جستجوی مقالات مرتبط با کلیدواژه « Genetic trend » در نشریات گروه « علوم دام »

Horses were breed for war, hunting, Transporting, recreational, and sports purposes (Khalili 2008). The criterion of selection is mainly based on the horse's own and their parents' performances rather than breeding value. Despite of relatively developed organization of horse husbandry in the country and availability of individual racing results for almost all the progeny and pedigree information of horses, the scientific methods are not applied in selection of the animals for improving the racing performance(Bakhtiari & Kashan 2009). Normally the criteria to estimate the racing performance are time traits (Langlois 1980, Tolley et al. 1985, Ekiz et al. 2005), handicap weights (Langlois 1980, Tolley et al. 1985), rank at finish (Chico 1994, Sobczynska and Lukaszewicz, 2003, Ekiz and Kocak 2005) and earning (Langlois 1980, Ekiz and Kocak 2005). Breeders have traditionally combined information from time trials and races with pedigree evaluations to select potential racing stock, but this evaluation has primarily been based on a subjective synthesis of available information. Although the Standardbred horse is extensively performance tested before selection of breeding stock, studies of the genetic and environmental factors that influence racing performance must be completed before specific selection criteria can be recommended to the industry (Tolley et al. 1983). Racing ability is the main selection criterion in race horses. Breeding value estimation for aspects of racing ability has been carried out following performance tests in many European countries(Àrnason et al. 1994). Traits such as rank, time, prize, etc. are used to estimate the genetic and phenotypic parameters of race horses(Sobczynska & Lukaszewicz 2004). Genetic parameters estimation of racing performance traits is important in breeding programs, therefore, appropriate methods should be used. This study aimed to estimate the genetic parameters of racing performance using a linear model in different breeds of Iranian race horses and estimation of their genetic and phenotypic trends. The result of this study would be used for designing a breeding program for Iranian race horses.

In this study, the performance records of Iranian horse breeds, including Thoroughbred, Crossbreed, Turkmen, and Arabian horse breeds from the horse racing club of the Iranian Equestrian Federation between 2006 to 2014 were used. Performance traits in this study include 1.Racing Time, 2.rank at the Finish, 3.Cumulative Earning, 4.Number of Places, and 5.Number of races. Data were collected and adjusted using Excel software and R scripts. The quality controls included outliers deletion and preparing records for statistical analysis. CFC software (Sargolzaei et al. 2006) was used to survey the structure of the pedigree. For fitting the appropriate model the significant effects were investigated and was applied by SAS software. Variance components and genetic parameters were estimated by the restricted maximum likelihood method for a single trait animal model using ASReml software. A genetic trend is a compilation of average EBV per generation and indicates the direction of change across generations. It is often visualized in a graph and is useful to check whether there are unexpected deviations from linearity, e.g. due to a selection limit. The genetic trend in the racing performance was estimated by calculating the linear regression of average breeding values within birth years on the birth year.

The heritability of finish time at races for Crossbreed and Thoroughbred horses in 1000, +1500, and +1600 distances were estimated in the range of (0.19-0.29) and (0.36-0.45), respectively, and it was 0.25 and 0.13 respectively for the Arabian horse breed in 1000 and +1500 distance, and it was 0.35, 0.38, and 0.44, respectively for the Turkmen horse breed in 1000, 1550 and 1600 distance. The heritability of the rank was in the range of (0.046-0.17), (0.12-0.16), (0.24-0.28) 0), and (0.13-0.22) based on the linear model (Animal model), respectively for Crossbreed, Thoroughbred, Arabian, and Turkmen horse breed. The heritability of the cumulative earning was 0.20, 0.072, 0.019, and 0.033 respectively for the Crossbreed, Thoroughbred, Arabian, and Turkmen horse breeds. The repeatability of finish time for Crossbreed and Thoroughbred in 1000, +1500, and +1600 distance were estimated in the range of (0.38-0.59) and (0.40-0.52), respectively. Also, it was 0.64 and 0.54 respectively for the Arabian horse breed in 1000 and +1500 distance and were 0.60, 0.67, and 0.59, respectively for Turkmen horse breed in 1000, 1550 and 1600 distance meters. The repeatability of the rank was in the range of, (0.14-0.19), (0.13-0.17), (0.2-0.40), and (0.13-0.30), respectively for Crossbreed, Thoroughbred, Arabian, and Turkmen horse breed. The genetic trend of this trait for Crossbreed and Thoroughbred in 1000, +1500, and +1600 distances were estimated in the range of (-0.0629 to -0.0173) and (-0.0384 to -0.0236), respectively. Also, the genetic trend were 0.0372 and -0.0335 respectively for Arabian horse breed in 1000 and +1500 distance and were 0.0104, 0.587, and -0.0462, respectively for Turkmen horse breed in 1000, 1550, and 1600 distance. These results showed an inconsistency between this study and other research (references) due to the number of data, environmental and managerial factors such as the experience of horses in the race, and the type of equipment and tools involved in the competition. Regarding the low estimated heritability of some performance traits in this study, genetic progress through indirect selection will be more usefulness than direct selection on these traits. As the application of modern genetic selection methodologies continues to gain popularity in the racing industry, contemporary heritability estimates from the current population of Thoroughbred, Crossbreed, Turkmen, and Arabian horse breeds will play a vital role in identifying which traits are better suited to selection and in the development of more accurate genomic evaluations for racing performance.

