ABSTRACT
Gum arabic finds extensive application and typically undergoes sterilization prior to utilization in the food industry. This study explored the impact of steam sterilization temperature and duration on the physicochemical and emulsification characteristics of gum arabic, accompanied by proposed mechanisms elucidating observed effects. The results showed that when gum arabic was treated with high temperature sterilization (110 °C â¼ 140 °C), the emulsion prepared turned unstable. The interfacial tension decreased from 8.26 mN/m to 6.77 mN/m after sterilization, while the elastic modulus decreased from 23.65 mN/m to 16.16 mN/m. Moreover, the circular dichroic chromatographic results indicated that the arabinogalactan protein (AGP) structure of gum arabic was more relaxed after high temperature treatment with ß-sheets content decreased from 36.2 % to 29.8 % and random coil content increased from 41.3 % to 51.8 %. Quartz crystal microbalance with dissipation (QCM-D) results demonstrated that emulsion surface film thickness and toughness decreased after sterilization treatment of gum arabic. The study indicates that high temperature sterilization may change protein structure in gum arabic and reduce the stability of prepared emulsions.
Subject(s)
Emulsions , Gum Arabic , Steam , Gum Arabic/chemistry , Emulsions/chemistry , Chemical Phenomena , Plant Proteins/chemistry , Temperature , Mucoproteins/chemistry , Sterilization/methods , Surface TensionABSTRACT
Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms are applied to binary, grey and color images for the first time. Without considering the image preparation, the proposed algorithms achieve exponential acceleration than the existing quantum and classical methods in all three cases. At the end of this paper, an experiment based on the real quantum computer of IBMQ and simulations verify the effectiveness of the algorithms.