Heritability estimates and genetic correlations of various production and reproductive traits of different grades of dairy cattle reared under subtropical condition
Funding information
This study was self-funded by the authors.
Abstract
Inheritance of economic traits and their genetic correlation was studied in different breeds and their various grades (crossbred’s cattle) under the subtropical condition. Data on principal parameters comprising 10 years, that is 2004–2014, were utilized for the present study. Different grades of dairy cows comprising Holstein Friesian (HF), Sahiwal x Friesian (SxHF), Jersey (J), Jersey x Achai (JxAC) and Achai (AC) were included in the study. Heritability estimates and genetic correlations of some important productive and reproductive traits were worked out. Heritability estimates of certain economic traits were found to be: birthweight, 0.32 ± 0.181; age at maturity, 0.11 ± 0.136; age at first calving, 0.19 ± 0.162; days open, 0.09 ± 0.121; calving interval, 0.14 ± 0.211; dry period, 0.11 ± 0.124; lactation length, 0.04 ± 0.212 and lactation yield, 0.46 ± 0.206. Genetic correlation showed that body weight was significantly and positively correlated with lactation length (0.30) and lactation yield (0.81), while negatively correlated with age at maturity, age at first calving, days open, calving interval and dry period (−0.09, −0.07, −0.16, −0.34 and −0.002, respectively). Calving interval was positively and significantly correlated with the dry period (0.56), lactation length (0.72) and lactation yield (0.37). Moderate to higher heritability estimates with adequate genetic variance was found for body weight and lactation yield. The moderate to higher heritability estimates of birthweight in the present study revealed that this important trait might be considered in selection criteria.
1 INTRODUCTION
The productive and reproductive performance traits of dairy cattle are affected by numerous genetic and environmental factors. The exploitation of the genetic variations is necessary for the development of any breed (Birhanu Mohammed, Kebede, & Tadesse, 2015). Pakistan has a large number of cattle population, well adapted to the local conditions and some of them are best tropical cattle breeds. However, out of this large population, only 10 per cent are recognized breeds and the rest are classified as non-descript (Khan, Rehman, Muqarrab, & Ahmad, 2008). The indigenous breeds of Pakistan are relatively low producing but have higher disease resistance ability than exotic breeds. In order to improve the low productivity of native cattle, the national breeding policy has given the emphasis on the upgradation of local cattle through selection and crossing with high producing exotic breeds. Therefore, the government of Pakistan has imported exotic breeds such as Holstein Friesian, and Jersey, in order to improve the production potential of local cattle. (Suhail et al., 2010). Reproductive efficiency is a critical factor in improving the profitability of dairy farms by increasing milk yield and reducing the cost of the herd. To meet the increasing demand for milk and meat, the conservation and improvement of local cattle germplasm are essential for the profitability of a dairy enterprise. Effective managemental practices, disease control and optimum nutrition are critical for the development of the genetic potential of an animal. Climatic stresses such as high humidity, high ambient temperature and inadequate or uneven rainfall negatively affect the productivity of dairy cows in tropical conditions. (Canaza-Cayo, Lopes, Cobuci, Martins, & Silva, 2018; Toghiani, 2012).
Heritability and genetic correlations are the two important parameters necessary for planning an efficient breeding programme. The heritability explains the difference among individuals associated with genetic variance. Sufficient knowledge of genetic parameters is necessary to determine that selection, effective management or both can improve a particular trait (Cavani et al., 2015). Genetic selection of some important traits has helped to transform and promote the development of the dairy industry. With the help of advanced technology and trait recording procedure, some important traits in dairy cattle population consider for selection have evolved over time in response to needs of producer, consumers and society (Miglior et al., 2017). Genetic correlation shows the relationship between two traits or traits of breeding values (Choudhary et al., 2003; Roman, Wilcox, & Martin, 2000). Estimation of heritability is the key tool for the purpose of genetic improvement among individuals and herds. It is important to know the contribution of additive genes under different climatic conditions regarding performance traits. Thus, the present study was initiated to evaluate the heritability of some production and reproductive traits and their correlation in different grades of dairy cows reared under the subtropical condition of Pakistan.
