The data on various production and reproduction traits was collected from the pedigree sheets of Badri cattle from Instructional Dairy farm Nagla of GB Pant University of Agriculture & Technology- Pantnagar, Uttarakhand India. Located in Himalayan foot hills, the Tarai region has a latitude of 290 N, longitude 79.30 E and an altitude of 243.84 m. It has a humid subtropical climate and experiences cold winter and blistering summer. The temperature during winters dips to a 2ºC and the summers may see a maximum rise of 43ºC with relative humidity ranging between 15 to 95%. The study was conducted on the production and reproduction data recorded from 2014 to 2020. Production traits recorded were TMY (kg), PY (kg) and DMY (kg). Reproduction traits recorded were SP (days), DP (days) and CI (days). The data for each trait was normalised by mean ± 3 standard deviations.

The NGF such as parity number of animal, season of calving and period of calving was classified into different fixed sub-class effects in order to evaluate the effect of NGF on the traits taken into consideration in the present study. The classification of NGF viz. season of calving, period and parity number is given in Table 1.

To subdue the non-orthogonality of effects due to unequal and disproportionate sub-class frequencies least-squares analysis was applied to determine the significance of NGF as suggested by (Harvey, 1990). For this study, the model, Y_ijkl = µ + P_i + S_j + Pr _k + e_ijkl, were, Y_ijkl is observation on l^th animal of i^th period, calved in j^th season having k^th parity, P_i is effect of i^th period, S_j is effect of j^th season of calving, Pr_k is effect of k^th parity of an animal, and e_ijkl is random error associated with each observation assumed to be normal in distribution with error zero and variance σ_e², was considered with the assumptions that the different components being fitted into the model are linear and independent.

Heritability estimates for various production and reproduction traits were obtained from sire component of variances using paternal half-sib correlation method (Becker, 1975). The model, Y_ij = m + s_i + e_ij, was used to estimate the heritability, where, Y_ij is observation of the j^th progeny of the i^th sire, m is effect of the i^th sire, normal in distribution with error zero and variance σ_e², e_ij is random error with error zero and variance σ_e². The s_i and e_ij were assumed to be independent of each other.

Analysis by Least-square maximum likelihood programme was performed using Harvey Software, Harvey (1990). The statistical significance of various non-genetic factors was set on by F-test.

Effect of parity and period was significant (P <0.01) on TMY while as, effect of season of calving was nonsignificant on TMY. TMY was significantly increasing with parity number of animal till fifth parity (Fig. 1). TMY was found highest in fifth parity (659.78 ± 55.29kg) and lowest in first parity (293.12 ± 49.11 kg). TMY showed significantly declining trend with period. In semblance to our findings, Bhutkar et al. (2014), Ratwan et al. (2016), Ratwan et al. (2019a) reported significant effect of parity number of animal, period of calving and non significant effect of season of calving on TMY. On the contrary, Verma et al. (2016) reported non significant effect of period of calving on TMY. Dongre et al. (2017) reported non significantly effect of parity number of animal on TMY.

Effect of parity and season of calving was found significant on PY (P <0.05) while period had non-significant effect on PY. PY was significantly increasing with parity number of animal (Fig. 2). The PY was observed highest in sixth parity (5.48 ± 0.27 kg) and lowest in first parity (3.64 ± 0.21 kg). The PY was observed significantly higher in summer (4.70 ± 0.17 kg) followed by rainy (4.52 ± 0.14 kg) and winter season (4.51 ± 0.15 kg). In agreement to our results, Tekerli et al. (2000) reported significant effect of season of calving on PY. Contrarily, Bhutkar et al. (2014) found significant effect of period of calving on PY.

Effect of parity number of animal and period of calving was found to be significant (P<0.05) while season of calving was non-significant on DMY. DMY was significantly increasing with increase in parity number of animal till fifth parity (Fig. 2). DMY was observed highest in fifth parity (2.68 ± 0.16 kg) and lowest in first parity (1.48 ± 0.14 kg). The DMY estimated was significantly declining with period. DMY was highest in 2014-15 (2.62 ± 0.15 kg) and lowest in 2018-2020 period (1.74 ± 0.09 kg). Findings of, Bayou et al. (2015) shows similar outcome of significant effect of parity number of animal and season of calving with non-significant effect on DMY as were formulated during this study. The increasing trend of production traits with advancement of parity number of animal is due to better development of mammary glands.

Effect of parity was significant (P<0.05) while period and season was non-significant on service period. SP showed significant declining trend with increase in parity number of animal except in fifth parity where it increased than previous parity number (Fig. 3).

SP was lowest in sixth parity (55.63±15.46 days) and highest in first parity (113.03±11.78 days). Bayou et al. (2015) delineated season of calving had a significant (p<0.01) effect on SP. Similar to our findings, Bayou et al. (2015), described receding trend in service period with advance in parity number of cattle. The present study is also supported by findings by other workers, who reported the longest SP (Giday, 2001) in young cows which may be rendered by lower energy back up as they are not able to divert most of the supplemental food for growth, production, reproduction and maintenance, thus energy backdrop defers the onset of postpartum heat. The results demonstrated in our study for the effect of season of calving on SP, supports the study of various workers, (Aynalem, 2006; Getinet et al., 2009). Effect of season, parity number of animal and period of calving was nonsignificant on dry period and calving interval.

The heritability estimated for production traits were low to medium in magnitude varying from 0.02 to 0.26 while as magnitude of heritability estimated for various reproduction traits was low, varying from 0.03 to 0.14 . Similar to our findings, Ratwan et al. (2018), reported low to medium range of heritability for production traits in Sahiwal cattle. Magnitude of heritability estimates of reproduction traits were in semblance as reported by Ratwan et al. (2019b). The heritability of TMY was found to be medium (0.26) in Badri cattle. The results were comparable with the findings of Hussain et al. (2014) and Ratwan et al. (2018) in Sahiwal cattle. Heritability estimate of peak yield was 0.15 which was comparatively lower than reported by Ratwan et al. (2018), in Sahiwal cattle. Magnitude of heritability estimate for DMY in Badri cattle was found low (0.02). Patond et al. (2013) reported higher heritability estimate (0.30) of DMY in Jersey cattle, as compared to this study. In the present study, the heritability of dry period (0.14) was similar to findings of Mohanty (2001) and Ratwan et al. (2018) in Sahiwal cattle. Findings of Rehman et al. (2008) and Banik and Gandhi (2010), revealed 0.05 and 0.02 heritability estimates of dry period which are comparatively lower than present result. Heritability of service period was found to be low (0.03) in Badri cattle which was comparable with findings of, Rehman et al. (2008) in Sahiwal cattle. Choudhary et al. (2003) and Ratwan et al. (2019b) reported higher estimates. Heritability estimate of calving interval was also found low (0.03). This was very lower compared with heritability estimates reported by Singh et al. (1999) and Ratwan et al. (2019b) in Sahiwal cattle.