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Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

The present study was conducted to assess the relation between different production and reproduction traits in Sahiwal cattle. Data up to sixth parity related to different production and reproducti...

Genetic persistencies of milk yield up to six parities were estimated for the first time in India to assess the sustainability of Sahiwal cattle. Monthly test day milk yield records of Sahiwal catt...

Background: The selection of genetically superior animals at an early stage of life, the molecular markers are used along with traditional selection. The study was carried out to identify the genetic polymorphism in the exon3 region of the Prolactin and enumerate its effect on milk production performance in Sahiwal cattle. Prolactin plays an imperative regulatory role in mammary gland development, milk emission and lactogenesis. Analysed the sequence of this gene to explore whether mutations in this sequence and it could be accountable for quantitative variations in milk production and its composition traits.Methods: Total DNA was isolated from the blood samples of 98 pedigreed Sahiwal population. Using PCR-RFLP method and direct sequencing, noticed a single-nucleotide polymorphism in exon3 region of the Prolactin gene in 156bp and also the effect of non- genetic factors on each trait was assessed by least-squares analysis for non-orthogonal data by a fixed model.Result: PCR-RFLP was done with RsaI restriction endonuclease for the identification of different genotypes. The frequency of G and A alleles of the Prolactin gene was evaluated as 0.575 and 0.425, whereas the frequencies of GG, GA and AA genotypes for the Prolactin gene were 0.45, 0.25 and 0.30, respectively. SNP (G55A) conferred an increase in test-day milk yield around 321.5g, in test day fat yield around 13.9g and in test day SNF yield increase was 19.4g, respectively. High correlation was perceived from test day (TD2) onwards between test day traits and lactation milk yield indicating that selection based on identified SNP in TD2 increased test day milk yield, fat yield and SNF yield by 1.1472 kg, 29.6gm and 45.4gm, respectively.

Background: The estimates of genetic parameters are useful in determining the appropriate method of selection that could further be implemented in the breed improvement programmes. The present study was, therefore, conducted to estimate the genetic parameters (heritability, genetic and phenotypic correlations) for monthly test day (TD) milk yields, peak yield (PY) and first lactation 305 days milk yield (FL305DMY) in Murrah buffaloes.Methods: Paternal half-sib correlation method was carried out by least-squares maximum likelihood programme to estimate genetic parameters of first lactation 4,209 and 408 records of monthly test day milk yield and peak yield, respectively, of 408 Murrah buffaloes (sired by 62 bulls) calved in between 1993 and 2017 at ICAR-National Dairy Research Institute, Karnal.Result: Heritability of FL305DMY and peak yield was estimated as 0.35±0.17 and 0.33±0.16, respectively. Heritability estimates for mid-lactation monthly test day milk yields were found to be moderate. Genetic correlation of monthly test day milk yields with FL305DMY was positive and highly significant for TD-4 to TD-9 and TD-11. Peak yield showed high genetic and phenotypic association with FL305DMY. High genetic and phenotypic correlation among monthly test day milk yields, peak yield and FL305DMY suggested that TD-4 to TD-9 and TD-11 test day milk yields and peak yield could be used for the selection of elite animals.

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

The ability of an individual to resist disease upon exposure to a pathogenic causal agent is popularly known as disease resistance; the mechanism is governed by a system of biological structure and processes within an organism, conferred as “immunity.” The two major components of immunity are innate immunity and acquired immunity. A set of genes control the expression and regulation of proteins or cytokines involved in immune functions. These are known as the immune-response genes, and their study is known as immunogenetics. Innate immunity refers to the immune system one is born with and is the initial response by the body to eliminate microbes and prevent infection, and it is nonspecific in nature. Acquired immunity is specific in nature and conferred by B-lymphocyte through the production of antibodies (also known as humoral immunity) and the T lymphocyte through cell-mediated immunity.

