Covariance Components Research Articles

МОДЕЛИРОВАНИЕ СЕЛЕКЦИОННОГО ИНДЕКСА ДЛЯ АЙРШИРСКОЙ ПОРОДЫ МОЛОЧНОГО СКОТА С ИСПОЛЬЗОВАНИЕМ ЭКСТЕРЬЕРНЫХ ПОКАЗАТЕЛЕЙ

The article presents results of selection efficiency of potential parents in Ayrshire breed using IAYR multiple-factor selection index, which includes productivity traits such as milk yield, fat and protein yield and integrated exterior parametres: UDC udder index and FLC leg index. As an original data array, a sample was generated with parameters for milk productivity and exterior characteristics of 574 Ayrshire first-calf heifers, which are daughters of 21 bulls from the leading breeding farm of Leningrad region. Calculation of phenotypic and genetic correlations was carried out in the course of the study, which revealed the greatest paratypical relationship between milk yield and fat yield rp = 0.912 at p <0.001, and the highest genetic relationship was noted between milk yield and protein yield rg = 0.960 at p <0.001. A high value of heritability coefficient for milk yield was established, which amounted to h2 = 0.506, which is connected with usage of imported servicing bulls with high genetic potential for herd reproduction. To determine the values of index weight coefficients, the variance and covariance components of variability of the studied parametres were calculated. Economic components of the parametres included in the developed equation are formed. As a result of selection modeling with an intensity of 10% according to the constructed equation of the productive-exterior index IAYR, a significant and reliable advantage in milk production by 1899 kg of milk was established in comparison with other animals, in terms of fat yield - by 64.7 kg and protein yield - by 51.7 kg.

Multivariate quantitative genetic analysis of body weight traits in Corriedale sheep.

In the present study, an attempt was made to elucidate the genetic parameters for body weight traits of lambs from Corriedale sheep population at different ages. Data were collected from 6874 lambs born over a span of 49 years from 1969 to 2017. The traits under study included body weight atbirth (BW), weaning (WW), 6 months of age (6MW), 9 months of age (9MW) and yearling stage (YW). Data were statistically analyzed using restricted maximum likelihood (REML) algorithm in WOMBAT program. A multi-variate animal model was fitted to the data incorporating season andperiod of lambing, sex of lamb and litter size as fixed effects. Variance and covariance components were estimated using the animal model after incorporating direct additive genetic effect of animal as random factor. Genetic and phenotypic correlations with corresponding standard errors were also estimated. The heritability estimates for BW, WW, 6MW, 9MW and YW were 0.130 ± 0.023, 0.300 ± 0.029, 0.292 ± 0.030, 0.191 ± 0.025 and 0.169 ± 0.024, respectively. The genetic correlation between different traits under study was high, except between BW and 9MW for which the estimate was moderate. Phenotypic correlation ranged from low to high for different trait combinations. Among different traits under study, only two traits showed moderate heritability i.e. WW and 6MW while heritability of other traits was low. Both these traits showed high correlation with all subsequent traits. Selection programme for Corriedale sheep should be based on WW which is expressed early in life and shall lead to moderate geneticresponseto selection.

Analysis of (co) variance components and estimation of breeding value of growth and production traits in Dahlem Red chicken using pedigree relationship in an animal model.

