Number Of Milkings Research Articles

Human milk oligosaccharides regulate human macrophage polarization and activation in response to Staphylococcus aureus.

Human milk oligosaccharides (HMOs) are present in high numbers in milk of lactating women. They are beneficial to gut health and the habitant microbiota, but less is known about their effect on cells from the immune system. In this study, we investigated the direct effect of three structurally different HMOs on human derived macrophages before challenge with Staphylococcus aureus (S. aureus). The study demonstrates that individual HMO structures potently affect the activation, differentiation and development of monocyte-derived macrophages in response to S. aureus. 6´-Sialyllactose (6'SL) had the most pronounced effect on the immune response against S. aureus, as illustrated by altered expression of macrophage surface markers, pointing towards an activated M1-like macrophage-phenotype. Similarly, 6'SL increased production of the pro-inflammatory cytokines TNF-α, IL-6, IL-8, IFN-γ and IL-1β, when exposing cells to 6'SL in combination with S. aureus compared with S. aureus alone. Interestingly, macrophages treated with 6'SL exhibited an altered proliferation profile and increased the production of the classic M1 transcription factor NF-κB. The HMOs also enhanced macrophage phagocytosis and uptake of S. aureus. Importantly, the different HMOs did not notably affect macrophage activation and differentiation without S. aureus exposure. Together, these findings show that HMOs can potently augment the immune response against S. aureus, without causing inflammatory activation in the absence of S. aureus, suggesting that HMOs assist the immune system in targeting important pathogens during early infancy.

Predicting bovine daily milk yield by leveraging genomic breeding values

The main goal of this work, conducted on a herd of 502 Holstein cows situated in Italy, is to propose a machine learning-based approach to forecast the individual bovine daily milk production by explicitly leveraging genotypic information. As part of our study, we also evaluated the importance in the prediction of genotypic and phenotypic variables usually available within herd. The methodology we propose is based on two consecutive models: a genomic prediction one to calculate the animal’s genomic breeding value from marker data, followed by a feed forward neural network combining such additive genetic effect and the environmental features (parity, days in milk, age at calving in months, month of calving) for milk yield forecasting. In particular, we both assess the inclusion of genomic breeding values calculated within herd or provided by the breeders’ association, discovering that the latter ones allow for better final predictions. The results of our model outperform the ones by a linear mixed model with the same inputs on average, day by day and at the individual level. Moreover, we propose a problem formulation that also leverages additional factors partially controllable by breeders: in this case, features such as the number of milkings and the concentrate consumption inside the automatic milking system prove to highly impact on the final prediction, and hence on milk production. To the best of our knowledge, the proposed problem formulation based on genomic breeding values is a novelty in the individual bovine milk yield machine learning forecasting literature. Given the low genotyping costs and the availability of a larger number of environmental features in farms equipped with a wide range of sensors, as automatic milking systems, our solution can support breeders’ herd management and animal monitoring, thanks to the possibility to forecast the full lactation curve in advance even for primiparous bovines and newborn calves. With this work, we successfully achieve our objectives of including genomic information in bovine milk yield machine learning-based forecasting, thus improving the performance on this task, and of evaluating the impact on prediction of common genotypic and phenotypic information available to breeders.

Characterization of variables related to high stability of raw cow milk.

This research paper analyzes the stability of raw cow milk in the alcohol test and seeks to understand to know the factors that influence milk stability and the occurrence of unstable non-acid milk. Milk samples were collected from the cooling tanks of rural farmers in the state of Paraná twice in summer and twice in winter. The farms were classified according to the production system: pasture with supplementation and feedlot. The following variables were analyzed: stability in the alcohol test, titratable acidity, ionized calcium concentration (iCa), chemical composition of milk, somatic cell count and standard plate count. The results showed that milk stability was greater in winter vs. summer, when the milk contained higher iCa, and in the feedlot vs. pasture system. The Pearson Correlation between variables (ethanol stability, milk composition, iCa, cooling tank temperature, milk volume, number of milking, number of cows milked, fat/protein ratio, distance and travel time) were analyzed. Stability was negatively correlated with iCa concentration and positively with lactose content. Logistic regression of the risk of unstable non-acid milk at 72% alcohol (UNAM72) showed that only iCa and lactose were determinants, while evaluation of the same risk at 78% alcohol revealed iCa, titratable acidity, lactose and milk urea nitrogen as risk factors. Under the dairy farming conditions of Paraná state, the frequency of UNAM72 was low (12.16%) and was higher in summer and in pasture systems with supplementation. In conclusion, in dairy herds bred with high technological level, with adequate nutritional and health management, the frequency of UNAM is low and is related to nutritional management abnd, perhaps, heat stress, factors that alter iCa and lactose levels.

