Binomial sampling plan for tomato russet mite (Aculopslycopersici (Tryon) (Acari: Eriophyidae) in protected tomato crops

Abstract

AbstractThe tomato russet mite (TRM), Aculops lycopersici, is a worldwide pest of cultivated tomatoes. Currently, no effective biological control agents are available on the market. Therefore, chemical spray applications are required. Fast and reliable detection, monitoring and evaluation of interventions are a challenge, slowing down the development of an appropriate integrated pest management (IPM) strategy. This study describes a binomial sampling plan with the aim to reduce the efforts and costs for an accurate monitoring of A. lycopersici. Sampling was performed by taking pictures of the upper leaf surface with a smartphone through an attached magnification lens. A binomial sampling plan was developed based on the linear relationship between ln(mean TRM densities) and ln(−ln(1‐PT), where PT is the proportion of samples with more than T (tally threshold) mites. The minimum precision threshold of 0.30 was determined for the different models. A resampling for validation of sample plans (RVSP) programme with a fixed sample number was used for validation of the model on an independent data set. The binomial sampling plans were validated at tally thresholds of T = 9 and T = 15 with fixed sample sizes of 15, 20, 25 and 30. Precision levels were satisfying within a range of PT‐values from 0.29 to 0.97 for T = 15 at a fixed sample size of 20. This range was much smaller for T = 9, where the PT‐values range between 0.40 and 0.92 at the same sample size. A binomial sampling model with T = 9 with a fixed sample size of 15, which has the lowest time investment, is feasible for glasshouse tomato growers in practice. However, for the development of pest management programmes, a more intensive and more accurate binomial sampling plan with T = 15 and a sample size of minimum 20 is suggested.