Dairy Cow Breeding Research Articles

MicroRNA-106b Regulates Milk Fat Metabolism via ATP Binding Cassette Subfamily A Member 1 ( ABCA1) in Bovine Mammary Epithelial Cells.

Research on the mechanisms that regulate milk fat synthesis in dairy cows is essential to identify potential molecular targets that in the long term can help develop appropriate molecular breeding programs. Although some studies have revealed that microRNA (miRNA) affect lipid metabolism by targeting specific genes, joint analysis of miRNA and target mRNA data from bovine mammary tissue has revealed few clues regarding the underlying mechanisms controlling milk fat synthesis. The objective of the present study was to use high-throughput sequencing and bioinformatics analysis to identify miRNA and mRNA pairs and explore further their potential roles in regulating milk fat synthesis. A total of 233 pairs of negatively associated miRNA and mRNA pairs were detected. Among those, there were 162 pairs in which the miRNAs were down-regulated and the target mRNAs were up-regulated. Among the identified miRNA, miR-106b can bind the 3'-UTR of the ATP binding cassette subfamily A member 1 ( ABCA1), a gene previously identified as having a positive association with bovine milk fat synthesis. The overexpression of miR-106b in bovine mammary epithelial cells caused a decrease in triglyceride and cholesterol content while the inhibition of miR-106b increased triglyceride and cholesterol content, confirming its role in lipid metabolism. The present study allowed for the construction of a miR-106b- ABCA1 regulatory network map, thus providing a theoretical basis to target this gene in the molecular breeding of dairy cows.

Analysis of the genetic architecture of energy balance and its major determinants dry matter intake and energy-corrected milk yield in primiparous Holstein cows

The focus of modern dairy cow breeding programs has shifted from being mainly yield based toward balanced goals that increasingly consider functional traits such as fertility, metabolic stability, and longevity. To improve these traits, a less pronounced energy deficit postpartum is considered a key challenge. On the other hand, feed efficiency and methane emissions are gaining importance, possibly leading to conflicts in the design of breeding goals. Dry matter intake (DMI) is one of the major determinants of energy balance (EB), and recently some efforts were undertaken to include DMI in genomic breeding programs. However, there is not yet a consensus on how this should be achieved as there are different goals in the course of lactation (i.e., reducing energy deficit postpartum vs. subsequently improving feed efficiency). Thus, the aim of this study was to gain more insight into the genetic architecture of energy metabolism across lactation by genetically dissecting EB and its major determinants DMI and energy-corrected milk (ECM) yield at different lactation stages applying random regression methodology and univariate and multivariate genomic analyses to data from 1,174 primiparous Holstein cows. Daily heritability estimates ranged from 0.29 to 0.49, 0.26 to 0.37, and 0.58 to 0.68 for EB, DMI, and ECM, respectively, across the first 180 d in milk (DIM). Genetic correlations between ECM and DMI were positive, ranging from 0.09 (DIM 11) to 0.36 (DIM 180). However, ECM and EB were negatively correlated (rg = -0.26 to -0.59). The strongest relationship was found at the onset of lactation, indicating that selection for increased milk yield at this stage will result in a more severe energy deficit postpartum. The results also indicate that EB is more affected by DMI (rg = 0.71 to 0.81) than by its other major determinant, ECM. Thus, breeding for a higher DMI in early lactation seems to be a promising strategy to improve the energy status of dairy cows. We found evidence that genetic regulation of energy homeostasis is complex, with trait- and lactation stage-specific quantitative trait loci suggesting that the trajectories of the analyzed traits can be optimized as mentioned above. Especially from the multivariate genomic analyses, we were able to draw some conclusions on the mechanisms involved and identified the genes encoding fumarate hydratase and adiponectin as highly promising candidates for EB, which will be further analyzed.