Different mechanisms exist for host immunity to combat bacterial infections. These involve antibody-mediated neutralization of toxins or enzymes, killing of bacteria by antibodies and complements, phagocytosis leading to destruction of bacteria through opsonization with antibodies and complements, activated macrophage-mediated destruction in the case of intracellular bacteria, and cytotoxic T cell– and natural killer cell–mediated direct killing of bacteria. Many cytokines, antibodies, and complements are involved in this process, the genetic control of which is described by the gene bank accession number and respective protein ID for different species—e.g., CD14, CD4, CD8, TLR-2, TLR-4, TLR-9, MD2, IL-1, TNF-α, NK cell, IL-1, IL-5, IL-6, IL-13, TLR-6, TLR-8, TLR-10, C3 complement, IgM, and IgG.

Adaptive immunity refers to antigen-specific defense mechanisms that take several days to become protective and are designed to remove a specific antigen. This immunity is developed throughout life. The two main types of immunity are innate immunity and adaptive immunity (humoral immunity and cell-mediated immunity). The chapter describes the genetic control of immunoglobulin and T cell– and B cell–mediated immunity through Bu-1. Immunoglobulin is a Y-shaped structure with two light and two heavy chains and, a separate set of genes is responsible for encoding the chains. The gene responsible for B cell immunity, Bu-1, is described. When B cells are activated, class switching can occur, which involves switch regions made up of multiple copies of short repeats (GAGCT and TGGGG) that occur at the level of DNA rearrangements. Selected diseases associated with Ig polymorphism are also discussed.

In the earlier chapters, we had discussed about conventional breeding techniques commonly employed for disease resistance. In this chapter, we had discussed about various advanced breeding techniques which can be successfully utilized for studying disease resistance. These techniques are best linear unbiased prediction, best linear unbiased estimate, maximum likelihood estimation, restricted (or “residual”) estimated maximum likelihood, threshold model, animal model, logit model, probit model, genome-wide association study, estimation of linkage disequilibrium, principal component analysis, cluster analysis, artificial neural network, meta-analysis, Bayesian statistics, data mining, and big data analysis.

Current genetic improvement programs have led to strong selection pressure on production traits, which may lead to decreased fitness traits including disease resistance. Breeding for disease resistance is the ultimate option leading to permanent overall improvement with a better economic return. Some limitations have been discussed, as disease-resistance traits are difficult to measure and too costly, as they are threshold traits. Heritability, genetic correlation, and rapid evolution of pathogens and parasites are major concerns for studying disease-resistance traits. Indicator traits are preferred in such cases. Disease-resistant traits are polygenic in nature, and multitrait selection with index selection has proved to be more efficient.

Parasitic infection can be broadly classified into three groups: protozoa, helminths, and ectoparasites. Unlike protozoan infection, parasites are resistant to complement. Macrophages are unable to phagocytose due to the tegument of helminths. Immune response against parasites, particularly helminths, is mediated by IgE antibodies and eosinophils. Antigen masking is an effective form of immune-response invasion by some parasites. Th2 is counterprotective in protozoan infection, while it is protective in parasitic infection.

Immune-response genes may be referred to as the set of genes that confer immunity or disease resistance to the livestock. The genes code for peptides related to innate or adaptive immunity. Genes for mitochondria and peroxisome also responsible for diseases. Metagenomics also has a role in causing disease. The main cytokines having a role in innate and adaptive response are IL-1, IL-6, IL-12, IL-16, TNF-α, IFN-α, IFN-β, and toll-like receptor transmembrane proteins expressed by cells of the innate immune system that recognize invading microbes and activate signaling pathways that launch immune and inflammatory responses to destroy invaders. The study of immune-response genes through bioinformatics is mentioned.

Innate immunity is the first line of defense after the entry of any pathogen into the body and is nonspecific in nature. The components of innate immunity may be classified broadly as epithelial barriers, cells, and humoral components. The pattern recognition receptors (toll-like receptors, CD14) and soluble factors (acute-phase proteins such as plasma protein, C-reactive protein, fibrin, complement, interferon, properdin, lactoferrin, transferrin, lactoperoxidase, lysozyme, and cytokines are mostly proteins and expressed and coded by respective genes. The chapter describes two possible modes of genetic control. First is the qualitative aspect, mutation in the coding region of a gene that leads to single-nucleotide polymorphism. The particular mutation may alter the domain of the peptide, its configuration, or the 3-D structure, leading to diminished function. Second is the quantitative expression level of the gene responsible for inflammatory mediators/cytokines assessed through real-time polymerase chain reaction. This genetic control may be due to mutation of the promoter region of the gene.

