title: Characterization of humic substances of different origin by means of mass spectrometry and neural networks.
abstract: Mass spectrometry fingerprinting of humic acids extracted from different soils has been carried out using laser desorption/ionization mass spectrometry (LDI-TOF MS). LDI-TOF MS provides characteristic mass spectra fingerprints for the humic acids of different origin. The information given in the fingerprints was evaluated for natural grouping trends in the samples by neural networks computing tools, such as self-organizing feature map (SOFM). This approach is efficient for recognizing patterns in the humic acids samples independently of their characteristic variability; variability characterizing natural products such as humic substances. The use of multi-layer perceptron artificial neural networks gave a successful classification of the samples.
authors.affiliation: Department of Analytical Chemistry, Nutrition and Food Science, University of La Laguna, Campus de Anchieta, 38071 La Laguna, Tenerife, Spain. empena@ull.es
authors.forename: Eladia M A
authors.initials: EM
authors.lastname: Peña-Méndez
authors.forename: Klára
authors.initials: K
authors.lastname: Novotná
authors.forename: Dagmar
authors.initials: D
authors.lastname: Gajdosová
authors.forename: Venerando
authors.initials: V
authors.lastname: González
authors.forename: Josef
authors.initials: J
authors.lastname: Havel
mesh_terms: D006812:Humic Substances / Q000032:analysis*; D016571:Neural Networks, Computer; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D006812:Humic Substances