Testing the Taguchi method to design and analyze integrated disease management strategies, for the control of late blight (Phytophthora infestans) on potato

BACKGROUND
Identifying robust integrated pest management (IPM) strategies requires the testing of multiple factors at the same time and assessing their combined effects e.g., on disease control. This makes field-based experiments large, resource intensive and expensive. Hence, there are limits to the number of treatment combinations that can be practically tested under field conditions. Taguchi approach to design of experiments (DOE) or the Taguchi approach is commonly employed to enhance the quality of industrial products. It uses smaller experiments than classical DOE but its applicability to late blight research, and agricultural research, has not been widely evaluated.

RESULTS
Two existing datasets, following the same protocol and investigating the effectiveness of different IPM treatments to control late blight, caused by Phytophthora infestans, on potato, were used to test the Taguchi approach. Disease severity was quantified as area under the disease progress curve (AUDPC). The method could accurately predict the performance of a cultivar and fungicide-based integrated disease management strategy from a small dataset and identified cultivar as a key factor for disease control. Linear regression demonstrated a strong and statistically significant relationship between AUDPC values collected during the original experiments and the predicted disease severity values generated using the Taguchi method.

CONCLUSIONS
The Taguchi approach can accurately predict disease severity, with predicted values similar to those collected during the original experiments. Moreover, associated analyses identified the most effective treatment combinations and the factors that exert the greatest influence on disease control. The relevance of this approach when designing and interpreting IPM strategies is discussed.