Background: Plant-based foods are frequently heterogenous systems, containing multiple starch fractions with distinct digestion rate constants. An unbiased determination of the number and digestion pattern of these fractions is a prerequisite for understanding the digestive characteristics of food.
Results: A non-linear least-squares procedure based on a conditional selection of simple first-order kinetics or a combination of parallel and sequential kinetics models was developed. The procedure gave robust results fitting manually generated data, and was applied to in vitro experimental digestion data of retrograded rice starches. By correlating fitting parameters with starch structural parameters, it showed that rice starches with a lower amylose content, longer amylose chains, and amylopectin intermediate chains had more digestible starch fractions after long-term retrogradation.
Conclusion: This procedure enables the structural basis of starch digestibility and the development of food products with slow starch digestibility to be better understood. © 2022 Society of Chemical Industry.
Keywords: first-order kinetics modeling; non-linear least-squares fitting; retrograded rice starch digestion; starch structure.
© 2022 Society of Chemical Industry.