(235e) Computer-Aided Design of Formulated Powdered Soft Drinks Integrating Heuristic Knowledge

Edible and soluble powders are paramount products in the food and beverage industries. Food powders can be distinguished not only by their chemical nature, physicochemical properties, and composition, but also by other characteristics such as particle size distribution, flowability, bulk and porosity density, compressibility, strength, reconstitution and by interaction with the environment (e.g., moisture sorption) ¹. All these characteristics influence functionality, stability, and suitability for certain final applications². Due to the complexity of powder matrixes, designers of novel powder products mainly rely in their experience for their formulation. For instance, when designing powder drinks, expert designers generally use a base formulation that is latter adjusted by adding specific ingredients (e.g. color, flavor, etc.). Then, by observing the behavior of the final mix, the designer fine-tunes the original formulation to improve product performance. At the end, a successful product is obtained when expert and consumer needs are satisfied. Shall it be approved; the product is sent for further evaluation in a larger scale to implement in the production line. Despite this design methodology has been effectively implemented in the food industry, it still involves long development times that delays launch to market and jeopardizes the potential success of the product with consumers. For this reason, the design of formulated consumer products is a major challenge in many industrial sectors from a technical and business point of view³.

In this regard, recent studies have tried to implement a design methodology, useful for structured products, incorporating a computer-aided approach⁴. In this case, product performance is assessed by mean of quantitative parameters or indicators that are then associated to specific physicochemical properties; the latter can be predicted from those of the ingredients using predictive mixing rules and processing models. Then, a mathematical model is constructed based upon such data, and it is further enhanced by incorporating expert’s knowledge (i.e., heuristics) and other restrictions in the form of constrains. Once the model is constructed, and having a portfolio of ingredients, it is possible to computationally develop formulations that would potentially fulfill the required product performance. Then, different formulations can be generated using a specific objective function such as minimizing ingredients costs, among other goals. Such formulations are computationally generated without any additional input, and only the most promising ones are sent for final prototyping and final assessment.

Considering the complexity of food powder, their variety in the market, and need for developing tools to accelerate product design, this project developed a heuristic-assisted computer-aided tool for the design of powder foods. In particular, a study case was built around a powdered drink. Based upon an extensive revision of literature and consultation with experts, it was possible to identify and incorporate main performance properties of powdered food products (e.g. flowability), their dependence on physicochemical properties of the ingredients (e.g. particle size distribution), sensory properties (e.g. sweetness, acidity) and quantity of some ingredients that affects its performance (e.g. anticaking quantity). Such dependency was transformed into mathematical models that enabled to predict the impact of the formulation in the performance of the product. Ingredients were defined according to recommendations from experts and market suppliers. Additionally, legal restrictions (e.g. max. content of certain ingredients) were transformed into inequalities that helped reducing the search space for suitable formulations. The computer tool was implemented in Python, and optimization of formulations was carried out by a MILP problem. A final experimental assessment of the computer-derived instantaneous powder soft drink products was carried out.

References

1. Barbosa-Canovas, G. V., Ortega-Rivas, E., Juliano, P., Yan, H. 2005. Food Powders Physical Properties, Processing, and Functionality. Springer New York, NY https://doi.org/10.1007/0-387-27613-0

2. Ho, T. M., Truong, T., Bhandari, B. R. 2017. Methods to characterize the structure of food powders - A review. Bioscience, Biotechnology and Biochemistry, 81(4), 651–671. https://doi.org/10.1080/09168451.2016.1274643

3. Rivera Gil, J. L., Serna, J., Arrieta-Escobar, J. A., Narváez Rincón, P. C., Boly, V., Falk, V. 2022. Triggers for chemical product design: A systematic literature review. AIChE Journal, 68(4), 1–16. https://doi.org/10.1002/aic.17563

4. Arrieta-Escobar, J. A., Bernardo, F. P., Orjuela, A., Camargo, M., Morel, L. 2019. Incorporation of heuristic knowledge in the optimal design of formulated products: Application to a cosmetic emulsion. Computers & Chemical Engineering, 122, 265–274. https://doi.org/10.1016/J.COMPCHEMENG.2018.08.032