Animal-based welfare indicators for dairy cows and their validity and practicality: a systematic review of the existing literature

Animal welfare is of increasing importance, with consumers preferring animal products made with ethical practices due to growing awareness. This shift highlights the need for reliable methods to evaluate welfare. This systematic review aims to assess the validity of current animal-based welfare indicators for dairy cows to aid farmers and agricultural professionals in evaluating and improving welfare amidst the lack of a clear legislative definition. The literature search spanned five databases: CAB Direct, PubMed, Scopus, Google Scholar and Livivo, covering publications in English and German from 2011 to 2021. Specific search terms were employed, and abstracts were screened for relevance. Publications were categorized based on exclusion criteria, with a final verification process conducted by three independent scientists. Research highlights correlations between welfare measures, farm characteristics and innovative indicators like hair cortisol concentration. Farming systems and housing methods significantly affect welfare, with pasture-based systems generally resulting in reduced lameness and improved behavior. Proper housing design and management practices are important, as they influence indicators like lameness and cleanliness. Heart rate variability and heart rate monitoring provide insights into dairy cow stress levels during milking and other stressors, making them valuable for welfare assessment. Biomarker research emphasizes the need to balance productivity and health in breeding strategies, as high milk production alone does not indicate good welfare. Behavioral studies and the human-animal relationship are key to understanding welfare. Precision Livestock Farming offers real-time assessment capabilities, although validation is needed. Stress physiology is complex, and while cortisol measurement methods are promising, further research is necessary. Assessment tools like the Animal Needs Index and routine herd data analysis are valuable for identifying welfare concerns. Key findings highlight the WQ® protocol's effectiveness and versatility, the challenge of its time demands, and the DCF protocol's promise for more practical and efficient welfare assessments. Commercial animal welfare audits should prioritize easily observable indicators and herd records due to logistical constraints in measuring biomarkers or heart rate variability. This focus on easily accessible indicators, such as body condition score, lameness, claw health, cleanliness, and somatic cell count allows effective welfare assessments, enabling prompt action to enhance wellbeing.

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

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

Cow Behavior Recognition Based on Wearable Nose Rings

This study introduces a novel device designed to monitor dairy cow behavior, with a particular focus on feeding, rumination, and other behaviors. This study investigates the association between the cow behaviors and acceleration data collected using a three-axis, nose-mounted accelerometer, as well as the feasibility of improving the behavioral classification accuracy through machine learning. A total of 11 cows were used. We utilized three-axis acceleration sensors that were fixed to the cow's nose, and these devices provided detailed and unique data corresponding to their activity; in particular, a recorder was installed on each nasal device to obtain acceleration data, which were then used to calculate activity levels and changes. In addition, we visually observed the behavior of the cattle. The characteristic acceleration values during feeding, rumination, and other behavior were recorded; there were significant differences in the activity levels and changes between different behaviors. The results indicated that the nose ring device had the potential to accurately differentiate between eating and rumination behaviors, thus providing an effective method for the early detection of health problems and cattle management. The eating, rumination, and other behaviors of cows were classified with high accuracy using the machine learning technique, which can be used to calculate the activity levels and changes in cattle based on the data obtained from the nose-mounted, three-axis accelerometer.

A new approach and insights on modelling the impact of production diseases on dairy cow welfare

Animal welfare is becoming an important consideration in animal health-related decision-making. Integrating considerations of animal welfare into the decision-making process of farmers involves recognising the significance of health disorder impacts in relation to animal welfare. Yet little research quantifies the impact, making it difficult to include animal welfare in the animal health decision-making process. Quantifying the impact of health disorders on animal welfare is incredibly challenging due to empirical animal-based data collection constraints. An approach to circumvent these constraints is to rely on expert knowledge whereby perceived welfare impairment weights are indicative of the negative welfare effect. In this research, we propose an expertise-based method to quantify the perceived impact of sub-optimal mobility (SOM) on the welfare of dairy cows, because of its welfare importance. We first quantified perceived welfare impairment weights of SOM by eliciting expert knowledge using adaptive conjoint analysis (ACA). Second, using the perceived welfare impairment weights, we derived the perceived welfare disutility (i.e., perceived negative welfare effect) of mobility scores 1-5 (1 = optimal mobility, 5 = severely impaired mobility). Third, using the perceived welfare disutility per mobility score, we quantified the perceived welfare impact at case- and herd-level of SOM for different SOM severity. Results showed that perceived welfare disutility increased with each increase in mobility score. However, the perceived welfare impact of SOM cases with lower mobility scores was higher compared to SOM cases with higher mobility scores. This was because of the longer-lasting duration of the SOM cases with lower mobility scores. Moreover, the perceived herd-level welfare impact was largely due to SOM cases with lower mobility scores because of the longer duration and more frequent incidence compared to the SOM cases with higher mobility scores. These results entail that better welfare of dairy cows with respect to SOM can be achieved if lower mobility scores are detected and treated sooner. Our research demonstrates a novel approach that quantifies the perceived impact of health disorders on animal welfare when empirical evidence is limited.

Hind feet position score: A novel trait to genetically reduce lameness incidence

Lameness is an important health and welfare issue that causes considerable economic losses in dairy herds. The objective of this study was to investigate whether the hind feet position score (HFPS) can be used as an auxiliary trait for genetic evaluation of lameness. The HFPS is evaluated by visual scoring of the position of both the hind-digits to the mid-line of the cow's body. The higher the heel height of the lateral claw, the higher is the HFPS, and the higher is the risk for development of lameness. In total, 3,478 records from 1,064 Fleckvieh cows from 35 farms were obtained between September 1, 2021, and March 5, 2022. Data collection was carried out by the regional milk recording organizations. Hind feet position was scored visually by trained personnel during routine milk performance testing in the milking parlor using a 3-class scoring system: score 1 = 0° to <17° indicating a balanced heel height of both the medial and the lateral claw; score 2 = angle of 17° to 24°; score 3 = angle of >24°. After all cows had been milked, locomotion scoring was performed for each animal using a 5-class scoring system with locomotion scores ranging between 1 (normal) and 5 (severely lame). Using HFPS, sensitivity and specificity were 69.5% and 66.8%, respectively, for detecting lameness defined by locomotion score ≥2. For genetic analyses, a bivariate linear animal model was fitted with fixed effects of herd, parity, lactation stage, and classifier, and random effects of animal and permanent environment. Heritabilities for HFPS and locomotion score were 0.07 and 0.10, respectively, and the genetic correlation between the 2 traits studied was 0.80. These results suggest that the HFPS could be used for genetic evaluations to reduce lameness incidence in dairy cattle.