2 MATERIALS AND METHODS
2.1 Source of data
Inheritance of economic traits was studied in different grades of dairy cattle at Cattle Breeding and Dairy Farm Harichand. A total of 224 dairy cows comprising 66 of Holstein Friesian (HF), 38 Sahiwal x Friesian (SxHF), 39 Jersey (J), 19 Jersey x Achai (JxAC) and 62 Achai (AC) cows of total 45 sire were used in the experimental trials. Data on the genetics of some reproductive traits comprising 10 years, that is 2004–2014, were utilized for the present study.
2.2 Data collection
Following data was collected from available records at the farm, to study the inheritance and genetic correlations of different economics traits of different grades of dairy cattle.
Animal identity, date of birth, birthweight, date of services, date of calving, date dried off, lactation yield and days in milk.
The following parameters were extracted from available records at the farm.
Age at maturity (AAM), age at first calving (AFC), calving interval (CI), days open (DO), dry period (DP), lactation length (LL) and lactation yield (LY).
2.3 Statistical analysis

2.4 Estimation of genetic transmission (h2)

The following analysis of variance table was used to calculate between and within sire mean squares.
Source of variation | df | Sum of square (SS) | Mean square (MS) |
---|---|---|---|
Correction term (C.T) | 1 |
![]() |
– |
Between sires | S-1 |
![]() |
![]() |
Progeny within sires | -S |
![]() |
![]() |
where, S: total number of sires; ni: number of observation for i-th sire; n: total number of observation.




(Swinger, Harvey, & Gregory, 1964).
where: S = number of sire; t = the intra class correlation equal to: Vars/Vars + Varw.

2.5 Genetic correlations

2.6 Ethics statement
The collection of this data was taken from dairy cattle at breeding and dairy farm Harichand from Khyber Pakhtunkhwa Province Pakistan. This retrospective study was reviewed and approved by the institutional animal care and use committee of The University of Agriculture Peshawar, department of livestock management breeding & genetics and was performed in accordance with the relevant guidelines and regulations.
3 RESULTS AND DISCUSSION
3.1 Descriptive statistics
In this study, the mean and standard errors along with the coefficient of variation are reported for certain traits of economic importance as shown in Table 1 and 2. The overall average birthweight recorded for different breeds was 25.36 ± 6.52 kg with a coefficient of variation of 1.62%. Jersey x Achai cows attained the maturity at the earliest age of 675.52 ± 79.89 days, while Holstein Friesian attained at latest age of 745.80 ± 110.12 days. The overall means for age at maturity in different breeds recorded was 713.75 ± 90.27 days with a coefficient of variation of 10.75%. The overall age at first calving of different breeds was found to be 1006.80.18 ± 96.50 days with a coefficient of variation of 8.05%. The highest days open was reported for Holstein Friesian (228.12 ± 84.28 days) while the shortest for Jersey x Achai (158.39 ± 95 days) cows. The overall means for days open in different breeds were recorded to be 187.81 ± 90.57 with a coefficient of variation of 42.08%. The overall means of calving interval of different breeds recorded were 498.29 ± 78.83 days with a coefficient of variation of 12.11%. Longer calving interval results in poor economic efficiency of lactating cows. The overall mean dry period in different breeds was recorded 176.85 ± 88.71 days with a coefficient of variation of 41.76%. The overall mean lactation length of 271.16 ± 44.24 days recorded for different breeds with a coefficient of variation of 12.58%. The highest lactation length of 290.48 ± 40.63 days was reported for Jersey, while the shorter lactation length of 233.49 ± 44.67 days for Achai cows. The overall mean lactation milk yield for different breeds was recorded 1535.71 ± 866.78 litres with a coefficient of variation of 17.92%.
