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Background and Aim: Teat disinfection is an important tool in reducing the incidence of bovine mastitis. Identifying the potential mastitis-causing bacterial species in milk can be the first step in choosing the correct teat disinfectant product. The objective of this study was to screen commercial teat disinfectants for inhibition against mastitis-associated bacteria isolated from various types of milk samples. Materials and Methods: Twelve commercially available teat disinfectant products were tested, against 12 mastitis-associated bacteria strains isolated from bulk tank milk samples and bacterial strains isolated from clinical (n=2) and subclinical (n=3) quarter foremilk samples using the disk diffusion method. Results: There was a significant variation (7-30 mm) in bacterial inhibition between teat disinfection products, with products containing a lactic acid combination (with chlorhexidine or salicylic acid) resulting in the greatest levels of bacterial inhibition against all tested bacteria (p

The development of precision grass measurement technologies is of vital importance to securing the future sustainability of pasture-based livestock production systems. There is potential to increase grassland production in a sustainable manner by achieving a more precise measurement of pasture quantity and quality. This review presents an overview of the most recent seminal research pertaining to the development of precision grass measurement technologies. One of the main obstacles to precision grass measurement, sward heterogeneity, is discussed along with optimal sampling techniques to address this issue. The limitations of conventional grass measurement techniques are outlined and alternative new terrestrial, proximal, and remote sensing technologies are presented. The possibilities of automating grass measurement and reducing labour costs are hypothesised and the development of holistic online grassland management systems that may facilitate these goals are further outlined.

The commercially available collar device MooMonitor+ was evaluated with regards to accuracy and application potential for measuring grazing behavior. These automated measurements are crucial as cows feed intake behavior at pasture is an important parameter of animal performance, health and welfare as well as being an indicator of feed availability. Compared to laborious and time-consuming visual observation, the continuous and automated measurement of grazing behavior may support and improve the grazing management of dairy cows on pasture. Therefore, there were two experiments as well as a literature analysis conducted to evaluate the MooMonitor+ under grazing conditions. The first experiment compared the automated measurement of the sensor against visual observation. In a second experiment, the MooMonitor+ was compared to a noseband sensor (RumiWatch), which also allows continuous measurement of grazing behavior. The first experiment on n = 12 cows revealed that the automated sensor MooMonitor+ and visual observation were highly correlated as indicated by the Spearman’s rank correlation coefficient (rs) = 0.94 and concordance correlation coefficient (CCC) = 0.97 for grazing time. An rs-value of 0.97 and CCC = 0.98 was observed for rumination time. In a second experiment with n = 12 cows over 24-h periods, a high correlation between the MooMonitor+ and the RumiWatch was observed for grazing time as indicated by an rs-value of 0.91 and a CCC-value of 0.97. Similarly, a high correlation was observed for rumination time with an rs-value of 0.96 and a CCC-value of 0.99. While a higher level of agreement between the MooMonitor+ and both visual observation and RumiWatch was observed for rumination time compared to grazing time, the overall results showed a high level of accuracy of the collar device in measuring grazing and rumination times. Therefore, the collar device can be applied to monitor cow behavior at pasture on farms. With regards to the application potential of the collar device, it may not only be used on commercial farms but can also be applied to research questions when a data resolution of 15 min is sufficient. Thus, at farm level, the farmer can get an accurate and continuous measurement of grazing behavior of each individual cow and may then use those data for decision-making to optimize the animal management.