Variance and covariance components of growth and production traits were analyzed employing REML animal model to assess the Dahlem Red (PD-3) chicken population for direct additive genetic, maternal effects and to estimate the estimated breeding value (EBV), genetic parameters, genetic trends and rate of inbreeding (ΔF) utilizing seven generation’s data. The generation and hatch had significant (P≤0.01) effect on the body weight at 0 day (BW0), 2 (BW2), 4 (BW4) and 6 weeks (BW6) and shank length at six weeks of age (SL6). The average least squares means (LSM) for BW6 and SL6 were 273.93±0.62 g and 53.97±0.05 mm, respectively. All the production traits were significantly (P≤0.01) influenced by generation and hatch. The average LSM for age at sexual maturity (ASM), egg production up to 40 weeks (EP40) and egg mass up to 40 weeks (EM40) were 168.82±0.25 d, 72.60±0.41 eggs and 4.21±0.07 kg, respectively. Model 5 with additive direct, maternal genetic, maternal permanent environmental and residual variance components was the best for BW0, BW2 and BW4 based on the AIC values obtained in WOMBAT. Model 4 was the best model for BW6, SL6, ASM, EP40 and EM40 with additive direct, maternal permanent environmental and residual variance components. Maternal effects were higher during early age, decreased with age, and remained present until 20 weeks of age. The heritability (h2) estimates were low to moderate in magnitude for all the growth traits and ranged from 0.02±0.03 to 0.19±0.03. The maternal heritability was high at hatch (0.35±0.06), decreased gradually until 4th week (0.02±0.01) and ceased afterwards. The heritabilities of EP40 (0.11±0.03) and EM40 (0.12±0.04) were low. The direct additive genetic correlations (ra) between BW2, BW4, BW6 and SL6 were high and positive (P≤ 0.05). The additive genetic and maternal permanent environmental correlation between EP40 and EM40 were high and positive (P≤ 0.05). The EBV of EM40 was significant (P≤ 0.05) with 0.48 kg/generation in PD-3 chicken at the end of the seventh generation. The EBV of EP40 showed an increasing trend with a genetic gain of 1.87 eggs per generation. The average inbreeding coefficient of the population was 0.019 and average ΔF was 0.007 over the last seven generations of selection. The EBV trends for primary and associated traits showed linear trends in the desired direction and negligible inbreeding.

The use of the spatial trend surface model to predict the distribution of health cadres from pharmacists in Wasit Governorate

Wasit governorate suffers from a poor distribution of health personnel from pharmacists, their concentration in some aspects, and their lack of others. In order to determine the pattern and distribution of the cadres of pharmacists, some of the spatial inference models were used in the prediction process to reach a fair distribution for pharmacists in the governorate, which is the trend surface model of the first, second and third degrees, reviewing the results using the Geo Data program. We estimated the trend surface model after assuming a certain spatial covariance function. In terms of parameters called covariance components, the components were estimated using the MLE method that adopted the Newton-Raphson iterative algorithm Then we compared these models to determine the best model that represents these data, using the criteria (AIC, BIC R2) and we concluded that the best model is the first-order trend surface model. To find out whether there is fairness in the distribution of pharmacists in the governorate the two statistical indicators were calculated the Lorenz curve and the Gini coefficient for the original and predicted data using the i-xplore program. The Lorenz curve showed the lack of equality in the distribution of pharmacists in the governorate and this was confirmed by the Gini coefficient, either for The data predicted, the Lorenz curve showed that there is fairness in the distribution of pharmacists within the governorate, and that the Gini coefficient proved that there is no discrepancy in the distribution.

Estimation of genetic parameters for pre-weaning growth traits in Central Anatolian Merino sheep

• Genetic parameters including maternal effects were estimated by this study. • Moderate heritability estimates were found for all pre-weaning growth traits. • Moderate negative genetic correlation was found between birth weight and weaning weight. • Moderate negative correlations were found between birth weight and average daily weight gain. • Remarkably low maternal heritability estimates were found for the traits. Quantitative traits such as pre-weaning growth is expressed as a result of combined genetic and environmental effects. The phenotypic expression of those traits in offspring is affected by direct genetic effect and sometimes also maternal genetic effect which is the ability of the dam to provide optimum nurturing conditions. The objective of the current study was to estimate genetic parameters for birth weight ( BW ), weaning weight ( WW ) and average pre-weaning daily weight gain ( ADWG ) in Central Anatolian Merino sheep. Observations of 9746 lambs descending from 171 rams and 2045 dams between 2014 and 2020 were included in the study. Generalized linear models were applied to determine the best fitting fixed effects model. Subsequently, the estimations of variance and covariance components were carried out by using the restricted maximum likelihood (REML) procedure applied on an animal linear mixed model including those significant effects on preceding analyses. In general, the direct heritability estimates of the traits were moderate for BW, WW and ADWG as found to be 0.22 ± 0.02, 0.32 ± 0.02 and 0.33 ± 0.02 respectively. On the other hand, maternal heritability estimates were considerably low for all traits with 0.04 ± 0.01 (BW), 0.03 ± 0.01 (WW) and 0.03 ± 0.01 (ADWG). The genetic correlations between BW and WW was moderate and negative as -0.30 ± 0.05 whereas, the phenotypic and residual correlations were close to zero. Similarly, the correlations between BW and ADWG were negative for all type of correlations. Especially, a moderate genetic correlation was found between the two traits as -0.37 ± 0.05. As expected, the correlations between WW and ADWG were quite high and positive for all type of correlations. The outcomes of the study will contribute to the world-wide sheep breeding literature with the crossbred performance of Merino and an indigenous sheep breed, as well as its parameters of interest in terms of designing breeding programmes with multi-trait selection indices.

