dairy cattle

One of the principal and challenging animal studies in population genetics is to identify the signs of selection to improve economic traits and reduce diseases. Johne's disease is an incurable chronic bacterial infection that primarily affects the lower parts of the small intestine of ruminants, although its pathology and symptoms vary among species. The economic consequences of Johne's disease include reduced production, loss of genetic value, increased sensitivity to other diseases, increased interval between calving, weight loss, reduced carcass value, reduced fertility (due to reduced serum progesterone formation and corpus luteum), decreased quality and quantity of milk (decreasing fat and protein and increasing somatic cells in milk), and premature elimination. According to the results of new research, this bacterium may be a zoonotic pathogen that plays a role in causing Crohn's disease (a chronic inflammatory bowel disease (IBD)) in humans. Even after milk pasteurization, this pathogen remains alive and is therefore a threat to the health of society. This disease is one of the main diseases economically and one of the most prevalent diseases, causing great economic damage to the livestock industry worldwide. In this study, an extensive genome-wide scan was performed using single nucleotide polymorphisms (SNPs) to identify the signs of selection between populations of Holstein cows affected by Johne's disease and healthy animals.

In this study, 145 Holstein cows of the Feka cattle farm in Isfahan were genotyped based on Illumina 30K chips. Cows were grouped into two sick and healthy groups, with 45 and 100 cows, respectively. Quality control indicators included the animal read rate (mind), SNP read rate (geno), rare allele frequency (MAF), and Hardy-Weinberg equilibrium. To identify important metabolic pathways, ClueGo (version 2.5.6) was used in Cytoscape software, which provides biological interpretations of genes. In this study, two statistics, iHS and RSB, were used to identify the signs of selection.

Using iHS statistics, 63 and 70 genes were identified in the diseased and healthy populations of Holstein cows, respectively. The important genes identified by iHS statistics included HCN2, DOCK4, ITGA8, and STAG1 in the patient population, and CAV2, CNTNAP4, MIB1, and TTC23 in the healthy population. After examining the selected regions, 39 and 53 genes were identified in the diseased and healthy populations of Holstein cows with RSB statistics. The important genes identified by RSB statistics included GRID2, PPIP5K2, and CTNNA2 in the patient population, and  DOCK1, PCDH9, and AK1 in the healthy population.

In the present study, the results of the iHS statistics showed that 84 and 96 genomic regions were under selection in the healthy and patient populations, as well as 152 and 129 genomic regions in the healthy and patient populations using the RSB statistics. Most of the genes identified in this study were related to immunity, cancer, bacterial invasion of cells, cell aging, cell response, growth, and cell adhesion, which are among the important biological traits and characteristics of living organisms. By identifying possible candidate genes related to and resistance to Johne's disease in cattle, this information can be used in breeding programs (selection to reduce or increase the expression and frequency of important genes) for Holstein cows in Iran. However, due to the incomplete information related to the function of the genes in cattle species and the small population used in this study, more extensive studies with more samples and the analysis of several separate populations will provide a better understanding of candidate genes for Johne's disease in the cattle population.

