mohammad razmkabir

There has been extensive ongoing research on honey bees over the last 100 years, mainly due to their vital role in society, particularly in agriculture, economics, food security, medicine, and even computing technologies. Our knowledge is growing faster than our ability to absorb it. The most common and prominent honey bee species in Iran is the western honey bee, Apis mellifera, which includes the Iranian honey bee, Carniolan, and Iranian × Carniolan hybrids. The objective of this study was to identify the effects of crossbreeding on population dynamics, egg-laying rate, propolis production, honey yields, pollen collection, and defensive behavior in Iranian (Apis mellifera meda) bees. In early March 2021 (the end of the colonies' wintering season), eight colonies of each of the three bee breeds were randomly selected and standardized based on honey and pollen storage, the number of brood frames, initial population, and hive type (Langstroth hives). The tested colonies did not receive any chemical treatments during the experiment. Data collection and recording of egg-laying rates and brood rearing were conducted weekly during spring 2021 at the Honey Bee Research Centre, University of Kurdistan, Sanandaj, Iran (35.27788; 46.99562). Data quality control and analysis were performed using the SAS program. The results showed that Iranian × Carniolan hybrids were more efficient than the parental stocks in terms of population dynamics and pollen collection (p<0.05), indicating positive heterosis and complementarity between the breeds. Carniolan (Apis mellifera carnica) bees demonstrated significantly favorable performance for honey yields (p<0.05). Iranian (Apis mellifera meda) bees were superior in propolis production and exhibited higher levels of aggressiveness, significantly (p<0.05). Heterosis was estimated based on the superiority of observed phenotypes in the hybrids relative to their inbred parents. The estimated heterosis values were -3.8% for honey yields, 32.6% for pollen collection, 10.0% for egg-laying rate, 24.5% for population growth rate, -2.1% for propolis production, and -16.3% for aggressiveness. The highest level of phenotypic diversity was observed in the Iranian honey bee, suggesting the potential benefits of this breed for selection programs. Additionally, the findings revealed that the controlled use of higher-performance lines, either in pure or hybrid forms, will improve the efficiency of honey bee colonies and is recommended.

The aim of this research was to study different economic selection indices to increase body weight in Markhoz goat breed. Body weight (BW) at different ages (birth, weaning, 6-month and 9-month) were categorized as several two- and three-traits selection indices. Genetic parameters were estimated with MTGSAM using the Bayesian statistical method. Selection index analyzes were done using SelAction software. The results of comparing three-trait indices showed that highest total economic gain resuled from I9 which was US$4.86. The total economic response for two-trait index belonged to I4 which was US$3.94 and higher than 5 others. The highest direct genetic gain from three-trait indices was predicted for 9-month weight in I8 and I9 indices to be about 0.63 kg. In addition, the highest direct genetic improvement resulting from two-trait indices was also predicted for the 9-month weight in the I3 to be 0.66 kg. Moreover, the selection and performance criteria revealed decrease in phenotypic variance, heritability, and genetic correlation of traits. These changes differed in alternative selection schemes, which influenced by the initial population parameters, selection intensity, direct or indirect selection, and the number of traits included in the selection index. In conclusion, to maximize the total economic gain, two selection indices I9 and I4 can be suggested for the current condition of the Markhoz goat population. However, to preserve the phenotypic/genetic variance of traits, it is necessary to focus on strategies such as selection intensity, economic coefficients, indirect selection, and increasing the number of traits in selection indices.

Artificial neural networks (ANN) have been widely used for both prediction and classification tasks in many fields of knowledge; however, few studies are available on animal science. The objective of this study was to prediction of breeding values of weaning weight in Markhoz goats based on the Mixed Model Equation (MME) and Artificial Neural Networks (ANNs). Quality control and calculation of descriptive statistics was performed using the GLM procedure of the SAS statistical package. The pedigree file included 5541 kids produced by 261 bucks and 1616 does. In the first step, genetic evaluations and Best Linear Unbiased Prediction (BLUP) of breeding values for weaning weight was computed with the mixed model equations, animal model by DMU program. Later, unique dataset was introduced to the ANN models by the R statistical program. A variety of models including, multilayer perceptron (MLP), radial basis function (RBF) and Support Vector Regression (SVR) were used to build the neural models. The artificial neural networks were trained and several networks (different hidden layers and nodes/ neurons) were evaluated. In artificial neural networks, the data were randomly divided to two parts (75% training and 25% for test/validation). Best architecture was selected according to the mean square of error and correlation. Correlation between true breeding value (BVs predicted by MME) and estimated breeding value (BVs predicted by ANNs) for MLP, RBF and SVR models were 0.72, 0.49 and 0.73, respectively. Analysis of farm data showed that the MLP and SVR models have higher performance than RBF for prediction of breeding values or ranking of individuals.

