جستجوی مقالات مرتبط با کلیدواژه « dairy cow » در نشریات گروه « علوم دام »

The genome-wide association study (GWAS) is a powerful approach to identify genomic regions associated with fertility traits that explain a significant portion of the genetic variance associated with these traits and identify the relevant causal mutations. Evaluating the correlation between each genotyped marker and trait is an essential strategy for GWAS studies that examine the effects of all markers by considering their possible interactions, environmental factors, and even mutual effects between markers. Recently, machine learning methods have been introduced to genomic topics, and the basis of these methods is different from the common methods of genomic evaluation. The machine learning method is used to estimate the genomic breeding values of the candidate animals by considering the training data (genotypic and phenotypic information of the reference population). One of the key advantages of this method is the ability to analyze large data. Machine learning is a branch of artificial intelligence whose goal is to achieve machines that can extract knowledge (learning) from the environment. A variety of machine learning methods (random forest, boosting, and deep learning) are used to model genetic variance and environmental factors, study gene networks, GWAS, study epistasis effects, and genomic evaluation. Random forest is one of the machine learning methods that has been successfully used in various fields of science. This research was conducted to identify markers and genes related to reproductive traits such as calving interval (CI), days open (DO), daughter pregnancy rate (DPR), and age at first calving (AFC) in Iranian Holstein dairy cattle. These traits have already been investigated with the ssGBLUP method and using a smaller sample size. However, in the present research, by using more genotyped animals, a random forest algorithm was used to identify markers and genes related to reproductive traits.
The records used in this research were provided by the National Animal Breeding Center and Promotion of Animal Products of Iran and included AFC, DO, CI, and DPR related to the genotyped bulls' daughters. In this research, the pedigree information of 2774183 animals was used. The genotypic information of the markers related to 2419 Holstein bulls was used. Genomic data quality control was performed using factors such as the number of genotyped SNPs per animal (ACR), the number of genotyped animals per SNP (CR), Hardy-Weinberg equilibrium (HWE), and minor allele Frequency (MAF). When filtering genomic data, the markers whose MAF was less than 5% were removed, and then the samples whose genotyped frequency was less than 90% were identified and removed. Then, the markers whose genotyping rate was less than 95% in the samples were identified and removed. Finally, the SNPs that deviated from the HWE test (P<10-6) were excluded from the analysis as a measure of genotyping error. To control the quality of genomic data, PLINK 1.9 software was used. Then Ranfog software was used in the Linux environment to perform analysis through random forest algorithm.
By using the random forest algorithm, a total of 21 important SNPs were observed, then important fertility trait candidate genes were identified by the gene ontology method, and 62 genes were within 250 Kb of these SNPs. The most significant SNP was observed for AFC. The main SNP for AFC is in ARS-BFGL-NGS-22647 BTA3, for CI is in ARS-BFGL-NGS-114194 (BTA11), for DO is in BTA-74076 -no-rs (BTA5), and for DPR is in ARS-BFGL-NGS-32553 (BTA26). The researchers, who studied fertility traits in Nellore cattle using machine learning methods, identified MPZL1 and CD247 genes on chromosome number 3 and this gene was associated with age at first calving. Many pathways of cell biology affect the performance of reproductive traits. Research has reported the relationship between the CD247 gene and pathways of biology, including cell development and function. Research has shown that the IFFO2 gene plays an important role in the molecular structure of cells, as well as in the mechanism of blastocyst formation, embryos, and the length of gestation in cattle. In a study conducted on the mouse population on the structure of the flagellum and the sperm maturation process, the role of the ALDH4A1 gene in the sperm maturation process was reported. The association of the RPS6KC1 gene with pregnancy rate and antral follicle number in Nellore heifers has been reported. The KAT2B gene is a transcriptional activator that plays an essential role in regulating the correction of histone acetylation and plays an important role in improving carcass quality, muscle and fat development, and metabolism in native Chinese cattle. In addition, they play a key role in regulating biological processes and are related to cell growth, metabolism and immune system function.
  According to the objectives of this research, new information on markers and candidate genes related to reproductive traits in Iranian Holstein dairy cattle was reported. The markers and candidate genes identified in the present research can be used in genomic selection to improve the reproductive traits of Holstein dairy cattle.

one of the most important and practical tools in increasing the production and profit of dairy cattle herds is to determine the exact aims of breeding, suitable genetic selection and breeding of premium cows. Based on animal breeding, breeders should make sure that the difference in the genetic merit of one or several traits leads to the difference in the phenotypic performance of the animal. Therefore, they want to reliably identify and select superior sires within and between breeds. Considering the importance of bulls in dairy herds and the use of their semen on a very wide level, this study aims to compare the information of genetic-economic indicators and productive, reproductive and health traits in the semen catalog of bulls with the actual performance of their daughters in Isfahan herds.

In this research, the information of 16 Holstein dairy herds located in Isfahan province during the years 2002 to 2017, was used. The number of productive livestock in the target herds was between 1000 and 5000 heads. Finally, 18,559 cows from the first to the fifth period of lactation, obtained from artificial insemination, which had known sires, were used. The genetic evaluation information of each sire that was used includes predicted transmitting ability (PTA), genetic-economic indicators: lifetime net merit (LNM$) and lifetime fluid merit (LFM$), production traits: milk, fat, protein, reproductive traits: sire conception rate (SCR), daughter pregnancy rate (DPR), daughter calving ease (DCE), daughter stillbirth (DSB) and health traits: production life (PL), somatic cell score (SCS), resistance to mastitis disease (Mas), metritis (Met) and retained placenta (RP) was based on the official evaluation of August 2019 by the USA council on dairy cattle breeding. Mixed and generalized linear models were used to assess the relationship between sire's PTA and daughters’ record. Sire's PTA were milk, fat, protein, daughter pregnancy rate, production life, somatic cell score, daughter calving ease, daughter stillbirth and lifetime net merit and lifetime fluid merit indices. Daughter records were milk-305, fat-305 and protein-305, open days, calving interval, age of first calving, number of productive days, calf birth weight, somatic cell score, number of inseminations per pregnancy, history of dystocia, stillbirth, metritis, retained placenta and mastitis traits. In this study, the analysis of data was done using R software and lme4 and lmerTest software packages.

