Effects of adding an automated monitoring device to the health screening of postpartum Holstein cows on survival and productive and reproductive performances

Evaluation of sensor-based health monitoring in dairy cows: Exploiting rumination times for health alerts around parturition

The use of sensor-based measures of rumination time as a parameter for early disease detection has received a lot of attention in scientific research. This study aimed to assess the accuracy of health alerts triggered by a sensor-based accelerometer system within 2 different management strategies on a commercial dairy farm. Multiparous Holstein cows were enrolled during the dry-off period and randomly allocated to conventional (CON) or sensor-based (SEN) management groups at calving. All cows were monitored for disorders for a minimum of 10 DIM following standardized operating procedures (SOP). The CON group (n = 199) followed an established monitoring protocol on the farm. The health alerts of this group were not available during the study but were later included in the analysis. The SEN group (n = 197) was only investigated when the sensor system triggered a health alert, and a more intensive monitoring approach was implemented according to the SOP. To analyze the efficiency of the health alerts in detecting disorders, the sensitivity (SE) and specificity (SP) of health alerts were determined for the CON group. In addition, all cows were divided into 3 subgroups based on their health status and the status of the health alerts in order to retrospectively compare the course of rumination time. Most health alerts (87%, n = 217) occurred on DIM 1. For the confirmation of diagnoses, health alerts showed SE and SP levels of 71% and 47% for CON cows. In SEN cows, SE of 71% and 75% and SP of 48% and 43% were found for the detection of ketosis and hypocalcemia, respectively. The rumination time of the subgroups was affected by DIM and the interaction between DIM and the status of health alert and health condition.

Use of rumination time in health risk assessment of prepartum dairy cows

The objectives of this observational cohort study were to evaluate the associations of rumination time (RT) in the last week of pregnancy with transition cow metabolism, inflammation, health, and subsequent milk production, reproduction, and culling. Pregnant nulliparous (n = 199) and parous (n = 337) cows were enrolled 21 d before the expected calving. RT and physical activity were monitored automatically by sensors from d -21 to 15 relative to calving. Blood samples were collected on d -14, -5, 4, 8, and 12 ± 1 relative to calving. Diagnoses of clinical health problems were performed by researchers from calving to 15 d in milk (DIM). In classification 1, cows were ranked based on average daily RT in the last week of pregnancy and classified into terciles as short RT (SRT), moderate RT (MRT), or long RT (LRT) for association analyses. In classification 2, RT deviation from the parity average was used in a receiver operating characteristic curve to identify the best threshold to predict postpartum clinical disease. Cows were then classified as above the threshold (AT) or below the threshold (BT). Compared with cows with LRT, cows with SRT had greater serum concentrations of NEFA (0.47 vs 0.40 ± 0.01 mmol/L), BHB (0.58 vs 0.52 ± 0.01 mmol/L), and haptoglobin (0.22 vs 0.18 ± 0.008 g/L) throughout the transition period, and reduced concentrations of glucose, cholesterol, albumin, and magnesium in a time-dependent manner. Parous cows with SRT had higher odds of postpartum clinical disease (adjusted odds ratio [AOR]: 3.7; 95% confidence interval [CI]: 2.1-6.4), lower odds of pregnancy by 210 DIM (AOR: 0.34; CI: 0.15-0.75), and lower milk production (46.9 vs 48.6 ± 0.5 kg/d) than parous cows with LRT. Deviation in prepartum RT had good predictive value for clinical disease in parous cows (area under the curve [AUC]: 0.65; CI: 0.60-0.71) but not in nulliparous (AUC: 0.51; CI: 0.42-0.59). Separation of parous cows according to the identified threshold (≤-53 min from the parity average) resulted in differences in serum concentrations of NEFA (AT = 0.31 ± 0.006, BT = 0.38 ± 0.014 mmol/L), BHB (AT = 0.49 ± 0.008, BT = 0.53 ± 0.015 mmol/L), and globulin (AT = 32.3 ± 0.3, BT = 34.8 ± 0.5 g/L) throughout the transition period, as well as in serum cholesterol, urea, magnesium, albumin, and haptoglobin in a time-dependent manner. BT parous cows had higher odds of clinical disease (AOR: 3.7; CI: 2.1-6.4), reduced hazard of pregnancy (AHR: 0.64, CI: 0.47-0.89), greater hazard of culling (AHR: 2.1, CI: 1.2-3.6), and lower milk production (46.3 ± 0.7 vs 48.5 ± 0.3 kg/d). External validation using data from 153 parous cows from a different herd and the established threshold in RT deviation (≤-53 min) resulted in similar predictive value, with the odds of postpartum disease 2.4 times greater in BT than AT (37.5 vs 20.1%). In conclusion, RT in the wk preceding calving was a reasonable predictor of postpartum health and future milk production, reproduction, and culling in parous cows but not in nulliparous cows.

