A binomial sampling method for estimating the density of blueberry aphid, Ericaphis fimbriata (Hemiptera: Aphididae), in commercial highbush blueberry

Abstract

Abstract An accurate and efficient sampling method is an important tool for insect pest management because it allows for consistent measurements across many samples. There are currently no proposed standardised sampling plans or spray thresholds for the aphid Ericaphis fimbriata Richards (Hemiptera: Aphididae) on highbush blueberry (Vaccinium corymbosum Linnaeus) in British Columbia, Canada, despite it being the primary vector for blueberry scorch virus (BlScV). A standard sampling plan for this pest would allow for rapid and consistent measurements of aphid abundance in commercial fields and would allow for more detailed study of the relationship between aphid abundance, damage, and the spread of BlScV. Binomial sampling plans use the presence:absence of a pest within a sample unit to estimate the proportion of infested sample units. Pest density (proportion of measured samples with individuals present) is linked to abundance (number of individuals), and the relationship between these two measures can be modelled mathematically. In the present study, we collected data on aphid density and aphid abundance in six varieties of highbush blueberry grown in the Fraser Valley, British Columbia. These data were used to construct a distribution-free binomial model that, when given a measure of aphid density, can predict aphid abundance within a given sample.