Natural additives with antioxidant properties can be used as biodegradable and sustainable alternatives to synthetic products, because they can inhibit the biodiesel oxidation reaction, increasing oxidative stability and extending its storage period. This research evaluated the efficiency of jabuticaba peels, gabiroba leaves, and hibiscus flowers in ethanolic extracts, analyzing through the simplex-centroid design, the induction periods (IP) and rate constants (k) of the biodiesel oxidation reaction at 110 °C. Antioxidant activity was observed in all extracts, either decreasing k or increasing the IP. The mathematical models obtained showed coefficients of determination greater than 0.9400, a non-significant lack of fit at the 5% level, and low dispersion between predicted and experimental data, indicating that the 1st order reaction fit was appropriate and can be used for predictive purposes. In this work, the optimization was performed with maximization of IP and minimization of k showing that the mixture containing 25% of jabuticaba peels extract and 75% of gabiroba leaves extract was the most suitable, because proportionally increased the IP and decreased k of the biodiesel oxidation reaction. It is possible to suggest the use of jabuticaba peels extract or gabiroba leaves extract as well as various combinations between them as antioxidant additives. products period extracts simplexcentroid simplex centroid design (IP (k 11 C °C 09400 0 9400 0.9400 nonsignificant non significant 5 level data st purposes work 25 75 suitable 1 0940 940 0.940 2 7 094 94 0.94 09 9 0.9 0.

The objective of the present work was to apply self-organizing feature maps (SOFM) and multilayer perceptron (MLP) to evaluate the protective capacity of tert-butylhydroquinone (TBHQ), butylhydroxyanisole (BHA), and butylhydroxytoluene (BHT) antioxidants against the biodiesel oxidation reaction. For this, the antioxidant concentration and the biodiesel compliance parameters were used as continuous input variables and the type of antioxidant as a categorical. The SOFM proved to be an adequate tool for the classification of biodiesel samples containing antioxidants. The performance of the 5 most active networks of the model ranged from 89 to 99% for training, testing, and validation with an error below 1.42 × 10-4. Statistical tests applied to validate the model showed no significant difference between predicted and experimental values. The global sensitivity analysis showed that the relative protection factor (RPF) contributed with 34.89%, the antioxidant with 31.49%, the induction period with 10.69%, the water content with 6.00%, and the others all together with 16.93% in the construction of the regression models by MLP. selforganizing self organizing (SOFM MLP (MLP tertbutylhydroquinone tert butylhydroquinone TBHQ, TBHQ , (TBHQ) BHA, BHA (BHA) BHT (BHT reaction this categorical 8 99 training testing 142 1 42 1.4 104. 104 10 4. 4 10-4 values RPF (RPF 3489 34 34.89% 3149 31 49 31.49% 1069 69 10.69% 600 6 00 6.00% 1693 16 93 16.93 (TBHQ (BHA 9 14 1. 10- 348 3 34.89 314 31.49 106 10.69 60 0 6.00 169 16.9 34.8 31.4 10.6 6.0 16. 34. 31. 10. 6.

Abstract The cosmetics industry searches for new products with sustainable, natural and non-toxic characteristics. Levan is a microbial exopolysaccharide composed of fructose units with β-2,6-glycoside bonds. Due to its biological properties, levan has a wide range of applications in cosmetics and pharmaceuticals industry. The effects of levan can be improved by its combination with biocompatible actives such as plant-derived compounds and vitamins resulting in a multifunctional cosmetic formulation. Thus, the aim of this study was to develop a new biocosmetic gel-anionic type containing 1 % of levan and plant-derived compounds, such as Aloe vera extract and avocado oil and vitamin E, using simplex lattice mixtures design. According to the statistical analyses, the concentrations to obtain a cosmetic with maximum antioxidant activity (76%), hydration capacity (98.37%) and spreadability (767.30 mm2), would be 10% (0.1 mL) of Aloe vera, and 90% (0.9 mL) of avocado oil. Cosmeceutical formulations showed good stability and did not show phase separation or visible changes being classified as normal. The development of innovative and sustainable cosmetic formulations, with natural, vegan and non-toxic molecules is of great importance for cosmetic industry.

The simultaneous diffusion of inorganic components in the olive pulp in wet brine was modeled based on Fick’s generalized 2nd Law and simulated using the finite element method. The main and crossed diffusion coefficients, the film coefficient and the Biot number were determined, with the application of the simplex optimization method, through the minimization of the percentage errors. The errors between the simulated and experimental data were 5.35% for NaCl and 4.77% for KCl and the adjusted main diffusion coefficients were 0.4358 × 10-12 m2 s-1 for NaCl and 0.5408 × 10-12 m2 s-1 for KCl. The system developed to simulate diffusion allows the control and modulation of the salts content that diffuses through the olive pulp. Ficks Fick s nd method determined 535 5 35 5.35 477 4 77 4.77 04358 0 4358 0.435 1012 10 12 10-1 m s1 1 s- 05408 5408 0.540 53 3 5.3 47 7 4.7 0435 435 0.43 101 10- 0540 540 0.54 5. 4. 043 43 0.4 054 54 0.5 04 0. 05

