engleski

A statistically accurate algorithm for fitting adsorption isotherms with application to the interaction between polyphenols and b-glucan

Introduction: Polyphenol bioaccessibility is affected by interactions between dietary fibers and polyphenols. Interactions can be studied by studying adsorption. Experimental results in adsorption are modelled with isotherm equations with an interesting distribution of errors. Traditional nonlinear least squares fitting can lead to statistical inconsistency and poor interpretation of adsorption and interactions. Accordingly, we developed new statistical methodology and an R algorithm suitable for fitting such isotherms. A particular aim was to study adsorption between gallic acid and - glucan as a dietary fiber and to interpret the adsorption using proper statistical fitting of isotherms. Materials and methods: Adsorption was conducted in a model solution (gallic acid, -glucan, buffer) at three pH values (1.5, 5.5, 10). Gallic acid was determined with Folin- Ciocalteu method. Results were modelled using Langmuir, Dubinin-Radushkevich and Hill isotherms with a novel statistical algorithm. Results: gallic acid had the highest adsorption at pH 10. Adsorption isotherms fitting by using the novel algorithm gave lower errors and allowed more precise interpretation of adsorption. The adsorption was described better with Langmuir model. Physical bonds between gallic acid and -glucan can be suggested. Conclusion: The new algorithm is statistically appropriate and a useful tool for adsorption and interaction interpretation.

adsorption isotherms ; algorithm ; bioaccessibility ;

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