Uncovering Patterns in Dairy Cow Behaviour: A Deep Learning Approach with Tri-Axial Accelerometer Data

The accurate detection of behavioural changes represents a promising method of detecting the early onset of disease in dairy cows. This study assessed the performance of deep learning (DL) in classifying dairy cows' behaviour from accelerometry data acquired by single sensors on the cows' left flanks and compared the results with those obtained through classical machine learning (ML) from the same raw data. Twelve cows with a tri-axial accelerometer were observed for 136 ± 29 min each to detect five main behaviours: standing still, moving, feeding, ruminating and resting. For each 8 s time interval, 15 metrics were calculated, obtaining a dataset of 211,720 observation units and 15 columns. The entire dataset was randomly split into training (80%) and testing (20%) datasets. The DL accuracy, precision and sensitivity/recall were calculated and compared with the performance of classical ML models. The best predictive model was an 8-layer convolutional neural network (CNN) with an overall accuracy and F1 score equal to 0.96. The precision, sensitivity/recall and F1 score of single behaviours had the following ranges: 0.93-0.99. The CNN outperformed all the classical ML algorithms. The CNN used to monitor the cows' conditions showed an overall high performance in successfully predicting multiple behaviours using a single accelerometer.

Ovarian and Energy Status in Lame Dairy Cows at Puerperium and Their Responsiveness in Protocols for the Synchronization of Ovulation

The purpose of this study was to assess the ovarian and energy status of multiparous lame dairy cows at the end of puerperium and investigate their responsiveness to estrous synchronization treatment regimens. Initial lameness scoring was performed at 28 ± 5 and 37 ± 5 d post partum, followed by lesion documentation and treatment. Cows were blocked by lameness severity and were randomly allocated to an estrous synchronization treatment regimen with seven days of progesterone supplementation (group LP, n = 26) or with an administration of PGF_2α twice, 14 d apart (group LC, n = 26). Non-lame cows served as controls (group C, n = 27) and the same treatment regimen was imposed as that for group LC. Twelve days after estrous presynchronization, an Ovsynch treatment regimen and timed AI were imposed. Ultrasonography of the ovaries and blood sampling for progesterone were used to assess cyclicity status, whereas β-hydroxybutyrate (BHBA) and non-esterified fatty acids (NEFA) were used to assess energy status. Lame cows were to a greater proportion non-cycling (36.5% vs. 11.1%; p = 0.02), had greater overall NEFA concentrations (0.32 ± 0.02 vs. 0.26 ± 0.02 mEq/L; p = 0.02) and a greater incidence of elevated NEFA concentrations (53.9% vs. 29.6%, p = 0.04) compared to control cows. However, no interaction between energy and lameness status was evident regarding non-cycling cows. The percentage of cows responding to the presynchronization, synchronization and ovulating did not differ between groups LP, LC, and C. The first-service conception rate (FSCR) tended to be greater for group C (37.0%) compared to group LP (16.0%; p = 0.08). Long-term reproductive performance did not differ between lame and control cows, although culling rates did (21.2% vs. 0%, respectivly; p = 0.01). The severity of lameness had an effect on culling rates (30.6% vs. 0% for cows with marked vs. moderate lameness; p = 0.01), whereas the type of lesion largely explained poor reproductive performance (FSCR 13.9% vs. 40.0% for cows with claw horn disruptions vs. infectious lesions; p = 0.04). Conclusively, cows that were lame during puerperium are at a greater risk of not cycling irrespective of energy status. Treatment regimens for the synchronization of ovulation seem to be efficient at resuming ovarian cyclicity. Marked lameness was detrimental to survivability, whereas cows with claw horn lesions had compromised reproductive capacity.

The Combined Use of Automated Milking System and Sensor Data to Improve Detection of Mild Lameness in Dairy Cattle

This study aimed to develop a tool to detect mildly lame cows by combining already existing data from sensors, AMSs, and routinely recorded animal and farm data. For this purpose, ten dairy farms were visited every 30–42 days from January 2020 to May 2021. Locomotion scores (LCS, from one for nonlame to five for severely lame) and body condition scores (BCS) were assessed at each visit, resulting in a total of 594 recorded animals. A questionnaire about farm management and husbandry was completed for the inclusion of potential risk factors. A lameness incidence risk (LCS ≥ 2) was calculated and varied widely between farms with a range from 27.07 to 65.52%. Moreover, the impact of lameness on the derived sensor parameters was inspected and showed no significant impact of lameness on total rumination time. Behavioral patterns for eating, low activity, and medium activity differed significantly in lame cows compared to nonlame cows. Finally, random forest models for lameness detection were fit by including different combinations of influencing variables. The results of these models were compared according to accuracy, sensitivity, and specificity. The best performing model achieved an accuracy of 0.75 with a sensitivity of 0.72 and specificity of 0.78. These approaches with routinely available data and sensor data can deliver promising results for early lameness detection in dairy cattle. While experimental automated lameness detection systems have achieved improved predictive results, the benefit of this presented approach is that it uses results from existing, routinely recorded, and therefore widely available data.

Effect of lameness on feeding behavior of zero grazed Jersey dairy cows

The dairy industry faces major challenges with high levels of lameness, in parallel to an increased consumer focus on animal welfare. This encourages farmers to consider more robust breeds, such as Jersey cows. As little is known about the behavior of this breed under loose housing conditions, the present study sought to describe the feeding behavior of lame and non-lame Jersey cows in different parities. Such breed-specific information of behavioral changes is needed for breed-specific herd management decisions and may contribute to identifying animals that are susceptible to developing lameness in the future, thus reducing impacts on the welfare and production of cows. Feeding data from 116 Danish Jersey cows were collected using automatic feeders, and lameness status was assessed by technicians every second week. The cows were kept in a loose housing system, with cubicles, a slatted concrete floor, and automatic milking robots. Eating time per visit and per day, the number of visits per day, and intervals between meals were analyzed using generalized linear mixed effects models. The effect of lameness was not significant for any variable. Primiparous Jersey cows had significantly longer eating times per day, shorter meal intervals, and a lower number of visits per day than older Jersey cows. Week in lactation affected the eating time per visit and per day, the number of visits, and between-meal intervals. In conclusion, we found no differences between lame and non-lame Jersey cows but between parities, which disagree with previous research on other breeds, suggesting that Jersey cows not just differ in size and looks but also in their behavioral reaction when lame. Although data from only one herd of a research center were used, this study has demonstrated the need for further research about breed-specific differences and their implications for the health and welfare of the animals.

