Development of an FT-NIR Method to Predict Process Cheese Functionality
2021-02
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Development of an FT-NIR Method to Predict Process Cheese Functionality
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2021-02
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Process cheese (PC) production involves using natural cheese, other dairy and non-dairy ingredients, heating, mixing, and cooling to form a final product. The properties of natural cheese, in particular, can be difficult to measure or control, leading to process cheese products with undesirable functional properties that may not be apparent until after cooling. Fourier-Transform Near Infrared (FT-NIR) spectroscopy methods exist for measuring fat and moisture in process cheese (Kapoor & Metzger, 2008) and could be a promising tool for predicting PC properties later in shelf life. In our study, calibrations were developed to correlate FT-NIR spectra of rapidly-cooled PC samples made at benchtop and pilot level production to several functional properties later in shelf life. Properties included heated sauce viscosity, oven melt area, firmness, and fat droplet size. Benchtop and pilot level PC samples were made with cheddar cheese of two different ages, cooked at two mixing speeds, and held at two hold times once final temperature was reached. Sample spectra were collected using a BUCHI NIRFlex N-500 FT-NIR spectrometer (BUCHI Labortechnik AG, CH). NIRCal 5.2 Chemometric Software (BUCHI Labortechnik) was used to correlate the spectra to functional properties using a cross-validation model and partial least squares regression. Across both the benchtop level and pilot level production of PC, 5 and 14 FT-NIR calibration models were created, respectively. Calibration models were developed using the chemometric software calibration wizard and optimized to achieve highest correlation coefficient and minimize standard error by adjusting pretreatments, spectral regions, and quantity of principal components. Many calibration models of different properties (melt area, viscosity, and firmness at different time points) achieved correlation coefficients above 0.6. These findings show that FT-NIR spectroscopy analysis of rapidly-cooled PC samples show potential to be used for predicting fat droplet size, PC sauce viscosity, and oven melt diameter of samples later in shelf life. Further calibrations of molten PC to final properties would show the feasibility of using a rapid, in-line FT-NIR method for process and quality control purposes.
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University of Minnesota M.S. thesis. 2021. Major: Food Science. Advisor: Tonya Schoenfuss. 1 computer file (PDF); 179 pages.
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