Accuracy and reliability of mastitis detection with electrical conductivity and milk colour measurement in automatic milking

Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality

To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow's productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.

Sensitivity and Specificity for the Detection of Clinical Mastitis by Automatic Milking Systems in Bavarian Dairy Herds

In automatic milking systems (AMSs), the detection of clinical mastitis (CM) and the subsequent separation of abnormal milk should be reliably performed by commercial AMSs. Therefore, the objectives of this cross-sectional study were (1) to determine the sensitivity (SN) and specificity (SP) of CM detection of AMS by the four most common manufacturers in Bavarian dairy farms, and (2) to identify routinely collected cow data (AMS and monthly test day data of the regional Dairy Herd Improvement Association (DHIA)) that could improve the SN and SP of clinical mastitis detection. Bavarian dairy farms with AMS from the manufacturers DeLaval, GEA Farm Technologies, Lely, and Lemmer-Fullwood were recruited with the aim of sampling at least 40 cows with clinical mastitis per AMS manufacturer in addition to clinically healthy ones. During a single farm visit, cow-level milking information was first electronically extracted from each AMS and then all lactating cows examined for their udder health status in the barn. Clinical mastitis was defined as at least the presence of visibly abnormal milk. In addition, available DHIA test results from the previous six months were collected. None of the manufacturers provided a definition for clinical mastitis (i.e., visually abnormal milk), therefore, the SN and SP of AMS warning lists for udder health were assessed for each manufacturer individually, based on the clinical evaluation results. Generalized linear mixed models (GLMMs) with herd as random effect were used to determine the potential influence of routinely recorded parameters on SN and SP. A total of 7411 cows on 114 farms were assessed; of these, 7096 cows could be matched to AMS data and were included in the analysis. The prevalence of clinical mastitis was 3.4% (239 cows). When considering the 95% confidence interval (95% CI), all but one manufacturer achieved the minimum SN limit of >80%: DeLaval (SN: 61.4% (95% CI: 49.0%−72.8%)), GEA (75.9% (62.4%−86.5%)), Lely (78.2% (67.4%−86.8%)), and Lemmer-Fullwood (67.6% (50.2%−82.0%)). However, none of the evaluated AMSs achieved the minimum SP limit of 99%: DeLaval (SP: 89.3% (95% CI: 87.7%−90.7%)), GEA (79.2% (77.1%−81.2%)), Lely (86.2% (84.6%−87.7%)), and Lemmer-Fullwood (92.2% (90.8%−93.5%)). All AMS manufacturers’ robots showed an association of SP with cow classification based on somatic cell count (SCC) measurement from the last two DHIA test results: cows that were above the threshold of 100,000 cells/mL for subclinical mastitis on both test days had lower chances of being classified as healthy by the AMS compared to cows that were below the threshold. In conclusion, the detection of clinical mastitis cases was satisfactory across AMS manufacturers. However, the low SP will lead to unnecessarily discarded milk and increased workload to assess potentially false-positive mastitis cases. Based on the results of our study, farmers must evaluate all available data (test day data, AMS data, and daily assessment of their cows in the barn) to make decisions about individual cows and to ultimately ensure animal welfare, food quality, and the economic viability of their farm.

Intramammary antibiotics with complementary acupuncture decreases milk serum N-acetyl-beta-D-glucosaminidase concentrations in dairy cattle with subclinical mastitis

The objective of this research is to determine whether intramammary antibiotics with complementary acupuncture can reduce bovine mammary inflammation due to subclinical mastitis. Lactating cows were selected based on milk with a somatic cell count (SCC) greater than 500,000 cells/ml. Pre- and post-treatment milk samples were collected to determine SCC, aerobic bacterial content, milk ion conductivity, total protein, lactate dehydrogenase (LDH) and N-acetyl-beta-D-glucosaminidase (NAGase) concentrations. Milk serum was prepared from milk samples by double centrifugation. Concentrations of LDH and NAGase were determined using commercial enzyme-linked immunosorbent assays. Cows being treated with intramammary antibiotics were separated by random assignment to the acupuncture group (n = 10) and a no-acupuncture (control) group (n = 9). Both the acupuncture and control group were restrained for 30 min in a head catch 12 hr apart for a total of four times. For front quarters affected by subclinical mastitis, the acupuncture points used were spleen (SP) 12, SP 17, SP 18, SP 21, stomach (ST) 18 and conception vessel (CV) 12. For rear quarters affected by subclinical mastitis, the acupuncture points used were bladder (BL) 30, BL 30-1, BL 49, kidney (KI) 10, conception vessel (CV) 2 and CV 3. All parameters were compared using a Student t test. Significance was defined as p < .05. Compared to control cows, complementary acupuncture treatment reduced NAGase enzymatic activity in quarters of cows with subclinical mastitis. The reduction in NAGase suggests that complementary acupuncture treatment may be associated with healing of the damaged mammary epithelial cells, which are the primary source of NAGase activity in milk serum.

Changes in milk L-lactate, lactate dehydrogenase, serum albumin, and IgG during milk ejection and their association with somatic cell count

In both conventional and automatic milking systems (AMS), sensitive and reliable mastitis detection is important for profitable milk production. Mastitis detection parameters must be able to detect mastitis when the somatic cell count (SCC) is only slightly elevated. Owing to the pre-milking teat cleaning process in AMS, sampling cannot take place before the occurrence of alveolar milk ejection and importantly, this can affect the ability of parameters to detect mastitis. The aim of the present study was to examine the effect of alveolar milk ejection on l-lactate, lactate dehydrogenase (LDH), serum albumin (SA) and immunoglobulin G (IgG) compared with SCC, a commonly used indicator of mastitis. In this experiment, milk samples were collected every 20 s from one quarter during a 120-s manual teat stimulation in ten cows. Samples were analysed for SCC, l-lactate, LDH, SA and IgG. Quarters were grouped by low (<5·0 log10 cells/ml), mid (5·0–5·7 log10 cells/ml), and high (>5·7 log10 cells/ml) SCC using the sample at t=0 s. Neither l-lactate nor LDH could statistically differentiate between low and mid-SCC quarters, but there were a significant difference in levels between the high-SCC quarters and low and mid-SCC quarters. SA could not differentiate between the low and mid-SCC quarters, but the SA levels for the high SCC quarters remained statistically different compared with low and mid-SCC quarters throughout the experiment. IgG could statistically differentiate between low and mid-SCC, although the high-SCC quarters were not statistically different from the mid-SCC quarters after 60 s. In the high-SCC quarters, a decrease was shown in all parameters during milk ejection, after t=60 s. In conclusion, alveolar milk ejection reduces the effectiveness of detection parameters when compared with SCC. With the exception of IgG, the ability of other tested parameters was not satisfactory to differentiate between quarters with low to mid-SCC levels