Selective signatures provide information about the stages of evolution of different species, including sheep, which lead to changes in their genome over many years. The aim of this study was to detect signatures of selection in the genome of Iranian sheep in the highlands. A total of 58 sheep from 4 breeds, two breeds scattered in the highlands and two breeds scattered in the lowlands, were genotyped using Illumina ovine SNP600K BeadChip genomic arrays. Two statistical tests of unbiased FST (Theta) and hapFLK were used to identify the selection signatures. The results of Theta revealed 22 genomic regions and the results of hapFLK revealed 15 genomic regions. Bioinformatics analysis demonstrated that many of genes had important effects on adaptation to hypoxia conditions e.g. rheumatoid arthritis (TXNDC5), hematopoiesis (FANCA), immunity and fighting infection (LEF1, NMUR1, PTMA and COPS7B), regulating blood pressure and responding to pain and inflammation (NMUR1) and suppressing cancer (CD82, GAS8, PRMT1, B3GNT7). For example, TXNDC5 and FANCA functional genes, which are located on chromosome 13 and 14, were related to reacts to hypoxic conditions and hematopoiesis. Also, genes such as LEF1, NMUR1, PTMA and COPS7B are effective in immunogenicity and fighting infection. Study of the reported QTL in these regions of the sheep genome showed that they overlapped with QTL of economically important traits such as corpuscular hemoglobin concentration, hematocrit, traits related to meat, carcass, milk, body weight, bone density, and the total number of lambs born. Due to the fact that little research has been done regarding adaptation to altitude in sheep, the results of this research may facilitate the identification of genes affecting adaptation to altitude. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes.

Natural and artificial selections change the allele frequencies among populations and consequently leave detectable patterns on the genome during domestication. A little information about the differences of genetic structures of Iranian native breeds that result in these selective pressures are available. Therefore, in this study, we examined genetic diversity using four native horse breeds including Turkmen (29 samples), Caspian (21 samples), Kurdish (67 samples) and Persian Arabian (52 samples).

For this purpose, three methods including Principal Component Analysis (PCA), neighbor joining (NJ) and admixture were investigated. In addition, with the integrating of three different selection of signature methods, including TajimaD, nucleotide divergency (pi) and integrated haplotype homozygosity score could identify the selection traces in these breeds. To integrate the different results of these three methods, De-correlated composite of multiple signals framework was used.

All the methods used to examine the genetic structure well separated these four breeds and showed a pattern related to geographical origin for their genetic diversity. By combining different methods of identifying the selection signatures, many genes affected by the selection pressure were identified in all four breeds. These genes were associated with specific GO terms and QTL, in which 16 shared candidate genes among all four breeds were identified as suggested candidates for selection. Additionally, 11 different QTL types was identified in all four studied breeds, which was divided into the category of traits related to adaptation, fitness through genetic disorders or morphological and behavioral traits.

Overall, the results of this study can help better understand the process of natural and artificial selections in Iranian horses. In addition, this research has helped to improve our understanding about the genetic differences between studied Iranian horse breeds, which can help in finding the best solution to preserve and improve genetic diversity.

