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 significant 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 (SOPs). 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 according to the SOPs was implemented. 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 the status of the health alerts and their health status, 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, a 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.

Application of behavior data to predictive exploratory models of metritis self-cure and treatment failure in dairy cows

The objective was to evaluate the performance of exploratory models containing routinely available on-farm data, behavior data, and the combination of both to predict metritis self-cure (SC) and treatment failure (TF). Holstein cows (n = 1,061) were fitted with a collar-mounted automated- health monitoring device (AHMD) from -21 ± 3 to 60 ± 3 d relative to calving to monitor rumination and activity. Cows were examined for diagnosis of metritis at 4 ± 1, 7 ± 1, and 9 ± 1 DIM. Cows diagnosed with metritis (n = 132), characterized by watery, fetid, reddish/brownish vaginal discharge (VD) were randomly allocated to one of 2 treatments: Control (CON; n = 62) - no treatment at the time of metritis diagnosis (d 0); Ceftiofur (CEF; n = 70) - subcutaneous injection of 6.6 mg/kg of ceftiofur crystalline-free acid on d 0 and 3 relative to diagnosis. Cure was determined 12 d after diagnosis and was considered when VD became mucoid and not fetid. Cows in CON were used to determine SC and cows in CEF were used to determine TF. Univariable analyses were performed using farm-collected data (parity, calving season, calving-related disorders, body condition score, rectal temperature, and days in milk at metritis diagnosis) and behavior data (i.e., daily averages of rumination, activity generated by AHMD, and derived variables) to assess their association with metritis SC or TF. Variables with a P ≤ 0.20 were included in the multivariable logistic regression exploratory models. To predict SC, the area under the curve (AUC) for the exploratory model containing only data routinely available on-farm was 0.75. The final exploratory model to predict SC combining routinely available on-farm data and behavior data increased the AUC to 0.87, sensitivity (Se) 87% and specificity (Sp) 71%. To predict TF, the AUC for the exploratory model containing only data routinely available on-farm was 0.90. The final exploratory model combining routinely available on-farm data and behavior data increased the AUC to 0.93, Se of 93% and Sp of 82%. Cross-validation analysis revealed that generalizability of the exploratory models was poor, which indicates that the findings are applicable to the conditions of the present exploratory study. In summary, the addition of behavior data contributed to increasing the prediction of SC and TF. Developing and validating accurate prediction models for SC could lead to a reduction in antimicrobial use, whereas accurate prediction of cows that would have TF may allow for better management decisions.

The Prediction of Clinical Mastitis in Dairy Cows Based on Milk Yield, Rumination Time, and Milk Electrical Conductivity Using Machine Learning Algorithms

In commercial dairy farms, mastitis is associated with increased antimicrobial use and associated resistance, which may affect milk production. This study aimed to develop sensor-based prediction models for naturally occurring clinical bovine mastitis using nine machine learning algorithms with data from 447 mastitic and 2146 healthy cows obtained from five commercial farms in Northeast China. The variables were related to daily activity, rumination time, and daily milk yield of cows, as well as milk electrical conductivity. Both Z-standardized and non-standardized datasets pertaining to four specific stages of lactation were used to train and test prediction models. For all four subgroups, the Z-standardized dataset yielded better results than those of the non-standardized one, with the multilayer artificial neural net algorithm showing the best performance. Variables of importance had a similar rank in this algorithm, indicating the consistency of these variables as predictors for bovine mastitis in commercial farms with similar automatic systems. Moreover, the peak milk yield (PMY) of mastitic cows was significantly higher than that of healthy cows (p < 0.005), indicating that high-yielding cattle are more prone to mastitis. Our results show that machine learning algorithms are effective tools for predicting mastitis in dairy cows for immediate intervention and management in commercial farms.

Alterations in Rumination, Eating, Drinking and Locomotion Behavior in Dairy Cows Affected by Subclinical Ketosis and Subclinical Acidosis

This study delves into the effects of subclinical ketosis (SCK) and subclinical acidosis (SCA) on various parameters related to dairy cow rumination, eating, drinking and locomotion behavior. The research hypothesized that these subclinical metabolic disorders could affect behaviors such as rumination, feeding, and locomotion. A total of 320 dairy cows, with a focus on those in their second or subsequent lactation, producing an average of 12,000 kg/year milk in their previous lactation, were examined. These cows were classified into three groups: those with SCK, those with SCA, and healthy cows. The health status of the cows was determined based on the milk fat-protein ratio, blood beta-hydroxybutyrate, and the results of clinical examinations performed by a veterinarian. The data collected during the study included parameters from the RumiWatch sensors. The results revealed significant differences between the cows affected by SCK and the healthy cows, with reductions observed in the rumination time (17.47%) and various eating and chewing behaviors. These changes indicated that SCK had a substantial impact on the cows' behavior. In the context of SCA, the study found significant reductions in Eating Time 2 (ET2) of 36.84% when compared to the healthy cows. Additionally, Eating Chews 2 (EC2) exhibited a significant reduction in the SCA group, with an average of 312.06 units (±17.93), compared to the healthy group's average of 504.20 units (±18.87). These findings emphasize that SCA influences feeding behaviors and chewing activity, which can have implications for nutrient intake and overall cow health. The study also highlights the considerable impact of SCK on locomotion parameters, as the cows with SCK exhibited a 27.36% reduction in the walking time levels. These cows also displayed reductions in the Walking Time (WT), Other Activity Time (OAT), and Activity Change (AC). In conclusion, this research underscores the critical need for advanced strategies to prevent and manage subclinical metabolic disorders within the dairy farming industry. The study findings have far-reaching implications for enhancing the well-being and performance of dairy cattle. Effective management practices and detection methods are essential to mitigate the impact of SCK and SCA on dairy cow health and productivity, ultimately benefiting the dairy farming sector.

Combination of milk variables and on-farm data as an improved diagnostic tool for metabolic status evaluation in dairy cattle during the transition period

Milk composition, particularly milk fatty acids, has been extensively studied as an indicator of the metabolic status of dairy cows during early lactation. In addition to milk biomarkers, on-farm sensor data also hold potential in providing insights into the metabolic health status of cows. While numerous studies have explored the collection of a wide range of sensor data from cows, the combination of milk biomarkers and on-farm sensor data remains relatively underexplored. Therefore, this study aims to identify associations between metabolic blood variables, milk variables, and various on-farm sensor data. Second, it seeks to examine the supplementary or substitutive potential of these data sources. Therefore, data from 85 lactations on metabolic status and on-farm data were collected during 3 wk before calving up to 5 wk after calving. Blood samples were taken on d 3, 6, 9, and 21 after calving for determination of β-hydroxybutyrate (BHB), nonesterified fatty acids (NEFA), glucose, insulin-like growth factor-1 (IGF-1), insulin, and fructosamine. Milk samples were taken during the first 3 wk in lactation and analyzed by mid-infrared for fat, protein, lactose, urea, milk fatty acids, and BHB. Walking activity, feed intake, and body condition score (BCS) were monitored throughout the study. Linear mixed effect models were used to study the association between blood variables and (1) milk variables (i.e., milk models); (2) on-farm data (i.e., on-farm models) consisting of activity and dry matter intake analyzed during the dry period ([D]) and lactation ([L]) and BCS only analyzed during the dry period ([D]); and (3) the combination of both. In addition, to assess whether milk variables can clarify unexplained variation from the on-farm model and vice versa, Pearson marginal residuals from the milk and on-farm models were extracted and related to the on-farm and milk variables, respectively. The milk models had higher coefficient of determination (R2) than the on-farm models, except for IGF-1 and fructosamine. The highest marginal R2 values were found for BHB, glucose, and NEFA (0.508, 0.427, and 0.303 vs. 0.468, 0.358, and 0.225 for the milk models and on-farm models, respectively). Combining milk and on-farm data particularly increased R2 values of models assessing blood BHB, glucose, and NEFA concentrations with the fixed effects of the milk and on-farm variables mutually having marginal R2 values of 0.608, 0.566, and 0.327, respectively. Milk C18:1 was confirmed as an important milk variable in all models, but particularly for blood NEFA prediction. On-farm data were considerably more capable of describing the IGF-1 concentration than milk data (marginal R2 of 0.192 vs. 0.086), mainly due to dry matter intake before calving. The BCS [D] was the most important on-farm variable in relation to blood BHB and NEFA and could explain additional variation in blood BHB concentration compared with models solely based on milk variables. This study has shown that on-farm data combined with milk data can provide additional information concerning the metabolic health status of dairy cows. On-farm data are of interest to be further studied in predictive modeling, particularly because early warning predictions using milk data are highly challenging or even missing.

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.

Evidence of personality-dependent plasticity in dairy calf movement behaviours derived from automated data collection

Individual consistency in behaviour, known as animal personality, and behavioural plasticity in response to environmental changes are important factors shaping individual behaviour. Correlations between them, called personality-dependent plasticity, indicate that personality can affect individual reactions to the environment. In farm animals this could impact the response to management changes or stressors but has not yet been investigated. Here we use ultra-wideband location sensors to measure personality and plasticity in the movement of 90 dairy calves for up to 56 days starting in small pair-housing enclosures, and subsequently moved to larger social housings. For the first time calves were shown to differ in personality and plasticity of movement when changing housing. There were significant correlations between personality and plasticity for distance travelled (0.57), meaning that individuals that travelled the furthest in the pair housing increased their movement more in the social groups, and for residence time (- 0.65) as those that stayed in the same area more decreased more with the change in housing, demonstrating personality-dependent plasticity. Additionally, calves conformed to their pen-mate's behaviour in pairs, but this did not continue in the groups. Therefore, personality, plasticity and social effects impact how farm animals respond to changes and can inform management decisions.

