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Genetic Evaluation of Sires Used in Frieswal Herd at Different Military Dairy Farms in India

Sumana Kundu Sharadindu Shil A. C. Patel R. S. Joshi P. Bali D. N. Rank
Vol 8(4), 180-194
DOI- http://dx.doi.org/10.5455/ijlr.20171111094001

A total of 1129 lactation records, of 384 Frieswal daughters from 1999 to 2013, collected from 3 Military Dairy Farms of Southern Command were analysed to determine the effects of Herd (HR), Genetic Group (GG), Season of calving (SS), Period of birth (PR) and Parity (PA) on calving interval in days (CI), lactation length in days (LL) and Standard lactation period yield in Kgs (SLPY). The age at first calving in days (AFC) was considered as covariable. The overall least squares means for CI, LL and SLPY were 434.52±14.97 days, 320.74±10.23 and 3090.16±203.16 kg respectively. HR, GG and PR had significant influence on AFC. SS had significant influence on CI. HR, PR and PA had significant influence on LL and SLPY. Heritability estimate for CI and LL were low (0.007±0.005 and 0.117±0.06) but high for SLPY (0.328±0.09).The genotypic and phenotypic correlations between CI, LL and SLPY were observed high and positive.


Keywords : Frieswal Cattle Genotypic and Phenotypic Correlation Heritability Least-Squares MDF

Introduction

India ranks first in milk production, accounting for 18.5 per cent of world production, achieving an annual output of 163.7 million tonnes during 2016-17(Anonymous, 2017). The military dairy farms (MDFs) were the largest source of crossbred cattle in India. The Frieswal project envisaged to evolve a National Milch Breed “Frieswal”, a Holstein (62.5%) – Sahiwal (37.5%) cross. As well, they were a rich source of data for the study of dairy animal improvement through the introduction of superior exotic inheritance (Mudgal and Arora, 1992). Sire evaluation is one of the most important aspects of dairy breed improvement programme as the contribution of sire path is higher than the dam path for overall genetic improvement of a trait. The success of a breeding programme depends on how early and how accurately bulls can be proved. Therefore, an accurate evaluation of the bull at minimum possible cost is of paramount importance for bringing about rapid genetic progress in dairy cattle (Kokate et al., 2012). Environmental impact, on the productive performance (Lactation Length, LL; Standardized Lactation Period Yield, SLPY) and reproductive efficiency (Calving Interval, CI) of the Frieswal cattle, was evaluated using Least Square Means (LSM) as a tool for sire evaluation. Reproduction and Production traits of dairy animals are low to moderately heritable indicating that the major part of variation in these traits are being governed by environmental factors (Japheth et al., 2015).

Also 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. Hence, the study was undertaken with the objective to evaluate the influence of non-genetic environmental factors on various economic traits and to estimate genetic parameters of production and reproduction traits in Frieswal cattle along with ranking of sires based on breeding value obtained from LSM.

Materials and Methods

Data Collection

The data for the present investigation pertained to a total of 384 Frieswal cattle (Holstein × Sahiwal crossbred) for a period of 15 years from 1999 to 2013 maintained at Military Farms viz. Ahmednagar (19.08°N,74.73°E), Deolali (19.951°N, 73.834°E) and Pimpri (18°37′07.04″N, 73°48′13.43″E) of Maharashtra, India. These are situated in the rain-shadow region of the Western Ghats. Climate of these districts are characterized by hot summer and general dryness throughout the year except during the period of southwest monsoon.