Breeds | Traits | |||||||
---|---|---|---|---|---|---|---|---|
Birthweight (kg) | Age at maturity (days) | Age at first calving (days) | Days open (days) | |||||
Mean ± SE | %CV | Mean ± SE | %CV | Mean ± SE | %CV | Mean ± SE | %CV | |
Holstein Friesian (HF) | 31.38 ± 5.52 | 9.35 | 745.80 ± 110.12 | 12.51 | 1037.73 ± 109.02 | 9.87 | 228.12 ± 84.28 | 37.29 |
Sahiwal x Friesian(SxHF) | 30.94 ± 5.60 | 10.26 | 711.81 ± 97.63 | 13.56 | 1004.68 ± 99.28 | 9.15 | 165.98 ± 87.05 | 38.02 |
Jersey (J) | 23.69 ± 5.64 | 5.14 | 720.18 ± 92.32 | 10.87 | 1029.53 ± 89.31 | 7.97 | 202.77 ± 75.95 | 37.76 |
Jersey x Achai (JxAC) | 22.75 ± 5.85 | 3.92 | 675.52 ± 79.89 | 4.88 | 967.26 ± 86.89 | 4.09 | 158.39 ± 95.88 | 50.57 |
Achai (AC) | 18.08 ± 2.83 | 0.023 | 715.47 ± 56.41 | 0.066 | 994.79 ± 84.59 | 0.04 | 183.80 ± 99.89 | 62.57 |
Overall | 25.36 ± 6.52 | 12.48 | 713.75 ± 90.27 | 10.75 | 1006.80 ± 96.50 | 8.05 | 187.81 ± 90.57 | 42.08 |
Breeds | Traits | |||||||
---|---|---|---|---|---|---|---|---|
Calving interval (days) | Dry period (days) | Lactation length (days) | Lactation yield (litres) | |||||
Mean ± SE | %CV | Mean ± SE | %CV | Mean ± SE | %CV | Mean ± SE | %CV | |
Holstein Friesian (HF) | 527.81 ± 73.61 | 12.07 | 211.97 ± 90.73 | 43.85 | 285.85 ± 31.75 | 10.09 | 2678.63 ± 767.95 | 15.18 |
Sahiwal x Friesian (SxHF) | 530.19 ± 54.19 | 9.67 | 150.76 ± 79.52 | 37.59 | 271.77 ± 36.13 | 12.96 | 1682.37 ± 579.31 | 14.15 |
Jersey (J) | 514.52 ± 60.83 | 12.18 | 172.16 ± 73.08 | 45.71 | 290.48 ± 40.63 | 13.76 | 1612.89 ± 689.84 | 21.44 |
Jersey x Achai (JxAC) | 459.54 ± 60.42 | 6.77 | 135.73 ± 81.59 | 38.36 | 274.24 ± 37.69 | 12.67 | 1110.29 ± 561.66 | 9.45 |
Achai (AC) | 459.26 ± 87.49 | 20.17 | 203.66 ± 94.47 | 42.25 | 233.49 ± 44.67 | 17.46 | 594.39 ± 94.40 | 16.15 |
Overall | 498.29 ± 78.83 | 12.11 | 174.85 ± 88.71 | 41.76 | 271.16 ± 44.24 | 12.58 | 1535.71 ± 866.78 | 17.92 |
3.1.1 Estimates of heritability
Heritability estimates for various productive and reproductive performance traits are presented in Table 3. Heritability is considered an important concept in the field of animal breeding as it is used for planning breeding programmes, estimating breeding values, determining management strategies and for prediction of response for selection.
