- Email: [email protected]
2005
Meat Science 88 (2011) 531–534
Contents lists available at ScienceDirect
Meat Science j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / m e a t s c i
Application of Classification and Regression Tree (CART) analysis on the microflora of minced meat for classification according to Reg. (EC) 2073/2005 P. Paulsen a,⁎, F.J.M. Smulders a, A. Tichy b, A. Aydin c, C. Höck a a b c
Institute of Meat Hygiene, Meat Technology and Food Science, Department for Farm Animals and Veterinary Public Health, Austria Platform Biostatistics Unit, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Vienna, Austria Department of Food Hygiene and Technology, Faculty of Veterinary Medicine, Istanbul University, Avcilar Campus, 34320 Avcilar, Istanbul, Turkey
a r t i c l e
i n f o
Article history: Received 21 October 2010 Received in revised form 15 January 2011 Accepted 4 February 2011 Keywords: Classification and Regression Tree analysis Minced meat Total aerobic count E. coli
a b s t r a c t In a retrospective study on the microbiology of minced meat from small food businesses supplying directly to the consumer, the relative contribution of meat supplier, meat species and outlet where meat was minced was assessed by “Classification and Regression Tree” (CART) analysis. Samples (n = 888) originated from 129 outlets of a single supermarket chain. Sampling units were 4–5 packs (pork, beef, and mixed pork–beef). Total aerobic counts (TACs) were 5.3 ± 1.0 log CFU/g. In 75.6% of samples, E. coli were b 1 log CFU/g. The proportion of “unsatisfactory” sample sets [as defined in Reg. (EC) 2073/2005] were 31.3 and 4.5% for TAC and E. coli, respectively. For classification according to TACs, the outlet where meat was minced and the “meat supplier” were the most important predictors. For E. coli, “outlet” was the most important predictor, but the limit of detection of 1 log CFU/g was not discriminative enough to allow further conclusions. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction European legislation requires food business operators to conduct microbiological own-checks. With respect to minced meat, detailed requirements are laid down in Reg (EC) 2073/2005 (EC, 2005). Per sampling day, five packing units have to be examined for food safety— (i.e. absence of Salmonella sp. in 10 or 25 g samples), and process hygiene criteria [i.e. numbers of total aerobic bacteria (TAC) and E. coli]. Results are evaluated by means of a three-class plan (two microbial limits “m”, “M”, see footnotes to Tables 1 and 2), also taking into account trend analysis. Unsatisfactory results in terms of food safety criteria require withdrawal of the product from the market or, under certain conditions, reprocessing. Unsatisfactory results in terms of process hygiene criteria require “improvements in production hygiene and improvements in selection and/or origin of raw materials” (EC, 2005). It is known that the extent of microbial contamination of minced meat reflects the conditions along the entire production chain from slaughter to the final product. Consequently, results from own-checks by minced meat producers reflect the cumulative hygienic performance of all links in this chain. Yet, it can be argued that — provided meat is procured from slaughterhouses with documented proof of their adherence to GHP, maintenance of their cold chain, and (in terms of EU legislation) a “satisfactory” or “acceptable” outcome of their ownchecks of carcasses, should allow the minced meat processor to produce a product fulfilling EU process hygiene criteria.
⁎ Corresponding author. Tel.: +43 1 25077 3318; fax: +43 1 25077 3390. E-mail address: [email protected] (P. Paulsen). 0309-1740/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.meatsci.2011.02.006
In Austria, for small food businesses supplying directly to the consumer (such as outlets of supermarket chains with their own butchering facilities, and processing either beef or pork or both into minced meat) the 5 samples shall be taken to represent the average amounts of minced meat from beef or pork or both. For minced meat to be consumed on the day of manufacture, the TAC criterion is not mandatory. For retail outlets, daily producing only small quantities of minced meat to be consumed at the day of manufacture, the requirement to analyse samples weekly or fortnightly is hardly affordable. Upon having introduced a simplified scheme relying on larger sampling time intervals, the question arose, whether the test results of large numbers of samples analysed over a one-year period would allow determination of the relative contribution of origin (slaughterhouse), species of meat and the mincing procedure in the outlet to the microbial contamination of the minced meat. To this end, an approach differing from commonly used mathematical procedures, such as ANOVA (e.g. Schmid et al., 2003) and discriminant analysis (e.g. Hinton et al., 1998) was used. 2. Material and methods 2.1. Samples A retrospective study was conducted on minced meat samples originating from a total of 129 outlets of one supermarket chain. The outlets received beef quarters, pork halves and (in case of organic beef) vacuum-packed primals. Before mincing, pork halves were skinned and further cut, while beef parts remained untrimmed. In all outlets, hygiene training and processing equipment were basically the
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P. Paulsen et al. / Meat Science 88 (2011) 531–534
Table 1 Compliance of individual packing units of minced meat with TAC and E. coli limits as stipulated in EU legislation. Type
Beef Organic beef Pork Beef + pork mix Total a b
n
210 47 103 528 888
TAC (%)a
E. coli (%)b
≤m
mb × ≤M
NM
≤m
mb × ≤M
NM
68.1 38.3 74.8 65.6 65.8
28.1 46.8 20.4 26.3 27.1
3.8 14.9 4.8 8.1 7.1
95.7 97.9 96.1 95.1 95.5
4.3 0.0 3.9 4.9 4.4
0.0 2.1 0.0 0.0 0.1
m = 500.000 and M = 5.000.000 CFU/g. m = 50 and M = 500 CFU/g.
