| Livestock Research for Rural Development 27 (9) 2015 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
A study was undertaken in Hungary with the objectives to evaluate Hungarian Simmental cattle growth traits and estimate genetic parameters. Calving ease, birth weight, weaning weight, weaning age, 205-day weight and average daily gain of Hungarian Simmental calves (n=6552, bulls=1479 , heifers=5073) were evaluated. The effects included in the model for the analysis of growth traits were sex (2 classes), birth year (13 classes), birth month (12 classes) and farm (8 classes). R software program was used to calculate variance analysis and least square means; PEST software was used for data file and pedigree file coding and VCE6 software was used for calculating heritablities and correlations.
Sex, year, month and farm significantly influenced CE, BW, WW, WA, 205W and ADG (P<0.001). Birth month and sex of the calf significantly (p<0.05) influenced CE, BW, 205W and ADG. The estimated heritablities of WW, BW, ADG and 205W were 0.26, 0.16, 0.31 and 0.25, respectively. Genetic correlation among weaning weight, birth weight, average daily gain and 205-day weight were positive but with calving ease was negative. Weaning weight had strong genetic correlation with average daily gain (r=0.98). Calving ease also had negative genetic correlation with 205-day weight (r=-0.02). The phenotypic correlation of average daily gain and 205-day weight was strong (0.79).
Key words: genetic correlation, phenotypic correlation, programmes and assessment
Estimating genetic parameters for various livestock traits is a main topic of animal breeding. Advances in statistical animal breeding have broadening its range of application and traits of interest provide great opportunities for animal agriculture (Sang 2003). Genetic parameter estimates are needed for implementation of breeding programs and assessment of progress of ongoing programs where accuracy in their estimation is of paramount importance (Wasike et al 2006). The genetic and phenotypic parameters in the field of quantitative genetics include heritability, genetic and phenotypic correlation and repeatability, which play vital role in formation of any suitable breeding plan for genetic improvement program (Aynalem 2006).
Biological variation is an important aspect of genetic progress since the aim of selective breeding is reliable identification of animals with superior genes to form parents of the next generation (Falconer and Mackay 1996). Classically, variance components were partitioned into genetic and environmental components.This has resulted in genetic and environmental variance.These components and their interactions are important in estimation of animal breeding values for each trait for selection purposes (Falconer and Mackay 1996). Effective breeding programmes depend on the accuracy of genetic and phenotypic parameter estimates, which include heritability, repeatability and correlation between traits (Burrow 2001).
In Hungary pork and poultry production far exceed beef production. Pig production is most important with a share of 16 % of total agricultural output, followed by poultry Production (10 %) and milk production also with 10 %. There is nearly no specialized beef production in Hungary, beef is a by-product of milk production and follows the herd size of dairy cows. Beef and veal meat production has declined by 68 % in the last decade (1992 to 2000), while cattle stocks declined by 40 % (European Commission; Directorate-General for Economic and Financial Affairs 2002).
The Hungarian Simmental Breed has a dual purpose. Association of Hungarian Simmental Breeders, which is responsible for improvement of the breed, was ambitious in this intention by involving beef traits (frame, muscularity, body conformation, udder conformation) in type classification as the first step (1992), then by initiating the setting up of central self-performance testing of sire candidates (from 1994), which is a help in choosing the bulls with best weight gain traits for artificial insemination. It is obvious that phenotypic data related to beef production give insufficient information on the progenies of sires, since estimation of slaughter traits is not possible (Füller 2010). Under this study one fitness trait and five growth traits were included. This study was conducted with the objectives to evaluate growth traits of Hungarian simmental cattle breed and estimate genetics parameter components which would be used in the national genetic evaluation of the breed and developing selection objectives.
A study was conducted in Hungary by taking data from Simmental cattle breed farm association. The Association of Breeders of Hungarian Simmental Cattle coordinated 1383 cattle farms in which the registered number of cattle were 27875 and 889 of these cattle farms kept 14877 milked (double utilized) cows while 494 cattle farms kept 12998 not milked ones (beef cattle). The organization of the breeding of the Hungarian Simmental cattle, their genetic development and international representation were managed by the Association of the Breeders of Hungarian Simmental Cattle; the number of members of which were 1462. The data used in this study was taken from 494 beef cattle farms (12998 beef cattle) simmental cattle breed association recording data base.