Association between Prepartum Alerts Generated Using a Commercial Monitoring System and Health and Production Outcomes in Multiparous Dairy Cows in Five UK Herds

Identifying cows that are at greater risk for disease prior to calving would be a valuable addition to transition management. Prior to the commercial release of software features in an automated behavioral monitoring system, designed to identify cows in the dry period at greater risk of disease postpartum, a retrospective analysis was carried out in five dairy herds to evaluate whether the software could identify prepartum cows that subsequently received health treatments postpartum and whether prepartum alerts (transition alerts) are associated with a reduction in milk production in the subsequent lactation. Herd management and production records were analyzed for cows receiving treatment in the first 21 d of lactation (days in milk, DIM) for clinical mastitis, reproductive tract disease (metritis, retained fetal membranes), metabolic disease (hypocalcemia, ketosis and displaced abomasum) and for cows exiting the herd by 60 DIM. Data was gathered for 986 cows, 382 (38.7%) of which received a transition alert and 604 (61.3%) that did not. During the first 21 DIM 312 (31.6%) cows went on to receive a disease treatment, of these 51.9% (n = 162/312) were transition alert cows and 48.1% (n = 150/312) non-transition alert cows, while 8.6% (n = 33/382) alert cows exited the herd by 60 DIM compared to 4.8% (n = 29/604) of cows that did not receive an alert. A cow receiving a transition alert (OR = 1.76, 95% confidence interval (CI) = 1.27-2.44) and increasing parity (OR = 2.03, 95% CI = 1.44-2.86) were both associated with increased risk of receiving a disease treatment in the first 21 DIM. The occurrence of a transition alert was negatively associated with both week 4 milk yield (daily average yield in fourth week of lactation) and predicted 305 d yield. Transition alerts correctly predicted 62.5% (95% CI: 59.3-65.5) of treatments with a sensitivity of 42.4% (95% CI: 37.4-45.5) and a specificity of 75.2% (95% CI: 71.5-78.6). Associations were identified between postpartum health and production outcomes and prepartum behavioral measures from an automated activity monitoring system.

β-Hydroxybutyrate Effects on Bovine Caruncular Epithelial Cells: A Model for Investigating the Peri-Implantation Period Disruption in Ketotic Dairy Cows

Ketosis is a metabolic disorder arising from a negative energy balance (NEB). It is characterized by high β-Hydroxybutyrate (BHBA) blood levels and associated with reduced fertility in dairy cows. To investigate the impact of BHBA on bovine caruncular epithelial cells (BCEC) in vitro, these cells were stimulated with different concentrations of BHBA. Cell metabolism and motility were examined using an MTT assay and Live-cell imaging. RT-qPCR was used to examine mRNA expressions of TNF, IL6, RELA, prostaglandin E2 synthase (PTGES2) and receptor (PTGER2) as well as integrin subunits ITGAV, ITGA6, ITGB1 and ITGB3. Stimulation with 1.8 and 2.4 mM of BHBA negatively affected cell metabolism and motility. TNF showed increased mRNA expression related to rising BHBA concentrations. IL6, RELA, ITGAV, ITGA6, ITGB1 and ITGB3 as well as PTGER2 showed no changes in mRNA expression. Stimulation with 0.6 and 1.2 mM of BHBA significantly increased the mRNA expression of PTGES2. This does not indicate a negative effect on reproductive performance because low BHBA concentrations are found in steady-state conditions. However, the results of the study show negative effects of high BHBA concentrations on the function of BCECs as well as an inflammatory response. This could negatively affect the feto-maternal communication during the peri-implantation period in ketotic dairy cows.

The Association between Prepartum Rumination Time, Activity and Dry Matter Intake and Subclinical Hypocalcemia and Hypomagnesemia in the First 3 Days Postpartum in Holstein Dairy Cows

Changes in prepartum behaviors such as total daily rumination (TDR), total daily activity (TDA) and dry matter intake (DMI) have the potential to be used as early indicators for cows at risk for subclinical hypocalcemia (SCH) or hypomagnesemia (HYM) after calving. Our objective was to investigate associations between average daily rate of change in total daily rumination (ΔTDR), total daily activity (ΔTDA) and dry matter intake (ΔDMI) from -3 days prepartum to calving with SCH and HYM at D0 or D3 relative to calving. Prepartum TDR, TDA and DMI were measured in 64 Holstein dairy cows. Blood samples were taken at D0 and D3 post-calving for the measurement of total plasma Ca and Mg concentration. Linear regression models were used to analyze the association between ΔTDR, ΔTDA and ΔDMI and SCH and HYM at D0 and D3 relative to calving. Potential confounding variables were offered to the models and backwards selection was used to determine which covariates to retain. No significant differences in prepartum ΔTDR, ΔTDA or ΔDMI were found between cows with or without SCH and HYM at D0 and D3. Our results suggest that the change in TDR, TDA and DMI in the last 3 days prepartum are not effective predictors for cows that will have SCH or HYM in the first 3 days postpartum.

Impact of sensor data pre-processing strategies and selection of machine learning algorithm on the prediction of metritis events in dairy cattle

With all the sensor data currently generated at high frequency in dairy farms, there is potential for earlier diagnosis of postpartum diseases compared with traditional monitoring methodologies. Our objectives were 1) to compare the impact of sensor data pre-processing on classifier performance by using multiple time windows before a given metritis event, while considering other cow-level factors and farm-scheduled activities; 2) to compare the performance of random forest (RF), k-nearest neighbors (k-NN), and support vector machine (SVM) classifiers at different decision thresholds using different number of past observations (time-lags) for the detection of behavioral patterns associated with changes in metritis scores; and 3) to compare classifier performance between each one of the five behaviors registered every hour by an ear-tag 3-axis accelerometer (CowManager, Agis Autimatisering, Harmelen, Netherlands). A total of 239 metritis events were created by comparing metritis scores between two consecutive clinical evaluations from cows that were retrospectively selected from a dataset containing sensor data and health information during the first 21 days postpartum from June 2014 to May 2017. Hourly sensor data classified by the accelerometer as either ruminating, eating, not active (including both standing or lying), and two different levels of activity (active and high activity) behaviors corresponding to the 3 days before each metritis event were aggregated every 24-, 12-, 6-, and 3-hour time windows. Multiple time-lags were also used to determine the optimal number of past observations needed for optimal classification. Similarly, different decision thresholds were compared in terms of model performance. Depending on the classifier, algorithm hyperparameters were optimized using grid search (RF, k-NN, SVM) and random search (RF). All behaviors changed throughout the study period and showed distinct daily patterns. From the three algorithms, RF had the highest F₁ score followed by k-NN and SVM. Furthermore, sensor data aggregated every 6- or 12-h time windows had the best model performance at multiple time-lags. We concluded that the data from the first 3 days post-partum should be discarded when studying metritis, and either one of the five behaviors measured with CowManager could be used when predicting metritis when sensor data were aggregated every 6- or 12-hour time windows, and using time-lags corresponding to 2-3 days before a given event, depending on the time window used. This study shows how to maximize sensor data in their potential for disease prediction, enhancing the performance of algorithms used in machine learning.

Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock.

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.

Evaluation of an indwelling bolus equipped with a triaxial accelerometer for the characterisation of the diurnal pattern of bovine reticuloruminal contractions

This observational study aimed to describe the diurnal pattern of reticuloruminal contraction rate (RRCR) and the proportion of time spent ruminating by cattle, using two commercial devices equipped with triaxial accelerometers: an indwelling bolus (placed in the reticulum) and a neck collar. The three objectives of this study were firstly to determine whether the indwelling bolus provided observations consistent with RRCR as determined by clinical examination using auscultation and ultrasound, secondly to compare estimates of time spent ruminating using the indwelling bolus and a collar-based accelerometer, and finally to describe the diurnal pattern of RRCR using the indwelling bolus data. Six rumen-fistulated, non-lactating Jersey cows were fitted with an indwelling bolus (SmaXtec Animal Care GmbH, Graz, Austria) and a neck collar (Silent Herdsman, Afimilk Ltd. Kibbutz Afikim, Israel), and data were collected over two weeks. Cattle were housed together in a single straw-bedded pen and fed ad libitum hay. To assess the agreement between the indwelling bolus and traditional methods of assessing reticuloruminal contractility in the first week, the RRCR was determined over 10 min, twice a day, by ultrasound and auscultation. Mean inter-contraction intervals (ICI) derived from bolus and ultrasound, and from auscultation were 40.4 ± 4.7, 40.1 ± 4.0 and 38.4 ± 3.3 s. Bland-Altmann plots showed similar performance of the methods with small biases. The Pearson correlation coefficient for the time spent ruminating derived from neck collars and indwelling boluses was 0.72 (highly significant, P < 0.001). The indwelling boluses generated a consistent diurnal pattern for all the cows. In conclusion, a robust relationship was observed between clinical observation and the indwelling boluses for estimation of ICI and, similarly, between the indwelling bolus and neck collar for estimating rumination time. The indwelling boluses showed a clear diurnal pattern for RRCR and time spent ruminating, indicating that they should be useful for assessing reticuloruminal motility.

