Index Development to Comprehensive Assess Liver Function during the Dairy Cows' Transition Period in Low-Tropic Conditions

The aim of this work was to develop a liver tissue function index during the transition period of dairy cows managed in low-tropic conditions. In two farms, twenty crossbred and synthetic native cows during the peripartum period were selected, and blood samples were taken on days -30 and -15 prepartum, the calving day, and 7, 20, 35, 50, 65, 80 and 105 days postpartum for serum metabolic tests. On each measurement day, body condition scores (BCS) and parameters on nitrogen metabolism (total protein-TP, albumin-ALB, globulin-GLOB, urea), adipose tissue metabolism (cholesterol-COL, non-esterified fatty acids-NEFA) and two transaminases (alanine aminotransferase-ALT and aspartate aminotransferase-AST) were evaluated. Data analysis included the Spearman correlation, principal components, multiple linear regression and cluster analysis. Results showed that regarding the days after calving and BCS, a liver tissue function index can be constructed using the TP, urea, COL, ALT and NEFA. The estimated index generated three groupings, both by days after calving and BCS. In the former, the index discriminated the metabolic behavior in the prepartum, parturition and postpartum periods, while in the latter, the index discriminated between extreme (2.25, 2.50 and 4.25), slightly low (2.75 and 3.0) and slightly high (3.25 to 4) conditions. The results allow us to conclude that it is feasible to construct mathematical function indexes for liver function to monitor metabolic changes during highly demanding productive phases in dairy cows under tropical conditions.

Predictive modelling of deviation from expected milk yield in transition cows on automatic milking systems

The transition period is a pivotal time in the production cycle of the dairy cow. It is estimated that between 30% and 50% of all cows experience metabolic or infectious disease during this time. One of the most common and economically consequential effects of disease during the transition period is a reduction in early lactation milk production. This has led to the utilisation of deviation from expected milk yield in early lactation as a proxy measure for transition health. However, to date, this analysis has been used exclusively for the retrospective assessment of transition cow health. Statistical models capable of predicting deviations from expected milk yield may allow producers to proactively manage animals predicted to suffer negative deviations in early lactation milk production. The objective of this retrospective cohort study was first, to explore the accuracy with which cow-level production and behaviour data collected on automatic milking systems (AMS) from 1-3 days in milk (DIM) can predict deviation from expected 30-day cumulative milk yield in multiparous cows. And second, to assess the accuracy with which predicted yield deviations can classify cows into groups which may facilitate improved transition management. Production, rumination, and physical activity data from 31 commercial AMS were accessed. A 3-step analytical procedure was then conducted. In Step 1, expected cumulative yield for 1-30 DIM for each individual cow-lactation was calculated using a mixed effect linear model. In Step 2, 30-Day Yield Deviation (YD) was calculated as the difference between observed and expected cumulative yield. Lactations were then assigned to one of three groups based on their YD, RED Group (0% YD). In Step 3, yield, rumination, and physical activity data from days 1-3 in lactation were used to predict YD using machine learning models. Following external validation, YD was predicted across the test data set with a mean absolute error of 9%. Categorisation of animals suffering large negative deviations (RED group) was achieved with a specificity of 99%, sensitivity of 35%, and balanced accuracy of 67%. Our results suggest that milk yield, rumination and physical activity patterns expressed by dairy cows from 1-3 DIM have utility in the prediction of deviation from expected 30-day cumulative yield. However, these predictions currently lack the sensitivity required to classify cows reliably and completely into groups which may facilitate improved transition cow management.

The Relationship between Reticuloruminal Temperature, Reticuloruminal pH, Cow Activity, and Clinical Mastitis in Dairy Cows

We hypothesized that reticuloruminal temperature, pH as well as cow activity can be used as parameters for the early diagnosis of clinical mastitis in dairy cows. Therefore, we aimed to detect the relationship between these factors and the disease. We randomly selected cows with clinical mastitis and clinically healthy cows (HG) out of 600 milking cows. We recorded the following parameters during the experiment: reticulorumen temperature (RR temp.), reticulorumen pH (RR pH), and cow activity. We used smaXtec boluses (smaXtec animal care technology^®, Graz, Austria). In this investigation, reticulorumen data obtained seven days before diagnosis were compared to HG data from the same time period. CM cows were observed on the same days as the healthy cows. The healthy group's RR pH was 7.32% higher than that of cows with CM. Reticulorumen temperature was also 1.25% higher in the CM group than in the control group. The healthy group had a higher average value for walking activity, which was 17.37% higher than the CM group. The data of reticulorumen pH changes during 24 h showed that during the day, the pH changed from 5.53 to 5.83 in the CM group. By contrast, pH changed from 6.05 to 6.31 in the control group. The lowest reticulorumen pH in the CM group was detected on the third day before diagnosis, which was 15.76% lower than the highest reticulorumen pH detected on the sixth day before diagnosis. The lowest reticulorumen pH in CM cows was detected at 0 and 1 days before diagnosis and it was 1.45% lower than the highest reticulorumen pH detected on the second day before diagnosis. The lowest walking activity in the CM group was detected 0 days before diagnosis, which was 50.60% lower than on the fifth day before diagnosis. Overall, the results confirmed our hypothesis that reticuloruminal temperature, reticuloruminal pH, and cow activity could be used as parameters for the early diagnosis of clinical mastitis in dairy cows.

