Safety of Commercially Available Beef Burger in Saudi Arabia
by
, and
Eman Hillal Al-Thubaiti
1,2, 
Abdulkader M. Shaikh Omar
1,
Abdelfatteh El-Omri
1,
Mohammed Al-Matary
1,
Ali H. Al-Mwallad
3 and
Seham Mahmoud Eldeeb
4,* 1
Department of Biology, Zoology Division, Faculty of Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
2
Biotechnology Department, College of Science, Taif University, Taif 26571, Saudi Arabia
3
Jeddah Municipality, Jeddah 21146, Saudi Arabia
4
Lecturer of Public Health and Community Medicine, Zagazig University, Ash Sharqiyah 44519, Egypt
*
Author to whom correspondence should be addressed.
Coatings 2021, 11(6), 686; https://doi.org/10.3390/coatings11060686
Submission received: 25 April 2021
/
Revised: 16 May 2021
/
Accepted: 22 May 2021
/
Published: 7 June 2021
/
Retracted: 16 August 2022
(This article belongs to the Special Issue Biomedical Application of Natural Plant Extracts)
Abstract
:The safety of meat has been at the forefront of societal concerns in recent years, and indications exist that challenges to meat safety will continue in the future. Major meat safety issues and related challenges include the need to control traditional and emerging pathogenic microorganisms, such as increased virulence and low infectious doses or resistance to antibiotics or food-related stresses. This study aimed to recognize microbial contamination and heavy metals content. Thirty-eight frozen and freshly prepared burger (local and imported) samples were collected from randomly selected supermarkets and fast-food restaurants in Jeddah. Yeasts/Molds had the highest count (204.3 CFU/mL) followed by total aerobic mesophiles (69.5 CFU/mL), total coliforms (16.2 CFU/mL) and Escherichia coli (10.0 CFU/mL). Salmonella species were positive in 39.5% of samples. Fresh burgers had more counts of TVC, total coliforms, Escherichia coli, and Bacillus cereus. Amoxicillin-clavulanate and Ampicillin had a high frequency of resistance in the studied sample. None of the studied samples had detectable traces of heavy metals’ elements. This research provides valid data to protect consumers from different health risks related to burgers in Saudi Arabia.
1. Introduction
Meat production has increased globally and quickly over the past 50 years. Regionally, the Asian continent is the largest meat producer with around half of total meat production. Saudi Arabia increased beef production in 1961 to reach 40,000 tons in 2018 [1]. Meat consumption in Kg per capita and the year was around 20 kg in 1961 and came to an average of 43 kg in 2014. These data indicate that meat production has been increasing at a much faster level than the population growth. In Saudi Arabia, the trend of meat consumption per capita is almost similar to the global figures. The consumption increased from 10 kg in 1961 to reach 50 kg/capita/year in 2019 [2].
According to 2019 Food and Agriculture Organization (FAO) data, Saudi Arabia’s production of camel meat was 108,679 tons, sheep meat was 90,395 tons, and cattle meat was 43,000 tons [3].
High meat consumption requires a lot of effort to maintain meat quality, from production to consumption. Safeguarding consumers from different levels of contamination is very challenging. Food contamination may be due to naturally happening contaminants in the environment or artificially-created by human interventions during various food processing, packaging, transportation, and storage [4].
The meat supply chain is very complex, and it is well-known that it is difficult to trace back different contaminants. Such complexity increases the risk of meat species substitution, ingredients adulteration, and contamination by foodborne pathogens or xenobiotics that may be present at much higher concentrations than usual [5].
Contamination of meat can come from unhygienic slaughtering, handling, and processing conditions, operators’ hands, unsanitary abattoir, or inherent micro-flora in animals’ normal tissues, air, and environment [6]. Different microbes are introduced at each stage of meat processing after slaughtering, which tend to contaminate the meat [7]. The presence of pathogenic microbes is distressing the hygienic quality of beef. Further, the microbial contamination of food can occur by unhygienic food handling. Food consumers also comprise a link in the chain of foodborne bacterial illnesses with improper storage and cooking of meat and meat products [8]. Pathogens such as B. cereus, C. jejuni, E. coli, L. monocytogenses, S. aureus, and Y. enterocolitica are known to produce foodborne infections and intoxications in humans. Therefore, it is necessary to assess the microbial load of the food by employing standard microbiological techniques [6].
Foodborne illnesses are preventable diseases that affect people globally and present a growing public health concern [9]. Currently, the burden of foodborne diseases in Kingdom of Saudi Arabia (KSA) is not known. Because there is only one system surveying these diseases, which belongs to the Ministry of Health (MOH), estimates of foodborne disease incidence rates are only available for the conditions that require MOH notification [10]. Other surveillance and epidemiological investigation systems are currently under development by the Saudi Food and Drug Authority [11].
It has been reported that more than 60% of foodborne diseases in KSA are caused by food prepared in restaurants. In Riyadh city alone, an average of 55 food service establishments is involved in outbreak incidence annually. However, as is the case in many countries, foodborne diseases may be underdiagnosed or underreported in the KSA. Obtaining more accurate estimates for these diseases is hindered by the shortage of sufficient infrastructure and specialized scientists and staff. The majority of surveyed consumers in the KSA thought restaurants were responsible for the foodborne disease they experienced [12].