ESTIMATE OF GENETIC AND PHENOTYPIC PARAMETERS FOR LITTER SIZE AND WEANING WEIGHT IN YANKASA SHEEP

Data on 964 and 1150 weaning weight and litter size records respectively, collected over a 10years period on Yankasa Sheep breeding project at the National Animal Production Research Institute (N.A.P.R.I), Zaria, were used in the study. The analysis was for estimation of genetic and phenotypic parameters for litter size and weaning weight in Yankasa sheep. Estimates of heritability for litter size and weaning weight were obtained from paternal half sib intraclass correlation. The genetic and phenotypic relationship between the litter size and weaning weight were estimated from the covariance and variance components of the two traits. Least squares means of 1.18±0.02 and 10.67±0.11 were obtained for litter size and weaning weight, respectively. Heritability (h2) estimates of 0.18±0.07 and 0.63±0.01 were obtained, respectively, for litter size and weaning weight. Genetic and phenotypic correlations of 0.83±0.052 and 0.23±0.094 respectively, were obtained, between weaning weight and litter size

Genetic analysis of litter size and number of kids born alive across parities in Spanish goat breeds using a random regression model

Genetic parameters of litter size (LS) and number of kids born alive (NBA) were estimated across parities in Florida and Payoya goat breeds using a threshold random regression model (RRM). We analysed the reproductive records for the Florida and Payoya breeds separately, and a total of 130.849 and 67.478 reproductive records from the first to the seventh parities from Florida and Payoya, respectively, were included in the analysis. Random regressions on Legendre polynomials of standardised parity were included for permanent environmental and additive genetic effects. We based our estimation of all the covariance components on Bayesian inference under categorical distribution and considered heterogeneous residual variances in the model. The estimates of heritabilities ranged from null to 0.37 for LS and from 0.02 to 0.20 for NBA, while the repeatability estimates were between 0.008–0.60 and 0.03–0.44 for LS and NBA, respectively. Phenotypic correlations within-trait along parities ranged widely from −0.31 to 0.97, while the genetic correlations within-trait through parities showed a wider range and magnitude of values, from −0.98 to 0.99 for LS and from −0.72 to 0.99 for NBA. The estimates of genetic correlations between LS and NBA in the different parities were positive in the first two parities and negative in the later ones. Due to the noticeable changes in variance and the incomplete genetic correlations, the use of a random regression model to analyse LS and NBA is recommended in goat breeds. HIGHLIGHTS A bivariate threshold random regression model has been used for the first time to estimate genetic parameters of litter size and number of kids born alive across parities in Spanish goat breeds. The evolution of genetic parameters along parities is different between Florida and Payoya that have different production systems, being more intensive in the case of the Florida breed. Estimates of variance were not constant across parities for both traits and breeds. Genetic correlations within-trait across parities were different from unity. Thus, LS and NBA should be treated as different traits in successive parities. Given that the estimates of variance and covariances are not constant across parities for both traits and breeds, the use of RRM is highly recommended.

Genetic analysis of growth, visual scores, height, and carcass traits in Nelore cattle.

