Skip to main content
International Journal of Microbiology logoLink to International Journal of Microbiology
. 2019 Mar 3;2019:3547072. doi: 10.1155/2019/3547072

Relationship of Sanitation Parameters with Microbial Diversity and Load in Raw Meat from the Outlets of the Metropolitan City Biratnagar, Nepal

Sanjay Mahato 1,2,
PMCID: PMC6421807  PMID: 30944568

Abstract

The main aim of this study is to assess the microbial load of raw meat from outlets of Biratnagar and its relationship with several sanitation parameters. Samples were taken from meat outlets, and required microbiological procedures were followed as per guidelines. Approximately 63.6% of microbes were present in meat with poor sanitation while 36.4% were present in meat with good sanitation. Fungal contamination in poorly kept mutton was one and half times greater than chicken/mutton of good sanitation. Fungi such as Penicillium (21.3%), Mucor (16.3%), Aspergillus (15%), and Trichosporon (13.8%) were most predominant. 73.8% of meat samples contained Staphylococcus spp., 61.3% contained E. coli, 48.8% of Pseudomonas spp., and 37.5% samples contained Salmonella spp. Outlets selling both types of meat showed no significant difference in microbial types. Mean of TVC of meat is 8.2 log CFU/g. Mean TVC of mutton (7.6 log CFU/g) is lower than mean TVC of chicken/meat (8.5 log CFU/g) and differed significantly. Tiled outlets showed comparatively lower bacterial contamination than cemented outlets which was statistically significant (t = −3.16, p=0.002). With the difference among microbial type and few sanitation parameters being statistically significant, it can be suggested that outlets should be tiled (p=0.002), showcased (p=0.001), and the meat-handling employee must wear washed apron (p=0.013). Proper cleaning of water supply and use area (p ≤ 0.001) and drainage (p=0.048) maintain a good meat sanitation (p ≤ 0.001) which reduces microbial contamination significantly. To diminish microbiological load on meat sold in the Biratnagar city, standard operating methods should be practiced.

1. Introduction

According to Heinz and Hautzinger [1], the Canadian annual per capita consumption of meat increased from 10 kg in the 1960s to 26 kg in 2000 and will reach 37 kg by the year 2030. As per Ministry of Agriculture and Development of Nepal, it has annual per capita consumption of 11.1 kg. A significant portion of meat and meat products are spoiled every year [2] at the consumer, retailer, and foodservice levels which have a substantial economic and environmental impact. A significant portion of this loss is due to microbial spoilage [3]. Livestock are often found being slaughtered for their meat in dirty, foul-smelling areas. The meat distribution is found to be violating the Animal Slaughterhouse and Meat Inspection Act, 1999, Kathmandu [4].

Inadequacy of different technical operations at any stage of slaughtering such as stunning, bleeding, skinning, evisceration, and carcass splitting will result in a rigorous negative impact on the product [5]. Hygiene, storage temperature, the acidity of the meat, and the structure of the muscular tissue affect the rate of meat spoilage. Liver spoils faster than the firm muscular tissue of beef [6]. Rigor mortis affected by stress conditions during slaughtering process affects the meat quality [7, 8]. Fat, protein, minerals, carbohydrate, and water present in meat [1] degrade because of digestive enzymes, microbial spoilage, and lipid oxidation [6]. Meat has a pH of 6.2–6.8, and the meat having lower value of pH is responsible for the breakdown of proteins, providing a favorable medium for the growth of bacteria [8, 9].

Meat and meat products provide excellent growth media for bacteria, yeasts, and molds, some of which are pathogens [10]. The skin and the intestinal tract of the animal are the chief sources of these microorganisms. The composition of microflora in meat depends on various factors such as preslaughter husbandry practices (free range vs intensive rearing), age of the animal at the time of slaughtering, handling during slaughtering, evisceration and processing, temperature controls during slaughtering, processing and distribution, preservation methods, type of packaging, and handling and storage by consumer [3]. Mold species include Cladosporium, Sporotrichum, Geotrichum, Penicillium, Alternaria, and Monilia and Mucor while yeasts species include Candida spp., Cryptococcus spp., and Rhodotorula spp. [11]. Bacterial species include Pseudomonas, Acinetobacter, Morexella, Alkaligenes, Micrococcus, Streptococcus, Sarcina, Leuconostoc, Lactobacillus, Proteus, Flavobacterium, Bacillus, Clostridium, Escherichia, Campylobacter, Salmonella, Streptomyces, Shigella, Staphylococcus, Yersinia, Listeria, Acrobacter, Mycobacterium, and Bacillus [1214]. Many of these bacteria can grow in chilling temperatures.