Milking activity is one of the most important daily activities in industrial dairy farms, which accounts for about 80 percent of the annual milking costs and more than 50 percent of the daily activities of each dairy farm. Milking speed (MS) is an important functional trait to dairy producers and in few countries (e.g. Canada), MS have been recorded for several years by milk recording agencies. Functional traits include traits related to animal health, feed efficiency, milkability, and calving ease. Milkability is the ease of milking in dairy cows (Gäde 2007). One of the important traits related to milkability is milking speed and usually, milkability is evaluated by measuring this trait (Gray et al. 2012). Milking speed refers to the amount of milk released from the mammary glands per minute (Klindworth 2003). Due to the effect of milking speed on udder health and labor productivity, this trait is considered a very important one from an economic point of view and has been emphasized in dairy cow selection programs for many years (Karacaören et al. 2006). However, there is evidence that increasing of milking speed is associated with increasing of udder health problems such as mastitis, and as a result, the optimal milking speed is considered by breeders. Milking speed can be assessed based on two indicators; 1) Scoring based on 1 to 5 points and 2) Using electronic stopwatch and flowmeter. The advantage of using a stopwatch is that it is being used easier than a flowmeter and the duration of its use is being reduced, However, the need for a technician to be present during milking is a major drawback of this method (Beard, K. 1993). This study aimed to estimate genetic parameters for milking speed and association between milking speed and milk components (somatic cell score, protein percentage, and fat percentage), in Holstein dairy cows in Isfahan province, Iran.

Data were 5292 observations related to 1762 cows in 7 herds of Holstein dairy cows in Isfahan between October 2015 and April 2016. The distribution of MS scores was skewed toward faster milking speeds. Milk components data, including fat percentage, protein percentage and somatic cell count, belong to the same date, was obtained from the Isfahan Farmers' Cooperative (Vahdat). Only herds with complete pedigree information and three milkings records per day were selectected for final dataset. The milking time of each animal was measured by using a stopwatch and recorded in the form. Data editing quality control was performed by using Excel (2013) and FoxPro 9.0. The average milking flow rate criterion(amount of produced milk in kilograms divided by the milking time in minutes) was used to evaluate the trait of milking speed. To generate data with normal distribution, the somatic cell count (SCC) was transformed to somatic cell score (SCS) by natural logarithmic conversion. Pedigree was traced back to the founder generation. (Co)variance components were estimated using a DMU software package with an average-information (AI)-REML algorithm for the analysis of multivariate mixed models (Madsen and Jensen, 2013).Genetic evaluations and Best Linear Unbiasd Prediction (BLUP) of breeding values for milking speed was computed with the animal model by DMU program.

The results of the analysis of variance showed that the effects of herd, milking frequency, parity, and stage of lactation on milking speed were significant (p <0.01) and remained in the model. However, the effect of age at the first calving on this trait was not significant (p > 0.05). Mean of milking speed of the animals in this study was 1.96 ± 0.75 kg/min, and the least square means of milking speed in the population was 2.11 (±0.01) kg/min. The highest least square means of milking speed belonged to the third-parity cows with a mean of 2/21 (±0.01) kg/min and the least square means of milking speed belonged to the primiparous cows with mean of 1/98 (±0.02). Older cows have higher-capacity gland cisterns, and consequently, their cisterns can store more milk than the cisterns of primiparous cows. More milk stored in the cisterns can put more pressure on the teat sphincter and escape more quickly. By stages of lactation, the highest least square means of milking speed was observed in group 4 (the cows in the 51 to 65 DIM) with mean of 2/32 (±0.05) kg/min which can be due to the location of the animal in its milk yield peak. Also, the lowest least square means of milking speed was related to group 15 (the cows in the 321 to 350) with mean of 1.79 (±0.04) kg/min. In late lacataion stage, the amount of milk produced by the cow will reach the lowest possible level during its lactation stage. The estimated heritability of the milking speed in this study was 0.22 (±0.06). The results of this study showed that the traits related to milkability have moderate heritability. A high genetic correlation was observed between milking speed and milk yield (0.90) and milking time (-0.83). The estimated genetic correlation between milking speed with fat percentage and protein percentage was high and negative, -0.69 and -0.47, respectively. In this study, the estimated genetic correlation between milking speed and somatic cell score showed that selecting to increase the milking speed would reduce the somatic cell count. In general, Genetic evaluations for MS can provide useful information for breeding decisions because of the moderate heritability of MS.

Milking speed has a moderate heritability that allows selection to improve this trait in breeding programs.

