Is a Professor in Livestock informatics at Scotland’s Rural College (SRUC) and Head of Edinburgh Genetic Evaluation Services (EGENES).
His main areas of research interest lie in the genetic and genomic improvement of farmed livestock for traits valuable to the animal, the farmer and society. This started in dairy cattle but has expanded to include beef, sheep, goats and pigs. Recent socio-economic developments and their resulting price spikes have sharply focussed attention on efficiency traits and environmental impact.
Recently, his group have begun exploring the use of Deep Learning to predict new phenotypes from milk mid infra-red (MIR) spectral data. Successes so far include predicting pregnancy status and bTB status and extracting new phenotypes automatically from sheep CT scans and goat udder images. They are expanding traits of interest to include Johnes disease, BVD and contaminants in milk. They are also looking to predict feed intake and methane emissions using MIR data in an international consortium.
The recent increase in the use of sexed semen has altered the way dairy cattle are bred, has increased the selection intensity in dairy and has increased the amount of beef produced by the dairy herd. This has opened up new areas of genetics research and genomic evaluation in an increasingly converging dairy and beef industry.
