Using food safety objectives to manage microbial risks

Part I RisksRisks

2.3 Using food safety objectives to manage microbial risks

Definitions of a food safety objective (FSO) and related terms are provided in Table 2.4. The principle of FSO is very simple, the initial level (Ho) minus the sum of all reductions (R) plus the sum of all growth (G) and recontamination (C) must be smaller than the FSO, a limit set by governments:

HoÿR ‡ G ‡ C < FSO …2:1†

This FSO is the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the appropriate level of protection (ALOP) (CAC, 2004). This clearly shows the philosophy: a risk of zero does not exist. It is much better to set an appropriate level and perform actions to achieve this objective than to have one's head in the sand. Of course, this appropriate level is not something that remains the same forever; it can be changed for societal, political or technical reasons.

The FSO is a maximal concentration that will result in a certain, appropriate level of cases. In this respect, definitions and the correct reporting of units are crucial. If one talks about concentration (organisms per gram) or dose (organ-isms per consumption, for example 100 g), there is a difference of a factor of 100. The use of disease cases per consumption or per year can also easily differ by a factor of 100 if for a certain food product 100 units are consumed per year.

It is also important to report whether a case is defined as infection, disease or death.

Table 2.4 Definitions of a food safety objective (FSO) and related terms

Food safety objective (FSO): The maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the appropriate level of protection (ALOP).

Performance objective (PO): The maximum frquency and/or concentration of a hazard in a food at a specified step in the food chain before the time of consumption that provides or contributes to an FSO or ALOP, as applicable.

Performance criteria (PC): The effect in frequency and/or concentration of a hazard in a food that must be achieved by the application of one or more control measures to provide or contribute to a PO or an FSO.

Source: Codex Alimentarius Commission (2004): ALINORM 04/27/13; Appendix III (p. 83).

38 Handbook of hygiene control in the food industry

Apart from the fact that it is difficult to estimate the number of cases based on an FSO (or the other way around, to derive an FSO from an ALOP), it is also very difficult to set a specific ALOP. It is difficult both to determine what is appropriate and also to `distribute' disease cases over various transmission routes. For example, one can set a level for campylobacteriosis (as the public health goal that is the result of food transmission and other sources), and needs to determine what the FSO for food products should be. In that case one should select what the specific ALOP will be for food transmission of this organism, since the FSO influences only the food transmitted part of all the cases but not any other sources that can cause campylobacteriosis. Secondly, an additional problem is that it is often not the product itself that gives the risk, but the fact that the product cross-contaminates other products, via utensils, surfaces or hands. The fact that it is difficult to set an ALOP does not mean that it should not be done. It is much better to do it directly based on the current state of knowledge and data than to wait until all information is available, since this will never be the case. However, if new information does become available, one should evaluate whether the level should be changed.

2.3.1 Distribution over the chain

A positive aspect about this concept is that once an FSO has been set, the objectives can be distributed over the whole chain from primary production to consumption. A performance objective (PO) can be set for every link in the chain, so that in total the FSO is achieved. This has the great advantage that the most efficient distribution of the objectives over the chain can be found: one has the flexibility to do more in the first stage, or in the last stage, or both. If the PO has been set for one stage, this can again be distributed over various process steps. This defines the performance criterion (PC), for example for a reduction step (pasteurisation) a 6 log reduction is necessary. With this criterion, one can then define process criteria that will attain this reduction (e.g. 72 ëC, 15 s). This is indicated in Fig. 2.6, which shows the relation with HACCP and critical limits. The advantage of this concept is that one has the flexibility to change limits in one stage, as long as one equalises this in another. For example, a process criterion can be changed so that only 5 log reductions are achieved if this factor of 10 is balanced in another process step, or even in another stage in the chain.

One of the problems in setting FSOs, and in relating FSOs to ALOPS, is the fact that it is not the setting of a limit that determines the health burden, but that in many cases extreme levels are determining. This can be illustrated by a very large survey published by Gombas et al. (2003) in which 31 700 ready-to-eat foods were sampled for Listeria. Of these samples, 1.8% were contaminated with Listeria (577 samples). Only 2 out of the 577 positive samples (0.006% of the 31 700 products) contained more than 10⁵ organisms per gram. If we determine the total exposure of all Listeria in these products, these two samples alone represented 97.5% of the total exposure in the 31 700 products, because of The range of microbial risks in food processing 39

their high contamination level. These samples are largely above every FSO that should be set. Therefore one could argue that it is then not so important where to set the limit, but how one controls the compliance, and especially how one can detect and, more importantly, prevent these low-frequency, extreme levels.

