Ranking Of Sires Research Articles

Transgenerational effects of the maternal gestational environment on the post-natal performance of beef cattle: A reaction norm approach.

In tropical beef cattle production systems, animals are commonly raised on pastures, exposing them to potential stressors. The end of gestation typically overlaps with a dry period characterized by limited food availability. Late gestation is pivotal for fetal development, making it an ideal scenario for inter- and transgenerational effects of the maternal gestational environment. Intergenerational effects occur due to exposure during gestation, impacting the development of the embryo and its future germline. Transgenerational effects, however, extend beyond direct exposure to the subsequent generations. The objective of the present study was to verify these effects on the post-natal performance of zebu beef cattle. We extended the use of a reaction norm model to identify genetic variation in the animals' responses to transgenerational effects. The inter- and transgenerational effects were predominantly positive (-0.09% to 19.74%) for growth and reproductive traits, indicating improved animal performance on the phenotypic scale in more favourable maternal gestational environments. Additionally, these effects were more pronounced in the reproductive performance of females. On average, the ratio of direct additive genetic variances of the slope and intercept of the reaction norm ranged from 1.23% to 3.60% for direct and from 10.17% to 11.42% for maternal effects. Despite its relatively modest magnitude, this variation proved sufficient to prompt modifications in parameter estimates. The average percentage variation of direct heritability estimates ranged from 19.3% for scrotal circumference to 33.2% for yearling weight across the environmental descriptors evaluated. Genetic correlations between distant environments for the studied traits were generally high for direct effects and far from unity for maternal effects. Changes in EBV rankings of sires across different gestational environments were also observed. Due to the multifaceted nature of inter- and transgenerational effects of the maternal gestational environment on various traits of beef cattle raised under tropical pasture conditions, they should not be overlooked by producers and breeders. There were differences in the specific response of beef cattle to variations in the quality of the maternal gestational environment, which can be partially explained by transgenerational epigenetic inheritance. Adopting a reaction norm model to capture a portion of the additive variance induced by inter- or transgenerational effects could be an alternative for future research and animal genetic evaluations.

Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle

BackgroundMany phenotypes in animal breeding are derived from incomplete measures, especially if they are challenging or expensive to measure precisely. Examples include time-dependent traits such as reproductive status, or lifespan. Incomplete measures for these traits result in phenotypes that are subject to left-, interval- and right-censoring, where phenotypes are only known to fall below an upper bound, between a lower and upper bound, or above a lower bound respectively. Here we compare three methods for deriving phenotypes from incomplete data using age at first elevation (> 1 ng/mL) in blood plasma progesterone (AGEP4), which generally coincides with onset of puberty, as an example trait.MethodsWe produced AGEP4 phenotypes from three blood samples collected at about 30-day intervals from approximately 5,000 Holstein–Friesian or Holstein–Friesian × Jersey cross-bred dairy heifers managed in 54 seasonal-calving, pasture-based herds in New Zealand. We used these actual data to simulate 7 different visit scenarios, increasing the extent of censoring by disregarding data from one or two of the three visits. Three methods for deriving phenotypes from these data were explored: 1) ordinal categorical variables which were analysed using categorical threshold analysis; 2) continuous variables, with a penalty of 31 d assigned to right-censored phenotypes; and 3) continuous variables, sampled from within a lower and upper bound using a data augmentation approach.ResultsCredibility intervals for heritability estimations overlapped across all methods and visit scenarios, but estimated heritabilities tended to be higher when left censoring was reduced. For sires with at least 5 daughters, the correlations between estimated breeding values (EBVs) from our three-visit scenario and each reduced data scenario varied by method, ranging from 0.65 to 0.95. The estimated breed effects also varied by method, but breed differences were smaller as phenotype censoring increased.ConclusionOur results indicate that using some methods, phenotypes derived from one observation per offspring for a time-dependent trait such as AGEP4 may provide comparable sire rankings to three observations per offspring. This has implications for the design of large-scale phenotyping initiatives where animal breeders aim to estimate variance parameters and estimated breeding values (EBVs) for phenotypes that are challenging to measure or prohibitively expensive.

