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

 In dairy cows, milk yield changes over the lactation period. Lactation curve modelling could be of importance from nutritional management and genetic selection point of view. The trajectory shape of the lactation curve has inclining and declining slopes which determine total amount of milk yield during the lactation. A great number of linear and nonlinear mathematical models have been so far utilized to describe the shape of the lactation curve in dairy cows. Among the models, mechanistic functions are considered to be more accurate than empirical models in terms of taking account of biological mechanisms undertaken in mammary gland to produce milk. To our knowledge, no research has been carried out to use a complex mechanistic model for describing the lactation curve of Iranian dairy cows. Based on this, the present research aimed to apply a five-parameter nonlinear mechanistic model for mathematical description of the shape of the lactation curve in Iranian first-parity dairy cows.

Animal Breeding Centre of Iran provided the data used in this research. Initial data in separate files were merged and edited by the SPSS software. Final data comprised 5596039 milk test day records from 821153 first-parity cows distributed in 579 herds of 26 provinces over the country. The cows were the progeny of 7957 sires and 530394 dams and calved between 1996 and 2020. The cows were categorized into two groups based on the age of first calving: <=25 or >25 months. Also, two groups of cows were created based on the proportion of Holstein gene inheritance: <100% (grade cows) or 100% (pure Holstein cows). A five-parameter nonlinear mechanistic model was applied to mathematically describe the shape of the lactation curve. The fitted mechanistic model had five parameters including MSmax (maximum milk secretion potential of the lactation), GR (relative proliferation rate of secretory cell number during early lactation), MSLmax (maximum secretion loss), NOD (proportion of parenchyma cell dead at parturition), and DR (relative decline rate in cell number) which their estimates were obtained for different seasons and ages of calving, as well as different genotypes (grade and pure Holstein) using NLIN procedure of the SAS software. Based on the estimated parameters of the model in each year of calving, phenotypic trends were calculated using the SPSS software.

The results indicated that Iranian first-parity dairy cows reach to peak of milk production during the third month of the lactation curve. Based on standard deviation as well as coefficient of variation (CV) of milk test day milk records, maximum variation was observed in the last month of the lactation period. The findings also indicated that cows calved in autumn had the greatest MSmax and GR while cows calved in spring and summer had the lowest magnitude for these parameters (P<0.05). The minimum magnitude of MSLmax and NOD were detected for the cows calved in summer (P<0.05). Regarding the DR parameter of the model, cows calved in spring were observed to have a minimum value. Maximum MSmax, Gr, and DR values ​​were determined for cows calving up to 25 months of age, while maximum MSLmax and NOD values ​​were observed for cows of later ages (P<0.05). Compared to pure Holstein cows, grade cows had higher MSLmax and NOD values, but other parameters were found to be greater in the pure Holstein cows (P<0.05), suggesting that the maximum milk secretion potential during lactation in pure Holstein cows is expected to be higher than that of grade cows. Annual phenotypic change trends were found to be 0.376 kg/year (R2=0.9), 0.00009869 (R2=071), -0.146 kg/year (R2=0.59), -0.011 (R2=0.85), and 0.001 (R2=0.85) for MSmax, GR, MSLmax, NOD, and DR, respectively (P<0.0001).     

This study found that the parameters of the mechanistic model fitted to the milk test day records of Iranian primiparous dairy cows are significantly influenced by the age and season of calving as well as the genotype of the cow. Cows calving in summer are expected to have more persistency. Moreover, pure Holsteins are more persistent than grade cows. Positive and negative annual trends have been detected for MSmax and MSLmax parameters, respectively, during 1996-2020 indicating a favorable increase in maximum milk secretion potential of the lactation and also a favorable decrease in maximum secretion loss over that period.

Environmental pollution, including pollution caused by urban and industrial sewage, factories and vehicles, causes pollution of natural resources in the environment, including water and fodder. The entry of these elements into the body of animals and their accumulation increases their concentration in products and enters the human food chain. Contamination of milk, meat and other edible tissues of animals with heavy metals is also a worrying issue and threatens food hygiene and human health because these elements are not naturally present in edible tissues and even very small amounts of them can be cause severe side effects. Scientists have mentioned the main cause of contamination of meat and animal tissues is feeding them from contaminated fodder sources or rearing them near contaminated areas. In the studies conducted in different countries, the amounts of heavy elements were more than allowed. In order to investigate the amounts of heavy metals including lead, cadmium, chromium, arsenic and nickel in milk and body tissues of dairy cows in North Khorasan province, two experiments were conducted in three regions and the amounts of heavy metals in milk and body tissues of dairy cows using the device Inductively coupled plasma-atomic diffusion (ICP) was measured, and studied.In the first experiment, three dairy cattle farms were selected from three regions, two farms were located in two regions at equal distances from large industries, and the third region was selected as a control region far from large industries. In each of the farms, 10 dairy cows (5 first lactation and 5 second lactation and above) was sampled and the amounts of elements were measured. In the second experiment, muscle, heart, liver, kidney and lung tissues were sampled from 5 dairy cows from each region that were removed and sent to the slaughterhouse for reasons such as mastitis and reproductive problems. Heavy metals, including lead, cadmium, chromium, arsenic and nickel, were measured in the tissues by an inductively coupled atomic diffusion plasma (ICP) device. The initial experiment's findings indicate that the levels of arsenic, cadmium, and lead in the milk of Holstein cows remained unaffected by varying regions. However, there were significant regional impacts on the levels of chromium and nickel in the milk of Holstein cows. Furthermore, the concentrations of arsenic, cadmium, nickel, and lead in the milk of Holstein cows were not influenced by the age of the cows or the interaction between region and age. In contrast, the concentration of chromium exhibited sensitivity to age and the interaction between region and age. These nuanced insights highlight the diverse influences on trace metal concentrations in Holstein cow milk, providing valuable information for understanding regional and age-related variations. The amount of arsenic, cadmium and lead metals in the thigh muscle tissue of Holstein cows in different regions was not significantly affected by regions. However, the amount of chromium and nickel in the thigh muscle tissue was significantly affected in different areas. The amount of arsenic, chromium, nickel and lead in the heart tissue was not significant in any of the regions (Shirvan, Esfrayen and Bojnoord). The amount of cadmium in the heart tissue of Holstein cows was significantly affected by different regions. Thus, the highest amount of cadmium in heart tissue was observed in Bojnord region and the lowest in Esfrayen region. The amount of chromium, nickel and lead in the tissue of all Holstein cows in different regions was not affected. However, the amount of arsenic and cadmium in the kidney tissue was significantly affected in different areas (Shirvan, Esfrayen and Bojnoord). Based on the obtained results, there was no significant difference in the amount of arsenic, cadmium and lead in lung tissue in different regions. However, the amount of chromium and nickel in the lung tissue of Holstein cows was significantly affected in different regions. Chromium enters various environmental sources (air, water and soil) from a wide range of natural and human sources, the most of which is emitted from industrial activities. When heavy metals are present in the air, feed and water of animals, they eventually accumulate in their tissues. While the levels of heavy metals did not exhibit significant differences across many investigated areas, it is noteworthy that the concentrations surpassed the standard values established for these metals in products like milk. The elevated concentrations raise concerns about the potential health implications associated with consuming products containing such heightened metal levels. An interesting observation emerges from the examination of elemental concentrations in tissues, irrespective of regions and distances. The lead element, in particular, demonstrated the highest concentrations, with the liver exhibiting the most notable accumulation compared to other tissues. This underscores the need for strategic interventions, and the consideration of solutions such as the application of absorbents to mitigate metal concentrations in dairy cattle products emerges as a viable recommendation. Implementing such measures could play a crucial role in ensuring the safety and compliance of dairy products with established standards.