The objective of this experiment was to establish the effect of low-concentrate (LC) and high-concentrate (HC) supplementation in the early and late periods of lactation on milk production and cow traffic in a pasture-based automatic milking (AM) system. In total, 40 cows (10 primiparous and 30 multiparous) were randomly assigned to one of the two treatments. The experimental periods for the early and late lactation trials extended from 23 February to 12 April 2015 and 31 August to 18 October 2015, respectively (49 days in each trial period). The early lactation supplement levels were 2.3 and 4.4 kg/cow per day for LC and HC, respectively, whereas the late lactation supplement levels were 0.5 and 2.7 kg/cow per day for LC and HC, respectively. Variables measured included milking frequency, milking interval, milking outcome and milking characteristics, milk yield/visit and per day, wait time/visit and per day, return time/visit and the distribution of gate passes. As the herd was seasonal (spring) calving, the experimental periods could not run concurrently and as a result no statistical comparison between the periods was conducted. There was no significant effect of treatment in the early lactation period on any of the milk production, milking characteristics or cow traffic variables. However, treatment did significantly affect the distribution of gate passes, with the HC cows recording significantly more gate passes in the hours preceding the gate time change such as hours 7 (P

Sensor technologies that measure grazing and ruminating behaviour as well as physical activities of individual cows are intended to be included in precision pasture management. One of the advantages of sensor data is they can be analysed to support farmers in many decision-making processes. This article thus considers the performance of a set of RumiWatchSystem recorded variables in the prediction of insufficient herbage allowance for spring calving dairy cows. Several commonly used models in machine learning (ML) were applied to the binary classification problem, i.e., sufficient or insufficient herbage allowance, and the predictive performance was compared based on the classification evaluation metrics. Most of the ML models and generalised linear model (GLM) performed similarly in leave-out-one-animal (LOOA) approach to validation studies. However, cross validation (CV) studies, where a portion of features in the test and training data resulted from the same cows, revealed that support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost) performed relatively better than other candidate models. In general, these ML models attained 88% AUC (area under receiver operating characteristic curve) and around 80% sensitivity, specificity, accuracy, precision and F-score. This study further identified that number of rumination chews per day and grazing bites per minute were the most important predictors and examined the marginal effects of the variables on model prediction towards a decision support system.

The experiments reported in this research paper aimed to investigate differences in the levels of chlorate (CHLO), perchlorate (PCHLO), trichloromethane (TCM) and iodine residues in bulk tank (BT) milk produced at different milk production periods, and to monitor those levels throughout a skim milk powder (SMP) production chain (BTs, collection tankers [CTs], whole milk silo [WMS] and skim milk silo [SMS]). Chlorate, PCHLO and iodine were measured in SMP, while TCM was measured in the milk cream. The CHLO, TCM and iodine levels in the mid-lactation milk stored in the WMS were lower than legislative and industrial specifications (0.0100 mg/kg, 0.0015 mg/kg and 150 µg/l, respectively). However, in late-lactation, these levels were numerically higher than the mid-lactation levels and specifications. Trichloromethane accumulated in the cream portion after separation. Perchlorate was not detected in any of the samples. Regarding iodine, the levels in mid-lactation reconstituted SMP were higher than that required by manufacturers (100 µg/l), indicating that the levels in milk should be lower than 142 µg/l. The higher residue levels observed in late-lactation could be related to the low milk volume produced during that period and changes in sanitation practices, while changes in feed management could have affected iodine levels. This study could assist in controlling and setting limits for CHLO, TCM and iodine levels in milk, ensuring premium quality dairy products.

peer-reviewed The seasonality of grass-based, seasonal-calving dairy systems results in disproportionately higher labor demands during the spring, when cows are calving, than in the remaining seasons. This study aimed to (1) examine the relationship between labor efficiency and profitability; (2) investigate strategies to reduce the hours worked per day by the farmer, family, and farm staff in the spring by having certain tasks outsourced; and (3) quantify the economic implications of those strategies. Data from an existing labor efficiency study on Irish dairy farms were used in conjunction with economic performance data from the farms. Tasks that required the highest level of farm labor per day in the spring were identified and hypothetical strategies to reduce the farm hours worked per day were examined. A stochastic budgetary simulation model was then used to examine the economic implications of employing these strategies and the effects of their use in conjunction with a proportionate increase in cow numbers that would leave the hours worked per day unchanged. The strategies were to use contractors to perform calf rearing, machinery work, or milking. Contracting out milking resulted in the greatest reduction in hours worked per day (5.6 h/d) followed by calf rearing (2.7 h/d) and machinery work (2 h/d). Reducing the hours worked per day by removing those tasks had slight (i.e.