Pseudomonas spp. are Gram-negative, nonfermentative rods, aerobic, and motile with polar flagella [10, 15] which are present everywhere including drinking water, domestic and wild animals, human beings, plants and also in a variety of foods. E. coli has been isolated worldwide from poultry meat which might be due to fecal contamination [16, 17]. Enteroinvasive, enteropathogenic, and enterotoxigenic types of E. coli can be a foremost cause of foodborne diarrhoea [18]. Transmission of Vibrio cholerae to humans occurs through ingesting contaminated water or food especially poultry products [19]. Contamination of meat by Staphylococcus species may occur during the phase of manufacturing and handling of final products [20]. Salmonella is the most incriminated pathogenic microorganisms of bacterial food poisoning especially present in poultry meat, with infection being through the handling of raw poultry carcasses and products, together with the consumption of undercooked poultry meat [21]. Shigella species have highly evolved invasive systems that cause bacillary dysentery or shigellosis [22].

The main aim of this study is to assess the microbial load of raw meat from outlets of Biratnagar and to understand its possible role in spoilage and foodborne illnesses. The study also statistically analyzes the relationship among sanitation parameters, microbial load, microbial diversity, and microbial type.

2. Materials and Methods

2.1. Study Area

This cross-sectional study was carried out in the Biratnagar city of Morang district, lying in the Terai region of Nepal from 2017 January to 2018 July. Random sampling was done to collect nonrepeated single meat samples from different meat outlets located in different places of Biratnagar. The experiments were carried out at Microbiology Laboratory of Mahendra Morang Adarsh Multiple Campus, Biratnagar. Each outlet in this study also slaughtered animals to sell meat in its outlet. In the slaughtering house, bleeding and skinning were done on the floor, and both procedures were performed by the same workers with the same knives. In the slaughtering house, hot water (80°C–90°C) was used during skinning process. Knives were not washed while cutting the different types of meat. Knives were washed only after the work used to stop for a longer period (>1 hr).

2.2. Sampling and Sample Processing

Sanitation parameters such as tiled or cemented; washing of slaughterhouse, apron, and chopping boards; uses of hand sanitizer; hygienic condition of slaughterhouse; water supply area and drainage; showcased meat; and cleanliness of slaughter personnel were selected, and on these bases, meat samples were categorized as good sanitation and poor sanitation types. Of 80 collected samples, 40 samples (20 mutton and 20 chicken) were grouped into good sanitation type and 40 samples (20 mutton and 20 chicken) were grouped into poor sanitation type.

A total of 80 meat samples collected from 40 outlets (40 chicken and 40 mutton) were processed. All the 40 outlets selected randomly were categorized as selling both kind of meat. Forty fresh samples of raw chicken meat (20 g; wing's part) and forty samples of raw mutton (20 g; thigh meat) were collected aseptically in a sterile capped plastic container from different meat shops and were transported to the laboratory in a icebox for microbial analysis within 1 hour of sampling. Sterile containers were used for each meat sample.

Twenty grams of the collected meat sample were measured and were aseptically cut into thin smaller pieces using a sterile knife, and the meat pieces were kept in a sterile conical flask containing 80 ml buffered peptone water (HiMedia, M028) and were incubated for 30 min and shaken vigorously on an interval of 5 min. Thus, a 10−1 dilution was prepared. A further dilution till 10−6 was prepared.