Traits | σ2a | σ2e | σ2p | h2 (±|SE|) | |e2 (±SE)| |
---|---|---|---|---|---|
Birthweight (kg) | 3.41 | 7.20 | 10.56 | 0.32 ± 0.181 | 0.68 ± 0.181 |
Age at maturity (days) | 152.22 | 1231.34 | 1383.86 | 0.11 ± 0.213 | 0.89 ± 0.213 |
Age at first calving (days) | 277.52 | 1044.02 | 1321.54 | 0.21 ± 0.162 | 0.79 ± 0.162 |
Days open (days) | 64.06 | 647.86 | 711.82 | 0.09 ± 0.121 | 0.91 ± 0.121 |
Calving interval (days) | 108.35 | 665.57 | 773.92 | 0.14 ± 0.211 | 0.86 ± 0.211 |
Dry period (days) | 109.16 | 883.35 | 992.53 | 0.11 ± 0.124 | 0.89 ± 0.124 |
Lactation length (days) | 2.07 | 49.62 | 51.69 | 0.04 ± 0.212 | 0.96 ± 0.212 |
Lactation milk yield (litres) | 120609.88 | 141582.52 | 262195.40 | 0.46 ± 0.206 | 0.54 ± 0.206 |
- Abbreviations: e2, heritability for environmental effect and residue; h2, heritability; SE, standard error; σ2a, additive genetic variance; σ2e, residual genetic variance; σ2p, phenotypic genetic variance.
3.2 Birthweight
Heritability estimates of birthweight in different breeds of dairy cattle were reported to be 0.32 ± 0.181. Shabana, Suhail, and Siddiqui (2002) reported relatively higher heritability estimates (0.46 ± 0.35) of birthweight in crossbred cows than the present findings. Olson, Cassell, McAllister, and Washburn (2009) reported significantly higher heritability with slightly lower standard error (0.49 ± 0.14) in Holstein, jersey and reciprocal crosses. The difference in heritability estimates of various research studies and their standard errors may be due to the changes in recording procedure, the correction for different non-genetic parameters and the methodology or model used for the estimate of heritability for the traits (Abou-Bakr, 2009). In addition to this herd size, feeding management of the different farm and climatic condition of the country may also be the cause of such variation (Hamrouni, Djemali, & Bedhiaf, 2014). The moderate to higher heritability estimates of birthweight in the present study revealed that this important trait might be considered in selection criteria.
3.3 Age at maturity
Heritability estimates of age at maturity in different breeds were recorded to be 0.115 ± 0.213. The present findings are relatively smaller than the findings of Abid, Syed, and Amjad (1995) who recorded heritability estimates of 0.19 ± 0.24 of age at maturity in Holstein Friesian cows. Although heritability estimate of the reproductive trait age at maturity is moderately susceptible to managemental practices, selection, efficient feeding and proper management would be helpful to attain early maturity. The age at maturity of different research workers are different, these can be attributed to the difference in feeding, and management practices applied at the farm. The selection of genetically superior breed and efficient management can decrease the puberty age and improve the reproductive efficiency of cows (Nogueira, 2004).
3.4 Age at first calving
Heritability estimates of 0.219 ± 0.162 were recorded for age at first calving in different breeds (Table 3). The present findings are in line with the findings of Solemani-Baghshah, Ansari-Mahyari, Edriss, and Nanaei (2014) and Faraji- Arough, Aslaminejad, and Farhangfar (2011) who reported heritability estimates of 0.19 ± 0.007 and 0.19 ± 0.005 in Isfahan and Iranian Holstein cows. Rehman, Khan, Bhatti, and Iqbal (2008) estimated the lower heritability (0.02 ± 0.019) for Sahiwal cows in Pakistan. Gaikwad-inamdar and Narayankhedkar (2000) reported the higher heritability for age at first calving (0.39 ± 0.28) than the present findings for crossbred cows (Gir × Holstein Friesian and Gir × jersey) in India. Several researchers reported that efficient management especially proper feeding determines pre-pubertal growth rate and higher reproductive performance. Through proper management and efficient feeding, cows grow faster, attain early maturity and served on time that in turn results in more output in term of higher milk yield and cows born during the lifetime.
