The effects of liveweight loss and milk production on the risk of lameness in a seasonally calving, pasture fed dairy herd in New Zealand

Metabolic imbalances, hoof injuries, and metabolic profile of high-producing Holstein × Gir cowsshowing lameness

ABSTRACT: This study attempted to determine the associations between metabolic imbalances and lameness or hoof injuries in high-producing Holstein × Gir cows, and to determine whether the metabolic profile affects the occurrence of lameness. Eighty cows were followed from -60 to 60 days relative to calving and hoof injuries were reported on days -60, 7 and 60. Locomotion score (LS), body condition score (BCS), the concentrations of non-esterified fatty acids, β-hydroxybutyrate, glucose, cholesterol, albumin, total protein, blood urea nitrogen (BUN), calcium, phosphorus, and magnesium, and the activity of aspartate aminotransferase were determined at days -42, -21, -7, 0, 7, 21 and 42. The McNemar and Chi-square tests were used to compare frequencies of lameness and hoof injuries over time and to verify the associations between lameness, BCS, hoof injuries, and metabolic disorders. Two-way repeated measures ANOVA was used considering groups (non-lame × lame cows) and variations of BCS and metabolites over time. Lameness and hoof injuries increased between days -60 (20% and 66.3%) and 60 (44.7% and 98.6%). Excessive postpartum loss of BCS (P=0.017) and subclinical hypocalcemia (P=0.012) were associated with lameness on day 60. In general, the metabolic profile did not differ between lame and non-lame cows but cholesterol, albumin, BUN and magnesium concentrations were higher in non-lame cows. The postpartum decrease in BCS can affect the occurrence of lameness, and the metabolic profile of lame cows shows little difference from that of non-lame cows.

Prediction of lameness using automatically recorded activity, behavior and production data in post-parturient Irish dairy cows

BACKGROUND

Although visual locomotion scoring is inexpensive and simplistic, it is also time consuming and subjective. Automated lameness detection methods have been developed to replace the visual locomotion scoring and aid in early and accurate detection. Several types of sensors are measuring traits such as activity, lying behavior or temperature. Previous studies on automatic lameness detection have been unable to achieve high accuracy in combination with practical implementation in a on farm commercial setting. The objective of our research was to develop a prediction model for lameness in dairy cattle using a combination of remote sensor technology and other animal records that will translate sensor data into easy to interpret classified locomotion information for the farmer. During an 11-month period, data from 164 Holstein-Friesian dairy cows were gathered, housed at an Irish research farm. A neck-mounted accelerometer was used to gather behavioral metrics, additional automatically recorded data consisted of milk production and live weight. Locomotion scoring data were manually recorded, using a one-to-five scale (1 = non-lame, 5 = severely lame). Locomotion scores where then used to label the cows as sound (locomotion score 1) or unsound (locomotion score ≥ 2). Four supervised classification models, using a gradient boosted decision tree machine learning algorithm, were constructed to investigate whether cows could be classified as sound or unsound. Data available for model building included behavioral metrics, milk production and animal characteristics.

RESULTS

The resulting models were constructed using various combinations of the data sources. The accuracy of the models was then compared using confusion matrices, receiver-operator characteristic curves and calibration plots. The model which achieved the highest performance according to the accuracy measures, was the model combining all the available data, resulting in an area under the curve of 85% and a sensitivity and specificity of 78%.

CONCLUSION

These results show that 85% of this model's predictions were correct in identifying cows as sound or unsound, showing that the use of a neck-mounted accelerometer, in combination with production and other animal data, has potential to replace visual locomotion scoring as lameness detection method in dairy cows.

Routine Herd Health Data as Cow-Based Risk Factors Associated with Lameness in Pasture-Based, Spring Calving Irish Dairy Cows

Simple Summary

Dairy cow lameness is considered one of the most important animal welfare and economic concerns for the dairy industry. Cow-based risk factors for lameness are not well described, especially in comparison to herd-level risk factors such as housing environment and roadway condition. This study investigates the use of routinely gathered herd health data as cow-based risk factors for lameness in dairy cows. A total of 1715 cows in 10 pasture-based Irish dairy herds were monitored for lameness during the spring and summer of 2013 and 2014 as part of the University College Dublin herd health programme. Herd health monitoring data analysed to identify potential risk factors for lameness consisted of milk production data, genetic merit information, calving details, peri-parturient disease records and body condition scores. This analysis showed a significant effect of increasing parity, lower body condition score at calving and excessive body condition loss after calving on the risk of cows being diagnosed as lame during the lactation. In conclusion, routinely gathered herd health monitoring data can be used to identify cows at increased risk of being lame and to implement lameness control strategies.

