HACCP methodology implementation of meat pâté hazard analysis in pork butchery

Food Control 21 (2010) 1500–1506

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HACCP methodology implementation of meat pâté hazard analysis in pork butchery G. Poumeyrol *, P. Rosset, V. Noel, E. Morelli AFSSA (Agence Française de Sécurité Sanitaire des Aliments – French Food Safety Agency), Laboratoire d’études et de recherches sur la qualité des aliments et sur les procédés agroalimentaires, 23 Avenue du Général de Gaulle, 94706 Maisons-Alfort Cedex, France

a r t i c l e

i n f o

Article history: Received 23 December 2009 Received in revised form 16 March 2010 Accepted 23 March 2010

Keywords: HACCP Hazard analysis Predictive microbiology Temperature Food safety Bacillus cereus Clostridium botulinum Clostridium perfringens Growth Inactivation

a b s t r a c t This paper sets out a bacterial hazard analysis methodology, based on the ISO 22000 standard, which could be adopted by small food manufacturers. The paper provides a practical example: meat pâté prepared by pork butchers. The results of the hazard analysis showed that many bacterial hazards, particularly Listeria monocytogenes, Salmonella and Staphylococcus aureus could be effectively controlled by good hygiene practices. For three microbial hazards – Bacillus cereus, Clostridium botulinum and Clostridium perfringens – specific control measures must be implemented. Hazard analysis provided the necessary basis for a rational choice of these specific control measures. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction The Hazard Analysis and Critical Control Point (HACCP) system is an internationally recognised method for ensuring food safety and its principles have to be applied according to the European regulation, e.g. EC N° 852/2004 (OJEU, 2004). A hazard analysis, the first HACCP principle, must be conducted with care and rigour as its results are then used to define control measures, monitoring and verification procedures. The different stages of this methodology have been defined according to Codex Alimentarius guidelines (CAC, 1997) and aim to ensure food safety management that complies with the ISO 22000 standard (2005). However, as they were drafted for any type of organisation, the requirements of these reference documents are general. In the field of microbiology, few published works describe in detail how to conduct a hazard analysis (Notermans & Mead, 1996; Van Gerwen, de Wit, Notermans, & Zwietering, 1997). In the 1990s, some papers reported the reasoning behind conducting qualitative hazard analysis (Notermans, Zwietering, & Mead, 1994; Untermann, 1998). In recent papers, the analysis of microbial hazards has essentially been based on quantitative risk assessment (QRA) (Fosse, Seegers, & Magras,

* Corresponding author. Tel./fax: +33 149 772 641. E-mail address: [email protected] (G. Poumeyrol). 0956-7135/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodcont.2010.03.017

2008; Van Schothorst, Zwietering, Ross, Buchanan, & Cole, 2009). In practice, it is difficult for small food manufacturers to implement these QRA methodologies. Therefore the purpose of this paper was to provide a bacterial hazard analysis methodology which called on both common reasoning usually applied to qualitative analysis and recent tools used for quantitative analysis. A practical example – meat pâté prepared by pork butchers – was provided. Results are discussed. 2. Hazard analysis methodology The present methodology, assessing only bacterial hazards, is based on the ISO 22000 standard (2005), a general reference document that we had to adapt to our own particular case. Hazard analysis requires knowledge of manufacturing processes and food microbiology skills; at least one of the food safety team member must be trained on HACCP principles. According to this standard, the hazard analysis must be carried out in two successive steps: the initial steps prior to developing the hazard analysis and the hazard analysis itself. The initial steps (ISO 22000, Section 7.3.) for hazard analysis involve characterisation of the food product and process. Based on data on food that has been measured and/or reported in scientific publications, a full description of the food product has to be drawn up, with information such as composition, physico-chemical

