Suppression of Interference of Fixative With Odorant Samples in Mass Spectrum Using ICA

• Main Authors: Dani Prasetyawan, Takamichi Nakamoto
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Odorant analysis; odor samples; fixatives; ICA; independent components; correlation coefficient
• Online Access: https://ieeexplore.ieee.org/document/9548911/

Odor sensing enables us to sense odorant stimuli. This sensation causes a deep subconscious response in humans in various ways and represents an indispensable sensation in daily life. However, unwanted compounds called fixatives, which can cause interference and contradiction in odorant analysis especially using mass spectrometry and human subject, are included in odorant samples. Moreover, we do not know the pure odorant mass spectrum. Therefore, it is essential to eliminate the interference of fixatives from the odor sample mass spectrum data and to extract the pure odor mass spectrum. In the present study, we performed independent component analysis (ICA) on the mass spectra of odor samples to remove the influence of fixatives. The advantage of the ICA in separating independent components without a priori knowledge of the original data is useful. The abundance of essential-oil mass spectra that we gathered were utilized as odorant samples. The results were compared with sensory test data from a human subject for a better study of fixative influence. It was revealed that ICA could extract the pure odor sample mass spectrum data without the influence of fixatives, even if the fixatives were added to the odor samples. This study’s outcomes allow us to analyze more odor samples for odorant analysis, not hindered by the influence of unwanted compounds.