Identification of aqueous pollen extracts using surface enhanced Raman scattering (SERS) and pattern recognition methods

Journal of Biophotonics

Volumn 9, Issue 1-2, 2016, Pages 181-189

  Seifert, Stephan ^a,b   Merk, Virginia ^a   Kneipp, Janina ^a,b  

^a HUMBOLDT UNIVERSITY   (Germany)

^b BAM FEDERAL INSTITUTE FOR MATERIALS RESEARCH AND TESTING   (Germany)

Author keywords

Artificial neural networks (ANN); Multivariate statistics; Pattern recognition; Pollen; Surface enhanced Raman scattering (SERS)

Indexed keywords

MULTIVARIANT ANALYSIS; NEURAL NETWORKS; PATTERN RECOGNITION; PLANTS (BOTANY); RAMAN SCATTERING; SUBSTRATES; SUSPENSIONS (FLUIDS);

BIOCHEMICAL INFORMATION; EXPERIMENTAL PROCEDURE; MULTIVARIATE STATISTICS; PATTERN RECOGNITION METHOD; POLLEN; SPECTRAL CONTRIBUTION; SURFACE ENHANCED RAMAN SCATTERING (SERS); WATER SOLUBLE FRACTION;

SURFACE SCATTERING;

GOLD; METAL NANOPARTICLE; PLANT EXTRACT; WATER;

ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; CLUSTER ANALYSIS; POLLEN; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; RAMAN SPECTROMETRY;

CLUSTER ANALYSIS; GOLD; METAL NANOPARTICLES; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PLANT EXTRACTS; POLLEN; PRINCIPAL COMPONENT ANALYSIS; SPECTRUM ANALYSIS, RAMAN; WATER;

EID: 84953362091     PISSN: 1864063X     EISSN: 18640648     Source Type: Journal    
DOI: 10.1002/jbio.201500176     Document Type: Article

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