Jerusalem Artichoke Tuber Processing: Influence of Pre-Treatment Methods, Lactic Acid, and Propionic Acid Bacteria Strains on Functional Fermented Beverage Production.

Fermented plant-based products are rapidly gaining popularity. Jerusalem artichoke is a medicinal plant that can be used to make fermented beverages. Samples were subjected to pretreatment (ultrasound at 35 kHz for 2, 4, and 6 min, freezing at -80 °C and -17 °C) while an untreated sample was used as control. It was shown that all types of pretreatments did not lead to an increase in protein, solids, polyphenols, and carbohydrates compared to the control sample. The greatest decrease in the values of these indicators occurs when pre-freezing tubers are used for Jerusalem artichoke dispersion production. It was also found that samples frozen at -80 °C had a significantly higher concentration of Ca, Si, Mg, and P whereas untreated samples frozen at -17 °C had more Al, K, Cu, Sr, and Cr. The processing method can affect the sensory descriptors of Jerusalem artichoke tuber dispersions to different extents, but the preference was for the control sample without pre-treatment. The fermentation of Jerusalem artichoke tuber dispersions demonstrated that S. thermophilus induced the most rapid fermentation (pH 4.75 in 5 h). The highest antioxidant activity after fermentation (55.39% FRSA) was shown for L. acidophilus H9, while the highest % FRSA value during the storage period was for L. bulgaricus (67.5%) on day 5 after fermentation. The highest viability among all selected microorganisms was detected for L. bulgaricus, L. acidophilus AT-41, and B. coagulans MTCC 5856 with the increase in biomass content by 2.3, 2.27, and 2.12 log10CFU/ml after fermentation. According to the results of sensory evaluation using hybrid hedonic scale the best results were shown for samples fermented with L. bulgaricus.

Social, ethical, environmental, economic and technological aspects of rabbit meat production - A critical review.

Rabbit (RM) has become a valuable source of nutrients since the 1970s, helping to transform the European food industry into the largest RM producer in the world. However, the RM industry is experiencing a critical period of ethical imbalance. This trend, described as feed conversion ratio, impacts the environmental and financial performance of RM farms, which could lead to an increase production of industrial waste. In addition, the loss of corporate ethical responsibility and sustainable development by RM-oriented companies has further exacerbated the situation. Our objective was to summarize current trends in the RM industry and markets, highlighting possible strengths and weaknesses. This review shows current approaches in sustainable techniques in RM production processes, ethical issue, environmental and processing responsibility of RM producers, as well as social responsibilities and ethical practices of slaughterhouses and RM producers, sustainable environmental practices of slaughterhouses, technological aspects and safety of RM and social drivers in RM market. The analysis of reviewed literature revealed the potential strategies for sustainable RM production.

Electrochemical platform for detecting Escherichia coli bacteria using machine learning methods.

We present an electrochemical platform designed to reduce time of Escherichia coli bacteria detection from 24 to 48-h to 30 min. The presented approach is based on a system which includes gallium-indium (eGaIn) alloy to provide conductivity and a hydrogel system to preserve bacteria and their metabolic species during the analysis. The work is dedicated to accurate and fast detection of Escherichia coli bacteria in different environments with the supply of machine learning methods. Electrochemical data obtained during the analysis is processed via multilayer perceptron model to identify i.e. predict bacterial concentration in the samples. The performed approach provides the effectiveness of bacteria identification in the range of 102-109 colony forming units per ml with the average accuracy of 97%. The proposed bioelectrochemical system combined with machine learning model is prospective for food analysis, agriculture, biomedicine.

Influence of pre-treatment methods on quality indicators and mineral composition of plant milk from different sources of raw materials.

BACKGROUND: Pre-treatment of plant materials is essential in producing plant-based products and can affect their various organoleptic and physicochemical characteristics. This work aimed to study the effect of pre-treatment of vegetable raw materials, namely ultrasonic processing and freezing of raw materials under various low-temperature conditions, to obtain multiple types of vegetable milk and determine their characteristics. RESULTS: It is shown that by applying a certain kind of pre-treatment of vegetable raw materials it is possible to adjust organoleptic parameters and the content of solids, protein, fat, carbohydrates, fiber and mineral composition of various types of vegetable milk from soy, rice, oats, wheat, peas, buckwheat, pumpkin seeds and lentils. Ultrasound pre-treatment allows increasing of polyphenol content by an average of 15-20% for all types of plant milk, except for lentil milk. The results showed that ultrasound treatment for 3 min had the most significant effect on the overall acceptability for lentils, pumpkin, rice and pea milk. Pre-freezing at a temperature regime of -17 and -85 °C contributed to an increase in Fe, K, Zn, Ca, Mg, Si and P by an average of 30-100%, depending on the plant material. CONCLUSION: Pre-treatment of vegetable raw materials, including freezing and ultrasonic treatment, can positively affect the macro- and micronutrient composition of plant milk. However, the effect may vary depending on the type of raw material and processing conditions. © 2023 Society of Chemical Industry.

