Development and validation of a computational model for steak double-sided pan cooking. (June 2021)

• Record Type: Journal Article
• Authors: Moya, J.; Lorente-Bailo, S.; Salvador, M.L.; Ferrer-Mairal, A.; Martínez, M.A.; Calvo, B.; Grasa, J.
• Is Part Of: Journal of food engineering. Volume 298(2021)
• Publication Date: 2021-06
• Subjects: Cooking -- Food model -- Beef meat -- Shrinkage -- Finite elements; Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Analyse -- Périodiques; Aliments -- Recherche -- Périodiques; 664.005
• DOI: 10.1016/j.jfoodeng.2021.110498
• Languages: English
• ISSNs: 0260-8774

Abstract

Abstract: The objective of this study was to develop and validate a numerical model to adequately simulate the double-sided pan cooking of beef in a domestic environment. The proposed model takes into account the heat flow from the pan to the meat and the moisture transfer, simultaneously with the meat deformation. The model considers the swelling pressure gradient caused by the shrinkage of the meat fibers and connective tissue due to the denaturation of proteins and the loss of the water holding capacity during cooking. The model results were successfully verified with experimental data of the central temperature and weight loss recorded during cooking for three degrees of doneness. The measured experimental temperatures at the center of the meat were 30 ± 3 °C (very rare), 44 ± 3 °C (rare) and 57 ± 2 °C (done) for a 19 mm steak thickness. Meanwhile, their water losses were 4 ± 2 %, 8 ± 1 % and 11 ± 2 %, respectively. The root mean squared errors of the model predictions were 2.16 °C (very rare), 3.56 °C (rare) and 4.57 °C (done) for the central temperature and 1.48 %, 2.08 % and 2.40 %, respectively for the water loss. The model also correctly predicts cooking times for steaks of different thicknesses, taking weight loss as a reference to set this time. The proposed model is postulated as a useful cooking assistance tool to estimate the optimal cooking time according to consumer preferences.