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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Veröffentlicht in:Journal of food science 2024-09, Vol.89 (9), p.5812-5822
Hauptverfasser: 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
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container_end_page 5822
container_issue 9
container_start_page 5812
container_title Journal of food science
container_volume 89
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
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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. 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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. 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source MEDLINE; Wiley Online Library Journals Frontfile Complete
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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