Effects of Genetic and Non-Genetic Factors on First Lactation Traits and Replacement Rate and its Components in Crossbred Cattle

Significance statement

Livestock research is now directed towards the investigation of crossbreeding to enhance genetic potential under different ecological niches for different objectives and to transmit a sizeable proportion of genes for milk production. This research study may be helpful in the future for rural development programs at the national and international levels. These research outcomes may serve as base information to the policy-making personnel and academicians for chalking out production strategy and upliftment of the rural economy.

The present study revealed a highly significant effect of the AFC group on milk yield in crossbred cattle. Early calvers produced comparatively lower milk than the optimum calvers. The crossbred herd under the study seems to have moderate productivity but higher AFC, FSP, FDP, and FCI which can be reduced to optimum levels by selection and improved husbandry practices, as there exists huge variation in these traits within the herd. The heritability estimates for first lactation traits were observed low to medium which revealed that genetic variability in these traits was existing and these traits could be improved through genetic selection along with better feeding and management practices. Four pregnancies were required to produce one replacement heifer. Heifers born to younger dams have a higher replacement rate.

Introduction

Crossbreeding was started to enhance genetic potential under different ecological niches for different objectives and to transmit a sizeable proportion of genes for milk production. The basic theme was to confluence the milk yield potential of exotic breeds and stress sustainability and disease resistance capabilities of indigenous breeds within [1] the crossbred progenies, which would be desirable to maintain them under the tropical climatic conditions of India. Crossbreeding has been in practice for several decades as a tool to improve the production performance of native cattle breeds [2]. The appraisal of a breeding program can be done by estimating genetic changes over a period of time. The observed phenotypic change in the performance of a population for an economic trait per year consists of two components viz. genetic trend resulting from the change in mean breeding value due to selection and environmental trend due to cumulative change in various non-genetic factors. The estimates of the trends are essential because they permit a comparison of realized trends with expected ones in the experimental situation and an assessment of progress in a particular trait. The magnitude of genetic trends must be known for comparison of sires. 

The evaluation of crossbred cattle in terms of the production performance traits along with the impact of certain non-genetic factors such as seasons, periods, and parities is essential to formulate breeding and selection strategies. For establishing an effective selection or breeding program, the knowledge of the genetic properties of production traits is of prime importance [3]. The genetic makeup of a population can be examined by considering into heritability and environmental factors affecting the performance of individuals in the herd [4]. The estimates of genetic parameters are very useful for an efficient selection program, which helps in predicting direct and correlated responses to selection. This ultimately helps in choosing a breeding system to be followed for future improvement and in estimating genetic gains. The replacement rate is the function of calf production traits, which are the prenatal calf losses by abortion and stillbirth, and postnatal mortality and culling of heifers from birth to reaching the age at first calving. Several environmental factors affect the replacement rate. The role of different non-genetic factors is of paramount importance to study the replacement rate and its components.

Therefore, the present investigation was planned to estimate the first lactation traits, heritability, replacement rate, and its components in crossbred cattle. It was done to evaluate the effects of genetic and non-genetic factors on these traits. The effects of the period, the season of calving, parity, and a genetic group of sire were also studied.

                      Materials and methods

The data were collected from history-cum-pedigree sheets of 390 crossbred cattle produced by 54 sires from their 2,204 calving records over 36 years (1981-2016) and maintained at the Instructional Dairy Farm (IDF), Pantnagar. The economic traits studied were: age at first calving (AFC), first lactation 305 days milk yield (FLMY-305), first lactation milk yield (FLMY), first lactation length (FLL), first service period (FSP), first dry period (FDP) and first calving interval (FCI). The least-squares technique [5] was employed to study the influence of season, period of calving, and AFC on first lactation traits. The duration of 36 years was divided into 6 periods of 6 years each viz. P1 (1981-1986), P2 (1987-1992), P3 (1993-1998), P4 (1999-2004), P5 (2005-2010) and P6 (2011-2016). Each year was further delineated into 3 seasons viz. S1 (April- June), S2 (July to October), S3 (November- March). 

The different components of replacement rate were considered as losses due to prenatal mortality, frequency of male birth, and female calf mortality and culling from birth to reaching the age at first calving. Seasons, periods, and parity were considered to be different non-genetic factors affecting the replacement rate and its components. The sixth or greater parity of lactation was clubbed into one to get a sufficient number of observations. The effect of season and period of birth, as well as parity of calving, were taken as causal factors for calves replacing parental stock.

                To study the effects of genetic groups of sire and different non-genetic factors such as periods, seasons, and AFC on various production and reproduction traits and to overcome the difficulty of disproportionate sub-class numbers and non-orthogonality, the data was analyzed by using least-squares analysis using the technique developed by Harvey [5]. The model used to analyze the data is given below:

Y_ijklm = µ + P_i + S_j+ M_k + A_l+ e_ijklm

Where, Y_ijklm is an observation on the m^th progeny in the i^th period of j^th sire in k^th season and l^th age group; µ= Overall mean; P_i = Effect of i^th period (i = 1……6); S_j= Random effect of j^th sire (j = 1…….54); M_k= Effect of k^th season (k = 1…3); A_{l =} Effect of l^th age group (l = 1…4); e_ijkl= Random error which is NID (0, σ_e²).

Duncan’s Multiple Range Test (DMRT) modified by Kramer [6] was used to make a pair-wise comparison among the means.

The heritability was estimated by the paternal half-sib correlation (Intra-sire correlation among daughters) method as described by Becker [7] was used as shown below:

Y_ij = µ + S_i + e_ij

Where, Y_ij= Value of j^th progeny under i^th sire; µ= Overall mean; S_i= Effect of i^th sire; e_ij= Random error which is NID (0, σ_e²).

The sire component of variance was estimated as

σ_s²=

σ_e²= MS_e

Where, σ_s² = Sire component of variance; σ_e²= Error component of variance; = Average number of progeny per sire

The following model was used to analyze the different components of the replacement rate concerning non-genetic factors: The analysis of variance was employed as per Tomar et al. [8] using the following model:

                Y _ijkl=μ + P_i + S_j+ L_k+ e_ijkl

Where, Y_ijkl= 1^th observation (replacement rate/its components) from a cow belonging to k^th paritry, calved in j^th season of i^th period; μ= overall mean; P_i = effect of i^th period of calving (i= 1,……6); S_j= effect of j^th season of calving (j= 1,……3); L_k = effect of k^th parity of lactation (j= 1, 2,……6); e_ijkl = random error specific to the particular observation.

