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.     

Estimating efficiency in automatic milking systems

Milking data of 34 single automatic milking system (AMS) units on 29 Galician dairy farms were analyzed to determine the system capacity in each farm under actual working conditions. Number of cows, milk yield, milkings per cow per day, actual milking time, rejected milking time, cleaning time, and machine downtime were used to determine the number of cows milked per AMS unit to obtain the optimal values of milkings per cow and milk production. Multiple linear regression data analysis was used to model the linear relationship between the dependent variable, milk yield per AMS per year, and the predictor variables: number of cows per AMS, milkings per cow per day, milk flow rate, and rejections per AMS per year. An AMS unit milked 52.7±9.0 cows daily at 2.69±0.28 milkings per cow, with a total milking downtime of 1,947±978 h/yr and a milk yield of 549,734±126,432 kg/yr. The predictor variables cow and milk flow rate had a greater level of influence on the milk yield per AMS than milkings per cow and rejections, and explained the 87% of the variation. The AMS in Galician dairy farms could facilitate an increase of 16±8.5 cows per AMS without impairing milking performance; in this way, the quantity of milk obtained per robot annually could be increased (185,460±137,460 kg). This would make it possible to recoup the cost of the system earlier. In the present situation, the daily milking throughput could be maximized at 2.4 to 2.6 milkings per cow.     

Water use on nonirrigated pasture-based dairy farms: Combining detailed monitoring and modeling to set benchmarks

Water use in intensively managed, confinement dairy systems has been widely studied, but few reports exist regarding water use on pasture-based dairy farms. The objective of this study was to quantify the seasonal pattern of water use to develop a prediction model of water use for pasture-based dairy farms. Stock drinking, milking parlor, and total water use was measured on 35 pasture-based, seasonal calving dairy farms in New Zealand over 2 yr. Average stock drinking water was 60 L/cow per day, with peak use in summer. We estimated that, on average, 26% of stock drinking water was lost through leakage from water-distribution systems. Average corrected stock drinking water (equivalent to voluntary water intake) was 36 L/cow per day, and peak water consumption was 72 L/cow per day in summer. Milking parlor water use increased sharply at the start of lactation (July) and plateaued (August) until summer (February), after which it decreased with decreasing milk production. Average milking parlor water use was 58 L/cow per day (between September and February). Water requirements were affected by parlor type, with rotary milking parlor water use greater than herringbone parlor water use. Regression models were developed to predict stock drinking and milking parlor water use. The models included a range of climate, farm, and milk production variables. The main drivers of stock drinking water use were maximum daily temperature, potential evapotranspiration, radiation, and yield of milk and milk components. The main drivers for milking parlor water use were average per cow milk production and milking frequency. These models of water use are similar to those used in confinement dairy systems, where milk yield is commonly used as a variable. The models presented fit the measured data more accurately than other published models and are easier to use on pasture-based dairy farms, as they do not include feed and variables that are difficult to measure on pasture-based farms.     

The effect of day-only versus day-plus-night cooling of dairy cows

The aim of this study was to assess effects on milk yield (MY), rumen temperature, and panting score when lactating dairy cows were cooled during the day only or during the day and night. The study was conducted over 106 d during using 120 multiparous Holstein-Friesian cows assigned to 2 treatments (60 cows/treatment; 2 pens/treatment): (1) day cooling (DC): overhead sprinklers (large droplet) and fans while in the dairy holding yard only, shade and fans at the feedpad, and a shaded loafing area; and (2) enhanced day+night cooling (EDN): overhead sprinklers (large droplet) and fans in dairy holding yard, ducted air blowing onto cows during milking, plus thorough wetting (shower array) on exit from dairy; shade and fans at feedpad (turned off at night); and shaded loafing area + ducted fan-forced air blowing onto cows at night. The ducted air at night was manually activated at 2030 h when the maximum daily temperature-humidity index exceeded 75 and remained on until 0430 h the next day. The cows were fed a total mixed ration ad libitum, and feed intake was determined on a pen basis. Rumen temperature and cow activity were obtained from each cow at 10-min intervals via rumen boluses. Panting scores were obtained by direct observation 4 times a day at approximately 0430, 0930, 1530, and 2030 h. Cows were milked twice daily: 0500 to 0600 h and 1600 to 1700 h. Individual MY were obtained at each milking and combined to give individual daily totals. The EDN cows had greater daily MY (+2.05 kg/cow per day) over the duration of the study compared with DC cows. Rumen temperature during the third heat wave was lower for EDN (39.51 ± 0.01°C) than for DC (39.66 ± 0.01°C) cows. During the most severe heat wave (heat wave 3), MY for the 2 groups was similar, but over the 6 d following the heat wave, EDN cows had greater daily MY (+3.61 kg/cow per day). Rumen temperature was lower for EDN (39.58 ± 0.01°C) than for DC (40.10 ± 0.01°C) cows.     

