ARTICLE

Monitoring of Microbial Contaminants of Beef, Pork, and Chicken in HACCP Implemented Meat Processing Plants of Korea

Jung Hyun Kim1, Sun Jin Hur2, Dong Gyun Yim3,*
Author Information & Copyright
1Department of Clinical Pathology, Kyung Bok University, Pocheon 11138, Korea
2Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea
3Department of Animal Science, Sangji University, Wonju 26339, Korea
*Corresponding Author : Department of Animal Science, Sangji University, Wonju 26339, Korea Tel: +82-33-730-0537 Fax: +82-33-730-0537 E-mail: tousa0994@naver.com

© Copyright 2018 Korean Society for Food Science of Animal Resources. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Jul 26, 2018 ; Revised: Jan 19, 2018 ; Accepted: Feb 19, 2018

Published Online: Apr 30, 2018

Abstract

This research was to evaluate microbial contamination levels in meat samples at hazard analysis critical control point (HACCP)-implemented processing plants that produce beef, pork, and chicken. During a period of about a year, a total of 178 samples (76 from beef, 89 from pork, and 13 from chicken) were obtained from raw materials (21.3%) and final products (78.7%). All samples were determined for each 25 g homogenized one. Samples were analyzed to determine the total aerobic plate count (APC), coliform count (CC), and E. coli count (ECC). By month, APC levels were the highest in September and the lowest in February (p<0.001). In comparison among season, APC levels in meat samples were the highest in the summer and the lowest in winter (p<0.001). By month, the highest CC prevalence was found in August, followed by October and then July (p<0.001). By season, the highest CC was obtained in summer, followed by autumn and then spring (p<0.001). All samples were negative for ECC. There was a direct correlation between the product form and coliform presence (p<0.001). In addition, there was a positive correlation between the APC and CC (r=0.261). The APCs in analyzed samples ranged from below <101 CFU/g to <107 CFU/g. In conclusion, the month and season had significant effects on microbial contamination levels at HACCP implemented processing plants. Interrelationships between (i) the product form and coliform, (ii) the APC and CC were revealed.

Keywords: beef; pork; chicken; meat processing plants; microbial contamination

Introduction

In Korea, the consumption and sales of meat products are increasing. Specifically, sales of meat products increased by 136.9% in 2000 compared to 1990 (45,644 [M/T]), by 43.26% in 2010 compared to 2000 (154,914 [M/T]), and by 4.25% in 2011 compared to 2010 (161,495 [M/T]) (Korea meat industries association, KMIA, 2015). These statistics show that consumers’ demand for meat products continues to increase. In recent years, there has been growing concern about meat products carrying pathogenic microorganisms, despite enhanced efforts in meat and processed meat hygiene (Bae et al., 2011). Contamination can occur during processing, by contact with facility equipment (e.g., grinders, belts, saws), by contact with food handlers (e.g., hand contact, knives), and exposure to other environmental sources (e.g., air, water) (Kim and Yim, 2016). Regulatory agencies require meat-packing plants to implement hazard analysis critical control point (HACCP) systems for meat production processes to reduce the numbers of pathogenic organisms (USDA, 2016). However, since the complete elimination of pathogens from raw meat is difficult or impossible, the goal of HACCP for meats focuses on reducing and preventing microbial growth (Kim and Yim, 2016). Presently, the HACCP system is used in many regulated food industries. In Korea, regulatory authorities introduced HACCP systems in meat processing plants in 1997, slaughter houses in 2000, livestock product plants in 2001, milk processing plants and meat sales and distribution points in 2004 (Kim and Yim, 2016). Monitoring of microorganisms in meat products is an important step in HACCP programs (Kim and Yim, 2017), and the proper storage of meat products is crucial to controlling contamination of meat by spoilage organisms (Kim and Yim, 2017). It has been suggested that HACCP systems at meat processing plants should be based on microbiological data, with estimates of the numbers of indicator organisms on meat products at various stages of processing (Gill et al., 2000). For raw meat products, safety and quality can be estimated by the use of indicator microorganisms, including total aerobic plate count (APC), coliform count (CC), and Escherichia coli count (ECC) (Kim and Yim, 2016). APC provides an estimate of overall bacterial populations. A higher APC usually relates to poorer quality and a reduced shelf life. The relationship between APC and the concentration of foodborne pathogens in raw meats is unclear. CC and ECC provide an estimate of fecal contamination and poor sanitation during processing. High CC and ECC generally correlate with higher levels of foodborne pathogens originating from feces (Kim and Yim, 2016). Meat can be further contaminated or cross-contaminated by various pathogenic bacteria after the slaughter process, such as during chilling, cutting, deboning, and slicing processes (Duffy et al., 2001). Thus, all processing conditions are important factors that can affect microbiological quality. To improve the safety of final meat products, more information is needed at the point where carcasses or meat cuts are contaminated in meat processing plants (Choi et al., 2013). However, data on seasonal variation and meat type in microbiological examinations of meat in different meat processing plants are limited. In particular, a microbiological assessment of meat in HACCP-implementing meat processing plants has not been conducted. Thus, the objective of this study was to investigate the microbial contamination of meat, and determine its association with month, season, sample type (raw or final products), meat type (beef, pork, or chicken), and prevalence in order to evaluate the microbiological hygienic level of HACCP-implementing meat processing plants in Korea. In addition, potential relationship between coliforms and season, meat type, and product form were studied by elucidating the relevant hygiene aspects.

