Sonoprocessing improves phenolics profile, antioxidant capacity, structure, and product qualities of purple corn pericarp extract.

For the first time, purple corn pericarp (PCP) was converted to polyphenol-rich extract using two-pot ultrasound extraction technique. According to Plackett-Burman design (PBD), the significant extraction factors were ethanol concentration, extraction time, temperature, and ultrasonic amplitude that affected total anthocyanins (TAC), total phenolic content (TPC), and condensed tannins (CT). These parameters were further optimized using the Box-Behnken design (BBD) method for response surface methodology (RSM). The RSM showed a linear curvature for TAC and a quadratic curvature for TPC and CT with a lack of fit > 0.05. Under the optimum conditions (ethanol (50%, v/v), time (21 min), temperature (28 °C), and ultrasonic amplitude (50%)), a maximum TAC, TPC, and CT of 34.99 g cyanidin/kg, 121.26 g GAE/kg, and 260.59 of EE/kg, respectively were obtained with a desirability value 0.952. Comparing UAE to microwave extraction (MAE), it was found that although UAE had a lower extraction yield, TAC, TPC, and CT, the UAE gave a higher individual anthocyanin, flavonoid, phenolic acid profile, and antioxidant activity. The UAE took 21 min, whereas MAE took 30 min for maximum extraction. Regarding product qualities, UAE extract was superior, with a lower total color change (ΔE) and a higher chromaticity. Structural characterization using SEM showed that MAE extract had severe creases and ruptures, whereas UAE extract had less noticeable alterations and was attested by an optical profilometer. This shows that ultrasound, might be used to extract phenolics from PCP as it requires lesser time and improves phenolics, structure, and product qualities.

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

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.