Data were provided by the Association of Hungarian Simmental Breed. The growth traits analysed included calving ease (CE score), birth weight (BW kg), weaning weight (WW kg), weaning age (WA day), 205-day weight (205W kg) and average daily gain (ADG g). The evaluation included the data of 6552 Cattle (1479 bulls and 5073 heifers) of growth traits. The pedigree sample size was 6552. Data on growth traits of Hungarian Simmental data were collected from 1999 to 2011. Pedigree information traits were also included for heritablities and correlations calculation.
Analyses of variance were conducted for Hungarian Simmental cattle growth traits in order to assess the environmental effects on beef performance using the Generalized Linear Model (GLM) of R software program. Preliminary analyses examined the relative proportions of variation that were accounted for by various fixed effects to establish the most suitable model to describe the data. The effects included in the model for the analysis of growth traits were sex (2 classes), birth year (13 classes), birth month (12 classes) and farm (8 classes). R software program was used for variance analysis and least square means (+s.e), PEST software program was used for data file and pedigree file coding, VCE6 software program was used for heritablities and correlations calculating. The parameter values were estimated with the animal model.
y= Xb + Zn + Wu + e
Where: y = vector of observation traits; b = vector of fixed effects; n = vector of random effects; u = vector of maternal permanent effect; e = vector of random residual effect; X = matrix of fixed effects; Z = matrix of random effects; W = matrix of maternal permanent effect. In the case of evaluation by an animal model the fixed effects were sex, farm, year and month. In case of weaning weight weaning age was fixed effect. Dam and animal were random effects.
The mean values of CE, BW, WW, WA, ADG and 205W were 1.41 score, 32.9 kg, 211 kg, 224 day, 1102 gm and 234 kg respectively. According to Bene et al (2010) finding, the overall mean WW of the Hungarian Simmental calves were 217 kg, the preweaning daily gain (PDG) 1.01kg/day, the 205-DW 242 kg and the WA 181 day. These values were higher than the current values except PDG and WA. Based on Bene et al (2010) finding, the maximum and minimum values of Hungarian Simmental cattle of WW, PDG, 205W and WA were 435kg, 1750g, 390kg, 301day and 100kg, 327g, 100kg and 80 day respectively. The Perisic et al (2009) finding BW,BW at 200 day, BW at 365 day and ADG of Sweden young simmental bulls were 48kg, 342kg, 610kg and 1348g respectively. According to Hailu Dadi et al (2003) finding on Growth Traits in a Multi-breed Beef Cattle Herd, the mean vale of birth weight, weaning weight and average daily gain were 35.8kg, 192kg and 0.75kg respectively. Hungarian simmental breed had lower values than Sweden young simmental bulls, but better values than the Multi-breed Beef Cattle Herd (Table 1).
|
Table 1. Over all results of Hungarian Simmental cattle growth traits |
|||||||
|
Traits |
N |
mean |
Sd |
CV(%) |
SE |
Max |
Min |
|
CE(score) |
6552 |
1.41 |
0.76 |
53.9 |
0.02 |
3 |
1 |
|
BW(kg) |
5856 |
32.9 |
4.75 |
14.5 |
0.1 |
64 |
20 |
|
WW(kg) |
6439 |
211 |
41.5 |
19.7 |
0.83 |
345 |
50 |
|
WA(day) |
6552 |
224 |
225 |
100 |
4.45 |
3061 |
12 |
|
205W(kg) |
6544 |
234 |
48 |
20.5 |
0.95 |
403 |
35 |
|
ADG(g) |
6552 |
1102 |
308 |
28 |
6,10 |
9167 |
36 |
|
CE, calving ease; BW, birth weight; WW, weaning weight; WA, weaning age; 205W, 205-day weight; |
|||||||
Sex significantly (P<0.001) influenced WW, WA, 205W and ADG. Birth year of the calf significantly (P<0.001) affected CE, BW, WW, WA, 205W, ADG and BW. Birth month of the calf significantlay (p<0.001) influenced CE, BW and WW. Birth month and sex of the calf significantlay (p<0.05) influenced CE, BW, 205W and ADG. Farm significantly (P<0.001) affected CE, BW, WA, 205W, ADG and WW (Table 2).
