Abstract
Commercial oleogelators rich in monoglycerides (MGs) are complex mixtures of acylglycerides with variable gelling properties, depending on the oil used and their concentration. In this study we developed a chemometric approach to identify the key parameters involved in gelling process. Analytical parameters have been defined, using GC and NMR analysis to identify fatty acids and acylglycerides composing the mixtures. Specific acylglyceride families and compound ratios were calculated to streamline the analytical results. To determine the key analytical parameters, artificial neural networks were used in a QSPR study related to the gelling properties measured by rheology through oscillatory experiments. At low oleogelator concentrations, the MGs especially rich in C16:0 and the ratio of specific isomers both have a positive influence on G′. For high oleogelator concentrations, C18:0-rich acylglycerides and unsaturated/saturated fatty acid ratios have a positive influence on G′. Conversely, at low concentrations, C18:0-rich acylglycerides show a lesser effect on G′.
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