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Microbial Preservation Performance of Cold Storage Units Assessed by Modeling of Time–Temperature Data

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Abstract

Globally, regulations focus on the energy use of cold chain units and not on their food preservation performance. Our hypothesis is that this reflects a lack of practical/science-based assessment protocols which is addressed in this work. About 3 million time–temperature values for fish fillets stored in the bottom drawer independently set at 0.0 °C and a peer-reviewed predictive model were used to assess the microbial preservation performance of a residential refrigerator operating at 5.0 °C. The temperature effect on the exponential growth rate of Pseudomonas spp. on fish fillets was used to generate a refrigerator preservation indicator (RPI) with values < 1, ~ 1, and > 1 describing excellent, acceptable, or poor microbial preservation performance, respectively. Experimental effects evaluated were refrigerator technology (single/variable speed compressor, SS/VS), ambient temperature (21.1/32.2 °C, LT/HT), refrigerator load (22.5/39 kg, RL/HL), and emulation of door openings during meal preparation. Deterministic RPI estimations for the VS compressor ranged from 1.28 to 1.71, while those for SS ranged from 1.13 to 1.24. Probabilistic estimations yielded confidence intervals also exceeding the desirable 1.0 value. Mean comparisons through Tukey’s HSD identified p-values < 0.05 for all main effects; nonetheless, compressor technology was the most influential factor since the compressor × ambient temperature interaction was significant for both compressors and the compressor × food load interaction was significant for VS compressors. It is concluded that users of cold chain units would benefit from regulations covering energy use and preservation performance with the latter assessed by RPI determinations.

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Data Availability

The authors declare that the data is available upon requests submitted to the correspondence author.

Abbreviations

HL:

High load (39.0 kg)

RL:

Regular load (22.5 kg)

HT:

High ambient temperature (32.2 °C)

LT:

Low ambient temperature (21.1 °C)

T min (°C):

Square root model constant associated with a theoretical minimum growth temperature

b :

Square root model constant, its value depends on the time units used and whether microbial counts are expressed as decimal or natural logarithm values

T (t):

Fish fillets center temperature as a function of time

T i (°C):

Average fish fillet center temperature during time interval \({\Delta t}_{i}\) (h)

T rec (°C):

Recommended temperature for refrigerated product handling (1.0 °C for fish fillets)

CFU/g:

Colony-forming unit/g

μ max (T i) (ln CFU/g h):

Exponential growth rate at Ti during time interval \({\Delta t}_{i}\), h

API (log CFU/g) \({\equiv \Delta logN}_{test}\)):

Absolute preservation indicator defined as the estimated microbial counts increase during the test time

RPI :

Refrigerator preservation indicator (RPI) defined as the ratio of the API for test temperatures divided by the API at constant Trec. RPI values < 1, ~1, and >1 correspond to excellent, acceptable, or poor refrigerated preservation performance, respectively.

TTE:

Time-temperature equivalent (Rosset et al., 2004)

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Funding

Author Enrique Martinez Martinez acknowledges the support from CONACyT – Mexico for his stipend scholarship (CVU No. 1106274) and Tecnologico de Monterrey for his doctoral program tuition waiver. Author J. Antonio Torres acknowledges the support from Tecnologico de Monterrey (Research chair funds GEE 1A01001 and CDB081) and from Embraco Mexico S de RL de CV.

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Authors and Affiliations

  1. Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, 64849, Monterrey, NL, Mexico

    Enrique Martínez Martínez, Reynaldo de la Cruz Quiroz, José Guadalupe Ríos Alejandro & J. Antonio Torres

  2. Formerly With Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, 64849, Monterrey, NL, Mexico

    Andrés García Cortés

  3. Formerly With Embraco Mexico S de RL de CV, 66603, Apodaca, NL, Mexico

    Fabian Fagotti

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  1. Enrique Martínez Martínez
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Contributions

Authors Enrique Martinez Martinez and Andres Garcia Cortes worked on the data analysis and preparation of a first draft. Author Enrique Martinez Martinez updated the data analysis, reprocessed the experimental data, implemented new statistical analysis, and prepared multiple revisions of the first draft. Author Reynaldo de la Cruz Quiroz participated in the conceptual project design, data acquisition and manuscript revisions. Author Jose Guadalupe Rios Alejandro participated in statistical analysis. Author Fabian Fagotti participated in the conceptual project design and in the interpretation of experimental findings from a cold chain manufacturer point of view. Finally, author J. Antonio Torres identified the research need, proposed and designed all experiments, provided overall project supervision, allocated resources, approved the methods and the analysis of the experimental data collected, revised all manuscript drafts, and edited and approved the final version here submitted and which has been shared with all coauthors.

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Correspondence to J. Antonio Torres.

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Highlights

• Time-temperature data converted into an effective microbial preservation performance indicator

• Indicator affected by the compressor technology, ambient temperature and food load

• Compressor speed control should consider energy use AND food preservation performance

• To improve preservation performance door openings length/frequency must be lowered

• To improve preservation performance temperature recovery time must be shortened

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Martínez Martínez, E., Cortés, A.G., de la Cruz Quiroz, R. et al. Microbial Preservation Performance of Cold Storage Units Assessed by Modeling of Time–Temperature Data. Food Bioprocess Technol (2024). https://doi.org/10.1007/s11947-024-03344-w

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