Optimization of oil extraction from Pitanga (Eugenia uniflora L.) leaves using simplex centroid design

Updating the status quo on the extraction of bioactive compounds in agro-products using a two-pot multivariate design. A comprehensive review

Extraction is regarded as the most crucial stage in analyzing bioactive compounds. Nonetheless, due to the intricacy of the matrix, numerous aspects must be optimized during the extraction of bioactive components. Although one variable at a time (OVAT) is mainly used, this is time-consuming and laborious. As a result, using an experimental design in the optimization process is beneficial with few experiments and low costs. This article critically reviewed two-pot multivariate techniques employed in extracting bioactive compounds in food in the last decade. First, a comparison of the parametric screening methods (factorial design, Taguchi, and Plackett-Burman design) was delved into, and its advantages and limitations in helping to select the critical extraction parameters were discussed. This was followed by a discussion of the response surface methodologies (central composite (CCD), Doehlert (DD), orthogonal array (OAD), mixture, D-optimal, and Box-Behnken designs (BBD), etc.), which are used to optimize the most critical variables in the extraction of bioactive compounds in food, providing a sequential comprehension of the linear and complex interactions and multiple responses and robustness tests. Next, the benefits, drawbacks, and possibilities of various response surface methodologies (RSM) and some of their usages were discussed, with food chemistry, analysis, and processing from the literature. Finally, extraction of food bioactive compounds using RSM was compared to artificial neural network modeling with their drawbacks discussed. We recommended that future experiments could compare these designs (BBD vs. CCD vs. DD, etc.) in the extraction of food-bioactive compounds. Besides, more research should be done comparing response surface methodologies and artificial neural networks regarding their practicality and limitations in extracting food-bioactive compounds.

Characterization model of silicon dioxide melting based On image analysis

The silicon dioxide is the hardest part to melt among the iron tailing components, the melting behavior of iron tailing can be represented by the melting behavior of silicon dioxide. Estimating the real-time melting rate of silicon dioxide in the time sequence provide guidance for the tailing addition and heat compensation in the process of slag cotton preparation, also indirectly improved the direct fiber forming technology of blast furnace slag. The position of silicon dioxide particles in the high-temperature molten pool during the melting process is changing constantly, using a strong weighted distance centroid algorithm to rack the centroid position of silicon dioxide particles during the melting process, and present the motion trail of centroid of silicon dioxide. In the paper, extracting indexes which represent the edge outline characteristics of silicon dioxide during the melting process of silicon dioxide using Snake active contour algorithm combined with Sobel operator, include shape, perimeter and area. Using the extracted skeleton characteristics, a three-dimensional skeleton generation model is created. From the skeleton data, estimating the volume of silicon dioxide and determine the parameter formula for the actual melting rate of silicon dioxide. The silicon dioxide melting rate at each moment is calculated by numerical simulation. The results of the Hough test circle and the silicon dioxide melting rate are verified. The rationality of the model is further determined.

Recent Applications of Mixture Designs in Beverages, Foods, and Pharmaceutical Health: A Systematic Review and Meta-Analysis

Design of Experiments (DoE) is a statistical tool used to plan and optimize experiments and is seen as a quality technology to achieve products excellence. Among the experimental designs (EDs), the mixture designs (MDs) stand out, being widely applied to improve conditions for processing, developing, or formulating novel products. This review aims to provide useful updated information on the capacity and diversity of MDs applications for the industry and scientific community in the areas of food, beverage, and pharmaceutical health. Recent works were selected following the Preferred Reporting Items for Systematic Review and Meta-Analyses statement (PRISMA) flow diagram. Data analysis was performed by self-organizing map (SOM) to check and understand which fields of application/countries/continents are using MDs. Overall, the SOM indicated that Brazil presented the largest number of works using MDs. Among the continents, America and Asia showed a predominance in applications with the same amount of work. Comparing the MDs application areas, the analysis indicated that works are prevalent in food and beverage science in the American continent, while in Asia, health science prevails. MDs were more used to develop functional/nutraceutical products and the formulation of drugs for several diseases. However, we briefly describe some promising research fields in that MDs can still be employed.

Optimal conditions for adsorption of zinc from industrial wastewater using groundnut husk ash

Zinc is a toxic metal ion and is of importance in water and wastewater because it causes dizziness as well as lethargy when ingested by man. In the current study, the groundnut husk ash was investigated as a potential adsorbent for adsorption of zinc(II) ions from industrial wastewater. Groundnut husk ash was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy and proximate analysis to identify the presence of the functional groups, surface morphology and the carbon content in the adsorbent respectively. To optimize the process parameters affecting the percentage removal of zinc(II) onto groundnut husk ash, the central composite design was used. The result of the optimization study showed an optimal percentage removal of 80.00%, with the optimal conditions of 1400 μm, 100 min, 25 °C, 40 mg/l and 20 mg for particle size, contact time, temperature, initial zinc concentration and adsorbent dosage respectively. The equilibrium data showed a better fit for Langmuir isotherm, when compared to Freundlich, Temkin and Dubinin-Radushkevich isotherms, with R² of 0.965. The adsorption kinetics was best described by pseudo-second-order kinetics with R² of 0.987. The thermodynamic study, on the other hand, showed a negative value of enthalpy change(∆H = - 27.021), indicating an exothermic as well as a spontaneous reaction, with the degree of spontaneity of the reaction ranging from - 55.487 ≤ ∆G ≤ - 56.427, which showed a corresponding increase in Gibb's free energy (∆G) with an increase in temperature.