Covariance components were estimated for growth traits (BW, birth weight; WW, weaning weight; YW, yearling weight), visual scores (BQ, breed quality; CS, conformation; MS, muscling; NS, navel; PS, finishing precocity), hip height (HH), and carcass traits (BF, backfat thickness; LMA, longissimus muscle area) measured at yearling. Genetic gains were obtained and validation models on direct and maternal effects for BW and WW were fitted. Genetic correlations of growth traits with CS, PS, MS, and HH ranged from 0.20 ± 0.01 to 0.94 ± 0.01 and were positive and low with NS (0.11 ± 0.01 to 0.20 ± 0.01) and favorable with BQ (0.14 ± 0.02 to 0.37 ± 0.02). Null to moderate genetic correlations were obtained between growth and carcass traits. Genetic gains were positive and significant, except for BW. An increase of 0.76 and 0.72 kg is expected for BW and WW, respectively, per unit increase in estimated breeding value (EBV) for direct effect and an additional 0.74 and 1.43, respectively, kg per unit increase in EBV for the maternal effect. Monitoring genetic gains for HH and NS is relevant to maintain an adequate body size and a navel morphological correction, if necessary. Simultaneous selection for growth, morphological, and carcass traits in line with improve maternal performance is a feasible strategy to increase herd productivity.

Genetic parameters, correlation and repeatability of agronomic characters of yellow passion fruit genotypes in three harvest cycles

The genetic improvement of sour passion fruit has the main objective of obtaining genotypes with high fruit yield and quality. The determination of the ideal early selection is extremely relevant to reduce costs and time in the selection of promising genotypes for use in genetic improvement programs. In this context, this work aimed to determine the ideal selection phase through estimates of genetic parameters, phenotypic, genotypic correlations and analysis of repeatability. A total of 14 yellow passion fruit hybrids in Lençóis (Bahia State, Brazil) were evaluated in a randomized block design with five replications and nine agronomic traits from three harvests with five fruits evaluated per repetition. Genetic parameters, repeatability coefficient and phenotypic and genotypic correlations were estimated for each evaluation cycle. For most parameters, the traits changed according to the evaluation cycle. Most of the genetic parameters showed favorable genetic conditions for the selection in the first harvest. The correlations between the traits fruit weight, peel and seedless pulp weight, fruit length and diameter were more stable in the different harvests. Through the repeatability analysis based on the principal components of covariance and correlation, it was possible to estimate a sample of 13 fruits per hybrid for prediction with accuracy of 90% for the physical traits of sour passion fruit.

Genetic analysis of reproductive efficiency in Spanish goat breeds using a random regression model as a strategy for improving female fertility

This study aimed to estimate genetic parameters of reproductive efficiency over a wide age range of females using a random regression model (RRM) in Spanish goat breeds. A total of 138,139 and 64,638 reproductive records from the first to the sixth parities from Florida and Payoya, respectively, were included in the analysis. Random regressions on Legendre polynomials of standardised age were included for permanent environmental and additive genetic effects. Estimation of the covariance components was based on the Bayesian inference using the GIBBS3F90 software. Differences among genetic variance components for reproductive efficiency were observed over the animal’s lifetime. The estimates of heritabilities were moderate, ranging from 0.21 to 0.32 for Florida and from 0.25 to 0.35 for Payoya, while the fractions of phenotypic variance explained by the permanent environmental effect were high, varying between 0.45–0.68 and 0.58–0.71 for Florida and Payoya, respectively. The correlations for permanent environmental effect over age ranged from 0.37 to 0.99, while the genetic correlations between the different ages varied from 0.36 to 0.98 for Florida and from 0.80 to 0.99 for Payoya. The results from this study support the validity of using an RRM to genetically analyse reproductive efficiency in Spanish dairy goats following the changes in variances and the genetic correlations different from unity over the animal’s lifetime. Moreover, reproductive efficiency is a highly heritable trait that is expressed early in a female’s life, and it could be used as a precocious selection criterion to improve female fertility in Spanish dairy goats. Highlights Reproductive efficiency (RE) has been proposed as a trait to improve female fertility in dairy goats. RE was genetically analysed using an RRM over a range of ages in females from the Florida and Payoya breeds raised under different production systems. Variance components for RE were not constant over age, while the genetic correlations between RE in the different ages were different from unity. The use of RRM for RE is therefore justified in both goat breeds.

