Tripartite Sequential classification Sampling Plans tomonitor Tetranychus urticae Pest mite Population through time

Abstract

The objective of this study was to develop and evaluate a tripartite sequential classification sampling plans to monitor pest mite Tetranychus urticae (Koch, 1836) through time.Three tripartite plans using Wald's Sequential Probability Ratio Test based on tally 0 and 5 binomial counts were developedfor use at different times. For each Wald’s plan, three hypotheses were tested and three probabilities (Pdeci; i=1; 2; 3) for making decision were simulated.Tripartite sequential classification sampling plans with tally 0 binomial counts was compared to dichotomous plans repeated every Δt and after 2Δt.Performance of monitoring protocols were studied by monitoring height T. urticae populations with logistic growth. The results showed that tripartite classification reduced from 30 to 40% of the expected bouts than dichotomous sampling plans after Δt and 2Δt days and reduce sampling cots. Monitoring protocol B reduced the probability of intervening and produced more sample bouts and more samples, which resulted in lower expected and 95th percentiles for density at intervention and expected loss compared to protocol A.The use of tripartite classification plan requiredadjustment of the cd2 and cd1 values to accomplish an efficient integrated pest management during growth season.