same. Between the mincing of meat from different species, machinery was cleaned, but not disinfected. All packages sampled were labelled with a “use-by” date, being the day of production. With few exceptions, the outlets were situated in Vienna. At the beginning of the working day (7–10 h), a set of five (occasionally 4) individual (original) packages of minced meat was sampled by the hygiene inspector of the supermarket chain directly from the production line and then transported to the laboratory at max. +2 °C, where they arrived within 4 h of production. The sample sets included all meat types processed in the outlet (i.e. pork, beef, mixed pork–beef, and organic beef). The total number of sample sets was 180, representing 888 individual samples (Table 1) produced in the period March 2008–March 2009. Meat suppliers (total 16) per outlet were known, and each supplier had been audited for adherence to GHP and compliance with EU requirements on microbial numbers on freshly slaughtered carcasses. Upon arrival in the laboratory, meat temperature was recorded (Testo 230, Testo, Germany), and samples were analysed within 2 h (TAC and E. coli) with a semi-automated MPN procedure (Tempo®, Biomerieux, F). As a previous study (Paulsen, Schopf, and Smulders, 2006) had demonstrated that these MPN results do not differ significantly from those obtained by ISO standardized colony-count methods, it is justifiable to use limits laid down in Reg. (EC) 2073/ 2005 which refer to ISO standards based on colony-count methods. 2.2. Statistical analysis of data For descriptive statistics, TACs were converted into log units and mean and standard deviation calculated. For E. coli results, the fraction of samples bLOD (1 log CFU/g) was recorded. For both criteria, the distribution according to Reg. (EC) 2073/2005 (i.e. “m”, “M”) was calculated per individual sample as well as per sampling unit. To determine the impact of meat type (species), outlet shop, meat supplier and month of sampling on E. coli and TAC, a Classification and Regression Tree (CART) was used (SPSS v.17; SPSS Inc., Somers, NY, USA). Due to the large number of data, the tree was pruned to avoid overfitted results. Dataset was split into a 50% training set and a 50% test set to validate association rules (“split half validation”). Results of CART analysis as total accuracy and standard error of risk are shown for test-data only. In addition, the relative importance of predictors in the model was calculated. Table 2 Compliance of sample units (5 individual samples/day) of minced meat with TAC and E. coli limits as stipulated in EU legislation. Classification per sample set, n (%)
TAC E. coli a
Satisfactorya
Acceptableb
Unsatisfactoryc
94 (52.5%) 163 (91.0%)
29 (16.2%) 8 (4.5%)
56 (31.3%) 8 (4.5%)
All results bm (for TAC: m = 500.000; for E. coli: m = 50 CFU/g). Maximum two results N m but ≤M. c More than two results N m or one or more results NM (for TAC: M = 5.000.000; for E. coli: M = 500 CFU/g). b
Classification and Regression Tree (CART) analysis is a method to classify objects using selected variables and verify classification rules by comparing results to the observation (“supervised learning”; Han and Kamber, 2006). This method was deliberately preferred over discriminant analysis, because the latter method assumes variables to be metrically scaled and normally distributed — which was not the case for the present data. Also, ANOVA was considered less suitable as the study, rather than primarily aiming at comparing microbial numbers between different meat types or suppliers, was designed firstly to assess the relative importance of predictors (outlet, meat supplier/slaughterhouse and meat type) of bacterial counts and secondly to determine the performance of those predictors for the purpose of classifying the microbiological condition of minced meat.
