Previous Page Table of Contents Next Page


Studies on factors affecting reproductive performance and mortality rates of Small East African goats and their crosses

L.A. Mtenga1, G. C. Kifaro1 and Berhanu Belay2

1Department of Animal Science and Production Sokoine University of Agriculture, P. O. Box 3004, Chuo Kikuu, Morogoro, Tanzania
² Ministry of Agriculture, P. O. Box 30579, Addis Ababa, Ethiopia


Abstract
Introduction
Materials and methods
Results
Discussion
Conclusion
References


Abstract

This study compares genetic and non-genetic factors affecting the reproductive performance and mortality rates of Kamorai x Small East African (SEA), Boer x SEA and SEA goats using records kept at the Department of Animal Science and Production, Sokoine University of Agriculture, Tanzania, between 1972 and 1989.

Age at first kidding and kidding interval ranged from 638 to 984 days and 293 to 419 days, respectively. Age at first kidding was significantly (P<0.001) influenced by period of kidding. Period of kidding and season of previous kidding affected kidding interval significantly (P<0.01 and P<0.05, respectively).

Overall average mortality rate was 40.6% and 25.7% for preweaning and postweaning periods, respectively. Animals with birth weights of less than 1.5 kg had the highest preweaning mortality rate (57.9%). The lowest preweaning mortality rate occurred in animals with a birth weight of greater than 2.6 kg (29.8 %). Twins exhibited a higher preweaning mortality rate than singles (48.3% vs 38.5%). Preweaning mortality was lower in period I (1972-1974) than in later years.

Non-genetic factors, especially period and season of kidding, were the main sources of variation in reproductive performance and mortality rate. Crossing SEA goats with Kamorai and Boer showed little improvement in these factors. Poor feeding management and disease control probably prevented the crosses from expressing their genetic potential.

Etude des facteurs influant sur les performances de reproduction et la mortalité de la petite chèvre d'Afrique de l'Est et de ses produits de croisement

Résumé

Les données enregistrées entre 1972 et 1989 au Département de science et de production animales de l'Université agricole de Sokoine (Tanzanie) ont été utilisées pour comparer les facteurs génétiques et les facteurs non génétiques qui agissent sur les performances de reproduction et les taux de mortalité des caprins Kamorai x petite chèvre d'Afrique de l'Est, Boer x petite chèvre d'Afrique de l'Est, et petite chèvre d'Afrique de l'Est.

L'âge au premier vêlage était compris entre 638 et 984 jours, et l'intervalle de vêlage entre 293 et 419 jours. La période de mise-bas avait un effet significatif (P<0,01) sur l'âge au premier vêlage. La période et la saison des mises-bas précédentes avaient un effet significatif (respectivement P<0,01 et P<0,05) sur l'intervalle de mise-bas.

La mortalité générale moyenne était de 40,6% avant le sevrage, et de 25,7% après le sevrage. Les animaux pesant moins de 1,5 kg à la naissance présentaient le taux de mortalité présevrage le plus élevé (57,9%) et ceux pesant plus de 2,6 kg, le taux de mortalité présevrage le plus bas (29,8%). La mortalité présevrage des chevreaux issus de naissances gémellaires était supérieure (48,3%) à celle des agneaux nés simples (38,5%). La mortalité présevrage au cours de la période I (1972-1974) était inférieure à celle enregistrée les années suivantes.

Les facteurs non génétiques, en particulier la période et la saison de mise-bas, constituaient les principales sources de variation des performances de reproduction et de la mortalité. Le croisement de la petite chèvre de l'Afrique de l'Est avec des animaux de race Kamorai et Boer n'a pas apporté d'améliorations en ce qui concerne ces facteurs. La piètre conduite de l'alimentation et de la prophylaxie sanitaire a probablement empêché les sujets de croisement d'extérioriser leur potentiel génétique.

