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Consistency of genetic parameters of productivity for ewes lambing in February, June and October under an 8-month breeding management
Small Ruminant Research 44 (2002) 1–8
Consistency of genetic parameters of productivity for ewes lambing in February, June and October under an 8-month breeding management C. Hansena,*, J.N.B. Shresthab a
Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AL T6G 2P5, USA b Dairy and Swine Research and Development Centre, Agriculture and Agri-Food Canada, P.O. Box 90, 2000 Route 108 est, Lennoxville, Que. Canada J1M 1Z3 Accepted 5 November 2001
Abstract Two flocks of ewes housed indoors year-round in a controlled environment and bred to lamb alternately at 4-month intervals in an 8-month breeding cycle resulted in 11,060 ewe records. These came from 3528 ewes of the Arcott breeds and their 814 sires, during 24 successive lambings over 8 years (1983–1990). Estimates of genetic parameters were assessed for consistency across February, June or October lambing seasons. Paternal half-sib estimates of heritabilities were 0.08–0.27 for reproductive traits, and 0.26–0.33 for ewe weight at breeding. Corresponding estimates for repeatabilities were 0.08–0.27, and 0.19–0.26. Heritability estimates for total lamb weight per ewe lambing were 0.12–0.28 at birth, 0.05–0.13 at 21 days, and 0.03–0.11 at 91 days. Corresponding estimates for repeatabilities were 0.0–0.08, 0.02–0.20 and 0.05–0.17. Estimates of genetic, phenotypic and environmental correlations between the reproductive traits and ewe weight at breeding were negligible. The genetic correlations between prolificacy and total lamb weight per ewe lambing were 0.63–0.88 at birth, 0.23–0.71 at 21 days, and 0.32–0.95 at 91 days. Corresponding estimates for fecundity were 0.77–0.92 at birth, 0.74–0.87 at 21 days, and 0.85– 0.92 at 91 days. Likewise, phenotypic (and environmental) correlations between prolificacy and total lamb weight per ewe lambing were 0.72–0.81 (0.77–0.84) at birth, 0.41–0.51 (0.37–0.54) at 21 days, and 0.47–0.55 (0.41–0.53) at 91 days. Corresponding estimates for fecundity were 0.89–0.93 (0.89–0.94) at birth, 0.73–0.80 (0.71–0.83) at 21 days, and 0.74–0.80 (0.70–0.82) at 91 days. Estimates of genetic correlations among lamb weights at birth, 21 and 91 days were 0.74–0.96. Correspondingly, phenotypic (and environmental) correlations were 0.65–0.93 (0.58–0.93). In general, all estimates of heritability, repeatability and correlation (genetic, phenotypic and environmental) for ewe productivity traits for the Canadian, Outaouais and Rideau breeds were consistent among the February, June and October lambing seasons. There was no evidence to suggest any bias due to the influence of variance associated with additive genetic season interaction in the parameter estimates. These findings demonstrate the validity of genetic parameter estimates pooled across lambing season and apply to the specific breeding protocol under conditions of 8-month breeding management. # 2002 Published by Elsevier Science B.V. Keywords: Seasonal effects; Heritability; Repeatability; Genetic and phenotypic correlations
1. Introduction *
Corresponding author. Tel.: þ1-780-492-1363; fax: þ1-780-492-4265. E-mail address: [email protected] (C. Hansen).
In North America, ewes in the majority of sheep flocks under conventional management are bred in the
0921-4488/02/$ – see front matter # 2002 Published by Elsevier Science B.V. PII: S 0 9 2 1 - 4 4 8 8 ( 0 2 ) 0 0 0 3 7 - 8
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fall to lamb in the winter. This is because domestic sheep in the northern hemisphere have an active breeding season in the fall and winter and an anestrous period in the spring and early summer. Seasonal effects associated with lambings have been shown to influence birth weight and daily gain of lambs, as well as the milk composition of the ewes. In New Zealand, Jenkinson et al. (1995) reported that Romney lambs born in the fall and winter had substantially lower birth weights than those born in spring. In Poland, Merino lambs born in November–December had higher weight gains than those born in May– June (Charon, 1988). This difference was probably related to seasonal variation in milk composition as milk fat content and protein percentages were highest for ewes lambing in November–December. In the USA, Fogarty et al. (1984) working with purebred and composite populations of sheep reported increases in the fertility and prolificacy from lambings in May and January compared to September under an accelerated lambing program. The systematic influence of season has been well established (Turner and Young, 1969), therefore genetic parameters are estimated independent of season. However, this procedure does not eliminate bias in the parameter estimate resulting from the influence of variance associated with additive genetic season interaction. In order to reduce the biological and economic costs associated with sheep production there has been considerable interest in increasing the frequency of lambings. Today, with increased interest in the use of controlled reproductive technology and the development of intensive sheep production systems, ewes are bred to lamb throughout the year. These sheep producers are using some variation of accelerated lambing procedures based on a controlled environment to enhance the ewe’s production potential. Furthermore, the number of ewes in North America lambing out-ofseason has been increasing steadily. It remains a common management practice to estimate breeding values based on genetic parameters derived from performance data of ewes and their offspring under conventional management. Correspondingly, associated studies estimating genetic parameters for outof-season lambing are seldom precise and lack adequate numbers of sires and dams (Fogarty, 1995). There is, therefore, a need to re-examine genetic
parameter estimates for possible differences among lambing seasons due to the presence of variance associated with additive genetic season interaction. To the authors’ knowledge there have been no studies to date to verify any possible effects that season of lambing may have on genetic parameters for ewe productivity traits. The present investigation was thus, undertaken to assess the influence of accelerated lambing seasons (February, June and October) in a controlled environment utilizing 8-month breeding cycles on the estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) for ewe productivity.
