Farm-level factors associated with lameness prevalence,productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.     

Association of housing and management practices with milk yield,milk composition,and fatty acid profile,predicted using Fourier transform mid-infrared spectroscopy,in farms with automated milking systems

Milk fatty acid (FA) profile can be divided into (1) de novo (C4–C14) that are synthesized in the mammary gland; (2) preformed (≥C18) that are absorbed from blood and originate from mobilized adipose tissues or dietary fat; and (3) mixed (C16), which have both origins. Our objectives were to describe the FA profile, as predicted using Fourier transform mid-infrared spectroscopy, of bulk tank milk from automated milking system (AMS) farms and to assess the association of management and housing factors with the bulk tank milk composition and FA profile of those AMS farms. The data used were collected from 124 commercial Canadian Holstein dairy farms with AMS, located in the provinces of Ontario (n = 68) and Quebec (n = 56). The farms were visited once from April to September 2019, and information were collected on barn design and herd management practices. Information regarding individual cow milk yield (kg/d), days in milk, parity, and the number of milking cows were automatically collected by the AMS units on each farm. These data were extracted for the entire period that the bulk tank milk samples were monitored, from April 2019 to April 2020 in Quebec and from August 2019 to May 2020 in Ontario. Across herds, milk yield averaged (mean ± standard error) 35.9 ± 0.4 kg/d, with 3.97 ± 0.01% fat and 3.09 ± 0.01% protein, whereas FA profile averaged 26.2 ± 0.1, 33.1 ± 0.1, and 40.7 ± 0.2 g/100 g of FA for de novo, mixed, and preformed, respectively. The FA yield averaged 0.34 ± 0.01, 0.44 ± 0.01, and 0.54 ± 0.01 kg/d for de novo, mixed, and preformed, respectively. Multivariable regression models were used to associate herd-level housing factors and management practices with milk production, composition, and FA profile. Milk yield was positively associated with using a robot feed pusher (+2.1 kg/d) and the use of deep bedding (+2.6 kg/d). The use of a robot feed pusher, deep bedding, and greater stall raking frequency were positively associated with greater yield (kg/d) of de novo, mixed, preformed, and de novo + mixed FA. Use of deep bedding was negatively associated with concentration of fat, de novo FA, mixed FA, and de novo + mixed FA, expressed in grams per 100 g (%) of milk. A wider lying alley width (≥305 cm) was associated with a greater concentration (g/100 g of milk) of de novo and de novo + mixed FA. Greater frequency of partial mixed ration delivery (>2×/d vs. 1 and 2×/d) was positively associated with a greater proportion (g/100 g of FA) of de novo, mixed, and de novo + mixed FA and negatively associated with the proportion of preformed FA. Overall, these associations indicated that bulk tank FA profile can be used as a tool to monitor and adjust management and housing in AMS farms.     

Management practices,physically effective fiber,and ether extract are related to bulk tank milk de novo fatty acid concentration on Holstein dairy farms

The objective of this study was to evaluate the relationship of management practices and dietary factors with de novo fatty acid concentration in bulk tank milk from commercial dairy farms milking Holstein cows. Farms were selected based on de novo fatty acid concentration during the 6 mo before the farm visit and were categorized as high de novo (HDN; 24.61 ± 0.75 g/100 g of fatty acids, mean ± standard deviation; n = 19) or low de novo (LDN; 23.10 ± 0.88 g/100 g of fatty acids; n = 20). Farms were visited once in February, March, or April 2015 and evaluated based on management and facility design known to affect cow behavior, physical and chemical characteristics of the diet, and ration formulation and forage analyses obtained from the farm's nutritionist. We observed no differences between HDN and LDN farms in farm size, time away from the pen for milking, days in milk, or body condition score. We detected no differences between HDN and LDN farms in milk fat or true protein yield; however, milk fat and protein content and de novo fatty acid yield per day were higher for HDN farms, as was gross income per unit of milk sold. High de novo farms tended to be more likely to deliver fresh feed twice versus once per day, have a freestall stocking density ≤110%, and provide ≥46 cm of feed bunk space per cow. We observed no detectable differences in forage quality or ration dry matter, crude protein, or starch content. However, ether extract was lower and physically effective neutral detergent fiber was higher for HDN farms. Feeding management, stocking density, dietary ether extract content, and the physical characteristics of the diet are related to de novo fatty acid, fat, and protein concentration in bulk tank milk from high-producing Holstein dairy farms.     