The consumer needs to be provided with safe and wholesome meat, which will not cause health problems. This can be achieved by practicing better farm animal management, good personal hygiene, and adequate food safety knowledge to all the meat handlers in the production chain [13].
This study was conducted in Jeddah city. The laboratory work was complete at the King Abdelaziz university faculty of sciences (biology science department) and Jeddah municipality Laboratory. The present communication aimed to describe microbial content diversity and hygienic quality of commercially available beef burgers using growth organisms, stains, and biochemistry tests.
2. Materials and Methods
2.1. Sample Collection
A random sample of five supermarkets and four fast-food restaurants in Jeddah was selected. The fieldwork was done under the Jeddah Municipality authority’s supervision through a signed agreement with King Abdulaziz University. A total of 38 sample units were collected from hypermarkets and fast-food restaurants, out of which 11 were frozen beef meat burgers collected from 3 producers, 15 sample units of fresh beef meat burger collected from 5 hypermarkets, and 12 sample units of beef meat burger collected from 4 fast-food restaurants (Table 1). Each sample unit was formed of a 100 g beef burger in a sterile plastic container. The collected sample was transported to Jeddah municipality Laboratory and King Abdul-Aziz University for immediate analysis in Icebox (4 °C).
2.2. Sample Preparation and Bacterial Culture (Aerobic and Anaerobic)
For microbial enumeration, 10 g of meat samples were transferred aseptically into a sterile stomacher bag containing 90 mL of sterile distilled water and homogenized using the Stomacher lab blender. Homogenized samples were serially diluted to prepare tenfold appropriate dilutions. From proper dilution, 0.5 mL aliquot was spread-plated on respective media for detection and counting of different groups of organisms.
2.3. Determination of Counts of Indicator Bacteria
Total aerobic mesophiles (TAM), total coliforms (TC), and fecal coliforms (FC), members of Enterobacteriaceae (EB), Staphylococcus aureus (SA), Bacillus cereus (BC), Listeria monocytogenes (LM), Streptococci, Pseudomonas aeruginosa, Salmonella species and yeasts/molds (YM) were counted on appropriate media.
For total aerobic mesophiles incubated (TAM) count, plate count agar (PCA) plates at 32 °C for 48–72 h. Inoculated violet-red bile agar (SRL) plates for total coliforms (TC) and fecal coliforms (FC) counts were incubated at 32 °C and 44.5 °C for 18–24 h in that order (Figure 1).
MacConkey agar supplemented with glucose was used to count Enterobacteriaceae and Pseudomonas aeruginosa after incubating plates at 35 °C for 24 h.
Mannitol salt agar (MSA) was employed to count Staphylococci. Purified colonies were tested for coagulase positivity as a confirmatory test for staphylococci. Bile esculin agar was used to measure counts of Streptococci. Yeasts/molds were counted on potato dextrose agar supplemented with 0.1 g chloramphenicol. After incubating plates at 25 °C for 3–5 days, typical Yeasts/Molds colonies were counted (Figure 2).
Detection of Salmonella spp. was done by adding 1 g of original suspension from minced meat into each of 10 mL nutrient broth media (Oxide) then incubated at 37 °C for 24 h, then inoculated in Xylose Lysine Desoxycholate (XLD) agar and Salmonella Shigella Agar (SS Agar). Incubation of inoculated plates and identification of presumptive Salmonella colonies were conducted. Further biochemical tests were done by employing different identification methods using triple sugar iron agar, lysine iron agar, Simmons citrate agar (Figure 3).
2.4. Staining, Biochemical and Phenotypic Features
Cultured colonies were examined morphologically and microscopically. Gram staining was used for classifying bacteria to Gram-negative or Gram-positive according to the method described by Smith and Hussey (2005) [14]. Catalase test was done to test the catalase activity. Bacterial cultures were grown on NA plates at 37 °C for 24 h. A loopful of each bacterial culture was mixed with a drop of hydrogen peroxide (H2O2) on a clean glass slide to observe the production of gas bubbles, which indicates a positive reaction [15]. Oxidase test was done. The presence of cytochrome oxidase was determined by smearing culture from a solid medium on filter paper impregnated with freshly made 1% aqueous solution of N-N-N-tetramethyl P phenylenediamine dihydrochloride. The appearance of dark purple color within 10 s indicates a positive reaction [16].
2.5. Antibiotic Susceptibility Test of the Isolated Bacteria
2.6. Heavy Metals
Inductively coupled plasma mass spectrometer (NEXION 350D CPMS, PerkinElmer Waltham, MA, USA) was used to measuring the concentration of heavy metals. It does this by aspirating the solution into an argon plasma which converts the elements into positively charged ions. These ions go through an interface (three cones with small holes in them) and ion optics to guide the ions towards a quadrupole. The quadrupole separates the ions based on their mass to charge ratio, and then the number of ions of each mass that goes through the quadrupole is measured by an electron detector. The concentration of each element is determined by comparing the number of ions from standards with those of the samples.