Effect of presence of calf on milking-induced release of prolactin and oxytocin during early lactation of dairy cows

The ability of dairy cows to release either prolactin or oxytocin in response to machine milking in a conventional milking parlor was reduced among cows maintained with their calves during the 1st wk postpartum. However, presence of the calf caused no prolonged inhibition; cows evaluated 9 or 23 days after calf removal released similar quantities of prolactin and oxytocin after milking compared to controls (cows whose calves were removed within 24 h after parturition) at the same stage of lactation. Ambient temperature on the day of sampling was positively associated with the premilking serum prolactin concentration among cows housed with or without their calves (correlation coefficients were .52 and .59), but neither ambient temperature nor premilking serum prolactin concentrations were closely associated with area under milking-induced prolactin response curves (correlation coefficients from -.15 to .18). Unlike basal serum prolactin concentration, ambient temperature on the day of sampling was not closely associated with premilking serum concentrations of oxytocin or quantities released to the milking stimulus (correlation coefficients from -.19 to -.12). These results confirm that the calf can inhibit maternal secretion of prolactin and oxytocin in the dairy cow. These data also indicate that the capacity of the cow to respond to the milking stimulus is independent of premilking serum concentrations of prolactin or oxytocin. Better understanding of factors that regulate the secretion of these hormones at milking may allow development of techniques to enhance hormonal response to milking stimuli and possibly enhance milk production.     

A reduction in milking frequency and feed allowance improves dairy cow immune status

Twice-daily milking is the most common milking regimen used globally. A reduction in milking frequency to once daily, combined with a reduced feed allowance (FA), could reduce the physiological stress associated with the transition to peak milk production, and hence improve immune function. This study investigated how milking frequency and FA affect dairy cow immune status. Cows (n = 48) were milked once a day (OAD) or twice a day (TAD) on 1 of 2 FA: high (HFA) or low (LFA), in a 2 × 2 factorial arrangement of treatments. After the mean calving date of March 11, HFA cows were offered ad libitum grass silage and 7 kg of concentrates/cow per day until March 22, then 4 kg of concentrates/cow per day until April 17, and thereafter allocated 31.3 kg of dry matter (DM) grass/cow per day. The LFA cows were offered 4 kg of concentrates/cow per day, 1 kg of concentrates/cow per day, and allocated 19 kg of DM grass/cow per day for the same respective periods. Milk yield was recorded daily and body condition score weekly, and somatic cell count was performed at approximately 2-wk intervals. Blood samples were collected prepartum (d -7 to -1) and at d 1 to 7, d 14 to 21, and d 42 to 49 postpartum. Total and differential leukocyte percentage, IFN-γ production in response to concanavalin A and phytohemagglutinin, and cortisol, haptoglobin (Hp), and serum amyloid A (SAA) concentrations were evaluated. Cows milked OAD had reduced milk yield and body reserve mobilization, but higher somatic cell counts. Milking frequency and diet had no effect on total leukocyte counts. Cows milked OAD had a higher lymphocyte percentage and lower monocyte percentage, and tended to have a lower neutrophil percentage than cows milked TAD. In addition, the LFA cows had a higher eosinophil percentage than cows fed the HFA. Milking frequency and diet had no effect on IFN-γ, Hp, SAA, or cortisol production. Utilization of strategies to reduce milk yield at the beginning of the lactation could not only reduce body reserve mobilization, but also help to maintain a functioning immune system, and thus improve cow welfare.     

