Principal component analysis cheese

Schievano, E., Pasini, G., Cozzi, G., and Mammi, S. (2008). Identification of the production chain of Asiago d Allevo cheese by nuclear magnetic resonance spectroscopy and principal component analysis.. Agric. Food Chem. 56, 7208-7214. 

After 30 min equilibration at room temperature, the measurement run started. An air flow (room air filtered through active carbon) was conveyed over the sensors at a constant rate (lcm3/s) for 10 s to stabilize the baseline. An automatic syringe then suckled Asiago cheese head-space and conveyed it over the sensor surfaces for 60s. The sensors were exposed again to the reference air flow to eventually recover the baseline. The total cycle time for each measurement was 5 min. No sensor drift was experienced during the measurement period. Each sample was evaluated three times and the average of the results was used for subsequent statistical analysis (principal component analysis (PCA)). 

Among the different chemometric methods, exploratory data analysis and pattern recognition are frequently used in the area of food analysis. Exploratory data analysis is focused on the possible relationships between samples and variables, while pattern recognition studies the behavior between samples and variables [95]. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) are the methods most commonly used for exploratory analysis and pattern recognition, respectively. The importance of these statistical tools has been demonstrated by the wide number of works in the field of food science where they have been applied. The majority of the applications are related to the characterization and authentication of olive oil, animal fats, marine and vegetable oils [95], wine [97], fruit juice [98], honey [99], cheese [100,101], and so on, although other important use of statistical tools is the detection of adulterants or frauds [96,102]. 

Gueireiro, J. S., Barros, M., Fernandes, R, Pires, P, and Bardsley, R. 2013. Principal component analysis of proteolytic profiles as markers of authenticity of PEXD cheeses. Food Chem. 136 1526-1532. 

Figure 6 Principal components analysis of volatile, nonvolatile, and sensory data of Parmigiano-Reggiano cheese. Variable loadings on the plane of the first two components. (From Ref. 42.)...

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