2. Materials and methods The sheep used in this study were from three newly developed breeds in Canada: Canadian, a meat-type sire breed, and Outaouais and Rideau, two fecund-type dam breeds, (Fahmy and Shrestha, 1992; Hansen and Shrestha, 1998). All sheep were raised at the Animal Research Centre’s (later known as the Centre for Food and Animal Research) Greenbelt farm, from 1975 to 1990 and managed under an accelerated lambing program of three lambings in two years. The sheep were housed year-round on expanded metal mesh floors in windowless barns. The entire population was separated into two flocks, each with equal contributions of the three breeds. Day length was maintained at 16 h light/8 h darkness (long day) in the growing barn until all lambs in a given room were 105 days of age, and then reduced to 9 h light/15 h darkness (short day). All ewe lambs were exposed to short day length until mating at 6.5–7.5 months of age. In the two flocks, ewes in estrus were asynchronous relative to the photoperiod and exposed to alternating 4-month photoperiods of long and short day lengths controlled by time clocks. Breeding was designed to take place at the end of a period of short days, so one or the other of the flocks lambed in February, June or October. Estrous cycle of all ewes at each breeding was synchronized using exogenous hormones, 40 mg FGA-impregnated sponge pessaries (Chronogest; Intervet, S.A., Angers, France) for 14 days and 250 or 500 IU PMSG (Equinex, Ayerst Laboratories, Montre´ al, Que´ ., Canada) administered intramuscularly at the time of sponge removal. Rams aged 11
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and 15 months were randomly assigned to mating lots of 8–10 ewe lambs and mature ewes (20–25 and 75– 80%, respectively). Any possible matings among halfsibs or more closely related animals were avoided. The rams sired offspring in both flocks, whereas ewe lambs born in one flock were selected as replacements for the alternate flock. Lambing occurred in the pens in which the ewes were bred. All lambs were raised on milk replacer diets from birth to weaning at 21 days of age. Body weights to the nearest 0.1 kg were recorded within 8 h of birth, and at 21 and 91 days of age. Details and descriptions of the management, artificial rearing, feeding protocols and controlled breeding procedures have been published (Heaney et al., 1982; Shrestha and Heaney, 1985; Shrestha et al., 1992). The care and handling of the sheep and lambs used in this study conformed to the guidelines established by the Canadian Council on Animal Care. Genetic parameters were estimated from purebred matings carried out during 24 breedings over 8 years (1983–1990). A total of 11,060 ewe records resulted from the matings of 3528 ewes and their 814 sires. In order to compute the genetic parameters, the Statistical Analysis System (SAS; SAS Institute Inc., 1999) was used. Fortran programs were written for all intermediate steps in the calculations that could not be computed with SAS. The general statistical model for each lambing season (February, June and October) included fixed effects of breed (Canadian, Outaouais and Rideau), age of ewe at lambing (6 age groups, 12–52 months or more in 8-month increments), and year (1983–1990). The random effects in the model were sire-within-breed, ewes-within-sires and residual error. Preliminary analyses showed all first-order interactions among fixed effects accounted for only a small proportion of the total variation and were generally non-significant. Higher order interactions were assumed to be negligible. Therefore, these interactions were omitted from the final model. In this study all lambs were raised on milk replacer diets from birth onwards, therefore, the effect of type of rearing was not considered. The reproductive traits studied included prolificacy (number of lambs born per ewe lambing) and fecundity (number of lambs born per 100 ewes exposed). In addition, body weight of ewes at breeding and the total lamb weight at birth, 21 and 91 days, either per ewe
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lambing or per 100 kg ewe weight were investigated. Lamb weight was adjusted to a constant age of 21 and 91 days by multiplying average daily gain during the period being considered by the number of days plus birth weight or adjusted weight at successive ages. Total lamb weight per ewe lambing, at birth, 21 and 91 days of age was calculated by adjusting weights of female lambs to a male equivalent basis and summing over the weight of lambs born in each litter (Demiro¨ ren et al., 1995). Variance components were estimated for each lambing season (February, June or October) by equating the sire-within-breed, ewe-within-sire and residual mean squares from the full model in the least squares analysis to their expectations and solving for the residual, ewe-within-sire and sire-withinbreed components of variance (Henderson, 1953). Heritability was estimated as four times the sireswithin-breed variance component divided by the total variance (sum of the sire-within-breed, ewe-withinsire and error variance components). Repeatability estimates were calculated as a ratio of the sum of the sire-within-breed and ewe-within-sire variance components to the total variance. Standard errors associated with these estimates were computed according to Dickerson (1969). Genetic correlations were then calculated as the sire-within-breed component of covariance divided by the square root of the product of the sires-within-breed variance components of the individual traits under consideration. Phenotypic correlations were calculated as the sum of the sirewithin-breed, ewe-within-sire and residual covariance components divided by the square root of the product of the sum of the sire-within-breed, ewe-within-sire and residual variance components of the individual traits. Environmental correlations were calculated as the residual covariance component minus twice the sire-within-breed component of covariance divided by the square root of the product of the residual variance minus twice the sire-withinbreed component of variance for the individual traits under consideration. Standard errors were calculated for the paternal half-sib estimates of genetic correlation according to the method of Mode and Robinson (1959). Individual estimates for the same trait were examined for differences based on the ‘t’-test. Further details on the statistical procedures have been published (Hansen and Shrestha, 1997, 1999).
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3. Results The distribution of number of ewe records and degrees of freedom for ewes and their sires associated with the ewe productivity traits for the different lambing seasons are presented in Table 1. Also presented are the means and standard errors for the traits investigated in the present study. The heritability and repeatability estimates for prolificacy, fecundity and ewe weight at breeding in the February, June and October lambing seasons are presented in Table 2. Though not significant, repeatability estimates were larger for the June lambing compared to those for the February and October lambings. The estimates of heritability and repeatability by lambing season for total lamb weight per ewe lambing at birth, 21 days and 91 days of age and the corresponding estimates for total lamb weight per 100 kg ewe weight are also presented. Although the heritablities were in the positive direction, only total lamb weight at birth in February (per ewe lambing and per 100 kg ewe weight, 0.28 and 0.27) and in October (per 100 kg ewe weight, 0.17) lambings were significant. Likewise, repeatability estimates in the June lambing were significant for total lamb weight per ewe lambing and per 100 kg ewe weight. Corresponding estimates were
also significant in the October lambing for total lamb weight at 21 and 91 days per 100 kg ewe weight. The repeatability estimates for total lamb weight at birth, 21 and 91 days were always larger in the June lambing than in the February and October lambings, however only birth weight varied significantly among lambings. Estimates of genetic correlations between ewe weight at breeding and prolificacy as well as fecundity for the February, June and October lambing seasons are presented in Table 3. The genetic, phenotypic and environmental correlations estimated between the reproductive traits and ewe weight at breeding were consistent across lambing seasons but failed to differ significantly. In general, the genetic relationships between reproductive traits and total lamb weight were significant. The exceptions were the genetic correlations in the October lambing between prolificacy and total lamb weight at 21 and 91 days. Nevertheless, there were no significant differences among lambing seasons for any estimate of genetic correlation between reproductive traits and total lamb weights. Estimates of phenotypic (and environmental) correlations between prolificacy and total lamb weight per ewe lambing (and per 100 kg ewe weight) at birth,
Table 1 Distribution of ewe records, degrees of freedom for ewes and their sires plus means (S.E.) for reproductive traits (prolificacy and fecundity), ewe weight at breeding and total lamb weight per ewe lambing (and per 100 kg ewe weight) in February, June and October lambings Source
February
June
October
No. of ewe records
3746
3746
3554
Degrees of freedom Ewes Sires
2095 762
2090 727
1995 743
149a 2.2 2.2a 0.02
178b 2.3 2.3b 0.02
165c 2.3 2.2a 0.02
Ewe weight at breeding (kg)
75.1a 0.17
75.7b 0.18
73.9c 0.19
Total lamb weight (kg) per ewe lambing At birth At 21 days At 91 days
8.5a 0.06 20.0a 0.19 57.1a 0.58
8.4a 0.06 19.4b 0.19 55.8b 0.57
7.5b 0.06 18.2c 0.19 55.1b 0.59
Total lamb weight (kg) per 100 kg ewe weight At birth 11.5a 0.09 At 21 days 27.5a 0.30 At 91 days 79.6a 0.92
11.3b 0.09 26.5b 0.30 76.6b 0.91
10.3c 0.09 25.4c 0.31 77.4b 0.94
Fecundity (%) Prolificacy
From Demiro¨ ren et al. (1995). Means within a row, not followed by the same letter differ significantly at the 0.05 level.