Abstract

Herd-level risk factors related to the cow’s environment have been associated with lameness. Uncomfortable stall surface and inadequate depth of bedding as well as abrasive alley way surface are contributing factors to increased levels of lameness. Access to pasture has been found as having a beneficial effect on cows’ locomotion. However, dairy cattle managed under grazing conditions are exposed to a different set of risk factors for lameness, mainly associated with cow tracks. Cow-based risk factors for lameness are not as clearly defined as the herd level risk factors. The objective of the present study was to use routine herd health monitoring data to identify cow-based risk factors for lameness and utilise this information to indicate cows at risk of developing lameness in the first 150 days of lactation. Lameness data were gathered from 10 pasture-based dairy herds. A total of 1715 cows were monitored, of which 1675 cows were available for analysis. Associations between lameness status and potential cow-level risk factors were determined using multivariable logistic regression. Parity 3 and 4 + cows showed odd ratios (OR’s) for lameness of 3.92 and 8.60 respectively (95% confidence interval (CI) 2.46–6.24; 5.68–13.0). Maximum loss of Body condition score (BCS) after calving exhibits OR’s for lameness of 1.49 (95% CI 1.08–2.04) if cows lost 0.5 in BCS after calving and 2.26 (95% CI 1.30–3.95) for cows losing more than 0.5 BCS. Animals calving in BCS 3.25 and ≥ 3.5 had correlating OR’s of 0.54 (95% CI 0.34–0.87) and 0.33 (95% CI 0.16–0.65) for being lame compared to cows calving with BCS ≤ 2.75. Data gathered as part of herd health monitoring can be used in conjunction with lameness records to identify shortcomings in lameness management. Findings and recommendations on lameness management can be formulated from readily available information on cow-based risk factors for lameness.

Aspects of lameness in pasture based dairy systems

Pasture-based dairy systems are implemented all over the world. Access to pasture is perceived to be advantageous for animal welfare in western societies. However, the benefits of grazing on lameness are not uniformly verifiable. This is related to the challenges that grazing cows face which are different from zero-grazing systems to some extent, but may nevertheless be deleterious. The distribution of lesion types comparing housed and pastured cattle differs between studies. This may be caused by differences in how strongly certain risk factors apply in these studies. Major risk factors for lameness in grazing cattle are related to the risk of trauma, for example from long walking distances and lack of track maintenance, and cow factors such as the adaptability of certain breeds to the grazing lifestyle. The consequences of lameness are similar to zero-grazing cattle and negatively affect animal welfare and productivity.

Cow- and herd-level factors associated with lameness in small-scale grazing dairy herds in Brazil

This cross-sectional study aimed to assess lameness occurrence and to identify the associated risk factors in small-scale grazing dairy herds. Forty four farms (mean lactating herd size was 42 cows, SD = 11.2, range: 28-74) located in the south of Brazil were visited twice, approximately 4 months apart, in 2015. Locomotion was scored in 1633 and 1836 cows at the first and second visit, respectively. Potential risk factors for lameness were assessed through inspection of cows and facilities, and a questionnaire for farmers about herd management practices. Multilevel logistic regressions, using herd as random effect, were fitted to investigate the cow-level risk factors for accumulated incident (not lame at the first visit but lame on the second), chronic (lame on both visits) and recovered (lame at the first visit but sound on the second) cases of lameness. A multilevel linear regression, using municipality as a random effect, was fitted for herd-level analysis. Cumulative lameness incidence between two visits (1110 cows in 41 herds) was 29.6% (range: 0-80); lameness prevalence (n = 44 herds) was 31% (10-70) and 35% (5-76) at the first and second visits, respectively. The odds of incident cases were greater in Holstein cows [odds ratio (OR) = 4.0, 95% confidence interval 2.1-7.6] compared with Jerseys, in cows in parities 2-3 (OR 2.5, 1.4-4.4) or >3 (OR 6.6, 3.3-13.1) relative to parity 1, in cows having a low body condition score (BCS) of 2-2.75 or 3 on the first visit (OR 2, 1.1-3.7), and in cows with observed hoof abnormalities (OR 2.5, 1.3-4.7). Similar associations were found for chronic cases, with Holstein and crossbred cows having greater odds of lameness, compared to Jersey, and chronic cases being more likely in cows with increasing parity, with BCS at first visit of 2-2.75, and with presence of hoof abnormalities. Jersey or crossbred cows (OR 3.2, 1.3-8.1) and cows in parity 1-2 (OR 3.6, 1.6-8.4) had higher probability of recovery from lameness. Having a herd composed of Holstein cows was associated with 13.5% (CI 4.3-22.8) greater incidence of lameness (n = 35). For every 1 km/h increase in the average speed of movement of the herd to or from milking, lameness incidence increased by 5% (CI 0.1-10). Given that the occurrence of lameness was high there is great opportunity to reduce lameness in this population. This study highlights some management and prevention practices that may reduce lameness in these grazing herds.

