Genetic analyses of novel temperament and milkability traits in Norwegian Red cattle based on data from automatic milking systems

The number of dairy cows milked in automatic milking systems (AMS) is steadily increasing in Norway. Capacity and efficiency of AMS are highly dependent on the individual cow's milking efficiency, such as milking speed and occupation time in the milking robot. Cows meet new challenges in herds utilizing AMS. Consequently, new or revised traits may be needed for genetic evaluation of dairy cattle. The AMS records relevant information on an individual cow basis. The aims of this study were to estimate genetic parameters of new automatically recorded milkability and temperament traits. Data from 77 commercial herds with Norwegian Red dairy cattle were analyzed by mixed linear animal models. The final data set contained 1,012,912 daily records from 4,883 cows in first to ninth lactation. For variance component estimation, univariate and bivariate models were used. Daily records of box time (BT), average flow rate (FR), kilograms of milk per minute of box time (MEF), handling time (HT), log-transformed HT, milking frequency, and milking interval were analyzed with repeatability models. Among these traits, FR, BT, and MEF showed the highest heritabilities of 0.48, 0.27, and 0.22, respectively, whereas heritability of log-transformed HT, HT, milking frequency, and milking interval was low (0.02–0.07). Unsuccessful milkings expressed as rejected milkings, incomplete milkings (IM), milkings with kick-offs (KO), and teat not found also showed low heritabilities (0.002–0.06). Due to low frequency, KO, rejected milkings, IM, and teat not found were also analyzed as proportions per lactation, which resulted in slightly higher heritability estimates. Genetic correlations were favorable and intermediate to strong between BT, HT, MEF, and FR with absolute values above 0.50. Intermediate and favorable correlations were found for IM and KO with BT, HT, MEF, and FR. Cow milkability in AMS can be improved by selection for reduced number of unsuccessful milkings, faster FR, increased MEF, and shorter BT and HT. Our results confirm that automatically recorded data on milkability and temperament can be valuable sources of information for routine genetic evaluations and that milking efficiency in AMS can be genetically improved.     

Milk cortisol concentration in automatic milking systems compared with auto-tandem milking parlors

Milk cortisol concentration was determined under routine management conditions on 4 farms with an auto-tandem milking parlor and 8 farms with 1 of 2 automatic milking systems (AMS). One of the AMS was a partially forced (AMSp) system, and the other was a free cow traffic (AMSf) system. Milk samples were collected for all the cows on a given farm (20 to 54 cows) for at least 1 d. Behavioral observations were made during the milking process for a subset of 16 to 20 cows per farm. Milk cortisol concentration was evaluated by milking system, time of day, behavior during milking, daily milk yield, and somatic cell count using linear mixed-effects models. Milk cortisol did not differ between systems (AMSp: 1.15 ± 0.07; AMSf: 1.02 ± 0.12; auto-tandem parlor: 1.01 ± 0.16 nmol/L). Cortisol concentrations were lower in evening than in morning milkings (1.01 ± 0.12 vs. 1.24 ± 0.13 nmol/L). The daily periodicity of cortisol concentration was characterized by an early morning peak and a late afternoon elevation in AMSp. A bimodal pattern was not evident in AMSf. Finally, milk cortisol decreased by a factor of 0.915 in milking parlors, by 0.998 in AMSp, and increased by a factor of 1.161 in AMSf for each unit of ln(somatic cell count/1,000). We conclude that milking cows in milking parlors or AMS does not result in relevant stress differences as measured by milk cortisol concentrations. The biological relevance of the difference regarding the daily periodicity of milk cortisol concentrations observed between the AMSp and AMSf needs further investigation.     