The past few decades have seen a dramatic decrease in the fertility of dairy cows. Thus, reproductive performance became one of the main concerns in the dairy cow industry. Improvement of fertility increases the farmer’s income by reducing the culling rate, increasing milk production, and reducing the calving interval. Factors involved in reproductive management are multifactorial such as management, nutrition, and genetics. Synchronization protocols are one of the main management tools that have improved the reproduction of high-producing dairy cows. Nevertheless, the efficiency of these protocols is still not satisfying and the current study was carried out to improve the double Ovsynch protocol in postpartum dairy cows.

A total of 318 healthy postpartum dairy cows were used in the current study. Data of parity and milk yield (1st and 2nd months) were recorded for all cows. Briefly, on 40 DIM, cows were subjected to a double Ovsynch program and were checked for corpus luteum via ultrasonography on d 57, at the start of the 2nd Ovsynch. Cows without CL were divided into two groups including control (DO-CL, continuing the routine program), and DO+CIDR (including one progesterone supplement). Those bearing CL were considered as DO-CL receiving routine injections. All cows were checked for pregnancy via ultrasonography on d 32, 60, and 120 post-AI, and pregnancy per artificial insemination (P/AI) and pregnancy loss rate were calculated. Data were analyzed using the GLIMMIX Procedure of SAS software.

Cows bearing CL at the start of TAI Ovsynch, compared to DO-CL and DO-CIDR groups, had significantly higher P/AI on d 32 (50.84 vs. 29.27 and 41.46%, P = 0.03), 60 (45.76 vs. 21.95 and 36.58%, P = 0.01), and 120 (43.22 vs. 21.95 and 34.14%, P = 0.03) post-AI. Although cows with CL at the start of the TAI program had 15% lower pregnancy loss compared to the control group, this trait in the 2nd (P = 0.31) and 3rd-4th month (P = 0.75) was not significantly affected by treatments. Parity (primiparous vs. multiparous) had a significant effect on P/AI on d 32 (P = 0.04), but not on d 60 (P = 0.17) and 120 (P = 0.28) post-AI. The effect of milk yield (M ≥ 36 vs. M ˂36) on P/AI at d 32 (P = 0.003), 60 (P = 0.001), and 120 (P = 0.001) was significant. Dairy cows in M ˂36 group compared to M ≥ 36 had significantly higher P/AI on d 32 (52.96 vs. 35.63%), 60 (46.62 vs 28.11%), and 120 (44.41 vs. 26.08%) post-AI. The effects of treatment × parity (P = 0.41) or treatment × milk yield (P = 0.45) interactions were not significant.

Improvement of P/AI via evaluating the presence of CL at the start of the TAI program and using a progesterone insert in cows without CL suggests an important role of progesterone during the growth of ovulatory follicles. Therefore, the identification of cows not bearing CL and applying progesterone is highly recommended. However, the difference between P/AI in cows that received CIDR compared to those in diestrous suggests that using a CIDR may not be sufficient and two CIDRs should be applied in order to achieve optimum results.

The scientists believe that human intervention has caused changes in climate conditions and these changes will be noteworthy in the future. Any significant change in climate variables can affect the milk production of industrial livestock farms.

In this research, the effect of temperature-humidity Index (THI) on milk production in Babolsar city was quantified, and then, using the SDSM model, the THI index was downscaled to the year 2100. Finally, the effect of climate change on milk production until the end of current century in three emission scenarios of RCP2.6, 4.5, and 8.5 were quantified.