Materials and Methods

Sample collection

A total of 178 meat samples (76 from beef, 89 from pork, and 13 from chicken) were collected from five randomly selected meat processing plants located in three administrative regions in Korea (Gyonggi, Gyeongsang, and Chungchong) over a one-year period during four different seasons. The samples from meat processing plants were taken at 10 medium sized abattoirs. The selection of the plants was made based on their capacities to process large amounts of meat (approximately 30 tons of meat per day), their variety of processing lines (beef, pork, and poultry), and their work with both raw materials and final products. Raw materials were collected at the beginning of the production line, while final meat products were obtained from freshly packed commercial meat. Collection was dependent on the cooperation of the owners. Experienced technicians or quality control staff at the plants carried out the microbiological sampling. The HACCP quality control system, including sanitation procedures, was adopted in all meat processing plants included in the study. After meat cutting and boning in the processing line, about 100 g of sample was taken from different portions (rump, midline, and brisket) in beef and pork of the whole meats and placed on pre-labeled styrofoam trays. The whole carcass was used for chicken samples. All samples were collected aseptically with the use of a sterile knife and placed in a sterile collection bag. In the poultry processing plants, the whole chicken carcass was used for samples. Trays were vacuum-packaged with multilayer polyolefin and polyvinylidene chloride film. After refrigeration (4-5°C), samples were transported to the laboratory where about 100 g of sample was taken from each carcass and analyzed within 24 hours. All samples were trimmed using a stainless steel knife that was sterilized with alcohol and flaming.

Microbiological analysis

Samples were analyzed to determine the total APC, CC, and ECC, which serve as hygiene indicators. For APC, 25 g samples were transferred aseptically into a sterile stomacher bag (STOMACHER® 400 CIRCULATOR, Seward, Ltd., UK) containing 225 mL of 0.85% sterile saline solution (NaCl, Difco Laboratories, USA) and homogenized for 2 min at room temperature to achieve a 1/10 dilution. Homogenized microbial extracts were serially diluted in sterile distilled water. Each diluted 1 mL sample was plated individually and spread thoroughly. The APC was determined using plate count agar (Difco Laboratories, USA) incubated at 37±1°C for 48 h. The diluted 1 mL samples were also plated on 3M Petrifilm (3M, USA) to count coliforms and E. coli. The petrifilm was also incubated at 37±1°C for 48 h. Blue colonies with bubbles were recorded and counted as E. coli and the pink or blue colonies with bubbles were counted as coliforms. All analyses were performed in triplicate, and results were expressed as the logarithm of colony-forming units per gram (Log CFU/g). In all cases, plate counts were determined and converted to log CFU values using standardized plate count rules (Vanderzant and Splittstoesser, 1992).