3. Results and discussion 3.1. TAC in minced meat Average TACs were 5.3 ± 1.0 log CFU/g, with a range of 3.0–7.9. In 7.1% of samples, the “M” limit of 6.7 log (or 5,000,000) CFU/g (EC, 2005) was exceeded. While one may assume that the use of vacuumpacked organic beef for mincing has biased TACs due to Lactic Acid Bacteria developing in the vacuum package, most samples (43 out of 63) with TACs N“M” in fact originated from the “mixed minced meat” group (Table 1). With respect to meat type, average TACs were 5.1 ± 0.9; 5.2 ± 0.9; 5.3 ± 1.0 and 5.8 ± 1.0 log CFU/g for pork, beef, pork– beef-mix and organic beef, respectively. TACs in minced meat at retail have been reported to range from b3 log to N8 log CFU/g; with average or mean values mostly above 6 log CFU/g. In Germany, Kleeberger and Busse (1975) reported an average of 6.8 log CFU/g (n= 41) from samples taken in the city of Freiburg, and Schellhaas (1982) a median of N7 log CFU/g (n= 209). In a British study conducted in Bath, Nychas, Robinson, and Board (1991) found average TACs in the range of 6.8 to 9.0 log CFU/g (n= 120), depending on packaging type and season. In Finland, Skrökki (1997) reported median TACs of 6.1 for beef (n= 37) and 6.6 log CFU/g for mixed beef–pork (n= 38). Retail samples from Vienna, Austria were characterized by median TAC of 7.2 log CFU/g (Paulsen et al., 2006; n = 117). It is not easy to compare these data with those from samples taken directly at production, because the time–temperature history is usually not known or reported in detail, although during the first 48 h after production, at +2 to +6 °C, the multiplication of the microflora is considered to be negligible (Louwers, Fries, and Reuter, 2000). Differences between manufacturers have been identified for butchers (Kleeberger and Busse, 1975; Teufel, Götz, and Großklaus, 1982), as well as for large processing plants producing minced meat (Hinton et al., 1998; Paulsen, Dicakova, Mate, and Bauer, 2002), although these rarely exceed 1 log unit. Mincing in retail shops seems to be associated with N1 log higher bacterial numbers as compared with the centralized large-scale production of minced meat. For instance, Hildebrandt, Hildebrandt, and Kleer (2001) report average TACs of N6 as opposed to 4.7 log CFU/g, respectively. This is substantiated by numerous studies reporting average TACs of 3.6–5.2 log CFU/g for samples taken directly at large production plants (e.g. Schalch, Eisgruber, and Stolle, 1996; Louwers et al., 2000; Schmid et al., 2003). Day-to-day variations have also been described in small-, as well as in large-scale production (Kleeberger and Busse, 1975; Nychas et al., 1991), as have seasonal variations (Schmid et al., 2003). The origin of the meat/carcass and the meat primals used can have a significant influence on TACs of minced meat (Schmid et al., 2003), but also hygiene deficiencies during mincing can account for N1 log increases in microbial numbers (Teufel et al., 1982). Whereas Louwers et al. (2000) reported somewhat lower TACs for pork as compared with beef (4.9 vs. 5.2 log CFU/g), Skrökki (1997) found higher TACs in mixed beef–pork compared to beef. However, in the present data set,
P. Paulsen et al. / Meat Science 88 (2011) 531–534
differences were negligible, maybe because machinery was not disinfected between processing meat from different species (Table 1). Considering these literature data, an average TAC of 5.3 log CFU/g in the samples in the present study is in the lower expected range for samples taken at production. This could either indicate improvements in processing hygiene, or special care taken during the production of samples destined for microbiological own-checks. 3.2. E. coli numbers in minced meat In 671 of 888 samples (75.6%), numbers of E. coli were below the limit of detection of 10 CFU/g, and an “M” of 500 CFU/g was exceeded only in a single sample (Table 1). In earlier studies results are expressed in terms of Enterobacteriaceae and Coliforms, or MPN results on E. coli, which complicates comparison. Average or median E. coli numbers in the range of b1–1.3 log CFU/g (Schalch et al., 1996; Hinton et al., 1998; Paulsen et al., 2006) or 1–2 log CFU/g (MAFF, 1997; Hildebrandt et al., 2001) have been reported for minced meat sampled at large-scale production plants as well as at retail, and frequencies of “positive” results (i.e. ≥1 log CFU/g) range from 21 (Hildebrandt et al., 2001) to 72% (MAFF, 1997). In the present study, the high fraction of “negative” samples, although desirable from a food hygienist's view, raises the question if the usual limit of detection is discriminative enough.
Table 2 demonstrates that the frequencies of “unsatisfactory” sample sets were 31.3 and 4.5% for TAC and E. coli, respectively. Per individual sample (Table 1), the “M” value was exceeded in 7.1% of samples for TAC, which automatically classifies the entire sample set as “unsatisfactory”. This percentage is lower than one would expect under small-scale production conditions (19–47%; Hildebrandt et al., 2001), but similar to the ca. 4% reported for large-scale operations (Schalch et al., 1996; Hildebrandt et al., 2001). For E. coli, only 0.1% of samples exceeded the “M” limit. This is clearly lower than the ca. 1.4% reported by Schalch et al. (1996) and Hildebrandt et al. (2001). Again, this can indicate improvements in processing hygiene. This, in turn, would suggest the timeliness of having introduced current microbiological limits, or, finally, that special care had been given to samples destined for microbiological own-checks. 3.4. Significance of meat type, supplier and outlet for the microbiological condition of minced meat samples CART analysis initially included the month of manufacture. However, this allowed no classification, because only a small fraction of samples exceeded the “m” and “M” limits. Consequently, this predictor was omitted and the final model only included “outlet shop”, “meat supplier” and “meat type”. With these predictors, the total accuracy for TAC was 64.0% (SE = 0.022) (Table 3) with “outlet shop” and “meat supplier” as most important predictors of roughly equal importance (100 vs. 92.1%). The relative importance of “meat type” was markedly lower (26.4%). For E. coli, total accuracy was 95.5% (SE = 0.010) (Table 4) with “outlet shop” as the most important predictor in the model. The relative Table 3 Performance of a model (CART analysis) predicting TAC classes in minced meat based on information about meat type, meat supplier and the outlet where meat is minced.