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Table 2 Paternal half-sib estimates of heritabilities (S.E.) and repeatabilities (S.E.) for reproductive traits (prolificacy and fecundity), ewe weight at breeding and total lamb weight per ewe lambing (and per 100 kg ewe weight) in February, June and October lambings Source
Heritability
Repeatability
February
June
October
February
June
October
Reproductive traits Prolificacy Fecundity (%)
0.27 0.09a 0.19 0.06a
0.21 0.08a 0.18 0.06a
0.22 0.08a 0.08 0.06
0.14 0.07a 0.08 0.04a
0.27 0.05a 0.20 0.04a
0.12 0.06a 0.08 0.05
Ewe weight at Breeding (kg)
0.26 0.06a
0.31 0.06a
0.33 0.07a
0.21 0.04a
0.26 0.04a
0.19 0.04a
0.12 0.07 0.13 0.07 0.13 0.07
0.12 0.08 0.05 0.08 0.03 0.08
0.08 0.07 0.02 0.07 0.05 0.07
0.25 0.05a 0.20 0.05a 0.17 0.05a
0.00 0.06 0.02 0.06 0.05 0.06
0.17 0.08a 0.11 0.08 0.08 0.08
0.00 0.07 0.08 0.08 0.01 0.07
0.27 0.05a 0.18 0.05a 0.17 0.05a
0.06 0.06 0.12 0.06a 0.13 0.06a
Total lamb weight (kg) per ewe lambing At birth 0.28 0.09a At 21 days 0.13 0.09 At 91 days 0.11 0.09
Total lamb weight (kg) per 100 kg ewe weight 0.05 0.07 At birth 0.27 0.09a At 21 days 0.11 0.08 0.07 0.07 At 91 days 0.09 0.08 0.06 0.07 a
Significantly different from zero (P < 0:01).
Table 3 Paternal half-sib estimates of genetic (S.E.), phenotypic and environmental correlations between reproductive traits (prolificacy and fecundity), ewe weight at breeding, and with total lamb weight per ewe lambing (and per 100 kg ewe weight) Lambing
Ewe weight at breeding
Total lamb weight per ewe lambing
Total lamb weight per 100 kg ewe weight
At birth
At 21 days
At 91 days
At birth
At 21 days
At 91 days
Genetic correlations Prolificacy February June October
0.02 0.28 0.31 0.24 0.28 0.24
0.88 0.07a 0.84 0.12a 0.63 0.19a
0.69 0.23a 0.71 0.25a 0.23 0.49
0.95 0.26a 0.85 0.23a 0.32 0.54
0.70 0.11a 1.02 0.47a 0.58 0.19a
0.69 0.25a 0.81 0.40a 0.41 0.30
0.94 0.32a 1.02 0.45a 0.49 0.32
Fecundity (%) February June October
0.29 0.20 0.36 0.19 0.01 0.28
0.92 0.03a 0.92 0.05a 0.77 0.23a
0.74 0.12a 0.87 0.09a NA
0.85 0.09a 0.92 0.09a NA
0.83 0.06a 0.96 0.07a 0.63 0.32a
0.74 0.16a 0.96 0.13a NA
0.81 0.14a 1.00 0.12a NA
Phenotypic (and environmental) correlations Prolificacy February June October
0.02 (0.05) 0.03 (0.03) 0.03 (0.11)
0.81 (0.84) 0.79 (0.83) 0.72 (0.77)
0.51 (0.54) 0.41 (0.37) 0.50 (0.51)
0.54 (0.53) 0.47 (0.41) 0.55 (0.53)
0.72 (0.77) 0.69 (0.70) 0.64 (0.71)
0.49 (0.52) 0.38 (0.33) 0.47 (0.49)
0.52 (0.51) 0.45 (0.37) 0.52 (0.51)
Fecundity (%) February June October
0.02 (0.08) 0.02 (0.04) 0.04 (0.02)
0.93 (0.94) 0.91 (0.92) 0.89 (0.89)
0.80 (0.83) 0.73 (0.71) 0.77 (0.74)
0.80 (0.82) 0.74 (0.70) 0.78 (0.74)
0.89 (0.91) 0.87 (0.87) 0.85 (0.86)
0.78 (0.80) 0.70 (0.66) 0.75 (0.73)
0.78 (0.80) 0.72 (0.65) 0.76 (0.73)
NA: Not available due to negative component of variance. a Significantly different from zero (P < 0:01).
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21 and 91 days, for the February, June and October lambing seasons are presented in Table 3. Corresponding estimates between fecundity and total lamb weight per ewe lambing (and per 100 kg ewe weight) are also presented. The phenotypic and environmental correlations between reproductive traits and total lamb weight were always in the positive direction and larger in magnitude. Nevertheless, seasonal variation in the estimates was not apparent. Though not significant, the phenotypic (and environmental) correlations for total lamb weight at birth, 21 and 91 days of age per ewe lambing were larger than those for total lamb weight per 100 kg ewe weight. The estimates of genetic correlations (P < 0:05) on a per ewe lambing basis, for February and June lambings were 0:93 0:16 and 0:96 0:32, respectively, between lamb weights at birth and 21 days; 0:74 0:19 and 0:88 0:36, respectively, between lamb weights at birth and 91 days; and 0:87 0:11 and 0:80 0:28, respectively, between lamb weights at 21 and 91 days of age. Corresponding estimates on a per 100 kg ewe weight basis, for October and February lambings were 0:99 0:21 and 1:03 0:23, respectively, between lamb weights at birth and 21 days. Similarly estimates for February lambing, were 0:86 0:32 between lamb weights at birth and 91 days; and 0:87 0:16 between lamb weights at 21 and 91 days of age. The estimates of phenotypic (and environmental) correlations within total lamb weight per ewe lambing for February, June and October lambings were 0.71, 0.67 and 0.73 (0.67, 0.60 and 0.72) between lamb weight at birth and 21 days; 0.68, 0.65 and 0.70 (0.66, 0.58 and 0.69) between lamb weight at birth and 91 days; and 0.91, 0.92 and 0.93 (0.91, 0.92 and 0.93) between lamb weights at 21 and 91 days of age. Corresponding estimates for total lamb weight per 100 kg ewe weight were 0.75, 0.72 and 0.78 (0.76, 0.69 and 0.77); 0.72, 0.70 and 0.74 (0.73, 0.66 and 0.73); and 0.92, 0.92 and 0.93 (0.92, 0.92 and 0.94).
