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Toward predictable biological control of Liriomyza trifolii (Diptera: Agromyzidae) infesting greenhouse cut chrysanthemums

Heinz, K.M., Nunney, L., Parrella, M.P.
Environmental entomology 1993 v.22 no.6 pp. 1217-1233
Chrysanthemum, Liriomyza trifolii, Diglyphus begini, parasitoids, biological control agents, simulation models, computer techniques
Implementation of augmentative biological control is often hindered by the inability to obtain accurate information on natural enemy release rates that will ultimately yield a salable crop within economic constraints. The purpose of this study was to develop and evaluate a computer model that attempts to predict augmentative releases of the parasitoid Diglyphus begini (Ashmead) (Hymenoptera: Eulophidae) to use for biological control against the serpentine leafminer Liriomyza trifolii (Burgess) (Diptera: Agromyzidae) infesting greenhouse-grown cut chrysanthemums. The model attempts to determine the appropriate release rate necessary to reduce leafminer densities below 1 larvae per 1,000 chrysanthemum leaves within 40 d after planting, after which time aesthetically important foliage forms on chrysanthemums. In the construction of this deterministic model, three simplifying assumptions have been made: (1) there is no insect movement between the greenhouse and outside, (2) greenhouse temperatures are a constant 27 degrees C, and (3) the greenhouse represents a homogeneous environment. Model simulations indicated that successful biological control was unlikely when parasitoid releases are initiated later than 14 d after planting regardless of the release rate. The simulations also demonstrated that D. begini release rates are not linearly related to L. trifolii densities, and that a parasitoid release strategy is not simply the determination of a proper wasp/leafminer ratio. Validation studies of the model's predictions provided mixed results. Following the release rates generated by the model, L. trifolii larval densities were not significantly greater than I per 1,000 leaves 40 d after planting. However, the model did not always track the succession and magnitude of leafminer population fluctuations with statistical accuracy. Two factors probably contributed to these errors in prediction: (1) the assumptions inherent to the model were not met during the validation trials, and (2) the leafminer subroutine of the model could not accurately predict L. trifolii densities in the absence of D. begini. In spite of these errors, leafminer damage to the harvested foliage was significantly lower in the treatments receiving D. begini releases than in the control treatments. In addition, when the model was tested in a commercial cut chrysanthemum greenhouse, L. trifolii was successfully controlled by releases of D. begini, resulting in the production and harvest of a salable cut chrysanthemum crop without the use of any pesticides. Finally, postvalidation reconstruction of the model, to include temperature-dependent variation in life history parameters, increased the predictive power of the model.