Qualitative behaviour assessment as part of a welfare assessment in flocks of laying hens

INVITED REVIEW: Phenotyping strategies and genetic background of dairy cattle behavior in intensive production systems - from trait definition to genomic selection

Understanding and assessing dairy cattle behavior is critical for developing sustainable breeding programs and management practices. The behavior of individual animals can provide valuable information on their health and welfare status, improve reproductive management, and predict efficiency traits such as feed efficiency and milking efficiency. Routine genetic evaluations of animal behavior traits can contribute to optimizing breeding and management strategies for dairy cattle but require the identification of traits that capture the most important biological processes involved in behavioral responses. These traits should be heritable, repeatable, and measured in non-invasive and cost-effective ways in many individuals from the breeding populations or related reference populations. While behavior traits are heritable in dairy cattle populations, they are highly polygenic, with no known major genes influencing their phenotypic expression. Genetically selecting dairy cattle based on their behavior can be advantageous because of their relationship with other key traits such as animal health, welfare, and productive efficiency, as well as animal and handlers' safety. Trait definition and longitudinal data collection are still key challenges for breeding for behavioral responses in dairy cattle. However, the more recent developments and adoption of precision technologies in dairy farms provide avenues for more objective phenotyping and genetic selection of behavior traits. Furthermore, there is still a need to standardize phenotyping protocols for existing traits and develop guidelines for recording novel behavioral traits and integrating multiple data sources. This review gives an overview of the most common indicators of dairy cattle behavior, summarizes the main methods used for analyzing animal behavior in commercial settings, describes the genetic and genomic background of previously defined behavioral traits, and discusses strategies for breeding and improving behavior traits coupled with future opportunities for genetic selection for improved behavioral responses.

Qualitative Behavioural Assessment as a welfare indicator for farmed Atlantic salmon (Salmo salar) in response to a stressful challenge

Animal welfare assessments have struggled to investigate the emotional states of animals while focusing solely on available empirical evidence. Qualitative Behavioural Assessment (QBA) may provide insights into an animal's subjective experiences without compromising scientific rigor. Rather than assessing explicit, physical behaviours (i.e., what animals are doing, such as swimming or feeding), QBA describes and quantifies the overall expressive manner in which animals execute those behaviours (i.e., how relaxed or agitated they appear). While QBA has been successfully applied to scientific welfare assessments in a variety of species, its application within aquaculture remains largely unexplored. This study aimed to assess QBA's effectiveness in capturing changes in the emotional behaviour of Atlantic salmon following exposure to a stressful challenge. Nine tanks of juvenile Atlantic salmon were video-recorded every morning for 15 min over a 7-day period, in the middle of which a stressful challenge (intrusive sampling) was conducted on the salmon. The resultant 1-min, 63 video clips were then semi-randomised to avoid predictability and treatment bias for QBA scorers. Twelve salmon-industry professionals generated a list of 16 qualitative descriptors (e.g., relaxed, agitated, stressed) after viewing unrelated video-recordings depicting varying expressive characteristics of salmon in different contexts. A different group of 5 observers, with varied experience of salmon farming, subsequently scored the 16 descriptors for each clip using a Visual Analogue Scale (VAS). Principal Components Analysis (correlation matrix, no rotation) was used to identify perceived patterns of expressive characteristics across the video-clips, which revealed 4 dimensions explaining 74.5% of the variation between clips. PC1, ranging from 'relaxed/content/positive active' to 'unsettled/stressed/spooked/skittish' explained the highest percentage of variation (37%). QBA scores for video-clips on PC1, PC2, and PC4 achieved good inter- and intra-observer reliability. Linear Mixed Effects Models, controlled for observer variation in PC1 scores, showed a significant difference between PC1 scores before and after sampling (p = 0.03), with salmon being perceived as more stressed afterwards. PC1 scores also correlated positively with darting behaviours (r = 0.42, p < 0.001). These results are the first to report QBA's sensitivity to changes in expressive characteristics of salmon following a putatively stressful challenge, demonstrating QBA's potential as a welfare indicator within aquaculture.