Introduction

Poor reproductive efficiency of tropical goats compared with temperate breeds has been documented in the literature (Wilson, 1989). However, tropical goats are able to adapt and reproduce under harsh environmental conditions (Kiwuwa, 1992) and have good fitness traits (Olayiwole and Adu, 1989; Kiwuwa, 1992). Rearing exotic goats under tropical conditions has disadvantages of high mortality and poor adaptation (Olayiwole and Adu, 1989; Kiwuwa, 1992). Tropical goats could be genetically improved by selecting for growth, reproduction and survivability. This has not been seriously undertaken because the process is time-consuming and expensive (Mchau, 1979). Good selection is also impossible in flocks with inadequate or non-existent records, as is the case in many developing countries (Olayiwole and Adu, 1989). Wilson (1989) and Kiwuwa (1992) suggest that selection should improve reproduction and growth while conserving the characteristics that adapt tropical goats to their environment. On the other hand it has been well documented (Kyomo, 1978; Mchau, 1979; Senyatso, 1986) that crossbreeding tropical goats with exotic 'improver' breeds could increase meat and milk production. This advantage has led to the introduction of crossbreeding programmes in Tanzania.

Data on the reproductive traits and mortality rates of the exotic Boer and indigenous Tanzanian goats and their crosses were collected at the Sokoine University of Agriculture between 1972 and 1989. Prior to this study the data had not been systematically analysed. The purpose of this study was to analyse the performance of the crossbred goats before their large-scale spread to the villages.

Materials and methods

Animals and management

The genetic groups involved in this study were the Small East African (SEA), Boer x SEA and Kamorai x SEA goats. The SEA goats were the dam line. This breed has been characterised by Mason and Maule (1960). The sire lines were the Boer and Kamorai, which have been characterised by Mason (1981). The goats were regularly provided concentrates between 1972 and 1974. Thereafter the regular provision of concentrates-was hampered by their scarcity.

Data collection and analyses

Data on reproductive traits were extracted from record cards for individual animals. Records on mortality rates were collected from liveweight records and yearly inventory books.

Reproductive traits studied were age at first kidding (AFK) and kidding interval (KI). For AFK the effects of genetic group, birth type of the first-kidding doe, season of birth and period of birth were studied. For KI the effects of genetic group, parity, season of previous kidding and period of kidding were studied.

AFK and KI were analysed using the GLM procedure in SAS (1988). The model used for the analysis of AFK was:

Yijklm = m +Bi+Tj+Mk+Rl+eijklm,

where:

Y = Age at first kidding (days)
i = genetic group (1-3)
j = type of birth (1 or 2)
k = season of birth (1-4)
l = period of birth (1-4)
m =doe
m = overall mean
B = the effect of genetic group
S = the effect of type of birth
M = the effect of season of birth
R = the effect of period of birth
e = the error term

The model used for analysing KI was:

Yijklm = m + Bi + Pj + Mk + Rl + eijklm

where:

Y = kidding interval (days)
m =doe
i = genetic group (1-3)
j = parity (1-3)
k = season of previous birth (1-4)
l = period of birth (1-4)
m = overall mean
B = effect of genetic group
P = effect of parity
M = effect of season of previous birth
R = effect of period of birth
e = error term

Seasons were grouped by weather pattern: season 1, February to April (late rains); season 2, May to July (cool dry season); season 3, August to October (hot dry season) and season 4, November to January (dry season). As there were only a small number of observations across the years, the data were divided into periods in order to assess effects over time: period 1 (1972-1974); period 2 (1975-1977); period 3 (1978-1980) and period 4 (>1981).

Mortality rates (MR) were determined for three periods: birth to weaning (16 weeks); 16 to 52 weeks of age; and birth to 52 weeks age. MR for each period was determined as the proportion of all kids born in period that have died.

Mortality rates were calculated by genetic group, sex, birth type, season of birth, period of birth and birth weight. These factors had further subclasses: genetic group (Kamorai x SEA, Boer x SEA and SEA); sex (male and female); birth type (singles and twins); and birth weight (1 to 1.5, 1.6 to 2.0, 2.1 to 2.5, 2.6 to 3.0 and 3.1 to 3.5 kg). Season and period of birth were classified in the same way as for reproductive traits.

The effects of the above factors on mortality rates were analysed using the chi-square test (X2) in a 2 x C contingency table (Snedecor and Cochran, 1989).

Results

Age at First

The overall mean age at first kidding during the whole period of the study was 810.78 days (SE = 172.73) (Table 1). Of the factors studied, only period of birth significantly (P<0.001) affected age at first kidding. Figures given in Table 1 show that does kidded at younger ages in periods 1 and 4 than in other periods. Although age at first kidding was not significantly affected (P>0.05) by birth type, female kids born as twins were on average 50.88 days older at first kidding than those born as singles.