Associations of udder-health indicators with cow factors and with intramammary infection in dairy cows

The objective of this study was to investigate if and how cow factors and intramammary infection (IMI) are associated with 4 different udder-health indicators in dairy cows as a first step in investigating whether the diagnostic performance of these indicators can be improved. The investigated indicators were somatic cell count (SCC), lactate dehydrogenase (LDH), N-acetyl-β-d-glucosaminidase (NAGase), and alkaline phosphatase (AP) measured in milk. In this cross-sectional study, approximately 1,000 cows from 25 dairy herds were sampled for bacteriology (quarter milk samples) during 3 consecutive days: the day before test milking, at the day of test milking, and at the day after test milking. The whole-udder test milking sample was analyzed for milk composition, SCC, LDH, NAGase, and AP. Cow data (parity, breed, milk yield, percentage of milk fat and protein, milk urea concentration, and days in milk from the sampled test milking) were collected from the Swedish milk-recording scheme. Of the sampled cows 485 were considered IMI negative and were used in multivariable mixed-effect linear regression models to investigate associations between cow factors and the udder-health indicators. A second modeling including all cows, both IMI negative and IMI positive (256 cows), was also performed. The results showed that all udder-health indicators were affected by cow factors but that different cow factors were associated with different indicators. Intramammary-infection status was significantly associated with all udder-health indicators except AP. Parity and milk urea concentration were the only cow factors associated with all indicators in all models. The significant cow factors explained 23% of the variation in SCC and >30% of the variation in LDH, NAGase, and AP in IMI-negative cows, showing that LDH, NAGase, and AP are more affected than SCC by cow factors. The IMI status explained 23% of the variation in SCC in the model with all cows but only 7% of the variation in LDH and 2% of the variation in NAGase, indicating that SCC has the best potential as a diagnostic tool in finding cows with IMI. However, further studies are needed to investigate whether the diagnostic properties of these udder-health indicators will improve with adjustment according to their associations with different cow factors when used as a diagnostic tool for finding cows with IMI.     

Three Times Daily Milking of Cows in California Dairy Herds

Twenty-eight California Holstein dairy herds were on twice daily milking for 3 to 17 mo and for 36 mo on three times daily milking. Effect of three times daily milking on yields of milk, fat-corrected milk, fat, and solids-not-fat, udder health, and reproductive performance was evaluated using Dairy Herd Improvement monthly herd summaries. Data for all cows in the herd and for first lactation cows were analyzed separately. Milk yield for the entire herd increased 12% above previous production on twice daily milking. Fat and solids-not-fat percentages were not affected by three times daily milking. First lactation cows milked three times daily yielded 14% more milk over previous twice daily levels. Fat percent was lower for first lactation cows on three time milking, but solids-not-fat percent did not change. Response to three time milking was not related to herd size or production while on twice daily milking. Udder health, evaluated by California Mastitis Test scores, and reproductive indexes were not affected by milking frequency.     

Modeling milk production and labor efficiency in modernized Wisconsin dairy herds

The 1999 Wisconsin Dairy Modernization Project was conducted to examine variation in milk production and labor efficiency among herds that had recently expanded. Data were obtained from a sample of Wisconsin herds that expanded between 1994 and 1998. Using rolling herd average milk production in 1998 as the dependent variable in the milk production model, milking frequency, bovine somatotropin use, sprinkler use, average linear somatic cell score, average age at first calving, average days dry, and rolling herd average milk production in 1994 predicted 69% of the variation in milk production. Milking three times daily, using bovine somatotropin, using sprinklers to cool cows, and decreasing linear somatic cell score, age at first calving, and days dry were associated with increased milk production. Each of these variables supports previous research from designed experiments with on-farm results. Variation in milk production is determined primarily by differences in management ability and management practices employed by the dairy producer. Using cows per full-time equivalent as the dependent variable in the labor efficiency model, acres per cow, number of people involved in the milking operation, milking system type, herd size, and interactions between milking system types and herd size predicted approximately 43% of the variation in labor efficiency. As expected, labor efficiency increased with larger herd sizes, fewer acres per cow, and fewer people involved in the milking process. Parallel milking parlors were associated with the highest cows per full-time equivalent followed by herringbone parlors, flat barns, and stall barns.     