2.3. Isolation and Enumeration of Microbes

The rinsate was inoculated on total plate count agar by the spread plate method to enumerate TVC. Plates were incubated at 37°C for 24 hrs. For isolation of E. coli and Salmonella spp., Eosin methylene blue (EMB) agar (HiMedia, Mumbai, India) plate and Xylose Lysine Deoxycholate Agar (XLDA) (HiMedia, Mumbai, India) plate were spread with 0.1 ml inoculum from several dilutions, respectively, and incubated at 37°C for 24 hrs and consequently subcultured onto nutrient agar (HiMedia, Mumbai, India) plate to get pure culture for further identification. Similarly, Cetrimide agar plate (HiMedia, Mumbai, India), thiosulfate-citrate-bile salts-sucrose (TCBS) agar plate (HiMedia, Mumbai, India), and Mannitol salt agar (MSA) plate (HiMedia, Mumbai, India) were used for cultivation of Pseudomonas spp., Vibrio spp., and Staphylococcus spp., respectively. For fungi isolation, inoculum was spread on Sabouraud Dextrose Agar (SDA) (HiMedia, Mumbai, India) plate and incubated at 25°C–27°C for 48 hrs.

Characterization and identification of the colony isolates were achieved by initial morphological examination of the colonies in the plate (macroscopically) for colonial appearance, size, elevation, form, edge, consistency, color, odor, opacity, and pigmentation. Gram staining, capsule staining, flagellar staining, and spore staining were essentially performed on isolates from the colonies as a preliminary identification of bacteria. Fungal molds and yeasts were identified by performing lactophenol cotton blue staining [23]. The bacterial isolates were identified by cultural, physiological, morphological, and biochemical tests as stated by Bergey's Manual of Determinative Bacteriology [24]. Biochemical characterization of the bacteria was done by performing specific tests such as catalase, oxidase, TSI, indole, methyl red, Voges–Proskauer and citrate tests, carbohydrate fermentation tests, coagulase, O/F tests, and urease test [25].

2.4. Data Analysis and Statistical Tools

The data were statistically analyzed using the Statistical Package the for Social Sciences (SPSS v21) software package. Data frequencies and cross tabulations were used to summarize descriptive statistics. Tables were used for data presentation. The chi-square test was performed on the data at a level of significance of 5%. The null hypothesis was that factors of sanitation parameter did not influence the types of microbes found in meat samples. For this purpose, the Pearson chi-square value or Fisher's exact test was adopted (whichever was suitable). The independent T-test and Pearson correlation test were performed on the obtained data.

3. Results

Out of 13 target microorganisms, a total of 132 isolates (100 bacteria + 32 fungi) were identified from 40 chicken samples while 129 (92 bacteria + 37 fungi) isolates were counted in 40 mutton samples (Table 1). Only one isolate was selected from one culture plate which compounded to a total of 261 isolates from 80 meat samples. Six (5 mutton + 1 chicken) samples showed growth with single microbe while remaining samples showed growth with multimicrobial growth. Mean of number of isolate types found in meat sample was 3.26 (chicken 3.3; mutton 3.23).

Table 1.

Type of microbes isolated from chicken, mutton, and meat.

S. No. Isolates Chicken isolates Mutton isolates Total meat isolates
Number (n) Percentage (%) Number (n) Percentage (%) Number (n) Percentage (%)
1 Pseudomonas spp. 19 47.5 20 50 39 48.8
2 E. coli 25 62.5 24 60 49 61.3
3 S. aureus 21 52.5 18 45 39 48.8
4 S. epidermidis 16 40 14 35 30 37.5
5 Salmonella spp. 17 42.5 16 40 33 41.3
6 Vibrio spp. 2 5 0 0 2 2.5
7 Mucor 8 20 5 12.5 13 16.3
8 Penicillium spp. 10 25 7 17.5 17 21.3
9 Alternaria spp. 2 5 4 10 6 7.5
10 Aspergillus spp. 2 5 10 25 12 15
11 Sporotrichum spp. 3 7.5 4 10 7 8.8
12 Trichosporon spp. 7 17.5 4 10 11 13.8
13 Candida spp. 0 0 3 7.5 3 3.8
Total 132 129 261

The TVC of meat was 8.2 log CFU/g. The TVC of chicken meat ranged from 4.6 log CFU/g to 9.5 log CFU/g for all chicken meat examined (Table 2). The TVC of mutton ranged from 4.3 log CFU/g to 8.7 log CFU/g. Mean TVC of mutton 7.6 log CFU/g from outlets were lower than mean TVC of chicken meat 8.5 log CFU/g (Figures 1 and 2). There were no significant differences (p ≤ 0.05) between the TVC of mutton and chicken meat.

Table 2.

Total viable count (TVC) in chicken and mutton sample.