In this study, body weight records of 19171 American Simmental beef cattle including 8758 bull and 10413 cows from 2000 to 2016 were used to estimate genetic parameters and trend. We conducted genetic evaluation of data from 5199, 10926, 7362 and 5636 genotyped beef cattle of gene-based single nucleotide polymorphisms (SNPs) for birth weight (BW), weaning weight direct (WWD), yearling weight (YW) and post-weaning weight gain (PWG), respectively. Genetic parameters estimated using univariate and bivariate animal models and BLUPf90 software. Heritabilities were estimated for BW, WW, YW and PWG 0.38 ± 0.02, 0.24 ± 0.01, 0.35 ± 0.01 and 0.22 ± 0.02 using univariate analysis, respectively. Genetic correlation between BW and PWG was 0.31. The highest and the lowest genomic accuracy were estimated for WWD (0.68) and PWG (0.27), respectively. Genetic trends were estimated for BW, WW, YW and PWG 0.13, 0.28, 3.43 and 0.05, respectively. In addition, slight changes were observed in the genetic trend of all traits, especially weaning weight direct and yearling weight across years of study which indicates the existence of specific selection goals and criteria in each of these traits. In general, three large-effect closely linked QTLs identified on BTA6 at 37 Mb, on BTA7 at 90 Mb and on BTA14 at 22 Mb. Because correlations were favorable between body weight traits, breeding program should be based on the simultaneous selection of these traits through the selection index.

The objective of this study was estimate of the genetic and phenotypic trends of growth traits in Moghani sheep. In this study, a total of 21,423 records of growth traits belong to Moghani lambs that collected by raising and breeding of Moghani sheep station between 2003 and 2010, was used. The SAS 9.1 statistical software was used to evaluate the effect of environmental factors. Variance components and genetic parameters were estimated using restricted maximum procedure and univariate animal model and with wombat software. Animal breeding value of were estimated using the best univariate animal model. Environmental factors, like birth year, sex, herd, type of birth, and the age of mother are the significant factors as fixed effects. Estimation of direct genetic trend for birth weight, weaning weight, 6 month weight, 9 month weight and 12 month weight were as 6±1, 8±1.5, 8±6, 11±5 and 86±5 gr per year, respectively. The phenotypic trend for mentioned traits was estimated 30±1, 116±1, 37±6, -342±5 and -43±5 gr per year, respectively. The results showed that before designing any breeding program, optimum environmental condition must be prepared for appearance of maximum genetic potential, so phenotypic and genetic trends will be desirable in the herd.

The estimate variance components with a satisfying accuracy of important economic traits such as reproductive traits is a prerequisite for designing breeding strategies. Genetic grouping was suggested in order to predict breeding values of phenotypic records in different years with high accuracy. As there is unknown information in the pedigree of Holstein dairy cows in Iran, genetic group animal models with unknown parents seem necessary. Therefore, the present study was conducted to estimate the genetic parameters, genetic trend and accuracy of estimated breeding values of some reproductive traits (i.e. calving to first service (CTFS), first service to conception (FSTC) and calving interval (CI)) in dairy cows with considering genetic grouping for animals with unknown parents.

Information on calving and insemination dates of the first three calving periods from 3361 herds of the Iranian Holstein, collected by the Animal Breeding Center of Iran during 1981 to 2013 was used. Animals with unknown parents were grouped based on the year of birth and sex and the traits were analyzed using two models, with (model 2) or without genetic grouping (model 1). The model with the lowest Bayesian information criterion (BIC) and the Akaic information criterion (AIC) is considered the best model. Spearman's rank correlation coefficient was used to change in animal rank by considering the genetic grouping. The accuracy of estimated breeding values and genetic trend of the traits was estimated using two models and was compared. Preparation of data for statistical and genetic analysis were carried out using R-software and ASReml software, respectively.

