Density survey should be carried out for applying integrated pest management strategies, but it is labor-intensive, time- and cost-consuming. Therefore, binomial sampling plans are developed for estimating and classifying the population density of whiteflies late larvae based on the relationship between the mean density per sample unit (7 leaflets) and the proportion of leaflets infested with less than T whiteflies ( ). In this study, models were examined using tally thresholds ranging from 1 to 5 late larvae per 7 leaflets. Regardless of tally thresholds, increasing the sample size had little effect on the precision of the binomial sampling plan. Based on the precision of the model, T=3 was the best tally threshold for estimating the densities of late larvae. Models developed using T=3 validated by Resampling Validation for Sampling Plan program. Above all, the binomial model with T=3 performed well in estimating the mean density of whiteflies in greenhouse tomato.

For effective control of Frankliniella occidentalis, one of polyphagous pests with resistance to insecticides, necessitates the implementation of an integrated pest management strategy. Therefore, estimation of pest density is essential and this is achieved through the application of spatial statistical analysis methods. Because traditional methods often overlook the correlation between sampling locations and data, geostatistical analysis using variogram and kriging is introduced. Variogram provides information on the independent distance between data points. Kriging is a spatial interpolation technique for estimating the values at unsampled locations. For assessing model fitness, cross-validation is used by comparing predicted values with actual observations. This study focuses on the application of geostatistical techniques to estimate F. occidentalis density in hot pepper greenhouse, thereby contributing to making decision.