Composition and properties of bovine milk: A study from dairy farms in northern Sweden; Part I. Effect of dairy farming system

This study was part of a larger project that aimed to understand the causes for increasing variation in cheese ripening in a cheese-producing region in northern Sweden. The influence of different on-farm factors on raw milk composition and properties was investigated and is described in this paper, whereas the monthly variation in the milk quality traits during 1 yr is described in our companion paper. The dairy farming systems on a total of 42 dairy farms were characterized through a questionnaire and farm visits. Milk from farm tanks was sampled monthly over 1 yr and analyzed for quality attributes important for cheese making. On applying principal component analyses to evaluate the variation in on-farm factors, different types of farms were distinguished. Farms with loose housing and automatic milking system (AMS) or milking parlor had a higher number of lactating cows, and predominantly Swedish Holstein (SH) breed. Farms associated with tiestalls had a lower number of lactating cows and breeds other than SH. Applying principal component analyses to study the variation in composition and properties of tank milk samples from farms revealed a tendency for the formation of 2 clusters: milk from farms with AMS or a milking parlor, and milk from farms with tiestall milking. The interaction between the milking system, housing system, and breed probably contributed to this grouping. Other factors that were used in the characterization of the farming systems only showed a minor influence on raw milk quality. Despite the interaction, milk from tiestall farms with various cow breeds had higher concentrations (g/100 g of milk) of fat (4.74) and protein (3.63), and lower lactose concentrations (4.67) than milk from farms with predominantly SH cows and AMS (4.32, 3.47, and 4.74 g/100 g of milk, respectively) or a milking parlor (4.47, 3.54, and 4.79 g/100 g of milk, respectively). Higher somatic cell count (195 × 10³/mL) and lower free fatty acid concentration (0.75 mmol/100 g of fat) were observed in milk from farms with AMS than in milk from tiestall systems (150 × 10³/mL and 0.83 mmol/100 g of fat, respectively). Type of farm influenced milk gel strength, with milk from farms with predominantly SH cows showing the lowest gel strength (65.0 Pa), but not a longer rennet coagulation time. Effects of dairy farming system (e.g., dominant breed, milking system, housing, and herd size) on milk quality attributes indicate a need for further studies to evaluate the in-depth effects of farm-related factors on milk quality attributes.     

Factors associated with productivity on automatic milking system dairy farms in the Upper Midwest United States

The objective of this study was to identify housing and management factors associated with productivity on automatic milking system (AMS) dairy farms measured as daily milk yield/AMS and daily milk yield/cow. Management, housing, and lameness prevalence data were collected from 33 AMS farms in Minnesota and Wisconsin during a farm visit. All farms in the study used free-flow cow traffic. Mixed model analysis of cross-sectional data showed that farms with automatic feed push-up via a robot produced more milk per AMS/day and per cow/day than farms where feed was pushed up manually. New versus retrofitted facility, freestall surface, manure removal system, and the number of AMS units/pen were not associated with daily milk yield per AMS or per cow. Cow comfort index (calculated as number of cows lying down in stalls divided by total number of cows touching a stall) was positively associated with daily milk yield/cow. Prevalence of lameness and severe lameness, number of cows per full-time employee, depth of the area in front of the AMS milking station, and length of the exit lane from the AMS milking station were not associated with daily milk yield per AMS or per cow. Multivariable mixed model analysis of longitudinal AMS software data collected daily over approximately an 18-mo period from 32 of the farms found a positive association between daily milk yield/AMS and average age of the cows, cow milking frequency, cow milking speed, number of cows/AMS, and daily amount of concentrate feed offered/cow in the AMS. Factors negatively associated with daily milk yield/AMS were number of failed and refused cow visits to the AMS, treatment time (the time spent preparing the udder before milking and applying a teat disinfectant after milking), and amount of residual concentrate feed/cow. Similar results were also found for daily milk yield on a per cow basis; however, as it would be expected, average days in milk of the herd were also negatively associated with daily milk yield/cow. These findings indicate that several management and cow factors must be managed well to optimize AMS productivity.     

