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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)
  • 투고 : 2012.02.07
  • 심사 : 2012.07.09
  • 발행 : 2012.10.31

초록

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.

키워드

참고문헌

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피인용 문헌

  1. Sequential Sampling Plan for Aphis gossypii (Hemiptera: Aphididae) based on Its Intra-plant Distribution Patterns in Greenhouse Cucumber at Different Growth Stages pp.2287-545X, 2015, https://doi.org/10.5656/KSAE.2015.10.0.046