Usefulness of the total and differential somatic cell count based udder health group concept for evaluating herd management practices and udder health in dairy herds

Subclinical mastitis and associated economic losses are a steady challenge in the dairy industry. The combination of the well-established somatic cell count (SCC) parameter and the new differential SCC (DSCC) opens up the possibility to categorise cows into four different udder health groups (UHG) based on results from a single milk recording/dairy herd improvement (DHI) test: UHG A: healthy/normal, ≤ 200,000 cells/mL and DSCC ≤ 65 %; B: suspicious, ≤ 200,000 cells/mL and DSCC > 65 %; C: (subclinical) mastitis, > 200,000 cells/mL and DSCC > 65 %; D: chronic/persistent mastitis, > 200,000 cells/mL and DSCC ≤ 65 %. The objectives of this study were to investigate 1) herd management practises among herds in different UHG categories and 2) herd performance parameters depending on the proportion of cows in UHG A. A total number of 41 herds in Styria, Austria, and Thuringia, Germany, were visited and interviewed for the first part of the study. The herds were categorised into 3 UHG categories depending on the proportion of cows in UHG A: I = >65 %; II = 55-65 %; and III = <55 %. Those with good udder health and best herd performance (+9 % milk yields, +11 % longevity, -35 % antibiotic treatments) applied distinct preventive measures, in particular excellent cubicle management and early antibiotic treatment (P < 0.05 each). However, preventive measures were applied to a lower extent in other herds. Herds were categorised differently using the UHG concept compared to SCC alone as the UHG-based categorisation allowed to clearer distinguish herds with medium-good from those with good udder health. A total number of 129,812 regular milk recording/DHI test day results of 890 Austrian and 183 German herds was used for the second part of the study. Results revealed a trend of increasing daily production as proportions of cows in UHG A increase. In conclusion, the UHG concept allowed clearer distinction of herds with good, medium-good, and poor udder health and could be used to promote practises leading to better animal health, less antibiotic treatments, and higher milk quality.

Udder health-related traits in cow milk: phenotypic variability and effect on milk yield and composition

The milk differential somatic cell count (DSCC) has been proposed in recent years as a mean by which to better monitor the udder health status (UHS) in dairy cows. Milk DSCC is the amount of polymorphonuclear neutrophils and lymphocytes contributing to the total somatic cell count (SCC) and can be determined on a routine basis in individual milk samples subjected to official analysis. In the present study, 522 865 milk test-day records of 77 143 cows were scrutinised to identify factors affecting the variability of both DSCC and SCC in Holstein Friesian, Jersey, Simmental and Rendena cows through linear mixed models. The fixed effects were breed, parity, lactation stage, sampling season, and all the first-order interactions of breed. Cow and herd-test-date were considered as random. Subsequently, four UHS groups were created (1: SCC ≤ 200 000 cells/mL and DSCC ≤ 65%; 2: SCC ≤ 200 000 cells/mL and DSCC > 65%; 3: SCC > 200 000 cells/mL and DSCC > 65%; 4: SCC > 200 000 cells/mL and DSCC ≤ 65%) to compare milk yield and quality. Milk SCS and DSCC differed across lactation, parity, sampling season and breed. In particular, Simmental cows had the lowest SCC and Jersey the lowest DSCC. Depending on the breed, UHS affected daily milk yield and composition to a different extent. The UHS group 4, i.e. the one grouping test-day records with high SCC and low DSCC, presented the lowest estimate of milk yield and lactose content no matter the breeds. Our findings support that udder health-related traits (SCS and DSCC) are useful information to improve udder health at individual cow and herd levels. Moreover, the combination of SCS and DSCC is useful to monitor milk yield and composition.