Change in Rumination Behavior Parameters around Calving in Cows with Subclinical Ketosis Diagnosed during 30 Days after Calving

We hypothesized that cows with SCK (blood BHB over >1.2 mmol/L) diagnosed within the first 30 days of calving can be predicted by changes in rumination and activity behavioral parameters in the period before calving and indeed subsequently. A total of 45 cows were randomly selected from 60 dry cows from at least 40 days before calving. All the cows were fitted with RuniWatch sensors monitoring both intake behaviors (faceband) and general movement and activity behavior (pedometer) (RWS-ITIN + HOCH, Switzerland). Following an adaptation period of 10 days, rumination, eating, and activity parameters were monitored for 30 days before calving and 30 days after calving. Considering the design of the study, we divided the data of cows into three stages for statistical evaluation: (1) the last thirty days before calving (from day -30 to -1 of the study); (2) day of calving; and (3) the first thirty days after calving (from day 1 to 30 of the study). We found that before calving, those cows with a higher risk of having SCK diagnosed after calving had lower rumination time, eating time, drinking gulps, bolus, chews per min, chews per bolus, downtime, maximal temperature, and activity change. On the calving day, in cows with higher risk of SCK after calving, we found lower rumination time, eating time, chews per min, chews per bolus, uptime, downtime, minimal temperature, other chews, eating chews, drinking time, drinking gulps, activity, average temperature, maximal temperature, activity change, rumination chews, and eating chews. After calving in cows with SCK, we found lower rumination time, eating time 1, eating time 2, bolus, chews per bolus, uptime, downtime, minimal temperature, maximal temperature, rumination chews, and eating chews. Moreover, after calving we found higher drinking gulps, drinking time, activity, activity change, average temperature, other chews, and eating chews in cows with SCK. From a practical point of view, we recommend that by tracking changes in rumination and activity behavior parameters registered with RuniWatch sensors (such as rumination time, eating time, drinking time, drinking gulps, bolus, chews per minute, chews per bolus, downtime, maximal temperature, and activity change) before, during, and after calving, we can identify cows with a higher risk of SCK in the herd.

Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health

During disease or toxin challenges, the behavioral activities of grazing animals alter in response to adverse situations, potentially providing an indicator of their welfare status. Behavioral changes such as feeding behavior, rumination and physical behavior as well as expressive behavior, can serve as indicators of animal health and welfare. Sometimes behavioral changes are subtle and occur gradually, often missed by infrequent visual monitoring until the condition becomes acute. There is growing popularity in the use of sensors for monitoring animal health. Acceleration sensors have been designed to attach to ears, jaws, noses, collars and legs to detect the behavioral changes of cattle and sheep. So far, some automated acceleration sensors with high accuracies have been found to have the capacity to remotely monitor the behavioral patterns of cattle and sheep. These acceleration sensors have the potential to identify behavioral patterns of farm animals for monitoring changes in behavior which can indicate a deterioration in health. Here, we review the current automated accelerometer systems and the evidence they can detect behavioral patterns of animals for the application of potential directions and future solutions for automatically monitoring and the early detection of health concerns in grazing animals.

Effects of feeding 25-hydroxyvitamin D3 with an acidogenic diet during the prepartum period in dairy cows: Mineral metabolism, energy balance, and lactation performance of Holstein dairy cows

Our objective was to determine the effects of feeding 25-hydroxyvitamin D₃ [25(OH)D₃], or vitamin D₃ (cholecalciferol) on plasma, mineral, and metabolite concentrations, mineral balance, mineral excretion, rumination, energy balance, and milk production of dairy cows. We hypothesized that supplementing 3 mg/d of 25(OH)D₃ during the prepartum period would be more effective than supplementing vitamin D₃ at the National Research Council (2001) levels to minimize calcium imbalance during the transition period and improve milk production of dairy cows. Forty multiparous, pregnant nonlactating-Holstein cows were enrolled in this study. Body weight, body condition score, parity, and milk yield in the previous lactation (mean ± standard deviation) were 661 ± 59.2, 3.46 ± 0.35, 1.79 ± 0.87, and 33.2 ± 6.43 kg/d, respectively. Cows were enrolled into the blocks (n = 20 for each treatment) at 30 d of the expected day of calving to receive an acidogenic diet (373 g/kg of neutral detergent fiber and 136 g/kg of crude protein, dry matter basis; -110 mEq/kg) associated with the treatments: (1) control (CTRL), vitamin D₃ at 0.625 mg/d (equivalent to 25,000 IU of vitamin D₃/d) or (2) 25(OH)D₃ at 3 mg/d (equivalent to 120,000 IU of vitamin D₃/d). All cows were fed with the base ration for 49 d after calving. Blood samples were taken on d 7, 0, 1, 2, 21, and 42, relative to calving. No effect of treatment was observed for prepartum dry matter intake or body condition score. A trend for increase of ionized Ca was observed for the cows fed 25(OH)D₃, compared with the CTRL, but no effect of treatment was detected for total Ca or total P. Feeding 25(OH)D₃ increased colostrum yield. The plasmatic concentration of 25-hydroxyvitamin D₃ was increased with 25(OH)D₃ supplementation. 25-Hydroxyvitamin D₃ supplementation increased plasma glucose concentration at parturition. The postpartum dry matter intake was not influenced by treatments. Feeding 25(OH)D₃ increases milk yield, 3.5% fat-corrected milk, and energy-corrected milk and improves milk yield components in early lactation. Overall, these findings suggest that 25(OH)D₃ at 3 mg/d can improve the energy metabolism and lactation performance, compared with the current-feeding practice of supplementing vitamin D₃ at 0.625 mg/d.

Waiting time in the premilking holding pen and subsequent lying and walking behaviors of Holstein cows

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Automated sensors allow monitoring of behavioral and physiological variables from large numbers of dairy cows, opening new possibilities for research.

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Waiting time in the premilking holding area can vary greatly among dairies and individual cows and could affect the time budget of cows.

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We found a moderate effect of waiting time before milking on lying time and lying bouts after the night milking.

The objective of this study was to assess the effect of waiting time (WT) in the premilking holding pen on the subsequent lying and walking behaviors of Holstein cows. A total of 108 cows (multiparous n = 95; primiparous n = 13), milked 3 times/d [AM (0700 h), PM (1500 h), and nighttime (2300 h)] were monitored for individual WT, which was defined as the time elapsed between the entrance of the first cow to the milking stall in a rotary milking system and the entrance of each subsequent cow housed in the same milking pen. Data for lying time (min), standing time (min), lying bouts (no.), and walking behavior (no. of steps) in 15-min intervals were collected using a commercial 3-dimensional accelerometer affixed on the hind left leg of each cow from early to mid lactation. Mean values (min/h, no./h) for each behavior calculated between consecutive milkings were compared among 3 WT categories: cows with WT ≤30 min (WT1), WT 30 to 60 min (WT2), and WT >60 min (WT3). The overall mean (SD) of WT during the study period was 31.2 (23.4) min, and the distribution of WT1, WT2, and WT3 in all cows through the monitoring period was 50.9, 43.3, and 5.7%, respectively. No significant effects were established for overall WT on any of the behaviors under analysis. However, subsequent analysis by milking shift indicated that, during the period following the night milking, cows in WT1 exhibited the shortest lying time, whereas cows in WT3 had the greatest number of lying bouts. No effect of WT category was observed on the number of steps after any of the milking shifts. Results of this study indicate a moderate effect of WT on lying behavior after the nighttime milking. Variables such as temperature-humidity index, parity, and time of day affected cow behavior and should be considered when evaluating the impact of routine management practices, such as milking, on commercial farms.

Behavioral changes of metritic primiparous cows treated with chitosan microparticles or ceftiofur

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Chitosan microparticles negatively affected the rumination and activity of cows with metritis.

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The negative effect of CM on rumination and activity indicates a negative systemic effect that may be associated with increased inflammation in the uterus.

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Regardless of treatment, cows with metritis had decreased rumination and activity starting 5 days before diagnosis until at least 2 days after diagnosis.

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The automated health-monitoring device was a useful tool to evaluate rumination and activity patterns after metritis treatment.

The main objective was to characterize behavioral changes in metritic primiparous cows treated with chitosan microparticles (CM) or ceftiofur (CEF). A secondary objective was to compare behavioral patterns of metritic cows with nonmetritic (NMET) cows. Nulliparous Holstein cows (n = 311) were fitted with a neck-mounted automated health-monitoring device (AHMD) from −21 to 60 d relative to calving. Cows diagnosed with metritis (d 0), characterized by watery, fetid, red-brownish uterine discharge within 21 d in milk were assigned randomly to CM (n = 45), intrauterine infusion of 24 g of CM dissolved in 40 mL of sterile distilled water on d 0, 2, and 4; CEF (n = 47), subcutaneous injection of 6.6 mg/kg ceftiofur crystalline-free acid on d 0 and 3; and control (CON; n = 39), no treatment. For comparison, NMET cows (n = 180) were matched with metritic cows according to age at calving and calving date. Postdiagnosis, there was an effect of treatment and an interaction between treatment and time on rumination and activity. The interaction showed that CM had lesser rumination than CEF from d 1 to 11, d 18, and d 20; CM had lesser rumination than CON from d 2 to 8; and CEF was not different from CON. The interaction showed that CM had lesser activity than CON on d 2, from d 6 to 11, and d 13 to 14; CM was not different from CEF; and CEF had lesser activity than CON on d 8, 9, 13, and 14. Prediagnosis, cows in CM, CEF, and CON had lesser rumination and activity than cows in NMET. Postdiagnosis, cows in CM, CEF, and CON had lesser rumination than NMET from d 0 to 2 and had lesser activity than NMET from d 0 to 5. In summary, CM decreased rumination and activity compared with CON, which indicates a negative systemic effect of CM. This may be associated with exacerbated inflammation in the uterus. Additionally, metritic cows had decreased rumination and activity prediagnosis, which may allow for the use of AHMD for metritis diagnosis.

Development of resilience indicator traits based on daily step count data for dairy cattle breeding

Background

Resilient animals are minimally affected by disturbances, such as diseases and heat stress, and quickly recover. Daily activity data can potentially indicate resilience, because resilient animals likely keep variations due to disturbances that threat animal homeostasis at a low magnitude. We used daily step count of cows to define resilience indicators based on theory, exploratory analysis and literature, and then investigated if they can be used to genetically improve resilience by estimating heritability and repeatability, and genetic associations with other resilience-related traits, i.e. health traits, longevity, fertility, and body condition score (BCS).