G. Poumeyrol et al. / Food Control 21 (2010) 1500–1506

properties (pH, aw, etc.), list of ingredients, packaging. Product use is defined by taking into account reasonably foreseeable uses by consumers. Process characterisation is based on the flow diagram that describes the process observed on site, step by step, even if certain steps may seem at first sight to be of no interest. The diagram can usefully be supplemented with temperatures measured during key stages in the process. Then the hazard analysis itself (ISO 22000, Section 7.4.) is conducted. This comprises three successive steps: hazard identification, hazard assessment and the selection and assessment of control measures. Hazard identification (ISO 22000, Section 7.4.2.): A list of all the bacterial hazards is the starting point for hazard identification. This list has to be as exhaustive as possible in order to consider all the possible hazards and can be compiled from scientific reviews or reported by organizations such as the WHO. It is used to define the most relevant hazards that could be expected in the food product under scrutiny, according to (i) epidemiological data on foodborne diseases linked to the food product, (ii) their prevalence in ingredients used for preparing the product, (iii) their potential occurrence in the process during operations such as handling, and (iv) their potential elimination during the process. At the end of this step, the identified relevant hazards are those potential initial hazards which are not completely eliminated by the inactivation treatment and any potential hazards which could be introduced through contamination after this treatment. Hazard assessment (ISO 22000, Section 7.4.3.): For a given process, each hazard has to be assessed, one after another. This must be performed at each stage according to the corresponding preestablished flow diagram. The possibility of each hazard being introduced, either through ingredients or handling, is assessed at every stage of the process, as is potential growth or inactivation of the hazard. This hazard assessment process is time-consuming and requires a significant amount of work. This stage can be simplified at two

D log ¼

lopt lnð10Þ



n X i¼1

ti

1501

grammes (operational PRPs). These last measures are essential and implemented specifically to control a defined hazard; the difference between them is the determination of critical limits for CCPs (NF V01-006, 2008). The reasoning developed during the hazard analysis itself will be useful later for determining all the other points of the HACCP plan: acceptable limits for CCPs and operational PRPs, monitoring and verification procedures. 3. Practical example: meat pâté prepared by pork butchers 3.1. Material and potential growth estimating method 3.1.1. Material The practical example was a study conducted in five pork butchers sampled in Paris and its suburbs. The food product under examination was meat pâté, prepared and sold on-site. Production workshops were small without any designated high risk zone. Only bacterial hazards were studied. The process was studied from preparation through to display for sale; thus, storage conditions and use of the meat pâté by consumers were not investigated. 3.1.2. Potential growth estimation For a few relevant bacterial hazards, it can be useful to assess their potential growth using simple and predictive microbiology models. Time–temperature profiles monitored for the food product represent the input data. For monitoring these profiles, a time– temperature indicator (Proges Plus, Willems, France) was introduced into the food’s core. Temperature was measured throughout the different stages of the process: baking, cooling, cold storage in a refrigerated room (RR) and in a refrigerated display cabinet (RDC). The growth potential of the hazards was estimated using the Perfringens Predictor freeware model from the ComBase website and/or a simple predictive microbiology model. The predictive microbiology model was the cardinal temperature model with inflection point (CTMI) (Rosso, 1993) or Rosso model. The total growth equation was:

ðT i  T max ÞðT i  T min Þ2 ðT opt  T min Þ½ðT opt  T min ÞðT i  T opt Þ  ðT opt  T max ÞðT opt þ T min  2T i Þ

levels. Firstly hazards can be studied in groups defined according to similarities in their (i) growth and inactivation parameters, (ii) spore-forming capability, (iii) pathogenicity at a low infectious dose, and (iv) contamination source (e.g. rhinopharyngitis, faeces). Moreover, if an inactivation treatment is effective in completely eliminating a hazard, only the stages after this treatment have to be studied. When the assessment of bacterial hazards has to be more accurate, a quantitative hazard assessment can be conducted by estimating growth and/or inactivation potential. For this estimation professionals can use simple predictive microbiology models or software available on websites (ComBase, Pathogen Modelling Program, Sym’Previus, etc.). Selection and assessment of control measures (ISO 22000, Section 7.4.4.): According to the hazard assessment results, control measures are then selected to prevent or eliminate significant hazards or reduce them to an acceptable level. These control measures are classified into two categories: (i) hazards controlled by prerequisite programmes (PRPs), i.e. measures included in good manufacturing practices (GMP) or/and in good hygiene practices (GHP); (ii) critical control points (CCPs) and operational prerequisite pro-

where ti is the timeframe (hours) between i and i + 1; Ti is the temperature (°C) assumed constant between i and i + 1; Tmin is the theoretical minimum growth temperature (°C) of the species; Tmax is the theoretical maximum growth temperature (°C) of the species; Topt is the theoretical optimum temperature (°C) of the species; lopt is the growth rate (h1) of the species in the food at temperature Topt. Thus estimating the potential bacterial growth required four microbial values: the theoretical growth temperatures (Tmin, Tmax, Topt), based only on the bacterium’s specificities and the optimal growth rate (lopt), which depended on the characteristics of the bacterium and also on the nature of the food. 3.2. Results 3.2.1. Initial steps in hazard analysis The food studied was a meat pâté made with pork products (meat, liver), spices (depending on the recipe: pepper, nutmeg, shallots, onion, garlic, parsley, thyme, bay leaf), egg or egg whites, UHT milk, alcohol (depending on the recipe: cognac, white wine, calvados, rum), nitrite salt (NaCl mixed with NaNO2) and additives