Based on the results, PTA milk and SCR of most of the bulls used in herds were average, while they were lower values for LNM$ and LFM$ indices and PTA, Fat, Pro and PL traits and higher values for SCS and DSB traits. Correlation between indices and PTA of different traits of sires showed that the highest correlation was between LNM$ and LFM$ indices and the lowest was between SCR and DSB, Milk and SCR and RP and SCR traits. The correlation between sires' PTA and their daughters' performance in productive, reproductive and health traits showed that the correlation level was in the range between -0.19 and 0.16. Also, the regression coefficients of productive, reproductive and health traits of daughters were estimated based on the PTA of their sires in the studied herds, which ranged from -32.273 (between the PTA of daughter calving ease and milk-305) and 3.679 (between PTA fat and milk-305). The estimation of the odds ratio of some traits from sires' PTA on the daughters' health and reproductive (classifiable) traits showed that values were close to one for mastitis resistance, daughters' pregnancy rate and production life traits from sires' PTA which indicates the low effects of sires' PTA on their daughters' performance. However, the estimation of the odds ratio of PTA sires, related to metritis disease resistance, somatic cell score, resistance to retained placental and daughters calving ease traits had inverse relationship with the metritis and retained placental diseases (0.85, 0.67 and 0.74) and direct relationship with dystocia (1.23), respectively. The transmitting ability of sires is predicted based on the performance of their daughters in dairy cattle breeding farms, the data of those farms were available to the semen production company, the difference between conditions such as climate and breeding management of the mentioned herds and the herds of this study, can be affected the interaction of genotype and environment.

In this study, the correlation coefficients between random variables of sires' PTA for productive traits (milk, fat and protein) with their daughters' performance were calculated to be higher compared to reproductive and health traits. Also, the rate of OR of resistance to metritis and RP diseases, SCS and DCE, showed the effects of sires' PTA on the performance of their daughters. Therefore, according to the results, it is possible to take more advantage from sires predicted transmitting ability for milk, fat, protein, DPR and SCS in proper selection of semen and improving the phenotypic performance of daughters. While available information in genetic evaluations of other traits were less reliable, probably due to low heritability or high genetic by environment interactions.

Heat stress in most parts of the world has a negative effect on the performance of dairy cows and reduces milk production in dairy cows. Supplementation of cows with micronutrients (minerals and vitamins), especially in the close up period, can have benefits in reducing the negative effects of heat stress and improve the yield of cows during the next lactation period. This study was conducted to investigate the effect of some nutrients on the physiological and performance processes of dairy cows in heat stress.

In this research, 24 multiparous dairy cows were used in the transition period. The cows were randomly divided into 2 groups of 12 and each group was assigned to a test treatment. Treatments include control group: only from the common diet and without nutritious additives and the second group, which in addition to the common diet, received a micronutrients for 21 days before parturition. After parturition, each of the control and treatment groups were again subdivided into two groups of 6, so that in each group, they were either fed with diets without micronutrients or enriched with micronutrients until 21 days after parturition.The supplement containing a micronutrient of the close up period, including micronutrients of selenium, copper, zinc, chromium, beta carotene, vitamin E, magnesium, ascorbic acid and niacin and the micronutrient supplementation of the freshly period in addition to the micronutrient above, contained sodium and potassium. The average temperature- humidity index was during the text period of 74 and cows were heat stress. The conditions of maintenance and management of nutrition and environment were the same for all the animals during the whole experiment period. Weight variations, feed intake and rectal temperature were determined each week 4 hours after feed intake in two consecutive days. The weight of the newborn calves, the weight of the placenta and the amount of colostrum produced during the first three milking was recorded.

The amount of dry matter intake during close up was higher in the micronutrient intake group than the control group, and in the last week of pregnancy there was a significant difference between them (P<0/05). Although weight gain during the close up was not affected by treatment, more weight gain was observed in the group receiving micronutrients. The numbers of pregnant days in cows receiving micronutrients were longer than the control group. The birth weight of calves in cows receiving micronutrients was higher than the control group. colostrum was also more produced in this group. Calves weaning weight was not affected by treatments. Feed intake during the lactating period was affected in the first week of lactation and receiving micronutrients transition period treatment in the third week had the highest feed intake, which in parallel with this week the milk production of this group was higher than other groups and its difference with other treatments was significant(P<0/05). Milk composition were not affected by treatments (P>0/05).

This experiment showed that heat stress can have a negative effect on the performance of dairy cows during the transition period and the use of micronutrients in this period can have beneficial effects on the repair of heat stress in dairy cows.

The aim of this study was to investigate the incidence, cull, abortion, stillbirth and weight loss due to Foot and Mouth Disease (FMD) outbreak and their interaction in different parity (primiparous and multiparous) in Iranian dairy cows. A total of 49,400 records of 20,330 cows were used in the period of 2009 to 2019, which were prepared from nine industrial dairy farms in Isfahan, Golestan, Fars, South Khorasan, Khorasan Razavi and Chaharmahal and Bakhtiari provinces. The incidence and mortality of FMD with FREQ procedure were estimated to be 43% and 11%, respectively and within herd incidence ranged from 18% to 59% and cull from 1 to 18%. The LOGISTIC procedure in SAS software was used to estimate the effects of FMD on the incidence of abortion, stillbirth, and weight loss and their interactions. The chance of occurrence the disease increased during the cold seasons in primiparous cows that had abortions and were in skinny BCS. Significant changes in the condition of affected cows compared to healthy cows showed an average of 23% decrease in BCS, 5% increase in abortion and 4% increase in stillbirth. Significantly, the chances of abortion, stillbirth and weight loss in multiparous cows in the normal and fatty BCS group were lower than in the primiparous cows with the same BCS group. In contrast, the chances of losing weight in multiparous cows which were in skinny BCS group, were higher than primiparous cows. The results of this study can be useful in analyzing management strategies to control and prevent FMD.