AbstractBackground and Object: Milk is the first and most important source of natural human food, which is rich in nutrients needed for human consumption, and its consumption is not a problem at any age. Milk can be obtained from different sources, such as goat,sheep, cow, buffalo and camel; however, cow's milk is the most popular sweet among all milk. On the other hand, milk is only an agricultural product whose production is not dependent on a specific season of the year. Also, the dairy industry has a special place for women in terms of employment. The objective of this research is to investigate the status of dairy cattle breeding, production of milk and dairy products, marketing of milk and dairy products, and challenges in the production and sale of dairy products in Logar province of Afghanistan. This research was conducted in 2023 in districts of Pol Alam, Mohammad Agheh, and Barki Barak, and a total of 55 villages and 255 animal handlers were covered using the targeted population method. Primary data of this research has been collected and analyzed with the help of Excel and SAS softwares. Results showed that more than 40% of Holstein and Brown Swiss foreign cattle breeds were nurturing in the research area, and the average number of dairy cattle in farms was 2 heads. The range of daily milk production in dairy farms was between 20.00 - 12.80 kg per day, and after the Holstein breed (13.02 kg/day), cross breed cattle (Holstein * Kandahari) with a production of 11.00 kg/ day had the best productivity.In addition, animal handlers sold 56.26% of produced milk as fresh milk, and the average income of dairy farm owners from selling milk and dairy products in one lactation period was 1700 dollars($$). Also, results showed that the majority of buyers of milk and dairy products in the region under research were cooperatives and private companies. According to the results of this research, the most important challenge in terms of ranking in milk production is the lack of banking facilities (lending) and the least challenge is the lack of vaccines and animal medicines. The most important challenge in marketing milk and dairy products is the lack of modern tools and machines for transportation milk and dairy products and the least challenge in this part is the effect of seasonal fluctuations in milk production. The general conclusion of the research showed that in Logar province, Holstein breed produced more milk and cross breed performed better compared to indigenous breeds, and farmers sold a large amount of their produced milk in the form of fresh milk, as well as the most important buyers of produced milk. There were cooperatives and private companies in Logar province. In order to improve the current situation, it is suggested to ranchers and farm owners to form livestock associations.

disadvantages of using sexed semen among dairy producers in terms of outcome and economic efficiency. A questionnaire containing 28 five-choice Likert scale questions was prepared to test the attitudes of respondents concerning the use of sexed sperm in terms of functional, economic, cognitive and infrastructural aspects. The respondents were the researchers, consultants and dairy farm employees. The findings indicated that farm employees, unlike the researchers, believed that sexed sperm was effective in reducing dystocia, and the conception rate was not deleteriously affected in differentclimates (P<0.01). Better performance of sex-sorted semen in heifers compared to multiparous cows was significantly confirmed by farm employees and consultants compared to the researchers (P<0.01). According to the researchers, the use sex- sorted semen is uncommon and hence the use of this type of sperm has a higher risk (P<0.01). The results of this study indicated that the attitude of employees in large industrial dairy farms is largely consistent with the scientific facts published in the field of sex-sorted semen, and the disagreement of this

Abortion in dairy cow can be categorized into two types of abortion: Rebreeding (RA, abortion incidence between 60 and 260 d of gestation, without change in lactation number), and new lactation abortion (NLA, abortion incidence after 200 d in gestation which leads to a new lactation). According to this definition, the losses of abortion might be different based on the type of abortion at the herd level. For this purpose, a partial budgeting model was developed to estimate the losses of abortion in 6 Holstein dairy herds located in Isfahan and Chaharmahal-Bakhtiari provinces during 2020. Financial losses due to reduction in productive and reproductive performances, replacement costs and calf loss were considered in this modeling. On average, loss of pregnancy was estimated 27.7 million IRR per case. Although the probability of NLA incidence was much lower than RA abortion (2.3% vs 12.5%), but NLA imposes significant financial losses to farmers (on average 32.4 million IRR vs. 22.0 million IRR per case). In general, decline in fertility was the most crucial factor of losses (63.3%) due to abortion, and decrease in milk yield (22.8%) placed in the second rank. The results obtained in this study can be used by farmers who make the optimal decision to keep or cull the aborted cows in the dairy farms.

