Growth traits of the Dorper sheep I. Factors influencing growth traits - Paramètres de croissance du mouton Dorper I. Facteurs agissant sur les paramètres de croissance

Abstract
Résumé
Introduction
Materials and methods
Results and discussion
Conclusion
Acknowledgement
References

B.A.O. Inyangala¹, J.E.O Rege¹ and S. Itulya²

¹Animal Production Department, University of Nairobi
P O Box 29053, Nairobi, Kenya

²Animal Science Department, Egerton University, P O Box 536, Njoro, Kenya

Abstract

Data on 969 Dorper lambs collected over a 10-year period (1978 to 1987) at Ol'Magogo were used in this study. Lamb traits studied were weights from birth to yearling and absolute growth rates between adjacent stages of growth. All the fixed effects studied influenced growth in one way or another. Sex was highly significant for all traits (P<0.01) except growth rates between weaning and six months (GR2), and six to nine months (GR3), and season of birth influenced all traits significantly (P<0.05) except birthweight (BIRTHW), growth rates between weaning and six months (GR2), and between nine and twelve months (GR4). The effect of parity was confined to pre-weaning traits (P<0.05), while period of birth was significant (P<0.05) on all traits except yearling weight (ADJTMW) and growth rate between weaning and six months (GR2).

Résumé

Cette étude repose sur les données recueillies pendant 10 ans (1978 à 1987) sur 969 agneaux de race Dorper à OL'Magogo Naivasha. Les paramètres étudiés sont le poids des agneaux de la naissance, à l'âge de 1 an, et leurs taux de croissance absolus à intervalles de temps consécutifs. Tous les effets fixes examinés influençaient la croissance d'une manière ou d'une autre. L'effet du sexe était très significatif pour tous les paramètres étudiés (P<0,01), à l'exception des taux de croissance entre le sevrage et l'âge de 6 mois (GR2) et entre 6 et 9 mois (GR3). La saison de naissance a montré un effet significatif (P < 0, 05) sur tous les paramètres excepté sur le poids à la naissance (BIRTHW), et les taux de croissance entre le sevrage et l'âge de 6 mois (GR2) et entre 9 et 12 mois (GR4). Alors que l'effet du rang de la naissance se limitait aux seuls paramètres examinés avant le sevrage, la saison de la naissance avait un effet significatif (P<0,05) sur tous les paramètres étudiés excepté sur le poids à 1 an (ADJTMW) et/e taux de croissance entre le sevrage et l'âge de 6 mois (GR2)

Introduction

The Dorper breed was developed in South Africa around 1942, mainly at Grootfontein College of Agriculture from initial crosses between Blackhead Persian ewes and Dorset Horn rams. The Dorper has a reputation for its adaptability to rather harsh environment. Characteristics of the breed include the ability to walk long distances and forage well in permanently dry areas and in times of drought, good mothering ability in the ewes, high ram fertility and vigour, excellent carcass conformation for good mutton production in comparison with the indigenous breeds and an unrestricted breeding season.

In Kenya, Dorper sheep accrue income mainly from meat and sale of surplus stock. Bodyweight and rate of gain are among the most economically important and easily measured traits of meat animals. Although weight is an important objective in selection, knowledge of the particular phase of the animal's growth upon which to base selection is of utmost importance. Studies on the environmental factors influencing growth traits are few for sheep reared under Kenyan conditions. Gumedze (1979) studied fertility in Dorper sheep at Ol'Magogo. Ouko Odenya (1982) and Kiriro (1986) studied lamb traits only up to weaning. A majority of studies have reported the performance of temperate sheep. There is an extreme paucity of information regarding the performance of sheep raised in Kenya.

The purpose of this study was to investigate environmental sources of variation influencing growth traits in a flock of Dorper sheep at various stages of growth, from birth to yearling.

Materials and methods

The data used in this study consisted of growth records of 969 Dorper lambs. These data were collected from records of the Sheep and Goat Development

Project (SGDP) based at Ol'Magogo, a substation of the National Animal Husbandry Research Centre (NAHRC), Naivasha, between 1978 through 1987.

Bodyweights analysed included weight at birth, at three months (weaning), at six months, at nine months and at months (yearling). Lambs were nursed by their dams up to weaning. Each lamb record included sire, dam and lamb identifications, type of birth and sex. Three seasons of birth were defined on the basis of the monthly rainfall distribution. Two rainy seasons were identified with April and May (season 1) forming the peak of the long rains while October and November were classified as a season of short rains (season 2). The remaining months were classified as a dry season (season 3).

