BINOMIAL SAMPLING FOR PREDICTING DENSITY OF RUSSIAN WHEAT APHID (HOMOPTERA, APHIDIDAE) ON WINTER-WHEAT IN THE FALL USING A MEASUREMENT ERROR MODEL

A binomial sampling model was developed for fall sampling of Russian wheat aphid, Diuraphis noxia (Mordvilko), in winter wheat, Triticum aestivum, in Alberta and Montana based on samples of whole plants collected from 24 fields over 2 yr. Percentage infestation was closely related to density, and the relationship was similar between Alberta and Montana. Measurement error regression models were discussed and used to develop new, less biased estimators of prediction equations for the density and a standard error of prediction. Using the new estimators, standard errors for whole plant, tiller, and complete count sampling were compared at various sample sizes. Whole-plant sampling with 80-100 plants per field was recommended for efficiently estimating aphid density. Under this procedure, the standard error was almost-equal-to 30% of the mean throughout most infestation levels. Simulation studies showed that the new estimators were less biased than ordinary least-squares estimators and easily modified to accommodate sampling plans other than simple random sampling.