Epidemics and Crop Yield

There are multiple uses for information on crop yield in relation to disease intensity. For instance, in addition to determining if a (potential) disease control method reduces disease intensity or the rate of disease increase, one can determine if the control has an effect on yield. In an extreme case, it is possible that a control reduces disease severity but does not change crop yield very much. Related to this, one can attempt to make optimal disease management decisions based on the cost of the controls and the benefit obtained from the controls (reduced yield loss and, thus higher income). One can also use this information to make predictions of yield for a given location or region, which is of benefit to crop producers and the individuals and groups who purchase the commodities. The relationship between yield and disease can furthermore be used to determine the economic importance of a given disease in a given region. Through risk assessment, one can use the information to assess the threat of a non-indigenous pathogen to a region or country. In this chapter we discuss general concepts of crop losses and the principles of data collection, followed by a presentation of the more empirical approaches to modeling that have been very popular over the last few decades. In the spirit of model parsimony, we show that a considerable understanding of crop losses can be obtained based on relatively simple models of yield in relation to epidemic and crop variables. In particular, we demonstrate how spatial heterogeneity of disease affects observed disease:yield relationships, and how temporal dynamics of disease increase can be linked to crop yield production.

Chapter topics include:

Introduction

Definitions and Concepts

Data and Relationships

Modeling Yield in Relation to Disease

An Example Analysis

Mechanistic Approaches to Crop Loss Assessment

Spatial Heterogeneity