Associations between different udder health groups defined based on a combination of total and differential somatic cell count and the future udder health status of dairy cows

Mastitis, in particular in its subclinical form, which may spread unnoticeable within a herd, continues to be a major challenge in the dairy industry. Somatic cell count (SCC) is a broadly used proxy for subclinical mastitis. The recently introduced Differential SCC (DSCC) representing the combined proportion of polymorphonuclear neutrophils and lymphocytes as a percentage of total SCC, can be used in combination with SCC to categorise cows into four different udder health groups (UHG) depending on actual test day results: UHG A: healthy/normal, ≤200,000 cells/mL and DSCC ≤65 %; B: suspicious, ≤200,000 cells/mL and DSCC >65 %; C: (subclinical) mastitis, >200,000 cells/mL and DSCC >65 %; D: chronic/persistent mastitis, >200,000 cells/mL and DSCC ≤65 %. The objective of our study was to investigate to what extent the UHG aid in determining different statuses of cows: I) leaving herd before next test day, II) having >200,000 cells/mL at the next test day, and III) having ≤200,000 cells/mL at the next 3 test days. Multivariable logistic regression analysis was used to evaluate these statuses based on routinely generated dairy herd improvement (DHI) data from Austria, China, Estonia, Germany, and Spain. Cows in groups C (odds ratio (OR): 2.13, 95 % confidence interval (CI): 1.95-2.34) and, particularly, D (OR: 3.91, 95 % CI: 3.31-4.62) were significantly more likely to leave herds compared to cows in group A. Late-lactating cows indicated the highest likelihood (OR: 16.03, 95 % CI: 14.44-17.81) to leave herds in our analysis. Interestingly, we found that cows in UHG B had significantly higher odds (OR: 2.77, 95 % CI: 2.58-2.98) to have >200,000 cells/mL at the next test day compared to cows in group A. As anticipated, cows in UHG B (OR: 0.40, 95 % CI: 0.38-0.42), C (OR: 0.08, 95 % CI: 0.07-0.09), and D (OR: 0.16, 95 % CI: 0.14-0.19) each were significantly less likely to have ≤200,000 cells/mL at the next 3 test days compared to cows in group A. Above described results are an example from Germany, but the same trends could be seen across all countries considered in our study. In conclusion, our findings illustrate that the UHG concept reveals additional valuable information about udder health and culling based a single test day over working with SCC only. Actual decisions in day-to-day farm management that could be taken were not investigated here and need to be further explored.

Investigation of dairy cow performance in different udder health groups defined based on a combination of somatic cell count and differential somatic cell count

Mastitis is still the costliest disease in milk production. In particular, its subclinical form, which may spread unnoticeably within a herd, is a major challenge. Somatic cell count (SCC) is broadly used as an indicator for mastitis and thus the basis for udder health management programmes, e.g. through dairy herd improvement (DHI) testing. Since recently, differential somatic cell count (DSCC, representing the combined proportion of polymorphonuclear neutrophils and lymphocytes as a percentage of total SCC) is available in addition. Our study was aimed to investigate dairy cow performance in four newly defined udder health groups (UHG) based on SCC and DSCC results from DHI testing. In total, 961,835 test-day results generated in Austria, China, Estonia, Germany, and Spain between January 2019 and March 2020 were available for data analyses. Cows were categorised into four UHG depending on test day SCC and DSCC results (UHG A: healthy/normal, ≤200,000 cells/mL and ≤65 %; B: suspicious, ≤200,000 cells/mL and >65 %; C: mastitis, >200,000 cells/mL and >65 %; D: chronic/persistent mastitis, >200,000 cells/mL and ≤65 %). Linear mixed effect models were used to compare the performance of cows between the UHG based on the parameters milk weight, energy-corrected milk, fat, protein, lactose, and estimated milk value. Highest performance was found for cows in UHG A and ranged between 21.4 (Austria) and 38.3 kg per cow and day (Spain). Interestingly, cows in group B were significantly less productive (0.9-2.4% less daily milk production) compared to those in group A. Cows in groups C (6.0-9.8% less daily production compared to group A) and D were, as expected, even less productive with a particularly significant drop for cows in group D (17.5-38.5% less daily production). These trends could be observed in all countries involved in this study. Proportions of cows in the four different UHG differed between countries, changed slightly within countries depending on season, differed depending on parity and days in milk, and were seen to vary hugely between herds. In conclusion, this study demonstrates changes in performance of dairy cows depending on their udder health status as defined based on the combination of SCC and DSCC. In particular cows in UHG B and D are of interest as they cannot be identified working with SCC only. Nevertheless, the actual udder health management measures that could be taken based on the new UHG still require further investigation.