Housing,management characteristics,and factors associated with lameness,hock lesion,and hygiene of lactating dairy cattle on Upper Midwest United States dairy farms using automatic milking systems

The objectives of this cross-sectional study were to describe housing and management practices on farms using automatic milking systems (AMS) in 2 states of the upper Midwest and to evaluate the association of various housing and management factors with 3 measures of animal welfare: prevalence of lameness, severe hock lesions, and dirty cows. Fifty-four farms were visited once to collect facility measurements and observations, interview the dairy producer, and score cows for locomotion, hock lesions, and hygiene. Median number of AMS units/farm was 2 (interquartile range = 1; range = 1 to 8). Factors concerning labor were the most commonly cited reason by dairy producers for making the transition to the AMS; additional commonly cited factors were an improvement in lifestyle and human health. Number of cows fetched per AMS, or manually brought to the AMS if not milked voluntarily, was 4.7 ± 2.3 cows/AMS per day (8% of cows) for free traffic flow farms and 3.3 ± 1.8 cows/AMS per day (5% of cows) for guided traffic flow farms. Cow resting surface was significantly associated with prevalence of lameness and severe lameness. Farms with sand-bedded freestalls (17.2%) and bedded packs (17.4%) had significantly lower lameness prevalence (score ≥3 on a 1 to 5 scale, with 1 = normal locomotion) than farms with mattress freestalls (30.5%), waterbeds (25.0%), and mattresses with access to pasture (22.6%). Farms with mattresses and access to pasture had similar lameness prevalence to farms with waterbeds, but were lower than farms with mattresses only. A somewhat similar result was found for severe lameness prevalence (score ≥4 on a 1 to 5 scale, with 1 = normal locomotion); farms with sand-bedded freestalls (2.8%), bedded packs (0.0%), and mattress freestalls with access to pasture (1.5%) had significantly lower prevalence than farms with mattresses (7.1%) or waterbeds (10.8%). Severe hock lesion prevalence (score = 3 on a 1 to 3 scale, with 1 = normal, 3 = swelling) in herds with sand-bedded freestalls, waterbeds, and bedded packs were similar and significantly lower than the prevalence in mattress-based freestalls. Cows housed in sand-bedded freestalls had significantly lower prevalence of dirty cows (score = 3 or 3.5 on a 1 to 5 scale, with 1 = clean) than those housed on mattresses and waterbeds, and had significantly lower prevalence of severely dirty cows (score = 4, 4.5 or 5 on a 1 to 5 scale, with 1 = clean) than all other housing systems except waterbeds, which was similar. Manure removal system (manual, automatic, or slatted floor) was significantly associated with prevalence of severely dirty cows; farms with manual scraping had lower prevalence of severely dirty cows than farms where alley scraping was practiced automatically or slatted floors were used. Dairy producers using AMS appeared to be successful with a variety of facility designs and management practices. Cow resting surface in AMS herds was associated with some animal health and welfare measurements.     

Producer estimates of prevalence and perceived importance of lameness in dairy herds with tiestalls,freestalls, and automated milking systems

Lameness is one of the most important welfare and productivity concerns in the dairy industry. Our objectives were to obtain producers' estimates of its prevalence and their perceptions of lameness, and to investigate how producers monitor lameness in tiestall (TS), freestall with milking parlor (FS), and automated milking system (AMS) herds. Forty focal cows per farm in 237 Canadian dairy herds were scored for lameness by trained researchers. On the same day, the producers completed a questionnaire. Mean herd-level prevalence of lameness estimated by producers was 9.0% (±0.9%; ±SE), whereas the researchers observed a mean prevalence of 22.2% (±0.9%). Correlation between producer- and researcher-estimated lameness prevalence was low (r = 0.19) and mean researcher prevalence was 1.6, 1.8, and 4.1 times higher in AMS, FS, and TS farms, respectively. A total of 48% of producers thought lameness was a moderate or major problem in their herds (TS = 34%; AMS =53%; FS = 59%). One third of producers considered lameness the highest ranked health problem they were trying to control, whereas two-thirds of producers (TS = 43%; AMS = 63%; FS = 71%) stated that they had made management changes to deal with lameness in the past 2 yr. Almost all producers (98%) stated they routinely check cows to identify new cases of lameness; however, 40% of producers did not keep records of lameness (AMS = 24%; FS = 23%; TS = 60%). A majority (69%) of producers treated lame cows themselves immediately after detection, whereas 13% relied on hoof-trimmer or veterinarians to plan treatment. Producers are aware of lameness as an issue in dairy herds and almost all monitor lameness as part of their daily routine. However, producers underestimate lameness prevalence, which highlights that lameness detection continues to be difficult in in all housing systems, especially in TS herds. Training to improve detection, record keeping, identification of farm-specific risk factors, and treatment planning for lame cows is likely to help decrease lameness prevalence.     