Türkiye’de Yetiştirilen Siyah Alaca İneklerin Doğrusal Tip Özellikleri, Birinci Laktasyon Karlılığı ve Verim Özellikleri Arasındaki Genotopik Korelasyonlar

Amaç: Bu çalışmanın amacı, ıslah programlarında kullanılmak üzere doğrusal tip özellikleri, verim özellikleri ve birinci laktasyon karlılığı arasındaki genetik korelasyonların tespitini yapmaktır.Materyal ve Metot: Araştırma 2012-2017 yılları arasında Hatay ilinde yürütülmüştür. Araştırmada toplam 810 baş birinci laktasyonda olan inek kullanılmıştır. Genetik parametrelerinin varyans ve kovaryanslarının analizi ise Multivariate Limited Maximum Likelihood testi ile gerçekleştirilmiştir.Bulgular: Ortalama inek başına birinci laktasyon net kar, 305-gün süt verimi, ilk buzağılama yaşı, ilk tohumlamada gebe kalma oranı ve kolay doğum oranı 540 US$, 6008 kg, 793 gün, %61.6 ve %91.7 olarak belirlenmiştir. Doğrusal tip özellikleri ile verim özelliklerinin kalıtım dereceleri sırasıyla; 0.10-0.42 ve 0.04-0.39 arasında tahmin edilmiştir. Birinci laktasyon karlılığı ile doğrusal tip özellikleri arasındaki genetik korelasyonlar -0.08 ve 0.42 arasında, birinci laktasyon karlılığı ile verim özellikleri arasındaki korelasyonlar 0.06 ve 0.34. arasında tahmin edilmiştir. Birinci laktasyon karlılığı ile en yüksek korelasyonu meme merkez bağı (0.42) gösterirken, en düşük korelasyonu meme derinliği (-0.08) göstermiştir. Yine birinci laktasyon karlılığı ile en yüksek korelasyonu süt proteini verimi (0.34) gösterirken, en düşük korelasyonu ilk tohumlamada gebe kalma oranı (0.09) göstermiştir. Doğrusal tip özellikleri ile verim özellikleri arasındaki genetik korelasyonlar -0.42 (Ayak açısı ve ilk tohumlamada gebe kalma oranı) ile 0.49 (Sütçü tip özelliği ve 305-gün süt verimi) arasında değişiklik göstermiştir.Sonuç: Araştırma sonuçları, birinci laktasyondaki daha fazla sütçü tipe sahip, ön meme bağlantısı güçlü, güçlü ayak ve bacak yapısına sahip ineklerin, birinci laktasyonda daha karlı olduklarını ve süt sığırı ıslah programlarında doğrusal tip özellikleri ile verim özellikleri arasındaki bu genetik korelasyonlardan yararlanılarak, daha isabetli seleksiyon yapılabileceğini ortaya koymuştur.

Estimation of co-variance components, genetic parameters, and genetic trends of reproductive traits in community-based breeding program of Bonga sheep in Ethiopia.

ObjectiveThe objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep.MethodsReproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/lambing.ResultsThe overall least squares mean±standard error of AFL, LI, LS, and ARR were 375± 12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were −0.0281 days, −0.016 days, −0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively.ConclusionImplications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

Maternal Genetic Effect on Expected Genetic Response of Selection Indices for Milk Production of Friesian Cows in Egypt

The present study aimed to estimate the genetic parameters of first lactation milk yield (FLMY), first lactation period (FLP), first dry period (FDP) and first calving interval (FCI) and inclusion these studied traits in selection indices through different animal models. The data utilized in this study were obtained from 1821 normal first lactation of Friesian cows belong to Sakha and EI-Karada Experimental stations of Animal Production Research Institute (APRI), Ministry of Agriculture, Dokki, Cairo, Egypt. Data were collected during the period from 1990 to 2016 and analyzed using the MTDFREML program. Covariance components were used to construct the different selection indices for FLMY kg, FLP day, FDP day and FCI day with four multiple animal models. Means for FLMY FLP, FDP and FCI were 2425 kg, 304 d, 170 d and 474 d, respectively. Direct additive heritability (h2a) for the above-mentioned traits were 0.32, 0.29, 0.27 and 0.18, respectively. The corresponding estimates of the maternal heritability (h2m) for the same traits were 0.25, 0.22, 0.30 and 0.27, successively. Estimates of direct genetic correlations among studied traits ranged from -0.52 to 0.61. Phenotypic correlations among investigated traits were ranging from -0.20 to 0.23. Animal model number two that included the additive and permanent effects had the highest accuracy. On the contrary, model number three that included additive and maternal effects. The ranking correlations among four animal models were higher than 0.93. This indicates that using one of the studied models can be achieved the genetic improvement. We would however recommend that included the permanent environmental effects on analytical models when selection for these traits in Friesian cows under Egyptian condition.

