Recent Applications of Mixture Designs in Beverages, Foods, and Pharmaceutical Health: A Systematic Review and Meta-Analysis.

Diego Galvan,Hágata Cremasco,Luciane Effting,Carlos Adam Conte-Junior

doi:10.3390/foods10081941

Abstract

Design of Experiments (DoE) is a statistical tool used to plan and optimize experiments and is seen as a quality technology to achieve products excellence. Among the experimental designs (EDs), the mixture designs (MDs) stand out, being widely applied to improve conditions for processing, developing, or formulating novel products. This review aims to provide useful updated information on the capacity and diversity of MDs applications for the industry and scientific community in the areas of food, beverage, and pharmaceutical health. Recent works were selected following the Preferred Reporting Items for Systematic Review and Meta-Analyses statement (PRISMA) flow diagram. Data analysis was performed by self-organizing map (SOM) to check and understand which fields of application/countries/continents are using MDs. Overall, the SOM indicated that Brazil presented the largest number of works using MDs. Among the continents, America and Asia showed a predominance in applications with the same amount of work. Comparing the MDs application areas, the analysis indicated that works are prevalent in food and beverage science in the American continent, while in Asia, health science prevails. MDs were more used to develop functional/nutraceutical products and the formulation of drugs for several diseases. However, we briefly describe some promising research fields in that MDs can still be employed.

Highlights

Food and health science studies are becoming more complex with a considerable increase in the number of variables, requiring robust methods for simultaneous data analysis [1]
5 January 2021), present in approximately 46% of the evaluated works, followed by Statistica (StatSoft Onc., South America, Tulsa, OK, United States (USA), https://www.statsoft.de/en/home accessed on 5 January 2021), with 22%, the Minitab (Minitab Inc., State College, PA, USA, https://www.minitab.com/ accessed on 5 January 2021) with 9%, the Statgraphics (Statistical Graphics Corporation, The Plains, Virginia, VA, USA, www.statgraphics.com accessed on 5 January 2021) with 5%, the Matlab (The Mathworks Inc., Natick, MA, USA, https://www.mathworks.com/ accessed on 5 January 2021) with 4%, and the JMP
The data presented in this meta-analysis indicated the mixture designs (MDs)’ capacity and applicability for the development or formulation of novel products applied in the area of food, beverage, and health science

Summary

Introduction

Food and health science studies are becoming more complex with a considerable increase in the number of variables, requiring robust methods for simultaneous data analysis [1]. These analyzes can be facilitated using mathematical and statistical fundamentals, known as chemometric methods, which can be divided into the design of experiments, multivariate data analysis, and multivariate calibration [2,3,4]

Objectives

Methods

Findings

Conclusion