Usefulness of differential somatic cell count for udder health monitoring: Association of differential somatic cell count and somatic cell score with quarter-level milk yield and milk components

Mastitis is the most common disease affecting dairy cattle and is associated with substantial milk loss. Somatic cell count has been widely used as an indicator of udder inflammation (e.g., subclinical mastitis). More recently, differential somatic cell count (DSCC) has become available as an auxiliary tool for milk quality control, with the potential to indicate different stages of inflammation when combined with SCC. This paper aimed to investigate the association of SCS and DSCC with milk yield and milk components at the quarter level. A convenience sample of 5 dairy herds using an automated milking system (AMS) was selected and visited every other week for milk sample collection. Fat, protein, and lactose content were analyzed at Lactanet (Canadian Network for Dairy Excellence, Sainte-Anne-de-Bellevue, Quebec, Canada) by mid-infrared spectroscopy using a MilkoScan FT6000. Determination of SCC and DSCC was also performed by Lactanet using a CombiFoss 7 DC instrument. Milk yield data were retrieved from the AMS. Given the hierarchical structure of the data, a linear mixed model was built with either milk yield or milk components as the outcomes. The results showed that elevated SCS, in combination with lower proportions of DSCC, was associated with the highest milk loss for primiparous and multiparous cows. For instance, the estimated milk loss for a quarter with a SCS of 7 and a DSCC of 55% was 1.45 kg/d compared with a quarter with a SCS of 2 and DSCC of 65% in multiparous cows. The association was similar when the outcome was the lactose content. Quarters with elevated SCS and lower DSCC had the lowest lactose percentage. No notable changes in fat content were observed across different SCS levels in multiparous cows, and quarters with higher DSCC had the lowest fat percentage in primiparous and multiparous cows. Protein content tended to be lower in quarters with increased SCS and low DSCC. In quarters from primiparous cows with DSCC levels above 70%, protein content showed slight variation across SCS levels. For multiparous cows, however, protein content remained relatively stable across different SCS and DSCC levels. In conclusion, our findings revealed that the combination of elevated SCS and low DSCC was associated with the most substantial milk loss. These results could be used to optimize udder health management.

Thermographic assessment of mastitis progression in sahiwal cattle: Insights into the patterns in the natural course of infection

Mastitis is a global concern in the dairy sector, demanding innovative solutions for effective management for quality lifetime milk production. In this study, infrared thermography (IRT) as a non-invasive technology was integrated into routine farm activities for continuous health monitoring of animals. For 30 days, we systematically monitored the udder health status in 40 Sahiwal cows (160 quarters), employing IRT along with the California Mastitis Test (CMT). We also assessed somatic cell count (SCC), microbial identification, and milk quality parameters of representative samples. The thermal imaging data was analyzed, considering both backward propagation from the 0th day to the -10th day and forward propagation from the 0th day to the +10th day. Our findings revealed that on the 0th day, the mean temperatures of the udder surface skin temperature (USST) and teat skin surface temperature (TSST) exhibited differences (p < 0.05) between the quarters affected by sub-clinical mastitis (SCM) and clinical mastitis (CM) in comparison to the healthy quarters, with the highest degree of difference observed. The observed temperature differences between CM and SCM quarters compared to healthy ranged from 1.8 to 3.62 °C and 0.98 to 3.23 °C for USST, and from 1.68 to 3.16 °C and 0.56 to 2.32 °C for TSST, respectively. Furthermore, our observations indicated that both udder and teat quarters responded differently to mastitis. A temperature rise of 1.37 °C in SCM quarters and 1.75 °C in CM quarters was observed between the -10th and -8th day relative to day 0, with the increase being more pronounced in the morning hours. Also, a notable temperature surge occurred during the -2nd and -1st days relative to the 0th day. The log10SCC values and milk quality parameters significantly differed (p < 0.05) between mastitis-affected and healthy samples. In addition, Staphylococcus spp. was identified as the predominant mastitis-causing pathogen in the bacteriological identification conducted in this study. Therefore, IRT efficiently assesses the initiation point of udder infection in Sahiwal cows, aiding in effective udder health management.

