Trop Anim Health Prod (2012) 44:337–341 DOI 10.1007/s11250-011-0026-8
ORIGINAL RESEARCH
Genetic parameters for birth weight, weaning weight and age at first calving in Brown Swiss cattle in Mexico José C. Segura-Correa & Ricardo C. Chin-Colli & Juan G. Magaña-Monforte & Rafael Núñez-Domínguez
Accepted: 8 November 2011 / Published online: 24 November 2011 # Springer Science+Business Media B.V. 2011
Abstract Heritabilities and genetic correlations between birth weight (n=13,741), adjusted 240-day weaning weight (WW, n=8,806) and age at first calving (AFC, n=3,955) of Brown Swiss cattle in Mexico were estimated. Data from 91 herds located in 19 of 32 states of Mexico from 1982 to 2006 were provided by the Mexican Brown cattle Breeder Association. Components of (co)variance, direct and maternal heritabilities were estimated for birth weight, WW and AFC using bivariate animal models. Direct and maternal heritabilities were 0.21 and 0.05 for birth weight, 0.40 and 0.05 for WW, whereas direct heritability for AFC was 0.08. The correlations between direct and maternal effects for birth weight and WW were −0.49 and −0.64, respectively. The genetic correlations between birth weight–WW and WW–
J. C. Segura-Correa (*) : R. C. Chin-Colli : J. G. Magaña-Monforte Facultad de Medicina Veterinaria y Zootecnia, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Km 15.5 Carretera Mérida-Xmatkuil, AP 4-116 Mérida, Yucatán, Mexico e-mail:
[email protected] R. C. Chin-Colli e-mail:
[email protected] J. G. Magaña-Monforte e-mail:
[email protected] R. Núñez-Domínguez Departamento de Zootecnia, Posgrado en Producción Animal, Universidad Autónoma Chapingo, Carretera México-Texcoco Km 38.5, 56230 Chapingo, Estado de México, Mexico e-mail:
[email protected]
AFC were 0.36 and −0.02, respectively. Under the conditions of this study, selection for increasing birth weight would increase WW, but increasing WW will not change AFC. Keywords Brown Swiss . Heritability . Genetic correlations . Tropics
Introduction Brown Swiss cattle are the main source of genes for commercial herds devoted to dual-purpose production systems in the tropics of Mexico. However, information on environmental and genetic factors that affect productive and reproductive traits on that breed is limited. In Mexico, genetic evaluation for preweaning traits of Brown Swiss cattle started in 2003 (Núñez et al. 2003). Improvement of reproductive traits seems to be of much economical impact in livestock production; therefore, reproductive traits should be included in the genetic evaluations and selection indexes in order to choose the best animals to increase animal production and productivity of the herd. However, before selection can be carried out, it is necessary to estimate the heritabilities and the genetic correlations between growth and reproductive traits to predict the response to selection for a given trait. There are few reports on parameter estimates in Brown Swiss cattle in Mexico (Estrada et al. 2008). Therefore, the objective of this study was to estimate the heritabilities and genetic correlations for birth weight, adjusted weaning weight and age at first calving for Brown Swiss cattle under the tropical and semi-arid conditions of Mexico.
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Materials and methods Origen and characteristics of the data Information from 1982 to 2006 from 91 Brown Swiss cattle farms, under tropical (81 farms) and semi-arid (ten farms) environments, located in 19 states of Mexico was used. Performance records were provided by the Mexican Brown Swiss Cattle Breeder Association. The production systems varied from grazing to supplementation with commercial feed. Reproduction occurs along the year and based mainly on controlled natural mating and artificial insemination. The studied traits were birth weight (BW, n= 13,741), adjusted 240day weaning weight (WW, n =8,806) and age at first calving (AFC, n=3,955). The complete data structure is shown in Table 1. Also, 10% of the data had dams with records as calves and more than 1.5 calves per cow. Bulls had more than five calves, which seems to be an appropriate structure for partition of the maternal and environmental permanent effects (Maniatis and Pollott 2003). Data from bulls with less than five calves were deleted from the study. Statistical analysis Contemporary groups were formed by farm, year, season of birth, sex of the calf (BW, WW), feed regime (WW) combination. Season of birth was defined according to monthly rainfall and temperature distribution in a year (SMN 2008). Connectivity among contemporary groups
Table 1 Structure and descriptive statistics of Brown Swiss cattle data in Mexico
was determined using the MILC program (Fries 1998). Data from unconnected contemporary groups were deleted. The matrix notation for the statistical model to be solved was: yi ¼ Xbi þ Zai þ Mmi þ Wpi þ ei ; where yi is the vector of observations for the ith trait, bi is the vector of contemporary fixed effects, ai is the vector of random animal effects, mi is the vector of random maternal genetic effects, pi is the vector of random common environmental effects and ei is the vector of random errors. X, Z, M and W are incidence matrices of 0 s and 1 s relating records of the trait to the fixed effects and random effects. The random effects were assumed to follow a normal distribution with a mean of zero and a (co)variance structure with 2 3 2 3 u As 2a As 2am 0 0 6 m 7 6 As As 2m 0 0 7 6 7 am 7 var6 7 ¼ 6 0 0 Is 2p 0 5 4p 5 4 e