Table 1. Least squares means and standard errors (days) for age at first kidding.

Effect

Age at first kidding (days)

n

Mean

SE

Overall mean

291

810.78

172.73

Genetic group




Kamorai x SEA

50

828.05

28.00

veer x SEA

61

806.34

26.31

SEA

180

790.44

18.47

Birth type




Single

210

782.83

15.83

Twins

81

833.71

27.11

Season of birth




1

49

833.36

28.63

2

75

832.99

25.33

3

88

798.08

23.34

4

79

768.67

24.15

Period of kidding




1

90

762.54b

16.70

2

75

883.0a

27.08

3

78

860.20a

26.47

4

48

728.26b

37.45

SE = Standard error.
ab = means within a column that have different superscripts are significantly different (P<0.03).

Kidding interval

Season of previous kidding and period of kidding had significant (P<0.05 and P<0.01, respectively) effects on the intervals between successive kiddings (Table 2). Does that kidded in season 1 had shorter subsequent kidding intervals than those kidding in other seasons. Does that kidded in period 4 had shorter subsequent kidding intervals than does that kidded in other periods. The differences in kidding intervals due to period of kidding were not significant (P>0.05) among periods 1, 2 and 3.

Table 2. Least squares means and standard errors (days) for kidding interval

Effect

Kidding interval (days)

n

Mean

SE

Overall mean

336

355.89

63.3

Genetic group





Kamorai x SEA

59

350.09

8.9


Boer x SEA

68

355.86

8.0


SEA

209

350.77

5.67

Parity





1

163

349.41

5.75


2

91

352.68

7.76


3

82

354.63

8.27

Season of previous kidding





1

44

331.31a

10.16


2

79

359.69b

7.78


3

85

362.08b

8.16


4

128

355.88b

6.54

Period of kidding





1

32

369.75a

12.66


2

166

365.83a

6.02


3

69

342.92a

8.12


4

69

325.45b

8.33

SE = standard error.
ab = means within the same column that have different superscripts are significantly different (P<0.05).

Mortality

The chi-square test indicated that differences in mortality rates among genetic groups were not significant (P>0.05). The Boer x SEA group had the highest mortality rates, SEA had the lowest and the Kamorai x SEA was intermediate (Table 3).

There was a significant influence (P<0.05) of birth type on the mortality rate of kids from birth to one year of age (Table 3). There was no significant difference (P>0.05) in mortality rate between singles and twins from 0 to 16 and 16 to 52 weeks of age. However, there was a tendency for the mortality rate to be higher for twins than for singles in all age groups (Table 3). Season of birth had a significant effect (P<0.05) on the mortality rate of kids from birth to 16 weeks and birth to one year. Kids born in season 1 had the highest mortality rate, followed by those born in season 2. Sex had no effect on mortality rate (P>0.05).

Birth weight had a significant effect on the mortality rate of kids from 0 to 16 weeks (P<0.01) and from 0 to 52 weeks of age (P<0.05). Mortality rate decreased with increasing birth weight (Table 3).

Preweaning mortality rate in kids was also significantly (P<0.05) affected by period of birth of the kids. Mortality rates were highest for kids born in period 4 and were lowest in kids born in period 1 (Table 3).

Table 3. Mortality rate of goat kids in different age groups by genetic group, sex, birth type, period of birth, season of birth and birth weight.

Factor

Birth to weaning

Weaning to 1 year

Birth to 1 year

Born

Died

(%)

At risk

Died

(%)

Born

Died

%

Genetic group











SEA

345

138

(40.0)

207

51

(24.6)

345

189

54.8


Boer x SEA

30

14

(46.7)

16

6

(37.5)

30

20

66.6


Kamorai x SEA

24

10

(41.7)

4

4

(28.6)

24

14

58.3

Total

399

162

(40.6)

237

61

(25.7)

399

223

55.9

Sex











Males

212

87

(41.0)

125

32

(25.6)

212

119

56.1


Females

187

75

(40.1)

112

29

(25.7)

187

104

55.6

Birth type











Single

312

120

(38.5)

192

45

(24.4)

312

165

52.9b


Twins

87

42

(48.3)

45

16

(29.9)

87

58

66.7a

Period of birth










1

1972-74

15

4

(26.7)