The objective of the present study was to perform genetic evaluation of dystocia, using linear (observed and adjusted) and threshold models in Holstein cattle. Data and pedigree information of 8 dairy herds were obtained from Vahdat Industrial Agriculturists & Dairymen Cooperative, Isfahan, Iran. Final data included 133876 calving records during 2005 to 2018. The fixed effects of the model were included, herd, year-season of calving, calf gender and age at first calving.  The random effects of the model were included sire, maternal grandsire, permanent environment of dam and residual effects. Furthermore, 305-day milk yield was considered as a covariate in the final equation. Quality control and data validation were conducted in SAS and Microsoft Excel. Genetic evaluations and prediction of breeding values for dystocia was computed, using different statistical models by DMU program. Direct heritability for dystocia for heifers and other cows based on linear model were 0.10 and 0.07 and based on threshold model were 0.13 and 0.10, respectively. Estimated heritability was higher in threshold model compare to the linear model. The results of this study showed that beyond the environmental improvement, genetic selection might be an option for decreasing dystocia. Estimated heritability for heifers and other cows by the linear model were adjusted on the underlying scale to 0.19 and 0.14, respectively. Estimated correlations between direct and maternal genetic effects were negative and ranged from -0.56 to -0.74, indicating the genetic antagonism between direct and maternal effects. The Spearman rank correlations for breeding values predicted from the linear and threshold models were significant and different from 1, indicating that ranking of animals are not unique in linear and threshold models. Based on the Akaike Information Criterion (AIC), threshold model was better and more accurate than linear model for genetic analysis of dystocia in Holstein cows.

The present study aimed to evaluate the effects of crossbreeding on milk yield, physical and chemical composition and fatty acid profiles of milk fat in Qazvini goats and its crosses with Saanen goats. Records of 316 lactations and 1745 test-day milk were available for Qazvini (Q), Qazvini×Saanen (QS), and QS×Saanen (QSS) goats. The least squares means and standard errors of daily milk yield in Q, QS, and QSS goats were 716±75, 1188±61, and 1373±107 g/day, during the lactation length of 163, 160 and 166 days, respectively. In Q milk, the percentages of total solids, fat, protein, lactose and ash, and the density (-1000, g L-1) and freezing point (-°C) were 15.12, 6.01, 3.39, 4.91, 0.80, 29.91 and -0.601 being higher (P<0.01) than those of crossbred goats (except for milk density). Concentration of milk saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) for Q, QS, and QSS were 68.31, 67.42, 75.34, and 2.74, 4.10 and 3.25 g/100g total fatty acids, respectively (P<0.05).   Concentration of monounsaturated fatty acids (MUFA) for those groups were 20.16, 19.18 and 18.43 g/100g total fatty acids, respectively (P>0.05). Despite decreased concentration of milk components, crossbreeding might be recommended in increasing the milk production and the amount of PUFA fatty acids in Qazvini goats.

The purpose of this study was to evaluate traditional, genomic, gene-assisted traditional selection and gene-assisted genomic selection methods for introgression a major gene in sheep population to improve the litter size trait using computer simulation. In this regard, a trait with heritability of 0.1, including two chromosomes each with a length of 100 cM, was simulated. On chromosome 1, a single QTL as the major gene was created that accounted for 40% of the total genetic variance. This QTL was located in the position of 25.7 cM. In breed A and B, animals were selected based for favorable and unfavorable to create two breeds that has been fixed for opposite alleles. Using the gene introgression approach, the favorable allele in breed A was insert to breed B and the new population was evaluated for genetic gain, accuracy of evaluation, frequencies of favorable allele and inbreeding rate. After five backcrossing generations, genetic gain in GasGenomic and Genomic methods was 26 and 62 percent higher than GasClassic and Classic methods, respectively. The frequency of favorable allele after five generations in Classic, Genomic, GasClassic and GasClassic was 0.387, 0.778, 0.965 and 0.975, respectively. The results of this study showed that if the goal is only introgression a major gene into an indigenous breed, by using gene-assisted classic selection, the frequency of a major gene can also be increased as much as obtain by the gene-assisted genomic selection.

The objective of this study was to compare introgression and synthetic breed strategies for litter size trait improvement in sheep using computer simulation. For this purpose, a trait with heritability of 0.1, consisting of two chromosomes was simulated. On chromosome 1, a single QTL as the major gene was created that accounted for 40% of the total genetic variance. The effect of favorable and unfavorable alleles for the QTL was fixed after seven generations in both A and B breeds, respectively. The introgression and synthetic breed strategies were compared using Classical and Classical with gene-assisted selection (GasClassical) methods. The genetic gain in introgression and synthetic breed strategies using GasClassical method was 39% and 16% higher than that of Classical method, respectively. The mean of inbreeding coefficient in the fifth generation in introgression strategy was 0.049 and 0.077 using the Classical and GasClassical methods, respectively, and in synthetic breed strategy was 0.11 and 0.008, respectively. The results of this study showed that the GasClassical method in comparison with the Classical method led to an increasing frequency of favorable allele (major gene) and genetic gain in both introgression and synthetic breed strategies. However, the genetic gain for one percent increase in inbreeding in the synthetic breed strategy was greater than that of introgression strategy, and as a result, the synthetic breed strategy performs better than introgression strategy.

