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Genetic Parameters of Production and Reproduction Traits and Factors affecting it in Frieswal Cattle

Parineeta Kakati Dhara Panchal Ashish Patel P. K. Bahuguna R. S. Joshi D. N. Rank
Vol 7(7), 190-199
DOI- http://dx.doi.org/10.5455/ijlr.20170513100842

Data on performance records of 1249 Frieswal daughters of 71 sires over a period of 13 years from 2000-2012 were analyzed to determine the effects of farm, parity, type of calving, period of birth and season of birth on lactation length (LL), 305-day milk yield (305-DY) and calving interval (CI). The age at first calving (AFC) was considered as covariable. The overall least-squares means for AFC, LL, 305-DY and CI were 31.45±0.89 months, 303.31 ± 7.02 days, 2997.01 ± 123.24 kg and 431.19 ± 16.53 days respectively. Period of birth had significant effect on age at first calving. Farm, type of calving and period of birth had significant effect on lactation length. Farm, parity and season of birth had significant effect on 305-day milk yield. Parity, type of calving, period of birth and season of birth had significant effect on calving interval. Heritability estimates for LL and CI were low (0.17 ± 0.10 and 0.11 ± 0.09), while it was high (0.51±0.14) for 305-DY. The phenotypic and genetic correlation between lactation length, 305-day milk yield and calving interval were observed high and positive.


Keywords : Frieswal Cattle Least-Squares Heritability Genetic Phenotypic Correlation

Introduction

Milk production is one of the most important economic traits in dairy cattle. India continues to be the largest producer of milk in the world. The milk production has increased significantly from the level of 102.6 million tonnes in 2006-07 to 155.5 million tonnes in 2015-16. However, the per capita availability of milk is just around 337 grams per day and there is huge local demand of milk (Anonymous, 2016). In spite of India’s position as the highest producer of milk, productivity of individual animal is low. Considering the large requirement of milk by Indian Army, crossbreeding of local cattle with exotic dairy breeds was introduced in India in 1875 to cater the need of milk by army. Military dairy farms (MDFs) were established in 1891 with the emphasis to develop high yielding crossbred cattle suitable to Indian climate. Project Directorate on Cattle (now CIRC, Central Institute for Research on Cattle), Meerut developed a synthetic breed “Frieswal” (5/8 Holstein Friesian and 3/8 Sahiwal), yielding 4000 kg of milk with 4% butter fat in a lactation of 300 days in collaboration with Ministry of Defence utilizing Military Dairy Farms herds (Anonymous, 2011). The military dairy farms are the largest source of crossbred animals in India and Asia.

Influence of non-genetic factors on various economic traits is required to be evaluated to adjust the data for significant effect of these factors on economic traits. The accurate estimates of genetic and phenotypic parameters viz. heritability, repeatability, genetic and phenotypic correlations amongst different traits are of utmost importance for any breed improvement programme. Identification of the best sires with maximum accuracy is of immense importance for any breed improvement programme, as sires are used extensively in various herds under progeny testing programme. The aim of present study was to evaluate the effects of non-genetic factors and to estimate genetic parameters of production and reproduction traits in Frieswal cattle.

Materials and Methods

Data on a total of 1249 lactations of Frieswal cows maintained at Military Farm, Guwahati, Dimapur and Bengdubi during 2000 to 2012 year of birth were utilized to study the influence of farm, parity, type of calving, period of birth and season of birth on traits viz. lactation length (LL), 305-day milk yield (305-DY), calving interval (CI) and age at first calving (AFC) (considered as covariable). Parity was considered from first to seventh parity; type of calving was divided as normal, retention of placenta (ROP), premature birth and dystokia; period of birth was classified into four periods as 2000-2003, 2004-2006, 2007-2009 and 2010-2012. Seasons were considered to be one of the main environmental factors that affect the performance of cows, as there is a wide variation in meteorological conditions during different seasons of the year. Season of birth was divided into four season viz. summer (March-May), rainy (June-September), autumn (October-November) and winter (December-February). The cows at all farms are bred through artificial insemination with the frozen semen from the Bull Rearing Unit, Frieswal Project, Military Farm, Meerut. The records on various reproduction and production traits of Frieswal cattle were analysed by least-squares (LS) analysis (Harvey, 1990) of fitting constants for the estimation of genetic parameters as well as to examine the simultaneous effects of different genetic and non-genetic factors affecting any trait. The least-squares (LS) model as