The results showed that in the current situations, Babolsar station has been involved in temperature-humidity stress for 5 months of the year, which will increase to 7 months by the end of this century. Also, the results showed that in near future (before 2050) the stress condition is not much different from the base period, but after that, even in RCP2.6 scenario, the differences with the base period will increase significantly, and the most intensity of stress level will occur., As a result, on more days of the year, heavy livestocks will experience tempreture-humidity stress. Quantification of the effect of temperature-humidity stress on milk production showed that for increase of one unit of daily THI more than 70, the milk production of each animal decreases by 327 grams. The investigation of milk reduction trend in the future showed that until the year 2100, not only the milk production will decrease in more months of the year, moreover, the daily losses of livestock farmers also increase. so that in the stressful months, the daily milk reduction from 1 to 2 kg per animal in base period, will increase to 1.5 to 3.5 kg. So, the losses caused by climate change on milk producers will increase by at least 45 and at most more than 100 percent.

According to the results of this research, the stress level of emergency will occur in the last decades of this century, which will lead to a sharp decrease in milk production. Therefore, if adaptation policies to climate change are not considered in the future, there may be happens widespread deaths of heavy livestock especially in critical months of July and August, which is a serious alarm for livestock industry of the Mazandaran province.

The aim of the present study was to estimate the impact of somatic cell count on daily milk yield of Iranian dairy cows using quantile regression statistical technique. A total of 784,532 test day records belonging to 93,259 first-parity cows distributed in 660 herds and calved during 2003-2013 were used. The studied trait was test day milk yield and the model was defined as a quantile regression. All of the estimated regression coefficients were negative, which indicated a decrease in the amount of daily milk production when milk somatic cell counts increased, so that, in the spite of lactation stage, on the basis of absolute value, the lowest and highest regression coefficients observed at ninety-fifth percentile and fifth, respectively. Considering lactation stage in the seventh stage of fifth percentile, the highest decrease was 238 g milk reduction per day, for increase of 100 thousand somatic cells per ml/L of milk, and in the 95th percentile of the fourth stage, the lowest decrease was 64 grams milk reduction per day, for increase 100 thousand somatic cells per ml/L of milk. The results revealed that in high quantiles of daily milk yield, the impact of SCC on milk production decreases indicating that high-producing cows are less influenced in terms of loss of milk production as SCC increases. The difference in the amount of somatic cell count on the amount of milk production in cows with different production potential should be considered in the genetic evaluation of herds.

The objective of this experiment was to determine the effects of fish meal supplementation on productive and reproduction performance in repeat breeder Holstein cows. Two hundred and sixty-one multiparous Holstein cows with at least three consecutive unsuccessful inseminations, without clinically detectable reproductive disorders, were randomly allocated to 1 of 3 dietary treatments. Dietary treatments were control, 2.5 or 5% fish meal, that replaced soybean meal. Cows were timed inseminated following the Double-Ovsynch protocol. Milk yield was (38.49, 39.92, and 41.42 kg/d, for cows fed the control, 2.5 and 5% FM diets respectively) of which the difference (P<0.01) between the control and 5% FM diets was significant. Likewise, 4% FCM was higher for treatment 5% FM relative to control (P<0.05). Milk fat, protein and lactose content (%) were not different among treatment (P>0.05) but milk protein yield was higher (P<0.05) for cows fed the 5% FM than control and 2.5% FM diets was significant. Plasma and milk urea nitrogen concentrations decreased significantly (P<0.05) affected fish meal by consumption. Plasma cholesterol concentration was higher for cows fed 5% FM compared to the control diet (P<0.01). Plasma progesterone concentration at 16 d post artificial insemination was greater for treatment 5% FM relative to control treatment (P<0.05). Pregnancy at the first service and cumulative (1st and 2nd service) for cows fed 5% FM content higher than control diet (P<0.05). These results indicated that supplementation the diet with 5% fish meal improved fertility and productive performance in repeat breeding cows.

Dairy milk is one of the most important economic products for any country. Also, milk fat has high impact on taste of milk and dairy products. The liver in ruminant animals including dairy cows plays an important role in carbohydrates metabolism, fats, vitamins, hormones, and etc. The absorbed nutrients pass through the liver from the gastrointestinal tract and enter the blood circulation system, and eventually enter the mammary glands of dairy cows. Therefore, the liver plays an essential role in cow lactation and fat production. All components that determine milk quality can be considered as quantitative traits controlled by many genes and influenced by environmental factors. If genetic markers can explain a significant part of the variation, they can be considered as ideal candidates for genomic selection. Previously, microsatellite markers were used to identify quantitative trait locus (QTL). But now, with the progress of science and the advent of the single-nucleotide polymorphisms (SNP) is used in genome-wide association studies (GWAS) to identify QTL. In dairy cows, some of the major genes with significant effects on milk fat have been identified in previous GWAS studies. Therefore, despite a large number of GWAS studies in dairy cows, the studies can be combined using meta-analysis to achieve higher power results. Meta-analysis is a statistical analysis that combines the results of scientific multiple studies. These studies contribute to our current understanding of the genetic regulation of milk fat yield traits. This approach provides a better understanding of the genetic architecture of complex traits. The network clustering algorithm and cluster identification is an important tool in the structural analysis of networks. The many clustering algorithms in different types are used for protein-protein interactions (PPIs) networks analysis. In this study, we used an algorithm known as MCODE to identify dense regions in the PPIs diagram. The overall purpose of PPIs network clustering is to a grouping of genes or proteins that are related according to some scales. The network of PPIs contains different proteins that play a role in different pathways. Because these genes or proteins are clustered based on the similarity of metric and are known as matrix distances. It is also important to predict molecular assemblies of protein interaction data because it provides another level of functional annotation. A total, the purpose of this study is to conduct a meta-analysis of GWAS in cluster analysis to identify genes that are effective in milk fat yield in dairy cows.

In this study, the data used were GWAS summary data. All data were collected from 19 published studies from 2010 to 2019. This research included main papers and dissertation (valid dissertations with published papers). All available genes were combined, synthesized, and evaluated using a meta-analysis method. The Cytoscape v3.7.2 software was used to analyze and visualize the genes examined by the STRING v1.5.0 plugin and to extract clusters from the MCODE v1.5.1 algorithm. Therefore, the results of the GWAS summary data were combined in molecular networks with PPIs, which have a significant role in increasing the association studies power to identify genes affecting milk fat trait. Also, the DAVID server was used to identify the gene ontology (GO) term enrichment in order todetect enriched biological terms associated with genomic regions and to identify gene networks using functional annotation clustering tools based on enriched pathways analysis.