Results

Two groups of resilience indicators were defined: indicators describing (1) mean step count at different lactation stages for individual cows, and (2) fluctuations in step count from individual step count curves. Heritability estimates were highest for resilience indicators describing mean step count, from 0.22 for the 2-week period pre-partum to 0.45 for the whole lactation. High mean step count was consistently, but weakly, genetically correlated with good health, fertility, and longevity, and high BCS. Heritability estimates of resilience indicators describing fluctuations ranged from 0.01 for number of step count drops to 0.15 for the mean of negative residuals from individual curves. Genetic correlations with health traits, longevity, fertility, and BCS were mostly weak, but were moderate and favorable for autocorrelation of residuals (− 0.33 to − 0.44) and number of step count drops (− 0.44 to − 0.56) with hoof health, fertility, and BCS. Resilience indicators describing variability of residuals and mean of negative residuals showed strong genetic correlations with mean step count (0.86 to 0.95, absolute), which suggests that adjustment for step count level is needed. After adjustment, ‘mean of negative residuals’ was highly genetically correlated with hoof health, fertility, and BCS.

Conclusions

Mean step count, autocorrelation and mean of negative residuals showed most potential as resilience indicators based on resilience theory, heritability, and genetic associations with health, fertility, and body condition score. Other resilience indicators were heritable, but had unfavorable genetic correlations with several health traits. This study is an important first step in the exploration of the use of activity data to breed more resilient livestock.

Associations between peripartum lying and activity behaviour and blood non-esterified fatty acids and β-hydroxybutyrate in grazing dairy cows

During early lactation, most dairy cows experience negative energy balance (NEB). Failure to cope with this NEB, however, can place cows at greater risk of developing metabolic disease. Our objective was to characterise, retrospectively, lying behaviour and activity of grazing dairy cows grouped according to blood non-esterified fatty acids (NEFAs) and β-hydroxybutyrate (BHB) as indicators of postpartum metabolic state. Blood was sampled weekly for up to 4 weeks precalving, on the day of calving (day 0), daily between 1 and 4 days postcalving, and then at least weekly between week 1 and week 5 postcalving for analysis of plasma NEFAs and BHB concentrations. Two hundred and forty-four multiparous Holstein-Friesian and Holstein-Friesian × Jersey cows were classified into one of three metabolic status groups based on maximum blood NEFAs and BHB concentrations during week 1 and 2 postcalving. A cow was classified as having either: (1) low NEFAs and low BHB (Lo-Lo; n = 78), when all blood samples were <1.0 mmol/L for NEFAs and ≤1.0 mmol/L for BHB during the first 2 weeks postcalving; (2) high NEFAs and low BHB (Hi-Lo; n = 134), when blood NEFAs were ≥1.0 mmol/L and blood BHB was ≤1.0 mmol/L at the same sampling time point during the first 2 weeks postcalving; or (3) high NEFAs and high BHB (Hi-Hi; n = 32), when blood NEFAs were ≥1.0 mmol/L and blood BHB was ≥1.2 mmol/L at the same sampling time point during the first 2 weeks postcalving. Accelerometers (IceTag or IceQube devices; IceRobotics Ltd.) were used to monitor lying and activity behaviours peripartum (-21 to +35 days relative to calving). Changes in lying behaviour and activity occurred before the mean day that cows were classified Hi-Hi and Hi-Lo (2.2 and 3.5 d postcalving, respectively). Up to 3 weeks preceding calving, Hi-Hi cows were more active, had fewer daily lying bouts (LBs), and spent less time lying than Lo-Lo cows. In addition, Hi-Hi cows had fewer daily LBs and were less active up to 4 weeks postcalving than Lo-Lo cows, but these differences were biologically small. Groups of grazing cows classified as experiencing a more severe metabolic challenge behave differently up to 3 weeks precalving than their herdmates with lower blood NEFAs and BHB postcalving. These altered behaviours may allow identification of individual cows at risk of a metabolic challenge, but further research is required.

Alteration in Activity Patterns of Cows as a Result of Pain Due to Health Conditions

Simple Summary

There are several conditions and diseases considered painful to cattle. One reason for the inconsistency in pain recognition and thus pain relief in cattle is the inadequate ability to identify and assess pain. In fact, both increased and/or reduced daily lying time can be indicative of pain in cattle. This review helps to properly interpret pain in cows through behavioural activity patterns and explores whether pain relief is capable to restore their normal activity.

Abstract

The main conditions and diseases considered painful in dairy cows are mastitis, lameness, calving (including dystocia and caesarean section) and metritis. The cattle literature reports that deviation from normal daily activity patterns (both increased and/or reduced daily lying time) can be indicative of painful conditions and diseases in cows. This narrative review discusses on how pain due to several health conditions in dairy cows modifies its activity pattern and explores if non-steroidal anti-inflammatory drugs (NSAIDs) are capable of restoring it. Divergent outcomes may differ depending upon the painful cause, the severity and the moment, and consequently its interpretation should be properly explained. For instance, cows with clinical mastitis reduced their time lying and increased the number of lying bouts and stepping due to pain caused by the swollen udder when cows are lying. However, lame cows show longer lying times, with a lower number of lying bouts and longer and more variable lying bouts duration, as compared to non-lame cows. When the relationship between painful disorders and daily activity patterns is studied, factors such as parity, bedding type and severity of disease are important factors to take into consideration. The potential benefits of the NSAIDs treatment in painful health disorders depend upon the type of drug administered, its dosage and administration mode, and the time of administration relative to the painful health disorder. This narrative review can be used as a tool to properly interpret and grade pain in cows through behavioural activity patterns and proposes directions for future investigations.

The Effect of Rumination Time on Milk Performance and Methane Emission of Dairy Cows Fed Partial Mixed Ration Based on Maize Silage

Simple Summary

Greenhouse gas emission has attracted considerable public attention in recent years, driving the search for genetic, nutritional, and management strategies to reduce methane emissions and increase the sustainability of milk production. Rumination activity has an important function in feed particle size reduction, condition of feeding behavior, and feed intake as well as in stabilizing rumen fluid pH through saliva production. A total of 365 high-yielding Polish Holstein -Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). We showed that a longer rumination time leads to a lower methane emission level. Therefore, strategies that increase chewing activity may be used to reduce the environmental impact of dairy cows production.

Abstract

The objective of this study was to determine the effect of the rumination time on milk yield and composition as well as methane emission during lactation in high-yielding dairy cows fed a partial mixed ration based on maize silage without pasture access. A total of 365 high-yielding Polish Holstein-Friesian multiparous dairy cows were included in the study covering 24 to 304 days of lactation. Methane emission, rumination time, and milk production traits were observed for the period of 12 months. Next, the data from the cows were assigned to three groups based on daily rumination time: low rumination up to 412 min/day (up to 25th rumination percentile), medium rumination from 412 to 527 min/day (between the 25th and 75th percentile), and high rumination above 527 min/day (from the 75th percentile). Rumination time had no effect on milk yield, energy-corrected milk yield, or fat and protein-corrected milk yield. High rumination time had an effect on lower fat concentration in milk compared with the medium and low rumination groups. The highest daily CH₄ production was noted in low rumination cows, which emitted 1.8% more CH₄ than medium rumination cows and 4.2% more than high rumination cows. Rumination time affected daily methane production per kg of milk. Cows from the high rumination group produced 2.9% less CH₄ per milk unit compared to medium rumination cows and 4.6% in comparison to low rumination cows. Similar observations were noted for daily CH₄ production per ECM unit. In conclusion, a longer rumination time is connected with lower methane emission as well as lower methane production per milk unit in high-yielding dairy cows fed a maize silage-based partial mixed ration without pasture access.

The Transition Period Updated: A Review of the New Insights into the Adaptation of Dairy Cows to the New Lactation

Recent research on the transition period (TP) of dairy cows has highlighted the pivotal role of immune function in affecting the severity of metabolic challenges the animals face when approaching calving. This suggests that the immune system may play a role in the etiology of metabolic diseases occurring in early lactation. Several studies have indicated that the roots of immune dysfunctions could sink way before the “classical” TP (e.g., 3 weeks before and 3 weeks after calving), extending the time frame deemed as “risky” for the development of early lactation disorders at the period around the dry-off. Several distressing events occurring during the TP (i.e., dietary changes, heat stress) can boost the severity of pre-existing immune dysfunctions and metabolic changes that physiologically affect this phase of the lactation cycle, further increasing the likelihood of developing diseases. Based on this background, several operational and nutritional strategies could be adopted to minimize the detrimental effects of immune dysfunctions on the adaptation of dairy cows to the new lactation. A suitable environment (i.e., optimal welfare) and a balanced diet (which guarantees optimal nutrient partitioning to improve immune functions in cow and calf) are key aspects to consider when aiming to minimize TP challenges at the herd level. Furthermore, several prognostic behavioral and physiological indicators could help in identifying subjects that are more likely to undergo a “bad transition”, allowing prompt intervention through specific modulatory treatments. Recent genomic advances in understanding the linkage between metabolic disorders and the genotype of dairy cows suggest that genetic breeding programs aimed at improving dairy cows’ adaptation to the new lactation challenges (i.e., through increasing immune system efficiency or resilience against metabolic disorders) could be expected in the future. Despite these encouraging steps forward in understanding the physiological mechanisms driving metabolic responses of dairy cows during their transition to calving, it is evident that these processes still require further investigation, and that the TP—likely extended from dry-off—continues to be “the final frontier” for research in dairy sciences.