Experimental Design & Data Classification

The records on AFC, CI, LL and standardized lactation period yield i.e. 300 days yield (SLPY) of Frieswal cattle of known pedigree and with normal lactation were only considered for the present study. Incomplete and abnormal lactation were excluded. Only animals having records in the range as AFC (650-2230 Days), CI (330-700 Days), LL (175 -754 Days) and SLPY (1100 -5850 Kg) were used in all type of Statistical analysis. The 15 years period were divided as 1999-2002 (P1), 2003-2006 (P2), 2007-2010 (P3), 2011-2013 (P4). To determine and account for the effect of different season, a year was divided into four seasons on the basis of meteorological classification of Pune, Maharashtra region as below (Meteorological Department, Government of Maharashtra). Four seasons of calving were defined. Summer season comprised a three calendar month period, monsoon season four calendar month period, Post monsoon two calendar month period and winter three calendar month period.
The season of calving were classified into summer (March-May), rainy (June-September), post monsoon (October-November), winter (December-February) and were denoted as S1, S2, S3 and S4 respectively. Frieswal cows were classified into two genetic groups as progenies of HF sire and Frieswal cows as progenies of inter-se mated animals and denoted respectively as Genetic Group 1 (GG1) and Genetic Group 2 (GG2). Lactation or parity from first to tenth were considered and denoted as (L1-L10).The herd, genetic groups, season of calving, period of birth and parity were considered as fixed effect in LSM. Sire was considered as random genetic effect.

Statistical Analysis

Least Square Analysis of Variance

Non-orthogonal data with unequal subclass numbers were subjected to least square analysis of variance without interactions using different models, based on the assumption that different components fitting in the model were linear, independent and additive to examine the effect of genetic as well as non-genetic factors on the traits considered as per standard procedures of Harvey (1990). Least squares and maximum likelihood program LSMLMW PC2 version as described by Harvey (1990) was used. DMRT (Duncan Multiple Range Test) was performed for mean comparisons (Duncan, 1955). Sire was treated as random effect, genetic groups and other non-genetic factors were taken as fixed effects in the models. For AFC the following least squares model was used-

Where,

= Performance Trait (AFC) of oth progeny of ith sire, jth genetic group located at kth herd born in lth season and mth period

μ = Overall population mean

Si = Random effect of ithsire (i= 1 to 72)

Gj = Fixed effect of jth genetic group (1-2)

Hk= Fixed effect of kthherd (1-3)

Jl= Fixed effect of lthseason (1-4)

Pm= Fixed effect of mthperiod (1-4)

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

 

For Production traits the Least Squares Model used as follows-

Where,

= Performance Traits (CI, LL and SLPY) of oth progeny ith sire, jthgenetic group located at kthherd born in lthseason, mthperiod and nth parity

Zijklmno = AFC to be taken as covariable with other traits in the model

= average AFC; bZX = regression of trait under study with AFC

μ = overall population mean

Si = Random effect of ith sire. (i= 1 to 72)

Gj = fixed effect of jth genetic group (1-2).

Hk= fixed effect of kthherd (1-3)

Jl= fixed effect of lthseason (1-4)

Pm= fixed effect of mthperiod (1-4)

Ln = fixed effect of nth parity (1-10)

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

SLPY was derived from the following formula as per Panicker et al. (2016)-

Standard Lactation Period Yield (SLPY) =

Where,

LY= Lactation Yield

LD= Lactation Days

ADY= Average. Daily Yield

Results and Discussion

Least Square Means of Age at First Calving (AFC)

The AFC reflects the rate of growth of the female. A late entry into the productive life reduces the economic value of the animals, due to the potentially decreased number of offspring produced in their lifetime. The overall least squares mean of AFC was 937.28 ± 47.65 days (Table 1). The least square mean of AFC was found to be 937.28±47.65 days. Least squares mean for AFC for Frieswal cattle has been reported as 978.71±3.22 days (Mathur, 2014), 29.72 ±0.45 months in Frieswal cattle at J&K MDF (Singh et al., 2014).

Effect of Different Genetic and Non-Genetic Factors on AFC

The least square means of AFC in this study were found as 927.54±47.97 days, 967.67±48.46 days and 916.63±47.77 days at Ahmednagar, Deolali and Pimpri MDFs respectively. Effect of herd or farm on AFC was highly significant (P<0.01) in this study (Table 4 and Fig.1). Significant influence of herd was also reported by Deshmukh and Kaikini (1991), Talbott et al (1997), Rao et al (2000) and by Mathur (2014) in Frieswal cows in India,.

