Traditional dry fermented sausages produced in small-scale processing units in Mediterranean countries and Slovakia. 1: Microbial ecosystems of processing environments

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MEAT SCIENCE Meat Science 77 (2007) 570–579 www.elsevier.com/locate/meatsci

Traditional dry fermented sausages produced in small-scale processing units in Mediterranean countries and Slovakia. 1: Microbial ecosystems of processing environments R. Talon a,*,1, I. Lebert a, A. Lebert b, S. Leroy a, M. Garriga c, T. Aymerich c, E.H. Drosinos d, E. Zanardi e, A. Ianieri f, M.J. Fraqueza g, L. Patarata h, A. Laukova´

i

a INRA, Centre de Clermont-Ferrand Theix, Unite´ de Recherche Microbiologie, 63122 Saint-Gene`s Champanelle, France INRA, Centre de Clermont-Ferrand Theix, Unite´ de Recherche Qualite´ des Produits Animaux, 63122 Saint-Gene`s Champanelle, France c IRTA-Food Technology, 17121 Monells, Spain d Laboratory of Food Quality Control and Hygiene, Department of Food Science and Technology, Agricultural University of Athens, 75 Iera Odos Str., Votanikos GR-118 55, Greece e Dipartimento di Produzioni Animali, Biotecnologie Veterinarie, Qualita` e Sicurezza degli Alimenti, Universita` degli Studi di Parma, 43100 Parma, Italy f Dipartimento di Scienze degli Alimenti, Universita` degli Studi di Teramo 64100 Teramo, Italy g Faculdade de Medicina Veterina´ria, CIISA, U.T. Lisbon, Av. da Universidade Te´cnica, Polo Universita´rio, Alto da Ajuda, 1300-477 Lisbon, Portugal h Universidade De Tras-os-Montes e Alto Douro, Centro de Cieˆncia Animal e Veterina´ria (CECAV), 5000-911 Vila Real, Portugal i Institute of Animal Physiology, Slovak Academy of Sciences, Sˇolte´sovej 4-6, 04001 Kosˇice, Slovakia b

Received 2 March 2007; received in revised form 4 May 2007; accepted 5 May 2007

Abstract Microbial ecosystems were surveyed in 314 environmental samples from 54 Southern and Eastern European small-scale processing units (PUs) manufacturing traditional dry fermented sausages. The residual microflora contaminating the surfaces and the equipment were analysed after cleaning and disinfection procedures. All the PU environments were colonised at various levels by spoilage and technological microflora with excessive contamination levels in some of the PUs. Sporadic contamination by pathogenic microflora was recorded. Salmonella and Listeria monocytogenes were detected in 4.8% and 6.7% of the samples, respectively, and Staphylococcus aureus was enumerated in 6.1% of the samples. Several critical points were identified, such as the machines for S. aureus and the tables and the knives for L. monocytogenes; this knowledge is crucial for the improvement of hygiene control systems in small and traditional meat processing industries. The variability of the residual contamination emphasized the different cleaning, disinfecting and manufacturing practices routinely followed by these small-scale processing units.  2007 Elsevier Ltd. All rights reserved. Keywords: Traditional dry fermented sausages; Small-scale processing unit; Microbial ecosystem; Environment; Hygiene

1. Introduction In many European countries, the demand for traditional food products has increased (Ro¨hr, Lu¨ddecke, Drusch, *

Corresponding author. Tel.: +33 0 4 73 62 41 70; fax: +33 0 4 73 62 42

68. E-mail address: [email protected] (R. Talon). Project coordinator of the EU project TRADISAUSAGE QLK1 CT-2002-02240. 1

0309-1740/$ - see front matter  2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.meatsci.2007.05.006

Mu¨ller, & Alvensleben, 2005; Wilcock, Pun, Khanona, & Aung, 2004). Moreover, food and gastronomy form an inherent link with tourism in Europe, with a renewed interest of consumers in typical and regional food. The latter are made in a non-industrial environment, characterised by small-scale batch production with a limited degree of mechanisation, and strongly identified with a place or region of origin (Kuznesof, Tregear, & Moxey, 1997). Within the processed meat sector, traditional production in Europe can be classified into two main categories.

R. Talon et al. / Meat Science 77 (2007) 570–579

The first one focuses on farm production in which raw meat is obtained from animals bred on the farm (in some regions, using locally-bred animals). In this case, meat processed either on the farm or in very small collective production units, as well as the resulting products, are sold directly by the farmer. This system is well developed in France, Germany, Belgium and the United Kingdom. It is also present in Italy, Slovakia and Northern Portugal. The second one focuses on production by local processing units that may or may not be owned by a butcher that manufactures traditional products from raw meat coming from several farms or slaughterhouses. In Portugal, Spain and Italy, raw materials may come from local slaughterhouses. The products are sold directly by the unit at the local market or supplied to restaurants and delicatessens. This form of production is developed in Southern France, Spain, Italy, Portugal and Germany (Conter et al., 2005; Fadda, Aymerich, Hugas, & Garriga, 2004; Rason, Lebecque, Leger, & Dufour, 2004). Dry fermented sausages, mainly manufactured with pork and/or lean beef and pork fat, account for a significant part of traditional meat products. Most of these products are seasoned and processed with traditional know-how and rely on the natural contamination of the raw materials that occurs during animal slaughtering and that increases during the manufacturing process. In traditional dry fermented sausages, this contaminating microflora colonises the processing unit’s environment and the products in a continuous symbiotic exchange. Such microflora includes useful microorganisms for the fermentation and flavour of sausages, as well as spoilage species and sometimes even pathogenic bacteria. Many studies have dealt with the microbiology of traditional fermented sausages (Aymerich, Martı´n, Garriga, & Hugas, 2003; Comi et al., 2005; Mauriello, Casaburi, Blaiotta, & Villani, 2004; Papamanoli, Tzanetakis, Litopoulou-Tzanetaki, & Kotzekidou, 2003; Rantsiou et al., 2005) but few studies have focused on the microbiology of surfaces and equipment of smallscale processing units (Chevallier et al., 2006; Corbiere Morot-Bizot, Leroy, & Talon, 2006). This paper presents a survey of the microbial ecosystem of environments in 54 processing units in five Mediterranean countries (Spain, Italy, France, Greece, Portugal) and one from East-Central Europe (Slovakia). The objec-