≤m mb × ≤M NM Total percent
Table 4 Performance of a model (CART analysis) predicting E. coli classes in minced meat based on information about meat type, meat supplier and the outlet where meat is minced. Observed
≤m mb × ≤ M NM Total percent
Predicted ≤m
mb × ≤ M
NM
Percent correct
421 11 1 97.3%
7 4 1 2.7%
0 0 0 0.0%
98.4% 26.7% 0.0% 95.5%
importance of the other predictors is 40.7% for “meat supplier” and 2.3% for “meat type”. Generally, the imbalanced sample set with a large fraction of samples b“m” will force the model to predict “better” results, i.e. it is biased to lower bacterial numbers (see also Table 3). This problem is not unique to CART, but cannot be avoided by applying logistic regression analysis. Provided the data reflect the situation in smallscale minced meat production and assuming they are not biased by special care during the production of samples destined for microbiological own-checks, this is an indication that currently valid criteria may not be discriminative enough. In addition, for enumerating E. coli, LOD should be lower than the common 1 log CFU/g. 3.5. Overall significance of results
3.3. Compliance with EU limits
Observed
533
Predicted ≤m
mb × ≤ M
NM
Percent correct
277 107 20 87.1%
24 9 0 7.1%
10 6 11 5.8%
89.1% 7.4% 35.5% 64.0%
The microbiological condition of minced meat samples (n= 888) taken from 129 small-size supermarket outlets was somewhat better than literature data would suggest for small-scale production. There was, however, a large variation in TACs (3.0–7.9 log CFU/g), although all outlets of this single supermarket chain operated according to identical hygiene standards and meat was obtained from audited suppliers. The outlet shop where the meat had been minced and the origin of the meat had roughly the same importance for classification according to TACs than had meat species. Hence, in case of test results being classified as “unsatisfactory”, not only the hygiene procedures in the outlet, but also the microbiological condition of the meat supplied needs to be re-evaluated, irrespective of the results of own-checks or GHP audit records provided by the meat supplier. For E. coli, “outlet” was the most important predictor, but the limit of detection of 1 log CFU/g is obviously not discriminative enough to allow further conclusions. Acknowledgements The participation of Dr. A. Aydin in this study was supported by a FEMS grant. Thanks are due to Dr. Riedl and Dr. Kirchmayer (Veterinary Administration of the province of Vienna) for comments on the sampling scheme. References EC (European Commission) (2005). Commission Regulation (EC) No. 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Official Journal of the European Union, L 338, 1−26. Han, J., & Kamber, M. (2006). Data mining. Concepts and techniques (2nd ed.). New York: Elsevier. Hildebrandt, A., Hildebrandt, G., & Kleer, J. (2001). Microbiological status of minced pork. A comparison of industrial and handicraft produced minced meat. Fleischwirtschaft, 81(8), 86−90. Hinton, M., Coombs, E., Tucker, V., Jones, S., Allen, V., Hudson, W. R., et al. (1998). The bacteriological quality of British beef 2. Frozen minced beef. Meat Science, 50, 395−402. Kleeberger, A., & Busse, M. (1975). Keimzahl und Florazusammensetzung bei Hackfleisch unter besonderer Berücksichtigung von Enterobakterien und Pseudomonaden. Zeitschrift für Lebensmitteluntersuchung und -forschung A, 158, 321−331. Louwers, J., Fries, R., & Reuter, G. (2000). Einfluß externer Faktoren auf die Ergebnisse mikrobiologischer Routineuntersuchungen von Hackfleisch. Proceedings 41. AT des Arbeitsgebietes Lebensmittelhygiene der DVG, Gießen (pp. 653−658). MAFF (1997). Microbiological survey of minced meat (1997). Accessed at: www.food. gov.uk/multimedia/pdfs/mincedmeat.pdf.
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Nychas, G. J., Robinson, A., & Board, R. G. (1991). Microbiological and physico-chemical evaluation of ground beef from retail shops. Fleischwirtschaft, 71, 1057−1059. Paulsen, P., Dicakova, Z., Mate, D., & Bauer, F. (2002). Beziehungen zwischen der routinemäßig bestimmten Mikroflora und dem Gehalt an biogenen Aminen von Faschiertem und Rohwürsten - Kurzmitteilung. Ernährung/Nutrition, 26, 156−159. Paulsen, P., Schopf, E., & Smulders, F. J. M. (2006). Enumeration of total aerobic bacteria and E. coli in minced meat and on carcass surface samples with an automated mostprobable-number method compared to colony count protocols. Journal of Food Protection, 69, 2500−2503. Schalch, B., Eisgruber, H., & Stolle, A. (1996). Praktische Erfahrungen mit den mikrobiologischen Anforderungen der EU-Hackfleischrichtlinie. Fleischwirtschaft, 76(9), 883−886.
