Livestock Research for Rural Development 23 (12) 2011 Guide for preparation of papers LRRD Newsletter

Citation of this paper

An analysis of inbreeding levels and factors affecting growth and reproductive traits in the Kenya Alpine dairy goat

A G Marete, J O Jung’a and R O Mosi*

Department of Animal production, University of Nairobi, Kenya
P.O.Box 23435-00100 Nairobi, Kenya
gitahimart@gmail.com
* School of Agriculture, Food Security and Biodiversity, Bondo University College

Abstract

The level of inbreeding of the Kenya Alpine dairy goat was investigated by use of Brian Kinghorn’s Pedigree viewer software. From 1,067 doe records, data on parentage was extracted and this resulted to 3,516 individual records that were used for calculating individual inbreeding coefficients for the period 1999 to 2009. The rate of inbreeding (ΔF) was estimated as the difference between the individual inbreeding (Ft) and the inbreeding of the parents (Ft-1) divided by (1-Ft-1).

The proportion of animals that was inbred increased from 0.00 (average F = 0) in 1990 to 0.38 in 2009 (average F = 0.012). Inbreeding depression on body weight was significant (P<0.05). In general the level of inbreeding in this population was very low. Further investigation on the birth weight and weaning weight was carried out. Regression analysis indicated that birth weight (p<0.05) and weaning weight (p<0.01) had improved in inbreds. The decrease in weight at first service and at first kidding was statistically insignificant. Kidding interval increased (p<0.01) due to inbreeding. Rate of decline in weight at first service and at first kidding, was different from zero (p<0.01). Effect of inbreeding on growth and reproductive traits in Kenya Alpine goats was not very pronounced in the flock.  

Keywords: foundation, genetic, mating, pedigree, phenotypic


Introduction

The unavoidable mating of related animals in closed populations leads to accumulation of inbreeding and decreased genetic diversity. Inbreeding has deleterious effect on additive genetic variance as well as on phenotypic values (Falconer and Mackay 1996). Heterozygosity and allelic diversities can be lost from small, closed, selected populations at a rapid rate. The loss of diversity and resulting increase in homozygosity may result in decreased productions and/or fitness of inbred animals. Furthermore inbreeding depression in domestic animals can lead to a decrease in selection response and in potential genetic gains in economic traits. Measurement of the effect of inbreeding on these traits is important in order to estimate the magnitude of change associated with increases in inbreeding. Inbreeding impairs growth, production, health, reproduction traits (such as fertility) and survival. The emergence of disorders due to recessive gene action may also occur. It is apparent that different breeds and populations, as well as different traits vary in their response to inbreeding. Some populations may show a very pronounced effect of increased inbreeding for a trait, whereas others may not demonstrate much of an effect (Analla et al 1998).

The rate of inbreeding needs to be limited to maintain diversity at an acceptable level so that genetic variation will ensure that future animals can respond to changes in the environment and to selection. Without genetic variation, animals cannot adapt to these changes (van Wyk et al 2009). The Kenya Alpine dairy goat breeding has been implemented for close to twenty years, during which period breeding bucks were sourced from Germany. The foundation stock was all from German Alpine with no records of their pedigrees. There was repeated sourcing of breeding bucks from Germany but due to lack of proper recording, it was not clear if considerations were made about their relationships. Eventually, due to the outbreak of the “Bovine Spongiform Encephalopathy” (Mad Cow Disease) in Europe, importation of live animals was banned. Since then, breeding bucks have been sourced locally from within the small Alpine population but without proper records and procedures to establish their relationships, they could not be used to control inbreeding. The breed has not yet been stabilized and therefore effects of inbreeding would reverse the initial breeding objectives. Although inbreeding leads to reduced fitness, the degree to which populations suffer from inbreeding and its effects can vary widely depending on population history, the trait examined lineage effect and the environment (Pray and Goodnight 1995; Husband and Schemske 1996; Dudash et al 1997; Bijma et al 1999; Reed and Bryant 2001; Frankham et al 2002; Reed and Frankham 2002).

The objective of this study was to analyze the rate of inbreeding in Kenya Alpine dairy goat and its effects on production and reproduction. 


