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Research Project: Genetic and Physiological Mechanisms Underlying Complex Agronomic Traits in Grain Crops

Location: Plant Genetics Research

Title: Updating the status quo on the extraction of bioactive compounds in agro-products using a two-pot multivariate design. A comprehensive review

item BOATENG, ISAAC - University Of Missouri
item KUEHNEL, LUCAS - University Of Missouri
item DAUBERT, CHRISTOPHER - University Of Missouri
item AGLIATA, JOSEPH - University Of Missouri
item ZHANG, WENXUE - University Of Missouri
item KUMAR, RAVINDER - University Of Missouri
item Flint-Garcia, Sherry
item AZLIN, MUSTAPHA - University Of Missouri
item SOMAVAT, PAVEL - University Of Missouri
item WAN, CAIXIA - University Of Missouri

Submitted to: Food and Function
Publication Type: Review Article
Publication Acceptance Date: 12/10/2022
Publication Date: 1/21/2023
Citation: Boateng, I.D., Kuehnel, L., Daubert, C.R., Agliata, J., Zhang, W., Kumar, R., Flint Garcia, S.A., Azlin, M., Somavat, P., Wan, C. 2023. Updating the status quo on the extraction of bioactive compounds in agro-products using a two-pot multivariate design. A comprehensive review. Food and Function. 2(14):569-601.

Interpretive Summary: Not required for review articles

Technical Abstract: Extraction is regarded as the most crucial stage in analyzing bioactive compounds. Nonetheless, due to the intricacy of the matrix, numerous aspects must be optimized during the extraction of bioactive components. Although one variable at a time (OVAT) is mainly used, this is time-consuming and laborious. As a result, using an experimental design in the optimization process is beneficial with few experiments and low costs. This article critically reviewed two-pot multivariate techniques employed in extracting bioactive compounds in food in the last decade. First, a comparison of the parametric screening methods (factorial design, Taguchi, and Plackett-Burman design) was delved into, and its advantages and limitations in helping to select the critical extraction parameters were discussed. This was followed by a discussion of the response surface methodologies (central composite (CCD), Doehlert (DD), orthogonal array (OAD), mixture, D-optimal, and Box-Behnken designs (BBD), etc.), which are used to optimize the most critical variables in the extraction of bioactive compounds in food, providing a sequential comprehension of the linear and complex interactions and multiple responses and robustness tests. Next, the benefits, drawbacks, and possibilities of various response surface methodologies (RSM) and some of their usages were discussed, with food chemistry, analysis, and processing from the literature. Finally, extraction of food bioactive compounds using RSM was compared to artificial neural network modeling with their drawbacks discussed. We recommended that future experiments could compare these designs (BBD vs. CCD vs. DD, etc.) in the extraction of food-bioactive compounds. Besides, more research should be done comparing response surface methodologies and artificial neural networks regarding their practicality and limitations in extracting food-bioactive compounds.