Before the estimation of genetic parameters, the data were adjusted for different significant non-genetic factors (season/period of calving and parity effects).

The study was undertaken in compliance of the ethical standards and the study and experimental protocols were approved by the Institutional Animal Ethics Committee of Govind Ballabh Pant University of Agriculture and Technology (GBPUA&T), Pantnagar, India. Moreover, the authors complied with the ARRIVE guidelines.

Results and Discussion

Effect of genetic and non-genetic factors on production and reproduction traits

                The effect of sire had a highly significant effect on age at first calving (AFC). However, the period of birth and season of birth had non-significant effects on AFC (Table 1).

                The effect of sire and season on first lactation 305-day milk yields (FLMY-305)were found significant in the present study (P ≤ 0.05) in crossbred cattle. However, the period of calving and AFC had a non-significant effect on FLMY-305 (Table 1).

                The effects of sire and AFC on first lactation milk yield (FLMY) were found highly significant (P ≤ 0.01) (Table 1). The least squares mean for first lactation milk yield varied from 2224.02 ± 125.46 for 4^th group (AFC ≥ 1500 days) to 2631.04 ± 110.39 days in 3^rd group (AFC = 1301-1500 days) (Table 2). Indicating that as for as first lactation milk yield is concerned the optimum age at first calving range in 1301-1500 days but at the same time it will reduce the herd life and lifetime milk yield. However, the period of calving and the season of calving had a non-significant effect on FLMY (Table 1).

The effect of sire and the period of calving had a significant (P ≤ 0.05) effect on the first lactation length (FLL) (Table 1). The least-squares mean for first lactation length varied from 308.57 ± 15.85 for Period 2 to 433.97 ± 40.79 day for Period 1 (Table 2). Suggesting that management in different periods influenced high lactation length vigorously. However, the effects of season and AFC on FLL were found non-significant (Table 1).

                The effect of sire and the period of calving had a highly significant (P ≤ 0.01) effect on first service period (FSP) in the present study (Table 1). However, the effects of the season of calving and AFC on FSP were found non-significant (Table 1).

                The effect of sire, the period of calving, the season of calving and AFC had a non-significant effect on first dry period (FDP) and first calving interval (FCI) (Table 1).

The sire effects are significant for all the traits under study except FDP and FCI indicating importance of genetic factor (sire) in influencing dairy character. Other non-genetic factors seem to have less influence on the traits under study.

Source of Variation	DF	Mean Sum of Squares (MSS Values)
AFC	FLMY-305	FLMY	FLL	FSP	FDP	FCI
SIRE	53	768091.77**	649106.54*	782209.90**	6651.58*	2523.56**	7020.76	11053.98
PERIOD	5	125936.96	1094322.74	1300544.19	14801.25*	8044.68**	5702.01	11172.96
SEASON	2	440059.56	512017.51*	485836.52	3496.40	1574.55	4896.13	6110.41
AFC	3	236542.35	156324.30	323655.32**	1546.14	4362.12	8121.05	6286.60
ERROR	326	275386.21	484833.42	661950.56	6428.32	1472.34	7042.11	11891.45

Table 1. Analysis of variance (ANOVA) for first lactation production and reproduction traits of crossbred cattle

** P ≤ 0.01; * P ≤ 0.05

Means and heritability estimates of first lactation production and reproduction traits

                The overall least squares mean for AFC was found as 1277.75 ± 101.56 days (Table 2) and the heritability estimates of AFC were found to be 0.31 ± 0.14 (Table 3). The overall least squares mean for FLMY was found to be 2746.23 ± 85.51 kg (Table 2) and the heritability of FLMY was estimated as 0.27 ± 0.07 (Table 3). The overall least squares mean of FDP was observed as 139.15±7.53 days (Table 2) and the heritability estimate of FDP was found to be 0.24 ± 0.13 (Table 3). The overall least-squares mean of FCI was found as 489.01 ± 9.79 days (Table 2) and the heritability estimate of FCI was found to be 0.21 ± 0.09 (Table 3). The moderate value of heritability’s AFC and FLMY suggested that there is a scope of improvement by selection with proper management practices. The moderate value of heritability for FDP and FCI indicates little influence of genetic factors on this trait. Hence, this trait can be improved only through managemental interventions.

The overall least squares mean for FLMY-305 was observed as 2673.48 ± 81.29 kg (Table 2) and the heritability of FLMY-305 was observed as 0.37 ± 0.12 (Table 3). The higher estimates of heritability for this trait indicated that this production trait is more influenced by additive genetic variability and, therefore, there is scope for improvement by selection with proper management practices.

The overall least squares mean forFLL was found to be 346.02 ± 7.44 days (Table 2). The heritability estimate of FLL was found to be 0.17 ± 0.08 (Table 3). The overall least-squares mean of FSP was found as 165.91 ± 5.39 days (2). The heritability estimate of FSP was found to be 0.17 ± 0.11 (Table 3). Since FLL and FSP traits are lowlily heritable it can be improved by employing family selection and better husbandry practices.

It may be seen from Table 2 that the crossbred herd under the study had higher AFC, FSP, FDP, and FCI which can be reduced to optimum levels by selection and improved husbandry practices, as there exists huge variation in these traits within the herd. The heritability estimates for most of traits are moderate indicating that there exists scope for improvement in these traits through genetic selection.

Source

No. of obs.

