To ensure the clarity, transparency, and replicability of the review process, the study was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This standard, widely recognized in biomedicine and other disciplines, establishes guidelines for authors to comprehensively report the purpose of the review, methodological procedures, and findings obtained through a checklist and a study selection flowchart. ¹¹

The exploratory literature search was conducted in the main international databases (Scopus, ScienceDirect, Web of Science, and Dimensions) using a combined strategy of Boolean operators, designed according to best practices for systematic reviews. The search terms were grouped using the OR operator to include synonyms and variants, AND to combine key concepts, ensuring a balance between breadth (sensitivity) and precision (specificity) of the results. The search strategy was developed iteratively to ensure comprehensiveness and accuracy. Initially, the query applied was TS = (Sensory AND food) AND (3D AND print). Subsequently, a synonymous term was incorporated, expanding the query to TS = (Sensory AND food) AND (3D AND print) OR (3D AND printing). To refine the scope and include specific sensory methodologies, additional terms were progressively added: first descriptive sensory tests (TS = (Sensory AND food) AND (3D AND print) OR (3D AND printing) OR descriptive), followed by discriminative tests (TS = (Sensory AND food) AND (3D AND print) OR (3D AND printing) OR descriptive OR discriminative), and finally affective sensory evaluation: TS = (Sensory AND food) AND (3D AND print) OR (3D and printing) OR descriptive OR discriminative OR liking. Figure 1 shows a concise summary of the PRISMA methodology used in this article. The complete PRISMA 2020 checklist for the included studies is provided in the supplementary materials (file: “ PRISMA 2020 Checklist Complete vf.pdf”), accessible through the Zenodo data repository (DOI: https://doi.org/10.5281/zenodo.17295507).

Subsequently, articles that met thematic relevance were selected, that is, those that addressed the use of 3D printing in food, including its sensory evaluation. The retrieved documents were filtered using predefined eligibility criteria and evaluated based on their methodological quality and relevance to the review objectives.

Inclusion criteria were defined to ensure the coherence and relevance of the analyzed corpus, considering: i) original studies with experimental designs that reported quantitative results; ii) research examining the application of 3D printing technologies in food.

In contrast, the following were excluded: i) research focused exclusively on technological parameters (e.g., printing speed, design software, or specific 3D printing/injection techniques); ii) applications of 3D printing in other industries; iii) studies focused on dysphagia that did not include sensory evaluation; iv) systematic reviews, meta-analyses, or other types of methodological reviews.

To conduct a comprehensive analysis of the selected publications, VOSviewer (version 1.6.19) was used to extract bibliometric information, including year of publication, country of origin, authors, and journals. From this data, visualizations were generated that facilitated the interpretation of patterns and relationships. To optimize the presentation of the results, Microsoft Office 2019 and complementary tools were used to create graphs and tables that summarized the collected information in a clear and organized manner.

The search strategies used in the Scopus, ScienceDirect, Web of Science, and Dimensions databases were defined based on the background review ( Figure 1). Data collection and registration took place in May 2025, including both original articles and reviews (n = 28 180). For the final selection, original articles were prioritized, considering the title, abstract, and keyword fields, without applying time restrictions (2019-2025). During the process, a precise alignment was achieved between the study objectives and the selected articles, resulting in a total of 65 relevant publications for analysis, from a total of 5 807 records initially identified on 3D printing in food. From the selected studies, a consolidated database was created that compiles relevant information on each document, including authors, titles, year of publication, journal, abstracts, and other pertinent data. This allowed for a detailed analysis of the scientific literature. The database of the selected articles is provided in the supplementary materials, name file: “ Database review sensory.xlsx”, in Zenodo ( https://doi.org/10.5281/zenodo.17295507).

The analysis of publication trends reveals that research interest in the sensory evaluation of 3D-printed foods is both recent and rapidly expanding ( Figure 2). Research in this specific field ( Figure 2a) consolidated around 2019 and has experienced exponential growth year after year, peaking in 2023. 2024 suggests that this upward trend not only continues but accelerates, indicating that the field is rapidly expanding and gaining significant momentum within the scientific community. This growth, demonstrated in this systematic review, seeks to synthesize the accumulated knowledge in this dynamic and evolving research landscape on the use of 3D-printed foods and their association with sensory perception. On the other hand, the different investigations reveal a scientific production led by China, with significant contributions from India, Turkey and several European countries ( Figure 2b), confirming the global interest in the field. The research is predominantly published in high-impact food science and technology journals (e.g., Food Hydrocolloids, Innovative Food Science and Emerging Technologies), as well as in specialized sensory and engineering publications ( Figure 2c), reflecting its multidisciplinary nature.