3.5 Days open
Heritability estimates of days open were recorded 0.09 ± 0.121 in different breeds of dairy cattle. Solemani-Baghshah et al. (2014) reported lower heritability estimates of days open to be 0.041 ± 0.004 than the present findings for Isfahan Holstein cows. Similarly, Rehman et al. (2008) also reported lower heritability estimate of 0.04 ± 0.020 for Sahiwal cattle in Pakistan. Days open is an excellent indicator of the reproductive performance of the herd. Longer days open adversely affecting calving interval and ultimately reproductive performance of the cows, as the length of days open increase marked increase in calving interval reported. Increase in days open also affects lactation milk yield and therefore the productive performance of the animals is decreasing. This increase in days open may be due to lack of proper heat detection, semen quality and skills of inseminators. Nonetheless, this could be improving through efficient management, proper heat detection and timely insemination.
3.6 Calving interval
Heritability estimates of calving interval in different breeds were recorded 0.14 ± 0.211. Solemani-Baghshah et al. (2014) and Faraji- Arough et al. (2011) reported heritability estimates of 0.019 ± 0.007 and 0.19 ± 0.005 for Isfahan and Iranian Holstein Friesian cows, respectively. Rehman et al. (2008) reported lower heritability estimates (0.02 ± 0.019) for Sahiwal cows in Pakistan. Gaikwad-inamdar and Narayankhedkar (2000) reported higher heritability estimates (0.39 ± 0.28) for crossbreed (Gir × Holstein Friesian and Gir × Jersey) cows in India. Calving interval is a crucial trait of determining the reproductive efficiency of the herd. The difference in calving intervals of different breeds might be due to change in climatic condition, genetics, lack of proper oestrous detection and silent heat. Other contributory factors for a longer calving interval might be due to improper management activity and longer days open. Calving interval could be significantly decreased by shortening days open through efficient management of the herd.
3.7 Dry period
Heritability estimates of the dry period were 0.11 ± 0.124 in different breeds of dairy cows. Suhail et al. (2010) reported heritability estimates of 0.10 ± 0.21 for Jersey cows, which are in close agreement with the findings of the present study. Rehman et al. (2008) investigated Sahiwal cows and reported estimates of heritability of 0.05 ± 0.02 of the dry period, which is slightly lower than the present findings. The dry period is a function of days open. Animals having longer days open would have a longer dry period and animals having shorter days open would have shorter dry period. Proper nutrition and breeding of the animals would help in shortening the length of post-partum services and an ultimate decrease in lactation length would occur.
3.8 Lactation length
Heritability estimates of lactation length for different breeds were recorded 0.04 ± 0.212. Ibrahim Eid, Elsheikh, Ibrahim, & Yousif (2012) reported the shorter heritability estimate of 0.003 ± 0.078 for lactation length than the present findings by paternal half sib’s method for Holstein Friesian cows. The present findings are more or less similar to the findings of Rehman et al. (2008) who recorded a heritability estimate of 0.09 ± 0.03 for Sahiwal cows in Pakistan.
3.9 Lactation milk yield
Heritability estimates of Lactation milk yield were 0.46 ± 0.206 in different breeds of dairy cows. Contrary to the present findings, Rehman et al. (2008) reported a lower heritability estimate of 0.11 ± 0.03 of lactation yield for Sahiwal cows. The heritability estimates of the LMY ranged widely from 0.06 to 0.39 (Ayied, Jadoa, & Abdulrada, 2011; Cilek & Sahin, 2009; Hamrouni et al., 2014; Nawaz, Nizamani, Marghazani, & Nasrullah and Fatih, A., 2013). Although the production performance of the animals was not up to expectations, but its heritability is relatively higher than other traits of performance. Therefore, it can be chosen in selection criteria. Furthermore, this could be significantly improved through selection of superior genetics animals, proper feeding and efficient management of the farm.
