genetic

Profitability of sheep in terms of meat production largely depends on growth traits and carcass characteristics. Despite the importance of the quality of sheep meat, few researches have been conducted in this field in the native sheep of the country. Therefore, the importance of examining the characteristics of animal carcasses, especially when they are still alive, is evident. The aim of the present study was to investigate the genetic and phenotypic relationship between biometric traits, body weights and carcass traits measured by ultrasound in Kurdi sheep of North Khorasan. Since the measurement of carcass traits is difficult and expensive, and in order to better design breeding programs to improve carcass traits, if there is a strong genetic relationship, it is possible to replace traits that are easier to measure with carcass traits that are difficult to measure.

The data of 658 Kurdi sheep in the Shirvan Kurdish sheep breeding and breeding station located in North Khorasan province in the northern area of eastern Iran between 57 degrees east longitude and 37.4 degrees north latitude in the spring, summer and autumn seasons of 2021 were used. The information related to pedigree and birth weights (658 records), three months (652 records), six months (638 records) and nine months (419 records) were extracted from the records recorded in the said station. General linear models (GLM) procedure of SAS software was used to investigate fixed effects on traits. To estimate the parameters and the genetic relationship between the mentioned traits, the restricted maximum likelihood (REML) method was used based on single and two traits animal models in WOMBAT software. Multivariate regression was used to obtain the prediction equation of carcass traits based on other studied traits.

Heritability of subcutaneous fat thickness, area, width and depth of ultrasound longissimus muscle were estimated as 0.1±0.06, 0.06±0.06, 0.10±0.03 and 0.08±0.03 respectively. A high positive genetic correlation was observed between subcutaneous fat thickness and longissimus muscle area (0.71±0.31). Ultrasound carcass traits had a high positive genetic correlation with tail traits. A high positive genetic genetic correlation was found between ultrasound carcass traits and height of the withers, height at rump, heart girth, belly circumference, body diagonal length, thigh circumference and rump depth. The model related to longissimus muscle area with the highest coefficient of determination (0.82) is more reliable than other models for prediction.

The low heritability of traits measured by ultrasound technology in Kurdi sheep of Shirvan Kurdi sheep breeding station showed that improving these traits through individual selection is not very effective and other selection methods (family selection or marker-assisted selection) should be used for improvement of these traits. Generally, due to relatively high coefficient of determination, regression models can be used to predict carcass traits in the flock of Shirvan Kurdi sheep station.

Survival records and pedigree information from Rayeni kids born between 1993 and 2009 from breeding station of Rayeni Cashmere goat, located in the Baft city, were used. Also, by completing questionnaire from breeding station of Rayeni Chashmere goat and flock nongovernmental, in Kerman province environmental factors affecting survival and survival rate were obtained. 11 herds with geographical diversity and different herd sizes in Kerman province were selected. The highest and lowest percentages of kid removal were related to fattening surplus (54.2%) and defective removal (0.4%), respectively. Death due to disease after fattening surplus was the most common cause of kid removal (22.3%). Survival rate in these herds was 89.94 percent. according to the results overall mean of lifetime cumulative was 310.3 days. The effect of fixed factors year and month of birth, sex of kid and kid’s birth weight as quadratic were significant. The estimates of heritability in logarithmic scale were low to medium (0.14 to 0.40), original scale were medium to high (0.25 to 0.70) and effective heritability were medium (0.23 to 0.61). Since the estimated genetic parameters for survival of goats are moderate, to improve the survival of goats from birth to one year of age and increase the economic profit of the farmer, while improving nutritional and managerial conditions, genetic selection within the breed can be considered.

Native fowl have become valuable genetic resources over the years due to their adaptation to harsh conditions in rural areas (Emamgholi et al 2009). Native fowl, despite their lower growth rate and lower egg production compared with broiler strains such as Ross and Cobb and layer strains such as Hy-Line and Lohman, perform much better in the rural system due to their good disease resistance and production under adverse nutritional and environmental conditions (Lakhi et al 2013). Breeding programs have a significant effect on improving the genetic structure of native fowl (Kiani manesh et al 2002). The purpose of this study was to combine the results of studies related to estimating genetic parameters for productive and reproductive traits in native fowl using meta-analysis method in order to improve the accuracy of estimations. In addition, the use of meta-analysis method eliminates the existing differences between studies by examining the heterogeneity between them (Field and Gillett 2010; Lortie et al 2013; Hooijmans et al 2014). Increasing the accuracy of estimates can consequently increase genetic improvement through selecting proper candidates to be parents of next generations. Higher performance will increase the courage of farmers to keep native fowl and therefore it help to keep the birds as a valuable genetic source for the future.

