Maria M. Gil , Fátima A. Miller , Teresa R.S. Brandão , Cristina L.M. Silva
{"title":"Predictions of Microbial Thermal Inactivation in Solid Foods: Isothermal and Non-isothermal Conditions","authors":"Maria M. Gil , Fátima A. Miller , Teresa R.S. Brandão , Cristina L.M. Silva","doi":"10.1016/j.profoo.2016.06.006","DOIUrl":null,"url":null,"abstract":"<div><p>This work focuses on the use of the Gompertz-inspired model to predict the thermal inactivation behaviour of microorganisms obtained in solid food products, validated for isothermal and non-isothermal conditions. Experiments were carried out in parsley, artificially inoculated with <em>Listeria innocua</em>. For the isothermal conditions tested, the predictive ability of the model was confined. The higher the temperature, the higher deviations observed (i.e. the model underestimates the inactivation behaviour). However, for the non-isothermal condition tested, the model predicted the microbial response accurately.</p></div>","PeriodicalId":20478,"journal":{"name":"Procedia food science","volume":"7 ","pages":"Pages 154-157"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.profoo.2016.06.006","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia food science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211601X16300116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work focuses on the use of the Gompertz-inspired model to predict the thermal inactivation behaviour of microorganisms obtained in solid food products, validated for isothermal and non-isothermal conditions. Experiments were carried out in parsley, artificially inoculated with Listeria innocua. For the isothermal conditions tested, the predictive ability of the model was confined. The higher the temperature, the higher deviations observed (i.e. the model underestimates the inactivation behaviour). However, for the non-isothermal condition tested, the model predicted the microbial response accurately.