Assessing refrigerated preservation performance using Listeria predictive microbiology models and temperature data: Refrigerator performance indicator and time‐temperature equivalent
Time‐temperature data for queso fresco (QF) cheese varieties stored in a residential refrigerator operating at 5°C and a predictive microbiology secondary model for Listeria monocytogenes in QF were used to estimate a refrigerator performance indicator (RPI) of microbial preservation. RPI values wer...
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creator | Gonzalez de la Garza, Daniela Martínez‐Martínez, Enrique Fernandez Villanueva, Gerardo Cruz Quiroz, Reynaldo Rodriguez‐Martinez, Veronica Fagotti, Fabian Welti‐Chanes, Jorge Torres, J. Antonio |
description | Time‐temperature data for queso fresco (QF) cheese varieties stored in a residential refrigerator operating at 5°C and a predictive microbiology secondary model for Listeria monocytogenes in QF were used to estimate a refrigerator performance indicator (RPI) of microbial preservation. RPI values were used to assess how compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5 kg regular load and 39 kg higher load) affected preservation performance. All deterministic and probabilistic RPI estimations slightly exceeded the desirable 1.0 value, i.e., the variable temperatures for the QF kept in the refrigerator were worse than keeping it constantly at the temperature recommended by food safety agencies for QF. Furthermore, the mean comparison of estimates of the time‐temperature equivalent indicator previously developed by French researchers showed similar behavior to those observed for RPI. Finally, statistical analysis showed that Tambient was the factor with the highest impact on refrigerator performance because of its impact on the sample temperature increase during door openings and when exposed to ambient temperature during product use. This highlights the need to reduce the time for product temperature recovery by improving the compressor operation logic. Also important are consumer behavior changes such as a reduction in product exposure to ambient temperature and in the door opening duration and frequency.
Practical Application
This study demonstrated how a quantitative tool (RPI) can assess refrigerator preservation performance. Although the findings presented can be applied to any cold chain segment, the data used was collected for its weakest link, the domestic refrigerator. Surveys show that 77% of them operate above the recommended 4°C. The RPI methodology is ready for use by refrigerator designers to assess performance improvements possible by modifications of the compressor operation logic. Moreover, it can be integrated into smart‐hubs monitoring the frequency and duration of refrigerator door openings to inform consumers when their habits are compromising the preservation performance of the refrigerator. |
doi_str_mv | 10.1111/1750-3841.17267 |
format | Article |
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Practical Application
This study demonstrated how a quantitative tool (RPI) can assess refrigerator preservation performance. Although the findings presented can be applied to any cold chain segment, the data used was collected for its weakest link, the domestic refrigerator. Surveys show that 77% of them operate above the recommended 4°C. The RPI methodology is ready for use by refrigerator designers to assess performance improvements possible by modifications of the compressor operation logic. Moreover, it can be integrated into smart‐hubs monitoring the frequency and duration of refrigerator door openings to inform consumers when their habits are compromising the preservation performance of the refrigerator.</description><identifier>ISSN: 0022-1147</identifier><identifier>ISSN: 1750-3841</identifier><identifier>EISSN: 1750-3841</identifier><identifier>DOI: 10.1111/1750-3841.17267</identifier><identifier>PMID: 39126699</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Ambient temperature ; Business metrics ; Cheese - microbiology ; cheese preservation ; cheeses ; cold chain ; Colony Count, Microbial - methods ; consumer behavior ; Cryopreservation ; Equivalence ; Food Microbiology - methods ; Food Preservation - methods ; Food safety ; Food Storage - methods ; Impact analysis ; Listeria ; Listeria monocytogenes ; Listeria monocytogenes - growth & development ; Listeria monocytogenes - isolation & purification ; Microbiology ; Microorganisms ; Performance assessment ; Performance prediction ; predictive microbiology ; refrigeration ; Refrigeration - methods ; refrigerator performance indicator ; Refrigerators ; single speed compressors ; Statistical analysis ; Technology assessment ; Temperature ; Time Factors ; variable speed compressors</subject><ispartof>Journal of food science, 2024-09, Vol.89 (9), p.5812-5822</ispartof><rights>2024 Institute of Food Technologists.