Discriminant model for predicting risk of blueberry maggot (Diptera: Tephritidae) infestations in southeastern North Carolina.
Endemic infestations by Rhagoletis mendax are sparsely distributed in North Carolina because not all blueberry (Vaccinium spp.) fields, or even areas within one field, support these populations. Physical site characteristics of cultivated highbush blueberry fields associated with the presence or absence of R. mendax infestations were measured, and discriminant analysis was used to classify the sites. A quadratic discriminant function using 4 variables (bush height, percentage of shade, percentage of soil organic matter, and percentage of sand) provided the best discrimination. A 2-variable function using only bush height and percentage of shade proved more economical to use and a chart was developed that allows field determination of the probability of an infestation by R. mendax. This method predicted infestation with 100% accuracy on a validation data set. These data represent the first successful application of this forest pest and fire management strategy to a horticultural crop. Because the variables associated with infestation all directly affect the character and temperature dynamics of soils, it is thought that desiccation of the puparia in the soil limits distribution of the pest in North Carolina. Thus, altering the crop environment through irrigation may increase the likelihood of an infestation.