Artificial intelligence in pest insect monitoring.
|Year of publication||2009|
|Type||Article in Periodical|
|Magazine / Source||Systematic Entomology|
|MU Faculty or unit|
|Description||Global problems of hunger and malnutrition induced us to introduce a new tool for semi-automated pest insect identification and monitoring: an artificial neural network system. Multilayer perceptrons, an artificial intelligence method, seem to be efficient for this purpose. We evaluated 101 European economically important thrips (Thysanoptera) species: extrapolation of the verification test data indicated 95% reliability at least for some taxa analysed. Mainly quantitative morphometric characters, such as head, clavus, wing, ovipositor length and width, formed the input variable computation set in a Trajan neural network simulator. The technique may be combined with digital image analysis.|