Implementation of RSM and ANN Optimization Approach for Natural Deep Eutectic Solvents-Based Extraction of Bioactive Compounds from Orange Peel.

The present investigation has focused on developing an eco-friendly method to extract bioactive compounds from orange peel using natural deep eutectic solvents (NADES). NADES-II composed of choline chloride (ChCl) and ethylene glycol (1:2) and 50% water shows the maximal extraction yield with higher antioxidant activity in terms of DPPH and ABTS scavenging activity with a high total phenolic content (TPC) and total flavonoid content (TFC). The microwave-assisted extraction (MAE) process was optimized using response surface methodology (RSM) and an artificial neural network (ANN). ANN showed a higher value of R 2 and lower values of other statistical parameters when compared to RSM. The ideal extraction conditions were optimized as a 13 min rising time, 52 °C temperature, a 21 min holding time, and a 20 mL/g liquid-to-solid ratio. MAE was compared with the conventional heating-stirring extraction (HSE) method using the NADES-II solvent under optimum conditions. The results show that higher extraction yield and antioxidant capacities (DPPH and ABTS), TPC, and TFC can be obtained from orange peel using the MAE process compared to the HSE process. Overall, this study shows an optimiztic approach for the extraction of bioactive compounds from an orange peel using eco-friendly solvents and microwave technology. It also highlights the potential of this approach for valorizing orange peel waste.

Process Standardization of Functionally Enriched Millet-Based Nutri-Cereal Mix Using D-Optimal Design Approach for Enhancing Food and Nutritional Security.

Millets are currently employed in a variety of ways, including direct consumption and usage in the manufacture of certain cuisines or snacks. The present investigation was aimed at optimizing functionally enriched millet-based nutri-cereal mix comprising chicken and vegetable for a nutrition-deficient population. A total of 16 experiments were carried out by using optimal (custom) design model of mixture design with 60% major ingredients, including malted sorghum flour (20-30%), malted green gram flour (15-25%), and boiled chicken powder (5-15%). To make 100% of the total nutri-cereal mixture, other ingredients such as malted pearl millet (10%), finger millet flour (10%), beetroot powder (2.5%), pumpkin powder (7.5%), skimmed milk powder (9.5%), and stevia powder (0.5%) were added. Numerical optimization was done using Design Expert software, version 13. The optimized ratio was 30% malted sorghum flour, 15% malted green gram flour, and 15% chicken powder. The predicted values of responses 5.101%, 3.616%, 1.963%, 11.165%, 28.005%, 50.149%, 330.282 kcal, and 0.373 were in accordance with experimental values 6.426%, 3.455%, 1.714%, 11.432%, 29.12%, 47.853%, 323.318 kcal, and 0.385 for moisture, ash, fat, fiber, protein, carbohydrates, energy, and water activity, respectively, with a small error percentage. The results of mineral content, phenolic content, and amino acid profiling revealed that the optimized Nutri-cereal mix have higher amounts of these components. The results also suggested that the optimized Nutri-cereal mix of these malted millet flours can potentially enhance the nutritional deficiency as well as improve food and nutritional security.