4. Discussion Seasonal effects attributed to environmental influences on ewe productivity traits are well documented (Glimp, 1971; Charon, 1988; Jenkinson et al., 1995). Glimp (1971) reported that the interval to first estrus
and conception was longest during August breeding, while prolificacy was maximum during October breeding. Fogarty et al. (1984)) reported that fertility and prolificacy under an accelerated lambing program increased in May (71% and 1.8, respectively) and January (57% and 1.9, respectively) lambings compared with September lambing (17% and 1.5, respectively). Consequently, the weight of lambs weaned per ewe exposed, which increased in May and January, sharply declined in September lambing. It was noted that ewes exposed for breeding in August to lamb in January after having lambed in May had a period of postpartum and post-lactational recovery under conditions of hot, stressful summer. In contrast, ewes that lambed in January and exposed for breeding in April to lamb in September avoided any heat stress that impaired recovery. In the present study, the heat stress persisted under conditions of controlled environment for sheep housed indoors year-round because the barns had no provision for climate control. A lower breeding efficiency early in the season and a general pattern of increasing fertility and litter size from January to February–April lambings followed by some decline in May lambing has been reported (Glimp, 1971). In addition, it is well known that the digestibility of the diet increases early in the grazing season in many parts of the world suggesting the presence of a genotype environment interaction in animal performance (Osoro et al., 1999). In the present study, the estrus cycles of ewes were synchronized and bred to lamb in February, June and October, therefore, the influence of lambing season was expected to be negligible. Even under such conditions, it was difficult to eliminate the influence of heat stress during the summer months and sustain operational requirements leading to substantial reduction in the fertility of the flock. In fact, ewe exhibiting the productivity traits for which genetic parameters were estimated by lambing season in this particular study, have previously been shown to have significantly larger litters, greater lamb mortality and lower total lamb weight at 91 days for lambings in June compared to those in February or October (Demiro¨ ren et al., 1995) even under a controlled environment and uniform feeding and management practices. Seasonal influences in a controlled environment may thus result from changes in temperature, level of management, variation in the quality and composition of roughage and nutrients in diets, the
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breed of sheep and other environmental influences. It must be noted that any increase in the magnitude of genotype effect among seasons increases the genotype season interaction component of variance. Despite the efforts made to maintain a relatively constant supply of nutrients for lambs raised artificially on milk replacer diets, there was some seasonal variation in the constituents of the diets fed to the sheep, which may have an impact on productivity. Furthermore, more serious interactions can involve the changing of ranking among genotypes and seasons. It is important to ascertain the fertility of the ram across seasons in order to minimize the influence of genotype season interaction on ewe productivity. Further evidence comes from studies on reproductive hormone levels and semen quality (Langford et al., 1987, 1998) in Canadian, Outaouais and Rideau Arcott rams. Although, the rams responded to a change from long to short day length with an elevated level of follicle stimulating hormone (FSH), luteinizing hormone and testosterone, and an increase in scrotal size and number of spermatozoa, a decline in prolactin and testicular regression occurred after 4 months of long day length. Continuous exposure to short day length resulted in FSH and testosterone remaining above basal levels. Although, prolactin levels were lower, scrotal size was maintained near maximum and the number of motile spermatozoa in the ejaculate increased. In fact, Langford et al. (1999) reported that the persistent memory of previous photoperiod changes accounted for spontaneous rhythms in pituitary and testicular activity in the short term. As this memory faded there was a decline of the regular changes challenging the existence of inherent cyclicity in the reproductive function of the rams. It appears therefore that seasonal influences, at least in rams of the Arcott breeds, may be negligible. In the present study, heritability, repeatability and correlations (genetic, phenotypic and environmental) estimated for ewe productivity in the February, June and October lambings pooled across breeds were independent of non-genetic factors such as the influence of year, sex of lamb and age of ewe at lambing. As the number of ewes that lambed during the non-breeding season continues to rise in the sheep industry, the genetic response to selection of offspring born and raised during these months needs to be effective year-around, and is therefore, of concern. If genotype season interactions
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were important, genetic parameters for ewe productivity could certainly vary from season to season. Comstock and Moll (1963) suggested that the benefit from genotype and environment should be based on the increase in additive genetic variance resulting from a positive correlation between genotype and genotype environment interaction. There is a possibility that influence of season on the various genetic parameters due to average differences in the reproduction and growth traits could, therefore, exist. However, the results of this study demonstrate that season did not have a significant effect on the estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) for ewe productivity. This may be due to the positive correlation between genotype and genotype season interaction in the design of the breeding protocol. Therefore, it appears that pooled estimates of genetic parameters derived independent of non-genetic factors (Hansen and Shrestha, 1997, 1998) can be utilized to select sheep under conditions of lambing at 8-month breeding cycle. The design of the matings employed during the course of the breeding program utilized repeat matings of rams to sire offsprings in both of the flocks where offspring from one flock were used as replacements in the alternate flock. This process appears to have equally contributed to consistent genetic progress in both flocks and minimized the influence of any genotype season interaction in ewe productivity. Evidence comes from the results of multi-trait selection that resulted in the genetic improvement of lamb weights amounting to nearly 1% of the mean annually over 20 years, confirming that genetic variability in early growth traits can be successfully utilized through artificial selection to improve ewe productivity (Shrestha et al., 1996). It is interesting to note that a trend for a higher repeatability estimate was observed during June lambing compared to February or October lambings. This trend was significant for total lamb weight at birth and was evident for all ewe productivity. The June lambing season most closely resembles the natural lambing season for sheep in Canada. Nevertheless, the reasons for this higher repeatability are not readily apparent. Environmental influences beyond the control of the study may thus be playing a role in stabilizing the performance of the ewes during their natural breeding and lambing season.
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In conclusion, estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) were independent of lambing season for the specific breeding protocol under conditions of 8-month breeding cycle, when lambs were fed a milk replacer diet and raised artificially in a controlled environment. The response to artificial selection can be achieved in accelerated lambing programs with the use of these genetic parameter estimates contributing towards increased efficiency of sheep breeding programs.
References Charon, K.M., 1988. The effect of the lambing season on milk composition, somatic cell content and weight gains of lambs of Polish Merino sheep: Proc. VI World Conference on Animal Production, p. 541. Comstock, R.E., Moll, R.H., 1963. Genotype-environment interactions. In: Hansen, H.D., Robinson, H.F. (Eds.), Proceedings of the Symposium on Statistical Genetics and Plant Breeding, National Academy of Sciences—National Research Council, Washington, DC, pp. 164–172. Demiro¨ ren, E., Shrestha, J.N.B., Boylan, W.J., 1995. Breed and environmental effects on components of ewe productivity in terms of multiple births, artificial rearing and 8-month breeding cycles. Small Rumin. Res. 16, 239–249. Dickerson, G.E., 1969. Techniques for research in quantitative animal genetics. In: Techniques and Procedures in Animal Production Research. Monographs of the American Society of Animal Science, Q Corporation, Albany, New York, pp. 36– 79. Fahmy, M.H., Shrestha, J.N.B., 1992. DLS and Arcott Sheep: New Canadian Breeds. Agriculture Canada, Research Branch, Ottawa, Ont., Technical Bulletin 1886/E, 30 p. Fogarty, N.M., Dickerson, G.E., Young, L.D., 1984. Lamb production and its components in pure breeds and composite lines. Part I. Seasonal and other environmental effects. J. Anim. Sci. 58, 285–300. Fogarty, N.M., 1995. Genetic parameters for live weight, fat and muscle measurements, wool production and reproduction in sheep: a review, wool production and reproduction in sheep: a review. Anim. Breed. Abstr. 63, 101–143. Glimp, H.A., 1971. Effect of breed and mating season on reproductive performance of sheep. J. Anim. Sci. 32, 1176– 1182. Hansen, C., Shrestha, J.N.B., 1997. Heritability and repeatability estimates for ewe productivity of three breeds under 8-month
