Adsorption between Quercetin Derivatives and β-Glucan Studied with a Novel Approach to Modeling Adsorption Isotherms

Abstract

Interactions between polyphenols and fibers are important for polyphenol bioactivities, and have been studied in vitro with adsorption process and isotherms. However, the theoretical interpretations of adsorption potentially can be affected by the method of isotherm modeling. The aim was to study the interactions between β-glucan and quercetin derivatives (quercetin-3-glucoside, quercetin-3-galactoside, quercetin-3-rhamnoside) by studying adsorption, and to potentially improve the modeling of adsorption isotherms. Quercetin derivatives were determined by using spectrophotometric method. Experimental results were modeled with Langmuir, Dubinin-Radushkevich, and Hill isotherms using non-linear regression, linear regression, and improved non-linear regression. For improved non-linear regression, code in the R programming language was developed. All quercetin derivatives adsorbed onto the surface of β-glucan. Improved non-linear regression gave somewhat lower errors and may be the most appropriate for adsorption interpretation. According to isotherms obtained with improved regression, it may be suggested that adsorption is higher for rhamnoside and glucoside of quercetin than for quercetin-3-galactoside which agrees with experimental results. Adsorption could be a physical process. The spatial arrangement of hydroxyl (OH) groups on the glycoside part of quercetin could affect the adsorption. In conclusion, a novel approach using improved non-linear regression has been shown to be a useful, novel tool for adsorption interpretation.

Polyphenols of Traditional Apple Varieties in Interaction with Barley β-Glucan: A Study of the Adsorption Process

“…The adsorption was then conducted with several different initial polyphenol concentrations and the resulting data ( q e vs. c e ) were modeled with Langmuir, Dubinin–Radushkevich, and Hill isotherm equations by using the improved non-linear modeling explained in our earlier paper [ 34 ]. As described [ 34 ], in isotherm diagrams ( q e vs. c e ), q e and c e were both measured values. They respond to the initial concentration, c o .…”

“…They respond to the initial concentration, c o . In the case of several measurements of q e for one initial c o , several q e values will be positioned in the q e vs. c e diagram on a diagonal line (due to the mass balance equation as explained in our earlier paper [ 34 ]). In appropriate modeling, the fitted curve and point calculated by the model ( q e model ) should lie on that diagonal line, which is not the case in standard non-linear regression.…”

“…The improved non-linear regression created in the R programming language fitted the data in a way that the calculated q e model values by the model were on the diagonal lines. It was shown that this way of modeling created a curve with lower standard errors, which enabled more precise determination of isotherm parameters [ 34 ]. For this reason, the improved non-linear regression was chosen for the data in this study too.…”

“…For that purpose, we used improved non-linear regression fitting methodology specifically designed for adsorption isotherms. The code for improved adsorption isotherm fitting, as described in [ 34 ], was developed as an R algorithm at Yale University by our group.…”

Study of Interactions Between Individual Phenolics of Aronia with Barley Beta-Glucan

“…This is due to the mass balance equation (Eq. 1) as explained in our previous paper [Jakobek et al, 2020b]. With a naive use of traditional non-linear regression, the q e,model is fitted to q e,measured to minimize the squares of vertical error, associated with a presumption of a model value of c e matching its measured value.…”