Table 1: Least Square Means (LSM) with Standard Error (S.E.) for Calving Interval (CI). Lactation Length (LL) and Standard Lactation Period Yield (SLPY) in Frieswal Cattle

Effect   CI (Days) LL (Days) SLPY (Kg) AFC (Days)
N LSM S.E. LSM S.E. LSM S.E. N LSM S.E.
Overall Mean (µ) 1129 434.52 14.97 320.74 10.23 3090.16 203.16 384 937.28 47.65
Herd (HR) HR1(Ahmednagar) 597 437.35a 15.47 323.31b 10.65 2955.69a 207.38 201 927.54a 47.97
HR2 (Deolali) 165 433.21a 16.29 327.87b 11.35 3256.76c 214.44 58 967.67b 48.46
HR3(Pimpri) 367 433.02a 15.11 311.02a 10.35 3058.04b 204.4 125 916.63b 47.77
Genetic group (GG) GG1 86 444.18a 17.02 325.54a 11.97 3193.98a 220.82 29 967.51a 49.16
GG2 1043 424.88a 15.48 315.94a 10.67 2986.35a 207.52 355 907.05b 48.06
Season of Calving

(SS)

S1(Mar-May) 315 434.62a 15.34 320.99a 10.54 3122.50a 206.27 102 937.84a 47.9
S2(June-Sep.) 265 446.13b 15.34 323.30a 10.54 3094.23a 206.27 97 940.11a 47.88
S3(Oct.-Nov.) 214 430.94a 15.68 321.63a 10.84 3043.45a 209.21 69 935.91a 48.11
S4(Dec.-Feb.) 335 426.43a 15.32 317.02a 10.52 3100.46a 206.09 116 935.26a 47.86
Period of Birth (PR) P1(1999-2002) 7 432.76a 29.79 396.16a 22.29 2648.90a 342.07 2 876.44a 63.96
P2(2003-2006) 64 437.13a 16.33 337.32b 11.38 3496.79b 214.72 19 899.29ab 48.34
P3(2007-2010) 481 431.85a 13.92 320.80b 9.3 3087.09b 194.41 130 956.22b 46.76
P4(2011-2013) 577 436.37a 14.36 328.67b 9.69 3127.87b 198.06 233 1017.16b 46.97
Parity (PA) L1 279 444.57a 15.34 315.65ab 10.54 2550.51a 206.27 Means with different superscripts within the factors differ significantly (P<0.05)
L2 242 432.44a 15.25 334.32b 10.46 3079.64b 205.49
L3 201 426.92a 15.19 325.53ab 10.42 3240.54bc 205.02
L4 151 419.21a 15.39 321.95ab 10.58 3304.90bc 206.7
L5 117 424.52a 15.78 319.11ab 10.92 3306.64bc 210.04
L6 77 428.56a 16.49 310.85ab 11.53 3087.72bc 216.22
L7 34 416.97a 18.57 300.52a 13.26 3190.69bc 234.64
L8 17 433.51a 22 334.53b 16.07 3399.80c 266.34
L9 5 441.05a 34.05 326.33ab 25.64 3020.04bc 384.75
L10 6 477.54a 31.67 318.58ab 23.78 2721.13a 360.87

The longest AFC was found at MDF, Deolali and the shortest was at MDF, Pimpri. Large variation in AFC reflects the scope of its improvement by improvised general managemental practices including feeding, timely heat detection and AI.

Table 4: Analysis of Variance for AFC in Frieswal cattle By LSM

    AFC
Source D.F. MS P
SIRE 71 80335.24** 0.0000
HR 2 125302.5** 0.0002
GG 1 141759.1** 0.0017
SS 3 1998.64 0.9328
PR 3 315470.7** 0.0000
ERROR 1674 14331.98  

 

 

 