A total, 223 genes were analyzed using the STRING plugin in Cytoscape software. Also, these genes were associated with at least one other gene and had a direct and partial correlation. In the gene network, the correlation created for milk fat yield trait included 213 genes or nodes and 219 edges (gene connection). The P-value calculated in the STRING network was statistically significant for enriched pathways in PPIs ( ).The collection of important genes and popular were evaluated using the MCODE plugin. Seven clusters were identified and grouped in this network. For instance, proteins in cluster 1 included: ARHGAP39, CPSF1, CYHR1, PPP1R16A, GRINA, MROH1, and SMPD5 genes. As shown in Table 2, cluster 1 (score=7) was connected with 7 node density to 21 nodes. This cluster showed proteins that play important roles in the internal space of the endoplasmic reticulum (cellular components), metal ion binding (molecular function), and integral to the membrane (cellular components). CPSF1, CYHR1, and GRINA are major genes involved in the internal space of the endoplasmic reticulum, metal ion binding, and membrane integral, respectively. It was found that clusters 1 and 2 have the highest score between all reported clusters.

The chart-based protein clustering was extracted from the PPIs network using the MCODE algorithm and the enriched pathways were extracted from the DAVID tool. This method determines the quality of the proteins involved in fat yield and helps to understand the molecular structure of proteins. These clusters based on existing biological knowledge can help data mining and system models understand network interactions and pathways. These protein clusters provide a deep insight into how genes interaction with each other in network analysis for fat yield. However, it was observed that meta-analysis of GWAS summary data can play an important role in the wide understanding of network visualization and cluster analysis of identified genes in enriched pathways. Therefore, cluster analysis can improve the identified genes power for economically important traits such as milk fat yield in a population of dairy cows and can be used in future genomic evaluations and breeding programs.

Understanding feed efficiency (FE) in dairy cows and its improvement is essential. Dry matter intake (DMI) is fundamentally important in nutrition because it establishes the amount of nutrients available to an animal for health and production. Residual feed intake (RFI) is calculated as the residual in the linear model to predict feed intake of individual animals and thus is essentially the difference between an individual’s observed feed consumption and its predicted feed consumption. An animal with a negative RFI consumes less than expected for its level of production and thus is more efficient when RFI is used to define feed efficiency. Because RFI is independent of production level, recent attention has been given to using RFI as a tool to assess feed efficiency in dairy cattle for purposes of genetic selection. Also, feed efficiency based fat-corrected milk (FCM4) dived DMI (FCM4/DMI) is another factor to depict feed efficiency. Therefore, this research aimed to investigate the dynamics of RFI and FCM4/DMI in Iranian Holstein dairy cows.

Lactating Iranian Holstein cows (n = 30; 10 primiparous and 20 multiparous), averaging (mean ± standard deviation, SD) 594 ± 62.6 kg of body weight, 38.81 ± 6.22 kg of milk/d, and 94.5 ± 21.5 day postpartum, were fed a diet balanced with CPM Dairy V3 ration software. Diet consisted of 40 % forage and 60 % concentrate and fed as total mixed ration (TMR). Cows were fed once per day a fresh diet and orts were removed and weighed daily before feeding. Milk yield was recorded electronically at each milking, and milk samples were obtained from 3 consecutive milkings per week. Milk samples were analyzed for fat, true protein, and lactose with infrared spectroscopy. Body weight (BW) for each cow was recorded 2 consecutive days per month immediately after the morning milking. Daily weight gain was calculated based on body weight for each cow at the beginning and end of each period (30 and 60-days period). Body condition score (BCS) was determined on a 5-point scale in 0.25 increments by a trained investigator and recorded for each cow at the beginning and end of each period (30 and 60-days period). Also, milk energy output (MilkE; Mcal/d), metabolic body weight for a cow (MBW), and energy expended for body tissue gain (ΔBodyE; Mcal/d) were estimated based on NRC 2001 equations. Dry matter intake for an individual cow during each 30 and 60-days period was regressed as a function of major energy sinks through the four different models (Model 1, Model 2, Model, and Model 4) using Mintab software (version 19). To define RFI, DMI was modeled as follows:〖Model 1: DMI〗_i= β_0+ β_1 ×MILKE_i+ β_2 × MBW_i+ β_3 × ∆BodyE_i+〖β_4 × 〖Weight G〗_i +β〗_5 × Parity_i+ β_6 × 〖Lactation W〗_i+ ε_i〖Model 2: DMI〗_i= β_0+ β_1 ×〖FCM4〗_i+ β_2 × MBW_i+ β_3 × 〖Weight G〗_i+ ε_i〖Model 3: DMI〗_i= β_0+ β_1 ×MILKE_i+ β_2 × MBW_i+ β_3 × ∆BodyE_i+β_4 × Parity_i+ ε_i〖Model 4: DMI〗_i= β_0+ β_1 ×MILKE_i+ ε_iWhere DMIi was the observed DMI, MilkEi was the observed milk energy output, MBWi was the average BW0.75, ΔBodyEi was the estimated change in body energy, based on measured BW and BCS, Weight Gi was daily weight gain, Parityi was the parity, Lactation Wi was week of lactation, and FCM4i was fat-corrected milk for ith cow. RFI was defined as the error term (ε_i) in the model. Also, we reported Pearson correlation coefficient between DMI, FCM4/DMI, and RFI with measured and estimated traits for a 30-days and 60-days period.