Olive samples were subjected to the salting process in brine containing 1196 mol m−3 of NaCl and 402 mol m−3 of KCl. Samples were collected during 60 h and salt concentration values were determined. With the finite element method (FEM) and the minimization of the errors percentage between the simulated and experimental values, the mass transfer coefficients in the film (hm) were obtained, being 1.0072 × 10−8 and 1.2499 × 10−8 for NaCl and KCl, respectively. The salts concentration at the olive/brine interface was simulated by FEM and analyzed via SOFM. A network with 4 × 4 topology and 10000 training epochs was used. It was observed that the influence of the stationary film formed on the surface of the olives during the salting process depends on the position, the salt involved in the diffusion and that the concentration of the salts, at each point, varies according to the immersion time. 119 m3 m 3 m− 40 KCl 6 determined (FEM hm (hm obtained 10072 1 0072 1.007 108 10 8 10− 12499 2499 1.249 respectively olivebrine olive SOFM 1000 used position point time 11 1007 007 1.00 1249 249 1.24 100 00 1.0 124 24 1.2 0 1. 12 2

Biodiesel is capable of replacing diesel because it has similar physicochemical properties, but this biofuel is susceptible to oxidation, which makes the application of antioxidant substances necessary. For this study, alcoholic extracts of senna leaves, hibiscus flowers, and blackberry were used. Biodiesel samples were submitted to physicochemical analysis to evaluate interference in the volume of these alcoholic extracts with antioxidant properties. The data obtained were processed using the neural network of the multilayer perceptron type (MLP). For the network’s training, 200 epochs were used. The samples were randomly divided into three groups, with 70% used for training, 15% for testing, and 15% for validation. The type of extract was considered as a categorical variable, the extract volume as a target variable, and the other ones as input variables. Among the 200 networks trained, with 5 to 20 hidden layers, the 5 with the best performance were highlighted. The Tukey test applied to the means showed no significant difference at the 5% level, between the value of the added volume and the means value predicted by the networks. The sensitive analysis showed that the most important input variable for the construction of the model was the type of extract.

Sodium chloride is used in the cheese salting process as it promotes sensory changes and food preservation. However, in excess can cause hypertension problems, and for this reason, it has been partially replaced by potassium chloride. In the present work, Prato cheese was subjected to joint diffusion of NaCl and KCl by immersion in static and stirred brine. The salt concentration values on the cheese surface were determined as a function of time. They were tabulated and presented to the self-organizing map (SOM)-type neural networks and the multilayer perceptron (MLP) for analysis and modeling of the film formed on the surface of the cheese during static and dynamic salting. The SOM network showed that the behavior of the diffusive process, on the surface of the cheese, depends on the analyzed position and that the points in which occupy similar positions, concerning the distance from the edge, have similar behavior. Regression models for NaCl and KCl were significant at the 5% level and can be used for predictive purposes.

The influence of the film formed during the salting of champignon mushrooms with brine containing NaCl and KCl was modeled using the finite elements method (FEM). It was verified that the film formed on the mushroom surface had a greater influence in the static salting since the diffusion of the ions was 7.5-fold smaller in this system than in the stirred salting. The application of self-organizing maps showed that the ions diffusion along the surface of the solid presented a heterogeneous occurrence and depended on the region for both static and stirred salting. A direct relation was observed among the mushroom surface morphology, the salts diffusion behavior, and the film formation. In addition, the film was not completely extinguished in the stirred system, although it has a minimal influence as the film formation is also dependent on the biosolid surface.

The NaCl and KCl diffusion in the film formed on the cheese surface during salting was simulated by the finite element method. The time and salts concentration values on the cheese surface were determined, tabulated, and presented to the multilayer perceptron neural network (MLP) for the regression modeling. The samples were divided into 70, 15 and 15% for training, testing, and validation, respectively. The networks with the best performance showed 5 to 12 hidden layers. The Tukey’s test showed that there was no significant difference, at the 5% level, between the time value used and the mean value modeled for training, testing, and validation for the NaCl. For the KCl, a significant difference was observed only for 2 training samples and 1 test sample. Sensitivity analysis showed that the discrete variable Z, which represents the static and dynamic systems, was the most important in the models’ construction.

Biodiesel is a biofuel produced by the esterification reaction. It is an option to replace fossil fuels, mainly diesel, due to its similar physical and chemical properties. In this research, a mathematical modeling was performed to predict the antioxidant mass to be added in a commercial biodiesel to achieve the minimum oxidative stability provided by the legislation. An equation for each additive was proposed, with the mass of these antioxidants considered as dependent variables and the conformity parameters as independent ones, obtaining multiple regression equations without intercept. The BHA and BHT antioxidants were used. The equations provided were lower at the 5% level and presented determination coefficients (R2) equal to 0.9790 and 0.9770 for the BHA and BHT, respectively, proving their predictability ability and also showing that they can be used to estimate the antioxidant mass to be added in a biodiesel to reach the current regulations.