Statistical analysis

STATA version 12.0 was used for the statistical analysis. Student’s t-test or ANOVA was used for comparison of the APCs and CCs by month, season, meat type, and product form and results are presented as the mean and standard errors. To compare the presence or absence of coliforms by season, meat type, and product form, data were analyzed by Chi-square test and results are presented as frequencies (percentages) instead means. Pearson correlation analyses were performed to evaluate the relationship between APC and CC. If necessary, logarithmic transformations were used for variables with skewed distributions. A two-sided with a p-value of <0.05 was considered statistically significant.

Results and Discussion

As shown in Table 1, samples are classified by month, season, meat type, and product form. Meat types consisted of 50% pork, 42.7% beef, and 7.3% chicken. For product form, 78.7% of samples came from finished products and the remainder (21.3%) came from raw materials. By month, the greatest number of samples was collected in December (18%), followed by November (12.4%), July (11.8%), August (10.1%), and then September (3.4%) (p<0.001). By season, the greatest number of samples was collected in summer (28.7%), followed by winter (27%), fall (24.7%), and then spring (19.7%) (p<0.05).

Table 1. General sample characteristics (n= 178)
Sample Number (%) p-value
Plants Meat packing plants 178 (100.0)
Month January 7 (3.9) <0.001
February 9 (5.1)
March 6 (3.4)
April 14 (7.9)
May 15 (8.4)
June 12 (6.7)
July 21 (11.8)
August 18 (10.1)
September 6 (3.4)
October 16 (9.0)
November 22 (12.4)
December 32 (18.0)
Season Spring 35 (19.7) 0.040
Summer 51 (28.7)
Autumn 44 (24.7)
Winter 48 (27.0)
Animal Beef 76 (42.7) 0.917
Pork 89 (50.0)
Chicken 13 (7.3)
Product form Raw material 38 (21.3) 0.496
Finished product 140 (78.7)

Results are shown as frequencies (%).

a Indicates that p-value for trend <0.05.

Download Excel Table

Table 2 shows the APC in meat samples at meat packing plants. A statistically significant relationship between APC and month, as well as APC and season, was found. By month, the highest APC was found in September, and then August, June, and July in descending order (p<0.001). This high APC in September might be due to a failure in temperature management (<15°C) in the meat processing plants. However, the APCs in meat samples were greatest in summer, followed by spring, fall, and winter (p<0.001). The APCs in meat processing plants were 3.62, 4.48, 3.57, and 2.46 CFU/g in spring, summer, autumn, and winter, respectively. This is similar to a report by Oh and Lee (2001), which noted that microbial contamination of carcass surfaces in beef processing plants were the highest in summer and the lowest in winter. These findings are in agreement with those reported by Kim and Yim (2016). The APC was also associated with meat type and product form, even though these results were not statistically significant. The APCs in meat processing plants were 3.59, 3.73, and 3.46 CFU/g in beef, pork, and chicken, respectively. This result was similar to a report by Kim and Yim (2016), which showed that the APCs of pork samples taken from work tables at meat processing plants were higher than 103 CFU/g. Gounadaki et al. (2008) reported the presence of Listeria monocytogenes, Salmonella spp., or Staphylococcus aureus was associated with elevated APCs and specific groups of spoilage microorganisms, and suggested the potential association between the general hygiene level and the presence of pathogenic bacteria. Manios et al. (2015) indicated that high contamination levels in meat may be the result of raw materials with a high initial microbial load, poor hygiene practices during processing, or high temperatures (>15°C) in the processing lines.

