Korean journal of applied entomology (한국응용곤충학회지)

Korean Society of Applied Entomology (한국응용곤충학회)
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Development of a Binomial Sampling Plan for Bemisia tabaci in Paprika Greenhouses

파프리카온실에서 담배가루이의 이항표본조사법 개발

  • Kang, Juwan (Department of Plant Medicine, Gyeongsang National University) ;
  • Choi, Wonseok (Department of Plant Medicine, Gyeongsang National University) ;
  • Park, Jung-Joon (Department of Plant Medicine, Gyeongsang National University)
  • 강주완 (경상대학교 식물의학과) ;
  • 최원석 (경상대학교 식물의학과) ;
  • 박정준 (경상대학교 식물의학과)
  • Received : 2016.08.29
  • Accepted : 2016.10.31
  • Published : 2016.12.01
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Abstract

Infestation of adults and pupae of sweetpotato whitefly, Bemisia tabaci, on paprika (Capsicum annuum var. angulosum) grown in greenhouses in Jinju, Gyeongnam province during 2014was determined by counts of the number of target stage of B. tabaci per leaflet. Binomial sampling plans were developed based on the relationship between the mean density per leaflet (m) and the proportion of leaflets infested with less than T whiteflies ($P_T$), according to the empirical model $(({\ln}(m)={\alpha}+{\beta}({\ln}(-{\ln}(1-P_T))))$. T was defined as the tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaflet in this study. Increasing the sample size, regardless of tally threshold, had little effect on the precision of the binomial sampling plan. Based on the precision of the model, T = 1 was chosen as the best tally threshold for estimating densities of B. tabaci adults and T = 3 was best tally threshold in B. tabaci pupae. Using the results obtained in the greenhouse, a simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) demonstrated the plan's validity. Above all, the binomial model with T = 1 and T = 3 provided reliable predictions of the mean densities of B. tabaci adults and pupae on greenhouse paprika.

경남 진주시 대곡면에 위치한 파프리카(Capsicum annuum var. angulosum) 온실에 피해를 주는 해충인 담배가루이(Bemisia tabaci) 성충과 번데기의 밀도를 엽 당 해충 수로 2014년 조사하였다. 이항표본조사법은 엽 당 담배가루이 성충과 번데기의 밀도(m)와 담배가루이 성충과 번데기가 T마리보다 많이 존재하는 잎의 비율($P_T$)과의 관계를 기본으로 하며, T는 경험적 이항분포모형$(({\ln}(m)={\alpha}+{\beta}({\ln}(-{\ln}(1-P_T))))$에서의 tally threshold로서 본 연구에서는 성충의 경우 1, 2, 3, 4, 5 그리고 번데기는 1, 3, 5, 7을 사용하였다. 표본수 증감은 T와 관계없이 이항분포 모형의 정확도에 영향이 거의 없었다. 이항분포모형의 정확도는 성충의 경우 T=1 일 때, 번데기의 경우 T=3일 때 가장 높았으며, 최적의 tally threshold인 것으로 나타났다. 마지막으로 분석에 사용하지 않은 독립된 자료를 이용하여 개발된 표본조사법의 유효성을 Resampling Validation for Sampling Plan (RVSP) 프로그램으로 평가하였다. 그 결과 파프리카 온실에서 담배가루이 성충과 번데기의 밀도추정에는 T=1 (담배가루이 성충), T=3 (담배가루이 용)인 경우가 적합한 것으로 판단되었다.