AFC (days)

FL305DMY (kg)

FLMY (kg)

FLL (days)

FSP (days)

FDP (days)

FCI (days)

Overall mean

390

1277.75 ± 101.56

2673.48 ± 81.29

2746.23 ± 85.51

346.02 ± 7.44

245.91 ± 5.39

139.15 ± 7.53

489.01 ± 9.79

Season

S1 (Summer)

69

1233.71 ± 117.34

2740.47 ± 112.64

2807.95 ± 124.95

352.78 ± 11.66

165.91 ± 5.39

148.22 ± 12.04

480.00 ± 15.65

S2 (Rainy)

96

1250.61 ± 111.70

2583.40 ± 102.05

2658.44 ± 111.85

338.85 ± 10.29

250.87 ± 6.37

135.46 ± 10.58

490.72 ± 13.75

S3 (Winter)

225

1348.93 ± 104.87

2696.57 ±  88.38

2772.31 ± 94.64

346.42 ± 8.45

244.00 ± 5.72

133.77 ± 8.61

496.31 ± 11.19

Period

P1 (1981-1986)

8

1082.35 ± 281.49

2363.53 ± 357.69

2509.24 ± 415.90

433.97 ± 40.79

231.21 ± 19.94

87.01 ± 42.65

587.43 ± 55.42

P2 (1987-1992)

49

1376.97 ± 136.76

2351.59 ± 146.20

2368.74 ± 165.75

308.57 ± 15.85

258.52 ± 8.60

148.63 ± 16.47

461.67 ± 21.40

P3 (1993-1998)

62

1283.68 ± 136.38

2639.79 ± 145.58

2680.56 ± 165.01

351.47 ± 15.77

265.79 ± 8.56

130.65 ± 16.39

475.55 ± 21.30

P4 (1999-2004)

131

1290.74 ± 125.57

2682.06 ± 127.31

2734.46 ± 142.90

325.57 ± 13.51

265.76 ± 7.63

155.60 ± 14.00

480.77 ± 18.20

P5 (2005-2010)

129

1229.35 ± 130.88

2795.80 ± 136.40

2945.08 ± 153.92

323.71 ± 14.64

261.45 ± 8.09

156.22 ± 15.19

480.21 ± 19.75

P6 (2011-2016)

11

1403.45 ± 202.15

3208.12 ± 245.75

3239.32 ± 284.16

332.80 ± 27.72

192.70 ± 13.87

156.80 ± 28.94

448.44 ± 37.61

AFC

A1 (≤1100)

141

_

2213.21 ± 74.32

2245.65 ± 112.36

320.49 ± 6.13

168.24 ±11.35

132.32 ±6.15

439.26 ±10.92

A2 (1101-1300)

112

_

2135.32 ± 80.42

2441.42 ± 99.01

318.85 ± 5.29

177.15 ± 11.56

127.13 ± 6.24

452.24 ± 7.96

A3 (1301-1500)

80

_

2225.24 ± 78.31

2631.04 ± 110.39

316.76 ± 6.54

174.57 ± 12.63

123.78 ± 6.38

457.54 ± 11.03

A4 (≥1500)

57

_

2336.01 ± 76.32

2224.02 ± 125.46

318.64 ± 7.47

185.10 ± 12.35

146.98 ± 8.32

468.47 ± 12.65

Table 2. Least-squares means and standard errors for first lactation production and reproduction traits of crossbred cattle

Traits	h2 ± S.E.
Age at first calving (AFC)	0.31 ± 0.14
First lactation 305 day milk yield (FLMY-305)	0.37 ± 0.12
First lactation milk yield (FLMY)	0.27 ± 0.07
First lactation length (FLL)	0.17 ± 0.08
First service period (FSP)	0.17 ± 0.11
First dry period (FDP)	0.24 ± 0.13
First calving interval (FCI)	0.21 ± 0.09

Table 3. Estimates of heritability of first lactation production and reproduction traits along with standard error in   crossbred cattle

Effect of non-genetic factors on replacement rate and its components

The seasons, period and parity had a significant (P ≤ 0.05)effect on pre-natal calf losses (abnormal births) in the present study (Table 4). The pre-natal calf losses due to abnormal births in crossbred cattle (Table 5) were observed to be varying from 8.32 percent in rainy season to 10.11 percent in the summer season. The pre-natal calf losses due to abnormal births in crossbred cattle (Table 5) were observed to be varying from 6.71 percent in Period VI to 10.79 percent in Period V, showing no pattern during different periods. Furthermore, the sudden increase in the incidence of pre-natal calf losses due to abnormal birth during II period could be due to some unpredicted managemental or environmental or health problems in the herd. The pre-natal calf losses due to abnormal births in crossbred cattle (Table 5) were observed to be varying from 5.34 percent (Parity 1) to 13.84 percent (Parity 4). There is no definite trend in pre-natal calf losses due to abnormal births among parity of calving on this trait.

The seasons had a non-significant effect on mortality ratesin the present study (Table 4). The period and parity had a highly significant (P ≤ 0.01)effect on mortality ratesin the present study (Table 4). The mortality ratesin female calves in crossbred cattle (Table 5) were observed to be varying from 14.57 percent during Period IV to 21.62 percent during Period II. These significant period differences in mortality rates of female calves could be attributed to the managemental and environmental reasons. The mortality ratesin female calves in crossbred cattle were observed to be varying from 6.07 percent (Parity 1) to 24.69 percent (Parity 6) (Table 5).

The seasons and parity had a non-significant effect on culling rates(Table 4). The period had highly significant (P ≤ 0.01)effect on culling rates (Table 4). The culling ratein female calves in crossbred cattle (Table 5) was observed to be varying from 21.95 percent in VI Period and 43.24 percent in II Period. The culling among the heifers is generally practiced as per the need of the herd and type of stock available for replacement. Therefore, generally culling is not practiced uniformly over different periods, which may result into significant variation in the culling of heifers.

The seasons, period and parity had a highly significant (P ≤ 0.01)effect on replacement rates on a female calf basis (Table 4). The replacement rates on female calf basis were observed to be varying from 46.04 percent in summer season to 61.03 percent in rainy season (Table 5). The replacement rates on female calf basis were observed to be varying from 35.14 percent in II Period to 60.98 percent in VI Period (Table 5). The lowest replacement rate during second period could be due to the observed higher mortality and culling rates among female calves. The replacement rates on female calf basis were observed to be varying from 20.99 percent in sixth Parity to 78.50 percent in first Parity (Table 5). Though there was no definite trend between dam’s parity and replacement rate.

The seasons had a significant (P ≤ 0.05)effect on replacement rates on total pregnancies basis (Table 4). The replacement rates on female calf basis were observed to be varying from 19.84 percent in the summer season to 28.60 percent in rainy season (Table 5). The period had highly significant (P ≤ 0.01)effect on replacement rates on total pregnancies basis (Table 4). The replacement rates on female calf basis were observed to be varying from 14.94 percent in 2^nd Period to 30.48 percent in the 6^th Period (Table 5). Significantly lower replacement rates during record period second may be because of very high abnormal births, death and culling rate during this period. The parity had non-significant effect on replacement rates on total pregnancies basis (Table 4). The replacement rates on female calf basis were observed to be varying from a lowest of 9.88 percent in sixth Parity to a highest value of 40.78 percent in third Parity (Table 5). No definite trend was observed for replacement rates among different dam^’s parities.