Chicken samples TVC of chicken (log CFU/g) Mutton samples TVC of mutton (log CFU/g)
C-1 5.26 M-1 4.48
C-2 5.40 M-2 5.04
C-3 6.46 M-3 4.28
C-4 7.40 M-4 6.26
C-5 8.70 M-5 7.54
C-6 4.83 M-6 4.61
C-7 8.32 M-7 5.18
C-8 4.65 M-8 4.57
C-9 8.34 M-9 6.51
C-10 7.20 M-10 8.28
C-11 7.11 M-11 7.34
C-12 8.61 M-12 8.53
C-13 5.32 M-13 4.58
C-14 5.68 M-14 5.57
C-15 7.04 M-15 6.91
C-16 8.81 M-16 5.46
C-17 6.71 M-17 6.04
C-18 6.20 M-18 5.93
C-19 6.96 M-19 6.26
C-20 8.40 M-20 7.04
C-21 7.58 M-21 8.40
C-22 4.61 M-22 4.49
C-23 6.76 M-23 6.48
C-24 8.81 M-24 7.04
C-25 8.65 M-25 7.32
C-26 4.95 M-26 4.53
C-27 4.88 M-27 4.54
C-28 7.04 M-28 6.65
C-29 6.34 M-29 4.54
C-30 9.40 M-30 7.95
C-31 7.89 M-31 6.04
C-32 5.76 M-32 5.32
C-33 9.46 M-33 8.65
C-34 7.79 M-34 7.04
C-35 4.83 M-35 4.54
C-36 6.78 M-36 5.71
C-37 4.67 M-37 4.49
C-38 4.72 M-38 4.52
C-39 8.45 M-39 7.00
C-40 9.46 M-40 8.48

Figure 1.

Figure 1

Total viable count in chicken.

Figure 2.

Figure 2

Total viable count in mutton.

Based on sanitation parameters (tiled or cemented; washing of slaughterhouse, apron, and chopping boards; uses of hand sanitizer; hygienic condition of slaughter house; water supply area and drainage; showcased meat; and cleanliness of slaughter personnel), meat samples were categorized as good sanitation and poor sanitation types. Out of 80 collected samples (40 mutton and 40 chicken), 40 samples (20 mutton and 20 chicken) were grouped into good sanitation type and 40 samples (20 mutton and 20 chicken) were grouped into poor sanitation type. Four (10%) of the outlets had improper washing while 12 (30%) of the outlet personnel wore unwashed apron (Table 3). Eight (20%) of the chopping box was in unwashed condition while taking the sample. Interestingly, none of the outlets washed the chopping board when chicken and mutton were alternately chopped. Neither of the meat-handling personnel used hand sanitizer. Nine (45%) of the outlet meat were kept in open and were not covered. Seventeen (42.5%) of the slaughter area had improperly cleaned water supply area, while 40% of outlets had no proper drainage facility.

Table 3.

Sanitation parameters of the meat outlets.

Outlets code no. Tiled/cemented Washing slaughter house Washing of apron Washing chopping board Washing of chopping board for different meat Use of hand sanitizer Showcased condition Water supply area Drainage Meat sanitation type
W IW W UW W UW
1 C No No C PC Yes Good
2 T No No C PC Yes Good
3 T No No C PC Yes Good
4 T No No UC IC No Poor
5 C No No C IC No Good
6 T No No C PC Yes Good
7 C No No UC IC Yes Poor
8 T No No C PC Yes Good
9 C No No UC IC No Poor
10 T No No C PC No Poor
11 C No No UC IC Yes Poor
12 C No No C PC Yes Good
13 C No No UC PC No Good
14 T No No C PC Yes Good
15 C No No UC IC Yes Poor
16 T No No UC PC Yes Poor
17 T No No C PC Yes Poor
18 C No No C IC No Good
19 T No No UC IC Yes Poor
20 C No No UC IC Yes Poor
21 C No No UC IC No Poor
22 T No No C PC Yes Good
23 C No No UC IC Yes Poor
24 T No No UC IC No Poor
25 C No No C PC Yes Good
26 T No No C PC Yes Good
27 T No No C PC Yes Good
28 T No No C PC No Poor
29 C No No UC PC No Good
30 C No No UC IC Yes Poor
31 C No No C PC Yes Good
32 C No No C IC No Good
33 C No No UC IC Yes Poor
34 C No No UC IC No Poor
35 C No No UC PC No Good
36 T No No C PC No Poor
37 T No No C PC Yes Good
38 T No No C PC Yes Good
39 T No No UC IC No Poor
40 T No No C PC No Poor

Observation during sample collection. W,  washed; IW,  improper washing; UW,  unwashed; UC,  uncovered; C,  covered; F, flies observed; PC, properly cleaned; IC,  improperly cleaned.

