جستجوی مقالات مرتبط با کلیدواژه « صمغ دانه مرو » در نشریات گروه « صنایع غذایی »

Fried food products are very popular due to their unique characteristics such as color, smell, taste and desirable texture. During the frying process, food is immersed in an oil bath at a temperature above the boiling point of water. This results in counter flow of water vapour (bubbles) and oil at the surface of the product. Colour changes measured may be used to predict both chemical and quality changes in a food. The colour parameters have previously proved valuable in describing visual colour deterioration and providing useful information for quality control in fruits and fruit products. The oil uptake problem associated with fried products can be decreased by using hydrocolloids as edible coating. Also, the sensorial examination results showed that the coated products with gums have total acceptability better than the uncoated samples. Using of hydrocolloids (gums) to decrease the oil uptake during deep-fat frying is one of the easy and most convenient way which does not needs changes in frying devises (Khazaei et al 2016; Salehi 2020a). The term “gum” is used to explain a group of naturally occurring polysaccharides. Gums have a good functional characteristic such as emulsifying, coating agents, packaging films, gelling, stabilizers, solubility and textural improvement (Salehi 2017). Gums influence on the gelatinization and retrogradation of starch and decreased the retrogradation of starch. Wild sage seed mucilage is a gum extracted from wild sage (Salvia macrosiphon L.) seeds. The performance of artificial neural networks (ANN) was reported by some researcher. They reported that these approaches are able to estimated characteristics of various fruits and vegetables with high precision. It has been shown that nonlinear approaches based on ANN are far better in generalization and estimation in comparison to empirical models. Determination of the best number of neurons in hidden layers of ANN models is generally carry out by trial and error. The genetic algorithm optimization method can be used to overcome this inherent limitation of ANN. Genetic algorithm is the search technique for optimal value, mimicking the mechanism of biological evolution. It has a high capability to find the optimum value of a complex objective function, without falling into local optima (Salehi 2020b; Amini et al 2021).

The cleaned wild sage seeds were firstly soaked in water at a seed/water a portion of 1:20, 25°C, and for 20 min. The mucilage extract was separated from the swollen wild sage seeds by passing the seeds through an extractor. Controlling frying conditions and using edible hydrocolloid coatings (gums) is one of the best ways in reduction of oil uptake, moisture retention and improving the appearance properties of fried foods. In this study, different concentrations of wild sage seed gum (0, 0.5, 1 and 1.5%) were used to coating of eggplant slices during deep frying at 150, 175 and 200°C and the relationship between process parameters and the quality of final product were modeled by genetic algorithm-artificial neural network method. To examine the changes in colour indexes including lightness (L*), redness (a*) and yellowness (b*), images were taken after the frying. In order to investigate the effect of frying temperature and wild sage seed gum concentration on the colour changes of fried eggplant, a computer vision system was used. Sample illumination was achieved with HP Scanner (Hp Scanjet 300). Neurosolution software (version 5, NeuroDimension, Inc., USA) was employed for making the GA-ANN model. In the hidden layers and output layer a sigmoid activation function was used (due to the highest r-values in comparison to the other functions, hyperbolic tangent and a linear).The Levenberg–Marquardt (LM) optimization method was applied to network training. The crossover probability and the mutation probability operators were adjusted equal to 0.9 and 0.01, respectively. Also, a sensitivity analysis was done to supply the measure of relative significance between the inputs of the ANN model and to show how the model output changed in response to input changes.

The results of this study showed that coating with wild sage seed gum reduced the oil uptake of the final product. Coating pretreatment maintained the final product moisture and moisture content of the sample coated with 1.5% wild sage seed gum was higher than the other samples. This process was modeled by genetic algorithm-artificial neural network method with 2 inputs include wild sage seed gum concentration and frying temperature and 5 outputs includes oil percentage, moisture content, and three main color indexes (yellowness (b*), redness (a*), and lightness (L*)). The results of modeling showed that a network with 3 neurons in a hidden layer and using the sigmoid activation function can predict the physicochemical properties of fried eggplant slices.

Wild sage seed gum concentration and oil temperature are the process parameters which affect the parameters of eggplant slices during frying. Sensitivity analysis results showed that the changes in the concentration of wild sage seed gum had the highest effect on the moisture content and then on the oil content of fried eggplant slices. Also, the change of frying temperature has the highest effect on the lightness index of fried samples.

Fried food products are very popular due to their unique characteristics such as color, smell, taste and desirable texture. Controlling frying conditions and using edible hydrocolloid coatings (gums) is one of the best ways in reduction of oil uptake, moisture retention and improving the appearance properties of fried foods. In this study, different concentrations of wild sage seed gum (0, 0.5, 1 and 1.5%) were used to coating of zucchini slices during deep frying at 155, 170 and 185°C and the relationship between process parameters and the quality of final product were modeled by genetic algorithm-artificial neural network method. The results of this study showed that coating with wild sage seed gum reduced the oil uptake of the final product and in terms of appearance characteristics, the coated samples were lighter. Coating pretreatment maintained the final product moisture and the size of the samples coated with 1.5% gum was larger than the other samples (lower surface changes percent). This process was modeled by genetic algorithm-artificial neural network method with 2 inputs include wild sage seed gum concentration and frying temperature and 7 outputs  include oil percentage, moisture content, yellowness index (b*), redness index (a*), lightness index (L*), color changes intensity (ΔE) and surface changes. The results of modeling showed that a network with 5 neurons in a hidden layer and using the sigmoid activation function can predict the physicochemical properties of fried zucchini slices. Sensitivity analysis results showed that the changes in the concentration of wild sage seed gum had the highest effect on the yellowness index and then on the surface color changes intensity index of fried zucchini slices. Also, the change of frying temperature has the highest effects on the color changes intensity and lightness indexes of fried samples.

