Establishing a predictive model for total fat content in Lipomyces starkeyi CBS 1807 by FT-NIR analysis - Ehnström, Irina (SLU/Department of Molecular Sciences, 2018)
This study investigates the potential of using near- infrared spectroscopy (FT-NIR) to establish a predictive model for total fat content in the oleaginous yeast Lipomyces strakeyi CBS 1807. FT-NIR- based quantification allows for rapid lipid determination compared to traditional extraction methods. The advantages of FT-NIR is not only rapid analysis, but also the ease of sample preparation resulting in little or no chemical waste. As FT-NIR is a chemometric analysis technique, it is possible to use a complete spectral structure in contrast to univariate analysis techniques, which only use one spectral datapoint. The spectra examined was within the wavelength range of 3600- 12800 cm-1 and two regions of the NIR spectra were chosen for the construction of the model (8771.2 cm-1 – 7922.6 cm-1) and (5986.3 cm-1 – 5322.9 cm-1). A calibration model was created based on the best RMSECV and R2 values (RMSECV= 3.17, R2 = 92.72) and used for further analysis of lipid content. Validation of the model was carried out by comparing predicted concentrations of lipids, using the model, to actual concentrations obtained from lipid extraction. The result from the calibration curve showed an average percentage error of ~ 24 %. These results show that further improvements are needed to increase the reliability of the model by the addition of a more representative set of test samples.