Behavioral changes in dairy cows with metritis in seasonal calving pasture-based dairy system

The aims of this study were to determine changes in lying and rumination behavior of transition dairy cows that were healthy or affected by metritis during the autumn and spring calving season in a temperate climate and determine the effect of some weather variables (precipitation and heat stress) on these behaviors. A total of 103 multiparous cows were monitored during the autumn (February to April) and spring calving season (July to October) from 10 d before to 10 d after calving. Cows were chosen retrospectively by diagnosis of metritis [autumn season, (n = 11); spring season, (n = 13)] or as healthy [autumn season, (n = 25); spring season, (n = 25)] based on vaginal discharge characteristics evaluated during the first 10 days in milk. In all animals, electronic data loggers recorded lying (Hobo Pendant G Acceleration, Onset Computer Corp.) and rumination behavior (Hi-Tag rumination monitoring system, SCR Engineers Ltd.) during the study period. We included precipitation level (>1 mm/d = with rain, and ≤1 mm/d = without rain) and heat stress [no heat stress = temperature-humidity index (THI) < 68 vs. heat stress = THI ≥ 68] as weather factors that may have affected lying and rumination behavior during the spring and autumn season in a temperate climate, respectively. Metritis during the spring calving season was associated only with longer lying times (≥1.3 h/d) after calving. During the autumn calving season cows with metritis lay down longer the day of calving (~2.1 h/d) and had fewer lying bouts of longer duration during the prepartum period compared with healthy cows. Rumination time did not differ by health status during the spring calving season, whereas cows with metritis during autumn ruminated 30, 21, and 24 min/d less than healthy cows during the prepartum, calving, and postpartum period, respectively. Precipitation and heat stress were associated with decreased daily lying and rumination time in sick cows. Our results indicate that differences in lying and rumination behavior depended on the metritis status, and support the idea that weather factors such as rainfall or heat stress requires to be considered in analyses of transition cow behavior in seasonal calving pasture-based dairy systems.

Transition cow metabolites and physical traits influence days to first postpartum ovulation in dairy cows

Physical activities are associated with the health of transition dairy cows and pregnancy outcomes are positively related to early resumption of postpartum estrous cycles. The objective was to assess key metabolites and patterns of prepartum and postpartum physical activity as they relate to the onset of first postpartum ovulation in lactating dairy cows. Close-up dry Holstein cows (n = 82) and late gestation heifers (n = 78) were enrolled beginning 3 wk before expected calving date (Day 0). Cows were fit with Cow SensOor ear tags to assess transitional changes in eating, resting, rumination, high activity, and ear-surface temperatures. Rectal temperatures were assessed and blood samples were collected on Days 0, 3, 7, and 14 to measure concentrations of glucose, free fatty acids (FFA), β-hydroxybutyrate (BHB), calcium, and haptoglobin. Body condition scores (BCS) and body weights (BW) were measured weekly, and blood samples were collected weekly from Day 21 ± 3 through 70 ± 3 to quantify changes in progesterone to detect luteal function after ovulation. Cows first ovulating before median Day 33 were classified as early (n = 76), whereas those first ovulating after Day 33 were classified as late (n = 84). Early ovulating cows first ovulated earlier (P < 0.001) than the late ovulation cows (24.3 ± 1.2 d [range: 16-32 d] vs. 48.8 ± 1.2 d [range: 33-74 d]), respectively. Mean days to first ovulation excluded seven cows that failed to ovulate before insemination. Compared with late ovulating cows, early ovulating cows had lesser (P < 0.05) concentrations of FFA, BHB, and haptoglobin on Days 0, 3, 7, and 14 in addition to having lesser (P < 0.05) rectal temperatures and ear-surface temperatures. Ear-surface temperatures began to decrease 4 d before parturition and remained less (P < 0.05) after calving than cows that subsequently ovulated late. Early ovulating cows tended (P = 0.07) to spend more time eating, and less (P = 0.02) time resting and being active during the first 3 wk after calving, and lost less (P = 0.03) BW and BCS during the first 9 wk compared with late ovulating cows. Although no differences were detected in yields of milk or energy-corrected milk during the first 9 wk after calving, early compared with late ovulating cows produced more (P < 0.01) milk protein. We concluded that metabolic measures during the first 2 wk after calving, and physical and behavioral traits are associated with the onset of postpartum ovarian activity.

Predictive models to identify Holstein cows at risk of metritis and clinical cure and reproductive/productive failure following antimicrobial treatment

Precision dairy farming, specifically the design of management strategies according to the animal's needs, may soon become the norm since automated technologies that generate large amounts of data for each individual are becoming more affordable. Our objectives were to determine whether the use of behavioral changes could improve the accuracy of prediction of the risk of metritis and the risk of clinical cure of cows diagnosed with metritis. Addition of behavioral data to the algorithms to predict the outcomes of interest increased their accuracy by 7 to 32%. The incidence of metritis in postpartum dairy cows ranges from 20 to 40%. Unfortunately, approximately 30% of cows treated with antimicrobials following the diagnosis of metritis fail to cure and have impaired reproductive performance. Automated behavior monitoring devices have become more affordable and accessible. In the current study, we investigated whether behavioral changes recorded by automated devices improve models for the prediction, within 42 h of calving, of metritis and acute metritis. Furthermore, we determined whether behavioral changes aid on the prediction, 24 h before the diagnosis of metritis, of cure in response to antimicrobial treatments and the reproductive (failure to become pregnant)/productive (bottom quartile of milk yield) success within 200 d in milk (DIM). At enrollment, Holstein cows (n = 555) from two farms were fitted with an automated device (HR-LDn tag, SCR Engineers Ltd., Netanya, Israel) 21 d before the expected calving date. Cows were examined for metritis (fetid, watery, red/brown uterine discharge) and were randomly assigned to receive ampicillin trihydrate or ceftiofur crystalline free acid treatments. Contemporary cows with no clinical diseases (NoCD = 362) were paired with cows with metritis. Cure from metritis was defined as the absence of fetid, watery, pink/brown uterine discharge and rectal temperature < 39.5 °C, 11 d after diagnosis. In addition, cows in the lowest quartile of milk production, within lactation and farm, and that were not pregnant by 200 DIM were classified as failure. We built models containing: routinely-available data [lactation number (1, 2, ≥3), calf sex, still birth, twining, dystocia, vaginal laceration score, days on the close-up diets], body condition score (BCS) and BCS change from enrollment to calving (ΔBCS), behavior (feeding, rumination, idle, and active time), and their interactions. The area under the curve (AUC) of the models containing routinely-available data, ΔBCS, and behavior data at 2 DIM to predict metritis [AUC = 0.82, 95% confidence interval (CI) = 0.78, 0.85] and acute metritis (AUC = 0.87, 95% CI = 0.83, 0.89) were (P < 0.01) excellent; whereas the models predicting cure (AUC = 0.92, 95% CI = 0.85, 0.95) and failure (AUC = 0.90, 95% CI = 0.84, 0.94) were outstanding. Behavioral changes peripartum contribute for the identification of cows at risk for metritis, allowing the development of preventive strategies. In addition, predicting whether cows will respond to antimicrobial treatment and succeed during lactation may allow for earlier decision-making regarding treatment and culling.

Assessment of the Relationship between Postpartum Health and Mid-Lactation Performance, Behavior, and Feed Efficiency in Holstein Dairy Cows

The objective of this study was to investigate the relationships between postpartum health disorders and mid-lactation performance, feed efficiency, and sensor-derived behavioral traits. Multiparous cows (n = 179) were monitored for health disorders for 21 days postpartum and enrolled in a 45-day trial between 50 to 200 days in milk, wherein feed intake, milk yield and components, body weight, body condition score, and activity, lying, and feeding behaviors were recorded. Feed efficiency was measured as residual feed intake and the ratio of fat- or energy-corrected milk to dry matter intake. Cows were classified as either having hyperketonemia (HYK; n = 72) or not (n = 107) and grouped by frequency of postpartum health disorders: none (HLT; n = 94), one (DIS; n = 63), or ≥2 (DIS+; n = 22). Cows that were diagnosed with HYK had higher mid-lactation yields of fat- and energy-corrected milk. No differences in feed efficiency were detected between HYK or health status groups. Highly active mid-lactation time was higher in healthy animals, and rumination time was lower in ≥4th lactation cows compared with HYK or DIS and DIS+ cows. Differences in mid-lactation behaviors between HYK and health status groups may reflect the long-term impacts of health disorders. The lack of a relationship between postpartum health and mid-lactation feed efficiency indicates that health disorders do not have long-lasting impacts on feed efficiency.

Association of days in close up, gestation length, and rumination around time of calving with disease and pregnancy outcomes in multiparous dairy cows

The purpose of this study was to evaluate the effect of rumination times and days spent in a close-up group before calving (DCU) on early-lactation health and reproductive outcomes in dairy cows. Data were gathered for 719 cows located in a single herd. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk; DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever, and displaced abomasum. Rumination times for each cow were downloaded daily from the herd's automated collar system used to generate heat and health alerts for each cow beginning at 21 d precalving until 14 d postcalving. During the first 30 DIM, 121 cows (18%) developed at least 1 disease-any combination of ketosis (40 cows, 5.9% of total), mastitis (17 cows, 2.5%), metritis (75 cows, 11%), milk fever (17 cows, 2.5%), or displaced abomasum (28 cows, 4.1%); 305 cows (45%) were pregnant again at 100 DIM, and an additional 139 cows (20%) were pregnant at 150 DIM. Principal component analysis was used to determine the relationship between gestation length and DCU and their association with the odds of developing disease in early lactation. We did not find any significant association between precalving rumination time and disease within the first 30 DIM. Higher rumination time in the week before calving was shown to be strongly linked to a shorter time to subsequent pregnancy, whereas rumination times postcalving were not associated with changes in the time to pregnancy. Principal component analysis showed that a curvilinear combination of gestation length and DCU (principal component 1) was significantly associated with changes in disease incidence in the first 30 DIM. Gestation length and time spent in close up are important management factors in reducing the incidence of disease in early lactation, and rumination times around calving may help predict future reproductive outcomes.