It can be seen that in most studies published on low fat yogurt, the effects of fat substitutes or process changes, including the homogenization process, have been considered separately. However, process changes, especially changes in homogenization pressure, in addition to the effect on yogurt, has also an effective role on fat substitutes such as hydrocolloids and can affect their functional characteristics. Therefore, in order to understand the proper conditions of industrial production, it is necessary to study these changes simultaneously. Due to the importance of low fat yogurt production, the effect of konjac gum, sage seed gum, homogenization rate and fat content on pH, texture, and color of low-fat yogurt was investigated using mixture-process variable experiments and modeling the properties obtained from this experimental method.
 
To prepare low-fat yogurt, firstly, the cream of 40% fat was added to the milk with 0.05% fat, sage seed gum, and konjac gum were added according to the design treatments and calculated by Pearson square method. The preparation was then heated to 90 °C and cooled down to 45 °C. The starter was then added and incubated in oven until reaching pH = 4.6. The yogurt was cooled down and dispersed in a 100 g cups of polyethylene. Texture analyzer was used for combination of back extrusion and texture profile analysis (TPA) test. The evaluated parameters were: hardness (N), cohesiveness, springiness, gumminess (N), chewiness (N), adhesiveness and adhesiveness force. pH was measured according to AOAC official method NO. 981.12.
 
The results showed that only the effect of fat content on the 99% level was significant on the pH of the samples, while konjac, sage seed gum, and homogenization rate had no significant effect. By increasing the fat content, the pH of the samples also significantly increased. It is likely that the increase in fat content will reduce the metabolic activity of the starter bacteria and thus increase the pH of the samples. Also, when the fat content of the samples was kept constant (1.75%), increasing the konjac gum and reducing the sage seed gum when the homogeneity of the samples was between 0 and 1200 rpm, the hardness of the samples initially increased and then decreased. When both gums were added at the same level, the hardness decreased indicating the high synergistic effect of these gums at low homogeneity rates. The results of this study showed that only linear effect of fat in 99% level on the adhesiveness force of samples was significant so that by increasing the fat content, the adhesiveness force of the samples increased. Also, the results showed that with increasing the konjac gum and reducing the sage seed gum, the gumminess of the samples first increased and then decreased. The most gumminess sample was in the conditions that both gums were used at the same level, indicating the high synergistic effect of these gums on the gumminess of the samples. The results of color measurement showed that only the linear effect of sage seed gum and the interaction effects of konjac gum-sage seed gum, konjac-gum on homogenization rates of L* samples were significant, and with increasing the level of konjac gum and reducing sage seed gum, L* samples decreased, but with increasing homogenization rates, L* samples increased. In this research, minimization of the fat content and adhesiveness force and maximization of the hardness and cohesiveness was considered as optimization aims. The optimum point calculated as 0.146% konjac gum, 0.053% sage seed gum, 2.42% fat content and 12300 rpm homogenization rate. In this conditio, the responses were: pH=4.5, hardness=3.25 N, adhesiveness force=0.815 N, cohesiveness 0.258 mm and L* 85/18. As a conclusion of this investigation, it could be said that these types of models could be utilized in industries to optimizing the formulation of such product, reducing the cost and increasing the acceptance.

Stabilizers are a group of bio-polymers which are used in ice cream formulations in order to create soft texture, uniformity, reducing growth of ice crystals and lactose during storage and may be used to increase resistance to melting. Among these factors are hydrocolloids. The aim of this study was to investigate the effect of substituting Salep with Salvia macrosiphon boiss seed gum (as a source of native gum) at levels of 0.1 and 0.2% on physicochemical and sensory characteristics of traditional ice cream. Physicochemical tests including resistance to melting, pH and specific gravity; and sensory evaluation including measurement of intensity of coldness, viscosity, liquefying rate and total acceptance were analyzed. Results showed that Salvia macrosiphon boiss gum was more and less effective than Salep. The highest resistance to melting (80.5%), liquefying rate (8.25) and total acceptance (6.6) belonged to the sample containing Salvia macrosiphon boiss gum. The highest pH (6.6), gravity (1.06), intensity of coldness (8.87) and viscosity (5.3) was obtained for the sample containing Salep. According to the results Salvia macrosiphon boiss gum can be considered as a substitute for Salep.

In this paper, the effect of two domestic seeds hydrocolloids (Basil seed and Sage seed gums) and one commercial hydrocolloid (pectin) on characteristics of non-fat concentrated yoghurt was studied. For this purpose, effect of different concentrations of these gums (0.05, 0.1, 0.15 and 0.2%) on physicochemical and sensory properties after 1 and 7 days were investigated and compared with control sample (without gum). Physicochemical characteristics were included total solids, syneresis, apparent viscosity and softness of concentrated yoghurt. Flavor, odor, color and mouth feeling were evaluated as sensory properties. With increasing the concentration of gums, total solids, syneresis, apparent viscosity and softness of samples decreased. Yogurts containing 0.05% gum was acceptable by panelists. The highest apparent viscosity and sensory acceptance were seen in samples containing sage seed gum, whereas samples containing pectin had the highest total solids and firmness. The apparent viscosity of samples decreased after 7 days storage, whereas the syneresis and softness increased, and sensory properties improved.