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.

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.

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.

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.

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.