Welfare of cattle during transport

In the framework of its Farm to Fork Strategy, the Commission is undertaking a comprehensive evaluation of the animal welfare legislation. The present Opinion deals with protection of cattle (including calves) during transport. Welfare of cattle during transport by road is the main focus, but other means of transport are also covered. Current practices related to transport of cattle during the different stages (preparation, loading/unloading, transit and journey breaks) are described. Overall, 11 welfare consequences were identified as being highly relevant for the welfare of cattle during transport based on severity, duration and frequency of occurrence: group stress, handling stress, heat stress, injuries, motion stress, prolonged hunger, prolonged thirst, respiratory disorders, restriction of movement, resting problems and sensory overstimulation. These welfare consequences and their animal-based measures are described. A variety of hazards, mainly relating to inexperienced/untrained handlers, inappropriate handling, structural deficiencies of vehicles and facilities, poor driving conditions, unfavourable microclimatic and environmental conditions, and poor husbandry practices leading to these welfare consequences were identified. The Opinion contains general and specific conclusions relating to the different stages of transport for cattle. Recommendations to prevent hazards and to correct or mitigate welfare consequences have been developed. Recommendations were also developed to define quantitative thresholds for microclimatic conditions within the means of transport and spatial thresholds (minimum space allowance). The development of welfare consequences over time was assessed in relation to maximum journey duration. The Opinion covers specific animal transport scenarios identified by the European Commission relating to transport of unweaned calves, cull cows, the export of cattle by livestock vessels, the export of cattle by road, roll-on-roll-off ferries and 'special health status animals', and lists welfare concerns associated with these.

Evaluation of a Binary Classification Approach to Detect Herbage Scarcity Based on Behavioral Responses of Grazing Dairy Cows

In precision grazing, pasture allocation decisions are made continuously to ensure demand-based feed allowance and efficient grassland utilization. The aim of this study was to evaluate existing prediction models that determine feed scarcity based on changes in dairy cow behavior. During a practice-oriented experiment, two groups of 10 cows each grazed separate paddocks in half-days in six six-day grazing cycles. The allocated grazing areas provided 20% less feed than the total dry matter requirement of the animals for each entire grazing cycle. All cows were equipped with noseband sensors and pedometers to record their head, jaw, and leg activity. Eight behavioral variables were used to classify herbage sufficiency or scarcity using a generalized linear model and a random forest model. Both predictions were compared to two individual-animal and day-specific reference indicators for feed scarcity: reduced milk yields and rumen fill scores that undercut normal variation. The predictive performance of the models was low. The two behavioral variables “daily rumination chews” and “bite frequency” were confirmed as suitable predictors, the latter being particularly sensitive when new feed allocation is present in the grazing set-up within 24 h. Important aspects were identified to be considered if the modeling approach is to be followed up.

Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review

Simple Summary

Cattle lameness detection as well as behaviour recognition are the two main objectives in the applications of precision livestock farming (PLF). Over the last five years, the development of smart sensors, big data, and artificial intelligence has offered more automatic tools. In this review, we discuss over 100 papers that used automated techniques to detect cattle lameness and to recognise animal behaviours. To assist researchers and policy-makers in promoting various livestock technologies for monitoring cattle welfare and productivity, we conducted a comprehensive investigation of intelligent perception for cattle lameness detection and behaviour analysis in the PLF domain. Based on the literature review, we anticipate that PLF will develop in an objective, autonomous, and real-time direction. Additionally, we suggest that further research should be dedicated to improving the data quality, modeling accuracy, and commercial availability.

Abstract

The growing world population has increased the demand for animal-sourced protein. However, animal farming productivity is faced with challenges from traditional farming practices, socioeconomic status, and climate change. In recent years, smart sensors, big data, and deep learning have been applied to animal welfare measurement and livestock farming applications, including behaviour recognition and health monitoring. In order to facilitate research in this area, this review summarises and analyses some main techniques used in smart livestock farming, focusing on those related to cattle lameness detection and behaviour recognition. In this study, more than 100 relevant papers on cattle lameness detection and behaviour recognition have been evaluated and discussed. Based on a review and a comparison of recent technologies and methods, we anticipate that intelligent perception for cattle behaviour and welfare monitoring will develop towards standardisation, a larger scale, and intelligence, combined with Internet of things (IoT) and deep learning technologies. In addition, the key challenges and opportunities of future research are also highlighted and discussed.

Farm-level factors associated with lameness prevalence, productivity, and milk quality in farms with automated milking systems

Impaired locomotion (lameness) may negatively affect the ability and desire of cows to milk voluntarily, which is a key factor in success of automated milking systems (AMS). The objective of this study was to identify factors associated with herd-level lameness prevalence and associations of lameness and other farm-level factors with milking activity, milk yield, and milk quality in herds with AMS. From April to September 2019, 75 herds with AMS in Ontario, Canada, were visited, and data on barn design and farm management practices were collected. Data from AMS were collected, along with milk recording data, for the 6-mo period before farm visits. Farms averaged 98 ± 71 lactating cows, 2.3 ± 1.5 robot units/farm, 43.6 ± 9.4 cows/robot, 36.4 ± 4.9 kg/d of milk, a milking frequency of 3.01 ± 0.33 milkings/d, and a herd average geometric mean SCC of 179.3 ± 74.6 (× 1,000) cells/mL. Thirty percent of cows/farm (minimum of 30 cows/farm) were scored for body condition (1 = underconditioned to 5 = over conditioned) and locomotion (1 = sound to 5 = lame; clinically lame ≥3 out of 5 = 28.3 ± 11.7%, and severely lame ≥4 out of 5 = 3.0 ± 3.2%). Clinical lameness (locomotion score ≥3) was less prevalent on farms with sand bedding, with increased feed bunk space per cow, and on farms with non-Holstein breeds versus Holsteins, and tended to be less prevalent with lesser proportion of underconditioned cows (with body condition score ≤2.5). Severe lameness occurrence (farms with any cows with locomotion score ≥4) was associated with a greater proportion of underconditioned cows and in farms with stalls with greater curb heights. Herd average milk yield/cow per day increased with lesser prevalence of clinical lameness (each 10-percentage-point decrease in clinical lameness prevalence was associated with 2.0 kg/cow per day greater milk yield) and greater milking visit frequency per day, and tended to be greater with increased feed push-up frequency. Lesser herd average somatic cell count was associated with lesser clinical lameness prevalence, herd average days in milk, and proportion of overconditioned cows, and somatic cell count tended to be lesser for farms with sand bedding versus those with organic bedding substrates. The results highlight the importance of minimizing lameness prevalence, using of sand bedding, ensuring adequate feed access and feed bunk space, and maintaining proper cow body condition to optimize herd-level productivity and milk quality in AMS herds.