Mastitis is one of the most frequent and costly diseases of the dairy cattle industry and causes many economic losses, which negatively affects milk yield and composition, fertility, longevity and welfare of cows. The best solution for reducing the economic and biological consequences is early and accurate prediction of mastitis based on indicator factors. So far, various statistical methods have been used to predict mastitis such as linear and multiple regression, and threshold models. Machine learning is another method that has recently widely been used to predict farm profitability, reproductive traits, longevity and abortion in dairy cow. Machine learning is defined as a set of methods for automatically finding patterns in data and then using those patterns to predict possible future data.

In this research, the performance of four machine learning algorithms including random forest, decision tree, Naïve Bayes and logistic regression and two sampling methods, over-sampling and under-sampling, were compared to predict risk of clinical mastitis based on data collected in two Holstein dairy herds in Isfahan province. Final dataset included 393504 records on cows calved during 2007 to 2017 of which 13653 cases (3.47%) were infected and 379851 cases (96.53%) were healthy. Factors related to mastitis, including parity, daily milk production, calving

Although nutrient imbalance does not play a role in the etiology of hypocalcemia and the existence of defects in physiological adaptations is the main cause of occurrences, the most common processes used to prevent the occurrences of hypocalcemia are nutritional and involve the use of some factors. Management in animal diets is close to calving. The aim if this study was to consider the effects of Anionic diets withdraw on metabolic response and productive and reproductive performance of Holstein cows during transition period.

Holstein cows (n = 200) with averaged parity 3.0±1.0 and BCS 3.5±0.5 randomly selected according to previous milk yield and assigned into one of two treatments: 1) control deit (DCAD= +100 mEq/kg dietary DM) and 2) Anionis diets (DCAD= -100 mEq/kg dietary DM). Diets fed from 3 week before expecting calving. At calving, 6, 12, 24, 36 and 48 h after calving and at 7, 14, 44 and 74 DIM serum concentrations of Ca, P and Mg were measured. Blood metabolites and liver enzymes were assessed on d 7 and 14 after calving. Dry matter intake (DMI) was monitored within the first 24 h of calving. Milk yield was recorded daily through 23 DMI thereafter it was recorded monthly until 2 months of lactation.

The yield of milk was greater in cows fed anionic diet compared to control group (40.39±0.73 vs. 39.27±0.55) within 3 weeks of lactation. Dry matter intake was lower in cows fed anionic diet compared to control group (12.10±0.12 vs. 12.90±0.13). Serum concentrations of P, Mg, beta-hydroxy butyric acid and non-esterified fatty acids were similar between groups. Mean concentrations of Ca in serum were not different between treatment groups at calving (0), 6 and 12 h after calving but were higher at 24 and 48 h after calving for cows that received anionic diets (P < 0.05). Incidence rates of dystocia, retained placenta and subclinical hypocalcaemia (P < 0.05) were less in cows received anionic diets. There were no differences between two groups in the incidence rate of clinical hypocalcaemia, endometritis and ovarian cysts (P > 0.05). Number of days to first service was shorter, the conception rate at first service was greater and open days was shorter in cows received anionic diets (P < 0.05). However, services per conception and Cows pregnant before 180 DIM were unchanged between two groups.

The results of the present study showed that the anionic diets increased milk production and first service conception rate via improve in health status of dairy cows.

A study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueAbstract While the physiological conditions of most animals are reflected in their body fluids, in dairy cows physiological conditions are reflected in milk combinations. When negative energy balance occur, production that caused body fat store destruction, goes in two major metabolic ways in liver and breast tissues. In breast tissues, free fatty acids increase fat to protein ratio and in liver, free fatty acid change metabolism leading to increase of ketone bodies. Lactation persistency in dairy cows is one of inheritable economic trait and important characteristic of the lactation curve. The change of this trait is under control of different factors such as animal genetics structure. The amount of cow production at the peak of milk production depends on the calving physical condition, genetics, the absence of infectious and metabolic diseases, and postpartum diet. Fat to protein ratio in early lactation is associated with performance during lactation. Fat to protein ratio is also correlated with some diseases such as retained placenta, displacement of abomasum, metritis, endometritis, mastitis and culling. Fat to protein ratio (FPR) in test day milk records is a good indicator for body fat metabolism and the level of negative energy balance, and that it could be used as a selection criterion to improve metabolic stability. Quantile regression has not been widely used for modeling of biologic characteristics of livestock and this research aimed to evaluate the shape of fat percentage, protein percentage and FPR in test day milk records of Iranian dairy cows using a polynomial quantile regression model. The data used in this study were provided by the Animal Breeding Centre, Iran. Initial data set were edited by Excel and Foxpro software. The traits under consideration were fat percentage, protein percentage and fat to protein ratio (calculated based on the magnitude of the first two traits). All cows had value for all traits. Final data comprised a total of 784,532 test day records collected from 93,259 first-parity dairy cows (progeny of 2741 sires and 79843 dams) distributed in 660 herds over the country and calved between 2003 and 2013. In the data, test day fat percentage and protein percentage had a minimum of 1 and 1.5 and a maximum of 7 and 7, respectively. By SPSS software, some statistical characteristics of the traits were calculated, and by SAS software a quadratic polynomial quantile regression model (in the range of quantiles 5 to 95) was fitted to the data. Based upon the fitted model, linear and quadratic regression coefficients were estimated for the effect of day of lactation on each trait in different quantiles. In the model, traits and day of lactation were response and independent variables, respectively. Quadratic effect of day of lactation is considered due to nonlinear variation of the traits over the course of the lactation curve. Mean fat percentage, protein percentage and fat to protein ratio over the lactation course were found to be 3.35%, 3.08% and 1.1, respectively. As expected, for each trait a nonlinear change was observed over the lactation period. The highest content fat to protein ratio occurs in the early period of lactation and the lowest was observed in the sixth and seventh months of lactation. In terms of absolute values, minimum (953.564) and maximum (1797.661) linear regression coefficient of days in milk were obtained in quantiles 5 and 95, respectively. The same trend was also observed for quadratic regression coefficient of days in milk. Linear and quadratic regression coefficients of fat and protein percentages ranged over different quantiles so that minimum and maximum absolute values were observed in quantiles 5 and 95, respectively. Quantile regression model is an appropriated statistical technique for evaluate the effects of an independent factor which differently affects the shape of a response variable. In this research, the effect of days in milk on three traits (fat and protein percentage, as well as fat to protein ratio) was modeled by quantile regression. The findings of the present research indicate that the curve shape of fat percentage, protein percentage and fat to protein ratio are different for the quantiles suggesting that these differences are needed to be taken into account in nutrition management and cattle breeding scheme.Keywords: Dairy cow, Modeling, Quantile regression, Ratio of milk compositionA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical techniqueA study on the curve of far percentage, protein percentage and fat to protein ratio in test day milk records of Iranian dairy cows using quantile regression statistical technique

