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Automatic milking systems (AMS), or milking robots, are becoming widely accepted as a milking technology that reduces labour and increases milk yield. However, reported amount of labour saved, changes in milk yield, and milk quality when transitioning to AMS vary widely. The purpose of this study was to document the impact of adopting AMS on farms with regards to reported changes in milking labour management, milk production, milk quality, and participation in dairy herd improvement (DHI) programmes. A survey was conducted across Canada over the phone, online, and in-person. In total, 530 AMS farms were contacted between May 2014 and the end of June 2015. A total of 217 AMS producers participated in the General Survey (Part 1), resulting in a 41% response rate, and 69 of the respondents completed the more detailed follow-up questions (Part 2). On average, after adopting AMS, the number of employees (full- and part-time non-family labour combined) decreased from 2.5 to 2.0, whereas time devoted to milking-related activities decreased by 62% (from 5.2 to 2.0 h/day). Median milking frequency was 3.0 milkings/day and robots were occupied on average 77% of the day. Producers went to fetch cows a median of 2 times/day, with a median of 3 fetch cows or 4% of the herd per robot/day. Farms had a median of 2.5 failed or incomplete milkings/robot per day. Producers reported an increase in milk yield, but little effect on milk quality. Mean milk yield on AMS farms was 32.6 kg/cow day. Median bulk tank somatic cell count was 180 000 cells/ml. Median milk fat on AMS farms was 4.0% and median milk protein was 3.3%. At the time of the survey, 67% of producers were current participants of a DHI programme. Half of the producers who were not DHI participants had stopped participation after adopting AMS. Overall, this study characterized impacts of adopting AMS and may be a useful guide for making this transition.

Background Since the abolition of EU milk quotas in 2015, the Irish dairy industry has expanded with a 16.6% increase in calf births since 2011. Calf losses have major implications for the economic viability and sustainability of dairy enterprises. There is a paucity of literature on mortality in calves from birth to six months, particularly at a national herd level. Previous studies have tended to focus on herd size as a risk factor for calf mortality rather than the possible influence of herd expansion. The purpose of this study is to quantify any association between dairy herd expansion and the risk of being classified as a high or low calf mortality herd based on analysis of national dairy herd identification and movement records in Ireland from 2016–2020. Results In calves aged under 6 months, herds that expanded > 20% (OR 1.23 95% CI: 1.10–1.37, p  < 0.001) and > 45% (OR 1.22, 95% CI:1.09–1.36, p  = 0.001), were more likely to have > 10% herd calf mortality, compared to herds that did not increase in size. Newly established herds were more likely to have poor mortality outcomes (OR 2.44, 95% CI: 1.82–3.29, p  < 0.001) compared to herds that did not increase in size. Herd expansion < 20% was not associated with mortality outcome. Herd ordinal location and herd size were significant risk factors for > 10% herd calf mortality. Conclusion This study has demonstrated that herds that have expanded > 20% over five years and newly established herds were more likely to have poor mortality outcomes. It suggests that new entrants into dairy farming may benefit from targeted emphasis on herd health management. The results also highlight the value of national data as a tool to determine optimisation of farm interventions and surveillance and policy decisions to prioritise animal health and welfare.

The aims of this study were to estimate mortality rates in Norwegian dairy calves and young stock up to 1 yr of age, identify risk factors for calf mortality, and evaluate the etiology of calf mortality based on postmortem analyses. The material comprised 3 data sets. The first data set included information on 289,038 offspring in 14,474 dairy herds registered in the Norwegian Dairy Herd Recording System (NDHRS) in 2005. The second included recordings on 5,382 offspring in 125 Norwegian dairy herds participating in a survey on calf health, and the third included results from postmortem analyses of 65 calves from 37 of the survey herds. The calf mortality rate during the first year of life in all herds registered in the NDHRS was 7.8%, including abortion (0.7%) and stillbirth (3.4%). The overall calf mortality rate in liveborn calves in the survey herds was 4.6%. Cows with severe calving difficulties had an odds ratio (OR) of 38.7 of stillbirth compared with cows with no calving difficulties. Twins and triplets showed an increased risk of stillbirth compared with singletons (OR = 4.2 and 46.3, respectively), as did calves born in free stalls compared with tie stalls (OR = 1.9). Respiratory disease increased the risk of death in all age groups with hazard ratios (HR) of 6.4, 6.5, 7.4, and 5.6 during the first week of life, 8 to 30 d of age, 31 to 180 d of age, and 181 to 365 d of age, respectively. Diarrhea increased the risk of death among calves younger than 180 d of age, but the influence was only significant during the first week of life and between 8 to 31 d of age (HR = 2.4 and 2.9, respectively). Calves born during the winter were more likely to die during the first week of life than calves born during the summer (OR = 1.2), and were more likely to die during the first month of life than calves born during the autumn (OR = 1.2). Calf mortality rates in all age groups increased with increasing herd size. Calves housed in a group pen from 2 wk of age were more likely to die during the first month of life than calves housed individually (HR = 1.5). Bronchopneumonia and enteritis were the most frequent postmortem diagnoses, with proportional rates of 27.7 and 15.4%, respectively.