Feasibility of using automatic milking system data from commercial herds for genetic analysis of milkability

The objective of this study was to investigate how useful data from automatic milking systems used in commercial herds are for genetic analysis of milkability traits. Data were available from 4,968 Swedish Holstein and Swedish Red cows over a span of 5 yr (2004–2009) from 19 herds. The analyzed milkability traits were average flow rate, box time, milking interval, and number of milkings per day. Variance components were estimated for genetic, permanent environmental, and residual effects in first and later (second and third) lactations, and were used for estimation of heritabilities and repeatablilites. The experiences of the data quality and editing procedures showed that almost half of the data and about a quarter of the cows had to be excluded from the analyses due to incomplete or inconsistent information. However, much more data are available than is needed for accurate genetic parameter estimations. For the genetic analysis, a repeatability animal model was used that included the fixed effects of herd, year and season, lactation month, and milk yield. The repeatability coefficients were at a high level: highest for average flow rate, with estimates between 0.8 and 0.9. The estimated heritability coefficients were in the range of 0.37 to 0.48, 0.21 to 0.44, 0.09 to 0.26, and 0.02 to 0.07 for average flow rate, box time, milking interval, and number of milkings, respectively. The results from the present study unraveled large genetic variation in milkability traits. The genetic parameter estimates were well in agreement with previous studies of milkability, which proves the feasibility of using data from automatic milking systems for genetic analysis.     

Comparison of functional aspects in two automatic milking systems and auto-tandem milking parlors

Milk yield, milking frequency, intermilking interval, teat-cup attachment success rate, and length of the milking procedure are important functional aspects of automatic milking systems (AMS). In this study, these variables were compared for 2 different models of AMS (AMS-1, with free cow traffic, and AMS-2, with selectively guided cow traffic) and auto-tandem milking parlors (ATM) on 4 farms each. Data on milking-stall visits and milkings of 20 cows were recorded on 3 successive days by means of video observations. Data were evaluated with mixed-effects models. Milk yield did not differ among the 3 milking systems. Milking frequency in the AMS was 2.47/d [95% confidence interval (CI) = (2.38, 2.56)], and was significantly higher than the 2 milkings/d in ATM. Milking frequency was lower for cows with a higher number of days in milk (DIM) in AMS-1 [change of −0.057/10 DIM, CI = (−0.070, −0.044)], but remained constant for cows with varying DIM in AMS-2 [change of −0.003/10 DIM, CI = (−0.034, 0.027)]. As a consequence, milking frequency was higher in early lactation [by 0.603, CI = (0.102, 1.103)] and lower in late lactation in AMS-1 than in AMS-2 [by −0.397, CI = (−0.785, −0.008)]. The intermilking interval showed the opposite pattern. Teat-cup attachment was more successful in AMS-1 than in AMS-2 (98.4 vs. 94.3% of the milkings), with some variation among farms (range: AMS-1 96.2 to 99.5%; AMS-2 91.5 to 96.1%). The length of the entire milking process did not differ among the milking systems [454 s, CI = (430, 478)], although the preparation phase was longer [changes in comparison with ATM: in AMS-1 by a factor of 2.90, CI = (2.30, 3.65), and in AMS-2 by 5.15, CI = (4.09, 6.48)] and the actual milking phase was shorter in both AMS-1 and AMS-2 than in ATM [changes in comparison with ATM: in AMS-1 by a factor of 0.76, CI = (0.62, 0.94), and in AMS-2 by 0.75, CI = (0.60, 0.93)]. The admission [changes in comparison with ATM: in AMS-1 by a factor of 2.56, CI = (1.55, 4.22), and in AMS-2 by 3.07, CI = (1.86, 5.08)] and preparation phases lasted longer in AMS-2 than in AMS-1, whereas the time required by the cows to leave the milking stall did not differ among the systems [changes in comparison with ATM: in AMS-1 by a factor of 0.89, CI = (0.55, 1.44), and in AMS-2 by 1.02, CI = (0.63, 1.66)]. In conclusion, different technical approaches to automatic milking led to differences in teat-cup attachment success rates, in the duration of several phases of the milking process, and in milking frequency. The capacity of an AMS could be further improved by shortening the preparation phase and reducing the proportion of failed milkings.     

