Heritability Estimates For Milk Yield Research Articles

Random regression models to estimate genetic parameters for milk yield, fat, and protein contents in Tunisian Holsteins.

This study aimed to find the parsimonious random regression model (RRM) to evaluate the genetic potential for milk yield (MY), fat content (FC), and protein content (PC) in Tunisian Holstein cows. For this purpose, 551,139; 331,654; and 302,396 test day records for MY, FC, and PC were analysed using various RRMs with different Legendre polynomials (LP) orders on additive genetic (AG) and permanent environmental (PE) effects, and different types of residual variances (RV). The statistical analysis was performed in a Bayesian framework with Gibbs sampling, and the model performances were assessed, mainly, on the predictive ability criteria. The study found that the optimal model for evaluating these traits was an RRM with a third LP order and nine classes of heterogeneous RV. In addition, the study found that heritability estimates for MY, FC, and PC ranged from 0.11 to 0.22, 0.11 to 0.17, and 0.12 to 0.18, respectively, indicating that genetic improvement should be accompanied by improvements in the production environment. The study also suggested that new selection rules could be used to modify lactation curves by exploiting the canonical transformation of the random coefficient covariance (RC) matrix or by using the combination of slopes of individual lactation curves and expected daily breeding values.

Changes in genetic parameters for milk yield and heat tolerance in the Thai Holstein crossbred dairy population under different heat stress levels and over time

The objectives of this study were to investigate changes in genetic parameters for milk yield (MY) and heat tolerance of the crossbred Thai Holstein Friesian population under different heat stress levels over time, and to investigate the threshold point of heat stress manifestation on milk production. Genetic parameters were estimated using single-step genomic REML (ssGREML) and traditional REML models. Data included 58,965 test-day MY records from 1999 to 2008 (old data) and 105,485 test-day MY records from 2009 to 2018 (recent data) from the first parity of 24,520 cows. The pedigree included 55,168 animals, of which 882 animals had genotypes. Variance components were estimated with the REMLF90 program using a repeatability model with random regressions on a function of temperature-humidity index (THI) for additive genetic and permanent environmental effects. Fixed effects included farm-calving season combination, breed group-months in milk combination, and age at first calving. Random effects included additive genetic (intercept and slope) effects, permanent environmental (intercept and slope) effects, and herd-month-year of test. The phenotypic mean for MY was 13.33 ± 4.39 kg/d in the old data, and 14.48 ± 4.40 kg/d in the recent data. Estimates over different THI levels for the intercept additive genetic variance using old data ranged from 2.61 to 2.77 and from 5.02 to 5.38 using recent data with the REML method. In ssGREML analyses (performed with recent data only) the estimates for the intercept additive genetic variance ranged from 4.71 to 5.05. Estimates for the slope additive genetic variance were close to zero in all cases, with the largest values (0.024-0.030) at the most extreme THI value (80). Using REML, the covariance between the intercept and the slope additive genetic effects (THI from 72 to 80) ranged from -0.001 to 0.019 with old data and from 0.027 to 0.060 with recent data. The same covariance ranged from 0.026 to 0.057 in ssGREML analyses. The covariance between the intercept and the slope permanent environmental effects ranged from -0.42 to -0.67 for all data and THI levels. Across THI levels, the genetic correlation between MY and heat tolerance varied from -0.06 to 0.13 with old data, from 0.16 to 0.30 with recent data in REML analyses, and from 0.15 to 0.30 in ssGREML analyses, suggesting that in the current population the top animals for MY are more resistant to heat stress. This was expected, because of the introduction of Bos indicus genes in the last years. Heritability estimates for MY ranged from 0.19 to 0.21 (old data) and from 0.33 to 0.40 (recent data) for REML analyses. Heritability estimates for MY using ssGREML ranged from 0.31 to 0.38. A decline in MY was found when the animals' breed composition had more than 97.3% of Holstein genetics, and it was greatest at THI 80. The heritability and genetic correlations observed in this study show that selection for MY is possible without a negative correlated response for heat tolerance. Although the inclusion of genomic information is expected to increase the accuracy of selection, more genotypes must be collected for successful application. Future research should address other production and fitness traits within the Thai Holstein population.

