Automatic detection of feeding- and drinking-related agonistic behavior and dominance in dairy cows

Graduate Student Literature Review: Social and feeding behavior of group-housed dairy calves in automated milk feeding systems

Automated milk feeders (AMF) allow farmers to raise calves in groups while generating individual records on milk consumption, drinking speed, and frequency of visits. Calves raised in groups benefit from social interaction, which facilitates learning and adapting to novelty. However, calves in large groups (>12 calves/feeder) experience a higher risk of disease transmission and competition than those housed individually or in smaller groups. Therefore, if group size, grouping strategy, and disease detection are not optimal, the health and performance of calves can be compromised. The objectives of this narrative literature review, from publications available as of February 2023, are to (1) describe the use of AMF in group housing systems for calves and the associated feeding behavior variables they automatically collect, (2) linking feeding behavior collected from AMF to disease risk in calves, (3) describe research on social behavior in AMF systems, and (4) introduce social networks as a promising tool for the study of social behavior and disease transmission in group-housed AMF-fed calves. Existing research suggests that feeding behavior measures from AMF can assist in detecting bovine respiratory disease and enteric disease, which are common causes of morbidity and mortality for preweaning dairy heifers. Automated milk feeder records show reduced milk intake, drinking speed, or frequency of visits when calves are sick. However, discrepancies exist among published research about the sensitivity of feeding behavior measures as indicators of sickness, likely due to differences in feeding plans and disease-detection protocols. Therefore, considering the influence of milk allowance, group density, and individual variation on the analysis of AMF data is essential to derive meaningful information used to inform management decisions. Research using dynamic social networks derived from precision data show potential for the use of social network analysis to understand disease transmission and the effect of disease on social behavior of group-housed calves.

Redefining dominance calculation: Increased competition flattens the dominance hierarchy in dairy cows

Dominance hierarchies are known for mitigating conflicts and guiding priority of access to limited resources in gregarious animals. The dominance hierarchy of dairy cows is typically investigated using agonistic interactions, often monitored at the feed bunk right after fresh feed delivery when competition is high resulting in frequent interactions. Yet, the outcome of agonistic interactions during times of high competition may be more influenced by cows' high valuation of fresh feed than their intrinsic attributes, such that the dominance hierarchy constructed using agonistic interactions under high versus low competition times might differ. We tested how the structure of the dominance hierarchy changes in relation to different levels of competition in a dynamic group of 48 lactating dairy cows over 10 mo, with 6 cows exchanged every 16 d for a total of 159 cows. Using a validated algorithm we continuously detected the actor and reactor of replacement behaviors in 30 feed bins as cows competed for feed. We also calculated the percentage of occupied feed bins to characterize competition at the moment of each replacement. These data were combined to create hierarchies using Elo ratings, separately for 25 occupancy levels ranging from 13% to 100%. For each 1% rise in feeder occupancy, hierarchy steepness fell by 2.41 × 10-3 ± 9.71 × 10-5 (SE), and the percentage of dyads where both cows replaced each other rose by 0.13% ± 0.01%. At the highest feeder occupancy level in comparison to the lowest one, we observed 7.57% more dyads in which the dominant individual (those won more interactions at the lowest feeder occupancy) started to lose proportionally more. The magnitude of decrease in the winning rate of the dominant individual in those dyads also got amplified by 1.06 × 10-3% ± 1.37 × 10-4% (SE) for each 1% increase in feeder occupancy. These findings illustrate how inferred hierarchies vary with competition, with high competition flattening the hierarchy due to increased success of subordinate animals. We suggest that during heightened competition, increased valuation of resources can affect competitive success more than the individual's intrinsic dominance attributes. We recommend against calculating dominance hierarchies based on agonistic interactions during periods of high competition alone, and more generally urge researchers to differentiate agonistic interactions based on context when constructing dominance hierarchies.