2.7. Statistical Analysis
Statistical analysis was done using SPSS software version 27 [17] and Open Epi version 2.3.1 [18]. Quantitative variables were summarized as a median and inter-quartile range. Qualitative variables were summarized as frequencies and proportions.
Shapiro-Wilk test was used to determine the distribution characteristics of variables and variance homogeneity. Kruskal-Wallis test and Dunn’s multiple comparison test were used to analyze quantitative variables. Pearson’s chi-square test was used to analyze qualitative variables. A p-value of ˂0.05 was accepted as statistically significant [19].
2.8. Administrative Considerations
Approval of Institutional Review Board of King Abdul-Aziz University, Faculty of science was taken after revision of study protocol. Official permission from the Jeddah Municipality authority was obtained after being informed about the nature and steps of the study. All participant’s data (supermarkets and restaurants) were confidential.
3. Results
Median counts of indicator bacteria in the studied sample were illustrated in Figure 4. Yeasts/molds had the highest count (204.3 CFU/mL) followed by total aerobic mesophiles (69.5 CFU/mL), total coliforms (16.2 CFU/mL) and Escherichia coli (10.0 CFU/mL). Salmonella species were positive in 39.5% of samples (Table 2).
There were statistically significant differences between the studied samples in the distribution of indicator bacteria. Fresh burgers had more total aerobic mesophiles, total coliforms, Escherichia coli, and Bacillus cereus (Table 3).
There were statistically significant differences between the studied isolates in staining, biochemical and Phenotypic features. Fresh burgers had less gram-positive and less oxidase test. Besides, fresh burger colonies had more circular clear colonies and circular cells (Table 4).
An antibiogram of the isolated bacteria was presented in Table 5. Almost all the isolated bacteria were sensitive to cefepime, ceftazidime, ciprofloxacin, imipenem, meropenem, levofloxacin, gentamicin and trimethoprim-sulfamethoxazole. However, amoxicillin-clavulanate and ampicillin had a high frequency of resistance in the studied sample.
Regarding heavy metals analysis results, none of the studied samples had detectable traces of heavy metals’ elements (Table 6).
4. Discussion
Meat and meat products are high in many nutrients, which are very prevalent in our ecosystem and are easily attacked by microbes. When preparing high-quality foods that are safer for the consumer, the presence of species in meat and meat products is the primary concern. Processed meat is more susceptible to microbial contamination during different processing stages. In similar studies, the most frequently identified bacterial pathogens associated with beef products are Salmonella spp., Bacillus cereus, Campylobacter spp., Clostridium perfringens, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, Yersinia enterocolitica, and Vibrio parahaemolyticus [20,21].
Ali et al. (2010) isolated various foodborne pathogens such as Escherichia coli O157:H7, Listeria spp., Salmonella enteritidis, and Shigella species from meat samples in retail meat shops, while microbiological examination of meat handling equipment in retail shops revealed Staphylococcus and Shigella spp. [22]. Likewise, Soyiri et al. (2008) recovered Staphylococcus aureus, Bacillus cereus, Clostridium perfringens, Escherichia coli, and Staphylococcus aureus from beef samples [23].
Median counts of Total Aerobic Mesophiles (69.5 CFU/mL) in the current study were lower than Kim and Yim (2016) but higher than Soepranianondo and Wardhana (2019) [24,25]. Ismail et al. (2013) studied the microbial quality of some meat products obtained from local markets in Egypt. They reported many fungi belonging to several genera such as Aspergillus, Candida, Cladosporium, Eupenicillium, Eurotium, Geotrichum, Mucor, Penicillium, Rhototorula besides aflatoxin B1. These researchers also isolated Clostridium perfringens and Staphylococcus aureus [26].
In the current study, the presence of Salmonella spp. (39.5%) was much higher than other studies Soepranianondo and Wardhana (2019) [24], Reid et al. [27], and Silva et al. [28]. The high prevalence of Salmonella spp. contamination found in this study might be due to inadequate hygiene and sanitation and an absence of the Hazard Analysis and Critical Control Point (HACCP) system in the slaughterhouses.
Median counts of Escherichia coli (10.0 CFU/mL) in the current study were low compared to Soepranianondo and Wardhana (2019) [24]. The high level of E. coli in beef meat might be caused by several factors, including E. coli which is a normal flora in the animal intestine, so it is possible that beef may come in contact with fecal contaminants [29], the nature of meat which was susceptible to E. coli contamination [30], high prevalence in developing countries due to large population in temporary shelter and poor hygiene, and the worker hands and the slaughtering equipment [31].
Median counts of S. aureus in the study were slightly lower than other results reported by similar studies [32,33,34]. S. aureus contamination might be caused by workers touching meat without using gloves or aerosols when talking, coughing, or sneezing [35]. In addition, it indicates that inadequate cleaning, unsatisfactory handling, and post-processing contamination from the polluted atmosphere around shops. The high prevalence of S. aureus in raw meat and handlers contain health hazards like toxin-mediated virulence and invasiveness to consumers [36,37,38].