0
0
0
Is 2e
where A is the numerator relationship matrix; I is the identity matrix; s 2a is the additive genetic variance for the direct effect; s 2m is the additive genetic variance for the maternal effect; s 2p is the common environmental variance;
s 2e is the residual variance and σam is the covariance between the direct and maternal additive genetic effects. Estimates of (co)variance components were obtained by using the multitrait derivative-free REML computer pro-
Concept
Birth weight
Weaning weight
Age at first calving
No. of animals with records No. of paternal grandparents No. of maternal grandparents No. of sires No. of dams No. of dams with records No. of records per dam (mean) % of dams with 1 record % of dams with 2 records % of dams with ≥3 records Mean ± SD (kg) Coefficient of variation
13,741 210 678 442 7,673 1,276 1.79 52.24 27.04 20.72 37.7±5.1 13.48
8,806 204 592 410 5,650 732 1.55 61.43 25.65 12.92 235.4±43.9 18.60
3,955 147 351 300 2,991 891 1.32 74.09 20.43 5.48 1,206±327 27.14
% of males No. of herds Contemporary groups
50.65 89 967
50.81 77 697
———— 61 381
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Table 2 Components of (co)variance for BW, WW and AFC in Brown Swiss cattle in Mexico
Table 4 Genetic (d1d2), environmental (e1e2) and phenotypic (p1p2) correlations between BW, WW and AFC in Brown Swiss cattle in Mexico
Components of (co)variance Trait
σ2d
σ2m
σ2c
σdm
σ2e
σ2P
BW
2.40
0.63
0.65
−0.61
8.62
11.7
WW
257.40
34.25
18.99
−59.62
399.45
650.6
AFC
5,738.72
64,334.4
70,073.1
σ2 d =direct additive genetic variance, σ2 m =maternal additive genetic variance, σ2 c =maternal permanent environmental variance, σdm = direct-maternal additive genetic covariance, σ2 e =residual variance, σ2 P =phenotypic variance
gram written by Boldman et al. (1995). Heritability for total genetic merit (h2t) was obtained according to Willham (1972) as h2T ¼ s 2a þ 1:5s am þ 0:5s 2m =s 2p , where the phenotypic variance (σ p) was: s 2p ¼ s 2a þ s 2m þ s am þ s 2e : 2
Results Tables 2 and 3 show the components of (co)variance and heritabilities for BW, WW and AFC. The additive direct (h2d) and maternal (h2m) heritability estimates were 0.21 and 0.05 for BW, and 0.40 and 0.05 for WW, whereas the h2d for AFC was 0.08. The h2T estimates for BW, WW and AFC were 0.26, 0.39 and 0.08, respectively. The genetic correlations between the direct and maternal effects (rdm) for BW and WW were antagonic (−0.49 and −0.64). Genetic, environmental and phenotypic correlations are shown in Table 4. The direct additive genetic correlation between BW and WW was 0.36 and between WW and EFC was −0.02. The environmental correlation between BW and WW was 0.40 and between WW and AFC was −0.04.
Table 3 Genetic parameters for BW, WW and AFC in Brown Swiss cattle in Mexico Genetic parameters Trait
h2d
h2m
rdm
h2T
BW WW AFC
0.21 0.40 0.08
0.05 0.05
−0.49 −0.64
0.15 0.28 0.08
h2 d =direct heritability, h2 m =maternal heritability, h2 T =total heritability, rdm =direct-maternal genetic correlation
Traits
d1d2
e1e2
p1p2
BW–WW WW–AFC
0.36 −0.02
0.15 −0.04
0.33 −0.29
Discussion There is no much information on genetic parameters in Brown Swiss cattle in the literature therefore our results are basically compared with studies in other breeds in Mexico and abroad. Heritabilities Birth weight The h2d (0.21) estimated for BW was higher than the reported for Brown Swiss cattle (0.15) by Muammer et al. (2008) in Turkey but lower than the values (0.22–0.40) reported for Simmental (RosalesAlday et al. 2004), Charolais (Ríos et al. 2007) and Nellore cattle (Medina-Zaldivar et al. 2005) in Mexico and Braunvieh cattle (Cucco et al. 2009) in Brazil. Differences between parameter estimates may be due to management and breed differences. Although the h2d estimated in this study is moderate, it is important and suggests a possible genetic improvement for this trait through selection. The h2m estimated in this study was low (0.05) but similar to the values notified for Brown Swiss (0.06) cattle in Turkey (Muammer et al. 2008) and Braunvieh (0.08) cattle in Brazil (Cucco et al. 2009). However, it is lower than the values (0.12–0.16) reported in Mexico for the Simmental (Rosales-Alday et al. 2004), Charolais (Ríos‐ Utrera et al. 2007) and Brahman (Parra-Bracamonte et al. 2007). This indicates that the maternal genetic variance is of low importance for the improvement of this trait. The negative value for rdm (−0.49) estimated in this study disagree with the positive value (0.92) notified for the Brown Swiss breed in Turkey (Muammer et al. 2008). However, is similar to the value (−0,47) notified by Cucco et al. (2009) in Braunvieh cattle and also agrees in sign with the value obtained in Mexico (−0.63 to −0.96) in other cattle breeds (Rosales-Alday et al. 2004; Parra-Bracamonte et al. 2007; Ríos‐Utrera et al. 2007). Our results also show that if BW is to be included in breeding programs, it is necessary to considerer both the additive genetic direct and the maternal genetic effects in the calculation of breeding values.
