Analysis of Discrimination Techniques for Low-Cost Narrow-Band Spectrofluorometers

Autor: Sergio Pérez, Albert-Miquel Sánchez, Jaume Piera, Ismael F. Aymerich
Rok vydání: 2015
Předmět:
Normalization (statistics)
Signal processing
Engineering
Time Factors
010504 meteorology & atmospheric sciences
Noise reduction
Wavelet Analysis
lcsh:Chemical technology
computer.software_genre
01 natural sciences
Biochemistry
Article
Fluorescence
Analytical Chemistry
Transformation
Cassification
Wavelet
lcsh:TP1-1185
14. Life underwater
Sensitivity (control systems)
Electrical and Electronic Engineering
Low-cost sensors
Instrumentation
0105 earth and related environmental sciences
Block (data storage)
Principal Component Analysis
Denoising
business.industry
Taxonomic discrimination
010401 analytical chemistry
Process (computing)
Signal Processing
Computer-Assisted
Reference Standards
Atomic and Molecular Physics
and Optics
0104 chemical sciences
Normalization
Spectrometry
Fluorescence
Transformation (function)
classification
Costs and Cost Analysis
Data mining
business
computer
Algorithms
Zdroj: Sensors
Volume 15
Issue 1
Pages 611-634
Sensors, Vol 15, Iss 1, Pp 611-634 (2014)
Sensors (Basel, Switzerland)
Digital.CSIC. Repositorio Institucional del CSIC
instname
ISSN: 1424-8220
2011-3048
Popis: 24 pages, 12 figures, 12 tables
The need for covering large areas in oceanographic measurement campaigns and the general interest in reducing the observational costs open the necessity to develop new strategies towards this objective, fundamental to deal with current and future research projects. In this respect, the development of low-cost instruments becomes a key factor, but optimal signal-processing techniques must be used to balance their measurements with those obtained from accurate but expensive instruments. In this paper, a complete signal-processing chain to process the fluorescence spectra of marine organisms for taxonomic discrimination is proposed. It has been designed to deal with noisy, narrow-band and low-resolution data obtained from low-cost sensors or instruments and to optimize its computational cost, and it consists of four separated blocks that denoise, normalize, transform and classify the samples. For each block, several techniques are tested and compared to find the best combination that optimizes the classification of the samples. The signal processing has been focused on the Chlorophyll-a fluorescence peak, since it presents the highest emission levels and it can be measured with sensors presenting poor sensitivity and signal-to-noise ratios. The whole methodology has been successfully validated by means of the fluorescence spectra emitted by five different cultures. © 2014 by the authors; licensee MDPI, Basel, Switzerland
This work was supported by the Spanish National Research Council (CSIC) under the project ANERIS (PIF-015-1), by the Ministerio de Ciencia e Innovación under Mestral Project CTM2011-30489-C02-01, and by the European Commission under Citclops Project FP7-ENV-308469. Ismael F. Aymerich is currently funded by the European Regional Development Fund (ERDF) and the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC) and under the project TACTICA. Sergio Pérez was involved in the SICUE program and funded by the Séneca fellowship, given by the Ministerio de Educación, during the development of this project
Databáze: OpenAIRE
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