Potential of milk mid-IR spectra to predict metabolic status of cows through blood components and an innovative clustering approach

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

Theoretical Unification and Practical Integration of Conventional Methods and Genomic Selection in Plant Breeding

Following successful application in dairy cow breeding, genomic selection (GS) has become a hot topic among plant geneticists and breeders. GS and conventional methods have the same goal of identifying best genotypes for a given crop and region, and should follow the same principles, particularly in dealing with genotype-by-environment (GE). Dealing with GE includes dividing a target region into meaningful mega-environments (MEs) based on repeatable GE patterns and then selecting for each ME. This requires different GS models be developed for different MEs. Selection for each ME requires testing at multiple locations for multiple years to account for the unrepeatable GE in the ME and to estimate the genetic main effect, GP. For a ME with large GE, multiple and diverse cultivars should be selected and recommended. The number of locations, years, and replications within trials required to achieve a certain level of heritability (i.e., selection reliability) for a trait (e.g., yield) can be estimated from existing multi-location, multiyear variety trial data. Instead of direct selection for GP, conventional selections have to resort to indirect selection, negative selection (culling), and a lengthy breeding cycle. GS offers the possibility for direct selection and positive selection for GP and thereby overcoming random GE and shortening the breeding cycle. To achieve this, GS models must be able to predict GP for a breeding population and its prediction accuracy should be measured by r(GM,GP), GM being GS predicted breeding values. This definition of prediction accuracy is the essential connection between GS and phenotype-based selection. This implies that GS models must be developed and evaluated using phenotypic data from multiple locations and multiple years representing the target ME. Using a single training population for model development and a different population for model evaluation will allow estimation of r(GM,GP), but it can be costly and may have limited relevance to a breeding program. A pragmatic GS framework was proposed in this paper, which is to use data from yearly preliminary yield trials for model development, in which a large number of new breeding lines are tested at several locations. A GS model can be developed for each training population-by-trial (location-year) combination, and all available GS models can be used to make predictions, leading to a genotype-by-model two-way table of predictions for the current-year’s breeding population. This table can then be analyzed the way a breeder would do to a genotype-by-environment two-way table of a trait to make selection decisions. This table can also be used to evaluate and select models as a breeder would do for their test environments. Instead of r(GM,GP), “rate of success”, defined as the inverse of the number of genotypes that have to go through yield trials in order to identify a new cultivar, can be used to measure the prediction accuracy of GS. The prediction accuracy or rate of success determines the best pathway to integrate GS into a practical breeding program. GS prediction accuracy is expected to improve with time as more GS models are developed and as the breeding populations and the target ME are better represented in the GS models. A real multi-location, multi-year oat (Avena saliva L.) variety trial dataset and a practical oat breeding program were used to facilitate the discussions

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Growth, productive performance, and udder health of crossbred Holstein x Simmental cows and purebred Holstein cows

The crossbreeding between dairy cow breeds has been used as an alternative to improve some characteristics such as milk composition, udder health, and reproductive aspects on dairy herds. The aim was to compare growth, milk yield and composition, and mammary gland health of crossbred Holstein x Simmental and purebred Holstein cows. Data were gathered from a farm located in Santa Catarina state, south of Brazil. Cow growth was assessed by weighing calves and heifers monthly. Yet for milk yield and udder health, data were taken from records of the official Dairy Herd Improvement Program carried out in the evaluated farm. These data were subjected to variance analysis using the MIXED procedure of SAS statistical software. Non-linear regressions were used to adjust the data to the growth curves. The crossbred Holstein x Simmental cows produced more milk than did purebreds (31.8 kg/day vs. 30.4 kg/day; p < 0.05), with higher contents of lactose (4.63% vs. 4.53%) and protein (3.14% vs. 3.03%), but no differences in fat content (3.00 vs. 2.96). Purebred cows had higher somatic cell score (SCS) 4.49 vs. 2.93 (P < 0.0001). Furthermore, no differences were found for the growth of calves and heifers. In conclusion, crossbred Holstein x Simmental cows have higher energy corrected milk as the Holstein ones, whit greater uncorrected milk yield only for cows with three or more lactations. Crossbreeds cows produce milk with better quality, indicated by lower SCS and higher solids content, besides showing a lower SCS and no differences regarding weight gain of calves and heifers.

Study on the Detection of Dairy Cows’ Self-Protective Behaviors Based on Vision Analysis

The study of the self-protective behaviors of dairy cows suffering dipteral insect infestation is important for evaluating the breeding environment and cows’ selective breeding. The current practices for measuring diary cows’ self-protective behaviors are mostly by human observation, which is not only tedious but also inefficient and inaccurate. In this paper, we develop an automatic monitoring system based on video analysis. First, an improved optical flow tracking algorithm based on Shi-Tomasi corner detection is presented. By combining the morphological features of head, leg, and tail movements, this method effectively reduces the number of Shi-Tomasi points, eliminates interference from background movement, reduces the computational complexity of the algorithm, and improves detection accuracy. The detection algorithm is used to calculate the number of tail, leg, and head movements by using an artificial neural network. The accuracy range of the tail and head reached [0.88, 1] and the recall rate was [0.87, 1]. The method proposed in this paper which provides objective measurements can help researchers to more effectively analyze dairy cows’ self-protective behaviors and the living environment in the process of dairy cow breeding and management.

