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Artificial neural networks in online semiautomated pest discriminability: An applied case with 2 Thrips species

Being faced with practical problems in pest identification, we present a methodical paper based on artificial neural networks to discriminate morphologically very similar species, Thrips sambuci Heeger, 1854 and Thrips fuscipennis Haliday, 1836 (Thysanoptera: Thripinae), as an applied case for more general use. | Turkish Journal of Agriculture and Forestry http://journals.tubitak.gov.tr/agriculture/ Research Article Turk J Agric For (2014) 38: 111-124 © TÜBİTAK doi:10.3906/tar-1305-8 Artificial neural networks in online semiautomated pest discriminability: an applied case with 2 Thrips species 1, 2 3 Peter FEDOR *, Eladia Maria PEÑA-MÉNDEZ , Halina KUCHARCZYK , 4 5 1 6 Jaromír VAŇHARA , Josef HAVEL , Martina DORIČOVÁ , Pavol PROKOP 1 Department of Environmental Ecology, Faculty of Natural Sciences, Comenius University, Bratislava, Slovakia 2 Department of Analytical Chemistry, Nutrition, and Food Science, Faculty of Chemistry, University of La Laguna, Campus de Anchieta, La Laguna, Tenerife, Spain 3 Department of Zoology, Faculty of Biology and Biotechnology, Maria Curie-Sklodowska University, Lublin, Poland 4 Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic 5 Department of Chemistry, Faculty of Science, Masaryk University, Brno, Czech Republic 6 Department of Biology, Faculty of Education, Trnava University, Trnava, Slovakia Received: 03.05.2013 Accepted: 09.07.2013 Published Online: 13.12.2013 Printed: 20.01.2014 Abstract: Being faced with practical problems in pest identification, we present a methodical paper based on artificial neural networks to discriminate morphologically very similar species, Thrips sambuci Heeger, 1854 and Thrips fuscipennis Haliday, 1836 (Thysanoptera: Thripinae), as an applied case for more general use. The artificially intelligent system may be successfully applied as a credible, online, semiautomated identification tool that extracts hidden information from noisy data, even when the standard characters have much overlap and the common morphological keys hint at the practical problem of high morphological plasticity. Statistical analysis of 17 characters, measured or determined for each Thrips fuscipennis and T. sambuci specimen (reared from larvae in our laboratories), including 15 .