In this meta-analysis study, previous studies in the field of estimating genetic parameters of productive and reproductive traits in Iranian native fowl were collected and used. These articles consisted of 33 articles which were published between years 2007 and 2016. Information used in current study included heritability, genetic and phenotypic correlations of productive and reproductive traits. These traits consisted of birth weight, weight at eight weeks of age, weight at twelve weeks of age, egg number, egg weight, age at sexual maturity and weight at sexual maturity. Cochran test and I2 criterion were used for testing heterogenty among used articles. The range of heterogeneity among studies could be from zero to 100 percent. Ranges of 0 to 25 percent, 25 to 50 percent, 50 to 75 percent and 75 to 100 percent indicate very low, low, moderate and high heterogeneity among studies, respectively. Fixed meta-analysis model is usually recommended for very low and low heterogeneity among studies and random meta-analysis model is normally used for moderate to high rates of heterogeneity among studies. Due to high heterogenty observed among studies in present study, random effects model meta-analysis was performed using Metacor package R software version 3,3,1 and Comprehensive Meta-Analysis (CMA) software version 3. The weighted average of the heritability, genetic and phenotypic correlations were calculated accordingly.

According to the results, the highest heritability among productive and reproductive traits was related to egg weight (0.42) and then weight at sexual maturity (0.41). The lowest heritability was related to egg number with a value of 0.20 and then birth weight with a value of 0.25. The highest positive genetic correlation between productive and reproductive traits was estimated between weight at eight and weight at twelve weeks of age (0.86) and then between weight at twelve weeks of age and weight at sexual maturity (0.64). The highest negative genetic correlation was related to the correlation between age at sexual maturity and egg number (-0.66), then egg number and egg weight (-0.19). Due to combing the results of individual studies using meta-analysis, the standard error of estimations for genetic parameters and consequently their 95% confidence interval were significantly reduced compared to individual studies (Bayssa et al 2021). This reduction indicates an increase in the accuracy of the estimates due to aggregating the results of individual studies (Field and Gillett 2010). A comparison between the results of independent studies and the results of meta-analysis shows a significant reduction in estimated standard errors for heritability and genetic and phenotype correlations in the meta-analysis method. For example, the amount of estimated standard error related to heritability of weight at twelve weeks of age in the meta-analysis was calculated to be 0.0009, while the range of reported standard error in the articles for the heritability of this trait was from 0.05 to 0.08. For weight at eight weeks of age the amount of standard error of heritability in the meta-analysis was estimated to be 0.0009, but the range reported for standard error of heritability for this trait in the articles was zero to 0.06. Similar reduction in the amount of estimated standard error were observed for reproductive traits. For example for egg number, the amount of error in the meta-analysis was estimated to be 0.0013, but the range reported in the articles was 0.01 to 0.13. The amount of estimated standard error related to egg weight in the meta-analysis was calculated to be 0.0009, while the range reported in the studied articles was from 0.004 to 0.07. This decreasing trend was similarly observed for other studied traits, which is due to the aggregation of the results obtained from independent studies.

The results of this study showed that the use of meta-analysis method by aggregating the results of individual studies, will increase the accuracy of genetic parameters of productive and reproductive traits in native fowls through increasing the sample size and reducing estimated standard errors. Therefore, by taking into consideration that Iranian native fowl are economically important animals and considerable demands for their products in the country, using genetic parameters obtained from this study with higher accuracy can play an effective role in the successful design of breeding programs for native fowls and promote genetic improvement in native fowl in Iran.