Parities were defined based on the number of times the ewes had lambed giving rise to parties 1, 2,3 and 4, the latter comprising ewes with 4 or more lambings. Due to disproportionate distribution of data across years which resulted into discontinuity in the data, it was not possible to include actual years in the analysis. Therefore, to adjust for differences in weather conditions across years, periods of birth were defined by grouping adjacent years on the basis of annual rainfall pattern. This otherwise uncommon-grouping method was implemented after examination of meteorological data, and was felt to be the best method under the circumstances. Period 1 consisted of the years 1978-1980 which received the highest rainfall, period 2 (1981-1985) received intermediate amounts while period 3 (1986-1987) received the lowest.

The absolute growth rates were derived by taking the difference in weight within the period and dividing it by the time interval in days. The absolute rate of gain for each lamb was calculated over five growth periods namely: Birth to weaning (GR1), weaning to six months (GR2), six to nine months (GR3), nine to 12 months (GR4) and birth to 12 months (OVRGRT). These, together with the bodyweights, constitute the 10 traits analysed in this study.

In view of the differences in actual age at which weights were taken, the latter were preadjusted as follows:

ADJWWT (adjusted 90-day weaning weight) = GR1 X 90 days + birthweight (BIRTHW)
ADJSMW (adjusted six-months weight) = GR2 X 90 days + ADJWWT
ADJNMW (adjusted nine-months weight) = GR3 X 90 days + ADJSMW
ADJTMW (adjusted 12 months weight) = GR4 X 90 days + ADJNMW.

Adjustment for fixed effects (sex, season of birth, period of birth, parity and dam breed) was achieved by including them in the model.

Statistical analysis: The statistical model used to relate-observations with independent variables was as follows:

Y_ijklmn = u + a _i + b_j + c_k + d_l + f_m + e _ijklmn

where

Y_ijklmn = the ijkimnp^th observation
u = an underlying constant for the trait
a_i = effect of the th sire (i= 1, ......, 63)

assumed random, N(O)

b_j = effect of the j^th season of birth (j = 1 2, 3)
c_k = effect of the k^th parity (k= 1, 2, 3, 4)
d_l = effect of the l^th period of birth (I= 1, 2, 3)
f_m = effect of the m^th sex (1 =male, 2=female)
e_ijlkm = random error associated with the ijklmnp^th observation; N (O)

The Least Squares Method (Harvey, 1982) in which sires were cross-classified with fixed effects was used in the analysis of the data.

Results and discussion

Analysis of fixed effects

Analysis of variance for bodyweights and growth rates are presented in Tables 1 and 2, respectively. Corresponding least squares means are presented in Tables 3 and 4 by subclasses.

Sex

Least squares means (Tables 3 and 4) indicate that male lambs performed, in all cases, considerably better than their female counterparts. These differences were significant (at least at P<0.05 level) for all the baits except for pre-weaning growth rate (GR2) and (GR3) for which it was not significant. Consistent superiority of male lambs has been widely reported (sass and Acharya, 1970; Vesely and Robison, 1970; Magid et al, 1981; Fitzhugh and Bradford, 1983; and Kiriro, 1986). This has been attributed to hormonal differences between sexes and their resultant effects on growth (Velardo, 1958; Bell et al, 1970).

Table 1. Analysis of variance of bodyweights (Dorper sheep).

Source of	Mean squares variation
	df	Birth	ADJWWT	ADJSMW	ADJNMW	ADJTMW
Sires	62	0.68**	18.14***	43.23***	66.03***	91.54***
Sex	1	9.44***	366.87***	525.05***	520.03***	1406.72***
Season of birth	2	0.04	65.18*	88.77**	105.03**	107.46*
Parity	3	2.13***	48.49**	23.27	7.48	1.16
Period of birth	2	1.40*	204.37***	321.42***	773.03***	73.20
Error	898	0.43	10.62	15.79	17.79	25.59

*** P<0.001; ** P<0.01; * P<0.05.

ADJWWT = adjusted 90-day weaning weight	ADJNMW = adjusted nine-months weight
ADJSMW = adjusted six-months weight	ADJTMW = adjusted 12-months (yearling) weight.

Table 2. Analysis of variance of growth rate (Dorper sheep).

Source of variation	Mean squares
	df	GR1	GR2	GR3	GR4	OVRGRT
Sires	62	0.002**	0.003***	0.005***	0.005***	0.001 ***
Sex	1	0.032***	0.002	0.000	0.027**	0.005***
Season of birth	2	0.009***	0.001	0.005*	0.004	0.004***
Parity	3	0.004*	0.001	0.001	0.001	0.000
Period of birth	2	0.022***	0.003	0.004***	0.070***	0.001**
Error	898	0.001	0.001	0.001	0.002-	0.0002

*** P < 0.001; ** P < 0.01; * P < 0.05.

GR3 = six to nine months

GR1 = birth to weaning	FR4 = nine to twelve months
GR2 = weaning to six months	OVRGRT = birth to 12 months.