ESTIMATION OF GENETIC PARAMETERS OF SOME PRODUCTIVE AND REPRODUCTIVE PERFORMANCE ASPECTS IN FRIESIAN CATTLE

34 Friesian cows records were analyzed reared at AL-Iśhagi dairy cattle station (50 km north of Baghdad) during the period 1996-2005. Heritability estimates for milk yield 305 day (MY305d), the period between calving and first estrous, services per conceptions, day open, lactation period , dry period , gestation period and calving interval were 0.17, 0.06, 0.07, 0.05, 0.07, 0.24, 0.02 and 0.03 respectively. Repeatability estimates for the same traits were 0.20, 0.12, 0.07, 0.11, 0.15, 0.15, 0.14, and 0.05 respectively. Genetic Correlation between (MY305d) and productive & reproductive traits were negative and highly significant (p>0.01(, and ranged between -0.30 and -0.73. While Phenotypic Correlation between (MY305d) and other traits were positive and high. Most Genetic and Phenotypic Correlations between studied traits except gestation period were positive and highly significant (p>0.01). Breeding Value (BV) estimated of sire for (MY305d) were ranged between 14.720 and -8.106. The highest and lowest values of Breeding Values of cows for (MY305d) were ranged between 352.224 and -159.705. Real Producing Ability (RPA) of cows for (MY305d) were predicted between 674.051 and -365.234 as a deviation from overall mean of flock.

Estimation of the genetic milk yield parameters of Holstein cattle under heat stress in South Korea.

ObjectiveThe objective of this study was to investigate the genetic components of daily milk yield and to re-rank bulls in South Korea by estimated breeding value (EBV) under heat stress using the temperature-humidity index (THI).MethodsThis study was conducted using 125,312 monthly test-day records, collected from January 2000 to February 2017 for 19,889 Holstein cows from 647 farms in South Korea. Milk production data were collected from two agencies, the Dairy Cattle Genetic Improvement Center and the Korea Animal Improvement Association, and meteorological data were obtained from 41 regional weather stations using the Automated Surface Observing System (ASOS) installed throughout South Korea. A random regression model using the THI was applied to estimate genetic parameters of heat tolerance based on the test-day records. The model included herd-year-season, calving age, and days-in-milk as fixed effects, as well as heat tolerance as an additive genetic effect, permanent environmental effect, and direct additive and permanent environmental effect.ResultsBelow the THI threshold (≤72; no heat stress), the variance in heat tolerance was zero. However, the heat tolerance variance began to increase as THI exceeded the threshold. The covariance between the genetic additive effect and the heat tolerance effect was −0.33. Heritability estimates of milk yield ranged from 0.111 to 0.176 (average: 0.128). Heritability decreased slightly as THI increased, and began to increase at a THI of 79. The predicted bull EBV ranking varied with THI.ConclusionWe conclude that genetic evaluation using the THI function could be useful for selecting bulls for heat tolerance in South Korea.

Genetic relationship between weaning weight and milk yield in Nguni cattle

A study was conducted to estimate the genetic relationship between weaning weight and milk yield in Nguni cattle. Milk yield data (n=125) were collected from 116 Nguni cows from Mara Research Station located in Limpopo Province and Loskop South Farm located in Mpumalanga Province using the weigh-suckle-weigh technique. Weaning weight data (n=19 065) were obtained from stud Nguni cattle from 146 herds distributed throughout South Africa. Estimates of (co)variance components for milk yield and weaning weight were calculated using PEST and VCE softwares. The average weaning weight, age of the calf at weaning and 24-h milk yield was 158.94 kg, 210 days and 5.25 kg/day, respectively. Heritability estimates for milk yield, direct and maternal weaning weight were 0.22±0.238, 0.47±0.039 and 0.25±0.029, respectively. Estimates of genetic correlations for milk yield and maternal weaning weight, milk yield and direct weaning weight, direct and maternal weaning weight were 0.97±0.063, −0.71±0.416 and −0.56±0.247, respectively. The results indicate that maternal weaning weight is genetically highly predictive of milk yield in Nguni cattle. Maternal breeding values for weaning weight could therefore be used as a selection criterion to improve milk yield in Nguni cattle.