Effect of genetic group on AFC was highly significant (P<0.01) (Table 4 and Fig. 2). Frieswal cows as progenies of Holstein Friesian sire (GG1) had highest AFC (967.51±49.16 days) than Frieswal cows as progenies of inter-se mated animals (GG2) (907.05±48.06 days). It was also reported by Deshmukh and Kaikini (1991) in Sahiwal and its crosses with exotic breeds, Sahana (1996) and Saha (2001) in Karan Swiss (KS) and in Karan Fries (KF) cattle. Season had no significant effect on AFC in the present study (Table 4 and Fig. 3). it was reported the same by Sahana and Gurnani (2000), Saha (2001) in Karan Swiss (KS) and in Karan Fries (KF) cattle, Haile et al. (2009), Manoj (2009) and Singh et al. (2014). Period was having highly significant effect (P<0.01) on AFC in this study (Table 4 and Fig. 4). Highest AFC was observed in Period 4 (1017.16±46.97 days). Period of birth was significant in Frieswal cattle as reported by Rao et al. (2000), Sahana and Gurnani (2000), Saha (2001), Gaur (2003), Manoj (2009), Sharma (2013) and Singh et al. (2014). The significant effect may indicate that, change in population structure, climatic conditions, fodder and feed availability and management practices over time has brought variation in AFC. The increasing trend of AFC was seen as above, indicating requirement of further improvement of management in these three farms. Heritability for AFC was 0.681±0.113.

Least Square Means of Calving Interval (CI)

The overall least square mean of CI was 434.52±14.97 days (Table 1). The CI observed in the present study can be considered satisfactory in Indian conditions. The least square mean of CI has been reported as 426.64 ±2.96 days in Frieswal cattle by Mathur (2014); 439.03±5.39 days CI in Karan Fries crossbred cattle by Japheth et al. (2015). The fact that calving interval increases with increase in percentage of exotic genes in crossbreds above 50% is widely reported by Teodoro and Madalena (2002) and Ahmad et al. (2004).

Effect of Different Genetic and Non-Genetic Factors on CI

Effect of herd on CI was found to be non-significant in the present study (Table 2 and Fig. 5). In contrast significant effect of herd on CI was found in Frieswal cattle in a study conducted at CIRC, Meerut involving 40 military farms across India with 39553 lactation records (Sharma, 2013).

Table 2: Analysis of Variance for CI, LL and SLPY in Frieswal cattle by LSM

  CI LL SLPY
Source D.F. MS P MS P MS P
SIRE 71 7467.46** 0.0007 3830.25* 0.01 1180186** 0.000
HR 2 1413.46 0.73 12872.07** 0.00 3029633** 0.00
GG 1 10320.59 0.13 2554.84 0.32 1194629 0.12
SS 3 18447.18** 0.00 1983.69 0.52 245010.3 0.70
PR 3 1340.62 0.82 8725.58* 0.02 3285362** 0.0003
PA 9 8073.79 0.06 8054.51** 0.00 7222906** 0.000
ERROR 1038 4504.84   2664.19   514133.3  
Regression of AFC 1 1823.02 0.52 4961.82 .17 1533799.47 0.08
Regression Const.   -0.01   -0.01   -0.33  

*= significant (p< 0.05) and ** = highly significant (p<0.01)

Non-significant effect of genetic group was found on CI in the present study (Table 2 and Fig. 6). Highly significant effect (P<0.01) of season of calving was found on CI (Table 2 and Fig. 7). Season 2 (Monsoon) had highest calving interval as 446.13±15.34 days. Similar finding has been described earlier by Duc and Taneja (1984) in Hariana x Holstein Friesian (HF) cattle and Hariana x Jersey crosses; Talbott et al (1997) in HF X Sahiwal (SW) cattle. The longest CI in monsoon period may be due to such as parasitical load in animal during this time, creating mineral deficiency in animal and for this reason animal suffered longest service period. Period of birth had non-significant effect on CI (Table 2 and Fig. 8). This result is in accordance to the study by Malau-aduli et al. (1996) in HF X Bunaji cattle. This indicates improved managemental practices for CI.

Non-significant effect of parity on CI was found in the present study (Table 2 and Fig. 9) and it supports the results by Malau-Aduli et al. (1996) in HF X Bunaji cross-bred cattle. In this present study timeline trend was found such that the CI tend to be decreased from 1st to 4th lactation and then again it increased from 5th to 10th lactation and in 10th lactation it was highest (477.54±31 days) amongst all.

Estimates of Genetic Parameters of CI

Heritability estimate for CI in the present study was 0.173±0.07 (Table 3), indicating additive genetic variance is very less, so there is small possibility of direct selection for the trait. Calving interval measurements frequently omit dams culled for low production or reproductive problems, causing reduction of additive genetic variance. This low heritability may indicate that variations in the trait, to a large extent, are being influenced by environmental factors such as herd management policies so sufficient improvement in the trait could be brought about by management interventions.