Knockoff boosted tree for model-free variable selection.

The recently proposed knockoff filter is a general framework for controlling the false discovery rate (FDR) when performing variable selection. This powerful new approach generates a 'knockoff' of each variable tested for exact FDR control. Imitation variables that mimic the correlation structure found within the original variables serve as negative controls for statistical inference. Current applications of knockoff methods use linear regression models and conduct variable selection only for variables existing in model functions. Here, we extend the use of knockoffs for machine learning with boosted trees, which are successful and widely used in problems where no prior knowledge of model function is required. However, currently available importance scores in tree models are insufficient for variable selection with FDR control. We propose a novel strategy for conducting variable selection without prior model topology knowledge using the knockoff method with boosted tree models. We extend the current knockoff method to model-free variable selection through the use of tree-based models. Additionally, we propose and evaluate two new sampling methods for generating knockoffs, namely the sparse covariance and principal component knockoff methods. We test and compare these methods with the original knockoff method regarding their ability to control type I errors and power. In simulation tests, we compare the properties and performance of importance test statistics of tree models. The results include different combinations of knockoffs and importance test statistics. We consider scenarios that include main-effect, interaction, exponential and second-order models while assuming the true model structures are unknown. We apply our algorithm for tumor purity estimation and tumor classification using Cancer Genome Atlas (TCGA) gene expression data. Our results show improved discrimination between difficult-to-discriminate cancer types. The proposed algorithm is included in the KOBT package, which is available at https://cran.r-project.org/web/packages/KOBT/index.html. Supplementary data are available at Bioinformatics online.

Genetic correlation estimates between age at puberty and growth, reproductive, and carcass traits in young Nelore bulls

The reduction of age at puberty in young bulls is an important issue to reduce the growing phase and promote substantial savings in production cost as well as to reduce the generation interval. This study aims to estimate genetic parameters for age at puberty in males (APM), growth, carcass, and reproductive-related traits in young Nelore bulls. Additionally, the direct and correlated response for growth, reproductive, and carcass traits were also estimated when a selection was applied for APM in such young bulls. APM was determined through evaluations carried out after weaning, using information from andrological clinical examination, ultrasound records, and scrotal circumference measurements. Records from 181,345 Nelore animals born between 2010 to 2017 were used. These animals were calves from 5,257 sires and 50,742 dams, and belonged to 18 farms located in the Midwest, Southeast, Northeast, and North regions of Brazil. The relationship matrix was built using information from 265,813 animals. The covariance components and the genetic parameters for APM, adjusted scrotal circumference at 365 (SC365) and 450 (SC450) days of age, adjusted weight at 210 (W210) and 450 (W450) days of age, age at first calving (AFC), ribeye area (REA), subcutaneous fat thickness (SFT), and rump fat thickness (RFT) were estimated using a linear animal model. A threshold animal model was used for Stayability (STAY) and early heifer pregnancy (PP30) traits. The heritabilities obtained were: 0.30 (APM), 0.33 (SC365), 0.37 (SC450), 0.14 (W210), 0.26 (W450), 0.08 (AFC), 0.29 (PP30), 0.19 (STAY), 0.32 (REA), 0.19 (SFT), and 0.28 (RFT). The genetic correlations estimates between APM and growth, reproductive, and carcass related traits were: -0.39 (SC365), -0.58 (SC450), -0.01 (W210), 0.08 (W450), 0.30 (AFC), -0.24 (PP30), 0.35 (STAY), 0.08 (REA), -0.05 (SFT), and -0.30 (RFT). The APM is a new approach to evaluate early sexual precocity in young bulls, and it would allow better identification of young candidates when compared to those selected based on scrotal circumference measures. Genetic progress is expected for APM in young bulls since it would favor the heifer's sexual precocity together with the dam's longevity without impacting growth and carcass traits. The results of this study encourage the use of male sexual precocity trait assisted by genomic selection to improve the genetic evaluation reliability of young bulls.

