Experimental Design and Optimization of Decolourization of Reactive Black-5 Dye Using Cloud Point Extraction

A two-phase separation method called cloud point extraction (CPE) does not use hazardous or flammable organic solvents. The efficient removal of the dye Reactive Black-5 (RB-5) from an aqueous solution using Triton X-114, a nonionic surfactant, is described in this study. Three-level factorial design and response-surface methods were used to quantify the impact of process variables on the CPE process, such as operating temperature and surfactant concentration. Investigations were conducted into how these process variables affected the ratio between the phase volumes, the concentration of dye in the surfactant-rich phase, and the residual amounts of dye in the diluted phase. As a result, ANOVA was used to create and validate mathematical models. The findings demonstrated that the correlation coefficients (R2) exceeded 0.98. The acquired findings showed that the suggested extraction process is efficient, and the proposed CPE approach removes 98% of the RB-5 dye under optimal conditions.

Semi-continuous production of xanthan in biofilm reactor using Xanthomonas campestris

Semi-continuous production of xanthan gum using self-immobilized Xanthomonas campestris cells in biofilm reactors was studied. Fermentation was carried out using two different designs of biofilm reactor equipped with a) stainless-steel support (SSS) and b) polyethylene support (PES). Fermentation was performed in three cycles with refreshing the media at the beginning of each: cycle 1, 0-27 h; cycle 2, 27-54 h; and cycle 3, 54-78.5 h. Results showed that the glucose consumption and the pH reduction in the PES biofilm reactor was faster compared to the SSS biofilm reactor. Scanning electron microscopy showed that the SSS was capable to immobilize more cells during the growth of X. campestris. The maximum concentration of xanthan gum in the SSS biofilm reactor obtained after 27 h (3.47 ± 0.71 g/L), while the maximum concentration of xanthan in the PES biofilm reactor obtained after 78.5 h (3.21 ± 0.68 g/L). Thermal stability analysis of xanthan using differential scanning calorimetry showed the presence of two fractures attributed to dehydration and degradation of polymer. The thermogram represented both endothermal and exothermal behaviour of xanthan polymer. Furthermore, the functional groups and molecular structure of the xanthan produced in this study was evaluated using Fourier transform infrared spectrometry and also proton nuclear magnetic resonance. in addition, the surface tension of (0.2 %, w/v) xanthan gum solution was in a range of 52.16-56.5 mN/m. Rheological analysis of xanthan showed that the G' values were higher than the G″ in all frequencies demonstrating a relatively high elasticity of the produced xanthan gum.

Microencapsulation May Preserve the Viability of Probiotic Bacteria During a Baking Process and Digestion: A Case Study with Bifidobacterium animalis Subsp. lactis in Bread

The high sensitivity of probiotic bacteria (PB) to many environmental factors limits the number of food products where they can be incorporated. This study aimed to examine the capability of a unique three-layered microcapsule structure to protect PB against extremely elevated temperatures and low pHs to allow their incorporation into bakery goods. The microcapsules were prepared first by granulation of a Bifidobacterium lactis (BL) strain, as a model PB, to form a core, and then coating the core with three consecutive protective layers. The physical features and the shape of the microcapsules obtained from three sequential preparations were characterized using various methods. A viable cell count was utilized to evaluate the efficiency of the microcapsule structure to protect the bacteria during a bread-baking process carried out at 180 °C for 40 min and also during the exposure to simulated gastric fluid (pH 1.2) for up to 1 h. The results showed that whereas the free bacteria (unprotected BL) encountered a significant viability loss under these conditions, the microencapsulated BL presented superior resistance.

Modelling the microbial dynamics and antimicrobial resistance development of Listeria in viscoelastic food model systems of various structural complexities

Minimal processing for microbial decontamination, such as the use of natural antimicrobials, is gaining interest in the food industry as these methods are generally milder than conventional processing, therefore better maintaining the nutritional content and sensory characteristics of food products. The aim of this study was to quantify the impact of (i) structural composition and complexity, (ii) growth location and morphology, and (iii) the natural antimicrobial nisin, on the microbial dynamics of Listeria innocua. More specifically, viscoelastic food model systems of various compositions and internal structure were developed and characterised, i.e. monophasic Xanthan gum-based and biphasic Xanthan gum/Whey protein-based viscoelastic systems. The microbial dynamics of L. innocua at 10 °C, 30 °C and 37 °C were monitored and compared for planktonic growth in liquid, or in/on (immersed or surface colony growth) the developed viscoelastic systems, with or without a sublethal concentration of nisin. Microscopy imaging was used to determine the bacterial colony size and spatial organisation in/on the viscoelastic systems. Selective growth of L. innocua on the protein phase of the developed biphasic system was observed for the first time. Additionally, significant differences were observed in the colony size and distribution in the monophasic Xanthan gum-based systems depending on (i) the type of growth (surface/immersed) and (ii) the Xanthan gum concentration. Furthermore, the system viscosity in monophasic Xanthan gum-based systems had a protective role against the effects of nisin for immersed growth, and a further inhibitory effect for surface growth at a suboptimal temperature (10 °C). These findings give a systematic quantitative insight on the impact of nisin as an environmental challenge on the growth and spatial organisation of L. innocua, in viscoelastic food model systems of various structural compositions/complexities. This study highlights the importance of accounting for system structural composition/complexity when designing minimal food processing methods with natural antimicrobials.

Learning-Based Cell Injection Control for Precise Drop-on-Demand Cell Printing

Drop-on-demand (DOD) printing is widely used in bioprinting for tissue engineering because of little damage to cell viability and cost-effectiveness. However, satellite droplets may be generated during printing, deviating cells from the desired position and affecting printing position accuracy. Current control on cell injection in DOD printing is primarily based on trial-and-error process, which is time-consuming and inflexible. In this paper, a novel machine learning technology based on Learning-based Cell Injection Control (LCIC) approach is demonstrated for effective DOD printing control while eliminating satellite droplets automatically. The LCIC approach includes a specific computational fluid dynamics (CFD) simulation model of piezoelectric DOD print-head considering inverse piezoelectric effect, which is used instead of repetitive experiments to collect data, and a multilayer perceptron (MLP) network trained by simulation data based on artificial neural network algorithm, using the well-known classification performance of MLP to optimize DOD printing parameters automatically. The test accuracy of the LCIC method was 90%. With the validation of LCIC method by experiments, satellite droplets from piezoelectric DOD printing are reduced significantly, improving the printing efficiency drastically to satisfy requirements of manufacturing precision for printing complex artificial tissues. The LCIC method can be further used to optimize the structure of DOD print-head and cell behaviors.