Effects of group size on agonistic interactions in dairy cows: a descriptive study

Group-housed cattle may engage in agonistic interactions over resources such as feed, which can negatively affect aspects of welfare. Little is known about how contextual factors such as group size influence agonistic behaviour. We explored the frequency of agonistic interactions at the feeder when cattle were housed in different-sized groups. We also explored the consistency of the directionality of agonistic interactions in dyads and of the number of agonistic interactions initiated by individuals across the group sizes. Four replicates of 50 cows each were assessed in two group-size phases. In Phase 1, cows were kept in one group of 50. In Phase 2, these same cows were divided into five groups of 10, maintaining stocking density (i.e., ratio of animals to lying stalls and feed bunk spaces). We measured agonistic replacements (i.e., interactions that result in one cow leaving the feed bin and another taking her place) at an electronic feeder using a validated algorithm. We used these data from Phase 1 to calculate individual Elo-ratings (a type of dominance score). Cows were then categorised into five dominance categories based upon these ratings. To ensure a consistent Elo-rating distribution between phases, two cows from each dominance category were randomly assigned to each small group of 10 cows. The mean ± SE number of replacements per cow was similar regardless of whether the cows were housed in groups of 50 (34.1 ± 2.4) or 10 (31.1 ± 4.5), although the groups of 10 were more variable. Further, 81.6 ± 7.7% (mean ± SD) of dyads had the same directionality across group sizes (i.e., the same individual won the majority of interactions in the dyad) and individuals were moderately consistent in the number of replacements they initiated (intraclass correlation coefficient = 0.62 ± 0.11; mean ± SD). These results indicate that the relationship between group size and agonistic behaviour is complex; we discuss these challenges and suggest new avenues for further research.

Increased Cattle Feeding Precision from Automatic Feeding Systems: Considerations on Technology Spread and Farm Level Perceived Advantages in Italy

Automation reduces the impact of farming on climate change and helps farmers adapt to its financial impact. Automatic feeding systems (AFSs) increase the ruminant's feeding precision and ease operators' workload. Such systems exist on a spectrum, requiring varied levels of operator support and installation complexity. A recent survey on farmers pointed out that those already running an AFS and those willing to buy one appreciate its ease of use, the resulting animal welfare, and the resulting overall benefits (increased production, farm profitability, and reduced feed waste). Whether technologically complex or not, studies have confirmed the benefits that farmers perceive to be underlying the remarkable reduction in the environmental impact of feeding operations (AFSs are electrically powered), the increase in animal welfare resulting from reduced conflicts around accessing the feed bunk, and the constant availability of fresh feed. However, their introduction should follow accurate and holistic structural and economic planning for existing and newly built facilities. The availability of public subsidies plays an essential role in pushing farmers to adopt the most modern digital technologies, whose benefits may even increase when farmers couple them with interconnected sensors to monitor animals' physiological states.

Invited review: Social dominance in dairy cattle: A critical review with guidelines for future research

Cattle are gregarious animals able to form social relationships. Dominance is one of the most widely studied social behaviors of dairy cattle, especially cows confined indoors. However, much of the past dairy cattle research has used an unstandardized approach, differing in definitions and conceptual understanding of dominance, as well as their methods of data collection and dominance calculation. The first of the 3 aims of this review is to evaluate how dominance relates to the social behavior of housed dairy cows. Cows engage in agonistic interactions to establish and reinforce dominance relationships. An individual's dominance is influenced by intrinsic characteristics, such as personality, and extrinsic factors, including group composition. When competing for resources, agonistic interactions can also be influenced by individual motivational differences, such as hunger, which may diminish the role of dominance in regulating competition. Our second aim is to critically review methods used to assess dominance in cows. This includes discussions on the effect of time and location of data collection on measured values as well as the viability and limitations of some dominance calculation methods. We propose that different methodologies lend themselves to different types of research questions. For example, the use of data stream-based methods that consider the sequence of interactions are useful for estimating how dominance fluctuates with changing conditions and can be used in a dynamically changing group. In contrast, matrix-based methods that aggregate social interactions may be best for identifying the social position of individuals and understanding how social characteristics influence the attributes of a stable hierarchy. Our third aim is to discuss the future of dominance research. We use a flowchart to illustrate guidelines for a more standardized approach to measuring dominance in cattle. We also identify areas in need of further conceptual clarification, suggest practical applications of dominance when managing dairy cattle, and discuss some limitations of dominance research.

