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    Characterization of antimicrobial activities of olive phenolics on yeasts using conventional methods and mid-infrared spectroscopy
    (2018) Canal, Canan; Ozen, Banu; Baysal, A. Handan
    Olive fruit is very rich in terms of phenolic compounds. Antimicrobial activities of various phenolic compounds against bacteria and fungi are well established; however, their effects on yeasts have not been examined. Aim of this study was to investigate the antimicrobial effects induced by olive phenolic compounds, including tyrosol, hydroxytyrosol, oleuropein, luteolin and apigenin against two yeast species, Aureobasidium pullulans and Saccharomyces cerevisiae. For this purpose, yeasts were treated with various concentrations (12.5-1000 ppm) of phenolic compounds and reduction in yeast population was followed with optical density measurements with microplate reader, yeast colony forming units and mid-infrared spectroscopy. All phenolic compounds were effective on both yeasts, especially 200 ppm and higher concentrations have significant antimicrobial activity; however, effects of lower levels depend on the type of phenolic compound. According to mid-infrared spectral data, significant changes were observed in 1200-900 cm-1 range corresponding to carbohydrates of yeast structure as a result of exposure to all phenolic compounds except tyrosol. Spectra of tyrosol and luteolin treated yeasts also showed changes in 1750-1500 cm-1 related to amide section and 3600-3000 cm-1 fatty acid region. Since phenolic compounds from olives were effective against yeasts, they could be used in food applications where yeast growth showed problem. In addition, FTIR spectroscopy could be successfully used to monitor and characterize antimicrobial activity of phenolic compounds on yeasts as complementary to conventional microbiological methods.
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    Characterization of Wine Yeasts during Wine Process using Different Techniques
    (2015) Canal, Canan; Baysal, A. Handan; Ozen, Banu
    Study of the microorganisms that colonise the skin of grapes has been an important topic in microbial taxonomy of especially yeasts associated with vines and vineyards. It is known that yeast microbiota on grapes and in musts is influenced by factors such as climatic conditions, geographical location of the vineyard and grape variety. Molecular methods have been used for the identification of yeasts from wines and the most relevant molecular methods used in the identification of yeast species are based on the variability of the ribosomal genes 5.8S, 18S and 26S. Previous results have demonstrated that the complex ITS regions (non-coding and variable) and 5.8S rRNA gene (coding and conserved) are useful in measuring close fungus phylogenetic relationships. Mid-infrared spectroscopy is a rapid technique which provides highly specific biochemical fingerprints of microorganisms and coupled with different chemometrics analyses offer a wide range of applications including detection, taxonomic level classification and characterization. The objective of this study was identification of yeast flora of 7 wine samples (red, rose and white) through entire wine process from must until the end of fermentation using molecular methods in comparison with cultural methods followed by mid-IR spectroscopic techniques to monitor the diversity of yeasts during a wine process. As a result, identified yeast species included M.pulcherrima (2/19, 11%), P.membranifaciens (3/19, 16%), H.uvarum (1/19, 5%) and S.cerevisiae (13/19, 68%) during the whole process. Multivariate analysis of the data showed that S.cerevisiae isolates formed a cluster which were probably starter cultures and this cluster was generally separated from the other three yeasts which were isolated at the beginning of wine process. Therefore, it was concluded that FTIR could be succesfully used as a complementary method of molecular techniques for differentiation of wine yeast species isolated at different steps of wine process and monitoring the food process microbiologically.
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    MONITORING OF WINE PROCESS AND PREDICTION OF ITS PARAMETERS WITH MID-INFRARED SPECTROSCOPY
    (2015) Canal, Canan; Ozen, Banu
    It was aimed to predict the chemical (ethanol, glycerol, organic acids, titratable acidity, °Brix, sugars, total phenolic and anthocyanin content) and microbiological parameters of red, rose and white wines during their processing from must to bottling using mid-infrared (IR) spectroscopy in combination with one of the multivariate statistical analysis techniques, partial least square (PLS) regression. Various spectral filtering techniques were employed before PLS regression analysis of mid-IR data. The best results were obtained from the second-order derivation for the chemical parameters except for alcohols. PLS models developed for the prediction of some of the chemical parameters have R2 values greater than 0.9, with low root mean square error values; however, prediction of microbial population from mid-IR spectroscopy did not provide accurate results. IR spectroscopic and chemical–chromatographic data were also used to investigate the differences between processing steps, and principal component analysis allowed clear separation of the beginning of the process from the rest.