|
Table 2. Analysis of variance for factors affecting growth performance |
|||||
|
Traits |
sources of varation |
Df |
MS |
F values |
Pr(F) |
|
CE |
Year |
12 |
32.0 |
74.4 |
< .0001 |
|
Month |
11 |
4.61 |
8.23 |
0.0002 |
|
|
Sex |
1 |
101 |
187 |
0.0044 |
|
|
Farm |
7 |
55.3 |
129 |
< .0001 |
|
|
BW |
Year |
12 |
216 |
10.0 |
< .0001 |
|
Month |
11 |
713 |
37.2 |
< .0001 |
|
|
Sex |
1 |
313 |
13.9 |
0.0303 |
|
|
Farm |
7 |
411 |
411 |
< .0001 |
|
|
WW |
Year |
12 |
14298 |
8.59 |
< .0001 |
|
Month |
11 |
32817 |
20.7 |
< .0001 |
|
|
Sex |
1 |
136710 |
81.8 |
< .0001 |
|
|
Farm |
7 |
220924 |
199 |
< .0001 |
|
|
WA |
Year |
12 |
3765435 |
89 |
< .0001 |
|
Month |
11 |
115278 |
1.94 |
0.0002 |
|
|
Sex |
1 |
1378309 |
23.4 |
< .0001 |
|
|
Farm |
7 |
519361 |
8.87 |
< .0001 |
|
|
205W |
Year |
12 |
28180 |
12.6 |
< .0001 |
|
Month |
11 |
38379 |
17.5 |
0.0145 |
|
|
Sex |
1 |
735670 |
357 |
< .0001 |
|
|
Farm |
7 |
294545 |
190 |
< .0001 |
|
|
ADG |
Year |
12 |
1610189 |
18.3 |
< .0001 |
|
Month |
11 |
799971 |
8.69 |
0.0043 |
|
|
Sex |
1 |
20978366 |
241 |
< .0001 |
|
|
Farm |
7 |
4047632 |
48.1 |
< .0001 |
|
|
CE, calving ease; BW, birth weight; WW, weaning weight; WA, weaning age; 205W, 205-day weight; |
|||||
CE, BW, WW, WA, ADG and were significantly different across the birth years. In 2007, 2008 and 2009 calves were born ease with assistance. In the rest years calves were born ease requiring no assistance. The peak and weak performance of BW were in 2003 (34.8+0.72) and in 1999 (27+1) respectively. The good and bad performance of WW were in 1999 (242+2.50) and in 2010 (198+1.65) respectively. CE, BW, WW, WA, ADG and were significantly different across the birth months. The maximum and minimum of mean BW (37.9 kg) and (30.6 kg) were in January and in November respectively. Except June and February the rest months were good for calving ease which calves were born ease requiring no assistance.
There was a significant difference in BW between sexes in which male calves weighed heavier at birth than females. Weights between sexes were significantly different where male calves tended to weigh heavier at weaning than female calves but male had less WA than female. ADG and 205W of male is higher than female. Calving ease, birth weight, weaning weight, weaning age, 205-days weight and average daily gain were significantly different across the farms (Table 3).
