock was kept. In the GMS, artificial insemination was done, for part of the time, while natural mating was practised in the CMF.

Few threshold heritability estimates for reproduction traits are available in the literature.  Heritabilities estimated with a threshold model for fertility were 0.20 (Snyman et al., 1997b) and 0.08 (Matos et al., 1997), for litter size at birth 0.27 (Snyman et al., 1997b), 0.14, 0.19 and 0.18 (Jorgensen, 1994), 0.24 (Konstantinov et al., 1994), 0.08 and 0.00 (Olesen et al., 1994), as well as 0.45 and 0.14 (Matos et al., 1997). For litter size at weaning the reported heritability estimates were 0.19 (Snyman et al., 1997b), as well as 0.11, 0.09 and 0.27 (Jorgensen, 1994). Snyman et al. (1997b) reported heritability estimates of 0.42 and 0.02 for fecundity and survival rate respectively. The heritabilities for fecundity and survival rate estimated in this study are lower than those reported earlier, while those for fertility, litter size at birth and litter size at weaning are within the range of reported estimates.

Heritabilities estimated from linear model paternal half-sib analyses, range from 0.01 (Atkins, 1986) to 0.22 (Martin et al., 1981) for fertility, from 0.08 (Basuthakur et al., 1973) to 0.35 (Abdulkhaliq et al., 1989) for litter size at birth and from 0.02 (Martin et al., 1981) to 0.26 (Abdulkhaliq et al., 1989) for litter size at weaning. The heritability estimates in this study for fertility, LSB and LSW are within the range of these published heritabilities and are similar to the heritabilities estimated for Merino sheep, which are reviewed by Fogarty (1995).

Snyman et al. (1997c) proposed that ewe selection should be based on reproductive performance. In flocks with an average lambing percentage of less than 100%, such as the CMF, selection for improved reproduction should be based on fertility, i.e. cull all ewes that failed to lamb. Due to a lack of sufficient replacement numbers in flocks with a poor reproductive performance, it would in many instances be necessary to keep some of the ewes that failed to lamb.

Maximum exploitation of the available genetic variation in a threshold trait such as fertility is, however, not very easy. Selection intensity is usually lower in traits with only one threshold, compared to those with two or three thresholds, as well as continuous traits (Bourdon, 1997). This is especially true when a larger or smaller proportion needs to be selected than the number of animals available of the favourable phenotype. Selection response would theoretically be greater if animals closer to the threshold on the underlying liability scale could be identified and selected. This is, however, not possible as there are, in the case of fertility, only two distinct phenotypes. This problem could to a large extent be eliminated by selection based on threshold estimated sire breeding values for the trait in question. Using estimated sire breeding values would not only increase selection intensity, but also accuracy of selection.

In ewe flocks with a high reproductive rate, such as the GMS, selection for improved reproduction performance should be based on fecundity or litter size at birth (combination of fertility and fecundity). These traits have  a higher heritability than fertility, and an increased selection intensity with these traits are possible, as they have more than one threshold. Alternatively, selection could be based on a genetically correlated continuous trait, such as total weight of lamb weaned (Snyman et al., 1997c), for which animal model EBVs for ewes can also be estimated.

 

3.3.3   Sire breeding values

Sire breeding values (expressed in units of residual standard deviation of the underlying scale) for the best and worst sire for the different traits are given in Table 3.6. It is interesting to note that in GMS the best sire for each trait had the most daughters with reproduction records, while in CMF the number of daughters with reproduction records for the best and worst sires was almost equal.

The higher heritability estimates obtained in the CMF are reflected in the wider range of sire breeding values compared to those of GMS. The range of sire breeding values indicate that there  is genetic variation between sires with regard to the reproductive traits which could be exploited during selection.

The main disadvantage of selection based on estimated sire breeding values is that these EBVs for reproductive traits are only available after the first parity of a sire=s first daughters. In normal sheep enterprises, this would be when the sire is already four years of age. At that stage, the rams have already been used for two years in the flock. The most important application of sire EBVs in practice would thus be in the identification of merit rams for use as national AI-sires.

