Understanding the Relationship between Microstructure and Physicochemical Properties of Ultrafiltered Feta-Type Cheese Containing Saturea bachtiarica Leaf Extract.

Microwave-assisted extraction was optimized to prepare Satureja bachtiarica leaf (SBL) extract based on antimicrobial (IZD) and antioxidant activities (DPPH) and extraction yield (EY). At optimum condition, i.e., 800 W power and 8 min, the best extraction results with EY = 16%, IZD = 73.56 mm, and DPPH = 24.2% were obtained. To develop a novel Feta-cheese, the influence of SBL extract, rennet, and starter concentrations were evaluated in terms of rheological, textural, and sensorial properties. At the optimized condition, the acceptance, taste, the strength of the network (A), and the distance between sequential cross-linking points (ξ) were 8.13, 8.07, 34,036.12 Pa·s1/z, and 5.41 nm, respectively. At the 60th day of storage time, the lowest z value (the network extensity parameter) of the cheese samples was observed. SEM image texture indices showed a good correlation with the studied instrumental texture parameters during 60 days of storage. The mold and yeast counts and their growth rate in the SBL extract-added cheese were lower than those for control one; whereas, the former cheese showed a greater LAB population between the 80th and 120th days. The antimicrobial and antioxidant qualities of SBL extract showed a significant influence on cheese properties.

Understanding the physics of hydrocolloids interaction using rheological, thermodynamic and functional properties: A case study on xanthan gum-cress seed gum blend.

Some rheological, thermodynamic and functional properties of selected hydrocolloids (xanthan gum-cress seed gum (XG-CSG)) blends at different ratios (1-0, 3-1, 1-1, 1-3, 0-1) were characterized to understand physically the biopolymers interaction and networks. XG showed a greater rigidity (elastic modulus, G'LVE = 58.60 Pa), total structural strength (complex modulus, G*LVE = 70.69 Pa), yield stress (limiting value of stress, τL = 7.58 Pa), emulsion capacity (EC = 6.78%) and foam stability (FC = 18.92%) than CSG (G'LVE = 7.05 Pa, G*LVE = 8.53 Pa, τL = 1.44 Pa, EC = 86.48% and FC = 14.98%), respectively. Among blends, 3-1 XG-CSG showed the highest G*LVE, foaming stability (FS) and the extent of recovery (Rr%). The results were summarized using the clustering technique and principal component analyses. The coefficient of the interaction of some parameters, Cole-Cole plots and Gibbs free energy changes (ΔG) of predisturbed and intact networks were investigated. In samples with an intact network, greater compatibility directly related to the extent of synergistic interaction, while in predisturbed samples, the lower compatibility directly related to the extent of synergistic interaction. Although all blends were highly incompatible with antagonistic behavior, 1-1 XG-CSG showed the lowest incompatibility (ΔG = 8028.60 J/mol) among samples with intact structure, while at disrupted state, 1-3 XG-CSG showed the lowest incompatibility (ΔG = 158.6 J/mol).

Classification of hydrocolloids based on small amplitude oscillatory shear, large amplitude oscillatory shear, and textural properties.