Comparing technical efficiency of farms with an automatic milking system and a conventional milking system

Changing from a conventional milking system (CMS) to an automatic milking system (AMS) necessitates a new management approach and a corresponding change in labor tasks. Together with labor savings, AMS farms have been found to have higher capital costs, primarily because of higher maintenance costs and depreciation. Therefore, it is hypothesized that AMS farms differ from CMS farms in capital:labor ratio and possibly their technical efficiency, at least during a transition learning period. The current study used actual farm accounting data from dairy farms in the Netherlands with an AMS and a CMS to investigate the empirical substitution of capital for labor in the AMS farms and to determine if the technical efficiency of the AMS farms differed from the CMS farms. The technical efficiency estimates were obtained with data envelopment analysis. The 63 AMS farms and the 337 CMS farms in the data set did not differ in general farm characteristics such as the number of cows, number of hectares, and the amount of milk quota. Farms with AMS have significantly higher capital costs (€12.71 per 100 kg of milk) than CMS farms (€10.10 per 100 kg of milk). Total labor costs and net outputs were not significantly different between AMS and CMS farms. A clear substitution of capital for labor with the adoption of an AMS could not be observed. Although the AMS farms have a slightly lower technical efficiency (0.76) than the CMS farms (0.78), a significant difference in these estimates was not observed. This indicates that the farms were not different in their ability to use inputs (capital, labor, cows, and land) to produce outputs (total farm revenues). The technical efficiency of farms invested in an AMS in 2008 or earlier was not different from the farms invested in 2009 or 2010, indicating that a learning effect during the transition period was not observed. The results indicate that the economic performance of AMS and CMS farms are similar. What these results show is that other than higher capital costs, the use of AMS rather than a CMS does not affect farm efficiency and that the learning costs to use an AMS are not present as measured by any fall in technical efficiency.     

Genetic diversity and molecular epidemiology of outbreaks of Klebsiella pneumoniae mastitis on two large Chinese dairy farms

Klebsiella pneumoniae is an opportunistic and environmental mastitis-causing pathogen, with potential for contagious transmission. Repetitive element sequence-based PCR was used to determine genetic diversity and explore potential transmission and reservoirs for mastitis caused by K. pneumoniae on 2 large Chinese dairy farms. A total of 1,354 samples was collected from the 2 dairy farms, including milk samples from cows with subclinical and clinical mastitis, bedding, feces, feed, teat skin, and milking liners. Environmental samples were collected from all barns and milking parlors and extramammary samples from randomly selected dairy cows on both farms. In total, 272 and 93 K. pneumoniae isolates were obtained from Farms A and B, respectively (with ~8K and 2K lactating cows, respectively). Isolation rates from clinical mastitis (CM), subclinical mastitis (SCM), and environmental or extramammary samples were 34, 23 and 37%, respectively for Farm A and 42, 3, and 34% for Farm B. The K. pneumoniae isolated from CM milk and extramammary or environmental sources had high genetic diversity (index of diversity >90%) on the 2 farms and from SCM on Farm A. However, on Farm B, 9 SCM isolates were classified as 2 genotypes, resulting in a relatively low index of diversity (Simpson's index of diversity = 0.39; 95% CI = 0.08–0.70). Genotypes of K. pneumoniae causing mastitis were commonly detected in feces, bedding, and milking liners (Farm A), or from teat skin, sawdust bedding, and feed (Farm B). Based on its high level of genetic diversity, we inferred K. pneumoniae was an opportunistic and environmental pathogen causing outbreaks of CM on these 2 large Chinese dairy farms. Nevertheless, that only a few genotypes caused SCM implied some strains had increased udder adaptability and a contagious nature or a common extramammary source. Finally, control of intramammary infections caused by K. pneumoniae on large Chinese dairy farms must consider farm-level predictors, as the 2 outbreaks had distinct potential environmental sources of infection.     