Genetic evaluations are computed to assess the genetic merit of animals based on mixed model equations. An important assumption for setting up these equations is that all genetic relationships among animals are available and correct. The objectives of the present study were to estimate the effects of incomplete pedigree and paternity errors on genetic evaluation. Data and pedigree of 100 dairy herds were obtained from Animal Breeding Center of Iran. Final data edited included milk yield records from 302860 first lactation Holstein cows. DMU Trace program was used for tracing ancestors and creating the full pedigree of animals. To simulate incomplete and wrong pedigrees, different scenarios including 8, 12, 16, 20, 24 percent of paternal identification numbers were removed or replaced using R program. Breeding values for milk yield was predicted by animal model using DMU program. Spearman's rank correlation was estimated for superior animals in different scenarios using SAS software. Estimates of heritability for full, incomplete and wrong pedigrees were 0.29, 0.26 and 0.27, respectively. The results showed a high variation in ranking of animals and determination of superior animals (P<0.01). As an example, at 12% level scenario, Spearman's rank correlation of BVs predicted from full pedigree with incomplete and wrong pedigrees were 0.65 and 0.60, respectively. Selection effectiveness, defined as the ratio of common superior animals in alternative scenarios, was decreased by increasing the rate of misidentification and errors (P<0.01). Incorrect pedigree and misidentification of animals could reduce accuracy of breeding values and consequently bias in animals ranking.

The aim of the study was to compare two strategies in Mazandaran native fowls using computer simulation.  Simulated traits included body weight at birth (BW1), at eight weeks of age (BW8), at twelve weeks of age (BW12), at maturation (BWM), age at sexual maturity (AFE), weight of first egg (EWM), mean egg weight from 28 to 32 weeks of age (EW28-32) and egg number (EN). The first strategy was to select cockerels based on breeding value of BW12 and hens based on a selection index with 4-traits including BW12, AFE, EW28-32 and EN. The second strategy was to select cockerels and hens using a selection index based on a 4-traits including BW12, AFE, EW28-32 and EN. After 10 generations, the first strategy improved BW1, BW12, BWM, EW28-32 and EWM to 1.49, 573.81, 397.58, 3.96, and 3.75 grams and AFE and EN to -3.51 days and 2.09 eggs, respectively. After 10 generations, the gain for traits in the second strategy for BW12, BWM, AFE and EN was 415.78, 218.74 grams and -9.77 days and 9.45 eggs, respectively. At the end of the tenth generation increase of inbreeding in the first and second strategies was 0.048 and 0.070, respectively.  The results showed that the first strategy was suitable for a breeder flocks with the aim of chickens suitable for broiler production and the second strategy was suitable for a dual-purpose flocks with the aim of producing egg and meat.

The aim of this study was to extract genes and probes hub based on Bayesian networks on probe and gene transcriptomic data over different tissues in Bovine species. Using raw probe and gene transcriptomic data in each tissue, genes and probes with the highest expression variances were extracted and fitted to Bayesian networks. The hub genes and hub probes were identified using the ratio of in-and-out degree.The size of the Markov Blanket was different in different networks. This might be indicative of existing of substructures topology of aforementioned network on different tissues. Using gene based network, in muscle (CBR1 and LOC788826); in mammary of (NID2, COL5A2, LOC616942 and FXYD3); in liver (LOC100132279; MGC127133; MBOAT2; CLDN2; ANKRD1; IGFBP1; DGAT2; CKMT1, ISG15, CKMT1), and in the ovary (LOC286871 and INHBA) were extracted as hub genes. It was shown that the hubs were different in different tissues. These results can be used for more accurate bioassays of each tissue. Using probe based network, two genes BOLA-DQB and JSP.1 would have function in liver and uterus tissues. The results of this study can reduce the gap between phonemics-and Genomics distance on investigated tissues in bovine species.