571

tive was to analyse the diversity of the residual spoilage, technological and pathogenic microflora contaminating the surfaces and equipment in order to assess the efficiency of hygienic practices. In parallel the microbial ecosystems of the sausages manufactured in these 54 processing units were surveyed and the data are presented in a second paper (Talon et al., 2007). 2. Materials and methods 2.1. Processing units The processing units investigated were all low-capacity meat product establishments according to the definition of the Council Directive 92/5/EEC (EEC, 1992), in other words, those without industrial structure and with total production capacity of less than 7.5 t/week. Three hundred and fourteen (314) traditional processing units (PUs) selected within the framework of the EU programme (QLK1-CT2002-02240) were located in five European Mediterranean countries and Slovakia and represented a large diversity of economic characteristics (Table 1). The PUs belonged to the ‘‘very small enterprises’’ category because they employed less than 10 people, and sometimes only two or three in France, Southern Italy and Northern Portugal. The 314 PUs were clustered according to their significant characteristics in terms of raw materials and processing criteria, and 10 representative PUs per each Mediterranean country (three for Slovakia) were selected according to the method of Rason et al. (2004). The microbial diversity in the environment was surveyed in the 54 PUs selected as being representative (Table 1). 2.2. Sampling procedure Sampling and analytical methods for the microbial analysis were mainly based on the International Organisation for Standardisation (ISO) and harmonised among the research teams participating in the project. Six environmental surface samples from mincing, mixing and stuffing machines, cutting tables, cold room storage walls and deboning knives were collected in each PU according to ISO 18593:2004. Samples were collected after cleaning

Table 1 Characteristics of the processing units (PUs) Country

Geographic area

PUs surveyed

Average number of employees

Selected PUs

France Greece Italy (Southern) Italy (Northern) Portugal (Southern) Portugal (Northern) Spain Slovakia

Massif Central region 13 Regions located throughout the country Abruzzo region Emilia Romagna and Lombardy regions Alentejo region Province of Tra´z-os-Montes e Alto Douro Catalonia autonomous region Entire country

108 50 25 25 26 25 50 6

3.0 4.3 2.3 4.6 8.7 3.0 4.7 8.5

F01–F10 G01–G10 IS01–IS05 IN01–IN05 PS01–PS06 PN01–PN05 C01–C10 S01–S03

572

R. Talon et al. / Meat Science 77 (2007) 570–579

and disinfection procedures routinely followed by each producer. Samples covering 500 cm2 of the environmental surface were collected using a sterile cloth dampened with a neutralising solution (Humeau, La Chapelle-sur-Erdre, France). Wet cloths were aseptically transferred to 25 ml of sterile buffered peptone water solution (BPW, AES Laboratory) and homogenised with a stomacher. Temperature and relative humidity were measured for each environmental sample at different places in each PU. 2.3. Microbial analysis Occurrence (presence/absence) of Salmonella and Listeria monocytogenes and enumeration of Pseudomonas, yeasts and moulds, lactic acid bacteria (LAB), Staphylococcus and Kocuria, Enterobacteriaceae, Enterococcus, Staphylococcus aureus and L. monocytogenes were performed according to the methods detailed in Table 2.

For enumeration, serial dilutions from BPW solutions were performed before plating in described culture media. For occurrence, BPW solutions were incubated at 37 C for 24–48 h and the presence of the pathogens was confirmed either by selective plating (Table 2) or specific PCR (Table 3). 2.4. PCR analysis for pathogenic bacteria A validated PCR identification protocol from the EU ‘‘Food PCR’’ project (QLK1-CT199-00226) for Salmonella, L. monocytogenes was used both for the confirmation of presumptive colonies and for determining presence or absence. S. aureus was confirmed according to Martineau, Picard, Roy, Ouellette, and Bergeron (1998). The PCR amplification conditions are detailed in Table 3. For the confirmation of the colonies grown in selective media described in Table 2, an isolated colony was sus-

Table 2 Microbial analysis Microflora

Medium

Incubation

References and ISO

Enterobacteriaceae

37 C – 24 h

Merck, Darmstad, Germany; ISO 7402:1993

Pseudomonas spp.