 

Table 3.6. Range of estimated sire breeding valuesa for each trait in the Grootfontein Merino stud (GMS) and Carnarvon Merino flock(CMF)

 

GMS

CMF

Trait

Best sire

(n)b

Worst sire

(n)

Best sire

(n)

Worst sire

(n)

Fertility

0.1819

-0.2102

0.3273

-0.4700

 

(99)

(67)

(38)

(18)

Fecundity

0.4814

-0.3073

0.7936

-0.3430

 

(92)

(43)

(31)

(25)

LSBc

0.4349

-0.3206

0.5834

-0.4266

 

(99)

(67)

(36)

(28)

LSWd

0.2606

-0.2606

0.6007

-0.4049

 

(117)

(42)

(36)

(28)

a  Expressed in units of residual standard deviation of the underlying scale

b  Number of daughters with reproduction records

c Litter size at birth

d Litter size at weaning

 

3.4   Conclusion

The heritability estimates and range of sire breeding values obtained in this study indicate that it would be possible to improve reproduction rate, but not survival rate, genetically through selection in these flocks. Threshold model sire breeding values for reproductive traits could be used most effectively in the identification of rams for use as national AI-sires. When the estimation of threshold animal model breeding values become possible, it would lead to a further increase in selection response if ewes could also be selected on EBVs for the respective traits.  A further advantage of using these animal model EBVs, is that they can be estimated much earlier than sire EBVs, and sire selection could be done on the performance of his dam.

 

CHAPTER 4

DIRECT AND CORRELATED SELECTION RESPONSE PER GENERATION IN TOTAL WEIGHT OF LAMB WEANED

 

4.1   Introduction

Sheep in South Africa are to a large extent kept under extensive farming conditions in harsh environments. In practice, it is expected from Merino ewes to produce a substantial amount of good quality wool, as well as to wean viable lambs under these conditions.

As previously discussed in Chapter 1, the composite trait total weight of lamb weaned per ewe mated is the best measurement of a ewe=s lifetime reproduction. For the purpose of the second part of this study, TWW (total weight of lamb weaned per ewe mated), NLB (number of lambs born per ewe mated) and NLW (number of lambs weaned per ewe mated) over the first three lambing opportunities of a ewe were taken as an indication of lifetime reproduction efficiency. The traits NLB and NLW were treated as continuous traits for this part of the study, as these traits are a combination of three separate lambing opportunities. The main objective in this part of the study was to calculate the direct and correlated expected selection response per generation in total weight of lamb weaned per ewe mated (TWW), number of lambs born (NLB) and number of lambs weaned (NLW) over three lambing opportunities and individual weaning weight (WW) of each lamb for selection based on WW, NLB, NLW or TWW. For this purpose, genetic and phenotypic correlations among these traits were estimated.

 

4.2   Material and methods

4.2.1   Data

Wool production was not included as Snyman et al. (1997a), using the same data sets, estimated genetic correlations (SE) of 0.26 (0.16) and 0.06 (0.11) between total weight of lamb weaned and clean fleece weight in the Grootfontein Merino stud and the Carnarvon Merino flock respectively. They concluded that selection progress in both clean fleece weight and TWW would be feasible in a well designed breeding plan for South African Merino sheep. Snyman et al. (1997c) argued that selection for increased number of lambs under extensive conditions, without taking the individual weaning weight of lambs into consideration, would be short-sighted. Weaning weight of individual lambs was therefore also included in the analysis, as it is a component trait of TWW.

Traits analysed in this study were number of lambs born to a ewe mated over three parities (NLB), number of lambs weaned to a ewe mated over three parities (NLW), total weight of lamb weaned per ewe mated over three parities (TWW), as well as weaning weight of individual lambs (WW).

TWW was calculated as fully described in paragraph 2.3. Weaning weight for all the lambs was adjusted to 120 days in both the flocks, followed by least-squares adjustments for sex of lamb. No adjustments were made for birth status. The total weight of lamb weaned per ewe mated for each lambing opportunity (TWW/EJ) was calculated by adding the adjusted weaning weights of all the lambs weaned by a ewe in a specific lambing season.

NLB, NLW and TWW over three parities were calculated by adding, respectively, litter size at birth, litter size at weaning and TWW/EJ for the first, second and third parities. Only data of ewes with three consecutive lambing opportunities were used in the analysis. The number of records available in the two flocks, as well as the mean, standard deviation (SD) and the coefficient of variation (CV) for the respective traits are summarized in Table 4.1.

 

4.2.2   Statistical analysis

(Co)variance components were estimated using the DFREML programme of Meyer (1989, 1991 & 1993). The heritability estimates for TWW, NLB and NLW were obtained by fitting single trait animal models, which included direct additive genetic effects and fixed effects for year-season of birth of the ewe for the reproductive traits. The heritability estimates for WW were obtained by fitting a single trait animal model which included both direct additive and maternal genetic effects. The fixed effects included for WW were year-season, sex, rearing status and age of dam, while age at weaning  was included as a linear covariable. Total heritability estimates for WW were used in all the calculations for the selection responses.