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Table 1 Meat pâté process flow diagram and main data to collect for the hazard analysis. Diagram flow

Data to collect

Stage N°

Process stages

1

Delivery of primary ingredients

2

Storage of primary ingredients

Refrigerated room

3 4

Chopping raw meat Adding nitrite salt

Knife, cutter, cutting board Weighing scale

5

Storage in refrigerated room

Refrigerated room

Hygiene practices: staff and equipments Measure of nitrite salt quantity: NaNO2 calculation Food or air temperature

6 7 8

Food processor Spatula, hands Spatula, hands

Duration Hygiene practices: staff and equipments Hygiene practices: staff and equipments Hygiene practices: staff and equipments

9 10

Mixing Adding other ingredients Dividing up in terracotta moulds Covering with bard and caul Baking

Hands Oven

Staff hygiene practices Food time temperature for VP calculation

11

Cooling

Blast chiller (1/5 of cases) Preparation room and then refrigerated room (4/5 of cases)

Cooling duration from 63 °C to 10 °C

12 13

Packaging Storage in refrigerated room

Refrigerated room

Hygiene practices: staff and equipments Air or food time–temperature

14

Display for sale meat pâté slicing

Display cabinet refrigerated room

Air or food temperature Duration

Measured data

Process means Characteristics and quality of primary ingredients Food temperature Food or air temperature

Hygiene practices: staff and equipments

Air temperature: between 2 °C and 8 °C NaNO2: 110 – 140 mg/kg Air temperature: between 2 °C and 8 °C P24 h

VP10 70 between 650 and 7000 5h 8–11 h

Air temperature: between 2 and 8 °C 1 to 10 days Alternates for 4 to 5 days: Air temperature: 12 h/day between 4 and 15 °C 12 h/day between 2 and 8 °C

(preservatives, colourings). The flow diagram summarising different studied processes and main data to collect for the hazard analysis are specified in Table 1. No rework was observed in this process. Raw meat was minced, seasoned, divided between several terracotta moulds, usually containing around 3 kg each, and then baked in oven. After baking and cooling, the meat pâté was partially vacuumpacked, then stored in a refrigerated room (RR) and displayed for sale in a refrigerated display cabinet (RDC). Temperatures monitored during cold storage were between 2 °C and 8 °C in the RR and between 4 °C and 15 °C in the RDC. At the time of sale, the meat pâté was cut into slices and wrapped in paper. The time needed for selling one terrine of meat pâté was 4 or 5 days, and it alternated between display in the RDC during shop opening hours and storage in the RR at night. Usually 3–8 terrines of meat pâté were prepared at the same time, thus the pâté’s shelf life varied between 4 and 5 days (if it was displayed for sale immediately after cooling) and 15 days (if it was displayed for sale for 5 days following 10 days in storage in the RR).

ficient to inactivate bacterial vegetative cells. As Campylobacter and Brucella hazards were inactivated by baking and could not recontaminate the meat pâté afterwards, they were also excluded. Finally, the identified relevant hazards were (i) those which were potentially present before baking, introduced by primary ingredients or handling (Table 2, column B) and not completely inactivated by baking (Table 2, column C) – i.e. spore forms of Bacillus cereus, Clostridium perfringens and Clostridium botulinum, and thermostable toxins from Staphylococcus aureus; (ii) those which could occur after baking, introduced by handling or contaminated surfaces (Table 2, column D) – i.e. Escherichia coli ETEC, EPEC, EIEC, E. coli STEC, Listeria monocytogenes, Salmonella typhi, Salmonella spp., Shigella spp., S. aureus and Yersinia enterocolitica. The references from the literature used to conduct hazard identification are given in Table 2, column E.