The amount of variance and the standard error of additive variance in model 2 was lower than model 1 and for the residual variance was conversely, but there was no significant difference between the values of the two models. Model 2 was selected the best model for all studied traits based on the goodness of fit criteria. Heritability of CI and CTFS using model 2 was estimated lower (non-significant) than model 1. The heritability value for all reproductive traits was estimated less than 0.05 by two models. The rank of males and females changed duo to genetic grouping. The accuracy of estimated breeding values (EBVs) for all studied traits in model 2 was significantly higher than model 1 (P <0.001). The genetic trend of all traits (exception of the FSTC in the first and third calving period) was positive by model 1 and 2, and the estimated values between the two models were different.

The results of the current study showed that using genetic grouping for reproductive traits analysis of Iranian Holstein cows and accurate prediction of genetic merit of animals seems necessary.

Fertility is considered an important economic trait in cattle, yet despite its importance, reproductive efficiency of dairy cattle has decreased dramatically in the past decades and is of increasing concern to farmers and the dairy industry (Ghiasi et al. 2011; Pryce et al. 2010). The decline in the reproductive efficiency of dairy cattle has become a challenging problem worldwide. Genetic response for fertility traits is expected to be small due to low heritabilities as shown in many studies. In the past decades, more attention has been placed on milk production in selection programs worldwide, which has caused a decline in female fertility due to the antagonistic genetic relationship between milk production and fertility (Pryce et al. 2010; Toghiani 2012). Therefore, it is necessary to include fertility traits in the breeding programs for improving fertility or stopping its downward genetic trend (Penagaricano et al. 2012). It is well documented that bull fertility is influenced by genetic factors. Semen production traits, such as volume and sperm concentration, were found to have moderate heritabilities (from 0.15 to 0.30), whereas some of the semen quality traits, such as motility and percentage of abnormal sperm, had moderate to high heritabilities (close to 0.60) (Rezende et al. 2018). The objective of this study was to assess genetic parameters for fertility traits in Holstein dairy cows and sire conception rate (SCR) a new phenotypic evaluation of bull fertility.

In this study information's related to heifers and cows 1 to 3 parity, 1992 to 2018, by the National Animal Breeding center and promotion of Animal Products of Iran and sire conception rate (SCR) 2008 to 2018, a phenotypic evaluation of bull fertility, has been provided to dairy producers the Council of Dairy Cattle Breeding (CDCB) were used. Traits included: sire conception rate (SCR), age at first service (AFS), age at first calving (AFC), days open (DO), calving interval (CI), gestation length (GL), Pregnancy rate (PR), Interval between first and last insemination (IFL), Days from calving to first service (DFS) and number of services per conception (NS). Edited data included the following: SCR between 7.6 % to -16 %, AFS between 320 and 900 days, AFC between 630 to 1350 days, CI between 300 and 700 days, IFL less than 290, GL between 260 and 290 days, DFS between 20 and 300 days, DO between 40 and 350 days, PR between -28 and 55 and NS between 1 and 10. Select the model equations and fixed effects were optimized using GLM procedure in SAS package. Subsequently, the multi-variate animal model analyses was carried out in order to estimate of direct additive genetic and phenotypic correlations between fertility traits. Estimation of genetic parameters using animal model in REML methodology was done by REMLF90 program.