From the foregoing discussion on replacement rates computed on total female calves born and total pregnancies, it could be concluded that about 4 pregnancies are required to produce one heifer that becomes the replacement of the old and low productive cow against a norm of 2-3 pregnancies. Furthermore, in a progeny testing program, it can be recommended that about 38 pregnancies are required from each sire out of which about 16 should be turned into female births, so that about 10-12 daughters per sire may be available for performance recording.

The average incidences of pre-natal calf losses due to abnormal births in crossbred cattle were observed to be 9.12 percent among 2204 total births (Table 5). These differences in prenatal calf losses could be attributed to genetic and managemental or environmental reasons.  The average mortality rates among the crossbred female calves born from birth to AFC were found to be 15.70 percent (Table 5). The overall female culling rate up to AFC, computed from total female calves born were estimated to be 30.15 percent (Table 5). The overall replacement rate on the basis of total female calves born were estimated to be 54.18 percent (the proportion of the female calves that reached to the AFC) and the rest 45.82 percent of female calves were lost due to their death and culling from the herd (Table 5). These values indicated that about 1/2 of the total females born reached to AFC and became the replacement to older cows in the herd. The overall replacement rates computed on the basis of total pregnancies in this crossbred herd under study were found to be 25.27 percent (Table 5). This observation indicated that about 4 pregnancies are required to produce one replacement heifer.

It may be concluded that replacement rates and its component traits are affected by periods, seasons, and parity. As expected, the heifer borne to younger dams have higher replacement rates.

Source of Variation	DF	MSS
Abnormal birth	Female mortality	Female culling	Replacement rate
FC	TC(TP)
Period	5	0.6331*	0.4913**	0.7910**	2.3891**	1.6367**
Season	2	0.4133*	0.4132	0.1043	0.7832*	0.8754*
Parity	5	0.3139*	0.3011*	0.1324	0.5979*	0.5706
Error	2191	0.1331 (2191)	0.2976 (1028)	0.1013 (1028)	0.1653 (1028)	0.1950 (2191)

         Table 4. Analysis of variance (ANOVA) for showing the effect of non-genetic factors on replacement rate and its component of crossbred cattle

** P ≤ 0.01; * P ≤ 0.05

 Figures in Parenthesis are the error degree of freedom, FC=Female Calf Basis, TP=Total Calf Basis (total Pregnancies)

Effect	Total births	Abnormal birth	Normal births	Female calf	Replacement Rate (%)
Total	Male	Female	Died	Culled	Retained	FC	TC (TP)
Overall	2204	201 (9.12)	2003 (90.88)	975 (48.68)	1028 (51.32)	161 (15.70)	310 (30.15)	557	54.18	25.27
Season
Winter	427	39 (9.13)	388 (90.87)	163 (42.01)	225 (57.99)	33 (14.66)	74 (32.89)	118	52.44	27.63
Summer	791	80 (10.11)	711 (89.89)	370 (52.32)	341 (47.96)	56 (16.42)	128  (37.53)	157	46.04	19.84
Rainy	986	82 (8.32)	904 (91.68)	442 (48.89)	462 (51.10)	72 (15.58)	108  (23.37)	282	61.03	28.60
Period
1981-86	26	2 (7.69)	24 (92.31)	14 (58.33)	10 (41.67)	0 (0.00)	4 (40.00)	6	60.00	23.08
1987-92	87	9 (10.34)	78 (89.66)	41 (52.56)	37 (47.44)	8 (21.62)	16 (43.24)	13	35.14	14.94
1993-98	351	28 (7.98)	323 (92.02)	165 (51.08)	158 (48.92)	24 (15.18)	27 (17.08)	107	67.72	30.48
1999-04	479	46 (9.60)	433 (90.40)	186 (42.96)	247 (57.04)	36 (14.57)	98 (39.67)	113	45.75	23.59
2005-10	769	83 (10.79)	686 (89.21)	356 (51.89)	330 (48.10)	51 (15.45)	111 (33.63)	168	50.90	21.85
2011-16	492	33 (6.71)	459 (93.29)	213 (46.41)	246 (53.59)	42 (17.03)	54 (21.95)	150	60.98	30.48
Parity
1	412	22 (5.34)	390 (94.66)	176 (45.13)	214 (54.87)	13 (6.07)	33 (15.42)	168	78.50	40.78
2	413	28 (6.78)	385 (93.22)	204 (52.99)	181 (47.01)	26 (14.36)	42 (23.20)	113	62.43	27.36
3	427	43 (10.07)	384 (89.93)	150 (39.06)	234 (60.94)	40 (17.09)	34 (14.53)	160	68.38	37.47
4	354	49 (13.84)	305 (86.16)	168 (55.08)	137 (44.92)	30 (21.89)	67 (48.90)	40	29.19	11.30
5	254	27 (10.63)	227 (89.37)	127 (55.95)	100 (44.05)	12 (12.00)	46 (46.00)	42	42.00	16.54
>6	344	32 (9.30)	312 (90.70)	150 (48.08)	162 (51.92)	40 (24.69)	88 (54.32)	34	20.99	9.88

Table 5. Per cent contribution of different components of replacement rate in relation to non-genetic factors

FC=Female Calf Basis, TP=Total Calf Basis (Total Pregnancies)   

