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http://dx.doi.org/10.7235/hort.2012.12021

A Binomial Sampling Plans for Aphis gossypii (Hemiptera: Aphididae) in Greenhouse Cultivation of Cucumbers  

Kang, Taek Jun (Entomology Program, Department of Agricultural Biotechnology, Seoul National University)
Park, Jung-Joon (Department of Applied Biology, Gyeongsang National University)
Cho, Kijong (Division of Environmental Science and Ecological Engineering, Korea University)
Lee, Joon-Ho (Entomology Program, Department of Agricultural Biotechnology, Seoul National University)
Publication Information
Horticultural Science & Technology / v.30, no.5, 2012 , pp. 596-602 More about this Journal
Abstract
Infestations of Aphis gossypii per leaf in greenhouse cultivation of cucumbers were investigated to develop binomial sampling plans. An empirical $P_T-m$ model, $ln(m)={\alpha}+{\beta}ln[-ln(1-P_T)]$, was used to evaluate relationship between the proportion of infested leaves with ${\leq}$ T aphids per leaf ($P_T$) and mean aphid density (m). Tally thresholds (T) were set to 1, 3, 5, 7, and 9 aphids per leaf to find appropriate T in greenhouse cultivation of cucumbers. Increasing sample size had little effect on the precision of the binomial sampling plan. However, the precision increased with tally threshold. The binomial model with T = 5 provided appropriate predictions of the mean densities of A. gossypii in the greenhouse cultivation of cucumbers. Using a binomial model with T = 5 (sample size = 200), a wide range of densities (1.2 - 222.8 aphids per leaf) could be estimated with precision levels of 0.346 - 0.380 for $P_T$ values between 0.15 and 0.96. Binomial models were validated at T = 5 and 7 using 12 independent data sets. Both binomial models were robust and adequately described aphid densities; most of the independent sampling data fell within 95% confidence intervals around the prediction model.
Keywords
cotton aphid; tally threshold;
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1 Anscombe, F.J. 1948. On estimating the population of aphids in a potato field. Ann. Appl. Biol. 35:567-571.   DOI
2 Baek, S., K. Cho, Y.H. Song, and J.-H. Lee. 2009. Sampling plans for estimating pepper fruit damage levels by Oriental tobacco budworm, Helicoverpa assulta (Guenee), in hot pepper fields. J. Asia Pac. Entomol. 12:175-178.   DOI
3 Binns, M.R. and J.P. Nyrop. 1992. Sampling insect populations for the purpose if IPM decision making. Annu. Rev. Entomol. 37:427-453.   DOI   ScienceOn
4 Binns, M.R. and N.J. Bostanian. 1990. Robust binomial decision rules for integrated pest management based on negative binomial distribution. Am. Entomol. 36:50-54.   DOI
5 Binns, M.R., J.P. Nyrop, and W. van der Werf. 2000. Sampling and monitoring in crop protection: the theoretical basis for developing practical decision guides. CABI Publishing, Wallingford, UK.
6 Bligaard, J. 2001. Binomial sampling as a cost efficient sampling method for pest management of cabbage root fly (Dipt., Anthomyiidae) in cauliflower. J. Appl. Ent. 125:155-159.   DOI
7 Cho, K., J.H. Lee, J.-J. Park, J.K. Kim, and K.B. Uhm. 2001. Analysis of spatial pattern of Frankliniella occidentalis (Thysanoptera: Thripidae) on greenhouse cucumbers using dispersion index and spatial autocorrelation. Appl. Entomol. Zool. 36:25-32.   DOI   ScienceOn
8 Cho, K. and J.-J. Park. 1997. Sequential estimation for binomial counts. Natural Resource Res. 5:185-192.
9 Cho, K., J.-J. Park, H. Park, and Y.H. Kim. 1998. Binomial Sampling Plans for Estimating Tetranychus urticae (Acari: Tetranychidae) Populations in Glasshouse Rose Grown by Arching Method. Kor. J. Appl. Entomol. 37:151-157.
10 Cho, K., S.H. Kang, and G.S. Lee. 2000. Spatial distribution and sampling plans for Thrips palmi (Thysanoptera: Thripidae) infesting fall potato in Korea. J. Econ. Entomol. 93:503-510.   DOI   ScienceOn
11 Jones, V.P. 1994. Sequential estimation and classification procedure for binomial counts, p. 175-205. In: L.P. Pedigo and G.D. Buntin (eds.). Handbooks of sampling methods for arthropods in agriculture. CRC, Boca Raton, FL.
