Abstract:
Saponification value, the average molecular weight of fatty acids, is a crucial parameter for detecting adulteration of edible oils. Conventionally, it is determined in a laboratory setup through a time-consuming, laborious titration process using chemical reagents. Herein, the application of Raman spectroscopy for quick SV estimation of oils is demonstrated. It was hypothesized that the SV can be predicted from Raman spectra since the spectral patterns reflect the composition of fatty acid triglycerides. Two model oil systems were studied: coconut-gingelly oil and coconut-sunflower oil. Univariate models built from Raman spectra were successful only for the specific oil system; hence, PLS-Regression was executed across the two systems. The PLSR model on the validation set returned the average error, percentage error, and root mean square error of prediction as 2.1, 0.99 %, and 2.4, respectively. This method offers several advantages of portability, little reagent use, minimal sample preparation, and reduced analysis time.