Analysis of the authorship of the included studies ( Figure 3a) identifies key researchers who are driving the field forward. Bhandari, B., and Zhang, M., emerged as the most prominent contributors, suggesting the presence of leading research groups that are laying the methodological groundwork in this area. The recurrence of these and other authors, such as Liu, Z., and Deyahastin, S., indicates that, while the field is global, cutting-edge knowledge is concentrated in a network of highly specialized research teams that are producing a significant volume of the research literature. Regarding design, the literature shows a clear focus on printing simple, standardized “geometric shapes” ( Figure 3b). Furthermore, analysis of printed materials and shapes reveals that sensory research has focused on foods with rheological properties suitable for extrusion, with mashed potatoes and chocolate being the most studied models. Furthermore, there is significant interest in meat systems and hydrocolloid-based gels. This suggests that the current phase of research prioritizes a fundamental understanding of how printing parameters and formulation affect sensory properties, using simplified models for better experimental control, before addressing complex, customized designs.

The analysis of terms appearing in the titles of the included studies ( Figure 4a) supports previous findings and further delineates the research scope within this field. The centrality of the terms ‘3D printing’ and ‘sensory property’ validates the focus of this review. Furthermore, the high frequency of words such as ‘characterization’, ‘effect’, and ‘impact’ demonstrates that the literature corpus is heavily weighted toward experimental studies that seek to establish causal relationships between printing process parameters, food formulation, and the resulting sensory properties. This indicates a mature field that goes beyond mere conceptual demonstration and delves into scientific process optimization. Furthermore, the analysis of the abstracts ( Figure 4b) provides the methodological and thematic specifics of the field. The results highlight that research focuses on specific sensory attributes, especially ‘appearance’ and ‘color’. This exploration confirms the use of a wide range of materials, from chocolate to hydrocolloids such as gelatin and alginate, and innovative ingredients such as spirulina. Critically, the recurrence of key rheological terms such as ‘yield stress’ and ‘infill level’ demonstrates that sensory optimization is intrinsically linked to the precise control of the physical properties of food inputs (inks). This dual focus on materials science and sensory evaluation is the hallmark of current research in this field.

The printing technologies used in the included studies ( Table 1) reveal an extremely diverse and evolving technological landscape. The range of equipment extends from low-cost, open-source 3D printers tailored for academic research to specialized, high-precision industrial systems for commercial applications. The prevalence of customized in-house developments (e.g., TNO printer, CARK, Yoli Lab 1.0) underscores that the technology is in a phase of intense innovation, where tailored solutions are often required to address specific research challenges. The specialization of several printers in particular materials, especially chocolate, highlights its role as a fundamental model material. This technological heterogeneity is an indicator of a young and dynamic field, but also presents a challenge for methodological standardization. The selection of printing equipment therefore emerges as a critical variable that directly influences the reported rheological and sensory results, a variable that must be carefully considered in any comparative analysis.

The distribution of food categories ( Figure 5) identifies the main areas of interest in 3D printing research. Meat products and chocolate emerge as the most studied categories, each representing a critical facet of the field: the former focuses on the nutritional and textural customization of complex protein systems, while the latter serves as an ideal model material due to its predictable thermoplastic behavior and high sensory acceptability. Other notable categories include gel and puree systems (e.g., mashed potatoes, lemon mousse), whose rheology is highly manipulability, and pastry products. It is relevant to note that geometric shapes are presented as a separate category, demonstrating that a considerable portion of research uses simple, standardized designs for methodological purposes. This approach allows for systematic relationships between printing parameters, material properties, and sensory outcomes.

The characterization of 3D-printed foods requires a multidimensional analytical approach, as evidenced by the diversity of techniques reported in Table 2. Rheological and texture evaluations emerge as fundamental pillars, applied in 100% of the studies to optimize printability and predict the mechanical behavior of products. ^{8, 12} TPA, in particular, allows quantifying how printing parameters such as infill level or extrusion speed modulate attributes such as hardness and elasticity. ¹³

Microstructural techniques (SEM, CLSM) are equally critical, revealing how layer-by-layer deposition generates unique microstructures that determine macroscopic properties such as flavor release and textural perception. ¹⁴ Complementarity with spectroscopic techniques (FTIR, LF-NMR) allows evaluating molecular changes during processing, especially for the design of protein- or polysaccharide-based inks. ¹⁵

The application of proximate and compositional chemical analyses strengthens the potential of 3D printing for nutritional personalization, while colorimetry and microbiology techniques ensure food quality and safety standards. The emergence of physiological methodologies (EMG, tribology) marks a trend towards the comprehensive assessment of the oral and digestive functionality of printed foods, bridging the gap between product design and consumer experience. ¹⁶ This convergence of analytical disciplines—from materials science to digestive physiology—constitutes the hallmark of advanced research in 3D printed foods.

