Classification and quantification of beet & cane sugar by using optical spectroscopy and chemometrics

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2022-9

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Eriklioğlu, Hilmi

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Sucrose is one of the main ingredients used in food industry. It is obtained mainly from two different sources; sugar beet and sugar cane. Due to govermental regulations, cane sugar is not allowed to be produced in Turkey. On the other hand, cane sugar can be illegally sold as beet sugar. Since molecular structure of sucrose is same, it is difficult to differentiate sources by using chemical methods. Therefore, developing more practical and affordable methods would be valuable for the food industry. Optical spectroscopy (UV-VIS-NIR) can be a promising technique for detection of differences. In this thesis, sucrose samples (cane, beet) were collected from nine countries to prepare 25% (w/w) sucrose water solutions and their absorbances were recorded (200-1380nm). Results showed that, spectral signature differences were observable between 200-600 nm. It is known that improving the prediction accuracy requires chemometrics, such as linear discriminant analysis (LDA), soft independent modelling of class analogy (SIMCA), k-nearest neighbors (KNN) and classification and regression trees (CART). All methods showed high performance, but LDA gave 100% correct classification with a simple interpretation. In addition, binary mixtures of these sugar were also prepared for quantification analysis. Multiple linear regression (MLR) with Savitsky Golay (SG) and the first derivative, gave the most acceptable results of root mean square error of calibration (RMSEC), prediction (RMSEP) and residual predictive deviation (RPD) values of 2.956, 3.026 and 10.251 respectively. The obtained results seemed promising for the plant source of sucrose to be detected by using UV region and chemometrics.

Subject Keywords

Sucrose, Sugar cane, Sugar beet, Optical spectroscopy, Chemometrics

URI

https://hdl.handle.net/11511/99393

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

H. Eriklioğlu, “Classification and quantification of beet & cane sugar by using optical spectroscopy and chemometrics,” M.S. - Master of Science, Middle East Technical University, 2022.