11

3

(27.3)

15

7

46.6

2

1975-77

81

25

(30.9)

56

12

(21.4)

81

37

45.7

3

1978-80

135

54

(40.0)

81

20

(24.7)

135

74

54.8

4

1981-

168

79

(47.0)

89

26

(29.2)

168

105

62.5

Season of birth











1 Nov-Jan

108

51

(47.2)

57

18

(31.6)

108

69

63.9


2 Feb-April

131

62

(47.3)

69

17

(24.6)

131

79

60.3


3 May-July

78

28

(35.9)

50

11

(22.0)

78

39

50.0


4 Aug-Oct

82

21

(25.6)

61

15

(24.6)

82

36

43.9

Birthweight (kg)











1.0-1.5

57

33

(57.9)

24

7

(29.2)

57

40

70.2


1.6-2.0

116

56

(48.3)

60

16

(26.6)

116

72

62.2


2.1-2.5

96

34

(35 4)

62

17

(27.4)

96

51

53.1


2.6-3.0

94

28

(29.8)

66

15

(22.7)

94

43

45.7


3.1-3.5

36

11

(30.5)

25

6

(24.0)

36

17

47.2

ab = means within the same column that have different superscripts are significantly different.

Discussion

Age at first kidding

The average age at first kidding was 810.78 days (SE=172.73). This value is close to those reported by Kyomo (1978) and Wilson and Murayi (1988), which range from 600 to 780 days for on-station studies. The values reported in this study are higher than those reported in studies of the traditional sector of sub-Saharan Africa, which range from 301 to 431 days (Wilson, 1988; Lebbie and Manzini, 1989). This is because, in this study, goats were mated for the first time at 72 weeks of age. It is also possible that feeding and general husbandry practices were substandard under station conditions, contributing to the greater age at first kidding in this study.

SEA goats tended to be younger than Kamorai x SEA and Boer x SEA at first kidding. Younger ages at first kidding for tropical goats compared with crosses have also been reported in the literature. Raja and Mukundan (1974) showed that purebred Malabari goats were younger at first kidding than were Jamunapari x Malabari goats. Wilson and Murayi (1988) also found that SEA goats were younger at first kidding than were Anglonubian x SEA goats. However, Devendra and Burns (1970) reported little variation in age at first kidding between Indian native and crossbred goats, and Kyomo (1978) found no difference between SEA and Kamorai x SEA goats.

Does born single tended to kid at a younger age than twins, which agrees with other findings (Wilson and Murayi, 1988; Wilson et al, 1989). Female twins were probably delayed in reaching puberty due to a lower-than-average growth rate (Wilson and Murayi, 1988; Wilson et al, 1989). For twins and singles to kid at the same age, twins may need supplements to their diet to encourage growth. This is especially true for twins from dams with low milk yields. Period of birth influenced age at first kidding, also reported by Wilson and Murayi (1988) and Wilson et al (1989). The effect of period of birth on age at first kidding was mainly a reflection of changed management practices (Wilson and Murayi, 1988), which was probably true for this study.

Kidding Interval

The overall mean kidding interval (Table 2) was close to values reported in studies carried out on experimental and multiplication stations in the tropics (Wilson and Murayi, 1988; Wilson et al, 1989). It is, however, longer than values found in the traditional sector, which ranged from 238 to 265 days (Wilson and Durkin, 1988; Lebbie and Manzini, 1989). The longer kidding intervals recorded on stations is the result of a controlled breeding policy imposed to achieve the best breeding season. Normally there is no imposition of seasonal breeding in the traditional sector and animals of all ages and sex run together day and night. In this study, although there was no well-defined seasonal breeding policy, mating was taking place only at night (between 1800 and 0800 hours), resulting in less exposure of the does for mating than in the traditional sector.

This study shows that the season of previous birth and period of birth were the only main sources of variation contributing to differences in kidding intervals. Does that had their previous kid in season 1 (late rains) showed shorter kidding intervals than does that gave birth in other seasons. This confirms the findings of Wilson and Murayi (1988), who reported shorter kidding intervals for dams that had their previous kid during the rainy season. Wilson and Durkin (1988) also reported a similar seasonal effect. This is possibly related to the availability of feed from pasture, which may have influenced ovulation rate and fertility.

