Objective To predict seasonal density fluctuation of Blattella germanica (B. germanica) using autoregressive integrated moving average (ARIMA) model and to assess the pesticide resistance in B. germanica.
Methods Sticky trap method was used for monitoring B. germanica density and infestation rate. ARIMA model was used to predict B. germanica density. Pesticide resistance of B. germanica was determined with residual film method and diagnostic dose method. Enzyme activities of B.germanica were determined with physiological and biochemical method.
Results The average density of B. germanica was 0.17 and the mean infestation rate of the pest was 7.63% for random sampling sites in farmer′s markets, restaurants, hotels, hospitals, and residential buildings in Tangshan city of Hebei province during 2007 – 2017; there were significant between sampling-sites differences in the density (F = 5.693) and the infestation rate (χ2 = 590.886) of B. germanica (both P < 0.01). The highest seasonal density (0.28) per sticky trap and infestation rate (11.36%) of B. germanica were observed in August of a year. A best-fitting model of ARIMA (0, 1, 3) × (0, 1, 1)12 was established for prediction of seasonal density fluctuation of B. germanica. Different levels of resistance to various pesticides were detected in the B. germanica trapped in the city. The activity of glutathione-S-transferase (GSTs) of the wild strains of B. germanica was not significantly different from that of the susceptible strain; the activity of multifunctional oxidase (MFO) and carboxylesterase (CarE) of the wild strains were higher than those of the susceptible strain but the activity of acetylcholinesterase (AChE) was lower than that of the susceptible strain.
Conclusion ARIMA model could be used in prediction of B. germanica density. Pesticide resistance is prevalent in B. germanica trapped in Tangshan city and the resistance is related to increased activity of MFO and CarE in wild strains of the pests.
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