This study was performed to investigate the polymorphisms in the ABCG2 (ATP-binding cassette sub-family G member 2) gene and to reveal the association of genotypes with breeding value (BV) for first lactation milk yield and milk composition traits of Karan Fries (HF crossbred) cattle. The traits were adjusted against the significant effect of non-genetic factors. PCR-RFLP analysis of ABCG2 (exon 14) gene revealed three genotypes. AA genotype in ABCG2 gene had significant effect on BV for average test day fat percentage. The identified potential genetic marker could be used for the development of Marker Assisted Selection (MAS) strategy for higher milk yield and milk composition traits in Karan Fries Cattle.

First lactation records of 351 Karan-Fries cows born to 27 bulls, having 3 or more progeny were used to evaluate sires by animal model (AM). Heritabilities, genetic and phenotypic correlations between the traits were estimated by univariate and bivariate linear animal models. The heritability estimates for 305 days or less milk yield (305MY), fat based energy corrected milk yield (FECMY), fat protein based energy corrected milk yield (FPECMY) and fat protein lactose based energy corrected milk yield (FPLECMY) were 0.23, 0.65, 0.11 and 0.39, respectively. There was a high (0.99) genetic and phenotypic correlation between 305MY, FECMY and FPLECMY. The high and positive genetic correlations between energy traits are indication of common genetic and physiological mechanism governing these traits. Comparison of ranks of the sires based on 305MY, FECMY and FPLECMY by animal model depicted a notable100 per cent level of similarity except for FPECMY in which the ranks were entirely different. There was a high heritability and genetic correlation between FECM and FPLECM. Genetic evaluation of Karan-Fries bulls based on energy corrected milk yield will increase the accuracy of selection than the conventional mil yield evaluation. It can help in mitigating the nutritional insecurity of the country in the long run.

Aim: The present study was performed to investigate the effect of genetic and non-genetic factors affecting milk fat yield and to estimate genetic parameters of monthly test day fat yields (MTDFY) and lactation 305-day fat yield (L305FY) in Murrah buffaloes. Materials and Methods: The data on total of 10381 MTDFY records comprising the first four lactations of 470 Murrah buffaloes calved from 1993 to 2014 were assessed. These buffaloes were sired by 75 bulls maintained in an organized farm at ICAR-National Dairy Research Institute, Karnal. Least squares maximum likelihood program was used to estimate genetic and non-genetic parameters. Heritability estimates were obtained using paternal half-sib correlation method. Genetic and phenotypic correlations among MTDFY, and 305-day fat yield were calculated from the analysis of variance and covariance matrix among sire groups. Results: The overall least squares mean of L305FY was found to be 175.74±4.12 kg. The least squares mean of overall MTDFY ranged from 3.33±0.14 kg (TD-11) to 7.06±0.17 kg (TD-3). The h 2 estimate of L305FY was found to be 0.33±0.16 in this study. The estimates of phenotypic and genetic correlations between 305-day fat yield and different MTDFY ranged from 0.32 to 0.48 and 0.51 to 0.99, respectively. Conclusions: In this study, all the genetic and non-genetic factors except age at the first calving group, significantly affected the traits under study. The estimates of phenotypic and genetic correlations of MTDFY with 305-day fat yield was generally higher in the MTDFY-5 of lactation suggesting that this TD yields could be used as the selection criteria for early evaluation and selection of Murrah buffaloes.