Dynamic rheological and mechanical properties of seven commercial (xanthan [XG], guar [GG], high methoxylated pectin [HMP], κ-carrageenan [κ-Car], agar [AG], alginate [ALG], and carboxymethylcellulose [CMC]) and four emerging hydrocolloids (basil seed gum [BSG], sage seed gum [SSG], Balangu-Shirazi seed gum [BSSG], and cress seed gum [CSG]) were investigated and the classification of the hydrocolloids were carried out based on them. AG belonged to the first class with 0.81 membership function (MF), κ-Car and HMP grouped in the second class with 0.68 and 0.71 MFs, respectively, XG, BSG, and SSG were depended to the third class with 0.61-0.70 MFs, finally, CMC, GG, BSSG, ALG, and CSG related to the fourth class, as the most populated class, with MF > 0.61. The first class contained the highest amount of hardness parameter (43.40 ± 2.76 g), the second class included the highest pseudoplasticity parameter (shear-thinning ratio = -0.54 ± 0.03) and relaxation time (66.25 ± 2.61 s) and the fourth cluster comprised the highest frequency dependency of viscous modulus (exponent of power-law model for viscous modulus vs. frequency = 0.30 ± 0.05). In addition, the results of this study showed that there was a distinct relationship between nonlinear harmonics in the stress wave and fundamental characteristics of hydrogel networks. The investigation of the rheo-mechanical properties of biopolymers in large deformation under shear and normal forces can have an important role in the prediction of the behavior of the material in real processes and application conditions, especially in the food industry. Due to the inconvenience of large deformation mechanical tests, such as Weissenberg effect, the complication of the results analyzing and sampling difficulty of semi-dilute samples; herein, we determined the correlation between large deformation (LAOS and texture analysis) and small deformation (SAOS) tests properties. The studied rheo-mechanical parameters showed high correlation with the four mentioned network parameters (more than 65% similarity index). Using these results, other scientists could rationally design the experiments and avoid experiments with similar parameters.

Biopolymers interaction elaborating using viscoelastic relaxation spectra, network parameters, and thermodynamic properties.

Herein, oscillatory rheological measurements were performed to study the interaction behavior of xanthan gum-sage seed gum blends at different ratios (SSG-XG: 1-0, 3-1, 1-1, 1-3, 0-1), from the dynamic viscosity behavior, relaxation spectrum, fracture properties, network parameters, and thermodynamic points of view at the temperature range of 10-90°C. Then, the coefficient of the interaction of four parameters, which were obtained from the clustering technique and Han curves, were used to investigate the interaction behavior quantitatively. At 90°C, SSG showed 2.01 extent of loss modulus overshoot, which was the highest value among different gum dispersions at different temperatures, while XG showed strain softening behavior. At 10 and 90°C, SSG and 1-1 SSG-XG showed the highest spreadability reflected by the slope of loss tangent after flow point stress (tan δAF ) of 0.52 and 0.40, respectively. The high values of ψ parameter, which represented the Gibbs free energy change, of both 1-3 and 3-1 SSG-XG blends and the lowest entropy value of 1-3 SSG-XG, suggested that the role of entropy change in incompatibility behavior of 1-3 SSG-XG was higher than that of 3-1 SSG-XG blend. With the increase in temperature from 10 to 70°C, the XG Euclidean distance from SSG decreased, while it increased from 70 to 90°C and showed the highest Euclidean distance with XG at 10°C (3.92) and 90°C (4.05). Interaction coefficients and Han curves results showed that all blends were incompatible with the lowest antagonistic behavior for 1-1 SSG-XG dispersion at 50°C. Often, a mixture of hydrocolloids, especially xanthan gum and a galactomannan, are employed in processed foods to modify their rheological properties and cut the cost. The synergistic/non-synergistic effect of biopolymers mixture, which is invaluable from the practical and economical points of view, seems to be mainly induced by their thermodynamic status of interaction. Our former study showed that the thermodynamic indices of mixing could be probed by mechanical parameters. On the other hands, we found that the mechanical properties of materials are highly temperature dependent. Therefore, in this study, to better investigate the effect of temperature on the biopolymers interaction, first we classified all the thermodynamic and mechanical properties (relaxation spectrum, fracture properties, and network parameters) of hydrocolloids into four classes, then one parameter was selected randomly from each class. The selected parameters were employed to investigate the synergistic/non-synergistic effect at all temperature ranges by determining the interaction coefficient and decide on the best interaction temperature.

Hydrocolloid clustering based on their rheological properties.