Association of milking interval and milk production rate in an automatic milking system

The primary aim of this research was to describe the association between milking interval (MI) and milk production rate (MPR) at the quarter level in a large commercial farm using an automatic milking system. A secondary aim was to determine whether a 2-h decrease in MI would increase MPR at the cow level in midlactation multiparous cows. Six months of data from 1,280 cows were used to assess the association between MI (h) and quarter MPR (kg/h). Increasing MI was associated with decreased MPR for early, mid, and late lactation, both primiparous and multiparous cows, and all 4 quarter positions and across time. The decrease in MPR is approximately 2%/h of increasing MI for multiparous cows and 1.5%/h for primiparous cows. Regardless of quarter, multiparous cows had a greater MPR than primiparous cows, and rear quarters had greater MPR than front quarters. An experiment to test the causal relationship between changing MI and cow-level MPR was conducted using 26 animal pairs matched on MI, days in milk, and milk yield. During the 21-d treatment period, the average MI of treatment cows was decreased by 2.4 h compared with control cows. In both the 21-d treatment and 42-d posttreatment periods, no significant difference was found in cow-level MPR between the treatment and control groups. Despite the negative association between increasing MI and MPR being consistent across all assessed days in milk windows and all quarters, results from this experiment suggest that intervention to decrease MI might require an MI change greater than 2 h or be applied in early lactation to significantly increase MPR.     

Association of quarter milking measurements and cow-level factors in an automatic milking system

The primary aim of this observational study, in a single herd milked using multiple automatic milking system units, was to describe associations of quarter milk yield variability and quarter peak milk flow rate with cow-level factors. Information from the current lactation of 1,549 primiparous and multiparous cows was collected from January to December 2015. Data from each individual milking used in the analysis included quarter milk yield (QMY), udder milk yield, quarter peak milk flow rate (QPMF), quarter average milk flow rate (QAMF), quarter milking time, and milking interval. Milking interval and milk yield were used to calculate milk production rate (kg/h) at the quarter and udder levels. We investigated associations between QPMF and milking interval, QPMF and days in milk, and QMY and QAMF. A strong association between QPMF and both QAMF and milking interval was observed. A moderate association was found between QPMF and stage of lactation. However, QMY was not a useful indicator of QPMF because of the weak association observed between these variables. In this study, rear quarter QPMF was significantly increased by 3% compared with front quarter QPMF (1.45 vs 1.41 kg/min). Quarter milk yield was calculated as a percentage contribution of total udder milk yield per 10-d in milk window and ranked from lowest to highest contribution. Quarter contribution to udder milk yield showed a high level of variability, with 39% of animals having all 4 quarters change contribution rank at least once during part of or the whole lactation. Only 14% of cows were observed to have no change in quarter rank. When quarter contribution was assessed, irrespective of physical position of quarter within the udder, the percent of highest to lowest contribution across the lactation was relatively stable. The standard deviation of quarter milk production rate for each cow was regressed against the same cow's peak udder milk production rate, within a lactation, to ascertain whether quarter milk production rate variance could be used to predict peak udder milk production rate. Knowledge of the intra-udder quarter milk production rate standard deviation for an individual cow is not useful in predicting peak udder milk production rate. Quarter milking time appears to be a useful indicator to predict the optimal order of teatcup attachment. Analysis from this large, single-herd population indicates that QPMF is associated with the cow-level factors milking interval and days in milk, and that intra-udder QMY is highly variable.     

Genetic evaluation of dairy sires for milking duration using electronically recorded milking times of their daughters

The potential of using electronically recorded data from on-farm milking parlor and herd management software programs for genetic evaluation of dairy sires for milking duration of their daughters was assessed in the present study. Single measurements of milking duration were collected weekly from 29 herds between June 1, 2003 and April 1, 2004. These included 73,547 observations corresponding to 10,152 Holstein cows from 1551 sires. Average milking duration for a single milking in our data set was 4.5 min. Estimated heritability of milking duration was 0.17, and predicted transmitting abilities (PTA) of individual sires ranged from -0.48 min for sires with the fastest milking daughters to 0.59 min for sires with the slowest milking daughters. The correlation between PTA for milking duration and PTA for somatic cell score (SCS) was -0.15, indicating that sires whose daughters milk most quickly also tend to transmit higher SCS to their progeny. Correlations between PTA milking duration and PTA for teat placement and teat length were -0.14 and 0.20, respectively, indicating that sires that transmit wide teat placement and long teats tend to have daughters that milk slowly. Based on the results presented herein, it appears that genetic selection based on objective, electronically recorded milking times is possible. This approach would greatly improve the quality and efficiency of data collection relative to conventional evaluations of milking speed, which are based on farmer surveys. The number of herds currently equipped to routinely capture milking times is limited, but this number is increasing very rapidly. Future research should focus on refinement of data reporting and validation systems, as well as estimation of the economic value of milking duration. This trait may have an intermediate optimum, because cows that milk too slowly will disrupt parlor flow and reduce milking efficiency, but cows that milk too quickly may be at greater risk for mastitis.     