Heat stress has adverse effects on the reproductive performances of dairy cattle and buffaloes. The dairy sector is a more vulnerable to global warming and climate change. The temperature humidity index (THI) is the widely used index to measure the magnitude of heat stress in animals. The objective of this paper was to assess the decline in performances of reproductive traits such as service period, conception rate and pregnancy rate of dairy cattle and buffaloes with respect to increase in THI. The review stated that service period in cattle is affected by season of calving for which cows calved in summer had the longest service period. The conception rate and pregnancy rate in dairy cattle were found decreased above THI 72 while a significant decline in reproductive performances of buffaloes was observed above threshold THI 75. The non-heat stress zone (HSZ) (October to March) is favorable for optimum reproductive performance, while fertility is depressed in HSZ (April to September) and critical HSZ (CHSZ) (May and June). Heat stress in animals has been associated with reduced fertility through its deleterious impact on oocyte maturation and early embryo development. The management strategies viz., nutrition modification, environment modification and timed artificial insemination protocol are to be strictly operated to ameliorate the adverse effects of heat stress in cattle and buffaloes during CHSZ to improve their fertility. The identification of genes associated with heat tolerance, its incorporation into breeding program and the inclusion of THI covariate effects in selection index should be targeted for genetic evaluation of dairy animals in the hot climate.

A study was conducted on calving records of Murrah buffaloes to study the influence of various functional traits on subsequent reproductive performance. The effects of calving abnormalities, uterine health problems, female fertility problems and udder health problem on calving to first service (CFS), service period (SP), dry period (DP) and calving interval (CI) were studied by the least-squares method using the SAS package. The increase in CFS, SP, DP and CI was 27.07%, 18.71%, 96.74% and 6.70%, respectively. Subsequently, the average milk yield per day of calving interval was found to be reduced (from 4.91 to 2.10 kg/day) in these animals in comparison with the normal calvers. A highly significant increase in average CFS, SP, DP and CI was found among animals susceptible to metritis (16.93%, 73.88%, 53.92% and 20.04%, respectively). The decrease in average milk yield per day of calving interval (MY/CI) was 18.55% in comparison with the animals not affected by metritis. The average MY/CI was obse...

The productive and reproductive performances of dairy animals have direct effect to milk production and profitability of dairy enterprise. The present study was carried out to analyse the productive and reproductive performance of cattle and buffaloes reared under farmers’ management in three states of differential dairy progress in India. Haryana, Maharashtra and Odisha states were purposively selected from highly, moderately and least dairy progressive states, respectively. The total sample size was 900 containing 300 dairy farmers from each state. The finding shows that the productive and reproductive performances of buffalos in Haryana are better than Maharashtra and Odisha. The productive and reproductive performances of Crossbred were found better in Haryana as well as Maharashtra than Odisha. In Haryana, very few farmers reared Indigenous cattle but the performances were better than Maharashtra and Odisha. The better performance of Haryana may be due to being home track of elite Murrah buffalo, Tharparker and Sahiwal breeds of Indigenous cattle, agro-climatic situations, veterinary services and managerial skills of dairy farmers. To improve the productive and reproductive performance of dairy animals in the moderately progressive (Maharashtra) and least progressive (Odisha) states efforts should be focused on breed improvement, better veterinary infrastructure and enhance the managerial skills of the farmers

Early selection of bulls having optimum age at first semen freezing play an important role in improving reproductive performance in a dairy herd. Twenty seven years data (1987-2013) on age at first semen freezing (AAFSF), conception rate based on first A.I. (CRFAI) , overall conception rate (OCR) and birth weight (B.WT) of 41 Sahiwal bulls belonging to 8 sets of Sahiwal improvement programme at ICAR-National Dairy Research Institute, Karnal, Haryana, India; were adjusted against environmental effects and subsequently analysed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Among the three developed models (I to III), it was observed that Model III having age at first semen freezing and birth weight fulfil the accuracy of model i.e.; having high coefficient of determination (R2) value (CRFAI = 67% and OCR= 69%), low mean error sum of square (MSSe), low conceptual predictive value (CP value) and low Bayesian information criterion (BIC). The results revealed that optimum age at first semen freezing of Sahiwal bulls should be 2.5 - 3.0 years for 3.10% higher conception rate based on first A.I. (48.86%) and 4.39% higher overall conception rate (48.78%) in comparison to Sahiwal bulls with more than 3.5 years of age (CRFAI :- 45.76% and OCR :- 44.39%).