In order to optimally use the inputs, the efficiency of economic units is of great importance. The purpose of this study is to investigate the technical efficiency and economic value of some traits of production, reproduction, survival and growth of Holstein cows in Pars agro-industry. For this purpose, required information including: manpower, cattle population, feed consumption and milk production quantities were collected from Pars Livestock Unit by documentary study, observation and face-to-face interview and their efficiency was calculated based on production and economic performance. The variables used in the research include herd size in terms of head, feed and concentrate in terms of weight, manpower in terms of men per day, health in terms of number of days per day, milk production and production of manure in terms of kilograms and incomes in Rials, which include Income from milk sales, Rial value of livestock manure produced, income from sales of voluntary and forced elimination of livestock, income from sales of bulls and heifers in dairy farms were examined. Deap 2.1 software was used for performance calculations. Optimal decision was calculated numerically by a iterative method using compecon toolbox in MATLAB program. Probability of pregnancy in the first, second, third and higher lactation periods based on data analysis and using logistic regression and GenMod procedure of SAS software Obtained, the results showed that the average of technical efficiency with constant efficiency compared to the scale was 0.83; the average efficiency with variable efficiency compared to the scale was 0.86 The scale efficiency of this company was estimated to be 0.96. The amount of technical efficiency in general was 0.83, allocation efficiency was 0.87 and economic efficiency was 0.72. This unit was efficient in March in terms of types of efficiency, which means that during this month, in addition to consuming a certain amount of product produced with a minimum of inputs, the minimum costs are also considered in the composition of inputs, so the unit in this month was technically, allocative, economically and economically efficient and has a constant return on scale. Also, the highest economic value in non-optimal conditions in survival, reproductive, productive and growth traits, and also for survival rate after weaning, first calving age, milk fat and body weight of adult animals was equal to 234297.30, -41835.16, 128664.12 and 454227.93 Rials, respectively. In optimal conditions, the highest economic value for survival, reproduction, production and growth traits was related to the set of traits of production lifespan, and the calving interval, milk fatproduction and daily weight gain before weaning were estimated at 4594.88,9084.67, 1582264.09 and -1464.87 Rials, respectively. The reason for the difference in economic values of traits in optimal conditions compared to non-optimal conditions is due to the application of optimal livestock replacement strategy, so that the farmer's policy in eliminating and replacing, affect herd profit.

Meta-analysis is a statistical approach for combining the results from independent studies with the same assumptions, that is able to increase the statistical analysis power and the repeatability of the results in the livestock researches, comparing to single-study analysis. The polymorphism in the major genes of Diacylglycerol O-Acyltransferase 1 (DGAT1) and Leptin have drawn much attention from animal scientists during recent years, for their possible roles in the economically important traits. However, the relationships between these genes and milk production traits have been incompatible in dairy cows, it means sometimes significant and some other times no significant association has been reported. The purpose of this study was to investigate the overall effect of DGAT1 and Leptin genes on some economically important traits including milk yield, fat and protein content and percentages in dairy cows by using meta-analysis.

in this study, all researches published in the validated journals and thesis up to 2018 were used. Following to quality control, 9 and 4 studies reported for K232A and Sau3AI polymorphisms of DGAT1 and Leptin genes were used, respectively. The analysis was carried out using the Stata v. 15. Non conformance index (I 2) was significant for all parameters, so that a random risk model was used. Data were analyzed for each variable using these models for measuring the effect size, 95% confidence interval and statistical significance level of the measurements. All variables were continuously in this study. The measurement of the effect size for continuous data was carried out using the standardized mean difference (SMD) that calculated for the polymorphisms of K232A and Sau3AI loci in DGAT1 and Leptin genes on the milk yield, fat and protein content and percentage.

the results of this study showed that the polymorphism in the K223A locus of DGAT1 gene, has a significant effect on lipid content and percentage, and can play an important role in increasing of their amounts, but its relationship with milk yield and protein content and percentage is not significant. Also, the results for Sau3AI polymorphism in the Leptin revealed that this locus had no significant effect on the traits investigated in this study.

Overall, the results of this study with identifying the overall effects of the studied genotypes of DGAT1 and Leptin genes on milk production traits in dairy cows can play an important role for planning next researches in this field.

Supplying the needs of dairy cows in the early lactation period that have low dry matter intake and high protein requirements is important. Methyl groups are not synthesized in the body of living organisms, but are supplied through feed sources such as betaine, choline, pyridoxine and methionine. Of the three sources (choline, betaine, and methionine) that have the methyl group in their structure, only betaine can be directly involved as a methyl group donor in the transmission cycle of this group in the liver, and many key bodily functions such as Growth, liver safety (effective role in fat metabolism and liver protection) and lactation are affected, so in the present study, the nutritional effects of protected betaine at one level and unprotected at two levels on bovine plasma parameters Holstein Dairy Cows was examined.