Cow characteristics associated with the variation in number of contacts between dairy cows

In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.

Evaluating accurate and efficient sampling strategies designed to measure social behavior and brush use in drylot housed cattle

Efficient sampling strategies expedite behavioral data collection. While multiple studies have evaluated sampling strategies for core behaviors in cattle, few have focused on social interactions. To identify sampling strategies that accurately captured cattle social behaviors and brush use feedlot steers (n = 3 pens; 9 steers/pen) were observed from 8:00 to 17:00. Average bout duration (sec), total duration per day (sec), and bout frequency were recorded for allogrooming, bar licking, tongue rolling, and brush utilization. Frequency was recorded for headbutting and mounting. Data was extracted from continuous observation datasets using eight different sampling strategies and the results subsequently compared. Differences among sampling strategies were evaluated using a non-parametric One-Way ANOVA Kruskal-Wallis Test. Pearson correlation evaluated the strength of association between a specific sampling strategy and continuous observations. Bout duration for allogrooming (P > 0.65), bar licking (P > 0.60), tongue rolling (P > 0.99), brush use (P > 0.99), and mounting frequency (P > 0.70) did not differ from continuous observations. Tongue rolling (r2 > 0.95, P <0.0001) and brush use (r2 > 0.70, P < 0.0003) were best captured when cattle were observed from 08:00 to 14:00. When cattle were continuously observed from 08:00 to 14:00 or for 15 minutes every 30 minutes, allogrooming (P > 0.2) (frequency, duration), bar licking (P > 0.95) (frequency, duration), brush use (P > 0.1) (frequency, duration), heat butt (P > 0.30) (frequency), or tongue rolling (P > 0.30) (frequency, duration) did not differ from continuous observations. Observing cattle for 15 minutes every 30 minutes yielded the highest accuracy for all behavioral metrics and was considered the most effective strategy for comprehensively evaluating cattle social behavior (r2 > 75; P < 0.05). These results provide insight into accurate and efficient sampling strategies that expedite social behavior data collection in cattle and will facilitate efficient generation of new knowledge regarding cattle social behaviors.

Continuous real-time cow identification by reading ear tags from live-stream video

In precision dairy farming there is a need for continuous and real-time availability of data on cows and systems. Data collection using sensors is becoming more common and it can be difficult to connect sensor measurements to the identification of the individual cow that was measured. Cows can be identified by RFID tags, but ear tags with identification numbers are more widely used. Here we describe a system that makes the ear tag identification of the cow continuously available from a live-stream video so that this information can be added to other data streams that are collected in real-time. An ear tag reading model was implemented by retraining and existing model, and tested for accuracy of reading the digits on cows ear tag images obtained from two dairy farms. The ear tag reading model was then combined with a video set up in a milking robot on a dairy farm, where the identification by the milking robot was considered ground-truth. The system is reporting ear tag numbers obtained from live-stream video in real-time. Retraining a model using a small set of 750 images of ear tags increased the digit level accuracy to 87% in the test set. This compares to 80% accuracy obtained with the starting model trained on images of house numbers only. The ear tag numbers reported by real-time analysis of live-stream video identified the right cow 93% of the time. Precision and sensitivity were lower, with 65% and 41%, respectively, meaning that 41% of all cow visits to the milking robot were detected with the correct cow’s ear tag number. Further improvement in sensitivity needs to be investigated but when ear tag numbers are reported they are correct 93% of the time which is a promising starting point for future system improvements.

Effects of Feeding and Drinking Behavior on Performance and Carcass Traits in Beef Cattle

Feed and water efficiency are important traits to improve beef cattle production’s economic and environmental sustainability. This study evaluated residual feed intake (RFI) and residual water intake (RWI) and their relationship with performance, ingestive behavior, and carcass traits in Caracu beef cattle. The data were analyzed using a generalized linear model with least squares means. The ingestive behavior, performance, and carcass traits were influenced by sex (p < 0.05). Males showed higher dry matter intake (DMI), average daily gain (ADG), mid-test metabolic weight (BW0.75), rib eye area, and rump fat thickness than females, besides spending more time drinking and eating. Low RFI animals exhibited higher DMI than high RFI animals. Low RWI animals ingested 3.89 L/d of water further than high RWI animals. The interaction between sex and RWI influenced the DMI, BW0.75, and backfat thickness. The ingestive behavior of low and high RFI animals was similar, although high RWI animals visited a smaller number of drinkers than low RWI animals. Water intake positively affects productive efficiency, and the combined use of RWI and RFI may help improve the selection of more efficient animals contributing to reducing the costs of beef cattle production and improving environmental sustainability.

