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Objective: The present study was aimed primarily for estimating various genetic parameters (heritability, genetic correlations) of reproduction (age at first calving [AFC], first service period [FSP]); production (first lactation milk, solid-not fat, and fat yield) and lifetime traits (lifetime milk yield, productive life [PL], herd life [HL]) in Tharparkar cattle to check the association of reproduction traits with lifetime traits through two different methods (Frequentist and Bayesian) for comparative purpose.Methods: Animal breeding data of Tharparkar cattle (n = 964) collected from Livestock farm unit of ICAR-NDRI Karnal for the period 1990 through 2019 were analyzed using a Frequentist least squares maximum likelihood method (LSML; Harvey, 1990) and a multitrait Bayesian-Gibbs sampler approach (MTGSAM) for genetic correlations estimation of all the traits. Estimated breeding values of sires was obtained by BLUP and Bayesian analysis for the production traits.Results: Heritability estimates of most of the traits were medium to high with the LSML (0.20±0.44 to 0.49±0.71) and Bayesian approach (0.24±0.009 to 0.61±0.017), respectively. However, more reliable estimates were obtained using the Bayesian technique. A higher heritability estimate was obtained for AFC (0.61±0.017) followed by first lactation fat yield, first lactation solid-not fat yield, FSP, first lactation milk yield (FLMY), PL (0.60±0.013, 0.60±0.006, 0.57±0.024, 0.57±0.020, 0.42±0.025); while a lower estimate for HL (0.38±0.034) by MTGSAM approach. Genetic and phenotypic correlations were negative for AFC-PL, AFC-HL, FSP-PL, and FSP-HL (–0.59±0.19, –0.59±0.24, –0.38±0.101 and –0.34±0.076) by the multi-trait Bayesian analysis.Conclusion: Breed and traits of economic importance are important for selection decisions to ensure genetic gain in cattle breeding programs. Favourable genetic and phenotypic correlations of AFC with production and lifetime traits compared to that of FSP indicated better scope of AFC for indirect selection of life-time traits at an early age. This also indicated that the present Tharparkar cattle herd had sufficient genetic diversity through the selection of AFC for the improvement of first lactation production and lifetime traits.

The genetic constitution is unique for each population as its composition is associated with the landscape reforms. Landscape genetics helps in understanding the structural genetic difference at population and individual levels based on gene flow in different geographical and environmental constituents. Gene flow is helpful in avoiding several adverse effects such as inbreeding, loss of heterogeneity (genetic variations), depression of population fitness, demographic problems of inbreeding and to decrease extinction risk. Livestock species are following devastating trends such as the extinction rate of biodiversity, demolition of bionetwork, and vanishing genetic diversity. This resulted adversely on livestock diversity which translates into a lack of apt reaction for future generations. Over the years, intense anthropogenic selection for highly productive cosmopolitan breeds resulted in a progressive ebb in the number of native breeds. Landscape genetics analyses are therefore very helpful in the practical conservative management of species of economic importance. In situ breed conservation can be done relevant by combining relevant information from different applied fields viz. geo-referencing, eco-climatic, epidemiological, spatial diversity at a genetic level and production aspect to strategize precedence judgments. This can be of great use to realize the genetic source of animal adaptation to the varied environmental conditions and production wise co-evolution pattern of livestock structure.

A total number of 802 and 300 records of Sahiwal and Tharparkar cows respectively were collected from history-cum-pedigree sheet for milk production and composition, animals born and reared at Livestock farm unit of ICAR-NDRI Karnal, Haryana, India. The period of study were divided into 6 periods of 5 years each (1990 to 2019). Presented analyzed data were received from selected herd for first lactation milk yield (FLMY), first lactation SNF yield (FLSNFY) and first lactation fat yield (FLFY) in both cattle breeds. Multivariate/Trivariate analyses were carried out by Bayesian approach using Gibbs sampler Animal model. Total heritability estimates for FLMY, FLSNFY and FLFY by Bayesian modeling were valued as 0.20±0.0125, 0.51±0.0114 and 0.45±0.0112 for Sahiwal and 0.46±0.0375, 0.54±0.0195 and 0.52±0.0204 for Tharparkar respectively along with its Monte Carlo Error. Direct genetic and environmental covariance between production traits were ranging from 94553 and 58851 for FLMY-FLFY to 180380 and 185780 for FLSNFY-FLFY in Sahiwal and from 116650 and 95344 for FLSNFY-FLFY to 245820 and 227400 for FLMY-FLFY in Tharparkar respectively. Comparable estimates of heritability and breeding values for ranking of sires were obtained by BLUP and Bayesian analyses from the presented data. Estimates of genetic and phenotypic (co)variance components and heritability estimates obtained using LSML which were positive but very medium to high for Sahiwal while genetic correlations were positive and high in Tharparkar. However, Gibbs Sampling (GS) is an advance and comparatively correct method of choice for many applications because of its greater robustness with comparable but slightly higher estimates of genetic parameters than LSML. The Gibbs Sampling method is flexible and dependable practice for the genetic evaluation and it can be useful in the breeding programs for highly heritable traits in Tharparkar as compared to low estimates in Sahiwal from present work.

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