Schellhaas, G. (1982). Zur mikrobiologischen Beschaffenheit von Hackfleisch und anderen Erzeugnissen aus frischem Fleisch. Fleischwirtschaft, 62, 582−587. Schmid, J., Schalch, B., Eichinger, K., Spannagel, U., Palitzsch, A., & Wolfram, G. (2003). Varianzanalytische Untersuchungen zur mikrobiologischen Beschaffenheit von gewolftem Rinderhackfleisch. Archiv für Lebensmittelhygiene, 54, 128−132. Skrökki, A. (1997). Hygienic quality of commercial minced meat as indicated by aerobic micro-organisms and coliform bacteria. Zeitschrift für Lebensmitteluntersuchung und -forschung A, 204, 391−394. Teufel, P., Götz, G., & Großklaus, D. (1982). Einfluß von Betriebshygiene und Ausgangsmaterial auf den mikrobiologischen Status von Hackfleisch. Fleischwirtschaft, 62, 1404−1408.
Contents lists available at ScienceDirect
Meat Science j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / m e a t s c i
Application of Classification and Regression Tree (CART) analysis on the microflora of minced meat for classification according to Reg. (EC) 2073/2005 P. Paulsen a,⁎, F.J.M. Smulders a, A. Tichy b, A. Aydin c, C. Höck a a b c
Institute of Meat Hygiene, Meat Technology and Food Science, Department for Farm Animals and Veterinary Public Health, Austria Platform Biostatistics Unit, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Vienna, Austria Department of Food Hygiene and Technology, Faculty of Veterinary Medicine, Istanbul University, Avcilar Campus, 34320 Avcilar, Istanbul, Turkey
a r t i c l e
i n f o
Article history: Received 21 October 2010 Received in revised form 15 January 2011 Accepted 4 February 2011 Keywords: Classification and Regression Tree analysis Minced meat Total aerobic count E. coli
a b s t r a c t In a retrospective study on the microbiology of minced meat from small food businesses supplying directly to the consumer, the relative contribution of meat supplier, meat species and outlet where meat was minced was assessed by “Classification and Regression Tree” (CART) analysis. Samples (n = 888) originated from 129 outlets of a single supermarket chain. Sampling units were 4–5 packs (pork, beef, and mixed pork–beef). Total aerobic counts (TACs) were 5.3 ± 1.0 log CFU/g. In 75.6% of samples, E. coli were b 1 log CFU/g. The proportion of “unsatisfactory” sample sets [as defined in Reg. (EC) 2073/2005] were 31.3 and 4.5% for TAC and E. coli, respectively. For classification according to TACs, the outlet where meat was minced and the “meat supplier” were the most important predictors. For E. coli, “outlet” was the most important predictor, but the limit of detection of 1 log CFU/g was not discriminative enough to allow further conclusions. © 2011 Elsevier Ltd. All rights reserved.
1. Introduction European legislation requires food business operators to conduct microbiological own-checks. With respect to minced meat, detailed requirements are laid down in Reg (EC) 2073/2005 (EC, 2005). Per sampling day, five packing units have to be examined for food safety— (i.e. absence of Salmonella sp. in 10 or 25 g samples), and process hygiene criteria [i.e. numbers of total aerobic bacteria (TAC) and E. coli]. Results are evaluated by means of a three-class plan (two microbial limits “m”, “M”, see footnotes to Tables 1 and 2), also taking into account trend analysis. Unsatisfactory results in terms of food safety criteria require withdrawal of the product from the market or, under certain conditions, reprocessing. Unsatisfactory results in terms of process hygiene criteria require “improvements in production hygiene and improvements in selection and/or origin of raw materials” (EC, 2005). It is known that the extent of microbial contamination of minced meat reflects the conditions along the entire production chain from slaughter to the final product. Consequently, results from own-checks by minced meat producers reflect the cumulative hygienic performance of all links in this chain. Yet, it can be argued that — provided meat is procured from slaughterhouses with documented proof of their adherence to GHP, maintenance of their cold chain, and (in terms of EU legislation) a “satisfactory” or “acceptable” outcome of their ownchecks of carcasses, should allow the minced meat processor to produce a product fulfilling EU process hygiene criteria.
