Functional regression in crop lodging assessment with digital images

Abstract

A method is proposed to predict a lodging score for a rice field based only on a digital overhead image of the field. This method converts the two-dimensional image data to a one-dimensional function by computing the average variance of transects across the image as a function of the transect angle. Then principles of functional data analysis are applied to estimate a regression function, and the predicted lodging score is an intercept term plus a measure of overall variability plus the inner product of the regression function and the periodogram of the average variance function. © 2002 American Statistical Association and the International Biometric Society.