Using Australian genomics to predict dairy cattle performance in New Zealand

Context The national breeding objective in New Zealand (NZ) was designed with the intention to breed dairy cows that efficiently convert feed into profit. The breeding worth index (BW) is used to rank bulls and cows according to their ability to meet this objective. The Australian equivalent to BW is the balanced performance index (BPI). These selection indexes represent national economic weights for important traits in dairy industry in each country. The introduction of Australian genomics has allowed the selection and ranking of young sires from around the world on BPI. Aims This study aims to demonstrate the relationship between different traits and selection indexes in Australia (AU) and NZ by comparing sires with daughter proofs in both countries and the validity of predicting BW for NZ sires using Australian genomic predictions and regression equations. Methods Data files for sires with daughters in both AU and NZ were merged to identify common bulls used in both countries. An analysis was conducted to determine whether Australian breeding values (ABVs) for sires could be used to predict the performance of the sires that have no progeny in NZ. ABVs for nine traits in BW were converted to their equivalent NZ breeding values (NBVs) and used to calculate an index equivalent to BW. Key results On the basis of a regression equation, a new index called genomic New Zealand index (gNZI) for selecting sires for NZ dairy herds was developed. The correlation coefficients between gNZI and BW in Holstein Friesian (HF), Jersey, and Red breeds were 0.90, 0.91, and 0.88 respectively. Conclusions The regression equation from genomic ABVs to produce gNZI was a reliable genomic predictor of future BW for sires with insufficient ancestry information in NZ and to enhance the ancestry proofs and increase the reliability of selecting young NZ-born bulls. Implications The high correlations between traits in AU and NZ and the simple proposed conversion method can build industry confidence when selecting young bulls using gNZI, as genomic prediction of BW through New Zealand Animal Evaluation (NZAEL) is not currently available.

Breeding practices and traits preference in dairy cattle in Gedeo agroforestry of Ethiopia

The study was conducted to identify breeding practices and traits preferences of the dairy cattle producers in the southern part of Ethiopia. Representative sample households were selected by SRS (Simple Random Sampling) techniques. A cross-sectional survey with a structured questionnaire was used to collect the data on the purpose of keeping dairy cattle, herd composition, source of dairy cattle, trait preference, and breeding practices performed by the farmers. The data were analyzed using statistical software SPSS 27, and chi-square was used to compare categorical variables. The herd composition of the Bule district is significantly different from the rest of the districts in the mean number of calves, heifers, and bulls. The Yirgachefe district significantly differs in the mean number of cows compared to other districts. The breed preference of most farmers (81.67%) is cross-bred bulls (Jersey and Holstein Frisian). There are not enough bulls on the farms; only 21.7% of them have a breeding bull, and the primary sources of bulls in the study community are the grazing areas and the neighbors. Respondents preferred artificial insemination (96.1%) to natural mating. Milk yield, appearance, and genotype were important traits in selecting a dam, whereas genotype, appearance, and fast growth rate were the most preferred traits in sire ranking. The farmers' breeding objectives were to improve milk production and increase cash income. Therefore, establishing a village-based mating program for the genetic improvement of dairy cattle in the study area is recommended to overcome the shortage of bulls.

Consequences of specialized breeding in the Swedish Warmblood horse population.

In many European warmblood studbooks, clear specialization toward either jumping or dressage horses is evident. The Swedish Warmblood (SWB) is also undergoing such specialization, creating a possible need for separate breeding programs and a discipline-specific Young Horse Test (YHT). This study investigated how far specialization of the SWB breed has proceeded and the potential consequences. Individuals in a population of 122,054 SWB horses born between 1980 and 2020 were categorized according to pedigree as jumping (J), dressage (D), allround (AR), or thoroughbred (Th). Data on 8,713 J horses and 6,477 D horses assessed for eight traits in YHT 1999-2020 were used to estimate genetic parameters within and between J and D horses and between different periods. Future scenarios in which young horses are assessed for either jumping or dressage traits at YHT were also analyzed. More than 80% of horses born in 1980-1985 were found to be AR horses, while 92% of horses born in 2016-2020 belonged to a specialized category. The average relationship within J or D category was found to increase during the past decade, whereas the relationship between these categories decreased. Heritability estimates for gait traits were 0.42-0.56 for D horses and 0.25-0.38 for J horses. For jumping traits, heritability estimates were 0.17-0.26 for J horses and 0.10-0.18 for D horses. Genetic correlations between corresponding traits assessed in J and D horses were within the range 0.48-0.81, with a tendency to be lower in the late study period. In the future scenarios, heritability and genetic variance both decreased for traits that were not assessed in all horses, indicating that estimation of breeding value and genetic progress for these traits could be affected by a specialized YHT. However, ranking of sires based on estimated breeding values (EBVs) and accuracy of EBVs was only slightly altered for discipline-specific traits. With continued specialization in SWB, specialization of the YHT should thus be considered.