Figures in parenthesis are percentage values

The effect of sire had a highly significant effect on AFC in the present study. Similarly, significant effects of sire were reported by Nehra et al. [9] in Karan Fries cattle. On the other hand, non-significant effects were observed by Dubey and Singh [10] in crossbred cattle.  The period of birth had a non-significant effect on AFC in the present study. Similar results were also reported on this trait by Nehra et al. [9] in Karan Fries cattle. However, a significant effect of the period of birth on AFC was reported on this trait by Mukherjee [11] in Frieswal cattle. The season of calving had a significant (P ≤ 0.05) effect on the FLMY-305 in the present study. Similar results were also reported by Dash et al. [12] in Karan Fries cattle. However, the non-significant effects were reported on this trait by Nehra et al. [9] in Karan Fries. The period of calving had a non- significant effect on the FLMY-305. Similar results were reported on the period of calving by Nehra et al. [9] in crossbred cattle. A significant effect was also reported on the period of calving by Dash et al. [12] in Karan Fries cattle. A significant effect was reported on AFC by Mukherjee [20] in Frieswal and Nehra et al. [22] in Karan Fries cattle. The effects of sire on FLMY were found highly significant (P ≤ 0.01) in the present study. Similarly, significant effects of sire were also reported on this trait by Mukherjee [11] in Frieswal cattle, Nehra et al. [9] in Karan Fries cattle. The period of calving had a non-significant effect on the FLMY. Similar results were reported on this trait by Saha et al. [13] in Karan Fries. The season of calving had a non-significant effect on FLMY. Similar results were reported by Saha et al. [13] in Karan Fries. However, significant effects were reported on this trait by Dash et al. [12] in Karan Fries cattle. The AFC had a highly significant (P ≤ 0.01) effect on AFC. The least-squares means for FLMY varied from 2224.02 ± 125.46 for the 4th group (AFC ≥ 1500 days) to 2631.04 ± 110.39 days in the 3^rd group (AFC = 1301-1500 days). Indicating that as for as FLMY is concerned the optimum AFC ranges in 1301-1500 days but at the same time, it will reduce the herd life and lifetime milk yield. Similar results were too described by Saha et al. [13] in Karan Fries. The period of calving had a significant (P ≤ 0.05) effect on the FLL. The least-squares mean for the FLL varied from 308.57 ± 15.85 for Period 2 to 433.97 ± 40.79 days for Period 1. Suggesting that management in different periods influenced high lactation length vigorously. Similar results were reported in this trait by Nehra et al. [9] and Dash et al. [12] in Karan Fries cattle. However, non-significant effects were reported by Mukherjee [11] in Frieswal cattle. The effects of the season of calving on FLL were found non-significant as can be seen from Table 2. Similar results were reported on this trait by Nehra et al. [9] in Karan Fries. However, significant effects were reported on this trait by Dash et al. [12] in Karan Fries cattle. Similarly, a significant effect was reported on AFC by Saha et al. [13] in Karan Swiss cattle. The effect of sire had a highly significant (P ≤ 0.01) effect on the FSP. Similarly, significant effects of sire were reported by Bhatia and Pandey [14] in crossbred cattle. However, the non-significant effects were reported by Mukherjee [11] in Frieswal cattle. The effect of the period of calving on the FSP was found to be highly significant. The least-squares means for the FSP varied from 192.70 ± 13.87 for Period-6 to 265.79 ± 8.56 days for Period-3. Similar results were reported in this trait by Divya [15] in Karan Fries cattle. However, the non-significant effects of the period on service period were reported on this trait by Bhatia and Pandey [14] in HF cross and Saha et al. [13] in Karan Fries cattle. The effects of season of calving on the FSP were found non-significant. Similar results were also reported in this trait by Divya [15] in Karan Fries cattle. However, significant effects were reported on this trait by Saha et al. [13] in crossbred cattle. The effect of sire had a non-significant effect on the FDP in the present study. Similarly, non-significant effects of sire were reported by Mukherjee [11] in Frieswal. However, significant effects were reported by Saha et al. [13] in Karan Fries cattle. The season of calving had a non-significant effect on the FDP as can be seen from Table 1. Similar results were also reported in this trait by Singh and Gurnani [16] in Karan Fries cattle. The AFC group had a non-significant effect on the FDP. Similar results were reported in this trait by Saha et al. [13] in Karan Fries cattle. However, the significant effects were reported by Mukherjee [11] in Frieswal. The effects of the period of calving on the FCI were found non-significant. Similar results were reported in this trait by Akhtar et al. [17] in HF crosses. However, the significant effects of the period on FCI were reported by Nehra et al. [22] in Karan Fries cattle.  The season of calving had a non-significant effect on the FCI. Similar results were reported in this trait by Nehra et al. [9] in Karan Fries cattle. However, significant effects were reported on this trait by Mukherjee [11] in Frieswal cattle, and Hammoud et al. [18] in Holstein Friesian cross.

The sire effects are significant for all the traits under study except FDP and FCI indicating the importance of genetic factor (sire) in influencing dairy character. Other non-genetic factors seem to have less influence on the traits under study.