Continuous assessment of the herd status is important in order to monitor and adjust to changes in the welfare and health status but can be time consuming and expensive. In this study, herd status indicators from routinely collected dairy herd improvement (DHI) records were used to develop a remote herd assessment tool with the aim to help producers and advisors benchmark the herd status and identify herd management issues affecting welfare and health. Thirteen DHI indicators were selected from an initial set of 72 potential indicators collected on 4324 dairy herds in Eastern Canada. Data were normalized to percentile ranks and aggregated to a composite herd status index (HSI) with equal weights among indicators. Robustness analyses indicated little fluctuation for herds with a small HSI (low status) or large HSI (high status), suggesting that herds in need of support could be prioritized and effectively monitored over time, limiting the need for time-consuming farm visits. This tool allows evaluating herds relative to their peers through the composite index and highlighting specific areas with opportunities for improvements through the individual indicators. This procedure could be applied to similar multidimensional livestock farming issues, such as environmental and socio-economic studies.

Optimising the number of replacement heifers needed will have positive economic and environmental consequences on herds that rear their own young stock. The number of heifers needed to be kept is closely related with the number of culled dairy cows in the herd. This study therefore looked at the variation that exists in culling rate and herd level factors associated with it. A dataset from 1903 dairy herds available included information at animal level (dates of culling, slaughter/death) and herd level (characteristics of reproduction, performance, health) over the years 2007 to 2010. The average culling rate for slaughter/death was used and was defined for each year as percentage of the herd size that died within 30 d after they were culled. The analysis of the association between average culling rate for slaughter/death and the characteristics of the herd was performed using a mixed model. The results showed that the average culling rate for slaughter/death was 25·4% and varied between 23% (2007) and 28% (2010). More than 70% of the herds have an average culling rate for slaughter/death of less than 30%, showing that there is room for lowering the average culling rate for slaughter/death. A higher average culling rate for slaughter/death is associated with a longer average calving interval, a higher average 305-d protein production, a higher average somatic cell count (SCC), a higher percentage of new high SCC, a more than 5% decrease in herd size, and herds that bought more than 1% of animals per year. A lower average culling rate for slaughter/death is associated with a longer average age, herds that bought less than 1% of animals per year and a more than 5% increase in herd size. In conclusion, the average culling rate for slaughter/death is associated with fertility, udder health and openness of the herd.

Prototheca bovis (P. bovis), an alga that has attracted considerable attention over the years as a causative microorganism of mastitis in dairy cows, exhibits limited susceptibility to specific aminoglycosides and antifungal agents, and no effective clinical treatment is currently available, thereby posing challenges for both prevention and treatment. To investigate the infection of P. bovis mastitis and its impact on raw milk production, a total of 348 raw milk samples were collected from August to December 2022 from a dairy farm in central China. P. bovis and other bacteria were detected, and the average infection rate of P. bovis in raw milk was 60.34% (210/348). The total number of colonies and the somatic cell count (SCC) of P. bovis positive samples were significantly higher than those of P. bovis negative samples (p < 0.01). The daily milk yield, 305-day milk yield, peak milk yield, and days to peak milk yield of the P. bovis positive samples were significantly lower than those of P. bovis negative samples (p < 0.01). A correlation analysis showed that P. bovis infection was negatively correlated with daily milk yield, 305-day milk yield, peak milk yield, and days to peak milk yield (p < 0.0001), while being positively correlated with the total number of colonies, SCC, milk loss, and protein percentage (p < 0.0001). These findings may help practitioners in comprehending the occurrence of Prototheca mastitis and developing more effective strategies for the prevention of P. bovis infections.

This research study aimed to evaluate the use of the milk leukocyte differential (MLD) to: (a) identify quarter milks that are culture-positive; and (b) characterize the milk leukocyte responses to specific groups of pathogens causing subclinical mastitis. The MLD measures the absolute number and relative percentage of inflammatory cells in milk samples. Using the MLD in two dairy herds (170 and 172 lactating cows, respectively), we studied all lactating cows with a most recent monthly Dairy Herd Improvement Association somatic cell count (SCC) >200 × 103 cells/ml. Quarter milk samples from 78 cows meeting study criteria were analysed by MLD and aseptically collected milk samples were subjected to microbiological culture (MC). Based upon automated instrument evaluation of the number and percentage of inflammatory cells in milk, samples were designated as either MLD-positive or – negative for subclinicial mastitis. Positive MC were obtained from 102/156 (65·4%) of MLD-positive milk samples, and 28/135 (20·7%) of MLD-negative milk samples were MC-positive. When MC was considered the gold standard for mastitis diagnosis, the calculated diagnostic Se of the MLD was 65·4% (IC95% = 57·4 to 72·8%) and the Sp was 79·3% (IC95% = 71·4 to 85·7%). Quarter milks positive on MC had higher absolute numbers of neutrophils, lymphocytes and macrophages, with higher neutrophils% and lymphocytes% but lower macrophages%. The Log10 (N/L) ratios were the most useful ratio to differentiate specific subclinical mastitis quarters from healthy quarters. Use of the MLD on cows with monthly composite SCC > 200 × 103 cells/ml for screening at quarter level identified quarters more likely to be culture-positive. In conclusion, the MLD can provide an analysis of mammary quarter status more detailed than provided by SCC alone; however, the MLD response to subclinical mastitis was not found useful to specifically identify the causative pathogen.