Genetic parameters of milking temperament and milking speed in Canadian Holsteins

The objectives of this study were to estimate genetic parameters of milking temperament (MT) and milking speed (MS) in Canadian Holsteins and to examine associations of bull proofs of MT and MS with other economically important traits. First-lactation data consisted of 1,940,092 and 2,620,175 cows for MT and MS, respectively. Milking temperament and MS were recorded on a scale from 1 to 5 from very nervous to very calm and from very slow to very fast, respectively. The linear animal model included the fixed effects of herd-year-season of calving, stage of lactation, age at first calving, and the random effects of animal and residual. Both single-trait and bivariate analyses were carried out to estimate genetic parameters of MT and MS. For genetic parameter estimation, 20,000 records from randomly selected herds were used. However, for breeding value estimation, all records were included. Heritability values were 0.128 and 0.139 for MT and MS, respectively. The genetic correlation between MT and MS was 0.247. Analysis of bull proof correlation of MT and MS with other traits indicated that these traits were lowly correlated with a wide range of traits such as production, reproduction, conformation, and auxiliary traits.     

Genomic-based genetic parameters for milkability traits derived from automatic milking systems in North American Holstein cattle

The number of dairy farms adopting automatic milking systems (AMS) has considerably increased around the world aiming to reduce labor costs, improve cow welfare, increase overall performance, and generate a large amount of daily data, including production, behavior, health, and milk quality records. In this context, this study aimed to (1) estimate genomic-based variance components for milkability traits derived from AMS in North American Holstein cattle based on random regression models; and (2) derive and estimate genetic parameters for novel behavioral indicators based on AMS-derived data. A total of 1,752,713 daily records collected using 36 milking robot stations and 70,958 test-day records from 4,118 genotyped Holstein cows were used in this study. A total of 57,600 SNP remained after quality control. The daily-measured traits evaluated were milk yield (MY, kg), somatic cell score (SCS, score unit), milk electrical conductivity (EC, mS), milking efficiency (ME, kg/min), average milk flow rate (FR, kg/min), maximum milk flow rate (FRM, kg/min), milking time (MT, min), milking failures (MFAIL), and milking refusals (MREF). Variance components and genetic parameters for MY, SCS, ME, FR, FRM, MT, and EC were estimated using the AIREMLF90 software under a random regression model fitting a third-order Legendre orthogonal polynomial. A threshold Bayesian model using the THRGIBBS1F90 software was used for genetically evaluating MFAIL and MREF. The daily heritability estimates across days in milk (DIM) ranged from 0.07 to 0.28 for MY, 0.02 to 0.08 for SCS, 0.38 to 0.49 for EC, 0.45 to 0.56 for ME, 0.43 to 0.52 for FR, 0.47 to 0.58 for FRM, and 0.22 to 0.28 for MT. The estimates of heritability (± SD) for MFAIL and MREF were 0.02 ± 0.01 and 0.09 ± 0.01, respectively. Slight differences in the genetic correlations were observed across DIM for each trait. Strong and positive genetic correlations were observed among ME, FR, and FRM, with estimates ranging from 0.94 to 0.99. Also, moderate to high and negative genetic correlations (ranging from −0.48 to −0.86) were observed between MT and other traits such as SCS, ME, FR, and FRM. The genetic correlation (± SD) between MFAIL and MREF was 0.25 ± 0.02, indicating that both traits are influenced by different sets of genes. High and negative genetic correlations were observed between MFAIL and FR (−0.58 ± 0.02) and MFAIL and FRM (−0.56 ± 0.02), indicating that cows with more MFAIL are those with lower FR. The use of random regression models is a useful alternative for genetically evaluating AMS-derived traits measured throughout the lactation. All the milkability traits evaluated in this study are heritable and have demonstrated selective potential, suggesting that their use in dairy cattle breeding programs can improve dairy production efficiency in AMS.     