Materials and Methods

The study animals

The Kenya Alpine dairy goat was used in this study. The breed was developed by crossing and grading-up of the East African goat using  the German Alpine buck in an effort to providing alternative source of income to small scale farmers’ in Kenya. For over 10 years, the Kenya Alpine dairy goats were bred through natural service, a process characterized by buck rotation facilitated by the Dairy Goat Association of Kenya. The goats were usually stall-fed and every household has on average between 3-6 goats. Milking was usually done in the morning after kids have suckled. The four genetic groups include:

            i.  Foundation (50% Alpine) - F1:  Pedigreee Alpine Buck (PAB) x Local doe.

            ii. Intermediate (75% Alpine) - Back cross 1 (R1):  PAB x F1 Females.

              iii. Appendix (87.5% Alpine) - Back cross 2 (R2):  PAB x R1.

              iv. Pedigree (≥87.5%):

                    a)      Interse mating of Back cross 2: R2 Male x R2 Female.  Offspring will remain 87.5% or more.

                    b)      PAB x R2 female- Grading-up. Offspring will be 93.25% or  more. 

Kenya Alpine dairy goats usually live in the Central and Eastern highlands of Nyeri and Meru Districts respectively, but in recent years they have spread to other areas of lower potential compared to the original entry areas. These areas are characterized by a humid to sub-humid climate with long, wet and cold wet seasons. Herds are usually zero grazed and stall fed on greens and very little or no concentrate supplementation is provided. Water is also provided in the shed. The kidding season is usually not synchronized but rather depends on conditions of pasture.

The onset of the bovine spongiform encephalopathy prompted the banning of importation of live animals from Germany and therefore breeding bucks were sourced from the local population. However, recently there has been an increasing concern in the manifestations of inbreeding effects in the dairy breed and thus the need to know the inbreeding rates in order to be able to plan a better breeding program. 

Data

Initially, 1,829 dairy card records were collected from individual farm house holds within the eight study districts. These records were made for the period starting from January 1999 and ending in January 2010. Out of these, 762 dairy card records (41.7%) were deemed to be outliers and the remaining 1,067dairy card records of does were used in this study. These records included the Animal tattoo number, Breeder, birth weight (Bwt), weaning weight (Wwt), age at first service (AFS) and consequent services, age at first kidding (AFK) and consequent kiddings, as well as paternal and maternal parents and grandparents. From these 1,067 dairy card doe records, information on parentage was extracted resulting in 3,516 records which were used for pedigree analysis.  The birth and weaning weights were measured at 7014days.

The kids were weaned at 403 days. Birth and weaning weights were measured for all the animals; Reproductive traits were evaluated on a total of 1282 records where three different ratios calculated as follow: fertility (% of does kidding of does bred); prolificacy (% of kids born of does kidding); fecundity (% of kids born of does bred).

Pedigree completeness was assessed by tracing back the pedigrees for five generations. Individual inbreeding coefficients (F) were calculated according to Wright’s equation (Wright 1922):

Fx = Σ ()n (1 + Fa)

Where F is the inbreeding coefficient of each animal; n the number of generations between the sire and dam respectively and their common ancestor; Fa is the inbreeding coefficient of the ancestor, common to both the sire and dam.  

 Statistical Analysis

Separate analyses were carried out to determine the overall effects of inbreeding in the Kenya Alpine dairy goat. The first two analyses were conducted to estimate the effect of fixed factors on growth traits and the effect of fixed factors on reproductive traits. Fixed effects affecting growth included the Age at first service, effect of type of birth, effect of month of birth and effect of the area of birth. These were fitted in Model I below. The fixed effects affecting reproduction included the effect of age at first kidding, effect of age at first service, the effect of type of birth, the effect of birth weight and effect of adjusted weaning weight at 70 days. These were fitted in model II. Analysis of fixed effects on the various traits was done using Statistical Analysis Software (SAS) Version 9.0. Estimation of means and frequencies, generalized linear models (GLM), Analysis of variance (ANOVA), was done using the same software. Initial population estimates such as population structure and grade distribution were done using Microsoft ExcelTM package version 2007. Data was sorted and re-arranged using Microsoft AccessTM package version 2007. Inbreeding estimates were carried out using Brian Kinghorn’s Pedigree Viewer software version 5.5. 