Keywords

References

  1. Ahn, K.S., Lee, K.Y., Choi, M.H., Kim, J.W., Kim, G.H., 2001. Effect of temperature and host plant on development and reproduction of the sweet potato whitefly, Bemisia tabaci (Homoptera: Aleyrodidae). Korean J. Appl. Entomol. 40, 203-209.
  2. Byrne, D.N., 1999. Migration and dispersal by the sweet potato whitefly, Bemicia tabaci. Agric. For. Meteorol. 97, 309-316. https://doi.org/10.1016/S0168-1923(99)00074-X
  3. Binns, M.R., Bostanian, N. J., 1990. Robust binomial decision rules for integrated pest management based on negative binomial distribution. AM. Entomol. 36, 50-54. https://doi.org/10.1093/ae/36.1.50
  4. Cho, K., Kang, S.H., Lee, G.S., 2000. Spatial distribution and sampling plans for Thrips palmi (Thysanoptera: Thripidae) infesting fall potato in Korea. Korean J. Appl. Entomol. 93, 503-510.
  5. Choi, W.S., Park, J.J., 2015. Development of sequential sampling plan for Bemisia tabaci in paprika greenhouses. Korean J. Appl. Entomol. Soc. 54, 159-167. https://doi.org/10.5656/KSAE.2015.06.0.019
  6. Elhag, E.A., Horn, D.J., 1983. Resistance of greenhouse whitefly (Homoptera: Aleyrodidae) to insecticides in selected Ohio greenhouses. J. Econ. Entomol. 76, 945-948. https://doi.org/10.1093/jee/76.4.945
  7. Jones, V.P., 1994. Sequential estimation and classification procedures for binomial counts. In: Pedigo LP, Buntin GD (eds) Handbook of Sampling Methods for Arthropods in Agriculture, CRC Press, Boca Raton, FL, pp. 175-205.
  8. Jones, D.R., 2003. Plant viruses transmitted by whitefies. Eur. J. Plant Pathol. 109, 195-219. https://doi.org/10.1023/A:1022846630513
  9. Kono, T., Sugino, T., 1958. On the estimation of the density of rice stems infested by the rice stem borer. Jpn. J. Appl. Entomol. Zoo. 2, 184-188. https://doi.org/10.1303/jjaez.2.184
  10. Kim, J.K., 2009. The population dynamics and management strategies of sweetpotato White fly, Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae). M. D. Dissertation, Gyengsang National University, Jinju, Korea. (in Korean with English abstract).
  11. Lee, M.H., Kang, S.K., Lee, S.Y., Lee, H.S., Choi, J.Y., Lee, G.S., Kim, W.Y., Lee, S.W., Kim, S.G., Uhm, K.B., 2005. Occurrence of the B- and Q-biotypes of Bemisia tabaci in Korea. Korean J. Appl. Entomol. 44, 169-175.
  12. Muniz, M., Nombela, G., 2001. Differential variation in development of the B-and Q-biotypes of Bemisia tabaci (Homoptera: Aleyrodidae) on sweet pepper at constant temperatures. Environ. Entomol. 30, 720-727. https://doi.org/10.1603/0046-225X-30.4.720
  13. Nyrop, J.P., Binns, M., 1991. Quantitative methods for designing and analyzing sampling programs for use in pest management. In: Pimentel D, Hanson A (eds) Handbook of Pest Managemnet in Agriculture, CRC Press, Boca Raton, pp. 67-132.
  14. Naranjo, S.E., Flint, H.M., Henneberry, T.J., 1996. Binomial sampling plans for estimating and classifying population density of adult Bemisia tabaci in cotton. Entomol. Exp. Appl. 80, 343-353. https://doi.org/10.1111/j.1570-7458.1996.tb00947.x
  15. Navas-Castillo, J., Fiallo-Olive, E., Sanchez-Campos, S., 2011. Emergingvirus diseases transmitted by whiteflies. Annu. Rev. Phytopathol. 49, 219-248. https://doi.org/10.1146/annurev-phyto-072910-095235
  16. Perring, T.M., Cooper, A.D., Rodriguez, R.J., Farrar, C.A., Bellow, T.S., 1993. Identification of a whitefly species by genomic and behavioral studies. Science. 259, 74-77. https://doi.org/10.1126/science.8418497
  17. Park, S.H., Lee, J.H., Woo, J.H., Choi, S., Park, S.D., Park, H.H., 2014. Economic Injury Level of Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidate) on Oriental Melon (Cucumis melo L.) in Greenhouse. The Korean Journal of Pesticide Science. 18, 196-201. (in Korean with English abstract). https://doi.org/10.7585/kjps.2014.18.3.196
  18. Sterling, W.L., 1975. Sequential sampling of cotton insect populations. Proceedings of the Beltwide Cotton Production and Research Conference. pp.133-135.
  19. Southwood, T.R.E., 1978. Ecological methods. Second edition. Chapman and Hall, London, England.
  20. Schaalje, G.B., Butts, R.A., Lysyk, T.J., 1991. Simulation studies of binomial sampling: A new variance estimator and density predictor, with special reference to russian wheat aphid (Homoptera: Aphididae). J. Econ. Entomol. 84, 140-147. https://doi.org/10.1093/jee/84.1.140
  21. Saguero-Navas, V.E., Funderburk, J.E., Mack, T.P., Beshear, R.J., Olson, S.M., 1994. Aggregation indices and sample size curves for binomial sampling of flower inhabiting Frankliniella spp. (Thysanoptera: Thripidae) on tomato. J. Econ. Entomol. 87, 1622-1626. https://doi.org/10.1093/jee/87.6.1622
  22. SAS Institute, 1995. SAS user's guide. SAS Institute, Cary, NC.
  23. Song, J.H., Lee, C.H., Kang, S.H., Kim, D.H., Kang, S.Y., Riu, K.Z., 2001. Binomial sampling plans for the citrus red mite, Panonychus citri (Mcgregor) (Acari: Tetranychidae) on satsuma mandarin groves in Jeju. Korean J. Appl. Entomol. 40, 197-202.
  24. Taylor, L.R., 1961. Aggregation, variance and the mean. Nature 189, 732-735. https://doi.org/10.1038/189732a0
  25. Tonhasca, J.R., Palumbo, J.C., Byrne, D.N., 1994. Binomial sampling plans for estimating Bemisia tabaci populations in cantaloupes. Researches on population ecology. 36, 181-186. https://doi.org/10.1007/BF02514934
  26. Van Lenteren, J.C., Woets, J.V., 1988. Biological and integrated pest control in greenhouses. Ann. Rev. Entomol. 33, 239-269. https://doi.org/10.1146/annurev.en.33.010188.001323
  27. Water, W.E., 1955. Sequential sampling in forest insect surveys. Forest. Sci. 1, 68-79.