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Background The objective of this study was to investigate the use of principal components (PC) as potential selection criteria to improve growth in sheep. The PC were derived from body weights of 2223 Muzaffarnagari lambs at birth, 90, 180, 270 and 360 days of age. Univariate animal models including various combinations of direct and maternal effects were fitted to the PC. Genetic correlations among PC and with body weights and estimated growth curve parameters for the Brody and Richards functions were estimated using bivariate animal models. Results The first three PC explained 94% of multivariate variation in body weights. PC1 contrasted lambs with larger versus smaller body weights at all postnatal ages. PC2 contrasted lambs with heavier versus lighter birth weights, with little emphasis on postnatal weights. PC3 placed positive emphasis on weights at birth and after 6 months of age but negative emphasis on weight at 3 through 9 months of age. Direct heritabilities for PC1, PC2, and PC3 were 0.19, 0.12 and 0.08, respectively. Maternal genetic and permanent environmental effects affected PC1 (0.04 and 0.08, respectively). PC2 was influenced by maternal genetic effects (0.10). Direct genetic correlations of PC1 with PC2 and PC3 were 0.48 and 0.72. The maternal genetic correlation between PC1 and PC2 was 0.97. Genetic relationships of PC1 with yearling weight and with estimates of final body weight from both growth functions exceeded 0.65. PC2 was genetically correlated with birth weight (≥ 0.64) and degree of maturity for body weight at birth (u 0 ; ≥ 0.83). PC3 had negative genetic correlations with measures of maturing rate (~ -0.86) and with u 0 ( -0.52 and -0.49), but positive correlations with final body weight (0.85 and 0.90) and time required to reach 50% of mature weight (0.83). Maternal genetic correlations of PC1 and PC2 with birth weight and u 0 exceeded 0.83. Conclusions We conclude that PC could be used as selection criteria in genetic improvement programs in sheep. Also, selection on PC1 and PC2 would likely be adequate to describe and improve direct and maternal genetic potentials for postnatal growth and birth weight, respectively, in Muzaffarnagari lambs.

The present study was undertaken to determine the effect of heat stress on milk production (test day milk yield) and compositional traits (fat%, protein%, fat yield, protein yield) as well as to observe the pattern of response to increasing heat load on these traits in Jersey crossbred cows, maintained at ICAR-National Dairy Research Institute, Eastern Regional Station, Kalyani, West Bengal, India. The weather information, obtained from the NASA POWER database based on the location of the farm latitude and longitude, was used to calculate the Temperature Humidity Index (THI). To analyze the data, a linear model was fitted to the milk production and compositional records, which were adjusted for additive genetic effect of animal, permanent environmental effect of animals and known environmental sources of variations. Subsequently, a segmented linear regression model was fitted, and the least squares estimates of production and composition traits in different classes of THI were used as the dependent variable. Two THI break-points (BP) for milk yield and one THI BP for fat yield, protein %, and protein yield were found. The first and second BP for milk yield was at THI 59 and 77, respectively, with a significant decline in milk yield of -0.04 kg/unit of THI at second BP. The BP for fat and protein yield was at THI 76, with a decline rate of -1.18 and − 0.61 g/unit of THI increase, respectively. The findings revealed the significant adverse effects of THI on milk production and composition traits in Jersey crossbred cattle.

Growth data on Jersey crossbred calves, maintained at ICAR-National Dairy Research Institute, Eastern Regional Station, Kalyani, Nadia, West Bengal, India, were collected and analysed to assess the influence of maternal effects on growth traits of calves. Traits considered for this study were birth weight (BW) and weights at 3 months (W3M), 6 months (W6M), 9 months (W9M) and 12 months (W12M) of age. Least-squares analyses were employed to obtain the effects of non-genetic factors on the traits of interest. Determination of influence of maternal effects on growth traits was estimated by fitting three univariate animal models (including or excluding maternal effects) using Bayesian approach. The most appropriate model for each trait was selected based on Deviance Information Criterion. Direct heritability ( h 2 ) estimates for BW, W3M, W6M, W9M and W12M were 0.31 ± 0.08, 0.26 ± 0.10, 0.48 ± 0.10, 0.44 ± 0.11 and 0.39 ± 0.14, respectively, under the best model. Permanent environmental maternal effects ( c 2 ) varied from 0.04 to 0.12 for all traits. Existence of maternal effects for all ages reflects the importance of maternal components for these traits. Moderate to high heritability estimates for growth traits indicate the possibility of modest genetic progress for these traits through selection under prevalent management system.

The present study aimed to estimate variance components and genetic parameters of the average daily gains from birth to 3-months (ADG1), 3- to 6-months (ADG2), 6- to 9-months (ADG3) and 9- to 12-months (ADG4) of age and corresponding Kleiber ratios (KR1, KR2, KR3 and KR4, respectively) in Jersey crossbred calves. Data for this study were collected from National Dairy Research Institute, Eastern Regional Station, Kalyani, West Bengal, India during 2013 to 2021. Genetic parameters for the traits were estimated using Bayesian procedure through Gibbs sampling by fitting six animal models. The deviance information criterion (DIC) was employed to determine the most appropriate model for each trait under investigation. Direct heritability estimates for ADGs and KRs ranged from 0.19 (ADG3) to 0.59 (ADG2) and 0.14 (KR3) to 0.72 (KR1), respectively. Significant maternal heritability ( m 2 ) was observed for average daily gains (17–24%) and Kleiber ratios (13–18%) at different age intervals under the best model. Estimates of permanent environmental effects ( c 2 ) of dam for ADG1, ADG2, KR2 and KR4 were only 1–4% of the total phenotypic variance in this study. Large negative estimates of correlations, ranging from -0.87 to -0.98, between direct and maternal ( r a , m ) effects for ADGs and KRs (except KR3) at different age intervals were observed. Total heritability ( h t 2 ) and maternal repeatability ( t m ) of the studied traits ranged 0.05–0.28 and 0.01–0.14, respectively. The moderate to high heritability estimates for all traits in this study indicate the possibility of genetic progress for these traits through selective breeding program.

The objective of this research was to determine the genetic parameters of the test day milk yield and milk constituents (fat, Solid-not-fat, total solid, protein, and lactose) in Bhadawari buffaloes maintained at the ICAR-Indian Grassland and Fodder Research Institute in Jhansi, Uttar Pradesh, India. Data on 2593 lactation records from 93 Bhadawari buffaloes, descended from 16 sires and 43 females were analyzed which covered a period of eight-years (2014 to 2021). In estimating the genetic parameters of all the traits under consideration, the Bayesian approach and Restricted Maximum Likelihood method were employed. The heritability estimates for test day milk yield (MY), fat (F), solid-not-fat (SNF), total solids (TS), protein (P), and lactose percentage of milk ranged between 0.05–0.06, 0.09–0.11, 0.12–0.13, 0.12–0.14, 0.01–0.08 and 0.06–0.07, respectively. For MY (0.05–0.06), F (0.12), SNF (0.08–0.09), TS (0.13), P (0.03–0.18), and lactose (0.06) in both approaches, a low proportion of variations linked to the permanent environmental effect (c 2 effect) of animals were detected. Repeatability measures for all the traits under study were low to moderate in nature, which ranged from 0.10 to 0.27. The genetic and phenotypic correlations between various traits analyzed exhibited a vast range of magnitudes where a low to high positive genetic correlations were observed for all except between milk yield and fat as well as milk yield and TS. The phenotypic correlations were also positive but low for all the traits under consideration except for milk yield with fat, SNF and TS.