In this study, we proposed an objective classification of seven commercial hydrocolloids and four novel hydrocolloids. Total of 74 rheological parameters was generated by steady (flow behavior, hysteresis loop, single shear decay, in-shear structural recovery experiments), dynamic (strain sweep and frequency sweep tests), and transient (creep/recovery and stress relaxation) shear measurements. Subsequently, the parameters were classified into seven categories with more than 60% similarity indexes in each group using agglomerative hierarchical clustering based on those properties related to the number of linkage, strength of linkage, distance of linkage, rupture and flow, rate of destruction, the extent of destruction, and the state of destructured samples in the absence of flow field. Fuzzy c-means classifier used to extract patterns for each class. Our results correspond to four different classes; κ-carrageenan and agar gum were categorized in the first class, high methoxyl pectin, xanthan, sage seed gum and basil seed gum in the second class, alginate gum and Balangu-Shirazi seed gum in the third class, and guar gum, cress seed gum and carboxymethyl cellulose in the fourth class. Using this classification technique, complete rheological patterns can be extracted for each class. This classification provides a map for other researchers to rationally design the best test type which could describe adequately different properties of materials and avoid experiments with a similar type of parameters. The main reason for the frequent use of hydrocolloids in various industries is their ability to modify the rheology. A lot of works have been done to study the rheological behavior of many hydrocolloids in model and food systems. As there is still demand for new sources of hydrocolloids with more specific functionality in foods, probing the similarities among commercial and emerging hydrocolloids could help us to rationally design structural features in different formulations, besides gives insight into the structure-function relationship between them. This object could be attained by clustering, a part of the pattern recognition theory. Contrary to the traditional clustering methods, in which the membership of a product is exclusive for only a class, in constraint clustering by fuzzy logic methods, a partial membership can be shared by two or more classes. In this way, using the fuzzy logic clustering method, we clustered a number of commercial and novel hydrocolloids based on the steady, transient, and dynamic shear rheological properties and found a specific pattern among them. PRACTICAL APPLICATIONS: The main reason for the frequent use of hydrocolloids in various industries is their ability to modify the rheology. A lot of works have been done to study the rheological behavior of many hydrocolloids in model and food systems. As there is still demand for new sources of hydrocolloids with more specific functionality in foods, probing the similarities among commercial and emerging hydrocolloids could help us to rationally design structural features in different formulations, besides gives insight into the structure-function relationship between them. This object could be attained by clustering, a part of the pattern recognition theory. Contrary to the traditional clustering methods, in which the membership of a product is exclusive for only a class, in constraint clustering by fuzzy logic methods, a partial membership can be shared by two or more classes. In this way, using the fuzzy logic clustering method, we clustered a number of commercial and novel hydrocolloids based on the steady, transient, and dynamic shear rheological properties and found a specific pattern among them.

Phytochemical analysis and antibacterial activities extracts of mangrove leaf against the growth of some pathogenic bacteria.

In this study, the effects of water, ethanol, methanol and glycerin at five levels (0, 31.25, 83.33, 125 and 250 ml) were investigated on the efficiency of mangrove leaf extraction using mixture optimal design. The antimicrobial effect of the extracts on Streptococcus pneumoniae, Enterococcus faecium and Klebsiella pneumoniae was evaluated using disk diffusion, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) methods. The mangrove leaf extraction components were identified through gas chromatography/mass spectrometry (GC/MS). Phytochemical analysis (alkaloids, tannins, saponins, flavone and glycosides) were evaluated based on qualitative methods. Antioxidant activity of extracts was measured using 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant potential (FRAP) methods. Maximum antimicrobial effect was observed in Enterococcus faecium and highest resistance against mangrove leaf extract in Enterococcus faecium and Klebsiella pneumoniae, respectively. Increasing concentration of mangrove extracts had a significant effect (p ≤ 0.05) on inhibition zone diameter. The MICs of the mangrove leaf extraction varied from 4 mg/ml to 16 mg/ml. The optimum formulation was found to contain glycerin (0 ml), water (28.22 ml), methanol (59.83 ml) and ethanol (161.95 ml). The results showed that the highest antioxidant activity was related to optimum extract of mangrove leaf and ethanolic extract respectively. The results of phytochemical screening of Avicennia marina leaves extract showed the existence of alkaloids, tannins, saponins, flavone and glycosides. 2-Propenoic acid, 3-phenyl- was the major compound of Avicennia marina. The results of non-significant lack of fit tests, and F value (14.62) indicated that the model was sufficiently accurate. In addition, the coefficient of variations (16.8%) showed an acceptable reproducibility.