Genomic Selection (GS) is a tool for prediction of breeding values for quantitative traits. For a successful application of GS, accuracy of predicted genomic breeding value (GEBV) is a key issue to consider. Here we investigated the accuracy of GEBV in 345 genotyped Iranian Holstein cattle. The study was performed on milk, fat, protein yield and somatic cell count. Four methods G-BLUP, Bayes B, Reproducing kernel Hilbert Spaces (RKHS) and Neural Networks (NN) were used to predict genomic breeding values and their accuracies. The GEBV accuracies varied between 0.39 for somatic cell count to 0.73 for fat yield. Bayes B gave the highest accuracies among methods. Bayes B and non- parametric methods tended to produce inflated predictions ( slope of the regression of GBV on EBV greater than 1). However, in all traits, lower estimates of MSE were obtained using G- BLUP. Bayes B regression model are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions.

Genetic parameters were estimated for somatic cell score (SCS) in dairy cattle of Iran using test day records. The records of first lactation were extracted from the database of National Animal Breeding Center for cows calved between 2001 and 2010. Data included 222923 test-day records, obtained from 29668 animals distributed in 100 different herds. Estimates were carried out through Gibbs sampling procedures and using a random regression test-day model. Lactation curve were described in the model with orthogonal Legendre polynomials on days in milk. In order to correct for heterogeneity effect of residual variance, lactation period (5 to 365 days in milk) was classified into 10 groups with unequal distances. According to the results, residual variance was highest at the beginning and it was steady and decreased slowly from the second months to the end of lactation. Low residual and permanent environment variances and high genetic variance were lead to increase of heritability at the end of lactation. The lowest and the highest of heritability were at days 68 (0.031) and 365 (0.098), respectively. Genetic correlations between individual test-day records were high for adjacent tests and decreased as the interval between tests increased. Daily breeding values and genetic curve across lactation were produced for all animals using predicted regression coefficients. Estimation of genetic and phenotypic trends for SCS were -0.0025 and -0.1075, respectively (P<0.01). The results show a desirable improvement for somatic cell score at genetic and phenotypic levels.

Introduction The mating of related individuals produces an inbred offspring and leads to an increased homozygosity in the progeny, genetic variance decrease within families and increase between families. The ration of homozygosity for individuals was calculated by inbreeding coefficient. Inbred individuals may carry two alleles at a locus that are replicated from one gene in the previous generations, called identical by descent. The inbreeding coefficient should be monitored in a breeding program, since it plays an important role at decreasing of homeostasis, performance, reproduction and viability. The trend of inbreeding is an indicator for determining of inbreeding level in the herd. Inbreeding affects both phenotypic means of traits and genetic variances within population, thus it is an important factor for delimitations of genetic progress in a population. Reports showed an inbreeding increase led to decrease of phenotypic value in some of the productive and reproductive traits.
Materials and Methods In the current study, the pedigree data of 14030 and 6215 records of Baluchi and Iranblack lambs that collected from 1984 to 2011 at the Abbasabad Sheep Breeding Station in Mashhad, Iran, 3588 records of Makoei lambs that collected from 1994 to 2011 at the Makoei sheep breeding station and 6140, records of Zandi lambs that collected from 1991 to 2011 at the Khejir Sheep Breeding Station in Tehran, Iran were used to estimating the inbreeding coefficient and its effects on lamb survival in these breeds. Lamb survival trait was scored as 1 and 0 for lamb surviving and not surviving at weaning weight, respectively. Inbreeding coefficient was estimated by relationship matrix algorithm (A=TDT') methodology using the CFC software program. Effects of inbreeding coefficient on lamb survival were estimated by restricted maximum likelihood (REML) method under 12 different animal models using ASReml 3.0 computer programme. Coefficient of inbreeding for each lamb added to models as a covariate. The most appropriate model for this trait was determined by Akaikes Information Criterion (AIC) test.
Results and Discussion The number of survival records for Baluchi, Iranblack, Makoei and Zandi sheep breeds were 10793, 4826, 3588 and 6140, respectively. The inbred individuals were 17.63, 58.25, 4.88 and 36.32 per cent for Baluchi, Iranblack, Makoei and Zandi sheep, respectively, (2473, 3620, 175 and 2230 head respectively). The mean of inbreeding coefficient for whole and inbred populations for Baluchi lambs were 0.66 and 3.73 per cent, respectively, for Iranblack lambs were 4.59 and 7.90 per cent, respectively, for Makoei lambs were 0.25 and 4.86 per cent, respectively and for Zandi lambs were 1.22 and 3.61 per cent, respectively. Maximum of inbreeding coefficient for Baluchi, Iranblack, Makoei and Zandi lambs was 31.25, 34.70, 25.00 and 31.35 per cent, respectively. The mean of lamb survival in Whole and inbred population for Baluchi lambs were 89.11 and 88.30 per cent, respectively, for Iranblack lambs were 84.44 and 83.84 per cent, respectively, for Makoei lambs were 90.40 and 86.95 per cent, respectively and for Zandi lambs were 87.37 and 86.90 per cent, respectively. The average of inbreeding coefficient for 4 breeds was increased. The estimation of positive inbreeding coefficient trend for Baluchi, Iranblack, Makoei and Zandi were 0.035±0.012, 0.31±0.03, 0.010±0.012 and 0.020±0.012 per cent on each year, respectively. The most suitable model for survival in Baluchi, Iranblack, Makoei and Zandi breeds was 7, 12, 2 and 1, respectively. The regression coefficient of inbreeding on lamb survival were -0.26±0.11, -0.35±0.11, -0.25±1.83 and -0.04±0.20 per cent for Baluchi, Iranblack, Makoei and Zandi sheep, respectively.
Conclusion The levels of inbreeding below 5% in whole population, or annual rates of inbreeding under 1% unlikely result in substantial reduction of performance and economic income in sheep production and serious genetic variation in the population. Inbreeding depression was observed for survival trait although the levels of inbreeding coefficient were acceptable in all of the breeds investigated in this study. Therefore, the general policy in the flocks should be continued to avoid mating between close relative parents and use of enough sires and dams selected per annum. Estimated inbreeding coefficients for Baluchi and Iranblack breeds showed high degree of close mating in these herd and due to the significant effect of inbreeding on survival, it is suggested that this breeding stations should use a breeding plan to avoid mating of close relative animals.