The model for Age at First Calving is

Where,

 = observation in lth cow borned in jth period, ith season with kth type of calving

= overall mean

 = effect of ith season of birth (summer, rainy, autumn and winter)

effect of jth period of birth (1 to 4)

effect of kth type of calving (normal, ROP, premature birth and dystokia)

 = random error, assumed to be normally and independently distributed with mean zero and constant variance i.e. NID (0,   ).

The model for other traits is

Where,

 = observation in oth individual of ith sire, borned in jth farm during mth period, lth season in kth parity with nth type of calving

= overall mean

 = effect of ith sire as random effect

 = effect of jth Farm as fixed effect (1 to 3)

effect of mth period of birth (1 to 4)

 = effect of lth season as fixed effect (summer, rainy, autumn and winter)

= effect of nth type of calving (normal, ROP, premature birth and dystokia)

effect of kth parity (1 to 7)

 = random error, assumed to be normally and independently distributed with mean zero and constant variance i.e. NID (0,   ).

Results and Discussion

The overall least-squares means of AFC (Table 1), LL, 305-DY and CI (Table 2) were observed to be 31.45 ± 0.89 months, 303.31 ± 7.02 days, 2997.01 ± 123.24 kg and 431.19 ± 16.53 days respectively. AFC in comparable range (31.90 ± 0.14 months) was reported by Raheja (1997) for Friesian × Sahiwal cattle. Earlier lower AFC has been reported in Frieswal cattle (Singh et al., 2014; Sumana, 2015). However, higher than the present estimates have also been reported in Jersey X Sahiwal and other crossbred cattle (Mishra and Prasad, 1998; Singh, 2007). Demeke et al. (2004) and Singh et al. (2013) reported an overall mean lactation length of 299 to 304 ± 9 days in crossbred cattle, which can be considered comparable with the present study. Conversely, a longer LL has been reported in Frieswal and Karan-Fries cattle (Singh et al., 2014; Japheth et al., 2015; Sumana, 2015). Lakshmi et al. (2009) estimated a mean 305-day milk yield of 2893.60 ± 0.82 kg in Holstein X Sahiwal cattle. Earlier, lower 305-DY has been observed in Deoni × Holstein Friesian crossbreds (Wondifraw et al., 2013). Higher 305-DY has also been observed earlier in HF crossbred and Karan-Fries cattle (Mathur, 2014; Japheth et al., 2015). Comparable CI (423.05 ± 12.24 to 439.03 ± 5.39 days) has been reported earlier in Frieswal and Karan-Fries cattle (Mathur, 2014; Singh et al., 2014; Japheth et al., 2015; Kumar et al., 2015; Sumana, 2015).

Table 1: Least-squares means (LSM) with standard error (S. E.) for AFC in Frieswal cattle

Effect Overall mean(µ) N LSM ± S.E.
377 31.45 ± 0.89
Farm HD1(Guwahati) 144 31.78 ± 0.94
HD2 (Dimapur) 85 31.70 ± 0.98
HD3(Bengdubi) 148 30.88 ± 0.93
Type of calving CT1 (Normal) 337 32.73 ± 0.38
CT2 (ROP) 33 31.82 ± 0.80
CT3 (Premature Birth) 4 28.65 ± 2.21
CT4 (Dystokia) 3 32.61 ± 2.53
Period of birth P1(2000-03) 14 31.57b ± 1.43
P2 (2004-06) 36 33.81c ± 1.04
P3 (2007-09) 149 30.98b ± 0.91
P4 (2010-12) 178 29.46a ± 0.90
Season of birth S1 (Summer) 82 32.13 ± 0.98
S2 (Rainy) 136 31.29 ± 0.93
S3 (Autumn) 60 30.56 ± 1.04
S4 (Winter) 99 31.82 ± 0.96