⁎ Corresponding author. Tel.: +43 1 25077 3318; fax: +43 1 25077 3390. E-mail address: [email protected] (P. Paulsen). 0309-1740/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.meatsci.2011.02.006
In Austria, for small food businesses supplying directly to the consumer (such as outlets of supermarket chains with their own butchering facilities, and processing either beef or pork or both into minced meat) the 5 samples shall be taken to represent the average amounts of minced meat from beef or pork or both. For minced meat to be consumed on the day of manufacture, the TAC criterion is not mandatory. For retail outlets, daily producing only small quantities of minced meat to be consumed at the day of manufacture, the requirement to analyse samples weekly or fortnightly is hardly affordable. Upon having introduced a simplified scheme relying on larger sampling time intervals, the question arose, whether the test results of large numbers of samples analysed over a one-year period would allow determination of the relative contribution of origin (slaughterhouse), species of meat and the mincing procedure in the outlet to the microbial contamination of the minced meat. To this end, an approach differing from commonly used mathematical procedures, such as ANOVA (e.g. Schmid et al., 2003) and discriminant analysis (e.g. Hinton et al., 1998) was used. 2. Material and methods 2.1. Samples A retrospective study was conducted on minced meat samples originating from a total of 129 outlets of one supermarket chain. The outlets received beef quarters, pork halves and (in case of organic beef) vacuum-packed primals. Before mincing, pork halves were skinned and further cut, while beef parts remained untrimmed. In all outlets, hygiene training and processing equipment were basically the
532
P. Paulsen et al. / Meat Science 88 (2011) 531–534
Table 1 Compliance of individual packing units of minced meat with TAC and E. coli limits as stipulated in EU legislation. Type
Beef Organic beef Pork Beef + pork mix Total a b
n
210 47 103 528 888
TAC (%)a
E. coli (%)b
≤m
mb × ≤M
NM
≤m
mb × ≤M
NM
68.1 38.3 74.8 65.6 65.8
28.1 46.8 20.4 26.3 27.1
3.8 14.9 4.8 8.1 7.1
95.7 97.9 96.1 95.1 95.5
4.3 0.0 3.9 4.9 4.4
0.0 2.1 0.0 0.0 0.1
m = 500.000 and M = 5.000.000 CFU/g. m = 50 and M = 500 CFU/g.
same. Between the mincing of meat from different species, machinery was cleaned, but not disinfected. All packages sampled were labelled with a “use-by” date, being the day of production. With few exceptions, the outlets were situated in Vienna. At the beginning of the working day (7–10 h), a set of five (occasionally 4) individual (original) packages of minced meat was sampled by the hygiene inspector of the supermarket chain directly from the production line and then transported to the laboratory at max. +2 °C, where they arrived within 4 h of production. The sample sets included all meat types processed in the outlet (i.e. pork, beef, mixed pork–beef, and organic beef). The total number of sample sets was 180, representing 888 individual samples (Table 1) produced in the period March 2008–March 2009. Meat suppliers (total 16) per outlet were known, and each supplier had been audited for adherence to GHP and compliance with EU requirements on microbial numbers on freshly slaughtered carcasses. Upon arrival in the laboratory, meat temperature was recorded (Testo 230, Testo, Germany), and samples were analysed within 2 h (TAC and E. coli) with a semi-automated MPN procedure (Tempo®, Biomerieux, F). As a previous study (Paulsen, Schopf, and Smulders, 2006) had demonstrated that these MPN results do not differ significantly from those obtained by ISO standardized colony-count methods, it is justifiable to use limits laid down in Reg. (EC) 2073/ 2005 which refer to ISO standards based on colony-count methods. 2.2. Statistical analysis of data For descriptive statistics, TACs were converted into log units and mean and standard deviation calculated. For E. coli results, the fraction of samples bLOD (1 log CFU/g) was recorded. For both criteria, the distribution according to Reg. (EC) 2073/2005 (i.e. “m”, “M”) was calculated per individual sample as well as per sampling unit. To determine the impact of meat type (species), outlet shop, meat supplier and month of sampling on E. coli and TAC, a Classification and Regression Tree (CART) was used (SPSS v.17; SPSS Inc., Somers, NY, USA). Due to the large number of data, the tree was pruned to avoid overfitted results. Dataset was split into a 50% training set and a 50% test set to validate association rules (“split half validation”). Results of CART analysis as total accuracy and standard error of risk are shown for test-data only. In addition, the relative importance of predictors in the model was calculated. Table 2 Compliance of sample units (5 individual samples/day) of minced meat with TAC and E. coli limits as stipulated in EU legislation. Classification per sample set, n (%)
TAC E. coli a
Satisfactorya
Acceptableb
Unsatisfactoryc
94 (52.5%) 163 (91.0%)
29 (16.2%) 8 (4.5%)
56 (31.3%) 8 (4.5%)
All results bm (for TAC: m = 500.000; for E. coli: m = 50 CFU/g). Maximum two results N m but ≤M. c More than two results N m or one or more results NM (for TAC: M = 5.000.000; for E. coli: M = 500 CFU/g). b
Classification and Regression Tree (CART) analysis is a method to classify objects using selected variables and verify classification rules by comparing results to the observation (“supervised learning”; Han and Kamber, 2006). This method was deliberately preferred over discriminant analysis, because the latter method assumes variables to be metrically scaled and normally distributed — which was not the case for the present data. Also, ANOVA was considered less suitable as the study, rather than primarily aiming at comparing microbial numbers between different meat types or suppliers, was designed firstly to assess the relative importance of predictors (outlet, meat supplier/slaughterhouse and meat type) of bacterial counts and secondly to determine the performance of those predictors for the purpose of classifying the microbiological condition of minced meat.