Short communication: Cow- and quarter-level milking indicators and their associations with clinical mastitis in an automatic milking system

The aim of this study was to assess associations of cow-, udder-, and quarter-level factors with the risk of clinical mastitis (CM) in cows managed using an automatic milking system. The primary hypothesis was that quarter peak milk flow rate (QPMF) is associated with increased risk of CM. A retrospective, case-control study was undertaken using data from a 1,549 cow farm using 20 automatic milking system units. All data from cows milked during March to December 2015 was available for analysis. Cases (n = 82) were defined as cows diagnosed with their first case of CM between 24 and 300 d in milk in the current lactation. Healthy control cows (n = 6/case) were randomly matched based on identical parity, existence of milk records during the day in milk period corresponding to the 15-d window before case diagnosis, average conductivity of <5.5 mS/cm in that window, and no history of CM in the current lactation. Logistic regression was used to estimate effects of parity, quarter position, day in milk at diagnosis of CM, average of QPMF 15 d before CM diagnosis, udder milk yield, and milking interval on the probability of CM. Of the 6 predictor variables included in the model, only milking interval was significantly associated with the increased risk of quarter CM. We concluded that in a high-production, freestall-housed North American herd using automatic milking system, milking interval, but not QPMF, was associated with risk of CM.     

Use of repeated measures analysis for evaluation of genetic background of dairy cattle behavior in automatic milking systems

Milking frequencies measured at official test days were used with repeated measurement analysis to reveal the environmental and genetic impact on the milking frequency of cows in automatic milking systems. Repeated measurements were 3 test-day observations per cow within days in milk (DIM) classes, with 1,216 cows in DIM class 1 (d 0 to 99), from 1,112 cows in DIM class 2 (d 100 to 199), and from 1,004 cows in DIM class 3 (d 200 to 299) kept in 15 farms. Selection criteria for models analyzing repeated measurements were Akaike and Schwarz Bayesian values, which favored the autoregressive [AR(1)] covariance structure over the compound symmetry model. Results from the AR(1) model indicated a significant impact of fixed herd and parity effects. Milking frequencies decreased with increasing parities and were greatest for first-parity cows. High daily milk yield was associated with higher milking frequencies. Heritabilities for milking frequency were 0.16, 0.19, and 0.22 in DIM classes 1, 2, and 3, respectively, from the AR(1) model. Higher heritabilities in the later stage of lactation were due to a substantial reduction of the residual variance. Genetic correlations between test-day milk yield and daily milking frequency were in the range of 0.46 to 0.57 for all DIM classes and between milking frequency and somatic cell score were near zero. For verification of results, milking frequencies of the same cows obtained from herd management programs were averaged within DIM classes. Heritabilities were slightly above the values from the AR(1) model. In conclusion, heritabilities for milking frequency in automatic milking systems are moderate enough to incorporate this behavioral trait in a combined breeding goal. The inevitable improvement of labor efficiency in dairy cattle farming demands such cows going easily and voluntarily in automatic milking systems.     