Bayesian Models combining Legendre and B-spline polynomials for genetic analysis of multiple lactations in Gyr cattle

We aimed with this study to combine Legendre polynomials (LEG) and linear B-splines (BSP) to describe simultaneously the first and second lactation of Gyr dairy cattle under a multiple-trait random regression models (MTRRM) framework. Additionally we proposed the application of self-organizing map to define the classes of residual variances under these models. A total of 26,438 and 23,892 milk yield test-day records were used, respectively, for the first and second lactations of 3253 Gyr cows. Two preliminary MTRRM analyses considering 10 residual classes were performed: the first one was based on LEG for systematic and random effects for both lactations; and the second one was based on BSP. Three classes were defined by using a self-organizing map: from 6 to 35; 36–185 and 186–305 days in milk. After definition of residual variance classes, a total of 16 MTRRM combining LEG and BSP were compared. The MTRRM based on BSP to describe the systematic effects of the first and second lactation, BSP to describe the random effects of the first lactation and LEG to describe the random effects of the second lactation (BSP-BSP-BSP-LEG) outperformed all other models. From the BSP-BSP-BSP-LEG model, heritability estimates for milk yield over time ranged from 0.1107 to 0.2902, and from 0.2036 to 0.3967, for the first and second lactation, respectively. In general, additive genetic correlation estimates between days in milk within each lactation and between lactations had medium magnitude (mean of genetic correlations were 0.6630, 0.6226 and 0.4749 for the first, second and between both lactations, respectively). We concluded that combining different functions under a MTRRM framework is a feasible alternative for genetic modeling of lactation curves in Gyr dairy cattle.

Genetic parameters for milk yield and reproduction traits in the Chilean Dairy Overo Colorado cattle breed

The objective of this study was to estimate genetic parameters for milk production and reproduction traits, with phenotypic and pedigree information from the Dairy Overo Colorado breed from southern Chile. Single and multi-trait mixed models were used to analyze the data. Analyses were performed using ASReml software. Heritability estimates for milk yield, fat yield, protein yield, fat content, protein content, age at first calving and calving interval, were 0.29, 0.34, 0.30, 0.56, 0.56, 0.01 and 0.002, respectively. Genetic correlations between yield traits were high and positive (≥ 0.81). Genetic correlations of milk yield with fat content (-0.32) and protein content (-0.30) were unfavorable. Genetic correlation estimates between age at first calving and yield traits were negative between -0.71 and -0.29. Phenotypic correlations between calving interval and milk yield traits were slightly positive (0.06-0.09), suggesting a weak relationship between reproduction and yield in this population. Genetic variation is considerable for milk production traits. Genetic improvement for age at first calving and calving interval may be slow, because small differences between animals and low reliabilities are expected for estimated breeding values for these traits due to low heritabilities. The design of an efficient breeding program for yield traits based on artificial insemination for this population is feasible using either progeny testing or genomic breeding value prediction for selecting sires.

Genetic analysis of coagulation properties, curd firming modeling, milk yield, composition, and acidity in Sarda dairy sheep

Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CFt) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k20, min), and 3measures of curd firmness (a30, a45, and a60, mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCTeq), the asymptotic potential curd firmness (CFP), the curd firming instant rate constant (kCF), and the syneresis instant rate constant (kSR). Two other derived traits were also calculated (CFmax, the maximum curd firmness value; and tmax, the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CFt with the other traits; statistical inference was based on the marginal posterior distributions of the parameters of concern. The marginal posterior distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an individual equation parameter exhibited larger genetic variation and a higher heritability estimate (0.32±0.11). The other curd firming and syneresis traits, whether as traditional single point observations or as individual equation parameters and derived traits, were characterized by heritability estimates lower than for coagulation time and for the corresponding bovine milk traits (0.06 to 0.14). Phenotypic and additive genetic correlations among the 11 technological traits contribute to describing the interdependencies and meanings of different traits. The additive genetic relationships of these technological traits with the single test-day milk yield and composition were variable and showed milk yield to have unfavorable effects on all measures of curd firmness (a30, a45, a60, CFP, and CFmax) and tmax, but favorable effects on both instant rate constants (kCF and kSR). Milk fat content had a positive effect on curd firmness traits, especially on those obtained from CFt equations, whereas the negative effects on both coagulation time traits were attributed to the milk protein and casein contents. Finally, in view of the estimated heritabilities and additive genetic correlations, enhancement of technological traits of sheep milk through selective breeding could be feasible in this population.

Homogeneity and heterogeneity of variance components for milk and protein yield at different cluster sizes in Iranian Holsteins

This study was conducted to investigate the homogeneity and heterogeneity of variance components for milk yield (MY) and protein yield (PY) at different cluster sizes and to evaluate effect of different data transformation methods on the ranking of elite animals in Iranian Holsteins. Data included 305-day lactation records for MY and PY from the first three lactations that were collected in the period from 1983 to 2014 by the Animal Breeding Center and Promotion of Animal Products of Iran. The mean and standard deviation of 305-day MY and PY for each herd were obtained and used as the basis for clustering the herds. Four different data transformation methods including Logarithmic, Arc sin, Square root and Box-Cox were applied and the data were tested for heterogeneity of variance before and after transformation using Bartlett's test. Genetic parameters and heritability estimates as well as animals’ breeding values (BVs) were estimated by the VCE program, using animal model. The results indicated the heterogeneity of variance in all clusters (P<0.01) before transformation. All methods of data transformation decreased the heterogeneity of variance components for MY and PY in the first three lactations and some of these methods caused removing the heterogeneity of variance. Results showed that the heritability estimates of MY and PY were decreased from the first lactation to third, also heritability estimates of transformed data were slightly higher than the original data ones. Some re-ranking of animals occurred from the transformation, but the Box-Cox method only had slight effects on the overall ranking and rank correlations of animals. The applied data transformation caused a substantial re-ranking of elite sires and dams in the EBV for each cluster. This study provided evidence that the applied transformation methods reduced the bias in the EBVs due to heterogeneous variances and increased the accuracy of bull-dam selection. Therefore, effects of heterogeneous variances need to be accounted for in genetic evaluation of Holstein cows in Iran.

Genetic parameter estimation for major milk fatty acids in Alpine and Saanen primiparous goats

Genetic parameters for 18 fatty acids or groups of fatty acids (FA), milk production traits, and somatic cell score (SCS) were estimated by restricted maximum likelihood with a repeatability animal model, using 45,259 test-day records from the first lactations of 13,677 Alpine and Saanen goats. Fatty acid data were collected as part of an extensive recording scheme (PhénoFinLait), and sample testing was based on mid-infrared spectra estimates. The total predicted FA content in milk was approximately 3.5% in Alpine and Saanen goats. Goat milk fat showed similar saturated FA to cattle and sheep, but higher contents of capric (C10:0) FA (~9.7g/100g of milk fat). Heritability estimates ranged from 0.18 to 0.49 for FA and estimates were generally higher when FA were expressed in g/100g of milk fat compared with g/100g of milk. In general, the 3 specific short- and medium-chain goat FA, caproic acid (C6:0), caprylic acid (C8:0), and especially capric (C10:0) acid, had among the highest heritability estimates (from 0.21 to 0.37; average of 0.30). Heritability estimates for milk yield, fat and protein contents, and SCS were 0.22, 0.23, 0.39, 0.09, and 0.24, 0.20, 0.40, and 0.15, in Alpine and Saanen goats, respectively. When FA were expressed in g/100g of milk, genetic correlations between fat content and all FA were high and positive. Genetic correlations between the fat content and FA groups expressed in g/100g of fat led to further investigation of the association between fat content and FA profile within milk fat. Accordingly, in both Saanen and Alpine breeds, no significant genetic correlations were found between fat content and C16:0, whereas the correlations between fat content and specific goat FA (C6:0 to C10:0) were positive (0.17 to 0.59). In addition, the genetic correlation between fat content and C14:0 was negative (−0.17 to −0.35). The values of the genetic correlations between protein content and individual FA were similar, although genetic correlations between protein content and FA groups were close to zero. Genetic correlations of milk yield or SCS with the FA profile were weak. Results for genetic parameters for FA, however, should be further validated, because the low predicting ability of certain FA using mid-infrared spectra and the limited calibration data set might have resulted in low accuracy. In conclusion, our results indicated substantial genetic variation in goat milk FA that supported their amenability for genetic selection. In addition, selection on protein and fat contents is not expected to have an undesirable effect on the FA profile in regard to specificity of goat products and human health.

Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

Abstract. The objective of this study was to estimate genetic parameters for milk yield and milk percentages of fat and protein in Iranian buffaloes. A total of 9,278 test-day production records obtained from 1,501 first lactation buffaloes on 414 herds in Iran between 1993 and 2009 were used for the analysis. Genetic parameters for productive traits were estimated using random regression test-day models. Regression curves were modeled using Legendre polynomials (LPs). Heritability estimates were low to moderate for milk production traits and ranged from 0.09 to 0.33 for milk yield, 0.01 to 0.27 for milk protein percentage and 0.03 to 0.24 for milk fat percentage, respectively. Genetic correlations ranged from −0.24 to 1 for milk yield between different days in milk over the lactation. Genetic correlations of milk yield at different days in milk were often higher than permanent environmental correlations. Genetic correlations for milk protein percentage ranged from −0.89 to 1 between different days in milk. Also, genetic correlations for milk percentage of fat ranged from −0.60 to 1 between different days in milk. The highest estimates of genetic and permanent environmental correlations for milk traits were observed at adjacent test-days. Ignoring heritability estimates for milk yield and milk protein percentage in the first and final days of lactation, these estimates were higher in the 120 days of lactation. Test-day milk yield heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in Iranian milking buffaloes.

Estimation of Genetic and Phenotypic Parameters for Production Traits and Somatic Cell Count for Jersey Dairy Cattle in Zimbabwe

Genetic and phenotypic parameters for production traits and somatic cell count (SCC) for Jersey dairy cattle in Zimbabwe were estimated. A total of 10986 lactation records were obtained from Zimbabwe Livestock Identification Trust, with cows calving in the period from 1996 to 2008. An ASReml program fitting an animal model was used for the analyses. Heritability estimates for milk yield, fat yield, protein yield, fat percentage, protein percentage, and Log10SCC were 0.30, 0.32, 0.33, 0.42, 0.44, and 0.08, respectively. The corresponding repeatability estimates were 0.39, 0.38, 0.39, 0.49, 0.51, and 0.16, respectively. The genetic and phenotypic correlations between different production traits ranged from −0.86 to 0.95 and from −0.88 to 0.98, respectively. The genetic and phenotypic correlations between production traits and Log10SCC were weak almost nonsignificantly differentl from zero. The results imply that milk traits for Jersey dairy cattle in Zimbabwe are more heritable. Therefore, these traits may be preferred by breeders as selection criteria for development of effective genetic improvement programme.