The study was conducted to identify the genetic variability in exon 5 region of GH1 gene and quantify its effect on production performance in Karan Fries cattle.PCR-RFLP method using Alu I restriction endonuclease was used for identification of genotypes. LL and LVgenotypes with frequencies as 0.46 and 0.54 and the frequency of L allele as 0.73 were found. Season of calving was only found significant (p £0.05) for fat yield of TD3, TD6 and TD10. The effect of SNP of GH1 gene (exon 5) increased the overall test day milk yield, fat yield and SNF yield by 1.05 kg, 43.2 gm and 103 gm.High correlations were obtained from TD3 onwards between test day traits and lactation milk yield indicating that selection based on identified SNP in TD3 increased test day milk yield, fat yield and SNF yield by 2.5229 kg, 62.9 gm and 215.9 gm, respectively.

The present study was conducted to identify the most suitable temperature humidity index (THI) model among seven reported THI models for analyzing the impact of thermal stress on monthly test day fat % (MTDF%),monthly test day SNF% (MTSNF%), monthly test day fat yield (MTDFY) and monthly test day SNF yield (MTDSNFY) of Murrah buffaloes at subtropical climatic conditions of Karnal, India. A total of 8868 MTDF% and 8606 MTDSNF% records from 1107 lactational records of Murrah buffaloes under five parities were included in the present study and weather information on dry bulb temperature (Tdb), wet bulb temperature (Twb) and relative humidity (RH in %) for the corresponding period of 20 years (March 1994- December 2013) were collected from ICAR-NDRI and ICAR-CSSRI, Karnal, respectively. The overall least-squares means for MTDF% ranged from 7.71 ± 0.067 in TD1 to 8.10 ± 0.08 in TD 9 and MTDSNF% ranged from 9.61 ± 0.01 in TD5 and TD 6 to 9.65 ± 0.01 in TD 8. The overall least squares means of MTDFY (g) ranged from 411.23 ± 14.74 to 745.98 ± 13.57 while for MTDSNFY (g) the value ranged from 491.90 ± 17.21 to 922.16 ± 15.17. Monthly average THI was computed for each of the seven models. The lowest monthly average THI value was found in January, while either May, June or July showed the highest average THI value for all seven THI models. Regression analysis was performed for identifying the best THI to assess the impact of heat stress on milk constituent traits under study anda negative association was found between the milk constituent traits and monthly average THI values.The THI model[THI = (0.55 × Tdb + 0.2 × Tdp) × 1.8 + 32 + 17.5]developed by NRC(1971)was identified as the most suitable THI model to assess the impact of heat stress on milk composition traits of Murrah indicating maximum decline in MTDF% (-0.005), MTDFY (-0.68 g),MTDSNF% (b=-0.0008) and MTDSNFY (-2.25 g) per unit rise in THI.

Aim The study was conducted at Artificial Breeding Research Centre, NDRI, Karnal, to determine the sexual behavior and its relationship with semen quality parameters in Sahiwal breeding bulls. Materials and methods A total of 63 ejaculates were collected from six adult Sahiwal bulls (age ~47 mo and bwt ~466 kg), to study the relationship of sexual behavior and semen quality. The degree of association between different variables was estimated by Pearson's correlation coefficient method. Results The results depicted that, sexual aggressiveness showed significantly high positive correlation with libido score (LS) and sexual behavior score (SBS). Reaction time (RT) and total time taken in mounts (TTTM) had a significant negative correlation with LS and SBS. Penile erection score and penile protrusion score (PPS) both had a significant positive correlation with ejaculatory thrust score, mating ability score, and SBS. Results of correlation among seminal attributes and with sexual behavior depicted that ejaculate volume had positive significant correlation with initial progressive motility (IPM), sperm concentration (SCON), head abnormality, total abnormality, hypo-osmotic swelling test (HOST), acrosomal integrity (AI) whereas, mass activity had positive significant correlation with IPM, SCON, non-eosinophilic spermatozoa count (NESC), HOST, AI, RT and TTTM and IPM had positive significant correlation with SCON, NESC, HOST, AI, and TTTM, whereas and HOST had positive significant correlation with AI. Among seminal attributes, SCON had a positive significant correlation with PPS where as head abnormalities had a positive significant correlation with RT and TTTM. Conclusion It can be concluded that the relationship of sexual behavior and semen quality parameters are reflecting that the sexual behavior of individual bulls is important to harvest good quality and quantity of semen as desired type of sexual preparation can be provided.