To Investigate the nutritional effects of protected and unprotected betaine on plasma parameters of dairy cows, 40 Holstein dairy cows (Average production 38 ± 2.1 kg and lactation days 5 to 35 days) with history of at least two deliveries were randomly used in 5 eight -head treatments. The experiment lasted one month (the first 14 days of the adaptation period and the next 16 days of the main experiment period). Experimental diets included: 1- control diet 2- diet containing 50 g of unprotected Betaine supplement 3- Diet containing 50 g of externally produced protected Betaine supplement 4- Diet containing 100 g of unprotected Betaine supplement; 5- Diet containing 50 g of protected Betaine produced. The cows received a perfectly mixed base diet containing the above Betaine additives. In two promises (10 am and 10 pm). The amount of dry matter consumed for each treatment was measured daily and Blood samples were also taken at the beginning and end of the experiment. Analysis of feed consumption data and plasma parameters were performed by SAS software and Mixed procedure.

In this experiment, no significant difference (P>0.05) in the amount of glucose, cholesterol, triglyceride, calcium, phosphorus and magnesium was observed between the experimental groups. The amount of non-esterified fatty acids (0.576 mm/l) and beta-hydroxy butyrate (0.428 mm/l) in the group receiving protected betaine production was lower than the other groups and their difference was significant at the level of P=0.0001 In addition, the amount of liver enzymes such as aspartate aminotransferase (5.11 IU/L), aspartate aminotransferase (56.1 IU/L) and alkaline phosphatase (0.396 IU/L) in the five treatment decreased compared to other groups and at the level (P <0.05) Became meaningful.

The results of the present experiment showed that there was a significant decrease (p < 0.05) in the amount of non-esterified fatty acids, beta-hydroxy butyrate and the amount of plasma liver enzymes due to the consumption of protected betaine produced compared to the control group in dairy cows. therefore, the use of 50 g of protected betaine produced in the early stages of lactation is recommended.

One of the most important and complex management decisions in dairy farms that greatly affects the economy and profitability of the dairy herd is the issue of culling. Regarding the importance of the subject, this study aimed to investigate the culling status and causes of Holstein dairy cattle in Qazvin province. For this research, the culling data of 35 industrial dairy herds under the cover of Qazvin Farmerschr('39') Union were collected and analyzed during one year. Herds were categorized into five categories(treatments) of dairy cows including herds by capacity less than 100 (low), 100-200 (relatively low), 200-500 (average), 1000-500 (relatively high) and more than 1000 heads (high)., The culling data were analyzed in a completely randomized design in two main categories of forced and optional removal. The results showed that there was a significant difference in mean parity of the cows between the different treatments and mean parity decreased with increasing capacity of the studied cows. The mean parity of culling cows in the studied herds in Qazvin province was 3.92. There was no significant difference between different treatments in the percentage of fresh cows, primiparous cows as well as the percentage of productive cows (lactating and dry). Clinical mastitis accounted for 5.08% of total culling in dairy herds and there was no significant difference between treatments for this disease. BLV disease accounted for 1.25% of the total culling in the dairy herds studied and the difference between relatively high and high treatments were significant (P≤0.05). There were no significant differences between treatments for acidosis, abomasal displacement, ketosis / fatty liver, milk fever and bloat. The results of this study showed that in high capacity dairy herds (more than 500 heads), cows are culled earlier from the herd. The voluntary removal ratio in industrial dairy herds in Qazvin province was 27.67%. The most important factor for removal in these dairy farms was infertility and reproductive malformations with the ratio of 31.85%.

