This study (purchase required) explores the ratio between the values of the saponification and iodine indices in edible oils. The relationship is used as the basis of a classification model. The approach is termed a Quantitative Structure-Property Relationship (QSPR) study..
The authors report that QSPRs were formulated in 144 vegetable oils, composed of 1–8 fatty acid components. Details of the varieties and sources used for the training and validation sets are not available in the online abstract. A set of 25,118 mixture descriptors was calculated as linear combinations of the non-conformational descriptors of the fatty acid components and their weight percent compositions. This approach was found useful for discerning natural oils. The Replacement Method variable subset selection technique was applied afterwards to select the best mixture descriptors in the predictive model.
To test the model, different vegetable oils with known composition, but unknown experimental saponification and iodine indices data, were successfully classified using the established QSPR.
The authors conclude that two-variable QSPR analysis can be extended to fats and other types of oils, such as fish oils. It also serves as a background and database for other methodologies.
Comments