Development of breeding values for susceptibility to virulent footrot in sheep: A strategy to accommodate variable disease progression at time of scoring

Genetic evaluations utilising footrot scores from industry flocks in their essence, incorporate data from a wide range of challenge environments, resulting in potentially large differences in means, variances and distribution of scores across challenges. The date that commencement of infection occurs is generally unknown, and progression of the infection varies with the prevailing environmental and management conditions, virulence of the bacterium Dichelobacter nodosus, as well as the genetic potential and (permanent) environmental ability of animals to resist footrot. In practice, animals are unlikely to be repeatedly scored to identify the best time for comparison, or monitor development of disease progression. Furthermore, field challenges are limited by the need to treat animals before their welfare is compromised. Therefore, the duration and intensity of infection varies and this affects comparisons between animals for their susceptibility. Diseases such as footrot are characterised by multiple categorical scores reflecting clinical stages that describe the progression and relative impact of the disease. This provides the opportunity for the transformation of the data to a standardised prevalence. Scoring events from multiple footrot field challenges under a standardised protocol were used to establish a series of transition matrices to describe disease progression between scores over time. These transition matrices were used to standardise challenge events to the more severe scoring events, observed later in the challenge. The accuracy of the transition technique was tested by comparing the ranking of animals and sires against the observed scores. Transitioning the data from low disease prevalence to the higher prevalence at the subsequent scoring event improved the correlations between the scoring events, at the animal level, by upwards of 0.10 across challenges. The utilisation of a transition matrix to transform low prevalence disease challenges by taking into account the natural biological rate of progression through the clinical stages of the disease provides a more accurate technique to account for variation in disease prevalence. The transition technique increases the acceptable range of disease expression targeted by producers when scoring virulent footrot challenges reducing the need for repeat scoring and allowing earlier treatment and reducing the impact of the disease on the host animal.

Recent prediction tools for estimation of first lactation 305 days milk yield using monthly test days for genetic evaluation in crossbred cattle

First lactation 305 days milk yield (FL305DMY) of progenies is an important criteria for selection of sires. In field progeny testing programme, prediction of FL305DMY based on test day records will reduce the cost of recording. The present study was aimed at evaluating the efficiency of different methods of prediction for FL305DMY based on monthly test day milk yield records in Karan Fries cattle and evaluation of sires based on the performance of its progenies. Methods of prediction were Wood’s incomplete gamma function and Artificial neural network (ANN). Efficiency of prediction was compared using error of prediction. Root mean square error was least for ANN method (5.72%). The attempt was made to evaluate Karan Fries sires based on actual and predicted FL305DMY so obtained utilising BLUP- AM method of sire evaluation. The breeding values of 48 Karan Fries sires having 3 or more daughters were estimated. Comparison of ranking of sires based on different methods of prediction was done using Spearman’s Rank correlation and RMSE values. The sire evaluation using ANN method based predicted values showed marginally higher rank correlation (0.91) and least RMSE (2.39%) with actual yield based on monthly test day records. Thus it was concluded that recoding at monthly intervals and use of ANN and conventional fitting Wood’s function can be used for evaluation of sires. Though both the methods are equally efficient, ANN showed marginal superiority.

Genotype-environment interaction effects on weight gain in cattle using reaction norms

The existence of genotype-environment interaction (GEI) using reaction norm models and their impact on the genetic evaluation of Nellore sires for body weight at 120, 210, 365 and 450 days of age was verified. Three models were used: animal model (AM) that disregards GEI and the one-step reaction norm model with homogeneous and heterogeneous residual variance (1SRNMH_het). Bayes Inference via Gibbs Sampling was used to estimate the variance components. The AM model better fits to weights at 120 and 210 days of age, while 1SRNMH_het was more adequate for body weights at 365 and 450 days of age, suggesting the existence of GEI. The posterior means of direct heritability were 0.33±0.01 and 0.36±0.01 and maternal heritability of 0.21±0.01 and 0.19±0.01 for body weights at 120 and 210 days of age, respectively. For body weights at 365 and 450 days of age, posterior means of heritability varied along the environmental gradient, but the ranking of sires based on breeding values was not changed by different environmental gradients. All rank correlations were greater than 0.80, strongly suggesting a scale effect of GEI. Despite the evidence of GEI on post-weaning weight gain, it did not change the ranking of sires. Therefore, it did not have a relevant impact on the genetic evaluation of sires because they are robust to environmental changes.