5. Conclusions
This research provides valid data to protect consumers from different health risks related to burgers in Saudi Arabia. The meat is exposed to multiple sources of contamination during slaughtering. Before, during, and after slaughter, the hygienic condition of animals can be crucial to the quality of the finished product. Therefore, it is necessary to control the microbiological quality of meat and meat products to achieve better quality and protection. In different meat products, attempts should be made to detect toxins such as aflatoxins, Clostridium perfringens toxins, and Staphylococcal aureus toxins. Easy, low-cost sensitive tests should also be established for routine microbiological monitoring of meat and meat products.
Author Contributions
Conceptualization, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M., A.H.A.-M. and S.M.E.; methodology, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M., A.H.A.-M. and S.M.E.; software, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; validation, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; formal analysis, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; investigation, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; resources, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; data curation, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; writing—original draft preparation, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; writing—review and editing, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; visualization, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M., A.H.A.-M. and S.M.E.; supervision, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; project administration, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M. and S.M.E.; funding acquisition, E.H.A.-T., A.M.S.O., A.E.-O., M.A.-M., A.H.A.-M. and S.M.E. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Approval of Institutional Review Board of King Abdul-Aziz University, Faculty of science was taken after revision of study protocol. Official permission from the Jeddah Municipality authority was obtained after being informed about the nature and steps of the study. All participant’s data (supermarkets and restaurants) were confidential.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available on request from the corresponding author.
Acknowledgments
The authors would like to thank Jeddah Municipality authority for the enthusiastic support during field work and deep thanks to Deanship of scientific research in Taif University for continuous efforts and support. Authors also acknowledge to Deanship of scientific research in King Abdul Aziz University for continuous support.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Ritchie, H.; Roser, M. Meat and Dairy Production. Our World in Data. Available online: https://ourworldindata.org/meat-production (accessed on 29 January 2021).
- OECD/FAO 2019. OECD-FAO Agricultural Outlook 2019–2028. Available online: http://www.fao.org/3/CA4076EN/CA4076EN_Chapter6_Meat.pdf (accessed on 24 April 2021).
- Food and Agricultural Organization. FAOSTAT. Available online: http://www.fao.org/faostat/en/ (accessed on 29 July 2018).
- Rather, I.A.; Koh, W.Y.; Paek, W.K.; Lim, J. The Sources of Chemical Contaminants in Food and Their Health Implications. Front. Pharmacol. 2017, 8, 830. [Google Scholar] [CrossRef] [PubMed]
- Esteki, M.; Regueiro, J.; Simal-Gándara, J. Tackling Fraudsters with Global Strategies to Expose Fraud in the Food Chain. Compr. Rev. Food Sci. Food Saf. 2019, 18, 425–440. [Google Scholar] [CrossRef]
- Kozačinski, L.; Hadžiosmanović, M.; Zdolec, N. Microbiological quality of poultry meat on the Croatian market. Vet. Arh. 2006, 76, 305–313. [Google Scholar]
- Ebel, E.; Schlosser, W.; Kause, J.; Orloski, K.; Roberts, T.; Narrod, C.; Malcolm, S.; Coleman, M.; Powell, M. Draft Risk Assessment of the Public Health Impact of Escherichia coli O157:H7 in Ground Beef. J. Food Prot. 2004, 67, 1991–1999. [Google Scholar] [CrossRef]
- Tachbele, E.; Erku, W.; Gebre-Michael, T.; Ashenafi, M. Cockroach-associated foodborne bacterial pathogens from some hospitals and restaurants in Addis Ababa, Ethiopia: Distribution and antibiograms. J. Rural Trop. Public Health 2006, 5, 34–41. [Google Scholar]
- World Health Organization. Food Safety and Foodborne Illness. Fact Sheet No. 237; World Health Organization: Geneva, Switzerland, 2007; p. 2007. [Google Scholar]
- Alsayeqh, A.F. Foodborne disease risk factors among women in Riyadh, Saudi Arabia. Food Control 2015, 50, 85–91. [Google Scholar] [CrossRef]
- Saudi Arabian Monetary Agency. Year 2013 Statistical Report. Available online: http://www.sama.gov.sa/ReportsStatistics/ReportsStatisticsLib/5600_R_Annual_Ar_49_2013_12_23.pdf (accessed on 19 May 2020).
- Al-Mutairi, S.; Connerton, I.; Dingwall, R. Food safety organisations in Saudi Arabia–Organisational, historical and future anal-ysis. Food Control 2015, 47, 478–486. [Google Scholar] [CrossRef]
- Sofos, J.N. Meat and Meat Products. In Food Safety Management; Elsevier: Amsterdam, The Netherlands, 2014; pp. 119–162. [Google Scholar]
- Smith, A.C.; Hussey, M.A. Gram stain protocols. Am. Soc. Microbiol. 2005, 1, 14. [Google Scholar]
- Reiner, K. Catalase Test Protocol; American Society for Microbiology: Washington, DC, USA, 2010; pp. 1–6. [Google Scholar]
- Shields, P.; Cathcart, L. Oxidase Test Protocol; American Society for Microbiology: Washington, DC, USA, 2010. [Google Scholar]
- IBM. IBM SPSS Statistics for Windows, Version 27; IBM Corp.: Armonk, NY, USA, 2020; Available online: http://www-01.ibm.com/support/docview.wss?uid=swg27049428 (accessed on 12 January 2021).