Effect of altering milking interval when milking 3 times in 2 days on milk and component yields in pasture-based dairy systems

Dairy farmers face challenges attracting and retaining staff, partly due to the difficulty meeting the desires of the modern workforce. These include flexible work hours and regular time off. The task of milking fundamentally impacts the ability of dairy farmers to meet these desires. Milking contributes to a large proportion of the hours spent working on dairy farms. The number of milkings (milking frequency) and their timing (milking interval) within a day influence the number of hours spent milking and what time in the day they occur. Milking 3 times in 2 d (3-in-2) reduces the amount of time spent milking compared with milking twice a day (TAD), without reducing milk yield as much as milking once a day (OAD). However, long intervals between 3-in-2 milkings can still lead to a long workday if farmers are expected to work between milkings. The objective of this study was to determine the effect of milking interval within a 3-in-2 milking frequency on milk yield and composition at 2 stages of lactation and compare these with OAD and TAD milking. Cows (n = 200) were milked in 5 groups of 40 at 3 intervals of 3-in-2: 8-20-20 h, 10-19-19 h, and 12-18-18 h, along with 24 h (OAD) and 10-14 h (TAD), for 6 weeks at early-lactation (mean 24 d in milk ± 7 d) and again at mid-lactation (mean 136 d in milk ± 18 d). Milk yields were recorded at each milking and milk samples collected weekly to determine composition. At both early- and mid-lactation there were no significant differences (P > 0.05) in milk, fat, protein or lactose yields between the 3 3-in-2 intervals. Cows milked 3-in-2 produced 8% less milk than cows milked TAD and 14% more than cows milked OAD, with smaller differences observed at mid-lactation between TAD and 3-in-2. For a 3-in-2 milking frequency, a shorter milking interval can be implemented on the days when cows are milked twice. This may allow farmers to shorten the working day when using 3-in-2, without compromising milk or component yields.

Comparison of dairy cow step activity under different milking schedules

Context Variations in the number of milkings each day and their timing are becoming increasingly common. How these changes affect cow behaviour is poorly understood. When cows are milked less frequently, their walking to and from the dairy is reduced and their amount of time spent at pasture increases; however, the impact on activity under different milking schedules has not been measured. Aims The objective of this study was to identify any differences in cow walking activity (steps per hour) among three milking frequencies and three milking schedules of 3-in-2 (milking three times in 2 days), at two stages of lactation (34 and 136 days in milk), over a period of 6 weeks. Time spent eating was assessed to help explain differences in activity within a day. Methods Data were collected from five groups of 40 cows (n = 200) milked, as follows: once a day (OAD); twice a day (TAD); 3-in-2 (three groups) at intervals of 12–18–18 h, 10–19–19 h, and 8–20–20 h. All cows were fitted with AfiAct pedometers, which recorded steps per hour. Eight cows in each treatment group were also fitted with CowManager SensOor™ ear tags, which recorded minutes per hour spent eating. Key results Cow steps per hour increased with an increasing milking frequency in both trial periods. When data associated with walking to and from milking were removed, there were still differences in cow step activity. Cows milked OAD took 30% fewer steps than TAD cows. The diurnal pattern of eating time differed between these two trial groups. The effect of milking time among the 3-in-2 trials showed that the shorter the time between the milkings on the day the cows were milked twice, the greater the number of steps per hour. There were graphical eating differences between the 8–20–20 trial group and 12–18–18 trial group on the day that cows were milked twice. Conclusions We conclude that both the number and timings of milkings affect a cow’s step activity and grazing behaviour. Implications Farmers should minimise the amount of time cows spend away from the paddock, especially in the afternoon, to minimise any changes to natural behaviour.

