Influence of polymorphism on the solid fat content determined by FID deconvolution

Abstract

One of the most important quality parameters of a fat, is its solid fat content (SFC). The standard method to determine the SFC is pNMR using a f-factor. This factor is determined with three standards. However, this contribution shows that SFC standards are not required when using deconvolution methods. At first, data acquisition was optimized. These experiments revealed that the deconvolution method worked better, if more sample was present in the detection zone of the NMR, due to a higher signal-to-noise ratio (SNR). Regarding deconvolution, a bi-Gaussian model and a model combining a Gaussian and Abragamian function were compared. Both models were able to fit the free induction decay (FID) data. Furthermore, the corresponding SFC values were comparable with the SFC values of the f-factor method when analyzing SFC standards or fats which were preprocessed using the AOCS tempering protocol. Upon evaluating the influence of the polymorphic states of cocoa butter, it became clear that the f-factor standards resemble fats containing β-polymorphs. As a further consequence, the f-factor method fails when α-polymorphs are present to a large extent. Overall this study shows that the deconvolution method is superior to the f-factor method since it does not require any standards and is less affected by the polymorphic state.

Practical Applications: This work shows that the solid fat content (SFC) of a fat can be calculated without the use of calibration standards. If deconvolution would replace the standard used pNMR method, it could potentially reduce the preparation time for the measurements, because no calibration is necessary. Next to this, it also lowers the cost of SFC determination, because no standards should be bought. Deconvolution also gives insight in the behaviour of the different components present in the sample, for example T2-values. There above, research towards deconvolution of pNMR signals is necessary as it could potentially also determine the presence of different fat crystal polymorphs present in samples.

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