Enzymatic removal of dags from livestock: an agricultural application of enzyme technology.

The effective removal of dags (manure balls) from cattle, sheep and goats is a significant issue for the livestock industry. Dags are hard recalcitrant deposits composed of materials, such as faeces, hair, soil, urine, feed and straw, and attach to the animal through the hair rather than the skin. Dags build up during wet periods, especially on long haired breeds, and can weigh up to 40 kg per animal for cattle. Dag removal prior to slaughter reduces the risk of microbial meat contamination and damage to the hide during leather processing. Existing removal methods include hair trimming or extensive hose washing that can result in stress to the animal and increased costs. An alternative solution is the application of enzyme formulations that target specific components of the dag so they are more easily removed by washing. Enzymes are already used in other cleaning applications and are proven for the breakdown of materials such as lignocellulose, protein or starch that are found in dags. This mini-review discusses the challenges of current dag removal methods and the state of the art and feasibility of applying enzyme formulations for the effective removal of dags. Although enzyme formulations are yet to be tested in large-scale cattle trials and questions remain regarding how they would be cost-effectively applied to live animals, the results at laboratory scale suggest further research is warranted. Overall, enzymes present an environmentally friendly solution to the high costs and animal welfare issues of current dag removal methods through significant reductions in cleaning time and water use. KEY POINTS: • Dag formation on livestock is a major issue for industry and for animal welfare. • Current methods are costly and challenging for operators and the animal. • Enzymes can degrade dag components to aid release with keratinases showing promise. • Dag removal needs to be field tested, and positive business cases must be generated.