The relationship between milking interval and somatic cell count in automatic milking systems

The aim of this study was to explore whether, during automatic milking, milking interval or its variation is related to somatic cell count (SCC), even when corrected for effects of production, lactation stage, and parity. Data on milking interval and production level were available from the automatic milking systems of 151 farms. Data on SCC, parity, and lactation stage were derived from dairy herd improvement records of the same farms. Mainly due to incomplete records, data of 100 farms were used in the final analysis. For every cow, only 1 test day was used in the final analysis. Milking interval, the coefficient of variation of milking interval, production rate, the difference in production rate between short- and long-term, parity, days in milk, and some biologically relevant interactions were used in a linear mixed model with farm as random variable to assess their association with log10-transformed SCC. None of the interactions was significantly related to SCC, whereas all main effects were, and thus, stayed in the final model. The effect of milking interval was, although significant, not very strong, which shows that the effect of milking interval on SCC is marginal when corrected for the other variables. The variation in milking intervals was positively related with SCC, showing that the variation in milking interval is even more important than the milking interval itself. In the end, this study showed only a limited association between milking interval and SCC when milking with an automatic milking system.     

Effect of automatic milking systems on milk yield in a hot environment

A comparative study was performed to evaluate differences in milk yield between an automatic milking system (AMS) and a conventional herringbone milking parlor system. Two herds of Italian-Friesian cows were reared in the same barn, located in the Po Valley in northern Italy. Twenty-five primiparous cows and 10 multiparous cows were milked with an AMS, while at the same time 29 primiparous and 9 multiparous were milked twice daily in a milking parlor on the other side of the barn. A selection gate allowed cows to access the AMS only if the interval from last milking was >5 h. Multiparous cows in the AMS yielded more milk than multiparous cows in the milking parlor (34.2 ± 0.7 vs. 29.4 ± 0.6 kg/d). There was no difference in milk yield between primiparous cows in the AMS and in the milking parlor (28.9 ± 0.4 vs. 28.8 ± 0.3 kg/d). Milking frequency in the AMS was significantly higher in primiparous (2.8 ± 0.03) than in multiparous cows (2.5 ± 0.04). The hot season negatively affected milk yield; the milk yield reduction was higher for cows milked with the AMS (−4.5 ± 0.6 kg/d) than in the milking parlor (−3.0 ± 0.8 kg/d). In the AMS, milking frequency decreased during the hot season in primiparous cows (−0.3 ± 0.1). We concluded that a positive AMS effect on milk yield is possible, but that steps must be taken to alleviate the discomfort involved with attracting cows to the AMS.     

Milk leakage--an increased risk in automatic milking systems

Milk leakage (ML), or milk observed dripping or flowing from one or more teats between milkings, has been associated with increased risk of udder infections and mastitis in dairy cows. Preliminary observations indicate that ML might occur more often in automatic milking systems (AMS) than in conventional milking systems (CMS), but comparative data on the incidence of ML in AMS or in CMS are not available. Therefore, the occurrence of ML at various observation periods was studied in one AMS with cows housed in a free-stall barn in comparison to CMS with cows housed either in a free-stall barn or a tie-stall barn and milked at regular intervals in a herringbone milking parlor. Relationships between ML and other cow and management factors were also examined. In each of 2 yr, all cows (n = 230 total; 46 cows present both years) were observed at 2-h intervals during six 24-h periods. At least one ML occurred in 39.0 (AMS) vs. 11.2% (CMS) of individual cows and in 16.2 (AMS) vs. 2.9% (CMS) of 24-h cow days studied. Milk leakage was not related to milk production, parity, stage of lactation, or estrous status. However, in the AMS, 62% of primiparous and 28% of multiparous cows leaked milk at least once. Milk leakage occurred more often in rear than in forequarters. Cows were usually lying down when ML was observed, but intervals from previous milking varied, especially in AMS. In AMS, about one-fifth of the ML observations occurred < or = 4 h after milking, and half of those were associated with disturbances at the previous milking. Milk flow rate was higher in quarters leaking milk than in other quarters. Strategies to reduce milk leakage in AMS may be important to minimize potential risks of udder disease.     