The overall least-squares means for AFC was found as 1277.75 ± 101.56 days. The result of the present finding is in close agreement with the findings of Dubey and Singh [10] in crossbreds. However, lower values of AFC have been observed by Nehra et al. [9] in Karan Fries cattle. The heritability estimates of AFC were found to be 0.31 ± 0.14 (Table 3). Similar findings were reported by Mukherjee [11] in crossbred cattle. Higher estimates of heritability of this trait were reported by Nehra [19] in crossbred cattle, while lower estimates were reported by PDC AR [20] in crossbred cattle.  The moderate value of heritability for this trait suggested that improvement could be possible in this trait by genetic selection along with better management practices. The overall least-squares mean for the FLMY-305was observed as 2673.48 ± 81.29 kg. The results of the present study were similar to those reported by Rao et al. [21] in crossbreds. The present value was lower to Karan Fries [22], Vrindavani [23] and Chawla et al. [24] crossbred cows under farm conditions and higher to HF×Deoni crossbred [25] cows, Dash et al. [12] and Nehra et al. [9] Karan Fries cattle. The heritability of the FLMY-305 was observed as 0.37 ± 0.12. Similar estimates were reported by Nehra [19] and Dash et al. [12] in Karan Fries cattle. However, a comparatively lower value was reported by Rashia [26] in crossbred cattle. The higher estimates of heritability for this trait indicated that this production trait is more influenced by additive genetic variability and, therefore, there is scope for improvement by selection with proper management practices. The overall least-squares mean for the FLMY was found to be 2746.23 ± 85.51 kg. The results of the present study were similar to those reported by Bhattacharya et al., [27] in Karan Fries.However, the higher values of first lactation milk yield have been observed by Mukherjee [11] in Frieswal. Hadge et al. [28] reported a lower estimate for FLMY for Jersey crossbred and Kharkar et al. [29] also reported a lower estimate for first lactation milk yield in Jersey x Red Kandhari than the present study. The heritability of the first lactation milk yield was estimated as 0.27 ± 0.07. However, lower values were estimated by Mukherjee [11] in crossbred cattle. The overall least-squares mean for the FLL was found to be 346.02 ± 7.44 days. The present value was in agreement with those reported in Frieswal cow (342.97 ± 12.14 days) by Minj et al. [30]. The present value was lower for Karan Fries [22] and Vrindavani [23] crossbred cows under farm conditions and higher for HF×Deoni crossbred [25] cows. However, the higher values of FLL have been observed by Nehra [19] in Karan Fries cattle while Kharkar et al. [29] reported lower lactation length in Jersey x Red Kandhari cattle than the present study. The FLL being the period of actual milk production, farmers try to increase it as much as possible. Simultaneously, nowadays farmers are also aware of the importance of an optimum dry period. Hence, there is always a compromise between these two traits. It has been observed that some farmers deliberately go on milking their pregnant cows for which they are not interested to keep their herd in the next lactation [30]. The heritability estimate of first lactation length was found to be 0.17 ± 0.08. Almost similar estimates were reported by Nehra [19] in crossbred cattle. However, the lower values than the present study were reported by Dash et al. [12], in crossbred cattle. Since this trait is lowly heritable it can be improved by employing family selection and better husbandry practices. The overall least-squares mean of the FSP was found as 165.91 ± 5.39 days (Table 1). The estimate was quite similar to those reported by Mukherjee [11] in Frieswal. However, the lower values of the FSP have been observed by Divya [15] in Karan Fries cattle. As the trait is governed by non-genetic factors, hence managemental practices may be improved for lowering the FSP. The overall least-squares mean of the FDP was observed as 139.15 ± 7.53 days. The estimates were similar to those reported by Mukherjee [11] in Frieswal. However, the lower values of the FDP have been observed by Kharkar et al. [29] in Jersey x Red Kandhari cattle. The heritability estimate of the FSP and FDP was found to be 0.24 ± 0.13 and 0.17 ± 0.11. The estimates of heritability similar to the present study were observed by Saha et al. [13] in crossbred cattle. However, the lower estimates of heritability than the present study were reported by Mukherjee [11] in crossbred cattle and the higher estimates of heritability for this trait than the present study were observed by Gaur [32] in crossbred cattle. The moderate value of heritability for this trait indicates little influence of genetic factors over this trait. Hence, this trait can be improved only through managemental interventions. The overall least-squares mean of the FCI was found as 489.01 ± 9.79 days. The lower values of the FCI have been observed by Nehra et al. [9] in Karan Fries cattle. Higher values than the present study were observed by Yadav et al. [33] in crossbred cattle. The heritability estimate of the FCI was found to be 0.21 ± 0.09. The estimates of heritability similar to the present study were reported by Nehra [19] in crossbred cattle. Higher values were reported by Saha et al. [13] in crossbred cattle, while lower values than the present study were reported by Mukherjee [11] in crossbred cattle.

The crossbred herd under the study had higher AFC, FSP, FDP, and FCI which can be reduced to optimum levels by selection and improved husbandry practices, as there exists huge variation in these traits within the herd. The heritability estimates for most of the traits are moderate indicating that there exists scope for improvement in these traits through genetic selection.

                The period had a significant (P ≤ 0.05) effect on pre-natal calf losses in the present study. The pre-natal calf losses due to abnormal births in crossbred cattle were observed to be varying from 6.71 percent in period VI to 10.79 percent in period V, showing no pattern during different periods. Similarly, significant effects of the period were reported by Singh et al. [34] in Holstein x Sahiwal. Furthermore, the sudden increase in the incidence of pre-natal calf losses due to abnormal birth during the II period could be due to some unpredicted managemental/environmental or health problems in the herd.  The seasons had a significant (P ≤ 0.05) effect on pre-natal calf losses in the present study. The pre-natal calf losses due to abnormal births in crossbred cattle were observed to be varying from 8.32 percent in the rainy season to 10.11 percent in the summer season. Similarly, significant effects of seasons were reported by Singh et al. [34]. However, non-significant season effects on pre-natal calf losses due to abnormal births were observed by Singh et al. [34] in crossbred cattle.  The parity had a significant (P ≤ 0.05) effect on pre-natal calf losses in the present study. The pre-natal calf losses due to abnormal births in crossbred cattle were observed to be varying from 5.34 percent (Parity 1) to 13.84 percent (Parity 4). There is no definite trend in pre-natal calf losses due to abnormal births among parity of calving on this trait. Similarly, significant effects of parity were reported by Mukherjee and Tomar [35] in Karan Swiss cattle. However, non-significant parity effects on pre-natal calf losses due to abnormal births were observed by Singh [31] in crossbred cattle. There is no definite trend in pre-natal calf losses due to abnormal births among parity of calving on this trait.The period had a highly significant (P ≤ 0.01) effect on mortality rates in the present study (Table 4). The mortality rates in female calves in crossbred cattle were observed to be varying from 14.57 percent during Period IV to 21.62 percent during Period II. These significant period differences in mortality rates of female calves could be attributed to management and environmental reason. Similarly, significant effects of the period were reported by Singh [31] in Karan Fries cattle. Seasons had a non-significant effect on mortality rates in the present study. Similarly, non-significant effects of seasons were reported by Singh [31] for crossbred cattle herds. However, the significant season effects on mortality rates have been observed by Singh et al. [34] in crossbred calves. Parity had a significant (P ≤ 0.05) effect on mortality rates in the present study (Table 4). The mortality rates in female calves in crossbred cattle were observed to be varying from 6.07 percent (Parity 1) to 24.69 percent (Parity 6). Similarly, significant effects of parity were reported by Singh et al. [34] for crossbred female calves. However, the non-significant parity effects on mortality rates have been observed by Singh [31] in Karan Fries cattle. Period of birth had a highly significant (P ≤ 0.01) effect on culling rates in the present study (Table 5). The culling rates in female calves in crossbred cattle were observed to be varying from 21.95 percent in Period VI and 43.24 percent in Period II. The culling among the heifers is generally practiced as per the need of the herd and the type of stock available for replacement. Therefore, generally culling is not practiced uniformly over different periods, which may result in a significant variation in the culling of heifers. Similarly, significant effects of the period were reported by Singh [31] for Karan Fries’s female calves. Seasons had a non-significant effect on culling rates in the present study. Similarly, non-significant effects of seasons were reported by Singh [31] for Karan Fries calves. Parity had a non-significant effect on the culling rate in the present study. Similarly, non-significant effects of parity were reported by Singh [31] for Karan Fries cattle. Period of birth had a highly significant (P ≤ 0.01) effect on replacement rates on the female calf basis in the present study. The replacement rates on the female calf basis were observed to be varying from 35.14 percent in II Period to 60.98 percent in Period VI. The lowest replacement rate during the second period could be due to the observed higher mortality and culling rates among female calves. Similarly, significant effects of the period were reported by Singh [31] in Karan Fries. The season had a significant (P ≤ 0.05) effect on replacement rates on the female calf basis in the present study. The replacement rates on the female calf basis were observed to be varying from 46.04 percent in the summer season to 61.03 percent in the rainy season. On the other hand, non-significant effects were observed by Singh [31] in Karan Fries cattle. Parity had a significant (P ≤ 0.05) effect on replacement rates on the female calf basis in the present study. The replacement rate on the female calf basis was observed to be varying from 20.99 percent in sixth Parity to 78.50 percent in first Parity. Though there was no definite trend between the dam’s parity and replacement rate. On the other hand, non-significant effects were observed by Singh [31] in Karan Fries cattle. Period of birth had a highly significant (P ≤ 0.01) effect on replacement rates on total pregnancies basis in the present study. The replacement rates on the female calf basis were observed to be varying from 14.94 percent in Period II to 30.48 percent in Period VI. Significantly lower replacement rates during the recording period II may be because of very high abnormal births, death, and culling rate during this period. Similarly, significant effects of the period were reported by Singh [31] for Karan Fries cattle. Seasons had a significant (P ≤ 0.05) effect on replacement rates on total pregnancies basis in the present study. The replacement rates on the female calf basis were observed to be varying from 19.84 percent in the summer season to 28.60 percent in the rainy season. On the other hand, non-significant effects were observed by Singh [31] in crossbred cattle. Parity had a non- significant effect on replacement rates on total pregnancies basis in the present study. The replacement rates on a female calf basis were observed to be varying from the lowest of 9.88 percent in the sixth Parity to the highest value of 40.78 percent in the third Parity. No definite trend was observed for replacement rates among different dam’s parities. Similarly, significant effects of the period were reported by Singh [31] in Karan Fries cattle.