Milk fatty acid characterization and genetic parameter estimates for milk conjugated linoleic acid in buffaloes

The objectives of this study were to analyse buffalo milk fat composition, to verify the activity of Delta(9)-desaturase enzyme in the mammary gland, as well as to estimate additive genetic variances for milk, fat and protein yield, and milk cis-9,trans-11 conjugated linoleic acid percentage (cis-9,trans-11 CLA%). A total of 3929 lactation milk yields (MY) records from 2130 buffaloes and 1598 lactation fat (FY) and protein (PY) yield records from 914 buffaloes were analysed. For cis-9,trans-11 CLA%percentage, a total of 661 milk samples from 225 buffaloes, daughters of 8 sires, belonging to 4 herds and calving in 2003 and 2004, were used. The genetic parameters and variance components were estimated by Restricted Maximum Likelihood applying an animal model. The fixed effects considered in the model were: contemporary group (herd, year, calving season) and age at calving (linear and quadratic effects) and lactation length (linear and quadratic effects) as covariables. Additive genetic and permanent environment effects were considered as random. The MY, FY, PY and CLA% means were 1482±355 kg, 90.1±24.6 kg, 56.9±15.2 kg and 0.69±0.16%, respectively. Heritability estimates for MY, FY, PY and CLA% were 0.28±0.05, 0.26±0.11, 0.25±0.11 and 0.35±0.14, respectively. There is enough additive genetic variation for buffalo milk, protein and fat yield to improve these traits through selection. The cis-9,trans-11 CLA% can be enhanced by selection in buffaloes and will contribute to improving human health. The activity and efficiency of Delta(9)-desaturase in the mammary was measured and confirmed.

GENETIC AND PHENOTYPIC PARAMETERS OF MILK YIELD AND REPRODUCTIVE PERFORMANCE IN THE FIRST THREE LACTATIONS OF EGYPTIAN BUFFALO

The objective of this work was to investigate early selection based on the first lactation to improve milk yield in the first three lactations. A total of 1911 lactation records each for milk yield, lactation length, age at first calving and average interval between successive calvings, representing 637 buffalo cows, daughters of 123 sires and 519 dams, were analyzed by fitting a multiple-trait animal model using REML procedure. The model included herd and year-season of birth as fixed effects and animal as random effect. The results revealed that the fixed effect of herd contributed significantly to variation in all studied traits except for age at first calving, while year-season of birth significantly affected milk per day/lactation, first lactation length, age at first calving and average interval between successive calvings. Heritability estimates for milk yield, cumulative milk yield, milk per day/lactation and first lactation length varied from 0.13 to 0.27. Heritability estimates for age at first calving and average interval between successive calvings were 0.11 and 0.07, respectively. Genetic and phenotypic correlations were high and positive for milk yield, cumulative milk yield, milk per day/lactation and first lactation length. While, it was moderate to low for these traits with both age at first calving and average interval between successive calvings. Results indicated that early genetic selection of milk yield for the first three lactations based on the first one is possible through a selection scheme in the Egyptian buffalo.

Accessing genotype by environment interaction using within‐ and across‐country test‐day random regression sire models

First-lactation test-day (TD) milk records of Luxembourg and Tunisian Holsteins were analysed for evidence of genotype by environment interaction (G x E). The joint data included 730 810 TD records of 87 734 cows and 231 common sires. Random regression TD sire models with fourth-order Legendre polynomials were used to estimate genetic parameters via within- and across-country analyses. Daily heritability estimates of milk yield from within-country analysis were between 0.11 and 0.32, and 0.03 and 0.13 in Luxembourg and Tunisia, respectively. Heritability estimates for 305-day milk yield and persistency (defined as the breeding value for milk yield on DIM 280 minus the breeding value on DIM 80) were lower for Tunisian Holsteins compared with the Luxembourg population. Specifically, heritability for 305-day milk yield was 0.16 for within- and 0.11 for across-country analyses for Tunisian Holsteins and 0.38 for within- and 0.40 for across-country analyses for Luxembourg Holsteins. Heritability for apparent persistency was 0.02 for both within- and across-country analyses for Tunisian Holsteins and 0.08 for within- and 0.09 for across-country analyses for Luxembourg Holsteins. Genetic correlations between the two countries were 0.50 for 305-day milk yield and 0.43 for apparent persistency. Moreover, rank correlations between the estimated breeding values of common sires for 305-day milk yield and persistency, estimated separately in each country, were low. Low genetic correlations are evidence for G x E for milk yield production while low rank correlations suggest different rankings of sires in both environments. Results from this study indicate that milk production of daughters of the same sires depends greatly on the production environment and that importing high merit semen for limited input systems might not be an effective strategy to improve milk production.

