Predicting lameness in dairy cattle using untargeted liquid chromatography-mass spectrometry-based metabolomics and machine learning.

Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness.

A randomised controlled trial to evaluate the impact of indoor living space on dairy cow production, reproduction and behaviour.

As a global society, we have a duty to provide suitable care and conditions for farmed livestock to protect animal welfare and ensure the sustainability of our food supply. The suitability and biological impacts of housing conditions for intensively farmed animals is a complex and emotive subject, yet poorly researched, meaning quantitative evidence to inform policy and legislation is lacking. Most dairy cows globally are housed for some duration during the year, largely when climatic conditions are unfavourable.

Clearance of Maedi-visna infection in a longitudinal study of naturally infected rams is associated with homozygosity for the resistance allele.

Maedi-visna (MV) is a lentiviral disease of sheep responsible for severe production losses in affected flocks. There are no vaccination or treatment options with control reliant on test and cull strategies. The most common diagnostic methods used at present are combination ELISAs for Gag and Env proteins with virus variability making PCR diagnostics still largely an experimental tool.

Schmallenberg virus neutralising antibody responses in sheep.

Background: Schmallenberg virus (SBV) is a midge borne virus of cattle and sheep. Infection is typically asymptomatic in adult sheep but fetal infection during pregnancy can result in abortion, stillbirth, neurological disorders and malformations of variable severity in newborn animals. It was first identified in Germany and the Netherlands in 2011 and then circulated throughout Europe in 2012 and 2013.

Feature Selection and Comparison of Machine Learning Algorithms in Classification of Grazing and Rumination Behaviour in Sheep.

Grazing and ruminating are the most important behaviours for ruminants, as they spend most of their daily time budget performing these. Continuous surveillance of eating behaviour is an important means for monitoring ruminant health, productivity and welfare. However, surveillance performed by human operators is prone to human variance, time-consuming and costly, especially on animals kept at pasture or free-ranging.

The Applied Development of a Tiered Multilocus Sequence Typing (MLST) Scheme for .

() is the causative pathogen of ovine footrot, a disease that has a significant welfare and financial impact on the global sheep industry. Previous studies into the phylogenetics of have focused on Australia and Scandinavia, meaning the current diversity in the United Kingdom (U.K.