Heritability estimates for all fertility traits were low, minimum heritability were estimated for IFL trait by heifers (0.002) and maximum amount for SCR trait (0.303). Heritability were estimated for other fertility traits 0.033, 0.005, 0.052, 0.048, 0.085, 0.108, 0.095, 0.059, 0.031, 0.025, 0.023, 0.017, 0.018, 0.013, 0.009, 0.013, 0.032, 0.028 and 0.018 for AFS, AFC, CI, OD, PR, GL_H, GL, DFS_1, DFS_2, DFS_3, IFL_1, IFL_2, IFL_3, IFL_123, NS_H, NS_1, NS_2 and NS_3, respectively. These estimates are in agreement with the results obtained by Ghiasi et al. (2011) and Rahbar et al. (2016) in Holstein cows. Heritability estimates obtained in this study were larger than the ones obtained by Toghiani Pozveh et al. (2009) for CI, DFS and DO in the previous study of Iranian Holsteins. The heritability estimates obtained for interval traits (DO, CI, and GL) were higher than those obtained for categorical (NS) or binary traits. However interval traits may be affected by management decisions such as the length of the voluntary waiting period or estrus synchronization applied in some farms (Ghiasi et al. 2011). In general, negative and moderate additive genetic and phenotypic correlations estimates were obtained between fertility traits. Estimated additive genetic correlations in the range of -0.56 (between GL and AFC) and 0.83 (between IFL and NS). However, estimated phenotypic correlations in the range of -0.80 (between PR and OD) and 0.85 (between GL and OD). The first one is formed by the traits that measure overall fertility of the cow (i.e. CI, OD and PR) which can be obtained directly from calving dates. In particular, OD and PR showed additive genetic (-0.39) and phenotypic (-0.80) correlation estimates which indicates that these two traits are genetically the same as expected because PR is a linear function of OD. The same results were found by VanRaden et al. (2004) and Ghiasi et al. (2011) in Holstein cattle. The mean breeding values were estimated -0.31 to 0.38, -4.14 to -3.34, -6.70 to -5.64, -0.0435 to -0.0064, -2.20 to -1.93, 9.16 to 10.73, 8.72 to 10.15, 3.29 to 4.21 and 4.34 to 5.84 for SCR, AFC, AFS, GL, PR, CI, OD, IFL DFS, respectively. However, the mean phenotypic values was positive, except SCR (range -0.62 to 0.66). These results were in agreement with reported Aghajari et al. (2015); Ansari-Lari et al. (2009) and Shirmoradi et al. (2010). Were estimated negative genetic trend for SCR (-2.22), AFS (-4.02 %), AFC (-2.66 %), GL (-0.07) and PR (-0.83) traits. Subsequently, for CI, DO, IFL and DFS traits, positive phenotypic trends were obtained. These estimated genetic and phenotypic trend agreed with other reports (Faraji-Arough et al. 2011; Rahbar et al. 2016).

Genetic parameters (heritabilities and genetic correlations) have been estimated for fertility traits in heifers and cows and fertility bulls. The results of this study indicated that breeding programs have paid little attention to reproductive traits in Iranian Holstein cows, and therefore it is recommended to pay more attention to these traits in order to improve the performance of Holstein cows. According to the results suggest that the genetic prediction of dairy bull fertility is feasible. This could have a positive effect on the dairy industry, for example, the early culling of bull calves with very low SCR predictions.

The lack of sufficient information in the pedigree of the animals prevents the correct estimation of the breeding values. Henderson proposed a genetic grouping for a more realistic estimation of breeding values for phenotypic records in different years. For these groups, the birth year, the year that the first daughter of the male had recorded, or the year that the male animal was used for insemination were used for grouping. In fact, this grouping was considered for calculating the genetic trend over the years. The incomplete recording of the animals in the population will result in the elimination of true genetic relationships between animals. Although, these animals are considered as the base animal in the analysis, but not born at the same time, and can affect the accuracy of estimated breeding values. The available pedigree information in Iran does not have a good quality index. So that the average of pedigree completeness criterion for Iranian Holstein cows has been reported less than 0.7. Genetic evaluation of Iranian Holstein cows with unknown parents may cause a bias in estimating genetic parameters and breeding values. The use of genetic groups in genetic analysis can partly correct the problem of animals with unknown parents. In this regard, the purpose of this study was to estimate the genetic parameters and breeding values of the production traits (milk, fat, protein) of Iranian Holstein cows with and without genetic grouping in model.

In this study, the pedigree of 1555702 heads of the Iranian Holstein cattle from 14623 sires and 697940 dams that collected by Animal breeding center of Iran till 2013, were used. Production traits, including milk, fat and protein corrected for 305 days and twice milking from first to third lactation periods were used to estimate variance components and breeding values. Herds under 100 heads were not considered for analysis and for all production traits; pedigree related to animals with the record was extracted from the general pedigree using CFC software and used. For animals with unknown parents, genetic grouping was performed based on the sex and the birth year. Traits at different lactation periods analyzed with (model 2) and without (model 1) genetic grouping in the model and genetic trend was calculated. Then the accuracy of breeding values and genetic trend of traits obtained from different models were compared with each other. The Spearman rank correlation was used to investigate the change in animal ranking in a result of considering the genetic grouping.

The additive genetic variance and their standard error were lower for milk, fat and protein production traits in model with genetic grouping (model 21) than the model without genetic grouping (model 1). The estimated heritability range for milk, fat and protein production in three lactation periods with model 1 was 0.094-0.162, 0.069-0.114, and 0.079-0.123, respectively, that these values were higher than model 21 in terms of magnitude. Spearman rank correlation between the estimated breeding values with model 1 and 21 was significantly different from 1, indicating a change in animal rank with consideration of genetic grouping in the model. The spearman rank correlation was lower for males than females, suggesting a higher change in male animal's rank than females. The average accuracy estimated breeding values with model 21 was higher than model 1 and the average accuracy difference was significant between two models. The genetic trend in the first, second and third lactation periods with the model 21 was estimated 63.06, 59.60 and 44.64 for milk production, 1.346, 1.095 and 0.943 for fat and 1.542, 1. 514 and 1.035 kg per year for protein, which were higher than the estimates of model 1.