Effects of targeted clinical examination based on alerts from automated health monitoring systems on herd health and performance of lactating dairy cows

Our objectives were to compare the proportion of lactating dairy cows diagnosed with health disorders (HD) and herd performance when using a health monitoring program designed to rely primarily but not exclusively on alerts from automated health monitoring (AHM) systems or a health monitoring program based primarily on systematic clinical examinations, milk yield monitoring, and visual observation of cows. In a clinical trial, at ∼30 d before expected parturition, nulliparous and parous Holstein cows, stratified by parity and days in gestation, were randomly assigned to the high-intensity clinical monitoring (HIC-M; n = 625) or automated monitoring (AUT-M; n = 624) treatment. Cows were fitted with a neck-attached rumination and physical activity monitoring tag, and individual daily milk yield data were collected from parlor milk meters. For cows in HIC-M, clinical examination was conducted daily until 10 d in milk (DIM) and then in response to milk yield reduction alerts or visual observation of clinical signs of HD over the course of 21 DIM. For cows in AUT-M, clinical examination until 21 DIM was because of health index (HI) score alerts and reduced milk yield alerts. The HI score alerts used were generated based on the manufacturer's settings for the system for the last 2-h period before cows were selected for examination. Visual observation of clinical signs of HD was used for identifying cows potentially missed by automated alerts. Binomial and quantitative data were analyzed by logistic regression and ANOVA with repeated measures, respectively. The percentage of cows diagnosed with at least 1 HD during the experimental treatments risk period tended to be greater and the incidence rate ratio of HD diagnosed was greater in the HIC-M than in the AUT-M treatment. We found no difference between treatments for cows that exited the herd up to 60 or 150 DIM, but more cows tended to exit the herd from 61 to 150 DIM in the HIC-M than in the AUT-M treatment. No differences were detectable between treatments in daily or total milk yield to 21 DIM or in weekly mean milk yield and total milk yield to 150 DIM. More cows were inseminated in estrus for first service if in the HIC-M treatment and had no HD diagnosed than if in the HIC-M treatment but with HD diagnosed, or in the AUT-M treatment and had no HD diagnosed. Cows in the AUT-M treatment with HD diagnosed did not differ from other groups. No differences between treatments were observed in pregnancies per artificial insemination or pregnancy loss for first service. Despite a reduction in the risk of diagnosis of HD, no evidence indicated that a health monitoring program that relied on AHM system alerts to select cows for clinical examination reduced herd performance compared with a more intensive program that included systematic clinical examinations of all cows for the first 10 DIM, reduced milk yield alerts, and visual observation. However, to obtain the same herd performance as with the HIC-M treatment, the AUT-M treatment required use of visual observation. In conclusion, a health monitoring program designed to rely primarily on targeted clinical examination based on alerts from automated health monitoring systems might be a feasible alternative to programs that rely more on clinical examination, provided that visual observation is used to identify cows not detected by automated alerts.

Metabolic-digestive clinical disorders of lactating dairy cows were associated with alterations of rumination, physical activity, and lying behavior monitored by an ear-attached sensor

The objective of this observational cohort study was to characterize the pattern of rumination time (RT), physical activity (PA), and lying time (LT) monitored by an automated health monitoring system, based on an ear-attached sensor, immediately before, during, and after clinical diagnosis (CD) of metabolic-digestive disorders. Sensor data were collected from 820 lactating Holstein cows monitored daily from calving up to 21 DIM for detection of health disorders (HD). Cows were grouped retrospectively in the no-clinical health disorder group (NCHD; n = 616) if no HD were diagnosed, or the metabolic-digestive group (METB-DIG; n = 58) if diagnosed with clinical ketosis or indigestion only. Cows with another clinical health disorder within -7 to +7 d of CD of displaced abomasum, clinical ketosis, or indigestion were included in the metabolic-digestive plus one group (METB-DIG+1; n = 25). Daily RT, PA, and LT, and absolute and relative changes within -7 to +7 d of CD were analyzed with linear mixed models with or without repeated measures. Rumination time and PA were smaller, and LT was greater for the METB-DIG and METB-DIG+1 group than for cows in the NCHD group for most days from -7 to +7 d of CD of HD. In general, daily RT, PA, and LT differences were larger between the METB-DIG+1 and NCHD groups than between the METB-DIG and NCHD groups. In most cases, RT and PA decreased to a nadir and LT increased to a peak immediately before or after CD of HD, with a return to levels similar to the NCHD group within 7 d of CD. Absolute values and relative changes from 5 d before CD to the day of the nadir for RT and PA or peak for LT were different for cows in the METB-DIG and METB-DIG+1 group than for the NCHD group. For PA, the METB-DIG+1 group had greater changes than the METB-DIG group. For cows affected by metabolic-digestive disorders, RT, PA, and LT on the day of CD and resolution of clinical signs were different than for cows in the NCHD group, but an increase in RT and PA or a decrease in LT was observed from the day of CD to the day of resolution of clinical signs. We conclude that dairy cows diagnosed with metabolic-digestive disorders including displaced abomasum, clinical ketosis, and indigestion presented substantial alterations in the pattern of RT, PA, and LT captured by an ear-attached sensor. Thus, automated health monitoring systems based on ear-attached sensors might be used as an aid for identifying cows with metabolic-digestive disorders. Moreover, RT, PA, and LT changes after CD might be positive indicators of recovery from metabolic-digestive disorders.