Crystal violet neutral red bile glucose agar (VRBG) Cetrimide-fucidin-cephaloridine agar (CFC)

25 C – 48 h

Lactic acid bacteria

Man-rogosa-sharpe (MRS)

Staphylococcus and Kocuria Enterococcus Yeasts and moulds

Mannitol salt phenol red agar (MSA) M-Enterococcus (ME) Yeast extract glucose chloramphenicol agar (YGC)  Semi-solid Rappaport-Vasiliadis medium (MSRV, supplemented with MSRV selective supplement)  Brillant-green phenol-red lactose sucrose agar  Baird Parker agar supplemented with egg yolk, tellurite emulsion (BP + EYT)  Baird Parker agar supplemented with rabbit plasma fibrinogen (BP + RPF) Listeria agar acc. to Ottaviani and Agosti (ALOA)

Oxoid (Basingstoke, United Kingdom); ISO 13720:1995 Merck, Darmstad, Germany; ISO 15214:1998 Merck, Darmstad, Germany Merck, Darmstad, Germany Merck, Darmstad, Germany; ISO 13681:1995 Merck, Darmstad, Germany

Salmonella (presence/absence) BPW enrichment 24–48 h 37 C Staphylococcus aureus

Listeria monocytogenes

30 C – 48/ 72 h anaerobic 30 C – 48 h 37 C – 48 h 25 C – 48 h 42 C – 24 h

37 C – 48 h 37 C – 24/ 48 h 37 C – 48 h 37 C – 48 h

Merck, Darmstad, Germany Merck, Darmstad, Germany AES Laboratory, Combourg, France; ISO 6888-1:1999 AES Laboratory, Combourg, France; ISO 11290-2:1998, ISO 11290-2:1998/Amd 1:2004

Table 3 PCR amplification conditions Species

Amplified fragment

Target

Primer sequence

PCR cycler profiles

Salmonella

284 bp

InvAa

139: 5 0 -GTGAAATTATCGCCACGTTCGGGCAA 141: 5 0 -TCATCGCACCGTCAAAGGAACC

Listeria monocytogenes

274 bp

prfAb

lip1: 5 0 -GATACAGAAACATCGGTTGGC lip2: 5 0 -GTGTAACTTGATGCCATCAGG

S. aureus

108 bp

Unknownc

Sa442-1: 5 0 AATCTTTGTCGGTACACGATATTCTTCACG Sa442-2: 5 0 CGTAATGAGATTTCAGTAGATAATACAACA

P: 94 C/1 min; DC: 30 cycles of 94 C/30 s; A: 64 C/30 s; E: 72 C/1 min; FI: 72 C/5 min P: 94 C/2 min; DC: 30 cycles 94 C/30 s; A: 60 C/30 s; E: 72 C/1 min; FI: 72 C/5 min P: 96 C/3 min; DC: 30 cycles of 95 C/1 s; A: 55 C/30 s; E: 72 C/30 s; FI: 72 C/5 min

The reaction conditions were: pre-incubation (P), denaturation cycles (DC), annealing (A), extension (E) and final incubation (FI). a Rahn et al. (1992). b Simon et al. (1996). c Martineau et al. (1998).

c

d

Minimum. Maximum. Temperature (C). Relative humidity (%) was not determined in the Greek PUs.

66.0 58.0 55.0 35.7 67.5 77.5 69.0 78.0 65.2 67.5 10 10 11 10 3 France Italy Portugal Spain Slovakia

a

99.0 90.0 90.0 81.3 67.5

Max

16.0 15.0 15.2 18.0 19.4 12.0 8.9 4.0 8.0 9.0 9.2 12.0

Min Median

11.9 10.0 12.3 11.6 14.0 12.0

RHd

b

20.4 11.0 16.0 17.7 19.4 15.0

95.0 90.0 90.0 81.3 90.0 55.0 58.0 55.0 35.7 85.0 80.5 68.8 78.0 67.0 90.0 99.0 90.0 90.0 81.3 67.5 66.0 58.0 55.0 35.7 67.5 77.5 68.8 78.0 65.2 67.5 99.0 90.0 90.0 94.2 67.5 66.0 58.0 55.0 35.7 67.5 77.5 68.8 78.0 65.2 67.5 100.0 90.0 86.0 94.2 67.5 64.0 28.0 40.0 43.6 67.5 89.0 72.5 79.0 56.1 67.5 99.0 90.0 90.0 81.3 67.5 66.0 58.0 55.0 35.7 67.5 80.5 69.0 78.0 65.2 67.5

Min

9.3 7.0 8.0 7.0 4.3 12.0 12.2 10.0 12.8 12.0 14.0 12.0

Median Max

16.0 14.0 16.0 17.7 19.4 10.0 6.9 7.0 8.0 9.0 9.2 10.0

Min Median

11.9 11.0 12.8 11.0 14.0 10.0 16.0 18.0 16.0 17.7 19.4 10.0

Max Min

6.9 7.0 8.0 7.0 2.1 10.0 11.9 11.0 12.8 12.0 13.3 10.0

Median Max

6.2 11.0 5.5 10.0 13.2 1.5 0.5 2.0 2.0 0.3 1.9 1.5

Min Median Max Min Median

3.1 4.0 4.0 4.0 4.4 1.5

Mincing machines Cold room Knives

b a

10 10 10 11 10 3

Temperature medians of cold rooms were lower than 4.4 C, with minimum values between 0.3 and 2.0 C (Table 4). The working areas of the PUs (machines, cutting tables and knives) had temperatures generally ranging from 10 to 14 C. Temperatures were sometimes high (18–20 C) or very low (2.1 and 4.0 C) in certain cases, regardless of the country. Recorded relative humidity (RH) median values usually varied between 65% and

France Greece Italy Portugal Spain Slovakia

3.1. Temperature and relative humidity in the environment

Tables

3. Results

n

A multiple analysis of variance (MANOVA) was used to analyse the main effect and interactions of two independent variables (country, sampling) on the dependent variables (microflora). The ‘‘main effect’’ was the direct effect of the independent variable on the dependent variable. The ‘‘interaction effect’’ was the joint effect of the two independent variables on the dependent variable. Multiple comparison tests of significance by a Newman–Keuls method to explore the relationships of independent values were used if the F-test showed that independent variables were related to the dependent variable. Statistical significance was set at the 5% level. MANOVA was calculated with the ANOVA routine by Statistica software (Statistica version 6.1, Statsoft inc., Maisons–Alfort, France).