Model I

Model I was used to estimate the effect of fixed factors on growth traits and the following model was fitted:

Yijkl = + Gi + Sj +Yk +Al +GSij +GAik +eijklm

 Where,

Yijkl is the observed mth parameter of a goat in the ith genetic group (I = 1, 5), born in the jth season of birth, in the kth year and in the lth area (a=1,4)

- is the underlying constant in each observation;

Gi is the effect of the ith genetic group;

Sj- is the effect of the jth season of birth;

Yk- Is the effect of the kth year of birth;

Al- is the effect of the lth area of birth;

GSij - is the effect due to interaction in the ith genetic group and the jth season;

GAik- is the interaction due to the ith genetic group and the lth area of birth;

eijklm- is the effect of random unpredictable factors, assumed to be normally distributed with a mean 0 and a variance, σ2 =1. 

Model II

Model II was used to estimate the effect of fixed factors on reproduction and the following model was fitted:

Yijkl = + Gi + Sj +Yk +Al +GSij +GAik +eijkl

 Where,

Yijkl is the observed ith AFK of a goat in the ith genetic group (I = 1, 5), born in the jth season of birth, in the kth year and in the lth area (l=1, 4)

- is the underlying constant in each observation;

Gi is the effect of the ith genetic group;

Sj- is the effect of the jth season of birth

Yk- Is the effect of the kth year of birth

Al- is the effect of the lth area of birth

GSij - is the effect due to interaction in the ith genetic group and the jth season

GAik- is the interaction due to the ith genetic group and the lth area of birth

eijkl- is the effect of random unpredictable factors, assumed to be normally distributed with a mean 0 and a variance σ2 =1. 


Results

3,516 goat records were available for this study and are presented in Table 1. Pedigree accounted for 32% of the records, Appendix 25%, Intermediate 16% and Foundation 27%. The range and frequency of inbreeding coefficients are presented in Table 2. Over 90% of the records had zero inbreeding. Over 7% had an inbreeding coefficient of 10% or less and 3% had an inbreeding coefficient of 13% or less. The rate of inbreeding was 0.019 F/year. For the different genetic groups, the rate of inbreeding was 0.184 Pedigree, 0.192 for Appendix, 0.201 for Intermediate and 0.253 for Foundation. Rates of inbreeding were not significantly different for all genetic groups; however, the rate of inbreeding was significantly lower for pedigree than for the other three grades.  

Table 1: Distribution of goat records by grade

Genetic group

Number of records

Percentage

Pedigree

1,125

32.00

Appendix

879

25.00

Intermediate

563

16.01

Foundation

949

26.99

Total

3,516

100.00



Table 2: Distribution of inbreeding coefficient (F)

F (%)

No.

Percent

0

3164

90.00

1

57

1.62

2

37

1.05

3

32

0.91

4

25

0.71

5

22

0.63

6

34

0.97

7

12

0.34

8

17

0.48

9

10

0.28

10

46

1.31

11

21

0.60

12

16

0.46

13

15

0.43

14

8

0.23

11

21

0.60

12

16

0.46

13

15

0.43

14

8

0.23

The analysis of pedigree (>87.5% pure) revealed that 13 animals out of 3,516 (0.40%) had a high inbreeding coefficient (F≥10%) with a mean value of 13.10% while the remaining 99.60% of doe kids were non-inbred. 

Birth and weaning weights

The means procedure of SAS showed that the Kenyan Alpine goats have a minimum birth weight of 1.5 kg and a maximum of 3.10 kg with a coefficient of variation of 17.3%. The youngest animal to be weaned in the sample population was around one and a half months and the oldest to be weaned was roughly three months old with a mean weaning age of 60.7811.51 days. The year and month of birth both significantly affected the birth weight at P<0.5 whereas the type of birth and area of birth were significant at P<0.001.

The area which recorded highest birth weight was Murang’a District with 3.4kg (P<0.0001) with Embu District recording the lowest birth weight of 3.1 kg (P<0.001). Kirinyaga, Nyeri and Vihiga Districts recorded similar birth weights with an interval 3.21≤BWt≤ 3.35.