Heterogeneity of Variance for Milk Traits at Climitical Regions in Holstein Dairy Cattle in Iran and the Best Method(s) for Data Transformation

In this research, heterogeneity of variance components in cattle populations at climatical regions in the first three lactations was studied. The data set included the following: 161328 records of first, 123369 records of second and 81013 records of third lactations, which was collected by Animal Breeding Center of Iran from 1983 to 2004. Records of three lactations were divided in the base of Domarten method. Bartlett test for heterogeneity of variance components was significant among all subgroups. In order to decrease the heterogeneity of variance components, we used several data transformation methods including Logarithmic, Square root and Arc sin transformations. Logarithmic transformation decreased the heterogeneity of variance components in the three lactations and other methods had not effect for removing the heterogeneity in any group. Genetic parameters and heritability were estimated for three lactations by MATVEC program, using animal model. Results showed that the heritability estimates of milk yield were decreased from the first lactation to the third; also the heritability estimates of transformed data were slightly higher than the original data. Comparison between estimated parameters in single trait and two traits analysis, before and after data transformation, showed that there were not significant differences between derived results.

Avaliação genética de caprinos da raça Alpina utilizando-se a produção de leite no dia do controle

Com os objetivos de estimar os parâmetros genéticos e predizer os valores genéticos para produção de leite no dia do controle (PLDC) e para produção acumulada (PAC), utilizaram-se dados de 356 cabras da raça Alpina, com 825 lactações e 26.389 controles semanais efetuados entre os anos de 1997 e 2004. A PLDC foi analisada considerando-se o efeito fixo de grupo contemporâneo (ano-mês de controle), a idade da cabra ao parto, como covariável, e os efeitos aleatórios genético aditivo e de ambiente permanente. Para PAC, o modelo incluiu os mesmos efeitos aleatórios, o efeito fixo de grupo contemporâneo (ano-mês de parto) e as covariáveis idade da cabra ao parto e duração da lactação. Em geral, as herdabilidades estimadas foram de maiores magnitudes na primeira lactação, nos controles intermediários, indicando possibilidade de resposta à seleção. As correlações de ordem entre os valores genéticos para a produção até 305 dias de lactação e as PLDC intermediárias foram maiores que as do início e do final da lactação. Apesar de a correlação de ordem ter sido alta, houve alterações na classificação dos reprodutores para produção até 305 dias de lactação quando a seleção foi praticada com base na PLDC aos 90 dias. A seleção pela PLDC e PAC no meio da lactação pode ser indicada como critério de seleção, em substituição à produção até 305 dias.

Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Co)variance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56) were higher than those obtained by RRM2 (0.15 to 0.31). Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

Estimates of correction factors for lactation length and genetic parameters for milk yield in buffaloes

Correction factors for milk yield at 90, 240, 270 and 305 days of lactation of buffaloes and genetic and environmental parameters for milk yield of these lactation periods were estimated. The data used consisted of 3888 lactation records of 1630 buffaloes from 10 herds reared in the State of São Paulo. Genetic parameters were estimated by the derivative free restricted maximum likelihood method, fitting an animal repeatability model. Heritability estimates for milk yield corrected for 90, 240, 270 and 305 days of lactation were 0.17, 0.15, 0.14 and 0.14, respectively. In this same order, repeatability estimates were 0.40, 0.44, 0.41 and 0.41. The genetic correlation estimates between these corrected milk yields ranged from 0.96 to 1.00. The multiplicative correction factors for the different classes of lactation lengths were efficient for adjustment of milk yield at 90, 240, 270 and 305 days of lactation.

