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Variance components and genetic parameters of growth traits and Kleiber ratio in Muzaffarnagari sheep
Small Ruminant Research 132 (2015) 79–85
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Variance components and genetic parameters of growth traits and Kleiber ratio in Muzaffarnagari sheep Ajoy Mandal a,∗ , M. Karunakaran a , D.K. Sharma b , Hasan Baneh c , P.K. Rout b a b c
Eastern Regional Station of National Dairy Research Institute, A/12 Block, Kalyani 7412 35, Nadia, West Bengal, India Central Institute for Research on Goats, Makhdoom, Mathura 281 122, Uttar Pradesh, India Young Researchers and Elite Club, Karaj Branch, Islamic Azad University, Karaj, Iran
a r t i c l e
i n f o
Article history: Received 7 October 2014 Received in revised form 10 September 2015 Accepted 6 October 2015 Available online 20 October 2015 Keywords: Growth traits Average daily weight gain Kleiber ratio Maternal effects Heritability Muzaffarnagari sheep
a b s t r a c t Estimates of (co)variance components and genetic parameters were obtained for birth weight (BW), weaning weight (WW), average daily weight gain from birth to weaning (ADG) and Kleiber ratio (KR) of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 30 years (1976–2005). Records of 5835 lambs descended from 176 rams and 1703 ewes were used in the study. Analyses were carried out by restricted maximum likelihood (REML) fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits. The best model was chosen after testing the improvement of the log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Heritability estimates for BW, WW, ADG and KR were 0.15, 0.16, 0.15 and 0.13, respectively. Maternal genetic effects contributed only 12% of the total variance for birth weight. Estimates of fraction of variance due to maternal permanent environmental effects (c2 ) for BW, WW, ADG and KR accounted for 6–12% of the total phenotypic variance in this study. The estimates of the direct genetic correlation among studied traits were positive, ranging from 0.18 (BW–KR) to 0.98 (WW–ADG), whereas permanent maternal environmental correlations among traits varied from from 0.55 (BW–KR) to 0.99 (WW–ADG). The estimates of the phenotypic and environmental correlation between traits under study ranged from 0.10 to 0.99 and −0.05 to 0.99, respectively. Results suggest that maternal additive effect was only important for birth weight whereas permanent environmental maternal effects were important for other traits in our study. The moderate heritability estimates for early growth traits and Kleiber ratio of sheep in this study indicates that modest rates of genetic progress may be possible for these traits from selection under the prevailing management system. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Early growth traits are important factors influencing the profitability of any meat producing enterprise. Promoting the growth potential of lambs is a possible alternative to increase meat production and improving breeding efficiency in any sheep breeding enterprise (Miraei-Ashtiani et al., 2007). Body weights and growth rates in pre-weaning are often considered as an early indicator of the late growth and economic benefit (Hanford et al., 2006). In any selection program aimed at increasing growth performance in order to achieve maximum output, improving weaning weight (WW) is necessary. This is possible by including a trait such as
∗ Corresponding author. Fax.: +91 33 2582 8264. E-mail addresses: [email protected], [email protected] (A. Mandal). http://dx.doi.org/10.1016/j.smallrumres.2015.10.009 0921-4488/© 2015 Elsevier B.V. All rights reserved.
Kleiber ratio (KR) in selection programs. Kleiber ratio, defined as growth rate/metabolic weight (body weight0.75 ), as suggested for measuring growth efficiency (Kleiber, 1947) was developed as an alternative ratio to select animals for breeding. Moreover, KR as an indication of efficiency of feed conversion is useful because it does not require individual intake to be measured and allows us to identify animals with high efficiency of growth relative to body size (Kleiber, 1947). Köster et al. (1994) suggested that KR could be used as a useful indicator of feed conversion and an important selection criterion for efficiency of growth. Animals that have a high KR are considered efficient users of feed (Ghafouri-Kesbi et al., 2011). Numerous studies have demonstrated that both direct and maternal influences are important for growth (Mandal et al., 2006; Kushwaha et al., 2009), average daily weight gains (Rashidi et al., 2008; Savar-Sofla et al., 2011; Mandal et al., 2012) and Kleiber ratio (Savar-Sofla et al., 2011; Mokhtari et al., 2012; Mohammadi
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A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85
Table 1 Characteristics of data structure for pre-weaning growth traitsa of Muzaffarnagari sheep. Items/traits
BW (kg)
WW(kg)
ADG(g)
KR
No. of records No. of animalsb No. of sires with progeny record No. of dams with progeny record Progeny per sire Progeny per dam Mean Standard deviation CV (%) Years of records
5835 6089 176 1703 33.15 3.43 3.46 0.72 20.81 30
5135 5339 176 1602 29.18 3.21 15.75 4.01 25.46 29
5135 5339 176 1602 29.18 3.21 135.94 41.46 30.50 29
5135 5339 176 1602 29.18 3.21 16.89 2.37 14.03 29
a b
BW, Birth weight, WW, Weaning weight, ADG, Average daily weight gain from birth to weaning, KR, Kleiber ratio (ADG/WW0.75 ). Animals in pedigrees.
et al., 2013b) of sheep. Many previous published research studies (Al-Shorepy, 2001; Mandal et al., 2006) showed that selection efficiency or genetic progress was largely dependent on the effective use of additive genetic variance, and maternal effects become more important for selection of early growth traits. So, accurate estimation of genetic parameters for economically important traits is needed for designing optimal breeding strategies for livestock species (Safari et al., 2005). The Muzaffarnagari sheep, an important mutton breed of India, is known for its relatively rapid growth, high feed conversion efficiency and very good adaptability (Mandal et al., 2003) in the semi-arid region of the country and widely distributed in the western Uttar Pradesh, near Meerut, Muzaffarnagar, Saharanpur, Bijnor and in the some parts of Delhi and Haryana. The breed has better potential for meat and carpet wool production than other Indian sheep breeds. The description of the study location as well as characteristics of the breed, its location, habitat and husbandry practices have been depicted by Mandal et al. (2000) for this breed. Most of reported heritabilities of growth traits of this breed are based on ratios of variance components estimated mainly by paternal half-sib method (Mandal et al., 2003), without taking into consideration the maternal effects. In a study by Mandal et al. (2006), direct and maternal (co)variance components for birth weight and weaning weight of lambs were reported for Muzaffarnagari sheep. The objective of this investigation was to extend those analyses to include estimation of the genetic parameters for direct and maternal effects on birth weight, weaning weight, pre-weaning average daily weight gain and Kleiber ratio of Muzaffarnagari sheep.
2. Materials and methods 2.1. Data Data were collected from an experimental breeding flock of Muzaffarnagari sheep, maintained at the Central Institute for Research on Goats (CIRG), Makhdoom, Uttar Pradesh, India, under the All India Coordinated Research Project on Sheep Breeding for Mutton Production for a period of 30 years (1976–2005). The data includes 5835 lamb records from 1703 ewes sired by 176 rams. The number of records analyzed ranged from 1389 to 2930, depending on the traits of interest (Table 1). Briefly, the flock included 250 breeding ewes reared under the semi-intensive feeding system, with animals allowed to graze for 6–7 h during the day and penned at night. The animals were provided were 250 g of growth ration, comprising of 72% total digestible nutrients (TDN) and 16% digestible crude protein (DCP). Generally maize (15%), barley (20%), ground nut cake (35%), wheat bran (20%), molasses (7%), mineral mixture (1.5%) and salt (1.5%) were the ingredients used in formulating the growth ration. Dry and green fodder was given ad libitum to these animals. Ewes were first exposed to rams at 12 to
14 months of age and hand-mated to selected sires. Breeding generally occurred in May and June and again in October and November; lambing therefore normally occurred in October and November and in March and April. One breeding ram was normally allowed to mate with 20 to 25 ewes, and breeding rams were used for approximately 3 years. On average, a ewe produces a lamb in every 1 or 1.5 years. At lambing, both lambs and dams were weighed. Each lamb was identified by a metal ear tag after birth and the lambing date, sex and birth type of each lamb were recorded. Lambs were kept with their dams in individual pens for 2 to 3 days after birth. Lambs were kept indoors during the suckling period, and were normally weaned at 3 months of age. Lambs were weighed at 15-day interval from birth to weaning at 3 months of age and thereafter at monthly intervals up to 12 months of age (Mandal et al., 2006). Animals were vaccinated against peste des petits for ruminants (PPR), enterotoxaemia and haemorrhagic septicaemia (HS). The traits analyzed for these analyses were birth weight (BW), weaning weight (WW), average daily weight gains (ADG) from birth to 90 days (weaning) and pre-weaning Kleiber ratio (KR). 2.2. Statistical analyses (Co)variance components were estimated by restricted maximum likelihood (REML) using a derivative-free algorithm fitting an animal model (DFREML, Meyer, 2000). Data were first analyzed by least-squares analysis of variance (Harvey, 1990) to identify the fixed effects to be included in the model. The statistical model included the fixed effect of birth year (30 levels), season of birth (2 levels), parity of dam (1, 2, 3, 4, 5, 6, ≥7), sex (2 levels) and birth status (single vs. twin) of lambs. All these effects were significant (P < 0.05) for all traits and all were included in the models subsequently used to estimate genetic parameters. Convergence of the REML solutions was assumed when the variance of function values (−2 log L) in the Simplex was less than 10−8 . To ensure that a global maximum was reached, analyses were restarted for several other rounds of iterations using results from the previous round as starting values. When estimates did not change, convergence was confirmed. Depending on the model, the log-likelihood function was maximized with respect to the direct and maternal additive variances, the permanent environmental variance of the dam and the genetic covariance between direct and maternal genetic effects. Standard errors were calculated for the estimated parameters as a part of the DFREML program (Meyer, 2000). Univariate animal models were fitted to estimate (co)variance components for each trait. The following six models were used: y = Xb + Za a + e,
(1)
y = Xb + Za a + Zc c + e,
(2)
y = Xb + Za a + Zm m + e with Cov (a, m) = 0,
(3)
A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85
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Table 2 Least-squares means along with standard errors of pre-weaning growth traitsa of Muzaffarnagari sheep. Effects
Traitsa BW (kg)
WW (kg)
ADG (g)
KR
Overall mean Birth year Birth season March–April October–November
3.14±0.01
13.86 ± 0.09
118.53 ± 1.00
16.18 ± 0.06
**
**
**
**
**
**
**
*
3.19 ± 0.02a 3.09 ± 0.02b
14.11 ± 0.11a 13.61 ± 0.10b
120.85 ± 1.13a 116.21 ± 1.11b
16.25 ± 0.07a 16.12 ± 0.06b
Parity of dam 1 2 3 4 5 6 7 or more
**
**
**
**
2.96 ± 0.02d 3.12 ± 0.02c 3.19 ± 0.02ab 3.18 ± 0.02ab 3.24 ± 0.03a 3.19 ± 0.04ab 3.14 ± 0.05bc
13.78 ± 0.11b 14.36 ± 0.12a 14.29 ± 0.12a 14.20 ± 0.14a 13.78 ± 0.17b 13.30 ± 0.23b 13.31 ± 0.33b
119.83 ± 1.19bc 124.46 ± 1.23a 122.80 ± 1.32ab 121.88 ± 1.48ab 116.53 ± 1.81cd 111.92 ± 2.40d 112.32 ± 3.52d
16.39 ± 0.07a 16.54 ± 0.07a 16.42 ± 0.08a 16.35 ± 0.09a 16.00 ± 0.11b 15.79 ± 0.14b 15.76 ± 0.21b
Sex of lamb Male Female
**
**
**
**
3.23 ± 0.02a 3.05 ± 0.02b
14.59 ± 0.10a 13.13 ± 0.10b
125.59 ± 1.11a 111.48 ± 1.10b
16.46 ± 0.07a 15.91 ± 0.07b
Birth status Single Twin
**
**
**
**
3.61 ± 0.01a 2.68 ± 0.03b
15.63 ± 0.07a 12.08 ± 0.16b
133.04 ± 0.79a 104.02 ± 1.69b
16.56 ± 0.05a 15.80 ± 0.10b
Means with different superscripts in each subclass within a column differ significantly (P < 0.05) from each other. * P < 0.05. ** P < 0.01. a For trait abbreviations see footnote of Table 1.