Table 3: ANOVA of factors affecting birth weight (Bwt)

Source

DF

Sum of Squares

Mean Square

F Value

Pr > F

Genetic group

4

5.84

1.46

5.36

0.0003

Type of birth (ToB)

2

7.15

3.58

13.14

<.0001

Year of birth (YoB)

16

4.81

0.301

1.11

0.345

Month of birth (MoB)

11

3.93

0.357

1.31

0.211

Area of Birth (AoB)

4

9.97

2.49

9.15

<.0001

R2

CV

Root MSE

Mean Bwt

 

 

0.106

16.78

0.522

3.11

 

 



Table 4: Cumulative frequency table on kids born and kids weaned

Type of Birth (ToB)

No. of kidding does

No. of kids born

Kids born (%)

No. of kids weaned

Kids weaned (%)

Kids born cumulative  Frequency

Kids weaned cumulative  Frequency

Single

345

345

39.93

266

77.10

345

266

Twin

246

492

56.94

285

57.92

837

551

Triplet

9

27

3.13

25

3.55

864

576

Total

600

864

100.00

576

66.67

-

-



a.       Fecundity rate = (Total births @kidding/total females @mating)* 100%

      =864/1067*100

      = 80.97%

b.      Fertility rate = (total does @birth/Total does @mating)*100%

= 600/1067*100

=56.23%

c.       Prolificacy = (Total of births/ Total of kidding does) *100%

= 864/600*100

=144%

Or

Prolificacy = Fecundity/ Fertility

= 80.97/ 56.23

=1.44 

Kidding interval days open and gestation period

Means of the Kidding Interval, the days open and gestation period were estimated using the means procedure of SAS, and the results are as shown in Table 5. Kidding interval ranged from 181days to 1203days with a mean of 392164 days. The days open also varied from between 30-1058days with a mean of 242166 days, but since the gestation period is biologically controlled, it had a very solid mean of 15219 days and a very small coefficient of variation of 12.55%.

An ANOVA was then carried out to discern effects on Kidding Interval by the five sources of variation as shown in Table 6. The grade, type of birth and area were not significant at P>0.05, but the month of kidding had an effect on the kidding interval (P<0.05). The year of kidding also had a significant effect at P<0.01.

Within the grades, KI revolves around 33515days with Local (0% Alpine) having the lowest KI of 321 days and Appendix (87.5% Alpine) the highest of 349 days. Pedigree (>87.5% Alpine) and Intermediate (75% Alpine) had almost similar KI of 333 and 334 days respectively whereas Foundation (50% Alpine) registered a KI of 345 days.

The month of kidding was most significant effect (P<0.05) so was the year of kidding (P<0.01). 

Table 5: ANOVA of factors affecting kidding interval (KI)

Source

DF

Sums of Squares

Mean Square

F Value

Pr > F

Genetic group

4

18842.40

4710.60

0.19

0.94

Type of birth (ToB)

2

47304.26

23652.13

0.95

0.39

Year of kidding (YoK)

11

1141189.98

103744.54

4.17

<.0001

Month of birth (MoB)

11

548168.63

49833.51

2.00

0.027

Area of birth (AoB)

5

74065.89

14813.18

0.60

0.704

R2

CV

Root MSE

Mean KI

 

 

0.17

40.36

157.74

390.88

 

 

Conclusions

Based on the scope and limitations of this study, the following conclusions were made:

  1. From the analysis carried out, there is not enough evidence to show that the Kenya Alpine dairy goat population is inbred. However there is imminent inbreeding as demonstrated by the physical sign in some of the animals such as under developed udders, bisexual individuals.

  2. While there was no significant difference in the growth of the different genetic groups of the Kenya Alpine dairy goat, their growth was most affected by the type of birth, the season of birth and the birth weight of the kid.

  3. The study showed that though Nyeri district was the pioneer district of the Kenya Alpine dairy goat, the breed has spread out in other areas of Central, Eastern and Western provinces. This meant that the Kenya Alpine dairy goat is continually being accepted as an alternative small holder milk production breed. However, the different genetic groups need to be vetted at different levels, to avoid erroneous registration of animals in genetic groups that they do not belong.


Recommendations

  1. In any population, there is always an acceptable level of inbreeding; the challenge usually is how to control this inbreeding. In the case of the Kenya Alpine dairy goats, there was no clear breeding programme and therefore, inbreeding could occur. There is therefore need to have a breeding programme and recording scheme developed.

  2. Lack of adequate data on parentage of these goats and health records made it difficult to carry out more studies on genetic relationships and on more economically important traits. Dairy Goat Association of Kenya should therefore enhance proper recording procedures that aim to capture all the vital information of an individual goat.

  3. A breeding programme for the Kenya Alpine dairy goat should be developed and implemented by a trained animal breeder. Furthermore, new software for buck rotation should be developed and put to use.


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Received 18 October 2011; Accepted 28 November 2011; Published 1 December 2011

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