Abstract
Wheat blast is a devastating disease caused by the
pathotype of
.
is capable of infecting leaves and spikes of wheat. Although symptoms of wheat spike blast (W
B) are quite distinct in the field, symptoms on leaves (W
B) are rarely reported because they are usually inconspicuos. Two field experiments were conducted in Bolivia to characterize the change in W
B and W
B intensity over time and determine whether multispectral imagery can be used to accurately assess W
B. Disease progress curves (DPCs) were plotted from W
B and W
B data, and regression models were fitted to describe the nature of W
B epidemics. W
B incidence and severity changed over time; however, the mean W
B severity was inconspicuous before wheat began spike emergence. Overall, both Gompertz and logistic models helped to describe W
B intensity DPCs fitting classic sigmoidal shape curves. Lin's concordance correlation coefficients were estimated to measure agreement between visual estimates and digital measurements of W
B 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 W
B severity can be quantified using a digital approach based on nongreen pixels. Quantification was precise (0.96 <
> 0.83) and accurate (0.92 < ρ > 0.69) at moderately low to high visual W
B severity levels. Additional sensor-based methods must be explored to determine their potential for detection of W
B and W
B at earlier stages.