Metritis and clinical mastitis events in lactating dairy cows were associated with altered patterns of rumination, physical activity, and lying behavior monitored by an ear-attached sensor

Understanding changes in parameters recorded by automated health monitoring systems based on ear-attached sensors on the days immediately before and after diagnosis of metritis and clinical mastitis can help develop dairy cow health monitoring strategies. The objective of this observational cohort study was to characterize rumination time, physical activity, and lying time monitored by an ear-attached sensor before, during, and after clinical diagnosis (CD) of metritis and clinical mastitis. Lactating Holsteins monitored daily for 21 d in milk for detection of health disorders were retrospectively included in the no clinical health disorder group (NCHD; n = 616) if no disorders were diagnosed. Cows were included in the metritis (MET; n = 69) or clinical mastitis (MAST; n = 36) group if diagnosed only with nonsevere metritis (watery, reddish, and fetid uterine discharge with or without pyrexia) or nonsevere clinical mastitis (visibly abnormal milk secretion with or without signs of udder inflammation, with no pyrexia and no systemic signs of disease), respectively. Cows diagnosed with severe metritis (signs of metritis plus systemic signs of disease) or severe clinical mastitis (signs of mastitis plus pyrexia and systemic signs of disease), and cows diagnosed with nonsevere metritis or clinical mastitis plus another disorder within -7 to +7 d of CD of metritis or clinical mastitis diagnosis, were included in the metritis plus (MET+; n = 25) or the clinical mastitis plus (MAST+; n = 15) group, respectively. Cows were fitted with an ear-attached accelerometer to measure rumination time, physical activity, and lying time. Mean daily values, mean value absolute change, and relative change for the mean daily value from 3 or 5 d before CD to the nadir for cows with metritis and clinical mastitis, respectively, were analyzed with linear mixed models with or without repeated measures. Rumination time and physical activity were lesser, and lying time was greater for the MET and MET+ groups than for the NCHD group for most days from -4 to +7 d of CD of metritis. Generally, daily rumination time, physical activity, and lying time differences were greater and more prolonged between the MET+ and NCHD than between the MET and NCHD groups. Similarly, cows in the MAST and MAST+ groups had lesser rumination time and physical activity than cows in the NCHD group for several days before diagnosis. Lying time was greater for the MAST+ than the NCHD group on d -1 and 0 relative to CD. Absolute values and relative changes from 3 d before CD to the day of the nadir for rumination time and physical activity, or peak for lying time, were different for cows in the MET and MET+ groups than for the NCHD group. Similar results were observed for the MAST and MAST+ groups compared with the NCHD group. For cows with metritis, either an increase in rumination time and physical activity or a decrease in lying time was observed from the day of CD to resolution of clinical signs, but no changes were observed for the NCHD. Cows with clinical mastitis and the NCHD group had different rumination times, physical activity, and lying times on the day of CD and resolution of clinical signs, but cows with clinical mastitis had no significant changes from the day of CD to resolution of clinical signs. We conclude that cows affected by metritis and clinical mastitis presented substantial alterations of the patterns of rumination time, physical activity, and lying time captured by an ear-attached sensor. Thus, automated health monitoring systems based on ear-attached sensors might be used as an aid for identifying cows with metritis and clinical mastitis. Moreover, behavioral parameter changes after CD might be good indicators of resolution of clinical signs of metritis but not mastitis.

Association between Rumination Times Detected by an Ear Tag-Based Accelerometer System and Rumen Physiology in Dairy Cows

Monitoring rumination activity is considered a useful indicator for the early detection of diseases and metabolic disorders. Accelerometer-based sensor systems provide health alerts based on individual thresholds of rumination times in dairy cows. Detailed knowledge of the relationship between sensor-based rumination times and rumen physiology would help detect conspicuous animals and evaluate the treatment's success. This study aimed to investigate the association between sensor-based health alerts and rumen fluid characteristics in Holstein-Friesian cows at different stages of lactation. Rumen fluid was collected via a stomach tube from 63 pairs of cows with and without health alerts (ALRT vs NALRT). Pairs were matched based on the day of lactation, the number of lactations, and health criteria. Rumen fluid was collected during and after health alerts. The parameters of color, odor, consistency, pH, redox potential, sedimentation flotation time, and the number of protozoa were examined. Results showed differences between both groups in odor, rumen pH, sedimentation flotation time, and protozoan count at the first rumen fluid collection. Within the groups, greater variations in rumen fluid parameters were found for ALRT cows compared to NALRT cows. The interaction between health alert and stage of lactation did not affect the rumen fluid parameters.