The objective followed in this study was to compare six software packages (DFREML, WOMBAT, ASReml, MATVEC, DMU and Thrgibbsf90) as based on some such features as being user friendly, easing computational facilities as well as accuracy and precision of the estimated genetic vs. environmental parameters. For conduction of the study, simulated and field data (Birth weights and weaning weight of Baluchi lambs) were utilized. In all the softwares, except for Thrgibbsf 90, estimates were obtained with restricted Maximum likelihood method via AI algorithm, but in Thrgibbsf 90, the estimates were obtained using Bayesian Gibbs Sampling. The results showed that the choice of software depends on user interest and the goal followed in the research. Since the estimated parameters come out to be similar, even in confidence intervals, there seems no concern to exist in estimation of genetic and environmental parameters (for continous variables) using linear models,and through an application of different softwares.

This experiment was conducted to determine the effects of either twice or thrice a day feeding regimens on performance and as well on plasma hormone and metabolite levels of broiler breeder hens during 24 to 38 wk of their productive age. Breeder pullets were provided form a commercial flock, and distributed in experimental units, in a compeletly randomized design with three feeding regimens (treatments) included 1, 2 or 3 feeding times per day with 4 replicates. Birds fed once a day, received all their total feed at 06:15 h, whereas birds fed twice a day, received 50% of their total feed allowance at 06:15 h and the other 50% at 12:15 h, and while birds fed thrice a day, received 33% of their total feed at 06:15 h, 33% at 12:15 h and the last portion at 18:15 h. Total daily feed did not differ among treatments. Blood samples were taken at the peak of production (32 wk of age) and at the end of trial (38 wk of age). For the 13 wk production period, total hen-day egg production through 38 wk of age in the hens that were provided feed twice and thrice a day was greater (67.1 and 67.2 vs 62.2 eggs/hen, P<0.01) than in hens fed once a day. Also, broiler breeder hens fed 2 or 3 times per day laid heavier eggs (P<0.01) compared with once a day fed birds. Twice and thrice a day fed birds carried significantly lower plasma T3, glucose and cholesterol concentration and higher 17 -estradiol level than did once a day fed birds (P<0.05). In conclusion, the twice and thrice a day feeding regimens improve the reproductive performance of broiler breeder hens during the early egg-laying cycle.