Identification of Changes in Rumination Behavior Registered with an Online Sensor System in Cows with Subclinical Mastitis

The aim of the present study is to determine the relationship between subclinical mastitis and rumination behavior registered with an online sensor system. Based on the findings of the general clinical examination of 650 milking cows, 10 cows with subclinical mastitis (SCM) and 10 clinically healthy cows (HG) were selected (without clinical signs of any diseases). Rumination behavior biomarkers were registered with RumiWatch noseband sensors (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Sensors were implanted on the first day after calving. Data from the RWS 13 days before diagnosis of SCM and 13 days after diagnosis of SCM were compared with HG data from the same period. Healthy cows were checked alongside SCM cows on the same days. In our study, we found that healthy cows spent more time engaging in rumination and drinking (p < 0.05) and also had more boluses per rumination. Moreover, among cows with subclinical mastitis, rumination time from day 4 to day 0 decreased by 60.91%, drinking time decreased by 48.47%, and the number of boluses per rumination decreased by 8.67% (p < 0.05). The results indicate that subclinical affects time and rumination chews registered with sensor systems. However, additional studies with larger numbers of animals are required to confirm these results. Furthermore, the impact of heat stress, estrus, and other effects on rumination behavior biomarkers should be evaluated.

Exploring the role of milk yield in the first week of lactation on the association between hyperketonemia and reproductive performance in dairy cattle

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No clear evidence was found to support an association between hyperketonemia and reproductive performance.

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Hyperketonemia was associated with lower risk of pregnancy among low-yielding cows.

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Early lactation plays a role in the association of hyperketonemia with reproduction.

The objective of this retrospective cohort study was to investigate whether the association of hyperketonemia (HYK) with reproductive performance differs based on milk production during the first week of lactation (wk 1). Data between calving and 150 d in milk (DIM) from 2,091 Holstein dairy cows from 5 commercial dairy herds in Minnesota were collected. The concentration of β-hydroxybutyrate (BHB) was measured twice between 3 and 10 DIM in whole blood to diagnose HYK (defined as BHB ≥1.2 mmol/L). The average wk 1 milk yield was classified into 3 levels (low = lower 25th percentile; mid = 25th to 75th percentile; high = upper 75th percentile) according to parity and herd. Log-binomial regression, Cox-proportional hazard regression, and linear regression models were used to investigate the association of HYK with pregnancy to first insemination, pregnancy by 150 DIM, and calving-to-conception interval (CCI) between groups, respectively. To describe the differences in these estimates between each wk 1 milk yield level, an interaction term of HYK and stratified levels of wk 1 milk yield was added. The incidence of HYK between 3 to 10 DIM was 14.2% (4.6% in primiparous cows and 19.4% in multiparous cows). In the study population, the effect of HYK on reproduction was greater in cows with low milk yield. Among cows with low milk yield levels, HYK was associated with lower risk of pregnancy to first insemination [risk ratio = 0.62; 95% confidence interval (CI): 0.39–0.98], lower risk of pregnancy up to 150 DIM (hazard ratio = 0.70; 95% CI: 0.51–0.96), and extended days of CCI (mean difference = 13.0; 95% CI: 5.1–20.9). In contrast, among cows with mid and high wk 1 milk yield levels, hyperketonemic (HYK+) cows had a similar reproductive performance to non-HYK (HYK−) cows. Our results suggest that early-lactation milk yield plays a role in the association of hyperketonemia with reproductive performance. These results merit further investigation to determine the role that early milk yield has in the association of hyperketonemia with health and productivity outcomes.

Monitoring and Improving the Metabolic Health of Dairy Cows during the Transition Period

Simple Summary

The transition from late gestation to early lactation is a challenging period for dairy cows. A successful transition period depends on metabolic adaptation to the new physiological state in early lactation and proper management in order to support the cow’s requirements. This review paper will discuss various aspects of routine and consistent approaches to collect and analyze herd records, to detect unintended disruptions in performance. In addition, we discuss how to incorporate methods to assess health, production, nutrition, and welfare information to monitor cows during the transition period. Lastly, we discuss management strategies that can be implemented to improve the metabolic health and performance of transition dairy cows.