The effect of period (year) of kidding on kidding interval has also been demonstrated by Adeoye (1985), Wilson and Durkin (1988) and Wilson and Murayi (1988). In this study the variation might have been associated with inconsistent management on the station.

Mortality

The effect of genetic group on mortality rate was small and non-significant. However, Boer x SEA tended to show higher mortality rates (Table 3). This is in agreement with other findings (Mchau, 1979; Senyatso, 1986). This may be due to the poor adaptation of Boer goats to harsh environmental conditions and increased susceptibility to disease. Similar conclusions have been drawn for crosses between Boer and indigenous tropical goats by Mchau (1979) and Senyatso (1986). In this study the major causes of mortality were not fully recorded. Nonetheless, from the limited records available, pneumonia seems to have been a major cause of death in kids.

Mortality was high in the preweaning period (Table 3). Similar results were reported by Kyomo (1978), Mchau (1979) and Sarmah et al (1981). Younger animals seem less able to withstand attack by both physical and biological agents due to their lack of immunity. This makes them more susceptible to enteric and respiratory infections (Ndamukong, 1985). Losses in the preweaning period can be minimised by providing proper shelter, prophylaxis and better nutrition.

This study showed that twins were more likely to die than were singles. This agrees with observations made by Sarmah et al (1981) and Wilson and Murayi (1988). Twins tended to have lower birth weights. Curtis (1969) concluded that animals with low birth weights had lower energy reserves and were therefore less able to withstand harsh environments; also if the dam has a poor milk yield, she may be unable to provide adequate nutrition for twins, thus increasing their susceptibility to disease.

Kids born during the wet season had a higher mortality rate than those born in the dry season. Similar trends have been reported elsewhere (Mazumdar et al, 1980; Sarmah et al, 1981; Chawla et al, 1982; Wilson, 1988). The higher mortality rate in the rainy season was associated with high rainfall and high relative humidity (Mazumdar et al, 1980), both of which are known to promote disease and parasitic infection.

The birth weight of the kid had an influence on pre and post-weaning mortality rates. This confirms earlier findings in tropical goats (Mazumdar et al, 1980; Singh et al, 1990). Mazumdar et al (1980) reported mortality rates of 100% for kids weighing 1.0 to 1.5 kg and 32.2% for kids weighing from 2.0 to 2.5 kg. This study shows a lower mortality rate for kids weighing 1.0 to 1.5 kg than Mazumdar et al (1980) (Table 3).

The effect of period of birth on viability of kids agrees with results published by Chawla et al (1982) and Wilson and Murayi (1988). Table 3 shows that kids born between 1972 and 1974 had lower pre-weaning and post-weaning mortality rates than those born in other periods. During this period disease prevention and feed provision were good. Thereafter, inconsistent management contributed to higher mortality rates. The standard of flock hygiene and disease monitoring needs improvement in order to lower mortality rates.

Conclusion

Crosses were expected to perform better in reproductive traits and survivability of kids compared to SEA goats but did not. This may be due to poor adaptation of the crosses and poor nutrition and disease control from 1975 to 1989.

References

Adeoye S A O. 1985. Reproductive performance of West African Dwarf goats in south-western Nigeria. In: Wilson R T and Bourzat D (eds), Small ruminants in African agriculture. Proceedings of a conference held at ILCA, Addis Ababa, Ethiopia, 30 September-4 October 1985. ILCA (International Livestock Centre for Africa), Addis Ababa, Ethiopia. pp. 19-24.

Chawla D S. Bhatnagar D S and Mishra R R. 1982. Factors affecting kid mortality in dairy goats. Indian Journal of Animal Sciences 52:166 171.

Curtis H J. 1969. Aging. In: Hafez E S E and Dyer I A (eds), Animal growth and nutrition. Lea and Fibger, Philadelphia, USA. pp. 165-174.

Devendra C and Burns M. 1970. Goat production in the tropics. Bureau of Animal Breeding and Genetics, Technical Communication 19. Commonwealth Agricultural Bureaux, Farnham Royal, UK. 184 pp.

Kiwuwa G H. 1992. Breeding strategies for small ruminant productivity in Africa. In: Rey B. Lebbie S H B and Reynolds L (eds), Small ruminant research and development in Africa. Proceedings of the First Biennial Conference of the African Small Ruminant Research Network, ILRAD (International Laboratory for Research on Animal Diseases), Nairobi, Kenya, 10-14 December 1990. ILCA (International Livestock Centre for Africa), Nairobi, Kenya. pp. 423-434.

