Content of aliphatic hydrocarbons in limpets as a new way for classification of species using artificial neural networks.
It is demonstrated that biological species like limpets can be classified according to their level of n-alkanes when artificial neural networks are applied. Marine intertidal and subtidal limpets of the Canary Islands (Spain), Patella piperata, Patella candei crenata and Patella ulyssiponensis aspera were selected as bioindicator organisms. Samples were collected at four stations on the coasts of Fuerteventura. Concentration of n-alkanes in the soft tissues of the limpets has been determined by gas chromatography. Data were treated with artificial neural networks (ANNs) and it was found that using suitable architecture of a supervised artificial neural network, the limpets can be successfully distinguished (classified) up to 98%.
Hernández-Borges
J
J
Department of Analytical Chemistry, Faculty of Science, Masaryk University, Kotlárská 2, Brno 611 37, Czech Republic.
Corbella-Tena
R
R
Rodríguez-Delgado
M A
MA
García-Montelongo
F J
FJ
Havel
J
J
D000473:Alkanes / Q000737:chemistry / Q000378:metabolism*; D000818:Animals; D015415:Biomarkers / Q000032:analysis; D002849:Chromatography, Gas; D008974:Mollusca / Q000145:classification* / Q000378:metabolism*; D016571:Neural Networks, Computer; D014874:Water Pollutants, Chemical / Q000032:analysis
D000473:Alkanes; D015415:Biomarkers; D014874:Water Pollutants, Chemical