A Simple and Quantitative Method to Evaluate Ice Recrystallization Kinetics Using the Circle Hough Transform Algorithm

Abstract

The formation of large ice crystals via recrystallization processes in foods and water-based materials often decreases the quality and structural integrity of the materials. Hence, there is a widespread academic and commercial interest in natural and synthetic ice crystal growth modifiers that inhibit the recrystallization of ice. Well-known natural ice crystal growth modifiers are antifreeze proteins (AFPs), which inhibit ice recrystallization by adsorbing on the surface of ice crystals. Reliable quantification of the ice recrystallization inhibition (IRI) efficiency is a long-sought goal. In this work, we describe a simple method to quantitatively evaluate IRI efficiency, based on automated image analysis using the circle Hough transform (CHT) algorithm. It enables robust and high throughput analysis of natural and synthetic ice recrystallization inhibitors. Here we use the method to evaluate the impact of a single-point mutation in the ice-binding site of QAE on its IRI activity. We find that the T18N mutant of QAE has virtually the same effective ice recrystallization inhibitory concentration as the wild-type QAE. This is in contrast to thermal hysteresis activity, evaluated by cryoscopy or sonocrystallization, where the mutation greatly decreases the activity.