It may therefore be concluded that about 4 pregnancies are required to produce one heifer that becomes a replacement of the old and low-productive cow against a norm of 2-3 pregnancies. Furthermore, in a progeny testing program, it can be recommended that about 38 pregnancies are required from each sire out of which about 16 should be turned into female births, so that about 10-12 daughters per sire may be available for performance recording.

The average incidences of pre-natal calf losses due to abnormal births in crossbred cattle were observed to be 9.12 percent among 2,204 total births.A higher incidence of pre-natal calf losses than this present estimate was observed by Singh et al. [34] in HF × Sahiwal cattle. However, lower pre-natal calf losses due to abnormal births were observed by Singh [31] in Karan Fries. These differences in prenatal calf losses could be attributed to genetic and managemental or environmental reasons. The average mortality rate among the crossbred female calves born from birth to age at first calving was found to be 15.70 percent.The overall female culling rate up to the age at first calving, computed from total female calves born was estimated to be 30.15 percent. The higher culling rates among female calves than the present study were reported by Singh [31] in Karan Fries.The overall replacement rate based on total female calves born was estimated to be 54.18 percent (the proportion of the female calves that reached the AFC) and the rest 45.82 percent of female calves were lost due to their death and culling from the herd (Table 4). These values indicated that about 1/2 of the total females born reached AFC and became the replacement to older cows in the herd. The lower replacement rates among female calves than the present study were reported by Singh [31] in Karan Fries cattle. The overall replacement rates computed based on total pregnancies in this crossbred herd under study were found to be 25.27 percent. This observation indicated that about 4 pregnancies are required to produce one replacement heifer. 

It may be concluded that replacement rates and their component traits are affected by periods, seasons and parity. As expected, the heifers borne to younger dams have higher replacement rates.

Conclusion

Based on ours finding the ANOVA revealed that there were no significant differences for almost all the first lactation traits understudy for different seasons and periods which were obvious because standard practices were adopted at the farm and adjustments to any situations were made as and when required. A highly significant effect of sire on almost all the first lactation traits indicated that superior sires had been used from time to time for the overall improvement of the herd. The study revealed a highly significant effect of the AFC group on milk yield in crossbred cattle. Early calvers produced comparatively lower milk than the optimum calvers. The crossbred herd under the study seems to have moderate productivity but higher AFC, FSP, FDP, and FCI which can be reduced to optimum levels by selection and improved husbandry practices, as there exists huge variation in these traits within the herd. The heritability estimates for first lactation traits were observed low to medium which revealed that genetic variability in these traits was existing and these traits could be improved through genetic selection along with better feeding and management practices. Four pregnancies were required to produce one replacement heifer. Heifers born to younger dams have a higher replacement rate. 

Acknowledgments

The authors acknowledge the help received from Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India, for conducting this study.

V.A.R.P. conducted research as M.V.Sc. student. R.K.S. and J.L.S. had conceived the hypothesis and designed the study plan.  M.K.S. and R.K.S. analyzed data, and drafted and edited the manuscript. S.K. and V.A.R.P. had collected the data and undertaken investigations. The competent authority of the University has given permission for the publication

Indian Council of Agricultural Research, New Delhi, India provided financial assistance under a “Development Grant” to the University for strengthening of teaching.

                The authors declare no competing interests.