Estimation of Genetic Parameters for Milk Production Rate and Its Stability in Holstein Population

Milk production rate (MPR) refers to the rate of milk secretion per hour (kg/h), calculated from the harvested milk yield and milking interval, and it is considered an appropriate measure to evaluate the production potential of cows. The objective of this study was to estimate the phenotypic and genetic parameters of milk production rate traits. In this study, the milking records of 4760 Holstein cows were collected, and four milk yield traits and six milk production rate traits were defined. The MIXED procedure was used to detect the impacts of non-genetic effects on milk yield and milk production rate traits, including parity, measured season and lactation stage. Variance and covariance components for milk yield and milk production rate traits were estimated using a univariate linear repeatability model. Parity, measurement season and lactation stage had significant effects (p < 0.01) on milk yield, milk production rate and its stability. Milk yield and milk production traits had high heritability, and ranged from 0.25 to 0.39. The stability of milk production rate had low heritability (0.04~0.05). Milk production rate is beneficial for the devolving novel trait in dairy breeding and provides new insights for herd management and genetic selection of production performance of dairy cattle.

The mouthpiece chamber vacuum pattern indicates the cessation of milk flow and suits as an indicator to reduce teat end vacuum at a quarter level

We investigated the suitability of the quarter mouthpiece chamber vacuum (MPCV) as an indicator for cessation of quarter milk flow to potentially adjust the teat end vacuum at a quarter level. We tested the hypothesis that a MPCV increase is a clear indicator of quarter milk flow cessation. In addition, we tested if a quarter-individual vacuum reduction at MPCV increase reduces the mechanical effect on the teat. Ten dairy cows were milked twice daily with a quarter-specific vacuum supply with continuously high (51 kPa; TRT51) or low vacuum setting (41 kPa; TRT41), or high vacuum setting combined with a quarter-specific vacuum reduction by 10 kPa immediately after the quarter-specific MPCV increase (TRT51/41). Whole udder milk flow was continuously recorded. Each treatment was repeated at 4 subsequent milkings. The high vacuum settings (TRT51; TRT51/41) reached higher values in peak flow rate and average milk flow and consequently shorter machine-on time. The time from start of milking until the steep increase of the MPCV was shorter in front than rear quarters, and hence the time from start of MPCV increase until end of milking was longer in front than rear teats. Teat condition of the right front teats was measured for teat wall diameter by ultrasound and teat tissue thickness by cutimeter at 5 and 20 min after each experimental milking. The teat measurements were taken at the teat tip (distal barrel) and 2 cm above the teat tip (proximal barrel). The proximal teat wall diameter tended to be higher in TRT51 than in TRT41, both 5 and 20 min after milking. The distal teat wall diameter at 5 min was greater in TRT51 than in TRT41. In TRT51/41 the teat wall diameter at both locations was intermediate, not significantly different from either TRT51 or TRT41. The distal teat tissue thickness was greater in TRT51 than in TRT41, and tended to be greater in TRT51/41 than in TRT41 at 5 min. The proximal teat tissue thickness at 5 min was higher in TRT51 and TRT51/41 than in TRT41. The teat tissue thickness decreased from 5 to 20 min only in the proximal barrel. The quarter-individual MPCV increase appears to be a suitable indicator of the cessation of milk flow. The lack of a significant reduction of mechanical effect on the teat by a reduced vacuum of 41 kPa indicates that the vacuum level chosen may be still too high under conditions of a separate vacuum supply for each quarter, which prevents a vacuum drop caused by the whole udder milk flow.