Table 4 Temperature and relative humidity around the processing surfaces and equipment per country

2.6. Multiple analysis of variance and Newman–Keuls tests

573

Tc

2.5.1. Principal component analysis The distribution of the microflora in the environment among the 54 processing units of the six countries surveyed was analysed by a principal component analysis (PCA) with the PCA routine by Statistica software (Statistica version 6.1, Statsoft inc., Maisons–Alfort, France). The following microflora were considered: yeasts and moulds, lactic acid bacteria, Staphylococcus/Kocuria, Enterococcus, Enterobacteriaceae, Pseudomonas. Six surface samples were considered: mincing, mixing and stuffing machines, cutting tables, cold rooms and knives.

16.0 18.0 15.2 18.0 19.4 12.0

Mixing machines

2.5. Statistical analysis

6.9 7.0 8.0 9.0 9.2 12.0

Stuffing machines

pended in 30 ll of sterile distilled water and 2–5 ll were added to the PCR reaction mix. To detect the above-mentioned pathogens in the BPW cultures incubated for 24–48 h at 37 C, a pre-treatment based on the Chelex DNA extraction was applied. Before amplification, 1 ml of enriched culture was spined and the pellet was resuspended in 300 ll 6% Chelex-100 (BioRad, Marnes-la-Coquette, France). The suspension was vortexed for 10 s and incubated at 100 C for 8 min. The tube was vortexed for 10 s and chilled on ice for 2 min. Supernatant containing purified DNA was obtained after a centrifugation at 10,000g and 4 C for 5 min. An aliquot (5 ll) was used as template DNA in the PCR reactions.

12.2 11.0 12.3 11.6 14.0 12.0

Max

R. Talon et al. / Meat Science 77 (2007) 570–579

574

R. Talon et al. / Meat Science 77 (2007) 570–579

80.5%. Maximum values of more than 85% were recorded for some PUs in all of the countries. By contrast, minimum values lower than 60% RH were only observed in Spain and Portugal (Table 4). 3.2. Pathogenic microflora Salmonella was detected in 4.8% of the 314 surface and equipment samples analysed (Table 5). Fourteen positive samples out of fifteen were detected in Greek PUs; these samples were mainly taken from knifes, cold rooms, and mincing and mixing machines of different PUs. L. monocytogenes was enumerated in 2.2% of the samples in four countries (Table 5) at levels ranging from 1.2 to 3.5 log cfu/100 cm2 on three knives, from 1.8 to 4 .0 log cfu/100 cm2 on three cutting tables and at 2.7 log cfu/ 100 cm2 on a mincing machine. It was detected in 6.7% of the surfaces, frequently on knives (7 out of 21) and tables (5). Their presence in other contaminated samples came from four stuffing machines, two cold room walls, two mincing machines and one mixing machine. S. aureus was enumerated in 6.1% of the samples in five countries. The levels ranged from 1.7 to 2.2 log cfu/100 cm2 on three cold room walls, from 2.2 to 3.0 log cfu/100 cm2 on three tables, and from 2.0 to 3.1 log cfu/100 cm2 on three knives. Higher contaminations were recorded for the machines, with levels ranging from 2.5 to 3.8 log cfu/ 100 cm2 on three stuffing machines, from 2.2 to 3.8 log cfu/100 cm2 on five mixing machines, and from 2.1 to 4.0 log cfu/100 cm2 on five mincing machines. 3.3. Other microflora A wide range of residual contamination after cleaning and disinfection procedures was observed on the surfaces of the machines, cold room walls, tables and knives, rang-

Table 5 Occurrence of pathogenic bacteria on the surfaces and equipment of processing units Country

France Greece Italy Portugal Spain Slovakia Total % a

na

57 48 65 66 60 18 314

Salmonellab presence 0 14 0 1 0 0 15 4.8

S. aureusc enumeration 0 6 4 6 1 2 19 6.1

L. monocytogenes Enumerationd

Presencee

2 0 1 3 1 0

4 0 1 10 6 0

7 2.2

21 6.7

Total number of environmental samples studied. Number of Salmonella-positive samples on 40 cm2. c Number of positive samples, detection limit for S. aureus: 1.7 log cfu/ 100 cm2. d Number of positive samples in 500 cm2, detection limit for L. monocytogenes: 1.0 log cfu/100 cm2. e Number of L. monocytogenes-positive samples. b

