Fractal Microstructure of Foods

Abstract

Process engineering of food materials is strongly associated with their microstructure, which quantification allows proper selection of equipment operating conditions, monitoring sensorial attributes and consumer’s acceptance. This evaluation has been carried out by applying the fractal approach using microscopy images that depict complex, ragged and irregular forms. Therefore, this review aimed to summarise the fundamentals, calculation methods and applications of fractal dimension (F_D), lacunarity (\(\Lambda\)) and multifractals for describing the microstructure of selected food systems including the calculation methods derived from the digital image analysis and recent investigations involving the fractal analysis in vegetal materials, animal food products, doughs, gels, starch, food-related micro- and nanoparticles, powders and fats. It was noted that several microscopy techniques were used broadly, and their selection depended on the sample type and specific region of interest. Regarding the calculation of fractal parameters, the box-counting method performed on images of the surface was prevalent in most of the revised pieces of research, finding F_D values from 1.60 (for binary images) to 2.99 (for grayscale images). Also, several relationships were found between F_D and temperature, composition and textural parameters. It was noted, however, that a specific trend was not detected given that variations in acquisition procedures and observation scale prevailed among the reported works. Besides, it was noteworthy that \(\Lambda\) and multifractals were unexploited, notwithstanding that these fractal properties can aid to achieve a thorough examination of food microstructure. Based on the inspection of fractals in the imaged microstructure, the present review is helpful to improve the management and control of food engineering processes based on food microstructure for obtaining higher quality products.