Effect of dry-off management on milking behavior,milk yield,and somatic cell count of dairy cows milked in automated milking systems

Milk production may be reduced before dry-off to decrease the risk of cows developing intramammary infections during the dry period. Such reductions in milk may be possible in automated milking systems (AMS) where milking frequency and feed allocation at the AMS can be controlled at the cow level. This study investigated the effect of dry-off management of cows milked in AMS on milk yield, milking behavior, and somatic cell count (SCC). Using a 2 × 2 factorial arrangement of treatments, applied from d 14 to 1 before dry-off, 445 cows from 5 commercial dairy farms in Quebec, Canada, were assigned within farm to either (1) reduced feed [RF; allowed a maximum of 0.75 kg/d of AMS pellet for the first week (14 to 8 d before dry-off) of treatment, and 0.50 kg/d for the second week (7 to 1 d before dry-off) of treatment], or (2) nonreduced feed (NF; allowed up to 2 kg/d of AMS pellet), and either (1) reduced milking (RM; reduced to 2 milkings/d or as many times as required to yield 17 kg/milking), or (2) nonreduced milking (NM; allowed up to 6 AMS milkings/d) and no maximum production. Feed and milking behavior data, as well as milk yield and SCC were collected from the AMS software. The RF cows had lower AMS feed delivered during the treatment period, as per the experimental design. Across the treatment period, the NF-NM cows had the highest milking frequency (2.7 times/d), followed by the RF-NM cows (2.4 times/d), and then both of the RM groups (1.8 times/d), which did not differ from each other. All cows, except the NF-NM cows, were gradually milked less frequently as dry-off approached. Across the entire 2-wk treatment period before dry-off, cows with RM allowance experienced a higher reduction in milk yield compared with the cows with no milking allowance restrictions (?4.8 vs. ?3.6 kg). Similarly, cows with a RF allocation tended to have a higher reduction in milk yield than cows with NF (?4.6 vs. ?3.7 kg). As result, those cows with both reduced milking permissions and feed allocation at the AMS experienced the greatest drop in milk production before dry-off. There were no differences between treatments for milking frequency or yield in the next lactation. Somatic cell score (calculated from SCC) was not different between treatments in the 2-wk or day before dry-off, nor in the first month after calving. Overall, these data suggest that reducing both milking frequency and feed quantity in the AMS is the most efficient method to decrease milk yield before dry-off, without negatively influencing milking frequency or yield in the next lactation, as well as without affecting milk quality.     

Comparing steam-flaked and pelleted barley grain in a feed-first guided-flow automated milking system for Holstein cows

Provision of a palatable feed in automated milking systems (AMS) is considered an essential motivating factor to encourage voluntary visits to the milking stall. Although the quantity and composition of AMS concentrates have been previously investigated, the form of the concentrate has not been extensively evaluated. The objective of this study was to evaluate the effects of feeding pelleted (PB; 132.9 ± 56 DIM, 47.4 ± 9.51 kg/d milk yield) versus steam-flaked barley (SFB; 133.0 ± 63 DIM, 40.5 ± 8.23 kg/d milk yield) in an AMS on dry matter intake, AMS visits, milk and milk component yield, and partial mixed ration (PMR) feeding behavior. Twenty-nine Holstein cows of varying parities were enrolled in this study. Cows were housed in freestall housing with a feed-first guided-flow barn design; 7 cows were housed in a separate freestall pen to enable individual PMR intake and feeding behavior monitoring. This study was conducted as a 2-way crossover, with two 21-d periods in which each cow received the same basal PMR but was offered 2 kg/d (dry matter basis) of PB or SFB in the AMS. Cows receiving the SFB had fewer voluntary AMS visits (2.71 vs. 2.90 ± 0.051, no./d), tended to have a longer interval between milkings (541.7 vs. 505.8 ± 21.02 min), spent more time in the holding pen before entering the AMS (139.9 vs. 81.2 ± 11.68 min/d), and had lower total box time (19.7 vs. 21.4 ± 0.35 min/d) than cows fed PB. Despite changes in AMS attendance, there were no differences for average milk (44.0 kg/d), fat (1.62 kg/d), and protein (1.47 kg/d) yields or AMS concentrate intake (2.02 kg/d). These behavioral changes indicate that offering SFB as an alternative to PB may reduce motivation for cows to voluntarily enter the AMS.     