Genetic parameters for test-day milk yield, lactation persistency, and fertility in low-, medium-, and high-production systems in Kenya

Genetic parameters for test-day milk yield, lactation persistency, and age at first calving (as a fertility trait) were estimated for the first 4 lactations in multiple-breed dairy cows in low-, medium-, and high-production systems in Kenya. Data included 223,285 test-day milk yield records from 11,450 cows calving from 1990 to 2015 in 148 herds. A multivariate random regression model was used to estimate variance and covariance components. The fixed effects in the model included herd, year, and test month, and age as a covariate. The lactation profile over days in milk (DIM) was fitted as a cubic smoothing spline. Random effects included herd, year, and test month interaction effects, genetic group effects, and additive genetic and permanent environmental effects modeled with a cubic Legendre polynomial function. The residual variance was heterogeneous with 11 classes. Consequently, the variance components were varied over the lactation and with the production system. The estimated heritability for milk yield was lower in the low-production system (0.04-0.48) than in the medium- (0.22-0.59) and high-production (0.21-0 60) systems. The genetic correlations estimated between different DIM within lactations decreased as the time interval increased, becoming negative between the ends of the lactations in the low- and medium-production systems. Low (0.05) to medium (0.60) genetic correlations were estimated among first lactation test-day milk yields across the 3 production systems. Genetic correlations between the first lactation test-day milk yield and age at first calving ranged from 0.27 to 0.49, 0 to 0.81, and -0.08 to 0.27 in the low-, medium-, and high-production systems, respectively. Medium to high heritabilities (0.17-0.44) were estimated for persistency, with moderate to high (0.30-0.87) genetic correlations between 305-d milk yield and persistency. This indicates that genetic improvement in persistency would lead to increased milk yield. The low to medium genetic correlations between test-day milk yield between production systems indicate that sires may be re-ranked between production systems. Therefore, we conclude that sires should be selected based on a genetic evaluation within the target production system.

Comparison of daughter's performance of progeny tested sires with pedigree selected sires in Holstein Friesian crossbred cattle

The present study was conducted to compare the estimated breeding values of progeny tested sires and pedigree selected sires for test day milk yield of crossbred Holstein Friesian cattle. First lactation milk yield records (1,20,198) of 12,971 daughters sired by 267 sires were collected from INAPH database maintained by NDDB. Variance and covariance components for test-day milk yield (TDMY) were estimated by different random regression test day models (RRTDM), viz. Cubic B- Spline function, Quadratic B-Spline function, Legendre polynomial (LP) function and Wilmink function using Average Information Restricted Maximum Likelihood (AIREML). Considering various criteria for comparison of different orders of TDMs, LP of 6th order for TDMY was the best fitted model for further estimation of breeding values. The heritability estimates ranged from 0.15 to 0.39 for TDMY using Leg_2 model. The additive genetic correlations were higher than the phenotypic correlations among different TDs. The additive genetic correlations between test day yields varied from 0.73 to 0.99. The expected progeny difference (EPD) for TDMYcalculated based on dam’s yield for the top ten and bottom ten PS bulls was 2,662.5 kg; whereas, the actual progeny difference (APD) for these bulls was -28.47 kg. While, EPD for top 10 and bottom 10 PT bulls selected based on EBVs was 2,820.52 kg whereas the APD for PT bulls was 890.48 kg. The difference in expected and actual MY of progeny was higher in PS bulls as compared to PT bulls indicating that the pedigree information for EPDs had a poor association with APDs and sire superiority is not reflected in progeny’s actual performance. The rank correlation between ranks of all PS and PT bulls were very poor and non-significant. The bulls selected based on estimated breeding values will give faster genetic progress and decision to select replacement bulls based on breeding values instead of dam’s yield will have positive effect on genetic progress.

Genetic parameters and correlations of related feed efficiency, growth, and carcass traits in Hanwoo beef cattle.