|
Table 3. Least square means (±s.e.) of growth traits by birth year, birth month, sex and farm |
||||||
|
Effects |
Traits |
|||||
|
CE (score) |
BW (kg) |
WW (kg) |
WA (kg) |
205W (kg) |
ADG (g) |
|
|
Birth Years | ||||||
|
1999 |
1.50+0.50 |
27.0+1.00 |
242+2.50 |
195+16.0 |
268+29.5 |
1251+90.0 |
|
2000 |
1.00+0.00 |
30.4+0.20 |
200+5.12 |
191+6.02 |
218+4.80 |
1039+23.2 |
|
2001 |
1.00+0.00 |
29.9+0.68 |
218+3.83 |
1124+210 |
259+11.3 |
612+99.3 |
|
2002 |
1.03+0.03 |
31.5+0.50 |
217+5.00 |
786+112 |
244+6.37 |
787+62.8 |
|
2003 |
1.21+0.05 |
34.8+0.72 |
218+4.88 |
194+3.52 |
233+4.75 |
1129+21.1 |
|
2004 |
1.08+0.03 |
34.6+0.54 |
221+3.10 |
187+4.12 |
268 +4.48 |
1223+18.7 |
|
2005 |
1.03+0.01 |
31.6+0.33 |
219+2.46 |
283+21 |
236+3.29 |
1031+20.7 |
|
2006 |
1.18+0.04 |
31.9+0.31 |
214+2.48 |
208+3.39 |
229+3.34 |
1063+15.0 |
|
2007 |
1.82+0.07 |
33.6+0.29 |
217+2.59 |
203+3.28 |
234+3.51 |
1110+17.4 |
|
2008 |
1.69+0.05 |
33.6+0.22 |
202+2.49 |
190+2.03 |
226+2.61 |
1100+24.1 |
|
2009 |
2.18+0.06 |
31.7+0.21 |
212+2.55 |
184+2.23 |
244+3.05 |
1175+15.4 |
|
2010 |
1.23+0.02 |
32.3+0.23 |
198+1.65 |
185+2.07 |
221+1.62 |
1092+9.28 |
|
2011 |
1.13+0.02 |
33.6+0.25 |
218+2.03 |
190+1.38 |
234+1.99 |
1142+11.3 |
|
Birth Months |
||||||
|
January |
1.36+0.05 |
37.9+0.45 |
213+3.06 |
221+16.1 |
229+3.13 |
1076+17.9 |
|
February |
1.56+0.05 |
34+0.31 |
223+2.04 |
211+7.80 |
240+2.31 |
1133+12.8 |
|
March |
1.46+0.04 |
32.4+0.18 |
222+1.54 |
240+11.9 |
243+1.86 |
1131+12.1 |
|
April |
1.43+0.04 |
32.0+0.20 |
210+1.68 |
225+13.0 |
238+2.28 |
1110+13.0 |
|
May |
1.39+0.04 |
31.9+0.18 |
215+2.38 |
204+8.72 |
241+2.82 |
1147+13.5 |
|
June |
1.58+0.05 |
31.8+0.23 |
198+2.55 |
209+16.84 |
236+3.73 |
1133+37.7 |
|
July |
1.36+0.07 |
30.6+0.30 |
197+4.24 |
285+40.5 |
220+5.09 |
998+28.0 |
|
August |
1.13+0.04 |
34.9+0.51 |
216+4.36 |
265+28.0 |
224+3.78 |
1024+22.6 |
|
September |
1.14+0.05 |
36.7+0.61 |
191+4.48 |
190+17.5 |
227+4.12 |
1108+26.3 |
|
October |
1.26+0.11 |
31.1+0.52 |
181+8.25 |
189+9.36 |
199+6.94 |
979+33.7 |
|
November |
1.09+0.04 |
30.6+0.21 |
185+3.68 |
202+10.9 |
195.+3.73 |
953+17.6 |
|
December |
1.02+0.02 |
31.5+0.45 |
179+8.30 |
205+10.1 |
187+6.51 |
909+30.2 |
|
Sexs |
||||||
|
Male |
1.78+0.04 |
33.6+0.18 |
225+1.38 |
181+1.41 |
265+1.96 |
1270+9.49 |
|
Female |
1.30+0.02 |
32.7+0.11 |
207+0.97 |
236+6.21 |
225+1.01 |
1051+7.12 |
|
Farms |
||||||
|
467346 |
1.02+0.01 |
28.0+0.02 |
245+1.64 |
206+1.26 |
251+1.80 |
1199+7.37 |
|
480714 |
1.58+0.08 |
35.0+0.26 |
142+3.84 |
217+29.8 |
163+4.01 |
910+66.7 |
|
515225 |
1.18+0.02 |
39.5+0.24 |
212+1.80 |
192+0.88 |
231+1.57 |
1105+7.78 |
|
970325 |
2.03+0.07 |
33.1+0.32 |
192+2.02 |
177+2.10 |
226+2.22 |
1095+10.5 |
|
993449 |
1.06+0.01 |
30.9+0.12 |
184+2.42 |
200+3.60 |
198+2.29 |
952+12.0 |
|
1466726 |
1.88+0.04 |
33.2+0.11 |