Table 2: Least-squares means with standard error (S.E.) for lactation length, 305-day milk yield and calving interval in Frieswal cattle

Effect Lactation Length 305-day Milk Yield Calving Interval
n LSM ± S.E. n LSM ± S.E. n LSM ± S.E.
Overall mean(µ) 1249 303.31 ± 7.02 1249 2997.01 ± 123.24 789 431.19 ± 16.53
Farm HD1 542 310.33± 7.44 542 2950.28a ± 130.56 354 438.84 ± 17.85
HD2 264 303.64b ± 7.66 264 3171.48b ± 134.51 169 430.28 ± 18.11
HD3 443 295.97a ± 7.31 443 2869.28a ± 128.26 266 424.46 ± 17.22
Parity PA1 377 302.64 ± 7.11 377 2649.66a ± 124.77 273 463.82d ± 16.00
PA2 300 313.15 ± 7.27 300 3112.76b ± 127.66 193 443.89cd ± 16.77
PA3 219 305.34 ± 7.55 219 3051.55b ± 132.55 141 417.88ab ± 17.53
PA4 170 302.59 ± 7.64 170 3136.51b ± 134.15 89 407.77a ± 18.47
PA5 97 299.72 ± 8.38 97 2989.56b ± 147.04 47 394.63± 20.56
PA6 56 302.78 ± 9.40 56 2993.67b ± 164.98 30 435.79bc ± 23.09
PA7 30 296.96 ± 11.05 30 3045.37b ± 194.05 16 454.57cd ± 27.75
Calving type CT1 1111 295.00a ± 2.56 1111 3263.88 ± 44.97 702 394.89a ± 6.49
CT2 123 312.84b ± 4.86 123 3238.23 ± 85.41 78 421.18a ± 11.57
CT3 10 305.01ab ± 15.37 10 2691.83 ± 269.93 5 404.60a ± 40.89
CT4 5 300.40ab ± 21.55 5 2794.11 ± 378.35 4 504.09b ± 45.64
Period of birth P1 97 339.97c ± 11.94 97 3391.16 ± 209.58 80 495.47d ± 25.64
P2 211 296.57b ± 8.62 211 2904.18 ± 151.34 162 442.88c ± 20.46
P3 617 287.84a ± 8.21 617 2901.85 ± 144.22 416 400.86b ± 19.55
P4 324 288.87a ± 8.99 324 2790.86 ± 157.89 131 385.57a ± 21.81
Season of birth S1 281 301.61 ± 7.69 281 3029.05bc ± 135.05 177 425.80ab ± 18.22
S2 456 303.53 ± 7.28 456 3110.43c ± 127.90 290 435.13bc ± 17.23
S3 219 301.56 ± 7.82 219 2965.30ab ± 137.24 149 411.88a ± 18.46
S4 293 306.54 ± 7.67 293 2883.28a ± 134.65 173 451.96c ± 18.29

Means with different superscripts within the factors differ significantly (P<0.05)

Effect of Farm

Least-squares analysis of variance revealed that effect of farm was highly significant on LL (P<0.01) (Table 4). The longest LL was observed for Guwahati MDF i.e., 310.33 ± 7.44 days followed by 303.64 ± 7.66 days for Dimapur and 295.97 ± 7.31 days for Bengdubi MDF. Sumana (2015) also observed highly significant effect of farm on LL in Frieswal cattle. Farm effect was found to be highly significant on 305-DY (P<0.01) in the present study. The highest 305-DY, 3171.48 ± 134.51 kg was obtained at Dimapur MDF, followed by 2950.28 ± 130.56 kg at Guwahati and 2869.28 ± 128.26 kg at Bengdubi MDF. Significant effect of farm on 305-DY was also reported in HF crossbred cattle (Mathur, 2014). Farm had no significant (P≥0.05) effect on AFC and CI (Table 3). However, Das et al. (2016) reported significant effect of farm on AFC in Friesian crossbred dairy cattle. While, Haile et al. (2009) observed significant effect of farm on CI in Holstein crossbred.