A major change in the diet of ruminants is not sufficiently compatible with the evolution of their gastrointestinal tract, reducing the stability of the rumen ecosystem and ultimately reducing the efficiency of food use. Therefore, under the use of Saccharomyces cerevisiae, it can be a suitable solution to maintain the balance of the microbial population and the optimal activity of microbes, improve the fermentation conditions of the rumen ecosystem and increase the production of ruminants.

In order to investigate the effect of Saccharomyces cerevisiae ode on milk composition, digestibility and blood parameters, dairy cows from 20 Simmental dairy cows with an average milk production of 32 4 4 kg / day were used in a completely randomized design. All 10 cows were randomly assigned to one treatment. Experimental treatments included: 1- control group of base diet without using yeast, 2- base diet + 10 g of Saccharomyces cerevisiae yeast per day per head of cattle, in which yeast was added to the animal feed as road. All diets contained equal concentrations of dry matter, metabolizable energy and crude protein. The cows were milked 3 times a day at 4 am, 12 noon and 7 pm. In the last 7 days of the experiment, in each milking meal, 50 ml of milk was sampled in separate containers and after mixing the milk samples related to the whole meals with each other (considering the share Daily milk production per serving), milk composition was measured. Blood samples were taken from the jugular vein of each cow on the last day of the experiment and 2 hours after morning feeding. To determine the apparent digestibility of feed nutrients, stool and feed samples were taken at the end of the 5 days of the experiment.

The use of Saccharomyces cerevisiae had no significant effect on milk fat, protein and lactose levels. The digestibility of organic matter, crude fat and insoluble fibers in neutral detergent using yeast increased significantly (p<0.05). However, increasing the digestibility of dry matter and crude protein was not significant. Also, the use of Saccharomyces cerevisiae caused a significant reduction in urea nitrogen (p<0.05), but had no significant effect on glucose levels.

According to the test results, the use of Saccharomyces cerevisiae significantly increased the digestibility of organic matter, insoluble fibers in neutral detergent and crude fat, it also improved the production of milk and its compounds. As a result, the use of 10 gr Saccharomyces cerevisiae in the diet of dairy cows is recommended.

The aim of this study was to estimate the economic values for residual feed intake and some production and performance traits in Iranian Holstein dairy cow. For this purpose, trait by trait or multiple traits of bio-economic modeling along with production and economic data were used. These data were collected from seven large herds of dairy cows in 2020. The economic values of the residual feed intake was calculated in four different age groups. The diets of different groups were formulated using CNCPS software. Index economic weights (multiplication of the economic values by discounted genetic expressions, in Rial and one cow per year) on average at the level of the studied farms were estimated to be IRR 14280 per kg of milk yield; IRR 291060 per kg of fat yield; IRR 232260 per kg of protein yield; IRR - 790860 per kg of residual feed intake; IRR 702588 per month of longevity and IRR- 113820 per day of days open. The sensitivity analysis showed that the price of concentrate ingredients has a greater effect on the economic value of the residual feed intake than of forage ingredients. In the genetic- economic analysis, the milk production with a relative emphasis of 50 percent was the most important trait in the breeding of Iranian dairy cows, while the relative emphasis on feed efficiency was only about 5 percent. The results of this research provide valuable information for economic values of traits that can be used to complete the national selection index and cost-benefit analysis.

Effect of sodium bicarbonate and pHmax buffer supplement on milk fat synthesis under milk fat depression conditions, using of 24 Holstein lactating cows were investigated in a completely randomized block design. Milk fat depression was induced in all cows for 10 d by feeding a diet containing high levels of starch. The experiment was conducted in two periods including: first period (day 1 to 20), allocation of cows to the treatments 1) control, 2) basal diet + 0.8% pHmax and 3) basal diet + 0.8% sodium bicarbonate and in the second period (days 21 to 30), all cows were fed the control diet. Buffer supplements increased milk fat concentration, without affecting dry matter intake, milk yield, and milk protein and lactose concentrations. The concentration of total trans fatty acids decreased in the experimental treatments compared to the control. The trans -10: trans -11 ratio was lower in cows receiving the buffer supplements compared with cows receiving the control, which indicating the effect of these compounds on the improvement of milk fat synthesis by stimulating normal fatty acid biohydrogenation pathways in the rumen. Addition of buffer supplements increased milk fat synthesis, which persisted for one week after cessation of mentioned compounds. Therefore, using of sodium bicarbonate and pHmax can maintain milk fat in dairy cows fed with diets containing high starch and under milk fat depression conditions. Also, using of pHmax reduces the costs of using common buffer compounds such as sodium bicarbonate.