Aim: The aim of the present investigation was to optimize the age at first use (AAFU) of semen of Murrah breeding bulls, which will help in early selection of bulls under progeny testing program for improving the reproductive performance in the herd. Materials and Methods: The data on AAFU, conception rate based on first A.I. (CRFAI), overall conception rate (OCR), and birth weight (B.WT) of 57 Murrah bulls during 1993-2014 at NDRI center pertaining to 14 sets of Network Project on Buffalo Improvement at ICAR-National Dairy Research Institute, Karnal, Haryana, India were adjusted for significant environmental influences and subsequently analyzed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Murrah breeding bulls. Comparative evaluation of three developed models (I-III) showed that Model III, having AAFU and B.WT, fulfill the accuracy of model as revealed by high coefficient of determination, low mean sum of squares due to error, low conceptual predictive value, and low Bayesian information criterion. Results: The results revealed that the average predicted CRFAI was highest (39.95%) at 4.5 years of age at first A.I/use. Similarly, average predicted OCR was highest (41.05%) at 4.5 years of age at first A.I/use of Murrah bulls. Conclusion: In organized herd under progeny testing program, Murrah bulls should be used at young age, i.e. prior to 3.5 years, which is expected to result in 5.08% better CRFAI and 1.63% better OCR in comparison to Murrah bulls used after 4.5 years of age.

In this study genome-wide di-methylated H3K4 (H3K4me2) and tri-methylated H3K27 (H3K27me3) modification profiles were analyzed in spermatozoa of buffalo bulls having wide fertility differences. The custom designed 4 × 180 K buffalo (Bubalus bubalis) ChIP-on-chip array was fabricated by employing array-based sequential hybridization using bovine and buffalo genomic DNA for comparative hybridization. The buffalo specific array developed had 177,440 features assembled from Coding sequences, Promoter and CpG regions comprising 2967 unique genes. A total of 84 genes for H3K4me2 and 80 genes for H3K27me3 were found differentially enriched in mature sperm of high and sub-fertile buffalo bulls. Gene Ontology analysis of these genes revealed their association with different cellular functions and biological processes. Genes identified as differentially enriched between high and sub-fertile bulls were found to be involved in the processes of germ cell development, spermatogenesis and embryonic development. This study presents the first genome-wide H3K4me2 and H3K27me3 profiling of buffalo bull sperm. Results provide a list of specific genes which could be made responsible for differential bull fertility. J. Cell. Biochem. 116: 743–753, 2015. © 2014 Wiley Periodicals, Inc.

Aim: The aim of the present study was to assess the influence of temperature and humidity prevalent under subtropical climate on the breeding values for fertility traits viz. service period (SP), pregnancy rate (PR) and conception rate (CR) of Murrah buffaloes in National Dairy Research Institute (NDRI) herd. Materials and Methods: Fertility data on 1379 records of 581 Murrah buffaloes spread over four lactations and climatic parameters viz. dry bulb temperature and relative humidity (RH) spanned over 20 years (1993-2012) were collected from NDRI and Central Soil and Salinity Research Institute, Karnal, India. Monthly average temperature humidity index (THI) values were estimated. Threshold THI value affecting fertility traits was identified by fixed least-squares model analysis. Three zones of non-heat stress, heat stress and critical heat stress zones were developed in a year. The genetic parameters heritability (h 2 ) and repeatability (r) of each fertility trait were estimated. Genetic evaluation of Murrah buffaloes was performed in each zone with respect to their expected breeding values (EBV) for fertility traits. Results: Effect of THI was found significant (p