In order to evaluate the effect of genotype by environment interaction on production traits of Holstein cattle of Iran, first lactation test day records of 344170, 135000 and 156840 of milk, fat and protein yield on 34417, 13500 and 15684 cows and SNP markers of 1935 genotyped bulls were used. The production data were retrieved from the Animal Breeding Center and Productions Improvement of Iran’s database which were collected from 2013 to 2018. To consider the interaction of genotype and environment, mean of temperature-humidity index (THI) in three days before each test day records as continuous environmental effect were retrieved from the 35 closest meteorological stations in the vicinity of 139 Holstein herds from 13 provinces. Variance and covariance components were estimated through a single-trait random regression model with orthogonal Legendre polynomials of second order for days in milk and THI using AIREMLF90 software. The results showed that changes in THI across lactation led tofluctuations in additive genetic variance over time. The change in heritability of milk production traits over lactation followed the same trend as additive genetic variance. The results from cross-validation analysis showed that including genomic information into the predictive model, increased prediction accuracy and including THI information increased unbiasedness. Due to the changes in milk production of daughters of bulls across days and THI , genotype by environment interaction should be considered when selecting bulls under different conditions.

The availability of thousands of polymorphic single nucleotides (SNPs) spread across the genomes made it possible to use genome-wide marker information to predict total breeding value in the implementation of genomic selection. The interaction between several gene loci contributes to the phenotypic changes associated with the expression of complex polygenic traits. The present study aimed to compare the performance of different models with additive and non-additive genetic effects, especially epistasis effects in predicting variance components and genomic breeding values as well as QTN in a dairy cow population based on Bayes Lasso model.

A population of dairy cattle was simulated based on a choice of four pathways to maximize the rate of genetic progress over ten generations with an effective size of 100 individuals in the base population. The genomic structure was assumed consisting of 3 chromosomes with a length of 100 cM and On each chromosome were located 1000 markers 2 allelic markers with a frequency of 0.5. 50 QTL double alleles with equal frequency were randomly assigned to each chromosome. For QTL allelic effects, a gamma distribution with a parameter slope of 0.4 was used in QMSim software and sampling was performed. Phenotypic and genotypic data of the last 10 generations were used for analysis. Marker effects, variance components and genetic parameters were estimated using the Bayes Lasso method in the form of 6 statistical models, that model 1 includes only the marker additive effects, model 2 includes the polygenic effects of animal, model 3 includes the combined effects of additive marker effects and polygenic effects of animal, model 4 includes the dominance effect of markers and polygenic effects of animal, model 5 includes the dominance and additive effects of markers in addition to the polygenic effects of animal, and finally, model 6 includes the additive, dominance and epistatic effects of markers in addition to the polygenic effects of animal. To control the type I error in estimating marker effects, Bonferroni test was used at 1% probability level.

The results of this study showed that the additive model or the polygenic model alone could not show the missing or hidden variance, in such a way that adding non-additive genetic effects including dominance and epistatic effects reduced the residual variance effects. Also in the complete model including additive and non-additive effects, the total genetic variance increased. With the addition of non-additive effects in the statistical model the Hertability in the broad sense was increased and the Hertabilitity in the narrow sense of trait decreased. The accuracy of breeding value estimation in model 1 was the lowest and in models 3 to 6 was the same. Model 5 with the lowest false positive QTN and the highest true positive proportion was the appropriate model for genetic evaluation of the studied traits. By including polygenic and non-additive effects in the model, the number of false positive errors was reduced.

The results of this study showed that the components of additive and dominance variance markers had a small share in the genetic diversity of the studied trait, but the polygenic effects of animal and epistatic had the largest share in the exploring of genetic diversity of trait. The results also showed that the major contribution of gene loci in the exploring of traits is related to additive genes with an additive effect that have a normal distribution. Ignoring non-incremental effects causes inflammation in the additive variance of the trait.

The aim of this experiment was to evaluate the effects of concentrate premixes containing of by-pass proteins (BP) in balanced low protein diets for essential amino acids on performance, blood metabolites and nitrogen efficiency of lactation Holstein dairy cows. Twenty-four multiparous Holstein cows (in 3rd parity and DIM 80±10) randomly were divided to three experimental rations including, 1) control ration with 17.5% CP based on NRC 2001 recommendations, 2) Low protein ration containing concentrate premix with 16.5% CP and 3) Low protein ration containing concentrate premix with 15.5% CP. The ratio of the rumen undegradable protein (RUP) to rumen degradable protein (RDP) in experimental diets was 37:63 and the ratio lysine to methionine was adjusted by concentrate premix up to 3:1 and 2.8:1 in the diet 16.5% and 15.5% CP, respectively. The results showed that the dry matter intake (DMI) increased linearly with a reduction of CP in the diets (P=0.048). The highest 3.5% fat corrected milk yield (FCM) and energy corrected milk (ECM) was recorded for 16.5% CP diet that showed a significant difference than other groups (P=0.038). Milk protein yield and milk nitrogen efficiency (MNE) showed significantl difference between control and 16% CP diets (P=0.05 and P=0.03, respectively). This study showed that decreased in CP levels compared to recommended NRC values (2001), and providing an optimal ratio of limiting amino acids can increase nitrogen yield while maintaining production.

