Rheological and thermal characterization of plant-based inks for optimal 3D food printing (3DFP)

Purpose The increasing demand for sustainable, nutritious and customizable food products has intensified interest in 3D food printing (3DFP). However, current 3DFP workflows rely heavily on trial-and-error experimentation to identify printable formulations, limiting reproducibility and scalability. The purpose of this study is to establish a predictive, rheology-based framework for assessing the printability of food inks prior to printing. By systematically linking flow behavior and temperature-dependent viscosity to extrusion performance, this study aims to reduce experimental iteration and provide a scientific basis for formulation and process selection in 3DFP. Design/methodology/approach Food inks based on symbiotic culture of bacteria and yeast (SCOBY), butterfly pea flower (BPF) and beetroot (BR), formulated with xanthan gum, were prepared and characterized. Steady shear rheological measurements were performed over a wide range of shear rates to capture viscoplastic and shear-thinning behavior. Flow properties were modeled using Bingham, Herschel−Bulkley and Casson constitutive equations. Temperature-dependent viscosity was evaluated using Arrhenius, Williams−Landel−Ferry and power-law models. The fitted parameters were translated into extrusion-relevant operating ranges for syringe-based material extrusion and validated through controlled 3D printing trials. Findings All investigated food inks exhibited shear-thinning viscoplastic behavior, which is essential for extrusion-based 3DFP. The Herschel−Bulkley and Casson models provided superior fits compared to the Bingham model. Temperature-dependent analysis revealed that BPF and BR inks were more sensitive to thermal variations than SCOBY, which showed greater thermal stability. Formulations selected within the predicted operating ranges demonstrated smooth extrusion, improved interlayer adhesion, accurate shape retention and uniform surface finish. In contrast, formulations outside these ranges resulted in irregular flow, poor layer bonding and structural distortion, confirming the effectiveness of the predictive framework. Originality/value This study introduces SCOBY and butterfly pea flower as printable food inks and presents a model-based framework that predicts printability prior to printing. By translating rheological and viscosity−temperature model parameters into practical extrusion operating ranges, the approach reduces reliance on trial-and-error experimentation. The framework further links predicted printability to extrusion performance and final product quality (shape retention, interlayer adhesion, texture, color and nutritional composition), supporting rational ink formulation, process optimization and print quality control in 3DFP.