The results showed that consideration of genetic grouping in the model reduced the additive genetic variances of traits and the heritability estimated were higher without consideration of genetic grouping. The significance of the Spearman rank correlation indicates that the rank of males and females changed by inserting genetic groups into the model and change in the animal's rank for males was higher than females. The high accuracy of estimated breeding values and the genetic trends of traits in the model with genetic grouping suggests that genetic grouping for animals with unknown parents has been done and entered into the model in order to more accurately estimate the breeding values and to better reflect the performance of the breeding programs.

In this study environmental effects, genetic and phenotypic trends for body weight traits in different age in Arabi Sheep estimated. In this study used a total of 11365 records on birth weight, 6930 records of weaning weight, 3275 records of 6 month weight, 2043 records of 9 month weight and 1750 records of 12 month weight. The data used in this study, collected during 1994-2015 in Khuzestan province. The breeding value of the animal were estimated by restricted maximum likelihood method. The SAS statistical software was used to evaluate the effect of environmental factors and Wombat software was employed to estimate animals breeding value. The SPSS software was used for estimation of the trends. Environmental factors such as birth year, Sex, birth type and age of Mather were significant on all traits and were fixed effects in model. Animal’s age was introduced to the model as covariate. Estimation of direct genetic trend for birth weight, weaning weight, 6 month weight, 9 month weight and 12 month weight were as -0.07, -17, 2, 1 and 1 gr per year respectively. The phenotypic trend for considered traits was respectively 5, 256, 76, 83 and 194 gr per year. It can be concluded that reduction of the average breeding value in the genetic trends and the oscillation in the phenotypic trend are due to reduction of recording accuracy and entering livestock with low breeding value to the herd or negative impact of environmental factors on the production potential of livestock.

The objective of this research was to investigate the impact of temperature-humidity Index (THI) on milk yield (MY) and fat percentage (FP) trend of Holstein dairy cattle in Mediterranean climate of Iran. Data included 348,868 and 302,851 test-day records, respectively for milk yield and fat percentage from 42,781 and 38,829 cows, respectively. Data were collected from 9 provinces located in the Mediterranean region of Iran between 2001 and 2016. The climate information from the nearest weather stations to each herd was used to calculate THI. Then the average of daily THI for 3 days before test date was considered as an environmental descriptor for milk production traits. Significance test using GLM procedure was applied to consider fixed effects in the model. Random regression model using Bayesian methodology was applied to estimate breeding values (EBV) across different combinations of days in milk (DIM) and THI via and subsequently, genetic trends for production traits were estimated along year of birth and THI values. The results showed that in addition to re-ranking of sires in different DIM, the different ranks were observed across different THI. In the other word, animals had different responses along THI and sires with higher EBVs for lower THI had lower EBVs for higher THI. Across THI, the re-ranking of sires for FP was more considerable than for MY. In other words, animal for FP were more sensitive in response to climate changes. For both traits, negative genetic trends were observed with increasing THI. In addition, in contrast with MY, a negative trend for FP was obtained based on year of birth. It could be concluded that THI has substantial effect on milk production traits and including this factor with applying random regression model could be useful to investigate heat tolerance of dairy cattle herds in Mediterranean climate.

For genetic progress evaluation of growth traits, the pedigree information of 12140 Raeini Cashmere goats in Raeini Chashmere goats breeding station from 1990 to 2010 were used. Investigated traits were included birth weight, weaning weight, 6 month weight, 9 month weight and 1 year weight. Variance components and genetic parameters of each trait was estimated by restricted maximum likelihood and six animal models using Wombat software. Direct heritability of birth weight, weaning weight, 6 month weight, 9 month weight and 1 year weight were 0.24, 0.29, 0.33, 0.35 and 0.37 respectively. Breeding values of animals for each trait was estimated using univariate animal model. Phenotypic, genetic and environmental trends of traits were estimated via regression of phenotypic value, breeding value and difference of breeding value from phenotypic value on the year of birth. Genetic trend of birth weight, weaning weight, 6 month weight, 9 month weight and 1 year weight were estimated 16.71, 85.83, 105.16, 123.67 and 122.53 gr/year respectively (p<0.01). The genetic gain of traits including birth weight, weaning weight, 6 month weight, 9 month weight and 1year weight were estimated 0.483, 0.561, 1.767, 1.647 and 1.465 Kg respectively. Regarding to positive genetic trends estimated for growth traits for Raeini goats, the livestock selection program, based on the breeding value in this breed, seems to lead to a good genetic improvement and this strategy should continue.