Hair coat score in Angus cattle: Comparison of linear and threshold models, genetic gain and correlations with growth, morphological and reproductive traits

Hair coat traits are used as indicators of animal adaptation because of their importance for thermoregulation and parasites resistance. These traits are evaluated visually based on a score in some beef cattle breeding programs. Data from 38,800 Angus animals were used to compare linear and threshold animal models in order to validate genetic parameters for visual scores of hair coat at weaning (WHC) and yearling (YHC), and conformation (YC), precocity (YP) and muscling (YM) at yearling. The genetic trends for WHC and YHC and their relationships with YC, YP, YM, birth weight (BW), weight gain from birth to weaning (BWG) and from weaning to yearling (YWG), scrotal circumference (SC), and gestation length (GL) were also obtained. For WHC and YHC, higher heritabilities were estimated with the threshold models (0.249±0.039 and 0.295±0.041, respectively) compared to the linear models (0.188±0.029 and 0.218±0.032, respectively). However, similar heritabilities were obtained with the two models for YC, YP and YM. Rank correlations between sire breeding values predicted for WHC and YHC using linear and threshold models ranged from 0.75 to 0.95, considering the top 2 to 50% of the selected sires. For YC, YP and YM, small changes in sire ranking are expected when these models are used (rank correlations higher than 0.86), regardless of the proportion of selected sires. Cross-validation strategies by regression showed that genetic selection for all visual scores will also promote improvements in phenotypic performance. Genetic trends were significant (P<0.05) and favorable for WHC and YHC. The genetic correlation between WHC and YHC was high and positive (0.848±0.055). Favorable and moderate genetic associations were estimated for WHC and YHC with YC, YP, YM, BWG and WYG, ranging from -0.329±0.108 to -0.589±0.07. The genetic correlations of WHC and YHC with BW, SC and GL were weaker and negative. According to our results, the threshold model is recommended for genetic evaluation of WHC and YHC in this population, and both models are indicated for YC, YP and YM. In general, genetic selection to increase growth, YC, YP, YM and SC will simultaneously reduce WHC and YHC, favoring animals that are more adapted to the environmental conditions of the tropics.

Genotype × environment interaction affects sire ranking for live weights in Avikalin sheep

Abstract The genotype by environment interaction alters the ranking of the animals at different ages in life due to the changing environment. This affects the selection efficiency of the breeding program. The objective of the present study was to compare the random regression model (RRM) and conventional animal models for better genetic evaluation of the Avikalin sheep. The genetic parameters were estimated for 7274 animals descended from 2418 dams and 409 sires for growth traits of Avikalin sheep, selected over 41 years (1976–2016). The RRM model of choice included a direct genetic, direct maternal, permanent environment for animal and maternal effects. The additive direct heritability (h2) using RRM for live weight at birth (BWT), three months (WWT), six months (6WT), nine months (9WT) and twelve months (12WT) were 0.18 ± 0.02, 0.28 ± 0.02, 0.35 ± 0.02, 0.45 ± 0.02 and 0.36 ± 0.02, respectively. The trends of variances in RRM were comparable to those trends obtained from the inclusive animal model that included the direct genetic, direct maternal and maternal permanent environmental components. The estimates of genetic correlation in RRM were higher (mostly

Sire selection and genetic improvement of dairy cattle assuming pure market competition

Breeding companies and farmers rely on selection indices to identify sires they expect to improve production system profitability. Such indices combine estimates of genetic merit for individual traits with corresponding economic values that are fixed based on circumstances at a particular time. Perfect market competition has also been proposed as an economic basis to value alternative sires. The objective of this study was to propose an economic model and develop it for the evaluation of dairy sires. The pure competition model (PUC) was used to evaluate the relationship between a profitability index based on the PUC approach versus the traditional selection index approach for 330 dairy sires comprising Holstein-Friesians, Jerseys, and Ayrshires. The correlation between these 2 selection indices was only 0.56, indicating that the conventional selection index did not correlate well with an index based on the PUC model. In particular, the higher ranking bulls were overvalued using the conventional selection index. Our study concluded that the use of fixed economic values is problematic for the delivery of consistent rankings in selection indices. In contrast, sire rankings based on PUC are more reliable because the sires are evaluated on the basis of efficiency gains rather than production while accounting for market prices and marginal values of dairy outputs over time.