Abstract A highly efficient tool that has stood out in data processing and treatment is Artificial Neural Networks (ANNs). Self-organized maps (SOM), which is a type of ANNs, are easy-to-view computational models that simulate information processing and knowledge acquisition. Applying this tool, we analyzed the behavior of the film formed on the mozzarella cheese surface when subjected to salting by immersion. In order to reduce the amount of NaCl in the food, KCl was used as a partial substitute in adequate amounts, without causing sensory changes in the cheese. The diffusion of salts in the brine is caused by the transfer of sodium and potassium ions, induced by concentration gradient of these salts inside and outside the food. The application of artificial neural networks proved to be an effective tool in the evaluation of the influence of the film on the diffusion process of Na+ and K+ ions, in the mozzarella cheese salting.

Abstract Problems related to high blood pressure have led consumers to choose foods with low levels of sodium chloride, and an alternative to reduce the salt content of this salt is its partial replacement with KCl. In order to not affect the sensory properties of cheese, salting was performed using a solution containing 70% of NaCl and 30% of KCl in a static and dynamic system. During the salting process by immersion, the mass transfer is affected by the formation of a film on the cheese surface. The analysis of the diffusion of salts in the film can be performed using self-organizing map (SOM) combined with the Finite Element Method (FEM). Through these tools, a greater influence of the film was observed when the static system was applied and that the diffusion is different according to the studied position. On the biosolid sides the diffusion was more pronounced than in the center, indicating a decrease in the film thickness towards the edges. The SOM combined with 3D modeling showed to be an efficient tool to investigate the formation, influence and behavior of the film during the diffusion of Na+ and K+ on salting of Prato cheese.

Biodiesel contains unsaturated methyl esters making it susceptible to oxidation reaction. Among the factors that cause oxidative instability is the contamination by transition metal ions that in small quantities catalyze the oxidation reaction. The objective of this work was to evaluate the relative protection factor of rosemary extract, in biodiesel, in the presence of transition metal ions. Chromatographic analysis and characterization of biodiesel were performed as well as the quantification of total phenolic compounds and extract activity. The ions Cr3+, Co2+ and Fe2+, at a concentration of 3.95 x 10-3 mol L-1, were added to the biodiesel with and without rosemary extract. The samples were submitted to the Rancimat test and to infrared region analyses. The infrared region spectra of the samples with Cr3+ are in accordance with the least catalytic power of this ion under the biodiesel oxidation. Samples with Co2+ ions, without extract, presented bands of aldehydes, and samples with Fe2+ ions show the formation of peroxide radicals, without rosemary extract at 48h. The antioxidant effect of the extract in biodiesel is observed by the reduction of the induction period of the samples. The relative protection factor proved to be a good tool to evaluate its efficiency.

Abstract In the elaboration of young red wine, it is necessary to obtain a clear product with stable color. The clarity and stability can be obtained using fining agents. The objective of this study was to evaluate the combined effect of fining with pea protein isolate (PPI), bentonite, and polyvinylpyrrolidone (PVPP) on a red wine, using the experimental design of mixtures. Merlot wine was used to evaluate the changes on monomeric flavan-3-ol, turbidity and anthocyanin levels promoted by the fining compounds. For all the parameters, the adjusted models showed influence of the combination of the three fining agents. Together, bentonite and PVPP have synergistic effect on the reduction in monomeric flavanol levels. Such synergistic effect was also observed with PPI and PVPP combination for the reduction in turbidity. However, for this same characteristic (turbidity), the combination of PPI and bentonite has antagonistic effect. To achieve broader wine fining objectives, the simultaneous optimization of the three response variables demonstrated the importance of the presence of the three refining agents in the following proportions: 25% PPI, 43% PVPP and 32% Bentonite. The isolated use of these additives would not result in the same effect on the three studied variables.

Biodiesel is a suitable alternative to replace the petro-diesel. The biodiesel is formed by unsaturated esters easily degraded by interferences of oxygen, temperature, contact with metals or contaminants. The aim of this research was to investigate the biodiesel degradation process via 1H nuclear magnetic resonance (NMR) spectroscopy, observing the olefinic, bis-allylic and allylic protons signals of the chemical bonds, and by the induction period of the Rancimat. Biodiesel samples with metallic ions (Fe and Cu) and with rosemary natural extract were analyzed. The metal compounds showed a catalytic effect in the samples and the rosemary natural extract showed to be efficient by retarding the degradation process. The extract was ineffective in the presence of iron. Through the 1H NMR spectra was possible to observe changes in the signal intensities of the olefinic, bis-allylic and allylic protons as well as the formation of oxidation products in the biodiesel in the degradation process.