The structure and function of resistant starch in glycaemia
Lead Research Organisation:
University of Surrey
Department Name: Nutrition & Metabolism
Abstract
Research Questions:
Can ALC content in food be reliably quantified by combining analytical techniques with an in vitro model of digestion?
Can molecular modelling predict the ability of alpha-amylase to bind to and digest ALCs made from different lipids?
Does increasing the ALC content of foods affect the physicochemical and sensory characteristics?
Objectives:
1. Literature survey to provide data for modelling.
2. Build molecular models of ALCs using molecular mechanics. Molecular orbital calculations will be used to predict NMR spectra using the GIAO method for comparison with experiment.
3. Produce modelled ALCs and controls and characterise by differential scanning calorimetry (DSC), nuclear magnetic resonance spectroscopy (NMR), complexing index, total resistant starch assay and x-ray diffraction (XRD).
4. In vitro digestion of ALCs using the INFOGEST model6 to determine resistance to digestion. Monitor fatty acid and maltose release. Molecular modelling of binding between ALCs and amylase.
5. Produce test foods (pasta meals) with increased ALC content vs controls.
6. Characterisation of ALCs in/from pasta, as above.
7. Sensory profiling and consumer analysis of pasta and aroma analysis as required. Characterisation of pasta texture (TA-XT2i), including firmness and elasticity.
8. In vitro digestion of test foods to determine digestibility of starch, FFAs release, and characterisation of digesta.
Can ALC content in food be reliably quantified by combining analytical techniques with an in vitro model of digestion?
Can molecular modelling predict the ability of alpha-amylase to bind to and digest ALCs made from different lipids?
Does increasing the ALC content of foods affect the physicochemical and sensory characteristics?
Objectives:
1. Literature survey to provide data for modelling.
2. Build molecular models of ALCs using molecular mechanics. Molecular orbital calculations will be used to predict NMR spectra using the GIAO method for comparison with experiment.
3. Produce modelled ALCs and controls and characterise by differential scanning calorimetry (DSC), nuclear magnetic resonance spectroscopy (NMR), complexing index, total resistant starch assay and x-ray diffraction (XRD).
4. In vitro digestion of ALCs using the INFOGEST model6 to determine resistance to digestion. Monitor fatty acid and maltose release. Molecular modelling of binding between ALCs and amylase.
5. Produce test foods (pasta meals) with increased ALC content vs controls.
6. Characterisation of ALCs in/from pasta, as above.
7. Sensory profiling and consumer analysis of pasta and aroma analysis as required. Characterisation of pasta texture (TA-XT2i), including firmness and elasticity.
8. In vitro digestion of test foods to determine digestibility of starch, FFAs release, and characterisation of digesta.
Organisations
People |
ORCID iD |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/T008776/1 | 30/09/2020 | 29/09/2028 | |||
| 2601544 | Studentship | BB/T008776/1 | 30/09/2021 | 30/03/2028 |