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Analysis of Spatial Patterns of Virus-Diseased Tobacco Plants. L. V. Madden, Associate professor, Department of Plant Pathology, Ohio Agricultural Research and Development Center (OARDC), The Ohio State University (OSU) Wooster 44691; T. P. Pirone(2), and B. Raccah(3). (2)Professor, Department of Plant Pathology, University of Kentucky, Lexington 40546; (3)Senior research scientist, Virus Laboratory, Agricultural Research Organization, The Volcani Center, Bet Dagan, Israel. Phytopathology 77:1409-1417. Accepted for publication 6 April 1987. Copyright 1987 The American Phytopathological Society. DOI: 10.1094/Phyto-77-1409.

Epidemics caused by tobacco etch virus (TEV) and tobacco vein mottling virus (TVMV) were monitored in six experimental fields of tobacco in Kentucky from 1983 to 1985. Aggregation of virus-diseased plants was determined by dividing fields into contiguous quadrats and using point pattern (e.g., variance-to-mean ratio and Lloyd’s patchiness [m* / m]) and spatial autocorrelation analyses. Spatial distribution of diseased plants was neither solely clustered nor random, but changed with time during the epidemics. All indices of aggregation indicated a random pattern at the beginning of the epidemics if the first disease assessment was early enough. Patchiness increased to a maximum (m* / m > 2) and then declined throughout the remainder of the epidemics. In many fields, patchiness also indicated randomness (~ 1) by the last assessment time. First-order autocorrelations (rw ra) increased throughout most epidemics, eventually indicating clustering (> 0.23). Autocorrelations often exceeded 0.5 at their maxima. When mean disease density approached 100% incidence, autocorrelations declined at the end of the epidemics. Spatial correlograms suggested a first-order autoregressive process. Iwao’s regression of mean crowding (sensu Lloyd) on mean virus disease density indicated a random pattern of clusters (slope ◊ 1). The sequence of diseased plants per row also was found to change with time based on separate ordinary runs analyses. Percentage of tobacco rows with a clustered pattern increased during most of the epidemics from a low initial level (< 10%); the percentage declined as disease incidence approached its maximum. In agreement with spatial autocorrelation analysis, maximum percentage of rows with a clustered pattern was reached before the last assessment date if disease density was high.

Additional keywords: dispersion, Nicotiana tabacum, potyviruses, quantitative epidemiology.