breeding cycles and artificial rearing of lambs. Small Rumin. Res. 24, 185–194. Hansen, C., Shrestha, J.N.B., 1998. Developing Synthetic Breeds of Sheep: a review of the Canadian experience. Proc. 6th World Congress on Genetic Applied to Livestock Production 24, 121–124. Hansen, C., Shrestha, J.N.B., 1999. Estimates of genetic and phenotypic correlations for ewe productivity traits of three breeds under 8-month breeding cycles and artificial rearing of lambs. Small Rumin. Res. 32, 1–11. Heaney, D.P., Shrestha, J.N.B., Peters, H.F., 1982. Performance of lambs fed milk replacers having two levels of fat. Can. J. Anim. Sci. 62, 837–843. Henderson, C.R., 1953. Estimation of variance and covariance components. Biometrics 9, 226–252. Jenkinson, C.M.C., Peterson, S.W., McDonald, M.F., McCutcheon, S.N., 1995. Seasonal effects on birth weight in sheep are associated with changes in placental development. N.Z. J. Agric. Res. 38, 337–345. Langford, G.A., Sanford, L.M., Marcus, G.J., Shrestha, J.N.B., 1999. Seasonal cyclic pituitary and testicular activities in rams. Small Rumin. Res. 33, 43–53. Langford, G.A., Shrestha, J.N.B., Sanford, L.M., Marcus, G.J., 1998. Reproductive hormone levels of early postpuberal ram lambs in relation to breed, adult testis size and semen quality. Small Rumin. Res. 29, 225–231. Langford, G.A., Ainsworth, L., Marcus, G.J., Shrestha, J.N.B., 1987. Photoperiod entrainment of testosterone, luteinizing hormone, follicle-stimulating hormone, and prolactin cycles in rams in relation to testis size and semen quality. Biol. Reprod. 37, 489–499. Mode, C.J., Robinson, H.F., 1959. Pleiotropism and the genetic variance and covariance. Biometrics 15, 518–537. Osoro, K., Olivan, M., Celaya, R., Martinez, A., 1999. Effects of genotype on the performance and intake characteristics of sheep grazing contrasting hill vegetation communities. Anim. Sci. 69, 419–426. SAS Institute Inc. 1999. SAS/STAT User’s Guide, Version 8. SAS Institute Inc. Cary NC. 3884 p. Shrestha, J.N.B., Heaney, D.P., 1985. Genetic and phenotypic parameters of early growth traits of lambs reared artificially in a controlled environment. Can. J. Anim. Sci. 65, 37–49. Shrestha, J.N.B., Heaney, D.P., Parker, R.J., 1992. Productivity of three synthetic Arcott sheep breeds and their crosses in terms of 8-month breeding cycle and artificially reared lambs. Small Rumin. Res. 9, 283–296. Shrestha, J.N.B., Peters, H.F., Heaney, D.P., Van Vleck, L.D., 1996. Genetic trends over 20 years of selection in the three synthetic Arcotts, Suffolk and Finnish Landrace sheep breeds.Part I. Early growth traits. Can. J. Anim. Sci. 76, 23–34. Turner, H.N., Young, S.S.Y., 1969. Quantitative genetics in sheep breeding, Cornell University Press, Ithaca, New York.
Consistency of genetic parameters of productivity for ewes lambing in February, June and October under an 8-month breeding management C. Hansena,*, J.N.B. Shresthab a
Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AL T6G 2P5, USA b Dairy and Swine Research and Development Centre, Agriculture and Agri-Food Canada, P.O. Box 90, 2000 Route 108 est, Lennoxville, Que. Canada J1M 1Z3 Accepted 5 November 2001
Abstract Two flocks of ewes housed indoors year-round in a controlled environment and bred to lamb alternately at 4-month intervals in an 8-month breeding cycle resulted in 11,060 ewe records. These came from 3528 ewes of the Arcott breeds and their 814 sires, during 24 successive lambings over 8 years (1983–1990). Estimates of genetic parameters were assessed for consistency across February, June or October lambing seasons. Paternal half-sib estimates of heritabilities were 0.08–0.27 for reproductive traits, and 0.26–0.33 for ewe weight at breeding. Corresponding estimates for repeatabilities were 0.08–0.27, and 0.19–0.26. Heritability estimates for total lamb weight per ewe lambing were 0.12–0.28 at birth, 0.05–0.13 at 21 days, and 0.03–0.11 at 91 days. Corresponding estimates for repeatabilities were 0.0–0.08, 0.02–0.20 and 0.05–0.17. Estimates of genetic, phenotypic and environmental correlations between the reproductive traits and ewe weight at breeding were negligible. The genetic correlations between prolificacy and total lamb weight per ewe lambing were 0.63–0.88 at birth, 0.23–0.71 at 21 days, and 0.32–0.95 at 91 days. Corresponding estimates for fecundity were 0.77–0.92 at birth, 0.74–0.87 at 21 days, and 0.85– 0.92 at 91 days. Likewise, phenotypic (and environmental) correlations between prolificacy and total lamb weight per ewe lambing were 0.72–0.81 (0.77–0.84) at birth, 0.41–0.51 (0.37–0.54) at 21 days, and 0.47–0.55 (0.41–0.53) at 91 days. Corresponding estimates for fecundity were 0.89–0.93 (0.89–0.94) at birth, 0.73–0.80 (0.71–0.83) at 21 days, and 0.74–0.80 (0.70–0.82) at 91 days. Estimates of genetic correlations among lamb weights at birth, 21 and 91 days were 0.74–0.96. Correspondingly, phenotypic (and environmental) correlations were 0.65–0.93 (0.58–0.93). In general, all estimates of heritability, repeatability and correlation (genetic, phenotypic and environmental) for ewe productivity traits for the Canadian, Outaouais and Rideau breeds were consistent among the February, June and October lambing seasons. There was no evidence to suggest any bias due to the influence of variance associated with additive genetic season interaction in the parameter estimates. These findings demonstrate the validity of genetic parameter estimates pooled across lambing season and apply to the specific breeding protocol under conditions of 8-month breeding management. # 2002 Published by Elsevier Science B.V. Keywords: Seasonal effects; Heritability; Repeatability; Genetic and phenotypic correlations
1. Introduction *
Corresponding author. Tel.: þ1-780-492-1363; fax: þ1-780-492-4265. E-mail address: [email protected] (C. Hansen).
In North America, ewes in the majority of sheep flocks under conventional management are bred in the
0921-4488/02/$ – see front matter # 2002 Published by Elsevier Science B.V. PII: S 0 9 2 1 - 4 4 8 8 ( 0 2 ) 0 0 0 3 7 - 8
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fall to lamb in the winter. This is because domestic sheep in the northern hemisphere have an active breeding season in the fall and winter and an anestrous period in the spring and early summer. Seasonal effects associated with lambings have been shown to influence birth weight and daily gain of lambs, as well as the milk composition of the ewes. In New Zealand, Jenkinson et al. (1995) reported that Romney lambs born in the fall and winter had substantially lower birth weights than those born in spring. In Poland, Merino lambs born in November–December had higher weight gains than those born in May– June (Charon, 1988). This difference was probably related to seasonal variation in milk composition as milk fat content and protein percentages were highest for ewes lambing in November–December. In the USA, Fogarty et al. (1984) working with purebred and composite populations of sheep reported increases in the fertility and prolificacy from lambings in May and January compared to September under an accelerated lambing program. The systematic influence of season has been well established (Turner and Young, 1969), therefore genetic parameters are estimated independent of season. However, this procedure does not eliminate bias in the parameter estimate resulting from the influence of variance associated with additive genetic season interaction. In order to reduce the biological and economic costs associated with sheep production there has been considerable interest in increasing the frequency of lambings. Today, with increased interest in the use of controlled reproductive technology and the development of intensive sheep production systems, ewes are bred to lamb throughout the year. These sheep producers are using some variation of accelerated lambing procedures based on a controlled environment to enhance the ewe’s production potential. Furthermore, the number of ewes in North America lambing out-ofseason has been increasing steadily. It remains a common management practice to estimate breeding values based on genetic parameters derived from performance data of ewes and their offspring under conventional management. Correspondingly, associated studies estimating genetic parameters for outof-season lambing are seldom precise and lack adequate numbers of sires and dams (Fogarty, 1995). There is, therefore, a need to re-examine genetic
parameter estimates for possible differences among lambing seasons due to the presence of variance associated with additive genetic season interaction. To the authors’ knowledge there have been no studies to date to verify any possible effects that season of lambing may have on genetic parameters for ewe productivity traits. The present investigation was thus, undertaken to assess the influence of accelerated lambing seasons (February, June and October) in a controlled environment utilizing 8-month breeding cycles on the estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) for ewe productivity.
