Augusto Tanamati

Sensory and physico-chemical characteristics of desserts prepared with egg products processed by freeze and spray drying

In this work, three freeze-dried (FD) egg products (whole egg (WE), egg yolk (EY) and egg white (EW)) were obtained and the acceptability of confections prepared with each was evaluated. Sensory analyses for confections were performed by hedonic testing with fifty panelists in each evaluation. The studied confections were: Condensed Milk Pudding (P), Quindim (Q) and Meringue (M). The results obtained for confections made with FD egg products were compared with the achieved through other formulations of the same desserts made with fresh (F) or spray-dried (SD) egg products. The sensory analysis results for confections made with FD egg products showed good acceptance by panelists. A principal component analysis of the sensory evaluation data was carried out to identify similarities between the different egg products. The PCA supported the conclusion that FD egg products can substitute their fresh and SD counterparts in dessert formulations with good acceptability while keeping the advantages conferred by the freeze-drying method.

Mid-infrared spectroscopy and support vector machines applied to control the hydrogenation process of soybean oil

The industrial hydrogenation of soybean oil is well established. However, its control is carried out through time-consuming methods. The objective of this study was to evaluate the mid-infrared spectroscopy (FTIR-ATR) in tandem with support vector machines (SVM) in controlling the hydrogenation process. Models were constructed to predict the content of saturated fatty acids (SFA), unsaturated fatty acids (UFA), monounsaturated fatty acids (MUFA), trans fatty acids (TFA), polyunsaturated fatty acids (PUFA) and the iodine value (IV). The values predicted by the SVM models were compared to values obtained through gas chromatography. Feasible multivariate models were obtained with r2 minimum of 0.96 and RMSEP in the range of 0.65–2.65. Feature selection using correlation spectra was also efficient, maintaining the performance of the models and reducing the number of variables used by up to 94%. Therefore, it was demonstrated that FTIR-ATR methodology with SVM could be applied to monitor industrial hydrogenation.

Formulation of mayonnaises containing PUFAs by the addition of microencapsulated chia seeds, pumpkin seeds and baru oils

There is an increasing demand for healthier foodstuff containing specific compounds such as Polyunsaturated Fatty Acids (PUFAs). In the case of PUFAs, protection against oxidative degradation is challengeable and microencapsulation emerges as an alternative. Mayonnaises containing microencapsulated oils could be a source of PUFAs. The objective was to formulate mayonnaises containing microencapsulated chia seeds oil, pumpkin seeds oil or baru oil. Micrometric particles with high encapsulation efficiency were produced and thermal analyses indicated an increased thermal stability of all oils after encapsulation. Rheology studies highlighted an increase in the mayonnaise viscosity when microparticles containing chia and pumpkin seeds oil were added. Mechanical texture was not affected by the presence of microparticles in the mayonnaise in all formulations tested. Nevertheless, samples containing microcapsules up to 5%wt were not distinguished from the base-mayonnaise in the sensorial test. Overall, enriched mayonnaises were successfully produced and encapsulation was efficient in protecting oils from oxidation.

Industrial Hydrogenation Process Monitoring Using Ultra-compact Near-Infrared Spectrometer and Chemometrics

The hydrogenation process of soybean oil is monitored through time-consuming methodologies that demand sample preparation and produce chemical residues. Thus, it is necessary to develop faster low-cost waste-free instrumentation methodologies. The aim of this work was to evaluate an ultra-compact near-infrared spectrometer in tandem with the partial least squares regression (PLSR) or support vector regression (SVR) in the control of the hydrogenation process. Models were used to predict the saturated fatty acids (SFA), unsaturated fatty acids (UFA), monounsaturated fatty acids (MUFA), trans fatty acids (TFA), polyunsaturated fatty acids (PUFA), and the iodine value (IV). The values predicted by the PLSR and SVR models were compared to the experimental values obtained by gas chromatography. A methodology for feature selection was also assessed, which was able to reduce by up to 85% the variables used in the models without loss of performance. The values obtained for root mean square error of cross validation, root mean square error of calibration, root mean square error of prediction, and r2 remained very close for both PLSR and SVR. Regarding RSD, all values were above 5% for the PLSR models, whereas for the SVR, the RSD presented values lower than 5% for IV and UFA. It is worth noting that the spectrometer used has low cost, effortless assembly, and easy handling, which allows its use in any environment. Through the results obtained, it was demonstrated that the ultra-compact NIRS spectrometer in tandem with PLSR or SVR represent an alternative to monitor the industrial hydrogenation process of soybean oil.