The heritability estimates of CI in triple cross HF dairy cattle was found to be 0.219±0.09 Patel (2007), 0.007±0.005 by Sharma (2013). The repeatability of the CI was found to be 0.06 (Table 3).  Patel (2007) earlier found in triple cross HF cattle repeatability of CI 0.32. A positive genetic correlation has been obtained between CI and LL ( ).

Table 3: Estimates of heritability, repeatability, genetic and phenotypic correlations among CI, LL and SLPY of Frieswal cattle By LSM

  CI LL SLPY Repeatability
CI 0.173 ± 0.07 0.870± 0.14 0.164± 0.24 0.06
LL 0.66 0.117± 0.06 0.044± 0.28 0.03
SLPY 0.13 0.25 0.328±0.09 0.10

h2 ± S.E. = along diagonal, rg± S.E. =above diagonal, rp=below diagonal, k =15.10 for Heritability estimation, k=8.57 for Repeatability estimation

The high positive genetic correlation indicates that selection for calving interval could promote moderate changes in the lactation length. Calving Interval has also positive correlation with SLPY ( ). Exclusion of individuals having less number of records would yield biased mean squares for ‘between individuals’ leading to a smaller variance component to individual and obviously in such a biased situation the estimate of repeatability will be small.

Least Square Means of Lactation Length (LL)

Overall LSM was estimated as 320.74±10.23 days for LL in the present study (Table 1). Lakshmi et al. (2009) reported 320.5±6.04 days of lactation length in HF X SW. Similar results were reported by Mathur (2014) and Singh et al. (2014).

Effect of Different Genetic and Non-Genetic Factors on LL

Herd effect was found to be highly significant on LL (P<0.01) in the present study (Table 2 and Fig. 10). Significant effect of herd on LL was also described by Mathur (2014). Lactation length was longest for Deolali MDF i.e.327.87±11.35 days and lowest for Pimpri MDF i.e. 311.02±10.35 days. Effect of genetic group on LL was found to be non- significant in the present investigation (Table 2 and Fig. 11). Dhara et al. (2006) also found similar result. Season of calving was having non- significant effect on LL (Table 2 and Fig. 12). Winter born cows displayed the lowest lactation length at all the MDFs (317.02±10.54 days), whereas the longest lactation length was observed in monsoon born cows (323.30±10.54 days) supporting results were obtained from Sharma (2013). Period of birth was having significant effect on LL (P<0.05) (Table 2 and Fig. 13).

Sharma (2013), Narwaria et al. (2015) and Samarai et al. (2015) also reported significant effect of period of birth on LL. This may be due to variation in management practices and availability of quality fodder over the periods. Highly significant effect (P<0.01) of parity was observed on LL in the present study (Table 2 and Fig. 14). Mathur (2014), Narwaria et al. (2015) and Samarai et al. (2015) also reported the same in Holstein cattle.

Estimates of Genetic Parameters of LL

Heritability estimate for LL was 0.117±0.06 in the present investigation (Table 3), which indicates small possibility of direct selection for the trait. Similar results were found by Patel (2007), Malhado et al (2013) and Mathur (2014). The repeatability of the LL was found to be 0.03 (Table 3). A positive genetic correlation was observed between LL and CI, (  ) and between LL and SLPY ( ). Low estimate of repeatability may be due to small number of sires used in the crossbreeding experiments.

Least Square Means of SLPY

Overall LSM for SLPY was found to be 3090.16±203.16kg (Table 1). Mathur (2014) reported an average SLPY of 3262.36 kg.