3.2.2. Hazard identification Hazard identification was conducted using a list compiled by the WHO (2008, Chap. 6.1), the corresponding bacterial hazards are shown in Table 2 (column A). According to the epidemiological data and the process study, the hazards Aeromonas hydrophila, Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus were excluded since their prevalence in the primary ingredients was negligible and since an absence of recontamination during the process was predictable. Then, inactivation potentialities associated with the process were studied for the other hazards. Pasteurisation values (VP 10 70 ), calculated according to Mafart (2000) from the temperature monitored during baking, were between 650 and 7000; they were suf-

3.2.4. B. cereus assessment B. cereus is a spore-forming bacterium whose enterotoxins are responsible for foodborne diseases. Vegetative cells and spores can occur in primary ingredients (meat, spices). B. cereus is a large taxonomic family made up of several genetic groups with different characteristics (Guinebretière et al., 2007). In this study, we decided to choose the V group because of its intermediate growth characteristics in comparison with the others. This group is slightly psychotropic and its spores have moderate heat resistance (Afchain, Carlin, Nguyen-The, & Albert, 2008; Guinebretière et al., 2007). According to Afchain et al. (2008), minimum (Tmin), optimum (Topt) and maximum (Tmax) temperatures were respectively +3 °C, 35.4 °C and 39.4 °C (values determined for B.

3.2.3. Hazard assessment The potential evolution of each identified hazard was assessed at each stage of the process. The hazards inactivated by cooking were not considered prior to this stage.

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G. Poumeyrol et al. / Food Control 21 (2010) 1500–1506 Table 2 Bacterial hazard identification applied to the meat pâté process.

(A) Bacterial hazards (according to WHO, 2008, Chap. 6.1)

Before baking (B) Contamination – in primary ingredients – after handling

Baking (C) Presence after baking

After baking (D) Recontamination

(E) References

Aeromonas hydrophila Bacillus cereus Brucella spp. Campylobacter spp. Clostridium botulinum Clostridium perfringens Escherichia coli ETEC – EPEC – EIEC Escherichia coli STEC L. monocytogenes Mycobacterium bovis Salmonella typhi Salmonella spp. (non typhi) Shigella spp. Staphylococcus aureus Vibrio cholerae Vibrio parahaemolyticus Vibrio vulnificus Yersinia enterocolitica

– X X X X X X X X X X X X X – – – X

– X – – X X – – – – – – – X (toxin) – – – –

– – – – – – X X X – X X X X – – – X

1, 3, 5 3, 3, 3, 3 3, 3, 3 2 3, 3, 3, 8 2, 8 3,

2 4, 5 5, 6 5 4, 5, 7 4, 5, 6 5

4, 5, 6, 7 5 5, 7 5, 8 5, 7

(1) Daskalov (2006), (2) ICMSF (1996), (3) Fosse et al. (2008), (4) Sagoo et al. (2009), (5) AFSSA (2009), (6) Zhao et al. (2001), (7) Mataragas, Skandamis, and Drosinos (2008), (8) Jaksic, Uhitil, Petrak, Bazulic, and Gumhalter Karolyi (2002) and (9) Yi-Cheng and Chengchu (2007).

cereus from the V group). The optimal growth rate (lopt) was 0.76 h1 (value determined for all the genetic groups). According to the calculated pasteurisation values, baking (Table 1: stage 10) was sufficient to inactivate vegetative cells but not enough to inactivate all spores. During cooling (Table 1: stage 11), spores can germinate after a lag time which varies greatly from a few hours to a few weeks, according to Afchain et al. (2008) and Membre, Kan-King-Yu, and de W. Blackburn (2008). Potential growth of B. cereus was not calculated during cooling. C. perfringens was the bacterial hazard studied at this stage because this bacterium grows faster than B. cereus. Potential B. cereus growth was estimated during cold storage and display for sale (Table 1: stages 13 and 14). This quantitative approach was performed to assess the efficiency of refrigeration conditions. We defined four scenarios representative of typically observed conditions of cold storage and display for sale. They combined two different temperature conditions with two shelf-life conditions. Temperature conditions were (i) 4 °C in the refrigerated room (RR) and 8 °C in the refrigerated display cabinet (RDC); (ii) 6 °C in the RR and 15 °C in the RDC. Shelf-life conditions were (i) 5 days (display for sale beginning immediately after cooling, with 12 h per day of storage in the RDC and 12 h per day of storage in the RR); (ii) 15 days (10 days of cold storage in the RR then 5 days of display for sale under the same storage conditions as above). The potential microbial growth for B. cereus was estimated for each scenario using the Rosso model, with a null lag-time because of a failsafe choice. The results (Table 3) showed potential growth could be high for 2 scenarios. Thus control measures (i.e. respect of maximum refrigeration temperature limits) have to be defined for preventing any high potential B. cereus growth. 3.2.5. C. botulinum assessment C. botulinum is an anaerobic spore-forming bacterium responsible for foodborne diseases due to neurotoxins produced during the growth of vegetative cells in food. C. botulinum vegetative cells and spores can occur in primary ingredients (meat). However, we observed that studied pork butchers added nitrite salt (NaCl with 0.6% NaNO2) to the meat pâté preparation (Table 1: stage 4). The