Table 2. Aerobic plate counts (APC) in samples from meat packing plants
Sample Mean±SE p-value
Month January 2.47±0.19 <0.001
February 2.40±0.00
March 2.56±1.55
April 3.31±0.98
May 4.25±0.67
June 4.48±0.29
July 4.34±0.52
August 4.64±0.72
September 5.05±0.56
October 3.41±0.81
November 3.28±0.80
December 2.47±0.16
Season Spring 3.62±1.12 <0.001
Summer 4.48±0.56
Autumn 3.57±0.97
Winter 2.46±0.15
Animal Beef 3.59±1.12 0.614
Pork 3.73±1.00
Chicken 3.46±1.08
Product form Raw material 3.39±1.00 0.140
Finished product 3.71±1.06

Results are shown as mean±SE. Means with different letters indicate a statistically significant difference (p<0.05) by Duncan’s multiple range test. p-values were calculated by ANOVA (unit: Log CFU/g).

a Indicates that p-value for trend <0.05. Logarithmic transformations were used for the APC.

A-K Means with different superscripts in the same column are significantly different (p<0.05).

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Table 3 shows the level of coliforms in meat samples from meat packing plants. E. coli was not detected in any samples, and coliforms were rarely recovered from meat samples. There were significant monthly and seasonal differences in the CC. The CC was found to be greatest in August, followed by October and then July (p<0.001), which is in agreement with the results of previous study (Kim and Yim, 2016). The CCs in meat processing plants were 0.24, 0.82, and 0.45 CFU/g in spring, summer, and autumn, respectively (p<0.001), which is much lower than the counts presented by Oh and Lee (2001). The CCs in meat processing plants were 0.31, 0.44, and 0.55 CFU/g in beef, pork, and chicken, respectively.

Table 3. Coliform counts (CC) in samples from meat packing plants
Sample Mean±SE p-value
Month January - <0.001
February -
March -
April 0.27±0.72
May 0.30±0.86
June -
July 1.00±1.26
August 1.14±1.49
September 0.43±1.05
October 1.07±1.25
November -
December -
Season Spring 0.24±0.72 <0.001
Summer 0.82±1.27
Autumn 0.45±0.96
Winter -
Animal Beef 0.31±0.82 0.544
Pork 0.44±1.01
Chicken 0.55±1.05
Product form Raw material 0.14±0.62 0.066
Finished products 0.46±0.99

Results are shown as mean±SE. Means with different letters indicate a statistically significant difference (p<0.05) by Duncan’s multiple range test. p-values were calculated by ANOVA (unit: Log CFU/g).

a Indicates that p-value for trend <0.05. Logarithmic transformations were used for CCs.

A-F Means with different superscripts in the same column are significantly different (p<0.05).

Download Excel Table

Coliforms were only found in the spring, summer, and fall. Chi-square testing was performed to determine whether there was a relationship between the detection of coliforms and the season, as shown in Table 4. The results showed that there was a significant relationship between the two factors (p<0.001). There were no significant differences in APCs according to the meat type or product form (data not shown). There was no significant difference in the CC based on the product form; however, there was a statistically significant relationship between the presence of coliforms and the product form (p<0.05) (Table 4). Previous studies have shown that the CC increases during meat processing, from raw materials to the final products (Manios et al., 2015). Manios et al. (2015) suggested that fecal contamination of the final products originates primarily from raw materials, emphasizing the need for special attention to hygiene in the slaughterhouse and meat processing facility.

Table 4. Correlation between coliforms and season, meat type, and product form
Sample Coliforms χ2/ p-value
Presence Absence
Season Spring 4 (14.3) 34 (22.7) 19.062/<0.001
Summer 16 (57.1) 42 (28.0)
Autumn 8 (28.6) 38 (25.3)
Winter 0 (0.0) 36 (24.0)
Meat type Beef 10 (35.7) 66 (44.0) 0.993/0.609
Pork 15 (53.6) 74 (49.3)
Chicken 3 (10.7) 10 (6.7)
Product form Raw material 2 (7.1) 36 (24.0) 3.993/0.046
Finished products 26 (92.9) 114 (76.0)

p-values were calculated by Chi-square test.

a Indicates that p-value for trend <0.05.