Validation of a Commercial Collar-Based Sensor for Monitoring Eating and Ruminating Behaviour of Dairy Cows

The use of sensor technologies to monitor cows' behavior is becoming commonplace in the context of dairy production. This study aimed at validating a commercial collar-based sensor system, the AFICollar^® (Afimilk, Kibbutz Afikim, Israel), designed to monitor dairy cattle feeding and ruminating behavior. Additionally, the performances of two versions of the software for behavior classification, the current software AFIfarm^® 5.4 and the updated version AFIfarm^® 5.5, were compared. The study involved twenty Holstein-Friesian cows fitted with the collars. To evaluate the sensor performance under different feeding scenarios, the animals were divided into four groups and fed three different types of feed (total mixed ration, long hay, animals allowed to graze). Recordings of hourly rumination and feeding time produced by the sensor were compared with visual observation by scan sampling at 1 minute intervals using Spearman correlation, concordance correlation coefficient (CCC), Bland-Altman plots and linear mixed models for assessing the precision and accuracy of the system. The analyses confirmed that the updated software version V5.5 produced better detection performance than the current V5.4. The updated software version produced high correlations between visual observations and data recorded by the sensor for both feeding (r = 0.85, CCC = 0.86) and rumination (r = 0.83, CCC = 0.86). However, the limits of agreement for both behaviors remained quite wide (feeding: -19.60 min/h, 17.46 min/h; rumination: -15.80 min/h, 15.00 min/h). Type of feed did not produce significant effects on the agreement between visual observations and sensor recordings. Overall, the results indicate that the system can provide farmers with adequately accurate data on feeding and rumination time, and can be used to support herd management decisions. Despite all this, the precision of the system remained relatively limited, and should be improved with further developments in the classification algorithm.

Identification of discriminating behavioural and movement variables in lameness scores of dairy cows at pasture from accelerometer and GPS sensors using a Partial Least Squares Discriminant Analysis

The behaviour and movement of lame dairy cows at pasture have been studied little, yet they could be relevant to improve the automatic detection of lameness in cows in pasture-based systems. Our aim in this study is to identify behavioural and movement variables of dairy cows at pasture that could discriminate lameness scores. Individual cow behaviours were predicted from accelerometer data and movements measured using GPS data. Sixty-eight dairy cows from three pasture-based commercial farms were equipped with a 3-D accelerometer and a GPS sensor fixed on a neck collar for 1-5 weeks, depending on the farm, in spring and summer 2018. A lameness score was assigned to each cow by a trained observer twice a week. Behaviours were predicted every 10 s based on accelerometer data, and then combined with the GPS position. Segmentation on behavioural time series was used to delineate each behavioural bout within each outdoor period. Thirty-seven behavioural and movement variables were then calculated from the behavioural bouts for each cow. A partial least square discriminant analysis was performed to identify the variables that best discriminate lameness scores. Time spent grazing, grazing bout duration, duration before lying down in the pasture, time spent resting, number of resting bouts, distance travelled during grazing, and dispersion were the most discriminant variables in the PLS-DA (VIP > 1). Severely lame cows spent 4.5 times less time grazing and almost twice as much time resting as their sound congeners, especially in the lying position. Exploratory behaviour was also reduced for both moderately and severely lame cows, resulting in 1.2 and 1.7 times less distance travelled respectively, especially during grazing. These variables could be used as additional variables to improve the performance of existing lameness detection devices in pasture-based systems.

Association of body condition with lameness in dairy cattle: a single-farm longitudinal study

This research communication describes the relationship between the occurrence of lameness and body condition score (BCS) in a sample of 288 cows from a single farm that were repeatedly scored in the course of 9 months while controlling for confounding variables. The relationship between BCS and lameness was evaluated using generalised linear mixed-effects models. It was found that the proportion of lame cows was higher with decreasing but also with increasing BCS, increased with lactation number and decreased with time since the last claw trimming. This is likely to reflect the importance of sufficient body condition in the prevention of lameness but also raises the question of the impact of overcondition on lameness and the influence of claw trimming events on the assessment of lameness. A stronger focus on BCS might allow improved management of lameness that is still one of the major problems in housed cows.

A Retrospective Case Study into the Effect of Hoof Lesions on the Lying Behaviour of Holstein-Friesian in a Loose-Housed System

Simple Summary

Lameness is a substantial welfare and economic problem in production animals. It can alter indicators of welfare such as lying time. Lying down is very important for cows, and they are highly motivated to perform this behaviour for 12 h or more per day. Conversely, cows that lie down too much or are uncomfortable standing may miss an opportunity to feed or drink if there is competition from sound (non-lame) cows. This study monitored different lesions that cause lameness in cattle through the use of accelerometers. The lesions included sole ulcers, sole haemorrhage, white line disease, interdigital hyperplasia and phelgmon, and digital dermatitis. Leg-based activity monitors that track the cows’ lying behaviour and mobility were used. From these data, it was found that cows with lesions on the foot spent longer lying down than those with no lesions, and cows with lesions in the soft tissue spent less time lying down than those with foot lesions. Trimming the cows’ feet altered the lying times of the cows with foot lesions and returned them closer to those of cows with no lesions.

Abstract

The association between hoof lesions and lying behaviour was assessed on a Holstein–Friesian dairy farm in England. Twenty-nine cows were included in the study. Cows with claw horn disruption lesions (CHDL, n = 8), soft tissue lesions (STL, n = 6), and no lesions (NL, n = 15) were assessed. Data were collected on parity, days in milk (DIM), and mobility scores. Cows were trimmed and treated, and lesions were recorded by a professional foot trimmer. Lying behaviour was assessed before and after claw trimming. The milking herd (n = 96) prevalence of lameness was 32.3%. Mobility was scored using the Agriculture and Horticulture Development Board (AHDB) Mobility Scoring system. Mobility scores were significantly different across lesions groups (p = 0.022). CHDL cows had a mean mobility score of 2.0 ± 0.9 (mean ± SD), STL were scored 1.2 ± 1.3, and NL cows were 0.9 ± 0.7. CHDL were associated with longer lying times (15.00 ± 1.04 h/d; p = 0.0006) and shorter standing times (9.68 ± 2.38 h/d; p = 0.0351) compared with NL lying times (11.77 ± 1.67 h/d) and standing times (12.21 ± 1.67 h/d). STL cows spent significantly less time lying (11.30 ± 2.44; p = 0.0013) than CHDL but not NL cows. No significant differences were found with any of the other lying behaviours. After trimming, CHDL cows spent significantly less time lying down than before trimming (13.66 ± 0.98; p = 0.0125). Cows with NL spent significantly more time lying down (12.57 ± 1.90; p = 0.0398) and had a shorter minimum lying bout duration (0.17 ± 0.09; p = 0.0236) after trimming. In conclusion, lying behaviour in dairy cattle was impacted by type of hoof lesions and hoof trimming.