Proximity sensors fitted to ewes and rams during joining can indicate the birth date of lambs

Knowing the birth date of lambs is important for the accuracy of breeding values, particularly when ranking potential sires for liveweight and growth. We used proximity sensors to measure the daily interactions between ewes and rams to test the hypothesis that the birth date of lambs could be predicted from the time of highest interactions between ewes and rams during joining. This was a pilot project with two plots of ewes (29 or 42 ewes per plot) and one ram per plot for a 26 day joining period. The day in which the ewe had the highest ratio of interactions with the ram relative to the other ewes in the plot was selected typically as the estimated day of conception. A threshold ratio of 1.5 was used which eliminated six ewes (the number of interactions between the ewe and ram compared with the average number of daily interactions for all ewes with the ram in the plot). The prediction of the date of birth was within five days of the actual birth date for 100% of the ewes (n = 55) and within two days for 82% of the ewes. Eighty five percent of the variation in date of birth of lambs was explained by the estimated date of conception. Using the remote sensors was a discreet way of measuring mating behaviour that proved to be a good tool for predicting the birth date of lambs. This can help breeders improve the accuracy of breeding values and the ranking of sires for early growth traits.

Efectos genéticos en el crecimiento predestete de corderos Hampshire

Se analizó en corderos Hampshire el peso a 30 días (P30; 1072) y al destete (P75; 1750) de 10 rebaños, para desarrollar dos objetivos: evaluar la expresión de los efectos genéticos en el crecimiento predestete, y analizar las posibles implicaciones en el progreso genético. Los análisis fueron univariados (ANAU) y bivariados (ANAB), a través de modelos mixtos que incluyeron los efectos fijos de grupos contemporáneos y la covariable de edad de la madre; y como aleatorios, los efectos genéticos directos y maternos, la covarianza genética entre ellos, y los efectos maternos de ambiente permanente. Se estimó la heredabilidad directa (h²) y materna (m²), las correlaciones genéticas (rdm), y los valores genéticos (VG). Con correlaciones de rango (CR) en los VG se analizó la jerarquización de la población y de los sementales; además, se analizaron las tendencias genéticas (TG) de los VG. La h² estuvo en el intervalo de 0.14±0.03 a 0.19±0.04; la m² en ANAU fue de 0.08±0.04 y 0.02±0.03, con estimación en ANAB de 0.22±0.05 y 0.13±0.03. La rdm del ANAU fue +1±0.15 en P30 y -1±0.18 en PD, cambiando en el ANAB a -0.46±0.10 y -0.20±0.07, respectivamente. El comportamiento de las TG en el ANAU estuvo asociada a la magnitud y el signo de las rdm; asimismo, las rdm del ANAU implicaron cambios en jerarquización de sementales, lo cual se vio reflejado en las TG y las CR.

Current situations of animal data recording, dairy improvement infrastructure, human capacity and strategic issues affecting dairy production in sub-Saharan Africa

An online survey on the state of existing dairy data, dairy improvement infrastructure and human capacity in sub-Saharan Africa (SSA) was undertaken with the aim of assessing whether the state of existing animal recording, dairy improvement methods and key issues facing dairy production together with means of addressing the issues differ among countries and regions of SSA. Respondents comprised experts and practitioners in livestock production and genetic resources from research institutes, animal breeding companies, universities, non-governmental organisations and government agricultural ministries. The main dairy farming system in which the respondents were involved was mixed crop-livestock system (30.2%), and this was mainly practised in the private land tenure system (46.3%). Data were analysed using linear model and paired Student t test in R software package. Respondents identified key issues affecting dairy production as poor genetic assessment of imported exotic breeds and crosses in Africa (62.3%), fluctuations in milk prices within both the formal and informal markets (50.9%), no comprehensive sire ranking systems (39.6%), housing and health management regimes which adversely affect milk yield (32.1%), poor market networks for dairy products (25.5%), poor feeding (13.3%), inadequate genetic technologies (9.4%) and poor animal performance recording systems (9.4%). Respondents emphasised the need for updated breeding policies, sire ranking systems, adequate farm management systems, capacity building, across-country collaborations and joint genetic assessments of dairy breeds found in sub-Saharan Africa. The current situation of dairy production though similar for the different countries, differed in order of emphasis and magnitude across the countries and regions in sub-Saharan Africa.