2. Materials and methods The sheep used in this study were from three newly developed breeds in Canada: Canadian, a meat-type sire breed, and Outaouais and Rideau, two fecund-type dam breeds, (Fahmy and Shrestha, 1992; Hansen and Shrestha, 1998). All sheep were raised at the Animal Research Centre’s (later known as the Centre for Food and Animal Research) Greenbelt farm, from 1975 to 1990 and managed under an accelerated lambing program of three lambings in two years. The sheep were housed year-round on expanded metal mesh floors in windowless barns. The entire population was separated into two flocks, each with equal contributions of the three breeds. Day length was maintained at 16 h light/8 h darkness (long day) in the growing barn until all lambs in a given room were 105 days of age, and then reduced to 9 h light/15 h darkness (short day). All ewe lambs were exposed to short day length until mating at 6.5–7.5 months of age. In the two flocks, ewes in estrus were asynchronous relative to the photoperiod and exposed to alternating 4-month photoperiods of long and short day lengths controlled by time clocks. Breeding was designed to take place at the end of a period of short days, so one or the other of the flocks lambed in February, June or October. Estrous cycle of all ewes at each breeding was synchronized using exogenous hormones, 40 mg FGA-impregnated sponge pessaries (Chronogest; Intervet, S.A., Angers, France) for 14 days and 250 or 500 IU PMSG (Equinex, Ayerst Laboratories, Montre´ al, Que´ ., Canada) administered intramuscularly at the time of sponge removal. Rams aged 11
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and 15 months were randomly assigned to mating lots of 8–10 ewe lambs and mature ewes (20–25 and 75– 80%, respectively). Any possible matings among halfsibs or more closely related animals were avoided. The rams sired offspring in both flocks, whereas ewe lambs born in one flock were selected as replacements for the alternate flock. Lambing occurred in the pens in which the ewes were bred. All lambs were raised on milk replacer diets from birth to weaning at 21 days of age. Body weights to the nearest 0.1 kg were recorded within 8 h of birth, and at 21 and 91 days of age. Details and descriptions of the management, artificial rearing, feeding protocols and controlled breeding procedures have been published (Heaney et al., 1982; Shrestha and Heaney, 1985; Shrestha et al., 1992). The care and handling of the sheep and lambs used in this study conformed to the guidelines established by the Canadian Council on Animal Care. Genetic parameters were estimated from purebred matings carried out during 24 breedings over 8 years (1983–1990). A total of 11,060 ewe records resulted from the matings of 3528 ewes and their 814 sires. In order to compute the genetic parameters, the Statistical Analysis System (SAS; SAS Institute Inc., 1999) was used. Fortran programs were written for all intermediate steps in the calculations that could not be computed with SAS. The general statistical model for each lambing season (February, June and October) included fixed effects of breed (Canadian, Outaouais and Rideau), age of ewe at lambing (6 age groups, 12–52 months or more in 8-month increments), and year (1983–1990). The random effects in the model were sire-within-breed, ewes-within-sires and residual error. Preliminary analyses showed all first-order interactions among fixed effects accounted for only a small proportion of the total variation and were generally non-significant. Higher order interactions were assumed to be negligible. Therefore, these interactions were omitted from the final model. In this study all lambs were raised on milk replacer diets from birth onwards, therefore, the effect of type of rearing was not considered. The reproductive traits studied included prolificacy (number of lambs born per ewe lambing) and fecundity (number of lambs born per 100 ewes exposed). In addition, body weight of ewes at breeding and the total lamb weight at birth, 21 and 91 days, either per ewe
3
lambing or per 100 kg ewe weight were investigated. Lamb weight was adjusted to a constant age of 21 and 91 days by multiplying average daily gain during the period being considered by the number of days plus birth weight or adjusted weight at successive ages. Total lamb weight per ewe lambing, at birth, 21 and 91 days of age was calculated by adjusting weights of female lambs to a male equivalent basis and summing over the weight of lambs born in each litter (Demiro¨ ren et al., 1995). Variance components were estimated for each lambing season (February, June or October) by equating the sire-within-breed, ewe-within-sire and residual mean squares from the full model in the least squares analysis to their expectations and solving for the residual, ewe-within-sire and sire-withinbreed components of variance (Henderson, 1953). Heritability was estimated as four times the sireswithin-breed variance component divided by the total variance (sum of the sire-within-breed, ewe-withinsire and error variance components). Repeatability estimates were calculated as a ratio of the sum of the sire-within-breed and ewe-within-sire variance components to the total variance. Standard errors associated with these estimates were computed according to Dickerson (1969). Genetic correlations were then calculated as the sire-within-breed component of covariance divided by the square root of the product of the sires-within-breed variance components of the individual traits under consideration. Phenotypic correlations were calculated as the sum of the sirewithin-breed, ewe-within-sire and residual covariance components divided by the square root of the product of the sum of the sire-within-breed, ewe-within-sire and residual variance components of the individual traits. Environmental correlations were calculated as the residual covariance component minus twice the sire-within-breed component of covariance divided by the square root of the product of the residual variance minus twice the sire-withinbreed component of variance for the individual traits under consideration. Standard errors were calculated for the paternal half-sib estimates of genetic correlation according to the method of Mode and Robinson (1959). Individual estimates for the same trait were examined for differences based on the ‘t’-test. Further details on the statistical procedures have been published (Hansen and Shrestha, 1997, 1999).