ДИАГНОСТКА СКРЫТОГО МАСТИТА ПУТЕМ ПОДСЧЕТА СОМАТИЧЕСКИХ КЛЕТОК В МОЛОКЕ КОРОВ

In this article, we present the course and results of scientific research aimed at calculation of the concentration of somatic cells in cow's milk to detect subclinical mastitis in individual farms of the Republic of Armenia. Comparison of somatic cell concentrations in milk from healthy and sick cows with subclinical mastitis, analysis and comparison of blood morphological parameters in sick and healthy animals has been implemented and the relationship between somatic cell concentration in milk and morphological abnormalities in sick cow blood has been identified. SC concentrations between 300 and 500 thousand/ml are indicative of mastitis risk. In this case, the type of reaction manifested was positive. It was found that the viscosity of the investigated solution "Somatic plus" + milk increases in proportion to the increasing concentration of somatic cells in the milk sample, which indicates subclinical mastitis. A study of the morphological parameters of blood in healthy and subclinical mastitis animals revealed some deviations from the reference values of blood parameters, leading to the conclusion that these changes in animals' blood are related to an increase in the number of milk's somatic cells. Increased leukocytes were found in sick animals' blood. This was followed by an increase in stab neutrophils, eosinophils, monocytes, lymphocytes, and ESR. As a result of all this, the body is experiencing inflammatory processes mobilizing its defensive mechanisms against pathogens.

Prediction of cow's fertility based on data recorded by automatic milking system during the periparturient period.

The results of most studies show the beneficial effect of milking automation on production parameters of dairy cows, but its effect on fertility traits is debatable. Therefore, a study was undertaken to predict cow fertility - services per conception (SC) and calving interval (CI) - based on automatic milking system (AMS) data collected in the periparturient period subdivided into the second and first week before calving, 1-4, 5-7, 8-14, 15-21 and 22-28days of lactation. SC and CI were predicted using daily indicators such as concentrate intake, number of milkings, cow box time, milking time, milking speed, colostrum and milk yield, composition, temperature and electrical conductivity. The study material was derived from the AMS management system and from the SYMLEK milk recording system. The analysis covered data for 16,329 milkings of 398 Polish Holstein-Friesian (PHF) cows, which were used in three AMS herds. The collected numerical data were statistically analysed by correlation analysis in parallel with decision tree technique (SAS statistical package). The present study showed that due to the low, mostly non-significant coefficients of correlation between AMS data collected between 2weeks before and 4weeks after calving, it is not possible to predict cow fertility based on single traits. It has been established that the decision tree method may help breeders, already during the postcalving period, to choose the level of factors associated with AMS milking, which will ensure good fertility of cows in a herd. The most favourable number of services per conception is to be expected from cows that were milked <1.6 times per day from 1 to 4days of lactation and electrical conductivity of their colostrum did not exceed 69 mS during that time. In turn, shortest CI (366days) will be characteristic of the cows whose average daily colostrum yield did not exceed 20.2kg and their daily concentrate intake from 8 to 14days of lactation was at least 5.0kg.

Atuação da assistência veterinária e conhecimento dos produtores rurais sobre antimicrobianos em Goiás, Brasil