Udder Ultrasonography of Dairy Cows: Investigating the Relationship between Echotexture, Blood Flow, Somatic Cell Count and Milk Yield during Dry Period and Lactation

Udder health of dairy cows is related to their productivity and welfare. The period from dry-off to calving and early lactation is crucial. Ultrasonography is a useful and practical tool for the examination of the mammary parenchyma and blood flow. This observational study investigated the relationship between udder echotexture features, blood flow volume (BFVol) in the milk vein, milk somatic cell count (SCC) and daily milk yield (DMY) from late lactation, throughout the dry period and consecutive early lactation. Seventeen repeated measurements were performed on twenty-one Holstein cows. The udder parenchyma was examined with B-mode ultrasonography. Udder echotexture was studied using 15 features: Numerical Pixel Value (NPV), Pixel Standard Deviation (PSD), Skewness, Excess, Contrast, Homogeneity, Correlation, Entropy, Run Percentage, Long-Run Emphasis, Grey Value Distribution, Runlength Distribution, Gradient Mean Value, Gradient Variance and Percentage of Non-zero Gradients. Blood flow in the milk vein was examined with spectral Doppler. Linear mixed-effects models were employed to investigate relationships between BFVol, udder echotexture features, SCC and DMY throughout the study period. Our models showed that a 1 kg increase in DMY was associated with a significant increase of 0.25 L/min in the expected BFVol and that a 1,000,000-cells/mL increase in SCC was associated with a significant BFVol decrease of 0.49 L/min, keeping all other variables constant. Multivariable models showed significant associations between DMY and NPV, between PSD and Long-Run Emphasis, and between SCC and NPV, PSD, Gradient Mean Value, Homogeneity, Gradient Variance and Entropy. In conclusion, udder echotexture and BFVol in the milk vein are related to SCC and milk yield. Ultrasonography can be used for the comprehensive assessment of udder health in support of precision dairy farming.

Optimising profitability and productivity of pasture-based dairy farms with automatic milking systems

There is a large variability in profitability and productivity between farms operating with automatic milking systems (AMS). The objectives of this study were to identify the physical factors associated with profitability and productivity of pasture-based AMS and quantify how changes in these factors would affect farm productivity. We utilised two different datasets collected between 2015 and 2019 with information from commercial pasture-based AMS farms. One contained annual physical and economic data from 14 AMS farms located in the main Australian dairy regions; the other contained monthly, detailed robot-system performance data from 23 AMS farms located across Australia, Ireland, New Zealand, and Chile. We used linear mixed models to identify the physical factors associated with different profitability (Model 1) and partial productivity measures (Model 2). Additionally, we conducted a Monte Carlo simulation to evaluate how changes in the physical factors would affect productivity. Our results from Model 1 showed that the two main factors associated with profitability in pasture-based AMS were milk harvested/robot (MH; kg milk/robot per day) and total labour on-farm (full-time equivalent). On average, Model 1 explained 69% of the variance in profitability. In turn, Model 2 showed that the main factors associated with MH were cows/robot, milk flow, milking frequency, milking time, and days in milk. Model 2 explained 90% of the variance in MH. The Monte Carlo simulation showed that if pasture-based AMS farms manage to increase the number of cows/robot from 54 (current average) to ∼ 70 (the average of the 25% highest performing farms), the probability of achieving high MH, and therefore profitability, would increase from 23% to 63%. This could make AMS more attractive for pasture-based systems and increase the rate of adoption of the technology.

Effect of transition to an automated milking system for a tie-stall barn on milk production and cow condition

The effect of the transition from a conventional milking (CM) system in a tie-stall barn to an automated milking (AM) system specialized for a tie-stall barn on milk yield, milk composition, teat-end score, body condition score (BCS), and lying time was evaluated. This study was conducted at a commercial dairy farm from -15 to 153 days after the installation of the AM system. Lactating cows milked with the CM system (average 85 heads) were gradually transitioned to the AM system, and finally, 57 heads were milked with the AM system. No obvious effects of the milking system on milk yield, milk components, BCS, and daily lying time were found based on comparisons between CM and AM cows in the same herd under the same situation of twice-daily milking. The linear mixed-effects model for teat-end scores showed higher scores for front than for rear teats, and small but negative estimates for independent variables of the day after AM, indicating worse teat-end condition for front than for rear teats and improvement of the condition with increased time since AM.