y = Xb + Za a + Zm m + e with Cov (a, m) = A am ,
(4)
y = Xb + Za a + Zm m + Zc c + e with Cov (a, m) = 0,
(5)
y = Xb + Za a + Zm m + Zc c + e with Cov (a, m) = A am
(6)
where y is a n × 1 vector of observations for each trait; b, a, m, c and e are vectors of fixed effects (birth year, season of birth, parity of dam, sex and birth status of lambs), direct additive genetic effects, maternal additive genetic effects, permanent environmental effects of dam and the residual effects, respectively; X, Za , Zm , Zc are the incidence matrices of fixed effects, direct additive genetic effects, maternal genetic effects and permanent environmental effect of the dam; A is the numerator relationship matrix between animals; and am is the covariance between additive direct and maternal genetic effects. The (co)variance structure for the model was: 2 V(a) = Aa2 , V(m) = Am , V(c) = IP c2 , V(e) = IR e2 and Cov (a, m) = A am
where IP and IR are identity matrices with orders equal to the number of dams and the number of lambs, respectively and 2 , 2 ,, and 2 are direct additive genetic variance, matera2 , m c e nal additive genetic variance, maternal permanent environmental variance, and residual variance, respectively. Estimates of heritability (h2 ), maternal heritability (m2 ) and permanent maternal environmental effects (c2 ) were calculated as ratios of estimates of 2 and 2 ,, respectively, to the phenotypic variance ( 2 ). The a2 , m c p direct-maternal correlation (ram ) was computed as the ratio of the estimates of direct-maternal covariance ( am ) to the product of the 2 . The total maternal effect, square roots of estimates of a2 and m tm = ¼h2 + m2 + c2 + mram h was calculated to estimate repeatability of ewe performance. The total heritability for each trait was estimated (Willham, 1972) as h2 t = h2 + 0.5 m2 + 1.5 mram h, which predicts the expected response to phenotypic selection. Log-likelihood ratio tests were used to choose the most appropriate model for each trait (Meyer, 1992). An effect was considered to have a significant influence when its inclusion caused a significant increase in log-likelihood, compared with a model in which it was ignored. Significance was tested at P < 0.05 by comparing differences in log-likelihoods to values for a chi-squared distribution with degrees of freedom equal to the difference in the number of
(co)variance components fitted for the two models. Genetic and phenotypic correlations among BW, WW, ADG and KR were estimated in a four-trait multivariate analysis with starting values for this analysis derived from single-trait analyses. 3. Results Number of observations, phenotypic means and standard deviations for BW, WW, ADG and KR of Muzaffarnagari lambs are shown in Table 1. In this data set, lambs were distributed over 30 years with 10 to 351 lambs in each year. Birth season discriminated between lambs born in autumn (n = 3161) and spring (n = 2674). Parity of the dam ranged from 1 to 7 with 1846, 1401, 1044, 738, 460, 240 and 106 lambs produced at parity 1, 2, 3, 4, 5, 6 and 7 or above, respectively. In this study, 51% of the lambs were males and 49% were females. Single and twin-born lambs represented 90.6% and 9.4% of the data, respectively. Coefficients of variation for these growth related traits under study ranged from 12.5 to 26.7% in this study. 3.1. Environmental effects The least squares means and standard errors for BW, ADG, WW and KR of lambs are presented in Table 2. In this study, the analyses of variance showed that the fixed effects explained 11 to 24% of the phenotypic variance in all the traits; and that effect of year of birth, parity of dam, season of birth, sex of lamb and birth status of lamb were important environmental sources of variation for all pre-weaning growth traits and Kleiber ratio of lambs. All the preweaning growth traits, viz. birth weight, weaning weight, average daily weight gain and Kleiber ratio of lambs fluctuated significantly (P < 0.01) among birth years of animals. The lambs born in 2–3 parities of dam had significantly (P < 0.05) higher body weights, weight gain and Kleiber ratio than lambs of younger or older ewes at preweaning stages of development. All the pre-weaning body weights, average daily weight gain and Kleiber ratio of lambs were significantly (P < 0.01) higher in lambs born in the month of March–April as compared to those born in the month of October–November. The male lambs showed higher growth, daily weight gain and Kleiber ratio at pre-weaning than their counterparts. Lambs from single
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A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85
Table 3 Estimates of (co)variance components (g2 ) and genetic parameters for birth weight, weaning weight, average daily weight gain and Kleiber ratio of Muzaffarnagari sheep. Traits
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
BW a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
0.146 – – – 0.229 0.374 0.39 (0.03) – – – 0.39 0.10 213.44
0.08 – – 0.061 0.219 0.36 0.22 (0.04) – – 0.17 (0.02) 0.22 0.23 292.46
0.049 0.080 – – 0.239 0.369 0.13 (0.03) 0.22 (0.02) – – 0.24 0.25 303.82
0.047 0.078 0.004 – 0.241 0.369 0.13 (0.03) 0.21 (0.02) 0.06 – 0.25 0.25 303.93
0.053 0.044 – 0.031 0.232 0.359 0.15 (0.04) 0.12 (0.03) – 0.09 (0.02) 0.21 0.25 312.79
0.051 0.042 0.002 0.031 0.233 0.360 0.14 (0.04) 0.12 (0.03) 0.05 0.09 (0.02) 0.21 0.25 312.85
WW a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
2.918 – – – 9.248 12.167 0.24 (0.03) – – – 0.24 0.06 −8854.14
1.908 – – 1.318 8.74 11.966 0.16 (0.03) – – 0.11 (0.02) 0.16 0.15 −8821.59
1.81 1.201 – – 9.162 12.172 0.15 (0.03) 0.10 (0.02) – – 0.20 0.14 −8835.38
1.611 0.979 0.313 – 9.281 12.184 0.13 (0.03) 0.08 (0.02) 0.25 – 0.21 0.14 −8834.79
1.838 0.182 – 1.188 8.768 11.975 0.15 (0.03) 0.02 (0.02) – 0.10 (0.02) 0.16 0.16 −8821.06
1.756 0.150 0.087 1.168 8.817 11.977 0.15 (0.03) 0.01 (0.02) 0.17 0.10 (0.02) 0.16 0.15 −8820.99
ADG a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
272.874 – – – 1040.058 1312.932 0.21 (0.03) – – – 0.21 0.05 −20814.3
190.285 – – 119.297 987.695 1297.277 0.15 (0.03) – – 0.10 (0.02) 0.15 0.14 −20790.3
192.202 88.539 – – 1031.785 1312.526 0.15 (0.03) 0.07 (0.02) – – 0.18 0.11 −20804.5
178.670 75.439 18.955 – 1039.798 1312.863 0.14 (0.03) 0.06 (0.02) 0.16 – 0.19 0.11 −20804.3
190.354 0.095 – 119.206 987.654 1297.309 0.15 0.00 – 0.10 0.15 0.14 −20790.3
196.403 2.440 −6.228 120.616 984.074 1297.305 0.15 0.002 −0.28 0.09 0.15 0.12 −20790.3
KR a2 a2 am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
0.788 – – – 3.573 4.361 0.18 (0.03) – – – 0.18 0.05 −6293.08
0.572 – – 0.261 3.483 4.317 0.13 (0.03) – – 0.06 (0.01) 0.13 0.09 −6282.81
0.675 0.095 – – 3.58 4.35 0.16 (0.04) 0.02 (0.02) – – 0.17 0.06 −6291.83
0.715 0.116 −0.04 – 3.559 4.351 0.16 0.03 -0.14 – 0.16 0.06 −6291.76
0.573 0.000004 – 0.26 3.483 4.317 0.13 0.00 – 0.06 0.13 0.09 −6282.81
0.773 0.026 −0.14 0.303 3.37 4.330 0.18 0.01 −1.00 0.07 0.13 0.08 −6281.34
2 a2 , direct additive genetic variance; m , maternal additive genetic variance; am , direct-maternal genetic covariance; c2 ,, maternal permanent environmental variance; e2 , 2 2 residual variance; p2 , phenotypic variance; h , direct heritability; m2 , maternal heritability; ram , direct-maternal genetic correlation; c 2 : c2 /; p2 ;ht , total heritability; tm , repeatability of the ewe performance.
birth also exhibited higher body weight, weight gains and Kleiber ratio than twin-born lambs in this study.
3.2. Genetic effects for different traits Estimates of (co)variance components and genetic parameters for birth weight, weaning weight, average daily weight gain and Kleiber ratio along with their likelihood values for each analysis under the six different models are summarized in Table 3. The birth and weaning weight dataset used here was slightly larger than
that analyzed by Mandal et al. (2006), but results were essentially unchanged for birth weight but somehow different for weaning weight from those reported before and will be discussed only briefly. The estimates of direct heritabilities varied from 0.13 to 0.39, 0.13 to 0.24, 0.14 to 0.21 and 0.13 to 0.18 for BW, WW, ADG and KR, respectively in different models. Thus model 1, which ignored maternal effects, resulted in overestimation of the direct heritability for all traits under study. Fitting of a permanent environmental maternal effect (model 2) led to a reduction in additive direct heritability of 43, 33, 29 and 24 percent as compared to model 1 for
A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85 Table 4 Estimated parametersa and their standard errors from the best model for each trait.
Model Items a2 2 m c2 , e2 p2 h2 m2 c2 2 ht tm
BW 5 0.053 0.044 0.031 0.232 0.359 0.15(0.04) 0.12(0.03) 0.09(0.02) 0.21 0.25
WW 2 1.908 – 1.318 8.740 11.966 0.16(0.03) – 0.11(0.02) 0.16 0.15
ADG 2 190.285 – 119.297 987.695 1297.277 0.15(0.03) – 0.10(0.02) 0.15 0.14
KR 2 0.572 – 0.261 3.483 4.317 0.13 (0.03) – 0.06(0.01) 0.13 0.09
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Table 5 Estimates of correlationsa between various growth traitsb from four trait analysis with appropriate models. Trait 1
Trait 2
ra1a2
BW BW BW WW WW ADG
WW ADG KR ADG KR KR
0.69 0.53 0.18 0.98 0.82 0.91
rc1c2 ± ± ± ± ± ±
0.07 0.10 0.14 0.01 0.05 0.03
0.76 0.69 0.55 0.99 0.95 0.98
re1e2 ± ± ± ± ± ±
0.04 0.05 0.07 0.001 0.01 0.01
0.32 0.16 −0.05 0.99 0.90 0.94
rp1p2 ± ± ± ± ± ±
0.03 0.03 0.03 0.001 0.01 0.003
0.48 0.34 0.10 0.99 0.90 0.94
± ± ± ± ± ±
0.01 0.01 0.02 0.00 0.003 0.001
a ra1a2 is the direct genetic correlation between traits 1 and 2; rc1c2 is the permanent maternal environmental correlation between traits 1 and 2; re1e2 is the residual correlations between traits 1 and 2; rp1p2 is the phenotypic correlations between traits 1 and 2. b See Table 1 for abbreviations.
Figures in parentheses are standard errors of the estimate. a See Table 3 for abbreviations.
