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ARS Home » Southeast Area » Fort Pierce, Florida » U.S. Horticultural Research Laboratory » Subtropical Insects and Horticulture Research » Research » Publications at this Location » Publication #172430
Title: EFFECT OF REDUCING SAMPLE SIZE ON DENSITY ESTIMATES OF CITRUS RUST MITE (ACARI: ERIOPHYIDAE) ON CITRUS FRUIT: SIMULATED SAMPLING

Author
item Hall, David
item CHILDERS, CARL - UNIV. OF FLORIDA
item EGER, JOE - DOW AGROSCIENCES

Submitted to: Journal of Economic Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/17/2005
Publication Date: 5/1/2005
Citation: Hall, D.G., Childers, C.C., Eger, J.E. 2005. Effect of reducing sample size on density estimates of citrus rust mite (Acari: Eriophyidae) on citrus fruit: simulated sampling. Journal of Economic Entomology. 98:1048-1057.

Interpretive Summary: Reducing the number of samples taken to estimate citrus rust mite densities on oranges reduced the accuracy and precision of estimates. The magnitude of inaccuracies of reduced sampling plans increased as mite densities increased, with inaccuracies generally being biased toward underestimating true densities. Sample allocation influenced the accuracy of density estimates. Examples of the magnitude of inaccuracies associated with reduced plans are presented in the publication. Sampling plans consisting of 48 to 80 samples per 4 ha provided better levels of precision than previously projected. Each of the sampling plans consistently provided mite detection except the plans consisting of 20 or 36 samples per 4 ha, which sometimes did not provide mite detection when the mean density was less than around five mites per cm2. The research results should help growers and researchers optimize the number of samples they take to detect mites and estimate mite densities.

Technical Abstract: The consequence of reducing sample size on the accuracy and precision of estimates of citrus rust mite densities on oranges was investigated. Sampling plans consisting of 360, 300, 200, 160, 80, 36 or 20 samples per 4 ha were evaluated through computer simulations using real count data from datasets of 600 sample units per 4 ha. The original and reduced sampling plans were hierarchical plans with different numbers of sample areas per 4 ha, trees per area, fruit per tree and samples per fruit. For each reduced sampling plan, individual estimates (n=100 simulations per dataset) were sometimes considerably below or above target densities. Accuracy of density estimates generally decreased as sample size was decreased, and the magnitude of inaccuracies increased as mite densities increased. Reducing sample size increased the likelihood of underestimates. Sample allocation influenced the accuracy of density estimates. Reducing the number of areas sampled per 4 ha generally increased the magnitude of inaccuracies more than did reducing the number of samples per area. For a set of original count data with a mean of six mites per cm2, simulations of 36 samples per 4 ha produced individual estimates ranging from zero (mites not detected) up to more than 16 mites per cm2 while 80 samples per 4 ha produced a range of from two up to ten mites per cm2. The simulations indicated sampling plans consisting of 48 to 80 samples per 4 ha provided better levels of precision than previously projected. Each of the sampling plans consistently provided mite detection except the plans consisting of 20 or 36 samples per 4 ha, which sometimes did not provide mite detection when the mean density was less than around five mites per cm2.