Successful animal breeding strategies rely on selecting superior animals to produce progeny which are expected to have better performance compared to contemporaries at different rearing environments (Doeschl-Wilson 2007). Based on this, the main aim of a breeding scheme is to promote genetic potential of livestock for the traits of great economic importance. Milk yield varies over a course of lactation as a result of continuous physiological mechanisms of growth and death of udder cells (Val-Arreola 2004). Mathematical models used for description of the lactation curve can be empirical (shape-oriented) or mechanistic (biology-oriented) (Farhangfar 2015). Using mechanistic (biological) models it would be possible to study genetic aspects of cows' lactation curve from the biology of milk secretion in udder tissue standpoint. Vast majority of the research undertaken on the lactation curve of Iranian dairy cows have been focused on the use of empirical models. This research was carried out with the objective of evaluating genetic characteristics of the lactation curve of Iranian Holstein grade and pure-bred dairy cows using a mechanistic model. The data used in this research were provided by Animal Breeding Centre, Karaj, Iran. The data set consisted of 1,448,292 test day milk records belonging to 161,676 first parity cows (progeny of 3979 bulls) in 921 herds (in 14 provinces over the country) and calved during 1997- 2012. Minimum and maximum number of test day records were 4 and 13, respectively. Based on the percentage of Holstein gene inheritance (H), cows were divided into four groups. Pollott-Gootwine mechanistic model with two parameters of MS (maximum secretion potential of the lactation) and DR (relative decline in cell numbers) was applied to describe the shape of lactation curve. This nonlinear function was fitted to the individual lactation curves and the parameters were estimated for each cow by using nonlinear procedure of SAS software. Heritability of MS and DR traits was estimated using a fitting univariate animal model. In the model, effects of province, contemporary group of herd-year-season, calving age, type of genotype, interval of first test day from calving, fat to protein ratio, length of lactation as well as random effect of cow were included. All relationship among the animals were taken into account through including pedigree. The model was run for each trait using DMU software and restricted maximum likelihood (REML) estimate of additive genetic and residual variance components and prediction of breeding value of the animals were obtained. Genetic trend was subsequently calculated through fitting weighted regression of mean breeding value on calving year. Additive genetic and residual variance components for MS were 5.7123 and 13.7759, respectively and the corresponding figures for DR were 0.0000012 and 0.0000051, respectively. Heritabilities of MS and DR were found to be 0.293 (SE=0.008) and 0.194 (SE=0.120), respectively indicating that there is relatively good genetic variation for the traits to be used in selection programmes. Mean predicted breeding value (PBV) of the cows with records were 0.255 (Kg) and -0.000005 for MS and DR, respectively. Regarding MS, cows with 50  H  75 had minimum PBV (0.072 Kg) while cows with 87.5  H 100 had maximum PBV (0.309 Kg) and the difference was statistically significant (P<0.05). Based upon mean PBV for MS, mean PBV for the trait of 305-day milk yield in pure-bred Holstein cows (H=100) was expected to be 82.96 Kg. Pearson correlation between breeding values of the traits was -0.29 (P<0.0001) suggesting that cows of high genetic potential for MS are expected to have low breeding value for DR. Phenotypic and genetic trends for MS were 0.52 (SE=0.017) and 0.063 (SE=0.004, R2=0.95) kg per year, respectively, while the corresponding figures for DR were -0.000025 (SE=0.0000021) and -0.000007 (SE=0.00000054, R2=0.92), respectively and that all the trends were statistically significant (P<0.0001). High heritability of MS and DR suggests that appropriate genetic gain could be obtained as the selection of the cows is based upon these traits. As DR is associated with lactation persistency, it could be therefore concluded that Iranian dairy cows have become phenotypically and genetically persistent over the years of 1997-2012.