Slightly and Moderately Lame Cows in Tie Stalls Behave Differently From Non-lame Controls. A Matched Case-Control Study

Lameness affects dairy cows worldwide and is usually associated with pain. Behavioral differences in lame compared to non-lame tie-stall-housed dairy cows might be less pronounced than in free-stall-housed, since the principle demands to a cow's locomotor system and thus the impact of lameness on behavior seem to be lower in tie stalls. Behavioral differences between lame and non-lame cows might be used to estimate the impact of lameness on the well-being of tied dairy cows. In the current study, lame cows were categorized as locomotion scoring between 2.25 and 3.25 on a 1–5 scale. The aim was to compare the eating, rumination and lying behavior of lame cows against non-lame tied dairy cows, in order to draw conclusions on the association of lameness, behavior and well-being in tied dairy cows. The eating and rumination behavior of 26, the lying behavior of 30, and the relative upright and lying activities of 25 matched case-control pairs were analyzed, considering the matching criteria farm, breed-type, and parity-group. Lame cows had fewer [mean of the pairwise differences (case–control) (mean_diff) = −2.6 bouts, CI_95% (−3.8–−1.4) bouts, p = 0.001], but longer lying bouts [mean_diff = 26.7 min per bout, CI_95% (10.1–43.4) min per bout, p = 0.006]. The lying time was shorter [mean_diff = −64.7 min, CI_95% (−104.4–−24.9) min, p = 0.006] in lame cows compared to their non-lame controls. Lame cows had a shorter eating time [mean_diff = −27.7 min, CI_95% (−51.5–−4.0) min, p = 0.042] and spent a larger proportion of their upright time ruminating [mean_diff = 7.2%, CI_95% (3.2–11.1)%, p = 0.001] instead of eating. The results of the current study indicate that the eating, rumination, and lying behavior of lame tied dairy cows is altered. These findings indicate that slight and moderate lameness (locomotion score between 2.25 and 3.25 on a 1–5 scale) are likely to be associated with an impaired well-being in affected tied dairy cows. This underlines the need to continuously reduce the lameness prevalence and severity in tied dairy herds.

Evaluating the association between early-lactation lying behavior and hoof lesion development in lactating Jersey cows

Objectives were to evaluate the association between behavior and hoof lesions (HL) in lactating dairy cows. Jersey cows without any visible HL on all 4 legs were enrolled at 20 ± 3 d in milk (DIM), examined for body condition score (BCS), and had an automatic activity monitor (AfiTag II, AfiMilk, Afikim, Israel) attached to their right hind leg. At 120 ± 3 DIM, activity monitors were removed and cows were re-examined for HL and BCS. Cows were classified according to HL status as either healthy or with HL at d 120. Because sole hemorrhage (SH) accounted for over 80% of HL on d 120, SH was reclassified according to the number of feet affected. Daily activity data (daily lying duration, lying bouts, lying bout duration, and number of steps) of 344 cows collected between d 20 and d 120 were analyzed using restricted maximum likelihood linear mixed models with an autoregressive covariance structure. Separate models were built to include specific activities, HL status at d 120, DIM, interaction between lesion status at d 120 and DIM, parity, season of calving, and BCS change from d 20 to d 120 as fixed effects. Cow was included in all models as random effect. Incidence of HL at d 120 was 58.4% (n = 201 out of 344). Compared with healthy cows, cows with HL at d 120 had reduced daily lying duration (-0.53 h; 95% CI: -0.78 to -0.28 h) in the early postpartum period. We found no evidence for a difference in number of lying bouts (0.41; 95% CI: -0.76 to 1.59;), lying bout duration (-3.04 min; 95% CI: -6.6 to 0.49), and number of steps (62.14; 95% CI: -89.62 to 213.91) between cows that remained healthy and those that developed HL. Compared with healthy cows, cows that developed SH in 1 or more feet had reduced daily lying duration in the early postpartum period. Irrespective of lesion status at d 120, daily lying duration and lying bout duration increased from d 20 to d 120, whereas lying bout number and number of steps decreased from d 20 to d 120. We concluded that cows that developed HL had a reduced daily lying duration in the early postpartum period. Therefore, reduced daily lying duration should be considered a risk factor for HL development in lactating dairy cows.

Association between hoof lesions and fertility in lactating Jersey cows

The objectives of this study were to evaluate the association between hoof lesions and fertility in dairy cows. Lactating Jersey cows (n = 1,639) were enrolled at 20 ± 3 d in milk (D20), examined and treated for presence of hoof lesions (HL), and evaluated for body condition score (BCS). Afterward, they were managed according to standard farm procedures, including estrus detection and presynchronization and a 5 d Cosynch-72 protocol for cows that failed to show estrus. Ovaries were scanned at 27 and 41 ± 3 d in milk, and cows with a corpus luteum greater than 20 mm on at least 1 exam were considered cyclic. At 120 ± 3 d in milk (D120), cows were re-examined for HL and BCS. Cows were classified at D20 according to HL status as healthy (n = 1,197) or having HL (n = 429), and according to HL category as healthy (n = 1,197) or having a sole hemorrhage (n = 280), noninfectious HL (sole ulcer, toe ulcer, or white line disease; n = 113), or infectious HL (digital dermatitis and foot rot; n = 36). Cows with HL at D20 had reduced odds of being cyclic (38.3 vs. 51.9%) and a longer interval from calving to first service (58 vs. 51 d) compared with healthy cows. Cows with infectious HL at D20 had reduced odds of pregnancy to first service (16.7 vs. 38.3%) compared with healthy cows. Cows with sole hemorrhage at D20 were more likely to lose pregnancies between d 32 and 64 after the first service postpartum compared with healthy cows (10.5 vs. 5.2%). Cows with sole hemorrhage at D20 had a smaller hazard of pregnancy (67.9 vs. 75.5%) at 150 d in milk and more days open (88 vs. 77d) compared with healthy cows. To assess the relationship between the development of HL and fertility, cows were classified as healthy (no HL at D20 and D120; n = 308), cured (any HL at D20 and no HL at D120; n = 72), new HL (no HL at D20 and any HL at D120; n = 597), and chronic (any HL at D20 and D120; n = 226). Sole hemorrhage accounted for 93% of new HL. The proportions of cows with HL at D20 and D120 were 26.9 and 68.4%, respectively. We found no evidence for a difference in pregnancy hazard at 150 d in milk between cows that remained healthy (n = 308) and cows that developed new HL (n = 597). Hoof lesions at D20, but not new HL, were associated with decreased odds of cyclicity, longer interval from calving to first service postpartum, and reduced pregnancy hazard in Jersey cows. The effect of an HL diagnosis in early lactation and management to reduce chronic HL in dairy cows warrants further investigation.