3. Results and discussion 3.1. TAC in minced meat Average TACs were 5.3 ± 1.0 log CFU/g, with a range of 3.0–7.9. In 7.1% of samples, the “M” limit of 6.7 log (or 5,000,000) CFU/g (EC, 2005) was exceeded. While one may assume that the use of vacuumpacked organic beef for mincing has biased TACs due to Lactic Acid Bacteria developing in the vacuum package, most samples (43 out of 63) with TACs N“M” in fact originated from the “mixed minced meat” group (Table 1). With respect to meat type, average TACs were 5.1 ± 0.9; 5.2 ± 0.9; 5.3 ± 1.0 and 5.8 ± 1.0 log CFU/g for pork, beef, pork– beef-mix and organic beef, respectively. TACs in minced meat at retail have been reported to range from b3 log to N8 log CFU/g; with average or mean values mostly above 6 log CFU/g. In Germany, Kleeberger and Busse (1975) reported an average of 6.8 log CFU/g (n= 41) from samples taken in the city of Freiburg, and Schellhaas (1982) a median of N7 log CFU/g (n= 209). In a British study conducted in Bath, Nychas, Robinson, and Board (1991) found average TACs in the range of 6.8 to 9.0 log CFU/g (n= 120), depending on packaging type and season. In Finland, Skrökki (1997) reported median TACs of 6.1 for beef (n= 37) and 6.6 log CFU/g for mixed beef–pork (n= 38). Retail samples from Vienna, Austria were characterized by median TAC of 7.2 log CFU/g (Paulsen et al., 2006; n = 117). It is not easy to compare these data with those from samples taken directly at production, because the time–temperature history is usually not known or reported in detail, although during the first 48 h after production, at +2 to +6 °C, the multiplication of the microflora is considered to be negligible (Louwers, Fries, and Reuter, 2000). Differences between manufacturers have been identified for butchers (Kleeberger and Busse, 1975; Teufel, Götz, and Großklaus, 1982), as well as for large processing plants producing minced meat (Hinton et al., 1998; Paulsen, Dicakova, Mate, and Bauer, 2002), although these rarely exceed 1 log unit. Mincing in retail shops seems to be associated with N1 log higher bacterial numbers as compared with the centralized large-scale production of minced meat. For instance, Hildebrandt, Hildebrandt, and Kleer (2001) report average TACs of N6 as opposed to 4.7 log CFU/g, respectively. This is substantiated by numerous studies reporting average TACs of 3.6–5.2 log CFU/g for samples taken directly at large production plants (e.g. Schalch, Eisgruber, and Stolle, 1996; Louwers et al., 2000; Schmid et al., 2003). Day-to-day variations have also been described in small-, as well as in large-scale production (Kleeberger and Busse, 1975; Nychas et al., 1991), as have seasonal variations (Schmid et al., 2003). The origin of the meat/carcass and the meat primals used can have a significant influence on TACs of minced meat (Schmid et al., 2003), but also hygiene deficiencies during mincing can account for N1 log increases in microbial numbers (Teufel et al., 1982). Whereas Louwers et al. (2000) reported somewhat lower TACs for pork as compared with beef (4.9 vs. 5.2 log CFU/g), Skrökki (1997) found higher TACs in mixed beef–pork compared to beef. However, in the present data set,
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differences were negligible, maybe because machinery was not disinfected between processing meat from different species (Table 1). Considering these literature data, an average TAC of 5.3 log CFU/g in the samples in the present study is in the lower expected range for samples taken at production. This could either indicate improvements in processing hygiene, or special care taken during the production of samples destined for microbiological own-checks. 3.2. E. coli numbers in minced meat In 671 of 888 samples (75.6%), numbers of E. coli were below the limit of detection of 10 CFU/g, and an “M” of 500 CFU/g was exceeded only in a single sample (Table 1). In earlier studies results are expressed in terms of Enterobacteriaceae and Coliforms, or MPN results on E. coli, which complicates comparison. Average or median E. coli numbers in the range of b1–1.3 log CFU/g (Schalch et al., 1996; Hinton et al., 1998; Paulsen et al., 2006) or 1–2 log CFU/g (MAFF, 1997; Hildebrandt et al., 2001) have been reported for minced meat sampled at large-scale production plants as well as at retail, and frequencies of “positive” results (i.e. ≥1 log CFU/g) range from 21 (Hildebrandt et al., 2001) to 72% (MAFF, 1997). In the present study, the high fraction of “negative” samples, although desirable from a food hygienist's view, raises the question if the usual limit of detection is discriminative enough.