The experiments reported in this research paper aimed to track the microbiological load of milk throughout a low-heat skim milk powder (SMP) manufacturing process, from farm bulk tanks to final powder, during mid- and late-lactation (spring and winter, respectively). In the milk powder processing plant studied, low-heat SMP was produced using only the milk supplied by the farms involved in this study. Samples of milk were collected from farm bulk tanks (mid-lactation: 67 farms; late-lactation: 150 farms), collection tankers (CTs), whole milk silo (WMS), skim milk silo (SMS), cream silo (CS) and final SMP. During mid-lactation, the raw milk produced on-farm and transported by the CTs had better microbiological quality than the late-lactation raw milk (e.g., total bacterial count (TBC): 3.60 ± 0.55 and 4.37 ± 0.62 log 10 cfu/ml, respectively). After pasteurisation, reductions in TBC, psychrotrophic (PBC) and proteolytic (PROT) bacterial counts were of lower magnitude in late-lactation than in mid-lactation milk, while thermoduric (LPC—laboratory pasteurisation count) and thermophilic (THERM) bacterial counts were not reduced in both periods. The microbiological quality of the SMP produced was better when using mid-lactation than late-lactation milk (e.g., TBC: 2.36 ± 0.09 and 3.55 ± 0.13 cfu/g, respectively), as mid-lactation raw milk had better quality than late-lactation milk. The bacterial counts of some CTs and of the WMS samples were higher than the upper confidence limit predicted using the bacterial counts measured in the farm milk samples, indicating that the transport conditions or cleaning protocols could have influenced the microbiological load. Therefore, during the different production seasons, appropriate cow management and hygiene practices (on-farm and within the factory) are necessary to control the numbers of different bacterial groups in milk, as those can influence the effectiveness of thermal treatments and consequently affect final product quality.

The objective of this study was to investigate the effect of omitting teat preparation prior to milking on the bacterial levels in milk directly after milking and after a period of milk storage. Eighty Holstein–Friesian dairy cows were assigned to two pre-milking teat preparation treatments: (i) washing of teats and drawing of foremilk, followed by drying with paper towels and (ii) no teat preparation. Individual cow measurements included individual quarter somatic cell count (SCC) and teat swabs for the presence of Bacillus cereus sensu lato. On seven monthly occasions, all milk produced over a 24 h period from each treatment group was segregated into a separate tank and sampled. Sub-samples of this milk were stored at 4 °C for 0, 24, 48 and 72 h, and the milk was analysed for total bacterial count (TBC), thermoduric bacterial count and the presence of B. cereus s. I. Individual quarter SCCs were numerically higher for unprepared teats (159,000 cells/mL) compared with those for prepared teats (133,000 cells/mL; P < 0.09). A similar trend was observed for bulk tank SCC, with the unprepared teat treatment tending to have a higher SCC (155,857 cells/mL) compared to the prepared teat treatment (102,286 cells/mL; P< 0.09). The TBC was not significantly higher from unprepared teats (3,152 cfu/ mL) compared with milk from prepared teats (1,678 cfu/mL) (P< 0.10). Milk TBC was significantly higher after storage for 72 h compared with that after 0, 24 and 48 h (P< 0.01). The results of this study indicate that under good hygienic conditions in an outdoor grazing situation, the omission of pre-milking teat preparation has a minimal effect on TBC and SCC.

