Sheep category can be classified using machine learning techniques applied to fatty acid profiles derivatised as trimethylsilyl esters

Eruptionof permanent incisors (dentition) is used as aproxy for age for definingmeat quality inAustralian sheep meat. However, this approach may not be reliable. While not presently available, an objective method could be used to determine sheep age, and thus sheep category, which would then potentially remove any inaccuracies that may occur in classifying sheep meat product. Statistical classification algorithms have been successfully used in bioinformatics. In this paperwe review theperformanceof three algorithms (support vectormachines, recursive partitioning and randomforests) for determining sheep age.The algorithmswere applied to themeasured fatty acid profiles of fat samples from533carcasses; 254 lamb (<1 year old), 131 hogget (~1–2 years old) and 148 mutton (>2 years old) samples. Three data pretreatments (range transformation, column mean centering and range transformation with mean centering) were also examined to determine their impact on the performance of the algorithms. The random forests algorithm, when applied to mean-centred data, gave 100%predictive accuracywhen classifying sheep category. This approach could be used for the development of an objective test for determining sheep age and category.