Feeding patterns and performance of cows in controlled cow traffic in automatic milking systems

Two groups of dairy cows monitored from 3 to 19 wk postpartum were subjected to 2 different cow traffic routines in an automatic milking system with control gates and an open waiting area. Using different time settings in the control gates, the groups of cows were separated by average milking frequency; cows in the high milking frequency routine had a minimum of 4 h between milkings (MF₄) and were milked 3.2 ± 0.1 times daily, whereas cows in the low milking frequency routine had at least 8 h between milkings (MF₈) and were milked 2.1 ± 0.1 times daily. Cows in the 2 groups were switched to the opposite milking frequency control for wk 18 and 19. The increased milking frequency resulted in a higher milk yield of about 9% through 16 wk of early lactation Although the higher milk yield was not significant when measured as energy-corrected milk, significant interactions of milking frequency and study period for milk yield and energy-corrected milk yield were consistent with a yield response when cows were milked more frequently. Meal criteria estimated for each individual cow were used to group feeding visits into meals. During MF₄, cows fed in fewer meals per day and had longer meals than during MF₈. The control gates were used efficiently, with only a few passages not resulting in actual meals. Although the voluntary meal intervals seemed to be short, the average milking frequency was far below that theoretically possible. This was explained by individual differences in milking frequency and long intervals from when a cow was redirected in a control gate until it arrived in the milking unit. A wide individual range in the voluntary interval between the first and the second meal in the milking cycle suggests that fixed time limits for control gates set on group level have no justifiable biological basis. It was also concluded that primiparous cows were well adapted to the automatic milking system after 2 wk in the barn.     

Using estimated nutrient intake from pasture to formulate supplementary concentrate mixes for grazing dairy cows

In pasture-based dairy systems, feeding a complex concentrate mix in the parlor during milking that contains cereal grains and protein supplements has been shown to have milk production advantages over feeding straight cereal grain. This experiment had the aim of testing whether further milk production advantages could be elicited by adjusting the composition of the concentrate mix in an attempt to match the expected nutrient intake from pasture during late spring. The experiment used 96 lactating dairy cows, grazing perennial ryegrass pasture offered at a target allowance of 30 kg of dry matter/cow per day (to ground level) during late spring (mid October to November) in southeastern Australia. Cows were allocated into 3 replicates of 4 treatment groups, with 24 cows in each treatment. Each treatment group was offered 1 of 4 dietary treatments in the parlor at milking: control consisting of crushed wheat and barley grains; formulated grain mix (FGM) consisting of crushed wheat, barley, and corn grains and canola meal; designer grain mix 1 (DGM1) consisting of the same ingredients as the FGM grain mix but formulated using the CPM Dairy nutrition model to take into account the expected nutrient intake from pasture; and designer grain mix 2 (DGM2) consisting of the same ingredients as DGM1 but with canola meal replaced by urea and a fat supplement (Megalac, Volac Wilmar, Gresik, Indonesia). Concentrate mixes were offered at 8.0 kg of dry matter/cow per day, except for DGM2 cows, which were offered 7.5 kg of dry matter/cow per day. The experiment ran for a total of 28 d; after a 14-d adaptation period, nutrient intake, milk production, and body weight were measured over a 14-d measurement period. Milk yield (kg) of cows fed the FGM diet was greater than that of the control cows but was not different from that of the DGM1 and DGM2 cows. However, milk fat and protein yields (kg) were greater for cows fed the FGM diet than for all other diets. There was no difference in estimated daily pasture or total dry matter intakes between the 4 treatment groups, despite cows fed the DGM2 treatment consuming less of the concentrate mix (average 6.5 kg of dry matter/cow per day when offered 7.5 kg of dry matter/cow per day). This research has demonstrated the potential for using a nutrition model to take into account the expected nutrient intake from pasture to formulate a concentrate mix (DGM1) to achieve similar milk yields, but also highlighted the need for near real-time analyses of the pasture to be grazed so as to also capture benefits in terms of milk fat and protein yield.     