Evaluation of the new differential somatic cell count parameter as a rapid and inexpensive supplementary tool for udder health management through regular milk recording

Mastitis, particularly in its subclinical form, is the costliest disease in milk production causing substantial financial losses to the dairy industry, impairing animal welfare, and one of the main reasons for treating dairy cows with antimicrobials. Somatic cell count (SCC) is broadly used as an indicator for mastitis or intramammary infection (IMI) and is the basis for udder health management programmes, e.g., through monthly dairy herd improvement (DHI) testing. While SCC shows the total number of cells in milk, the new Differential SCC (DSCC) shows also the combined proportion of polymorphonuclear neutrophils (PMN) and lymphocytes as a percentage of the total SCC. In this study, we investigated the test characteristics of DSCC as a new supplementary indicator for mastitis screening. We collaborated with 11 herds totalling 969 dairy cows and collected metered DHI samples once a month over four months. The IMI status was assessed through analysis of aseptic composite hand-stripped samples using culture and followed by species identification using MALDI-ToF. The pathogens detected were categorised as 'no', 'minor', 'major', or 'other' pathogens. The results of our study showed that the DSCC parameter was significantly associated with the IMI status and the cow's parity but not with days in milk or test-day milk weight. On the other hand, SCC was associated with all these four factors. DSCC counts were significantly higher in samples of cows with IMI caused by major pathogens as compared to cows with no IMI or IMI by minor or other pathogens. SCC alone, DSCC alone, and the combination of DSCC and SCC were further compared based on test characteristics using exemplary cut-offs. For example, working with a cut-off of 200,000 cells/ for SCC alone compared to working with the combination of DSCC of 65 % and/or 200,000 cells/mL to classify cows as infected by major pathogens, the sensitivity increased from 78 % to 92 % and the specificity decreased from 87 % to 66 %. With the combination, the positive predictive value changed from 52 % to 34 %, and the negative predictive value stayed at the same level (96 % vs 98 %). In summary, our study provides first insights on test characteristics of the DSCC parameter used in combination with the well-established SCC for monitoring udder health using DHI testing. This combination opens up the possibility to further improve udder health monitoring programmes (e.g., improved identification of IMI caused by major pathogens) but more work on the subject is needed.

Investigation of differential somatic cell count as a potential new supplementary indicator to somatic cell count for identification of intramammary infection in dairy cows at the end of the lactation period

The objective of this study was to investigate the new differential somatic cell count (DSCC) as a supplementary indicator to SCC for the identification of intramammary infection (IMI) in dairy cows at the end of the lactation period. Different approaches for identification of cows with IMI (i.e. often based on SCC) and targeted antimicrobial treatment of those rather than of all cows have been developed (i.e. selective dry cow treatment). Recently, DSCC representing the proportion of polymorphonuclear neutrophils and lymphocytes, has been introduced as an additional indicator for the presence of IMI. We used the last dairy herd improvement (DHI) samples taken within 42 d prior to dry-off as well as hand-stripped samples collected within 5 days prior to dry-off to measure DSCC and SCC. The bacteriological status was determined using quarter foremilk samples collected close to drying off. In total, 582 cows were dried off during our study but not all of them could be included in the data analysis for different reasons (e.g. incomplete data, samples too old for reliable determination of SCC and DSCC, contamination). Eventually, the final data set comprised of 310 cows of which 64 and 149 were infected with major and minor pathogens, respectively, and 97 were uninfected. The area under receiver-operating characteristics curves (AUC) were calculated to compare the diagnostic abilities of the different parameters. The AUC for identification of IMI by major pathogens when using the combination of DSCC and SCC was 0.64 compared to 0.62 for SCC alone and 0.62 for DSCC alone. The different parameters were further compared based on test characteristics and predictive values. For example, classifying cows as infected based on a cut-off of 200,000 cells/ml for SCC alone and in terms of using DSCC combined with SCC based on either >60% and/or >200,000 cells/ml, the sensitivity changed from 47 to 66% and the specificity from 74 to 54%. At the same time, the negative predictive value changed from 84 to 86% and the positive predictive value from 32 to 27%. Test characteristics and predictive values of the parameters DSCC and SCC were similar using DHI and hand-stripped samples. In conclusion, our study provides first indications on test characteristics and predictive values for the combination of DSCC and SCC. However, more work on this subject and the actual practical application is needed.