Development and Validation of a Fixed-Precision Sequential Sampling Plan for Aster Leafhopper (Homoptera: Cicadellidae) in Carrot

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Abstract

From 1995 to 1997, data sets (351) were collected from 30 fields in central and southern Minnesota to determine the most efficient, fixed-precision, sequential sampling plan for density estimation of aster leafhopper, Macrosteles quadrilineatus Forbes, in carrot, Daucus carota (L.). Conventional and organic farms were sampled to obtain a range of leafhopper densities likely to be encountered with various management practices. Densities ranged from 0.01 to 6.97 leafhoppers per sweep. Taylor's a and b parameters were estimated from 266 data sets and used in conjunction with 15 independent data sets to validate the sampling plan with resampling software. The results showed that, for a density range of 0.01-1.61 leafhoppers per sweep, 20 samples of 10 sweeps each must be taken to achieve an average precision level of 0.25 (SE/mean). In subsequent analyses, results were partitioned into low (<0.17 leaflioppers per sweep) and high (≥0.17 leafhoppers per sweep) density data sets. Further analysis, using modified precision levels, showed that either 86 samples of 10 sweeps each (low densities) or 5 samples of 10 sweeps each (high densities) were needed to achieve the desired average precision level of 0.25. Implementation of this plan requires growers to collect a minimum of 5 samples of 10 sweeps each; if the mean density ≥0.17, then mean actual precision ≈0.25, and no further sampling is necessary. For densities <0.17, an additional 5 samples of 10 sweeps each should be taken, and final density estimated (precision may be >0.25). Final density can be compared with the aster yellows index for control guidelines.

Original languageEnglish (US)
Pages (from-to)1463-1468
Number of pages6
JournalEnvironmental entomology
Volume27
Issue number6
DOIs
StatePublished - Dec 1998

Keywords

  • Carrot
  • Integrated pest management
  • Macrosteles quadrilineatus
  • Resampling software
  • Sequential sampling

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