- Dean, A.; Sullivan, K.; Soe, M. OpenEpi: Open Source Epidemiologic Statistics for Public Health. 2013. Updated 2013/4/6. Available online: https://www.OpenEpi.com (accessed on 1 February 2021).
- World Health Organization. World Health Statistics 2017: Monitoring Health for the SDGs; World Health Organization: Geneva, Switzerland, 2017. [Google Scholar]
- Biswas, A.K.; Kondaiah, N.; Anjaneyulu, A.S.; Mandal, P.K. Causes, concerns, consequences and control of microbial contami-nants in meat-A review. Int. J. Meat Sci. 2011, 1, 27–35. [Google Scholar] [CrossRef]
- Zhao, C.; Ge, B.; De Villena, J.; Sudler, R.; Yeh, E.; Zhao, S.; White, D.G.; Wagner, D.; Meng, J. Prevalence of Campylobacter spp., Esch-erichia coli, and Salmonella serovars in retail chicken, turkey, pork, and beef from the Greater Washington, DC, area. Appl. Environ. Microbiol. 2001, 67, 5431–5436. [Google Scholar] [CrossRef]
- Ali, N.H.; Farooqui, A.; Khan, A.; Khan, A.Y.; Kazmi, S.U. Microbial contamination of raw meat and its environment in retail shops in Karachi, Pakistan. J. Infect. Dev. Ctries. 2010, 4, 382–388. [Google Scholar] [CrossRef]
- Soriyi, I.; Agbogli, H.K.; Dongdem, J.T. A Pilot Microbial Assessment of Beef Sold In The Ashaiman Market, A Suburb Of Accra, Ghana. Afr. J. Food Agric. Nutr. Dev. 2008, 8, 91–103. [Google Scholar] [CrossRef]
- Kim, J.-H.; Yim, D.-G. Assessment of the Microbial Level for Livestock Products in Retail Meat Shops Implementing HACCP System. Food Sci. Anim. Resour. 2016, 36, 594–600. [Google Scholar] [CrossRef]
- Soepranianondo, K.; Wardhana, D.K. Analysis of bacterial contamination and antibiotic residue of beef meat from city slaugh-terhouses in East Java Province, Indonesia. Vet. World 2019, 12, 243. [Google Scholar] [CrossRef] [PubMed]
- Ismail, S.A.; Shehata, A.A.; El-Diasty, E.M. Microbiological quality of some meat products in local markets with special reference to mycotoxins. J. Glob. Vet. 2013, 10, 577–584. [Google Scholar]
- Reid, C.-A.; Avery, S.; Hutchison, M.; Buncic, S. Evaluation of sampling methods to assess the microbiological status of cattle hides. Food Control 2002, 13, 405–410. [Google Scholar] [CrossRef]
- Da Silva, F.F.P.; Horvath, M.B.; Silveira, J.G.; Pieta, L.; Tondo, E.C. Occurrence of Salmonella spp. and generic Escherichia coli on beef carcasses sampled at a brazilian slaughterhouse. Braz. J. Microbiol. 2014, 45, 17–24. [Google Scholar] [CrossRef] [PubMed]
- Yousuf, A.H.; Ahmed, M.K.; Yeasmin, S.; Ahsan, N.; Rahman, M.M.; Islam, M.M. Prevalence of microbial load in shrimp, Penaeus monodon and prawn, Macrobrachium rosenbergii from Bangladesh. World J. Agric. Sci. 2008, 4, 852–855. [Google Scholar]
- Trabulsi, L.R.; Keller, R.; Gomes, T.A.T. Typical and Atypical EnteropathogenicEscherichia coli. Emerg. Infect. Dis. 2002, 8, 508–513. [Google Scholar] [CrossRef]
- Bryant, J.; Brereton, D.A.; Gill, C.O. Implementation of a validated HACCP system for the control of microbiological contamina-tion of pig carcasses at a small abattoir. Can. Vet. J. 2003, 44, 51. [Google Scholar]
- Schlegelova, J.; Nápravnıková, E.; Dendis, M.; Horvath, R.; Benedık, J.; Babak, V.; Klımová, E.; Navratilova, P.; Šustáčková, A. Beef carcass contamination in a slaughterhouse and prevalence of resistance to antimicrobial drugs in isolates of selected microbial species. Meat Sci. 2004, 66, 557–565. [Google Scholar] [CrossRef]
- Bernard, R.K. Determination of Bacteriological Quality of Fresh Beef Post-Harvesting in Nygacho Slum, Kericho. Master’s Thesis, Kenyatta University, Nairobi County, Kenya; p. 50.
