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Sometimes plant pathologists assess disease intensity when they are primarily interested in other response variables, such as yield loss or toxin concentration in harvested products. In these situations, disease intensity potentially could be considered a surrogate of yield or toxin. A surrogate is a variable which can be used instead of the variable of interest in the evaluation of experimental treatments or in making predictions. Surrogates can be measured earlier, more conveniently, or more cheaply than the variable of primary interest, but the reliability or validity of the surrogate must be shown. We demonstrate ways of quantifying two facets of surrogacy by using a protocol originally developed by Buyse and colleagues for medical research. Coefficient-of-determination type statistics can be used to conveniently assess the strength of surrogacy on a unitless scale. As a case study, we evaluated whether field severity of Fusarium head blight (i.e., FHB index) can be used as a surrogate for yield loss and deoxynivalenol (DON) toxin concentration in harvested wheat grain. Bivariate mixed models and corresponding approximations were fitted to data from 82 uniform fungicide trials conducted from 2008 to 2013. Individual-level surrogacy—for predicting the variable of interest (yield or DON) from the surrogate (index) in plots with the same treatment—was very low. Trial-level surrogacy—for predicting the effect of treatment (e.g., mean difference) for the variable of interest based on the effect of the treatment on the surrogate (index)—was moderate for yield, and only low for DON. Challenges in using disease severity as a surrogate for yield and toxin are discussed.

Is Disease Intensity a Good Surrogate for Yield Loss or Toxin Contamination? A Case Study with Fusarium Head Blight of Wheat