Effect of oral calcium administration on metabolic status and uterine health of dairy cows with reduced postpartum rumination and eating time

Background

Hypocalcemia has detrimental effects on health and performance of dairy cows. As hypocalcemic cows show reduced feed intake, we hypothesized that cows with reduced combined rumination and eating time (CRET) may benefit from Ca supplementation. The objective was to evaluate the effect of postpartum oral Ca administration on metabolic status (Calcium [Ca], fatty acids [FA], and β-Hydroxybutyrate [BHB] serum concentrations) and incidence of puerperal metritis (PM) in dairy cows with reduced postpartum CRET. Cows in an organic-certified dairy, diagnosed with reduced CRET (< 489 min/d; n = 88) during the first day postpartum were assigned into 1 of 2 treatments: i) Calcium administration (CA; n = 45) that received 1 Ca oral capsule (Bovikalc bolus, Boehringer Ingelheim, St. Joseph, MO) containing CaCl2 and CaSO4 (43 g of Ca) once per day, for 3 consecutive days, starting at d 1 postpartum; and ii) Control (CON; n = 43) that did not receive oral Ca. A convenience group consisting of cows with CRET ≥489 min/d was used for comparison and did not receive oral Ca (NOR; n = 96).

Results

At day 1 postpartum cows with reduced CRET had lower Ca serum concentrations (CA = 2.08 mmol/L; CON = 2.06 mmol/L) compared with NOR cows (2.17 mmol/L). Calcium concentrations at d 3, 5, and 12 postpartum were not different among the three groups. Serum FA concentrations at d 1, 3 and 5 postpartum were higher in both CA and CON cows compared with NOR. At d 12, only CA cows had higher FA concentrations than NOR cows. Serum BHB concentrations at d 3 were highest in CA, with no difference between CON and NOR. At d 5, BHB concentrations were higher in CA, followed by CON, and NOR. No effect was observed for Ca administration on incidence of PM and reproductive performance. CON cows had lower survival at 30 DIM (86.5%) than NOR cows (97.9%).

Conclusions

The use of remote sensor technology identified cows with reduced rumination and eating time that had lower postpartum serum concentrations of calcium and altered metabolic status. However, oral calcium administration to cows with reduced CRET did not affect incidence of metabolic disorders nor reproductive health and subsequent pregnancy. Although survival at 30 days postpartum was lower for non-Ca supplemented cows, the identification of effective interventions in cows with reduced CRET requires further consideration.

Association between early postpartum rumination time and peak milk yield in dairy cows

Limited information is available on the relationship between rumination time (RT) in the early postpartum period and milk production later in lactation. Therefore, the objectives of this study were to (1) investigate the association of change in RT and average RT during the immediate postpartum period with peak milk yield (PMY) in dairy cows, and (2) determine the best model based on days in milk (DIM) to evaluate this association. Cows from 33 free-flow automatic milking system farms were included in this study, where retrospective milk production and RT data were collected for 12 mo. Cows were categorized by parity number into parity 1 (P1, n = 1,538), parity 2 (P2, n = 1,354), or parity ≥3 (P3+, n = 1,770). For each cow, PMY was identified as the highest daily milk yield up to 180 DIM for P1 and 120 DIM for P2 and P3+ cows. Five change in RT variables and 5 average RT variables were created corresponding to the first 2 to 6 DIM. Change in RT variables were the slope coefficients for change in RT/d related to DIM = 1 extracted from simple linear regressions, and average RT variables were the arithmetic mean RT. Five models analyzing PMY and corresponding variables calculated over the first 2 to 6 DIM had fixed effects of average RT, change in RT, parity, average RT × parity interaction, change in RT × parity interaction, and a random intercept for farm. Peak milk yield occurred at (median) 75, 44, and 46 DIM for P1, P2, and P3+, respectively. Overall PMY was (mean ± standard deviation) 54 ± 11 kg and it increased as parity increased. A positive association was found between change in RT and PMY, and average RT and PMY for P2 and P3+ cows in all 5 models corresponding to the first 2 to 6 DIM, indicating that greater average RT and quicker increase in RT after calving are associated with greater PMY for multiparous cows. Although the model including all 6 DIM had the greatest accuracy, results indicated that rumination data collected over the first 2 DIM may also provide adequate information for the association of average RT and change in RT with PMY in P2 and P3+ cows. For each 100 min/d increase in change in RT over the first 6 DIM, PMY increased by 4.3 (95% confidence interval: 2.2-6.3) and 4.8 (95% confidence interval: 3.2-6.5) kg for P2 and P3+ cows, respectively. Peak milk yield increased by 2.3 (95% CI: 1.7-2.8) and 2.2 (95% confidence interval: 1.7-2.6) kg for each 100 min increase in average RT over the first 6 DIM for P2 and P3+ cows, respectively. No association was observed between rumination behaviors and PMY for P1 cows. Results from this study indicate that the length of time for multiparous cows to achieve a stable RT in the early postpartum period combined with average RT during the same period may be useful in predicting their overall lactation milk production.

Rumination time as an early predictor of metritis and subclinical ketosis in dairy cows at the beginning of lactation: Systematic review-meta-analysis

Daily rumination time (RT; min/d) is recognized as an important tool for assessing the health of dairy cows, which may depend on the disease, lactation stage and individual cows. Using a systematic review-meta-analysis, this study evaluated whether the variation in RT is effective for early detection of metritis and subclinical ketosis (SCK) in dairy cows in the pre and post-partum periods (from three weeks before to three weeks after calving). The research was carried out in four electronic databases - Scopus, Science Direct, Pubmed and Web of Science. The main inclusion criteria were original research; evaluation of RT in dairy cows; and use of RT for early identification of metritis and/or SCK in post-partum dairy cows. A random effect meta-analysis (MA) was conducted for each disease (metritis and SCK) separately, with the RT means of healthy and sick groups, measured in the pre and post-partum. The effect size used was the mean difference (MD).Twenty-two trials from six studies were included in the MA, involving 1494 dairy cows. For metritis, four trials from three studies in the pre-partum period were considered as well as five trials from four studies in the post-partum. For SCK, six trials from four studies pre-partum and seven trials from five studies in the post-partum period were taken into consideration. The heterogeneity between studies for metritis was null (I² = 0%) and low (I² = 5.7 %) in the pre-partum and in the post-partum, respectively. The MD of RT between healthy cows and those with metritis was different in the pre (MD =0.411 min/d; P < 0.001) and in the post-partum (MD =0.279 min/d; P < 0.001). In SCK, heterogeneity was high in the pre (I² = 69 %) and in the post-partum (I² = 58.1 %), and the MD of RT was similar between healthy and sick cows (P> 0.05). In a meta-regression, RT from primiparous cows showed a lower predicted value for MD (0.48 min. d; P < 0.05) compared to multiparous cows, and the increment in each unit of milk production decreased the predicted MD value by 0.08 min. d (P < 0.001). Our MA demonstrates that RT is a good predictor for early detection of metritis in pre and post-partum; however, it is not an adequate predictor for SCK. Further investigations using more frequent blood sampling and the same threshold values for BHB are required to assess the adequacy of rumination time to predict SCK.

Prediction of Lactational Milk Yield of Cows Based on Data Recorded by AMS during the Periparturient Period

Simple Summary

Barns equipped with the automatic milking system (AMS) record huge amounts of data on milk flow rate, milk yield and composition, milk temperature, amount of concentrate intake and rumination time. Our study attempted to use this information, recorded during the periparturient period (divided into subperiods: second (14–8 days) and first (7–1 days) week before calving; 1–4, 5–7, 8–14, 15–21 and 22–28 days of lactation), to predict lactation milk yield in Polish Holstein–Friesian cows. In the first stage of statistical analysis, coefficients of simple correlation between lactation milk yield and AMS parameters were calculated. We found that prediction of lactation milk yield based on individual pieces of data may be ineffective—the calculated coefficients of correlation were low or moderate. In the next step of data analysis, we used a modern data mining technique in the form of decision trees. Based on the graphic, easy-to-interpret decision tree, we concluded that the highest lactation yield is to be expected for cows with completed lactations (survived until the next lactation), which were milked 4.07 times per day on average in the 4th week of lactation.

Abstract

Early prediction of lactation milk yield enables more efficient herd management. Therefore, this study attempted to predict lactation milk yield (LMY) in 524 Polish Holstein–Friesian cows, based on information recorded by the automatic milking system (AMS) in the periparturient period. The cows calved in 2016 and/or 2017 and were used in 3 herds equipped with milking robots. In the first stage of data analysis, calculations were made of the coefficients of simple correlation between rumination time (expressed as mean time per cow during the periparturient period: second (14–8 days) and first (7–1 days) week before calving, 1–4, 5–7, 8–14, 15–21 and 22–28 days of lactation), electrical conductivity and temperature of milk (expressed as means per cow on days 1–4, 5–7, 8–14, 15–21 and 22–28), amount of concentrate intake, number of milkings/day, milking time/visit, milk speed and lactation milk yield. In the next step of the statistical analysis, a decision tree technique was employed to determine factors responsible for LMY. The study showed that the correlation coefficients between LMY and AMS traits recorded during the periparturient period were low or moderate, ranging from 0.002 to 0.312. Prediction of LMY from the constructed decision tree model was found to be possible. The employed Classification and Regression Trees (CART) algorithm demonstrated that the highest lactation yield is to be expected for cows with completed lactations (survived until the next lactation), which were milked 4.07 times per day on average in the 4th week of lactation. We proved that the application of the decision tree method could allow breeders to select, already in the postparturient period, appropriate levels of AMS milking variables, which will ensure high milk yield per lactation.

