Binomial Sequential Classification Sampling Plans for Russian Wheat Aphid (Homoptera: Aphididae) Management: Robustness Varying with Tally Thresholds of Aphids in Sample Units

Abstract

Binomial sequential classification sampling plans were developed for use in classifying populations of the Russian wheat aphid, Diuraphis noxia (Mordvilko), below or above a mean intervention-threshold density (>miT) for management decision making. Based on 4 yr of field data from summer and fall populations on wheat and barley in the northwestern United States, the proportion of tillers with no more than T (tally threshold) aphids (PT) was related to mean aphid density (m) with an empirical model in the form of In[-In(PT)] = a + b ln(m) and the negative binomial distribution. Three mean intervention threshold (mIT) values (one, five, and 10 aphids per tiller) with a series of T values were used to satisfy needs for control of aphid populations varying in density at different crop stages. The sampling plans were evaluated using operating characteristic and average sample number functions computed using the empirical PT − m model or the negative binomial distribution model. The robustness of the sampling plans improved with increasing T values. When using empty tillers (T = 0), the resulting sampling plans were not robust for all mIT values considered. Based on the operating characteristic and average sample number functions, the recommended T values for use are 2-4 for crops at stages before the end of booting given mIT = 1, 15-25 for crops at stages before heading given mIT = 5, and 20-40 for crops at stages after heading or flowering given mIT = 10. Sampling stop lines for each mIT and T are provided along with a discussion of their application to sampling aphid populations in the field.