Dairy cows did not rely on social learning mechanisms when solving a spatial detour task

As herd-living animals, cattle have opportunities to observe and learn from others. While there is evidence of simpler processes of information transfer in cattle (social facilitation and stimulus enhancement), true social learning mechanisms in cattle remain largely unexplored. This study aimed to investigate if dairy cows possess cognitive abilities to acquire new behavior through social learning in a spatial detour task. Thirty-two dairy cows (ages 2–9 years) participated in the study. A food reward was placed behind a U-shaped formation (4 x 2 m), allowing the cows to see but not reach the reward without first detouring around the obstacle. The U-shape provided two routes (~18 m walking distance) to the reward, of which one was used for demonstration. Two cows were demonstrators and 30 cows were divided into two groups, assigned as either observers of demonstration (n = 15) or controls not observing demonstration (n = 15). Cows had three attempts (trials) to solve the task. Response variables were: success, latency to reach the reward, concordance in choice of route to detour, and time spent facing the test arena before each trial started. The study found no significant differences in success or latency between observers and controls, although observers spent a greater proportion of the time before trials facing the test arena. However, successful observers tended to be faster than successful controls. Individual cows were generally consistent in their choice of route, and cows choosing the demonstrated route were significantly faster than cows that did not. Success in solving the task decreased over trials, likely due to decreasing food motivation. Age had a significant effect on success in 2^nd and 3^rd trial, with younger cows being more successful. The lacking effect of treatment on success suggests that the age effect may be explained by a higher motivation, rather than social learning. Adding to the sparse knowledge of social learning in farm animals, these results indicate that cows did not utilize social learning mechanisms when solving the detour task. Future research should focus on clarifying whether cattle possess cognitive abilities necessary for social learning, as well as if /when social learning is a primary strategy.

socialh: An R package for determining the social hierarchy of animals using data from individual electronic bins

Cattle have a complex social organization, with negative (agonistic) and positive (affiliative) interactions that affect access to environmental resources. Thus, the social behaviour has a major impact on animal production, and it is an important factor to improve the farm animal welfare. The use of data from electronic bins to determine social competition has already been validated; however, the studies used non-free software or did not make the code available. With data from electronic bins is possible to identify when one animal takes the place of another animal, i.e. a replacement occurs, at the feeders or drinkers. However, there is no package for the R environment to detect competitive replacements from electronic bins data. Our general approach consisted in creating a user-friendly R package for social behaviour analysis. The workflow of the socialh package comprises several steps that can be used sequentially or separately, allowing data input from electronic systems, or obtained from the animals’ observation. We provide an overview of all functions of the socialh package and demonstrate how this package can be applied using data from electronic feed bins of beef cattle. The socialh package provides support for researchers to determine the social hierarchy of gregarious animals through the synthesis of agonistic interactions (or replacement) in a friendly, versatile, and open-access system, thus contributing to scientific research.

Effects of Housing and Management Factors on Selected Indicators of the Welfare Quality® Protocol in Loose-Housed Dairy Cows

The objective of this study was to examine the effects of housing and management factors on animal welfare indicators in dairy cows using a benchmarking approach. In total, 63 conventional dairy cattle farms with zero-grazing in Northern Germany were assessed using selected animal welfare indicators (body condition score, integument alterations, lameness, milk somatic cell count, and social behaviour) of the Welfare Quality® protocol. Additionally, housing characteristics such as designs of barns, cubicles, and floors were documented during farm visits and farmers were interviewed concerning their common management routines. Farms were categorized into a high welfare or low welfare group by calculating upper and lower tertiles for each of the animal welfare indicators separately. Both groups were compared regarding housing conditions and management practices using univariable and multivariable logistic regressions. Several associations between housing and management factors and animal welfare indicators were demonstrated in univariable analysis (p < 0.20). Significant effects within multivariable logistic regression analysis were determined for lameness (routine use of foot-baths), milk somatic cell count (milking frequency) and social behaviour (cow-to-stall ratio) (p < 0.05). Comparing farms with higher and lower animal welfare status can provide useful information about effective options to improve animal welfare.

