Exploring the physiological basis of positive welfare: Does a dairy cow’s housed environment lead to changes in metabolomic signals, production, and behaviour?
A dairy cow’s living space leaves chemical traces in her milk that could reveal whether she is content or stressed. The study will house two groups of cows in different amounts of space inside a flexible barn, then analyse milk samples using mass spectrometry to detect metabolomic biomarkers—the final products of gene expression. Researchers will also track behaviour and milk yield, using machine learning to link chemical profiles to the animals’ affective state, the combination of short-term emotions and long-term moods. This matters because objective measures of animal welfare are scarce. Current methods rely on subjective behavioural assessments, which can miss subtle physiological changes. If the team can identify reliable metabolomic signals tied to positive welfare, farmers could use routine milk testing to assess how housing conditions affect their herds. The potential impact is practical: better housing design that improves animal health and productivity without guesswork. For the dairy industry, this could mean more efficient production and clearer welfare standards. The research is applied, not fundamental—it directly tests a hypothesis about environment, metabolism, and behaviour in a real farming context.
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This study aims to i) evaluate the impact of living space on the metabolome of housed dairy cows and ii) evaluate the relationship between the metabolome and specific behavioural and physiological responses. Quantitative measurement of welfare is a critically important but challenging area for exploration. We hypothesise that using metabolomic profiling, the final products in the cascade of gene expression, alongside biological rhythm, production and behaviour data has the potential to offer insight into affective state when dairy cows are provided different housed environments. Affective state is the combination of short-term emotions and long-term moods, both of which may be associated with alterations in the metabolome which is reactive to change. Dairy cattle are generally housed during their lifetime. In previous research living space has had substantial physiological impacts on production and behaviour. Objective measures of affective state would be transformational in terms of understanding welfare and behaviour, in order to determine the success of changes to an animal’s environment. This would complement subjective methods such as qualitative behaviour assessment. Two groups of dairy cows will be exposed to different living space conditions using a unique flexible housing dairy barn. Analysis of metabolomic biomarkers will be undertaken at key time intervals using untargeted direct infusion mass spectrometry (DIMS) based metabolomics on milk samples. Using machine learning methods, key metabolites will be identified, and metabolic pathways explored to understand the impact of living space provision. The relationship between metabolomic profiles and cow behaviour patterns and milk yield performance will be explored.
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