3.9.1 Genetic correlation
Genetic correlation between various productive and reproductive performance traits are presented in Table 4. Genetic correlation has always been considered an important part of the breeding programme. Genetic correlation estimation is relatively difficult compared to heritability; therefore, the concept of genetic correlation is less understood than the heritability estimates. Genetic correlation between variables may range from −1.0 to 1.0, it may be negative or positive while the heritability must be positive and range from 0.0 to 1.0.
Traits2 | BW | AAM | AFC | DO | CI | DP | LL | LMY |
---|---|---|---|---|---|---|---|---|
BW | 1.00 | −0.09** | −0.07* | −0.16** | −0.34** | −0.002 | 0.30** | 0.81** |
AAM | 1.00 | 0.77** | 0.05 | 0.08* | 0.08 | −0.01 | 0.14** | |
AFC | 1.00 | 0.01 | 0.07 | 0.02 | −0.01 | 0.12** | ||
DO | 1.00 | 0.77** | 0.72** | 0.26** | 0.24** | |||
CI | 1.00 | 0.56** | 0.28** | 0.37** | ||||
DP | 1.00 | −0.15** | −0.01 | |||||
LL | 1.00 | 0.53** | ||||||
LMY | 1.00 |
- Abbreviations: AAM, age at maturity; AFC, age at first calving; BW, body weight; DO, days open; CI, calving interval; DP, dry period; LL, lactation length; LMY, lactation milk yield.
- * p < 0.05 and
- ** p < 0.01.
The genetic correlation of birthweight with lactation length (r = 0.30; p < 0.01) and lactation milk yield (r = 0.81; p < 0.01) was positive and significant. Dandapat, Banerjee, and Chakraborty (2010) found a positive correlation of birthweight with first calving interval (0.0654) for crossbreds and Sahiwal cows. Strong positive correlation of birthweight with lactation and milk yield and negative correlation with age at maturity and other important parameters shows the marked importance of birthweight for selection and consideration of this important trait for effective reproductive performance.
Positive and significant genetic correlation of age at maturity with age at first calving (r = 0.77; p < 0.01) and lactation milk yield (r = 0.14; p < 0.01) was reported (Table 4). Calving interval was positively and significantly correlated with age at maturity (r = 0.08; p < 0.05). Present findings were in perfect relationship with the results of Shabana et al. (2002), who recorded highly significant correlation of age at maturity (r = 0.83; p < 0.01) with age at second calving. Findings of Ahmad, Khan, Manan, and Abdullah. (2005) were also in agreement with present findings who found a significant correlation (p < 0.05) of age at maturity with age at first calving. These finding revealed that early maturing cows had shorter age at first calving. Age at maturity was negatively correlated with lactation length (−0.01) and was not significant.
A positive and highly significant genetic correlation of age at first calving with lactation milk yield (0.13; p < 0.01) (Table 4). Age at first calving was positively correlated with days open (0.01), calving interval (0.07) and dry period (0.02), while negatively correlated with lactation length (−0.01) and were not significant. Present findings are in line with the results of Ahmad et al. (2005) who analysed data on Sahiwal cows and their crosses with Jersey and Friesian and reported a positive correlation (0.63) between age at first calving and lactation milk yield. From these findings, it was concluded that lactation milk yield is related to age at first calving. Hence, reducing the age at first calving will increase the lactation milk yield. Age at first calving is very important with the reproductive point of view as it determines the time that when an animal starts its production and therefore could influence the productive life of an animal.
Significant and positive genetic correlation of days open with calving interval (r = 0.77; p < 0.01) and dry period (r = 0.72; p < 0.01), lactation length (r = 0.26; p < 0.01) and lactation milk yield (r = 0.24; p < 0.01) was reported in the present findings (Table 4). Birhanu, et al., 2015) reported strong and positive genetic correlation between calving interval and days open of 0.997 ± 0.0009 and 0.998 ± 0.0004 in Ethiopian Boran and Boran x Holstein Friesian cows, respectively. Toghiani (2012) reported a weak and positive genetic correlation of 0.111 between days open and calving interval.
