Are Predatory Mites Effective as Biological Control Agents to Suppress Oligonychus ilicis (Acari: Tetranychidae) in Blueberry Plantings?
Southern Red Mite, Oligonychus ilicis McGregor (Acari: Tetranychidae), is an important polyphagous spider mite pest that causes economic damage to many ornamentals and fruit crops. Blueberry growers in the Southeastern United States, including Florida and Georgia, have experienced severe losses due to outbreaks of O. ilicis, and a series of research has been conducted using a few acaricides to suppress O. ilicis population. Predatory mites are an important management tool used for controlling spider mites; however, predators have not been successfully evaluated in blueberry systems. Amblyseius swirskii, Phytoseiulus persimilis, and Neoseiulus californicus (Acari: Phytoseiidae) are among the most economically important arthropod agents used in augmentative biological control. To evaluate the potential of these three predatory mites for use in blueberry plantings, we conducted experiments under controlled conditions in the greenhouse and laboratory. In preliminary laboratory experiments, P. persimilis and N. californicus reduced O. ilicis motile stages, indicating the potential of the two species to suppress the O. ilicis population. Under greenhouse conditions, N. californicus and P. persimilis reduced the oviposition rate after 7 days of release and the number of motile stages after 14 days of release. This is the first report of using Pytoseiidae mites to suppress O. ilicis in blueberry systems.
Steps to reproduce
The statistical analyses were performed using R versão 3.6.1 (Team, R. C. (2019). For the Laboratory bioassays the consumption rates of eggs and motile stages were analyzed using Generalize Linear Model (GLM) procedure assuming binomial distribution. The difference between treatments (consumption rate of eggs and motiles) for each time of evaluation was compared by using Tukey`s HSD test (p<0.05). For the greenhouse experiments Eggs, motiles, and total number of eggs and motiles were analyzed using Generalize Linear Mixed Model (GLMM) with the negative binomial distribution. We consider the treatments as fixed variables and the two dates of carrying out the experiment as aleatory variables. The first sample was considered as covariable to analyze the total number of eggs and motiles. The function “glmer.nb” (package ‘MASS’) was utilized and the averages were compared utilizing glht” function of multcomp packages (Hothorn et al. 2008). To verify the quality of the estimated model, quantile residuals were generated from 1,000 simulations of the models used with “simulateResiduals” function using the DHARMa package version 0.3.3.0 (Hartig 2020).