Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices
A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein m...
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Veröffentlicht in: | International journal of food microbiology 2021-07, Vol.349, p.109230-109230, Article 109230 |
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creator | Kern, Christian Stefan, Thorsten Sacharow, Julia Kügler, Philipp Hinrichs, Jörg |
description | A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein matrix that was inoculated by one single central injection of starter culture. The resulting spatio-temporal distributions of lactococci strains, lactose, lactic acid/lactate and pH allowed us to optimize a number of parameters of the predictive model. Using the optimized model, the agreement between simulation and experiment was found to be satisfactory, with the pH matching best. The predictive model unveiled that effective diffusion of substrate and metabolites were crucial for an eventual homogeneous distribution of the measured substances. Hence, while using the optimized parameters from the single injection model, an injection technology for starter culture to inoculate and ferment casein matrices homogeneously was developed by means of solving another optimization problem with respect to injection positions. The casein matrix inoculated by the proposed injection pattern (21 injections, distance = 19 mm) showed sufficient homogeneity (bacterial activity and pH distribution) after the early stages of ripening, demonstrating the potential of application of the injection technology for fermentation of casein-based foods e.g. cheese.
•Spatially explicit food models were created and refined via reaction-diffusion equations.•Model describes early ripening of cheese (8 wk) with centrally injected Lactococci.•The model satisfactorily predicts concentration changes over space and time.•Development of new injection technology for cheese ripening based on model |
doi_str_mv | 10.1016/j.ijfoodmicro.2021.109230 |
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•Spatially explicit food models were created and refined via reaction-diffusion equations.•Model describes early ripening of cheese (8 wk) with centrally injected Lactococci.•The model satisfactorily predicts concentration changes over space and time.•Development of new injection technology for cheese ripening based on model</description><identifier>ISSN: 0168-1605</identifier><identifier>EISSN: 1879-3460</identifier><identifier>DOI: 10.1016/j.ijfoodmicro.2021.109230</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Casein ; Cheese ripening ; Fermentation ; Fermented food ; Finite element method ; Food ; Homogeneity ; Injection ; Lactic acid ; Lactose ; Mathematical models ; Metabolites ; Model validation ; Optimization ; Parameters ; pH effects ; Prediction models ; Reaction-diffusion equations ; Ripening ; Semisolids ; Spatio-temporal predictive modeling in food ; Starter cultures ; Substrates ; Technology</subject><ispartof>International journal of food microbiology, 2021-07, Vol.349, p.109230-109230, Article 109230</ispartof><rights>2021</rights><rights>Copyright Elsevier BV Jul 2, 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c382t-7562e584facb510650784aa5d904b8ac50d7267fb0b0d61774993620e2f656383</citedby><cites>FETCH-LOGICAL-c382t-7562e584facb510650784aa5d904b8ac50d7267fb0b0d61774993620e2f656383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ijfoodmicro.2021.109230$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Kern, Christian</creatorcontrib><creatorcontrib>Stefan, Thorsten</creatorcontrib><creatorcontrib>Sacharow, Julia</creatorcontrib><creatorcontrib>Kügler, Philipp</creatorcontrib><creatorcontrib>Hinrichs, Jörg</creatorcontrib><title>Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices</title><title>International journal of food microbiology</title><description>A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein matrix that was inoculated by one single central injection of starter culture. The resulting spatio-temporal distributions of lactococci strains, lactose, lactic acid/lactate and pH allowed us to optimize a number of parameters of the predictive model. Using the optimized model, the agreement between simulation and experiment was found to be satisfactory, with the pH matching best. The predictive model unveiled that effective diffusion of substrate and metabolites were crucial for an eventual homogeneous distribution of the measured substances. Hence, while using the optimized parameters from the single injection model, an injection technology for starter culture to inoculate and ferment casein matrices homogeneously was developed by means of solving another optimization problem with respect to injection positions. The casein matrix inoculated by the proposed injection pattern (21 injections, distance = 19 mm) showed sufficient homogeneity (bacterial activity and pH distribution) after the early stages of ripening, demonstrating the potential of application of the injection technology for fermentation of casein-based foods e.g. cheese.