BW, WW, ADG and KR, respectively and this effect accounted for 17, 11, 10 and 6% of phenotypic variance (p < 0.05), respectively for these traits. Model 3, which included only direct and maternal additive effects, yielded an estimate of m2 that explained 22, 10, 7 and 2% of phenotypic variance for BW, WW, ADG and KR of lambs, respectively while correspondingly reducing the estimate a2 for these traits. Both model 2 and model 3 were superior in goodness of fit to model 1 (P < 0.05). Further, fitting a non-zero covariance ( am ) along with a maternal genetic effect (Model 4) resulted in very similar log-likelihood values to that of Model 3 for all these traits. In Model 5, which attempted to disentangle genetic and environmental components of the dam effects, the estimates of m2 converged to 0.00 or very small, indicating practically no additive maternal variance for all these traits except birth weight, where it yielded an estimate of m2 that explained only 12% of phenotypic variance and was almost similar to the size of the estimate of h2 . Allowing a direct-maternal genetic covariance ( am ) in Model 6 yielded estimates of ram ranging from −1.00 to 0.17 for these traits, and the inclusion of the covariance component did not improve goodness of fit when compared to Model 5. Model 5 was thus the preferred model for description of birth weight: additive direct, additive maternal, and maternal permanent environmental components were independent and accounted for 15, 12, and 9% of phenotypic variance, respectively. The model with only a permanent environmental effect due to the dam (Model 2) was clearly most suitable for WW, ADG and KR of animals (Table 4). The total heritability, defined as the value to calculate the expected response to phenotypic selection, for BW, WW, ADG and KR of lambs ranged from 0.21 to 0.39, 0.16 to 0.24, 0.15 to 0.21 and 0.13 to 0.18, respectively under different models and these values were moderate in nature, indicating some scope for selection response for these traits. The estimates of repeatability of ewe effects on BW, WW, ADG and KR of lambs include both total maternal and ewe transmitted additive effects for these traits, which ranged from 0.10 to 0.25, 0.06 to 0.16, 0.05 to 0.14 and 0.05 to 0.09, respectively depended on model used. 3.3. Correlation estimates among different traits The results obtained from multivariate analyses using all four traits are presented in Table 5. Direct genetic correlation estimates between traits under study were positive and low to high in magnitude, ranging from 0.18 for BW–KR to 0.98 for WW–KR. Estimates of additive genetic correlations of BW with WW, ADG and KR were low to moderately high, ranging from 0.18 to 0.69; corresponding phenotypic correlations varied from 0.10 to 0.48. The maternal permanent environmental correlation estimates between BW and other traits were also moderately high & positive and ranged from
0.55 to 0.76. The estimates of additive genetic, maternal permanent environmental, phenotypic and residual correlations of WW-ADG and WW-KR were high in magnitude, which ranged from 0.82 to 0.99. Similarly high (0.91–0.98) and positive additive genetic, maternal permanent environmental, phenotypic and residual correlations existed between ADG and KR of animals in our study. The environmental correlations estimates between all traits were positive, ranging from 0.16 for BW–ADG to 0.99 for WW–ADG except BW–KR, where the estimate was −0.05 in the present study. 4. Discussion The overall least squares means obtained in this study were well comparable with the other studies for birth weight (Prince et al., 2010; Shokrollahi and Zandieh, 2012; Mohammadi et al., 2013b), weaning weight (Prince et al., 2010; Ghafouri-Kesbi and Baneh, 2012), average daily weight gain (Prince et al., 2010) and Kleiber ratio of lamb (Savar Sofla et al., 2011; Mohammadi et al., 2011). The coefficients of variations of these growth related traits in this study ranged from 14.03% to 30.50% and were within the range of the reported values of Miraei-Ashtiani et al. (2007), Zamani and Mohammadi (2008), Savar Sofla et al. (2011) and Abbasi et al. (2012) for other sheep breeds. Different environmental factors (period of birth, parity of dam, season of birth, sex and birth status of lamb) was found to have significant effect on BW, WW, pre-weaning ADG and KR of lambs of various breeds (Abbasi et al., 2012; Prakash et al., 2012; Mohammadi et al., 2013b). The estimated values for direct (0.15) and maternal heritabilities (0.12) of BW in this study were in agreement with some of the published values reported in the literature for other meat-type breeds (Savar Sofla et al., 2011; Shokrollahi and Zandieh, 2012; Mohammadi et al., 2013b). Lower (Thiruvenkadan et al., 2012; Rashidi, 2012) and higher direct heritability estimates (Baneh et al., 2010; Roshanfekr et al., 2011; Ulutas et al., 2013) for this trait were observed in other sheep breeds. Several workers (Roshanfekr et al.,2011; Rashidi, 2012; Shokrollahi and Zandieh, 2012) reported higher maternal heritability estimates ranging from 0.18 to 024 for BW than our estimates. However, Abbasi et al. (2012) and Mohammadi et al. (2013a) observed lower maternal heritability estimates for this trait. In an earlier study, Mandal et al. (2006) observed the lower estimates of direct (0.09) and maternal (0.07) for birth weight in the Muzaffarnagari lamb. The low heritability estimates for birth weight in our study can perhaps be explained by a generally poor nutritional level of ewes creating a large environmental variation. The permanent maternal environmental (c2 ) effects for birth weight (0.09) in our study was similar to the findings of Mandal et al. (2006), Ghafouri-Kesbi and Eskandarinasab (2008), Baneh et al. (2010), Rashidi (2012) and Kamjoo et al. (2014) in various sheep breeds. Safari et al. (2005) and Abbasi et al. (2012) reported the c2 effect (0.19) for this trait in meat breeds which
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is higher than the present findings. However, lower estimates for c2 of birth weight were reported in other sheep breeds (Zamani and Mohammadi, 2008; Shokrollahi and Zandieh, 2012). The low productivity and the poor environment could partially explain low maternal effects for this breed in this study. Direct heritability estimate of 0.16 for WW was well consistent with the findings of Thiruvenkadan et al. (2011), Rashidi (2012), Mohammadi et al. (2013a,b), Kamjoo et al. (2014) and El-Wakil et al. (2014) in other sheep breeds. Direct heritability estimates for this trait obtained from the study of Baneh et al. (2010) and Shokrollahi and Baneh (2012) were higher than our estimates. However, Ghafouri-kesbi and Eskandarinasab (2008) in Zandi sheep, Senemari et al. (2011) in Zandi sheep, Savar Sofla et al. (2011) in Moghani sheep and Abbasi et al. (2012) in Iranian Baluchi sheep reported lower heritability (0.06–0.10) than our study. The c2 effect for WW (0.11) in the present study was within the range of 0.01 (Shokrollahi and Zandieh, 2012) to 0.14 (Safari et al., 2005). The estimates of direct heritability (0.21) and c2 effect (0.10) for weaning weight was obtained by Mandal et al. (2006) in Muzaffarnagari sheep. The results of this study suggest that the importance of additive maternal effects was practically nil at weaning, however, permanent environmental maternal was important at this stage. Our estimate of direct heritability (0.15) for ADG from birth to weaning was similar to the findings of other workers (Rashidi et al., 2008; Mokhtari et al., 2012; El-Wakil et al., 2014) in various sheep breeds. The low heritability estimate for pre-weaning average daily weight gain of lambs in the present study can be explained by generally poor nutritional level of ewes creating a large environmental variation and the result of this study suggest that only slow genetic progress may be obtained for these traits from selection under the prevailing management system. The permanent maternal environmental (c2 ) effects on average daily weight gains during this developmental stage accounted for only 10% of the total phenotypic variance in this study. These findings were similar with findings of Ozcan et al. (2005) in Turkish Merino (0.09) sheep, Mokhtari et al. (2012) in Arman (0.12) sheep and Khorsand et al. (2014) in Afshari sheep (0.08). However, lower estimates, ranged from 0.00 to 0.06, than our study were documented by other workers (Zamani and Mohammadi, 2008; Savar-Sofla et al., 2011) in other sheep breeds. Estimates of permanent environmental effects due to dam were higher than those for maternal heritability for these traits in the present study. This could be an indication of the large influence of environment on milk production of the ewe. Estimate of the direct heritability for Kleiber ratio (0.13) at weaning in the present study (Table 4) were well comparable with the findings of Eskandarinasab et al. (2008), Savar-Sofla et al. (2011) and Ghafouri-Kesbi (2013) who reported similar estimates of h2 for Kleiber ratio at pre-weaning in Afshari, Moghani and Mehraban breeds of sheep, respectively. However, lower h2 estimates ranged from 0.03 to 0.05 for this trait were estimated by Mohammadi et al. (2011) in Zandi sheep, Mokhtari et al. (2012) in Arman sheep and Mohammadi et al. (2013b) in Shal sheep. The permanent maternal environment effects (c2 ) for Kleiber ratio in our study was 0.06 (Table 4), which was similar to the estimates of Savar-Sofla et al. (2011) in Moghani sheep (0.07), Mokhtari et al. (2012) in Arman sheep (0.07) and Mohammadi et al. (2013b) in Shal sheep (0.06) but lower than the estimate of Mohammadi et al. (2011) who reported the value of 0.21 for this trait in Sanjabi sheep. The Kleiber ratio proposed as an efficient selection criterion for feed efficiency under low-input range conditions and provides good indication of how economically an animal grows (Mohammadi et al., 2011). According to our study, the growth efficiency in terms of the Kleiber ratio of Muzaffarnagari sheep is lowly heritable and thus trait could be applied in selection for increasing the efficiency of growth, but the selection response would be slow under prevailing management condition.
The total heritabilities (Table 4) can be used to calculate the expected response to phenotypic selection for growth traits and Kleiber ratio and were moderate in magnitude, ranging from 0.13 to 0.21, indicating some scope for selection progress in these traits. The total heritabilities observed in this study were well comparable to the findings of other studies for birth weight (Safari et al., 2005; Mohammadi et al., 2013), weaning weight (Safari et al., 2005; Rashidi, 2012; Mohammadi et al., 2013; Jalil-Sarghale et al., 2014), pre-weaning ADG (Mokhtari et al., 2012; Mohammadi et al., 2012) and Kleiber ratio (Mohammadi et al., 2010) for various sheep breeds. The estimates of repeatabilities of ewe effects for growth traits as well as for Kleiber ratio include both total maternal and ewe transmitted additive effects, which ranged from 0.09 to 0.25 under the best model (Table 4). Other published reports on maternal repeatabilities estimates for birth weight (Mokhtari et al., 2012), weaning weight (Rashidi, 2012), pre-weaning ADG (Ozcan et al., 2005; Safari et al., 2005) and KR (Mokhtari et al., 2012) for different sheep breeds were similar to the findings of the present study. Estimates of tm for all growth traits and Kleiber ratio (Table 3) in Muzaffarnagari sheep were essentially the same for Model 2 through 6, suggesting that the repeatability of ewe performance was estimated consistently across the different maternal-effect models for these traits. The direct genetic correlations of BW with WW, ADG and KR in this study were positive and varied from low to high (Table 5). Our results are in agreement with the findings of other published literatures (Ozcan et al., 2005; Rashidi et al., 2008; Mohammadi et al., 2010, 2013; Roshanfekr et al., 2011; Savar-Sofla et al., 2011; Mokhtari et al., 2012) for different sheep breeds. Similar to our estimates, several authors reported high and positive genetic correlation for WW–ADG (Miraei-Ashtiani et al., 2007; Rashidi et al., 2008; Eskandarinasab et al., 2008; Mohammadi et al., 2010, 2013; Roshanfekr et al., 2011; Abbasi et al., 2012; Mokhtari et al., 2012) and WW-KR (Abegaz et al., 2005; Rashidi et al., 2008; Eskandarinasab et al., 2008; Mohammadi et al., 2010, 2011; Mokhtari et al., 2012) in different breeds of sheep. Duguma et al. (2002) stated that WW and ADG are genetically the same traits, thus selection can be performed based on one of these traits. The high and positive direct genetic and phenotypic correlations between WW and other traits in the present study indicates that if selection is thus based on WW, improvement in all the components of growth traits may follow. The high genetic and phenotypic correlations were observed between ADG and KR (ra = 0.91 and rp = 0.94) in the present study (Table 5). Similar to our results, the higher genetic and phenotypic correlations between pre-weaning ADG and KR at weaning were reported by Ghafouri-Kesbi et al. (2011) and Mohammadi et al. (2011) in Zandi sheep (ra = 0.84–0.97, rp = 0.77–0.92) and Savar-Sofla et al. (2011) in Moghani sheep (ra = 0.90, rp = 0.85). However, Mokhtari et al. (2012) and Mohammadi et al. (2013b) obtained somewhat lower estimates for genetic and phenotypic correlation between ADG and KR in Arman sheep (ra = 0.75, rp = 0.39) and Shal sheep (ra = 0.79, rp = 0.43), respectively. The high and positive maternal permanent environmental correlations, ranging from 0.55 to 0.99, between all traits in the present study were well within the range of other reported values of different sheep breeds (Rashidi et al., 2008; Abbasi et al., 2012). The high genetic and phenotypic correlations of WW with ADG and KR and of ADG with KR in our study indicate that they are under similar genetic control and selection for WW will increase the pre-weaning ADG and the efficiency of feed utilization at weaning in Muzaffarnagari lambs. Therefore, improvement in KR at weaning is possible through selection on body weight, especially WW.