 The main aim of dairy farms is to increase the economic milk production of each cow in each lactation period. Therefore, the effective genetic and environmental factors should be identified and evaluated. Today, the main cause of economic losses to dairy herds is low reproductive efficiency. Any factor that causes delay or non-pregnancy of dairy cows leads to reduced milk production and calf birth. Stress is known as a major factor in reducing of fertility of dairy farms. Therefore, it is necessary to find management solutions that can reduce the side effects of this factor. The objective of this study was to evaluate the effect of insemination in pre- and post-milking time on pregnancy rate of Holstein Cows in Isfahan province. 

This research was conducted in the winter season between 2015 and 2020 in two large industrial herds in Isfahan. 2340 Holstein cows with 1 to 5 lactations were studied. The cows were randomly divided into two equal groups. According to the time of estrus observation and calculation of insemination time, half of the cows (1170 heads) were inseminated during 2 hours after milking and the other half during 2 hours before milking. Statistical analyzes were done using SAS software version 9.4. Descriptive statistics were estimated for enumerated data with frequency procedure (Proc FREQ) and for continuous data with mean procedure (Proc MEANS). Logistic regression method (Proc GLIMMIX) was used to analyze the results of insemination (1 = lead to pregnancy and 0 = no lead to pregnancy). The final model was including the fix effects of herd-year-season, insemination time compared to milking (pre- and post-milking), age at insemination time (2 levels including less equal and more than 40 months), MIM (nine levels), interaction effect of insemination time and age, interaction effect of insemination time and milk yield level (low and high producing) and the random effect of semen as bulls.

Odds of pregnancy of inseminated cows in the post-milking time was more than inseminated cows in the pre-milking time (1.5 times). Also, in the group of high producing cows (with a milk average yield of more than 51 kg) and low aging cows group (less equal 40 months), the odds ratio of pregnancy of post-milking insemination was estimated higher than pre-milking insemination (1.6 and 1.85, respectively). Comparison of least squares mean (LS Means) of pregnancy rate in cows based on the time of insemination showed that in generally there is a 0.09 pregnancy difference between insemination time in pre- and post-milking. The mean of pregnancy rate in pre- and post-milking insemination was 0.31 and 0.40, respectively. Due to be significant of the odds ratio in the group of high producing cows (with a milk average yield of more than 51 kg), comparison of least squares mean of pregnancy rate in insemination times showed a difference of 0.1 in this group. The mean of pregnancy rate of high producing cows in pre- and post-milking insemination was 0.30 and 0.40, respectively. Also, due to be significant of the odds ratio in the group of low aging cows (less than equal to 40 months), the difference of least squares mean of pregnancy rate at insemination times was estimated 0.15. In other words, the mean of pregnancy rate of low aging cows in pre- and post-milking insemination was 0.34 and 0.49, respectively. For low producing (less than 51 kg) and high aging cows (more than 40 months), although the mean of pregnancy rate at insemination time of post-milking was numerically higher than pre-milking, no significant difference was observed. Although there is a little information for the physiological factors of higher pregnancy in cows that have been inseminated in post-milking, it seems that reducing stress and consequently lower cortisol concentrations due to discharging milk of udder can be an effective factor. 

The results of this study showed that the time of insemination based on milking time makes a significant difference in the pregnancy rate of Holstein cows. It was also found that high producing cows with a milk average yield of more than 51 kg and low aging cows with age of less than equal to 40 months had the maximum chance of pregnancy at the time of insemination of post-milking due to reduced effect of milking stress at insemination time. Although the physiological reasons need to be carefully investigated, the findings of this study can be recommended as a suitable solution for insemination of low aging and high producing cows to increase herd fertility.

The aim of the present experiment was to evaluate the effect of feeding a glucogenic diet on the somatotropic axis of early lactation Holstein dairy cows. Sixteen fresh cows were used in a completely randomized design with two treatments and eight replicates in each treat. In the treatment of glucogenic diet, cows received 600 g of encasulated glucose daily as top dressed. In the control treatment, the cows received daily the same amount of glucose and coating material (mainly fat). Experimental diets were fed from day 4 to 30 after calving. Milk production and dry matter intake were recorded daily. Blood samples collected on days 4, 15 and 29 after parturition from coccygeal vein. The results show that there is no significant difference between treatments in terms of milk yield, energy corrected milk yield, 3.5% fat corrected milk yield, dry matter intake and blood glucose concentration. The glucogenic diet caused a significant increase in blood insulin (P<0.05) and a numerical increase in blood IGF-1 (P<0.15). Cows that received control diet showed a significant decrease in IGF-1 concentration (P<0.05) but no significant decrease was observed for cows received diet containing glucogenic supplement. The results of this study showed that feeding a glucogenic supplements can affect the somatotropic axis of early cows and cause an increase glucose turnover and blood insulin and relative improvement of blood IGF-1 levels.

Ovarian cyst is one of the most important diseases that leads to reproductive disorders and many economic losses in dairy cows. The aim of the present study was to evaluate the blood serum biochemical parameters including glucose, phosphorus, total protein, blood urea nitrogen and triglyceride, and also some clinical features in cows with ovarian cysts and compare them with healthy cows. In this study 80 dairy cows were divided to 2 groups of cows with ovarian cysts and healthy cows that contain 40 cows, then blood samples and their clinical information were collected. The results of the present study showed that the most type of the ovarian cysts are luteal, and anestrus is the most common clinical symptom observed in cows with ovarian cysts. Furthermore, evaluation of serum biochemical parameters showed that there were no significant differences in BUN, phosphorus and total serum protein levels between cystic and healthy cows, while glucose and triglycerides levels were significantly different. It can be concluded that low glucose and high triglyceride levels play an important role in the development of ovarian cysts in the study area.