Kyomo M L. 1978 Meat from goats in Tanzania. PhD thesis, University of Dar es Salaam, Tanzania. 292 pp.

Lebbie S H B and Manzini A T. 1989. The productivity of indigenous goats under traditional management in Swaziland. In: Wilson R T and Azeb Melaku (eds), African small ruminant research and development. Proceedings of a conference held at Bamenda, Cameroon, 18-25 January 1989. ILCA (International Livestock Centre for Africa), Addis Ababa, Ethiopia. pp. 39-50.

Mason I L. 1981. Breeds. In: Gall G (ed), Goat production. Academic Press, London, UK. pp. 57-110.

Mason I L and Maule J P. 1960. The indigenous livestock of Eastern and Southern Africa. Bureau of Animal Breeding and Genetics, Technical Communication 14. Commonwealth Agricultural Bureaux, Farnham Royal, UK. 151 pp.

Mazumdar N H. Mazumdar A and Goswami K K. 1980. Studies on some factors affecting mortality and survival rates in Pashmina kids. Indian Journal of Animal Sciences 50:251-255.

Mchau K W. 1979. Influence of Boer goats for crossing with Tanzanian goats. MSc thesis, University of Dar es Salaam, Tanzania. 92 pp.

Ndamukong K J N. 1985. Effects of management system on mortality of small ruminants in Bamenda, Cameroon. In: Wilson R T and Bourzat D (eds), Small ruminants in African agriculture. Proceedings of a conference held at ILCA, Addis Ababa, Ethiopia, 30 September 4 October 1985. ILCA (International Livestock Centre for Africa), Addis Ababa, Ethiopia. pp. 108-116.

Olayiwole M B and Adu I F. 1989. Past and present research on sheep and goats breeding in Nigeria. In: Adeniji K O (ed), Improvement of small ruminants in West and central Africa. Proceedings of a workshop held at Ibadan, Nigeria, 21-25 November 1988. OAU (Organization of African Unity), Nairobi, Kenya. pp. 61-69.

Raja C A and Mukundan G.1974. Age at first kidding, kidding rate and kidding interval in Malabari and Majunapari-Malabari crosses. Karala Journal of Veterinary Science 4:165-169.

Sarmah P C, Thakuria K, Sarma H K, Borah H P. Mohan M and Pant K P. 1981. Note on kid mortality in Assam local breed. Indian Journal of Animal Sciences 51:248-249.

SAS (Statistical Analysis System). 1988. Statistical analysis system user's guide. Statistical Analysis System Institute, North Carolina, USA. 1028 pp.

Senyatso E K. 1986. Performance of sheep and goats in Botswana comparative studies. II. In: Adeniji K O and Kategile J A (eds), Improvement of small ruminants in eastern and southern Africa. Proceedings of a workshop held at Nairobi, Kenya, 10-14 December 1986. IBAR (Inter African Bureau for Animal Resources), Nairobi, Kenya. pp. 61-66.

Singh D K, Mishra H R and Singh C S P. 1990. Genetic and non-genetic factors affecting pre-weaning survivability in kids. Animal Production 51:504-559.

Snedecor G W and Cochran W G. 1989. Statistical methods. 8th ed. Iowa State University Press, Ames, Iowa, USA. 503 pp.

Wilson R T. 1988. The productivity of Sahel goats and sheep under transhumant management in northern Burkina Faso. Bulletin of Animal Health and Production in Africa 36:348-355.

Wilson R T. 1989. Reproductive performance of African indigenous small ruminants under various management systems: a review. Animal Reproduction Science 20:265-286.

Wilson R T and Durkin J. 1988. Livestock production in central Mali: Reproductive components in traditionally managed sheep and goats. Livestock Production Science 19:523-529.

Wilson R T and Murayi T. 1988. Productivity of the Small East African goat and its crosses with Anglonubian and the Alpine in Rwanda. Tropical Animal Health and Production 20:219-228.

Wilson R T. Murayi T and Rocha R. 1989. Indigenous African small ruminant strains with potentially high reproductive performance. Small Ruminant Research 2:107-117.


Previous Page Top of Page Next Page