고추온실에서 꽃노랑총채벌레(Frankliniella occidentalis)의 이항표본추출법을 개발하였다. 무작위로 선택된 고추를 상, 중 하단으로 나누어, 각 구간에서 세 개의 꽃에 있는 꽃노랑총채벌레를 70% 에탄올이 든 바이알에 털어서 채취한뒤 실체현미경 하에서 밀도를 확인하였다. 꽃노랑총채 벌레의 평균밀도와 3가지 Tally threshold (1, 3, 5) 밀도 이상인 감염비율(PT)간의 이항관계 모형을 평가하여 개발하고 검증하였다. 꽃노랑총채벌 레의 이항표본조사를 위한 최적의 Tally threshold는 3으로 나타났다. 개발된 이항표본추출법의 검증은 이항표본추출법 개발에 사용되지 않은 독 립적 자료를 사용해서 RVSP (Resampling Validation for Sampling Plan) 프로그램으로 진행했으며, 고정 표본 크기(FSS)와 Wald의 순차적 확률비 검정(SPRT)을 사용했다. FSS는 Tally threshold를 3으로, SPRT는 상한값 0.55와 하한값 0.32로 설정해 1000번의 시뮬레이션을 수행했 다. 시뮬레이션 결과 실제 평균과 예측 평균 간의 차이가 없었으므로 개발된 이항표본조사법이 효과적인 것으로 나타났다.

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.