The contribution of previous lameness events and body condition score to the occurrence of lameness in dairy herds: A study of 2 herds

It has been demonstrated that low body condition and previous occurrence of lameness increase the risk of future lameness in dairy cows. To date the population attributable fraction (PAF), which provides an estimate of the contribution that a risk factor makes toward the total number of disease events in a population, has not been explored for lameness using longitudinal data with repeated measures. Estimation of PAF helps to identify control measures that could lead to the largest improvements on-farm. The aim of this study was to use longitudinal data to evaluate the proportion of lameness that could be avoided in 2 separate herds (2 populations) through (1) reduced recurrence of previous lameness events, (2) and moving body condition score (BCS) into more optimal ranges. Data were obtained from 2 UK dairy herds: herd A, a 200-cow herd with 8 yr of data from a total of 724 cows where lameness events were based on weekly locomotion scores (LS; 1 to 5 scale), and herd B, a 600-cow herd with data recorded over 44 mo from a total of 1,040 cows where treatment of clinical cases was used to identify lameness events. The PAF for categories of BCS were estimated using a closed equation appropriate for multiple exposure categories. Simulation models were used to explore theoretical scenarios to reflect changes in BCS and recurrence of previous lameness events in each herd. For herd A, 21.5% of the total risk periods (cow-weeks) contained a lameness event (LS 3, 4, or 5), 96% of which were repeat events and 19% were recorded with BCS <2 (3 wk previously; 0 to 5 scale). When lameness events were based on 2 consecutive weeks of LS 4 or 5, 4% of risk periods were recorded as lame, of which 89.5% were repeat events. For herd B, 16.3% of the total risk periods (consecutive 30 d) contained a lameness event (72.6% were repeat events) and 20% were recorded with BCS ≤2 (0 to 120 d previously). The median PAF for all previous lameness was between 79 and 83% in the 2 herds. Between 9 and 21% of lameness events could be attributed to previous lameness occurring >16 wk before a risk period. The median PAF estimated for changes in BCS were in the region of 4 to 11%, depending on severity of lameness. Repeated bouts of lameness made a very large contribution to the total number of lameness events. This could either be because certain cows are initially susceptible and remain susceptible, due to the increased risk associated with previous lameness events, or due to interactions with environmental factors. This area requires further research.

Lameness Prevalence and Risk Factors in Large Dairy Farms in Upstate New York. Model Development for the Prediction of Claw Horn Disruption Lesions

The main objectives of this prospective cohort study were a) to describe lameness prevalence at drying off in large high producing New York State herds based on visual locomotion score (VLS) and identify potential cow and herd level risk factors, and b) to develop a model that will predict the probability of a cow developing claw horn disruption lesions (CHDL) in the subsequent lactation using cow level variables collected at drying off and/or available from farm management software. Data were collected from 23 large commercial dairy farms located in upstate New York. A total of 7,687 dry cows, that were less than 265 days in gestation, were enrolled in the study. Farms were visited between May 2012 and March 2013, and cows were assessed for body condition score (BCS) and VLS. Data on the CHDL events recorded by the farm employees were extracted from the Dairy-Comp 305 database, as well as information regarding the studied cows’ health events, milk production, and reproductive records throughout the previous and subsequent lactation period. Univariable analyses and mixed multivariable logistic regression models were used to analyse the data at the cow level. The overall average prevalence of lameness (VLS > 2) at drying off was 14%. Lactation group, previous CHDL, mature equivalent 305-d milk yield (ME305), season, BCS at drying off and sire PTA for strength were all significantly associated with lameness at the drying off (cow-level). Lameness at drying off was associated with CHDL incidence in the subsequent lactation, as well as lactation group, previous CHDL and ME305. These risk factors for CHDL in the subsequent lactation were included in our predictive model and adjusted predicted probabilities for CHDL were calculated for all studied cows. ROC analysis identified an optimum cut-off point for these probabilities and using this cut-off point we could predict CHDL incidence in the subsequent lactation with an overall specificity of 75% and sensitivity of 59%. Using this approach, we would have detected 33% of the studied population as being at risk, eventually identifying 59% of future CHDL cases. Our predictive model could help dairy producers focusing their efforts on CHDL reduction by implementing aggressive preventive measures for high risk cows.