Correspondence and requests for materials should be addressed to M.K.S

References

1. Patoo RA, Singh DV, Singh, SK, Singh, MK Singh AK, Kaushal S (2016) Colostrum and Milk Composition during postpartum period in Hill cow, Sahiwal and Crossbreds cow. Indian Journal of Animal Research, 50(2):211-214.
2. Patoo RA, Singh DV, Singh SK, Chaudhari BK, Singh AK, Singh MK, Kaushal S (2016) Comparative study on some morphological and performance traits of hill cattle, Sahiwal and crossbred cattle. Indian Journal of Animal Research 50(2):148-151.
3. Chaudhari M, Kumar R, Khanna AS, Dalal DS,  Jakhar A (2013) Genetic studies on reproduction traits in crossbred cattle. Haryana Vet 52:75-78.
4. Falconer DS, Mackay TFC (1997) An Introduction to Quantitative Genetics. Addison Wesley Longman Ltd. UK.
5. Harvey WR (1990) Users Guide for LSMLMW, Mixed Model Least Squares and Maximum Likelihood Computer Program. PC-2 Version. Ohio State University, Columbus, USA.
6. Kramer CY (1957) Extension of multiple range tests to group correlated adjusted means. Biometrics 13:13-17.
7. Becker WA (1975) Manual of Quantitative Genetics. Washington State Univ. Press, Pullman.
8. Tomar SS, Arun K, Ajay K (1991). New approach for genetic analysis of proportion data without transformation. Asian Journal of Dairy Research 10:87-90.
9. Nehra M, Singh A, Gandhi RS, Chakravarty AK, Gupta AK., Sachdeva GK (2013). Phenotypic, genetic and environmental trends in milk yield and milk production efficiency traits in Karan Fries cattle. Indian J Ani Res 47(3):402-406.
10. Dubey PP, Singh CV (2005) Estimates of genetic and phenotypic parameters considering first lactation and lifetime performance traits in Sahiwal and crossbred cattle. Indian J Ani Sci 75(11):1289-1294.
11. Mukherjee S (2005) Genetic evaluation of Frieswal cattle. Thesis, Ph.D. National Dairy Research Institute Karnal, India.
12. Dash SK, Gupta AK, Singh A, Chakravarty AK, Valsalan J, Shivahre PR, Divya P (2016) Analysis of genetic trend in fertility and production traits of Karan Fries (Holstein Friesian crossbred) cattle using BLUP estimation of breeding values. Indian J Dairy Sci 69(2):234-236.
13. Saha S, Joshi BK Singh A (2010) Generation-wise genetic evaluation of various first lactation traits and herd life in Karan Fries cattle. Indian J Ani Sci 80(5):451–456.
14. Bhatia ST, Pandey RS (1990) Factors affecting service period in crossbred dairy cows. Asian J Dairy Res 9(1):11-14.
15. Divya P (2012) Single versus multi-trait models for genetic evaluation of fertility traits in Karan Fries cattle. Thesis, M.V.Sc. National Dairy Research Institute, Karnal, India (2012).
16. Singh MK, Gurnani M (2004) Performance evaluation of Karan Fries and Karan Swiss cattle under the closed breeding system. Asian Australasian J Anim Sci 17(1):1-6.
17. Akhtar J, Singh M, Kumar D, Sharma RK (2003) Factors affecting economic traits in crossbred cattle. Indian J Ani Sci 73(4):464-465.
18. Hammoud MH, El-Zarkouny SZ, Oudah EZM (2010) Effect of sire, age at first calving, season and year of calving and parity on reproductive performance of Friesian cows under semiarid conditions in Egypt. Archiva Zootechnica 13(1):60-65.
19. Nehra M (2012) Genetic analysis of performance trends in Karan-Fries cattle. Thesis, M.Sc. National Dairy Research Institute (Deemed University), Karnal, India.
20. Project Directorate on Cattle (2003-04) Annual Report for Meerut.
21. Rao MK, Reddy A,  Bhaskar BV (2000) Performance of crossbred dairy cattle in Farmers herd. Indian J Ani Sci 70(6):608-612.
22. Japheth KP, Mehla RK, Imtiwati, Bhat SA (2015) Effect of non-genetic factors on various economic traits in Karan Fries crossbred cattle. Indian J Dairy Sci 68(2):163-169.
23. Singh RR, Dutt T, Kumar A, Tomar AKS, Singh M (2011) On-farm characterization of  Vrindavani cattle in India. Indian J Anim Sci 81(3):267-271.
24. Chawala AR, Banos G, Komwihangilo DM, Peters A, Chagunda MGG (2017) Phenotypic and genetic parameters for selected production and reproduction traits of Mpwapwa cattle in low-input production systems. South African Journal of Animal Science 47(3):307-319.
25. Wondifraw Z, Thombre BM, Bainwad DV (2013) Effect of non-genetic factors on milk production of Holstein Friesian × Deoni crossbred cows. Afr J Dairy Farming Milk Prod 1(4):79-84.
26. Rashia N (2010) Genetic evaluation of the lactation curve in Karan Fries cattle. Thesis. Ph.D. NDRI (Deemed University), Karnal, India.
27. Bhattacharya TK, Patil VK, Joshi JD, Mahapatra AS, Badola S (2002) Dairy performance of Tharparkar, Holstein-Friesian and their crosses. Indian J Ani Sci 72(2):154-156.
28. Hadge MR, Kuralkar SV, Ali SZ, Kharkar KP, Sawaimul AD (2012) Genetic studies on performance traits of Sahiwal and Sahiwal x Jersey crossbred cows. Indian J Anim Res 46:92-94.
29. Kharkar K, Kuralkar SV, Hadge MR (2015) Productive performance of Red Kandhari and its Jersey crosses in different Lactations. Indian J Anim Res 49(5):599-601.
30. Minj SK, Singh DV, Singh CB, Prasad SK, Sanjay K, Anil K (2017) First lactation production traits of Frieswal cows under field conditions. Indian J Anim Prod Mgmt 33(3-4), 99-105.
31. Singh L (2001) Genetics of replacement rate in Karan Fries cattle. Ph.D. Thesis, NDRI, Deemed University, Karnal, India.
32. Gaur GK (2003) Estimating breeding values of Frieswal bulls for the performance traits: Indian J Ani Sci, 73(1):79-82.
33. Yadav JS, Dutt G, Yadav MC (2004) Genetic studies of some lactation traits in crossbred cows. Indian J Ani Sci 74(2):1232-1233.
34. Singh CV, Kumar Dhirendra, Kumar D, Singh H (2002) Genetic and non-genetic variation in components of replacement rates in crossbred and Sahiwal cattle. Indian J Dairy Sci 55(4):244-247.
35. Mukherjee K, Tomar SS (2000) Genetic and non-genetic factors affecting abnormal births in Karan Swiss cattle.  Indian J Ani Res 34(1):29-32.