Table 2 demonstrates that the frequencies of “unsatisfactory” sample sets were 31.3 and 4.5% for TAC and E. coli, respectively. Per individual sample (Table 1), the “M” value was exceeded in 7.1% of samples for TAC, which automatically classifies the entire sample set as “unsatisfactory”. This percentage is lower than one would expect under small-scale production conditions (19–47%; Hildebrandt et al., 2001), but similar to the ca. 4% reported for large-scale operations (Schalch et al., 1996; Hildebrandt et al., 2001). For E. coli, only 0.1% of samples exceeded the “M” limit. This is clearly lower than the ca. 1.4% reported by Schalch et al. (1996) and Hildebrandt et al. (2001). Again, this can indicate improvements in processing hygiene. This, in turn, would suggest the timeliness of having introduced current microbiological limits, or, finally, that special care had been given to samples destined for microbiological own-checks. 3.4. Significance of meat type, supplier and outlet for the microbiological condition of minced meat samples CART analysis initially included the month of manufacture. However, this allowed no classification, because only a small fraction of samples exceeded the “m” and “M” limits. Consequently, this predictor was omitted and the final model only included “outlet shop”, “meat supplier” and “meat type”. With these predictors, the total accuracy for TAC was 64.0% (SE = 0.022) (Table 3) with “outlet shop” and “meat supplier” as most important predictors of roughly equal importance (100 vs. 92.1%). The relative importance of “meat type” was markedly lower (26.4%). For E. coli, total accuracy was 95.5% (SE = 0.010) (Table 4) with “outlet shop” as the most important predictor in the model. The relative Table 3 Performance of a model (CART analysis) predicting TAC classes in minced meat based on information about meat type, meat supplier and the outlet where meat is minced.
≤m mb × ≤M NM Total percent
Table 4 Performance of a model (CART analysis) predicting E. coli classes in minced meat based on information about meat type, meat supplier and the outlet where meat is minced. Observed
≤m mb × ≤ M NM Total percent
Predicted ≤m
mb × ≤ M
NM
Percent correct
421 11 1 97.3%
7 4 1 2.7%
0 0 0 0.0%
98.4% 26.7% 0.0% 95.5%
importance of the other predictors is 40.7% for “meat supplier” and 2.3% for “meat type”. Generally, the imbalanced sample set with a large fraction of samples b“m” will force the model to predict “better” results, i.e. it is biased to lower bacterial numbers (see also Table 3). This problem is not unique to CART, but cannot be avoided by applying logistic regression analysis. Provided the data reflect the situation in smallscale minced meat production and assuming they are not biased by special care during the production of samples destined for microbiological own-checks, this is an indication that currently valid criteria may not be discriminative enough. In addition, for enumerating E. coli, LOD should be lower than the common 1 log CFU/g. 3.5. Overall significance of results
3.3. Compliance with EU limits
Observed
533
Predicted ≤m
mb × ≤ M
NM
Percent correct
277 107 20 87.1%
24 9 0 7.1%
10 6 11 5.8%
89.1% 7.4% 35.5% 64.0%
The microbiological condition of minced meat samples (n= 888) taken from 129 small-size supermarket outlets was somewhat better than literature data would suggest for small-scale production. There was, however, a large variation in TACs (3.0–7.9 log CFU/g), although all outlets of this single supermarket chain operated according to identical hygiene standards and meat was obtained from audited suppliers. The outlet shop where the meat had been minced and the origin of the meat had roughly the same importance for classification according to TACs than had meat species. Hence, in case of test results being classified as “unsatisfactory”, not only the hygiene procedures in the outlet, but also the microbiological condition of the meat supplied needs to be re-evaluated, irrespective of the results of own-checks or GHP audit records provided by the meat supplier. For E. coli, “outlet” was the most important predictor, but the limit of detection of 1 log CFU/g is obviously not discriminative enough to allow further conclusions. Acknowledgements The participation of Dr. A. Aydin in this study was supported by a FEMS grant. Thanks are due to Dr. Riedl and Dr. Kirchmayer (Veterinary Administration of the province of Vienna) for comments on the sampling scheme. References EC (European Commission) (2005). Commission Regulation (EC) No. 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Official Journal of the European Union, L 338, 1−26. Han, J., & Kamber, M. (2006). Data mining. Concepts and techniques (2nd ed.). New York: Elsevier. Hildebrandt, A., Hildebrandt, G., & Kleer, J. (2001). Microbiological status of minced pork. A comparison of industrial and handicraft produced minced meat. Fleischwirtschaft, 81(8), 86−90. Hinton, M., Coombs, E., Tucker, V., Jones, S., Allen, V., Hudson, W. R., et al. (1998). The bacteriological quality of British beef 2. Frozen minced beef. Meat Science, 50, 395−402. Kleeberger, A., & Busse, M. (1975). Keimzahl und Florazusammensetzung bei Hackfleisch unter besonderer Berücksichtigung von Enterobakterien und Pseudomonaden. Zeitschrift für Lebensmitteluntersuchung und -forschung A, 158, 321−331. Louwers, J., Fries, R., & Reuter, G. (2000). Einfluß externer Faktoren auf die Ergebnisse mikrobiologischer Routineuntersuchungen von Hackfleisch. Proceedings 41. AT des Arbeitsgebietes Lebensmittelhygiene der DVG, Gießen (pp. 653−658). MAFF (1997). Microbiological survey of minced meat (1997). Accessed at: www.food. gov.uk/multimedia/pdfs/mincedmeat.pdf.
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