Table 3: Least-squares analysis of variance for AFC in Frieswal cattle

Source of Variation d. f. AFC
MS P
Farm 2 30.17 0.1951
Type of calving 3 27.73 0.2103
Period of birth 3 192.12** 0.00
Season of birth 3 32.44 0.1515
Error 365 18.38

** = Significant (P < 0.01)

Table 4: Least-squares analysis of variance for lactation length, 305-day milk yield and calving interval in Frieswal cattle

Source of Variation d. f. Lactation Length 305-day Milk Yield Calving Interval
MS P MS P MS P
Sire 70 3848.29** 0.0001 1651330.90** 0.00 6490.35 0.676
Farm 2 10784.86** 0.0061 4843989.50** 0.0006 6405.45 0.4066
Parity 6 4490.76 0.051 7930028.16** 0.00 53903.38** 0.00
Type of calving 3 10441.16** 0.0022 1266681.80 0.1174 27113.30** 0.01
Period of birth 3 11734.67** 0.001 1262993.06 0.1182 38771.48** 0.0012
Season of birth 3 1158.32 0.6521 1752266.53* 0.0435 27779.47** 0.0089
Error 1160 2104.22 648207.49 7108.38
Regression of AFC 1 6027.04 0.0908 2330127.72 0.0582 29.52 0.9486

*= Significant (P < 0.05) and **= Significant (P < 0.01)

Effect of Parity

Effect of parity was highly significant (P<0.01) on 305-DY in the present investigation. Fourth parity had the highest 305-DY of 3136.51 ± 134.15 kg while first parity had the lowest 305-DY of 2649.66 ± 124.77 kg. Wondifraw et al. (2013) and Narwaria et al. (2015) also observed highly significant effect of parity on 305-DY. Parity also had highly significant effect (P<0.01) on CI in the present study. First parity had the longest CI of 463.82 ± 16.00 days, while fifth parity had the shortest CI of 394.63 ± 20.56 days. Kumar et al. (2015), Japheth et al. (2015) and Narwaria et al. (2015) also reported significant effect of parity on CI in Frieswal, Karan-Fries and Sahiwal cattle, respectively. A non-significant effect of parity on LL was observed in the present study. Singh et al. (2014) also reported a non-significant effect of parity on LL in HF x Sahiwal cattle.

Effect of Type of Calving

The distribution of records under different categories of type of calving was highly skewed as almost 90% records belonged to the normal birth while abnormal birth constituted only 10%. The overall effect of type of calving on LL was observed to be highly significant (P<0.01) but there were significant difference in LL only among normal calving and ROP type of calving. Normal calving had the lowest LL of 295.00 ± 2.56 days, while all abnormal calving (dystokia, premature birth and retention of placenta) had significantly higher LL ranging from 300.40 ± 21.55 days (dystokia) to 312.84 ± 4.86 days (retention of placenta). Actually, most of authors reported that abnormal calving had shorter LL but in present study it was found that controversial effect of abnormal calving, which strengthen the LL may be due to long term and repeated hormonal therapy after abnormal calving especially in ROP, Premature birth. Effect of type of calving on CI was found to be highly significant (P<0.01) in Frieswal cattle in the present study. Normal calving had the shortest CI of 394.89 ± 6.49 days, whereas, all other abnormal calvings had significantly longer CI ranging from 404.60 ± 40.89 to 504.09 ± 45.64 days. On AFC and 305-DY, the effect of type of calving was observed to be non-significant (P≥0.05) in the present study. Studies on the effects of type of calving is apparently lacking in the literature.