Multi-country investigation of factors influencing breeding decisions by smallholder dairy farmers in sub-Saharan Africa

Artificial insemination (AI) and selective bull mating are considered as robust methods for dairy cattle breeding. Globally, these methods have been used to enhance productivity and realize rapid genetic gains. However, these technologies have had low adoption rates in sub-Saharan Africa (SSA). Even though available evidence suggests that this is due to various infrastructural and technical challenges. There is limited information about what drives this low uptake of AI from a farmer’s perspective. Therefore, the main objective of this study was to determine and characterize factors that influence the choice by smallholder farmers between bull service and AI for dairy cow breeding. Further, the relationships between the breeding choices and the bio-physical elements of dairy farming, mainly, farmer characteristics, household income levels, farm management practices, and institutional support structures, were investigated. Data were collected through face-to-face interviews from a total of 16,308 small-scale dairy farmers in Ethiopia (n = 4679), Kenya (n = 5278), Tanzania (n = 3500), and Uganda (n = 2851). The questionnaire was coded in an electronic form using Open Data Kit (ODK) platform to allow for real-time data entry and management. Descriptive statistics, chi-square test, and a t-test were used to evaluate the independent and dependent variables, while logistic regression and factor analysis were used to identify factors that influenced farmers’ breeding decisions. Results showed that there was a significant difference in animal husbandry practices between farmers who used artificial insemination (AI) and those who practiced bull mating. The majority of farmers who used AI kept records, purchased more animal feeds, had more labor by hiring workers whose average wages were higher than those of bull service farmers. However, farmers who used AI pay more for services such as water access and breeding while their service providers had to cover long distances compared to farmers who used bulls. This indicates limited access to services and service providers for AI farmers. The ratio of AI to bull service users was even for Ethiopia and Kenya, while in Uganda and Tanzania, more farmers preferred bull service to AI. It was established that the factors that influence farmers’ breeding decision were not the same across the region. Factors such as farmer’s experience in dairy farming, influence of the neighbor, farmer’s ability to keep records, and management practices such as water provision and availability of feeds had a significant association (p < 0.001) with AI adoption among dairy farmers. In contrast, large herd and large land size negatively influenced AI adoption. Institutional settings including cost of AI service and the distance covered by the service provider negatively affected (p < 0.001) the choice of AI as a breeding option. There was a high probability of continued use of a specific breeding method when there was a previous conception success with that same method. Based on the results obtained, we recommend that improvement of institutional settings such as the availability of AI service providers, as well as better access to services such as water, animal feed, and animal health provision, be treated as critical components to focus on for enhanced AI adoption. Most importantly, there is a need to avail training opportunities to equip farmers with the necessary skills for best farm management practices such as record keeping, proper feeding, and selective breeding.

Expression profiling of peripheral blood miRNA using RNAseq technology in dairy cows with Escherichia coli-induced mastitis

E. coli is the main causative agent of mastitis in dairy cows, but the mechanism of molecular regulation underlying the occurrence and development of mastitis has not yet been fully elucidated. In this study, an E. coli-induced mastitis model was created and RNASeq technology was used to measure the miRNA expression profiles at different times post-infection (0, 1, 3, 5, 7 dpi), as well as to screen for differentially expressed miRNA. The results show detection of 2416 miRNAs, including 628 known miRNAs and 1788 newly discovered miRNAs. A total of 200 differentially expressed miRNAs were found at different time points. Bioinformatics analysis showed that these differentially expressed miRNAs may regulate the occurrence and development of mastitis in dairy cows through seven signal transduction pathways, namely cytokine-cytokine receptor interaction, MAPK signaling pathway, chemokine signaling pathway, leukocyte transendothelial migration, T cell receptor signaling pathway, Toll-like receptor signaling pathway, and cell adhesion molecules. In addition, bta-miR-200a, bta-miR-205, bta-miR-122, bta-miR-182 and the newly discovered conservative_15_7229 might be involved in immune process in late stage of E. coli-induced mastitis. The results of this study lay the foundation for molecular network analysis of mastitis and molecular breeding of dairy cows.

