Multiobjective optimization of a frying process balancing acrylamide formation and quality: Solution analysis and uncertainty propagation
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Peñalver Soto, José Lucas; Muñoz Guillermo, María; Garre Pérez, Alberto; Iguaz Gainza, Asunción; Fernández Escámez, Pablo Salvador; [et al.]Knowledge Area
Matemática AplicadaSponsors
This work has been supported by the Spanish Research Agency—AEI (MCIN/AEI/10.13039/ 501100011033) through projects PID2020-116318RB-C32 and MTM2017-84079-P (co-funded by “ERDF A way of making Europe”, by the European Union). JLPS is grateful to the JAE-INTRO program from CSIC (Grant no JAEINT_19_00775).Publication date
2022Publisher
MDPIBibliographic Citation
Peñalver-Soto, J.L.; Muñoz-Guillermo, M.; Garre, A.; Iguaz, A.; Fernández, P.S.; Egea, J.A. Multiobjective Optimization of a Frying Process Balancing Acrylamide Formation and Quality: Solution Analysis and Uncertainty Propagation. Foods 2022, 11, 3689. https://doi.org/ 10.3390/foods11223689Keywords
Multi-objective optimizationModel-based optimization
Equivalent solutions
Uncertainty
Monte Carlo
Frying operation
Acrylamide
Quality
Abstract
In this study, we performed multi-objective model-based optimization of a potato-frying process balancing between acrylamide production and a quality parameter (yellowness). Solution analysis revealed that, for most of the Pareto solutions, acrylamide levels exceeded the EFSA recommendation. Almost equivalent optimal solutions were found for moderate processing conditions (low temperatures and/or processing times) and the propagation of the uncertainty of the acrylamide production model parameters led to Pareto fronts with notable differences from the one obtained using the nominal parameters, especially in the ranges of high values of acrylamide production and yellowness. These results can help to identify processing conditions to achieve the desired acrylamide/yellowness balance and design more robust processes allowing for the enhancement of flexibility when equivalent optimal solutions can be retrieved
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