In order to estimate genetic parameters and genetic trends of growth traits in Lori Bakhtiari sheep using structural equation models and standard multivariate models, pedigree and phenotypic data which were collected from 1994 to 2011 in Lori Bakhtiari sheep breeding station were used. The studied growth traits included birth weight (BW), average daily gain from birth to weaning (ADG1), weaning weight (WW), average daily gain from weaning to six-month weight (ADG2) and six-month weight (6MW). Three different models including standard multivariate model (SMM), multivariate temporal recursive model (TRM) and multivariate fully recursive model (FRM) were considered. Based on DIC values, TRM had the highest plausibility. Under TRM, structural coefficients between BW-ADG1, ADG1-WW, WW-ADG2 and ADG2-6MW were estimated to be 9.343, 0.03, 10.632 and 0.14, respectively. Direct heritability estimates for mentioned traits were 0.32-0.29, 0.2-0.22, 0.17-0.18, 0.11-0.11 and 0.16-0.16, respectively. The estimated values for genetic trends under SMM and TRM were 6-23, 0.7-3, 69-129, 0.4-1.2 and 110-187 grams per year for BW, ADG1, WW, ADG2 and 6MW, respectively. The results of genetic analyses of growth traits indicated the necessity of considering causal relationships between the studied traits for developing efficient breeding program in Lori Bakhtiari sheep

For genetic analyses of growth traits of Kermani sheep including body weight at birth, three, six, nine and twelvemonths of age, 10, 459 body weight records measuredon 3132 animals originated from 78 sires and 1163 dams were used. The data were collected at Kermani sheep breeding station during 1988 to 2010. The data were analyzed using a multivariate animal model. In the model, animal age, sex, type of birth, year and season of birth were fitted as fixed effects. Maternal genetic effects as well as the direct additive genetic effects were fitted as the random effects. Heritability estimates of the body weight measured at birth, 3, 6, 9 and 12 months of ages were 0.14, 0.33, 0.34, 0.12, and 0.16, respectively. The genetic correlations between the growth traits were in a range of 0.78 to 0.98. These results show that the growth traits can be improved genetically. In the station, the genetic trends of the traits investigated were generally erratic and the genetic progress was low which were mostly due to the lack of an efficient breeding program. The genetic progress can be achieved if the animals are genetically evaluated based on their individual performance records and pedigree information.

In this research, investigation of genetic, phenotypic and environmental trends of biometric traits in Makuie sheep was performed using collected data from 1989 to 2012 at Makouei sheep breeding station. Estimation of trends was performed by multivariate animal model using the DFREML software. Genetic, phenotypic and environmental trends were estimated by regression of breeding values average, phenotypic values average and average of difference between breeding values with phenotypic values on birth year, respectively. Results showed that heritability estimates for biometric traits including height at withers, height at rump, body length, heart girth and thigh circumference were 0.23±0.05, 0.25±0.05, 0.19±0.04, 0.28±0.05 and 0.06±0.04, respectively; and the highest genetic and phenotypic correlations were between height at withers and height at rump traits (0.98 and 0.93, respectively). Genetic trends of mentioned traits were 0.25±0.07, 0.26±0.07, 0.59±0.05, 0.22±0.09 and 0.23±0.03 cm; phenotypic trends were 0.08±0.08, 0.07±0.05, 0.39±0.06, -0.23±0.16 and 0.08±0.05 cm and environmental trends were -0.16±0.06, -0.15±0.06, -0.20±0.06, -0.45±0.15 and -0.16±0.04 cm, respectively. Total genetic improvement after 24 years was low and the highest improvement was observed in body length and chest girth traits therefore, it can be concluded that despite the positive genetic trend, selection in this herd were not based on breeding value and regular plan.

The objective of the present study was to estimate genetic, phenotypic and environmental trends for body weight traits at different ages in Kourdi sheep. Thus, the records of growth traits from 5144 lambs (from 161 rams and 1982 ewes) were used. The studied traits were birth weight (5069 records), 3-month weight (3968 records), 6-month weight (3519 records), 9-month weight (2840 records) and 12-month weight (2595 records) that collected from 1996 to 2013 in Kordi Breeding Station in Shirvan city of northern Khorasan province. Variance components and genetic parameters were estimated applying restricted maximum likelihood method fitting six animal models using WOMBAT. The most appropriate model for each trait was determined based on likelihood values. Breeding values were estimated via mixed model equations by the best model for univariate analysis. Genetic, phenotypic and environmental trends were calculated by regression of means of predicted breeding values, phenotypic means and difference between estimated means of breeding values and phenotypic means on birth year for each trait, respectively. Direct heritability estimates for birth, 3, 6, 9 and 12 month weights were 0.10±0.03, 0.28±0.03, 0.32±0.04, 0.22±0.03 and 0.20±0.04, respectively. Direct genetic trends for birth, 3, 6, 9 and 12 month weights were 4.13±0.25, 117.01±5.91, 148.24±5.78, 110.01±5.83 and 122.21±6.89 g per year, respectively. The phenotypic trends for these traits were -7.47, -126.32, -490.21, -493.69 and -599.48 g per year, respectively.