 

Table 4.1. The number of records, mean, standard deviation (SD) and coefficient of variation for the respective traits in the Grootfontein Merino stud (GMS) and the Carnarvon Merino flock (CMF)

Trait

No. records

Mean

SD

CV%

Grootfontein Merino Stud

WWa

7035

27.74kg

5.41

19.50

WWb

1712

26.59kg

5.45

20.50

TWWab

1777

90.84kg

36.19

39.84

NLBab

1777

4.04 

1.28

31.78

NLWab

1777

3.33 

1.33

39.81

Carnarvon Merino Flock

WWa

8480

20.75kg

4.30

20.72

WWb

1960

20.50kg

2.82

18.61

TWWab

1971

37.63kg

21.76

57.83

NLBab

1971

2.22 

1.00

45.11

NLWab

1971

1.88 

1.03

55.15

a Univariate analysis - for the total data set

b Bivariate analysis - only data of ewes with three lambing opportunities

Bivariate animal models were fitted for the estimation of genetic and phenotypic correlations among traits. The same effects were included for the bivariate analysis as for the univariate analysis, except sex, which was not included for WW in the bivariate analysis. The standard errors for the genetic correlations were calculated as described by Falconer & Mackay (1996).

The direct selection response for each trait was calculated using the following formula:

R = ih2δP

where   R is the direct selection response,

i is the selection intensity,

h2 is the heritability and

δP is the phenotypic standard deviation of the trait.

For the purpose of this study, it was assumed that 5% males and 50% females were selected. The selection intensities for  the males and females were taken from the Appendix Table A of Falconer & Mackay (1996). The selection intensities used in this study were calculated as the unweighted means of the selection intensities of males and females.

Correlated selection response was calculated using the following formula:

CRY = ihXhYrAδPY

where   CRY is the correlated response in Y if selection is based on X,

i is the selection intensity,

hX is the square-root of the heritability of X,

hY is the square-root of the heritability of Y,

rA is the genetic correlation between X and Y and

δ   PY is the phenotypic standard deviation of Y.

 

4.3   Results and discussion

From Table 4.1 it is evident that the CMF had lower means for WW, NLB, NLW and TWW, compared to the GMS. This is due to the harsh conditions under which CMF was kept. These conditions resulted in the large number of ewes which failed to wean a lamb during first parity and the lower weaning weight of the lambs.

The high CV of the reproduction traits was expected, as the data contained records from ewes which failed to wean a lamb over the three lambing opportunities on the one hand, as well as from ewes that weaned up to 8 lambs on the other.

Heritability estimates for WW, TWW, NLB and NLW, as well as the genetic and phenotypic correlations among these traits are summarized in Table 4.2 for both flocks. Heritability estimates obtained with a linear animal model (AM) reported in the literature for NLB, NLW and TWW are summarized in Table 4.3. Heritability estimates obtained with an AM for WW ranged from 0.09 (Burfening & Kress, 1993) to 0.45 (Brash et al., 1994d) and were extensively reviewed by Fogarty (1995) and Snyman et al. (1995).

 

Table 4.2. Heritability (SE) estimates (on diagonal) for and genetic (above diagonal) and phenotypic (below diagonal) correlations among the traits in the Grootfontein Merino stud and Carnarvon Merino flock

 

WW

TWW

NLB

NLW

Grootfontein Merino Stud

WW

0.21a

(0.04)

0.65

(0.15)

0.32

(0.16)

0.34

(0.16)

TWW

0.08

(0.03)

0.19

(0.05)

0.91

(0.03)

0.97

(0.01)

NLB

0.06

(0.03)

0.71

(0.01)

0.23

(0.05)

0.97

(0.01)

NLW

0.04

(0.03)

0.95

(0.01)

0.77

(0.01)

0.17

(0.05)

Carnarvon Merino Flock

WW

0.30a

(0.05)

0.78

(0.08)

0.45

(0.12)

0.57

(0.12)

TWW

0.19

(0.02)

0.21

(0.04)

0.89

(0.04)

0.98

(0.01)

NLB

0.14

(0.02)

0.82

(0.01)

0.19

(0.04)

0.93

(0.02)

NLW

0.14

(0.02)

0.96

(0.01)

0.84

(0.01)

0.16

(0.04)

a - Total heritability

The heritability estimates obtained in this study for TWW, NLB and NLW accord well with the estimates obtained by Snyman (Unpublished) and Snyman et al. (1997a), but were slightly higher than the other AM heritability estimates found in the literature (Table 4.3). The estimates obtained for WW are within the range of heritabilities reported in the literature.

