The Netherlands.- Lice, ticks, and helminths are a concern in livestock and aquaculture production. The impact of these can be reduced by genetic improvement of resistance in livestock and aquaculture populations. For optimum implementation in breeding programs, the economic value of resistance has to be known. A method to predict the economic value of resistance to these parasites was developed.
Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. R0, which is the appropriate breeding goal trait. The emphasis on improvement of R0 and other traits in breeding programs is optimized when based on economic values, but no method exists to derive the economic value of R0 for macroparasitic diseases. Researchers from Wageningen University and Research developed a method to derive the economic value of R0 for macroparasitic diseases. The method was applied to determine the economic value of R0 for sea lice in salmon.
The costs of a disease are the sum of production losses and expenditures on disease control. Depending on farm management, genetic improvement of R0 will lower production losses, expenditures, or both. Depending on the management strategy, the economic value of R0 follows from the reduction in production losses at constant expenditures, or from the reduction in expenditures at constant losses.
Sea lice are one of the major challenges in Norwegian salmon aquaculture. For sea lice in salmon, the economic value was estimated at 0.065€/unit R0/kg production. This implies that a genetic standard deviation improvement of R0 would correspond to a cost reduction of about 130 million € for the whole of Norway. In comparison, costs of treatment sum up to about 380 million €.
KPE (Kasper) Janssen MSc
Kasper Janssen, Hans Komen, Helmut W. Saatkamp, Mart C. M. de Jong and Piter Bijma. Derivation of the economic value of R0 for macroparasitic diseases and application to sea lice in salmon. Genetics Selection Evolution 2018, 50:47. https://doi.org/10.1186/s12711-018-0418-6 https://gsejournal.biomedcentral.com/articles/10.1186/s12711-018-0418-6
Source: Wageningen University