Association between Udder and Quarter Level Indicators and Milk Somatic Cell Count in Automatic Milking Systems

Simple Summary

In dairy cattle herds milked by automatic systems, the absence of a human milker originates the need for control systems to monitor the milking process and cow conditions. Modern milking robots are equipped with a lot of sensors that, at each milking (2.5–3 times a day), record data on milk yield and quality, milking efficiency, cow welfare, and health with particular focus to udder conditions. Mastitis is one of the most frequent and serious diseases of dairy cow that negatively affects milk quality and yield, reduces animal welfare, and often implies the use of antimicrobial drugs. At the moment, the alerting systems for mastitis risk is generally based on monitoring milk electrical conductivity, color, and/or temperature, but these indicators have limited reliability. Other information gathered by automatic sensors, already implemented in commercial robots, could be useful to early detect mastitis. Using a multivariate approach, our study showed that the deviations over time of milk electrical conductivity, milk yield, and milk flow of single quarters in comparison with the whole udder are potential indicators, alone or in combination, for altered udder conditions. The results could be useful for the development of new algorithms more effective in the early detection of mastitis.

Abstract

Automatic Milking Systems (AMS) record a lot of information, at udder and quarter level, which can be useful for improving the early detection of altered udder health conditions. A total of 752,000 records from 1003 lactating cows milked with two types of AMS in four farms were processed with the aim of identifying new indicators, starting from the variables provided by the AMS, useful to predict the risk of high milk somatic cell count (SCC). Considering the temporal pattern, the quarter vs. udder percentage difference in milk electrical conductivity showed an increase in the fourteen days preceding an official milk control higher than 300,000 SCC/mL. Similarly, deviations over time in quarter vs. udder milk yield, average milk flow, and milking time emerged as potential indicators for high SCC. The Logistic Analysis showed that Milk Production Rate (kg/h) and the within-cow within-milking percentage variations of single quarter vs. udder milk electrical conductivity, milk yield, and average milk flow are all risk factors for high milk SCC. The result suggests that these variables, alone or in combination, and their progression over time could be used to improve the early prediction of risk situations for udder health in AMS milked herds.

Short communication: Increasing the teatcup removal settings of the last milking quarter did not reduce box time in a pasture-based automatic milking system

This research followed our previous experimental and simulation work on the effect of different teatcup removal settings based on the rolling average milk flowrate and on milking duration at the quarter and udder levels. The aims of this experiment were to (1) quantify the differences in quarter milking duration in a pasture-based automatic milking system and (2) test the effect of increasing the milk flowrate at which teatcups are removed on the last milking quarter on udder milking duration, box time, milk production rate, and somatic cell count (SCC). Milking duration is an important component of efficiency and profitability in conventional and automatic milking systems. Additionally, quarters within an udder have significantly different milk yields and milking durations. This study used data from April to May 2018 of a pasture-based automatic milking system to evaluate quarter milking duration differences between quarters of an udder. Subsequently, we experimentally evaluated the use of 2 percentage-based teatcup removal settings applied to the last milking quarter (i.e., the last quarter with a teatcup still attached) on milking duration, box time, milk production rate, and SCC. The teatcup removal settings were at 30 or 50% of the last quarter's rolling average milk flowrate, while the other quarters remained at the 30% level. The selection of the quarter that would receive the more aggressive teatcup removal setting was determined by identifying the last quarter with a teatcup attached in every milking. Sixty-nine cows were divided into 2 groups that each received 1 of the 2 treatments for a 1-wk period and then switched to the other treatment for a second week. For the months of April and May 2018, quarter milking duration was significantly different between the quarter with the longest and the second longest milking duration within an udder. The quarter with the longest milking duration was milked on average 49 s longer than the quarter with second longest milking duration. However, in 36% of the milkings, the quarter with the longest milking duration was different from that of the previous milking. In the experimental part of this study, we saw no differences in milking duration, box time, milk production rate, or SCC between the 30 and 50% teatcup removal setting applied to the last milking quarter. Further research on using a variation of this percentage-based setting to target the quarter with the average longest milking duration or using an absolute milk flowrate switch-point or a maximum milking duration setting on the last quarter for reducing cow milking duration and box time is warranted.