 

Table 4.3. Heritability estimates obtained with a linear animal model for NLB, NLW and TWW reported in the literature

NLBa

NLWb

TWWc

Breed

Reference

0.12

0.04

 

Rambouillet

Burfening et al., 1993

0.00

 

 

Border Leicester

Brash et al., 1994a

0.06

0.04

 

Dorset

Brash et al., 1994b

0.03

0.03

 

Corriedale

Brash et al., 1994c

0.09

0.04

0.06

Hyfer

Fogarty et al., 1994

 

 

0.17

Afrino

Snyman et al., 1997a

0.26

0.17

 

Afrino

Snyman, Unpublished

a - Number of lambs born

b - Number of lambs weaned

c - Total weight of lamb weaned

High estimates of genetic correlations among the reproduction traits were obtained in both GMS and CMF, while the genetic correlations of WW with TWW, NLB and NLW were moderate. The phenotypic correlations between WW and the reproduction traits were low, while the phenotypic correlations among the reproduction traits were moderate to high. Genetic and phenotypic correlations among these traits reported in the literature are summarized in Table 4.4. Although the estimates found in the literature vary substantially the estimates of this study were within the reported range of correlations.

 

Table 4.4. Genetic and phenotypic correlations among WW, NLB, NLW and TWW reported in the literature

Trait 1

Trait 2

Genetic correlation

Phenotypic correlation

Breed

Reference

1

2

0.32

0.13

Romney

Ch=ang &Rae, 1972

1

2

‑0.61

0.05

Romney

Baker et al., 1982

1

2

0.25

0.05

Merino

Davis, 1987

1

2

‑0.01

0.04

Afrino

Snyman et al., 1997d

1

3

0.34

0.09

Merino

Davis, 1987

1

3

0.11

0.03

Afrino

Snyman et al., 1997d

1

4

0.75

0.15

Afrino

Snyman et al., 1997d

2

3

0.42

0.64

Various

Fogarty et al., 1985

2

3

0.91

0.73

Merino

Davis, 1987

2

3

1.20

0.54

Galway

More O=Farrell, 1976

2

3

0.99

0.87

Afrino

Snyman et al., 1997d

2

4

0.50

0.58

Various

Fogarty et al., 1985

2

4

0.83

0.79

Afrino

Snyman et al., 1997d

3

4

0.88

0.92

Galway

More O=Farrell, 1976

3

4

0.97

0.95

Various

Fogarty et al., 1985

3

4

0.84

0.92

Afrino

Snyman et al., 1997d

1 - Weaning weight

2 - Number of lambs born

3 - Number of lambs weaned

4- Total weight of lamb weaned

 

Table 4.5. The direct (on diagonal) and correlated selection  response (off diagonal) per generation for the respective traits and these responses expressed as a percentage of the mean of each trait in Grootfontein Merino stud (GMS) and Carnarvon Merino flock (CMF)

 

 

Response in kg and number of lambs

 

Response as percentage of the means

Trait under selection

WW

kg

TWW

kg

NLB

NLW

WW

%

TWW

%

NLB

%

NLW

%

Grootfontein Merino Stud

 

 

 

 

WW

1.16

6.01

0.12

0.12

4.18

6.63

2.95

3.51

TWW

0.70

9.03

0.33

0.33

2.52

9.97

8.21

9.91

NLB

0.38

9.20

0.41

0.36

1.37

10.16

10.20

10.81

NLW

0.36

8.50

0.34

0.32

1.30

9.38

8.45

9.61

Carnarvon Merino Flock

 

 

 

 

WW

1.36

5.92

0.07

0.04

6.55

15.72

3.15

2.13

TWW

0.89

6.37

0.25

0.26

4.34

16.91

11.26

13.83

NLB

0.21

5.38

0.27

0.24

1.02

14.28

12.16

12.77

NLW

0.14

5.47

0.23

0.24

0.68

14.52

10.36

12.77

 

The direct and correlated selection responses for each trait and these responses expressed as a percentage of the mean of each trait are given in Table 4.5. The selection response per generation in WW and TWW were measured as the average gain in kg and for NLB and NLW as the average gain in number of lambs born or weaned. In GMS the expected direct selection response in WW, TWW, NLB and NLW were 1.16 kg, 9.03 kg, 0.41 lambs and 0.31 lambs respectively, while in CMF, the respective responses were 1.36 kg, 6.37 kg, 0.27 lambs and 0.24 lambs. The correlated selection response per generation to selection based on TWW in the GMS were 0.70 kg, 0.33 lambs and 0.33 lambs in WW, NLB and NLW respectively and in CMF were 0.89 kg, 0.25 lambs and 0.26 lambs respectively.