- Kumar, P.; Rao, J.; Haribabu, Y. Manjunath Microbiological Quality of Meat Collected from Municipal Slaughter Houses and Retail Meat Shops from Hyderabad Karnataka Region, India. Apcbee Procedia 2014, 8, 364–369. [Google Scholar] [CrossRef]
- Gilbert, U.; Harrison, A. Occurrence of enterotoxin producing Staphylococcus aureus in meat market in Nigeria. J. Food Infect. 2001, 56, 25–35. [Google Scholar]
- Kadariya, J.; Smith, T.C.; Thapaliya, D. Staphylococcus aureusand Staphylococcal Food-Borne Disease: An Ongoing Challenge in Public Health. BioMed Res. Int. 2014, 2014, 1–9. [Google Scholar] [CrossRef] [PubMed]
- Marrone, R.; Smaldone, G.; Ambrosio, R.L.; Festa, R.; Ceruso, M.; Chianese, A.; Anastasio, A. Effect of beetroot (Beta vulgaris) extract on Black Angus burgers shelf life. Ital. J. Food Saf. 2021, 10. [Google Scholar] [CrossRef]
- Gogliettino, M.; Balestrieri, M.; Ambrosio, R.L.; Anastasio, A.; Smaldone, G.; Proroga, Y.T.R.; Moretta, R.; Rea, I.; De Stefano, L.; Agrillo, B.; et al. Extending the Shelf-Life of Meat and Dairy Products via PET-Modified Packaging Activated with the Antimicrobial Peptide MTP1. Front. Microbiol. 2020, 10, 2963. [Google Scholar] [CrossRef] [PubMed]
Figure 1.
Single colonies were isolated from frozen and freshly prepared burger samples.
Figure 2.
Selective media to detect different microorganisms in frozen and fresh burger samples and fast-food restaurants samples.
Figure 2.
Selective media to detect different microorganisms in frozen and fresh burger samples and fast-food restaurants samples.
Figure 3.
Xylose Lysine Desoxycholate (XLD) agar and Salmonella Shigella Agar (SS Agar) for detect Salmonella species and triple sugar iron agar test, lysine iron agar test, Simmons citrate agar test.
Figure 3.
Xylose Lysine Desoxycholate (XLD) agar and Salmonella Shigella Agar (SS Agar) for detect Salmonella species and triple sugar iron agar test, lysine iron agar test, Simmons citrate agar test.
Figure 4.
Median counts of indicator bacteria in the studied sample: YM: yeasts/molds, TAM: total aerobic mesophiles, TC: total coliforms, EC: Escherichia coli, S: Streptococci, BC: Bacillus cereus, PA: Pseudomonas aeruginosa, SA: Staphylococci aureus, LM: Listeria monocytogenes.
Figure 4.
Median counts of indicator bacteria in the studied sample: YM: yeasts/molds, TAM: total aerobic mesophiles, TC: total coliforms, EC: Escherichia coli, S: Streptococci, BC: Bacillus cereus, PA: Pseudomonas aeruginosa, SA: Staphylococci aureus, LM: Listeria monocytogenes.
Table 1.
Types and outlet distribution of the studied samples.
| Type of Sample | Code * | No of Samples |
|---|---|---|
| Frozen burger | AFB | 4 |
| SNFB | 4 | |
| SFB | 3 | |
| Fresh burger | BFB | 3 |
| BNFB | 3 | |
| DFB | 3 | |
| MFB | 3 | |
| RFB | 3 | |
| Fast-food restaurants | GB | 3 |
| HB | 3 | |
| KB | 3 | |
| MB | 3 | |
| Total | 38 | |
* Codes were used to keep trademarks, supermarkets, and restaurants confidential.
Table 2.
Distribution of Salmonella species in the studied sample.
| Salmonella Species | No of Samples | Percentage from Total (%) |
|---|---|---|
| Positive | 15 | 39.5 |
| Negative | 23 | 60.5 |
| Total | 38 | 100 |
Table 3.
Comparison between the different types of the sample regarding counts of Indicator bacteria.
Table 3.
Comparison between the different types of the sample regarding counts of Indicator bacteria.