The objective of this research was to evaluate the influence of veterinary care on milk production and quality variables in rural properties of Goiás. The objective was also to verify the farmers' knowledge on antimicrobials. A total of 132 farms were visited in the state of Goiás, where interviews were carried out in order to characterize the farm, the influence of veterinary assistance on productive and sanitary aspects, and the way antimicrobials were used. Pearson's chi-square test (χ2) was used to verify the dependency or independence of variables. It was verified that 55.3% of the farms had dairy production below 250 L per day. However, 60.2% of the total milk produced on the 132 farms visited came from only 15 farms (11.4%), with production above 1,000 L per day. Veterinary assistance was present in 56% of the farms and a significant association was identified between veterinary assistance and the variables: type of farm (p = 0.025), husbandry system (p = 0.015), number of milkings per day (p = 0.0007), daily production per cow (p = 0.0006), and antimicrobial prescription (p &lt; 0.0001). The farmers know that milk with antimicrobial residues must be discarded; however, they do not do it properly. Farms with lower average daily production per cow showed higher use of antimicrobials on their own initiative (p = 0.02). With urgency, the expansion of technical assistance and training of farmers regarding milk production is required to prevent risks associated with public health in Goiás.

Assessment of welfare indicators in grazing dairy cows in Northeast Brazil

The welfare of dairy cows is a major global concern, due to its impact on cow health and productivity, as well as public health. The aim of this study was to identify the main problems related to welfare in dairy herds managed on pasture in the state of Paraíba, Brazil. For this investigation, a cross-sectional study was conducted in 12 dairy farms in the municipalities of Areia, Alagoa Grande, Serraria, and Pilões, Paraíba, Brazil. Each farm was visited only once, recording the number of cows in the herd, type and number of milkings per day, daily milk yield, and access time to the pasture. Body condition score, cleanliness score, bodily injuries, and qualitative behavioral assessment (QBA) were measured. A total of 335 dairy cows were evaluated; herds ranged from 14 to 43 lactating cows, with an average milk yield of 8.4 ± 3.25 kg day-1. Of the 335 cows observed, 26% had a low body condition score, 82% had bodily injuries, and 20% had dirt on their legs. For the QBA, a principal component analysis (PCA) indicated that PC1 had a high correlation mainly with positive body expressions (e.g., sociable, active, and happy), and PC2 was associated with negative terms of body expression (e.g., apathetic, frustrated, and fearful). In conclusion, evaluating indicators of cows’ body condition, bodily injury, and cleanliness highlighted the importance of promoting improvements in pasture, management, and housing conditions to enable better performance, health, and welfare of the animals.

Genetic, farm, and lactation effects on behavior and performance of US Holsteins in automated milking systems

Selecting for favorable behavior and performance could enhance the efficiency of production in automated milking systems (AMS). The objectives of this study were to describe AMS behavior and performance in Holsteins, estimate genetic parameters among AMS traits, and determine genetic relationships of AMS traits with other routinely recorded traits. The edited data included 1,101,651 individual milking records and 394,636 daily records from 2,531 lactations and 1,714 cows that resided on 3 farms; data were obtained from the Dairy Data Warehouse (Assen, Netherlands) cloud. Traits considered were individual milking and daily totals for milk yield, milking time, milk harvest rate (the ratio of milk yield to milking time), milk flow rate, electrical conductivity, machine kickoffs, incomplete milkings, and blood in milk; the number of milkings per day and 305-d mature-equivalent milk yield (305ME) were also evaluated. Individual milkings were evaluated with mixed models that included fixed effects of week of lactation, lactation group (1, 2, ≥3), hour of day, and farm; random effects included cow within lactation, lactation group by week of lactation, and interactions of farm with date, hour, week of lactation, and year-season of calving. Daily records were evaluated with 3-trait animal models that included 305ME and 2 AMS traits with random additive genetic and permanent environment effects. Estimated breeding values were extracted and correlated with yield, conformation, and udder health genetic evaluations. Farm specific robot access policies had notable effects on week of lactation patterns for milk yield and number of milkings. Mature cows had higher milk harvest rates (2.05 kg/min) than first-lactation cows (1.73 kg/min) with larger differences in early lactation. First-lactation cows were more likely to kick off the machine (15.04%) than mature cows (8.62%), particularly in early lactation. Heritability estimates were generally lower for behavior traits (0.03 for incomplete milkings and 0.08 for kickoffs) than for milk harvest rate (0.30) and flow rate (0.55). Udder conformation traits did not have favorable genetic correlations with AMS traits, with the exception that longer teats were correlated with fewer kickoffs (-0.34) and incomplete milkings (-0.49); increased milk harvest rate and flow rate were unfavorably associated with genetic merit for udder health. There is genetic variation for milking efficiency and behavioral traits, suggesting genetic selection to enhance efficiency in AMS systems is possible. Genetic associations with udder conformation indicate that selection for udder morphology is unlikely to substantially improve milking efficiency. This calls for more direct selection of traits related to AMS efficiency.

