Optimization of a master formulation of food thickener using statistical mixture planning

Authors

DOI:

https://doi.org/10.33448/rsd-v11i16.37528

Keywords:

Deglutition Disorders; Food additives; Experimental design.

Abstract

Dysphagia is characterized by a swallowing disorder or any difficulty in the transit of the food bolus from the mouth to the stomach of congenital or acquired origin, which may be associated with complications. Thickening agents are used to improve the consistency of foods or beverages for the treatment of oropharyngeal dysphagia, in order to rehabilitate the patient's oral feeding. Most thickeners are natural carbohydrates such as xanthan gum. Statistical mixture planning is applied to efficiently determine the set of conditions that are required to obtain a product with desirable characteristics, making masterful pharmaceutical powder development more efficient compared to trial and error application. The objective of this work was to optimize a thickener formulation composed of maltodextrin, xanthan gum and potassium chloride through statistical mixing planning. After the design of the statistical planning matrix with the definition of the proportions of the raw materials to be used in each proposed formulation, they were evaluated for their viscosity in a Brookfield viscometer, having as parameter the ranges established by the National Dysphagia Diet (NDD) for each consistency: Nectar, Honey and Pudding. Based on the response surface elaborated through the statistical planning matrix of mixtures, and on the experimental findings of viscosity, solubility, dispersion and appearance of the formulations, it was possible to obtain a formulation that presented better performance, considering the previously established acceptance ranges, according to the NDD, performing as few experiments as possible.

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Published

28/11/2022

How to Cite

TEIXEIRA, L. V. M.; MELO, A. S. P. de; FRAGA , A. G. M.; SANTOS, E. P. dos; AGUIAR, P. F. de; LEAL, F. D.; VILLA, A. L. V. Optimization of a master formulation of food thickener using statistical mixture planning. Research, Society and Development, [S. l.], v. 11, n. 16, p. e28111637528, 2022. DOI: 10.33448/rsd-v11i16.37528. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/37528. Acesso em: 5 nov. 2024.

Issue

Section

Health Sciences