Sinusoidal function to describe the growth curve of dairy heifers

The objective of the present study is to introduce a sinusoidal function into dairy research and production by applying it to bodyweight records (from 1 to 24 months) from six dairy cow breeds reported by the Dairy Heifer Evaluation Project of Penn State Extension (USA) from 1991 to 1992. The function was evaluated with regard to its ability to describe the relationship between bodyweight and age in dairy heifers, and then compared with seven standard growth functions, namely monomolecular, logistic, Gompertz, von Bertalanffy, Richards, Schumacher and Morgan. The models were fitted to monthly bodyweight records of dairy heifers using non-linear regression to derive estimates of the parameters of each function. The models were tested for goodness of fit by using adjusted coefficient of determination, root mean square error, Akaike’s information criterion and Bayesian information criterion. Values of adjusted coefficient of determination were generally high for all models, suggesting the generally appropriate fit of the models to the data. The sinusoidal function provided the best fit of the growth curves for Brown Swiss, Guernsey and Milking Shorthorn breeds due to the lowest values of root mean square error, Akaike’s information criterion and Bayesian information criterion. According to the chosen statistical criteria, the Richards function provided the best fit for Ayrshire heifers, and the monomolecular the best for Holstein and Jersey. The least accurate estimates were obtained with the logistic. In conclusion, the sinusoidal function introduced here can be considered as an appropriate alternative to standard growth functions when modelling growth patterns in dairy heifers.

The Slaughtening Causes with Dental and Gingival Lesions in Dairy Cows within Postmortem Period

Background: A regular and balanced feeding is essential for the animals in order to maintain their normal physiological function and be productive at the desired level. Digestion activities start with chewing in the mouth and the healthy dental arch is needed to perform a complete chewing function. Abnormal dental development and other dental pathologies impair digestive functions by negatively affecting chewing functions. The aim of the present study was to classified dental anomalies, dental degenerations, dental and gingival lesions seen in dairy cows and was aimed to reveal these lesions and depending on these disorders the reasons for slaughtering in dairy cows.Materials, Methods &amp; Results: The material of this study consists of 600 dairy cows, being slaughtered for a year, and 170 dairy cows, detected dental anomalies, dental degenerations and dental-gingival lesions in the postmortem examination. Detailed macroscopic and radiological examinations of mandibles and maxillae of the dairy cows with dental and gingival lesions in postmortem examination were performed. The detailed information of the cases, such as: age, race, breeding, living region and slaughtering causes, etc. of dairy cows, suffering from dental lesions was recorded from slaughterhouse data access. In this study, 87 cases (51.18%) of the determined dental lesions were defined as dental degeneration, 34 cases (20%) as caries, 30 cases (17.64%) as dental abnormalities in the formation and dental arch and 19 cases (11.18%) as periodontal inflammation.Discussion: In dairy cow breeding, there is a close relationship between production costs and business profitability and animal disease and fertility problems. Although the existence of negative effects of dental lesions directly on the digestive functions is known in dairy cattle breeding; there was no study about the state of dental diseases in dairy cow. In this respect, this research is quite important both for revealing the proportion of dental diseases seen in dairy cow and for drawing attention to the relationship between these diseases and the reasons for slaughtering of dairy cow. In this study, various dental anomalies, dental degenerations, dental and gingival lesions (28.33%) were detected in 170 dairy cows; The decreased milk production in 38 cases (22.35%), infertility in 65 cases (38.24%), gastrointestinal system diseases such as abomasal dislocation, constipation and indigestion in 38 cases (22.35%), foot diseases in 19 cases (11.18%) and economic reasons in 10 cases (5.88%) were determined as slaughtering reasons of the cases. The results of this research indicate that dental and gingival lesions may be regarded as preliminary results in the development of digestive system diseases, and then the various detailed clinical studies are needed to determine whether there is a relationship between digestive system diseases and dental diseases. As a result; this study first classified the dental lesions determined after slaughter in cattle and revealed the relationship between the reasons for slaughtering of dairy cows of the determined dental lesions. The results obtained in this study showed that dental anomalies, caries and periodontal inflammation effect significantly on the dairy cow fertility.