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5. Conclusion The results of the present study demonstrated that environmental factors played a significant role on body weights, average daily gain and Kleiber ratio of Muzaffarnaagri sheep from birth to weaning. The low heritability estimates of traits under study indicate that only slow genetic progress may be possible for these traits from selection under the prevailing management system. The maternal additive effect was only important for weight at birth, whereas a permanent environmental maternal effect existed from birth to weaning for all traits under study. Thus the results suggest that both direct and permanent environmental maternal effects must be taken into consideration for analyzing the growth traits and Kleiber ratio of Muzaffarnagari sheep. Further, the results also indicate that selection for WW will be effective for improving KR of lambs due to existence of high genetic correlation between these traits. Conflict of interest This research paper does not have any conflict issue. Acknowledgements Authors are thankful to the Director, CIRG, for providing the facilities to carry out this work. The support extended by the Director, NDRI, Karnal, Haryana, for preparing this manuscript is also gratefully acknowledged. We wish to acknowledge the contribution of the all former incharges, associated with the Muzaffanagari sheep project, for management and recording of data. References Abbasi, M.A., Abdollahi-Arpanahi, R., Maghsoudic, A., Vaez Torshizic, R., Nejati-Javaremi, A., 2012. Evaluation of models for estimation of genetic parameters and maternal effects for early growth traits of Iranian Baluchi sheep. Small Rumin. Res. 104, 62–69. Al-Shorepy, S.A., 2001. Estimates of genetic parameters for direct and maternal effects on birth weight of local sheep in United Arab Emirates. Small Rumin. Res. 39, 219–224. Baneh, H., Hafezian, S.H., Rashidi, A., Gholizadeh, M., Rahimi, G., 2010. Estimation of genetic parameters of body weight traits in Ghezel sheep. Asian–Aust. J. Anim. Sci. 23, 149–153. El-Wakil, Salwa, I., Gad, S.M.A., 2014. Evaluation of direct and maternal (co)variance components and heritabilities for some body weights and growth traits in Barki sheep. Egypt. J. Sheep Goat Sci. 9 (1), 21–30. Eskandarinasab, M., Ghafouri-Kesbi, F., Abbasi, M.A., 2008. Different models for evaluation of growth traits and Kleiber ratio in an experimental flock of Iranian fat-tailed Afshari sheep. J. Anim. Breed. Genet. 127, 26–33. Ghafouri-Kesbi, F., 2013. (Co)variance components and genetic parameters for growth rate and Kleiber ratio in fat-tailed Mehraban sheep. Arch. Tierz. 56 (55), 564–572. Ghafouri-Kesbi, F., Abbasi, M.A., Afraz, F., Babaei, M., Baneh, H., Arpanahi, R.A., 2011. Genetic analysis of growth rate and Kleiber ratio in Zandi sheep. Trop. Anim. Health Prod. 43, 1153–1159. Ghafouri-Kesbi, F., Baneh, H., 2012. Genetic parameters for direct and maternal effects on growth traits of sheep. Arch. Tierz. 55 (6), 603–611. Ghafouri-Kesbi, F., Eskandarinasab, M.P., 2008. An evaluation of maternal influences on growth traits: the Zandi sheep breed of Iran as an example. J. Anim. Feed Sci. 17, 519–529. Hanford, K.J., van Vleck, L.D., Snowder, G.D., 2006. Estimates of genetic parameters and genetic trend for reproduction, weight, and wool characteristics of Polypay sheep. Livest. Sci. 102, 72–82. Harvey, W.R., 1990. User’s Guide for LSMLMW MIXMDL, PC-2 Version, Columbus, OH, USA. Jalil-Sarghale, A., Kholghi, M., Moradi shahrebabak, M., Moradi shahrebabak, H., Mohammadi, H., Abdollahi-arpanahi, R., 2014. Model comparisons and genetic parameter estimates of growth traits in Baluchi sheep. Slovakian J. Anim. Sci. 47 (1), 12–18. Kamjoo, B., Baneh, H., Yousefia, V., Mandal, A., Rahimi, G., 2014. Genetic parameter estimates for growth traits in Iran-Black sheep. J. Appl. Anim. Res. 42 (1), 79–88. Khorsand, A., Hafezian, S.H., Teimouri-Yansari, A., Farhadi, A., 2014. Genetic parameters of direct and maternal effects for growth traits of Afshari sheep. Iran. J. Appl. Anim. Sci. 4 (1), 69–74.
85
Kleiber, M., 1947. Body size and metabolic rate. Physiol. Rev. 27, 511–541. Köster, E., Van der Westhuizen, J., Erasmus, G.J., 1994. Heritability estimates for different Kleiber ratios obtained from growth performance data in a Hereford herd. South Afr. J. Anim. Sci. 24, 71–72. Kushwaha, B.P., Mandal, A., Arora, A.L., Kumar, R., Kumar, S., Notter, D.R., 2009. Direct and maternal (co)variance components and heritability estimates for body weights in Chokla sheep. J. Anim. Breed. Genet. 126, 278–287. Mandal, A., Dass, G., Rout, P.K., 2012. Model comparisons for estimation of genetic parameters of pre-weaning daily weight gains in Muzaffarnagari sheep. Small Rumin. Res. 106, 118–124. Mandal, A., Neser, F.W.C., Rout, P.K., Roy, R., Notter, D.R., 2006. Genetic parameters for direct and maternal effects on body weights of Muzaffarnagari sheep. Anim. Sci. 82, 133–140. Mandal, A., Pant, K.P., Nandy, D.K., Rout, P.K., Roy, R., 2003. Genetic analysis of growth traits in Muzaffanagari sheep. Trop. Anim. Health Prod. 35, 271–284. Mandal, A., Singh, L.B., Rout, P.K., 2000. The Muzaffarnagari sheep, a mutton breed in India. Anim. Genet. Res. Information, Rome, Food and Agricultural Organization, 28, 19–25. Meyer, K., 1992. Variance components due to direct and maternal effects for growth traits of Australian beef cattle. Livest. Prod. Sci. 31, 179–204. Meyer, K., 2000. DFREML programs to estimate variance components by restricted maximum likelihood using a derivative-free algorithm–User Notes. Miraei-Ashtiani, S.R., Seyedalian, S.A.R., Shahrbabak, M.M., 2007. Variance components and heritabilities for body weights traits in Sangsari sheep, using univariate and multivariate animal models. Small Rumin. Res. 73, 109–114. Mohammadi, H., Shahrebabak, M.M., Vatankhah, M., Shahrebabak, H.M., 2013a. Direct and maternal (co)variance components, genetic parameters, and annual trends for growth traits of Makooei sheep in Iran. Trop. Anim. Health Prod. 45, 185–191. Mohammadi, H., Shahrebabak, M.M., Shahrebabak, H.M., Bahrami, A., Dorostkar, M., 2013b. Model comparisons and genetic parameter estimates of growth and the Kleiber ratio in Shal sheep. Arch. Tierz. 56 (26), 264–275. Mohammadi, K., Rashidi, A., Mokhtari, M.S., Beigi Nassiri, M.T., 2011. The estimation of (co)variance components for growth traits and Kleiber ratios in Zandi sheep. Small Rumin. Res. 99 (2), 116–121. Mohammadi, Y., Rashidi, A., Mokhtari, M.S., Esmailizadeh, A.K., 2010. Quantitative genetic analysis of growth traits and Kleiber ratios in Sanjabi sheep. Small Rumin. Res. 93, 88–93. Mokhtari, M.S., Moradi Shahrebabak, M., Moradi Shahrebabk, H., Sadeghi, M., 2012. Estimation of (co)variance components and genetic parameters for growth traits in Arman sheep. J. Livest. Sci. Tech. 1 (1), 38–47. Ozcan, M., Ekiz, B., Yilmaz, A., Ceyhan, A., 2005. Genetic parameter estimates for lamb growth traits and greasy fleece weight at first shearing in Turkish Merino sheep. Small Rumin. Res. 56, 215–222. Prakash, V., Prince, L.L.L., Gowane, G.R., Arora, A.L., 2012. Factors affecting post-weaning average daily gain and Kleiber ratios in Malpura sheep. Indian J. Anim. Sci. 82 (12), 1598–1600. Prince, L.L.L., Gowane, G.R., Chopra, A., Arora, A.L., 2010. Estimates of (co)variance components and genetic parameters for growth traits of Avikalin sheep. Trop. Anim. Health Prod. 42, 1093–1101. Rashidi, A., 2012. Genetic parameter estimates of body weight traits in Iran-Black sheep. J. Livest. Sci. Tech. 1 (1), 54–60. Rashidi, A., Mokhtari, M.S., Jahanshahi, A.S., Abadi, M.R.M., 2008. Genetic parameter estimates of pre-weaning growth traits in Kermani sheep. Small Rumin. Res. 74, 165–171. Roshanfekr, H., Mamouei, M., Mohammadi, K., Rahmatnejad, E., 2011. Estimation of genetic and environmental parameters affected pre-weaning traits of Arabi lambs. J. Anim. Vet. Sci. 10 (10), 1239–1243. Safari, E., Fogarty, N.M., Gilmour, A.R., 2005. A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep. Livest. Prod. Sci. 92, 271–289. Savar-Sofla, S., Nejati-Javaremi, A., Abbasi, M.A., Vaez-Torshizi, R., Chamani, M., 2011. Investigation on direct and maternal effects on growth traits and the Kleiber ratio in Moghani Sheep. World Appl. Sci. J. 14 (9), 1313–1319. Senemari, M., Kalantar, M., Khalajzadeh, S., Gholizadeh, M., 2011. Genetic and phenotypic parameters of body weight in Zandi sheep. Afr. J. Biotechnol. 10 (68), 15444–15449. Shokrollahi, B., Baneh, H., 2012. (Co)variance components and genetic parameters for growth traits in Arabi sheep using different animal models. Genet. Mol. Res. 11 (1), 305–314. Shokrollahi, B., Zandieh, M., 2012. Estimation of genetic parameters for body weights of Kurdish sheep in various ages using multivariate animal models. Afr. J. Biotechnol. 11, 2119–2123. Thiruvenkadan, A.K., Karunanithi, K., Muralidharan, J., Babu, R.N., 2011. Genetic analysis of pre-weaning and post-weaning growth traits of Mecheri sheep under dry land farming conditions. Asian–Aust. J. Anim. Sci. 24 (8), 1041–1047. Ulutas, Z., Sirin, E., Aksoy, Y., Sahin, A., Kuran, M., 2013. Estimates of (co)variance components for direct and maternal effects on birth weight of Karayaka lambs. Trop. Anim. Health Prod. 45, 953–956. Willham, R.L., 1972. The role of maternal effects in Animal breeding: III. Biometrical aspects of maternal effects in animal. J. Anim. Sci. 35, 1288–1293. Zamani, P., Mohammadi, H., 2008. Comparison of different models for estimation of genetic parameters of early growth traits in the Mehraban sheep. J. Anim. Breed. Genet. 125, 29–34.
