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], kappa-carrageenan [kappa-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), kappa-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.