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2897-e2e5fe45b0b4b61c45d5c610ef1452911d9150860cf94381d082f46bcf094fb63</cites><orcidid>0000-0003-0893-0109</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2F1750-3841.17267$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F1750-3841.17267$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39126699$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gonzalez de la Garza, Daniela</creatorcontrib><creatorcontrib>Martínez‐Martínez, Enrique</creatorcontrib><creatorcontrib>Fernandez Villanueva, Gerardo</creatorcontrib><creatorcontrib>Cruz Quiroz, Reynaldo</creatorcontrib><creatorcontrib>Rodriguez‐Martinez, Veronica</creatorcontrib><creatorcontrib>Fagotti, Fabian</creatorcontrib><creatorcontrib>Welti‐Chanes, Jorge</creatorcontrib><creatorcontrib>Torres, J. Antonio</creatorcontrib><title>Assessing refrigerated preservation performance using Listeria predictive microbiology models and temperature data: Refrigerator performance indicator and time‐temperature equivalent</title><title>Journal of food science</title><addtitle>J Food Sci</addtitle><description>Time‐temperature data for queso fresco (QF) cheese varieties stored in a residential refrigerator operating at 5°C and a predictive microbiology secondary model for Listeria monocytogenes in QF were used to estimate a refrigerator performance indicator (RPI) of microbial preservation. RPI values were used to assess how compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5 kg regular load and 39 kg higher load) affected preservation performance. All deterministic and probabilistic RPI estimations slightly exceeded the desirable 1.0 value, i.e., the variable temperatures for the QF kept in the refrigerator were worse than keeping it constantly at the temperature recommended by food safety agencies for QF. Furthermore, the mean comparison of estimates of the time‐temperature equivalent indicator previously developed by French researchers showed similar behavior to those observed for RPI. Finally, statistical analysis showed that Tambient was the factor with the highest impact on refrigerator performance because of its impact on the sample temperature increase during door openings and when exposed to ambient temperature during product use. This highlights the need to reduce the time for product temperature recovery by improving the compressor operation logic. Also important are consumer behavior changes such as a reduction in product exposure to ambient temperature and in the door opening duration and frequency.
Practical Application
This study demonstrated how a quantitative tool (RPI) can assess refrigerator preservation performance. Although the findings presented can be applied to any cold chain segment, the data used was collected for its weakest link, the domestic refrigerator. Surveys show that 77% of them operate above the recommended 4°C. The RPI methodology is ready for use by refrigerator designers to assess performance improvements possible by modifications of the compressor operation logic. Moreover, it can be integrated into smart‐hubs monitoring the frequency and duration of refrigerator door openings to inform consumers when their habits are compromising the preservation performance of the refrigerator.</description><subject>Ambient temperature</subject><subject>Business metrics</subject><subject>Cheese - microbiology</subject><subject>cheese preservation</subject><subject>cheeses</subject><subject>cold chain</subject><subject>Colony Count, Microbial - methods</subject><subject>consumer behavior</subject><subject>Cryopreservation</subject><subject>Equivalence</subject><subject>Food Microbiology - methods</subject><subject>Food Preservation - methods</subject><subject>Food safety</subject><subject>Food Storage - methods</subject><subject>Impact analysis</subject><subject>Listeria</subject><subject>Listeria monocytogenes</subject><subject>Listeria monocytogenes - growth & development</subject><subject>Listeria monocytogenes - isolation & purification</subject><subject>Microbiology</subject><subject>Microorganisms</subject><subject>Performance assessment</subject><subject>Performance prediction</subject><subject>predictive microbiology</subject><subject>refrigeration</subject><subject>Refrigeration - methods</subject><subject>refrigerator performance indicator</subject><subject>Refrigerators</subject><subject>single speed compressors</subject><subject>Statistical analysis</subject><subject>Technology assessment</subject><subject>Temperature</subject><subject>Time Factors</subject><subject>variable speed