As discussed in Chapter 1, the best measurement of a ewe=s lifetime reproduction is the composite trait total weight of lamb weaned per ewe mated. Due to this fact and the purpose of this study, is TWW the trait in which genetic improvement is being sought. The deviation of the selection responses of selection based on WW, NLB and NLW were therefore expressed as a percentage of the selection responses obtained for selection based on TWW in each of the traits and these deviations are given in Table 4.6.

Selection based on WW alone would lead to about 50% higher selection response in WW compared to selection based on TWW in both flocks. In GMS the response in TWW would be "34% lower if selection is based on WW, while in CMF only 7% lower response would be obtained. In both flocks the responses in NLB and NLW would be more than 63% lower for selection based on WW compared to selection based on TWW.

In GMS the selection response in WW for selection based on either NLB and NLW would be about half of that of selection on TWW and about a third of that of selection on WW. In CMF the selection response in WW would be more than 75% lower compared to selection based on TWW. Selection based on NLB in GMS would lead to a slightly higher response in TWW compared to direct selection for TWW, while NLW in GMS and NLB and NLW in CMF the selection responses in TWW would be between six and 15% lower. The selection responses in NLB and NLW in GMS were about 24% and 10% higher for selection based on NLB compared to selection on TWW. For selection based on NLW in GMS the selection responses were almost the same as that of selection based on TWW. In CMF selection for NLB would lead to 8% higher response in NLB and 8% lower response in NLW compared to selection for TWW. Selection based on NLW in CMF would lead to "8% lower selection responses in both NLB and NLW.

It is evident from Table 4.6 that selection based on TWW and NLB in the GMS and on TWW and WW in CMF would theoretically result in the highest selection responses in TWW. The low phenotypic correlations between TWW and WW in both these flocks indicate that the highest producers for the current flock would not necessarily be selected. In large areas of South Africa sheep are run under harsh conditions and in most of these flocks the lambing percentages are already high. Under these conditions an unnecessary increase in the number of lambs born would be undesirable. The results of this study supported claims that TWW is the best indication of lifetime reproduction in the current flock, as well as in future generations.

Table 4.6. The deviation of the selection responses of selection based on WW, NLB and NLW expressed as a percentage of the selection response obtained for selection based on TWW in each of these traits in Grootfontein Merino stud and Carnarvon Merino flock

Trait under selection

WWa

%

TWWb

%

NLBc

%

NLWd

%

Grootfontein Merino Stud

TWW

100.0

100.0

100.0

100.0

WW

165.7

66.6

36.4

36.4

NLB

54.3

101.9

124.3

109.1

NLW

51.4

94.1

103.0

97.0

Carnarvon Merino Flock

TWW

100.0

100.0

100.0

100.0

WW

152.8

92.9

28.0

15.4

NLB

23.6

84.5

108.0

92.3

NLW

15.7

85.9

92.0

92.3

a - Weaning weight

b - Total weight of lamb weaned

c - Number of lambs born

d - Number of lambs weaned

 

4.4   Conclusion

This study has shown that selection on any of the traits studied should theoretically improve reproductive performance of the current flock and that of future generations. The selection responses estimated in this study indicate that direct selection for TWW would be the most suitable selection criteria to improve reproductive performance. This should be a very important point to consider in flocks where the lambing and weaning percentages are already high and an unnecessary increase in the number of lambs, without taking the individual weaning weight of the lambs into consideration, is undesirable.

 

CHAPTER 5

GENERAL CONCLUSION

The most important result of this study is that the reproductive performance, defined as the total weight of lamb weaned per ewe mated, can be improved genetically through either direct or indirect selection.

Although selection objectives and criteria in sheep farming enterprises differ from breed to breed, country to country and from farm to farm, reproduction and survival are the only traits that are universally important. This is why ewe selection should be aimed at improving the lifetime reproduction and production efficiency in the current flock, as well as the genetic merit of future generations.