| Counts of Indicator Bacteria (CFU/mL) | Frozen Burger | Fresh Burger | Fast-Food Restaurants | p-Value |
|---|---|---|---|---|
| Yeasts/molds: | ||||
| Median (IQ-Range) | 214.8 (245.0) | 113.8 (358.0) | 191.7 (920.5) | 0.6 |
| TAM: | ||||
| Median (IQ-Range) | 30.7 (66.3) a | 102.9 (143.2) b | 85.0 (183.9) a | 0.02 * |
| Total coliforms: | ||||
| Median (IQ-Range) | 6.8 (25.0) a | 35.1 (126.0) b | 11.8 (31.9) a | 0.02 * |
| Escherichia coli: | ||||
| Median (IQ-Range) | 4.0 (8.7) a | 12.3 (24.1) b | 10.3 (14.5) b | 0.04 * |
| Streptococci: | ||||
| Median (IQ-Range) | 5.3 (8.0) | 4.3 (29.2) | 7.3 (10.2) | 0.8 |
| Bacillus cereus: | ||||
| Median (IQ-Range) | 0.33 (0.0) a | 40.6 (38.3) b | 4.3 (23.8) a | <0.001 * |
| Pseudomonas aeruginosa: | ||||
| Median (IQ-Range) | 0.33 (0.67) | 0.0 (0.0) | 0.17 (0.63) | 0.1 |
| Staphylococci: | ||||
| Median (IQ-Range) | 0.33 (0.67) | 0.33 (1.0) | 1.4 (1.7) | 0.2 |
| Listeria monocytogenes: | ||||
| Median (IQ-Range) | 0.0 (0.67) | 0.0 (1.3) | 0.0 (0.46) | 0.9 |
| Salmonella: | ||||
| Positive | 5 (45.5%) | 5 (33.3%) | 5 (41.7%) | 0.8 |
| Negative | 6 (54.5%) | 10 (66.7%) | 7 (58.3%) | |
* Statistically significant. a,b values with different alphabetic letters are statistically significantly different.
Table 4.
Comparison between the different types of the sample regarding staining, biochemical and Phenotypic features of isolates.
Table 4.
Comparison between the different types of the sample regarding staining, biochemical and Phenotypic features of isolates.
| Variables | Frozen Burger | Fresh Burger | Fast-Food Restaurants | p-Value | |||
|---|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | ||
| Gram staining: | |||||||
| Positive | 8 | 40.0 | 8 | 15.7 | 18 | 58.1 | <0.001 * |
| Negative | 12 | 60.0 | 43 | 84.3 | 13 | 41.9 | |
| Aerobic/Anaerobic: | |||||||
| Aerobic | 15 | 75.0 | 23 | 45.1 | 15 | 48.4 | 0.1 |
| Anaerobic | 5 | 25.0 | 23 | 45.1 | 15 | 48.4 | |
| Facultative anaerobic | 0 | 0.0 | 5 | 9.8 | 1 | 3.2 | |
| Catalase test: | |||||||
| Positive | 16 | 80.0 | 46 | 90.2 | 29 | 93.5 | 0.3 |
| Negative | 4 | 20.0 | 5 | 9.8 | 2 | 6.5 | |
| Oxidase test: | |||||||
| Positive | 11 | 55.5 | 11 | 21.6 | 18 | 58.1 | 0.001 * |
| Negative | 9 | 45.0 | 40 | 78.4 | 13 | 41.9 | |
| Colony shape: | |||||||
| Circular | 15 | 75.0 | 47 | 92.2 | 20 | 64.5 | 0.007 * |
| Irregular | 5 | 25.0 | 4 | 7.8 | 11 | 35.5 | |
| Colony color: | |||||||
| Clear | 12 | 60.0 | 42 | 82.4 | 14 | 45.2 | 0.008 * |
| White | 8 | 40.0 | 9 | 17.6 | 16 | 51.6 | |
| Yellow | 0 | 0.0 | 0 | 0.0 | 1 | 3.2 | |
| Margin: | |||||||
| Entire | 13 | 65.0 | 33 | 64.7 | 15 | 48.4 | 0.5 |
| Curled | 4 | 20.0 | 14 | 27.5 | 9 | 29.0 | |
| Undulate | 3 | 15.0 | 3 | 5.9 | 6 | 19.4 | |
| Lobate | 0 | 0.0 | 1 | 2.0 | 1 | 3.2 | |
| Surface: | |||||||
| Convex | 10 | 50.0 | 24 | 47.1 | 11 | 35.5 | 0.4 |
| Umbonate | 5 | 25.0 | 20 | 39.2 | 13 | 41.9 | |
| Pulvinate | 4 | 20.0 | 5 | 9.8 | 2 | 6.5 | |
| Raised | 1 | 5.0 | 2 | 3.9 | 4 | 12.9 | |
| Flat | 0 | 0.0 | 0 | 0.0 | 1 | 3.2 | |
| Cell shape: | |||||||
| Rode-shaped | 19 | 95.0 | 2 | 3.9 | 5 | 16.1 | <0.001 * |
| Circular | 1 | 5.0 | 49 | 96.1 | 26 | 83.9 | |
* Statistically significant.
Table 5.
Antibiogram of the isolated bacteria.
