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Cheddar cheese classification based on flavor quality using a novel extraction method and Fourier transform infrared
A Subramanian1, W J Harper, L E Rodriguez-Saona
1Department of Food Science and Technology, The Ohio State University, 2015 Fyffe Court, Columbus, OH 43210, USA.
A new method uses solvent extraction and Fourier transform infrared spectroscopy (FTIR) to quickly classify Cheddar cheese flavor. This rapid analysis accurately predicts cheese flavor quality, offering a cost-effective tool for the dairy industry.
Area of Science:
- Food Science
- Analytical Chemistry
- Spectroscopy
Background:
- Traditional sensory analysis of Cheddar cheese flavor is costly and time-intensive.
- Objective, rapid methods are needed for quality control in cheese production.
Purpose of the Study:
- To develop a fast and simple method for classifying Cheddar cheese based on flavor quality.
- To utilize solvent extraction and FTIR spectroscopy for flavor analysis.
Main Methods:
- Water-soluble compounds were extracted from powdered cheese using water, chloroform, and ethanol.
- Infrared spectra of extracts were analyzed using soft independent modeling of class analogy (SIMCA) for pattern recognition.
- Cheeses were classified based on flavor profiles determined by trained sensory panels.
Main Results:
- SIMCA models successfully created well-separated clusters for 15 cheese samples.
- Cluster orientation correlated with specific flavor characteristics (e.g., fermented, sour, good Cheddar).
- Discrimination was attributed to organic acids, fatty acids, esters, and amino acids.
Conclusions:
- The developed solvent extraction and FTIR-SIMCA technique provides rapid (under 20 min/sample) and accurate classification of Cheddar cheese flavor.
- This method offers a cost-effective alternative to traditional sensory analysis for the cheese industry.
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