Abstract

The peripartum period of a dairy cow is characterized by several physiological and behavioral changes in response to a rapid increase in nutrient demands, to support the final stages of fetal growth and the production of colostrum and milk. Traditionally, the transition period is defined as the period 3 weeks before and 3 weeks after parturition. However, several researchers have argued that the transition period begins at the time of dry-off (~60–50 days prior to calving) and extends beyond the first month post-calving in high producing dairy cows. Independent of the definition used, adequate adaptation to the physiological demands of this period is paramount for a successful lactation. Nonetheless, not all cows are successful in transitioning from late gestation to early lactation, leading to approximately one third of dairy cows having at least one clinical disease (metabolic and/or infectious) and more than half of the cows having at least one subclinical case of disease within the first 90 days of lactation. Thus, monitoring dairy cows during this period is essential to detect early disease signs, diagnose clinical and subclinical diseases, and initiate targeted health management to avoid health and production impairment. In this review, we discuss different strategies to monitor dairy cows to detected unintended disruptions in performance and management strategies that can be implemented to improve the metabolic health and performance of dairy cows during the transition period.

Relation of Subclinical Ketosis of Dairy Cows with Locomotion Behaviour and Ambient Temperature

Simple Summary

The use of innovative tools and the registration of new biomarkers can help with identification of certain diseases in fresh dairy cows earlier and more accurately, thus improving the quality of treatment and reducing the losses incurred. One of the most often diagnosed diseases of postpartum cows is subclinical ketosis. According to our knowledge there exists limited information about how subclinical ketosis is related to locomotion behaviour (walking activity, feeding time with head position down, feeding time with head position up, change between activities) and average, minimal and maximal ambient temperature. We hypothesized that continuous maximal monitoring of cow locomotion behaviour (in combination with measuring the ambient temperature) could identify cows with subclinical ketosis. In addition, we hoped that changes of the above-mentioned parameters prior to clear clinical signs of subclinical ketosis would aid in earlier detection of the disease.

Abstract

Rumination time, chewing time and drinking time are indicators that can be assessed in case of cow disease. In this research, two groups of cows were formed: cows with subclinical ketosis (SCK; n = 10) and healthy cows (HG; n = 10). Behaviour such as walking activity, feeding time with head position up, feeding time with head position down, change of activity and average, minimal and maximal ambient temperature of cows were recorded by the RumiWatch noseband system (RWS; RumiWatch System, Itin+Hoch GmbH, Liestal, Switzerland). The RWS comprises a noseband halter with a built-in pressure sensor and a liquid-filled pressure tube. Data from each studied cow were recorded for 420 h. According to the results of our study, it was determined that cows diagnosed with subclinical ketosis showed a tendency to change their activity more frequently. Our data indicates that minimal and maximal ambient temperatures are related with SCK.

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.

Preliminary Experiment Using Sensors for Cow Health Monitoring after Surgical Treatment for the Left Displacement of the Abomasum

The aim of the current study was to determine the effectiveness of two surgical techniques regarding cow respiratory rates, heart rates, and rumination time using two sensors: an experimental device created by the Institute of Biomedical Engineering of Kaunas University of Technology (Lithuania) and the Hi-Tag rumination monitoring system (SCR) produced by SCR Engineers Ltd., Netanya, Israel. The cows were divided into two groups: the PA1 group, containing cows treated by percutaneous abomasopexy (n = 10), and the RSO2 group, containing cows treated by right side omentopexy (n = 8). For the control group (KH), according to the principle of analogs (number of lactations, breed, and days in milk), we selected clinically healthy cows (n = 9). After the surgical treatment for the abomasal displacement, the experimental device was applied for the recording of the heart and breathing rates, 12 h tracking of the rumination time was implemented using the SCR, and the body temperature was measured. After 12 h, the blood was taken for biochemical and morphological tests. With the help of experimental sensors, we found that the more efficient abomasal displacement surgical method was the right side omentopexy: During the first 12 h after right side omentopexy, we found a 5.19 beats/min lower (1.10 times lower) average value of the respiratory rate, a 1.13 times higher level of the heart rate, a 0.15 °C higher temperature, and a 3.29 times lower rumination time compared to the clinically healthy cows. During the first 12 h after percutaneous abomasopexy, we found a 5.19 beats/min higher (1.07 times) average value of heart rate, a 0.02 °C higher temperature, a 6.21 times lower rumination time, and a 0.12 beats/min lower (1.01 times lower) average value of respiratory rate compared to the clinically healthy cows.

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.

