Microstructural Characterization of Multiphase Chocolate Using X-Ray Microtomography

In this study, X-ray microtomography (mu CT) was used for the image analysis of the microstructure of 12 types of Italian aerated chocolate chosen to exhibit variability in terms of cocoa mass content. Appropriate quantitative 3-dimensional parameters describing the microstructure were calculated, for example, the structure thickness (ST), object structure volume ratio (OSVR), and the percentage object volume (POV). Chemical analysis was also performed to correlate the microstructural data to the chemical composition of the samples. Correlation between the mu CT parameters acquired for the pore microstructure evaluation and the chemical analysis revealed that the sugar crystals content does not influence the pore structure and content. On the other hand, it revealed that there is a strong correlation between the POV and the sugar content obtained by chemical analysis. The results from this study show that mu CT is a suitable technique for the microstructural analysis of confectionary products such as chocolates and not only does it provide an accurate analysis of the pores and microstructure but the data obtained could also be used to aid in the assessment of its composition and consistency with label specifications. Practical Application: X-ray microtomography (mu CT) is a noninvasive and nondestructive 3-D imaging technique that has several advantages over other methods, including the ability to image low-moisture materials. Given the enormous success of mu CT in medical applications, material science, chemical engineering, geology, and biology, it is not surprising that in recent years much attention has been focused on extending this imaging technique to food science as a useful technique to aid in the study of food microstructure. X-ray microtomography provides in-depth information on the microstructure of the food product being tested; therefore, a better understanding of the physical structure of the product and from an engineering perspective, knowledge about the microstructure of foods can be used to identify the important processing parameters that affect the quality of a product.