Incidence of milk leakage after dry-off in European dairy herds, related risk factors, and its role in new intramammary infections

The incidence of milk leakage (ML) after dry-off (DO) and related risk factors was studied in 1,175 dairy cows from 41 commercial herds in 8 European countries: Belgium, Czech Republic, Denmark, France, Germany, Italy, the Netherlands, and Spain. Milk leakage was assessed twice for 30 s each during 3 visits at 20 to 24 h, 30 to 34 h, and 48 to 52 h after DO. Information related to dry-cow management and udder health was collected at herd and cow level, including individual somatic cell count (ISCC) from test-day controls and occurrence of clinical mastitis cases from DO until 30 d in lactation. Mixed-effect logistic regression analyses were used to identify possible risk factors for ML and to study the association between ML and new intramammary infections. Intramammary infections were defined as clinical mastitis cases during the dry period and in the first 30 d in lactation or a rise in ISCC from before to after the dry period (threshold: 200,000 cells/mL) or both. Milk leakage was observed in 24.5% of the cows between 20 and 52 h after DO, where the herd incidence varied between 0.0 and 77.8%. The reduction in number of milkings in the weeks before DO had statistically significant effect on the ML incidence. When the milking frequency was reduced from 3 times/d to 2 or maintained at twice a day, cows had 11 (95% CI = 3.43-35.46) or 9 (95% CI = 1.85-48.22) times higher odds of leaking milk, respectively, compared with cows where the milking frequency was reduced from twice to once a day. Also, the milk production 24 h before DO was associated with ML incidence. Hence, cows with a milk production between 13 and 21 L or above 21 L had 2.3 (95% CI = 1.48-3.53) and 3.1 (95% CI = 1.79-5.3) times higher odds of leaking milk, respectively, compared with cows with a milk production below 13 L. A higher ML incidence was present in the group of cows with an average ISCC in the last 3 mo before DO ≥200,000 cells/mL (odds ratio = 1.7; 95% CI = 1.13-2.41) compared with cows with an average ISCC <100,000 cells/mL. Quarters with ML tended to have 2.0 times higher odds of developing clinical mastitis compared with quarters not leaking milk. Cows with ML tended to have 1.5 times higher odds of intramammary infections (i.e., an increase of ISCC or clinical mastitis) compared with cows without ML.

Evaluation of the Energy Utilization Index in Sheep Milk Cooling Systems

The energy consumption of sheep milk cooling systems (MCSs) was quantified in this study to provide original information filling a literature gap on the impact of sheep milk cooling on the energy and economic balance in dairy farms. Performance and energy monitoring tests were conducted simultaneously on 22 MCSs in Sardinia (Italy). The results determined the cooling time as a function of the performance class and number of milkings. The Energy Utilization Index (EUI) was applied to measure the energy required to cool down the milk and estimate the incidence on its price. The average EUI was 1.76 kWh 100 L−1 for two-milkings and 2.43 kWh 100 L−1 for four-milkings MCSs, whereas the CO2 emissions ranged from 998 to 1378 g CO2 100 L−1 for two- and four-milkings MCSs, respectively. The estimated energy consumption for the storage of refrigerated sheep milk was 0.12 kWh 100 L−1. The malfunctioning MCSs averagely consumed 31% more energy than regular systems. The energy cost for cooling accounted for 0.61% on the current sheep milk price in Italy. Based on the analysis, the reported EUI values can be used as a preliminary indicator of the regular operation of MCSs.