12 Kapatos, E.T., E.T. Stratopoulou, A. Sahinoglou, J.A. Tsitsipis, and D.P. Lycouresis. 1996. Development of an optimum sampling plan for the population of Aphis gossypii (Hom., Aphididae) on cotton in Greece. J. Appl. Entomol. 120:245-248.   DOI
13 Lee, D.H, J.-J. Park, J.-H. Lee, Y.H. Song, and K. Cho. 2005. Development and validation of binomial sampling plans for estimating leafmine density of Liriomyza trifolii (Diptera: Agromyzidae) in greenhouse tomatoes. Appl. Entomol. Zool. 40:579-587.   DOI
14 Kim, J.K., J.-J. Park, H. Park, and K. Cho. 2001. Unbiased estimation of greenhouse whitefly, Trialeurodes vaporarioum, mean density using yellow sticky trap in cherry tomato greenhouses. Entomol. Exp. Appl. 100:235-243.   DOI
15 Kono, T. and T. Sugino.1958. On the estimation of the density of rice stem borer. Jpn. J. Appl. Entomol. Zool. 2:184-188.   DOI
16 Kuno, E. 1991. Sampling and analysis of insect populations. Annu. Rev. Entomol. 36:285-304.   DOI   ScienceOn
17 Nachman, G. 1984. Estimates of mean population density and spatial distribution of Tetranychus urticae (Acarina: Tetranychidae) and Phytoseiulus persimilis (Acrina: Phytosiidae) based upon the proportion of empty sampling unit. J. Appl. Ecol. 21:903-913.   DOI
18 Naranjo, S.E. and W.D. Hutchison. 1997. Validation of arthropod sampling plans using a resampling approach and analysis. Am. Entomol. 43:48-57.   DOI
19 Naranjo, S.E., H.M. Flint, and T.J. Henneberry. 1996. Binomial sampling plans for estimating and classifying population density of adult Bemisia tabaci in cotton. Entomol. Exp. Appl. 80: 343-353.   DOI
20 Nyrop, J.P. and M.R. Binns. 1991. Quantitative methods for designing and analyzing sampling program for use pest management, p. 67-132. In: D. Pimental (ed.). Handbook of pest management in agriculture. Vol. II. 2nd ed. CRC, Boca Raton, FL.
21 Salguero Navas, V.E., J.E. Funderburk, T.P. Mack, R.J. Beshear, and S.M. Olson. 1994. Aggregation indices and sample size curves for binomial sampling of flower in habiting Frankliniella species (Thysanoptera: Thripidae) on tomato. J. Econ. Entomol. 87:1622-1626.   DOI
22 Nyrop, J.P., A.M. Agnello, J. Kovach, and W.H. Reissig. 1989. Binomial sequential classfication sampling plans for European red mite (Acari: Teternychidae) with special reference to performance criteria. J. Econ. Entomol. 82:482-490.   DOI
23 Park, Y.-L. and J.J. Tollefson. 2006. Development and economic evaluation of spatial sampling plans for corn rootworm Diabrotica spp. (Col., Chrysomelidae) adults. J. Appl. Entomol. 130:337-342.   DOI
24 Pedigo, L.P. 1994. Introduction to sampling arthropod populations, p. 1-11. In: L.P. Pedigo and G.D. Butin (eds.). Handbook of sampling methods for arthropods in agriculture. CRC, Boca Raton, FL.
25 SAS Institute. 2004. SAS/STAT User's Guide for Personal Computer, Version 9.2. SAS Institute, Cary, NC.
26 Schaalje, G.B., R.A. Butts, and T.J. Lysyk. 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.   DOI
27 Shepard, M. 1980. Sequential sampling plans for soybean arthropods, p. 79-93. In: M. Kogan and D.C. Herzog (eds.). Sampling methods in soybean entomology. Springer, NY.
28 Silver, A.R.J., H.F. van Emden, and M. Battersby. 1995. A biochemical mechanism of resistance to pirimicarb in two glasshouse clones of Aphis gossypii. Pesticide Sci. 43:21-29.   DOI
29 Sokal, R.R. and F.J. Rohlf. 1981. Biometery. 2nd ed. W.H. Freeman, San Francisco.
30 Song, J.H. 2003. Development of optimum sampling plan of citrus red mite based on its spatial distribution in Jeju citrus groves. PhD Diss. Jeju National University, Jeju, Korea.
31 Southwood, T.R.E. 1978. Ecological Methods. 2nd ed. Chapman & Hall, London
32 Taylor, L.R. 1961. Aggregation, variance, and the mean. Nature 189:732-735.   DOI
33 Wilson, L.T. and P.M. Room. 1983. Clumping patterns of fruit and arthropods in cotton with implications for binomial sampling. Environ. Entomol. 12:50-45.   DOI