DOI QR코드

DOI QR Code

Modeling and Validation of Population Dynamics of the American Serpentine Leafminer (Liriomyza trifolii) Using Leaf Surface Temperatures of Greenhouses Cherry Tomatoes

방울토마토에서 잎 표면온도를 적용한 아메리카잎굴파리(Liriomyza trifolii) 개체군 밀도변동 모형작성 및 평가

  • Park, Jung-Joon (Department of Applied Biology, Gyeongsang National University) ;
  • Mo, Hyoung-Ho (Institute of Life Science and Natural Resources, Korea University) ;
  • Lee, Doo-Hyung (Department of Entomology, Comstock Hall, Cornell University) ;
  • Shin, Key-Il (Department of Statistics, Hankuk University of Foreign Studies) ;
  • Cho, Ki-Jong (Division of Environmental Science and Ecological Engineering, Korea University)
  • Received : 2012.02.15
  • Accepted : 2012.07.02
  • Published : 2012.09.01

Abstract

Population dynamics of the American serpentine leafminer, Liriomyza trifolii (Burgess), were observed and modeled in order to compare the effects of air and tomato leaf temperatures inside a greenhouse using DYMEX model builder and simulator (pre-programed module based simulation programs developed by CSIRO, Australia). The DYMEX model simulator consisted of a series of modules with the parameters of temperature dependent development and oviposition models of L. trifolii were incorporated from pre-published data. Leaf surface temperatures of cherry tomato leaves (cv. 'Koko') were monitored according to three tomato plant positions (top, > 1.8 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at the same three positions using a self-contained temperature logger. Data sets for the observed air temperature and average leaf surface temperatures were collected (top and bottom surfaces), and incorporated into the DYMEX simulator in order to compare the effects of air and leaf surface temperature on the population dynamics of L. trifolii. The initial population consisted of 50 eggs, which were laid by five female L. trifolii in early June. The number of L. trifolii larvae was counted by visual inspection of the tomato plants in order to verify the performance of DYMEX simulation. The egg, pupa, and adult stage of L. trifolii could not be counted due to its infeasible of visual inspection. A significant positive correlation between the observed and the predicted numbers of larvae was found when the leaf surface temperatures were incorporated into the DYMEX simulation (r = 0.97, p < 0.01), but no significant positive correlation was observed with air temperatures(r = 0.40, p = 0.18). This study demonstrated that the population dynamics of L. trifolii was affected greatly by the leaf temperatures, though to little discernible degree by the air temperatures, and thus the leaf surface temperature should be for a consideration in the management of L. trifolii within cherry tomato greenhouses.

중요 시설해충인 아메리카잎굴파리(Liriomyza trifolii (Burgess))의 개체군 밀도변동모형을 방울토마토 온실내 대기온도와 잎 표면온도를 이용하여 모형 정확성을 비교하였다. 모형 개발에 이용된 생물적 변수들은 기존 발표된 자료들을 사용하였고 모형 작성은 DYMEX$^{(R)}$ 프로그램을 이용하였다. 온도에 따라 상이한 발육기간과 산란수는 생리적 연령으로 표준화시킨 발육완료 분포모형, 연령 특이적 산란수 및 생존율을 비선형회귀 모형에 적합시켜 밀도변동 모형을 개발하였다. 줄내림방식의 방울토마토에서 식물체를 3개의 위치(상단: 지상 1.6 m 이상, 중단: 지상 0.9 - 1.2 m 사이, 하단: 지상 0.3 - 0.5 m 사이)로 나누고 각 위치별로 온실 내 대기 온도와 잎 표면 온도를 기록하였다. 온실 내 잎 표면 최대온도는 대기중 최대온도보다 항상 낮게 유지되고 있었으며, 하단, 상단, 중단의 순으로 온도가 낮아지는 경향을 보였다. 개발된 모형검정을 위한 초기이입 시기와 밀도는 6월초 성충 5마리가 총 50개의 알을 잎에 산란한 것으로 설정하였다. 온실 내 대기 온도와 잎 표면 온도를 이용하여 아메리카잎굴파리 유충 발육모형과 성충의 산란모형을 DYMEX로 프로그래밍하고 모의실험을 하였다. 모의실험결과를 평가하기 위해 기상자료를 수집한 동일한 온실에서 아메리카잎굴파리 유충 밀도를 육안조사 하였으나, 알, 번데기, 성충의 경우 육안조사가 어려워 대상에서 제외하였다. 육안조사결과 밀도변동패턴이 방울토마토 잎 표면 온도를 이용한 모의실험결과 밀도변동패턴과 유사하였다. 육안조사결과와 육안조사시기의 DYMEX모의실험 결과값을 상관분석 한 결과, 육안조사결과와 잎 표면 온도를 이용한 모의실험 결과가 유의한 양의 상관관계를 보였다(r = 0.97, p < 0.01). 대기 온도를 이용한 모의실험 결과와는 유의하지 않은 상관관계를 보였다(r = 0.40, p = 0.18). 본 연구결과 방울토마토 온실에서 아메리카잎굴파리 개체군 밀도변동의 적절한 예측을 위해서는 잎 표면 온도를 고려해야 하는 것으로 나타났다.