Characterization of the colostrum and transition milk proteomes from primiparous and multiparous Holstein dairy cows

Colostrum plays a vital role in the nutrition, development, and immunity of a newborn calf. This study aimed to characterize the protein profile of colostrum and to identify changes in the colostrum proteome across parity during the transition to mature milk. Colostrum and transition milk samples were collected at milkings 1, 2, 4, and 14 after calving from multiparous (n = 10) and primiparous cows (n = 10). Samples were skimmed, fractionated, and enriched before analysis for low-abundance proteins by liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Changes in protein abundances were analyzed using PROC MIXED in SAS (SAS Institute Inc., Cary, NC) with determination of the adaptive false discovery rate adjustment using a MULTTEST procedure to identify effects of parity (P), milking number (MN), and their interaction (MN×P). We identified 86 proteins through LC-MS/MS, including 3 low-abundance proteins that were affected by P, 78 that were affected by MN, and 36 affected by MN×P. Prominent ontological groupings of proteins affected by MN included defense or immunity proteins, such as immunoglobulins. Proteins involved in the plasminogen activating cascade and more broadly, blood coagulation, were affected by MN×P. The results of this study add to increasing knowledge of the colostrum and transition milk proteomes, and this is the first study to find evidence of different abundances of these proteins when examined across P, MN, and MN×P. These findings aid in the identification of potential milk protein biomarkers for mammary health during the early postpartum period.

The effect of physiological state, milk production traits and environmental conditions on milk fat globule size in cow's milk.

This research was carried out to quantify the effects of a range of variables on milk fat globule (MFG) size for a herd of Holstein-Friesian cows managed through an automatic milking system with year-round calving. We hypothesised that the overall variation in average MFG size observed between individual animals of the same herd cannot sufficiently be explained by the magnitude of the effects of variables that could be manipulated on-farm. Hence, we aimed to conduct an extensive analysis of possible determinants of MFG size, including physiological characteristics (parity, days in milk, days pregnant, weight, age, rumination minutes, somatic cell count) and milk production traits (number of milkings, milk yield, fat yield, protein and fat content, fat-protein ratio) on the individual animal level; and environmental conditions (diet, weather, season) for the whole herd. Our results show that when analysed in isolation, many of the studied variables have a detectable effect on MFG size. However, analysis of their additive effects identified days in milk, parity and milk yield as the most important variables. In accordance with our hypothesis, the estimated effects of these variables, calculated using a multiple variable linear mixed model, do not sufficiently explain the overall variation between cows, ranging from 2.70 to 5.69 µm in average MFG size. We further show that environmental variables, such as sampling day (across seasons) or the proportion of pasture and silage in the diet, have limited effects on MFG size and that physiological differences outweigh the effects of milk production traits and environmental conditions. This presents further evidence that the selection of individual animals is more important than the adjustment of on-farm variables to control MFG size.

Comparing dairy farm milk yield and components, somatic cell score, and reproductive performance among United States regions using summer to winter ratios

Heat stress abatement is a challenge for dairy producers in the United States, especially in the southern states. Thus, managing heat stress is critical to maintain dairy cow performance in the summer. The ability to employ a metric to measure heat stress and evaluate abatement strategies may benefit dairy producers by providing meaningful feedback on the effectiveness of current and future management strategies with the goal of improving heat stress management. Therefore, this study aimed to explore the use of the summer to winter performance ratio metric to quantify and compare farm performance variables among regions of the United States. Monthly performance data recorded by the Dairy Herd Improvement Association from 2007 to 2016, for all US Dairy Herd Improvement Association herds processing records through Dairy Records Management Systems (Raleigh, NC), were obtained. Season dates were based on the astronomical definition of the Northern Hemisphere with summer as June 21 to September 21 and winter as December 21 to March 19. States were grouped into regions based on climate zone classification. Performance records included a total of 16,573 herds [Northeast (n = 7,955), Midwest (n = 6,555), Northern Plains (n = 305), Southeast (n = 1,370), and Southern Plains (n = 388) regions]. Herd test day performance variables energy-corrected milk, somatic cell score, milk fat and protein percentage, conception rate, heat detection rate, and pregnancy rate in summer and winter were used to calculate summer to winter ratios for each region. The MIXED procedure of SAS 9.4 (SAS Institute Inc., Cary, NC) was used to compare test day performance variables. The effects of year, mean days in milk, mean 150-d milk, mean herd size, and number of milkings per day were included as covariates in the models. Dairy cattle performance in all climate regions was negatively affected by summer heat stress, but some regions greater than others. A difference was also observed among regions when comparing summer to winter ratios for each performance parameter. This indicates that summer performance varies by climate region identified by the summer to winter ratio and demonstrates usefulness of the metric to monitor degree of heat stress based on performance.

