Caracterização físico-química, reológica e sensorial de iogurte obtido pela mistura dos leites bubalino e caprino

Milk from different animals can be used for dairy production. Yoghurt is a popular fermented milk product and considered to be one of the greatest importance in terms of consumer acceptance and consumption. The present research deals with the production of strawberry set-type yoghurt by mixing goat and buffalo s milk and it has the objective of taking advantage of the intrinsic characteristics of each milk to produce a final product with desirable attributes. It was conducted by analyzing five experimental groups with different proportions of goat and buffalo s milk: C 100% goat s milk; 7C3B - 70% goat s milk and 30% buffalo s milk, 5C5B - 50% goat s milk and 50% buffalo s milk, 3C7B 30% goat s milk and 70% buffalo s milk; B - 100% buffalo s milk. Each group was evaluated for total solids content and the acidification profile was monitored every 30 minutes by pH analysis. The yoghurt samples were analyzed for physical-chemical (pH, acidity, protein, fat, total and reducing sugars, ash and total solids), rheological (syneresis and viscosity) and sensory characteristics (appearance, odor, consistency and flavour). Samples with higher percentual of bubaline milk reached Vm faster, but the time necessary for pH 4.6 (Te) were similar between groups. Statistical differences (p<0.05) were observed for fat and total solids content of yoghurt, with superior values for groups higher proportions of buffalo s milk. The parameters of behavior reached by the model of Ostwald of Waale pointed yoghurt samples as non-Newtonian and pseudoplastic fluids. Yoghurt made only with goat s milk (C) had higher values (p<0.05) for syneresis, which can be explained by its fragile coagulum. Additionally, this group also had the lowest sensory scores for the attributes consistence and taste, while bubaline yoghurt (B) obtained the best acceptance indexes for all of the appraised parameters

Recuperação e purificação de quitosanases usando adsorção em leito expandido com streamline DEAE com modelagem e simulação usando redes neurais

Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature

Decaimento bacteriano em lagoas de estabilização no Nordeste brasileiro

Stabilization pond system consisting in more sewage treatment used in Rio Grande do Norte (RN), Brazil, representing about 90% of all systems. Fecal bacteria are removed mainly facultative ponds and in maturation ponds. Many factors influence bacterial decay, such as the levels of pH and DO, temperature, light intensity, HDT and nutrient availability. The bacterial decay rate (Kb) is calculated considering many variables, but the hydraulic regime is a significant influence for microorganisms removal, and the dispersed flow which best characterizes a stabilization pond. However, some authors developed equations for the Kb accordant plug flow and complete mixing. This research study aimed to evaluate the bacterial decay of fecal coliform and Enterococcus sp. in stabilization ponds designed to treat domestic sewage, full-scale, in RN. All systems have assessed pretreatment, a facultative pond (LF) followed by two maturation (LM1 and LM2). The parameters availed were: temperature, pH, DO, BOD5, COD, fecal coliform, Enterococcus sp., Chlorophyll a, total suspended solids, fixed and volatile. In general, there were not significant differences for pH, DO and temperature in the ponds, except for the new systems, since they have low flow and hydraulic loads. The removal of organic matter in the ponds was low, about 70%, and nearly all are overloaded organic and operational problems. The bacterial removals were low, with average 96% for LF for fecal coliform, and 98% for Enterococcus sp.; LM1 were in itself a removal for fecal coliform about 71%, and 81% for Enterococcus sp.; LM2 have efficiency of 69% for fecal coliform, and 68% for Enterococcus sp. The equation proposed by Von Sperling (1999), according to the dispersed flow regime, generated empirical values of Kb more approximate to calculated values of Kb. On average, the calculated Kb to coliforms in the LF was 0.31 d-1, and for both maturation ponds were 0.35 d-1. For Enterococcus sp. the average was 0.40 d-1 for LF, 0.55 d-1 for LM1, and 0.58 d-1 for LM2. These results also showed that the Kb obtained in full-scale systems are smaller than those found in pilot-scale ponds. Moreover, one can say that the equation proposed by Marais (1974), according to the complete-mix regime, overestimates Kb. Actual results of Kb indicated that fecal coliforms are more resistant to adverse conditions present in stabilization ponds than Enterococcus sp., therefore, an indicator of microbiological safety and efficiency. The factors significant interventions in the rate of bacterial decay were concentrations of COD, the organic loading and HDT. The few Kb relationship between pH, DO and temperature were not significant. Finally, we conclude that it s essential to correct operation and maintenance, for not performing these activities is one of the main factors contributing to low rates of bacterial decay.