The production records on 680 Gir cows with 1257 lactations sired by 52 bulls, maintained at Cattle Breeding Farm, Junagadh Agricultural University, Junagadh, Gujarat, India, for 24 years (1987 ' 2010) were studied. The data were analyzed to for genetic correlation of standard lactation milk yield (SLMY) with different traits viz., lactation milk yield (LMY), peak milk yield (PMY), lactation length (LL), dry period (DP), calving interval (CI) and age at first calving (AFC). The analysis revealed highly significant (P<0.01) genetic correlation between SLMY and lactation milk yield, lactation length and peak milk yield were 0. 985 ?? 0. 015, 0. 744??0.209 and 0. 868 ?? 0.066 respectively. While non-significant (P>0.05) genetic correlations between SLMY and dry period, age at first calving and calving interval was -0.472 ?? 0.217, 0.006 ?? 0.178 and - 0.100 ?? 0.269.
Genetic correlation is the proportion of variance by which two traits share genetic causes. Traits with zero heritability, the observable differences in a trait between in a population that is due to genetic differences, the genetic correlation of traits is not depended with their heritability: i.e., two traits can have a very low genetic correlation even when the heritability of each is high and vice versa. The genetic correlation give idea about how much of the genetic influence on two traits is common to both: if it is more than zero, this suggests that the two traits are governed by common genes. This can be an important part on conceptualizations of the two traits: traits which seem different phenotypically but which share a same genetic basis require to be describe in detail for how these genes can govern both traits.
High production efficiency in livestock production is an economically desirable attribute that targets ultimately for genetic up gradation. In fact, the economy of dairy industry mainly rely upon the performance parameters of dairy animals, therefore, it becomes more relevant to tackle out the means for ameliorating the performance efficiencies by developing certain guidelines for selection. Indeed, the knowledge of genetic variability with respect to each trait and co-variability existing among different traits are a beacon light for planning appropriate selection and breeding strategies for the genetic improvement of dairy animals.
Genetic correlations have great importance in selection when changes in one trait are induced through selection on other trait in which a genetic correlation exists. Main goal of breeding-selection work is to create new generations which would exceed in their production results than the previous generation and demonstrate greater production effects in milk production. For all this the knowledge of the genetic correlations of major traits and degree of heritability to progeny is require. The present study is focusing on correlations among several milk traits and reproductive indices, with the aim of identifying relevant correlations that can be used in the selection process.
Materials and Methods:
In order to achieve the objective, the data pertinent to production traits on 680 Gir cows with 1257 lactations, calving from 1987 to 2010, progeny of 52 sires maintained at Cattle Breeding Farm, Junagadh were considered.
The duration of 24 years was divided into 6 periods of four years each. The three seasons were delineated as winter (November-February), summer (March-June) and monsoon (July-October) on the basis of geo-climatic conditions prevailing in the region. The Parity was considered up to 12th lactation. Records of cows with some specific or non-specific diseases, reproductive disorder and physical injury were excluded from the present investigation.
The mixed model was used for estimation of genetic correlation of standard lactation milk yield with other traits.
Mixed model used is as follow:
Yijkmn = ?? + Pi + Cj + Lk + Sm + eijkmn
Yijklmn - Performance trait of individual animal (n), calved in (i)th period, and (j)th season, of the (k)th parity, born to (m)th sire
?? - overall population mean
Pi - fixed effect of period of calving ( i = 1 to 6)
Cj - fixed effect of season of calving ( j = 1 to 3)
Lk - fixed effect of parity ( k = 1 to 12)
Sm - random effect of sire ( m = 1 to 52)
eijkmn - random error with mean zero and variance ??2E
The least-squares and maximum likelihood computer program of Harvey (1990) was used to estimate genetic correlation of standard lactation milk yield with other traits. Duncan's multiple range test as modified by Kramer (1957) was employed for making all possible pair wise comparison.
The estimates of genetic correlations between SLMY and lactation milk yield (0.985 ?? 0.015), lactation length (0.744 ?? 0.209) and peak milk yield (0.868 ?? 0.066) were found to be positive and highly significant (P<0.01) in present study. While genetic correlations between SLMY and age at first calving (0.006 ?? 0.178), calving interval (-0.100 ?? 0.269) and dry period (-0.472 ?? 0.217) were found in present study (Figure).
