Interplot Interference: A Model for Planning Field Experiments with Aerially Disseminated Pathogens

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Abstract
A model of disease gradients was used to compute the relative quantities of aerially dispersed, infective inoculum lost from and exchanged between experimental field plots. These quantities were included in a model of disease development to estimate the influence of negative and positive interplot interference on research results. The magnitude of inoculum loss and exchange was a function of plot size, shape, spacing between plots, and steepness of the disease gradient. Neighboring plots that differed markedly in disease severity were more influenced by interplot interference than were plots with similar disease severities. Plot sizes and spacings that limited interplot interference to acceptable levels were identified. The models were quantified and some predictions were validated for potato late blight in New York [USA].

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