Female calves (n = 108) were assigned to 6 cold milk feeding treatments in two experiments for a 70-day period. Live-weight (LW) was measured weekly, with an additional LW taken at day 410 and post-calving for animals in experiment 1. In Experiment 1, the effect of feeding frequency and age of turnout to pasture on calf performance and 1st lactation milk yields were evaluated. The whole milk (WM) feeding treatments applied were (i) once daily feeding (OD), (ii) twice daily feeding (TD), (iii) OD feeding, outdoors at 38 days (ODO). In Experiment 2, the effects of feeding milk replacer (MR) as opposed to WM and age of turnout to pasture on calf performance were evaluated. The treatments applied were (i) OD feeding with WM (OD), (ii) OD feeding with milk replacer (MR) (ODMR), (iii) OD feeding with MR, outdoors at 38 days (ODMRO). Experiment 1: There were no differences (P > 0.05) in LW or average daily gain between TD and OD calves at day 80 or 410. ODO calves had lower LW at day 80 as compared to OD or TD (P This study showed that while some differences were observed in calf LW at day 80, these differences had no effect on LW at day 410 or 1st lactation milk yield. It can be concluded that calves can be successfully reared when fed OD with WM or MR, indoors and when turned out to pasture at 38 days of age.

The relationship between bulk tank somatic cell count (SCC) and farm management and infrastructure was examined using data from 398 randomly selected, yet representative, Irish dairy farms where the basal diet is grazed grass. Median bulk tank SCC for the farms was 282,887 cells/ml ranging from 82,209 to 773,028 cells/ml. Two questionnaires were administered through face-to-face contact with each farmer. Herd-level factors associated with bulk tank SCC were determined using linear models with annual somatic cell score (i.e., arithmetic mean of the natural logarithm of bulk tank SCC) included as the dependent variable. All herd level factors were analysed individually in separate regression models, which included an adjustment for geographical location of the farm; a multiple regression model was subsequently developed. Management practices associated with low SCC included the use of dry cow therapy, participation in a milk recording scheme and the use of teat disinfection post-milking. There was an association between low SCC and an increased level of hygiene and frequency of cleaning of the holding yard, passageways and cubicles. Herd management factors associated with bulk tank SCC in Irish grazing herds are generally in agreement with most previous studies from confinement systems of milk production. Deposited by bulk import

A study was carried out to investigate the effect of restricting silage feeding on time of calving and calving performance in Holstein-Friesian cows. In the treatment group (n = 1,248 cows, 12 herds) silage feeding commenced in the evening (17:00 to 20:00 h), after a period of restricted access (2 to 10 h) while in the control group ad-libitum access to silage was provided over the 24 h period (n = 1,193 cows, 12 herds). Daytime and nighttime calvings were defined as calvings occurring between the hours of 06:30 and 00:29 and between 00:30 and 06:29, respectively. Restricting access to silage resulted in less calvings at night compared to cows with ad-libitum access to silage (18 vs 22%, P < 0.05). Cows with restricted access to silage had a higher percentage of difficult calvings (11 vs 7%, P < 0.001) and stillbirths (7 vs 5%, P < 0.05) compared to cows in the control group. The percentage of calvings at night was lower (13%) when access to silage was restricted for 10 h compared to 2, 4 or 6 h (22, 18, 25%, respectively) (P < 0.001). Calf sire breed, calf gender or cow parity did not influence time of calving. In conclusion, offering silage to pregnant Holstein-Friesian cows in the evening, after a period of restricted access, reduced the incidence of nighttime calvings, but increased the incidence of dystocia and stillbirth.

