Raman spectroscopy based characterization of cow, goat and buffalo fats.

In this study, Raman spectroscopy has been utilized to characterize buffalo, cow and goat fat samples by using laser wavelengths at 532 and 785 nm as excitation sources. It has been observed that Raman spectra of cow fats contain beta-carotene at 1006, 1156 and 1520 cm-1, which are absent in buffalo and goat fats. The Raman bands at 1060, 1080, 1127 and 1440 cm-1 represent the saturated fatty acids, and their concentration is found relatively higher in buffalo fats than cow and goat. Similarly, the Raman band at 1650 cm-1 represent conjugated linoleic acid (CLA) which shows its relatively higher concentration in goat fats than cow and buffalo. The Raman band at 1267 cm-1 represent unsaturated fatty acids, which shows its relatively higher concentration in goat fats than cow and buffalo. The Raman bands at 838, 870 and 1060 cm-1 depict relatively higher concentration of vitamin D in buffalo fats than cow and goat. Principal component analysis has been applied to highlight the differences among three fat types which based upon the concentration of fatty acids, CLA and vitamin D.

Raman spectroscopy based differentiation of typhoid and dengue fever in infected human sera.

This study investigated the potential of Raman spectroscopy, to differentiate between two different types of human pathological conditions with some symptom similarity; typhoid and dengue. Raman spectra were recorded from 20 Salmonella Typhi infected and 22 dengue virus (DENV) infected sera samples using laser wavelength 785 nm. When Raman spectrum (540 to 1830 cm-1) of serum samples was compared it showed significant variations. Twelve characteristic Raman bands at 562, 649, 716, 780, 838, 1099, 1144, 1156, 1260, 1386, 1556 and 1746 cm-1 were recorded specifically in case of the typhoid infected samples, whereas four Raman bands at 756, 1218, 1672 and 1686 cm-1 were found specifically in the DENV infected samples. For statistical differentiation principal component analysis (PCA) and linear discriminant analysis (LDA) was applied which successfully separated two sets of data. These disease specific Raman signatures may be labeled as biomarkers for identification as well as differential diagnosis of typhoid and dengue infection. Hence we propose that Raman spectroscopy has the potential to not only identify but also to differentiate between different pathological conditions, having some similar symptoms like high grade fever in this case.