The present study was aimed to assess the role of genotype× environment interaction (G×E) and generation interval on the genetic gain caused by importing the genetic materials of dairy cattle in a country without advanced breeding program. Changing allele substitution effects of quantitative trait loci (QTLs) underlying the trait was used to simulate G×E. To this end, three levels of 100 (control), 75 and 50% overlapping of QTL effects in imported sires at the heritability levels of 0.1, 0.3, and 0.5, as well as three scenarios of continuous replacing and discontinuous replacing with one and two generations of foreign genetic materials were considered. Moreover, the effect of decreasing the accuracy of genomic prediction in traits with the low level of heritability was investigated. Based on the performance of daughters of sires in the local population of control scenario, import-based strategies were better than on the strategies of local population. The genetic correlation created in 75% and 50% overlapping of QTL effects were as 0.7 and 0.5, respectively. Although the trend of genetic response increased by decreasing genetic correlation over the time, it was not equal to origin population. Maximum genetic gain (2.56) was observed with a heritability of 0.5 in continuous replacing and absence of G×E. A decrease in the accuracy of prediction resulted in exacerbation of G×E. In general, more genetic improvement is transmitted from origin population to local population only by importing the genetic materials related to populations with higher genetic mean and also by considering G×E in different traits.

Increased homozygosity resulted from mating of relatives is considered as one of the challenges faced in dairy farming industry which has attracted the attentions. This research has been conducted to measure homozygosity based on SNP and ROH in high- and low-producing Holstein cows. In current research, both random regression and pedigree index approaches were used to obtain candidate animals for genotyping process. The samples were obtained from 150 Holstein dairy cows (75 by high- and 75 by low-EBV for milk production). We proposed a suitable method, by integrating breeding value estimation calculated by random regression and pedigree index, to select the candidate animals for genotyping. The results showed that putting too much emphasis on production traits in high-producing dairy cows had negative impact on the traits associated with fertility (DPR = -0.55) and productive life (PL = 0.1). The calculated homozygosity based on ROH showed different amount of variation in different chromosomes in the cows with high and low production which may be related to uneven distribution of genes influencing production traits in different chromosomes.

Efficiency is one of the most important factors in productivity growth, especially in agriculture. The purpose of this study was to measure the technical, allocative  and economic efficiency and to identify the factors affecting them in dairy cattle stations of Moghan agro-industry company. The data of this research were gathered in 2017 by documentary study, observation and interview. In this research, Deap 2.1 and Eviews 10 software were used for analyzing performance calculations and determining effective factors, respectively. In order to design a data envelopment analysis model, the main variables used in the research included the herd size per head, feed and concentrate in kilograms, manpower in terms of man-days, hygiene per day, milk production and manure production in kilograms and total revenues were determined. Efficiency calculations were carried out with the assumption of the daily operation of milk production stations in the form of firm performance and the results were obtained daily, monthly and annual. Tobit regression analysis and parents' statistics were used to determine the effective factors on the amount of efficacy. The results showed that the technical efficiency with constant returns was 0.844 and with the return on the variable of 0.962. The company's scale efficiency was 0.918, in which 16 days performance of the company was recorded with a slower return to scale and 349 days with incremental returns to scale. The technical efficiency value in the general condition was 0.901, the allocation efficiency was 0.845 and the economic efficiency was 0.761. In general, milk production efficiency was the highest in January and the lowest in April. Factors affecting the amount of technical efficiencies of feed and concentrate and health variables. The effect of feed and concentrate in livestock diets and the level of health has been negatively affected by technical efficiency. Effect of feed and concentrate variables on negative economic efficiency and positive health variable. In terms of the effectiveness of different efficiencies on the income of milk production, technical efficiency and allocation had a negative effect and economic efficiency had a positive effect.