Mycotoxins in milk are a public health concern and have to be regularly monitored. A survey on the presence of aflatoxin M1 (AFM1) and ochratoxin A (OTA) in raw bulk milk was conducted in 2003 in the northwest of France, the main French milk-producing basin. Randomly selected farms (n = 132) were characterized by a diet based on corn silage and containing a large proportion of on-farm produced cereals, feeding sources that are frequently contaminated by mycotoxins. Farms were surveyed twice in winter and in summer. At each sampling time, a trained surveyor completed a questionnaire recording farm management procedures and production traits. The AFM1 was found in 3 out of 264 samples but at levels (26 ng/L or less) that are below the European legislation limit of 50 ng/L. Traces of AFM1 (less than 8 ng/L) were also found in 6 other samples. The OTA was detected in 3 samples also at low levels, 5 to 8 ng/L. Farms that tested positive to the presence of mycotoxins, 12 in total including 6 farms that had traces of AFM1, differed from negative farms by a more extensive use of total mixed rations, 58 vs. 27%. In addition, the positive farms tended to have lower milk yields. Although the incidence of milk contamination with AFM1 and OTA at the farm level was low during the period studied, production and management data from the surveyed farms suggest a link between feeding management practices and mycotoxin contamination.

The objectives were to describe culling patterns and reasons for culling across lactation, estimate mortality and the proportion of cows leaving from 21 d before an expected calving date through 60 d in milk (DIM; CULL60) for Pennsylvania (PA) dairy herds, and to describe production measures for herds with high and low mortality and CULL60. Weekly culling frequencies and reasons for culling from 3 wk before a reported expected calving date through ≥100 wk of lactation were calculated for all PA cows with at least 1 Dairy Herd Improvement test in 2005. It was estimated that at least 5.0% of PA dairy cows died in 2005, and that at least 7.6% were culled by 60 DIM. The majority of cows exiting the herd by 60 DIM either died (35.1%) or had a disposal code of injury/other (29.9%). A total of 137,951 test-day records from 20,864 cows in herds with high mortality (>8.0%) and CULL60 (>12.0%) and 136,906 test-day records from 12,993 cows in herds with low mortality (<1.4%) and CULL60 (<2.9%) were retained to describe differences among herds with high and low survival. Least squares means for weekly milk yield, fat and protein percentages, and somatic cell score (SCS) were estimated with a model that included fixed effects for herd environment (high or low survival) and week nested within herd environment and lactation; random effects were cow, herd-test-day, and error. Cows from herds with high mortality and CULL60 produced more milk in lactations 1 (+1.9±0.15 kg/d) and 2 (+0.9±0.16 kg/d), but less in lactations 4 (−0.7±0.22 kg/d), 5 (−1.4±0.29 kg/d), and ≥6 (−0.7±0.32 kg/d) and had higher SCS (+0.24±0.02), more change in early-lactation fat percentage (−1.77% vs. −1.59%), and a greater frequency of fat-protein inversions (3.6±0.3%). There is an opportunity to manipulate management practices to reduce mortality and early-lactation culling rates, which will improve cow welfare and the efficiency of dairy production by capturing a greater proportion of potential lactation milk yield, increasing cow salvage values, and reducing replacement costs.

Knowledge of reproductive risk factors for culling is useful in making insemination and culling decisions and helps motivate efforts to reduce or eliminate risk factors. The objective of this study was to describe survival and reproductive risk factors for culling in Holstein dairy herds with at least 200 cows. Results were calculated from 2,345,015 DHI lactation records from 727 herds with at least 200 cows from 2001 to 2006. Herds were located in 36 states primarily located east of the Mississippi River. Kaplan-Meier survival curves were obtained and daily hazards of culling were calculated with the actuarial method. Cox regression was performed with the GLIMMIX procedure in SAS (SAS Institute Inc., Cary, NC). The hazard of culling increased with parity number. Cows in their sixth parity had 3 times greater hazards than cows in their first parity. Medium remaining productive life for cows calving in parity 1 to 6 were 907, 697, 553, 469, 423, and 399 d, respectively. Daily hazards of culling first peaked approximately 30 d after calving and then again later in lactation, after 280 d, for older cows. Hazards for first-parity cows peaked earlier, around d 10 after calving, and the first-parity cows had lower risks of culling later in lactation than older cows. Pregnant cows had 3 to 7 times lower hazards of culling than open cows. Hazards of culling increased for cows that had greater calving difficulty, gave birth to males or twins, were in herds with shorter days to first insemination, or had longer days to conception. The possible to likely use of a synchronized breeding program increased from 21.9% in 2001 to 41.4% in 2006. Cows in herds that did not use a synchronized breeding program had slightly lower risks of culling than those in herds that at least possibly used a synchronized breeding program.