A more general approach for predicting the glycemic index (GI) values of commercial noodles

Glycemic index (GI) is important however there is currently a lack of specific model to predict the GI for noodles. Various models have been proposed in literature for foods including rice, whereas the results from rice cannot be assumed to be applicable for noodles. In this study, static in vitro digestion experiments using standard commercial noodles with known clinical GI ranging between 37 ∼ 53 were conducted using different protocols with the digestograms fitted by mathematical kinetics models. Mathematical equations were established based on the statistic relationships between the digestion kinetics parameters with GI and glycemic load (GL) values. Results showed that compared with digestion using the INFOGEST protocol, the indices of AUR90 deduced from the digestion of noodle strands of ∼ 1 cm in length using porcine pancreatin (1 mg/mL), showed the best potential in predicting the eGI and GL values of noodles with an Eqn of eGI = −0.0001 × AUR90 + 52.5530 and eGL = −0.0002 × AUR90 + 34.9670, respectively. Here, the AUR90 represents the area under the curve of reducing sugar content normalized to total available carbohydrates versus digestion time within the first 90 min. The in vitro method presented provides for rapid and accurate prediction of eGI and GL values of noodles and other carbohydrate foods as well.