ing from undetected to counts higher than 8 log cfu/ 100 cm2. The entire microbial data set was described by applying a principal component analysis (Fig. 1). Two principal components were chosen from the eigenvalue results (data not shown), and accounted for 79.7% of the total variation of the initial data set. Fig. 1(a) shows a high significance of principal component 1 that explained 62.1% of the total data variance. This axis was influenced by almost all of the microbial groups in only one direction (negative values). This means that when PUs were contaminated, they were contaminated by the entire microflora except yeasts and moulds. In fact, principal component 2 (17.6%) was influenced by yeasts and moulds. In Fig. 1(b), principal component 1 separated the PUs according to the level of residual contamination in the environment. Most Italian PUs were characterised by low contamination, regardless of the microbial groups and the surface samples (Fig. 1). When contaminated, the most highly contaminated surfaces were mainly the knives and the tables; on these surfaces, the maximum counts of Pseudomonas reached 5.0 log cfu/100 cm2, and the maximum counts of yeasts and moulds were 5.3 and 4.2 log cfu/ 100 cm2, respectively (Table 6). PUs in France, Portugal and Spain had a wide range of contamination levels – ranging from low to high. Heavily contaminated samples were also contaminated with yeasts and moulds (principal component 2, Fig. 1). Cold rooms and mixing machines were generally the least contaminated surfaces, while knives and tables were the most contaminated. Pseudomonas counts for the latter reached median values of around 4 log cfu/100 cm2. The highest Staphylococcus/Kocuria and LAB populations were observed on knives, ca. 7.0 log cfu/100 cm2 (Table 6). In Portugal, even though other microflora were found at low levels, yeasts and moulds and Pseudomonas were always recorded. Maximal yeast and mould populations reached 7.2 log cfu/100 cm2 on a table. High Pseudomonas populations of 7.2 log cfu/ 100 cm2 were enumerated on knives. Other microbial groups such as Enterococcus, Staphylococcus and Kocuria, LAB and Enterobacteriaceae had residual contamination levels ranging from undetectable levels to 5–6 log cfu/ 100 cm2. In Spain, the most highly contaminated surfaces were stuffing machines, mincing machines and cutting tables, with median values between 3.5 and 4.5 log cfu/ 100 cm2, 3.3 and 4.7 log cfu/100 cm2 and 1.9 and 4.7 log cfu/100 cm2, respectively. Greek PUs also revealed a wide range of microbial contamination. Surface samples were characterised by high contamination mainly associated with high Enterococcus and low yeast and mould levels (Fig. 1). In many samples, in fact, Enterococcus levels were higher than 7.0 log cfu/100 cm2 (Table 6). Slovak PUs had intermediate levels of contamination when compared to units in the Greek group and the France–Portugal–Spain group (Fig. 1, Table 6). The multifactorial analysis of variance shows that the country variable had a highly significant effect on all of

R. Talon et al. / Meat Science 77 (2007) 570–579

a

575

1 YM

Axis 2

PSE LAB 0 ENB STA PH

-1

1

0

ENC

-1 Axis 1

b

3

FRANCE PORTUGAL SPAIN

2

ITALY

1

SPAIN

Axis 2

FRANCE PORTUGAL

0

ITALY SLOVAKIA -1 GREECE

-2

SLOVAKIA

GREECE -3 -6

-5

-4

-3

-2

-1

0

1

2

3

Axis 1 Fig. 1. Principal component analysis (axis 1 – 62.1% and axis 2 – 17.6%) applied to the surface microbial data in the processing units of the six countries. (a) Scree plot, presentation of the variables: YM – yeasts and moulds; LAB – lactic acid bacteria; STAPH – Staphylococcus and Kocuria; ENC – Enterococcus; ENB – Enterobacteriaceae; PSE – Pseudomonas. (b) Presentation of the samples (54 processing units · 6 surface samples): h France; + Greece; n Italy; s Portugal; } Spain; * Slovakia; j mean and name of each country.

the microflora, whereas the sampling variable only had a significant effect on the Enterococcus, Enterobacteriaceae and Pseudomonas. The interaction between the country and sampling variables only had a significant effect on the Enterobacteriaceae and LAB (Table 7). Concerning the main effect of the country, Newman– Keuls tests confirmed that the Italian PUs presented the

lowest level of microbial contamination for five microbial groups out of six, with mean counts lower than 1.0 log cfu/100 cm2 (Table 8). On the contrary, the Greek PUs had the highest significant contamination for Staphylococcus and Kocuria, Enterococcus and Enterobacteriaceae (Table 8). The PUs from Slovakia can be distinguished on the basis of their low levels of yeasts and moulds and

Tables c

Knives Mina

Maxb

4.0 4.0 4.4 2.2 3.2 4.3

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

6.8 7.1 6.9 3.1 6.4 7.1

Median

Median

576

Table 6 Microflora levels (log cfu/100 cm2) measured on the processing surfaces and equipment per country Cold room

