Computer-aided food engineering (CAFE) can reduce resource use in product, process and equipment development, improve time-to-market performance, and drive high-level innovation in food safety and quality. Yet, CAFE is challenged by the complexity and variability of food composition and structure, by the transformations food undergoes during processing and the limited availability of comprehensive mechanistic frameworks describing those transformations. Here we introduce frameworks to model food processes and predict physiochemical properties that will accelerate CAFE. We review how investments in open access, such as code sharing, and capacity-building through specialized courses could facilitate the use of CAFE in the transformation already underway in digital food systems.
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A.D. gratefully acknowledges financial support from the USDA Agriculture and Food Research Initiative competitive grant no. 2018-67017-27827. B.N. and P.V. gratefully acknowledge financial support from KU Leuven (project C1 C16/16/002), the Research Foundation – Flanders (FWO) (project G090319N) and the European Commission (H-2020 project ENOUGH 101036588). The views expressed in this manuscript are those of the authors and do not necessarily reflect the position or policy of PepsiCo, Inc.
C.K. is an employee of PepsiCo R&D. All other authors declare no competing interests.
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Datta, A., Nicolaï, B., Vitrac, O. et al. Computer-aided food engineering. Nat Food 3, 894–904 (2022). https://doi.org/10.1038/s43016-022-00617-5