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

Automated monitoring devices (AMD) have become more affordable, and consequently more popular among dairy producers. We hypothesized that the addition of AMD-generated health alerts to a health-screening program improves survival, milk production, and reproductive success. In addition, we hypothesized that cows diagnosed with clinical disease that have AMD alerts are at greater risk of culling, lower milk production, and decreased risk of pregnancy than cows without AMD alerts. Holstein cows (nulliparous = 282, parous = 328) were enrolled at -60 ± 3 d (d 0 = calving), when they were fitted with an AMD and assigned randomly to 1 of 2 health-screening strategies: (1) control: AMD alerts not provided to farm personnel; and (2) automated device: AMD alerts provided to farm personnel. Twice daily, study personnel determined which cows had AMD alerts (health index ≤79, rumination <200 min/d, or difference between current rumination and the average of the 3 preceding days <0) and provided the information to farm personnel. Farm personnel examined cows at 3, 5, and 9 d in milk (DIM) and when daily milk yield decreased ≥25% on consecutive days. We detected no differences between health-screening strategies regarding morbidity (control = 49.7 ± 3.3%, automated device = 52.8 ± 3.2%), but the interaction between health-screening strategy and parity tended to be associated with the number of clinical diseases per cow (primiparous: control = 0.46 ± 0.06, automated device = 0.65 ± 0.07 cases/cow; multiparous: 0.88 ± 0.08, automated device = 0.86 ± 0.08 cases/cow). Cows enrolled in the automated device strategy were more likely to be treated with supportive therapy (64.4 ± 3.1 vs. 55.0 ± 3.2%), whereas primiparous cows in the automated device strategy were more likely to be treated with anti-inflammatory drugs than those in the control strategy (41.6 ± 4.7 vs. 23.8 ± 4.0%). Health-screening strategy did not affect survival or total milk yield up to 22 wk postpartum, but cows in the automated device strategy had reduced risk of pregnancy after the first 2 services (54.5 ± 3.0 vs. 46.2 ± 3.2%). Cows diagnosed with a clinical disease without AMD alerts had reduced risk of removal from the herd by 150 DIM (5.7 ± 2.0 vs. 19.0 ± 3.3%), greater risk of pregnancy after the first 2 services (49.6 ± 4.5 vs. 33.6 ± 3.9%), and greater milk by 22 wk postpartum (6.7 ± 0.2 vs. 5.3 ± 0.2 × 10³ kg) than cows diagnosed with a clinical disease that had an AMD alert. Adding AMD-generated health alerts to the health screening of postpartum cows in a herd with an existing screening program did not improve survival, milk yield, or reproductive success. In addition, AMD alerts in cows diagnosed with a clinical disease may be indicative of the future success of such cows.

Influence of Subclinical Ketosis in Dairy Cows on Ingestive-Related Behaviours Registered with a Real-Time System

Simple Summary

Earlier disease detection may benefit cows by improving responses to treatment. We expected that changes in rumination before evident clinical signs of subclinical ketosis would result in the earlier identification of disease. Cows with subclinical ketosis showed lesser average values for the following parameters: rumination time and rumination chews (1.48 and 1.68 times respectively; p < 0.001), drinking time (1.50 times; p < 0.001), chews per minute, bolus and chews per bolus (1.12, 1.45 and 1.51 times; p < 0.001). From the 15th day before the diagnosis of ketosis, rumination time in the healthy group was greater than that in subclinical ketosis cows from −0.96% (−17 day) to 187.79% (0 days, p < 0.001). Eating time at the beginning of the experiment in healthy cows was 48.92% and at the end of the period was −91.97% lesser compared to subclinical ketosis (p < 0.001).

Abstract

According to the literature, rumination time can be used as biomarker in the diagnosis of subclinical ketosis (SCK). We hypothesized that SCK in cows influences ingestive-related behaviours registered with the real-time system. The aim of the current study was to determine the influence of SCK on dairy cows’ ingestive-related behaviours registered with a real-time system. Twenty Lithuanian Black and White breed dairy cows were selected based on the following criteria: First day after calving, having two or more lactations (on average 3.0 ± 0.13 lactations), and being clinically healthy. The experiment lasted 18 days. Cows were tested 24 h a day for 17.5 days. On the day of diagnosis (day 0), data were recorded for 12 h. During the experimental period, one cow was studied for a total of 420 h. For the registration of rumination behaviour, the RumiWatch system (RWS) was used. It was found that cows with SCK showed lesser average values for the following parameters: rumination time and rumination chews (1.48 and 1.68 times respectively; p < 0.001), drinking time (1.50 times; p < 0.001), chews per minute, bolus and chews per bolus (1.12, 1.45 and 1.51 times; p < 0.001). From the 15th day before the diagnosis of SCK, rumination time in health cows was greater than that in SCK cows from −0.96% (−17 day) to 187.79% (0 days, < 0.001). We estimated the greater average value of drinking time in healthy cows compared with SCK cows from 34.22% on day −17 to −121.67% on day 0 (p < 0.001). Decrease in rumination time was associated with a significant increase in the probability of risk of SCK. Further studies are needed with a larger number of cows with SCK.

Predicting the risk of retained fetal membranes and metritis in dairy cows according to prepartum hemogram and immune and metabolic status

Uterine diseases affect a significant proportion of dairy cows, causing significant economic losses. Immune and metabolic statuses are associated with the risk of retained fetal membranes (RFM) and metritis. The hypothesis of this study was that it is possible to use such responses to predict the risk of RFM and metritis. Data from cows (Jersey = 143, Holstein = 116) previously used in four experiments were used. Cow factors [parity, BCS change from -28 to 0 d relative to calving, calf sex, calving problems (twins, stillbirth, dystocia)] were evaluated for their association with the risk of RFM and metritis. Blood samples collected in the last week of gestation were used to measure polymorphonuclear leukocyte phagocytosis, oxidative burst, and expression of CD18 and CD62L, total blood count, haptoglobin optical density, and concentrations of glucose, non-esterified fatty acids, and β-hydroxybutyrate. Cows were treated with egg ovalbumin at -21, -7, and 7 d relative to calving and blood samples were used to determine the anti-ovalbumin IgG optical density. Univariable analyses were carried out to identify variables associated with the risk of RFM and metritis. The significant (P ≤  0.15) variables were included in multivariable models from which variables with P >  0.15 were removed in a backward stepwise fashion. Risk of RFM was reduced in the absence of calving problems [adjusted odds ratio (AOR) 95 % confidence interval (CI) = 0.13 (0.02, 0.86)], when intensity of phagocytosis [AOR (95 % CI) = 0.50 (0.25, 1.04)] and expression of CD62L [AOR (95 % CI) = 0.71 (0.46, 1.09)] by polymorphonuclear leukocyte were greater, and when prepartum non-esterified fatty acid concentration was lower [AOR (95 % CI) = 8.71 (0.49, 153.84)]. Calf sex [AOR (95 % CI) = 0.35 (0.10, 1.25)], calving problem [AOR (95 % CI) = 0.14 (0.02, 1.08)], PMNL phagocytosis intensity [AOR (95 % CI) = 0.72 (0.47, 1.11)], polymorphonuclear leukocyte intensity of expression CD18 [AOR (95 % CI) = 0.78 (0.60, 1.00)] and CD62L [AOR (95 % CI) = 0.77 (0.60, 0.98)], and haptoglobin optical density [AOR (95 % CI) = 1.16 (0.97, 1.39)] were associated with metritis. Indexes generated from the estimates of the multivariable analyses to predict the risk of RFM [area under the curve = 0.77 (95 % CI = 0.70 to 0.84)] and metritis [area under the curve = 0.76 (95 % CI = 0.70, 0.81)] demonstrated that polymorphonuclear leukocyte function, non-esterified fatty acid concentration, and haptoglobin optical density prepartum may be used as predictors of uterine diseases.

Associations between lying behavior and activity and hypocalcemia in grazing dairy cows during the transition period

Hypocalcemia is a common metabolic disorder of transition dairy cows that is considered a gateway disease, increasing the risk of other health disorders and reducing cow performance. Clinical milk fever is associated with long periods of recumbency, and it is plausible that cows experiencing non-paretic hypocalcemia may spend more time lying; hence, lying behavior and activity measures may be useful in identifying at-risk cows. The objective of this study was to describe associations among blood calcium (Ca) status at calving and lying behavior and activity measures during the transition period in grazing dairy cows. Blood was sampled on the day of calving (d 0), and d 1, 2, 3, and 4 postcalving, and analyzed for total plasma Ca concentration. Twenty-four multiparous Holstein-Friesian and Holstein-Friesian × Jersey grazing dairy cows were classified, retrospectively, as clinically hypocalcemic (CLIN; blood Ca ≤ 1.4 mmol/L at 1 or more consecutive samplings within 48 h postcalving, but without parturient paresis). These cows were pair-matched (using milk production potential from their estimated breeding value for milk protein, mean body weight at wk -5 and -6 precalving, and, where possible, parity) with 24 cows classified as subclinically hypocalcemic (SUB; blood Ca > 1.4 and < 2.0 mmol/L at 2 consecutive samplings within 48 h postcalving), and 24 cows classified as normocalcemic (NORM; blood Ca ≥ 2.0 mmol/L at 3 consecutive samplings within 72 h postcalving). Lying behavior and activity were monitored using triaxial accelerometers from -21 to +35 d relative to calving. Data were summarized to calculate daily lying time (h/d), daily number of lying bouts (LB; no./d), mean LB duration (min/bout), and the number of steps taken (steps/d). On d 0, the CLIN group were less active and spent approximately 2.6 h longer lying than the SUB and NORM groups, particularly between 0200 and 1400 h. On d 0, the NORM group had fewer LB (16.3/d) than the SUB and CLIN groups (18.2 and 19.2/d, respectively). These differences in behavior were no longer detected 2 d postcalving, and no further differences were observed. The day before calving, the CLIN group spent 1.4 h longer lying down than did the SUB and NORM groups. Further, the relative change in steps from a precalving baseline period (d -14 to -7) until d 0 was positively, linearly associated with blood Ca concentration within 24 h postcalving. Future work should consider daily and temporal changes in behavior in individual cows to determine the potential for these measures to allow early detection of hypocalcemia.