Genetic variants of fatty acid elongase 6 in Chinese Holstein cow

In the dairy industry, genetic variants have contributed to the improvement of milk production traits. Fatty acid elongase 6 (ELOVL6), which elongates saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs), plays a distinct role in the balance of long-chain fatty acids composition in animals. ELOVL6 catalyzes the elongation of palmitic acids (C16:0) which is the most common saturated fatty acid found in animals and also an essential precursor to synthesize other long-chain fatty acids. However, the genetic variant research of bovine ELOVL6 on milk quality traits is still unknown. Therefore, our study aimed to detect the single nucleotide polymorphism (SNPs) of bovine ELOVL6 and explored the relationship between SNPs and milk quality traits including milk yield, fat content, protein content and somatic cell score. In this study, three SNPs, including SNP1 (g16379651A>G), SNP2 (g16458976A>G) and SNP3 (g16511290A>G), have been identified in intron 3 and 3′UTR regions of ELOVL6 in Chinese Holstein (CH) cows. Besides, the results of genetic diversity analysis, linkage disequilibrium and haplotype analysis indicated that these SNPs presented moderate polymorphisms which reflected relatively high genetic diversity. No strong linkage among these SNPs were detected in sampled population of cows. Moreover, the results of correlation analyses demonstrated that these SNPs of bovine ELOVL6 were significantly related to milk yield (P < 0.05). The SNP1 was also correlated with somatic cell score, whereas the SNP3 was associated with fat content. The 21 combined genotypes (diplotypes) were highly significantly correlated (P < 0.01) with milk yield. These results revealed that the genetic variants of bovine ELOVL6 influenced the milk production of CH cows. Hence, the three SNPs could be regarded as molecular markers in marker-assisted selection (MAS) of the dairy cow breeding.

Variability in Biochemical Composition of Milk Among Three Representative Breeds of Dairy Cows from Romania

Variability in Biochemical Composition of Milk Among Three Representative Breeds of Dairy Cows from Romania

Productive longevity of cows of dairy breeds depending on the duration of their first service period

Recently, in the breeding and commodity farms of our country can be observed a rapid decrease in the duration of productive use dairy cattle. A considerable amount of scientific researches are conducted on the effects of hereditary and environmental factors on productive indicators longevity, researches are done on various ways to increase durability productive use of dairy cattle. In this aspect, reproductive ability of cows is important, which must be taken into account while individual estimation for the next selection of the most valuable animals that combine high milk productivity with high fertility. Therefore, the goal of our research was to study the productive longevity of dairy cows depending on the duration of their first service period and find the optimal duration of this indicator for a particular breed. The research was carried out on cows of Holstein, Ukrainian Black-and-White and Red-and-White breeds. Retrospective analysis of duration and the effectiveness of life-time use of cows was carried out according to the method Yu P. Polupan (2010). It was found that average duration of the first service-period of cows was 167.7 days on the studied Holstein populations, 180.3 – on the Ukrainian Black-and-White and Ukrainian Red-and-White – 142.1 days. The longest duration of life, productive use, lactations and the highest milk yields had cows with the duration of the first service period of 121–150 days among the Holstein breed, 151–180 – Ukrainian Black-and-White and 91–120 days and Ukrainian Red-and-White. The worst, by the indicators of productive longevity, were individuals with 60 days and no more of the first service period. Correlation analysis showed the different level of the connection between the duration of the service period animals and indicators of their lifelong use, which in most cases had a reverse nature. This kind of connection indicates that with the extension of the duration of service period of cows, the duration of their productive use and lifetime productivity decreases. In Holstein breed animals, the correlation coefficients between the above named indicators ranged from -0.462 to 0.370, Ukrainian Black-and-White – from -0.113 to 0.144 and Ukrainian Red-and-White – from 0.279 to 0.149. Strength of influence of the duration of the first service-period on life duration, productive use and lactation of cows, depending on the breed, was 12.5–36.5%, for lifetime productivity – 9.7–34.6 and on the one day of life, productive use and lactation – 11.3–35.9%.