The results showed that RFI was observed and measured in our study population and it is possible to classify animals based on RFI. The model adjusted R2 for models 1, 2, 3 and 4 were 88.51, 78.82, 80.05, and 64.41 respectively, in a 60-days period. The mean ± SD for models 1, 2, 3 and 4 were 0 ± 0.86, 0 ± 1.25, 0 ± 1.18, and 0 ± 1.68 (kg DM per a day), respectively. For model 1 (in 60-days period, full model), milk energy output (MilkE), metabolic body weight for a cow (MBW), energy expended for body tissue gain (ΔBodyE), daily weight gain, and week of lactation were significant (P<0.05) except for parity which showed a significant trend (P<0.1). Partial regression coefficients for MilkE, MBW, ΔBodyE, daily weight gain, parity, and week of lactation for the model 1 used to predict DMI were 0.566, 0.1, 3.46, -9.51, 4.13, and 0.1771, respectively. For model 3 (in 60-days period), milk energy output (MilkE), metabolic body weight for a cow (MBW), and energy expended for body tissue gain (ΔBodyE) were significant (P<0.05) except for parity. Partial regression coefficients for MilkE, MBW, ΔBodyE, and parity in the model 3, were 0.429, 0.1381, 0.791, and 0.229, respectively. Pearson correlation coefficient for RFI between model 1 with 2, 3 and 4 was 0.817, 0.728, and 0.515, respectively (P<0.01). The same trend was observed for a 30-days period. Pearson correlation coefficient for DMI between 60-days and 30-days period was 0.994 and for RFI between 60-days and 30-days period was 0.882. Also, based on Pearson correlation coefficient for DMI, FCM4/DMI, and RFI with other biological parameters, we observed that there were the reasonable correlations, significant at the P=0.01. Surprisingly, there was a negative correlation between FCM4/DMI and milk protein percentage (P<0.0001). Also, negatively significant trend between RFI with milk fat and protein percentage (P<0.1) was observed.

Measuring feed efficiency through RFI in a 30-days period is predictable. Although the model 1 used in this study and its parameters explained DMI in accurate manner, scientific exploration for finding other parameters for improvement of model R2 is suggested. Therefore, finding the effective models would result in an accurate estimation of RFI for individual dairy cows, classifying efficient and inefficient dairy cows correctly and clarifying the reasons for these differences through a holistic approach. Also, the study of the reasons for the significant negative correlation between FE and RFI with milk protein and fat percentage as a novel observation in our study is recommended in the future.

Mastitis is an inflammatory disease in dairy cows that occurs in response to infectious factors. This inflammatory disease have a high negative economic impact on dairy industry. In recent decades, somatic cell score has been used as an indirect method to control mastitis. Resistance to infection disease may be defined as the ability of an animal to have an immune response to prevent the spread of pathogens after infection. Previous studies showed that animals differ in their genetic ability for immune competence. Genetic resistance to mastitis involves interconnected biological mechanisms that result from differences in the response to mastitis that activate and regulate different levels of the immune response. A better understanding of the immune system and the metabolic pathways involved in responding to various pathogens may be used as a complementary approach to control of the disease. Several studies have been evaluated genetic mechanisms affecting somatic cells score in dairy cows. Many candidate genes affecting somatic cells score has been introduced. But the complex relationships between genes and pathways that affect them have not been fully identified yet. The main purpose of this study is to integrate the results of recent genome-wide association studies on somatic cells score using meta-analysis to obtain a set of important genes and pathways.

In this study, a search for the genome-wide association studies dataset in Google Scholar was performed using the keywords Dairy cows, Genome wide association studies, and Somatic cells score. Gene sets were available in different populations of dairy cow breeds (Holstein and Friesian breeds and red cows) in 11 independent studies from 2011 to 2019. 218 candidate genes for somatic cells score were found from genome-wide association studies. The number of common genes in dairy cows was examined using Venn diagram. Then, all available genes were combined and evaluated using meta-analysis. The ClueGO v2.5.4 plugin were used to conduct gene ontology analysis and KEGG pathways. The CluePedia v1.5.4 plugin in Cytoscape v3.7.2 were used to visualize genes and protein-protein interactions.

The results showed that U6, DCK, and NPFFR2 genes as the key candidate genes have an important role in combating infection and pathogens in the development of mastitis. Some biological processes, cellular components, molecular functions, and related pathways were identified. The most important biological process, cellular components and molecular function pathways were mesenchymal cell development (P=3.92e-04), apical plasma membrane (P=2.83e-03), and solute: cation symporter activity (P=3.71e-04), respectively.

Generally, the results of this study showed that meta-analysis based on a large number of original data revealed the most important candidate genes involved in the fight against mastitis pathways, this information provides a solid foundation for the development of new treatments for mastitis. Therefore, identification of important genes and gene ontology term enrichment (with high power and accuracy) can play an effective role in genomic evaluation and design of breeding programs aimed at controlling mastitis in dairy cows.

The aim of this research was estimation of genetic parameters for the fat: protein trait (FPR) in daily milk test records of Iranian dairy cow. From a total of 295,820 monthly daily milk test records, 29,582 first-parity cows in 622 herds were used which were calved from 1997 to 2012. The trait was analyzed using a covariance function. Orthogonal Legendre polynomials with a 3th order were implemented to take account of genetic and environmental aspects of milk production over the course of lactation. The data were analyzed with the help of DXMRR software. Maximum phenotypic and genetic correlations (0.209 and 0.988) was obtained between the ninth and tenth month Maximum permanent environment correlation (0.938) was observed between the seventh and eighth months. The lowest (0.029) and highest (0.064) heritability’s were obtained for the third and first months of the lactation, respectively. Low heritability magnitudes showed that there is a low genetic variation for FPR trait which is suggesting much more effects of environmental factors.

