Wine quality testing by using terahertz spectroscopy

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Fen Edebiyat Fakültesi, Kimya Bölümü, Türkiye

Tezin Onay Tarihi: 2018

Öğrenci: GALİP YİYEN

Danışman: OKAN ESENTÜRK

Özet:

In this study, a recently developing technique called Terahertz (THz) Spectroscopy is being tested for its use in wine analysis. The technique is cost effective, reproducible and harmless to the sample. Thus, its applications in pharmacy, security and food analysis have increased recently. THz spectroscopy is a powerful technique since it is able to measure the electric field and, therefore, provides information about frequency dependent absorption coefficient and refractive index. In this thesis, a preliminary study on wine chemicals and on wine quality analysis were carried out by both THz-TDS and FT-THz spectrometers. The steps were i) determination of an optimum sample cell parameters for both THz-TDS and FT-THz measurements for ~10-15% (v/v) ethanol and water mixtures, ii) determination of chemicals that are most effective in wine quality in terms of color, scent and especially the taste of wines, iii) collection of time domain and frequency domain spectra of all the chemicals and water ethanol mixtures, iv) collection of time domain spectra of all the wine samples and v) application of Principle Component Analysis (PCA) to the collected data. The spectra of wine chemicals were collected in pellet form, then in two solution forms (solid solution with polyethylene (PE) as solvent and saturated liquid solution with pure ethanol) in order to determine the main spectral features of the chemicals. Distinct and well resolved absorption features were observed and most of these bands appear to be associated with intramolecular motions. On the other hand, the results of PCA analyses of the absorbance, refractive index and dielectric properties of wines obtained from THz-TDS spectra were used on classification of wines according to their alcohol content, grape types, and more. Though the results are very promising, they show that a controlled sample set and many more wine samples are needed for a better classification