Cow-level associations of lameness,behavior, and milk yield of cows milked in automated systems

This study evaluated differences in behavior and productivity between lame and nonlame cows in herds with automated milking systems (AMS). We monitored 30 cows per herd on 41 farms with AMS in Canada (26 herds in Ontario and 15 herds in Alberta). During a 6-d period, milking data (n = 1,184) and lying behavior data (n = 1,209) were collected from cows on 41 farms. Rumination behavior (n = 569) and activity (n = 615) data were available for cows at 22 farms. Locomotion was scored using a numerical rating system (NRS; 1 = sound; 5 = extremely lame). Cows were defined as clinically lame with NRS ≥ 3 (n = 353, 29%) and nonlame with NRS < 3 (n = 865, 71%). Greater parity, lower body condition, and lower environmental temperature were factors associated with lameness. When accounting for other factors, lame cows produced 1.6 kg/d less milk in 0.3 fewer milkings/d. Lame cows were 2.2 times more likely to be fetched more than 1 time during the 6-d period and spent 38 min/d more time lying down in bouts that were 3.5 min longer in comparison with nonlame cows. As the number of cows per AMS unit increased, the frequency of milkings and refusals per cow per day decreased and cow activity increased. For each 13.3-percentage-point increase in freestall stocking density (cows per stall), daily lying time decreased by 13 min/d and cows were 1.6 times more likely to be fetched more than 1 time during the 6-d period. There was no difference in daily rumination or activity between lame and nonlame cows or in night:day rumination time, but lame cows had greater night:day activity ratios. This study supports the growing knowledge that lameness has negative effects on milk production, voluntary milking behavior, and lying behavior of cows in herds with AMS. These results may help dairy producers gain a better appreciation of the negative effects of even moderate cases of lameness and may help motivate them to improve their lameness monitoring and treatment protocols.     

Reliability of sampling strategies for measuring dairy cattle welfare on commercial farms

Our objective was to evaluate how the proportion of high-producing lactating cows sampled on each farm and the selection method affect prevalence estimates for animal-based measures. We assessed the entire high-producing pen (days in milk <100; range = 81–241 cows) on 10 California farms using measures from the Welfare Quality Protocol for Cattle. Cows were restrained in head locks and visually evaluated for body condition, dirtiness, skin alterations (hair loss, lesions, or swelling), discharge (ocular, nasal, vulvar), diarrhea, and impaired respiration. Lameness was scored upon release. Prevalence was calculated as a percentage of assessed cows. The most common conditions were dirty hindquarters (33.5 ± 10.7%, mean ± standard deviation) and lesions or swelling on the carpal joint (34.4 ± 7.0%) and hock (26.4 ± 16.7%). Diarrhea (8.0 ± 5.8%), lameness (moderate = 7.3 ± 4.7%, severe = 2.2 ± 2.2%), and neck (5.8 ± 12.6%), flank (4.5 ± 5.0%), or hindquarter alterations (5.5 ± 3.9%) were less common. Very fat cows, vulvar discharge, and impaired respiration were rare (≤1%) and were excluded from further analysis. Four sampling strategies were used to generate 20 estimates for each animal-based measure. The strategies were (1) selecting every 10th, 5th, 4th, 3rd, 2nd, 2 of 3, or 3 of 4 cows at the feed bunk (7 estimates/measure); (2) randomly selecting 7 matching proportions of the pen; (3) randomly selecting cows using 3 sample size calculations from the Welfare Quality Protocol; and (4) selecting the first, middle, or final third of cows exiting the milking parlor. Estimates were compared with true values using regression analysis and were considered accurate if they met 3 criteria: the coefficient of determination was ≥0.9 and the slope and intercept did not differ significantly from 1 and 0, respectively. All estimates met the slope and intercept criteria, whereas the coefficient of determination increased when more cows were sampled. All estimates were accurate for neck alterations, ocular discharge (22.2 ± 27.4%), and carpal joint hair loss (14.1 ± 17.4%). Selecting a third of the milking order or using the Welfare Quality sample size calculations failed to accurately estimate all measures simultaneously. However, all estimates were accurate when selecting at least 2 of every 3 cows locked at the feed bunk. Using restraint position at the feed bunk did not differ systematically from computer-selecting the same proportion of cows randomly, and the former may be a simpler approach for welfare assessments.     