Effect of Different Genetic and Non-Genetic Factors on SLPY

Herd effect was found to be highly significant on SLPY (P<0.01) in the present study (Table 2 and Fig. 15). Similar effect was found by Mathur (2014). SLPY was lowest for Ahmednagar MDF i.e.2955.69±207.38 kg and highest in Deolali MDF i.e. 3256.76±214.44 kg. Effect of genetic group was found to be non-significant on SLPY in the present study (Table 2 and Fig. 16). Effect of season of calving was found to be non- significant on SLPY in the present study (Table 2 and Fig. 17). Cows born during post-monsoon recorded the lowest SLPY in all the farms (3043.45±209.21 kg), whereas longest lactation length was observed in summer season (3122.50±206.27 kg). Hyder et al. (2007) also reported the same in HF X SW breeds. Effect of period of birth was found to be highly significant on SLPY in the present study (P<0.01) (Table 2 and Fig. 18). Period 2 (2003-2006) showed highest SLPY (3496.79±214.72 kg) while lowest SLPY (2648.90±342.07kg) was observed in period 1 (1999-2002). Hyder et al. (2007), Barbosa et al. (2008), and Sharma (2013) also reported the same. Parity had highly significant effect (P<0.01) on SLPY in the present study (Table 2 and Fig. 19). Hyder et al. (2007) and M’hamdi et al. (2012) also reported significant effect of parity on SLPY in crossbred cattle.

Estimates of Genetic Parameters of SLPY

Heritability estimate for SLPY was observed to be 0.328±0.09 in the present study (Table 3). The heritability estimate for SLPY was moderate, suggesting that this trait has enough additive genetic variation to respond well to direct mass selection and selective breeding of sires. The estimates of heritability of SLPY in triple cross HF dairy cattle was reported as 0.28±0.18 by Patel (2007).The repeatability of the SLPY in the present study was found to be 0.103 (Table 3) whereas Patel (2007) reported repeatability of 0.46 for SLPY in triple cross HF cattle. In the present study estimate of low repeatability may be due to the potential biases in estimation of variance component that were introduced by computer software package, system of feeding and management might have masked the full expression of genetic differences and environment effect and possibly a negative covariance might have existed between the yields in adjacent years because of imbalances in body reserve from year to year in a given location as also opined by Khan et al. (1988).

Ranking of Sires as Per Breeding Values Obtained From LSM

Least square analysis for unequal subclasses Harvey (1990) adjusts the data for the environmental factors and also takes into consideration the non-orthogonality of the data. As per the breeding values of the sires obtained from LS model for CI, LL and SPLY (Table 5) the sire HF99 for CI, MAHAVEER for LL and HONDA for SLPY (Table 6) was found securing top rank amongst others.

Table 5: Sire Rankings (Up To 50th Rank) by Least Square

  CI LL SLPY   CI LL SLPY
Rank Siren BV Siren BV Siren BV Rank Siren BV Siren BV Siren BV
1 71 -39.11 37 23.91 56 385.08 26 18 -6.82 45 2.22 17 45.46
2 22 -19.71 7 20.55 78 326.68 27 69 -6.61 60 1.8 34 34.65
3 29 -16.43 70 17.47 35 306.37 28 6 -6.48 18 0.52 1 31.87
4 46 -16.36 58 15.7 27 298.37 29 3 -5.88 54 0.34 46 20.26
5 48 -16.25 17 15.47 49 285.89 30 45 -5.21 26 0.18 16 16.58
6 23 -15.8 35 15.07 75 283.03 31 32 -4.85 61 0.15 25 16.57
7 34 -14.78 41 14.81 20 256.12 32 50 -4.46 32 -0.15 23 10.74
8 72 -14.72 5 13.31 39 227.03 33 19 -4.37 25 -0.47 12 -2.33
9 13 -14.43 43 13.25 28 213.06 34 2 -2.56 46 -0.65 68 -3
10 65 -14.42 12 11.78 45 212.3 35 28 -2.33 36 -0.82 54 -4.71
11 30 -14.18 67 11.51 64 190.19 36 27 -1.89 27 -0.82 55 -5.04
12 42 -14.08 78 9.85 15 173.16 37 33 -0.94 56 -1.19 6 -17.24
13 73 -12.31 72 8.51 4 165.41 38 66 0.38 11 -1.52 37 -18.66
14 36 -11.7 73 8.29 72 165.26 39 54 1.59 19 -2.07 42 -26.16
15 24 -11.66 10 8.24 41 165.13 40 41 2.46 44 -2.11 2 -26.36
16 68 -11.47 20 6.06 73 124.87 41 39 2.88 53 -2.31 66 -41.09
17 38 -11.4 15 5.97 13 123.62 42 59 3.07 74 -2.54 61 -42.65
18 4 -11.05 55 5.77 21 112.13 43 74 3.49 48 -2.81 40 -44.19
19 51 -10.93 39 4.6 71 109.93 44 64 3.74 2 -3.06 22 -47.69
20 21 -10.26 16 4.19 3 89.22 45 16 4.14 21 -3.53 44 -50.51
21 52 -9.6 34 3.4 70 73.88 46 11 4.56 64 -3.61 24 -54.36
22 76 -9.24 77 3.3 58 63.88 47 1 7.22 68 -3.64 69 -70.6
23 40 -9.11 47 2.47 32 60.96 48 25 7.36 1 -4.16 47 -71.19
24 49 -8.02 3 2.44 26 54.22 49 10 7.45 38 -4.32 53 -71.55
25 53 -7.97 75 2.3 10 45.55 50 60 7.94 65 -4.52 43 -77.47