Genotype × birth type or rearing-type interactions for growth and ultrasound scanning traits in Merino sheep

This study explores the interaction between genetic potential for growth in Merino lambs and their birth type (BT) or rearing type (RT). Data on birthweight (BWT), weaning weight (WWT), post-weaning weight (PWWT), scan fat (PFAT) and eye muscle depth (PEMD) were used from 3920 single and 4492 twin-born lambs from 285 sires and 5279 dams. Univariate analysis showed a significant sire × BT interaction accounting for 1.59% and 2.49% of the phenotypic variation for BWT and WWT, respectively, and no significant effect for PWWT, PFAT and PEMD. Sire × RT interaction effects were much smaller and only significant for PEMD. Bivariate analysis indicated that the genetic correlation (rg) between trait expression in lambs born and reared as singles versus those born and reared as twins were high for BWT, WWT, PWWT (0.91 ± 0.02 – 0.96 ± 0.01), whereas rg for PFAT and PEMD were lower (0.81 ± 0.03 and 0.86 ± 0.02). The rg between traits expressed in lambs born and reared as singles versus those born as twins but reared as singles were lower: 0.77 ± 0.08, 0.88 ± 0.03, 0.66 ± 0.06 and 0.61 ± 0.08 for WWT, PWWT, PFAT and PEMD, respectively. A different RT only affected the expression of breeding values for PFAT and PEMD (rg 0.62 ± 0.04 and 0.47 ± 0.03, respectively). This study showed genotype × environment interaction for BWT and WWT (sire × BT interaction) and for PEMD (sire by RT interaction). However, sires’ breeding value of a model that accounts for sire × BT interaction provides a very similar ranking of sires compared with a model that ignores it, implying that there is no need to correct for the effect in models for genetic evaluation.

Sire Evaluation Based on First Lactation 305 Day Milk Yield and Monthly Part Lactation Records in Sahiwal Cattle

A total of 476 milk yield records of Sahiwal cows maintained at National Dairy Research Institute (NDRI) Karnal over a period of 51 years (1961-2011) were investigated and among which 371 animals completed their 305 days lactation length were used for the study, which are daughters of 51 sires with five or more progenies per sire. Sahiwal sires were evaluated on the basis of actual, predicted 305-DMY, expected breeding value based on 1st -3rd monthly part lactation milk yield records, expected breeding value based on 1st -6th and 1st -10th monthly part lactation milk yield records. It was inferred that the ranking of sires on the basis of FL305-DMY was significantly different from other criteria of selection.

Ranking quarter horse sires via models of offspring performance.

ABSTRACTThe 2016 Equibase data set of American Quarter Horse starts in North America was analyzed, with the purpose of ranking the sires of the racehorses. A speed z-score derived from the race times and distances was used as a racing performance measure. Mixed effects models were used on various subsets of the data based on race distance and sire offspring number. The sire categorical variable was considered as a random effect. Various statistical criteria were used to optimize the model. The constructed models were then varied in terms of the random and fixed effects included, and the conditional modes of the sire effects were extracted from these models. The benefit of the sire ranking that comes from this analysis is that it is controlled for track, jockey, trainer, weather, and several other variables that can impact speed. Sires are typically valued for high rankings for offspring earnings and winners. Yet a sire with a low stud fee may still produce offspring with a high ranking using our z-score model. The offspring of this bargain sire have the potential to produce fast offspring that could pay a dividend on a relatively low cost investment. The model sire ranking approach described in this paper is clearly bringing a new approach to the field of sire rankings.

