Browsing by Subject "Gas Chromatography-Mass Spectrometry"

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Open Access
Induction of triacylglycerol production in Chlamydomonas reinhardtii: comparative analysis of different element regimes
(Elsevier, 2014) Çakmak, Z. E.; Ölmez, T. T.; Çakmak, T.; Menemen, Y.; Tekinay, T.
In this study, impacts of different element absence (nitrogen, sulfur, phosphorus and magnesium) and supplementation (nitrogen and zinc) on element uptake and triacylglycerol production was followed in wild type Chlamydomonas reinhardtii CC-124 strain. Macro- and microelement composition of C. reinhardtii greatly differed under element regimes studied. In particular, heavy metal quotas of the microalgae increased strikingly under zinc supplementation. Growth was suppressed, cell biovolume, carbohydrate, total neutral lipid and triacylglycerol levels increased when microalgae were incubated under these element regimes. Most of the intracellular space was occupied by lipid bodies under all nutrient starvations, as observed by confocal microscopy and transmission electron micrographs. Results suggest that sulfur, magnesium and phosphorus deprivations are superior to nitrogen deprivation for the induction triacylglycerol production in C. reinhardtii. On the other hand, FAME profiles of the nitrogen, sulfur and phosphorus deprived cells were found to meet the requirements of international standards for biodiesel.
Open Access
Profiling turkish honeys to determine authenticity using physical and chemical characteristics
(2009) Senyuva H.Z.; Gilbert J.; Silici, S.; Charlton, A.; Dal, C.; Gürel, N.; Cimen, D.
Seventy authentic honey samples of 9 different floral types (rhododendron, chestnut, honeydew, Anzer (thymus spp.), eucalyptus, gossypium, citrus, sunflower, and multifloral) from 15 different geographical regions of Turkey were analyzed for their chemical composition and for indicators of botanical and geographical origin. The profiles of free amino acids, oligosaccharides, and volatile components together with water activity were determined to characterize chemical composition. The microscopic analysis of honey sediment (mellissopalynology) was carried out to identify and count the pollen to provide qualitative indicators to confirm botanical origin. Statistical analysis was undertaken using a bespoke toolbox for Matlab called Metabolab. Discriminant analysis was undertaken using partial least-squares (PLS) regression followed by linear discriminant analysis (LDA). Four data models were constructed and validated. Model 1 used 51 variables to predict the floral origin of the honey samples. This model was also used to identify the top 5 variable important of projection (VIP) scores, selecting those variables that most significantly affected the PLS-LDA calculation. These data related to the phthalic acid, 2-methylheptanoic acid, raffinose, maltose, and sucrose. Data from these compounds were remodeled using PLS-LDA. Model 2 used only the volatiles data, model 3 the sugars data, and model 4 the amino acids data. The combined data set allowed the floral origin of Turkish honey to be accurately predicted and thus provides a useful tool for authentication purposes. However, using variable selection techniques a smaller subset of analytes have been identified that have the capability of classifying Turkish honey according to floral type with a similar level of accuracy. © 2009 American Chemical Society.