Dairy cow breed interacts with stocking rate in temperate pasture-based dairy production systems

Economic optimum stocking rates for grazing dairy systems have been defined by accounting for the pasture production potential of the farm [t of dry matter (DM)/ha], the amount of feed imported from outside the farm (t of DM/ha), and the size of the cow (kg). These variables were combined into the comparative stocking rate [CSR; kg of body weight (BW)/t of feed DM available] measure. However, CSR assumes no effect of cow genetics beyond BW, and there is increasing evidence of within-breed differences in residual feed intake and between-breed differences in the gross efficiency with which cows use metabolizable energy for milk production. A multiyear production system experiment was established to determine whether Jersey (J) and Holstein-Friesian (HF) breeds performed similarly at the same CSR. Fifty-nine J cows and 51 HF cows were randomly allocated to 1 of 2 CSR in a 2 × 2 factorial arrangement; systems were designed to have a CSR of either 80 or 100 kg of BW/t of feed DM (J-CSR80, J-CSR100, HF-CSR80, and HF-CSR100 treatment groups). Data were analyzed for consistency of farmlet response over years using ANOVA procedures, with year and farmlet as fixed effects and the interaction of farmlet with year as a random effect. The collated biological data and financial data extracted from a national economic database were used to model the financial performance for the different breed and CSR treatments. On average, annual and individual season pasture DM production was greater for the J farmlets and was less in the CSR100 treatment; however, the effect of CSR was primarily driven by a large decline in pasture DM production in the HF-CSR100 treatment (breed × CSR interaction). This interaction in feed availability resulted in a breed × CSR interaction for the per-cow and per-hectare milk production variables, with HF cows producing more milk and milk components per cow in the CSR80 treatment but the same amount as the J cows in the CSR100 treatment. On a per-hectare basis, HF cows produced the same amount of 4% fat-corrected milk and lactose as J cows in the CSR80 treatment, but less fat; at CSR100, J cows produced more 4% fat-corrected milk, fat, and protein per hectare than HF cows. Our results support a greater gross efficiency for use of metabolizable energy by the J cow; 11% less total metabolizable energy was required to produce 1 kg of fat and protein at a system level. Economic modeling indicated that profitability of both breeds was less at CSR100, but the decline in profitability with increasing stocking rate was much greater in the HF breed. Holstein-Friesian cows were more profitable at CSR80 but were less profitable at CSR100.

The effect of dairy cow breed on milk production, cow traffic and milking characteristics in a pasture-based automatic milking system

Despite the increasing frequency of integrated automatic milking (AM) and pasture-based systems, there is limited knowledge available on the suitability of different dairy cow breeds to these systems. Thus, the objective of this experiment was to establish the performance of three breeds in a pasture-based AM system with respect to milk production, cow traffic and milking characteristics. The breeds examined were Holstein Friesian (HF), Jersey x HF (JEX) and Norwegian Red x HF (NRX), all of which have been previously identified as being compatible with conventional milking pasture-based systems. The experiment was conducted in mid-lactation and variables measured included milking frequency, -interval, -outcome and -characteristics, milk yield/milking and per day, wait time/visit and per day, return time/visit and the daily distribution of milking events. Data were statistically analysed using least squares means mixed procedure models, while the proportion of different milking events were analysed using the logistics procedure. While there were no significant differences between breeds for milking frequency, or milk production, significant differences did exist for proportion of successful and failed milkings events, with NRX cows recording the highest and lowest proportions, respectively. JEX also recorded a significantly shorter dead time/quarter at 17.6s/milking compared to the HF and NRX breeds at 28.5 and 27.7s/milking, respectively. Significant differences also existed with regard to cow traffic, with the NRX breed returning from pasture more quickly and waiting a shorter time both per visit and per day in the pre-milking yard. The distribution of milking events differed between the breeds examined, with the JEX cows recording less milkings in the hour after the pre-selection gate changes of 0000h and 1600h. JEX also recorded a significantly greater proportion of milkings than the NRX and HF cows during the hours at which the lowest proportion of total milking events were recorded (0400–0600h). For the optimisation of the AM system it is important to have an even distribution of milkings throughout the day. Based on the evidence from the current experiment, this may be best achieved by a mixed breed herd rather than a single breed herd. However, the performance of the examined breeds should also be analysed in the context of the whole AM farm system, over an entire lactation, taking into consideration the range of variables that contribute to a profitable farm system.