Calving interval was found positively and significantly genetically correlated with dry period (r = 0.56; p < 0.01), lactation length (r = 0.28; p < 0.01) and lactation milk yield (r = 0.37; p < 0.01) (Table 4). Javed, Abdullah, Akhtar, and Afzal (2004) reported a similar correlation between calving interval and first lactation milk yield (0.46 ± 0.46) for Sahiwal cattle. Rahbar, Aminafshar, Abdullahpour, and Chamani (2016) reported significant and positive correlation of calving interval with days open. The lower heritability estimate (14%) of calving interval suggested a relatively smaller contribution of genetic factors to this trait. Thus, direct selection for this trait is expected to bring slower progress.
The dry period was negatively and significantly genetically correlated with lactation length (−0.15; p < 0.01), while negatively correlated with lactation milk yield (−0.01) (Table 4). The present findings are in perfect correlation with the findings of Ahmad et al. (2005) who reported that dry period was positively and significantly (p < 0.01) correlated with post-partum service period and negatively and significantly (p < 0.01) correlated with daily milk yield per calving interval.
Lactation length was significantly and positively correlated with lactation milk yield (r = 0.53; p < 0.01). Similarly, Birhanu et al. (2015) reported positive genetic correlation of lactation length with total lactation milk yield in Ethiopian Boran (0.997 ± 0.0009) and their Crosses (0.998 ± 0.00004) which are in agreement with the present findings.
The highly significant while negative genetic correlation of milk yield with other parameters was found in the present study. Dabdoub (2009) reported a negative and significant correlation of milk production with age at first calving, which is in agreement with the results of the present research study. Similarly, Canaza-Cayo et al. (2018) also reported negative genetic correlation between 305MY and AFC (−0.49) implies that part of the additive genes that positively influence milk yield acts on reducing age at the first calving. Therefore, the selection process to increase milk yield would result in a greater precocity of heifers. Therefore, improving the environmental condition and efficient management along with the improved genetic potential of dairy cows would be more effective tactics for high milk production.
The most effective and rapid approach to improve the large size population of local and non-descript cattle is through crossbreeding with exotic dairy cattle breeds. Past experience of crossbreeding of local and non-descript cattle with exotic breeds such as Holstein Friesian and Jersey proved to be an effective tool of bringing rapid genetic improvement. The crossbreeding of local cows with the exotic cattle breed semen has resulted in increasing the milk production by 5 to 8 times. In order to improve the low productivity of native cattle, the national breeding policy has given the emphasis on the upgradation of local cattle through crossing with high producing exotic breeds. Therefore, the government of Pakistan has imported exotic breeds such as Holstein Friesian, and Jersey, in order to improve the production potential of local cattle. Although the Productive and reproductive performance traits reported in the present study are quite different among different breeds, but for more reliable estimates a large sample size data are required for heritability estimates and genetic correlation. Therefore, for reliable estimates combined heritability estimates were reported for all breeds.
4 CONCLUSION AND RECOMMENDATIONS
It is concluded that moderate to higher heritability estimates with adequate genetic variance were found for body weight and lactation yield. Body weight was found to be a good candidate character for increasing milk production at the lowest age at maturity and age at first calving. The moderate to higher heritability estimates of birthweight in the present study revealed that this important trait might be considered in selection criteria. Calving interval, which is also a crucial reproductive trait, could be minimized through efficient feeding and proper reproductive management of the herd. Due to the relatively higher standard errors associated with the estimated parameters, a larger sample size on half sibs should be recorded for estimates that are more reliable.
ACKNOWLEDGEMENTS
We would like to acknowledge Mr. Hamza Khan and his team from the school of English and American studies (Eötvös Loránd University) for critical reading and editing of this manuscript.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
AUTHOR CONTRIBUTIONS
Ilyas Ali collected the data and wrote the manuscript. Syed Muhammad Suhail designed the study and helped in revision of the manuscript. Muhammad Shafiq helped to design, analysis and revision of the manuscript.