ObjectiveThis study aimed to estimate the genetic parameters and genetic correlations for related feed efficiency, growth, and carcass traits in Hanwoo cattle.MethodsPhenotypic data from 15,279 animals born between 1989 and 2015 were considered. The related feed efficiency traits considered were Kleiber ratio (KR) and relative growth rate (RGR). Carcass traits analyzed were backfat thickness (BT), carcass weight, eye muscle area, and marbling score. Growth traits were assessed by the average daily gain (ADG), metabolic body weight (MBW) at mid-test age from 6 to 24 months, and yearling weight (YW). Variance and covariance components were estimated using restricted maximum likelihood using nine multi-trait animal models.ResultsThe heritability estimates for related feed efficiency (0.28±0.04 for KR and RGR) and growth traits (0.26±0.02 to 0.33±0.04) were moderate, but the carcass traits tended to be higher (0.38±0.04 to 0.61±0.06). The related feed efficiency traits were positively genetically correlated with all the carcass traits (0.37±0.09 to 0.47±0.07 for KR, and 0.14±0.09 to 0.37±0.09 for RGR), except for BT, which showed null to weak correlation. Conversely, the genetic correlations of RGR with MBW (−0.36±0.08) and YW (−0.30±0.08) were negative, and those of KR with MBW and YW were close to zero, whereas the genetic correlations of ADG with RGR (0.40±0.08) and KR (0.70±0.05) were positive and relatively moderate to high. The genetic (0.92±0.02) correlations between KR and RGR were very high.ConclusionSufficient genetic variability and heritability were observed for traits of interest. Moreover, the inclusion of KR and/or RGR in Hanwoo cattle breeding programs could improve the feed efficiency without producing any unfavorable effects on the carcass traits.

Bayesian estimates of genetic parameters of non-return rate and success in first insemination in Japanese Black cattle.

ObjectiveThe objective of present study was to estimate heritability of non-return rate (NRR) and success of first insemination (SFI) by using the Bayesian approach with Gibbs sampling.MethodsHeifer Traits were denoted as NRR-h and SFI-h, and cow traits as NRR-c and SFI-c. The variance covariance components were estimated using threshold model under Bayesian procedures THRGIBBS1F90.ResultsThe SFI was more relevant to evaluating success of insemination because a high percentage of animals that demonstrated no return did not successfully conceive in NRR. Estimated heritability of NRR and SFI in heifers were 0.032 and 0.039 and the corresponding estimates for cows were 0.020 and 0.027. The model showed low values of Geweke (p-value ranging between 0.012 and 0.018) and a low Monte Carlo chain error, indicating that the amount of a posteriori for the heritability estimate was valid for binary traits. Genetic correlation between the same traits among heifers and cows by using the two-trait threshold model were low, 0.485 and 0.591 for NRR and SFI, respectively. High genetic correlations were observed between NRR-h and SFI-h (0.922) and between NRR-c and SFI-c (0.954).ConclusionSFI showed slightly higher heritability than NRR but the two traits are genetically correlated. Based on this result, both two could be used for early indicator for evaluate the capacity of cows to conceive.

Angular momentum and rotational energy of mean flows in toroidal magnetic fields

We derive the balance equation for the Favre averaged angular momentum in toroidal not necessarily axisymmetric magnetic field equilibria. We find that the components of angular momentum are given by the covariant poloidal and toroidal components of and parallel flow velocities and we separately identify all relevant stress tensors, torques and source terms for each of these components. Our results feature the Favre stress generalisations of previously found Reynolds stresses like the diamagnetic or parallel stress, as well as the density gradient drive term. Further, we identify the magnetic shear as a source of poloidal angular momentum and discuss the mirror and the Lorentz force. Here, we find that the geodesic transfer term, the Stringer-Winsor spin-up term and the ion-orbit loss term are all part of the Lorentz force and are in fact one and the same term.Discussing the relation to angular velocity we build the inertia tensor with the help of the first fundamental form of a flux-surface. In turn, the inertia tensor is used to construct a flux-surface averaged rotational energy for surface flows of the plasma. The evolution of this rotational energy features a correction of previous results due to the inertia tensor. In particular, this correction suggests that density sources on the high-field side contribute much more to zonal flow energy generation than on the low field side.Our derivation is based on a full-F, electromagnetic, gyro-kinetic model in a long-wavelength limit. The results can be applied to gyro-kinetic as well as gyro-fluid theories and can also be compared to drift-kinetic and drift-fluid models. Simplified cases for the magnetic field geometry including the axisymmetric purely toroidal and purely poloidal magnetic fields are discussed, as are the angular momentum balance of the electromagnetic fields, the ion-orbit loss mechanism and the parallel acceleration.