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Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres
Variance components and genetic parameters of growth traits and Kleiber ratio in Muzaffarnagari sheep Ajoy Mandal a,∗ , M. Karunakaran a , D.K. Sharma b , Hasan Baneh c , P.K. Rout b a b c
Eastern Regional Station of National Dairy Research Institute, A/12 Block, Kalyani 7412 35, Nadia, West Bengal, India Central Institute for Research on Goats, Makhdoom, Mathura 281 122, Uttar Pradesh, India Young Researchers and Elite Club, Karaj Branch, Islamic Azad University, Karaj, Iran
a r t i c l e
i n f o
Article history: Received 7 October 2014 Received in revised form 10 September 2015 Accepted 6 October 2015 Available online 20 October 2015 Keywords: Growth traits Average daily weight gain Kleiber ratio Maternal effects Heritability Muzaffarnagari sheep
a b s t r a c t Estimates of (co)variance components and genetic parameters were obtained for birth weight (BW), weaning weight (WW), average daily weight gain from birth to weaning (ADG) and Kleiber ratio (KR) of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura, India, over a period of 30 years (1976–2005). Records of 5835 lambs descended from 176 rams and 1703 ewes were used in the study. Analyses were carried out by restricted maximum likelihood (REML) fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits. The best model was chosen after testing the improvement of the log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Heritability estimates for BW, WW, ADG and KR were 0.15, 0.16, 0.15 and 0.13, respectively. Maternal genetic effects contributed only 12% of the total variance for birth weight. Estimates of fraction of variance due to maternal permanent environmental effects (c2 ) for BW, WW, ADG and KR accounted for 6–12% of the total phenotypic variance in this study. The estimates of the direct genetic correlation among studied traits were positive, ranging from 0.18 (BW–KR) to 0.98 (WW–ADG), whereas permanent maternal environmental correlations among traits varied from from 0.55 (BW–KR) to 0.99 (WW–ADG). The estimates of the phenotypic and environmental correlation between traits under study ranged from 0.10 to 0.99 and −0.05 to 0.99, respectively. Results suggest that maternal additive effect was only important for birth weight whereas permanent environmental maternal effects were important for other traits in our study. The moderate heritability estimates for early growth traits and Kleiber ratio of sheep in this study indicates that modest rates of genetic progress may be possible for these traits from selection under the prevailing management system. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Early growth traits are important factors influencing the profitability of any meat producing enterprise. Promoting the growth potential of lambs is a possible alternative to increase meat production and improving breeding efficiency in any sheep breeding enterprise (Miraei-Ashtiani et al., 2007). Body weights and growth rates in pre-weaning are often considered as an early indicator of the late growth and economic benefit (Hanford et al., 2006). In any selection program aimed at increasing growth performance in order to achieve maximum output, improving weaning weight (WW) is necessary. This is possible by including a trait such as
∗ Corresponding author. Fax.: +91 33 2582 8264. E-mail addresses: [email protected], [email protected] (A. Mandal). http://dx.doi.org/10.1016/j.smallrumres.2015.10.009 0921-4488/© 2015 Elsevier B.V. All rights reserved.
Kleiber ratio (KR) in selection programs. Kleiber ratio, defined as growth rate/metabolic weight (body weight0.75 ), as suggested for measuring growth efficiency (Kleiber, 1947) was developed as an alternative ratio to select animals for breeding. Moreover, KR as an indication of efficiency of feed conversion is useful because it does not require individual intake to be measured and allows us to identify animals with high efficiency of growth relative to body size (Kleiber, 1947). Köster et al. (1994) suggested that KR could be used as a useful indicator of feed conversion and an important selection criterion for efficiency of growth. Animals that have a high KR are considered efficient users of feed (Ghafouri-Kesbi et al., 2011). Numerous studies have demonstrated that both direct and maternal influences are important for growth (Mandal et al., 2006; Kushwaha et al., 2009), average daily weight gains (Rashidi et al., 2008; Savar-Sofla et al., 2011; Mandal et al., 2012) and Kleiber ratio (Savar-Sofla et al., 2011; Mokhtari et al., 2012; Mohammadi
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Table 1 Characteristics of data structure for pre-weaning growth traitsa of Muzaffarnagari sheep. Items/traits
BW (kg)
WW(kg)
ADG(g)
KR
No. of records No. of animalsb No. of sires with progeny record No. of dams with progeny record Progeny per sire Progeny per dam Mean Standard deviation CV (%) Years of records
5835 6089 176 1703 33.15 3.43 3.46 0.72 20.81 30
5135 5339 176 1602 29.18 3.21 15.75 4.01 25.46 29
5135 5339 176 1602 29.18 3.21 135.94 41.46 30.50 29
5135 5339 176 1602 29.18 3.21 16.89 2.37 14.03 29
a b
BW, Birth weight, WW, Weaning weight, ADG, Average daily weight gain from birth to weaning, KR, Kleiber ratio (ADG/WW0.75 ). Animals in pedigrees.
et al., 2013b) of sheep. Many previous published research studies (Al-Shorepy, 2001; Mandal et al., 2006) showed that selection efficiency or genetic progress was largely dependent on the effective use of additive genetic variance, and maternal effects become more important for selection of early growth traits. So, accurate estimation of genetic parameters for economically important traits is needed for designing optimal breeding strategies for livestock species (Safari et al., 2005). The Muzaffarnagari sheep, an important mutton breed of India, is known for its relatively rapid growth, high feed conversion efficiency and very good adaptability (Mandal et al., 2003) in the semi-arid region of the country and widely distributed in the western Uttar Pradesh, near Meerut, Muzaffarnagar, Saharanpur, Bijnor and in the some parts of Delhi and Haryana. The breed has better potential for meat and carpet wool production than other Indian sheep breeds. The description of the study location as well as characteristics of the breed, its location, habitat and husbandry practices have been depicted by Mandal et al. (2000) for this breed. Most of reported heritabilities of growth traits of this breed are based on ratios of variance components estimated mainly by paternal half-sib method (Mandal et al., 2003), without taking into consideration the maternal effects. In a study by Mandal et al. (2006), direct and maternal (co)variance components for birth weight and weaning weight of lambs were reported for Muzaffarnagari sheep. The objective of this investigation was to extend those analyses to include estimation of the genetic parameters for direct and maternal effects on birth weight, weaning weight, pre-weaning average daily weight gain and Kleiber ratio of Muzaffarnagari sheep.
2. Materials and methods 2.1. Data Data were collected from an experimental breeding flock of Muzaffarnagari sheep, maintained at the Central Institute for Research on Goats (CIRG), Makhdoom, Uttar Pradesh, India, under the All India Coordinated Research Project on Sheep Breeding for Mutton Production for a period of 30 years (1976–2005). The data includes 5835 lamb records from 1703 ewes sired by 176 rams. The number of records analyzed ranged from 1389 to 2930, depending on the traits of interest (Table 1). Briefly, the flock included 250 breeding ewes reared under the semi-intensive feeding system, with animals allowed to graze for 6–7 h during the day and penned at night. The animals were provided were 250 g of growth ration, comprising of 72% total digestible nutrients (TDN) and 16% digestible crude protein (DCP). Generally maize (15%), barley (20%), ground nut cake (35%), wheat bran (20%), molasses (7%), mineral mixture (1.5%) and salt (1.5%) were the ingredients used in formulating the growth ration. Dry and green fodder was given ad libitum to these animals. Ewes were first exposed to rams at 12 to
14 months of age and hand-mated to selected sires. Breeding generally occurred in May and June and again in October and November; lambing therefore normally occurred in October and November and in March and April. One breeding ram was normally allowed to mate with 20 to 25 ewes, and breeding rams were used for approximately 3 years. On average, a ewe produces a lamb in every 1 or 1.5 years. At lambing, both lambs and dams were weighed. Each lamb was identified by a metal ear tag after birth and the lambing date, sex and birth type of each lamb were recorded. Lambs were kept with their dams in individual pens for 2 to 3 days after birth. Lambs were kept indoors during the suckling period, and were normally weaned at 3 months of age. Lambs were weighed at 15-day interval from birth to weaning at 3 months of age and thereafter at monthly intervals up to 12 months of age (Mandal et al., 2006). Animals were vaccinated against peste des petits for ruminants (PPR), enterotoxaemia and haemorrhagic septicaemia (HS). The traits analyzed for these analyses were birth weight (BW), weaning weight (WW), average daily weight gains (ADG) from birth to 90 days (weaning) and pre-weaning Kleiber ratio (KR). 2.2. Statistical analyses (Co)variance components were estimated by restricted maximum likelihood (REML) using a derivative-free algorithm fitting an animal model (DFREML, Meyer, 2000). Data were first analyzed by least-squares analysis of variance (Harvey, 1990) to identify the fixed effects to be included in the model. The statistical model included the fixed effect of birth year (30 levels), season of birth (2 levels), parity of dam (1, 2, 3, 4, 5, 6, ≥7), sex (2 levels) and birth status (single vs. twin) of lambs. All these effects were significant (P < 0.05) for all traits and all were included in the models subsequently used to estimate genetic parameters. Convergence of the REML solutions was assumed when the variance of function values (−2 log L) in the Simplex was less than 10−8 . To ensure that a global maximum was reached, analyses were restarted for several other rounds of iterations using results from the previous round as starting values. When estimates did not change, convergence was confirmed. Depending on the model, the log-likelihood function was maximized with respect to the direct and maternal additive variances, the permanent environmental variance of the dam and the genetic covariance between direct and maternal genetic effects. Standard errors were calculated for the estimated parameters as a part of the DFREML program (Meyer, 2000). Univariate animal models were fitted to estimate (co)variance components for each trait. The following six models were used: y = Xb + Za a + e,
(1)
y = Xb + Za a + Zc c + e,
(2)
y = Xb + Za a + Zm m + e with Cov (a, m) = 0,
(3)
A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85
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Table 2 Least-squares means along with standard errors of pre-weaning growth traitsa of Muzaffarnagari sheep. Effects
Traitsa BW (kg)
WW (kg)
ADG (g)
KR
Overall mean Birth year Birth season March–April October–November
3.14±0.01
13.86 ± 0.09
118.53 ± 1.00
16.18 ± 0.06
**
**
**
**
**
**
**
*
3.19 ± 0.02a 3.09 ± 0.02b
14.11 ± 0.11a 13.61 ± 0.10b
120.85 ± 1.13a 116.21 ± 1.11b
16.25 ± 0.07a 16.12 ± 0.06b
Parity of dam 1 2 3 4 5 6 7 or more
**
**
**
**
2.96 ± 0.02d 3.12 ± 0.02c 3.19 ± 0.02ab 3.18 ± 0.02ab 3.24 ± 0.03a 3.19 ± 0.04ab 3.14 ± 0.05bc
13.78 ± 0.11b 14.36 ± 0.12a 14.29 ± 0.12a 14.20 ± 0.14a 13.78 ± 0.17b 13.30 ± 0.23b 13.31 ± 0.33b
119.83 ± 1.19bc 124.46 ± 1.23a 122.80 ± 1.32ab 121.88 ± 1.48ab 116.53 ± 1.81cd 111.92 ± 2.40d 112.32 ± 3.52d
16.39 ± 0.07a 16.54 ± 0.07a 16.42 ± 0.08a 16.35 ± 0.09a 16.00 ± 0.11b 15.79 ± 0.14b 15.76 ± 0.21b
Sex of lamb Male Female
**
**
**
**
3.23 ± 0.02a 3.05 ± 0.02b
14.59 ± 0.10a 13.13 ± 0.10b
125.59 ± 1.11a 111.48 ± 1.10b
16.46 ± 0.07a 15.91 ± 0.07b
Birth status Single Twin
**
**
**
**
3.61 ± 0.01a 2.68 ± 0.03b
15.63 ± 0.07a 12.08 ± 0.16b
133.04 ± 0.79a 104.02 ± 1.69b
16.56 ± 0.05a 15.80 ± 0.10b
Means with different superscripts in each subclass within a column differ significantly (P < 0.05) from each other. * P < 0.05. ** P < 0.01. a For trait abbreviations see footnote of Table 1.