compressors</subject><issn>0022-1147</issn><issn>1750-3841</issn><issn>1750-3841</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc1u1DAQxy0EokvhzA1Z4sIlrSexnYRbVSgfWgmJj7PlxOOVqyRO7WSrvfEIPA7Pw5Pg7JYVcKkvlke_-Y08f0KeAzuDdM6hFCwrKg5nUOayfEBWx8pDsmIszzMAXp6QJzFes-VdyMfkpKghl7KuV-TnRYwYoxs2NKANboNBT2joGDBi2OrJ-YGOGKwPvR5apPOeXbs4YXB64YxrJ7dF2rs2-Mb5zm92tPcGu0j1YOiE_bhY54DU6Em_pp-Pk3z4R-6GJNtX942ux1_ff_zdjzez2-oOh-kpeWR1F_HZ3X1Kvl29_Xr5Plt_evfh8mKdtXlVlxnmKCxy0bCGNxJaLoxoJTC0wEVeA5gaBKska23NiwoMq3LLZdNaVnPbyOKUvDp4x-BvZoyT6l1ssev0gH6OqgBRVExK4PejLK29qtLUhL78D732cxjSR5IQkrASfJl9fqDSYmNM-agxuF6HnQKmlvzVkrZa0lb7_FPHizvv3PRojvyfwBMgD8Ct63B3n099vHrz5WD-DafYwBE</recordid><startdate>202409</startdate><enddate>202409</enddate><creator>Gonzalez de la Garza, Daniela</creator><creator>Martínez‐Martínez, Enrique</creator><creator>Fernandez Villanueva, Gerardo</creator><creator>Cruz Quiroz, Reynaldo</creator><creator>Rodriguez‐Martinez, Veronica</creator><creator>Fagotti, Fabian</creator><creator>Welti‐Chanes, Jorge</creator><creator>Torres, J. 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Antonio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing refrigerated preservation performance using Listeria predictive microbiology models and temperature data: Refrigerator performance indicator and time‐temperature equivalent</atitle><jtitle>Journal of food science</jtitle><addtitle>J Food Sci</addtitle><date>2024-09</date><risdate>2024</risdate><volume>89</volume><issue>9</issue><spage>5812</spage><epage>5822</epage><pages>5812-5822</pages><issn>0022-1147</issn><issn>1750-3841</issn><eissn>1750-3841</eissn><abstract>Time‐temperature data for queso fresco (QF) cheese varieties stored in a residential refrigerator operating at 5°C and a predictive microbiology secondary model for Listeria monocytogenes in QF were used to estimate a refrigerator performance indicator (RPI) of microbial preservation. RPI values were used to assess how compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5 kg regular load and 39 kg higher load) affected preservation performance. All deterministic and probabilistic RPI estimations slightly exceeded the desirable 1.0 value, i.e., the variable temperatures for the QF kept in the refrigerator were worse than keeping it constantly at the temperature recommended by food safety agencies for QF. Furthermore, the mean comparison of estimates of the time‐temperature equivalent indicator previously developed by French researchers showed similar behavior to those observed for RPI. Finally, statistical analysis showed that Tambient was the factor with the highest impact on refrigerator performance because of its impact on the sample temperature increase during door openings and when exposed to ambient temperature during product use. This highlights the need to reduce the time for product temperature recovery by improving the compressor operation logic. Also important are consumer behavior changes such as a reduction in product exposure to ambient temperature and in the door opening duration and frequency.
Practical Application
This study demonstrated how a quantitative tool (RPI) can assess refrigerator preservation performance. Although the findings presented can be applied to any cold chain segment, the data used was collected for its weakest link, the domestic refrigerator. Surveys show that 77% of them operate above the recommended 4°C. The RPI methodology is ready for use by refrigerator designers to assess performance improvements possible by modifications of the compressor operation logic. Moreover, it can be integrated into smart‐hubs monitoring the frequency and duration of refrigerator door openings to inform consumers when their habits are compromising the preservation performance of the refrigerator.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>39126699</pmid><doi>10.1111/1750-3841.17267</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-0893-0109</orcidid></addata></record> |
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subjects | Ambient temperature Business metrics Cheese - microbiology cheese preservation cheeses cold chain Colony Count, Microbial - methods consumer behavior Cryopreservation Equivalence Food Microbiology - methods Food Preservation - methods Food safety Food Storage - methods Impact analysis Listeria Listeria monocytogenes Listeria monocytogenes - growth & development Listeria monocytogenes - isolation & purification Microbiology Microorganisms Performance assessment Performance prediction predictive microbiology refrigeration Refrigeration - methods refrigerator performance indicator Refrigerators single speed compressors Statistical analysis Technology assessment Temperature Time Factors variable speed compressors |
title | Assessing refrigerated preservation performance using Listeria predictive microbiology models and temperature data: Refrigerator performance indicator and time‐temperature equivalent |
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