Out of 261 isolates, 95 (36.4%) and 166 (63.6%) microbial isolates were obtained from good sanitation and poor sanitation type meat samples, respectively (Table 3). Among 95 isolates from good sanitation, 37 bacterial and 15 fungal isolates were of chicken while 29 bacterial and 14 fungal isolates were from mutton. Among 166 isolates from poor sanitation, 63 bacterial and 17 fungal isolates were from chicken while 63 bacterial and 23 fungal isolates were from mutton.

Most prevalent bacterial contamination was of Staphylococcus spp. followed by E. coli, Pseudomonas spp., and Salmonella spp. Among 80 samples, 73.8% of meat samples contained Staphylococcus spp., 61.3% of samples contained E. coli, 48.8% of samples contained Pseudomonas spp., and 37.5% samples contained Salmonella spp. (Table 1; Figure 3). Vibrio spp. were present in only 2.5% samples. Among 69 fungal isolates, the number of Penicillium spp., Mucor, Aspergillus spp., Trichosporon spp., Sporotrichum spp., Alternaria spp., and Candida spp. were 17 (21.3%), 13 (16.3%), 12 (15%), 11 (13.8%), 7 (8.8%), 6 (7.5%), and 3 (3.8%), respectively (Table 1; Figure 4).

Figure 3.

Figure 3

Proportion of bacteria in meat samples.

Figure 4.

Figure 4

Proportion of fungi in meat samples.

From the analysis of presence of microbial isolates in meat samples against sanitation parameters, it was evident that microbial load was much higher in cemented outlets, improperly washed slaughter area, unwashed chopping box, personnel wearing unwashed apron, uncovered meat, improperly cleaned water supply area, improper drainage facility, and poorly sanitated meat. E. coli was the foremost bacteria found in most of the sanitation parameters such as improperly washed slaughter house (87.5%) when compared to properly washed (58.3%); unwashed apron (70.8%) vs washed apron (57.1%); unwashed chopping box (75%) vs washed (57.8%); showcased meat (72.2%) vs uncovered (52.3%); improper drainage (71.9%) vs proper (54.2%); cemented outlets (77.5%), improperly cleaned water supply area (85.3%), and poor sanitation meat (85%) (Tables 410). Pseudomonas spp. contamination sharply decreased with proper sanitation measures. Staphylococcal contamination inconveniently reduced/increased in proper sanitation measures taken (Tables 46). Salmonella spp. was present next to E. coli and Pseudomonas spp. in improperly washed slaughter house (50%), unwashed apron (58.3%), unwashed chopping box (62.5%), and improperly maintained drainage (62.6%). This study showed that proper washing of aforementioned parameters highly reduced its presence in meat. Vibrio spp. was barely present in samples which were specific to cemented outlets, improperly cleaned slaughter, and water supply area (Tables 46).

Table 4.

Chicken samples vs slaughterhouse/outlets sanitary conditions.

