The efficiency and consumer operation of domestic refrigerators

Flynn, Orla M.J; Blair, I. D.; McDowell, D.A.

doi:10.1016/0140-7007(92)90046-w

Cited by 52 publications

(19 citation statements)

References 2 publications

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“…During the last decade, a large number of mathematical models for L. monocytogenes growth have been published (9,11,16,19,21,24,26,31,38), and some of them have been targeted to pasteurized milk (1,40,49). However, since the available data show that conditions that prevail during the chill chain vary significantly (8,17,23,27,28,34,44,45,48), the value of a deterministic application of these models as a tool in safety management of pasteurized milk would be limited.…”

mentioning

confidence: 99%

Probabilistic Model for Listeria monocytogenes Growth during Distribution, Retail Storage, and Domestic Storage of Pasteurized Milk

Koutsoumanis¹,

Pavlis²,

Nychas

et al. 2010

Appl Environ Microbiol

134

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A survey on the time-temperature conditions of pasteurized milk in Greece during transportation to retail, retail storage, and domestic storage and handling was performed. The data derived from the survey were described with appropriate probability distributions and introduced into a growth model of Listeria monocytogenes in pasteurized milk which was appropriately modified for taking into account strain variability. Based on the above components, a probabilistic model was applied to evaluate the growth of L. monocytogenes during the chill chain of pasteurized milk using a Monte Carlo simulation. The model predicted that, in 44.8% of the milk cartons released in the market, the pathogen will grow until the time of consumption. For these products the estimated mean total growth of L. monocytogenes during transportation, retail storage, and domestic storage was 0.93 log CFU, with 95th and 99th percentiles of 2.68 and 4.01 log CFU, respectively. Although based on EU regulation 2073/2005 pasteurized milk produced in Greece belongs to the category of products that do not allow the growth of L. monocytogenes due to a shelf life (defined by law) of 5 days, the above results show that this shelf life limit cannot prevent L. monocytogenes from growing under the current chill chain conditions. The predicted percentage of milk cartons-initially contaminated with 1 cell/1-liter carton-in which the pathogen exceeds the safety criterion of 100 cells/ml at the time of consumption was 0.14%. The probabilistic model was used for an importance analysis of the chill chain factors, using rank order correlation, while selected intervention and shelf life increase scenarios were evaluated. The results showed that simple interventions, such as excluding the door shelf from the domestic storage of pasteurized milk, can effectively reduce the growth of the pathogen. The door shelf was found to be the warmest position in domestic refrigerators, and it was most frequently used by the consumers for domestic storage of pasteurized milk. Furthermore, the model predicted that a combination of this intervention with a decrease of the mean temperature of domestic refrigerators by 2°C may allow an extension of pasteurized milk shelf life from 5 to 7 days without affecting the current consumer exposure to L. monocytogenes.

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mentioning

confidence: 99%

Probabilistic Model for Listeria monocytogenes Growth during Distribution, Retail Storage, and Domestic Storage of Pasteurized Milk

Koutsoumanis¹,

Pavlis²,

Nychas

et al. 2010

Appl Environ Microbiol

134

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“…There was no correlation between the temperature setting and refrigerator temperature. It was found that for some refrigerators, in spite of setting at the coolest position, the temperature is still high (>5 C) [1,2]. .…”

Section: Introductionmentioning

confidence: 99%

“…. Few (15% in the UK survey) or no (Northern Ireland and New Zealand surveys) families use a thermometer to control temperature [1,2]. .…”

Section: Introductionmentioning

confidence: 99%

Study of domestic refrigerator temperature and analysis of factors affecting temperature: a French survey

Laguerre¹,

Derens²,

Palagós³

2002

International Journal of Refrigeration

156

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A survey was carried out in France from April to June 1999. Temperatures were recorded at three levels (top, middle and bottom) of the refrigerator compartment using a data logger. A questionnaire was filled in, enabling the following information to be obtained: characteristics of the family, characteristics of the refrigerator and the use conditions. One hundred and forty-three domestic refrigerators were surveyed, but due to various technical problems, only 119 sets of recorded temperatures were exploitable. The temperatures of the surveyed refrigerators were: average 6.6 C, minimum 0.9 C and maximum 11.4 C. Statistical analysis such as clustering and segmentation were used. It was found that the heterogeneousness of temperature inside each refrigerator seems to be dependent on the type. This study shows the influence of the use conditions on the temperature. No one factor exerts a single direct effect; a combination of the effects of all factors is observed. # 2002 Elsevier Science Ltd and IIR. All rights reserved. C (minimum 0.9 C et maximum 11.4 C). Des analyses statistiques telles que l'arbre de classification et de segmentation ont e´te´utilise´es. L'e´tude a montre´que l'he´te´roge´ne´ite´de tempe´rature dans le compartiment d'un re´frige´r-ateur de´pend du type de re´frige´rateur. L'influence des conditions d'utilisation sont mises en e´vidence. Le niveau de tempe´rature des re´frige´rateurs est le re´sultat de nombreuses interactions entre les diffe´rents parame`tres et non d'un seul des parame`tres en particulier. #

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“…Data can be found on energy consumption (Dlugoszewski & Minczewski, 1984) evaporator coil design (Karpinski, 1984) and the shelf life advantages to be gained with product stored in a special refrigerator containing a 0°C chamber with fan air circulation (Olsson, 1988). However, there appears to be little published data on temperature control within domestic refrigeration apart from that carried out in the United Kingdom (Evans et al, 1991, Flynn et al, 1992, James & Evans, 1992a. To study domestic cooling 2 joints and 2 drumsticks of simulated chicken (Tylose) and 2 one litre cartons of orange juice that had all been equilibrated at 20°C were placed in the refrigerators and their temperatures monitored.…”

Section: Domestic Refrigerationmentioning

confidence: 99%

The chill chain “from carcass to consumer”

James

1996

Meat Science

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To provide safe meat and meat products of high organoleptic quality, attention must be paid to every aspect of the chill chain. The process commences with the initial chilling of the freshly slaughtered carcass and continues through to the storage of the chilled retailportion within the home. Within the chill chain are two different categories of refrigeration processes. In the first group are those such as primary and secondary chilling, where the aim is to change the average temperature of the meat. In the others, such as chilled storage, transport and retail display, maintaining the initial temperature of the meat or meat product is the prime aim. Failure to understand the needs of each process results in excessive weight loss, higher energy use, reduced shelf life or a deterioration in product quality.

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The efficiency and consumer operation of domestic refrigerators

Cited by 52 publications

References 2 publications

Probabilistic Model for Listeria monocytogenes Growth during Distribution, Retail Storage, and Domestic Storage of Pasteurized Milk

Probabilistic Model for Listeria monocytogenes Growth during Distribution, Retail Storage, and Domestic Storage of Pasteurized Milk

Study of domestic refrigerator temperature and analysis of factors affecting temperature: a French survey

The chill chain “from carcass to consumer”

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