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Potential of psyllium as an ingredient in 3D-printed gluten-free snacks evaluated by rheology, NIR and physical properties

With its good gelling properties, psyllium is a promising component that could improve the printability of food “ink”, while its high soluble fiber content increases the nutritional value of food. In this study, we investigated how different amounts of psyllium (1, 2, 3%) and water (110, 115, 120%) affected the rheology and 3D printing properties of a gluten-free blend of millet flour (50 g), sweet potato flour (15 g), rice protein (25 g), salt (0.9 g), baking powder (1.8 g), and oil (18 g). The experiments followed a full factorial design. Frequency sweep tests (1-30 Hz, 30°C) were performed on MCR 92 rheometer to determine storage/loss modulus, loss factor, yield stress, and complex viscosity. Foodbot D2 with 1 mm nozzle diameter was used to print dough in the previously designed shape of the letter "K" in a circle with 16 layers. The printing parameters were: 30°C, 1.5 mm layer height, and 20 mm/s printing speed. The shape was frozen, weighed and photographed. Print quality (sample height, diameter, and printing precision) was evaluated using ImageJ image processing program. NIR spectroscopy was used for predicting dough quality by recording continuous NIR spectra (range 904-1699 nm) before printing. The influence of each parameter on the output values was assessed by analysis of variance (ANOVA) with p<0.05, while numerical optimization was performed to obtain the highest possible printing quality. The experimental design, ANOVA, optimization, multivariate analysis of spectral data and principal component analysis (PCA) were performed using Statistica. Optimization predicted that the best snack dimensions, print quality, and precision would be achieved with 1.8% psyllium and 113.5% water. After optimization 38 evaluation, prediction errors for height, diameter, precision, score, and loss factor were less than 10%, while prediction errors for other rheological parameters were about 30%. PCA showed good separation of samples based on the first three factors. The 3D PCA showed that the primal factor by which the samples differed was the amount of psyllium added. These results confirm the potential of NIR spectroscopy for qualitative analysis of dough composition prior to 3D printing.

3D printing ; psyllium ; rheology ; NIR spectroscopy

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