Reducing milking frequency in early lactation improved the energy status but reduced milk yield during the whole lactation of primiparous Holstein cows consuming a total mixed ration and pasture

To investigate the immediate and long-term performance effects of milking frequency during early lactation of primiparous dairy cows consuming a total mixed ration and pasture, 20 Holstein cows were assigned in a randomized block design to either once-daily (1×) or twice-daily (2×) milking during the first 8 wk of lactation (treatment period). After the treatment period, all cows were milked 2× until wk 43 of lactation. Cows were fed a total mixed ration (approximately 15 kg of DM/cow per day) and allowed to graze an oat pasture (Avena sativa). Dry matter intake was 19.1 kg of DM/cow per day on average and was not affected by treatments. Milk yield was 40% lower in cows milked 1× during the treatment period, and a carryover effect existed until wk 21 of lactation, resulting in a final reduction of 15% of milk yield in the whole lactation. Milk lactose concentration decreased, whereas fat and protein concentrations increased for cows milked 1×. Mobilization of energy reserves during the treatment period occurred in both groups, but cows milked 1× showed greater body condition score and greater backfat thickness. In conclusion, milking 1× during the first 8 wk of lactation resulted in immediate and carryover negative effects on milk and milk solid yield without affecting feed intake, resulting in the improved energy status of primiparous dairy cows.     

Effect of suckling on the release of oxytocin, prolactin, cortisol, gastrin, cholecystokinin, somatostatin and insulin in dairy cows and their calves

The aim of the present study was to examine how different types of early interaction between dairy cows and their calves influence milking/suckling-related hormone release in the cows and sucking/bucket-drinking related hormone release in calves. Eighteen cows of the Swedish Red and White breed were studied during the first week after parturition. The cows were machine milked twice daily, and allotted to one of three treatments: [1] cow and calf were kept together and the cow was allowed to suckle the calf for 30 min about 1 h before each milking; [2] cow and calf were kept together and the calf was bucket fed twice daily; and [3] cow and calf were separated immediately after parturition, and the calf was kept in a single box and was bucket fed twice daily. Blood samples were collected around day 7 from both cows and calves. The plasma levels of oxytocin, prolactin, cortisol, gastrin, cholecystokinin (CCK), somatostatin and insulin were analysed. In the cows the levels of oxytocin, prolactin and cortisol were influenced by all three treatments, except for the level of cortisol which did not respond to suckling. The main finding was that the release of oxytocin was as significantly greater during suckling compared with machine milking. In the calves, the hormone levels were also influenced by the different milk feeding routines. The plasma concentrations of oxytocin, gastrin, CCK and insulin increased in response to milk ingestion in all treatments. However, during sucking, the increase of oxytocin was significantly greater than during bucket drinking. In addition, a strong correlation between oxytocin and insulin was found in response to sucking. Further, significant increases in prolactin and somatostatin, and a decrease in cortisol were found during sucking. The level of somatostatin also increased in response to bucket feeding when calves were kept separately. During bucket feeding, no significant correlation was found with oxytocin, but strong correlations between the gastrointestinal hormones gastrin, CCK, somatostatin and insulin were seen. Together these data suggest that different hormonal patterns were triggered in the cows by suckling and milking and in the calves by sucking and bucket drinking. This is further supported by different correlation patterns observed in the calves in response to sucking and bucket feeding. The present findings imply that management routines for cows and calves during the first week after parturition have consequences for the physiology of the animals.     

