# 3D Printing Progress in Gluten-Free Food--Clustering Analysis of Advantages and Obstacles
###### Abstract
Both protein and vegetable products have already been 3D printed via extrusion devices, providing the texture categories defined by the International Dysphagia Dietary Standardization Initiative. In that particular case, 4D food printing can offer more benefits by creating forms that are more appealing through color change and flavor release after extrusion [13]. Physically, extrusion-based 3D printing is achieved by depositing viscoelastic raw material through a printer nozzle to create three-dimensional food structures layer by layer. Currently, progress has been made by studying the feasibility of printing food materials, the formulation of printing materials, and the optimization of printing parameters to produce personalized food in the future [14]. For the 3D printing of flour products, an important role is played by the components that are structure formers, such as protein and gluten, which give food a viscoelastic structure. Rice flour, for example, is widely used to make gluten-free products; however, being low in protein and gluten-free is not used natively in 3D printing technologies [15]. Many gluten-free product formulations are based on the use of rice flour, but due to its low protein content, rice flour requires additional components to improve its 3D printing capability. It has been proposed to mix rice flour with Jagerry to improve the viscoelastic properties of the 3D printing mass, as well as an alternative to using sugar, for the production of gluten-free products using 3D printing [16]. The sustainable perception of gluten-free food consumption is also growing. Gluten-free products based on naturally gluten-free flours became perceived as a healthier and, sometimes, more sustainable solution for today's consumers. Producing gluten-free foods can be more environmentally friendly if done properly [17]. The production of gluten-free products, as well as the use of 3D printing for dietary products, has its own peculiarities. In particular, gluten-free complex powder mixtures have great potential for 3D printing personalized nutritious snacks. It was found that the quality of printing gluten-free products was strongly influenced by the particle size of the raw material, the diameter of the nozzle, and the amount of water [5]. Thus, understanding the interplay among all those parameters, as well as their impact on the printing process, can be crucial to achieving the best print accuracy and quality of 3D-printed snacks. During 3D printing, natural or other food additives that function as binding agents are commonly added to achieve the desired viscosity and rheological properties, supporting ease of extrusion and printed structure after deposition [18]. However, this does not mean that printing other materials without a binding mechanism is impossible; examples of such food formulas include a combined high-fiber flour paste, rice dough, and wheat dough enriched with alternative types of insect-derived proteins [19]. Thus, it is relevant to note that the suitability of food materials for 3D printing can largely depend on the components/composition of the food material and the corresponding dynamic viscosity and rheological properties, which do not necessarily require systematic modifications to determine sufficient fluidity, plasticity and mechanical properties of the ink. As the following example shows, 3D printing can often require a purely experimental approach. While increasing the content of skim milk and sugar in cookie dough that does not contain stabilizers or gum resulted in increased deformation of dough samples (rice, tapioca, and wheat) and greater collapse of 3D structures after baking, respectively [20], tapioca dough with reduced sugar and milk content has better viscoelastic properties, supporting structurally stable 3D printed cookies. Numerous studies have established that the printability of food system formulations, especially gluten-free formulations, can be determined based on computed rheological data [21; 22; 23; 24]. [PERSON] et al.