The present study was conducted on Sahiwal (N = 314) cows that have attained first calving maintained at Livestock Research Centre, ICAR-National Dairy Research Institute, Karnal (Haryana), India, during 20162017. The experimental animals were housed under loose housing system. The feeding management practices and feed ingredients were same for all animals in the herd. Limited concentrates and ad libitum green fodders were provided to meet the nutrient requirement of the animals.

The different traits body weight at different age i. e. Birth, 6 Months (6M), 12 Months (12M), 18 Months (18M), 24 Months (24M), 30 Months (30M), Weight at First Calving (WFC), were considered for study. The records were classified into four periods P1 (2001-2004); P2 (2005-2008); P3 (2009-20102); P4 (2013-2017). Each year was divided into the four seasons viz. like S1: winter (December-March), S2: summer (April-June), S3: rainy (July-September), and S4: autumn (October -November). These data were collected from birth register and history-cum-pedigree sheets maintained in the Livestock record unit of Animal Genetics and Breeding Division and Livestock Research Centre, ICAR- National Dairy Research Institute, Karnal.

The data on birth weight and age at first caving were classified into different groups based on the following Sturge’s formula (1926).

Where,

where,

where,

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Prior to estimation of genetic parameters, the data were adjusted for different significant non genetic factors and the adjusted records were used for subsequent analysis. The heritability, genetic and phenotypic correlations were estimated only from those progeny groups of sires having a minimum of five daughters. Paternal half-sib correlation (intrasire correlation among daughters) method was used to estimate heritability of different traits. The genetic and phenotypic correlations among different body weights and first lactation traits were estimated from the analysis of variance and covariance among sire groups as given by Becker (1975).

Analysis of variance revealed highly significant effect (P ≤ 0.01) of period of birth on all the different growth traits under investigation (Table 1). In accordance with this study, Gandhi and Kumar (2014) and Manoj et al. (2014) also observed highly significant effect of period of birth on all the different growth traits in Sahiwal calves. Effect of season of birth was significant (P ≤ 0.05) on W6, W12, W18 and W24 whereas BW, W30 and WFC were not significantly affected by season of birth (Table 1). Our findings were in agreement with the findings of Manoj et al. (2014). Contrary to present finding Singh et al. (2011) reported significant influence of season on birth weight in Sahiwal calves. Heifers born of rainy and autumn season had higher body weights at different ages over the heifers born of other two seasons. Though non significant, the heifers born during autumn season had higher and heaviest body weight (357.94 ± 7.08 kg) at age of first calving. The exposure of autumn born calves to favourable winter season during initial phase of life would have attributed to higher growth rate during first six months of their age leading to healthy foundation health. Summer born calves were exposed to hot humid rainy season not favorable for higher growth rate. The least squares analysis of variance showed highly significant (P ≤ 0.01) regression of body weights at 6M, 12M, 18M, 24M, 30M of age and first calving on birth weight in Sahiwal cows. Effect of various non genetic factors on first lactation traits is presented in Table 2. Analysis of variance revealed significant effect (P ≤ 0.01) of period on all the first lactation traits under investigation. This was in conformity with the findings of Kumar and Gandhi (2011), Manoj et al. (2012), and Raja and Gandhi (2015). Contrary to present findings Kathiravan et al. (2009), Narwaria et al. (2015) and Praveen (2016) reported non significant effect of period on FCI and FSP. Effect of season of calving was found to be non significant on different first lactation traits expect FCI (P ≤ 0.05). Similar to our findings Kumar and Gandhi (2011) and Manoj et al. (2012) reported non significant effect of season of calving on first lactation traits. On the other hand Narwaria et al. (2015) observed significant effect of season on different first lactation traits under investigation. Animals calved during summer season had lower FL305DMY than those calved during rainy and autumn season had highest FL305DMY, though no significant differences were found out in milk yield. It can be assumed that low milk yield in the summer was found out because of temperature stress during the summer season. The regression of FL305DMY on age at first calving was found to be statistically highly significant (P ≤ 0.01) in Sahiwal cattle for overall data.