| Antibiotics | Isolated Bacteria | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| TAM | TC | EC | S | BC | LM | PA | SA | Salm. | ||
| AMK | S | 32 | 31 | 29 | 30 | 22 | 10 | 9 | 22 | 11 |
| R | 6 | 7 | 9 | 8 | 16 | 6 | 6 | 5 | 4 | |
| AMC | S | 4 | 2 | 3 | 9 | 8 | 2 | 1 | 5 | 2 |
| R | 34 | 36 | 35 | 29 | 30 | 14 | 14 | 22 | 13 | |
| AMP | S | 4 | 2 | 3 | 9 | 8 | 2 | 1 | 5 | 2 |
| R | 34 | 36 | 35 | 29 | 30 | 14 | 14 | 22 | 13 | |
| ATM | S | 21 | 14 | 17 | 22 | 19 | 12 | 9 | 20 | 8 |
| R | 17 | 24 | 21 | 16 | 19 | 4 | 6 | 7 | 7 | |
| FEP | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| FOX | S | 22 | 15 | 15 | 24 | 17 | 13 | 11 | 17 | 9 |
| R | 16 | 23 | 23 | 14 | 21 | 3 | 4 | 10 | 6 | |
| CAZ | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| CRO | S | 35 | 34 | 36 | 35 | 33 | 14 | 11 | 25 | 13 |
| R | 3 | 4 | 2 | 3 | 5 | 2 | 4 | 2 | 2 | |
| CXM | S | 21 | 14 | 17 | 22 | 19 | 12 | 9 | 20 | 8 |
| R | 17 | 24 | 21 | 16 | 19 | 4 | 6 | 7 | 7 | |
| CEF | S | 11 | 12 | 10 | 7 | 9 | 2 | 2 | 4 | 1 |
| R | 27 | 26 | 28 | 31 | 29 | 14 | 13 | 23 | 14 | |
| CIP | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| CST | S | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| R | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 | |
| ETP | S | 30 | 29 | 33 | 31 | 28 | 14 | 13 | 22 | 11 |
| R | 8 | 9 | 5 | 7 | 10 | 2 | 2 | 5 | 4 | |
| GEN | S | 36 | 38 | 38 | 37 | 36 | 16 | 15 | 26 | 15 |
| R | 2 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | |
| IPM | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| LVX | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| MEM | S | 38 | 38 | 38 | 38 | 38 | 16 | 15 | 27 | 15 |
| R | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
| NIT | S | 21 | 14 | 17 | 22 | 19 | 12 | 9 | 20 | 8 |
| R | 17 | 24 | 21 | 16 | 19 | 4 | 6 | 7 | 7 | |
| TZP | S | 27 | 24 | 20 | 25 | 20 | 14 | 11 | 21 | 9 |
| R | 11 | 14 | 18 | 13 | 18 | 2 | 4 | 6 | 6 | |
| TGC | S | 35 | 37 | 38 | 36 | 36 | 15 | 15 | 26 | 14 |
| R | 3 | 1 | 0 | 2 | 2 | 1 | 0 | 1 | 1 | |
| SXT | S | 36 | 38 | 38 | 37 | 36 | 16 | 15 | 26 | 15 |
| R | 2 | 0 | 0 | 1 | 2 | 0 | 0 | 1 | 0 | |
YM: yeasts/molds, TAM: total aerobic mesophiles, TC: total coliforms, EC: Escherichia coli, S: Streptococci, BC: Bacillus cereus, PA: Pseudomonas aeruginosa, SA: Staphylococci aureus, LM: Listeria monocytogenes. AMK: Amikacin, AMC: Amoxicillin-clavulanate, AMP: Ampicillin, ATM: Aztreonam, FEP: Cefepime, FOX: Cefoxitin, CAZ: Ceftazidime, CRO: Ceftriaxone, CXM: Cefuroxime, CEF: Cephalothin, CIP: Ciprofloxacin, CST: Colistin, ETP: Ertapenem, GEN: Gentamicin, IPM: Imipenem, LVX: Levofloxacin, MEM: Meropenem, NIT: Nitrofurantoin, TZP: Piperacillin-tazobactam, TGC: Tigecycline, SXT: trimethoprim-sulfamethoxazole.
Table 6.
Results of heavy metals analysis in the studied samples.
| Heavy Metals | Frozen Burger | Fresh Burger | Fast-Food Restaurants |
|---|---|---|---|
| Lead (mg/100g) | <0.01 | <0.01 | <0.01 |
| Cadmium (mg/100g) | <0.002 | <0.002 | <0.002 |
| Arsenic (mg/100g) | <0.02 | <0.02 | <0.02 |
| Chromium (mg/100g) | <0.1 | <0.1 | <0.1 |
| Mercury (mg/100g) | <0.001 | <0.001 | <0.001 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Al-Thubaiti, E.H.; Shaikh Omar, A.M.; El-Omri, A.; Al-Matary, M.; Al-Mwallad, A.H.; Eldeeb, S.M. Safety of Commercially Available Beef Burger in Saudi Arabia. Coatings 2021, 11, 686. https://doi.org/10.3390/coatings11060686
AMA Style
Al-Thubaiti EH, Shaikh Omar AM, El-Omri A, Al-Matary M, Al-Mwallad AH, Eldeeb SM. Safety of Commercially Available Beef Burger in Saudi Arabia. Coatings. 2021; 11(6):686. https://doi.org/10.3390/coatings11060686
Chicago/Turabian StyleAl-Thubaiti, Eman Hillal, Abdulkader M. Shaikh Omar, Abdelfatteh El-Omri, Mohammed Al-Matary, Ali H. Al-Mwallad, and Seham Mahmoud Eldeeb. 2021. "Safety of Commercially Available Beef Burger in Saudi Arabia" Coatings 11, no. 6: 686. https://doi.org/10.3390/coatings11060686
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