•Spatially explicit food models were created and refined via reaction-diffusion equations.•Model describes early ripening of cheese (8 wk) with centrally injected Lactococci.•The model satisfactorily predicts concentration changes over space and time.•Development of new injection technology for cheese ripening based on model</description><subject>Casein</subject><subject>Cheese ripening</subject><subject>Fermentation</subject><subject>Fermented food</subject><subject>Finite element method</subject><subject>Food</subject><subject>Homogeneity</subject><subject>Injection</subject><subject>Lactic acid</subject><subject>Lactose</subject><subject>Mathematical models</subject><subject>Metabolites</subject><subject>Model validation</subject><subject>Optimization</subject><subject>Parameters</subject><subject>pH effects</subject><subject>Prediction models</subject><subject>Reaction-diffusion equations</subject><subject>Ripening</subject><subject>Semisolids</subject><subject>Spatio-temporal predictive modeling in food</subject><subject>Starter cultures</subject><subject>Substrates</subject><subject>Technology</subject><issn>0168-1605</issn><issn>1879-3460</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqNkUFr3DAQhUVpoNuk_0Ehl168GUmWbPdWlrQNBBJIchZaaZzK2JYraQNL_ny1bA4hp5wGHt97M9Ij5JzBmgFTl8PaD30IbvI2hjUHzorecQGfyIq1TVeJWsFnsipsWzEF8gv5mtIAAFIIWJGXu4jO2-yfkU7B4ejnJxp6mv8iRRPHPU3ZPGE6aAknX6UwekcPK2n0C86F_0HvF5N9qDJOS4hmpG4_m3JRon5-67ImYVEmk6O3mM7ISW_GhN9e5yl5_HX1sPlT3dz-vt78vKmsaHmuGqk4yrbujd1KBkpC09bGSNdBvW2NleAarpp-C1twijVN3XVCcUDeK6lEK07J92PuEsO_HaasJ58sjqOZMeyS5lIwKTrOm4JevEOHsItzua5QJbdWLWOF6o5U-fOUIvZ6iX4yca8Z6EMtetBvatGHWvSxluLdHL1YXvzsMepkPc62tBDRZu2C_0DKfw7UnF4</recordid><startdate>20210702</startdate><enddate>20210702</enddate><creator>Kern, Christian</creator><creator>Stefan, Thorsten</creator><creator>Sacharow, Julia</creator><creator>Kügler, Philipp</creator><creator>Hinrichs, Jörg</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7QR</scope><scope>7T7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20210702</creationdate><title>Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices</title><author>Kern, Christian ; Stefan, Thorsten ; Sacharow, Julia ; Kügler, Philipp ; Hinrichs, Jörg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-7562e584facb510650784aa5d904b8ac50d7267fb0b0d61774993620e2f656383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Casein</topic><topic>Cheese ripening</topic><topic>Fermentation</topic><topic>Fermented food</topic><topic>Finite element method</topic><topic>Food</topic><topic>Homogeneity</topic><topic>Injection</topic><topic>Lactic acid</topic><topic>Lactose</topic><topic>Mathematical models</topic><topic>Metabolites</topic><topic>Model validation</topic><topic>Optimization</topic><topic>Parameters</topic><topic>pH effects</topic><topic>Prediction models</topic><topic>Reaction-diffusion equations</topic><topic>Ripening</topic><topic>Semisolids</topic><topic>Spatio-temporal predictive modeling in food</topic><topic>Starter cultures</topic><topic>Substrates</topic><topic>Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kern, Christian</creatorcontrib><creatorcontrib>Stefan, Thorsten</creatorcontrib><creatorcontrib>Sacharow, Julia</creatorcontrib><creatorcontrib>Kügler, Philipp</creatorcontrib><creatorcontrib>Hinrichs, Jörg</creatorcontrib><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of food microbiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kern, Christian</au><au>Stefan, Thorsten</au><au>Sacharow, Julia</au><au>Kügler, Philipp</au><au>Hinrichs, Jörg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices</atitle><jtitle>International journal of food microbiology</jtitle><date>2021-07-02</date><risdate>2021</risdate><volume>349</volume><spage>109230</spage><epage>109230</epage><pages>109230-109230</pages><artnum>109230</artnum><issn>0168-1605</issn><eissn>1879-3460</eissn><abstract>A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein matrix that was inoculated by one single central injection of starter culture. The resulting spatio-temporal distributions of lactococci strains, lactose, lactic acid/lactate and pH allowed us to optimize a number of parameters of the predictive model. Using the optimized model, the agreement between simulation and experiment was found to be satisfactory, with the pH matching best. The predictive model unveiled that effective diffusion of substrate and metabolites were crucial for an eventual homogeneous distribution of the measured substances. Hence, while using the optimized parameters from the single injection model, an injection technology for starter culture to inoculate and ferment casein matrices homogeneously was developed by means of solving another optimization problem with respect to injection positions. The casein matrix inoculated by the proposed injection pattern (21 injections, distance = 19 mm) showed sufficient homogeneity (bacterial activity and pH distribution) after the early stages of ripening, demonstrating the potential of application of the injection technology for fermentation of casein-based foods e.g. cheese.
•Spatially explicit food models were created and refined via reaction-diffusion equations.•Model describes early ripening of cheese (8 wk) with centrally injected Lactococci.•The model satisfactorily predicts concentration changes over space and time.•Development of new injection technology for cheese ripening based on model</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ijfoodmicro.2021.109230</doi><tpages>1</tpages></addata></record> |
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subjects | Casein Cheese ripening Fermentation Fermented food Finite element method Food Homogeneity Injection Lactic acid Lactose Mathematical models Metabolites Model validation Optimization Parameters pH effects Prediction models Reaction-diffusion equations Ripening Semisolids Spatio-temporal predictive modeling in food Starter cultures Substrates Technology |
title | Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices |
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