Mincing machines

Min

Max

Median

Min

Max

3.7 3.3 4.0 2.6 2.7 4.2

2.7 1.7 <1.7 <0.7 <0.7 2.7

6.7 5.6 5.3 5.0 6.0 7.3

1.1 <1.7 0.9 <0.7 <0.7 1.5

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

Mixing machines

Median

Min

Max

6.7 5.0 4.8 4.7 1.7 3.9

2.6 2.6 3.4 2.2 <0.7 2.2

1.5 <1.7 1.7 <0.7 <0.7 <0.7

Stuffing machines

Median

Min

Max

4.7 5.5 5.5 3.4 3.1 5.3

1.8 <1.7 2.3 <0.7 <0.7 1.5

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

5.4 5.8 5.3 4.0 2.1 3.5

Median

Min

Max

2.9 2.2 2.7 1.7 1.7 2.7

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

6.7 5.4 5.7 3.9 6.1 7.1

YM LABd STAPHe ENCf ENBg PSEh

Greece n = 10

YM LAB STAPH ENC ENB PSE

<0.7 3.2 5.5 7.1 4.5 4.0

<0.7 <1.7 <1.7 <0.7 2.4 <0.7

3.5 5.5 6.8 8.7 5.5 5.9

<0.7 1.9 6.4 6.2 4.9 4.6

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

4.8 6.2 8.7 9.4 7.8 6.5

<0.7 4.6 4.3 5.3 4.1 3.1

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

3.3 8.1 9.6 10.0 8.2 8.8

<0.7 4.9 5.8 4.1 3.7 5.1

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

4.0 7.3 7.0 7.8 7.2 7.7

<0.7 5.5 5.2 6.2 5.7 3.9

<0.7 4.7 3.9 3.9 4.2 1.7

3.4 6.7 6.9 7.2 6.4 6.9

<0.7 2.8 2.7 3.7 3.1 2.9

<0.7 <1.7 <1.7 <0.7 <0.7 2.2

3.0 5.3 7.0 8.8 5.9 3.7

Italy n = 10

YM LAB STAPH ENC ENB PSE

1.8 <1.7 <1.7 <0.7 <0.7 <0.7

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

4.2 4.2 3.9 2.5 2.9 5.0

1.7 <1.7 <1.7 <1.3 <1.3 <1.3

<1.3 <1.7 <1.7 <1.3 <1.3 <1.3

5.3 3.2 2.0 1.3 2.4 5.1

1.1 <1.7 <1.7 <0.7 <0.7 <0.7

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

3.0 2.3 2.6 <0.7 <0.7 1.9

1.5 <1.7 <1.7 <0.7 <0.7 <0.7

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

3.7 2.3 2.5 <0.7 2.3 4.7

1.6 <1.7 <1.7 <0.7 <0.7 <0.7

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

3.3 1.9 1.8 <0.7 <0.7 1.9

1.7 <1.7 <1.7 <0.7 <0.7 <0.7

0.9 <1.7 <1.7 <0.7 <0.7 <0.7

3.1 1.9 2.6 <0.7 <0.7 0.8

Portugal n = 11

YM LAB STAPH ENC ENB PSE

2.9 2.2 3.0 1.6 2.7 4.2

<0.7 <0.7 <0.7 <0.7 <0.7 <0.7

7.2 4.8 5.2 3.7 6.4 7.2

4.1 2.9 2.7 2.4 3.3 4.2

1.5 <0.7 <0.7 <0.7 <0.7 <0.7

5.5 4.7 5.9 5.2 4.3 7.6

2.4 <0.7 <0.7 <0.7 <0.7 0.9

<0.7 <0.7 <0.7 <0.7 <0.7 <0.7

5.1 3.5 3.4 1.6 3.3 7.1

2.3 1.8 2.8 0.7 2.3 3.1

0.7 <0.7 <0.7 <0.7 <0.7 <0.7

5.1 4.7 5.2 4.2 5.5 6.2

2.3 <0.7 2.8 <0.7 <0.7 3.1

<0.7 <0.7 <0.7 <0.7 <0.7 <0.7

4.6 5.0 4.5 3.0 3.6 6.8

2.3 <0.7 2.6 1.4 1.3 2.1

0.7 <0.7 <0.7 <0.7 <0.7 <0.7

3.2 5.0 3.8 2.8 4.3 6.2

Spain n = 10

YM LAB STAPH ENC ENB PSE

3.6 3.5 3.9 1.9 2.6 4.7

1.2 <1.7 <1.7 <0.7 <0.7 <0.7

7.1 8.3 5.7 4.8 5.7 8.0

3.2 2.8 3.3 0.9 1.6 3.5

1.8 <1.7 <2.0 <0.7 <0.7 <0.7

6.8 5.0 5.8 4.4 3.2 8.0

3.2 <1.7 3.4 <0.7 <0.7 2.8

<0.7 <1.7 <1.7 <0.7 <0.7 <0.7

4.8 3.3 8.2 2.4 2.2 4.0

3.7 3.7 4.7 3.3 3.4 4.2

2.7 2.5 3.2 1.3 <0.7 1.9

7.0 8.6 5.9 6.1 8.3 8.0

3.0 1.1 3.1 1.7 0.7 2.8

1.2 <1.7 0.7 <0.7 <0.7 <0.7

4.5 4.2 4.8 4.1 3.5 4.2

4.5 3.5 4.2 2.8 4.4 4.3

2.5 <1.7 <1.7 <0.7 <0.7 <0.7

8.1 8.4 7.0 6.1 7.9 8.9

Slovakia n = 3

YM LAB STAPH ENC ENB PSE

2.1 2.2 3.8 2.9 2.9 3.7

<0.7 <0.7 2.9 2.4 2.8 2.5

2.2 5.4 6.7 4.5 3.7 4.1

<0.7 3.3 3.5 2.8 2.9 <0.7

<0.7 2.6 2.4 <0.7 2.1 <0.7

2.8 3.6 4.3 4.1 3.4 1.1

2.8 4.5 4.7 2.4 1.3 <0.7

<0.7 3.7 3.8 <0.7 <0.7 <0.7

3.7 4.7 5.5 2.7 3.3 1.1

<0.7 4.3 4.6 2.4 3.0 2.7

<0.7 3.5 3.7 2.4 1.7 <0.7

4.2 4.7 4.7 4.5 3.4 4.5

2.7 2.7 4.0 0.7 2.3 <0.7

<0.7 <0.7 3.5 <0.7 2.1 <0.7

4.1 4.3 4.8 3.3 4.4 2.4

<0.7 4.4 4.1 2.4 2.2 <0.7

<0.7 2.5 3.5 <0.7 2.1 <0.7

0.4 4.6 6.6 4.1 2.4 <0.7

a b c d e f g h

Minimum. Maximum. Yeasts and moulds. Lactic acid bacteria. Staphylococcus and Kocuria. Enterococcus. Enterobacteriaceae. Pseudomonas.