 Cows need a lot of energy to produce milk in early lactation. Due to the low dry matter intake in this period, it is necessary to increase diet energy concentration. Therefore, fat supplements are often used to increase the concentration of metabolizable energy for reduce mobilization of adipose tissue in fresh cows. Many studies shown that adding fat to diet of lactating cows, improves milk production and increases lactation persistency. Increasing milk yield by 2 to 10 percent was reported in cows receiving fat supplement compared to control. One of the limitations of using fat supplements for ruminant is its negative effects on digestion of fiber. In some studies, using of unprotected fat sources reduced digestibility of fibers and milk fat percentage in early lactation. In contrast, some researchers have reported that adding protected fats to the diet of lactating cows increased milk production and had not negative effect on milk fat. The reason for this was minimum effect of protected fat on ruminal fermentation. Usual protected fats include crystalline or prilled fatty acids, formaldehyde treated protein encapsulated fatty acids, hydrogenated lipids, fatty acyl amides and calcium salts of fatty acids. Calcium salts of fatty acids are lower degradable than other fat sources in rumen. More studies should be done because of the low production of calcium salts of fatty acids in Iran and as well as the demand for better quality of fat supplements.

Materials and Methods :

Twenty one Holstein cows were used under days in milk 30±8.5 with body weight 573 ± 69.4. The cows were divided into three groups (3primiparous and 4 multiparous) and were offered following rations for 100 days period:1- control (without fat supplementation), 2- ration containing fat supplement A (laboratory made for this research in Bu-Ali Sina University), 3- ration containing fat supplement B (Persia fat, Kimia Danesh Alvand Co, Tehran, Iran). Diets were designed to be iso-nitrogenous. After morning milking and before feeding, cows were weighed and body scored in 30, 70 and 100 days in milk. The cows were milked three times daily. The TMR was fed at 0530, 1430 and 2230hours daily. Feed intake and milk yield were recorded daily and weekly sampling was performed to determine milk, feed and feces compositions. Milk samples were analyzed for protein, fat and lactose. Feed and feces samples were analyzed for DM, Ash, CP, ether extract and ADF. Digestibility of ration nutrients was determined using acid insoluble ash as an indigestible marker. Blood samples were withdrawn on 45, 70 and 100 days in milk. Blood samples then were centrifuged at 4 ºC and 3000×g for 15 minutes. Then plasma was analyzed for glucose, cholesterol, triglyceride and non-esterified fatty acids. At the end of the experiment milk samples were collected to determine milk fatty acids profile. The fatty acids were determined using a direct method for fatty acid methyl ester synthesis using a gas chromatograph. Data were analyzed as a completely randomized design using the MIXED procedure of SAS.    

 in this study using fat supplements had not effect on BCS. Dry matter intake was not affected by diets. Milk production were higher in cows receiving fat supplement A than control while was not different compared to fat supplement B. milk production increased significantly after two weeks. During the treatment period, control increased milk fat percentage. Milk fat increasing was started in second week of experiment. The amount of milk lactose increased due to the milk production increasing in cows receiving fat supplement compared to control. FCM was not different between treatments. In this study, fat supplement A and B increased blood cholesterol. Amount of triglyceride increased but was not significant. NEFA and glucose were not affected by diets. C14:0, C14:1 and C18:2 were influenced by rations. Percent of C8:0 was higher in control than other treatments by 16 percent, it was not significant. Percent of C18:1 was higher in cows receiving fat supplement A and B than control, but was not significant. Rations had not affected on nutrients digestibility.

 according to the results, fat supplement A can be used as fat source in early lactation.

The effect yeast on performance and blood metabolites of cows with paratuberculosis (Johne’s disease) The purpose of this study was to evaluate the effect of dietary supplementation of yeast SCAY-3PLUS on health and productivity of dairy cows infected by Mycobacterium avium subspecies paratuberculosis (Johne's disease). Multiparous Holstein dairy cows (129±24 DIM) with clinical Johne's disease assigned equally into control and yeast group. Cows in yeast group (n=10) received yeast in the diet for 20 days, while cows in the control group (n=10) did not receive the yeast. Dry matter intake and changes in BCS as well as milk production and composition were not affected by the experimental diets (P> 0.05). Rectal temperature and serum concentrations of cholesterol, triglycerides and β- Hydroxy butyrate were not affected by the treatment (P> 0.05). Dietary supplementation of the yeast increased significantly the manure score in infected cows (p < 0.05). The average antibody titer changes (ELISA) for the control and yeast group were -19/74 and - 53/6 respectively, and the yeast treatment reduced the antibody titer of Johne's disease in infected cows. In conclusion, dietary supplementation of the yeast, used as a probiotic, was therapeutic for adult paratuberculosis cows, and is useful to improve manure score and antibody titer changes in cows with paratuberculosis.

The aim of this study was the comparison of two protocols of estrus synchronization in two natural climates and heat stress condition on reproductive performance and concentration of plasma estrogen and progesterone hormones in Holstein dairy cows. One hundred and ten multiparous Holstein dairy cows (28 kg average daily milk yield and parity one to four calved) were randomly assigned to two protocolgroups: 1) Double-Ovsynch (DO; n=60), the cows received GnRH-7d-PGF2α-2d-GnRH and Ovsynch (GnRH-7d- PGF2α-56h-GnRH-16h- AI) was initiated 7 d later; 2) Presynch-Ovsynch (PO; n=50), the cows received PGF2α-14d-PGF2α and Ovsynch was initiated 12 d later. The both of the protocols were done in two seasons of summer and winter. The calving rate in cows that were synchronized at winter season was greater than cows synchronized in summer (36.4 vs 18.2%; P= 0.04). Mean of the number of insemination to conception was lower in cows that synchronized in winter compared to cows synchronized in summer (1.46 vs 1.74; P= 0.02). Mean of measured estrogen and progesterone hormones concentrations was higher in cows that synchronized in winter compared to summer (P < 0.05). Overall, mean of reproductive traits and hormones concentration is higher in cows that synchronized in winter than in summer and the protocol of estrus synchronization had no effect on reproductive performance.

