Abstract

In total quality management, the main goal is to solve the problems encountered in a way that will not occur again. Experimental design is a statistical technique widely applied in every field and makes many contributions to the improvement of quality. This study aims to perform GMO (Genetically Modified Organism) analysis quickly, reliably and at the lowest cost by providing multi-response optimization of real-time PCR (Polimerase Chain Reaction) parameters to search and properly amplify the GMO gene region in maize using experimental design techniques. In this study, the ct value, which plays a role in the detection of genetically modified products, which are thought to have many risks, and the factors affecting the PCR product concentration and the levels of these factors were determined. The effects of these factors on the response values were determined by the central composite design method, one of the surface response methods, in Minitab.18 program and the factors were optimized. The model was validated by performing validation experiments using optimum factor levels.

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