Universal optimization method for 3D printing sugar-reducing food

By defining and optimizing the porosity and odor concentration of 3D-printed low-sugar foods, a quantitative model was constructed, which solved the problem of insufficient sweetness perception in existing technologies and realized an efficient, standardized and scalable optimization method for the development of low-sugar foods.

CN122389326APending Publication Date: 2026-07-14CHINA ACAD OF ART
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Patent Information

Application Number
CN202610519221.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-20
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

The current development of sugar-reduced foods lacks a systematic approach, making it difficult to accurately coordinate the internal structure and amount of aroma substances in food under the premise of sugar reduction. This results in insufficient sweetness perception, long research and development cycles, high costs, and unstable results.

Method used

By defining core parameters, constructing a quantitative model, solving for the optimal parameter combination, optimizing the porosity and odor concentration of 3D-printed sugar-reduced foods, and using multiple linear regression analysis to establish a sweetness similarity model, we can ensure that the sensory evaluation indicators reach their best.

Benefits of technology

It significantly shortens the R&D cycle and costs, increases efficiency by 40%, achieves standardization and high efficiency in food development, ensures that different researchers obtain consistent optimal results, and has universal applicability that can be extended to other sugar-reduced foods.

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Abstract

The invention discloses a universal optimization method for 3D printing sugar-reducing food. Comprising the following steps: S1, defining and measuring core parameters, wherein the core parameters comprise porosity P of a 3D printing food matrix, odor concentration C of an odor active component accounting for the total mass ratio of the food matrix, sucrose reduction Suc compared with traditional full-sugar food, and a sensory evaluation index S of a sensory evaluator on the sweet similarity between the sugar-reduced food and the traditional full-sugar food; s2, constructing a quantitative model: acquiring multiple groups of different data corresponding to P, C and S through experimental design under the condition of setting a sucrose reduction Suc value in advance, and fitting by adopting a multiple linear regression method based on the data to obtain the quantitative model of the sweetness similarity S about the porosity P and the odor concentration C; the problem that in the prior art, on the premise that a certain sugar reducing proportion is guaranteed, how to set printing parameters and a formula is difficult to be clearly guided, so that the optimal comprehensive sensory experience is obtained is solved.
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