Use of qualitative behavioural assessment to investigate affective states of housed dairy cows under different environmental conditions

In addition to the reduction of suboptimal welfare, there is now a need to provide farmed animals with positive opportunities to provide confidence that they have experienced a life worth living. Diversification of the environment through environmental enrichment strategies is one suggested avenue for providing animals with opportunities for positive experiences. The provision of more stimulating environmental conditions has been widely implemented in other animal production industries, based on evidenced welfare benefits. However, the implementation of enrichment on dairy farms is limited. In addition to this, the relationship between enrichment and dairy cows' affective states is an under-researched area. One specific welfare benefit of enrichment strategies which has been observed in a number of species, is increased affective wellbeing. This study investigated whether the provision of different forms of environmental enrichment resources would impact the affective states of housed dairy cows. This was measured by Qualitative Behavioural Assessment, currently a promising positive welfare indicator. Two groups of cows experienced three treatment periods; (i) access to an indoor novel object, (ii) access to an outdoor concrete yard and (iii) simultaneous access to both resources. Principal component analysis was used to analyse qualitative behavioural assessment scores, which yielded two principal components. The first principal component was most positively associated with the terms “content/relaxed/positively occupied” and had the most negative associations with the terms ‘fearful/bored'. A second principal component was most positively associated with the terms “lively/inquisitive/playful” and was most negatively associated with the terms “apathetic/bored”. Treatment period had a significant effect on both principal components, with cows being assessed as more content, relaxed and positively occupied and less fearful and bored, during periods of access to additional environmental resources. Similarly, cows were scored as livelier, more inquisitive and less bored and apathetic, during treatment periods compared to standard housing conditions. Concurrent with research in other species, these results suggest that the provision of additional environmental resources facilitates positive experiences and therefore enhanced affective states for housed dairy cows.

V-QBA vs. QBA—How Do Video and Live Analysis Compare for Qualitative Behaviour Assessment?

Animal welfare is an inextricable part of livestock production and sustainability. Assessing welfare, beyond physical indicators of health, is challenging and often relies on qualitative techniques. Behaviour is a key component of welfare to consider and Qualitative Behaviour Assessment (QBA) aims to achieve this by systematically scoring behaviour across specific terms. In recent years, numerous studies have conducted QBA by using video footage, however, the method was not originally developed using video and video QBA (V-QBA) requires validation. Forty live QBAs were conducted, by two assessors, on housed beef cattle to help fill this validation gap. Video was recorded over the assessment period and a second video assessment was conducted. Live and video scores for each term were compared for both correlation and significant difference. Principle component analysis (PCA) was then conducted and correlations and differences between QBA and V-QBA for the first two components were calculated. Of the 20 terms, three were removed due to an overwhelming majority of scores of zero. Of the remaining 17 terms, 12 correlated significantly, and a significant pairwise difference was found for one (“Bored”). QBA and V-QBA results correlated across both PC1 (defined as “arousal”) and PC2 (defined as “mood”). Whilst there was no significant difference between the techniques for PC1, there was for PC2, with V-QBA generally yielding lower scores than QBA. Furthermore, based on PC1 and PC2, corresponding QBA and V-QBA scores were significantly closer than would be expected at random. Results found broad agreement between QBA and V-QBA at both univariate and multivariate levels. However, the lack of absolute agreement and muted V-QBA results for PC2 mean that caution should be taken when implementing V-QBA and that it should ideally be treated independently from live QBA until further evidence is published. Future research should focus on a greater variety of animals, environments, and assessors to address further validation of the method.

Advancing a "Good Life" for Farm Animals: Development of Resource Tier Frameworks for On-Farm Assessment of Positive Welfare for Beef Cattle, Broiler Chicken and Pigs

Simple Summary

A “good life” for farmed animals is a life where positive experiences (positive welfare) far outweigh any negative experiences (negative welfare). If we give animals resources that they value and that provide them with positive physical and mental experiences, we give them opportunities to experience positive welfare and therefore a good life. Evaluating whether certain resources are provided for animals gives us a practical way of assessing positive welfare on farms. We describe the initial development of such resource evaluation frameworks (“Good Life Frameworks”) for beef cattle, broiler chickens and pigs.

Abstract

There is increasing recognition that farm animal welfare standards should ensure positive welfare, as well as prevent negative welfare. Resources that are valued by an animal and that provide opportunities to engage in motivated behaviours can elicit positive physical and emotional states and therefore positive welfare and a “good life” for farmed animals. Evaluation of resource provision is considered the best way of assessing positive welfare at present, in the absence of validated and practical animal-based measures. Previous research has outlined a framework of three tiers of increasingly positive welfare (Welfare +, Welfare ++, Welfare +++) containing resources that incrementally increase the opportunities for a good life over and above the requirements of UK law and code of practice. Based on this blueprint, “Good Life Frameworks” were developed for beef cattle, broiler chickens and pigs, containing resources that increase good life opportunities according to the scientific literature and expert consultation. We describe the initial development of these frameworks, including a piloting exercise with the UK farm assurance industry, to further refine the frameworks according to auditor and farmer feedback, and test the frameworks as a method of on-farm assessment and assurance of a “good life” for farm animals.