Symposium review: The impact of management and facilities on cow culling rates

This symposium review examines the association between comfort and cow longevity, with a particular emphasis on optimizing resting behavior in confinement-housed systems. Housed dairy cattle demonstrate a variety of negative behavioral and physiological effects when lying time is restricted, with cows prioritizing the recovery of rest over feeding when both are deprived. There is, however, wide individual-cow variation in daily lying times, influenced by an array of cow-, housing-, and management-related factors. Cow-related factors include individual preference, parity, stage of lactation cycle, milk yield, ill health, and lameness. Lying time tends to increase with age and days in milk and during periods of ill health, whereas milk yield is negatively correlated with lying time. The effect of lameness is complicated by severity and by interactions with bedding type, which modifies the cows' ability to rise and lie down. Generally, lame cows suffer prolonged lying bouts of greater variability in length and take fewer bouts per day. Often this results in an overall increase in lying time. Thus, higher standards of cow comfort and improved cow health are not always reflected by longer lying times. Housing and management factors that influence resting behavior include the design of the resting area, access to the resting space, and the thermal microenvironment of the lying area. Provision of dry, deep loose bedding, stocking cows to allow each animal access to a resting space, allowing sufficient time to access the resting area, and providing heat abatement to reduce heat load optimize resting behavior. Because lameness and poor body condition are commonly found in culled dairy cattle, the link between cow comfort and culling is likely mediated through lameness onset and management. Optimal comfort helps prevent the onset of lameness and facilitates recovery once cows become lame, which limits the effect of lameness on feeding behavior and reduces the risk for other health-related disorders, poor reproductive performance, and early herd removal. Cow comfort cannot be assessed by measuring the duration of lying time alone. Rather, comfort is reflected by the optimization of resting behavior, providing facilities and management to allow cows to lie down when they choose to do so for as long as they need to.

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.

Influence of Lameness on the Lying Behaviour of Zero-Grazed Lactating Jersey Dairy Cattle Housed in Straw Yards

Thirty-five lactating Jersey cows were recruited to the study. They were grouped according to locomotion score (LS), where low scores indicate normal gait. LS-1 (n = 12), LS-2 (n = 12) and LS-3 (n = 11) were used. Locomotion scores were balanced for parity and stage of lactation. Lying behaviour was recorded using IceTag™ data loggers attached to the cows for four consecutive days. The study animals remained in the straw based yards with grooved concrete flooring throughout the duration of the study. All data were normally distributed and assessed using a one-way ANOVA with a post hoc Tukey test. There were no statistically significant differences between locomotion score and the time spent lying, active and standing of zero-grazed lactating Jersey dairy cattle housed on straw yards. Lame cows (LS-3) had significantly shorter lying bouts than sound cows (LS-1) (34 min vs. 42 min, respectively). There has been limited research to date measuring the lying behaviour of cattle on straw and into the Jersey breed. The cows had longer than expected standing times and an increased frequency of lying bouts. This may have been attributed to the stocking density in which the cows were kept. We also reported a prevalence of lameness within the herd of 38%.

Short communication: Effects of mammary biopsy in the dry period on activity and feeding behavior of dairy cows

In dairy cattle, mammary biopsies are commonly used to study development and function of the mammary gland. The objective of this study was to investigate changes in activity and feeding patterns following the mammary biopsy procedure. Pregnant, nonlactating Holstein dairy cows (20 d before expected calving date) were exposed to either (1) a biopsy procedure, in which a mammary tissue sample (60 × 4 mm in diameter) was obtained from cows (n = 9) using a biopsy tool from the rear left quarter, following administration of a sedative (xylazine, 20 µg/kg of body weight) and local anesthetic (3 mL of lidocaine), or (2) a sham procedure, in which cows (n = 8) were removed from the pen and restrained for a similar duration of time as for the biopsy procedure. Behavior of cows was monitored for 5 d, beginning on the day following biopsy (approximately 14 h after the procedure). Cows were fitted with accelerometers to record daily lying time, lying bout frequency, and lying side. Daily individual feed intake was recorded using the Calan Broadbent feeding system, and feeding time and meal characteristics were determined from a subset of cows (n = 6 per treatment) using a change-of-state data logger to record the times the cows were accessing the feed bunk. Total daily lying time did not differ between treatments [13.9 h/d; standard error (SE) = 0.56], but biopsied cows had more frequent, shorter lying bouts on the biopsied side on d 1 following the procedure (6.67 vs. 4.25 bouts/d, SE = 1.03, and 70.0 vs. 97.0 min/bout, SE = 8.6; left vs. right side), whereas control cows had no side preference. We found no effects of treatment on feed intake and feeding time but, on the first day after treatment, biopsied cows had meals that were more frequent (7.2 vs. 4.6 meals/d; SE = 0.93) and tended to be shorter (28.2 vs. 60.9 min/meal; SE = 11.8) than control cows. In conclusion, we did not detect effects of mammary biopsy on feed intake or lying time during our time frame of observation, but activity patterns were altered, which could be indicative of increased overall restlessness and specific pain in the biopsied quarter.

Better recovery from lameness among dairy cows housed in hospital pens

Housing in hospital pens may be beneficial for lame cows due to soft flooring and less competition for resources. We compared recovery from lameness among dairy cows housed in designated hospital pens, with deep-litter straw, with recovery among cows housed together with the rest of the lactating cows in their home pens, with cubicles and slatted or solid concrete floors. Additionally, we compared lying behavior in the 2 groups of cows. A total of 168 lame dairy cows from 5 herds were included in the study. Each herd was visited once weekly, and lame cows (locomotion score 3 or 4 on a 5-point scale) were examined in a hoof-trimming chute, trimmed, and randomly assigned to 1 of 2 treatments: housing in a hospital pen (termed "treatment"; 72 cows) or housing under the herds' standard conditions together with the rest of the lactating cows in the herd (termed "control"; 96 cows). Cows were locomotion scored weekly until they were no longer lame or until they had been part of the trial for 3 weeks (i.e., 2, 3, or 4 locomotion scorings per cow). We categorized cows to describe the progression of lameness over time: recovery (divided into fast, medium, or slow), improvement without recovery, constant lameness, or worsening of lameness. Lying behavior was recorded in a sample of 60 of the 168 cows for a period of 5 d. Overall, recovery from lameness was significantly different between treatment and control cows. The proportion of cows included in the study with locomotion score 4 and a subsequent improvement was significantly higher among treatment cows than among control cows. Among cows included with locomotion score 4, 40% of treatment cows also had a locomotion score 4 at the fourth locomotion scoring, 46% had improved to a score 3, and 14% were no longer lame. In comparison, 73% of control cows had a locomotion score 4 at the fourth locomotion scoring, 16% had improved to a score 3, and 11% were no longer lame. We found no differences between treatment and control cows for mean daily lying time, number of steps per day, number of daily lying bouts, or mean duration of lying bouts. Housing of lame dairy cows in a hospital pen with a soft surface, easier access to feed and water, a smaller group size, and reduced waiting time for milking may have positive effects on recovery from lameness. Typically, farmers have housed only severely lame cows in hospital pens. However, our results indicate that less severely lame cows may also benefit from a stay in a hospital pen.

Associating cow characteristics with mobility scores in pasture-based dairy cows

The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.