Different vacuum levels, vacuum reduction during low milk flow, and different cluster detachment levels affect milking performance and teat condition in dairy cows

Traditionally, machine milking is performed at a constant vacuum supply. The system vacuum has to be set high enough to allow a sufficiently high vacuum at the teat end, despite the inevitable vacuum drop caused by milk flow. This leads to an increased vacuum load on the teat, especially when milk flow ceases at the end of milking. We tested the hypothesis that a milk flow-controlled adaptation of vacuum settings during milking allows even higher vacuum levels than are usually recommended during the period of high milk flow if the vacuum is reduced during low milk flow. Combined with a high cluster detachment flow rate level, increased milking performance is expected without an increased effect on teat tissue. Ten Holstein dairy cows were milked with a bucket milker with the claw vacuum adjusted in the absence of milk flow at a regular (43 kPa) and high (48 kPa) claw vacuum, with and without vacuum reduction during low milk flow (<2 kg/min), and combined with different cluster detachment levels (0.2, 0.6, and 1 kg/min). Each treatment was applied in each cow during 4 subsequent milkings in a randomized crossover design. Both claw vacuum and milk flow were continuously recorded throughout milking. Teat tissue thickness was measured using a cutimeter and teat wall diameter was measured by B-mode ultrasonography at 5 min after the end of milking. Milk yield was not affected by either vacuum settings or detachment levels. Machine-on time in treatments with vacuum reduction was shorter at high than at low vacuum and decreased with increasing detachment levels. Average milk flow was higher at high than at low vacuum and reached highest values in milkings without vacuum reduction at both vacuum levels. The average milk flow was higher at a cluster detachment of 1 kg/min than at 0.2 kg/min. However, both teat tissue thickness and (as a tendency) teat wall diameter at 5 min after cluster detachment were higher in milkings at high vacuum without vacuum reduction compared with all other treatments. In conclusion, high claw vacuum up to 48 kPa increases milking performance because of higher milk flow and reduced machine-on time. Negative effects of high vacuum on teat tissue are prevented by reducing vacuum during low milk flow (<2 kg/min) at the start and end of milking. Additionally, using a high cluster detachment level reduces machine-on time without a loss of harvested milk.

The relationships between udder-quarter somatic-cell counts and milk and milking parameters in cows managed with an automatic milking system

Context Some milking parameters such as milk yield, milk flow, milking duration, milk conductivity and somatic-cell count can all be listed as economically important traits in dairy practice. Aims The aim of the study was to investigate the relationships among lactation stage, lactation number, milking season and milk-performance traits at an udder-quarter level, including somatic-cell count (SCC), milk yield (MY), milking duration (MD), time in box (TB), milk flow (MF) and milk conductivity (MC). An additional aim was to analyse milking-parameter levels in milkings with a SCC lower and higher than 400000 cells/mL. Methods The study included an analysis of 1621582 successful milkings obtained from six herds of dairy cattle equipped with milking robots (AMS). Key results The study confirmed that MD and MY differed greatly between front and rear quarters. Rear quarters took longer to be milked but produced more milk. During the first 100 days of lactation, the primiparous cows spent more time in the robot than did multiparous cows; however, in the second and third lactations, older cows were spending more time in the AMS. For primiparous cows, MF increased with time, being the highest at the end of lactation (&gt;200 days in milk). A different trend has been found in the group of multiparous cows, where a steady decrease in MF was observed with subsequent lactation stages. A lower MC was recorded for cows in their first lactation than for multiparous cows. Data obtained from primiparous cows showed the highest MC to occur between 100 and 200 days of lactation. In the group of multiparous cows, MC increased with the lactation stage. It was also shown that the mean values obtained for MY, MD and TB were higher for cows with a lower SCC (&lt;400000). Correlations between lnSCC (the natural logarithm of SCC) and MY and between lnSCC and MD were negative and low, while those between lnSCC and MC and lnSCC and MF were positive. Moderate correlations were found between lnSCC and total MC. Conclusions The study confirmed the differences in the performance of different udder quarters in relation to MY, MD, TB, MF, MS and SCC. Implications AMS provides farmers with vast data on milk and milking parameters. By monitoring changes in these parameters, farmer may be able to predict the level of production of their herd and the health of cows.