Table 3 Potential growth of Bacillus cereus calculated for different time–temperature conditions of meat pâté cold storage and display for sale. Room temperature (°C)

Refrigerated Refrigerated Refrigerated Refrigerated a b

room (RR): 4 °C display cabinet (RDC): 8 °C room (RR): 6 °C display cabinet (RDC): 15 °C

Potential Bacillus cereus growth (D log10) Meat pâté shelf-life 5 daysa

15 daysb

0.6

0.6

3.6

4.5

Each day: 12 h in RR + 12 h in RDC. 10 days in RR + 5 days of display for sale (each day: 12 h in RR + 12 h in RDC).

quantity of nitrite was carefully weighed. Nitrite salts are known to prevent production of C. botulinum toxins, mainly because they inhibit the germination of C. botulinum spores. According to the calculated pasteurisation values, the cooking treatment was sufficient to inactivate vegetative cells but not enough to inactivate all spores. Thus, if sodium nitrite is added in sufficient quantity, germination of surviving spores can be prevented and, consequently, growth of vegetative cells will not be observed during cooling and the subsequent stages. So as the controlled addition of sodium nitrite was considered as a sufficient control measure, it was not useful to estimate potential C. botulinum growth. 3.2.6. C. perfringens assessment C. perfringens is a spore-forming bacterium responsible for foodborne diseases due to an enterotoxin produced during sporulation of vegetative cells in the gastrointestinal tract. Vegetative cells and spores can occur in primary ingredients (meat, spices). According to the calculated pasteurisation values for this process, cooking treatment (Table 1: stage 10) was sufficient to completely inactivate vegetative cells but not enough to inactivate all the spores. During cooling after cooking (Table 1: stage 11), surviving spores could germinate after a spore lag time, then vegetative cells could grow, generally as long as the food temperature is above 15 °C (de Jong, 2003). Taking into account this minimum growth temperature, we estimate growth of C. perfringens cannot occur

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during cold storage in the refrigerated room (measured temperatures were between 2 and 8 °C), nor during display for sale in the refrigerated display cabinet (measured temperatures were between 4 and 15 °C). Thus potential C. perfringens growth was estimated to assess efficiency of cooling. In order to take into account the differences in results provided by the usual predictive microbiology models, we used two models: on the one hand, the Perfringens Predictor freeware model available from the ComBase website, which automatically defines growth parameters and spore lag time according to pH (6.2), NaCl concentration (2%), and cured nature of the meat, and on the other hand the Rosso model, whose growth parameters must be defined by the user. For our practical example, we adopted a safe approach and thus defined lopt = 3.54 h1 (Amézquita, Weller, Wang, Thippareddi, & Burson, 2005) and a spore lag time of 1 h 30 (SmithSimpson & Schaffner, 2005). We used the usual growth parameters: Tmin = 10 °C, Topt = 44 °C, Tmax = 52 °C (de Jong, Beumer, & Zwietering, 2005). Three of the measured time–temperature profiles were analysed because they were typical of the usually observed practices. Cooling time durations were measured from 63 °C to 10 °C as required by French regulations. The results (Table 4) show significant potential C. perfringens growth for a few time–temperature profiles. This highlights that the cooling step is an essential control measure to prevent this hazard. 3.2.7. Hazard assessment of E. coli ETEC, EPEC and EIEC, E. coli STEC, L. monocytogenes, S. typhi, Salmonella spp., Shigella spp. and Y. enterocolitica These bacterial hazards were grouped together because, while they were all inactivated by cooking, they could occur in food following this step. The hazard analysis was conducted step by step for each of these hazards. First it emphasised that, when these hazards occurred in primary ingredients (Table 1: stages 1–9), they were completely inactivated by cooking because they are heat-sensitive. Operations prior to baking therefore have no effect on the evolution of these hazards in food. On the other hand when these hazards occurred during packaging after baking (Table 1: stage 12), contaminations affected only product surfaces and good hygiene practices could be effective enough. Lastly good hygiene practices (GHP) had to be strictly applied during display for sale (Table 1: stage 14). At this stage, handling and slicing operations could induce sizeable contamination, particularly L. monocytogenes and Salmonella. Moreover measured temperature and display duration ranges – respectively between 4 and 15 °C in RDC and 4 or 5 days long – make it possible for them to grow. The GHP efficiency could be assessed by appropriated bacteriological analysis (e.g. colony count technique at 30 °C and/or enumeration of Enterobacteriaceae at 37 °C). Conformity with food safety criteria (EC N°2073/2005 – OJEU, 2005 amended by EC N°1441/2007 – OJEU, 2007) at sale stage has also to be assessed, namely L. monocytogenes under Table 4 Potential growth of Clostridium perfringens estimated for different cooling practices. ComBase modelling: Input data: pH: 6.2; NaCl: 2%; meat product is cured Rosso modelling: Input data: Tmin: 10 °C; Topt: 44 °C; Tmax: 52 °C; lopt: 3.56 h1; sodium nitrite: 156 ppm.