The aim of this study was to investigate the effect of different levels of live yeast on ruminal function and health of dairy cows fed diets containing low and high concentrations of non-fiber carbohydrates (NFC). In this experiment, six cannulated dairy cows were randomly assigned in a Latin square design with six periods (14-days) and six treatments including 1- diet contain low NFC free of live yeast, 2-diet contain low NFC with 5 g/d of live yeast, 3-diet contain low NFC with 10 g/d of live yeast, 4-diet contain high NFC free of live yeast, 5-diet contain high NFC with 5 g/d of live yeast and 6-diet contain high NFC with 10 g/d of live yeast. Dry matter intake, rumination, ruminalparameters and blood metabolites were determined in the different periods. Dry matter intake, rumination activity, nutrient digestibility, mean ruminal pH and temperature were not affected by treatments. General and plasma indicators of animal healthwere also not affected by treatments. Overall, the results of this experiment indicated that dietary supplementation with live yeasthad no significant effect on rumen function and health in cows fed diets containing different concentrations of NFC.

The aim of this study was to identify the factors affecting the culling of dairy cows and their impact on reproductive performance and costs of the herd so that optimal decisions can be made in replacing dairy cows and thereby increase the annual income of dairy cattle. For this purpose, data collected from four active cattle breeding units in Ardabil province (including biological parameters and financial information of herds) during the years 2017 to 2018 were used. To simulate the herd status under different conditions, a bio-economic model developed in Dairy VIP software was used, and the MATLAB software compecon toolbox was optimized for production system. Dynamic programming was used to determine the optimal replacement strategy. This planning is a mathematical approach that is suitable for solving problems with several successive decision steps. Dairy cattle were described with state variables including lactation period, milk production capacity and different animal health states. The average annual milk yield and forced removal rate were 13480 kg and 16.1%, respectively. According to the observed results, the highest total annual culling rate occurred when the rate of pregnancy of productive animal decreased by 5%. The major effective changes in economic performance due to the reduction in the rate of forced culling was related to the reduction in the cost of purchasing alternative heifers. The average herd optimal life (interval between first calving to removal) was obtained for the baseline scenario of 4.99 years. The optimal annual replacement rate, which is equal to the sum of the optional and non-optional elimination rates, was 20% for the baseline scenario in this study. So that culling of dairy cows older than the optimum age leads to increased profitability of livestock units. The results of the dynamic programming model also showed that optimal maintenance for medium and high-yielding cows is equal to seven and eight lactation periods. The results of this study can help producers to identify important factors in annual herd profitability and to make sound management decisions to improve economic profit.

Inbreeding, which has been defined as the mating between relative animals, leads to increase homozygous genotypes and decrease heterozygous genotypes in a population. As a result, the progenies of such mating are inbred (Wakchaure and Genguly 2015). Reduction of the traits associated with physiological efficiency and reproductive potential are the most important impacts of inbreeding in the farm animals (Filho et al. 2015, Fleming et al. 2018). Traits in livestock have different heritabilities suggesting that they are not influenced by inbreeding in a similar pattern and that although animals’ fitness is generally deteriorated; the magnitude of inbreeding depends on the type of the trait (Roff 1998; Derose and Roff, 1999, Wright et al. 2008, Mikkelsen et al. 2010). Until now, all studies regarding effects of inbreeding on productive and reproductive traits of dairy cows have been focused on using the statistical models in which inbreeding coefficient was included as covariable (Behmaram et al. 2017) or as the classified variable (Amirzadeh 2012). As inbreeding coefficient is defined as a covariable in the model, only a regression coefficient is estimated describing average changes of the trait per increasing / decreasing inbreeding coefficient. As a matter of fact, inbreeding may unequally influence the shape of distribution of the trait. Based on this assumption, this research aimed to estimate inbreeding effects on some productive and reproductive traits of Iranian dairy cows using Quantile regression statistical method.     

The data set was provided by Animal Breeding Centre, Iran. Foxpro (version 2.6) and UEStudio (version 09) software were utilized for editing initial data. Final data consisted of 580,802 records belonging to 580,802 first-parity cows distributed in 1,185 herds (over 20 provinces of the country) and calved between years 1991 and 2015. The traits under consideration were lactation milk yield (TMILK), 305d, 2X milk yield (MILK3052X), average daily milk yield (ADM), lactation length (LL), and age at the first calving (AFC). The average of the traits in the final data set was 9,447 Kg, 7,792 Kg, 30 Kg, 315 d and 25.6 m, respectively. Holstein gene percentage (HGP) of the cows in the pedigree file was set to be in the range of 50 to 100 and AFC of the cows was set to be between 18 and 48 months. Inbreeding coefficient (IC) of individual animals was calculated by CFC software (Sargolzaei et al. 2006). Fitting a series of the Quantile regression models was conducted with the use of SAS (version 9.4) software. Quantile regression, which was introduced by Koenker and Bassett (1978), extends the regression model to conditional quantiles of the response variable, such as the 90th percentile. Quantile regression is particularly useful when the rate of change in the conditional Quantile, expressed by the regression coefficients, depends on the Quantile (Chen 2005). In all the models used in this research, fixed effects of province, year and month of calving, as well as linear co-variables of HGP, IC and AFC (except of the model for AFC as the trait) were included. For TMILK, lactation length was also included as linear co-variable. Moreover, in addition to the quantile models and for the sake of estimating usual regression coefficient, general linear model (GLM) was also fitted for each trait in which a single regression coefficient of the trait on IC was defined. Ordinary least-squares regression can be used to estimate conditional percentiles by making a distributional assumption such as normality for the error term in the model. The main advantage of Quantile regression over ordinary least-squares regression is its flexibility for modeling data with heterogeneous conditional distributions (Chen 2005).      