 

 

 

 

 

 

 

 

Table 6: Sire ID and name of the Sires of three Farms

S. No. Sire ID* Sire Name No.  of progeny S. No. Sire ID* Sire  Name No.  of progeny
1 1 SUBHASH 10 41 45 PURAN 5
2 2 TYSON 82 42 46 KALA 6
3 3 ANKIT 2 43 47 DARA 7
4 4 HARI 69 44 48 JATIN 8
5 5 MONTI 68 45 49 MOHAN 20
6 6 SALVI 48 46 50 HF1275 2
7 7 MADHOSH 56 47 51 NAGA 13
8 10 FAKIR 6 48 52 FLORA 9
9 11 DAMAN 70 49 53 RAM 2
10 12 SARWAN 28 50 54 OM 1
11 13 KOBRA 23 51 55 KANS 20
12 15 RADHE 13 52 56 HONDA 12
13 16 SALUTE 1 53 58 SAKA 3
14 17 SALONI 6 54 59 ANGAR 7
15 18 HIPPY 45 55 60 HF107 2
16 19 SHIV 12 56 61 MONTU 3
17 20 FAIZ 30 57 63 KUNJ 1
18 21 SPIKE 4 58 64 GAJRAJ 14
19 22 JASVIR 3 59 65 BHARAT 10
20 23 LOZAR 60 60 66 GYAN 2
21 24 LION 64 61 67 PARA 6
22 25 SHAM 2 62 68 MADAN 11
23 26 LORD 12 63 69 BAROD 1
24 27 KARAN 23 64 70 NAZIR 4
25 28 GAGAN 28 65 71 HF99 14
26 29 MANGU 13 66 72 BAZ 10
27 30 LOTAN 34 67 73 HASAN 14
28 32 164 RANGILA 8 68 74 HF69 2
29 33 ALOK 9 69 75 HF978 2
30 34 26 BABAR 21 70 76 LOHAN 7
31 35 ADARSH 16 71 77 WJR871 3
32 36 ASIF 23 72 78 HF1492 3
33 37 MAHAVEER 3        
34 38 HIRA 16  

*SIRE IDs are not Farm ID of the Sires.

 

35 39 MANJU 19
36 40 417 MAHI 2
37 41 MADHAV 10
38 42 KAMESH 3
39 43 MAJNU 9
40 44 KALI 2

Conclusion

Study on Frieswal cattle maintained at Military Farm Ahmednagar, Deolali and Pimpri in Maharashtra, revealed that effect of Sire and season on CI; Sire, Herd, Period of birth and Parity on LL; Sire, Herd, Period of birth and Parity on SLPY were found to be significant suggesting there is a chance for selective breeding and increased yield from Frieswal by improving such effects through still better managemental practices. The low to moderate heritability estimates for reproduction trait i.e. CI and production trait LL and high estimate of heritability was found for SLPY. High heritability observed in the present study for SLPY presented scope for further improvement through selective breeding of sires. The phenotypic and genotypic correlation between these three traits were positive denoting that selection for improvement in one trait would automatically improve the other production traits due to the correlated response to selection.

Acknowledgements

We are thankful to Director of Military Dairy Farm, Southern Command, Kirkee for providing us the data on Frieswal cattle.

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