 One of the most important environmental factors affecting the dairy industry is the temperature changes that showed a negative impact on the industry over the past few years. Increasing temperatures have declined the production and reproductive performance of herds in the tropics. Huge losses are caused annually due to heat stress. Heat stress in dairy cows is caused by a combination of environmental factors (temperature, relative humidity, solar radiation and air movement). Continual genetic selection for greater performance results to increased sensitivity to heat stress. It was one of the reasons why lactation curve during summer has decreasing trend compared to spring in which lactation curve maintained within high levels. Dairy cows at the beginning of lactation have small chances to fight off a thermal stress, and thus it has the strongest effect on the production of milk in the first 60 days of lactation. A negative balance of energy in dairy cows at the beginning of lactation is even more increased by creating and emitting of higher quantity of thermal energy in the period when animals consume less food. For this reason, a high-yielding dairy cows are more sensitive to heat stress than cows having a lower genetic potential for milk production. Impacts of heat stress on reproductive efficiency have been well documented and reviewed. Heat stress has been shown to alter the duration of estrus, colostrum quality, conception rate, uterine function, endocrine status, follicular growth and development, luteolytic mechanisms, early embryonic development and fetal growth. Therefore, the purpose of this study was to investigate the effect of heat stress on yield of dairy cattle in different months of production and also to estimate genetic parameters of production and reproductive traits under heat stress.

 In this study, 169655 records of 60322 dairy cows in different parity in Isfahan province of Iran were used. The studied traits included productive and reproductive traits. Milk test day and fat percent as productive traits and open days and days to first service were considered as reproductive traits. Climatic records of herds were collected from 7 stations less than 70 km away from herds and temperature-humidity index (THI) was calculated for each month in each herd. Dairy milk production records ranged from 5 kg to 60 kg for milk and milk fat percentage from 1 to 7%. Genetic and phenotypic trends were considered by regression of the estimated breeding values on year of the birth. The model used included the effect of herd-year of calving, calving month, parity and temperature-humidity index. An animal model was used to estimate genetic parameters of reproductive traits and random regression was used for production traits. SAS software was used to investigate the significance level of independent factors and DMU software was used to estimate genetic parameters.

 The results showed that the threshold of temperature-humidity index is 72 and more than it has adverse effects on performance. Average days open and difference to first service in different Parity 112 and 60 days respectively and was estimated the average heritability of days open and difference to first service 0.02 and 0.06, respectively. With increase in temperature- humidity index, mean of production traits decreased and this decrease for milk and fat yield traits occurred at temperature-humidity threshold of 72 and 65, respectively. The average of heritability was calculated as 0.32 for milk yield and 0.24 for milk fat percentage. The results indicated that with increasing temperature humidity index in 72 the genetic variance for both traits was increased. In on other words, the cows after heat stress (THI=72). Genetic differences were significantly increased. The results of this study indicate that the additive genetic variances were higher in early lactation (5 to 100 days of lactation), for both milk yield and fat percentage.

 Genetic variance increased with increasing temperature-humidity index (THI = 72) for the two traits of milk and fat production. Also breeding value of open day correction and difference to first calving under heat stress decreased. In other words, there is a significant genetic difference between animals exposed to heat stress after temperature-humidity index 72. Therefore, it may be possible to genetically identify animals more resistant to heat stress as parents of the next generation.

In this study, genetic parameters and (co) variance components were estimated for weights at birth, 3, 6, 9 month, daily weight gain and Keliber ratio from birth to 3 month and also form 3 month to 9 month. Records of 2544 kids, the progeny of 149 sires and 851 dams were used to analysis data by MTGSAM program. Six different animal models were fitted for all traits. The most appropriate model for weight at 6, 9 and daily weight gain and Keliber ratio form 3 to 9 month was model 2. Estimated direct heritability varied from 0.01 to 0.36, which was minimum (0.01) for daily weight gain and Keliber ratio from birth to 3 month and maximum (0.36) for birth weight. The genetic and phenotypic trends for all traits were estimated near to zero and non-significant. Generally, differences between estimated genetic trends for these traits and estimated values of other studies, is due to difference in animal breeding standard followed by different program selection, difference between models and calculation method, effects of environment, interaction between genetic and environmental, nutrition and climate conditions.

