Encapsulation of debittered pomelo juice using novel Moringa oleifera exudate for enrichment of yoghurt: A techno-functional approach

Debittering of pomelo juice was conducted using 3.7 g of activated resin, resulting in a 36.8% reduction in bitterness without affecting the bioactive properties of juice. The debittered juice was then encapsulated with Moringa oleifera exudate at various ratios (1-5%), yielding a powder with a slightly rough surface. Total phenol content (TPC) increased by 46-56% compared to the debittered juice. Functional yoghurt containing encapsulates at concentrations of 1% and 2% demonstrated that the 2% concentration led to longer storage duration, resulting in increased acidity and syneresis compared to the control. TPC of the yoghurt (161.89-198.22 μg Gallic acid equivalent (GAE)/g) remained significantly higher (p < 0.05) than that of the control (47.15 μg GAE/g) and acacia gum-based yoghurt (141.89-171.37 μg GAE/g), decreasing with storage duration. Addition of encapsulates significantly altered the yoghurt's texture, resulting in lower firmness (0.57 to 0.64 N) compared to the control, while adhesiveness values remained comparable (6.33 to 6.25 g.s). The highest values of G' and G" were observed in samples containing 2% encapsulates with moringa compared to those with acacia gum. This study suggests potential avenues for further exploration in functional foods with enhanced health benefits.

Determination of Drying Characteristics and Physicochemical Properties of Mint (Mentha spicata L.) Leaves Dried in Refractance Window

Drying is one of the most common and effective techniques for preserving the quantitative and qualitative characteristics of medicinal plants in the post-harvest phase. Therefore, in this research, the effect of the new refractance window (RW) technology on the kinetics, thermodynamics, greenhouse gasses, color indices, bioactive properties, and percentage of mint leaf essential oil was investigated in five different water temperatures in the form of a completely randomized design. This process was modeled by the methods of mathematical models and artificial neural networks (ANNs) with inputs (drying time and water temperature) and an output (moisture ratio). The results showed that with the increase in temperature, the rate of moisture removal from the samples increased and as a result, the drying time, specific energy consumption, CO2, NOx, enthalpy, and entropy decreased significantly (p < 0.05). In addition, the drying water temperature had a significant effect on the rehydration ratio, color indices, bioactive properties, and essential oil percentage of the samples (p < 0.05). The highest value of rehydration ratio was obtained at 80 °C. By increasing temperature, the main color indices such as b*, a*, L*, and Chroma decreased significantly compared to the control (p < 0.05). However, with the increase in temperature, the overall color changes (ΔE) and L* first had a decreasing trend and then an increasing trend, and this trend was the opposite for the rest of the indicators. The application of drying water temperature from 50 to 70 °C increased antioxidant, phenol content, and flavonoid content, and higher drying temperatures led to a significant decrease in these parameters (p < 0.05). On the other hand, the efficiency of the essential oil of the samples was in the range of 0.82 to 2.01%, and the highest value was obtained at the water temperature of 80 °C. Based on the analysis performed on the modeled data, a perceptron artificial neural network with 2-15-14-1 structure with explanation coefficient (0.9999) and mean square error (8.77 × 10-7) performs better than the mathematical methods for predicting the moisture ratio of mint leaves.

Conductive hydro drying of ripened papaya: optimization and product characterization

This study addresses the product-process characterization of refractance window drying of ripened papaya, considering the abundant availability and underutilization of the perishable product. A statistical design approach with varied drying temperature, time and sample thickness has been adopted to characterize moisture content, total phenolic content, total flavonoid content, vitamin C, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity. The model fitting, analysis of variance, and numerical optimization showed that the quadratic model was the most suitable model for the response variables. The optimum process parameters were attained at a drying temperature of 90 °C, time 86.92 min, and sample thickness of 2.93 mm. The optimal responses were moisture content 2.81%, total phenolic content 305.58 mg GAE/g, total flavonoid content 51.92 mg QUE/g, DPPH radical scavenging activity 91.56% and vitamin C 219.88 mg/100 g. With such high essential nutrients, refractance window dried ripened papaya can be utilized for commercially viable value-added food products.