Methods of analysis for georeferenced sample counts of tarnished plant bugs in cotton J. L. Willers Æ J. N. Jenkins Æ J. M. McKinion Æ Pat Gerard Æ K. B. Hood Æ J. R. Bassie Æ M. D. Cauthen Published online: 10 October 2008 Ó Springer Science+Business Media, LLC 2008 Abstract The problem of analyzing georeferenced cotton pest insect samples when a large percentage of the counts are zero is examined. The use of appropriate statistical methods for their analysis is required. To demonstrate this, georeferenced samples (n = 63) of tarnished plant bugs (TPBs; Lygus lineolaris [Palisot de Beauvois] (Het- eroptera: Miridae)) were analyzed by three statistical methods and the results were compared. Correlation analysis of the sample counts with 25 classes of cotton growth derived from an unsupervized classification of multispectral imagery was followed by a complete enumeration analysis comprising three scenarios. The first scenario assumed the insect samples were unstratified. A distribution of sample averages was created by complete enumeration of all combinations of samples taken four at a time. The second scenario used imagery of the cotton fields to allocate the samples among three cotton growth categories (marginal, good or best) derived by a supervized classification of the 25 unsupervized classes. The insect samples associated with these categorical habitats were completely enumerated using allocations of 4, 6, 8 or 10 samples at a time from various sample sizes to determine how different allocations affected the results. The mean was not affected, but the standard deviation decreased with increased allocation sizes in all habitats. The third scenario used the two observers and three habitat categories to create six J. L. Willers (&)  J. N. Jenkins  J. M. McKinion Genetics and Precision Agriculture Research Unit, USDA - ARS, P.O. Box 5367, Mississippi State, MS 39762, USA e-mail: jeffrey.willers@ars.usda.gov P. Gerard Department of Applied Economics and Statistics, Clemson University, Clemson, SC, USA K. B. Hood Perthshire Farms, Gunnison, MS, USA J. R. Bassie Bassie Ag Service, Cleveland, MS, USA M. D. Cauthen Cauthen Entomological Service, Rena Lara, MS, USA 123 Precision Agric (2009) 10:189–212 DOI 10.1007/s11119-008-9085-x