216+0.95 |
236+12.2 |
61.9+1.68 |
1203+10.8 |
|
3040414 |
1.19+0.03 |
31.7+0.23 |
236+2.17 |
317+24.6 |
244+2.33 |
1065+21.9 |
|
4790723 |
1.00+ 0.00 |
30.1+0.05 |
193+2.70 |
214+3.80 |
197+2.71 |
937+14.0 |
|
CE, calving ease; BW, birth weight; WW, weaning weight; WA, weaning age; 205W, 205 days weight; |
||||||
The estimated heritablity values of BW, WW, ADG, CE and 205W were 0.15, 0.26, 0.31, 0.16 and 0.25 respectively.The weaning weight, average daily gain and 205-day weight values were lower than the results of Bene et al(2010), the direct heritability of weaning weight, pre-weaning daily weight and 205-day weight h2d = 0.40, 0.42 and 0.37 respectively, but higher than the results of Lengyel et al (2003) (h2 d = 0.10, 0.13 and 0.14 respectively). According to the Canadian Simmental Association (2014) finding, the heritability values of Canadian Simmental cattle breed birth weight, weaning weight and calving ease were 0.04, 0.23 and 0.18 respectively and higher value than this work.
The genetic correlation among weaning weight, birth weight, average daily gain and 205-day weight were positive but with calving ease was negative. Weaning weight had strong genetic correlation with average daily gain and 205-day weight. Calving ease also had negative genetic correlation with 205-day weight. Birth weight was geneticaly correlated with all other traits weakly. Average daily gain had strong genetic correlation with weaning weight and 205-day weight. The van Niekerk and Neser (2006) result showed on Limousine cattle, the genetic correlation between birth weight and weaning weight, birth weight and yearly weight, weaning weight and yearly weight were 0.42, 0.37 and 0.99 respectively. According to Neser1 et al (2012) finding on growth traits in Brangus cattle, the genetic correlation among birth weight and weaning weight, birth weight and yearly weight, and weaning weight versus yearly weight were 0.78, 0.75 and 0.86 respectively. The recent result had lower genetic correlation values than Limousine cattle and Brangus cattle values.
The phenotypic correlation of weaning weight and calving ease were negative but with average daily gain and 205-day weight were strong positive correlation. Calving ease also had negative genetic correlation with 205-day weight. Weaning weight had strong genetic correlation with average daily gain and 205-day weight. Birth weight was phenotypically correlated with all other traits weakly. Average daily gain had strong phenotypic correlation with weaning weight and 205-day weight. The van Niekerk and Neser (2006) result showed on Limousine cattle, the phenotypic correlation between birth weight and weaning weight, birth weight and yearly weight, weaning weight and yearly weight were 0.16, 0.14 and 0.52 respectively and had higher values than the current study values.
