Rapid Method for Classification of Cheddar Cheese Based on Flavor Quality using Infrared Spectroscopy
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Date
2007-04-02T13:28:13Z
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Abstract
Flavor quality of Cheddar cheese significantly influences its consumer acceptance, price and food processing application. Cheese flavor is currently determined using trained human tasting panels. This approach is expensive and time consuming. Rapid and high-throughput instrumental methods for predicting the flavor quality of Cheddar cheese would save time and money for the cheese industry. The objective of this research was to develop a rapid and simple technique based on Fourier transform infrared spectroscopy to predict the flavor quality of Cheddar cheese.
Fifteen Cheddar cheese samples were ground into powders using liquid nitrogen. The water-soluble compounds from the cheese powder, without interfering compounds such as complex fat and protein, were extracted using water and organic solvents. Aliquots (10 µL) of the extract were placed on the sampling accessory, dried and scanned in the spectrometer (4000 to 700 cm-1). The spectra were matched with the flavor quality to build statistical classification models.
The models provided 3D plots in which all the 15 cheese samples formed well separated clusters, whose orientation correlated well with their cheese flavor characteristics (fermented, unclean, low flavor, sour, good cheddar, etc.). The discrimination of the samples was mainly due to organic and fatty acids and their esters (1500 to 900 cm-1), which are known to contribute significantly to cheese flavor. The total analysis time, including the sample preparation time, was less than 20 min per sample. This technique can be a rapid, inexpensive, high-throughput and simple tool to the cheese industry for predicting the flavor quality of cheese.
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Cheddar Cheese, Flavor Quality, Infrared Spectroscopy