The purpose of this study was to investigate the genetic, phenotypic and environmental trends of growth traits in Shal sheep. In this regard, records were collected on the growth traits of 6692 lambs that were collected from 1997 to 2013 at Shal Sheep breeding station located in Qazvin province. The studied traits included birth weight (6690 records), three months weight (6654 records), six month weight (6662 records), nine months weight (6599 records) and twelve months weight (6528 records). Genetic parameters were estimated using WOMBAT software with limited likelihood method. The genetic, phenotypic and environmental trends of the traits were estimated using the regression coefficient of average breeding values, phenotypic and environmental on birth year, respectively. Direct heritability of body weight at different ages based on the most suitable model for birth weight, three, six, nine, and twelve months were 0.13±0.02, 0.57±0.05, 0.52±0.05, 0.79±0.04, and 0.73±0.05 respectively. Correlation between direct and maternal incremental genetics in all negative traits was obtained. The genetic trend for the traits was -0.86, -10.19, -27.45, -15.73 and -2.44 g/y, respectively. The phenotypic trend was 12.84, -65.19, -57.35, -53.92 and -57.59 g/y, respectively, and also the environmental trends were estimated and environmental trends were 4.33, -21.56, -26.47, -0.98 and -41.91 g/y, respectively. Genetic, phenotypic and environmental trends of all traits were not significant. The results of this study indicate that there is no positive genetic growth of Shal sheep weight traits in recent years. Therefore, appropriate breeding programs are recommended for genetic improvement of the mentioned traits in shal sheep.

The aim of present study was to estimate genetic and phenotypic trends for body weight traits at some ages in Lori-Bakhtiari lambs. In this study a total of 7721 records on birth weight, 6462 records of one month weight, 7275 records of weaning weight 5745 records of 6 month weight, 3326 records of 9 month weight and 3088 records of 12 month weight of Lori-Bakhtiari sheep was used to reveal the genetic and phenotypic trend of growth traits. The data was collected in Shahrekord sheep breeding station during 1989-2010. The SAS statistical software was used to evaluate the effect of environmental factors. Wombat software was employed to estimate genetic parameters and animals breeding value. Environmental factors, like birth year, sex, birth type and the age of mother were significant factors as fixed effects (P

The aim of this study was to estimate the genetic trend and genetic parameters of survival traits in Baluchi sheep using survival records from 27978 Baluchi sheep, which were collected by the Animal Breeding Center of Iran during1979 to 2009. Genetic parameters of lamb survival from 1 to 400 days of age and from 1 to the last recording date. Traits were estimated using animal model (with or without permanent environment of dam) for right censored data assuming an exponential distribution via Gibbs sampling. Effect of year and month of birth, sex, litter size and herd were assumed as fixed. The posterior mean of direct heritability for survival from 1 to 400 days of age and from 1 to the last recording date in first and second model ranged from 0.135- 0.158 and 0.085- 0.168, respectively. Posterior mean permanent variance ratio was 0.076 for survival from 1 to 400 days of age and 0.144 for survival from1 to last recording date. The genetic trend for these traits was −0.0005 and −0.001, respectively. Heritability for survival trait suggested that genetic selection for this trait would be effective in the breeding programs.

In dairy cattle genetic evaluation, the use of real records as well as accurate statistical model are of great importance.
The main objective of the present research was to compare two methods of genetic evaluation of Holstein cows for milk yield. The records were unadjusted (for days in milk) and adjusted (for 305-days) milk yields.
A total of 332,160 records obtained from 332,160 first-parity Iranian Holsteins in 2,318 herds and collected from 1990 to 2010 were utilized. Animal models were used in which the effects of herd, year and month of calving, cow type (crossbred or pure), inseminated sperm (internal, external or unknown), covariables of lactation length (only for unadjusted milk trait), calving age, as well as additive genetic random effect of the cows were included. DMU software was applied to fit the models.
Heritability of unadjusted and adjusted milk traits were 0.23 (SE=0.004) and 0.25 (SE=0.004), respectively and significantly different from each other. For the bulls, correlation between breeding values obtained from two methods considerably increased as the number of their daughters increased. The magnitude of genetic trends in two methods were found to be 22.18 (for unadjusted milk) and 18.5 (for adjusted milk) kg per year which were not significantly different from each other.
With respect to the advantage of real records, it is suggested that unadjusted milk records to be used in an animal model (with covariable of lactation length) for predicting breeding value of Iranian Holstein cattle.