Chitin extraction from crab shells was studied experimentally and optimized aiming to obtain chitosan with predefined deacetylation degree and molecular mass. To find out the optimum operating conditions that ensure the obtaining of a chitosan with highest deacetylation degree and specific molecular mass four parameters were varied: the concentration of NaOH and the temperature for deproteinization step, respectively HCl concentration and the number of acidic treatments for the demineralization stage. The experiment was carried on following Taguchi orthogonal array L9, and the best combination of factors was found using the desirability function approach. The optimization results showed that 5% NaOH concentration and low temperatures lead to a chitosan with high deacetylation degree. High molecular mass chitosan is obtained when a single step acidic treatment is used, while a chitosan with low molar mass is obtained for multiple acid contacts and higher HCl concentration.

Shrimp waste is a valuable source for chitin extraction and consequently for chitosan preparation. In the process of obtaining chitosan, a determining step is the chitin deacetylation. The main characteristic of chitosan is the degree of deacetylation, which must be as high as possible. The molar mass is another important parameter that defines its utilizations, and according to these, high or low molar masses are required. The present study is an attempt to optimize the deacetylation step to obtain chitosan with a high degree of deacetylation and high or low molar mass. The study was carried out based on experimental data obtained in the frame of a central composite design where three working parameters were considered: NaOH concentration, liquid:solid ratio, and process duration. The regression models defined for the degree of deacetylation (DD) and for the mean molar mass (MM) of chitosan powders were used in the formulation of optimization problems. The objectives considered were simultaneous maximum DD and maximum/minimum MM for the final chitosan samples. For these purposes, multiobjective optimization problems were formulated and solved using genetic algorithms implemented in Matlab^®. The multiple optimal solutions represented by trade-offs between the two objectives are presented for each case.

Any change in the composition or physicochemical parameters of honey outside the standardized intervals may be deemed fraud, irrespective of direct introduction of certain substances or feeding honeybees with syrups. Simple and rapid tools along with more sophisticated ones are required to monitor fraudulent practices in the honey trade. In this work, UV–Vis spectroscopy was used to identify and quantify six Romanian honey types (five monofloral and one polyfloral) mixed with commercially available corn syrup, corn syrup with plant extracts, inverted syrup, and fruit syrup at different concentrations (5%, 10%, 20%, 30%, 40%, and 50%). Relevant spectral features were used to develop a neural model, which was able to pinpoint adulteration, regardless of the honey and adulterant type. The proposed model was able to detect adulteration levels higher than 10%, thereby serving as a cost-effective and reliable tool to monitor honey quality.

New green and sustainable sources were chosen to obtain chitosan, an important material, with many applications in different fields. The present study is focused on egg capsules of Rapana venosa waste as raw material for chitosan oligomers. As previous studies revealed that chitosan extraction from this material takes place with a low yield, the present research aimed to optimize this step. A 2² experimental plan, with three replicates in the center, was proposed to investigate the influence of NaOH concentration and temperature on the yield extraction. After a primary analysis of the experimental data, a favorable temperature value was selected (90 °C) at which the total dissolution of the egg capsules was obtained. Then, at this temperature, the experimental plan was extended exploring the influence of the NaOH concentration on three levels (5, 6, and 7%) and the extraction duration on two levels (60 and 85 min). Based on all experimental data, a neural model was obtained and validated. The neural model was used to maximize the yield, applying Genetic Algorithm (GA) implemented in Matlab^®. The resulting optimal solution is: NaOH concentration 6.47%, temperature 90 °C, duration 120 min, with a yield value of 7.05%.

Chitosan is a natural polymer with numerous biomedical applications. The cellular activity of chitosan has been studied in various types of cancer, including melanoma, and indicates that these molecules can open new perspectives on antiproliferative action and anticancer therapy. This study analyzes how different chitosan conformations, such as α-chitosan (CH) or β-oligochitosan (CO), with various degrees of deacetylation (DDA) and molar mass (MM), both in different concentrations and in CH–CO mixtures, influence the cellular processes of SK-MEL-28 melanocytes, to estimate the reactivity of these cells to the applied treatments. The in vitro evaluation was carried out, aiming at the cellular metabolism (MTT assay), cellular morphology, and chitinase-like glycoprotein YKL-40 expression. The in vitro effect of the CH–CO mixture application on melanocytes is obvious at low concentrations of α-chitosan/β-oligochitosan (1:2 ratio), with the cell’s response supporting the hypothesis that β-oligo-chitosan amplifies the effect. This oligochitosan mixture, favored by the β conformation and its small size, penetrates faster into the cells, being more reactive when interacting with some cellular components. Morphological effects expressed by the loss of cell adhesion and the depletion of YKL-40 synthesis are significant responses of melanocytes. β-oligochitosan (1.5 kDa) induces an extension of cytophysiological effects and limits the cell viability compared to α-chitosan (400–900 kDa). Statistical analysis using multivariate techniques showed differences between the CH samples and CH–CO mixtures.

The goal of this study was to explore how different operating parameters influence the performance of a polyvinyl alcohol (PVA) membrane in pervaporation for separating ethanol–water mixtures. Specifically, the focus was on understanding how variations in feed composition, temperature, and permeate pressure affect the separation efficiency. The study aimed to provide a range of operating conditions that offer a balance between maximizing both the purity and quantity of ethanol. This was achieved through statistical models, which were generated by simulating the pervaporation process under various conditions using COMSOL Multiphysics^® 6.3 and following a Box–Behnken design. It was found that similar operating conditions (temperature ~100 °C; pressure ~4–5 kPa) are suitable for both kinds of mixtures near azeotrope, with higher water content (~0.15 mass fraction) and lower water content (~0.05 mass fraction) obtaining very high recuperation degrees (generally above 99%). For more concentrated solutions (lower water content), it was possible to obtain optimal trade-off solutions (separation degree vs. retentate enrichment in ethanol), even at lower temperatures (~80 °C).