International Journal of Pest Management (2011) 57, 205-216

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Federico Lessio, Enrico Borgogno Mondino and Alberto Alma (2011)
Spatial patterns of Scaphoideus titanus (Hemiptera: Cicadellidae): a geostatistical and neural network approach
International Journal of Pest Management 57 (3), 205-216
Abstract: The spatial distribution of the leafhopper Scaphoideus titanus Ball, the vector of the pathogen Flavescence dorée of grapevine, was studied in the Asti Province (Piedmont) Italy. Field sampling of adults was carried out using yellow sticky traps both in vineyards subjected to different pest management regimes, and in woods containing American grapevines. The spatial correlation of S. titanus captures was studied using geostatistical analyses. An artificial neural network (ANN) was designed to operate as a spatial predictor driven by external factors (elevation, slope, height above channel, agricultural communities, perimeter-to-area ratio, potential solar radiation, and pest management) for estimating the population density of the leafhopper. The captures were spatially related up to 210 m: the variogram fitting was significant, but resulted in low R 2 values. The ANN achieved a significant generalization of the infestation levels of S. titanus, permitting prediction maps based upon simulated pest management scenarios to be obtained. The most important factors affecting S. titanus population density were pest management, and secondarily agricultural communities.
(The abstract is excluded from the Creative Commons licence and has been copied with permission by the publisher.)
Link to article at publishers website
Database assignments for author(s): Alberto Alma

Research topic(s) for pests/diseases/weeds:
population dynamics/ epidemiology

Pest and/or beneficial records:

Beneficial Pest/Disease/Weed Crop/Product Country Quarant.

Scaphoideus titanus Grapevine (Vitis) Italy