2.3.2 Quantitative methods

To estimate the values in the FSO equation one can use microbiological methods or use quantitative microbiology. Characteristic numbers (Zwietering, 2002) showing the change in log numbers can supply the necessary numbers for the equation in a direct way for every stage in the chain, with the first characteristic number, the step characteristic (SC):

SC ˆ kt

ln …10†for growth (G) or inactivation (R) …2:2†

in which k is the specific growth rate or inactivation rate (depending on the temperature and other factors) and t is the time.

It should be noted that SC is only `condition' dependent, i.e. the effect of a heat treatment remains the same whether the initial level of microorganisms is 10<sup>3</sup> organisms/g or 1 organism/g, e.g. a 6D reduction. Therefore, growth and inactivation are `additive' on a logarithmic scale. If growth and inactivation processes are considered to follow first order kinetics, it is possible to express a process without recontamination as:

N ˆ N0exp…k1t† exp…k2t† exp…k3t† exp…k4t† . . . …2:3†

with k the specific growth or inactivation rate, depending on the actual conditions in the stage.

On a log scale these kinetics become additive:

Fig. 2.6 FSO: link limits with end result.

40 Handbook of hygiene control in the food industry

log…N† ˆ log…N₀† ‡ k₁t

ln …10†‡ k₂t

ln …10†‡ k₃t

ln …10†‡ k₄t ln …10†

ˆ H₀‡ SC₁‡ SC₂‡ SC₃‡ SC₄ …2:4†

If, for example, SC₂ is an inactivation, and the other three growth,

G ˆ SC₁‡ SC₃‡ SC₄ and R ˆ SC₂. In principle, the outcome will be equal if process steps are interchanged. It does not matter if first a 4 log growth and then a 6 log reduction takes place, or first a 6 log reduction and then 4 log growth: in both cases the result will be an overall 2 log reduction. This can also be seen from the fact that in eqn 2.2 the effect is dependent only on k and not on the actual level.

There are three exceptions:

1. If within growth the stationary phase is reached, but this is generally not the case for pathogens (and should not be).

2. If the number of organisms in a product unit becomes smaller than 1. Even in that case for large numbers of product units and proportional dose±

response relations without threshold, this does not have an overall effect on the outcome of the risk estimate.

3. History effects may make stages interdependent.

In order to incorporate contamination in the calculations, one can use the second characteristic number, the contamination characteristic (CC):

CC ˆ log Nin‡ Rc

Nin

 

for (re)contamination …C† …2:5†

in which Ninis the numbers entering the stage and Rcis the (re)contamination rate (in colony-forming units/g).

CC is not only condition dependent but also state dependent, depending on the number of entering microorganisms. Contamination is `additive' on a linear scale and not on a logarithmic scale.

For a case where in all stages of the process both growth or inactivation and contamination can take place, one gets:

N ˆ f‰‰…N0‡ Rc1† exp…k1t† ‡ Rc2Š exp…k2t† ‡ Rc3Š exp…k3t† ‡ Rc4g exp…k4t† . . . …2:6†

In this case the final effect can be totally different if contamination occurs at stage 1, 2, 3 or 4 (for example before or after pasteurisation). This can also be seen from eqn 2.5 where the characteristic number depends on the recon-tamination level (R_c) and on the actual state (N_in). A recontamination with 10 cells per gram is much more important if the actual concentration is 1 cfu/g than if it is already 100 cfu/g. This is illustrated in the following example (Fig. 2.7).