Luteinizing hormone (LH) is one of the most important reproductive hormones that is secreted by the anterior pituitary gland and plays a key role in regulating the estrous cycle, maturation of ovarian follicles, ovulation, corpus luteum formation, corpus luteum development and maintenance. The LH message is transmitted through by binding it to its extracellular receptors, so that after binding to its own receptor (LHR), LH activates the intracellular cascade chain by activating the secondary messenger cAMP, and ultimately the expression of specific proteins and enzymes. Therefore, the interaction of luteinizing hormone (LH) with its specific receptor (LHR) is one of the key steps in the path of follicular maturation and ovulation. Polymorphisms and LHR splicing are among the genetic changes that can affect LH function and consequent reproductive efficiency.The aim of this study was to compare the tertiary structure of different LHR polymorphisms and their binding affinity to LH in dairy cows.

For this purpose, LHR amino acid sequences were obtained from Gene bank. Firstly, Polymorphisms were identified by alignment analysis. Their related third structures were predicted by homology modeling technique using Modeller software. The created structures were observed and evaluated using PyMol 2.5.1 graphics software and Ramachandran plot. Also, different physico-chemical parameters of the modeled proteins such as isoelectric point, molecular weight, and number of negative and positive sequences and Grand Average of hydropathicity (GRAVY) were calculated using ProtParam tool in Expasy database. Then, the affinity of LH to each of the LHR polymorphism was evaluated using molecular docking technique based on binding energy and spatial position indices.

Based on the results, only two polymorphisms (LHR1 and LHR2) were identified among the studied sequences. The predicted models for the two polymorphisms have a good quality and there was no difference in structural and physicochemical parameters between them. Docking results showed that, despite the difference in total binding energy between the two polymorphisms, this difference could not be attributed to amino acid substitution and this difference is probably related to an orientation of the LH relative to the LHR1 and LHR2. Most of the amino acids that were involved in hydrogen bonding were similar in both the LH-LHR1 and LH-LHR2 complexes.

In general, the results of this study can be used to the relationship between LHR polymorphism and its physiological activity.

The main aim of the present research was the genetic analysis of the first lactation milk yield trait and evaluation of the impact of selection for milk on the phenotype of age at first calving in Iranian dairy cows using quantile regression. Lactation milk records of 327190 first parity cows (progeny of 5260 sires and 235172 dams) in 637 herds (in 15 provinces) and calved between 2007 and 2015 were utilized. Genetic analysis was carried out with the use of an animal model. In the model, fixed effects of the province, herd, year and month of calving, covariates of lactation length, age at first calving, percentage of Holstein gene, as well as the random effect of the cow were included. The model was fitted on the data using the DMU package. Regression of age at first calving on predicted breeding value was fitted through a quantile regression model. The findings revealed that the heritability of lactation milk yield was equal to 0.276. Annual genetic gain in grade and Holstein purebred were found to be 17.352 (R2=0.913) and 23.398 (R2=0.962) Kg, respectively (P<0.0001). All estimated regression coefficients were negative in different percentiles of age at first calving and ranged between -0.0009 and -0.0344 (month per Kg) which indicates that the influence of genetic potential of cows for milk yield on different parts of calving age distribution is not the same.

In the dairy industry, it is important to identify the genotypes resistant to mastitis while select high-yielding dairy cows. Bovine β-difensin gene polymorphism can be used as a molecular marker in the selection of mastitis-resistant dairy cows. The aim of this study was to investigate the relationship between point mutation of β4-difensin gene and the occurrence of clinical mastitis in the dairy cows using RFLP-PCR method and identification of superior genotype of dairy cows β-difensin gene for mastitis resistance.

blood sample (with EDTA anticoagulant) was taken from total 73 cows (32 with a history of mastitis and 41 with no history of mastitis) in an industrial dairy farm. After DNA extraction amplification of the region of bovine β-difensin gene (393 bp) was performed. PCR products were digested by endonuclease (NlaIII (Hin1II)) for rapid detection of polymorphism in the 2239 region of the β-difensin gene (C to T conversion). Statistical analysis was performed by Chi-square test.

Allele frequencies were 0.68 and 0.32 for C and T, respectively. Statistical analysis was performed by Chi-square test. The results of this study indicate the association between number of mastitis and polymorphism in the β-difensin gene. In other words, the incidence of mastitis was  numerically lower in cows with T allele than in cows without it (p=0.07).

It can be concluded that the bovine β-difensin gene can also be used as a molecular marker in the selection of dairy cows to reduce the incidence of mastitis.

In the livestock industry around the world, most decisions are about increasing profitability per head, which is not an independent process and is affected by the interactions of biological functions such as (production, reproduction and health) and prices that are changed by policy. Replacement and breeding affect profitability (Nasre Esfahani, 2018). Issues such as feed price fluctuations and the lack of coherent policies to support the dairy industry in the country have made the profession one of the most risky jobs in the economy. When a producer wants to make the decision to remove or replace a cow, it is best to compare the future benefits and expected benefits of keeping a cow or replacing an animal with another. The most important objective of a livestock unit is to maximize the profit of the herd, one of the issues affecting this profit is the criteria and rate of elimination (Rogers et al,1988). If culling and replacement are not optimal, the cows are removed sooner or later than the optimal deadline, the profitability of the herd decreases. The need to determine the optimal time to remove cows requires simultaneous consideration of several biological and economic variables (De Vries,2006). The removal decision must be based on the anticipated future earnings of the cow. The longer the livestock has a livelihood in the herd, the more profit the livestock earns. The decision to properly, optimally and reasonably eliminate livestock is made by comparing the present value of the future cash flow of the cow present in the herd to the present value of the future cash flow of its replacement heifers, ultimately occupying the most valuable animal in the present (Groenendall et al,2005). The application of dynamic programming in the animal sciences is more on animal substitution issues. The optimal policy at each stage represents the best decision from that stage to the final stage. This method calculates an expected value for each of the situations that can be faced and the decision maker selects the best decision based on the expected value based on the situations ahead. Several dynamic programming models for optimal replacement decision making in dairy herds have been proposed by (De Vries,2004) and (Van Arendonk,1985). (Cardoso et al,1999) reported optimizing replacement and inoculation policies in dairy cows by calculating monthly income, costs and probability of elimination.