Associations of reproductive indices with fertility outcomes, milk yield, and survival in Holstein cows

The study is part of a research effort investigating potential associations between genomic variation and fertility of Holstein cows. The objective was to compare the reproductive performance of Holstein cows in 3 categories of 2 reproductive indices (RI) that were developed for the allocation of cows in a ranking for potential fertility, based on the predicted probability of pregnancy. The associations between categories of the developed indices and multiple fertility variables in a large multistate population of Holstein cows were tested. In addition, we analyzed associations among the RI categories with milk yield and survival. Based on phenotypic information from individual cows, 2 reproductive indices (RI1 and RI2) were developed, representing a predicted probability that a cow will become pregnant at first artificial insemination postpartum, as a function of explanatory variables used in a logistic model. Data from a total of 11,733 cows calving in 16 farms located in 4 regions of the United States (Northeast, Midwest, Southeast, and Southwest) were available. Cows were enrolled at parturition and monitored weekly for reproductive events, health status, milk yield, and survival. To develop the indices, potential significant effects were initially tested by univariate analyses. Effects with P ≤ 0.05 were offered to the multivariate analysis, and the final models were determined through backward elimination, considering potentially significant interactions. The final model for RI1 included the random effect of farm and a complement of significant fixed effects as explanatory variables influencing a pregnancy outcome: (1) incidence of retained fetal membranes; (2) metritis; (3) clinical endometritis; (4) lameness at 35 days in milk (DIM); (5) resumption of postpartum ovulation by 50 DIM; (6) season of calving; and (7) parity number. The model for RI2 included (1) parity number; (2) body condition score at 40 DIM; (3) incidence of retained fetal membranes; (4) metritis; (5) resumption of postpartum ovulation by 50 DIM; (6) region; (7) subclinical ketosis; (8) mastitis; (9) clinical endometritis; and (10) milk yield at the first milk test after calving; as well as the interaction effects of postpartum resumption of ovulation by 50 DIM × region; mastitis × region; and milk yield at the first milk test after calving × parity number. Multivariate logistic regression, ANOVA, and survival analysis were used to test the correspondence between the resulting RI and individual fertility, milk yield, and survival from the population. To facilitate the analyses, the resulting RI values were categorized as low for cows in the lowest quartile, medium for cows within the interquartile range, or high for cows in the top quartile. We found consistent agreement between categories of the predicted RI and the measures of fertility and survival collected from individual cows. We conclude that the proposed RI represent a viable approach to refine the allocation of cows into potential low- and high-fertility populations.

Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part I. Metabolic and digestive disorders

The objectives of this study were to evaluate (1) the performance of an automated health-monitoring system (AHMS) to identify cows with metabolic and digestive disorders-including displaced abomasum, ketosis, and indigestion-based on an alert system (health index score, HIS) that combines rumination time and physical activity; (2) the number of days between the first HIS alert and clinical diagnosis (CD) of the disorders by farm personnel; and (3) the daily rumination time, physical activity, and HIS patterns around CD. Holstein cattle (n=1,121; 451 nulliparous and 670 multiparous) were fitted with a neck-mounted electronic rumination and activity monitoring tag (HR Tags, SCR Dairy, Netanya, Israel) from at least -21 to 80 d in milk (DIM). Raw data collected in 2-h periods were summarized per 24 h as daily rumination and activity. A HIS (0 to 100 arbitrary units) was calculated daily for individual cows with an algorithm that used rumination and activity. A positive HIS outcome was defined as a HIS of <86 during at least 1 d from -5 to 2 d after CD. Blood concentrations of nonesterified fatty acids, β-hydroxybutyrate, total calcium, and haptoglobin were determined in a subgroup of cows (n=459) at -11±3, -4±3, 0, 3±1, 7±1, 14±1, and 28±1 DIM. The sensitivity of the HIS was 98% [95% confidence interval (CI): 93, 100] for displaced abomasum (n=41); 91% (95% CI: 83, 99) for ketosis (n=54); 89% (95% CI: 68, 100) for indigestion (n=9); and 93% (95% CI: 89, 98) for all metabolic and digestive disorders combined (n=104). Days (mean and 95% CI) from the first positive HIS <86 and CD were -3 (-3.7, -2.3), -1.6 (-2.3, -1.0), -0.5 (-1.5, 0.5), and -2.1 (-2.5, -1.6) for displaced abomasum, ketosis, indigestion, and all metabolic and digestive disorders, respectively. The patterns of rumination, activity, and HIS for cows flagged by the AHMS were characterized by lower levels than for cows without a health disorder and cows not flagged by the AHMS from -5 to 5 d after CD, depending on the disorder and parameter. Differences between cows without health disorders and those flagged by the AHMS for blood markers of metabolic and health status confirmed the observations of the CD and AHMS alerts. The overall sensitivity and timing of the AHMS alerts for cows with metabolic and digestive disorders indicated that AHMS that combine rumination and activity could be a useful tool for identifying cows with metabolic and digestive disorders.