Comparative assessment of feed preparation technologies for Ukrainian breeds of dairy cows

The analysis of variance of the breed's influence on the milk yield in the farms has established that there is no difference between the milk yields of Ukrainian black-and-white dairy breed and Ukrainian red-and-white dairy breed. Influence of breed on milk yields was not significant (P>0.05). Therefore, an assessment of feeding technologies and development of a model for prediction of milk yield were carried out without taking into account the breeds. Average duration of working action, called unloading from the shovel, amounts 6.82±0.43 s without weighing and 14.94±3.61 s with weighing during loading. The measure of influence of the feed unloading type on the duration of that working action η2=0.217 (P<0.001). Coefficient of correlation between number of forage in feed mixture and: total number of working actions of feeder in cycle of feed preparation amounted 0.58 (P<0.01); specific number of working actions of feeder for service 1 cow in cycles of preparing of feeds was 0.41 (P<0.05); expenses of forage loader for servicing 1 cow in cycles of forages loading equaled 0.60 (P<0.05). The mechanisms of influence of ergonomic components' characteristics of preparation, delivery and distribution of feeds on behavior, milk productivity, labor productivity and efficiency of different technological processes were found and formalized. The model of evaluation of expected milk yields at the farm on base of feeding technology characteristics was developed. The model includes the variables: method of feeding of different forms of forages (total mixed / mixed + separately / separately), number of forage types in ration and method of dosage. The model describes 83% of variation of milk yields significantly (P<0.01). Ceteris paribus, the farms, which apply feeding a total mixed rations ad libitum, are capable to get milk yields on 1581-2585 kg higher than farms, which realize feeding technology less rationally.

Адаптаційна здатність корів української червоної молочної породи

Адаптаційна здатність корів української червоної молочної породи

Tongue reshaping: a new surgical method to prevent self-sucking in dairy cows.

Self-sucking behaviors lead to substantial milk loss and inflammation of the udder and teats among dairy cows. Both conservative and surgical approaches are available to prevent such behavior; however, the current methods are limited by variable efficacy and risk of complications. The objective of the present study was to evaluate a new minimally invasive technique for reshaping of the tongue to prevent self-sucking. The current technique was performed on five mixed breed dairy cows aged 4-6 years and with a mean weight 320 kgs. Reshaping of the normal contour of the tongue was achieved by the application of multiple interrupted inverting sutures to the ventral surface to prevent the tongue from forming “U” shape. Post-operative approach included antiseptic mouth wash with povidone iodine solution twice daily and recording the healing process and complications. The mean operative time was 12±1 minutes. No complications except superficial pressure wounds from 3rd up to 10th day post-operative were observed. At three months follow up all treated cows had stopped self-sucking. One-shot tongue reshaping is an easy, minimally invasive, effective, and time-saving procedure for the treatment of self-sucking among dairy cows, with the advantage of causing little tissue damage.

Symposium review: Breeding a better cow—Will she be adaptable?

Adaption is a process that makes an individual or population more suited to their environment. Long-term adaptation is predicated on ample usable genetic variation. Evolutionary forces influencing the extent and dynamics of genetic variation in a population include random drift, mutation, recombination, selection, and migration; the relative importance of each differs by population (i.e., drift is likely to be more influential in smaller populations) and number of generations exposed to selection (i.e., mutation is expected to contribute substantially to genetic variability following many generations of selection). The infinitesimal model, which underpins most genetic and genomic evaluations, assumes that each quantitative trait is controlled by an infinitely large number of unlinked and non-epistatic loci, each with an infinitely small effect. Under the infinitesimal model, selection is not expected to noticeably alter the allele frequencies, despite a potential substantial change in the population mean; the exception is in the first few generations of selection when genetic variance is expected to decline, after which it stabilizes. Despite the common use of the heritability statistic in quantitative genetics as a descriptor of adaption or response to selection, it is arguably the coefficient of genetic variation that is more informative to gauge adaptation potential and should, therefore, always be cited in such studies; for example, the heritability of fertility traits in dairy cows is generally low, yet the coefficient of genetic variation for most traits is comparable to many other performance traits, thus supporting the observed rapid genetic gain in fertility performance in dairy populations. Empirical evidence from long-term selection studies, across a range of animal and plant species, fails to support the premise that selection will deplete genetic variability. Even after 100 yr (synonymous with 100 generations) of selection in corn for high protein or oil content, there appears to be no obvious plateauing in the response to selection. Although populations in several selection experiments did reach a selection limit after multiple generations of directional selection, this does not equate to an exhaustion of genetic variance; such a declaration is supported by the observed rapid responses to reverse selection once implemented in long-term selection studies. New technologies such as genome-wide enabled selection and genome editing, as well as having the potential to accelerate genetic gain, could also increase the genetic variation, or at least reduce the erosion of genetic variance over time. In conclusion, there is no evidence, either theoretical or empirical, to indicate that dairy cow breeding programs will be unable to adapt to evolving challenges and opportunities, at least not because of an absence of ample genetic variability.