Residue concentration of cefquinome taking into account different milk fractions and comparing the performance of two screening tests.

This Research Communication describes the residue concentration of a dry cow antibiotic in two different milk fractions and describes effects of milk fraction and milk composition on the test performance of a rapid screening and a microbial inhibitor test. Thirteen dry cows were treated with an intramammary dry cow antibiotic containing 150 mg cefquinome. Quarter foremilk and stripping samples were collected on the first 10 d postpartum. All milk samples were analyzed for milk composition by the local Dairy Herd Improvement Association and were tested for antibiotic residues using the rapid screening test Milchtest BL and the microbial inhibitor test Delvotest BR Brilliant Plates. The residue concentration of cefquinome was determined in foremilk and stripping samples from milkings 1, 2, 3, 5, and 7 after calving using high performance liquid chromatography - tandem mass spectrometry. The logarithm of cefquinome concentration (logCef) was higher in foremilk than in stripping samples and higher in milk samples with lower lactose content. Furthermore, logCef decreased with the number of milkings (P < 0.001). The Milchtest BL was more likely to be not evaluated (i.e. no test and control line or no control line appeared) in stripping samples and milk samples with higher protein content. In the Delvotest BR Brilliant Plates milk samples with higher protein content were more likely to have a false positive result (i.e. the screening test result was positive, but the HPLC-MS/MS result was below the detection limit of the screening test). These results indicate that foremilk is the recommended milk fraction to be tested for residues of cefquinome and that a high protein content can be a cause of test failure and false positive results when milk during the first 10 d postpartum is tested for antibiotic residues using screening tests.

Modern technologies of robotized cowing milk

The studies were conducted in the conditions of LLC “Milk Group” of Sukhinichsky district of Kaluga region. The object of research is robotic milking machines, Swedish breed cows and Danish red breeds. Equality of development of the front and rear lobes, the udder index, the average milk flow rate and the frequency of delivery can be achieved only with long-term selection by type, good severity of signs of milkiness. Based on the selection of cows for milking on a robotized milking plant, the following requirements were put forward: high milk productivity and milk yield, tightly attached udder, nipples of the same size, the lower point of which should not be below 33 cm from the floor level, the minimum distance between the rear nipples in 3 cm, between the front nipples - 12.5 - 30 cm, the thickness of the nipples in the range of 1.5-3.5 cm, the rear nipples should be located 3 cm lower than the lower part of the udder, the minimum distance between the front and rear These udder teats - 7 cm, an angle of deviation from vertical teats should not exceed 30 °. The main reasons for the insignificant loss of milk during robotic milking are the milking of cows that do not have a full-fledged milk-giving reflex or the reflex was inhibited at the beginning of the milking of milk with a delay in putting the teat on the teats of the udder. The size of one-time milk yield, with the exception of the program indicators of this restriction on the milk yield, is determined by the frequency of effective visits to the robot (i.e., the multiplicity of milking during the day). In robotic milking, the frequency of milkings varies by day periods relatively little and drops to a minimum only in the second half of the night, in our opinion, due to the relatively late distribution of feed mixtures. It is also noted that cows of all ages have the same number of milkings on a robotized unit within 2 times.

Viable and Total Bacterial Populations Undergo Equipment- and Time-Dependent Shifts during Milk Processing.