Keywords

References

  1. Briere, J.-F., P. Pracros, A.-Y. Le Roux and J.-S. Pierre. 1999. A novel rate model of temperature-dependent development for arthropods. Environ. Entomol. 28: 22-29. https://doi.org/10.1093/ee/28.1.22
  2. Campbell, C.L. and L.V. Madden. 1990. Introduction to Plant Epidemiology. 532 pp. Wiley-Interscience, New York.
  3. Classen, A.T., S.C Hart, T.G. Whitman, N.S. Cobb and G.W. Koch. 2005. Insect infestations links to shifts in microclimate: Important climate change implications. Soil Sci. Soc. Am. J. 69: 2045-2057.
  4. Ferro, D.N., R.B. Chapman and D.R. Penman. 1979. Observations on insect microclimate and insect pest management. Environ. Entomol. 8: 1000-1003. https://doi.org/10.1093/ee/8.6.1000
  5. Kim, J.-K., J.-J. Park, H. Park and K. Cho. 2001. Unbiased estimation of greenhouse whitefly, Trialeurodes vaporariorum, mean density using yellow sticky trap in cherry tomato greenhouses. Entomol. Exp. Appl. 100: 235-243. https://doi.org/10.1046/j.1570-7458.2001.00868.x
  6. Kim. J.-K., J.-J. Park, C.H. Pak, H. Park and K. Cho. 1999. Implementation of yellow sticky trap for management of greenhouse whitefly in cherry tomato greenhouse. J. Kor. Soc. Hort. Sci. 40: 549-553.
  7. Lee, D.H. 2004. Spatial patterns of Liriomyza trifolii and Trialeurodes vaporariorum and their spatial associations in tomato greenhouses. Thesis of MS degree, Korea University. Seoul, Korea.
  8. Leibee, G.L. 1984. Influence of temperature on development and fecundity of Liriomyza trifolii (Burgess) on celery. Environ. Entomol. 13: 497-501. https://doi.org/10.1093/ee/13.2.497
  9. Maywald, G.F., D.J. Kriticos, R.W. Sutherst and W. Bottomley. 2007a. DYMEX model builder, version 3: user's guide. 166pp. Hearne Scientific Software Pty. Ltd. Melbourne 3000, Australia.
  10. Maywald, G.F., W. Bottomley and R.W. Sutherst. 2007b. DYMEX Model simulator, version 3: user's guide. 163pp. Hearne Scientific Software Pty. Ltd. Melbourne 3000, Australia.
  11. Minkenberg, O.P.J.M. 1988. Life history of the agromyzid fly Liriomyza trifolii on tomato at different temperatures. Entomol. Exp. Appl. 48: 73-84. https://doi.org/10.1111/j.1570-7458.1988.tb02301.x
  12. MRI-KMA (Meteorological Research Institute - Korea Meteorological Administration). 1990. Simulation of the greenhouse and plant canopy microclimates (I) - Studies on the meteorological elements and heat fluxes. 81pp. MRI-KMA, Seoul, Korea.
  13. MRI-KMA (Meteorological Research Institute - Korea Meteorological Administration). 1991. Simulation of the greenhouse and plant canopy microclimates (II). 58pp. MRI-KMA, Seoul, Korea.