Standard lactation milk yield and lactation milk yield
Bhatia (1980) studied 816 records, the progeny of 77 sires in seven different herds of Sahiwal cows and found genetic correlation of Standard lactation milk yield and lactation milk yield was 0.96. Hussain (1988) and Gandhi and Gurnani (1988) found genetic correlation between these two traits under study as 0.73 and 0.81 in Indian and Pakistani Sahiwal, respectively.
However, Javed et al. (2004) found genetic correlations between Standard lactation milk yield and lactation milk yield was 0. 01 ?? 0.77, it was very much contrary with present study data.
Figure: Genetic correlation (GC) and standard error (SE) of various traits
comparison with standard lactation milk yield
Standard lactation milk yield and lactation length
Javed et al. (2004) reported genetic correlations between Standard lactation milk yield and lactation length were 0.48 ?? 0.38. Tomar and Singh (1981) reported the genetic correlation between the two traits as 0.16 in Sahiwal cattle, which was lower than that reported in present study. However, Khan (1987) found genetic correlation 0.78 between these two traits in Holstein Friesian cows in Pakistan as similar to present study.
Ahmad et al. (2001) use bivariate model and estimates of genetic correlation found 0.91 between these traits under study in Sahiwal cattle and their crossbreds with Jersey and Friesian. The same authors use multivariate analysis for same data set, and reported that the genetic correlation between these two traits increases up to 0.98. These differences in estimates may be due to method of estimation or number of lactation or data set.
The genetic correlation found in present study (0.744 ?? 0.209) indicates the plieotropic effect of the genes between these two traits. It also gives idea that lactation length would be increased as a correlated response when selection doing for standard lactation milk yield. However, more than 10 month lactation length would not be economical.
Standard lactation milk yield and peak milk yield
Sengar et al. (1987) in Tharparkar cattle (0.434 ?? 0.129) reported highly significant genetic correlation between SLMY and peak milk yield, which was similar to the present finding. Ulmek (1990) also reported genetic correlation between SLMY and peak milk yield was greater than one in Gir cows.
This positive correlation between these two traits was indicating selection for trait under study will give positive increase in peak milk yield.
Standard lactation milk yield and dry period
The genetic correlations between Standard lactation milk yield and dry period obtained by Javed et al. 2004 was 0.49 ?? 0.46. The estimate of genetic correlation obtained in study of Javed et al. (2004) is not in line with present findings and also contrary findings reported by Katoch and Yadav (1990), who found 0.75 ?? 0.67 genetic correlations between these two traits in Jersey cattle.
This difference may be found due to different breed, number of lactation or different data set. The results of present findings indicated that the selection for higher standard milk yield would not affect dry period as a correlated response, which is advantageous.
Standard lactation milk yield and age at first calving
The genetic correlations between Standard lactation milk yield and age at first calving was 0.61 ?? 0.30 reported by Javed et al. (2004), Which was positive and high than that found in present study. The result of present study was also contrary with finding (0.77) as reported by Bhatnagar et al. (1983) in Indian Sahiwals. Study of Ahmad et al. (2001) also found 0.63 as high genetic correlation between the same traits as of present investigation after analysing a combined data set on Pakistani Sahiwal and their crosses with Jersey and Friesian cattle.However, Khan et al. (1999) studied data of Sahiwal cattle and reported a negative genetic correlation -0.12 ?? 0.14 between these two traits.
Non significant genetic correlations between standard lactation milk yield and age at first calving found in present study indicated that the two traits are not under influence of the same genes and selection for high standard lactation milk yield will not affect the age of first calving.
Standard lactation milk yield and calving interval
Sharma et al. (1982) found negative genetic correlation in Sahiwal cattle between these two traits. Ahmad et al. (2001) also found a negative genetic correlation -0.56 with higher standard error after analysing a data set of Sahiwal cattle and their crossbreds in Pakistan. However, Javed et al. (2004) found genetic correlation between Standard lactation milk yield and calving interval was 0.46 ?? 0.46 in Sahiwal cattle. It gives idea that the two traits were under study having the influence of the same genes. In other words, selection for improvement in SLMY will cause prolonged calving intervals which is not advantageous for economical milk production. Khan et al. (1999) and Van Vleck (1989) and Mantysaari also found similar positive and highly significant correlation between these two traits in Sahiwal breed of cattle.