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3. Results The distribution of number of ewe records and degrees of freedom for ewes and their sires associated with the ewe productivity traits for the different lambing seasons are presented in Table 1. Also presented are the means and standard errors for the traits investigated in the present study. The heritability and repeatability estimates for prolificacy, fecundity and ewe weight at breeding in the February, June and October lambing seasons are presented in Table 2. Though not significant, repeatability estimates were larger for the June lambing compared to those for the February and October lambings. The estimates of heritability and repeatability by lambing season for total lamb weight per ewe lambing at birth, 21 days and 91 days of age and the corresponding estimates for total lamb weight per 100 kg ewe weight are also presented. Although the heritablities were in the positive direction, only total lamb weight at birth in February (per ewe lambing and per 100 kg ewe weight, 0.28 and 0.27) and in October (per 100 kg ewe weight, 0.17) lambings were significant. Likewise, repeatability estimates in the June lambing were significant for total lamb weight per ewe lambing and per 100 kg ewe weight. Corresponding estimates were
also significant in the October lambing for total lamb weight at 21 and 91 days per 100 kg ewe weight. The repeatability estimates for total lamb weight at birth, 21 and 91 days were always larger in the June lambing than in the February and October lambings, however only birth weight varied significantly among lambings. Estimates of genetic correlations between ewe weight at breeding and prolificacy as well as fecundity for the February, June and October lambing seasons are presented in Table 3. The genetic, phenotypic and environmental correlations estimated between the reproductive traits and ewe weight at breeding were consistent across lambing seasons but failed to differ significantly. In general, the genetic relationships between reproductive traits and total lamb weight were significant. The exceptions were the genetic correlations in the October lambing between prolificacy and total lamb weight at 21 and 91 days. Nevertheless, there were no significant differences among lambing seasons for any estimate of genetic correlation between reproductive traits and total lamb weights. Estimates of phenotypic (and environmental) correlations between prolificacy and total lamb weight per ewe lambing (and per 100 kg ewe weight) at birth,
Table 1 Distribution of ewe records, degrees of freedom for ewes and their sires plus means (S.E.) for reproductive traits (prolificacy and fecundity), ewe weight at breeding and total lamb weight per ewe lambing (and per 100 kg ewe weight) in February, June and October lambings Source
February
June
October
No. of ewe records
3746
3746
3554
Degrees of freedom Ewes Sires
2095 762
2090 727
1995 743
149a 2.2 2.2a 0.02
178b 2.3 2.3b 0.02
165c 2.3 2.2a 0.02
Ewe weight at breeding (kg)
75.1a 0.17
75.7b 0.18
73.9c 0.19
Total lamb weight (kg) per ewe lambing At birth At 21 days At 91 days
8.5a 0.06 20.0a 0.19 57.1a 0.58
8.4a 0.06 19.4b 0.19 55.8b 0.57
7.5b 0.06 18.2c 0.19 55.1b 0.59
Total lamb weight (kg) per 100 kg ewe weight At birth 11.5a 0.09 At 21 days 27.5a 0.30 At 91 days 79.6a 0.92
11.3b 0.09 26.5b 0.30 76.6b 0.91
10.3c 0.09 25.4c 0.31 77.4b 0.94
Fecundity (%) Prolificacy
From Demiro¨ ren et al. (1995). Means within a row, not followed by the same letter differ significantly at the 0.05 level.
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Table 2 Paternal half-sib estimates of heritabilities (S.E.) and repeatabilities (S.E.) for reproductive traits (prolificacy and fecundity), ewe weight at breeding and total lamb weight per ewe lambing (and per 100 kg ewe weight) in February, June and October lambings Source
Heritability
Repeatability
February
June
October
February
June
October
Reproductive traits Prolificacy Fecundity (%)
0.27 0.09a 0.19 0.06a
0.21 0.08a 0.18 0.06a
0.22 0.08a 0.08 0.06
0.14 0.07a 0.08 0.04a
0.27 0.05a 0.20 0.04a
0.12 0.06a 0.08 0.05
Ewe weight at Breeding (kg)
0.26 0.06a
0.31 0.06a
0.33 0.07a
0.21 0.04a
0.26 0.04a
0.19 0.04a
0.12 0.07 0.13 0.07 0.13 0.07
0.12 0.08 0.05 0.08 0.03 0.08
0.08 0.07 0.02 0.07 0.05 0.07
0.25 0.05a 0.20 0.05a 0.17 0.05a
0.00 0.06 0.02 0.06 0.05 0.06
0.17 0.08a 0.11 0.08 0.08 0.08
0.00 0.07 0.08 0.08 0.01 0.07
0.27 0.05a 0.18 0.05a 0.17 0.05a
0.06 0.06 0.12 0.06a 0.13 0.06a
Total lamb weight (kg) per ewe lambing At birth 0.28 0.09a At 21 days 0.13 0.09 At 91 days 0.11 0.09
Total lamb weight (kg) per 100 kg ewe weight 0.05 0.07 At birth 0.27 0.09a At 21 days 0.11 0.08 0.07 0.07 At 91 days 0.09 0.08 0.06 0.07 a
Significantly different from zero (P < 0:01).
Table 3 Paternal half-sib estimates of genetic (S.E.), phenotypic and environmental correlations between reproductive traits (prolificacy and fecundity), ewe weight at breeding, and with total lamb weight per ewe lambing (and per 100 kg ewe weight) Lambing
Ewe weight at breeding
Total lamb weight per ewe lambing
Total lamb weight per 100 kg ewe weight
At birth
At 21 days
At 91 days
At birth
At 21 days
At 91 days
Genetic correlations Prolificacy February June October
0.02 0.28 0.31 0.24 0.28 0.24
0.88 0.07a 0.84 0.12a 0.63 0.19a
0.69 0.23a 0.71 0.25a 0.23 0.49
0.95 0.26a 0.85 0.23a 0.32 0.54
0.70 0.11a 1.02 0.47a 0.58 0.19a
0.69 0.25a 0.81 0.40a 0.41 0.30
0.94 0.32a 1.02 0.45a 0.49 0.32
Fecundity (%) February June October
0.29 0.20 0.36 0.19 0.01 0.28
0.92 0.03a 0.92 0.05a 0.77 0.23a
0.74 0.12a 0.87 0.09a NA
0.85 0.09a 0.92 0.09a NA
0.83 0.06a 0.96 0.07a 0.63 0.32a
0.74 0.16a 0.96 0.13a NA
0.81 0.14a 1.00 0.12a NA
Phenotypic (and environmental) correlations Prolificacy February June October
0.02 (0.05) 0.03 (0.03) 0.03 (0.11)
0.81 (0.84) 0.79 (0.83) 0.72 (0.77)
0.51 (0.54) 0.41 (0.37) 0.50 (0.51)
0.54 (0.53) 0.47 (0.41) 0.55 (0.53)
0.72 (0.77) 0.69 (0.70) 0.64 (0.71)
0.49 (0.52) 0.38 (0.33) 0.47 (0.49)
0.52 (0.51) 0.45 (0.37) 0.52 (0.51)
Fecundity (%) February June October
0.02 (0.08) 0.02 (0.04) 0.04 (0.02)
0.93 (0.94) 0.91 (0.92) 0.89 (0.89)
0.80 (0.83) 0.73 (0.71) 0.77 (0.74)
0.80 (0.82) 0.74 (0.70) 0.78 (0.74)
0.89 (0.91) 0.87 (0.87) 0.85 (0.86)
0.78 (0.80) 0.70 (0.66) 0.75 (0.73)
0.78 (0.80) 0.72 (0.65) 0.76 (0.73)
NA: Not available due to negative component of variance. a Significantly different from zero (P < 0:01).