Transition dairy cow health is associated with first postpartum ovulation risk, metabolic status, milk production, rumination, and physical activity

Our objective was to determine the association of health status during the first 60 d in milk (DIM) and first postpartum ovulation risk, physical activities recorded by an activity monitor, and metabolic and milk measures in Holstein cows. Late-gestation heifers and close-up dry cows in 1 herd fitted with CowManager SensOors (Agis, Harmelen, the Netherlands) were enrolled in the study 3 wk before expected parturition to assess ear skin temperature and daily rumination, eating, inactivity, and activity times. Blood samples were collected at calving (d 0), and on d 3, 7, and 14 to assess concentrations of free fatty acids, β-hydroxybutyrate (BHB), calcium, glucose, and haptoglobin. In addition, weekly measures were conducted for body condition, body weight, and progesterone through 63 ± 3 DIM when ovulation was synchronized (GnRH-1 - 7 d - PGF_2α - 24 h - PGF_2α - 32 h - GnRH-2 - 16 h - artificial insemination). Disease diagnosed in 68 of 160 cows (42.5%) was distributed equally between primiparous (48.5%) and multiparous (51.5%) cows. Cows were classified as diseased when any case of metritis, digestive disorders, ketosis, hypocalcemia, calving problems, mastitis, or lameness occurred during the first 60 DIM. Odds of early ovulation by median postpartum d 33 was 1.92 times greater in healthy than diseased cows. Incidence of individual diseases included metritis (18.8%), digestive disorders (17.5%), ketosis (BHB >10 mg/dL; 11.9%), hypocalcemia (Ca <2.2 mmol/L; 10.6%), calving problems (6.3%), mastitis (3.1%), and lameness (3.1%). Odds of early ovulation were 2.48, 2.65, and 5.72 times greater in healthy cows compared with cows diagnosed with metritis, digestive disorders, or ketosis, respectively. Diseased compared with healthy cows had greater concentrations of free fatty acids, BHB, haptoglobin, greater rectal temperature, and lesser concentration of serum calcium on d 0, 3, 7, and 14 than healthy cows. Plasma glucose was not affected by health status, but was lesser in concentration on d 3, 7, and 14 compared with day of calving. Weekly (calving through 9 wk) body condition scores tended to be and weekly body weights were greater in healthy compared with diseased cows. Activity measures differed by health status during prepartum (d -14 through -1) and postpartum (d 0 through 20) periods except for eating time. Healthy cows spent less time being inactive during both periods compared with diseased cows and had greater postpartum rumination times than diseased cows. Mean daily milk yield during the first 14 wk in milk was greater in healthy than diseased cows by 2.1 ± 0.8 kg. We conclude that disease negatively affects early postpartum ovulation risk and is associated with measurable changes in periparturient physical activity and postpartum metabolic profiles.

Sensor technology to support herd health monitoring: Using rumination duration and activity measures as unspecific variables for the early detection of dairy cows with health deviations

A significant number of lactating dairy cows are affected by health disorders in the early postpartum period. Precision dairy farming technologies have tremendous potential to support farmers in detecting disordered cows before clinical manifestation of a disease. The objective of this study was to evaluate if activity and rumination measures obtained by a commercial 3D-accelerometer system, i.e. "lying", "high active", "inactive", and "rumination" times, can be used for early identification of cows with health deviations before the clinical manifestation of disease. A total of 312 Holstein cows equipped with an ear attached accelerometer (Smartbow GmbH, Weibern, Austria) were monitored and analyzed from 14 days prior to parturition to eight days in milk (DIM). Animals were checked daily for clinical disorders from zero to eight DIM using standard operating procedures and by blood β-hydroxybutyrate measurements at three, five, and eight DIM. Cows that presented no symptoms of health problems and with BHB concentrations <1.2 mmol/L in the first eight DIM were classified as healthy (n = 156) and used as the reference in this study. Cows with disorders were allocated in groups with one disorder (n = 65) and >1 disorders (n = 91). "Rumination" durations per day were already shorter five days before the clinical diagnosis (D0) in diseased cows (401.9 ± 147.4 min/day) compared with healthy controls (434.6 ± 140.3 min/day). "Rumination" time decreased before the diagnosis, with a nadir at Day -1 for healthy cows and cows with >1 disorder (392.0 ± 147.9 vs. 313.4 ± 162.6 min/day). Cows with one disorder reached a nadir on Day -3 (388.8 ± 158.6 min/day). Similarly, the "high active" time started to become shorter three days before the clinical diagnosis in diseased cows compared to healthy cows (164.1 ± 119.1 vs. 200.3 ± 111.5 min/day). The times cows spent "inactive" were significantly longer three days before clinical diagnosis in diseased cows compared to healthy cows (421.7 ± 168.3 vs. 362.8 ± 117.6 min/day). "Lying" time started to become significantly longer one day before the diagnosis of disorders in disordered cows compared to healthy cows (691.8 ± 183.3 vs. 627.3 ± 158.0 min/day). On average, these results indicated a strong disturbance of physiological parameters before the clinical onset of disease. In summary, it was possible to show differences between disordered and healthy cows based on activity and "rumination" data recorded by a 3D-accelerometer.

Effect of subclinical and clinical hypocalcemia and dietary cation-anion difference on rumination activity in periparturient dairy cows

Rumination involves a complex series of muscle contractions that bring a bolus of ingesta to the mouth for further mastication before it is swallowed again. Healthy cows ruminate 8 to 9 h/d. Hypocalcemia is known to disrupt nerve and muscle function. Our hypothesis was that hypocalcemia in periparturient cows would reduce rumination activity. Twenty-six Holstein cows entering their third lactation or greater were fed a control diet [dietary cation-anion difference (DCAD) = +196 mEq/kg of dry matter (DM)] or a low DCAD diet supplemented with anions (DCAD = -9 mEq/kg of DM) prepartum. Periparturient plasma Ca concentration and rumination rate were determined. Four of 12 control cows developed clinical milk fever, necessitating intravenous Ca therapy. Rumination rate decreased in all cows around the time of calving. Rumination rate on the first and second day of lactation was highly correlated with the cow's plasma Ca concentration on the first day of lactation. In one of our statistical models, a normocalcemic cow was defined as a cow whose plasma Ca concentration remained above 2.00 mM. Cows were retrospectively classified as normocalcemic, subclinically hypocalcemic, or clinically hypocalcemic (milk fever). Only 4 cows were considered normocalcemic, and all had been fed the low DCAD diet. Normocalcemic cows spent more time ruminating on the first day after calving than subclinically hypocalcemic cows or cows with milk fever. Cows with milk fever had a lower rumination rate than normocalcemic cows through d 3 of lactation. Rumination activity in cows with milk fever was almost nondetectable in the hours before and after intravenous Ca treatment for an extended period, despite the return of muscle function that allowed the cows to stand and eructate following treatment. Other statistical models using different definitions of normocalcemia gave qualitatively similar results. Diet had a great effect on plasma Ca concentration and rumination rate. Even when cows with clinical milk fever were removed from the control cow data set, cows on the low DCAD diet had significantly greater plasma Ca concentrations in the first 36 h after calving and a higher rumination rate on d 1 of lactation (248 ± 26 min) than control cows (158 ± 32 min).

The influence of Megasphaera elsdenii on rumen morphometrics of cull cows immediately stepped up to a high-energy finishing diet

Forty-five beef cull cows [body weight (BW) = 503 ± 58 kg; body condition score (BCS) = 2.1 ± 0.6] were randomized into two treatments to compare the effects of oral drenching of no probiotic vs. 100 mL of Megasphaera elsdenii NCIMB 41125 (M. elsdenii culture; Lactipro Advance; 2 × 10⁸ cfu/mL; MS Biotec, Inc., Wamego, KS) on the realimentation of cull cows. The study featured a rapid 0-d step-up of concentrate-naïve cull cows to a 90% concentrate diet (1.43 Mcal/kg of NE_g). The cows were finished for 35 d and were fitted with a wireless rumination tag (Allflex Flex Tag; SCR Engineers, Ltd, Netanya, Israel), which tracked head movement to record eating and chewing activity. Rumen morphometrics was recorded on the harvest floor, with each carcass assigned a rumenitis score, and a fragment of the cranial sac removed for further papillae analysis. An additional 23, thin, non-fed cull cows were harvested at the same abattoir to compare the effects of concentrate realimentation on ruminal morphometrics. Megasphaera elsdenii culture-drenched cattle registered a 13.3% increase in rumination time (39.27 min/d, P = 0.03) during the first week of the trial compared to controls. A numerical rumination advantage for M. elsdenii culture-administered cattle was observed during week 2 of trial (P = 0.17), with no differences between treatments from weeks 3 to 5 (P ≥ 0.40). Subjective rumenitis evaluations approached a tendency (P = 0.12), with non-M. elsdenii culture-drenched concentrate-fed cattle logging twice the score of their day 0 cohorts (2.52 vs. 1.17) suggesting considerable lactic insults occurred to the ruminal epithelium in the short 35-d trial. Despite the short feeding duration, concentrate realimentation prompted a significant improvement in mean papillae area (P < 0.01). Among concentrate-fed treatments, M. elsdenii culture-drenched cattle posted superior absorptive surface area (P = 0.01) and a greater ratio of papillae area of absorptive surface area (P = 0.05), suggesting that M. elsdenii culture is favorably altering the ecology of the rumen and promoting papillae growth perhaps by mitigating lactate-driven pH drops. In conclusion, M. elsdenii culture application in a 0-d step-up protocol to finishing diets can help mitigate the effects of ruminal acidosis.

Alterations in sick dairy cows' daily behavioural patterns

The recent development of dairy production is characterised by increasing herd sizes and therefore increasingly complicated visual observation of cow behaviour, which is traditionally the basis for diagnoses of production diseases. The limitation of the direct visual behavioural observation due to the increasing number of individual cows implies a growing need for an automated detection of changes within behavioural patterns to identify cows that show sickness behaviour. Sensor systems can be used to measure behavioural patterns such as activity, resting, feeding and rumination. Behavioural patterns change with the occurrence of sickness but also interact with external factors. Changes such as prolonged lying duration or shortened feeding duration caused by metabolic disorders or infections, respectively, then serve as a detection tool for sick individuals. The aim of the present review is to outline the impact of production diseases on the daily behavioural patterns of dairy cows by referring to sickness behaviour.