Automatic lameness detection in cattle

There is an increasing demand for health and welfare monitoring in modern dairy farming. The development of various innovative techniques aims at improving animal behaviour monitoring and thus animal welfare indicators on-farm. Automated lameness detection systems have to be valid, reliable and practicable to be applied in veterinary practice or under farm conditions. The objective of this literature review was to describe the current automated systems for detection of lameness in cattle, which have been recently developed and investigated for application in dairy research and practice. The automatic methods of lameness detection broadly fall into three categories: kinematic, kinetic and indirect methods. The performance of the methods were compared with the reference standard (locomotion score and/or lesion score) and evaluated based on level-based scheme defining the degree of development (level I, sensor technique; level II, validation of algorithm; level III, performance for detection of lameness and/or lesion; level IV, decision support with early warning system). Many scientific studies have been performed on levels I-III, but there are no studies of level IV technology. The adoption rate of automated lameness detection systems by herd managers mainly yields returns on investment by the early identification of lame cows. Long-term studies, using validated automated lameness detection systems aiming at early lameness detection, are still needed in order to improve welfare and production under field conditions.

Space-use patterns highlight behavioural differences linked to lameness, parity, and days in milk in barn-housed dairy cows

Lameness is a key health and welfare issue affecting commercial herds of dairy cattle, with potentially significant economic impacts due to the expense of treatment and lost milk production. Existing lameness detection methods can be time-intensive, and under-detection remains a significant problem leading to delayed or missed treatment. Hence, there is a need for automated monitoring systems that can quickly and accurately detect lameness in individual cows within commercial dairy herds. Recent advances in sensor tracking technology have made it possible to observe the movement, behaviour and space-use of a range of animal species over extended time-scales. However, little is known about how observed movement behaviour and space-use patterns in individual dairy cattle relate to lameness, or to other possible confounding factors such as parity or number of days in milk. In this cross-sectional study, ten lame and ten non-lame barn-housed dairy cows were classified through mobility scoring and subsequently tracked using a wireless local positioning system. Nearly 900,000 spatial locations were recorded in total, allowing a range of movement and space-use measures to be determined for each individual cow. Using linear models, we highlight where lameness, parity, and the number of days in milk have a significant effect on the observed space-use patterns. Non-lame cows spent more time, and had higher site fidelity (on a day-to-day basis they were more likely to revisit areas they had visited previously), in the feeding area. Non-lame cows also had a larger full range size within the barn. In contrast, lame cows spent more time, and had a higher site-fidelity, in the cubicle (resting) areas of the barn than non-lame cows. Higher parity cows were found to spend more time in the right-hand-side area of the barn, closer to the passageway to the milking parlour. The number of days in milk was found to positively affect the core range size, but with a negative interaction effect with lameness. Using a simple predictive model, we demonstrate how it is possible to accurately determine the lameness status of all individual cows within the study using only two observed space-use measures, the proportion of time spent in the feeding area and the full range size. Our findings suggest that differences in individual movement and space-use behaviour could be used as indicators of health status for automated monitoring within a Precision Livestock Farming approach, potentially leading to faster diagnosis and treatment, and improved animal welfare for dairy cattle and other managed animal species.

Chicken or the Egg: The Reciprocal Association Between Feeding Behavior and Animal Welfare and Their Impact on Productivity in Dairy Cows

Feeding behavior in dairy cattle has a significant impact on feed efficiency, which is important for increasing the profitability of livestock and, at the same time, reducing the environmental impact. Feeding behavior can be measured by feeding time, meal duration, meal frequency, feeding rate, and rumination time. Higher feed intake is related to lower feed efficiency; whereas, an increase in feeding time facilitates chewing, reduces feed particle size and increases its digestibility. More frequent and shorter meals are usually associated with a more efficient use of feed due to improvement of feed digestibility. Rumination time is positively associated with milk production. Impaired health is associated with variations in feeding behavior, which can be used to identify and predict some diseases such as ketosis, mastitis, or lameness. Changes in rumination time are also a reliable indicator of mastitis, lameness, ketosis, abomasal displacement, and the onset of calving. In addition to the cause-effect relationship between disease and changes in feeding behavior, there are also some cases in which changes in feeding behavior may lead to an increased risk of disease, as exemplified by the relationship of feeding rate with sub-acute ruminal acidosis. Feeding behavior is regulated by internal and external factors and some of them are relevant for animal welfare. The main welfare-associated factors influencing feeding behavior are social behavior and temperament, and environmental effects. Cattle are social animals and hierarchy has a notable impact on feeding behavior, especially when access to feed is limited. Competition for feed causes a reduction in the average feeding time but increases feeding rate. Excitable animals visit the feeder more often and spend less time per meal. High environmental temperature affects feeding behavior, as heat-stressed cattle change their feeding pattern by concentrating the feeding events in crepuscular hours, leading to an increased risk of sub-acute ruminal acidosis. In conclusion, feeding behavior is a determinant feature for improving efficiency, productivity and welfare of dairy cattle. Routine assessment of feeding behavior allows monitoring of health and production status of dairy cattle at the individual and farm level, which is a useful tool to optimize the management of livestock.

A 100-Year Review: Metabolic modifiers in dairy cattle nutrition

The first issue of the Journal of Dairy Science in 1917 opened with the text of the speech by Raymond A. Pearson, president of the Iowa State College of Agriculture, at the dedication of the new dairy building at the University of Nebraska (J. Dairy Sci. 1:4-18, 1917). Fittingly, this was the birth of a new research facility and more importantly, the beginning of a new journal devoted to the sciences of milk production and manufacture of products from milk. Metabolic modifiers of dairy cow metabolism enhance, change, or interfere with normal metabolic processes in the ruminant digestive tract or alter postabsorption partitioning of nutrients among body tissues. Papers on metabolic modifiers became more frequent in the journal around 1950. Dairy farming changed radically between 1955 and 1965. Changes in housing and feeding moved more cows outside, and cows and heifers in all stages of lactation, including the dry period, were fed as a single group. Rations became wetter with the shift to corn silage as the major forage in many rations. Liberal grain feeding met the requirements of high-producing cows and increased production per cow but introduced new challenges; for example, managing and feeding cows as a group. These changes led to the introduction of new strategies that identified and expanded the use of metabolic modifiers. Research was directed at characterizing the new problems for the dairy cow created by group feeding. Metabolic modifiers went beyond feeding the cow and included environmental and housing factors and additives to reduce the incidence and severity of many new conditions and pathologies. New collaborations began among dairy cattle specialties that broadened our understanding of the workings of the cow. The Journal of Dairy Science then and now plays an enormously important role in dissemination of the findings of dairy scientists worldwide that address existing and new technologies.