Milk yield and milking station visits of primiparous versus multiparous cows on automatic milking system farms in the Upper Midwest United States

The objective of this study was to investigate milk yield and frequency of visits to the milking station of primiparous versus multiparous cows at different stages of lactation on farms with automatic milking systems (AMS) in the Upper Midwest United States. Forty farms were included in the study, and daily AMS software data were collected for 18 mo. For the investigation of milk yield and milking visits, stage of lactation was categorized into 14 periods, 7 d in length for the first 28 d in milk (DIM) and 30 d in length thereafter until 328 DIM. Cow traffic flow to the AMS (free or guided) was included in the model. For the evaluation of failures and refusals, stage of lactation was categorized into 6 periods, 7 d in length each for the first 28 DIM, and 2 periods of 150 d in length each thereafter until 328 DIM. Failures are milking station visits where a cow fails to be milked due to lack of machine attachment although it is time for the cow to be milked. Refusals are milking station visits before adequate time has passed since previous milking, thus the cow leaves the milking station without being milked. Data from lactation days beyond 328 DIM were excluded from the study. Primiparous cows in free-flow systems produced less milk than multiparous cows until the 11th stage of lactation and produced more milk from the 12th stage until the end of the study period. Primiparous cows in guided-flow systems produced less milk than multiparous cows all 14 stages of lactation, but were approaching the milk yield of multiparous cows at the end of the study period. This was a biologically normal lactation curve for primiparous cows. However, estimated peak ratio (primiparous vs. multiparous cows' peak milk yield) was lower than industry standards. Both traffic flow systems had fewer milking visits for primiparous cows compared with multiparous cows in early lactation. This lower milking frequency persisted until the 11th stage of lactation in free-flow systems. In guided-flow systems, primiparous cows were milked less frequently until the 5th stage of lactation, had similar milking frequency in the 6th stage of lactation, and were milked more frequently thereafter. Failures were greater for primiparous cows during all stages of lactation. However, the greatest differences were detected in the early stages of lactation. Primiparous cows had 0.067 more failures/cow per day on average than multiparous cows during wk 1 of lactation. For the remaining lactation stages, differences in failures ranged from 0.003 to 0.039. Refusals were less frequent (0.4 to 0.6/d) for primiparous cows during the first 2 wk of lactation, similar for wk 3 of lactation, and more frequent for the remaining lactation stages (0.10 to 0.14/d). Failures and refusals were only evaluated in free-flow systems. These findings appear to indicate a potential lagging performance for primiparous cows in early lactation as compared with multiparous cows. Additional investigation into improving the adaptation of primiparous cows to AMS in early lactation may be warranted.     

Increasing the revenues from automatic milking by using individual variation in milking characteristics

The objective of this study was to quantify individual variation in daily milk yield and milking duration in response to the length of the milking interval and to assess the economic potential of using this individual variation to optimize the use of an automated milking system. Random coefficient models were used to describe the individual effects of milking interval on daily milk yield and milking duration. The random coefficient models were fitted on a data set consisting of 4,915 records of normal uninterrupted milkings collected from 311 cows kept in 5 separate herds for 1 wk. The estimated random parameters showed considerable variation between individuals within herds in milk yield and milking duration in response to milking interval. In the actual situation, the herd consisted of 60 cows and the automatic milking system operated at an occupation rate (OR) of 64%. When maximizing daily milk revenues per automated milking system by optimizing individual milking intervals, the average milking interval was reduced from 0.421 d to 0.400 d, the daily milk yield at the herd level was increased from 1,883 to 1,909 kg/d, and milk revenues increased from €498 to €507/d. If an OR of 85% could be reached with the same herd size, the optimal milking interval would decrease to 0.238 d, milk yield would increase to 1,997 kg/d, and milk revenues would increase to €529/d. Consequently, more labor would be required for fetching the cows, and milking duration would increase. Alternatively, an OR of 85% could be achieved by increasing the herd size from 60 to 80 cows without decreasing the milking interval. Milk yield would then increase to 2,535 kg/d and milk revenues would increase to €673/d. For practical implementation on farms, a dynamic approach is recommended, by which the parameter estimates regarding the effect of interval length on milk yield and the effect of milk yield on milking duration are updated regularly and also the milk production response to concentrate intake is taken into account.     