Effect of Period of Birth

There were unequal numbers of records under different period of birth. Cows born during 2000 to 2003 and 2004 to 2006 (P1 and P2) had lower number of records in comparison to cows born during 2007 to 2009 and 2010 to 2012 (P3 and P4) due to unavailability of records of that period. Period had highly significant effect (P<0.01) on AFC in present study, may be due to during different period of time different managemental practices were adopted viz. feeding practices to heifers, early insemination etc. The highest AFC of 33.81 ± 1.04 months was observed for cows born during 2004 to 2006, followed by 31.57 ± 1.43 months for cows born during 2000 to 2003, 30.98 ± 0.91 months for cows born during 2007 to 2009 and 29.46 ± 0.90 months for cows born during 2010 to 2012. Effect of period of birth was also found to be significant on AFC by Japheth et al. (2015) in Karan-Fries cattle. Period of birth had also significant effect on LL (P<0.01) in the present study, may be due to during different period of time different managemental practices were adopted viz. milking up to late lactation (milking in late pregnancy) Vs. early drying off, which affects the lactation length in cows. Longest LL was observed in the cows born during 2000 to 2003 birth period (339.97 ± 11.94 days), whereas shortest LL was seen in cows born during 2007 to 2009 (287.84 ± 8.21 days). Narwaria et al. (2015) reported significant effect of period of birth on LL in crossbred cattle. Effect of period of birth on CI was highly significant (P<0.01) in the present study. The shortest CI (385.57 ± 21.81 days) was shown by cows born during 2010-2012, followed by 2007-2009 (400.86 ± 19.55), 2004-2006 (442.88 ± 20.46) and 2000-2012 birth period (495.47 ± 25.64 days). Kumar et al. (2015) also reported significant effect of period of birth on CI in Frieswal cattle. Effect of period of birth was found to be non-significant on 305-DY in the present study (P≥0.01). Fadellmoula (2007) also reported non-significant effect of period of birth on 305-DY in crossbred cattle.

Effect of Season of Birth

Cows born during monsoon or rainy season (June to September) had highest number of records in comparison to other seasons i.e., summer, autumn and winter. Effect of season of birth was found to be significant on 305-DY (P<0.05) in the present study. Cows born during monsoon season had the highest 305-DY (3110.43 ± 127.90 kg), whereas lowest 305-DY was observed for cows born during winter season (2883.28 ± 134.65 kg). Narwaria et al. (2015) also reported highly significant effect of season of birth on 305-DY in different crossbred cattle. Highly significant effect (P<0.01) of season of birth was found on CI; Winter born cows had the longest CI of 451.96 ± 18.29 days; while autumn born cows had the shortest CI of 411.88 ± 18.46 days. Singh et al. (2014), Kumar et al. (2015) and Narwaria et al. (2015) also observed significant effect of season of birth on CI in HF crossbred cattle. Season of birth had no significant effect on AFC and LL (P≥0.05) in the present study. Non-significant effect of season of birth on AFC was also reported by Singh et al. (2014) in Frieswal cattle. Wondifraw et al. (2013) and Singh et al. (2014) also reported non-significant effect of season of birth on LL in the crossbred cattle.

Estimates of Genetic Parameters

Heritability

Heritability estimate of various traits are presented in Table 5.

Table 5: Estimates of heritability (along diagonal), genetic (rg) (above diagonal) and phenotypic (rp) (below diagonal) correlations among lactation length, 305-day milk yield and calving interval of Frieswal cattle

Traits Lactation Length 305-day milk yield Calving Interval
Lactation length 0.17 ± 0.10 0.663 ± 0.23 0.783 ± 0.30
305-day milk yield 0.44 0.51 ± 0.14 0.452 ± 0.38
Calving interval 0.64 0.21 0.11 ± 0.09

Heritability estimate for LL was 0.17 ± 0.10 in the present investigation. Komatwar et al. (2009) estimated heritability of LL as 0.15 ± 0.001 in Friesian X Sahiwal cattle. A high heritability estimation of 0.51 ± 0.14 was observed for 305-DY in present study. Normally, heritability of milk yield falls in the range of 0.20 to 0.40. The over estimation of heritability could be due to the variation in the genetic potential of sires and their unequal distribution among the farms. Lakshmi et al. (2010) observed a medium estimate of 0.20 ± 0.08 for heritability of 305-DY of in Frieswal cattle. Mudgal et al. (1990) also reported high heritability estimate of 305-DY (0.48 ± 0.05) in Friesian X Red Sindhi cattle. Low estimate of heritability of 0.11 ± 0.09 was found for CI in the present study. Vinothraj et al. (2016) also observed a medium heritability of 0.22 ± 0.10 for CI in Jersey X Red Sindhi herd. In contrast, Mathur (2014) estimated low heritability of 0.016 ± 0.006 for CI in Frieswal cattle. CI is a reproduction trait having low heritability. Calving interval is influenced more by environmental factors and sufficient improvement in the trait could be brought about by management interventions.