Bacillus cereus spores during housing of dairy cows: factors affecting contamination of raw milk

The contamination of raw milk with Bacillus cereus spores was studied during the indoor confinement of dairy cattle. The occurrence of spores in fresh and used bedding material, air samples, feed, feces, and the rinse water from milking equipment was compared with the spore level in bulk tank milk on 2 farms, one of which had 2 different housing systems. A less extensive study was carried out on an additional 5 farms. High spore concentrations of >100 spores/L in the raw milk were found on 4 of the farms. The number of spores found in the feed, feces, and air was too small to be of importance for milk contamination. Elevated spore contents in the rinse water from the milking equipment (up to 322 spores/L) were observed and large numbers of spores were found in the used bedding material, especially in free stalls with >5 cm deep sawdust beds. At most, 87,000 spores/g were found in used sawdust bedding. A positive correlation was found between the spore content in used bedding material and milk (r = 0.72). Comparison of the genetic fingerprints obtained by the random amplified polymorphic DNA PCR of isolates of B. cereus from the different sources indicated that used bedding material was the major source of contamination. A separate feeding experiment in which cows were experimentally fed B. cereus spores showed a positive relationship between the number of spores in the feed and feces and in the feces and milk (r = 0.78). The results showed that contaminated feed could be a significant source of spore contamination of raw milk if the number of spores excreted in the feces exceeded 100,000/g.     

Milking system and premilking routines have a strong effect on the microbial community in bulk tank milk

In this study, we investigated the variation in the microbial community present in bulk tank milk samples and the potential effect of different farm management factors. Bulk tank milk samples were collected repeatedly over one year from 42 farms located in northern Sweden. Total and thermoresistant bacteria counts and 16S rRNA gene-based amplicon sequencing were used to characterize microbial community composition. The microbial community was in general heterogeneous both within and between different farms and the community composition in the bulk tank milk was commonly dominated by Pseudomonas, Acinetobacter, Streptococcus, unclassified Peptostreptococcaceae, and Staphylococcus. Principal component analysis including farm factor variables and microbial taxa data revealed that the microbial community in milk was affected by type of milking system. Milk from farms using an automatic (robot) milking system (AMS) and loose housing showed different microbial community composition compared with milk from tiestall farms. A discriminant analysis model revealed that this difference was dependent on several microbial taxa. Among farms using an automatic milking system, there were further differences in the microbial community composition depending on the brand of the milking robot used. On tiestall farms, routines for teat preparation and cleaning of the milking equipment affected the microbial community composition in milk. Total bacteria count (TBC) in milk differed between the farm types, and TBC were higher on AMS than tiestall farms (log 4.05 vs. log 3.79 TBC/mL for AMS and tiestalls, respectively). Among tiestall farms, milk from farms using a chemical agent in connection to teat preparation and a more frequent use of acid to clean the milking equipment had lower TBC in milk, than milk from farms using water for teat preparation and a less frequent use of acid to clean the milking equipment (log 3.68 vs. 4.02 TBC/mL). There were no significant differences in the number of thermoresistant bacteria between farm types. The evaluated factors explained only a small proportion of total variation in the microbiota data, however, despite this, the study highlights the effect of routines associated with teat preparation and cleaning of the milking equipment on raw milk microbiota, irrespective of type of milking system used.     