Meta-analysis method was used for gathering studies done on genetic parameters estimation in Holstein cows to increase the accuracy of estimations. For this purpose, data from 96 articles on genetic parameter estimation of productive and reproductive traits on Iranian Holstein dairy cows were used. Productive traits were milk production, amount of milk fat, amount of milk protein, milk fat percentage and milk protein percentage and reproductive traits were age at first calving, calving interval, dry days, open days, pregnancy period and lactation period.

First, heritability estimates, genetic and phenotypic correlations were obtained from articles. After data preparation, the meta-analytical model with random effects using Metacor package, R 3.3.1 software and CMA ver.3 software were used for estimating weighted average of heritability and genetic and phenotypic correlations, standard errors and 95% confidence interval for productive and reproductive traits. Investigating available studies showed high heteroginty among studies. Therfore, using fixed model meta-analysis was not possible for estimating weighted average of effects. Data were reanalysid using CMA software and results of random model meta-analysis were reported as final results.

The weighted average of heritability for productive traits in dairy cows were between 0.19 and 0.27. Milk protien percentage had the highest (0.27) and milk fat had the lowest (0.19) heritability estimates amonge productive traits. The weighted average of heritability for reproductive traits was in the range of 0.03 to 0.14. Pregnancy period (0.14) had the highest and open days had the lowest (0.03) heritability estimates amonge reproductive traits. The weighted average of genetic correlations of productive and reproductive traits was in the range of -0.56 to 0.88 and the mean weight of the phenotypic correlations of traits was in the range of -0.42 to 0.83. Comparing the results of meta-analysis in present study with the results of individual studies showed that aggregating studies and analyzing by meta-analysis improves the accuracy of the results through reducing standard errors. For example, in studied articles the range of heritability estimates for milk production were between 0.047-0.41, for milk fat were between 0.05-0.56 and for milk protein were between 0-0.7. However, after using meta-analysis method, these ranges were reduced to 0.23-0.25 for milk production, 0.17-0.21 for milk fat and 0.19-0.29 for milk protein. In addition, because of aggregating studies and increasing the amount of data, standard error of estimates in meta-analysis were considerably reduced compared to standard error of estimates in individual studies, especially for productive traits.

Using methods like Meta-analysis will increase the performance of breeding programs and will improve genetic progress of economic traits of animals by gathering all available information, especially for populations with no or not accurate data.

The optimization of the reference population in genomic evaluation plays an important role in livestock breeding, because of its potential impact on the accuracy of estimating the marker effects and genomic breeding values. In the present study, seven different train set selection methods including selection of all, selection of the highest and lowest performances, random selection, selection of individuals with the most and least marker and QTL similarity were evaluated. In genome wide association study selection of all as train set detected common SNPs which make a high variation on the trait. However selective train set was just reported rare SNPs with a major effect on the trait. In genomic selection simultaneous use of high-density markers and selective train set in comparison with low-density and selection of all as train set reduced accuracy, but did not change the ranking of animals. There was also an interaction between train set selection method and generation (P≤0.0134) as well as the linkage disequilibrium (P≤ 2e-16). In general, selection of all animals as a train set resulted in higher accuracy compared to six selective train set methods. There were no differences between the methods of selecting train set in populations with a low effective size (r2 = 0.255, Ne =100), but in populations with a high effective size (r2 = 0.086, Ne =400) methods, with different accuracy predicted genomic breeding values. The highest and lowest accuracy were respectively belonged to most QTL and marker similarity methods.

In this study 7363 records of birth weight, weaning weight, weight at six months and nine months of age from Lori sheep were used to estimate the genetic and phenotypic trend of growth traits under nomadic rearing system.
The records that related to the nomadic herds were collected during years of 2001 to 2010 by agricultural organization of Lorestan province.
(Co) variance components, genetic parameters and breeding values of growth traits were estimated using restricted maximum likelihood method based on univariate animal model by the DFREML software.
The highest and the lowest direct heritability estimated were birth weight (0.33) and weight in six months (0.052), respectively. The genetic and phenotypic trends were calculated using SPSS software, based on dependency of the breeding value mean and dependency of phenotypic mean on birth year, respectively. The direct genetic trend for birth weight, weaning weight, six months and nine months weight were 13±2, 73±5, 48±8 and 242±21 gr/year, respectively. Phenotypic trend for birth weight, weaning, six months and nine months weights were 38±12, 242±74, 185±98, 129±94 gr/year, respectively. Direct and maternal genetic improvement of birth, weaning, six months weights after 10 years were 161.42 and 52.40, 571.99 and 140.39, 466.14 and 140.71 gr, respectively and direct genetic progress for nine months weight was 469.59 gr.
Genetic trend of traits under study was positive and upward. Considering that the highest direct and maternal heritability estimates in this study was related to birth weight, this attribute can be considered in breeding programs.