S. no. Isolates Outlets Slaughter house Apron wash Chopping box wash Showcased Water supply area Drainage Meat sanitation
Cemented (%) Tiled (%) Improperly washed (%) Properly washed (%) Unwashed (%) Washed (%) Unwashed (%) Washed (%) Uncovered (%) Covered (%) Improper cleaning (%) Proper cleaning (%) Improper (%) Proper (%) Poor (%) Good (%)
1 Pseudomonas spp. 65 30 25 50 58.3 42.9 37.5 50 72.2 27.3 70.6 30.4 50 45.8 70 25
2 E. coli 85 40 100 58.3 75 57.1 75 59.4 77.8 50 94.1 39.1 75 54.2 85 40
3 Staphylococcus aureus 50 55 25 55.6 41.7 57.1 50 53.1 77.8 31.8 58.8 47.8 68.8 41.7 65 40
4 Staphylococcus epidermidis 30 50 25 41.7 41.7 39.3 50 37.5 22.2 54.5 17.6 56.5 37.5 41.7 40 40
5 Salmonella spp. 65 20 25 44.4 41.7 42.9 62.5 37.5 55.6 31.8 52.9 34.8 56.3 33.3 50 35
6 Vibrio spp. 10 0 50 0 8.3 3.6 12.5 3.1 5.6 4.5 11.8 0 6.3 4.2 5 5
7 Mucor 40 0 25 19.4 25 17.9 0 25 33.3 9.1 35.3 8.7 18.8 20.8 30 10
8 Penicillium spp. 5 45 25 25 8.3 32.1 25 25 16.7 31.8 23.5 26.1 31.3 20.8 25 25
9 Aspergillus spp. 10 0 0 5.6 16.7 0 0 6.3 0 9.1 11.8 0 12.5 0 0 10
10 Sporotrichum spp. 15 0 0 8.3 25 0 0 9.4 16.7 0 17.6 0 6.3 8.3 15 0
11 Alternaria spp. 0 10 0 5.6 16.7 0 0 6.3 0 9.1 0 8.7 0 8.3 0 10
12 Candida spp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
13 Trichosporon spp. 20 15 75 11.1 25 14.3 12.5 18.8 16.7 18.2 23.5 13.0 12.5 20.8 15 20

Table 5.

Mutton samples vs slaughterhouse/outlets sanitary conditions.

S. no. Isolates Outlets Slaughter house Apron Wash Chopping box wash Showcased Water supply area Drainage Meat sanitation
Cemented (%) Tiled (%) Improperly washed (%) Properly washed (%) Unwashed (%) Washed (%) Unwashed (%) Washed (%) Uncovered (%) Covered (%) Improper cleaning (%) Proper cleaning (%) Improper (%) Proper (%) Poor (%) Good (%)
1 Pseudomonas spp. 65 35 50 50 58.3 46.4 62.5 46.9 66.7 36.4 76.5 30.4 56.3 45.8 75 25
2 E. coli 70 50 75 58.3 66.7 57.1 75 56.3 66.7 54.5 76.5 47.8 68.8 54.2 85 35
3 Staphylococcus aureus 40 50 25 47.2 66.7 35.7 50 43.8 55.6 36.4 58.8 34.8 43.8 45.8 60 30
4 Staphylococcus epidermidis 45 25 50 33.3 25 39.3 25 37.5 38.9 31.8 23.5 43.5 37.5 33.3 30 40
5 Salmonella spp. 50 30 75 36.1 75 25 62.5 34.4 50 31.8 70.6 17.4 75 16.7 65 15
6 Vibrio spp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
7 Mucor 10 15 0 13.9 0 17.9 0 15.6 27.8 0 29.4 0 18.8 8.3 25 0
8 Penicillium spp. 10 25 25 16.7 8.3 21.4 12.5 18.8 11.1 22.7 17.6 17.4 6.3 25 10 25
9 Aspergillus spp. 15 35 25 25 16.7 28.6 0 31.3 16.7 31.8 17.6 30.4 0 41.7 15 35
10 Sporotrichum spp. 10 10 25 8.3 0 14.3 25 6.3 11.1 9.1 11.8 8.7 12.5 8.3 20 0
11 Alternaria spp. 10 10 0 11.1 25 3.6 12.5 9.4 0 18.2 11.8 8.7 18.8 4.2 10 10
12 Candida spp. 15 0 50 2.8 25 0 0 9.4 16.7 0 17.6 0 6.3 8.3 15 0
13 Trichosporon spp. 15 5 0 11.1 25 3.6 12.5 9.4 16.7 4.5 17.6 4.3 12.5 8.3 20 0

Table 6.

Both chicken and mutton samples vs slaughterhouse/outlets sanitary conditions.