Short communication: The effects of regrouping in relation to fresh feed delivery in lactating Holstein cows

This study tested whether separating regrouping from the time of fresh feed delivery mitigated the effects of regrouping on cow behavior and milk production. Cows (n = 26) were individually introduced into a stable group of 11 animals/pen fed twice daily. Animals were randomly assigned to early regrouping (at 0300 h, approximately 10.5 h after fresh feed delivery and 3.5 h before the next fresh feed delivery) and late regrouping (between 0630 and 0730 h, coinciding with access to fresh feed). For 3 d, starting immediately after regrouping, video recordings continuously monitored feeding and perching (i.e., standing with the 2 front feet in the lying stall) behavior and displacements at the feed bunk. Data loggers were used to quantify lying time and the number of standing bouts; milk production was automatically recorded at each milking. Daily feeding and lying times and the number of standing bouts per day did not differ between treatments or experimental days. Daily perching time and the number of displacements at the feed bunk did not differ between treatments but decreased with experimental day. Average milk production on d 2 and 3 after regrouping (30.6 ± 1.5 kg/d) was lower than during the 3 d before regrouping (32.3 ± 1.5 kg/d), but we observed no effect of treatment on this decline. We conclude that regrouping at a time not associated with fresh feed delivery does not mitigate the negative effects of regrouping.     

Short communication: Stall occupancy behavior of Nili Ravi buffaloes (Bubalus bubalis) when first introduced to freestall housing

The aim of the present study was to assess stall occupancy of Nili Ravi buffaloes when first introduced to freestall housing. Thirty Nili Ravi buffaloes of different parity, weight, and pregnancy status were enrolled from the dairy farm of the University of Veterinary and Animal Sciences, Lahore, Pakistan. All of the enrolled animals had no previous experience with freestalls. The selected buffaloes were introduced to the freestall shed. During an adaptation period of 7 d, all buffaloes had 24 h of free access to lie down in 1 of 3 areas: (1) freestalls, (2) alleys, and (3) an outside open area. After the adaptation period, all buffaloes were housed indoors during nighttime (restricted period) to ensure that only freestalls or alleys were available as lying areas. An observer monitored animals at 0100 h and recorded the number of animals lying in freestalls, in alleys, and in the outside open area. The results indicated that during the adaptation period, herd-level freestall occupancy in buffaloes remained below 10%. During the restricted period, herd-level stall occupancy was 0, 13, 50, and 90% on d 1, 2, 5, and 17, respectively. Buffaloes with parity ≥3 took fewer days (6.6 ± 1.0; mean ± standard error of the mean) to occupy stalls than buffaloes with parity 2, 1, and heifers (13.2 ± 1.5, 16.7 ± 2.1, and 13.5 ± 2.1 d, respectively). Body weight and pregnancy status of buffaloes did not have any effect on stall occupancy. Buffaloes showed adjacent stall occupancy, filling opposite stalls first. The results indicated that older buffaloes occupied freestalls earlier than younger buffaloes. Our findings would help better manage buffaloes in freestall housing.     

Reproductive hormone use and its association with herd-level factors on Dutch dairy farms

We studied the use of the 3 commonly used reproductive hormones, namely prostaglandins, GnRH, and progesterone, and associated herd-level factors on 760 Dutch dairy farms from 5 veterinary clinics. From 2017 to 2019 we collected data on the sales of reproductive hormones, converted this data into the number of reproductive hormone doses conducted, and expressed this as the annual number of reproductive hormone doses per 100 adult dairy cows. Additional herd-level information was available for 2019. Due to the excess of zeros in the data set (i.e., a substantial number of farms did not use any hormones), we used a zero-inflated negative binomial model to identify related herd-level factors for the use of reproductive hormones. In the entire study period of 2017 to 2019, 5.8% of the dairy farms did not use any reproductive hormones, with the proportion of nonusers varying between 0.0 and 10.3% per veterinary clinic. This proportion was around 13.5% on an annual basis. Prostaglandins were the most frequently used reproductive hormone in Dutch dairy cows (62.9%), followed by GnRH (33.1%) and progesterone (4.0%). Furthermore, participating in a veterinary herd health management program had a significant effect on reproductive hormone use. These farms used more reproductive hormones than farms that did not participate in a herd health management program and were less represented in the group of nonuser farms. Technologies, such as pedometers and automatic milking systems, also had an effect on reproductive hormone use. The presence of pedometers or activity monitors did not reduce the use of the reproductive hormones but was associated with a greater frequency of users. Farms with an automatic milking system used more reproductive hormones than farms with a conventional milking system. With this study, we have made a first step in achieving transparency in the Dutch dairy industry by providing an objective overview of reproductive hormone use on Dutch dairy farms and identifying associations with some herd-level factors.