R. Talon et al. / Meat Science 77 (2007) 570–579

France n = 10

R. Talon et al. / Meat Science 77 (2007) 570–579

577

Table 7 Multiple analysis of variance results to evaluate the effect of country and sampling variables on the microflora dfg

YMa

LABb

SSh

MSi

Fj

pk

SS

MS

F

p

SS

MS

F

p

1256.3 61.7 4.5 2.9 2.5

509.5 25.0 1.8 1.2

0.000 0.000 0.109 0.263

1320.8 347.2 23.0 172.6 1013.5

1320.8 69.4 4.6 6.9 3.6

363.6 19.1 1.3 1.9

0.000 0.000 0.279 0.007

2261.2 626.0 10.4 66.7 905.2

2261.2 125.2 2.1 2.7 3.2

696.9 38.6 0.6 0.8

0.000 0.000 0.669 0.712

Intercept Country Sampling Country * Sampling Error

1 5 5 25 279

1256.3 308.4 22.4 72.3 687.9

Total

314

1121.6

1585.2

d

MS

F

p

SS

MS

F

p

SS

MS

F

p

1029.0 129.5 7.6 3.0 2.9

359.3 45.2 2.6 1.0

0.000 0.000 0.024 0.418

1117.5 423.3 75.9 156.1 781.1

1117.5 84.7 15.2 6.2 2.8

399.1 30.2 5.4 2.2

0.000 0.000 0.000 0.001

1560.1 393.6 82.3 116.1 1159.3

1560.1 78.7 16.5 4.6 4.2

375.5 18.9 4.0 1.1

0.000 0.000 0.002 0.322

1 5 5 25 279

1029.0 647.6 37.9 74.3 799.0

Total

314

1612.0

c d e f g h i j k

PSEf

ENB

SS Intercept Country Sampling Country * Sampling Error

b

1642.7

e

ENC

a

STAPHc

1503.5

1774.9

Yeasts and moulds. Lactic acid bacteria. Staphylococcus and Kocuria. Enterococcus. Enterobacteriaceae. Pseudomonas. Degree of freedom. Sums of the squares. Mean squares. Fisher. Probability (no significant effect, p > 0.05; significant effect, 0.01 < p 6 0.05; very significant effect, 0.001 < p 6 0.01; highly significant effect, p 6 0.001).

Table 8 Newman–Keuls tests to evaluate the effect of country variables on the microflora Mean

YMa

Italy France Portugal Spain Slovakia Greece

1.7 3.0 2.8 3.7 1.5 0.7

ag b b d a c

Table 9 Newman–Keuls tests to evaluate the effect of sampling variables on the microflora

LABb

STAPHc

ENCd

ENBe

PSEf

Mean

YMa

0.3 2.4 1.5 2.7 3.4 3.5

0.3 2.9 2.3 3.6 4.3 4.6

0.1 1.6 1.2 2.1 2.3 5.0

0.3 1.6 1.8 2.2 2.6 4.3

0.7 2.7 3.0 3.6 1.2 3.6

Cold room Mixing machines Stuffing machines Mincing machines Knives Tables

1.8 2.0 2.4 2.4 2.8 2.8

b a c a a a

e ab a bc cd d

c ab b a a d

c a ab ab b d

b a a a b a

a

bg ab ab ab a a

LABb

STAPHc

ENCd

ENBe

PSEf

1.6 1.7 2.1 2.4 2.4 2.4

2.5 2.5 2.6 3.1 2.9 3.0

1.4 1.5 1.7 2.3 2.2 2.2

1.0 1.4 2.2 2.2 2.5 2.6

1.8 2.2 2.4 2.7 3.3 3.3

a a a a a a

a a a a a a

a a a a a a

b b a a a a

b b ab ab a a

a

Yeasts and moulds. Lactic acid bacteria. c Staphylococcus and Kocuria. d Enterococcus. e Enterobacteriaceae. f Pseudomonas. g Data expressed as the microflora mean level per country, in log cfu/ 100 cm2; per column, two similar letters indicate country belonging to the same group.

Yeasts and moulds. Lactic acid bacteria. c Staphylococcus and Kocuria. d Enterococcus. e Enterobacteriaceae. f Pseudomonas. g Data expressed as the microflora mean level per country, in log cfu/ 100 cm2; per column, two similar letters indicate environmental sample belonging to the same group.