S. no. Isolates Outlets Slaughter house Apron wash Chopping box wash Showcased Water supply area Drainage Meat sanitation
Cemented (%) Tiled (%) Improperly washed (%) Properly washed (%) Unwashed (%) Washed (%) Unwashed (%) Washed (%) Uncovered (%) Covered (%) Improper cleaning (%) Proper cleaning (%) Improper (%) Proper (%) Poor (%) Good (%)
1 Pseudomonas spp. 65 32.5 37.5 50 58.3 44.6 50 48.4 69.4 31.8 73.5 30.4 53.1 45.8 72.5 25
2 E. coli 77.5 45 87.5 58.3 70.8 57.1 75 57.8 72.2 52.3 85.3 43.5 71.9 54.2 85 37.5
3 Staphylococcus aureus 45 52.5 25 51.4 54.2 46.4 50 48.4 66.7 34.1 58.8 41.3 56.3 43.8 62.5 35
4 Staphylococcus epidermidis 37.5 37.5 37.5 37.5 33.3 39.3 37.5 37.5 30.6 43.2 20.6 50 37.5 37.5 35 40
5 Salmonella spp. 57.5 25 50 40.3 58.3 33.9 62.5 35.9 52.8 31.8 61.8 26.1 65.6 25 57.5 25
6 Vibrio spp. 5 0 25 0 4.2 1.8 6.3 1.6 2.8 2.3 5.9 0 3.1 2.1 2.5 2.5
7 Mucor 25 23.1 12.5 16.7 12.5 17.9 0 20.3 30.6 4.5 32.4 4.3 18.8 14.6 27.5 5
8 Penicillium spp. 7.5 35 25 20.8 8.3 26.8 18.8 21.9 13.9 27.3 20.6 21.7 18.8 22.9 17.5 25
9 Aspergillus spp. 12.5 17.5 12.5 15.3 16.7 14.3 0 18.8 8.3 20.5 14.7 15.2 6.3 20.8 7.5 22.5
10 Sporotrichum spp. 12.5 5 12.5 8.3 12.5 7.1 12.5 7.8 13.9 4.5 14.7 4.3 9.4 8.3 17.5 0
11 Alternaria spp. 5 10 0 8.3 20.8 1.8 6.3 7.8 0 13.6 5.9 8.7 9.4 6.3 5 10
12 Candida spp. 7.5 0 25 1.4 12.5 0 0 4.7 8.3 0 8.8 0 3.1 4.2 7.5 0
13 Trichosporon spp. 17.5 10 37.5 11.1 25 8.9 12.5 14.1 16.7 11.4 20.6 8.7 12.5 14.6 17.5 10

Table 7.

The chi-square test of different microbial isolates of chicken against several sanitation parameters.

S. No. Isolates Outlets tiled/cemented Slaughterhouse wash Apron wash Chop box Wash Showcase Water supply area Drainage Meat sanitation
χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p
1 Pseudomonas spp. 4.912 0.027 0.607b 0.807 0.369 0.698b 8.021 0.005 6.320 0.012 0.067 0.796 8.12 0.004
2 E. coli 8.64 0.003 0.278b 0.477 0.686 3.259 0.071 12.61 ≤0.001 1.778 0.182 8.64 0.003
3 Staphylococcus aureus 0.1 0.752 0.331b 0.807 0.369 1b 8.386 0.004 0.474 0.491 2.824 0.093 2.506 0.113
4 Staphylococcus epidermidis 1.667 0.197 0.638b 1a 0.69b 4.310 0.038 6.155 0.013 0.069 0.792 ≤0.001 1
5 Salmonella spp. 8.286 0.004 0.624b 0.005 0.944 0.25b 2.283 0.131 1.319 0.251 2.063 0.151 0.921 0.337
6 Vibrio spp. 0.487b 0.008c 0.515b 0.364b 1b 0.174b 1b 1b
7 Mucor 0.003b 1b 0.677 0.173 0.110 0.053b 1b 0.235b
8 Penicillium spp. 8.533 0.008 1b 0.231 1a 0.464 1a 0.556 0.0 1
9 Aspergillus spp. 0.487b 1c 0.085b 1b 0.492b 0.174b 0.154b 0.487b
10 Sporotrichum spp. 0.231b 1c 0.022b 1b 0.083b 0.069b 1b 0.231b
11 Alternaria spp. 0.487b 1c 0.085b 1b 0.492b 0.499b 0.508b 0.487b
12 Candida spp.
13 Trichosporon spp. 1b 0.013b 0.410b 1a 1b 0.432b 0.681b 1b

χ 2 value denotes the Pearson chi-square value with degree of freedom (df) = 1. a25%, b50%, and c75% of cells have expected count less than 5, respectively. Tested by Fisher's exact test with the level of significance at p ≤ 0.05.

