Discriminant models for predicting risk of blueberry maggot (Diptera: Tephritidae) infestations in southeastern North Carolina.
Pearson G.A. | Meyer J.R.
Endemic infestations of the blueberry maggot, Rhagoletis mendax Curran, 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 blueberry maggot infestations were measured, and discriminant analysis was used to classify the sites. A quadratic discriminant function using four variables (bush height, percentage of shade, percentage of soil organic matter, and percentage of sand) provided the best discrimination. A two-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 blueberry maggots. 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, we believe that desiccation of the puparia in the soil limits maggot distribution in North Carolina. Thus, altering the crop environment through irrigation may increase the likelihood of an infestation.
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