Ultrasound assisted extraction of phytochemicals from Piper betel L.

Piper betel contains phytochemicals with diverse pharmacological effects. The objective of this study was to enhance the extraction efficiency of phytochemicals and the chlorophyll content using ultrasonication. The Box-Behnken design was employed to optimize the time (10, 20, 30 min), temperature (20, 30, and 40 °C), and solid-solvent ratio (1:10, 1:20, 1:30) by utilizing response surface methods with three independent variables. Multiple parameters, including extract yield, total phenol, total flavonoid, antioxidant activity, and chlorophyll content were used to optimize the conditions. The linear relationship between power intensity and responses was determined to be statistically significant, with a p-value less than 0.01. The interaction effect of temperature, time, and ratio of solid solvent was shown to be statistically significant (p < 0.05) for all the obtained results. The optimal parameters for achieving the highest extract yield were as follows: a temperature of 40 °C, a sonication time of 30 min, and a solid solvent ratio of 1:10. These conditions result in an extract yield of 21.99 %, a total flavonoid content of 44.97 mg/GAE, a total phenolic content of 185.05 mg/GAE, a DPPH scavenging activity of 99.1 %, and a chlorophyll content of 49.95 mg/ml. This study highlights the significance of customized extraction methodologies for optimizing the bioactive capacity of phytochemicals derived from betel leaves. The elucidation of extraction parameters and the resultant phytochemical profiles serves as a fundamental framework for the advancement of innovative pharmaceuticals and nutraceuticals, capitalizing on the therapeutic attributes of this traditional medicinal botanical.

Exploring the Ecological Implications, Gastronomic Applications, and Nutritional and Therapeutic Potential of Juglans regia L. (Green Walnut): A Comprehensive Review.

The green walnut, which is frequently overlooked in favor of its more mature sibling, is becoming a topic of great significance because of its unique ecological role, culinary flexibility, and therapeutic richness. The investigation of the bioactive substances found in green walnuts and their possible effects on human health has therapeutic potential. Juglans regia L. is an important ecological component that affects soil health, biodiversity, and the overall ecological dynamic in habitats. Comprehending and recording these consequences are essential for environmental management and sustainable land-use strategies. Regarding cuisine, while black walnuts are frequently the main attraction, green walnuts have distinct tastes and textures that are used in a variety of dishes. Culinary innovation and the preservation of cultural food heritage depend on the understanding and exploration of these gastronomic characteristics. Omega-3 fatty acids, antioxidants, vitamins, and minerals are abundant in green walnuts, which have a comprehensive nutritional profile. Walnuts possess a wide range of pharmacological properties, including antioxidant, antibacterial, antiviral, anticancer, anti-inflammatory, and cognitive-function-enhancing properties. Consuming green walnuts as part of one's diet helps with antioxidant defense, cardiovascular health, and general well-being. Juglans regia L., with its distinctive flavor and texture combination, is not only a delicious food but also supports sustainable nutrition practices. This review explores the nutritional and pharmacological properties of green walnuts, which can be further used for studies in various food and pharmaceutical applications.

Ultrasound-assisted extraction of phytochemicals from green coconut shell: Optimization by integrated artificial neural network and particle swarm technique.

This study employs artificial neural network (ANN) and particle swarm optimization (PSO) to maximize antioxidant and antimicrobial activity from green coconut shells. Phytochemical analysis was carried out on the extract obtained from ultrasound-assisted extraction performed at different combinations of time (10, 20, and 30 min), temperature (30, 35, and 40 °C), and the ratio of solid-solvent (1:10, 1:20, and 1:30 g/ml). The presence of these bioactive compounds exhibits antimicrobial and antioxidant activities. Quantitative analysis showed that the total phenolic compounds ranged from 7.08 to 33.46 mg GAE/g, flavonoids ranged from 2.09 to 28.46 mg QE/g, tannins ranged from 70.5 to 141.09 mg TAE/g, and antioxidant activity of 49.98-66.1 %. The FTIR analysis detected the presence of C[bond, double bond]O, O-H, and C-H bonds. The optimized condition of ultrasound-assisted extraction (UAE) was compared with the optimized condition of the microwave. The result of ultrasound-assisted extraction was observed to be better than microwave-assisted extraction.

Extraction and Encapsulation of Phytocompounds of Poniol Fruit via Co-Crystallization: Physicochemical Properties and Characterization.

Poniol (Flacourtia jangomas) has beneficial health effects due to its high polyphenolic and good antioxidant activity content. This study aimed to encapsulate the Poniol fruit ethanolic extract to the sucrose matrix using the co-crystallization process and analyze the physicochemical properties of the co-crystalized product. The physicochemical property characterization of the sucrose co-crystallized with the Poniol extract (CC-PE) and the recrystallized sucrose (RC) samples was carried out through analyzing the total phenolic content (TPC), antioxidant activity, loading capacity, entrapment yield, bulk and traped densities, hygroscopicity, solubilization time, flowability, DSC, XRD, FTIR, and SEM. The result revealed that the CC-PE product had a good entrapment yield (76.38%) and could retain the TPC (29.25 mg GAE/100 g) and antioxidant properties (65.10%) even after the co-crystallization process. Compared to the RC sample, the results also showed that the CC-PE had relatively higher flowability and bulk density, lower hygroscopicity, and solubilization time, which are desirable properties for a powder product. The SEM analysis showed that the CC-PE sample has cavities or pores in the sucrose cubic crystals, which proposed that the entrapment was better. The XRD, DSC, and FTIR analyses also showed no changes in the sucrose crystal structure, thermal properties, and functional group bonding structure, respectively. From the results, we can conclude that co-crystallization increased sucrose's functional properties, and the co-crystallized product can be used as a carrier for phytochemical compounds. The CC-PE product with improved properties can also be utilized to develop nutraceuticals, functional foods, and pharmaceuticals.

Modelling of ultrasonic assisted osmotic dehydration of cape gooseberry using adaptive neuro-fuzzy inference system (ANFIS).

In the present investigation, the cape gooseberry (Physalis peruviana L.) was preserved by the application of osmotic dehydration (sugar solution) with ultrasonication. The experiments were planned based on central composite circumscribed design with four independent variables and four dependent variables, which yielded 30 experimental runs. The four independent variables used were ultrasonication power (XP) with a range of 100-500 W, immersion time (XT) in the range of 30-55 min, solvent concentration (XC) of 45-65 % and solid to solvent ratio (XS) with range 1:6-1:14 w/w. The effect of these process parameters on the responses weight loss (YW), solid gain (YS), change in color (YC) and water activity (YA) of ultrasound assisted osmotic dehydration (UOD) cape gooseberry was studied by using response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS). The second order polynomial equation successfully modeled the data with an average coefficient of determination (R2) was found to be 0.964 for RSM. While for the ANFIS modeling, Gaussian type membership function (MF) and linear type MF was used for the input and output, respectively. The ANFIS model formed after 500 epochs and trained by hybrid model was found to have average R2 value of 0.998. On comparing the R2 value the ANFIS model found to be superior over RSM in predicting the responses of the UOD cape gooseberry process. So, the ANFIS was integrated with a genetic algorithm (GA) for optimization with the aim of maximum YW and minimum YS, YC and YA. Depending on the higher fitness value of 3.4, the integrated ANFIS-GA picked the ideal combination of independent variables and was found to be XP of 282.434 W, XT of 50.280 min, XC of 55.836 % and XS of 9.250 w/w. The predicted and experimental values of response at optimum condition predicted by integrated ANN-GA were in close agreement, which was evident by the relative deviation less than 7%.