Temperature dependency of the interaction between xanthan gum and sage seed gum: An interpretation of dynamic rheology and thixotropy based on creep test.

The viscoelastic (transient and dynamic) and time-dependent rheological behaviors of XG (xanthan gum), SSG (sage seed gum) and their blends at various ratios (1-3, 1-1, and 3-1 SSG-XG) and temperatures (10, 30, and 50C) were investigated using creep and recovery analyses. The creep compliance was converted to stress relaxation data; then, the structural kinetic model satisfactorily fitted the time-dependent relaxation modulus. Furthermore, dynamic rheology of mixtures was investigated using creep analyses. The most important contribution of the Maxwell spring to deformation (53.51%), was that corresponding to the SSG at 50C and the most important contribution of the Maxwell dashpot to the maximum deformation, were those corresponding to the XG (61.44%) and 1-3 SSG-XG (58.91%) samples both at 50C. The breakdown rate constant ( α) of the crosslinked gum structure in SSG and 3-1 SSG-XG under the application of external shear stress increases with temperature from 10 to 50C in the range of 0.14-0.32 (1/s) and 0.14-0.24 (1/s), respectively, whereas other dispersions showed the reverse trend. Among all dispersions, only XG and 1-3 SSG-XG demonstrated crossover frequency at 9.95 and 31.47 rad/s, respectively, at 50C, indicative of the lowest entanglement density for 1-3 SSG-XG. The greatest interaction between SSG and XG occurred for 3-1 ratio at 50C, which was confirmed by the Han curves. PRACTICAL APPLICATIONS: Hydrocolloid blends, particularly those consisting of xanthan gum and a galactomannan from new source can provide a range of attractive textural properties. Rheological studies contribute to the description of the molecular structure and prediction of the structural changes during their manufacturing processes. Sage seed gum (SSG), as a polyelectrolyte galactomannan, has a great potential to exert stabilizing, thickening, gelling and binding properties in food, cosmetics, and pharmaceutical systems. Therefore, we elaborate the interactions between SSG and xanthan gum and also the effect of temperature using transient measurements. In this way, we show that the viscoelastic (transient and dynamic) and time-dependent rheological behaviors may be investigated using single creep/recovery tests. This new insight into transient measurements is useful to characterize the interaction behavior of similar biopolymers blends.

Application of intelligent modeling to predict the population dynamics of Pseudomonas aeruginosa in Frankfurter sausage containing Satureja bachtiarica extracts.

Stepwise regression, Genetic Algorithm-Artificial Neural Network (GA-ANN) and Co-Active Neuro Fuzzy Inference System (CANFIS) were used to predict the effect of Satureja extracts (water and ethanol) on the population dynamics of Pseudomonas aeruginosa in a complex food system (Frankfurter sausage). The stepwise regression, GA-ANN and CANFIS were fed with four inputs: concentration (at five levels 0, 2000, 4000, 6000 and 8000 ppm), type of extract (water and ethanol), temperature (at three levels 5, 15 and 25°Ð¡) and time (1-20 days). The results showed that the stepwise regression was good for modeling the population dynamics of P. aeruginosa (R(2) = 0.92). It was found that ANN with one hidden layer comprising 14 neurons gave the best fitting with the experimental data, so that made it possible to predict with a high determination coefficient (R(2) = 0.98). Also, an excellent agreement between CANFIS predictions and experimental data was observed (R(2) = 0.96). In this research, GA-ANN was the best approach to simulate the population dynamics of P. aeruginosa. Furthermore, Satureja bachtiarica ethanol extract was able to reduce P. aeruginosa population, showing stronger effect at 5 °C and the concentration of 8000 ppm.