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21 and 91 days, for the February, June and October lambing seasons are presented in Table 3. Corresponding estimates between fecundity and total lamb weight per ewe lambing (and per 100 kg ewe weight) are also presented. The phenotypic and environmental correlations between reproductive traits and total lamb weight were always in the positive direction and larger in magnitude. Nevertheless, seasonal variation in the estimates was not apparent. Though not significant, the phenotypic (and environmental) correlations for total lamb weight at birth, 21 and 91 days of age per ewe lambing were larger than those for total lamb weight per 100 kg ewe weight. The estimates of genetic correlations (P < 0:05) on a per ewe lambing basis, for February and June lambings were 0:93 0:16 and 0:96 0:32, respectively, between lamb weights at birth and 21 days; 0:74 0:19 and 0:88 0:36, respectively, between lamb weights at birth and 91 days; and 0:87 0:11 and 0:80 0:28, respectively, between lamb weights at 21 and 91 days of age. Corresponding estimates on a per 100 kg ewe weight basis, for October and February lambings were 0:99 0:21 and 1:03 0:23, respectively, between lamb weights at birth and 21 days. Similarly estimates for February lambing, were 0:86 0:32 between lamb weights at birth and 91 days; and 0:87 0:16 between lamb weights at 21 and 91 days of age. The estimates of phenotypic (and environmental) correlations within total lamb weight per ewe lambing for February, June and October lambings were 0.71, 0.67 and 0.73 (0.67, 0.60 and 0.72) between lamb weight at birth and 21 days; 0.68, 0.65 and 0.70 (0.66, 0.58 and 0.69) between lamb weight at birth and 91 days; and 0.91, 0.92 and 0.93 (0.91, 0.92 and 0.93) between lamb weights at 21 and 91 days of age. Corresponding estimates for total lamb weight per 100 kg ewe weight were 0.75, 0.72 and 0.78 (0.76, 0.69 and 0.77); 0.72, 0.70 and 0.74 (0.73, 0.66 and 0.73); and 0.92, 0.92 and 0.93 (0.92, 0.92 and 0.94).
4. Discussion Seasonal effects attributed to environmental influences on ewe productivity traits are well documented (Glimp, 1971; Charon, 1988; Jenkinson et al., 1995). Glimp (1971) reported that the interval to first estrus
and conception was longest during August breeding, while prolificacy was maximum during October breeding. Fogarty et al. (1984)) reported that fertility and prolificacy under an accelerated lambing program increased in May (71% and 1.8, respectively) and January (57% and 1.9, respectively) lambings compared with September lambing (17% and 1.5, respectively). Consequently, the weight of lambs weaned per ewe exposed, which increased in May and January, sharply declined in September lambing. It was noted that ewes exposed for breeding in August to lamb in January after having lambed in May had a period of postpartum and post-lactational recovery under conditions of hot, stressful summer. In contrast, ewes that lambed in January and exposed for breeding in April to lamb in September avoided any heat stress that impaired recovery. In the present study, the heat stress persisted under conditions of controlled environment for sheep housed indoors year-round because the barns had no provision for climate control. A lower breeding efficiency early in the season and a general pattern of increasing fertility and litter size from January to February–April lambings followed by some decline in May lambing has been reported (Glimp, 1971). In addition, it is well known that the digestibility of the diet increases early in the grazing season in many parts of the world suggesting the presence of a genotype environment interaction in animal performance (Osoro et al., 1999). In the present study, the estrus cycles of ewes were synchronized and bred to lamb in February, June and October, therefore, the influence of lambing season was expected to be negligible. Even under such conditions, it was difficult to eliminate the influence of heat stress during the summer months and sustain operational requirements leading to substantial reduction in the fertility of the flock. In fact, ewe exhibiting the productivity traits for which genetic parameters were estimated by lambing season in this particular study, have previously been shown to have significantly larger litters, greater lamb mortality and lower total lamb weight at 91 days for lambings in June compared to those in February or October (Demiro¨ ren et al., 1995) even under a controlled environment and uniform feeding and management practices. Seasonal influences in a controlled environment may thus result from changes in temperature, level of management, variation in the quality and composition of roughage and nutrients in diets, the
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breed of sheep and other environmental influences. It must be noted that any increase in the magnitude of genotype effect among seasons increases the genotype season interaction component of variance. Despite the efforts made to maintain a relatively constant supply of nutrients for lambs raised artificially on milk replacer diets, there was some seasonal variation in the constituents of the diets fed to the sheep, which may have an impact on productivity. Furthermore, more serious interactions can involve the changing of ranking among genotypes and seasons. It is important to ascertain the fertility of the ram across seasons in order to minimize the influence of genotype season interaction on ewe productivity. Further evidence comes from studies on reproductive hormone levels and semen quality (Langford et al., 1987, 1998) in Canadian, Outaouais and Rideau Arcott rams. Although, the rams responded to a change from long to short day length with an elevated level of follicle stimulating hormone (FSH), luteinizing hormone and testosterone, and an increase in scrotal size and number of spermatozoa, a decline in prolactin and testicular regression occurred after 4 months of long day length. Continuous exposure to short day length resulted in FSH and testosterone remaining above basal levels. Although, prolactin levels were lower, scrotal size was maintained near maximum and the number of motile spermatozoa in the ejaculate increased. In fact, Langford et al. (1999) reported that the persistent memory of previous photoperiod changes accounted for spontaneous rhythms in pituitary and testicular activity in the short term. As this memory faded there was a decline of the regular changes challenging the existence of inherent cyclicity in the reproductive function of the rams. It appears therefore that seasonal influences, at least in rams of the Arcott breeds, may be negligible. In the present study, heritability, repeatability and correlations (genetic, phenotypic and environmental) estimated for ewe productivity in the February, June and October lambings pooled across breeds were independent of non-genetic factors such as the influence of year, sex of lamb and age of ewe at lambing. As the number of ewes that lambed during the non-breeding season continues to rise in the sheep industry, the genetic response to selection of offspring born and raised during these months needs to be effective year-around, and is therefore, of concern. If genotype season interactions
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were important, genetic parameters for ewe productivity could certainly vary from season to season. Comstock and Moll (1963) suggested that the benefit from genotype and environment should be based on the increase in additive genetic variance resulting from a positive correlation between genotype and genotype environment interaction. There is a possibility that influence of season on the various genetic parameters due to average differences in the reproduction and growth traits could, therefore, exist. However, the results of this study demonstrate that season did not have a significant effect on the estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) for ewe productivity. This may be due to the positive correlation between genotype and genotype season interaction in the design of the breeding protocol. Therefore, it appears that pooled estimates of genetic parameters derived independent of non-genetic factors (Hansen and Shrestha, 1997, 1998) can be utilized to select sheep under conditions of lambing at 8-month breeding cycle. The design of the matings employed during the course of the breeding program utilized repeat matings of rams to sire offsprings in both of the flocks where offspring from one flock were used as replacements in the alternate flock. This process appears to have equally contributed to consistent genetic progress in both flocks and minimized the influence of any genotype season interaction in ewe productivity. Evidence comes from the results of multi-trait selection that resulted in the genetic improvement of lamb weights amounting to nearly 1% of the mean annually over 20 years, confirming that genetic variability in early growth traits can be successfully utilized through artificial selection to improve ewe productivity (Shrestha et al., 1996). It is interesting to note that a trend for a higher repeatability estimate was observed during June lambing compared to February or October lambings. This trend was significant for total lamb weight at birth and was evident for all ewe productivity. The June lambing season most closely resembles the natural lambing season for sheep in Canada. Nevertheless, the reasons for this higher repeatability are not readily apparent. Environmental influences beyond the control of the study may thus be playing a role in stabilizing the performance of the ewes during their natural breeding and lambing season.
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In conclusion, estimates of heritability, repeatability and correlations (genetic, phenotypic and environmental) were independent of lambing season for the specific breeding protocol under conditions of 8-month breeding cycle, when lambs were fed a milk replacer diet and raised artificially in a controlled environment. The response to artificial selection can be achieved in accelerated lambing programs with the use of these genetic parameter estimates contributing towards increased efficiency of sheep breeding programs.
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