When the improvement of lifetime reproduction, in other words total weight of lamb weaned, was studied, two scenarios were used. The first was for a flock with a low reproduction rate (lambing percentage < 100%), such as the Carnarvon Merino flock. The second scenario was for a flock with a high reproduction rate (lambing percentage > 100%), such as the Grootfontein Merino stud. The selection objectives for increased lifetime reproduction would therefore differ between these two flocks. Two more factors that would have an influence on these selection objectives, is the fact that the Merino is pre-eminently a wool producer and the fact that sheep in South Africa is to a large extent kept under extensive farming conditions in harsh, arid environments. It is therefore important for both stud and commercial breeders that breeding ewes produce a substantial amount of good quality wool, while rearing viable lambs with a good quality carcass.

In the case of the first scenario, where the reproduction rate is low, selection for improved reproduction should be based on fertility, i.e. cull all the ewes that failed to lamb. It may be necessary to keep some of the ewes that failed to lamb due to a lack of sufficient replacement numbers in a flock with a poor reproduction performance. Maximum exploitation of the available genetic variation in fertility are not very easy. This is due to the fact that selection intensity is usually lower in traits, such as fertility, with only one threshold, compared to traits, such as fecundity, with two or three thresholds (Bourdon, 1997). However, the selection response in fertility would be greater if animals closer to the threshold on the underlying liability scale could be identified and selected. Selection based on threshold estimated sire breeding values for the trait in question would eliminate this problem and would lead to an increased selection intensity, as well as in the accuracy of selection. The main disadvantage of selection based on estimated sire breeding values is that these EBVs are only available after the first parity of a sire=s first daughters. When the estimation of threshold animal model breeding values become possible, it would lead to a further increase in selection response if ewes could also be selected on EBVs for the respective traits.  A further advantage of using these animal model EBVs, is that they can be estimated much earlier than sire EBVs, and ram selection could be done on the performance of its dam.

The selection strategies suggested in this study are in concurrence with Kritzinger et al. (1983)  who suggested that the reproduction rate within the current flock could be improved through the  culling of ewes that failed to lamb during their first lambing. This is further supported by Lee & Atkins (1996), who in turn argued the fertility at an early age can be seen as an indicator of both the fertility and the rearing ability of ewes in later life, thus the reproduction rate in the current flock could be improved if Merino ewes that failed to bear or rear a lamb in early life are culled. The genetic variation in and covariation among the component traits will influence the extent of improvement in the reproduction rate of future generations if selection is done by culling ewes that failed to bear or rear a lamb at early age.

Culling of ewes that fail to lamb would increase the reproduction rate of a flock, but not necessarily the TWW per ewe. Selection for weaning weight could be combined with fertility in the selection objectives to improve TWW. The high genetic correlations between TWW and WW, as well as the selection response in TWW for selection on WW indicate that selection for WW would increase the TWW of a flock. However, the low phenotypic correlations obtained between these two traits would not guarantee that the top producers for the current flock would be selected, if selection is based on WW. These selection objectives should be followed until the reproduction rate of such a flock has improved to an acceptable level. The emphasis should then be shifted to improve the lifetime reproduction of a flock through direct selection for TWW.

In the second scenario, where the reproduction rate is already high, selection should be aimed at improving TWW further by direct selection. An important fact to note is that the environment under which a flock is kept will dictate the acceptable reproduction rate for that specific environment. In some areas a lambing percentage of 110% would be acceptable, while in other areas 150% would be acceptable. In areas  where the lambing percentages are already at the acceptable rate, an increase in the number of lambs born would be undesirable, as it may lead to less wool of a poorer quality being produced by a ewe (Kennedy, 1967; Shelton & Menzies, 1968), as well as the weaning of inferior lambs. It is therefore more sensible to improve the quality of the lambs of a ewe, rather than the quantity of lambs per ewe. It is evident from the results of this study that it is possible to improve the lifetime reproduction of a ewe without an unnecessary increase in the number of lambs by selection for TWW. The slight increase in the number of lambs from selection for TWW, would be compensated for by the fact that TWW is a composite trait that is likely to improve several component traits, such as the mothering ability and the milk production of a ewe, the number of lambs and the viability of the lambs.