y = Xb + Za a + Zm m + e with Cov (a, m) = A am ,
(4)
y = Xb + Za a + Zm m + Zc c + e with Cov (a, m) = 0,
(5)
y = Xb + Za a + Zm m + Zc c + e with Cov (a, m) = A am
(6)
where y is a n × 1 vector of observations for each trait; b, a, m, c and e are vectors of fixed effects (birth year, season of birth, parity of dam, sex and birth status of lambs), direct additive genetic effects, maternal additive genetic effects, permanent environmental effects of dam and the residual effects, respectively; X, Za , Zm , Zc are the incidence matrices of fixed effects, direct additive genetic effects, maternal genetic effects and permanent environmental effect of the dam; A is the numerator relationship matrix between animals; and am is the covariance between additive direct and maternal genetic effects. The (co)variance structure for the model was: 2 V(a) = Aa2 , V(m) = Am , V(c) = IP c2 , V(e) = IR e2 and Cov (a, m) = A am
where IP and IR are identity matrices with orders equal to the number of dams and the number of lambs, respectively and 2 , 2 ,, and 2 are direct additive genetic variance, matera2 , m c e nal additive genetic variance, maternal permanent environmental variance, and residual variance, respectively. Estimates of heritability (h2 ), maternal heritability (m2 ) and permanent maternal environmental effects (c2 ) were calculated as ratios of estimates of 2 and 2 ,, respectively, to the phenotypic variance ( 2 ). The a2 , m c p direct-maternal correlation (ram ) was computed as the ratio of the estimates of direct-maternal covariance ( am ) to the product of the 2 . The total maternal effect, square roots of estimates of a2 and m tm = ¼h2 + m2 + c2 + mram h was calculated to estimate repeatability of ewe performance. The total heritability for each trait was estimated (Willham, 1972) as h2 t = h2 + 0.5 m2 + 1.5 mram h, which predicts the expected response to phenotypic selection. Log-likelihood ratio tests were used to choose the most appropriate model for each trait (Meyer, 1992). An effect was considered to have a significant influence when its inclusion caused a significant increase in log-likelihood, compared with a model in which it was ignored. Significance was tested at P < 0.05 by comparing differences in log-likelihoods to values for a chi-squared distribution with degrees of freedom equal to the difference in the number of
(co)variance components fitted for the two models. Genetic and phenotypic correlations among BW, WW, ADG and KR were estimated in a four-trait multivariate analysis with starting values for this analysis derived from single-trait analyses. 3. Results Number of observations, phenotypic means and standard deviations for BW, WW, ADG and KR of Muzaffarnagari lambs are shown in Table 1. In this data set, lambs were distributed over 30 years with 10 to 351 lambs in each year. Birth season discriminated between lambs born in autumn (n = 3161) and spring (n = 2674). Parity of the dam ranged from 1 to 7 with 1846, 1401, 1044, 738, 460, 240 and 106 lambs produced at parity 1, 2, 3, 4, 5, 6 and 7 or above, respectively. In this study, 51% of the lambs were males and 49% were females. Single and twin-born lambs represented 90.6% and 9.4% of the data, respectively. Coefficients of variation for these growth related traits under study ranged from 12.5 to 26.7% in this study. 3.1. Environmental effects The least squares means and standard errors for BW, ADG, WW and KR of lambs are presented in Table 2. In this study, the analyses of variance showed that the fixed effects explained 11 to 24% of the phenotypic variance in all the traits; and that effect of year of birth, parity of dam, season of birth, sex of lamb and birth status of lamb were important environmental sources of variation for all pre-weaning growth traits and Kleiber ratio of lambs. All the preweaning growth traits, viz. birth weight, weaning weight, average daily weight gain and Kleiber ratio of lambs fluctuated significantly (P < 0.01) among birth years of animals. The lambs born in 2–3 parities of dam had significantly (P < 0.05) higher body weights, weight gain and Kleiber ratio than lambs of younger or older ewes at preweaning stages of development. All the pre-weaning body weights, average daily weight gain and Kleiber ratio of lambs were significantly (P < 0.01) higher in lambs born in the month of March–April as compared to those born in the month of October–November. The male lambs showed higher growth, daily weight gain and Kleiber ratio at pre-weaning than their counterparts. Lambs from single
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A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85
Table 3 Estimates of (co)variance components (g2 ) and genetic parameters for birth weight, weaning weight, average daily weight gain and Kleiber ratio of Muzaffarnagari sheep. Traits
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
BW a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
0.146 – – – 0.229 0.374 0.39 (0.03) – – – 0.39 0.10 213.44
0.08 – – 0.061 0.219 0.36 0.22 (0.04) – – 0.17 (0.02) 0.22 0.23 292.46
0.049 0.080 – – 0.239 0.369 0.13 (0.03) 0.22 (0.02) – – 0.24 0.25 303.82
0.047 0.078 0.004 – 0.241 0.369 0.13 (0.03) 0.21 (0.02) 0.06 – 0.25 0.25 303.93
0.053 0.044 – 0.031 0.232 0.359 0.15 (0.04) 0.12 (0.03) – 0.09 (0.02) 0.21 0.25 312.79
0.051 0.042 0.002 0.031 0.233 0.360 0.14 (0.04) 0.12 (0.03) 0.05 0.09 (0.02) 0.21 0.25 312.85
WW a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
2.918 – – – 9.248 12.167 0.24 (0.03) – – – 0.24 0.06 −8854.14
1.908 – – 1.318 8.74 11.966 0.16 (0.03) – – 0.11 (0.02) 0.16 0.15 −8821.59
1.81 1.201 – – 9.162 12.172 0.15 (0.03) 0.10 (0.02) – – 0.20 0.14 −8835.38
1.611 0.979 0.313 – 9.281 12.184 0.13 (0.03) 0.08 (0.02) 0.25 – 0.21 0.14 −8834.79
1.838 0.182 – 1.188 8.768 11.975 0.15 (0.03) 0.02 (0.02) – 0.10 (0.02) 0.16 0.16 −8821.06
1.756 0.150 0.087 1.168 8.817 11.977 0.15 (0.03) 0.01 (0.02) 0.17 0.10 (0.02) 0.16 0.15 −8820.99
ADG a2 2 m am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
272.874 – – – 1040.058 1312.932 0.21 (0.03) – – – 0.21 0.05 −20814.3
190.285 – – 119.297 987.695 1297.277 0.15 (0.03) – – 0.10 (0.02) 0.15 0.14 −20790.3
192.202 88.539 – – 1031.785 1312.526 0.15 (0.03) 0.07 (0.02) – – 0.18 0.11 −20804.5
178.670 75.439 18.955 – 1039.798 1312.863 0.14 (0.03) 0.06 (0.02) 0.16 – 0.19 0.11 −20804.3
190.354 0.095 – 119.206 987.654 1297.309 0.15 0.00 – 0.10 0.15 0.14 −20790.3
196.403 2.440 −6.228 120.616 984.074 1297.305 0.15 0.002 −0.28 0.09 0.15 0.12 −20790.3
KR a2 a2 am c2 e2 p2 h2 m2 ram c2 2 ht tm log L
0.788 – – – 3.573 4.361 0.18 (0.03) – – – 0.18 0.05 −6293.08
0.572 – – 0.261 3.483 4.317 0.13 (0.03) – – 0.06 (0.01) 0.13 0.09 −6282.81
0.675 0.095 – – 3.58 4.35 0.16 (0.04) 0.02 (0.02) – – 0.17 0.06 −6291.83
0.715 0.116 −0.04 – 3.559 4.351 0.16 0.03 -0.14 – 0.16 0.06 −6291.76
0.573 0.000004 – 0.26 3.483 4.317 0.13 0.00 – 0.06 0.13 0.09 −6282.81
0.773 0.026 −0.14 0.303 3.37 4.330 0.18 0.01 −1.00 0.07 0.13 0.08 −6281.34
2 a2 , direct additive genetic variance; m , maternal additive genetic variance; am , direct-maternal genetic covariance; c2 ,, maternal permanent environmental variance; e2 , 2 2 residual variance; p2 , phenotypic variance; h , direct heritability; m2 , maternal heritability; ram , direct-maternal genetic correlation; c 2 : c2 /; p2 ;ht , total heritability; tm , repeatability of the ewe performance.
birth also exhibited higher body weight, weight gains and Kleiber ratio than twin-born lambs in this study.
3.2. Genetic effects for different traits Estimates of (co)variance components and genetic parameters for birth weight, weaning weight, average daily weight gain and Kleiber ratio along with their likelihood values for each analysis under the six different models are summarized in Table 3. The birth and weaning weight dataset used here was slightly larger than
that analyzed by Mandal et al. (2006), but results were essentially unchanged for birth weight but somehow different for weaning weight from those reported before and will be discussed only briefly. The estimates of direct heritabilities varied from 0.13 to 0.39, 0.13 to 0.24, 0.14 to 0.21 and 0.13 to 0.18 for BW, WW, ADG and KR, respectively in different models. Thus model 1, which ignored maternal effects, resulted in overestimation of the direct heritability for all traits under study. Fitting of a permanent environmental maternal effect (model 2) led to a reduction in additive direct heritability of 43, 33, 29 and 24 percent as compared to model 1 for
A. Mandal et al. / Small Ruminant Research 132 (2015) 79–85 Table 4 Estimated parametersa and their standard errors from the best model for each trait.
Model Items a2 2 m c2 , e2 p2 h2 m2 c2 2 ht tm
BW 5 0.053 0.044 0.031 0.232 0.359 0.15(0.04) 0.12(0.03) 0.09(0.02) 0.21 0.25
WW 2 1.908 – 1.318 8.740 11.966 0.16(0.03) – 0.11(0.02) 0.16 0.15
ADG 2 190.285 – 119.297 987.695 1297.277 0.15(0.03) – 0.10(0.02) 0.15 0.14
KR 2 0.572 – 0.261 3.483 4.317 0.13 (0.03) – 0.06(0.01) 0.13 0.09
83
Table 5 Estimates of correlationsa between various growth traitsb from four trait analysis with appropriate models. Trait 1
Trait 2
ra1a2
BW BW BW WW WW ADG
WW ADG KR ADG KR KR
0.69 0.53 0.18 0.98 0.82 0.91
rc1c2 ± ± ± ± ± ±
0.07 0.10 0.14 0.01 0.05 0.03
0.76 0.69 0.55 0.99 0.95 0.98
re1e2 ± ± ± ± ± ±
0.04 0.05 0.07 0.001 0.01 0.01
0.32 0.16 −0.05 0.99 0.90 0.94
rp1p2 ± ± ± ± ± ±
0.03 0.03 0.03 0.001 0.01 0.003
0.48 0.34 0.10 0.99 0.90 0.94
± ± ± ± ± ±
0.01 0.01 0.02 0.00 0.003 0.001
a ra1a2 is the direct genetic correlation between traits 1 and 2; rc1c2 is the permanent maternal environmental correlation between traits 1 and 2; re1e2 is the residual correlations between traits 1 and 2; rp1p2 is the phenotypic correlations between traits 1 and 2. b See Table 1 for abbreviations.
Figures in parentheses are standard errors of the estimate. a See Table 3 for abbreviations.
