Effects of Theileria orientalis Infection on Health Status and Productivity of Dairy Cows Reared inside Barns.

The objective of the present study was to investigate the effects of Theileria orientalis on the severity of anemia, the prevalence of disease within 21 days after calving and productivity in cows raised inside barns. This longitudinal observational study, which was conducted on a commercial dairy farm in Japan, involved 627 Holstein cows subjected to PCR analysis for T. orientalis. In study 1, we collected blood samples from 156 sick cows within 21 days after calving, and we found the prevalence of T. orientalis infection to be 65.4%. In study 2, we randomly selected 471 cows during the dry period and collected blood samples to conduct PCR analysis for T. orientalis and determined the prevalence of T. orientalis infection to be 69.0%. Compared with the values for the T. orientalis-uninfected group, the T. orientalis-infected cows had significantly decreased hemoglobin concentrations and hematocrit, but there were no differences in the other complete blood count indexes between the two groups. In addition, there were no differences in productivity and the prevalence of major diseases between the T. orientalis-infected and uninfected cows. In summary, T. orientalis had few effects on anemia, productivity and the health of cows raised inside a barn.

Epidemiological study to investigate the incidence and prevalence of clinical mastitis, peracute mastitis, metabolic disorders and peripartum disorders, on a dairy farm in a temperate zone in Japan.

BACKGROUND: Our aim was to investigate the incidence and prevalence of clinical mastitis, peracute mastitis, metabolic disorders, and peripartum disorders, and to examine factors affecting the prevalence of each disease in cows raised on a large dairy farm in a temperate climate in Japan. The present study was performed on a large commercial dairy farm with approximately 2500 Holstein cows. Data were collected from 2014 to 2018, and involved 9663 calving records for 4256 cows. RESULTS: The incidence rate on the farm was 21.9% for clinical mastitis, 10.4% for peracute mastitis, 2.9% for metabolic disorders, and 3.2% for peripartum disorders. The prevalence rates for clinical mastitis, peracute mastitis, metabolic disorders, and peripartum disorders were 28.0, 13.3, 3.7, and 4.0%, respectively. In all four diseases, the probability of time to occurrence for each disease was associated with parity and calving season (P < 0.05). Regarding metabolic disorders and peripartum disorders, the probability of occurrence decreased during the first 10 days after calving. CONCLUSIONS: Our results showed that clinical mastitis occurred most often in this temperate zone, and that metabolic disorders and peripartum disorders occurred from calving to day 10 post-calving.

Technical note: Calving prediction in dairy cattle based on continuous measurements of ventral tail base skin temperature using supervised machine learning.

In this study, we developed a calving prediction model based on continuous measurements of ventral tail base skin temperature (ST) with supervised machine learning and evaluated the predictive ability of the model in 2 dairy farms with distinct cattle management practices. The ST data were collected at 2- or 10-min intervals from 105 and 33 pregnant cattle (mean ± standard deviation: 2.2 ± 1.8 parities) reared in farms A (freestall barn, in a temperate climate) and B (tiestall barn, in a subarctic climate), respectively. After extracting maximum hourly ST, the change in values was expressed as residual ST (rST = actual hourly ST - mean ST for the same hour on the previous 3 d) and analyzed. In both farms, rST decreased in a biphasic manner before calving. Briefly, an ambient temperature-independent gradual decrease occurred from around 36 to 16 h before calving, and an ambient temperature-dependent sharp decrease occurred from around 6 h before until calving. To make a universal calving prediction model, training data were prepared from pregnant cattle under different ambient temperatures (10 data sets were randomly selected from each of the 3 ambient temperature groups: <15°C, ≥15°C to <25°C, and ≥25°C in farm A). An hourly calving prediction model was then constructed with the training data by support vector machine based on 15 features extracted from sensing data (indicative of pre-calving rST changes) and 1 feature from non-sensor-based data (days to expected calving date). When the prediction model was applied to the data that were not part of the training process, calving within the next 24 h was predicted with sensitivities and precisions of 85.3% and 71.9% in farm A (n = 75), and 81.8% and 67.5% in farm B (n = 33), respectively. No differences were observed in means and variances of intervals from the calving alerts to actual calving between farms (12.7 ± 5.8 and 13.0 ± 5.6 h in farms A and B, respectively). Above all, a calving prediction model based on continuous measurement of ST with supervised machine learning has the potential to achieve effective calving prediction, irrespective of the rearing condition in dairy cattle.

Exploration of factors determining milk production by Holstein cows raised on a dairy farm in a temperate climate area.

In this study, we examined factors that affected milk production by cows raised in a temperate climate area. We conducted this study on a large dairy farm containing approximately 2000 Holstein cows, located in a temperate climate area. We collected 7803 calving records for 4069 cows from 2012 to 2016. We then assessed the effect of hot weather on milk yield by examining three climate factors: season, maximum temperature (MAX), and the temperature and humidity index (THI). We found that increases in heat stress caused linear decreases in milk yield (P < 0.05). Additionally, the effects of the three climate factors on milk yield varied depending on cow parity and days open (P < 0.05). Thus, management procedures should consider cow parity and lactating stage to minimize the negative effects of heat stress on milk production. We also found that the lowest Akaike information criterion value was obtained in our model when using THI for 305-day milk yield. This suggests that THI is a more accurate variable for evaluating heat stress than MAX or season.

Evaluation of the natural vertical transmission of Theileria orientalis.

Bovine theileriosis, caused by Theileria orientalis, is endemic from East Asia to Oceania. Even though the disease is mainly transmitted by Haemaphysalis ticks, the T. orientalis parasite can also be transmitted vertically. To develop proper control measures, the frequency of each transmission route must be elucidated. However, the frequency of vertical transmission, including transplacental transmission, of T. orientalis in naturally infected cattle is still controversial. This study aimed to clarify the frequency of the vertical transmission of T. orientalis in naturally infected cattle. Blood samples were collected from 204 T. orientalis-infected dams and their 211 newborn calves (including 7 sets of twins) within the first 24 h as well as 30 days after birth. Furthermore, 31 and 24 calves born to T. orientalis-infected and uninfected dams, respectively, were continuously surveyed for infection until 5 months of age. A total of 5 (2.4%) dams were diagnosed with mild anemia, whereas most of the dams were asymptomatic based on hematological examination and clinical signs. PCR analysis was performed on whole blood to determine the presence of T. orientalis in calves, and no calves were PCR positive 0 and 30 days after birth. However, 9.6% and 0% of the calves born to T. orientalis-infected and uninfected dams, respectively, tested positive at 3 and 5 months of age. The sampled calves were fed in-house, and the survey was conducted during the cold season; thus, horizontal transmission through blood-sucking insects rarely occurred. Therefore, the vertical transmission of T. orientalis took as long as 3 months to become detectable by PCR and occurred in approximately 10% of field cattle.