Methods applied with trained panels

The sensory methodologies employed ( Table 3) reveal a clear emphasis on descriptive over discriminative methods. The predominant technique is Quantitative Descriptive Analysis (QDA), reported in 18 of the reviewed studies. ^{17– 34} This underscores that the primary focus of current research is the comprehensive characterization and detailed mapping of the sensory profile of 3D-printed foods. This approach is essential for understanding how printing and formulation variables translate into specific sensory attributes, which constitutes the cornerstone for product optimization in this emerging technology. ^{7, 9} The application of these methodologies by trained or semi-trained panels, along with the use of robust statistical analyses (ANOVA, PCA), confirms adherence to the standards of rigor inherent to sensory science. ³⁵ However, the remarkable diversity of reported scales (unstructured linear scales of 7, 9, 10, and 15 cm, and 3- to 4-category rating scales), although effective at the individual study level, poses a significant challenge for the direct comparison of results across studies and for meta-analysis of data. The limited application of both traditional and emerging sensory methodologies represents a critical shortcoming of the studies reviewed. Future research should incorporate alternative techniques supported by harmonized protocols to strengthen the evaluation and development of food products. ³⁶

The paucity of discriminative methods, with only one study ³⁷ using a 2-CFA test, is particularly revealing. It suggests that the field has largely moved beyond the initial phase of simply detecting differences and is now focusing on a deeper understanding of the organoleptic properties of these novel products. This transition from simple research questions (“is there a difference?”) to more complex ones (“what is the exact nature of the difference and how can it be controlled?”) is an indicator of the progressive maturation of food 3D printing research. ³⁸ The dominance of QDA is therefore an appropriate methodological response to the need to generate multidimensional, high-resolution data that allow correlating material and process properties with the final sensory experience of the consumer.

Methods applied with consumers

When used with consumers, the sensory methodologies employed ( Table 4) reveals a predominance of affective methods, reported in 52 studies, ^{19, 20, 22, 23, 25– 27, 32, 33, 39– 81} which underlines the focus on consumer acceptance. as a key criterion for the development of 3D printed products. These methods, which include hedonic scales and preference tests, have been rigorously applied through both parametric and non-parametric statistical analyses. ³⁵ Descriptive methods are also represented, with 5 studies using CATA ^{19, 44, 46, 59, 61} and 4 studies applying TDS. ^{61, 75, 82, 83} The use of CATA reflects a trend towards rapid and efficient methods for sensory characterization with consumers, ⁸⁴ while the application of TDS demonstrates a growing interest in capturing the temporal dimension of sensory perception in 3D printed products. ⁸⁵ The limited application of physiological methods (only 1 study ⁶² ) suggests an area of opportunity for future research. Electromyography (EMG) and other physiological techniques could provide additional insights into the interaction between the structural properties of printed foods and their oral processing. ⁸⁶ The diversity of reported scales and methods, although effective at the individual level, poses challenges for comparison across studies. Therefore, methodological standardization will emerge as a critical need as the field matures. ⁸⁷

The literature on the sensory evaluation of 3D-printed foods highlights a rapidly advancing field with both notable achievements and persistent challenges. Five key research pathways can be identified: First, the limited use of both traditional and emerging sensory methodologies—across diverse scales, trained panel techniques, and consumer tests—highlights the need for standardized evaluation protocols and good sensory practices to establish robust links between instrumental and sensory properties. ^{7, 9, 87} Second, bridging the gap between material science and sensory perception requires integrative studies linking printing parameters, rheological and microstructural features, and sensory responses, supported by advanced tools such as oral tribology, EMG, and digestion models, to move from “printability” to “eatability”. ^{12, 36} Third, research should expand toward personalized nutrition and sustainability, using 3D printing to tailor foods for specific populations and to valorize alternative resources (by-products, insects, algae, plant proteins), while addressing sensory acceptance through parameter optimization. ^{2, 15} Fourth, technological innovations and AI integration offer opportunities to design multi-material structures with novel sensory experiences and to apply machine learning for predictive sensory-driven printing, moving beyond trial-and-error approaches. ^{6, 14} Finally, progress depends on consumer-centric approaches and market translation, including large-scale overall liking studies, strategies to reduce neophobia, and techno-economic analyses to scale up production from prototypes to viable commercial products. ^{35, 38}