Indirect Genetic Effects: A Cross-disciplinary Perspective on Empirical Studies

Indirect genetic effects (IGE) occur when an individual's phenotype is influenced by genetic variation in conspecifics. Opportunities for IGE are ubiquitous, and, when present, IGE have profound implications for behavioral, evolutionary, agricultural, and biomedical genetics. Despite their importance, the empirical study of IGE lags behind the development of theory. In large part, this lag can be attributed to the fact that measuring IGE, and deconvoluting them from the direct genetic effects of an individual's own genotype, is subject to many potential pitfalls. In this Perspective, we describe current challenges that empiricists across all disciplines will encounter in measuring and understanding IGE. Using ideas and examples spanning evolutionary, agricultural, and biomedical genetics, we also describe potential solutions to these challenges, focusing on opportunities provided by recent advances in genomic, monitoring, and phenotyping technologies. We hope that this cross-disciplinary assessment will advance the goal of understanding the pervasive effects of conspecific interactions in biology.

The effects of cow dominance on the use of a mechanical brush

An animal's social position within a group can influence its ability to perform important behaviours like eating and resting, but little is known about how social position affects the ability to express what are arguably less important but still rewarding behaviors, such as grooming. We set out to assess if dominance measured at the feeder is associated with increased use of a mechanical brush. Over a 2-year period, 161 dry cows were enrolled in a dynamically changing group of 20 individuals with access to a mechanical brush. We determined dominance using agonistic behaviors at the feeder and retrospectively analyzed brush use for the 12 most, and 12 least dominant individuals during the week before calving. Cows that were more dominant at the feeder used the brush more, especially during peak feeding times. Agonistic interactions at the brush did not differ between dominants and subordinates and were not related to brushing duration. These findings indicate that social position, calculated using competition for feed, affects mechanical brush access such that subordinates use the brush less than dominant cows independent of competition or time of day.

Individual and environmental factors associated with defecation while lying down in dairy cows

Cows typically defecate while standing. Freestalls are designed to position standing cows such that their feces fall into the alley. Cows sometimes defecate while lying down, increasing the risk that feces contaminate the stall surface. We conducted 2 studies investigating cow-level and environmental factors associated with defecating while recumbent. In experiment 1, we hypothesized that conditions making it more difficult for cows to stand up (including greater age, high body weight, pregnancy, and lameness) would increase the risk of this behavior. We followed 92 cows for 12 d, scanning stalls 5 times/d using live observation. Almost half (48%) of all cows defecated while recumbent at least once; cows that spent more time lying down and that were earlier in gestation were at highest risk. Weight, parity, age, and lameness were not associated with this behavior. In experiment 2, we tested how overstocking influenced the occurrence of defecating while recumbent. We predicted overstocking would increase the occurrence of this behavior, especially when cows were in stalls at more preferred locations. We recorded stall occupancy, displacement attempts, and defecating while recumbent in 4 groups of 36 cows tested at both 100% and 150% lying stall stocking densities for 2 nights each using a crossover design. Overstocking resulted in higher stall use and more displacements, but less lying and fewer perching events. We did not detect any relationship between use of specific stalls or competition and defecating while recumbent. Most recorded displacements were associated with perching. Increased time perching increased the likelihood of defecating while recumbent, perhaps because perching cows were less dominant or more reluctant to stand up once lying down in the stall. Overstocking did not increase defecating while recumbent, likely because cows spent less time lying down. Together, these results indicate that defecating while recumbent can be common, and points to some of the cow-level factors associated with this behavior.