Phenotypic and Genetic Correlations

In the present study, a positive genetic and phenotypic correlations were observed between LL and 305-DY (??= 0.663 ± 0.23, ??= 0.44) and between LL and CI (??= 0.783 ± 0.30, ??= 0.64). A positive genetic and phenotypic correlations were obtained between 305-DY and CI (??= 0.452 ± 0.38, ??= 0.21). Positive correlations between LL and 305 or less days milk yield were also reported in crossbred cattle by Narwaria et al. (2015). Eid et al. (2012) reported that total lactation milk yield had positive phenotypic correlations with daily milk yield and LL in Friesian cattle. Sumuna (2015) estimated positive genetic and phenotypic correlations of CI with LL (??= 0.87 ± 0.14, ??= 0.66), SLPY (??= 0.164 ± 0.24, ??= 0.13) in Frieswal cattle. Positive genetic correlation between the traits implies that selection for improvement in one trait would automatically improve the other traits as a correlated response to selection. However, LL and CI should be optimum and need not to be raised to improve standard lactation yield.

Conclusions

Study on Frieswal cattle maintained at Military Farm, Guwahati, Dimapur and Bengdubi revealed that AFC was affected only by period of birth but not by farm, type of calving and season of calving. LL was affected by farm, type of calving and period of birth. 305-DY was affected by farm, parity and season of birth. CI was affected by parity, type of calving, period of birth and season of birth. Heritability estimates for LL and CI were low, while it was high for 305-DY. The phenotypic and genotypic correlation between LL, 305-DY and CI were observed high and positive.

Acknowledgements

We are thankful to Director of Military Farm, Head Quarter, Eastern Command for providing and tracking of all the data on Frieswal cattle.