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Weaning weight adjusted to 240 days of age The h2d estimate (0.41) for WW was equal to that reported (0.41) for weaning weight by Cucco et al. (2009) for Braunvieh cattle in Brazil (0.41); however, is higher than the values reported in Mexico for Simmental (0.33, Rosales-Alday et al. 2004), Brahman (0.22, Parra-Bracamonte et al. 2007) and Charolais (0.33, Ríos‐Utrera et al. 2007) but slightly lower than the value for the Nellore cattle (0.43) reported in Mexico by Medina-Zaldivar et al. (2005). As mention before, differences between heritability estimates may be due to management and breed differences. Because of the moderate heritability here found, it is possible to improve this trait through genetic selection. Regarding the h2m, our estimate (0.05) was lower than those (0.12–0.18) reported for Hereford, Angus and Charolais cattle (Donoghue and Bertrand 2004) and for the Braunvieh breed (0.22) in Brazil (Cucco et al. 2009). This suggests that under the present conditions of this study, the maternal genetic variance of WW is not very important to improve this trait in Brown Swiss cattle in Mexico. Differences in parameter estimates may be due among others to management, population structure and breed differences. The low maternal heritability estimated suggests that the maternal environment (mainly milk yield) was not an important component affecting growth in Brown Swiss cattle. The rdm estimated in this study was negative and high (−0.64) but lower than the values reported by RosalesAlday et al. (2004) and Ríos-Utrera et al. (2007) for beef cattle and by Cucco et al. (2009) in Braunvieh cattle. The negative genetic correlation between the direct and maternal effects probably is due to the pleiotropic antagonic effects of the genes that influence the maternal ability and growth of the calf (Lee and Pollak 2002; Wilson and Réale 2006), the selection criteria used, data structure problems and model used. Age at first calving The h2d (0.08) estimated for AFC was low and inferior to the value notified for Romosinuano cattle (0.16) in Colombia (Suárez et al. 2006), Brown Swiss (0.28) in Mexico (Estrada et al. 2008) and Nellore (0.17) in Brazil (Boligon et al. 2010); although is similar to the average value (0.06) reported by Koots et al. (1994). Therefore, the genetic improvement will be slow but constant, which emphasizes the important role of the environmental factors in the improvement of this trait. Correlation between BW and WW The genetic correlation (0.36) estimated between BW and WW was moderate and favorable, which suggests the presence of common genes for both traits. Therefore, the selection of animals with high BW will increase WW and vice versa. However, it should be taken into account that whereas increasing WW is a
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desirable thing, increasing BW may increase the frequency of dystocia (Zaborski et al. 2009), especially in first calving cows. The phenotypic correlation (0.33) between BW and WW although slightly lower than the genetic one, shows an important grade of relationship between those two traits. The environmental correlation (0.15) estimated suggests the presence of common environmental effects for both traits. Correlation between WW and AFC The genetic correlation (−0.02) estimated between WW and AFC was closest to zero, which suggests that an increase in WW by selection will not affect the AFC of Brown Swiss cattle. Similar results were reported in Nellore cattle (0.008 and −0.09) by Nieto et al. (2007) and Garnero et al. (2001), respectively. The phenotypic correlation was negative (−0.29) and higher than the genetic one, whereas the environmental correlation (−0.04) was slightly greater. In conclusion, additive direct heritabilities estimates for BW and WW indicate that the genetic improvement of these traits through the selection is possible. A more rapid improvement of AFC performance could be achieved through better management practices and feeding. Although the direct and maternal effects are low and their genetic relationship is antagonic, they should be taken in account to avoid bias in the genetic evaluations. An increase in BW will cause an increase in WW and vice versa; however, the improvement of WW seems not to affect the AFC of Brown Swiss cattle.
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