Abstract
A Raman analysis of biological samples has been drastically progressed with application of multivariate
analytical techniques (chemometrics). Biological samples, especially live cells and tissues have inherent
variation in their molecular compositions, for example, a cell shows a large molecular variation during its
cell cycle. It is because chemometrics based on statistical techniques, such as principal component analysis
(PCA), are required to extract valuable information. For the application of chemometrics, spontaneous
Raman spectroscopy is useful because it is highly stable. We have applied Raman spectroscopy
with chemometrics to analyze fat metabolism in live animal. A Raman probe allowed one to obtain
Raman spectra of subcutaneous fat with a totally noninvasive manner. Partial least square regression
(PLSR) analytical model was applied to quantify concentrations of specific fatty acid chains in the fat
tissues.