The purpose of this study was to determine the removal rate under the optimal alternative milking strategy for different production and health conditions in dairy cattle of Ardabil province. One of the most important management decisions that affect livestock production is the timely replacement of dairy cattle with young heifers. Using the system analysis method, the economic system of the dairy cattle was split into income and cost components and each of these components was subdivided into other parts. Then, using the existing models and using the Compecon Combinator tool kit, Matlab programming language was used to simulate a bioeconomic model. The objective function was to maximize the net present value of the livestock in a planning horizon with 10 lactation periods. Dairy cattle were defined by state variables including lactation period, milk production capacity, and different mastopathic outbreaks..In each stage, dairy cattle were classified by state variables including production capacity in 3 levels (low production, moderate and high production), and health status in 3 levels (non-disease, treatable disease, and disease that eliminated livestock). he results of the model analysis showed that the maintenance of dairy cows up to the sixth stomach and the average cows production until the fourth stomach is economically justified and the maintenance of low production cows is not recommended.

The aim of this study was to assess the impact of heat stress on production of dairy cows of National Research and Development Station for Dual-Purpose Cattle (Gavdasht, located in Babol city). In this order from 3876 test-day records which have been collected from 159 heads of Holstein cattle during the years 2015 to 2018 were used. Using meteorological data of the nearest synoptic station, two climate index with different weightings of dry bulb temperature and humidity were calculated and compared. Because longer periods of heat stress might have a more severe effect than shorter periods, 1-, 2-, and 3-d periods were also considered, by averaging the weather data measurements. Generally, regression analysis with a generalized linear mixed model was used to study the change in test day milk yield in response to climate conditions. Goodness of fit of models were determined using coefficient of determination (R2) and mean square error (MSE). Based on these results, the index with the temperature and relative humidity (THI) was determined as the best indicator for studying the climatic conditions of this study area. It was also observed that the average weather data 2 d before the test date (TD) explained more of the variability of milk yield than weather data 1 or 3 d before TD or on the TD itself. The starting point of heat stress for the Holstein cattle of Gavdasht Research Station was around 74 and their yield decreased by -0.12 kg per unit increase of THI ≥ 74.

Information theory is a branch of mathematics. Information theory is used in genetic and bioinformatics analyses and can be used for many analyses related to the biological structures and sequences. Bio-computational grouping of genes facilitates genetic analysis, sequencing and structural-based analyses. In this study, after retrieving gene and exon DNA sequences affecting milk yield in dairy cattle, the entropy in orders one to four for each gene and eta exons was calculated. In order to extract gene distances, mutual information method was calculated. The results of mutual information of DNA and exon sequences were entered as input into 7 general clustering algorithms. In order to aggregate the results of clustering, AdaBoost algorithm was used. Finally, the results of AdaBoost algorithm were investigated by GeneMANIA prediction server to explore the results from gene annotation point of view. Integrated result of each clustering algorithm due to AdaBoost algorithm, which implied as gene tree, indicated that proposed method biologically grouped set of genes as it was proved by their gene annotation using GeneMANI. We believe that the proposed method might be used with other DNA based clustering competitive methods and therefore, it can be used to group set of genes in other species.

