Optimization of enzyme-assisted improvement of polyphenols and free radical scavenging activity in red rice bran: A statistical and neural network-based approach

Ultrasound-assisted extraction and encapsulation of betalain from prickly pear: Process optimization, in-vitro digestive stability, and development of functional gummies

The study aimed to extract and encapsulate betalain pigment from prickly pear (Opuntia ficus-indica) using ultrasound-assisted extraction and eco-friendly glycerol. Subsequent analysis encompassed assessing its thermal stability, shelf-life, bio-accessibility, and biological properties. The process optimization employed Response Surface Methodology (RSM), focusing on glycerol concentration (20-50 %), sample to solvent ratio (1:10-1:20), temperature (30-60 °C), and time (10-30 min). Optimal conditions were determined as 23.15 % glycerol, 1:10 sample to solvent ratio, 10.43 min treatment time, and 31.15 °C temperature. Under these conditions, betalain content reached 858.28 mg/L with a 93.76 % encapsulation efficiency. Thermal stability tests (80-180 °C; 30 & 60 min) showed degradation of betalain with higher temperatures and longer durations, affecting the visual aspect (ΔE) of the pigment. Encapsulated betalain exhibited favorable shelf stability, with optimal storage life of 404.27 days at 4 °C in amber conditions, compared to 271.99 days at 4 °C without amber, 141.92 days at 25 °C without amber, and 134.22 days at 25 °C with amber. Bio-accessibility of encapsulated betalain was significantly higher (2.05 ± 0.03 %) than conventionally extracted pigment (1.03 ± 0.09 %). The encapsulated pigment displayed strong anti-inflammatory properties in dosages of 2-20 µL, with no cytotoxic effects. Additionally, incorporation into gummies was successful and visually approved by sensory panellists. Glycerol proved to be a green encapsulating agent for betalain, offering high shelf life and bio-accessibility, making it suitable for food industry applications. The encapsulated pigment demonstrated robust thermal stability and shelf life, making it suitable for food industry applications. This study highlights glycerol's potential as a sustainable alternative for natural pigment extraction.

Recent advances in bio-based extraction processes for the recovery of bound phenolics from agro-industrial by-products and their biological activity

Usually found bound to other complex molecules (e.g., lignin, hemicellulose), phenolic compounds (PC) are widely present in agro-industrial by-products, and their extraction is challenging. In recent times, research is starting to highlight the bioactive roles played by bound phenolics (BPC) in human health. This review aims at providing a critical update on recent advances in green techniques for the recovery of BPC, focusing on enzymatic-assisted (EAE) and fermentation-assisted extraction (FAE) as well as in the combination of technologies, showing variable yield and features. The present review also summarizes the most recent biological activities attributed to BPC extracts until now. The higher antioxidant activity of BPC-compared to FPC-coupled with their affordable by-product source make them medicinally potent and economically viable, promoting their integral upcycling and generating new revenue streams, business, and employment opportunities. In addition, EAE and FAE can have a biotransformative effect on the PC itself or its moiety, leading to improved extraction outcomes. Moreover, recent research on BPC extracts has reported promising anti-cancer and anti-diabetic activity. Yet further research is needed to elucidate their biological mechanisms and exploit the true potential of their applications in terms of new food products or ingredient development for human consumption.

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.

Large-scale production of enzymes for biotechnology uses

Enzymes are biocatalysts that speed up the chemical reaction to obtain the final valuable product/s. Biotechnology has revolutionized the use of traditional enzymes to be applicable in industries such as food, beverage, personal and household care, agriculture, bioenergy, pharmaceutical, and various other segments. With respect to the exponential growth of enzymes in biotech industries, it becomes important to highlight the advancements and impact of enzyme technology over recent years. In this review article, we discuss the existing and emerging production approaches, applications, developments, and global need for enzymes. Special emphasis is given to the predominantly utilized hydrolytic microbial enzymes in industrial bioprocesses.