a b

Cooling situation

Time duration (h) from 63 °C to 10 °C

Clostridium perfringens potential growth (Dlog10) ComBase

Rosso model

Aa Bb Db

5 8 11

0 0.1 1.4

0.5 1.4 3.3

Cooling in blast chiller, then in refrigerated room. Cooling in preparation room, then in refrigerated room.

100 cfu/g (n = 5, c = 0) and absence of Salmonella in 25 g (n = 5, c = 0). 3.2.8. S. aureus assessment S. aureus is a pathogenic bacterium responsible for foodborne diseases due to its heat-resistant toxins produced in food. Although the bacterium can occur in primary ingredients, its toxins are only produced if food is kept above 10 °C for several hours (ICMSF, 1996). In this case, baking is unable to inactivate the toxins and consequently the S. aureus toxin will ultimately be found in the food. In addition, S. aureus vegetative cells may also contaminate food after baking because of inadequate food handling by ‘‘germ carriers” or operators with rhinopharyngeal or cutaneous infections. Thus, before and after baking, the strict GHP application, such as respect of the cold chain or personal hygiene, is sufficient to prevent S. aureus foodborne diseases. 3.3. Discussion: selection and assessment of control measures Good hygiene practices (GHP) and good manufacturing practices (GMP) – particularly in our case, respect of baking time temperature conditions – must be applied at each step of the process. When they are strictly applied, they are effective enough to control the thermolabile hazards: E coli ETEC, EPEC and EIEC, E. coli STEC, L. monocytogenes, S. typhi, Salmonella spp., Shigella spp., Y. enterocolitica and S. aureus (Table 5). GHP application is mainly important during display for sale because of handling and slicing operations. However specific control measures (CCPs) must be implemented in order to prevent the following hazards: C. botulinum during preparation, C. perfringens during cooling after cooking and B. cereus during display for sale (Table 5). The application of a decision tree, recommended by C. Alimentarius (CAC, 1997) as a logical reasoning guidance for determining CCPs, shows these stages (preparation, cooling, display for sale) are CCPs. Indeed at each one are both linked: (i) a control measure which is essential to control these hazards to acceptable levels; (ii) a measurable critical limit which warrants efficiency of control measure (C. botulinum: recommended quantities of nitrite salt; C. perfringens: maximum time duration of cooling; B. cereus; maximum temperature in RDC). Meat pâté must be prepared in a way that ensures control of C. botulinum (Table 1: stage 4). The control measure to apply is the addition of a sufficient quantity of nitrite salt (defined by the sodium nitrite NaNO2 concentration). Thus this stage is defined as CCP. According to European Directive 2006/52/EC (OJEU, 2006) and EFSA (2003), the maximum dose of sodium nitrite (NaNO2) in meat products is 150 mg/kg. This measure is an easy and effective way to control this particularly dangerous hazard, responsible for severe and even fatal diseases. Cooling after cooking (Table 1: stage 11), stage defined as CCP, must be short enough to limit the growth of C. perfringens. We defined the maximum growth increment according to USDA recommendations (2001), i.e. 1 log. Calculated with either model, ComBase or Rosso, the potential growth obtained by practice A (Table 4: meat pâté cooled in blast chiller) was the only one consistent with this required increment. Cooling in preparation room is too long (around 8–11 h, even 21 h observed in one case) and induces a growth increment above 1 log. B. cereus will also be controlled because their growth rate is slower than C. perfringens. Refrigerated display for sale (Table 1: stage 14) is a stage defined as CCP to control B. cereus hazard. It was decided to use the same maximal growth increment for B. cereus (1 log10) as the one defined by the USDA (2001) for C. perfringens. The estimated potential growth (Table 3) indicated that the cold storage duration at adequate temperatures in the RR (64 °C) and the RDC (68 °C)