An imaginary production process is chosen and Staphylococcus aureus is selected as the pathogen that can be present in the product. During the first production step (mixing) growth is an important factor causing an increase of more than 1 log cfu/g (GC ˆ 1:36). When contamination takes place in the next The range of microbial risks in food processing 41

Fig. 2.7 Evaluation of a production process contaminated with Staph. aureus with characteristic numbers GC (growth characteristic), RC (reduction characteristic) and CC (contamination characteristic). Bold numbers indicate changes in number of organisms larger than 1 log.

step (homogenising) with 1 cfu/g, this does not give a high increase in total number of Staph. aureus cells, since the concentration after the mixing step was already 1.36 log cfu/g (or 23 cfu/g). At the heating step, there is a large reduction of cells (RC ˆ ÿ6:49 log units). When contamination takes place after this heating step (packaging) with 1 cfu/g, this becomes a very important step (CC ˆ 5 log units). Because of the heating step, almost all Staph. aureus cells are inactivated and additional contamination, although at a low level, thus causes a high increase in concentration. When growth is possible during storage, the product can end up with a high number of bacteria (GC ˆ 7 log units). This example shows that the relevance of recontamination strongly depends on the number of microorganisms already present on the product and thus on the process stage.

In the whole process H₀ˆ 0 (or 1 cfu/g), G ˆ 1:36 ‡ 0:08 ‡ 0:08‡

0:22 ‡ 6:96 ˆ 8:7, R ˆ ÿ6:49, C ˆ 0:02 ‡ 5:04 ˆ 5:06, resulting in an exposure of 0 ‡ 8:7 ÿ 6:49 ‡ 5:06 ˆ 7:27 log cfu/g (see log N in the storage step).

2.3.3 Quantification of recontamination

Growth and inactivation can be modelled using various predictive models, such as the first order models as presented previously. Contamination, however, is more difficult to quantify. Nevertheless, attempts should be made to incorporate this factor in the FSO equation so that the relevance of contamination can be compared with growth and inactivation. Recontamination can take place at several stages in a production process. Examples are through biofilm formation in process lines, contaminated equipment via air, or at consumer level where cross-contamination can occur. A way to obtain cross-contamination in the kitchen is the use of the same cutting board to cut chicken followed by preparation of a salad. Cross-contamination then depends on the transfer rates of microorganisms from one surface to the next. Transfer rates from chicken to stainless steel vary between 0 and 10% with a mean of 1.6% for Salmonella and 2.4% for Campylobacter. Transfer from stainless steel to cucumber has a larger variation (between 0 and 100%) with a mean of 34.8% for Salmonella and 42.5% for Campylobacter (Kusumaningrum et al., 2004). This means that when a chicken is contaminated with Campylobacter at a concentration of 4 log cfu/

cm²(or 10⁴cfu/cm²), the mean number of microorganisms on the stainless steel surface will be 2.4 log cfu/cm² (or 240 cfu/cm² ˆ 2.4% of 10 000). The cucumber salad will then be contaminated with 2 log cfu/cm²(or 102 cfu/cm² since 42.5% of 240 ˆ 102). This means that when around 50% is transferred, on a log scale this means that both surfaces end up with around the same concentration (initially 2.4 log (240 cfu/cm²), after transfer 2.13 log (140 cfu/

cm²) left on the surface (57.5 % of 240 cfu/cm²) and 2 log on the cucumber (42.5% of 240 cfu/cm²)).

There are several models available to quantify the various recontamination routes in the production process (den Aantrekker et al., 2002). A relatively The range of microbial risks in food processing 43

simple model to quantify recontamination via the air was developed by Whyte (1986):

Rcˆ CairvsAt=W …2:7†

where Rc is the contamination rate (cfu/g), Cair is the concentration of micro-organisms in the air (cfu/m³), vs is the settling velocity (m/s), A is the exposed product area (m²), t is the exposure time (s), and W is the weight of the product (g).For example, during the production of sliced meat, the product with A ˆ 140 cm²and W ˆ 17 g is exposed to the air for 45 s, resulting in a contamination level of 4 cfu/product or 0.2 cfu/g (C_airis 3.39 log cfu/m³and v_sis ÿ2.59 log m/

s) (den Aantrekker et al., 2003). This means that when the product is sterile, contact with contaminated air causes an increase in concentration with 4 cfu/

product.

Although these simple models do not incorporate all factors that may be of relevance, they can be used to provide an indication of the importance of air contamination compared with the initial contamination of the product and possible growth and inactivation during the production process.