Browsing by Subject "zingerone"
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(2012)This thesis is constructed as a part of a larger research project aiming to increase understanding of polyketone reductases (PKR) and develop applications from them. PKRs are enzymes in biosynthetic pathways leading to several aromatic secondary metabolites in plants. The previous work in the research group has led to establishment of several callus cultures from plants belonging to the genus Rubus in the family Rosaceae. The aim in the experimental part of this thesis is the identification and semi-quantitation of raspberry ketone (RK) and related aromatics in the cell suspension cultures initiated from the previously established callus cultures. RK is biosynthetically produced by reduction of p-hydroxybenzalacetone (p-OH-BA) by benzalacetone reductase (BAR). As a part of the experimental work, p-OH-BA has to be chemically synthetized and analysed. Special emphasis is placed to experiment, develop and validate an extraction method for phenolic compounds using ASE 200 working station. In the review part of this thesis, the basic procedures of chemical analysis are described, optimization and validation of analytical methods are discussed, and lastly studies related to raspberry ketone (RK) are summarized. The detection limit is 0.73 µg/ml for RK with the established UPLC-UV method, and the quantitation limit (QL) is 2.22 µg/ml. At the QL, the standard deviation of the extraction method is 8.9 % and the results are 6.4 % higher than expected. At the high end of the standard curve the extraction results are 18.7 % higher than expected. Some changes are proposed to optimize the method. Analysis of the cell line extracts with the established UPLC-UV method did not readily reveal any of the studied compounds. Although the interpretation of the results of the MS experiment is still underway, RK was detected from the arctic bramble cell line Ra15. Also, a possible derivative of zingerone was detected from cloudberry cell line extract even without the corresponding standard compound. This shows the power of the MS in metabolite profiling, and gives a course for future studies.
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