Progress 09/01/23 to 08/31/24
Outputs
Target Audience:The research matters on a social level for persons in need of personalized nutrition and customized food delivery, the reason why it is helpful is because the soft delivery of nutrient dense foods on a personalized basis can aid those in health application such as treating dysphagia or eating disorders. Personalized nutrition can aid athletes in personalized nutrition. The delivery method is also applicable for military applications where deployed persons may need efficient and personalized foods or in space exploration missions.Additionally, 3D food printing is an efficient means to deliver foods to address allergy concerns and help nutritious foods reach underserved ares. Work has been conducted with a target audience of student and lab researcher instruction to teach food engineering and design principles for addressing these health issues. Classroom instruction for 3D food printing design principles for 3D printing with a highlight of food applications were provided in undergraduate course for Medical Design and Entrepreneurship for Mechanical Engineers and graduate level course Advanced Engineering Desing for Mechanical Engineers. One undergraduate and two Master's students have conducted research studies in the PD's laboratory for food printing that has included formal instruction for food printing, texture analysis, food ink characterization, and dimensional analysis for printed foods. internships and MS internships in the lab. has been covered in University courses. Food engineering, engineering design, industry contacts. Contact and networking were conducted with two 3D food printing companies for informal education and learning regarding translational research from food printing research to practice. Outreach was conducted through the Research Made Accessible program for informal education of one high school student regarding research in food engineering and printing. Changes/Problems:A key goal in this Seed Grant project is establishing a collaboration with comparable experimental setups between laboratories at TTU and OSU which has required a setup period in establishing regular communication among researchers at each institution and shared protocols. We have successfully established a productive collaborative environment with some aspects of setups and logistics in this new collaboration requiring further time for training and setup that have created a short delay on expenditures at OSU while Dr. Egan and Dr. Maleky have focused on establishing the setup and protocols at TTU. We plan to request a no-cost extension to effectively use the remaining funding for carrying out the project for OSU goals that build from TTU work in initial food ink characterization. Our work to-date has been carried out according to the planned grant work as described in the accomplishments section and we anticipate the continued work in the next reporting period will continue building in the direction of the original proposal. Assessment of printability was planned with 3D scanning software, however, the data with 3D scanning was not consistent and difficult to analyze in comparison to 2D imaging that has greater reliability and requires less computational resources. We plan to conduct automated printability assessment with 2D imaging approach to generate bulk data for training the machine learning algorithm. As we continue into the next year of the research and better determine the scope of the machine learning algorithm integration with 3d food printing and predicting results, the scope and focus of data collection will be adjusted to demonstrate algorithm predictability for a subset of food printing cases while informing feasibility of the machine learning approach as a whole. We are continuing to follow protocols according to the Data Management Plan. What opportunities for training and professional development has the project provided?Professional development and training has been provided for 1 PhD graduate student and 1 MS graduate student at TTU. These students were trained in food ink preparation, 3D food printing processes, and relevant lab work for printing and characterizing 3D printed foods. How have the results been disseminated to communities of interest?Results were disseminated through an oral presentation to the engineering design community via the 2024 American Society of Mechanical Engineers International Design Engineering Technical Conference Design for the Manufacturing and the Lifecycle Conference Track through published paper with accompanying oral presentation. Results were disseminated through poster and oral presentation at the 2024 USDA NIFA AFRI Novel Foods and Innovative Manufacturing Technologies Project Director's meeting. Results were disseminated through a research poster presentation at the TTU Whitacre College of Engineering Research Day Research Day, 2024. What do you plan to do during the next reporting period to accomplish the goals?In the next reporting period research will focus on Specific Objective 2 to create and train a machine learning algorithm based on food ink characterization for protein mixtures and hydro-oleocolloids that are characterized for printability, texture analysis, and rheological properties. The machine learning will take inputs for food mixtures and mechanical properties of food and output expected printability based on training data. Further ingredients will food ink design will be conducted, especially to understand how food ingredients relate to rheological/textural properties, that then relate to printability. Multiple types of ingredient combinations will be explored to create a proof-of-concept machine learning algorithm to predict properties and/or printability from ingredient combinations that is informed by scientific experiments that characterize underlying food science and mechanics principles to interpret results.
Impacts
What was accomplished under these goals?
Specific Objective 1 was planned for first year and Specific Objective 2 focused for second year, with accomplishments in the first year of the project accomplishing goals for each specific objective. For Specific Objective 1 Printability characterization for protein inks has been conducted for inks with potato mixed reinforced with pea protein and also hydrooleocolloids reinforced with whey protein. Our working hypothesis was investigated by altering the relative rations of ingredients (e.g. water, potato, and pea protein weight) and conducting texture analysis while also measuring dimensions of printed objects for each ink. Specific experiments conducted included systematically altering the relative amount of mashed potato, pea protein, and water to form protein inks with varied physical and sensory properties. Designs were generated to test overhang features for protein inks to assess their printability that can be used as input data to train the machine learning algorithm. Each protein ink was characterized for moisture content, pH, and textural properties. Specific experiments were also conducted to systematically alter ingredients for hydroolleocolloids by altering the amount of protein and wax in the system. The hydroollecolloids were printed to determine favorable ratios of ingredients to produce these novel foods and ensure consistent manufacturing. We successfully printed the hydroollecolloids which provides a positive result to continue the research into year 2 while investigating further ingredient combinations. For Specific Objective 2 Work has been conducted for planning the algorithm for machine learning and collecting preliminary data to link food ink ingredients, to mechanical properties, to printability that the machine learning algorithm will predict to personalize foods for users.
Publications
- Type:
Conference Papers and Presentations
Status:
Awaiting Publication
Year Published:
2024
Citation:
Khalil, I., F. Maleky, R. Pal, and P. Egan. Manufacturability of protein-reinforced foods with overhang designs. ASME IDETC Design for Manufacturing and the Lifecycle Conference. Washington, DC, 2024.(12 pages)
- Type:
Book Chapters
Status:
Submitted
Year Published:
2025
Citation:
Kahlil, M., A. Habib, Y. Kondabathula, O. Adebo, F. Maleky, and P. Egan. Multi-material printing for medical design. Food Additive Manufacturing: Materials, Process, and Products. Taylor and Francis Group, submitted.
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