임의회귀 검정일 모형을 이용한 홀스타인 젖소의 1산차 산유형질 및 체세포지수에 대한 유전모수

우리나라 젖소 종모우의 국가단위 종축평가방법의 일환으로 이용되고 있는 산유형질 및 체세포지수의 305일 보정에 의한 유전평가 방법론에 대한 대안을 제시하기 위한 사전 연구의 일환으로써 검정일 기록을 이용하여 공변량 함수를 활용한 검정일 임의회귀모형에 대한 효율성을 검정하고 각 산유형질에 대한 비유일수별 유전적 변이를 추정하여 제시하고자 본 연구를 수행하였다. 본 연구에 이용된 자료는 농협중앙회에서 수행하고 있는 젖소 산유능력 검정사업에서 조사된 산유능력 검정기록과 한국종축개량협회에서 조사된 개체별 혈통자료를 이용하여 분석을 실시하였다. 분석에 이용된 자료는 혈통이 알려진 1산차 개체로써 검정일별 축군당 3기록 이상을 갖고 부모가 모두 알려진 개체만을 이용하였으며 한 유기동안에 개체별 7회 이상의 기록을 갖는 개체만을 선별하였다. 또한 자료분석의 효율성을 기하기 위하여 측정자료의 이상치는 제외하였으며 축군들간의 혈연적으로 연결되지 않은 축군 자료는 제외하였다. 분석모형은 단형질 개체모형으로써 검정년도-월-연령의 효과를 고정효과 공변량모형으로 적합시켰고 개체별 상가적 유전효과 및 영구환경효과를 개체내 검정일에 대한 임의 공변량 효과로 적합하여 모형을 설정, 유전분석을 실시하였다. 여기서 사용된 공변량은 검정일에 대하여 1차항 및 2차항을 포함하는 다항 공변량 함수를 활용하였다. 분석결과 유량에 대한 검정일별 유전력은 0.13~0.29으로 추정되었으며 검정일별 변이가 큰 것으로 추정되었다. 반면에 유지방율에 대한 유전력은 0.09~0.11으로 비교적 낮게 추정되었으며 유단백율에 대한 유전력은 0.12~0.19으로 추정되었다. 무지고형분율에 대한 유전력은 0.17~0.23으로 추정되었으며 체세포지수에 대한 유전력은 0.02~0.04으로 아주 낮게 추정되었다. 유량에 대한 유전적 변이가 비유일별로 다소 크게 추정되어 비유일에 따른 잔차 변이의 이질성(Heterogeneosity)이 클 것으로 사료되었으며 이러한 효과를 고려한 모형개발에 대한 연구가 필요할 것으로 사료되었으며 또한 다산차 기록을 활용한 분석 등에 대한 연구가 필요할 것으로 사료되었다. 국가단위 종축평가에 적합하기 위한 모형제시를 위해서는 본 분석에서 활용한 모형을 확장하여 분석된 종모우별 유전능력과 305d 사전 보정에 의한 평가에서의 순위와의 비교 연구가 선행되어야 할 것으로 사료되었다. The objective of this study was to estimate genetic parameters for test-day milk production and somatic cell score using field data collected by dairy herd improvement program in Korea. Random regression animal models were applied to estimate genetic variances for milk production and somatic cell score. Heritabilities for milk yields, fat percentage, protein percentage, solid-not-fat percentage, and somatic cell score from test day records of 5,796 first lactation Holstein cows were estimated by REML algorithm in single trait random regression test-day animal models. For these analyses, Legendre polynomial covariate function was applied to model the fixed effect of age-season, the additive genetic effect and the permanent environment effect as random. Homogeneous residual variance was assumed to be equal throughout lactation. Heritabilities as a function of time were calculated from the estimated curve parameters from univariate analyses. Heritability estimates for milk yields were in range of 0.13 to 0.29 throughout first lactation. Heritability estimates for fat percentage, protein percentage and solid-not-fat percentage were within 0.09 to 0.11, 0.12 to 0.19 and 0.17 to 0.23, respectively. For somatic cell score, heritabilities were within 0.02 to 0.04. Heritabilities for milk productions and somatic cell score were fluctuated by days in milk with comparing 305d milk production.