We set out to identify the viable and total bacterial content in milk as it passes through a large-scale, dairy product manufacturing plant for pasteurization, concentration, separation, blending, and storage prior to cheese manufacture. A total of 142 milk samples were collected from up to 10 pieces of equipment for a period spanning 21 h on two collection dates in the spring and late summer of 2014. Bacterial composition in the milk was determined by 16S rRNA marker gene, high-throughput DNA sequencing. Milk samples from the late summer were paired such that half were treated with propidium monoazide (PMA) to enrich for viable cells prior to quantification by PCR and identification by DNA sequence analysis. Streptococcus had the highest median relative abundance across all sampling sites within the facility on both sampling dates. The proportions of Anoxybacillus, Thermus, Lactococcus, Lactobacillus, Micrococcaceae, and Pseudomonas were also elevated in some samples. Viable cells detected by PMA treatment showed that Turicibacter was enriched after high-temperature short-time pasteurization, whereas proportions of Staphylococcus were significantly reduced. Using clean-in-place (CIP) times as a reference point, Bacillus, Pseudomonas, and Anoxybacillus were found in high relative proportions in several recently cleaned silos (<19 h since CIP). At later times (>19 h after CIP), 10 of 11 silos containing elevated viable cell numbers were enriched in Acinetobacter and/or Lactococcus These results show the tremendous point-to-point and sample-dependent variations in bacterial composition in milk during processing.IMPORTANCE Milk undergoes sustained contact with the built environment during processing into finished dairy products. This contact has the potential to influence the introduction, viability, and growth of microorganisms within the milk. Currently, the population dynamics of bacteria in milk undergoing processing are not well understood. Therefore, we measured for total and viable bacterial composition and cell numbers in milk over time and at different processing points in a cheese manufacturing facility in California. Our results provide new perspectives on the dramatic variations in microbial populations in milk during processing even over short amounts of time. Although some of the changes in the milk microbiota were predictable (e.g., reduced viable cell numbers after pasteurization), other findings could not be easily foreseen based on knowledge of bacteria contained in raw milk or when the equipment was last cleaned. This information is important for predicting and controlling microbial spoilage contaminants in dairy products.

The Effect of Hoof Trimming on Milk Yield in Dairy Cattle

Hoof trimming is necessary for conformation and health of cattle. It is performed to prevent hoof lesions and maintenance the symmetry and shape of claw. At the same time it is a stress factor in dairy cattle. The aim of the study was to investigate the stress effects of hoof trimming on milk yield in healthy dairy cattle. Twenty Simmental dairy cattle were used as material. Functional hoof trimming was performed for all cattle. Dairy milk yield was measured before and after hoof trimming period. There were personal increases and decreases of milk yield recorded in animals. However, these increase and decrease were not statistically significant. As a result of this study hoof trimming is necessary for claw health and prevention for foot diseases. In healthy dairy cattle it causes stress and to decreases in milk yield. On the other hand the hoof trimming time, environmental factors such as flooring system and management style, and the animal related factors such as lactation period and stage, number of milking, breed and age affect the milk yield with hoof trimming positively or negatively. Keywords : Cattle, Dairy, Hoof, Milk, Simmental DOI : 10.7176/JSTR/5-5-07

Effects of an automatic milking system on milk yield and quality of Mediterranean buffaloes

A study was carried out to evaluate the effects of an automatic milking system (AMS) on milk yield and composition of buffalo (Mediterranean-type Bubalus bubalis) cows. Performed from January 2015 to December 2015 in an organic buffalo dairy farm equipped with both a traditional tandem milking parlor and an AMS, the study involved 90 primiparous buffaloes randomly allotted to a tandem or AMS group from 5 to 10 d of lactation onward. Number of milkings per day and daily milk yield of each cow were recorded, and individual milk sampling was carried out twice a month. Compared with the tandem, the AMS group showed significantly higher daily milk yield and persistence of lactation. Use of the AMS resulted in higher protein and casein contents, and lower somatic cell and total bacterial counts, whereas fat, freezing point, and pH were unaffected by the system. We conclude that, in terms of milk yield and quality, automatic milking may be a suitable alternative to conventional milking for buffaloes.