|
Table 4. Genetic parametrs (heritablities on diagonal, genetic correlations above diagonal, and phenotypic correlations bellow diagonal) |
|||||
|
Traits |
WW |
CE |
BW |
ADG |
205W |
|
WW (kg) |
0.26 |
-0.003 |
0.22 |
0.98 |
0.87 |
|
CE (score) |
-0.004 |
0.15 |
0.03 |
0.02 |
-0.02 |
|
BW (kg) |
0.08 |
0.08 |
0.16 |
0.18 |
0.24 |
|
ADG (g) |
0.97 |
0.007 |
0.07 |
0.31 |
0.79 |
|
205W (kg) |
0.88 |
-0.01 |
0.05 |
0.83 |
0.25 |
|
WW, weaning weight; CE, calving ease; BW, birth weight; ADG, average daily gain; 205W, 205 days weight. |
|||||
Genetic parameter estimates are needed for implementation of breeding programmes and assessment of progress of ongoing programmes. This study reveals that the overall mean values of Hungarian simmental cattle breed were lower than the previous studies. Hungarian simmental breed had lower values than Sweden young simmental bulls, but better values than the Multi-breed Beef Cattle Herd. All the heritability values were moderate (0.2<h2 <0.4) except birth weight which was low (h2<0.2). The genetic correlation between weaning weight and average daily gain (r=0.98) was very strong; the genetic correlation between weaning weight and 205-day weight (r=0.87) was strong; the genetic correlation between calving ease and birth weight (r=0.03) and birth weight and 205-day weight (r=0.24) were low. The phenotypic correlation between weaning weight and average daily gain (r=0.97) was very strong; the phenotypic correlation between weaning weight and 205-day weight (r=0.88) and average daily gain and 205-day weight (r=0.83) were strong; the phenotypic correlation between calving ease and birth weight (=0.08) was low. So, this study would be used in the national genetic evaluation of the breed and developing selection objectives.
Aynalem H 2006 Genetic and economic analysis of Ethiopian Boran cattle and their crosses with holstien Friesian in centeral Ethiopia. PhD. dissertation submitted to national dairy esearch institute, Karnal (Deemed University), India.
Burrow H M 2001 Variances and covariances between productive and adaptive traits and temperament in a composite breed of tropical beef cattle. Livestock Production Science. 70: 213- 233.
European Commission; Directorate-General for Economic and Financial Affairs 2002 The European Commission forecast for the candidate countries. Spring 2002.
Falconer D S and Mackay F C 1996 Introduction to Quantitative Genetics. 4th/Ed. Longman group, England.
Fűller I 2010 Development of selection for beef production. traits in Hungarian Simmental cattle breed. Ph.D. Dissertation Thesis. University Of Kaposvár. Faculty of Animal Science. Department of Large Animal Breeding and Production.phd.ke.hu/fajlok/1275040173-thesis_talan.pdf
Hailu Dadi, Schoeman S J and Jordaan G F 2003 Multitrait Estimates of (Co) Variance Components and Genetic Parameters of Preweaning Growth Traits in a Multibreed Beef Cattle Herd. Eth. J. Anim. Prod. 3(1) - 2003: 13-24.
Lengyel Z, Komlosi I, Balika S, Major T, Erdei I and Szabo F 2003 Reproduction and weaning results of Hungarian Limousin populations. Sire model. Hung. J. Anim. Prod. 52, 25-38 [in Hungarian].
Neser F W C, van Wyk J B, Fair M D, Lubout P and Crook B J 2012 Estimation of genetic parameters for growth traits in Brangus cattle. S. Afr. j. anim. sci. vol.42 n.5 Pretoria Jan. 2012
Perišić P, Skalicki Z, Petrović M M, Bogdanović V and Ružić Muslić D 2009 Simmental Cattle Breed in Different Production System. Institute for Animal Husbandry, Belgrade-Zemun, Biotechnology in Animal Husbandry 25 (5-6), p 315-326.
Sang Hyon O H 2003 Estimation of genetic parameters for Boar semen traits. PhD. Dissertation submitted to the Faculty of North Carolina State University, Department of Animal Science. Raleigh.
Szabolcs Bene, Füller Imre, Attila Fordos and Ferenc Szabo 2010 Weaning results of beef Hungarian Fleckvieh calves. Genetic parameters, breeding values. Archiv Tierzucht 53: 1, 26-36, ISSN 0003-9438.
Van Niekerk M and Neser F W C 2006 Genetic parameters for growth traits in South African Limousin cattle. South African Journal of Animal Science 2006, 36 (Issue 5, Supplement 1).
Wasike C B, Ilatsia E D, Ojango J M K and Kahi A K 2006 Genetic parameters for weaning weight of Kenyan Boran cattle accounting for direct-maternal genetic covariances. South African Journal of Animal Science 2006, 36 (4).
Received 15 March 2015; Accepted 15 July 2015; Published 1 September 2015