The effectiveness of sire evaluation is the backbone of any breed improvement programme as much as 61% of genetic gain in dairy cattle results from selection of sires through &ldquo;bulls to breed cows&rdquo; and &ldquo;bulls to breed bulls&rdquo; path. The application of latest and simplex method of sire evaluation like BLUPF90 in Indian breeds is scanty. The present investigation was planned to evaluate the Red Sindhi sires by this method and to compare the effectiveness of BLUPF90 method with other conventional methods of sire evaluation in Red Sindhi cattle. The records of production and reproduction performances of first lactation traits of 717 Red Sindhi cows, progeny of 58 sires, spread over a period of 40 years (1966-2005) &nbsp;from CCBF, Chiplima, Orissa under the control of Department of Animal Husbandry, Dairying and Fisheries, Ministry of Agriculture, Government of India and CBF, Kalsi, Deheradun, Uttarakhand were analyzed. The present study was single and multi-trait evaluation of breeding values of Red Sindhi sires. The overall least squares population mean for first lactation milk yield (FLMY) was 1536.35&plusmn;54.87 kg. The average breeding value of sires of single trait from different methods ranged from 1536.35 kg (LSM, DFREML and BLUPF90-Dairy Pack) to 1588.50 kg (simple daughter average) but in multi-trait method the breeding value does not vary with each other. The comparison of different method of sire evaluation based on single trait for FLMY only shows that the DFREML model for single trait should be preferred over the BLUP, LSM and simple daughter average methods for evaluating the sire breeding value. However, if a sire-breeding value is to be computed from multi traits then BLUPF90 model may be preferred over DFREML model.

Sire evaluation using animal model versus different&nbsp;conventional methods in red sindhi cattle

Background: The present study aimed to evaluate the fitness of Beetal goats through a combination of logistic regression and Bayesian statistical approaches using data from the Directorate of Livestock Farms, GADVASU, Ludhiana. 
 
Methods: Fitness classification based on mortality records and non-genetic factors such as sex, season and year of birth from 2015 to 2023 were extracted from records at the Directorate of Livestock Farms, GADVASU. A total of 530 animal records belonging to 230 dam families sired by 52 males were used, out of which 230 death records were reported and 466 animals survived upto one year of age. 
 
Result: Logistic regression analysis revealed that all three variables significantly influenced survival, with female goats and those born in cooler seasons showing higher odds of being classified as high-fitness. Bayesian analysis was subsequently performed on the filtered dataset using the BLUPF90 suite to estimate additive genetic variance and heritability. The estimated heritability of 0.1791 indicated a modest genetic basis for fitness, with environmental factors contributing the majority of variance. These findings underscore the complex, multifactorial nature of fitness in goats, providing insights for sustainable breeding strategies that enhance health resilience without compromising adaptability. The study also identifies specific years and seasons that influence survivability trends, offering practical implications for livestock management and genetic selection programs.

Genetic Assessment of Fitness in Beetal Goats

<div>Background: Genetic parameter and covariance component estimation is an important aspect of animal breeding, as it helps to quantify additive and non-additive genetic variances. The precise estimation is also essential for reliable prediction of breeding values. The milk production for each animal in lactation has shown increasing trend over the last seven decades in the herd under study. The important fact is that more than 50% progress is associated with genetic progress and rest is credited to advances in management practices. However, on the other hand the picture is different while tracking for fertility over this period that showed a decline trend. The continuous selection for milk production traits leads to decline in reproduction traits. Thus, present study is planned to study the effect of continuous selection for milk yield on fertility traits and the probable measures to overcome these effects. The study was conducted on Sahiwal cattle herd maintained at ICAR-NDRI, Karnal. 
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Methods: The data was collected from records belonging to 1955-2024 on first lactation production and reproduction like FLTMY, FL305dMY, FSP, FCI, DPR and AFC traits. The effect of non-genetic factors was estimated using least-squares analysis by General Linear Model of SPSS. The variance and (co)variance components were estimated by using the BLUPF90 family of programs. 
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Result: The genetic variability measured by genetic parameters indicated that genetic and phenotypic correlation between production and reproduction traits was negative and between productions traits were high in the study. Overall, the genetic trend was positive in the present study for production traits whereas the reproduction traits exhibited unfavourable or inconsistent trends. The information generated in the present study will be useful in planning future breeding activities for further improvement of the breed.</div>

Sire evaluation using animal model versus different conventional methods in red sindhi cattle

Genetic Assessment of Fitness in Beetal Goats

Genetic Evaluation of Reproductive Performance and Milk Production in Sahiwal Cows