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G. Poumeyrol et al. / Food Control 21 (2010) 1500–1506 Table 5 Hazard assessment elements and proposed control measures. N°

Process stages

Main bacterial hazards to control

Hazard evolution

Control measures (classification)

1

Delivery of primary ingredients Storage of primary ingredients Chopping raw meat Adding nitrite salt Storage in refrigerated room Mixing Adding other ingredients Dividing up in terracotta moulds Covering with bard and caul Baking Cooling Packaging

B. cereus, C. botulinum, C. perfringens, S. aureus B. cereus, S. aureus

Initial contamination eventual growth Growth

Primary ingredient quality delivery temperatures (GHPa) Cold storage temperature (GHP)

B. cereus, C. perfringens, S. aureus C botulinum B. cereus, S. aureus

Contamination by handling Growth inhibition Growth

Hygiene practices: staff and equipments (GHP) Nitrite salt: measured quantity (CCP) Cold storage temperature (GHP)

B. cereus, C. perfringens, S. aureus B. cereus, C. perfringens, S. aureus B. cereus, C. perfringens, S. aureus

Contamination Contamination Contamination

Hygiene practices: staff and equipments (GHP) Hygiene practices: staff and equipments (GHP) Hygiene practices: staff and equipments (GHP)

B. cereus, C. perfringens, S. aureus Pathogen thermolabile bacteriac B. cereus, C. perfringens Pathogen thermolabile bacteriac

Contamination Inactivation Growth Contamination

Storage in refrigerated room

B. cereus

Growth

Pathogen thermolabile bacteriac

Recontamination and eventual growth Growth

Cold storage temperature efficient covering (GHP)

Recontamination and eventual growth

Hygiene practices: staff and equipments (GHP)

2 3 4 5 6 7 8 9 10 11 12 13

14

Display for sale meat pâté slicing

B. cereus Pathogen thermolabile bacteria

a b c

c

Recipe time temperature (GMPb) Fast cooling (CCP) Efficient covering hygiene practices: staff and equipments (GHP) Cold storage temperature (GHP)

Temperature below critical limit (CCP)

GHP: Good Hygiene Practices. GMP: Good Manufacturing Practices. Pathogen thermolabile bacteria: E coli, L. monocytogenes, S. typhi, Salmonella spp., Shigella spp., Y. enterocolitica, S. aureus.

was sufficient to control the growth of B. cereus in meat pâté. When the RR and RDC temperatures greatly exceeded these values, potential growth was greater than the recommended value. In this case, professionals must acquire more efficient equipment or modify their processes in order to shorten shelf life: for example they could use smaller terracotta moulds in which case display for sale would be less than 5 days.

4. Conclusion This paper sets up a methodology, applied to a practical example, to conduct bacterial hazard identification and to assess the identified hazards. This hazard assessment leads to the discrimination between hazards controlled by prerequisite programmes (PRPs) – i.e. good hygiene practices (GHP) and good manufacturing practices (GMP) – and hazards controlled by specific control measures. In order to improve the assessment of these last hazards, potential growth estimation can be conducted, using simple predictive microbiology models, in view to assess the effects of professional practices on bacterial food safety; an approach which is a quite useful tool for selecting relevant control measures. A lot of time and specific skills are required to conduct this methodology. Such thought processes could seem impracticable for small manufacturers, but professional organizations could conduct these hazard analysis studies for several small companies with similar activities. In this study – meat pâté fabrication in pork butchery – hazard analysis showed that only 3 specific control measures, applied at stages defined as critical control points (CCPs), had to be implemented: control of C. botulinum, C. perfringens and B. cereus respectively by nitrite salt addition during preparation, short cooling duration, appropriate refrigeration temperatures during display for sale. Nevertheless respect of good hygiene practices was also quite important throughout the process, particularly during display for sale in view to minimize L. monocytogenes, Salmonella and S. aureus contaminations due to handling and slicing.

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