In this research, the artificial neural networks (ANNs) and multi-layered non-fuzzy inductive inference system (ANFIS) were used to model the output energy in dairy and beef cattle farms. For this purpose, according to Cochran's relation, 105 beef and dairy farms were randomly selected from five townships which were the main producers of this sector in Mazandaran province from 2016-2017. Using the energy balance of inputs and outputs, the input and output energy averages in beef production farms were calculated to be 16994.76 and 3449.85 MJcow-1 and for dairy production farms were equal to 100100 and 58277 MJcow-1, respectively. Also, ER (Energy Ratio), EP (Energy Productivity), SE (Special Energy) and NE (Net Energy) indices for dairy production farms were 0.58, 0.08 KgMJ-1, 12.5 MJKg-1 and -41825.93 MJcow-1, respectively and for beef production farms were calculated as 0.2, 0.02 KgMJ-1, 50 MJKg-1and 13544.91 MJcow-1, respectively. Using the results of statistical analysis of the data, modeling of the output energy for each unit of input energy was performed by two above methods (ANNs and ANFIS). The results showed that the model of nervous- fuzzy inference comparative multi-layered system with the correlation coefficient of 0.9899 for steer farms and 0.9933 for dairy farms, had better performance and accuracy than that of the artificial neural network with the correlation coefficient of 0.8118 and the structure of 6-16-1 for beef farms and correlation coefficient of 0.9837 and the structure of 5-12-1 for dairy farms.

During the last few decades, there has been an increase in the development of mathematical models, as both research tools and management tools that can integrate our current knowledge of reproductive events and then would be helpful in predicting the reproductive efficiency of farm animals. This paper presents a conceptualized mathematical modeling of hormonal and metabolites interactions over non-estrous and negative energy balance phase in dairy cow. Anestrus occurs annually and after each calving. The anestrus period in high milk-producing cows due to the negative balance of energy produced by high milk production in the first few days after parturition is a constant challenge in the modern world of dairy cow worldwide. For this reason, many scientific efforts have been made to explore the biological aspects of this phase. Due to the complexity of the existing relationships between effective parameters, descriptive-analytical biological analyses have not succeeded in elucidating this biological system. In this research, it was attempted to look at the elaborating factors playing in this phase, at same time, it was tired to pinpoint and explore this phase from biological system perspective.
Material and In the present study, first diverse information on the various aspects of the factors affecting on the postpartum negative balance of energy and reproduction performance of dairy cows were initially collected. Then, this information was converted to their sound mathematical equations. Efforts have been made to simplify the long and unprocessed equations from well-known factors including liver glucose, blood glucose, pancreatic insulin and blood insulin, IGF-1 liver and blood, and hypothalamic GnRH affecting on this biological phase to be simplified using ordinary differential equations. In other part of this study, By using the data published in the scientific articles and expanding them by using Curve Expert software, the computer simulation process was performed by MATLAB software (Version 9.1) and the predictive models were developed for some system parameters. The results showed that the system of ordinary differential equations was able to predict good blood glucose (AARD = 0.388) and insulin (AARD% = 0.638), but they were not able to provide accurate predictions for pancreatic insulin and blood IGF-1.
The present model was a starting point to reach a comprehensive model which should be completed gradually. In this model, it was tried to use empirical data from reliable sources in simulation model, a matter that was more or less successful in this research.

In the present study two genetically connected small and large populations were simulated and the effect of different sources of information from foreign populations on the accuracy of predicted genomic breeding values of young animals of the small population was investigated. A large population consist of 200000 animals over 15 generations and a small population consist of 5000 animals over 3 generations were generated with QMSim simulation software in a such way that the small population was connected to the large one. Three scenarios were defined for estimating the accuracy of genomic evaluations based on various sources of available information. In the first scenario, the accuracy of genomic breeding values was estimated based on the genomic breeding values of individuals in the small population. In the second scenario, the accuracy of genomic breeding values of animals was estimated using the information of individuals in the small population accompanied with the genomic breeding values of male individuals from the large population. In the third scenario, phenotypic, genotypic and pedigree data of individuals from the large population were integrated to estimate the genomic breeding values of individuals in the small population. The averages for accuracy of estimated genomic breeding values were 0.34, 0.40 and 0.50 under the first, second and third defined scenarios, respectively. Furthermore, the averages for regression coefficient of prediction for genomic breeding values were 0.73, 0.83 and 0.93 under the first, second and third defined scenarios, respectively. The obtained results revealed that the integration of phenotypic, genotypic and pedigree information of both large and small populations had the most advantage for estimating the genomic breeding values of selected candidates in the small populations.