Aim: The aim was to estimate genetic parameters of weekly test-day (TD) milk yields and first lactation 305-day milk yield (FL305DY) in Murrah buffaloes. Materials and Methods: The data on 39059 weekly test-day milk yield (WTDY) records during first lactation of 961 Murrah buffaloes calved from 1977 to 2012 and sired by 101 bulls maintained in an organized farm at National Dairy Research Institute, Karnal was analyzed to study the effect of genetic and non-genetic factors. Least squares maximum likelihood program was used to estimate genetic and non-genetic parameters affecting WTDY and FL305DY. Heritability was estimated using paternal half-sib correlation method. The genetic and phenotypic correlations among WTDY and 305- day milk yield was calculated from the analysis of variance and covariance among sire groups. Results: The least squares means for FL305DY was found to be 1853.49±15.88 Kg. The least squares means of overall WTDY ranged from 2.44±0.07 kg (TD-43) to 7.95±0.06 kg (TD-8). Effect of period, season and age at first calving groups was found to be highly significant (p

Aim: The present investigation was conducted for evaluating the efficacy of estimating breeding values (BVs) using univariate animal model in comparison to sire model. The various parameters considered for evaluating the efficiency of both linear models were coefficient of determination (R 2 ), coefficient of variation (CV), within sire variance or error variance and spearman's rank correlation estimates. Materials and Methods: Data for the present investigation were spread over a period of 34 years from 1978 to 2012 and consisted of a total of 1988 lactation records of Holstein Friesian crossbred cows sired by 186 crossbred bulls. Results: The percentage of sires having BV (estimated by animal model) more than the average BV for the traits viz. age at first calving (AFC), first service period (FSP), first lactation length (FLL), first calving interval (FCI), first lactation 305 day milk yield (F305MY), first lactation total milk yield (FTMY), milk yield per day of first lactation length (MY/FLL) and milk yield per day of first calving interval (MY/FCI) were 48.05, 49.39, 55.07, 49.21, 50.00, 51.39, 48.67, 50.39%, respectively. The animal model had higher R 2 , lower CV and error variance for most of the fertility and production traits. The spearman's rank correlation estimates indicated similarity of rankings by both the linear models as the animal model is an improvement of sire model. Conclusion: Animal model had a wider range of BVs indicating the greater differentiating ability of the model. Based on R 2 , CV and error variance animal model was found to be superior in comparison to sire model.

The investigation was carried out on 1,629 calving records of 462 Sahiwal cows calved between 1988 and 2013 at National Dairy Research Institute, Karnal, Haryana, India to study culling pattern as well as the effect of selection on milk production. Average culling and mortality rate per lactation of Sahiwal cows were 23.82 and 4.54%, respectively. The culling was found due to teat and udder problems (32.47%), followed by reproductive problems (22.73%) and low milk production (10.82%) in the herd. Most of the voluntary culling (based on the low milk yield) was observed during second and third lactations. Stage of lactation and milk yield had significant influence on culling during first lactation whereas, period had significant influence on culling during second lactation. Sahiwal cows yielding more than 8 kg of milk/day were less likely to cull and the probability of culling of cows increased after the completion of 360 days of first lactation. Most probable producing ability of per day milk yield [MPPA (PDMY)] was estimated for selected and culled cows. There is an intense need to minimize the involuntary culling of cows by providing better feeding and management so that more of cows can be saved in herd, which will in turn facilitate in increasing selection intensity and selection differential in the herd and ultimately help in faster genetic improvement of Sahiwal cows.

Premature disposal of female calves before reaching milch herd and undesirable disposal of lactating cows are the major constraints in achieving larger herd size. During the early lactations, younger cows are supposed to give higher milk yield and undesirable disposal of early calvers, thereby, greatly hampers profitability of a dairy farm. Knowledge of the incidence of disposal along with reasons in various age groups and at various parities is essential to identify which age group or parity is more vulnerable for disposal. Moreover, knowledge of various genetic and non-genetic factors associated with disposal of animals may also be helpful in developing breeding and management strategies to reduce the incidence of disposal. In most of the studies, it was found that major reasons of disposal of dairy cattle were mortality among female calves and involuntary culling among adult lactating cows. Maximum mortality in female calves was observed during earlier ages and pneumonia, gastro-enteritis and debility were major reasons of female calf mortality. Whereas, most of the adult cows left the herd, due to teat and udder and reproductive problems. Moreover, indigenous breeds were found to be more adapted to Indian tropical climatic conditions in comparison to crossbred and exotic cattle breeds.