Social network analysis (SNA) is a technique to study behavioral dynamics within a social group. In SNA, it is an open question whether it is possible to characterize animal-level behaviors by using group-level information. Also, it was believed that the combined use of SNA would provide a more comprehensive understanding of social dynamics. In light of these two factors, here we explain an approach to evaluate animal importance to a group by considering the variability in group-level structural information, which is computed by joining the animal- and group-level SNA measures node centrality and network entropy, respectively. Moreover, two other metrics, animal social interaction range and nearest-neighbor frequency matrix, which represent a social affiliation of each animal within the group, are computed to help address the general challenges in graph-based SNA and, thereby, improve the precision of animal importance measures. Finally, we derive the joint distribution of animal importance of the group in detecting atypical social behaviors. The approach is tested using tracking data of dairy cows. The reliability of the derived animal importance was superior to the already existing animal importance measures. To illustrate the usability of the animal importance metric, a simulation study was conducted to identify sick and estrus animals in a group. The social affiliation of sick cows was less when compared to healthy cows. Also, their individual distributions of animal importance were shifted toward the left of the mean of the animal importance distributions of healthy cows. Consequently, the joint distribution of animal importance of the group exhibited a bimodal distribution with a left tailored shape. The behavior of cows in estrus was opposite to that of sick cows. Moreover, with the increasing number of sick and estrus cows in the group, respectively, the group entropy decreased with larger variance and slightly increased with less variance. Therefore, the entropy-based animal importance metric has superior performances when evaluating animal importance to the group compared to the existing metrics. It can be used for generating alerts for the early detection of atypical social behaviors associated with, for instance, animal health, veterinary, and welfare.

A study was carried out to investigate the effect of six pre-milking teat preparation procedures on lowering the staphylococal, streptococcal and coliform microbial count on teat skin prior to cluster application. The teat preparations included 'Iodine', 'Chlorhexidine' teat foam, 'Washing and drying' with paper, 'No preparation', 'Chlorine' teat foam, and disinfectant 'Wipes'. Teat preparations were applied for five days to 10 cows for each treatment during two herd management periods (indoors and outdoors). Teats were swabbed on day four and five before teat preparation and repeated after teat preparation. The swabs were plated on three selective agars: Baird Parker (Staphylococcus spp.), Edwards (Streptococcus spp.), and MacConkey (coliform). Following incubation, microbial counts for each pathogen type were manually counted and assigned to one of six categories depending on the microbial counts measured. The results were analysed by logistic regression using SAS 28. The main analysis was conducted on binary improvement scores for the swabbing outcomes. There were no differences for staphylococcal, streptococcal and coliform bacterial counts between treatments, measured 'before' teat preparation. Treatments containing 'Chlorhexidine' teat foam (OR = 4.46) and 'Wipes' (OR = 4.46) resulted in a significant reduction (P < 0.01) in the staphylococcal count on teats compared to 'Washing and drying' or 'No preparation'. 'Chlorine' teat foam (OR = 3.45) and 'Wipes' (3.45) had the highest probability (P < 0.01) of reducing streptococcal counts compared to 'Washing and drying' or 'No preparation'. There was no statistical difference between any of the disinfectant treatments applied in reducing coliforms. Thus, the use of some disinfectant products for pre-milking teat preparation can have beneficial effects on reducing the levels of staphylococcal and streptococcal pathogens on teat skin.

Research has shown that total bacterial count (TBC), which is the bacterial growth per ml of milk over a fixed period of time, can be decreased by good hygiene and farm management practices. The objective of the current study was to quantify the associations between herd management factors and bulk tank TBC in Irish spring calving, grass-based dairy herds. The relationship between bulk tank TBC and farm management and infrastructure was examined using data from 400 randomly selected Irish dairy farms where the basal diet was grazed grass. Herd management factors associated with bulk tank TBC were identified using linear models with herd annual total bacterial score (i.e., arithmetic mean of the natural logarithm of bulk tank TBC) included as the dependent variable. All herd management factors were individually analysed in a separate regression model, that included an adjustment for geographical location of the farm. A multiple stepwise regression model was subsequently developed. Median bulk tank TBC for the sample herds was 18,483 cells/ml ranging from 10,441 to 130,458 cells/ml. Results from the multivariate analysis indicated that the following management practices were associated with low TBC; use of heated water in the milking parlour; participation in a milk recording scheme; and tail clipping of cows at a frequency greater than once per year. Increased level of hygiene of the parlour and cubicles were also associated with lower TBC. Herd management factors associated with bulk tank TBC in Irish grazing herds were generally in agreement with most previous studies from confinement systems of milk production. Deposited by bulk import