Temporal Dynamics of Wheat Blast Epidemics and Disease Measurements Using Multispectral Imagery

Abstract

Wheat blast is a devastating disease caused by the Triticum pathotype of Magnaporthe oryzae. M. oryzae Triticum is capable of infecting leaves and spikes of wheat. Although symptoms of wheat spike blast (WSB) are quite distinct in the field, symptoms on leaves (WLB) are rarely reported because they are usually inconspicuos. Two field experiments were conducted in Bolivia to characterize the change in WLB and WSB intensity over time and determine whether multispectral imagery can be used to accurately assess WSB. Disease progress curves (DPCs) were plotted from WLB and WSB data, and regression models were fitted to describe the nature of WSB epidemics. WLB incidence and severity changed over time; however, the mean WLB severity was inconspicuous before wheat began spike emergence. Overall, both Gompertz and logistic models helped to describe WSB intensity DPCs fitting classic sigmoidal shape curves. Lin’s concordance correlation coefficients were estimated to measure agreement between visual estimates and digital measurements of WSB intensity and to estimate accuracy and precision. Our findings suggest that the change of wheat blast intensity in a susceptible host population over time does not follow a pattern of a monocyclic epidemic. We have also demonstrated that WSB severity can be quantified using a digital approach based on nongreen pixels. Quantification was precise (0.96 < r> 0.83) and accurate (0.92 < ρ > 0.69) at moderately low to high visual WSB severity levels. Additional sensor-based methods must be explored to determine their potential for detection of WLB and WSB at earlier stages.