Exploring the Potential of Precision Livestock Farming Technologies to Help Address Farm Animal Welfare

The rise in the demand for animal products due to demographic and dietary changes has exacerbated difficulties in addressing societal concerns related to the environment, human health, and animal welfare. As a response to this challenge, Precision Livestock Farming (PLF) technologies are being developed to monitor animal health and welfare parameters in a continuous and automated way, offering the opportunity to improve productivity and detect health issues at an early stage. However, ethical concerns have been raised regarding their potential to facilitate the management of production systems that are potentially harmful to animal welfare, or to impact the human-animal relationship and farmers' duty of care. Using the Five Domains Model (FDM) as a framework, the aim is to explore the potential of PLF to help address animal welfare and to discuss potential welfare benefits and risks of using such technology. A variety of technologies are identified and classified according to their type [sensors, bolus, image or sound based, Radio Frequency Identification (RFID)], their development stage, the species they apply to, and their potential impact on welfare. While PLF technologies have promising potential to reduce the occurrence of diseases and injuries in livestock farming systems, their current ability to help promote positive welfare states remains limited, as technologies with such potential generally remain at earlier development stages. This is likely due to the lack of evidence related to the validity of positive welfare indicators as well as challenges in technology adoption and development. Finally, the extent to which welfare can be improved will also strongly depend on whether management practices will be adapted to minimize negative consequences and maximize benefits to welfare.

A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle

In order to base welfare assessment of dairy cattle on real-time measurement, integration of valid and reliable precision livestock farming (PLF) technologies is needed. The aim of this study was to provide a systematic overview of externally validated and commercially available PLF technologies, which could be used for sensor-based welfare assessment in dairy cattle. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature review was conducted to identify externally validated sensor technologies. Out of 1,111 publications initially extracted from databases, only 42 studies describing 30 tools (including prototypes) met requirements for external validation. Moreover, through market search, 129 different retailed technologies with application for animal-based welfare assessment were identified. In total, only 18 currently retailed sensors have been externally validated (14%). The highest validation rate was found for systems based on accelerometers (30% of tools available on the market have validation records), while the lower rates were obtained for cameras (10%), load cells (8%), miscellaneous milk sensors (8%), and boluses (7%). Validated traits concerned animal activity, feeding and drinking behavior, physical condition, and health of animals. The majority of tools were validated on adult cows. Non-active behavior (lying and standing) and rumination were the most often validated for the high performance. Regarding active behavior (e.g., walking), lower performance of tools was reported. Also, tools used for physical condition (e.g., body condition scoring) and health evaluation (e.g., mastitis detection) were classified in lower performance group. The precision and accuracy of feeding and drinking assessment varied depending on measured trait and used sensor. Regarding relevance for animal-based welfare assessment, several validated technologies had application for good health (e.g., milk quality sensors) and good feeding (e.g., load cells, accelerometers). Accelerometers-based systems have also practical relevance to assess good housing. However, currently available PLF technologies have low potential to assess appropriate behavior of dairy cows. To increase actors' trust toward the PLF technology and prompt sensor-based welfare assessment, validation studies, especially in commercial herds, are needed. Future research should concentrate on developing and validating PLF technologies dedicated to the assessment of appropriate behavior and tools dedicated to monitoring the health and welfare in calves and heifers.

Computerized assessment of dominance hierarchy in baboons (Papio papio)

Dominance hierarchies are an important aspect of Primate social life, and there is an increasing need to develop new systems to collect social information automatically. The main goal of this research was to explore the possibility to infer the dominance hierarchy of a group of Guinea baboons (Papio papio) from the analysis of their spontaneous interactions with freely accessible automated learning devices for monkeys (ALDM, Fagot & Bonté Behavior Research Methods, 42, 507-516, 2010). Experiment 1 compared the dominance hierarchy obtained from conventional observations of agonistic behaviours to the one inferred from the analysis of automatically recorded supplanting behaviours within the ALDM workstations. The comparison, applied to three different datasets, shows that the dominance hierarchies obtained with the two methods are highly congruent (all rs ≥ 0.75). Experiment 2 investigated the experimental potential of inferring dominance hierarchy from ALDM testing. ALDM data previously published in Goujon and Fagot (Behavioural Brain Research, 247, 101-109, 2013) were re-analysed for that purpose. Results indicate that supplanting events within the workstations lead to a transient improvement of cognitive performance for the baboon supplanting its partners and that this improvement depends on the difference in rank between the two baboons. This study therefore opens new perspectives for cognitive studies conducted in a social context.

