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Modification and Validation of a Semi-Automated In vitro Method for Predicting the Glycemic Index of Starchy Foods

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dc.contributor.advisor Duncan, Alison
dc.contributor.advisor Ramdath, Dan
dc.contributor.author El-Fahkhri, Rasem
dc.date.accessioned 2017-01-03T20:32:32Z
dc.date.available 2017-01-03T20:32:32Z
dc.date.copyright 2016-12
dc.date.created 2016-12-21
dc.date.issued 2017-01-03
dc.identifier.uri http://hdl.handle.net/10214/10151
dc.description.abstract The glycemic index (GI) can assist with determining the effect of food on blood glucose levels. The Englyst method is commonly used in vitro method to predict the GI, but it does not use food as eaten. The aim of this study was to establish and validate a modified semi-automated Englyst method that better estimates the GI of foods as consumed. The method was successfully established through a simulated upper gastrointestinal digestion protocol and compared with in vivo GI values. Predicted GI (pGI) was calculated from starch digestion profiles. In vivo GI was moderately correlated with pGI (r (18)= 0.51; p < 0.05), but highly correlated (r (18)= 0.72; p < 0.05) with rapidly digestible starch (RDS). Both pGI and RDS can be used as predictors for in vivo GI. This novel finding and the modified method can be used together to effectively predict the GI of starchy foods. en_US
dc.language.iso en en_US
dc.subject In vitro starch digestion en_US
dc.subject Glycemic Index en_US
dc.subject Rapidly digestable starch en_US
dc.subject Englyst method en_US
dc.title Modification and Validation of a Semi-Automated In vitro Method for Predicting the Glycemic Index of Starchy Foods en_US
dc.type Thesis en_US
dc.degree.programme Human Health and Nutritional Sciences en_US
dc.degree.name Master of Science en_US
dc.degree.department Department of Human Health and Nutritional Sciences en_US
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