The estimation of genetic parameters is an essential part of animal breeding as they estimate gene transmission from one generation to the next. It helps to select superior individuals in breeding programme for improving future populations (Bourdon, 2000). Genetic parameters that are of interest include heritability, genetic and phenotypic correlation estimates. The measures of heritability of various traits and their phenotypic and genetic correlations are the parameters which determine the genetic improvement in the population. The estimates of heritability for BW, W6, W12, W18, W24, W30 and WFC were 0.12 ± 0.28, 0.67 ± 0.34, 0.49 ± 0.33, 0.19 ± 0.29, 0.19 ± 0.30, 0.42 ± 0.32 and 0.43 ± 0.22 respectively (Table 5). Similar to present findings, different researchers (Gandhi and Kumar 2014 and Manoj et al. 2014) also revealed lower estimates of heritability for these traits in various breeds of cattle including Sahiwal. On contrary the direct heritability estimates of these traits from our study was lower compared with previous estimates in different native and exotic breeds of cattle including Sahiwal calves (Yin and Konig 2018). Singh et al. (2011) reported a moderate estimate (0.29± 0.10) of heritability for birth weight in Vrindavani calves. The heritability estimates of weight at twenty four months, thirty months and calving were higher in present investigation. Genetic parameters of different first lactation traits are presented in Table 5. The heritability estimate for AFC, FL305DMY, FLL, FCI and FSP obtained in the present study were low to medium and had reasonably low standard errors. The results indicated that these production traits are influenced more by additive genetic variability and hence there is a scope for improvement. The heritability estimate of AFC was found to be low (0.11 ± 0.09) which was in agreement with the findings reported by Manoj et al. (2012), Verma (2015) and Parveen et al. (2018). Comparatively higher estimates of heritability were reported by Hussain et al. (2014). Moderate heritability estimate was observed for FL305DMY (0.26 ± 0.11). Manoj et al. (2012) reported almost similar heritability in Sahiwal cattle. The moderate value of heritability of trait in present study revealed that the trait was more influenced by environmental factors and improvement of this trait could be done by better feeding, breeding and managemental practices.

The estimate of genetic correlation of birth weight with W6 and W12 were significantly positive indicating presence of maternal effect till age of one year body weight. But the genetic correlations of birth weight with body weight at 18M to till first calving were significantly negative and ranged from -1.26 to -0.21. It suggested that selection for heifers with high body weight should not be practiced on the basis of early body weight till one year of age in Sahiwal cows. The young stage growth traits are usually influenced by maternal effect, hence selection for getting heavy weighted heifers must not be practiced on the basis of early recorded young growth traits. The genetic correlation between body weight at 6M, 12M, 18M, 24M, WFC and AFC was negative and significant (-0.75 ± 0.11, -0.61 ± 0.12, -1.08 ± 0.22, -1.88 ± 0.09, -0.61 ± 0.23 respectively) which is desirable. Most of the growth traits had moderate phenotypic correlations with each other. The genetic correlations between first lactation traits were significantly medium to high and positive which indicate simultaneous performance enhancement in one trait while selecting other. FL305DMY is expected to improve the performance of first lactation traits through correlated response and selection of animals on the basis of FL305DMY would lead to advantageous enhancement in all these correlated production, and reproduction traits. However association of FL305DMY with FCI was observed to be low, negative, and non-significant. This result was in agreement with the findings reported by Parveen et al. (2018). The genetic correlation of FLL was high and positive with FL305DMY and FCI and low with AFC. The results indicated that the longer FLL is expected to improve the FL305DMY since cows with high FLTMY tended to have longer lactation length whereas higher correlation of FLL with FCI could be due to the reason that FLL is one of the components of calving interval. Similar findings were also reported by Parveen et al. (2018). The phenotypic correlations of FL305DMY with FLL, FCI and FSP were observed to be positive, low to high and significant. Hence, this association suggested that higher FL305DMY is likely to improve the performance of other related production and reproduction traits. However, the correlation of FL305MY with AFC was found to be low and non-significant. Findings similar to the present study were also observed by Banik and Gandhi (2010) and Parveen et al. (2018). Even though phenotypic correlations amongst body weights and first lactation traits were mostly found to be non-significant, highly significant phenotypic correlations were observed between AFC and different body weights like 6M, 12M, 18M, 24M, 30M and WFC. Similarly, phenotypic correlations between FL305DMY and body weights at 6 and 30M were significant (P < 0.05), whereas those between FL305DMY and WFC was highly significant (P ≤ 0.01). Highly significant phenotypic correlations were also observed in case of 12M body weight with FCI and FSP.