Short communication: Genetic evaluation of milking speed for Brown Swiss dairy cattle in the United States

Genetic parameters and relative breeding values were estimated for milking speed of US Brown Swiss dairy cattle. Owner-recorded milking-speed scores on a scale of 1 (slow) to 8 (fast) were collected by the Brown Swiss Association as part of its linear type appraisal program starting in 2004. Data were 7,366 records for 6,666 cows in 393 herds. The pedigree file included information for 21,458 animals born in 1985 or later. Six unknown-parent groups that each included 4 birth years were defined. The model included fixed effects for herd appraisal date and parity-lactation stage and random effects for permanent environment, animal, and error. Within parity (1, 2, and ≥3), 6 groups were defined: unknown calving date, four 90-d lactation stages, and lactations with >400 d in milk. Heritability of 0.22 and repeatability of 0.42 were estimated by average-information REML; residual variance was 1.13. Little trend in estimated breeding value was found for cows born from 1999 through 2002. Although solutions increased with lactation stage for first-parity cows by 0.37, no clear trend was found for later parities. Genetic evaluations for milking speed were expressed as relative breeding values with a mean of 100 and a standard deviation of 5. The 121 bulls with ≥10 daughters had milking speed evaluations that ranged from 83 to 112 and had correlations of 0.56 with productive life evaluations and −0.40 with somatic cell score evaluations. The association of faster milking speed with lower somatic cell score was not expected. The moderate heritability found for milking speed indicates that the evaluations (first released in May 2006) should be useful in detecting bulls with slow-milking daughters.     

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.     

Effects of automatic cluster remover settings on average milking duration,milk flow,and milk yield

A crossover study design was used in five commercial dairy herds to study the effect of altering the switch point settings for automatic cluster remover units on the average duration of unit attachment, milk flow, and milk yield. Automatic cluster remover switch point settings were alternated, for 1-wk periods, between 0.50 and 0.64 kg/min (1.1 and 1.4 lb/min) in one herd and between 0.73 and 0.82 kg/min (1.6 and 1.8 lb/min) in the four remaining herds. Parlor data were captured at 329 separate milking sessions (range 39 to 92 per herd), representing 239,393 individual cow milkings. While increasing the automatic cluster remover switch point setting was not associated with a change in average milking duration in one herd, it had the effect of significantly reducing the average milking duration by between 10.2 and 15.6 s per cow in the remaining four herds. Milk flow was significantly increased at higher switch point settings for all five herds. Higher automatic cluster remover switch point settings did not have a negative effect on milk yield in any of the herds studied and, in fact, were associated with increased milk yield in two of the five herds. Decreasing milking duration while either maintaining or increasing the volume of milk harvested should ultimately lead to improved milking efficiency and parlor performance. Modifying systems to increase automatic cluster remover switch point settings offers an important potential opportunity to increase parlor efficiency in commercial dairy herds.     

The effect of manual forestripping on milking performance of Holstein dairy cows

The objective of this study was to evaluate the effects of forestripping as a premilking stimulation technique on milk yield, milking unit attachment time, and milk flow rates in Holstein dairy cattle. Multiparous Holstein cows (n = 24) were divided into two groups (HPE, high producing, early lactation; LPL, low producing, late lactation) based on prestudy milk yield and stage of lactation. Within the production group, cows were randomly assigned into treatment (n = 6) and control groups (n = 6) in a switchback design. Cows were milked twice daily and treatments were switched after 20 milkings. Premilking udder preparation for the treatment group was as follows: forestripping, predipping with 0.5% iodine, and drying with paper towels followed by unit attachment. Udder preparation for the control group was identical except forestripping was not performed. Data were analyzed by using the PROC Means and PROC Mixed models described by SAS. During the study, cows in the HPE group produced significantly more milk and had longer milking unit attachment times compared with cows in the LPL group. The milk flow rate was 0.36 kg/min faster for the HPE cows compared with the LPL cows. There was no significant effect of order of treatment administration on any outcome variable. There were no significant differences in milk yield, milk unit attachment time, or milk flow for animals that were forestripped compared with animals that were not forestripped. In this study, the addition of forestripping to an otherwise acceptable premilking udder preparation routine did not increase milking performance of multiparous Holstein dairy cows.