Table 3. Least squares means and standard errors of bodyweights (Dorpers).

Category		No. of observations	Birth(kg)	ADJWWT (kg)	ADJSMW (kg)	ADJNMW (kg)	ADJTMW (kg)
Overall mean± SE		969	4.12±0.10	19.48±0.51	24.62±0.85	29.68±1.09	35.92±1.28
Males		469	4.22±0.10	20.12±0.52	25.39±0.87	30.44±1.10	37.17±1.29
Females		500	4.01±0.10	18.84±0.52	23.85±0.86	28.92±1.10	34.66±1.29
Season of birth	1	380	4.10±0.10	20.22±0.50	25.15±0.85	29.31±1.08	36.44±1.27
	2	17	4.16±0.18-	17.68±0.93	22.89±1.27	29.18±1.48	34.08±1.75
	3	572	4.09±0.09	20.54±0.46	25.82±0.81	30.54±1.05	37.22±1.23
Parity	1	622	3.98±0.10	18.61±0.51	24.00±0.85	29.36±1.09	35.79±1.27
	2	236	4.20±0.10	19.52±0.52	24.61±1.87	29.47±1.10	35.93±1.29
	3	82	4.14±0.12	19.73±0.61	24.72±0.95	29.55±1.17	35.88±1.38
	4	29	4.14±0.12	19.73±0.61	24.72±0.95	29.55±1.17	35.88±1.38
Period of birth	1	578	4.37±0.17	20.02±0.86	24.37±1.20	30.64±1.41	38.14±1.67
	2	170	3.91±0.13	17.45±0.66	22.41±099	25.76±1.21	34.51±1.43
	3	221	4.06±0.14	20.97±0.72	27.07±1.05	32.64±1.27	35.10±1.50

For abbreviations see Tables 1 and 2.

Table 4. Least squares. means and standard errors of rates of growth (Dorpers).

Category		No. of observations	GR1 (kg/d)	GR2 (kg/d)	GR3 (kg/d)	GR4 (kg/d)	DVRGRT (kg/d)
Overall means ± SE		969	0.170±0.005	0.057±0.007	0.056±0.009	0.069±0.009	0.098±0.004
Males		469	0.176±0.005	0.058±0.007	0.056±0.009	0.074±0.010	0.100±0.004
Females		500	0.164±0.005	0.055±0.007	0.056±0.009	0.063±0.009	0.095±0.004
Season of birth	1	380	0.179±0.005	0.054±0.007	0.046±0.009	0.079±0.009	0.089±0.004
	2	17	0.150±0.010	0.057±0.011	0.069±0.012	0.054±0.013	0.114±0.005
	3	572	0.182±0.004	0.058±0.006	0.052±0.009	0.074±0.009	0.090±0.003
Parity	1	622	0.162±0.005	0.059±0.007	0.059±0.009	0.071±0.009	0097-±0004
	2	236	0.170±0.005	0.056±0.007	0.053±0.009	0.071 0.010	0.096±0.004
	3	82	0.173±0.006	0.055±0.008	0.053±0.009	0.070±0.010	0.098±0.004
	4	29	0.176±0.008	0.056±0.009	0.057±0.011	0.063±0.012	0.099±0.005
Period of birth	1	578	0.173±0.009	0.048±0.010	0.069±0.012	0.083±0.013	0.099±0.005
	2	170	0.150±0.007	0.055±0.008	0.037±0.010	0.097±0.011	0.092±0.004
	3	221	- 0.187±0.007	0.067±0.009	0.061±0.011	0.027±0.011	0.101±0.004

For abbreviations, see Tables 1 and 2.