Estimating milk loss based on somatic cell count at the cow and herd level

There is a direct relationship between elevated somatic cell count (SCC) in an individual cow milk production and milk loss. This relationship has been used at the herd level to estimate an overall herd milk loss due to subclinical mastitis and to use recovery of this lost milk as a financial benefit to cover the cost of intervention strategies to improve milk quality. The objective of this study was to estimate the recoverable milk revenue on a per cow basis for herds moving from one herd average SCC level to a newer, lower level. Test-day records from 1,005,697 dairy cows in 3,741 herds between 2009 to 2019 were used. Milk yield loss for each cow in each herd on test day was estimated using a mixed effects regression equation, and then summed to estimated total herd milk loss. These herd average daily milk loss estimates were then related to the bulk tank SCC, and the distribution of underlying individual cow SCC were examined. The distributions in daily herd milk loss for various bulk tank SCC values were generated, and estimates of recoverable milk loss were generated to simulate a herd moving from their current bulk tank SCC to a new lower level. The results indicate that estimates of total herd milk yield loss vary with the distribution of cow-level SCC and parity within the herd, so it is imperative that milk loss be calculated on a per cow basis. Further, the recoverable milk loss estimates based on moving to a lower bulk tank SCC where milk loss is still occurring was relatively small compared with the traditional assumption that all milk loss would be recovered, and less than most herd owners and advisors would expect.     

Assessment of the productivity effects associated with epizootic hemorrhagic disease in dairy herds

Epizootic hemorrhagic disease is caused by a Culicoides-borne Orbivirus. In cattle, the disease is characterized by reduced milk production and mortality. Recent outbreaks of epizootic hemorrhagic disease virus (EHDV) in North Africa, Israel, and Turkey increase the risk of its invasion into central and northern Europe. An outbreak of EHDV in Israel during the fall of 2006 enabled an assessment of the consequent production losses to the dairy cattle industry. Reduction in milk production and involuntary culling were modeled using a 4-yr database of monthly milk and mortality records from 48 affected and 63 unaffected herds. These indices were compared between periods of outbreak and no outbreak and assessed for various levels and exposure onset. Geospatial kriging interpolation of serological results from 127 herds was used to assess the total outbreak losses for the dairy cattle industry in Israel. Herds affected during the first, second, and third month of the outbreak (September-November) experienced an average loss of 207 (95% CI = 154-261), 137 (63-211), and 52 (27-76) kg of milk/milking cow, respectively, during the outbreak period. An average excess mortality and involuntary culling of 1.47/100 cows was documented in herds affected in September. High correlation was observed between EHDV seroprevalence and milk loss; average milk loss for herds with seropositivity of 26 to 50, 51 to 75, and 76 to 100% was 84, 133, and 204 kg of milk/milking cow, respectively. A 1.42% (0.91-1.93%) increase in mortality was observed in herds with seroprevalence above 50%. Losses for the dairy cattle industry interpolated from these data were estimated at US$2,491,000 (US$1,591,000-3,391,000), an average loss of US$26.5/cow in the Israeli dairy cattle. This equals 0.55% of the average total value production of a dairy cow in Israel. This is the first study to estimate the production losses caused by EHDV or any bluetongue-like disease.     

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.     

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.     

Simulation model of quarter milk flowrates to estimate quarter and cow milking duration and automated milking system's box duration