BW, WW, ADG and KR, respectively and this effect accounted for 17, 11, 10 and 6% of phenotypic variance (p < 0.05), respectively for these traits. Model 3, which included only direct and maternal additive effects, yielded an estimate of m2 that explained 22, 10, 7 and 2% of phenotypic variance for BW, WW, ADG and KR of lambs, respectively while correspondingly reducing the estimate a2 for these traits. Both model 2 and model 3 were superior in goodness of fit to model 1 (P < 0.05). Further, fitting a non-zero covariance ( am ) along with a maternal genetic effect (Model 4) resulted in very similar log-likelihood values to that of Model 3 for all these traits. In Model 5, which attempted to disentangle genetic and environmental components of the dam effects, the estimates of m2 converged to 0.00 or very small, indicating practically no additive maternal variance for all these traits except birth weight, where it yielded an estimate of m2 that explained only 12% of phenotypic variance and was almost similar to the size of the estimate of h2 . Allowing a direct-maternal genetic covariance ( am ) in Model 6 yielded estimates of ram ranging from −1.00 to 0.17 for these traits, and the inclusion of the covariance component did not improve goodness of fit when compared to Model 5. Model 5 was thus the preferred model for description of birth weight: additive direct, additive maternal, and maternal permanent environmental components were independent and accounted for 15, 12, and 9% of phenotypic variance, respectively. The model with only a permanent environmental effect due to the dam (Model 2) was clearly most suitable for WW, ADG and KR of animals (Table 4). The total heritability, defined as the value to calculate the expected response to phenotypic selection, for BW, WW, ADG and KR of lambs ranged from 0.21 to 0.39, 0.16 to 0.24, 0.15 to 0.21 and 0.13 to 0.18, respectively under different models and these values were moderate in nature, indicating some scope for selection response for these traits. The estimates of repeatability of ewe effects on BW, WW, ADG and KR of lambs include both total maternal and ewe transmitted additive effects for these traits, which ranged from 0.10 to 0.25, 0.06 to 0.16, 0.05 to 0.14 and 0.05 to 0.09, respectively depended on model used. 3.3. Correlation estimates among different traits The results obtained from multivariate analyses using all four traits are presented in Table 5. Direct genetic correlation estimates between traits under study were positive and low to high in magnitude, ranging from 0.18 for BW–KR to 0.98 for WW–KR. Estimates of additive genetic correlations of BW with WW, ADG and KR were low to moderately high, ranging from 0.18 to 0.69; corresponding phenotypic correlations varied from 0.10 to 0.48. The maternal permanent environmental correlation estimates between BW and other traits were also moderately high & positive and ranged from
0.55 to 0.76. The estimates of additive genetic, maternal permanent environmental, phenotypic and residual correlations of WW-ADG and WW-KR were high in magnitude, which ranged from 0.82 to 0.99. Similarly high (0.91–0.98) and positive additive genetic, maternal permanent environmental, phenotypic and residual correlations existed between ADG and KR of animals in our study. The environmental correlations estimates between all traits were positive, ranging from 0.16 for BW–ADG to 0.99 for WW–ADG except BW–KR, where the estimate was −0.05 in the present study. 4. Discussion The overall least squares means obtained in this study were well comparable with the other studies for birth weight (Prince et al., 2010; Shokrollahi and Zandieh, 2012; Mohammadi et al., 2013b), weaning weight (Prince et al., 2010; Ghafouri-Kesbi and Baneh, 2012), average daily weight gain (Prince et al., 2010) and Kleiber ratio of lamb (Savar Sofla et al., 2011; Mohammadi et al., 2011). The coefficients of variations of these growth related traits in this study ranged from 14.03% to 30.50% and were within the range of the reported values of Miraei-Ashtiani et al. (2007), Zamani and Mohammadi (2008), Savar Sofla et al. (2011) and Abbasi et al. (2012) for other sheep breeds. Different environmental factors (period of birth, parity of dam, season of birth, sex and birth status of lamb) was found to have significant effect on BW, WW, pre-weaning ADG and KR of lambs of various breeds (Abbasi et al., 2012; Prakash et al., 2012; Mohammadi et al., 2013b). The estimated values for direct (0.15) and maternal heritabilities (0.12) of BW in this study were in agreement with some of the published values reported in the literature for other meat-type breeds (Savar Sofla et al., 2011; Shokrollahi and Zandieh, 2012; Mohammadi et al., 2013b). Lower (Thiruvenkadan et al., 2012; Rashidi, 2012) and higher direct heritability estimates (Baneh et al., 2010; Roshanfekr et al., 2011; Ulutas et al., 2013) for this trait were observed in other sheep breeds. Several workers (Roshanfekr et al.,2011; Rashidi, 2012; Shokrollahi and Zandieh, 2012) reported higher maternal heritability estimates ranging from 0.18 to 024 for BW than our estimates. However, Abbasi et al. (2012) and Mohammadi et al. (2013a) observed lower maternal heritability estimates for this trait. In an earlier study, Mandal et al. (2006) observed the lower estimates of direct (0.09) and maternal (0.07) for birth weight in the Muzaffarnagari lamb. The low heritability estimates for birth weight in our study can perhaps be explained by a generally poor nutritional level of ewes creating a large environmental variation. The permanent maternal environmental (c2 ) effects for birth weight (0.09) in our study was similar to the findings of Mandal et al. (2006), Ghafouri-Kesbi and Eskandarinasab (2008), Baneh et al. (2010), Rashidi (2012) and Kamjoo et al. (2014) in various sheep breeds. Safari et al. (2005) and Abbasi et al. (2012) reported the c2 effect (0.19) for this trait in meat breeds which
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is higher than the present findings. However, lower estimates for c2 of birth weight were reported in other sheep breeds (Zamani and Mohammadi, 2008; Shokrollahi and Zandieh, 2012). The low productivity and the poor environment could partially explain low maternal effects for this breed in this study. Direct heritability estimate of 0.16 for WW was well consistent with the findings of Thiruvenkadan et al. (2011), Rashidi (2012), Mohammadi et al. (2013a,b), Kamjoo et al. (2014) and El-Wakil et al. (2014) in other sheep breeds. Direct heritability estimates for this trait obtained from the study of Baneh et al. (2010) and Shokrollahi and Baneh (2012) were higher than our estimates. However, Ghafouri-kesbi and Eskandarinasab (2008) in Zandi sheep, Senemari et al. (2011) in Zandi sheep, Savar Sofla et al. (2011) in Moghani sheep and Abbasi et al. (2012) in Iranian Baluchi sheep reported lower heritability (0.06–0.10) than our study. The c2 effect for WW (0.11) in the present study was within the range of 0.01 (Shokrollahi and Zandieh, 2012) to 0.14 (Safari et al., 2005). The estimates of direct heritability (0.21) and c2 effect (0.10) for weaning weight was obtained by Mandal et al. (2006) in Muzaffarnagari sheep. The results of this study suggest that the importance of additive maternal effects was practically nil at weaning, however, permanent environmental maternal was important at this stage. Our estimate of direct heritability (0.15) for ADG from birth to weaning was similar to the findings of other workers (Rashidi et al., 2008; Mokhtari et al., 2012; El-Wakil et al., 2014) in various sheep breeds. The low heritability estimate for pre-weaning average daily weight gain of lambs in the present study can be explained by generally poor nutritional level of ewes creating a large environmental variation and the result of this study suggest that only slow genetic progress may be obtained for these traits from selection under the prevailing management system. The permanent maternal environmental (c2 ) effects on average daily weight gains during this developmental stage accounted for only 10% of the total phenotypic variance in this study. These findings were similar with findings of Ozcan et al. (2005) in Turkish Merino (0.09) sheep, Mokhtari et al. (2012) in Arman (0.12) sheep and Khorsand et al. (2014) in Afshari sheep (0.08). However, lower estimates, ranged from 0.00 to 0.06, than our study were documented by other workers (Zamani and Mohammadi, 2008; Savar-Sofla et al., 2011) in other sheep breeds. Estimates of permanent environmental effects due to dam were higher than those for maternal heritability for these traits in the present study. This could be an indication of the large influence of environment on milk production of the ewe. Estimate of the direct heritability for Kleiber ratio (0.13) at weaning in the present study (Table 4) were well comparable with the findings of Eskandarinasab et al. (2008), Savar-Sofla et al. (2011) and Ghafouri-Kesbi (2013) who reported similar estimates of h2 for Kleiber ratio at pre-weaning in Afshari, Moghani and Mehraban breeds of sheep, respectively. However, lower h2 estimates ranged from 0.03 to 0.05 for this trait were estimated by Mohammadi et al. (2011) in Zandi sheep, Mokhtari et al. (2012) in Arman sheep and Mohammadi et al. (2013b) in Shal sheep. The permanent maternal environment effects (c2 ) for Kleiber ratio in our study was 0.06 (Table 4), which was similar to the estimates of Savar-Sofla et al. (2011) in Moghani sheep (0.07), Mokhtari et al. (2012) in Arman sheep (0.07) and Mohammadi et al. (2013b) in Shal sheep (0.06) but lower than the estimate of Mohammadi et al. (2011) who reported the value of 0.21 for this trait in Sanjabi sheep. The Kleiber ratio proposed as an efficient selection criterion for feed efficiency under low-input range conditions and provides good indication of how economically an animal grows (Mohammadi et al., 2011). According to our study, the growth efficiency in terms of the Kleiber ratio of Muzaffarnagari sheep is lowly heritable and thus trait could be applied in selection for increasing the efficiency of growth, but the selection response would be slow under prevailing management condition.
The total heritabilities (Table 4) can be used to calculate the expected response to phenotypic selection for growth traits and Kleiber ratio and were moderate in magnitude, ranging from 0.13 to 0.21, indicating some scope for selection progress in these traits. The total heritabilities observed in this study were well comparable to the findings of other studies for birth weight (Safari et al., 2005; Mohammadi et al., 2013), weaning weight (Safari et al., 2005; Rashidi, 2012; Mohammadi et al., 2013; Jalil-Sarghale et al., 2014), pre-weaning ADG (Mokhtari et al., 2012; Mohammadi et al., 2012) and Kleiber ratio (Mohammadi et al., 2010) for various sheep breeds. The estimates of repeatabilities of ewe effects for growth traits as well as for Kleiber ratio include both total maternal and ewe transmitted additive effects, which ranged from 0.09 to 0.25 under the best model (Table 4). Other published reports on maternal repeatabilities estimates for birth weight (Mokhtari et al., 2012), weaning weight (Rashidi, 2012), pre-weaning ADG (Ozcan et al., 2005; Safari et al., 2005) and KR (Mokhtari et al., 2012) for different sheep breeds were similar to the findings of the present study. Estimates of tm for all growth traits and Kleiber ratio (Table 3) in Muzaffarnagari sheep were essentially the same for Model 2 through 6, suggesting that the repeatability of ewe performance was estimated consistently across the different maternal-effect models for these traits. The direct genetic correlations of BW with WW, ADG and KR in this study were positive and varied from low to high (Table 5). Our results are in agreement with the findings of other published literatures (Ozcan et al., 2005; Rashidi et al., 2008; Mohammadi et al., 2010, 2013; Roshanfekr et al., 2011; Savar-Sofla et al., 2011; Mokhtari et al., 2012) for different sheep breeds. Similar to our estimates, several authors reported high and positive genetic correlation for WW–ADG (Miraei-Ashtiani et al., 2007; Rashidi et al., 2008; Eskandarinasab et al., 2008; Mohammadi et al., 2010, 2013; Roshanfekr et al., 2011; Abbasi et al., 2012; Mokhtari et al., 2012) and WW-KR (Abegaz et al., 2005; Rashidi et al., 2008; Eskandarinasab et al., 2008; Mohammadi et al., 2010, 2011; Mokhtari et al., 2012) in different breeds of sheep. Duguma et al. (2002) stated that WW and ADG are genetically the same traits, thus selection can be performed based on one of these traits. The high and positive direct genetic and phenotypic correlations between WW and other traits in the present study indicates that if selection is thus based on WW, improvement in all the components of growth traits may follow. The high genetic and phenotypic correlations were observed between ADG and KR (ra = 0.91 and rp = 0.94) in the present study (Table 5). Similar to our results, the higher genetic and phenotypic correlations between pre-weaning ADG and KR at weaning were reported by Ghafouri-Kesbi et al. (2011) and Mohammadi et al. (2011) in Zandi sheep (ra = 0.84–0.97, rp = 0.77–0.92) and Savar-Sofla et al. (2011) in Moghani sheep (ra = 0.90, rp = 0.85). However, Mokhtari et al. (2012) and Mohammadi et al. (2013b) obtained somewhat lower estimates for genetic and phenotypic correlation between ADG and KR in Arman sheep (ra = 0.75, rp = 0.39) and Shal sheep (ra = 0.79, rp = 0.43), respectively. The high and positive maternal permanent environmental correlations, ranging from 0.55 to 0.99, between all traits in the present study were well within the range of other reported values of different sheep breeds (Rashidi et al., 2008; Abbasi et al., 2012). The high genetic and phenotypic correlations of WW with ADG and KR and of ADG with KR in our study indicate that they are under similar genetic control and selection for WW will increase the pre-weaning ADG and the efficiency of feed utilization at weaning in Muzaffarnagari lambs. Therefore, improvement in KR at weaning is possible through selection on body weight, especially WW.