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Simple Summary

Social behaviour of farm animals significantly impacts management interventions in the livestock sector and, thereby, animal welfare. Evaluation and monitoring of social networks between farm animals help not only to understand the bonding and agonistic behaviours among individuals but also the interactions between the animals and the animal caretaker. The interrelationship between social and environmental conditions, and the subtle changes in the behaviours of farm animals can be understood and precisely measured only by using sensing technologies. This review aims to highlight the use of sensing technologies in the investigation of social network analysis of farm animals.

Abstract

Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal behaviour under domesticated conditions in comparison to natural behaviours found in wild settings has the potential to address issues of animal welfare effectively, such as focusing on reproduction and production success. This review discusses and evaluates to what extent social network analysis (SNA) can be incorporated with sensor-based data collection methods, and what impact the results may have concerning welfare assessment and future farm management processes. The effectiveness and critical features of automated sensor-based technologies deployed in farms include tools for measuring animal social group interactions and the monitoring and recording of farm animal behaviour using SNA. Comparative analyses between the quality of sensor-collected data and traditional observational methods provide an enhanced understanding of the behavioural dynamics of farm animals. The effectiveness of sensor-based approaches in data collection for farm animal behaviour measurement offers unique opportunities for social network research. Sensor-enabled data in livestock SNA addresses the biological aspects of animal behaviour via remote real-time data collection, and the results both directly and indirectly influence welfare assessments, and farm management processes. Finally, we conclude with potential implications of SNA on modern animal farming for improvement of animal welfare.

Familiarity influences social networks in dairy cows after regrouping

Regrouping is common practice when managing dairy cow groups, and it is known to have disruptive effects on behavior and production. The presence of a small group of familiar cows upon regrouping may provide social support and mitigate some of the negative effects. In this study we investigated (1) how regrouping affects social relationships among familiar cows and (2) if cows prefer familiar individuals over unfamiliar ones as social partners after regrouping. We used 3 established groups of cows to create 2 new groups, each containing 14 cows, using subgroups of familiar animals (i.e., 4, 6, and 4 cows) from the original groups. The new groups were similar in respect to the age, parity, and sire of cows. The frequencies of grooming and displacements were determined in the walking alley, lying stalls, and feed bunk by observing 48 h of continuous video before regrouping, directly after regrouping, and 1 wk later. First, social network analysis was applied to investigate the effects of regrouping on the relationships within the subgroups of familiar cows. Second, we determined if familiar cows were more or less connected than would be expected by chance (i.e., assortment), considering displacement, grooming, and feed bunk neighbor networks (derived from electronic feeder data) after regrouping. Regrouping increased the number of displacements, especially in the walking alley. Within the subgroups of familiar cows, regrouping resulted in slightly more displacements, but the network structure did not change. The frequency of grooming among familiar cows remained stable across all observation periods, and the network structure was not affected by regrouping. We found positive assortment in grooming and feed bunk neighbor networks, thereby suggesting that cows preferred familiar individuals as grooming partners and feeding neighbors directly after regrouping and, to a smaller extent, 1 wk later. The effect of familiarity on displacements depended on the pen area. The weak assortment directly after regrouping at the feed bunk indicated that familiar cows displaced each other more than unfamiliar ones, possibly because they were neighbors more often. Our results indicated that a small group of familiar cows may provide ongoing social buffering after regrouping. Further research with multiple groups and larger group sizes is needed to determine whether similar effects are consistently present when groups of familiar cows are subjected to regrouping.

A Review of Welfare Indicators of Indoor-Housed Dairy Cow as a Basis for Integrated Automatic Welfare Assessment Systems

Simple Summary

Many techniques have been developed to measure single indicators of reduced welfare in farm animals, such as changes in the walking pattern to detect lameness in dairy cows. However, there is still a need to combine these single measurements to get a more complete picture of the wellbeing of an animal. Based on a literature review on dairy cow welfare, this review provides a basis for the development of an integrated automatic system to assess the welfare of dairy cows on the farm. It provides an overview of the main welfare issues for dairy cows, such as lameness, heat stress, or pain and of the most established indicators that could help to detect these welfare issues on the farm. We found that there are several indicators, such as reduced feed intake, that are common to most welfare issues and that are therefore suitable to detect reduced welfare in general, while other indicators mainly identify one welfare issue, such as increased respiratory rate, as an indicator of heat stress. Combining these different types of indicators would provide a good basis to develop an integrated automatic system that could assist farmers in the detection of reduced welfare on their farms.