In the second scenario, selection of young ewes could be done in two phases. The first phase of selection should be done on the ewes own weaning weight and her mother=s total weight of lamb weaned, as well as conformation and wool traits. Due to the fact that selection intensity in ewes are relatively low, the emphasis should be placed on reproduction traits rather than conformation and wool traits. With ram selection, more emphasis could be placed on the conformation and wool traits. The selected ewes should then be mated and after their first parity further selection should be based on their own reproductive performance. An important part of improving the reproductive performance of a flock, is the culling of ewes that failed to rear a lamb(s) to weaning.

In the past WW, especially in the Merino sheep, was not regarded as an important selection criterion and it was therefore not recorded in most flocks. From the results of this study it is evident that WW should be recorded, as it plays an integral role in the evaluation of ewe productivity.

 

ABSTRACT

The purpose of this study was to evaluate different ewe productivity measures and to identify the most efficient selection criteria to improve total weight of lamb weaned per ewe mated in the Grootfontein Merino stud and the Carnarvon Merino flock.

Due to the fact that several of the component traits of total weight of lamb weaned are categorical traits, these traits were evaluated with threshold procedures, as it is the method of choice for discontinuous data. The main objective of the first part of this study were therefore to estimate heritabilities and determine the range of sire breeding values for these component traits. The traits included were fertility (whether a ewe lambed or not; coded as 0 or 1), fecundity (number of lambs born to a ewe that lambed; 1, 2 or 3), litter size at birth (number of lambs born to a ewe mated; 0, 1, 2 or 3), litter size at weaning (number of lambs weaned to a ewe mated; 0, 1, 2 or 3) and survival rate (whether a lamb born alive, was dead or alive at weaning; 0 or 1). Data collected on the Grootfontein Merino stud from 1968 to 1996 and on the Carnarvon Merino flock from 1964 to 1983 were used for these analysis. The total number of records available in the respective flocks were 11335 and 10079.

The estimated heritabilities on the underlying scale for the respective traits were 0.072, 0.173, 0.131, 0.092 and 0.000 for the Grootfontein Merino stud and 0.203, 0.311, 0.201, 0.183 and 0.000 for the Carnarvon Merino flock. The heritability estimates and the range in sire breeding values indicated that it would be possible to improve reproduction, but not survival rate, genetically through selection in these flocks.

The best measurement of a ewe=s lifetime reproduction is the composite trait total weight of lamb weaned per ewe mated. For the purpose of the second part of this study, TWW (total weight of lambed weaned per ewe mated), NLB (number of lambs born per ewe mated) and NLW (number of lambs weaned per ewe mated) over the first three lambing opportunities of a ewe were taken as an indication of lifetime reproduction efficiency. The traits NLB and NLW were treated as continuous traits for this part of the study, as these traits are a combination of three separate lambing opportunities, which extended the number of categories and resulted in a near normal distribution. The main objective in this part of the study was to calculate the direct and correlated selection response per generation in total weight of lambed weaned per ewe mated (TWW), number of lambs born (NLB) and number of lambs weaned (NLW) over three lambing opportunities, as well as individual weaning weight (WW) of each ewe for selection based on TWW, NLB, NLW or WW. For this purpose, genetic and phenotypic correlations among these traits were estimated. The same data sets used in the threshold analyses were used for the calculation of the selection responses.

Estimated heritabilities for the respective traits were 0.19, 0.23, 0.17 and 0.21 for the Grootfontein Merino stud and 0.21, 0.19, 0.16 and 0.30 for the Carnarvon Merino flock. High genetic correlations (0.89 to 0.98) among the reproduction traits were obtained in both flocks, while the genetic correlations of WW with TWW, NLB and NLW were moderate (0.32 to 0.78). The phenotypic correlations between WW and the reproduction traits were low (0.04 to 0.19), while the phenotypic correlations among the reproduction traits were moderate to high (0.71 to 0.96). In the Grootfontein Merino stud approximately the same selection response in TWW could be expected from direct selection on TWW (9.03kg) and indirect selection on NLB (9.20kg). In the Carnarvon Merino flock the highest selection response in TWW (6.37kg) would be achieved through direct selection for TWW.

The selection responses estimated in this study indicate that direct selection for TWW would be the most suitable selection criterion to improve reproductive performance, without an unnecessary increase in the number of lambs born. From the results of this study it is evident that WW should be recorded, as it plays an integral role in the evaluation of ewe productivity.

 

OPSOMMING

Die doel van hierdie studie was om verskillende ooiproduktiwiteitsmaatstawwe te evalueer en om die mees effektiewe seleksiekriterium vir verhoogde totale massa lam gespeen per ooi gepaar in die Grootfontein Merino stoet en die Carnarvon Merinokudde te bepaal.