In this study, (co)variance components and heritability for performance traits of body weight in 12 weeks, body weight at sexual maturity, age at sexual maturity and egg number of 43,180 birds native Azerbaijan during 14 generations (1988 to 2010) were estimated. Data analysis were undertaken using restricted maximum likelihood method through applying a multivariate animal model. Heritability of the traits was in the range of 0.097 (egg number) to 0.409 (body weight in 12 weeks). High genetic correlations were found between age at sexual maturity and egg number (-0.83) and between body weight at 12 weeks and body weight at sexual maturity (0.744). Genetic trends for body weight at 12 weeks, body weight at sexual maturity, age at sexual maturity and the number of eggs were 14.29 g, -5.5 g, -1.62 day and 0.23 numbers, respectively. The findings of this research revealed that lowering the age of sexual maturity will increase the egg number.

The present study was conducted to estimate genetic parameters and genetic, environmental and phenotypic trends of milk production traits in Holstein cattle of Hamedan province. In this study 11986 305-d records of first three parities of Hamedan province Holstein cattle, which were gathered during 1990-2011, were used. Variance-covariance components and breeding values were estimated using animal mixed model, based on Average Information algorithm of Restricted Maximum Likelihood (AI-REML). Herd-year-season and parity were fixed effects and directs additive and permanent environmental factors were considered as random effects. Heritability estimates for milk yield, fat corrected milk yield, fat percentage, protein percentage, fat yield and protein yield were 0.16, 0.14, 0.20, 0.11, 0.15 and 0.13 and their repeatability estimates were 0.44, 0.39, 0.31, 0.20, 0.35 and 0.39, respectively. Genetic trends of these traits were, 3.42 kg/yr, 2.51 kg/yr, -0.002 %/yr, -0.000 %/yr, 0.082 kg/yr and -0.020 kg/yr, environmental trends were 85.89 kg/yr, 67.61 kg/yr, -0.028 %/yr, -0.007 %/yr, 1.12 kg/yr and 1.62 kg/yr and their phenotypic trends were 89.54 kg/yr, 70.26 kg/yr, -0.030 %/yr, -0.007 %/yr, 1.22 kg/yr and 1.69 kg/yr, respectively. The results of this study showed that the production traits of Hamedan province Holstein cattle did not have noticeable genetic improvements in past years and most of milk and fat yield increment have been induced by improvement of environmental conditions.

In this study, 2554 calving records from 1484 Holstein cows were used.
The data were collected from one of the East Azerbaijan herds, during 2009 to 2013. The studied traits were production traits (305 d milk and 305 d fat yields) and reproduction disorders (dystocia and retained placenta).
Estimation of genetic parameters was performed by repeatability animal linear (305 d milk and 305 d fat yields) and threshold models (dystocia and retained placenta), by single and two-trait analyses.
Heritability for 305 d milk yield and 305 d fat with single-trait analysis were estimated 0.33 and 0.23, respectively and the repeatability of these traits were estimated 0.35 and 0.25, respectively. Heritability of dystocia and retained placenta were estimated 0.09 and 0.1, respectively and the repeatability for both was estimated 0.11. Genetic correlation between production traits were estimated 0.98 and genetic correlation between reproduction disorders were estimated 0.51. Estimated genetic correlations between production traits and reproduction disorders were from -0.85 (305 d fat and retained placenta) to 0.21 (305 d milk yield and dystocia).
Considering negative genetic correlation between milk production and dystocia and a relatively strong positive correlation between these two reproductive disorders, planning of selection programs in dairy cows based on a combination of production and reproduction traits is recommendable. Also ignoring these relationships in selection may negatively influence overall performance in a long term.