Diffusion-Limited Processes in Hydrogels with Chosen Applications from Drug Delivery to Electronic Components.

Diffusion is one of the key nature processes which plays an important role in respiration, digestion, and nutrient transport in cells. In this regard, the present article aims to review various diffusion approaches used to fabricate different functional materials based on hydrogels, unique examples of materials that control diffusion. They have found applications in fields such as drug encapsulation and delivery, nutrient delivery in agriculture, developing materials for regenerative medicine, and creating stimuli-responsive materials in soft robotics and microrobotics. In addition, mechanisms of release and drug diffusion kinetics as key tools for material design are discussed.

Food gels: principles, interaction mechanisms and its microstructure.

Food hydrogels are important materials having great scientific interest due to biocompatibility, safety and environment-friendly characteristics. In the food industry, hydrogels are widely used due to their three-dimensional crosslinked networks. Furthermore, they have attracted great attention due to their wide range of applications in the food industry, such as fat replacers, encapsulating agents, target delivery vehicles, and many more. In addition to basic and recent knowledge on food hydrogels, this review exclusively focuses on sensorial perceptions, nutritional significance, body interactions, network structures, mechanical properties, and potential hydrogel applications in food and food-based matrices. Additionally, this review highlights the structural design of hydrogels, which provide the forward-looking idea for future applications of food hydrogels (e.g., 3D or 4D printing).

Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection.

We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min. Machine learning and robotized bioanalytical platforms require the principles such as hydrogel-based actuators for fast and easy analysis of bioactive analytes. Bacteria are fragile and environmentally sensitive microorganisms that require a special environment to support their lifecycles during analytical tests. Here, we develop a bio-electrochemical platform based on the soft hydrogel/eutectic gallium-indium alloy interface for the detection of Streptococcus thermophilus and Bacillus coagulans bacteria in various mediums. The soft hydrogel-based device is capable to support bacteria' viability during detection time. Current-voltage data are used for multilayer perceptron algorithm training. The multilayer perceptron model is capable of detecting bacterial concentrations in the 104 to 108 cfu/mL range of the culture medium or in the dairy products with high accuracy (94%). Such a fast and easy biodetection is extremely important for food and agriculture industries and biomedical and environmental science.

Periodic Self-Assembly of Poly(ethyleneimine)-poly(4-styrenesulfonate) Complex Coacervate Membranes.

Coacervation is a self-assembly strategy based on the complexation of polyelectrolytes, which is utilized in biomedicine and agriculture, as well as automotive and textile industries. In this paper, we developed a new approach to the on-demand periodic formation of polyelectrolyte complexes through a Liesegang-type hierarchical organization. Adjustment of reaction conditions allows us to assemble materials with a tunable spatiotemporal geometry and establish materials' production cycles with a regulated periodicity. The proposed methodology allows the membrane to self-assemble when striving to reach balance and self-heal after exposure to external stimuli, such as potential difference and high pH. Using chronopotentiometry, K+ ion permeability behavior of the PEI-PSS coacervate membranes was demonstrated. The periodically self-assembled polyelectrolyte nanomembranes could further be integrated into novel energy storage devices and intelligent biocompatible membranes for bionics, soft nanorobotics, biosensing, and biocomputing.

Biocompatible pH-Degradable Functional Capsules Based on Melamine Cyanurate Self-Assembly.

Development of adaptive self-regulating materials and chemical-biological systems-self-healing, self-regulating, etc.-is an advanced modern trend. The very sensitive pH-controlled functionality of supramolecular assemblies is a very useful tool for chemical and biochemical implementations. However, the assembly process can be tuned by various factors that can be used for both better functionality control and further functionalization such as active species, e.g., drugs and dyes, and encapsulation. Here, the effect of a dye, sodium fluorescein (uranine) (FL), on the formation of a self-assembled melamine cyanurate (M-CA) structure is investigated and calculated with density functional theory (DFT) and molecular dynamics. Interestingly, the dye greatly affects the self-assembly process at early stages from the formation of dimers, trimers, and tetramer to nucleation control. The supramolecular structure disassembly and subsequent release of trapped dye occurred under both high- and low-pH conditions. This system can be used for time-prolonged bacterial staining and development of supramolecular capsules for the system chemistry approach.