Abstract

For on-farm welfare assessment many automatic methods have been developed to detect indicators of reduced welfare. However, there is still a need to integrate data from single sources to obtain a complete picture of the welfare of an animal. This review offers a basis for developing integrated automatic systems to assess dairy cow welfare by providing an overview of the main issues that challenge cow welfare (e.g., lameness) and of well-established indicators that could detect these issues on the farm. Based on a literature review of 4 reviews on cow welfare in general and 48 reviews on single welfare issues, we identified 18 different major welfare issues and 76 matching indicators that could be detected automatically on the farm. Several indicators, e.g., feed intake, showed a consistent association with welfare across many different issues. Although some of these indicators are discussed critically, this means there are many indicators that potentially could detect reduced welfare in general. Other types of indicators could detect one specific welfare issue, e.g., increased respiratory rate for heat stress. These different types of indicators combined provide a basis to develop integrated automatic systems that ultimately would help farmers to detect welfare problems at an early stage.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Estimating Conformational Traits in Dairy Cattle With DeepAPS: A Two-Step Deep Learning Automated Phenotyping and Segmentation Approach

Assessing conformation features in an accurate and rapid manner remains a challenge in the dairy industry. While recent developments in computer vision has greatly improved automated background removal, these methods have not been fully translated to biological studies. Here, we present a composite method (DeepAPS) that combines two readily available algorithms in order to create a precise mask for an animal image. This method performs accurately when compared with manual classification of proportion of coat color with an adjusted R² = 0.926. Using the output mask, we are able to automatically extract useful phenotypic information for 14 additional morphological features. Using pedigree and image information from a web catalog (www.semex.com), we estimated high heritabilities (ranging from h² = 0.18–0.82), indicating that meaningful biological information has been extracted automatically from imaging data. This method can be applied to other datasets and requires only a minimal number of image annotations (∼50) to train this partially supervised machine-learning approach. DeepAPS allows for the rapid and accurate quantification of multiple phenotypic measurements while minimizing study cost. The pipeline is available at https://github.com/lauzingaretti/deepaps.

Competition Strategies of Metritic and Healthy Transition Cows

Simple Summary

Competition for feed is a social stressor for dairy cows and is associated with an increased risk of illness. We investigated how cows trade off the motivation to feed together with group mates against the risk of competitive interactions at the feeder, and in this way identified each individual’s competition strategy. We then related these strategies to cow health. Competition strategies varied between cows and showed low to moderate stability over time. Strategies of metritic and healthy cows did not differ before or after calving, but metritic cows changed strategies more upon entering the social group after calving, particularly in the days before diagnosis. We conclude that cows show individual competition strategies, and that automated measures of strategy change may help in detecting metritis.

Abstract

Our study aimed to characterize social competition strategies in transition cows, and determine how these varied with health status. We retrospectively followed 52 cows during 3 periods (PRE: d −6 to −1 prepartum, POST1: d 1 to 3 postpartum, POST2: d 4 to 6 postpartum). Cows diagnosed with metritis on d 6 postpartum (n = 26) were match paired with healthy cows (n = 26). Measures of agonistic behavior (i.e., replacements at the feeder) and feeding synchrony were determined by an algorithm based on electronic feed bin data, and used to calculate competition strategies via principal component analysis. We found consistent strategies, defined by two components (asynchrony and competitiveness; explaining 82% of the total variance). We observed no differences in strategies when comparing healthy and metritic cows, but metritic cows tended to change their strategies more between PRE and POST1, and between POST1 and POST2, indicating that strategies change in association with parturition and metritis. We conclude that cows show individual variation in competition strategies, and that automated measures of strategy change may help in detecting metritis.