Based upon the analysis of main pedigree file, the total number of animals was 1,941,871 (16,169 sires and 895,376 dams) among which the number of base and non-base animals were 246,388 (3,936 sires and 120,287 dams) and 1,695483 (12,233 sires and 775,089 dams), respectively.Total number of inbred animals in the pedigree was 1,211,343. Average IC for total as well as inbred animals was found to be 0.9149% (minimum 0% and maximum 47.02%) and 1.4651% (minimum 0.00038% and maximum 47.02%), respectively. For the cows with records for all five traits, IC ranged from 0 to 38.45% with the average of 1.13% (SD=1.63%). Estimate of annual change of IC was found to be 0.017 (SE=0.005), which was statistically significant (P<0.01) indicating that there is a positive increase of inbreeding in Iranian dairy cows’ population over the time. Within each trait, different Quantiles were unequally influenced as animal’s IC increased. Vast majority of the estimated regression coefficients in different Quantiles were statistically significant (P<0.05). Based upon fitting Quantile regression model and the average estimated regression coefficients, it was found that TMILK, MILK3052X, ADM, LL, and AFC changed -5.5 (Kg), -2.6 (Kg), -18 (g), 0.35 (d) and 0.30 (d), respectively as the IC of the animal increased by 1%. Estimated simple regression coefficients based on fitting GLM models were found to be -9.83 Kg (SE=1.332 Kg), -6.9 Kg (SE=0.169 Kg), -32 gram (SE=4.2 gram), 0.2087 d (SE=0.08234 d) and 0.0158 m (SE=0.0024 m), respectively and all were statistically significant (P<0.05).     

This research indicated that different Quantiles of some productive and reproductive traits of Iranian dairy cows are not equally affected by inbreeding phenomenon suggesting that Quantile regression models are needed to be utilized in the future research for evaluating the impacts of inbreeding on the other traits, which are of great economic importance.

Eighty multiparous lactating dairy cows averaging days in milk 35-d were allocated in two separate experimental diet (Glucogenic vs. Lipogenic) in a changeover design. The performance, blood metabolites, liver enzymes and insulin were evaluated. The study lasted 44 days in two 22 days periods with the first 17 d as adaptation period and the last 5 days as sample collection period. The results show that neither dry matter intake nor milk yield were affected with treatments (P > 0.05). However, the cows received the lipogenic diet showed to have greater milk fat content, and cows received glucogenic diet showed to have greater milk protein content. Regarding the blood metabolites results show that blood glucose was tended to be greater in glucogenic diet (P = 0.08). Howevere triglyceride and blood urea concentrations were constant between two treatments. The concentrations for BHB (P = 0.04) as well as cholesterol (P= 0.05) were increased in lipogenic diet fed dairy cows. The insulin concentration was increased significantly in lipogenic diet fed cows (P = 0.02). The results show that regardless the improvement in glucose as well as BHB concentration in blood of dairy cows fed with glucogenic diet, howevere fat corrected milk as well as milk energy output were improved for lipogenic diet. In addition increased insulin and cholesterol in dairy cows fed higher fat content has potential to improve dairy cow’s fertility. In conclusion based on our results the lipogenic diet may be recommendable for dairy cows fed high RUP level.

Thirty multiparous Holstein dairy cows used to aim the investigation of the effects of zinc from different sources on bioavailability, production performance, and digestibility. Dairy cows in a complete randomized design randomly allocated to one of five dietary treatments that consist of 1) control (no supplement Zn), 2) Zn glycine complex (ZnGly), 3) Zn Hydroxychloride (ZnHcl), 4) Zn oxide (ZnO), 5) Zn sulfate (ZnSO4). The result indicated that different sources of zinc had not affected glucose, cholesterol and triglyceride (P>0.10). The used of different sources of zinc significantly increased of serum zinc to compare control (P<0.010).  Results showed that, BCS, milk, energy-corrected milk, fat-corrected milk yield and milk yield composition in dairy cows were not significantly affected by Zn source (P>0.10). Somatic cell count tended to decrease in ZnGly (P=0.096) and ZnHcl (P=0.073) in compare of control group. Dry matter intake was not different between treatment (P>0.10). Daily zinc intake, fecal zinc, the zinc concentration in milk per liter/or day, the zinc concentration in milk per liter/or day, apparent absorption and retention of zinc significantly were higher in zinc supplemented group in compare of control (P<0.010). Also, the used of different sources of zinc had not significantly affected on digestibility of dry matter, organic matter, and Ash (P>0.10). Therefore, the results of this study suggested that used of zinc sources in dairy cows diet ZnGly and ZnHcl have higher bioavailability than inorganic sources of zinc and also might improve milk quality throw decrease of somatic cell count.

The aim was to determine the effect of different dietary n-6/n-3 fatty acid (FA) ratio during the postpartum period on plasma haptoglobin, metabolic profile, and insulin resistance in Holstein dairy cows. 24 multiparous cows were randomly assigned to three treatments with a ratio of omega-6 fatty acids to omega-3: 2.5 to 1 (low ratio); 4.5 to 1 (average ratio); and 6.5 to 1 (high ratio) were distributed. Blood samples were collected on d 7, 14, 28, 42, 56 and 70 postpartum to determine blood metabolites and haptoglobin concentrations. Intravenous glucose tolerance tests and insulin challenges were performed on d 28 and 42 of experiment. Plasma concentrations of haptoglobin were significantly higher in the cows fed with high ratio than the other two treatments. The 42-day postpartum results of insulin challenge test indicates that the change in the ratio of fatty acids to moderate treatment causes an increase in the clearance rate and a decrease in the area under the curve of the insulin. The results of this study indicate that the moderate ratio of omega-6 to omega-3 fatty acids in dairy cows decreases insulin resistance by reducing inflammatory factors.