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Table 5 represents the correlation between the APC and CC. One hundred and seventy-eight samples with APC and 160 samples with CC were examined. The average APCs and CCs for samples were 3.65 and 0.39 CFU/g. We examined the correlation between these counts, and found a positive correlation between the two types of bacteria (r=0.261***). Although coliforms cannot directly indicate the presence of E. coli O157, they may be useful as indirect indicators. More data are needed to confirm these findings.

Table 5. Correlation between aerobic plate count and coliform count (unit: Log CFU/g)
Sample Number Mean±SE Correlations
1 2
Aerobic plate count 178 3.65±1.06 1.00 0.261
Coliform count 160 0.39±0.94 1.00

***p< 0.001.

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The distribution of APCs and CCs in beef, pork, and chicken samples from meat processing plants are presented in Table 6. The APCs in analyzed samples ranged from below the detection limit (<101 CFU/g) to <107 CFU/g. The prevalence of aerobic bacteria in samples with APCs ranging from 102-105 CFU/g in beef was 35.8%. The most commons APCs in pork were 104-105 and 102-103, followed by 103-104 and 105-106 CFU/g. The wide distribution of APCs can be attributed to the variability in the origin and extent of processing of the analyzed meat samples, e.g., intact or processed meat (Manios et al., 2015). Most beef, pork, and chicken samples showed CCs of less than 102. Counts in all samples remained below the guidelines for maximum microbiological limits for meat (ministry of food and drug safety, MFDS, 2018). Kim et al. (2000) found that the percentage of pork samples with APCs less than 104 CFU/cm2 and ECs less than 102 CFU/cm2 were 82% and 80%, respectively.

Table 6. Distribution of aerobic plate count (APC) and coliform count (CC) for beef, chicken, and pork samples in meat packing plants
Animal samples Bacteria Distribution of bacterial count (CFU/g)
<102 102 –<103 103 – <104 104 – <105 105 – <106 106 – <107 >107
Beef (%)
(n=76)
APC 1 (1.5) 24 (35.8) 13 (19.4) 24 (35.8) 4 (6.0) 1 (1.5) -
CC 68 (89.5) 7 (9.2) 1 (1.3) - - - -
Pork (%)
(n=89)
APC - 25 (30.5) 18 (22.0) 33 (40.2) 6 (7.3) - -
CC 76 (85.4) 9 (10.1) 4 (4.5) - - - -
Chicken (%)
(n=13)
APC - 6 (54.5) - 5 (45.5) - - -
CC 10 (76.9) 3 (23.1) - - - - -
Download Excel Table

Interestingly, the APCs and CCs of chicken samples were generally lower than those of beef and pork samples, which agrees with a report by Lee et al. (2007). Coliforms in meat may be attributable to the presence of feces during the slaughtering process. Although all samples were negative for E. coli, coliforms were detected in some of meats from the plants. Minimizing the presence of bacteria in meat is essential, because E. coli and coliforms can cause serious public health problems (Lowe et al., 2001). According to our study, it is crucial that sanitary operation in which meat are processed are strictly controlled to prevent microbial contamination of the meat.

Conclusion

The present study provides essential information about the hygienic levels at HACCP implemented meat processing plants through the assessment of microbiological data. Data from this study can be used to identify critical control points for the verification of hygiene control procedures. It could be concluded that the prevalence of APC in samples from meat processing plants was highest in August and the CC was found to be highest in August. Correlation between (i) the product form and coliform, (ii) the APC and CC were revealed. Further study should be required for microbiological assessment of meat cut at all operational stages such as the slaughterhouse, processing line, and retail outlets.

Acknowledgements

This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Agri-Bio industry Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (315017-05-3-HD080).

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