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5. Conclusion The results of the present study demonstrated that environmental factors played a significant role on body weights, average daily gain and Kleiber ratio of Muzaffarnaagri sheep from birth to weaning. The low heritability estimates of traits under study indicate that only slow genetic progress may be possible for these traits from selection under the prevailing management system. The maternal additive effect was only important for weight at birth, whereas a permanent environmental maternal effect existed from birth to weaning for all traits under study. Thus the results suggest that both direct and permanent environmental maternal effects must be taken into consideration for analyzing the growth traits and Kleiber ratio of Muzaffarnagari sheep. Further, the results also indicate that selection for WW will be effective for improving KR of lambs due to existence of high genetic correlation between these traits. Conflict of interest This research paper does not have any conflict issue. Acknowledgements Authors are thankful to the Director, CIRG, for providing the facilities to carry out this work. The support extended by the Director, NDRI, Karnal, Haryana, for preparing this manuscript is also gratefully acknowledged. We wish to acknowledge the contribution of the all former incharges, associated with the Muzaffanagari sheep project, for management and recording of data. References Abbasi, M.A., Abdollahi-Arpanahi, R., Maghsoudic, A., Vaez Torshizic, R., Nejati-Javaremi, A., 2012. Evaluation of models for estimation of genetic parameters and maternal effects for early growth traits of Iranian Baluchi sheep. Small Rumin. Res. 104, 62–69. Al-Shorepy, S.A., 2001. Estimates of genetic parameters for direct and maternal effects on birth weight of local sheep in United Arab Emirates. Small Rumin. Res. 39, 219–224. Baneh, H., Hafezian, S.H., Rashidi, A., Gholizadeh, M., Rahimi, G., 2010. Estimation of genetic parameters of body weight traits in Ghezel sheep. Asian–Aust. J. Anim. Sci. 23, 149–153. El-Wakil, Salwa, I., Gad, S.M.A., 2014. Evaluation of direct and maternal (co)variance components and heritabilities for some body weights and growth traits in Barki sheep. Egypt. J. Sheep Goat Sci. 9 (1), 21–30. Eskandarinasab, M., Ghafouri-Kesbi, F., Abbasi, M.A., 2008. Different models for evaluation of growth traits and Kleiber ratio in an experimental flock of Iranian fat-tailed Afshari sheep. J. Anim. Breed. Genet. 127, 26–33. Ghafouri-Kesbi, F., 2013. (Co)variance components and genetic parameters for growth rate and Kleiber ratio in fat-tailed Mehraban sheep. Arch. Tierz. 56 (55), 564–572. Ghafouri-Kesbi, F., Abbasi, M.A., Afraz, F., Babaei, M., Baneh, H., Arpanahi, R.A., 2011. Genetic analysis of growth rate and Kleiber ratio in Zandi sheep. Trop. Anim. Health Prod. 43, 1153–1159. Ghafouri-Kesbi, F., Baneh, H., 2012. Genetic parameters for direct and maternal effects on growth traits of sheep. Arch. Tierz. 55 (6), 603–611. Ghafouri-Kesbi, F., Eskandarinasab, M.P., 2008. An evaluation of maternal influences on growth traits: the Zandi sheep breed of Iran as an example. J. Anim. Feed Sci. 17, 519–529. Hanford, K.J., van Vleck, L.D., Snowder, G.D., 2006. Estimates of genetic parameters and genetic trend for reproduction, weight, and wool characteristics of Polypay sheep. Livest. Sci. 102, 72–82. Harvey, W.R., 1990. User’s Guide for LSMLMW MIXMDL, PC-2 Version, Columbus, OH, USA. Jalil-Sarghale, A., Kholghi, M., Moradi shahrebabak, M., Moradi shahrebabak, H., Mohammadi, H., Abdollahi-arpanahi, R., 2014. Model comparisons and genetic parameter estimates of growth traits in Baluchi sheep. Slovakian J. Anim. Sci. 47 (1), 12–18. Kamjoo, B., Baneh, H., Yousefia, V., Mandal, A., Rahimi, G., 2014. Genetic parameter estimates for growth traits in Iran-Black sheep. J. Appl. Anim. Res. 42 (1), 79–88. Khorsand, A., Hafezian, S.H., Teimouri-Yansari, A., Farhadi, A., 2014. Genetic parameters of direct and maternal effects for growth traits of Afshari sheep. Iran. J. Appl. Anim. Sci. 4 (1), 69–74.
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Kleiber, M., 1947. Body size and metabolic rate. Physiol. Rev. 27, 511–541. Köster, E., Van der Westhuizen, J., Erasmus, G.J., 1994. Heritability estimates for different Kleiber ratios obtained from growth performance data in a Hereford herd. South Afr. J. Anim. Sci. 24, 71–72. Kushwaha, B.P., Mandal, A., Arora, A.L., Kumar, R., Kumar, S., Notter, D.R., 2009. Direct and maternal (co)variance components and heritability estimates for body weights in Chokla sheep. J. Anim. Breed. Genet. 126, 278–287. Mandal, A., Dass, G., Rout, P.K., 2012. Model comparisons for estimation of genetic parameters of pre-weaning daily weight gains in Muzaffarnagari sheep. Small Rumin. Res. 106, 118–124. Mandal, A., Neser, F.W.C., Rout, P.K., Roy, R., Notter, D.R., 2006. Genetic parameters for direct and maternal effects on body weights of Muzaffarnagari sheep. Anim. Sci. 82, 133–140. Mandal, A., Pant, K.P., Nandy, D.K., Rout, P.K., Roy, R., 2003. Genetic analysis of growth traits in Muzaffanagari sheep. Trop. Anim. Health Prod. 35, 271–284. Mandal, A., Singh, L.B., Rout, P.K., 2000. The Muzaffarnagari sheep, a mutton breed in India. Anim. Genet. Res. Information, Rome, Food and Agricultural Organization, 28, 19–25. Meyer, K., 1992. Variance components due to direct and maternal effects for growth traits of Australian beef cattle. Livest. Prod. Sci. 31, 179–204. Meyer, K., 2000. DFREML programs to estimate variance components by restricted maximum likelihood using a derivative-free algorithm–User Notes. Miraei-Ashtiani, S.R., Seyedalian, S.A.R., Shahrbabak, M.M., 2007. Variance components and heritabilities for body weights traits in Sangsari sheep, using univariate and multivariate animal models. Small Rumin. Res. 73, 109–114. Mohammadi, H., Shahrebabak, M.M., Vatankhah, M., Shahrebabak, H.M., 2013a. Direct and maternal (co)variance components, genetic parameters, and annual trends for growth traits of Makooei sheep in Iran. Trop. Anim. Health Prod. 45, 185–191. Mohammadi, H., Shahrebabak, M.M., Shahrebabak, H.M., Bahrami, A., Dorostkar, M., 2013b. Model comparisons and genetic parameter estimates of growth and the Kleiber ratio in Shal sheep. Arch. Tierz. 56 (26), 264–275. Mohammadi, K., Rashidi, A., Mokhtari, M.S., Beigi Nassiri, M.T., 2011. The estimation of (co)variance components for growth traits and Kleiber ratios in Zandi sheep. Small Rumin. Res. 99 (2), 116–121. Mohammadi, Y., Rashidi, A., Mokhtari, M.S., Esmailizadeh, A.K., 2010. Quantitative genetic analysis of growth traits and Kleiber ratios in Sanjabi sheep. Small Rumin. Res. 93, 88–93. Mokhtari, M.S., Moradi Shahrebabak, M., Moradi Shahrebabk, H., Sadeghi, M., 2012. Estimation of (co)variance components and genetic parameters for growth traits in Arman sheep. J. Livest. Sci. Tech. 1 (1), 38–47. Ozcan, M., Ekiz, B., Yilmaz, A., Ceyhan, A., 2005. Genetic parameter estimates for lamb growth traits and greasy fleece weight at first shearing in Turkish Merino sheep. Small Rumin. Res. 56, 215–222. Prakash, V., Prince, L.L.L., Gowane, G.R., Arora, A.L., 2012. Factors affecting post-weaning average daily gain and Kleiber ratios in Malpura sheep. Indian J. Anim. Sci. 82 (12), 1598–1600. Prince, L.L.L., Gowane, G.R., Chopra, A., Arora, A.L., 2010. Estimates of (co)variance components and genetic parameters for growth traits of Avikalin sheep. Trop. Anim. Health Prod. 42, 1093–1101. Rashidi, A., 2012. Genetic parameter estimates of body weight traits in Iran-Black sheep. J. Livest. Sci. Tech. 1 (1), 54–60. Rashidi, A., Mokhtari, M.S., Jahanshahi, A.S., Abadi, M.R.M., 2008. Genetic parameter estimates of pre-weaning growth traits in Kermani sheep. Small Rumin. Res. 74, 165–171. Roshanfekr, H., Mamouei, M., Mohammadi, K., Rahmatnejad, E., 2011. Estimation of genetic and environmental parameters affected pre-weaning traits of Arabi lambs. J. Anim. Vet. Sci. 10 (10), 1239–1243. Safari, E., Fogarty, N.M., Gilmour, A.R., 2005. A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep. Livest. Prod. Sci. 92, 271–289. Savar-Sofla, S., Nejati-Javaremi, A., Abbasi, M.A., Vaez-Torshizi, R., Chamani, M., 2011. Investigation on direct and maternal effects on growth traits and the Kleiber ratio in Moghani Sheep. World Appl. Sci. J. 14 (9), 1313–1319. Senemari, M., Kalantar, M., Khalajzadeh, S., Gholizadeh, M., 2011. Genetic and phenotypic parameters of body weight in Zandi sheep. Afr. J. Biotechnol. 10 (68), 15444–15449. Shokrollahi, B., Baneh, H., 2012. (Co)variance components and genetic parameters for growth traits in Arabi sheep using different animal models. Genet. Mol. Res. 11 (1), 305–314. Shokrollahi, B., Zandieh, M., 2012. Estimation of genetic parameters for body weights of Kurdish sheep in various ages using multivariate animal models. Afr. J. Biotechnol. 11, 2119–2123. Thiruvenkadan, A.K., Karunanithi, K., Muralidharan, J., Babu, R.N., 2011. Genetic analysis of pre-weaning and post-weaning growth traits of Mecheri sheep under dry land farming conditions. Asian–Aust. J. Anim. Sci. 24 (8), 1041–1047. Ulutas, Z., Sirin, E., Aksoy, Y., Sahin, A., Kuran, M., 2013. Estimates of (co)variance components for direct and maternal effects on birth weight of Karayaka lambs. Trop. Anim. Health Prod. 45, 953–956. Willham, R.L., 1972. The role of maternal effects in Animal breeding: III. Biometrical aspects of maternal effects in animal. J. Anim. Sci. 35, 1288–1293. Zamani, P., Mohammadi, H., 2008. Comparison of different models for estimation of genetic parameters of early growth traits in the Mehraban sheep. J. Anim. Breed. Genet. 125, 29–34.