Amir Jajarmi; Bahareh Emadzadeh; Rassoul Kadkhodaee
Abstract
Introduction: Carrageenans are a family of linear sulphated polysaccharides that have broad applications in the food sector and pharmaceutical industry. Based on the degree of sulphation (polyelectrolytes) in carrageenan, only Kappa and Iota carrageenan have the ability of forming a gel structure. The ...
Read More
Introduction: Carrageenans are a family of linear sulphated polysaccharides that have broad applications in the food sector and pharmaceutical industry. Based on the degree of sulphation (polyelectrolytes) in carrageenan, only Kappa and Iota carrageenan have the ability of forming a gel structure. The mechanical characteristics of their gels, however, is affected by the polyelectrolyte nature of their chains. Iota and kappa carrageenan provide elastic soft gel and brittle rigid one, respectively, in the presence of calcium and potassium salts as their favored ions; while their mixture provides a broad range of structures with unique textures. The combination of these two biopolymers would result in a broad range of unique textures for different applications. The aim of this Study was to determine the effect of chain association (molecular association) on the textural properties of kappa- Iota carrageenan mixed gel. The texture of gels was investigated through the puncture test to determine some properties including hardness, toughness, deformability modulus, resilience, yield point, and proportional limit. In addition, the stress relaxation test was applied to evaluate the effect of the chain association formed in the network on the stress decay parameter.
Materials and Methods: A commercial Kappa-carrageenan, Genugel type, and Iota- carrageenan, Genuvisco type without further purification were purchased from CP Kelco (Lille Skensved, Denmark). Potassium chloride (KCl) and calcium chloride dihydrate (CaCl2•2H2O) of analytical grade were purchased from Merck company. The mixtures were prepared in 2:1, 1.5:1.5 and 1:2 ratios and the final concentration of 0.3% w/w biopolymer. Both calcium and potassium chloride were added using a strategy adopted for each salt for keeping the same ionic strength of molar concentrations of 2.5, 5 and 7 mmol in the biopolymer dispersions. The mechanical properties of the gels were investigated using an XT. T2 Texture Analyzer (Stable Micro Systems, Surrey, UK). Peltier system was utilized in adjusting the temperature at 4oC. The samples were equilibrated at least 10 min before performing the test. Crosshead speed was adjusted at 10 mm/min to a 12 mm depth (50% from total length) from the surface of the samples using a 1 mm diameter cylindrical aluminum probe for puncture test and a 2 mm/min crosshead speed using a 75 mm diameter cylindrical aluminum probe in 20% strain was applied for the stress relaxation test during 60 second time interval. Pleg and Normand equation was applied for the determination of viscoelastic properties of samples.
Result & discussion: Among different methods in the mechanical study of biopolymer gel, the puncture test is a promising method due to its ability in applying normal and shear forces on and into the structure simultaneously. In the presence of calcium and Potassium salts, the same pattern in the puncture curve was observed with increasing of ionic strength in the medium. According to the chain association formed as a result of the ion type, the pattern shows a transient from the elastic to the plastic deformation with different limits. The hardness as a parameter that indicates a composite biopolymer network resistance to break up, showed a higher value for the network containing Potassium salt. It would be due to the formed intra chain association in the system. For calcium salt, the results revealed a small variation in the hardness parameter with increasing the ionic strength. The area under the curve of stress- time is defined as toughness of the structure. The network formed by the intra chain association in the presence of potassium shows a free chain movement which leads to a plastic deformation with absorbing more energy before breaking the gel structure. Concerning the type of chain association, higher values of deformability modulus in the gels containing calcium salt is reasonable. Resilience, yield point and proportional limit are the characters related to the network homogeneity and bond stretching. In the networks with no depletion region, applying an external force to the body would lead to a uniform change in the initial state of the structure. In this kind of netwoks, the force distributed in the whole structure uniformly and local stress is not created. The chain movement as a result of bond stretching, causes a back stress occurance in the structure. When the primary stress is eliminated, the accumulated back stress will make the polymer to return to its original form. Interweaving the network by the intra chain association will result in a homogenous network formation and subsequently, to a higher parameter values in the linear region. The large deformation measurements were performed through the stress relaxation test to study the response of the structure during the interval times and to evaluate the viscoelastic properties of biopolymers network. Longer stress decay time was observed for the network developed in the presence of Potassium salt. The result obtained by studying the stress decay rate was in agreement with the properties observed from the evaluation of the linear region in the puncture test. On the other hand, the deformability modulus values conform to the result from hypothetical asymptotic level of the normalized relaxation parameter.