In this study, using raw data collected from industrial dairy farms of Ardabil between 2015 and 2018, the biological parameters of the herd, such as the shape of the lactation curve, the risk of forced removal and the possibility of pregnancy in different lactation periods and Different months after calving were estimated. The financial information of the herd was also obtained in the form of an economic questionnaire from the studied units. It was further developed by incorporating biological parameters and financial information into a bio economic model in Dairy Vip software. The feature of this software is that it simulates the livestock over time and also calculates the performance of the herd based on breeding and replacement decisions with the goal of maximizing profitability. Milk production was evaluated using daily milk production records and fitting the incomplete gamma curve (Wood). Dairy Vip software defined average daily milk production levels in the herd by entering lactation data (raw milk quantity, incremental milk slope to peak production and milk slope decrease until peak production). Mean milk yield of 305 days at first to third lactation and peak lactation was reported in Table 1.The mean 21-day inoculation rate and cattle breeding rate were 49.3% and 37%, respectively. By default Dairy Vip software, a maximum livestock can be in the herd 24 months after calving. The risk of fetal loss from the second to the eighth month was 6.24, 4.16, 2.08, 1.11, 0.45, 0.19, and 0.19 percent, respectively. A Dynamic programming model was developed to determine the optimal replacement policy for cows in dairy farms and in economic conditions in Ardabil province. The objective function investigated in this study was to maximize the present value of net income from current cows and alternative heifers. Markov chain simulation was used to estimate the expected statistics under optimal policy.

The implications of the decision policies for optimum and non-optimum removal using Dairy Vip software are presented in Table 3. With the implementation of optimal policies, the overall annual removal rate increased from 30.11% to 43.8%. However, the forced removal rate fell by 2.3%. Pregnancy rate increased from 18/15 to 18.2% and increased by 2.89%. Based on the above results, it can be inferred that the economic importance of increasing the pregnancy rate is more urgent in herds with poorer reproductive performance. Also, the non-optimal catch rate dropped from 33.9% to 37%, indicating an increased likelihood of livestock being pregnant in different months. The 21-day inoculation rate ranged from 47.6 to 49.3%, indicating appropriate cow inoculation. By reducing the days of gestation in dairy cows can increase milk production, which in this study reduced the optimal days of gestation from 139 days to 132 days, which resulted in a significant 7-day decrease in milk production and finally annual. Open days are the interval from birth to the next gestation period, from 167 days to 161 days. With the decline in pregnancy, the rate of pregnancy increased. Calving distance also decreased from 13.6 to 13.3, which was reduced to 0.3 per month, which in turn increased annual milk production. As shown in Table 3, the optimal daily milk yields were increased from 41.4 to 44.2 by the optimal policies, which increased the daily milk yield by 3 kg per cow. And the annual yield of milk increased from 12548 to 13483 kg per cow. Reducing the average days of lactation increased the daily and annual production of productive cows by 3 and 935 kg, respectively.

Decisions to optimize voluntary removal and estimation of livestock value by computer simulation in Dairy VIP software enable improved economic returns. This improvement is due to the decrease in average lactation days in the herd resulting in increased milk production, cattle sales and calf production. Although the implementation of optimal policies is associated with increased livestock removal and replacement costs and increased feed costs, however, the increased revenue from implementing these policies could well offset the increased costs. In general, it can be concluded that increasing milk production in medium-sized cows is the most important factor in increasing economic profit. The results of this study showed that low-yielding animals showed their least future benefit in early lactation, indicating that they should be eliminated sooner.

Selenium is one these trace mineral elements which is essential for health, immunity and maximum production performance of animals. Selenium is an essential trace element, and its importance for animal health and productivity has been well confirmed. Selenium has known to be involved in enzyme activity and preventing oxidative damage to body tissue. Selenium plays important roles in antioxidant defence systems, prevents cell damage and is necessary for growth, fertility, and immune system in farm animals. Recently, nano -elemental Se has attracted wide spread attention due to its high bioavailability and low toxicity, because nanometer particulates exhibit novel characteristics, such as great specific surface area, high surface activity, a lot of surface active centres, high catalytic efficiency and strong adsorbing ability and over and above the character of low toxicity of Se0. Dietary selenium is an essential trace element for animals and humans with a variety of biological functions. It plays important roles in the regulation of thyroid hormone metabolism, cell growth and antioxidant defence systems thus, together with alpha-tocopherol prevents cells against oxidative stress damage, also these compounds are necessary for growth, fertility, and immune system health in animals and humans. The in situ and in vitro usually use for determining of effect of additives on digestibilities of t feeds. Regarding to the importance of TMR feeding on dairy cattle nutrition, determining of its digestibilities with additive and without additive is necessary. The aim of this study was to investigate the effects of different forms of selenium sources on digestibility of high production lactating dairy cows TMR in vitro and in situ Techniques.

