Plasticity and consistency of lying and ruminating behaviours of heifers exposed to different cubicle availability: A glance at individuality

Welfare of dairy cows

This Scientific Opinion addresses a European Commission's mandate on the welfare of dairy cows as part of the Farm to Fork strategy. It includes three assessments carried out based on literature reviews and complemented by expert opinion. Assessment 1 describes the most prevalent housing systems for dairy cows in Europe: tie-stalls, cubicle housing, open-bedded systems and systems with access to an outdoor area. Per each system, the scientific opinion describes the distribution in the EU and assesses the main strengths, weaknesses and hazards potentially reducing the welfare of dairy cows. Assessment 2 addresses five welfare consequences as requested in the mandate: locomotory disorders (including lameness), mastitis, restriction of movement and resting problems, inability to perform comfort behaviour and metabolic disorders. Per each welfare consequence, a set of animal-based measures is suggested, a detailed analysis of the prevalence in different housing systems is provided, and subsequently, a comparison of the housing systems is given. Common and specific system-related hazards as well as management-related hazards and respective preventive measures are investigated. Assessment 3 includes an analysis of farm characteristics (e.g. milk yield, herd size) that could be used to classify the level of on-farm welfare. From the available scientific literature, it was not possible to derive relevant associations between available farm data and cow welfare. Therefore, an approach based on expert knowledge elicitation (EKE) was developed. The EKE resulted in the identification of five farm characteristics (more than one cow per cubicle at maximum stocking density, limited space for cows, inappropriate cubicle size, high on-farm mortality and farms with less than 2 months access to pasture). If one or more of these farm characteristics are present, it is recommended to conduct an assessment of cow welfare on the farm in question using animal-based measures for specified welfare consequences.

Behavioral Fingerprinting: Acceleration Sensors for Identifying Changes in Livestock Health

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

The Value of ‘Cow Signs’ in the Assessment of the Quality of Nutrition on Dairy Farms

The aim of this review is to provide dairy farm advisors, consultants, nutritionists, practitioners, and their dairy farmer clients with an additional toolkit that can be used in the assessment of the quality of their dairy cattle nutrition. Cow signs are behavioral, physiological, and management parameters that can be observed and measured. They are detected by examining and observing the cattle. Other physiological parameters such as fecal scoring, rumen fill, and body condition scoring are also included in ‘cow signs’. The assessment should be both qualitative and quantitative; for example, is the cattle individual lame and what is the severity of lameness. The ‘diagnosis’ of a problem should be based on establishing a farm profile of ‘cow signs’ and other relevant information. Information gathered through assessment of cow signs should be used as an advisory tool to assist and improve decision making. Cow signs can be used as part of an investigation and or farm audit.

Invited review: Lying time and the welfare of dairy cows

Adequate time lying down is often considered an important aspect of dairy cow welfare. We examine what is known about cows' motivation to lie down and the consequences for health and other indicators of biological function when this behavior is thwarted. We review the environmental and animal-based factors that affect lying time in the context of animal welfare. Our objective is to review the research into the time that dairy cows spend lying down and to critically examine the evidence for the link with animal welfare. Cows can be highly motivated to lie down. They show rebound lying behavior after periods of forced standing and will sacrifice other activities, such as feeding, to lie down for an adequate amount of time. They will work, by pushing levers or weighted gates, to lie down and show possible indicators of frustration when lying behavior is thwarted. Some evidence suggests that risk of lameness is increased in environments that provide unfavorable conditions for cows to lie down and where cows are forced to stand. Lameness itself can result in longer lying times, whereas mastitis reduces it. Cow-based factors such as reproductive status, age, and milk production influence lying time, but the welfare implications of these differences are unknown. Lower lying times are reported in pasture-based systems, dry lots, and bedded packs (9 h/d) compared with tiestalls and freestalls (10 to 12 h/d) in cross-farm research. Unfavorable conditions, including too few lying stalls for the number of cows, hard or wet lying surfaces, inadequate bedding, stalls that are too small or poorly designed, heat, and rain all reduce lying time. Time constraints, such as feeding or milking, can influence lying time. However, more information is needed about the implications of mediating factors such as the effect of the standing surface (concrete, pasture, or other surfaces) and cow behavior while standing (e.g., being restrained, walking, grazing) to understand the effect of low lying times on animal welfare. Many factors contribute to the difficulty of finding a valid threshold for daily lying time to use in the assessment of animal welfare. Although higher lying times often correspond with cow comfort, and lower lying times are seen in unfavorable conditions, exceptions occur, namely when cows lie down for longer because of disease or when they spend more time standing because of estrus or parturition, or to engage in other behaviors. In conclusion, lying behavior is important to dairy cattle, but caution and a full understanding of the context and the character of the animals in question is needed before drawing firm conclusions about animal welfare from measures of lying time.

Developing and evaluating threshold-based algorithms to detect drinking behavior in dairy cows using reticulorumen temperature

In this study, we assessed for the first time the use of a reticuloruminal temperature bolus and a thresholding method to detect drinking events and investigated different factors that can affect drinking behavior. First, we validated the detection of drinking events using 16 cows that received a reticuloruminal bolus. For this, we collected continuous drinking behavior data for 4 d using video recordings and ambient and water temperature for the same 4 d. After all the data were synchronized, we performed 2 threshold algorithms: a general-fixed threshold and a cow-day specific threshold algorithm. In the general-fixed threshold, a positive test was considered if the temperature of any cow fell below a fixed threshold; in the cow-day specific threshold, a positive test was considered when the temperature of specific cows fell below the threshold value deviations around the mean temperature of the cow for that day. The former was evaluated using a threshold varying between 35.7 and 39.5°C, and the latter using the formula μ-n10σ, where µ = mean of the temperature of each cow for one day, n = 1, 2, …, 20, and σ = standard deviation of the temperature of each cow on that day. The performance of the validation of detection using each of the threshold types was computed using different metrics, including overall accuracy, precision, recall (also known as sensitivity), F-score, positive predictive value, negative predictive value, false discovery rate, false omission rate, and Cohen's kappa statistic. The findings of the first study showed that the cow-day specific threshold of n = 10 performed better (true positives = 466; false positives = 167; false negatives = 165; true negatives = 8,416) than using a general-fixed threshold of 38.1°C (true positives = 449; false positives = 181; false negatives = 182; true negatives = 8,402). With the information gained in this first study, we investigated the different factors associated with temperature drop characteristics per cow: number of drops, mean amplitude of the drop, and mean recovery time. For this, we used data from 54 cows collected for almost 1 yr to build a mixed-effect multilevel model that included days in milk, parity, average monthly milk production, and ambient temperature as explanatory variables. Cow characteristics and ambient temperature had significant effects on drinking events. Our results provide a platform for automated monitoring of drinking behavior, which has potential value in prediction of health and welfare in dairy cattle.