000110768 001__ 110768
000110768 005__ 20231215090955.0
000110768 0247_ $$2doi$$a10.1016/j.jfoodeng.2021.110498
000110768 0248_ $$2sideral$$a123145
000110768 037__ $$aART-2021-123145
000110768 041__ $$aeng
000110768 100__ $$0(orcid)0000-0002-0293-6270$$aMoya, J.$$uUniversidad de Zaragoza
000110768 245__ $$aDevelopment and validation of a computational model for steak double-sided pan cooking
000110768 260__ $$c2021
000110768 5060_ $$aAccess copy available to the general public$$fUnrestricted
000110768 5203_ $$aThe 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.
000110768 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FSE/T07-20R$$9info:eu-repo/grantAgreement/ES/DGA-FSE/T24-20R$$9info:eu-repo/grantAgreement/ES/MICINN-AEI/RTC-2017-5965-6
000110768 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000110768 590__ $$a6.203$$b2021
000110768 592__ $$a1.115$$b2021
000110768 594__ $$a10.5$$b2021
000110768 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b26 / 144 = 0.181$$c2021$$dQ1$$eT1
000110768 593__ $$aFood Science$$c2021$$dQ1
000110768 591__ $$aENGINEERING, CHEMICAL$$b29 / 142 = 0.204$$c2021$$dQ1$$eT1
000110768 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000110768 700__ $$0(orcid)0000-0001-9471-8520$$aLorente-Bailo, S.$$uUniversidad de Zaragoza
000110768 700__ $$0(orcid)0000-0001-6013-3399$$aSalvador, M.L.$$uUniversidad de Zaragoza
000110768 700__ $$0(orcid)0000-0001-5765-2972$$aFerrer-Mairal, A.$$uUniversidad de Zaragoza
000110768 700__ $$0(orcid)0000-0002-8375-0354$$aMartínez, M.A.$$uUniversidad de Zaragoza
000110768 700__ $$0(orcid)0000-0001-9713-1813$$aCalvo, B.$$uUniversidad de Zaragoza
000110768 700__ $$0(orcid)0000-0002-6870-0594$$aGrasa, J.$$uUniversidad de Zaragoza
000110768 7102_ $$15005$$2555$$aUniversidad de Zaragoza$$bDpto. Ing.Quím.Tecnol.Med.Amb.$$cÁrea Ingeniería Química
000110768 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000110768 7102_ $$12008$$2780$$aUniversidad de Zaragoza$$bDpto. Produc.Animal Cienc.Ali.$$cÁrea Tecnología de Alimentos
000110768 773__ $$g298 (2021), 110498 [12 pp]$$pJ. food eng.$$tJOURNAL OF FOOD ENGINEERING$$x0260-8774
000110768 8564_ $$s7246659$$uhttps://zaguan.unizar.es/record/110768/files/texto_completo.pdf$$yPostprint
000110768 8564_ $$s1289178$$uhttps://zaguan.unizar.es/record/110768/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000110768 909CO $$ooai:zaguan.unizar.es:110768$$particulos$$pdriver
000110768 951__ $$a2023-12-15-08:59:25
000110768 980__ $$aARTICLE