Pseudomonas (Table 8). The lowest LAB counts were recorded in Italy and Portugal. No significant differences were observed for the other countries. Concerning the effect of sampling variables, cold rooms and mixing machines were the least contaminated samples, with mean counts ranging from 1.0 to 2.5 log cfu/100 cm2 (Table 9). On the contrary, stuffing and mincing machines, tables and knives were the most highly contaminated, with counts ranging from 1.7 to 3.3 log cfu/100 cm2. Pseudomo-

nas and Staphylococcus/Kocuria were the genus with the highest recorded levels.

b

b

4. Discussion This work surveyed the residual pathogenic, spoilage and technological microflora of 314 environmental samples from 54 European meat processing units and contributed to knowledge of the microbial ecosystems of food environ-

578

R. Talon et al. / Meat Science 77 (2007) 570–579

ments. The processing unit surfaces were contaminated and colonised by spoilage and technological microflora, but not by a specific bacterial genus. Only sporadic contamination by pathogenic microflora was recorded. The highest contamination was recorded on knives, cutting tables, and stuffing and mincing machines after cleaning and disinfection procedures. Chevallier et al. (2006) observed that contamination was high on the wooden table (block) and the stuffing machine of a French processing unit manufacturing traditional sausages. Legnani, Leoni, Berveglieri, Mirolo, and Alvaro (2004) showed that when the surfaces of catering establishments were contaminated (total count >104 cfu/cm2), 22.2% came from table surfaces, 7.8% from meat grinders and mincers and 6.7% from knives. Residual contamination could be caused by meat or fat residues not properly removed after cleaning, as well as from insufficient cleaning and disinfection procedures. Consequently, residues may act as vectors to transmit bacteria from surfaces to meat (Gill & McGinnis, 2004). Unclean, insufficiently or inadequately cleaned pieces of equipment have often been identified as the source of pathogens (Reij & Den Aantrekker, 2004). Indeed, many studies using molecular typing methods have investigated the pathogenic microflora of food processing environments and food processing lines, such as E. coli in a beef-packing plant (Aslam, Greer, Nattress, Gill, & McMullen, 2004), L. monocytogenes in pork and poultry processing plants and products (Chasseignaux et al., 2001) and Salmonella species in pork slaughter and cutting plants (Giovannacci et al., 2001). In the present study, pathogens such as S. aureus, L. monocytogenes or Salmonella were detected in a few environmental samples. After cleaning and disinfection procedures, 6.7% of the samples of the 54 processing units were L. monocytogenes-positive, with knives, tables and stuffing machines representing the most frequently contaminated surfaces (33%, 24% and 19%, respectively). As stated in the new EU regulation 2073/2005 (EC, 2005), food business operators should sample the processing area and equipment for L. monocytogenes as part of their sampling scheme. These results thus show that knives, tables and stuffing machines are the major critical points. Therefore, better cleaning and disinfection procedures should be applied. High variability in the contamination by L. monocytogenes was recorded on surfaces and equipment in different plants. For example, in a poultry meat plant and a pork plant, 18.3% and 16.4% of the samples were contaminated, respectively (Chasseignaux et al., 2001). In two other pork plants, no contamination remained on the equipment, and only 2.6% of the samples were contaminated in a third one (Chasseignaux et al., 2002). In the present study, Salmonella was present in 4.8% of 314 samples and was mainly found in one country out of the six investigated. Giovannacci et al. (2001) showed that in two pork slaughterhouse environments, Salmonella was isolated from cold room floors and walls but not from the

cutting rooms. The results of the present study showed that 6.1% of the surfaces were contaminated by S. aureus (>1.7 log cfu/100 cm2). This incidence is higher than that recorded in other studies involving catering establishments, where 0.7% of 140 samples were found to be unsatisfactory (>2.0 log cfu/100 cm2) (Legnani et al., 2004). Few data in the literature concerned residual spoilage microflora. Spoilage microflora (Pseudomonas and enterobacteria) was enumerated at various levels in the processing units studied, as was already mentioned by Chevallier et al. (2006). In the present study, 55.6% of the investigated surfaces recorded values <2 log cfu/100 cm2 for Enterobacteriaceae, which were considered acceptable according to the EU (EC, 2001, 2004). Cold rooms followed by mixing machines with 79.6% and 70.8%, respectively, recorded the highest percentage of the surfaces with acceptable levels. By contrast the percentages observed in tables (37.7%), knifes (38.9%), mincing (50.9%) and stuffing machines (57.1%) suggest that the disinfection of these surfaces should be improved. Although this Commission decision has been recently repealed (EU, 2006) the mentioned values for Enterobacteriaceae as an indicator should be useful for producers to ensure that the safety criteria stated in 2073/2005 (EC, 2005) are met. The results of the present study on technological microflora showed that surfaces and equipment had residual contamination for Staphylococcus and Kocuria and LAB. Their levels varied from undetectable to high counts, with a maximum exceeding 8.0 log cfu/100 cm2. LAB were generally less present on the surfaces than Staphylococcus and Kocuria. In the study of Chevallier et al. (2006), Gram-positive catalase-positive cocci were always detected on the surfaces at levels ranging from undetected to 6.7 log cfu/100 cm2, and LAB were rarely detected except on the block and the stuffing machine (4.6 log cfu/100 cm2 and 3.1 log cfu/100 cm2). Corbiere Morot-Bizot et al. (2006) also showed that all environmental samples were colonised by Gram-positive catalase-positive cocci, with counts ranging from 2.3 to 7.0 log cfu/100 cm2. 5. Conclusion The study targeted microbial ecosystems of food processing environments, which are not usually surveyed. The 54 processing units of traditional fermented sausages located in different Mediterranean countries and Slovakia showed a high variability of microbial levels in their environments, some of them with excessive levels of spoilage microflora. The different cleaning, disinfecting and manufacturing practices of the small-scale processing units could be responsible for this variability. However, it should be stressed that contamination by pathogens constituted sporadic cases. The study highlighted efficient cleaning and disinfection procedures for some processing units but insufficient ones for others. Several critical points were identi-

R. Talon et al. / Meat Science 77 (2007) 570–579

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