Speaker
Prof.
John van Duynhoven
(Unilever)
Description
Understanding the behaviour of fat crystal dispersions in oil under industrial processing conditions is of considerable industrial interest. Knowledge of the transient structural hierarchy in fat crystal networks under dynamic conditions will impact directly the rational design and engineering of lipid-based food materials with enhanced shelf-life stability and sensorial quality. Moreover, this will provide the necessary means to develop the relationship between processing and the growth of the multi-length scale structure of a fat network. Fat crystal network formation predominantly depends cooling rate and lipid composition. While knowledge on the crystal polymorphism exists, we only have limited understanding how nanoscale fat crystallites promote hierarchical multiscale networks. The average crystallite thickness (ATD) can be derived from the Full Width at Half Maximum (FWHM) of the first order diffraction line by making use of the Scherrer equation. This approach relies on long range order and may be biased towards assessment of thicker plates. Hence we also implemented an NMR method that solely relies to the low molecular mobility in the crystalline phase. First the magnetization of the crystalline phase was selected by means of a double quantum filter subsequently the redistribution of magnetisation toward the mobile and non-crystalline phase was monitored. By fitting a one-dimensional model for spin-diffusion this approach also yielded ATD values and these compared well with those obtain from SAXS and the Scherrer equation. These NMR and SAXS methods could be implemented on lab-based equipment and were applied on model and real-life complex fat blends subjected to different cooling regimes; average crystallite thicknesses as obtained by these methods were in good agreement. Depending on blend composition and cooling regime also a distribution in crystallite thickness can be introduced. The aforementioned approaches do not take such heterogeneity into account, hence we implemented the Bertaut-Warren-Averbach method to derive crystallite thickness distributions (CTD) from SAXS data obtained at the ID02 beamline at ESRF. Thus CTD signatures could be recognized that were specific for blend composition and cooling regime, both in semi- as in full food products.
| Topic Area / Session | Lipids |
|---|
Primary author
Prof.
John van Duynhoven
(Unilever)
Co-authors
Dr
Adrian Voda
(Unilever R&D)
Dr
Kees van Malssen
(Unilever R&D)
Dr
Michiel Meeuse
(Unilever R&D)
Oleksandr Mykhaylyk
(University of Sheffield)
Mr
Ruud den Adel
(Unilever R&D)