The study was designed to investigate the relationship between growth trait and biometric traits in Baluchi sheep. This study was conducted to estimate the genetic and phenotypic biometric traits including daily gain (ADG) and height at withers (HW), height at back (HB), body length (BL), heart girth (HG), leg girth (LG) and testis girth (TG) in Baluchi sheep. Total data of 4542 records from six experimental herds of Jahad Organization Research Centre of Mashhad County were collected since 2001 to 2011. Data were analyzed using General Linear Model (GLM) of SAS. For the estimation of genetic parameters and genetic correlation between traits, animal model uni and multi-trait by restricted maximum likelihood (REML) of WOMBAT 32 (Meyer 2007) have been used. The mean heritability of ADG, BL, HG, HW, HB, TG and LG traits was estimated 0.13±0.01, 0.11±0.06, 0.21±0.07, 0.17±0.06, 0.32±0.1 and 0.2±0.06 respectively. The results of the current study showed that the TG trait has the highest heritability. The estimations shows genetic improvement will be predictable in biometric traits of Baluchi sheep. The genetic correlation between traits was positive, ranged between 0.15-0.97. Moreover, phenotypic correlation was positive and was estimated in range of 0.32 to 0.94.

In this study، the number of 1802 longevity records of ewes collected during 1989 to 2010 in Breeding Station of Lori-Bakhtiari sheep flocks were used to estimate of genetic، environmental and phenotypic trends for economic lifetime. The breeding values of a ewe’s lifetime were estimated by restricted maximum likelihood procedure under an animal model of univariate analysis. The best linear unbiased prediction of breeding values estimated and genetic trends were estimated as a regression coefficient of average breeding values on the birth year of ewes. The environmental and phenotypic trends estimated as a regression coefficient of average environmental deviation and phenotypic deviation (deviations of phenotypic values from overall mean) on the birth year of ewes. The results showed that، genetic trend of longevity was positive (0. 033 days) but insignificant from zero. While the environmental and phenotypic trends were equal to -27. 81 and -27. 78 days، respectively، and significantly different from zero (P<0. 05). Thus، selection for growth traits did not affect longevity traits as genetically and to exhibit negative phenotypic trend for longevity the environmental factors should improve firstly

Data of Kermani sheep which collected during 2003-2009 were used in this study. The data included birth weight (BW)، weaning weight (WW)، six month weight (6MW)، nine month weight (9MW) and yearling weight (YW) traits. Estimate of (CO) variance component with the DFREML program and animal model with unitrait and multitrait analysis. In this study، fitting six different animal models and significant effects on the models were tested by likelihood ratio. In this breed، direct additive genetic analysis without other random effects result in overestimated direct heritability. underestimate the maternal effect especially، maternal additive effects، with and without genetic covariance effect، showed that a significant portion of phenotypic variance of body weight at different ages، especially before weaning due to maternal genetic effect. Estimate direct Heritability of the traits by univariate analysis was 0. 003، 0. 1، 0. 08، 0. 0006 and 0. 06، respectively. Direct heritability results by multitrait analysis was 0. 42، 0. 17، 0. 09، 0. 02 and 0. 11، respectively. Genetic correlation between BW with WW and 6MW were 0. 33 and 0. 15 and the correlation for BW and YW was 0. 09. phenotypic correlations between yearling weight، BW and WW were 0. 01 and 0. 09 respectively، and the other traits were negative correlation. This result indicate sever weight changes controlled by environmental conditions.