Short communication: Early modification of the circadian organization of cow activity in relation to disease or estrus

Biological rhythms are an essential regulator of life. There is evidence that circadian rhythm of activity is disrupted under chronic stress in animals and humans, and it may also be less marked during diseases. Here we investigated whether a detectable circadian rhythm of activity exists in dairy cows in commercial settings using a real-time positioning system. We used CowView (GEA Farm Technologies) to regularly record the individual positions of 350 cows in a Danish dairy farm over 5 mo and to infer the cows' activity (resting, feeding, in alley). We ran a factorial correspondence analysis on the cows' activities and used the first component of this analysis to express the variations in activity. On this axis, the activities obtained the following weights: resting = -0.15; in alleys = +0.12; feeding = +0.34. By applying these weights to the proportions of time each cow spent on each of the 3 activities, we were able to chart a circadian rhythm of activity. We found that average level of activity of a cow on a given day and its variations during that day varied with specific states (i.e., estrus, lameness, mastitis). More specifically, circadian variations in activity appeared to be particularly sensitive and to vary 1 to 2 d before the farmer detected a disorder. These findings offer promising avenues for further research to design models to predict physiological or pathological states of cows from real-time positioning data.

Daily lying time, motion index and step frequency in dairy cows change throughout lactation

Lying behaviour in dairy cows has the potential to be used for welfare assessment or problem detection, but knowledge about variation in normal lying behaviour is scarce. Accelerometer data were collected at four Danish farms from 366 Holstein dairy cows in loose-housing systems in 2008 and 2009. Daily lying time decreased steeply during early lactation to a minimum around four weeks after calving, followed by a steady increase towards the end of lactation. Motion index and step frequency during walking exhibited a similar pattern. An adapted version of Wilmink's function for lactation curves was used to model these behaviours in relation to days in milk. The results demonstrate the importance of including information about days in milk when interpreting data on lying behaviour and activity.

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow’s gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.

Lameness Affects Cow Feeding But Not Rumination Behavior as Characterized from Sensor Data

Using automatic sensor data, this is the first study to characterize individual cow feeding and rumination behavior simultaneously as affected by lameness. A group of mixed-parity, lactating Holstein cows were loose-housed with free access to 24 cubicles and 12 automatic feed stations. Cows were milked three times/day. Fresh feed was delivered once daily. During 24 days with effectively 22 days of data, 13,908 feed station visits and 7,697 rumination events obtained from neck-mounted accelerometers on 16 cows were analyzed. During the same period, cows were locomotion scored on four occasions and categorized as lame (n = 9) or not lame (n = 7) throughout the study. Rumination time, number of rumination events, feeding time, feeding frequency, feeding rate, feed intake, and milk yield were calculated per day, and coefficients of variation were used to estimate variation between and within cows. Based on daily sums, using each characteristic as response, the effects of lameness and stage of lactation were tested in a mixed model. With rumination time as response, each of the four feeding characteristics, milk yield, and lameness were tested in a second mixed model. On a visit basis, effects of feeding duration, lameness, and milk yield on feed intake were tested in a third mixed model. Overall, intra-individual variation was <15% and inter-individual variation was up to 50%. Lameness introduced more inter-individual variation in feeding characteristics (26–50%) compared to non-lame cows (17–29%). Lameness decreased daily feeding time and daily feeding frequency, but increased daily feeding rate. Interestingly, lameness did not affect daily rumination behaviors, fresh matter intake, or milk yield. On a visit basis, a high feeding rate was associated with a higher feed intake, a relationship that was exacerbated in the lame cows. In conclusion, cows can be characterized in particular by their feeding behavior, and lame cows differ from their non-lame pen-mates in terms of fewer feed station visits, faster eating, less time spent feeding, and more variable feeding behavior. Further, daily rumination time was slightly negatively associated with feeding rate, a relationship which calls for more research to quantify rumination efficiency relative to feeding rate.

The effect of lameness on the environmental performance of milk production by rotational grazing

Dairy production leads to significant environmental impacts and increased production will only be feasible if the environmental performance at farm level permits a sustainable milk supply. Lameness is believed to become more prevalent and severe as herd sizes increase, and can significantly reduce milk output per cow while not influencing other attributes of the production system. The objective of this work was to quantify the effect of lameness on the environmental performance of a typical grazed grass dairy farm and evaluate the theoretical value of sensor-based real-time lameness management. Life cycle assessment was used to compare a typical baseline farm with scenarios assuming increased lameness severity and prevalence. It was found that lameness could increase the farm level global warming potential, acidification potential, eutrophication potential and fossil fuel depletion by 7-9%. As increased herd sizes will increase cow: handler ratio, this result was interpreted to suggest that the use of sensors and information and communication technology for lameness detection could improve management on dairy farms to reduce the adverse impact on environmental performance that is associated with lameness.

Evaluation of two methodologies for lameness detection in dairy cows based on postural and gait abnormalities observed during milking and while restrained at headlock stanchions

Lameness is a critical issue on dairies with an impact on production and animal welfare. Early lameness detection followed by effective treatments could improve prognosis and cure rate of lame cows. Current methods for lameness detection are based on locomotion score (LS) that requires observation of cows walking, preferably at the exit of the milking parlor. This is a time-consuming task that is difficult to implement on large dairies. Therefore, a common methodology for lameness detection is based on milkers' and cow pushers' observations of cows walking to the milking parlor or standing at the milking stall (MPP). Observation of postural abnormalities predictive of lameness while cows are locked at stanchions (S) can be used as an alternative detection method. The objective of this research was to study the association between postural and gait abnormalities observed with S and MPP methodologies and lameness using LS≥3 as the reference method, as well as to evaluate the epidemiological characteristics of those methods as a diagnostic test for lameness. A secondary objective was to describe the type of hoof lesions observed with postural and gait abnormalities detected with LS, MPP, and S methodologies. A cross-sectional study design was performed on 2274 cows from one farm in California (US). Arched back, cow-hocked, wide-stance, and favored-limb postures as well as uneven gait were observed. Both lameness detection methodologies, S and MPP, indicated that arched back and favored-limb were postural abnormalities associated with lameness. However, the epidemiological test characteristics for each of the postures evaluated as a diagnostic test for lameness indicated that both detection methods, S and MPP, had good specificity (>0.91) but poor sensitivity (0.04-0.39). A convenience sample of 104 cows, selected based on LS>3, favored-limb, presence of two or more abnormal postures, and gait anomalies with either S or MPP methods, received a hoof examination. Lesions were observed on cows selected by LS (17/24), MPP (21/30), and S (33/60) criteria, suggesting a lack of concordance between lameness detection methodologies and visible hoof lesions. Nevertheless, due to the lack of acceptance of LS as the lameness detection method on large commercial dairies in California, it is imperative that future research evaluates modifications of S and MPP lameness detection techniques, considering hoof lesion as reference method.