The genetic correlations are strongly governed by gene frequencies; these differences may be give ideas about the genetic makeup of different populations.
The genetic correlations between Standard lactation milk yield and production or reproduction traits were have higher importance when talking about lactation milk yield, peak milk yield and lactation length, suggesting that all these traits were govern by similar genes. A non-significant genetic correlation between Standard lactation milk yield and age at first calving gives idea that selection for higher Standard lactation milk yield will not increases the age at first calving which is economically advantageous. Similarly, selection for Standard lactation milk yield will also in negatively correlation with the dry period and calving intervals in Gir cattle, it will be desirable correlated response which is advantageous economically as per dairy production control.
Ahmad. M., J. H. J. van der Werf and K. Javed, 2001. Genetic and phenotypic correlations for some economic traits in dairy cattle. Pakistan Vet. J., 21(2): 81-86.
Bhatia, S. S., 1980. Note on the selection for lifetime milk production in Sahiwal cattle. Indian J. Anim. Sci., 50: 450-453.
Bhatnagar, D. S., V. K. Taneja, S. B. Basu and K. M. K. Murthy, 1983. Genetic parameters of some economic traits in Sahiwal cattle. Indian J. Dairy Sci., 36: 402-406.
Gandhi, R. S. and M. Gurnani, 1988. Association amongst different productive and reproductive traits in Sahiwal cattle. Asian J. Dairy Res., 7: 171-174.
Hussain, S. M., 1988. Studies on Sahiwal cattle in Pakistan: II. Genetic and phenotypic parameters of some lifetime production functions. MSc. Thesis, Univ. Agri., Faisalabad, Pakistan.
Harvey, W. R. (1990). Users' Guide for LSMLMW and MIXMDL, Mixed model least squares and maximum likelihood computer program. PC-2 version, the Ohio State University, Columbus, USA.
Javed, K., M. Abdullah M. Akhtar and M. Afzal, 2004. Phenotypic and genetic correlations between first Lactation milk yield and some performance traits in Sahiwal cattle. Pakistan Vet. J., 24 (1): 9-12.
Katoch, S. and M. C. Yadav, 1990. Genetic parameters of milk yield in Jersey cows. Indian Vet. J., 67: 711-714.
Khan, A. U., 1987. Genetic and phenotypic parameters of some performance traits of Holstein Friesian cattle kept under sub-tropical conditions of the North West Frontier Province of Pakistan. M.Sc. Thesis, Univ. Agri., Faisalabad, Pakistan.
Khan, U. N., A. Dahlin, A. H. Zafar, M. Saleem, M. A. Chaudhry and J. Philipsson, 1999. Sahiwal cattle in Pakistan: Genetic and environmental causes of variation in body weight and reproduction and their relationship to milk production. Anim. Sci., 68: 97- 108.
Kramer, C. Y. (1957). Extension of multiple range tests to group correlated adjust means. Biometrics 13: 13.
Mantysaari, E. and L. D. Van Vleck, 1989. Estimation of genetic parameters for production and reproduction in Finish Ayrshire cattle. J. Dairy Sci., 72: 2375-2386.
Sengar, M.S., Tomar, N.S. and Arora, V.K. (1987). Genetic and phenotypic studies of some economic traits of Tharparkar cows. Indian vet. J.,64: 146-49.
Sharma, P. P., N. S. Tomar and V. K. Arora, 1982. Genetic and phenotypic performances of Sahiwal and Holstein Friesian x Sahiwal crossbred cows. Vet. Res. J., 5: 53-58.
Tomar, N. S. and B. P. Singh, 1981. Genetic trends of some economic traits in Hariana cows. Indian Vet J., 58: 701-709.
Ulmek, B.R. 1990. Genetic studies of production traits in Gir Cattle. Ph.D. Thesis, Gujarat Agril. Univ., Sardar Krushinagar.
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