Season of birth

The effect of season of birth was significant for all traits except birthweight, preweaning growth rate and growth in the interval six to nine months. The effect of season of birth arises from seasonal variation in the physical environment resulting from changes in weather conditions (including rainfall amounts, temperature, and humidity) which directly affect feed availability, especially in a situation (such as is the case in this study) with no supplementary feed. Seasonal influence on a trait such as birthweight operates through its effect on the dam's uterine environment mostly in late gestation (Eltawil et al, 1970). Such factors operating in seasons prior to lambing will be manifested in birthweight. This may explain the higher (albeit non-significant) birthweight of lambs born in the dry season, lambs born in the long dry season during the critical stages of gestation. Such lambs would be expected to weigh more at birth compared to those whose dams underwent a nutritionally stressful period during gestation. It is, therefore, expected that the season when the ewe is in gestation is likely to play a more important role in birthweight than the actual season of birth. On the other hand, season of birth plays an important role in growth performance indirectly through its influence on the dam's nutrition (and hence amount of milk available to the unweaned lamb) and later, directly, through its effect on the pasture availability and quality on which the lamb is subsequently weaned. Growth traits are known to have positive correlations, both genetic and phenotypic (Osman and Bradford, 1965; Dzakuma et al, 1978; Mavrogenis et al, 1980; Stobart et al, 1986). The significance of season of birth for early growth performance may thus be responsible, as a carryover effect, for its significant influence on growth traits up to yearling. That growth rate from weaning to six months was not significantly influenced by season of birth - although season of birth was a significant source for growth rate before and after this period - may be due to the post-weaning stress which may have obscured the effect of season of birth. In general, seasons 1 and 3 were associated with better performance than season 2 (the short rains). The impact of this advantage early in life appears to be perpetuated up to yearling. As far as the bodyweights are concerned, season 3 was consistently associated with superior performance. From the results of this study, it is evident that lambs born in the dry season performed better than those born in the rainy season. It is therefore recommended that breeding at Ol'Magogo should be planned so that lambing would occur in the dry season. This way, would lambs benefit from favourable prenatal nutrient availability via their dams. However, lambing in the dry season has serious nutritional implications to the ewes. This is a time when ewes require good pastures so as to support their young and improve their own body condition. The best compromise would be to time lambing to occur towards the end of the dry season just preceding the rainy season.

Parity of dam

Parity was a significant source of variation for birthweight, pre-weaning growth rate and adjusted weaning weight (P<0.01). Least squares means (Tables 3 and 4) indicate that as far as pre-weaning growth rate and weaning weight are concerned, the performance of lambs improved with increase in parity. That young ewes tend to produce smaller lambs at birth has been documented (sass and Acharya, 1970; Wilson, 1987). First parity ewes are still growing and thus must provide for their own growth in addition to the foetal demand. It is generally known that mothering ability, especially milk production, increases with parity; older ewes are larger in body and are better milkers (sass and Acharya, 1970; Eltawil et al, 1970; Wright et al, 1975; Stobart et al, 1986). Hence, influence of the superior maternal environment of such ewes is expected to be translated into better lamb performance up to weaning. It was, therefore, not surprising that post-weaning growth performance was not significantly influenced by parity. The effect of parity of dam on lambs is thus imparted as maternal influence whose direct influence is limited to the nursing period.

Period of birth

Period of birth was a significant source of variation for all traits except birthweight and yearling weight. As has been alluded to in Materials and Methods, period of birth was defined by grouping adjacent years which, from meteorological data, generally had a similar rainfall pattern. To this end, the significance of this factor was only important because it facilitated the adjustments of records for the effect of 'periods'. Any particular period, on its own, has no important bearing on the interpretation of the results and therefore did not have any management implications.

Conclusion

In order to improve breeding value, selection must be based on genotypic rather than environmental superiority. Thus, variation due to definable environmental effects must be removed by use of suitable adjustment factors. Ideally, these adjustments would be developed individually for each management unit (i.e. flock), but only rarely is sufficient data available to allow this. The next possible level for development of adjustment factors is within either definable groups of management units, or definable genetic groups. It is necessary that all known sources of variation influencing the traits of importance be included in the model of analysis, otherwise the results of the study may not be reliable. If less factors are included there is often a tendency to obtain overestimates of the genetic parameters of interest. In this study, for example, it would have been quite useful to include such factors as age of dam, and type of birth and rearing as some of the adjustment factors. However, type of birth and rearing was not included in the model of analysis because genetic parameters were also being estimated based on paternal half-sibs only, while age of dam was not available in the original data set.

The trait of interest ought to be investigated in the environment under which it is to be typically expressed, since this environment may be the one which is necessary for revealing certain desirable or undesirable genes or, in contrast, the sought-after genetic differences may be of little importance or indistinguishable in this environment. For instance, traits evaluated at Ol'Magogo should not necessarily be expected to behave in the same way in a quite different environment, such as the Kenyan highlands. Genetic improvement of many traits might be more effectively accomplished by evaluating them, and others correlated with them, under particular environmental circumstances or during a specific period in the life cycle, depending upon the particular genes involved and the correlations among them.

Acknowledgement

This work received financial support from the Norwegian Agency for International Development (NORAD). Permission to use project data was granted by the Ministry of Livestock Development, Government of Kenya. We are indebted to the support and cooperation we received from staff of the Sheep and Goat Development Project, Naivasha.

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