The aims of this research were (1) to develop a model to simulate a herd of cows and quarter milk flowrates for a milking and derive quarter and udder milking durations and box duration (i.e., the time a cow spends inside the robot) for a group of cows milked with an automatic milking system (AMS); (2) to validate the simulation by comparing the model outcomes with empirical data from a commercial AMS dairy farm; and (3) to apply teatcup removal settings to the simulation to predict their effect on quarter and cow milking duration and box duration in an AMS. For model development, a data set from an AMS farm with 32 robots milking over 1,500 cows was used to fit the parameters to the variables days in milk, parity, and milking interval, which were subsequently used to create a herd of cows. A second data set from 2019 from an AMS farm with 1 robot milking 60 cows that contained quarter milk flowrates (at 2-s intervals) was used to extract the parameters necessary to simulate quarter milk flowrates for a milking. We simulated a herd of cows, and each was assigned a parity, days in milk, milking interval, and milk production rate. We also simulated milk flowrates every 1 s for each quarter of each cow. We estimated quarter milking duration as the total time that flowrate was greater than 0.1 kg/min after a minimum of 1 min of milk flow. We incorporated a randomly sampled attachment time for each quarter and calculated cow milking duration as the time from the first quarter attached to the last quarter detached. We included a randomly sampled preparation time which, added to cow milking duration, represented box duration. For simulation application, we tested the effect of quarter teatcup removal settings on quarter and cow milking duration. The settings were based on absolute flowrate (0.2, 0.4, and 0.6 kg/min) or a percentage of the quarter's 30-s rolling average milk flowrate (20, 30, and 50%). We simulated over 84,000 quarter milkings and found that quarter milking duration (average 212 s) had a mean absolute percent error (MAPE) of 7.5% when compared with actual data. Simulated cow milking duration (average 415 s) had a MAPE of 8%, and box duration (average 510 s) had a MAPE of 12%. From simulation application, we determined that quarter milking duration and box duration were reduced by 19% (209 vs. 170 s) and 6.5% (512 vs. 479 s), respectively, when increasing the teatcup removal flowrate from 0.2 to 0.6 kg/min. Quarter milking duration and box duration were 7% (259 vs. 241 s) and 3% (590 vs. 573 s) longer respectively by using a teatcup removal setting of 20% of the quarter's rolling average milk flowrate, compared with 30%. Both results agree with previous research. This simulation model is useful for predicting quarter and cow milking and box duration in a group of cows and to analyze the effect of milking management practices on milking efficiency.     

A field trial on the effect of propylene glycol on milk yield and resolution of ketosis in fresh cows diagnosed with subclinical ketosis

The purpose of this study was to determine the effect of oral propylene glycol (PG) administration on ketosis resolution and milk yield in cows diagnosed with subclinical ketosis (SCK). Cows from 4 freestall dairy herds (2 in New York and 2 in Wisconsin) were each tested 6 times for SCK from 3 to 16 d in milk on Mondays, Wednesdays, and Fridays. Subclinical ketosis was defined as a β-hydroxybutyrate (BHBA) concentration of 1.2 to 2.9 mM/L, and clinical ketosis was defined as ≥3.0 mM/L. Cows with SCK were randomized to the treatment group (oral PG) or control group (no PG); treatment cows were drenched with 300 mL of PG once daily from the day they tested 1.2 to 2.9 mM/L until the day they tested <1.2 mM/L. Outcomes evaluated for all farms included time from SCK until BHBA test <1.2 mM/L or until BHBA test ≥3.0 mM/L. Individual milk weights for the first 30 d of lactation were evaluated for the 3 farms monitoring daily milk. Semiparametric proportional hazards models were used to evaluate time to event outcomes; repeated-measures ANOVA was used to assess milk weights. A total of 741 of 1,717 (43.2%) eligible enrolled cows had at least one BHBA test of 1.2 to 2.9 mM/L. Of these, 372 were assigned to the treatment group and 369 to the control group. Based on hazard ratios, PG-treated cows were 1.50 times more likely (95% confidence interval = 1.26 to 1.79) to resolve their SCK and 0.54 times less likely (95% confidence interval = 0.34 to 0.86) to develop clinical ketosis than control cows. Across the 3 herds measuring individual milk weights, treated cows produced 0.23 kg more milk per milking in the first 30 d of lactation than control cows, for a total difference of 0.69 kg/cow per day. After identification of a treatment by herd interaction, stratification by herd showed that treated cows produced more milk per milking on farm A (0.44 kg) and farm B (0.53 kg) in the first 30 d of lactation than control cows, for a total difference of 1.34 and 1.59 kg/d, respectively; milk production did not differ (0.02 kg per milking) between the 2 groups on farm D. These results show the positive effects of oral PG administration in fresh cows with SCK by helping to resolve SCK and preventing clinical ketosis. In addition, oral PG improves milk yield during early lactation in cows diagnosed with SCK.