References

  1. Anonymous. 2011. Reports on directory of Frieswal Bulls. Project Directorate on Cattle, Meerut (UP).
  2. Anonymous. 2016. Basic Animal Husbandry and Fisheries Statistics. Ministry of Agriculture, Department of animal husbandry, Dairying and Fisheries. Krishi Bhawan, New Delhi.
  3. Das, S.K., Gupta, A.K., Singh, A., Chakravarty, A.K., Valsalan, J., Shivahre, P.R., Panmei, A. and Divya, P. 2016. Analysis of genetic trend in fertility and production traits of Karan Fries (Holstein Friesian crossbred) cattle using BLUP estimation of breeding valuesIndian Journal of Dairy Sciences. 69(2).
  4. Demeke, S., Neser, F.W.C. and Schoeman, S.J. 2004. Estimates of genetic parameters for Boran, Friesian, and crosses of Friesian and Jersey with the Boran cattle in the tropical highlands of Ethiopia: milk production traits and cow weight. Journal of Animal Breeding and Genetics. 121: 163–175.
  5. Eid, I.I., Elsheikh, M.O. and Yousif, I.S. 2012. Estimation of genetic and non genetic parameters of Friesian cattle under hot climate. Canadian Center of Science and Education. Journal of Agricultural Sciences. 4(4).
  6. Fadlelmoula, A.A., Abu Nekheila, A.M. and Yousif, I.A. 2007. Lactation performance of crossbred dairy cows in the Sudan. Research Journal of Agricultural and Biological Sciences. 3(5): 389-393.
  7. Haile, A., Joshi, B.K., Ayalew, W., Tegegne, A. and Singh, A. 2009. Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian in central Ethiopia: Reproductive traits. Journal of Agricultural Sciences. 147: 81-89.
  8. Harvey, W.R. 1990. Users’ guide for LSMLMW and MIXMDL Package. Mix Model Least-squares and Maximum Likelihood Computer Programme. PC-2 version. Mimeograph, Columbia, Ohio, USA.
  9. Japheth, K.P., Mehla, R.K., Imtiwati. and Bhat, S.A. 2015. Effect of non-genetic factors on various economic traits in Karan Fries crossbred cattle. Indian Journal of Dairy Sciences. 68(2): 163-169.
  10. Komatwar, S.J., Deshpande, A.D., Kulkarni, M.D., Kulkarni, K.A., Yadav, G.B., Shisodeand, M.G. and Khanvilkar, A.V. 2009. Estimation of heritability and repeatability of production traits in Holstein Friesian × Sahiwal crossbreds. Journal of Bombay Veterinary College. 17(1): 72-73.
  11. Kumar, S., Alex, R., Singh, U., Kumar, A. and Das, A.K. 2015. Comparative performance evaluation of Frieswal bulls in organized farms and farmers’ herds. Indian Journal of Animal Science. 85(3): 316–319.
  12. Lakshmi, S.B., Gupta, B.R., Prakash, M.G., Sudhakar, K. and Sharma, S. 2009. Genetic analysis of production performance of Holstein Friesian × Sahiwal cows. Tamilnadu Journal of Veterinary Animal Sciences. 5(4): 143-148.
  13. Lakshmi, S.B., Gupta, B.R., Prakash, M.G., Sudhakar, K. and Sharma, S. 2010. Genetic analysis of production performance of Frieswal cows. Tamilnadu Journal of Veterinary Animal Sciences. 6(5): 215-222.
  14. Mathur, A.K. 2014. Annual Report of Central Institute for Research on Cattle, 2013-14, Meerut, U.P.
  15. Mishra, A.K. and Prasad, R.B. 1998. Performance of purebred, half bred and thrice- breed crosses of Sahiwal with exotic dairy breeds. Indian Journal of Animal Production Management. 14(4): 203-205.
  16. Mudgal, K.C., Taylor, C.M. and Singh. A. 1990. Factors affecting milk yield in crossbred cattle. Indian Veterinary Journal. 67(2): 182-184.
  17. Narwaria, U.S., Mehla, R.K., Verma, K.K., Lathwal, S.S., Yadav, R. and Verma, A.K. 2015. Study of short lactation in Sahiwal cattle at organized farm. Veterinary World. 8(5): 690-694.
  18. Raheja, K.L. 1997. Factors affecting first lactation and lifetime production traits in Sahiwal and Hariana halfbreds. Indian Journal of Dairy Science. 50(2): 152-155.
  19. Singh, S., Das, A.K., Chakraborty, D., Taggar, R.K, Kumar, N., Gupta, P. and Mahajan, V. 2014. Studies on genetic and non-genetic factors affecting performance traits of Frieswal cows. Indian Journal of Animal Research. 48(6): 537-540.
  20. Singh, S., Tailor, S.P., Mishra, S., Kothari, M.S. and Garg, M.K. 2013. Prediction of first lactation 305-day milk yield using monthly part and test day yields in Surti buffaloes. Indian Journal of Animal Science. 83(11): 1219–1220.
  21. Singh, V. K. 2007. Genetic studies on some economic traits and sire evaluation by different methods in crossbred cattle. Ph.D. thesis. G.B. Pant University of Agriculture and Technology, Pantnagar, Uttaranchal.
  22. Sumana, K. 2015. Genetic evaluation of sires used in Frieswal herd at different military dairy farms in India. M.V.Sc. thesis. Anand Agricultural University, Anand, Gujarat.
  23. Vinothraj, S., Subramaniyan, A., Venkataramanan, R., Joseph, C. and Sivaselvam, S.N. 2016. Genetic evaluation of reproduction performance of Jersey × Red Sindhi crossbred cows. Veterinary World. 9(9): 1012-1017.
  24. Wondifraw, Z., Thombre, B.M. and Bainwad, D.V. 2013. Effect of non-genetic factors on milk production of Holstein Friesian × Deoni crossbred cows. African Journal of Dairy Farming and Milk Production. 1(4): 079-084.
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