Partial consolidated bioprocessing of pretreated Pennisetum sp. by anaerobic thermophiles for enhanced bioethanol production

Rapid industrialization and consumption of fossil fuels have led to considerable progress in the production of renewable biofuels like bioethanol. Lignocellulosic biomass such as grasses serves as cheap feedstocks for the production of bioethanol. However, the process involved in lignocellulosic bioethanol production is expensive which restricts its industrial production. The present study thus attempted to investigate a partially consolidated bioprocessing (PCB) approach using two isolated anaerobic thermophiles i.e. Bacillus paranthracis and Bacillus nitratireducens for direct conversion of ultra-sonication assisted sodium hydroxide (UA-NaOH) pretreated Denannath grass to bioethanol in co-culture consortium batch fermentation experiments. The process parameters for the PCB approach were optimized using the Box-Behnken design of Response Surface Methodology (RSM). The parameters that were considered were substrate concentration (5-10 g), incubation time (30-66 h), inoculum volume [1:1 to 3:3 (% v/v) and temperature (50-65 °C). The maximum ethanol concentration of 8.46 mM (0.39 g/L from 7.5 g/L of substrate loading) and ethanol yield (Yp/s) of 0.55 g/g of reducing sugar was obtained at 57.5 °C. In the same conditions the cellulase and xylanase activities were 0.8 U/mL and 11.53 U/mL respectively, while the lactate and acetate concentrations were 0.2 mM (0.009 g/L) and 2.9 mM (0.13 g/L) correspondingly. An increase in the substrate loadings to 250 g/L in a batch fermenter (3 L) resulted in the production of 373.35 mM (17.1 g/L) of ethanol concentration and Yp/s of 0.16 g/g of reducing sugar.

Application of enzyme-assisted extraction of baicalin from Scutellaria baicalensis Georgi

Endophytes may depend on degrading the plant cell wall with cellulases for their survival. Therefore, cellulase produced by endophytes may be useful in releasing the active ingredient of medicinal plants. Scutellaria baicalensis Georgi is a traditional Chinese medicinal plant widely used in China and baicalin is one of its main active ingredients. In this study, fresh S. baicalensis Georgi was used to isolate endophytes, Congo red staining was used to screen cellulase-producing strains, and HPLC was used to determine the content of baicalin in S. baicalensis Georgi. As a result, a highly active strain of endophyte capable of the extraction of high levels of baicalin was obtained. The strain was named HG-5 and identified as Bacillus sp. Scanning electron microscopy analysis confirmed that the enzyme better promotes the dissolution of plant active ingredients. After optimizing the enzyme production and extraction processes, we found that when compared with the traditional extraction method, the baicalin yield was increased 79.31% after extraction with the HG-5 enzyme. The current study provides a novel approach and method for the use of endophyte cellulase to improve the extraction of compounds from medicinal plants.

Interpretation of ANN-based QSAR models for prediction of antioxidant activity of flavonoids

Quantitative structure-activity relationships (QSARs) built using machine learning methods, such as artificial neural networks (ANNs) are powerful in prediction of (antioxidant) activity from quantum mechanical (QM) parameters describing the molecular structure, but are usually not interpretable. This obvious difficulty is one of the most common obstacles in application of ANN-based QSAR models for design of potent antioxidants or elucidating the underlying mechanism. Interpreting the resulting models is often omitted or performed erroneously altogether. In this work, a comprehensive comparative study of six methods (PaD, PaD₂ , weights, stepwise, perturbation and profile) for exploration and interpretation of ANN models built for prediction of Trolox-equivalent antioxidant capacity (TEAC) QM descriptors, is presented. Sum of ranking differences (SRD) was used for ranking of the six methods with respect to the contributions of the calculated QM molecular descriptors toward TEAC. The results show that the PaD, PaD₂ and profile methods are the most stable and give rise to realistic interpretation of the observed correlations. Therefore, they are safely applicable for future interpretations without the opinion of an experienced chemist or bio-analyst. © 2018 Wiley Periodicals, Inc.