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.

Plant secondary metabolites such as terpenes, phenolics, glycosides, and alkaloids play various functional roles including pigmentation, foliar and floral volatile synthesis, hormonal regulation, and direct and indirect defenses. Among these, phenolic compounds are commonly found in plants, but vary in the distribution of their specific compounds among plant families. Polyphenols, including anthocyanins and tannins, are widely distributed and have been well documented for their roles- primarily in plant pigmentation and also in plant defenses. However, commercialization of such compounds for use in insect pest management is severely hampered by expensive, inefficient, and time-consuming extraction protocols. Using a recently developed inexpensive and easy extraction method using the byproducts of pigmented (purple) corn processing, we examined whether the crude pericarp extract rich in polyphenols can affect the growth and development of tobacco hornworm (Manduca sexta L.) caterpillars. Our findings show that purple corn pericarp extract negatively affected M. sexta egg hatching and larval mass gain and prolonged developmental time compared to regular yellow corn extract or an artificial control diet. We also found that these effects were more severe during the early stages of caterpillar development. These results conclusively demonstrate that purple corn pericarp, an inexpensive by-product of the corn milling industry, is a valuable product with excellent potential as an insect antifeedant.

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.

Purple corn pericarp, a processing waste stream, is an extremely rich source of phytochemicals. Optimal polyphenol extraction parameters were identified using response surface methodology (RSM) by combining a deep eutectic solvent (DES) and ultrasound-assisted extraction (UAE) method. After DES characterization, Plackett–Burman design was used to screen five explanatory variables, namely, time, Temp (temperature), water, Amp (amplitude), and S/L (solid-to-liquid ratio). The total anthocyanin concentration (TAC), total polyphenol concentration (TPC), and condensed tannin (CT) concentration were the response variables. After identifying significant factors, the Box–Behnken design was utilized to identify the optimal extraction parameters. The experimental yields under the optimized conditions of time (10 min), temperature (60 °C), water concentration (42.73%), and amplitude (40%) were 36.31 ± 1.54 g of cyanidin-3-glucoside (C3G), 103.16 ± 6.17 g of gallic acid (GA), and 237.54 ± 9.98 g of epicatechin (EE) per kg of pericarp, with a desirability index of 0.858. The relative standard error among the predicted and experimental yields was <10%, validating the robustness of the model. HPLC analysis identified seven phytochemicals, and significant antioxidant activities were observed through four distinct assays. Metabolomic profiling identified 57 unique phytochemicals. The UAE technique combined with DES can efficiently extract polyphenols from purple corn pericarp in a short time.