Amir Jajarmi; Masoud Taghizadeh
Abstract
Introduction: Lime (Citrus aurantifolia L) is belonged to citrus family and has two varieties on the basis of sweet or sour taste; two well known varieties of sour lime are Persian and Key that are cultivated in the southern of Iran. Based on FAO statistics, Iran produced about 615,000 tons of lime in ...
Read More
Introduction: Lime (Citrus aurantifolia L) is belonged to citrus family and has two varieties on the basis of sweet or sour taste; two well known varieties of sour lime are Persian and Key that are cultivated in the southern of Iran. Based on FAO statistics, Iran produced about 615,000 tons of lime in 2010, and is ranked among 10 lime producersinworld wide. Physical properties of fruits are essential information in designing equipments and processes being used in different manufacturing stages such as harvesting, cleaning, sorting and grading, transporting, packaging, as well as estimating of cooling and heating loads during heat transfer processes. Moreover, physical properties affect products acceptability since consumers usually prefer fruits and vegetables with brighter color, appropriate size and uniform shape. Among physical properties, weight, volume and projected area are important parameters for designing sorting equipment.Materials and methods: In this study, lime samples were selected from Key variety which is cultivated in southern of Iran. From the whole, physical properties of about 300 limes were investigated and regression model were developedto estimate weight and volume on the basis of length, width, thickness and projected area.In order to determine the initial moisture, tenlime samples were randomly selected and taken in to hot air oven at 80C for 24 h. The average values of three replicateswerereported.The major dimensions (Length (L), width (W), thickness (T)) were measured using a micrometer with an accuracy of 0.01 mm.Projected area of limes was calculated in three dimensions using image processing technique. Apparent color for the lime samples was also measured in terms of CIE ‘L*’ (lightness), “a*” (redness and greenness) and “b*” (yellowness and blueness), using image processing techniques. Step wise regression was used to develop multivariate models. In this method, the independent variables would enter the equation successively based upon their degree of dependency. In order to estimate weight and volume of lime samples,three category modelswere developed as follow. 1- Regression models based on length, width and thickness. 2-Regression models for predicting weight of lime based on calculated volume. 3- Regression models based on projected area. When there are a large number of variables in the database, it is very likely that subsets of variables are highly correlated with each other.In this study, principle component analysis (PCA)was applied in order to have an accurate and reliable evaluation from existed correlation between physical properties of lime.Result and discussion: The initialmoisture content of limeswas found to be 84.34%.The averaged values of length, width and thickness of limes were35.84, 32.92 and 32.56, respectively. The static coefficient of friction for limes was determined on fourdifferent surfaces namely plywood, galvanized iron sheet, rubber and glass. The glass and plywood showedmaximum and minimum static coefficient of friction respectively. In addition, the sphericity and aspect ratio of lime were found to be 94.32% and 92.18%, respectively. The obtained sphericityvalues were similar to values reported by Sharifi et al., (2007) for orange variety of Tamson and lower than orange varieties of Navel reported by Topuz et al., (2006). The obtained results showed high correlation between three major dimensions and lime’s weight. The predictive models for lime have lower coefficient in comparison with LorestaniandTabatabaeefar(2006) research report forheterogeneous shape of limes. Among regression models for weight prediction of limes, the best model was obtained on the basis of the third projected area with R2of 0.921. The regression models on the basis of calculated volume showed appropriate performance for prediction of lime’s weight. Among regression models on the basis of dimensions, the single parameter model based on lime’s width found to bethe highest coefficient for prediction of volume. Similar toweight prediction, single parameter model on the basis of the third projected area showed the best performance for volume prediction. Conclusion: The results obtained from principle component analysis confirmed the regression models and showed high correlation between physical properties such as projected area, dimension, weight and volume with each other as well as positive correlation with coefficient of friction on the rubber surface and negative correlation on theglass surface.