3 male ruminally cannulated sheep, average 43±4.8 kg of BW, were used in a replicated 3×3 Latin square experiment. Sheep were fed twice daily (08:00 and 18:00 h) at maintenance nutrition requirements with a basal diet consisting of 400 g/kg (dry matter) DM of basal concentrates and 600 g/kg DM of forage. Sheep were placed in metabolic cages individually and fresh water was freely available during the experimental period. This experiment was conducted in three periods of 28 days with 21 d adaptation period and 7 d for data tacking. Treatments were: 1. Basal diet + 0.3 ppm nano selenium, 2. Basal diet + 0.3 ppm organic selenium, 3. Basal diet + 0.3 ppm inorganic selenium. In gas production method, 300 mg of each treatment weighted and incubated for 2, 4, 6, 8, 12, 16, 24, 36, 48, 72, 96 hours. The Nylon bag method used to estimate ruminal disappearance of dry matter. Ruminal degradability was measured using nylon bag technique on day 22–28 of the experimental period. The samples 5 g of feed were weighed in 6 cm×12cm nylon bags made of monofilament Pecap polyester . Samples were incubated separately in duplicate bags and suspended in the rumen of each sheep and removed after 0, 2, 4, 8, 12, 16, 24, 36, 48 and 72 hours. All removed bags were rinsed in cold water until the bags were clean; the bags immediately were dried in an oven at 65◦C for 12 h, then 105 ◦C for 24 h in order to determine DM disappearance. in three steps digestion method, about 5 g of feed stuffs weighted in 6 cm×10cm nylon bags made of monofilament Pecap polyester . Samples were incubated separately in duplicate bags and suspended in the rumen of each sheep and removed after 12 hours. All removed bags were rinsed in cold water until the bags were clean; the bags immediately were dried in an oven to determine DM disappearance.

During most of incubation hours, the volume of produced gas was higher in nano selenium, organic selenium, inorganic selenium and control treatments, respectively. However, significant differences between treatments were occurred after 36 h of incubation. The most gas production potential (A) was measured in nano selenium, organic selenium and inorganic selenium compared with control treatments. There were not any significant differences between nano selenium and organic selenium in gas production potential. there wasn’t any significate differences between treatments in degradability of TMR dry matter. In three steps digestion experiment, nano treatment was higher than inorganic treatment in post ruminal digestion of TMR dry matter.

The results showed that the addition of various sources of selenium to the diet may improve rumen function.

For mathematically-oriented investigators, DNA is a string. Therefore, they consider a DNA sequence as a string of symbols whose correlation structure can be characterized almost completely by all possible base-base correlation functions at any range, short or long or their corresponding power spectra. Long-range correlations between bases in the DNA sequence are a statistical feature found in the genome of many eukaryotes. The existence of long-range DNA correlations indicates the existence of DNA rearrangement or duplication processes. These types of phenomena are not directly applicable to breeding and are mostly used in evolutionary studies. Our basic assumption in this study was that by extracting long-range DNA correlations between all the different nucleotides within a gene, it is possible to achieve a degree of correlation between them in the first place and possibly better run SNP-based researches. Due to many furious issues, not all investigations of a complete characterization of long-scale correlation structure of DNA sequences were motivated by biology arena. Rather, many such investigations were motivated by the issues of mathematical modeling, cryptography language code detections, dynamical systems, stochastic processes, and noise detections. Perhaps due to this reason, long-scale correlation structure has not yet become part of the toolbox in the “mainstream” DNA sequence analysis in human genetics and breeding settings. Prediction of DNA correlations from a sequence with finite length could be done with, frequency-count estimator, indirect Bayesian estimator, direct Bayesian estimator. Here we followed the ideas by CorGen theory.

24 genes selected out of genes affecting milk yield of dairy cow. The number, length and length of each exon and its position on the chromosome were obtained from the NCBI gene bank and the sequences were saved in FASTA format. Using software previously designed in #C language, according to the research request, the accession numbers of the studied genes was entered and the appropriate output was obtained. CorGen software was used to calculate the long-range DNA correlations of the genes involved in milk production.

The results showed that there is a significant level of long-term correlation in DNA sequence of a number of genes such as EZR, FGG, KRT6A, RAB1A, EIF3L, TBC1D20, ZNF419, S100A16, MRPL3, TPPP3, PHF10. The reduction power of the fitting function of the power function was based on the long-range correlations obtained from genes of different lengths, in the range of 0.146 and 0.643, so it can be concluded that reducing the range of long-range correlations by increasing the interval between DNA sequence intervals does not follow a random process. And so, the fractal geometry of nature is also seen in these genes. This research was an attempt for the first to address long-DNA correlation in dairy cattle genes. There are at least two goals for this job. First, there has been discordant on the result of correlation structure in DNA sequences. Due to this matter of what the actual result is, some researches still believe that DNA sequences do not exhibit any feature long-range DNA correlation which cannot be explained by the basic known stochastic processes such as random sequence or Markov chain - with the first one having no correlation inherently in its theory and the second one considers only short-range correlations. Resolving this disagreement can be straightforward once everybody agrees to use the same measure of correlation, use the same estimator, and apply this estimator of the correlation to the same sequence. The second is to highlight more biologically-motivated study of correlation structure of long range DNA sequences especially in animal breeding. Although this research does not accomplish this task, the intention was to at least put forward the issue. Most of the current studies of correlation (especially the long range one) in DNA sequences are based-base base statistical correlations. This base-base correlation won't not be a powerful tool to reveal the correlation on a global scale or between larger blocks in DNA-sequences.

The genes studied have been shown to have high complexity and mode of invariant on their DNA. This type of analysis can be generalized to the work of breeding setting. A more complete characterization of long-range correlation between base pairs at both short and long distances became possible only as long DNA sequences became more commonly available. Now thanks to stupendous growth of DNA generating technologies, almost the entire whole genome of an organism can be sequences in low cost price with high speed time. Therefore, a raw data shall be available for many researchers who are looking for to check new DNA correlation hypotheses in handy DNA sequences. The claim of DNA base-base statistical correlation at long distances in DNA sequences is sought to be still a few steps away from finding a Naive organization principle of the genome.

The genes studied have been shown to have high complexity and mode of invariant on their DNA. This type of analysis can be generalized to the work of breeding setting. A more complete characterization of long-range correlation between base pairs at both short and long distances became possible only as long DNA sequences became more commonly available. Now thanks to stupendous growth of DNA generating technologies, almost the entire whole genome of an organism can be sequences in low cost price with high speed time. Therefore, a raw data shall be available for many researchers who are looking for to check new DNA correlation hypotheses in handy DNA sequences. The claim of DNA base-base statistical correlation at long distances in DNA sequences is sought to be still a few steps away from finding a Naive organization principle of the genome.