  14. Park, J.-J., J.-H. Lee, K.-I. Shin, S.E. Lee and K. Cho. 2011a. Geostatistical analysis of the attractive distance of two different sizes of yellow sticky traps for greenhouse whitefly, Trialeurodes vaporariorum (Westwood) (Homoptera: Aleyrodidae), in cherry tomato greenhouses. Aust. J. Entomol. 50: 144-151. https://doi.org/10.1111/j.1440-6055.2010.00796.x
  15. Park, J.-J., K.W. Park, K.-I. Shin and K. Cho. 2011b. Evaluation and comparison of effects of air and tomato leaf temperatures on the population dynamics of greenhouse whitefly (Trialeurodes vaporariorum) in cherry tomato grown in greenhouses. Kor. J. Hort. Sci. Technol. 29: 420-432.
  16. Parrella, M.P. 1987. Biology of Liriomyza. Annu. Rev. Entomol. 32: 201-224. https://doi.org/10.1146/annurev.en.32.010187.001221
  17. RDA (Rural Development Administration). 2001. Tomato cultivation. 270pp. RDA, Suwon, Korea.
  18. RDA (Rural Development Administration). 2002. Compilation of Agricultural Science and Technology in Korea. Vol. 21. 929pp. RDA, Suwon, Korea.
  19. Rosenberg, N.J., B.L. Blad and S.B. Verma. 1983. Microclimate: The Biological Environment. 2nd ed. 495pp. Wiley, New York.
  20. SAS Institute. 2004. SAS/STAT 9.1 User's guide. 4420pp. SAS Institute, Cary, North Carolina.
  21. Southwood, T.R.E. 1978. Ecological methods. 2nd ed. 524pp. Chapman and Hall, London.
  22. Speyer, E.R. and W.J. Parr. 1949. Animal pests. I. Tomato leaf-miner (Liriomyza solani, Hering). Rep. Exp. Res. Stn. Cheshunt. 35: 48-56.
  23. Wagner, T.L., H.I. Wu, P.J.H. Sharpe, R.M. Schoolfield and R.N. Coulson. 1984. Modeling insect development rates: A literature review and application of a biophysical model. Ann. Entomol. Soc. Am. 77: 208-225. https://doi.org/10.1093/aesa/77.2.208
  24. Weibull, W. 1951. A statistical distribution function of wide applicability. J. Appl. Mech. 18: 293-297.
  25. Willmer, P.G. 1982. Microclimate and the environmental physiology of insects. Adv. Insect Physiol. 16: 1-57. https://doi.org/10.1016/S0065-2806(08)60151-4
  26. Zoebisch, T.G., D.J. Schuster, G.H. Smerage and J.L. Stimac. 1992. Mathematical descriptions of oviposition and egg and larval development of Liriomyza trifolii on tomato foliage. Environ. Entomol. 21: 1341-1344. https://doi.org/10.1093/ee/21.6.1341

Cited by

  1. Construction and Evaluation of Cohort Based Model for Predicting Population Dynamics of Riptortus pedestris (Fabricicus) (Hemiptera: Alydidae) Using DYMEX vol.54, pp.2, 2015, https://doi.org/10.5656/KSAE.2015.03.0.007
  2. Research Status and Future Subjects to Predict Pest Occurrences in Agricultural Ecosystems Under Climate Change vol.16, pp.4, 2014, https://doi.org/10.5532/KJAFM.2014.16.4.368