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Authors: C. C. Castro 1 ; J. S. Silva 1 ; V. V. Lopes 2 and R. C. Martins 1

Affiliations: 1 Universidade do Minho, Portugal ; 2 INETI - Instituto Nacional de Engenharia Tecnologia e Inovação, Portugal

Keyword(s): Saccharomyces cerevisiae, Morphology, LWUV-VIS-SWNIR reflectance spectroscopy, Singular value decomposition, Classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Laser and Opto-Electronics Signal Processing Applications ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: In this manuscript we explore the feasibility of using LWUV-VIS-SWNIR (340 - 1100 nm) spectroscopy to classify Saccharomyces cerevisiae colony structures in YP agar and YPD agar, under different growth conditions, such as: i) no alcohol; ii) 1 % (v/v) Ethanol; iii) 1 % (v/v) 1-Propanol; iv) 1 % (v/v) 1- butanol; v) 1 % (v/v) Isopropanol; vi) 1 % (v/v) (±)-1-Phenylethanol; vii) 1 % (v/v) Isoamyl alcohol; viii) 1 % (v/v) tert-Amyl alcohol (2-Methyl-2-butanol); and ix) 1 % (v/v) Amyl alcohol. Results show that LWUV-VISSWNIR spectroscopy has the potential for yeasts metabolic state identification once the spectral signatures of colonies differs from each others, being possible to acheive 100% of classification in UV-VIS and VISSWNIR. The UV-VIS region present high discriminant information (350-450 nm), and different responses to UV excitation were obtained. Therefore, high precision is obtained because UV-VIS and VIS-NIR exhibit different kinds of information. In the future, high precisi on analytical chemistry techniques such as mass spectroscopy and molecular biology transcriptomic studies should be performed in order to understand the detailed cell metabolism and genomic phenomena that characterize the yeast colony state. (More)

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Paper citation in several formats:
C. Castro, C.; S. Silva, J.; V. Lopes, V. and C. Martins, R. (2009). YEAST METABOLIC STATE IDENTIFICATION BY FIBER OPTICS SPECTROSCOPY. In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2009) - BIOSIGNALS; ISBN 978-989-8111-65-4; ISSN 2184-4305, SciTePress, pages 169-178. DOI: 10.5220/0001551201690178

@conference{biosignals09,
author={C. {C. Castro}. and J. {S. Silva}. and V. {V. Lopes}. and R. {C. Martins}.},
title={YEAST METABOLIC STATE IDENTIFICATION BY FIBER OPTICS SPECTROSCOPY},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2009) - BIOSIGNALS},
year={2009},
pages={169-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001551201690178},
isbn={978-989-8111-65-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSTEC 2009) - BIOSIGNALS
TI - YEAST METABOLIC STATE IDENTIFICATION BY FIBER OPTICS SPECTROSCOPY
SN - 978-989-8111-65-4
IS - 2184-4305
AU - C. Castro, C.
AU - S. Silva, J.
AU - V. Lopes, V.
AU - C. Martins, R.
PY - 2009
SP - 169
EP - 178
DO - 10.5220/0001551201690178
PB - SciTePress