Mortenson, Aimee Kwong2015-02-202015-02-202014-10https://hdl.handle.net/11299/169992University of Minnesota M.S. thesis. October 2014. Major: Food Science. Advisors: Christine Nowakowski, Baraem Ismail. 1 computer file (PDF); ix, 74 pages, appendices A-B.Understanding sucrose crystallinity is important especially as the food industry has reduced sugar content in products. Robust quantification methods determine crystallinity effects from formulation and/or processing changes. Differential Scanning Calorimetry (DSC) quantifies crystallinity within products, albeit requiring sample destruction. Fourier Transform Infrared (FTIR) spectroscopy can quantify different materials and has the potential of mapping crystallizing areas within a complex food matrix. Additionally, this method can be used to quantify sucrose crystallinity by a non-destructive, rapid means.Currently the methods used to quantify for sucrose crystallinity have been explored in pharmaceutical, lower moisture systems, where complex food matrices are not a factor. The objectives were to create a FTIR method to quantify the amount of crystalline sucrose in mixtures at various concentrations and to determine feasibility of spatial analysis capabilities using FTIR microscope methods.The development of the method was built using model systems of sucrose and carbohydrate blends. Crystallinity was measured via both FTIR and DSC. Samples were freeze-dried and held at different humidity levels to determine which IR peaks were independent of moisture content. IR spectral peaks that correlated best with the DSC measured sucrose crystallinity content were identified. Different calibration methods were concurrently used to obtain the best statistical fit using TQ Analyst® software. FTIR spatial analyses were performed on samples to assess feasibility of the method and commercialized baking mixes were tested to determine efficacy of the bulk method on complex food matrices.Three regions of interest (1087 cm-1, 991 cm-1, and 909 cm-1) were found to have the best Partial Least Squares (PLS) correlation to the crystallinity percentage. A Performance Index of 96.3 and a Root Mean Square Error of Prediction 0.925 were achieved with the three regions. These results show the potential of a robust method to quantify heterogeneous microdomains within foods, without interference from complex matrices. The three regions were statistically comprehensive at defining the variables as a bulk method. The spatial analysis using the FTIR microscope was affected by sucrose orientation, beam intensity, and shifts in peaks. A lower magnification spatial method would be a more applicable use of this method in an inline FTIR technology. The future application of this technology is to combine observed microdomains and correlate them to events such as stickiness or drying rates, for example.enCrystallinityDSCFTIR spectroscopyInline technologyQuantificationSucroseFood scienceThesis or Dissertation