In this study, records of 64220 first lactation dairy cows were used. Data were collected from 749 herds during 1996 to 2009 by the Animal Breeding Center of Iran. Data included of production (305 d milk yield, 305 d fat percentage, 305 d protein percentage and lactation length) and reproduction (dry days, age at first calving, calving interval and days open) traits. Data analysis was performed by restricted maximum likelihood procedure using DFREML software. The estimated heritabilities of milk yield, fat percentage and protein percentage and lactation length were 0.197, 0.282, 0.333 and 0.031, respectively. The estimated heritabilites of dry days, age at first calving, calving interval and days open were 0.015, 0.079, 0.035 and 0.036, respectively. Genetic correlations between production traits were from 0.52 for milk yield and fat percentage to 0.74 for fat percentage and protein percentage. Genetic correlations between reproduction traits were from 0.07 (age at first calving and calving interval) to 0.95 (dry days and calving interval). Estimated genetic correlation between production and reproduction traits were from -0.63 (milk yield and dry days) to 0.96 (lactation length calving interval). Considering negative genetic correlation between production and reproduction traits, planning of selection programs in dairy cows based on a combination of production and reproduction traits is recommendable.

(Co) variance components and genetic parameters for growth traits including birth weight (BW), weaning weight (WW) and six-month weight (6MW) as well as parameters, genetic and phenotypic trends of reproductive traits including total weight of lambs weaned per the ewe (TWLW) and the number of lambs born at birth per ewe (NLBE) in Lori sheep were estimated using the Bayesian method. The data included 7363 records for BW, 7054 records for WW, 6765 records for 6MW, 1012 records for TWLW and 1048 records for NLBE. The data were collected by the Agricultural Organization of Lorestan Province between the 2001 to 2010 years (for growth traits) and 2003 to 2010 years (for reproductive traits). The estimates of direct heritability for lamb body weights were 0.36 at birth, 0.11 at weaning and 0.05 at six months of age. The genetic and phenotypic trends reproductive traits were calculated based on regression of the mean of breeding value on birth year and mean of phenotypic value on birth year, respectively. Heritability, genetic and phenotypic trends for TWLW trait were 0.05, 5.4±1.16 and 255±0.45 grams per year, respectively. Heritability, genetic and phenotypic trends of NLBE trait were 0.09, 0.002±0.02 and 0.125±0.07, respectively. Genetic improvement of TWLW and NLBE traits at considered period were 31.64 grams and 0.008 of Lamb. The estimate of heritability at birth was higher than other traits so selection based on this trait would increase the genetic advances. Genetic and phenotypic trends for reproductive traits were not significant and the genetic trend was low.

Genetic and phenotypic parameters were estimated for calving interval (CI)، open days (OD)، conception rate (CR)، gestation length (GL)، number of service per conception (NSPC)، interval from calving to first service (CTFS)، age at first calving (AFC) and Interval from first service to conception (FSTC) in 6 large Holstein dairy herds in East Azerbaijan province. The reproductive traits used in this study were collected from 1997 to 2009 at the Livestock Service of the Ministry of Jihad Agriculture. Genetic and phenotypic parameters of the traits were estimated using restricted maximum likelihood (REML) procedure under univarite and multivariate animal models applying WOMBAT software. The estimated heritabilities for CI، OD، CR، GL، NSPC، CTFS، AFC and FSTC were 0. 047، 0. 041، 0. 073، 0. 060، 0. 071، 0. 21، 0. 12 and 0. 044، respectively. The estimated genetic correlations among the traits ranged from 0. 002 for OD–NSPC to 0. 97 for FSTC–NSPC. The estimated phenotypic correlations were generally lower than those of genetic correlations and ranged from 0. 001 to 0. 71.

In this study, calving records of 4221 Iranian native buffaloes from 621 herds which were collected by the Animal Breeding and Livestock Products Improvement Center of Iran from 2003 to 2010 were used to estimate heritability, genetic and phenotypic correlations between milk production, milk fat production, age at first calving and first calving interval using univariate and bivariate animal models. The highest and the lowest heritabilities were estimated for milk production (0.46±0.01) and first calving interval (0.01±0.29), respectively. Heritability estimates for age at first calving and milk fat production in the studied population were 0.21±0.21 and 0.27±0.17, respectively. Positive and high genetic correlation between milk yield and milk fat production (0.55) in this study indicated that milk fat increased along with increasing in milk production. Negative and medium genetic correlation between milk production and age at first calving (-0.25) indicated that genetic selection for milk production cause decrease in age at first calving. Positive and high genetic correlation between age at first calving and first calving interval (0.96) indicated that selection based on lower age at first calving cause reduced first calving interval.