Editing and modeling of milk production data for genetic evaluation of Murrah buffaloes

Abstract: The objective of this work was to assess the effect of editing and modeling of milk production data for genetic evaluation of Murrah buffaloes. Six strategies for evaluating milk production were analyzed: observed milk production (OMP); adjustment of milk production data to 305 (MP305) and 270 (MP270) days of lactation; removal of the 5 (MP5%) and 10% (MP10%) shortest lactation periods; and milk production along the lactation period as linear covariate (MPCO). Genetic parameters were estimated using the Bayesian inference, with heritability estimates of 0.19 to 0.23 and repeatability estimates of 0.35 to 0.36. Sires classified by OMP were high correlated to those classified by the other models, however, correlations to MP270, MP305 and MPCO decreased when considering only the best 20% sires. OMP showed greater differences in absolute mean deviations when compared with MPCO, MP270 and MP305. The strategies of analysis had similar heritabilities and stabilities. However, changes in the ranking of sires with better classifications, due to overestimation of genetic values, as occurred in the models MP305, MP270 and MPCO, may lead to a decrease in the genetic progress of the herd.

Evaluation of Sires Using Different Sire Evaluation Methods on the Basis of First Lactation Traits in Sahiwal Cattle

The records of 1367 crossbred cattle sired by 112 bulls were analysed to estimate breeding values and to compare various methods of sire evaluation viz. BLUP, LSM and sire evaluation methods on the basis of age at first calving, first service period, first lactation period, first dry period, and first calving interval. The average breeding value for FLMY. FLL, AFC, FCI, and FDP were estimated as 1711.63 kg, 320.38 days, 1299.54 days, 524.25 days and 207.60 days by method, 1941.16 kg, 321.60 days, 1287.12 days, 514.86 days and 195.57 days by LSM method and 1890.06 kg, 313.70 days, 1281.25 days, 508.56 days and 194.46 days by BLUP method. The accuracy, efficiency and stability of EBV’s of sires for the first lactation and lifetime traits were compared by different methods to judge their effectiveness. The estimated breeding values of sires for all the first lactation traits by , LSM and BLUP revealed that EBV’s of sires estimated by least squares method showed smaller genetic variation in comparison to and BLUP methods. The LSM was adjudged as the most efficient method of sire evaluation. The LSM had minimum error variance for most of the first lactation traits and considered to be more superior over other two methods i.e., and BLUP. The product moment correlations among the estimated breeding value of sires for first lactation traits by , LSM and BLUP methods ranged from medium to very high and significant (P<0.01) in all the three methods of sire evaluation. The rank correlations among the breeding value of sires estimated based on first lactation traits were medium to high and significant (P<0.01). The results indicated that least square method (LSM) had the lower error sum of square for all the first lactation traits and least square method (LSM) is relatively more accurate as compared to best linear unbiased prediction (BLUP) method but not overall. The LSM had higher R2 value for the first lactation traits as 40.50% (FLMY), 18.17% (FLL), 23.94% (FCI), 24.59% (FDP) and 48.47% (AFC) than the BLUP method. The estimated R2 values are less which indicates that both methods are less suitable for present data. Therefore as for as stability is concerned among the methods of sire evaluation, the LSM method was most stable being its CV (%) which is closest to the CV (%) of unadjusted data. The rank correlations obtained were highest and statistically significant (P<0.01) and ranged from 0.74 ( and BLUP) to 0.88 ( and LSM). The highest rank correlations among the breeding values estimated from different methods revealed that rankings of sires were similar to the extent of 74 to 88 per cent from these methods of sire evaluation.

Genetic Parameters and Sire Ranking for the Adjusted Estimate of Mozzarella Cheese Production in Italian Mediterranean Buffalo

The objectives of this study were to investigate the effect of adjusting mozzarella cheese production (APKM) compare to the unadjusted PKM on genetic parameters and sire ranking in Italian buffalo. 337,158 lactation records at 270d, from years 1997 to 2014, up to fifth parity, of 136,525 animals were analyzed. Estimated Breeding Values (EBVs) for APKM and PKM were predicted by BLUP-Animal Model with the fixed effects of age-parity, days-open, and contemporary-group; and the random factors of animal, permanent environmental and residuals. APKM showed lower heritability (0.23) than that of PKM (0.31) which might be due to the lower genetic correlation between APKM and milk yield (MY) (0.09) compared to that of PKM with MY (0.25). APKM positively changed sire ranking with increasing rank of sire with positive EBVs of Protein and Fat percentage, and decreasing rank of sire with negative EBVs of Protein and Fat percentage. Due to the larger correlation between PKM and MY, by selecting through the PKM, one risk is to increasing the number of buffalo that produce more milk, not optimal for making mozzarella cheese. Whereas, genetic selection through the APKM will increase the number of high-yielding buffalo with positive EBVs for Protein and Fat percentage