As gevolg van die feit dat sekere komponent-eienskappe van totale massa lam gespeen kategoriese eienskappe is, is besluit om dié eienskappe te evalueer d.m.v. >n drumpelwaarde metode. Die hoof doelwit van die eerste gedeelte van die studie was om oorerflikhede en teelwaardes vir verskeie reproduksie-eienskappe en lamoor-lewingstempo te beraam. Die volgende reproduksie-eienskappe is ontleed, naamlik vrugbaarheid (of >n ooi gelam het of nie; 0 of 1), fekunditeit (aantal lammers gebore per ooi gelam; 1, 2 of 3), aantal lammers gebore (aantal lammers gebore per ooi gepaar; 0, 1, 2 of 3), aantal lammers gespeen (aantal lammers gespeen per ooi gepaar; 0, 1, 2 of 3) en lamoorlewingstempo (of >n lam wat lewendig gebore is, dood of lewendig is met speen; 0 of 1).

Die beraamde oorerflikhede op die onderliggende skaal vir die onderskeie eienskappe was 0.072, 0.173, 0.131, 0.092 en 0.000 vir die Grootfontein Merinostoet en 0.203, 0.311, 0.201, 0.183 en 0.000 vir die Carnarvon Merinokudde onderskeidelik. Dit is duidelik van uit die beraamde oorerflikhede en ook die variasie van vaarteelwaardes vir die verskillende eienskappe dat die reproduksie-eienskappe, maar nie lamoorlewings-tempo nie, geneties deur seleksie verbeter kan word.

Die beste maatstaf vir >n ooi se leeftydsreproduksie is die saamgestelde eienskap totale massa lam gespeen. Vir die doel van die tweede gedeelte van hierdie studie is TWW (totale massa lam gespeen per ooi gepaar), NLB (aantal lammers gebore per ooi gepaar) en NLW (aantal lammers gespeen per ooi gepaar) oor drie lamkanse is geneem as >n indikasie van die leeftydsreproduksie van >n ooi. Die eienskappe NLB en NLW is gehanteer soos  kontinue-eienskappe aangesien dié eienskappe >n kombinasie van drie lamkanse is. Die hoof doelwit van hierdie gedeelte van die studie was om die direkte en gekorreleerde seleksieresponsie per generasie te bereken in totale massa lam gespeen per ooi gepaar (TWW), aantal lammers gebore (NLB), aantal lammers gespeen (NLW) oor drie lamkanse en individuele speenmassa van elke ooi (WW) vir seleksie gebaseer op TWW, NLB, NLW of WW. Vir hierdie doel is die genetiese en fenotipiese korrelasies tussen die eienskappe beraam. Dieselfde data as wat gebruik is vir die ontledings in die eerste deel van die studie was ook gebruik vir die berekening van die seleksieresponsies.

Beraamde oorerflikhede vir die onderskeie eienskappe was 0.19, 0.23, 0.17 en 0.21 vir die Grootfontein Merinostoet en 0.21, 0.19, 0.16 en 0.30 vir die Carnarvon Merino kudde. Hoë genetiese korrelasies (0.89 tot 0.98) tussen die reproduksie-eienskappe is vir beide kuddes bereken, terwyl genetiese korrelasies van WW met TWW, NLB en NLW matig was (0.32 tot 0.78). Die fenotipiese korrelasies tussen WW en die reproduksie-eienskappe was laag (0.04 tot 0.19), terwyl dié tussen die reproduksie-eienskappe matig was (0.71 tot 0.96). In die Grootfontein Merinostoet kan ongeveer dieselfde seleksieresponsie in TWW verwag word met direkte seleksie vir TWW (9.03kg) en indirekte seleksie vir NLB (9.20kg). In die Carnarvon Merinokudde kan die hoogste seleksieresponsie in TWW (6.37kg) met direkte seleksie vir TWW verwag word.

Vanaf die seleksieresponsies beraam in die studie is dit duidelik dat direkte seleksie vir TWW die mees geskikste seleksiekriteria is om reproduksieprestasie van >n ooi te verbeter, sonder om die aantal lammers gebore onnodig te verhoog. Vanuit die resultate van die studie is dit duidelik dat WW gemeet moet word, aangesien dit >n essensiële deel vorm in die evaluasie van ooiproduktiwiteit.

 

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Published

M.Sc. Agric.-Thesis. (U.O.F.S)