Table 8.

The chi-square test of different microbial isolates of mutton against several sanitation parameters.

S. No. Isolates Outlets tiled/cemented Slaughterhouse wash Apron wash Chop box wash Showcase Water supply area Drainage Meat sanitation
χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p
1 Pseudomonas spp. 3.6 0.058 1b 0.476 0.490 0.695b 3.636 0.057 8.286 0.004 0.417 0.519 10.0 0.002
2 E. coli 1.667 0.197 0.638b 0.729 0.439b 0.606 0.436 3.342 0.068 0.851 0.356 10.417 0.001
3 Staphylococcus aureus 0.404 0.525 0.613b 3.252 0.071 1b 1.473 0.339 2.283 0.131 0.017 0.897 3.636 0.057
4 Staphylococcus epidermidis 1.758 0.185 0.602b 0.484a 0.689a 0.218 0.641 1.710 0.191 0.073 0.787 0.44 0.507
5 Salmonella spp. 1.667 0.197 0.283b 0.005a 0.229b 1.364 0.243 11.526 0.001 13.611 ≤0.001 10.417 0.001
6 Vibrio spp.
7 Mucor 1b 1c 0.298b 0.563b 0.013b 0.009b 0.373b 0.047b
8 Penicillium spp. 0.407b 0.552b 0.652b 1a 0.427b 1b 0.210b 0.407b
9 Aspergillus spp. 2.133 0.144 1b 0.693 0.165a 0.464a 0.471a 0.003a 2.133 0.144
10 Sporotrichum spp. 1b 0.355c 0.297b 0.172b 1b 1b 1b 0.106b
11 Alternaria spp. 1b 1c 0.073b 1b 0.114b 1b 0.283b 1b
12 Candida spp. 0.231b 0.022c 0.022b 1b 0.083b 0.069b 1b 0.231b
13 Trichosporon spp. 0.605b 1c 0.073b 1b 0.310b 0.294b 1b 0.106b

χ 2 value denotes the Pearson chi-square value with degree of freedom (p)=1. a25%, b50%, and c75% of cells have expected count less than 5, respectively. Tested by Fisher's exact test with the level of significance at p ≤ 0.05.

Table 9.

The chi-square test of different microbial isolates of chicken and mutton meat (in combination) against several sanitation parameters.

S. No. Isolates Outlets type Slaughterhouse wash Apron wash Chop box wash Showcase Water supply area Drainage Meat sanitation
χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p χ 2 p
1 Pseudomonas 8.455 0.004 0.45 0.713b 1.26 0.262 0.013 0.911 11.22 0.001 14.532 ≤0.001 0.409 0.523 18.061 .000
2 E. coli 8.901 0.003 0.140b 1.327 0.249 1.593 0.207 3.32 0.068 14.403 ≤0.001 2.537 0.111 19.013 .000
3 Staphylococcus aureus 0.450 0.502 0.265b 0.403 0.526 0.013 0.911 8.410 0.004 2.402 0.121 1.201 0.273 6.054 .014
4 Staphylococcus epidermidis 0.0 1 1a 0.254 0.614 ≤0.001 1 1.347 0.246 7.216 0.007 ≤0.001 1 0.213 0.644
5 Salmonella 8.717 0.003 0.711b 4.129 0.042 3.727 0.054 3.589 0.058 10.269 0.001 13.075 .000 8.717 .003
6 Vibrio spp. 0.494b 0.009b 0.513b 0.362b 1b 0.178b 1b 1b
7 Mucor 4.501 0.034 1a 0.745 0.061 9.843 0.002 11.266 0.001 0.245 0.621 7.44 .006
8 Penicillium 9.038 0.003 0.676a 3.418 0.064 1a 2.119 0.145 0.015 0.901 0.199 0.655 0.672 0.412
9 Aspergillus 0.392 0.531 1a 0.745a 0.111a 2.282 0.131 0.004 0.949 0.11a 3.529 0.060
10 Sporotrichum 0.432b 0.536a 0.423b 0.622a 0.234b 0.129b 1b 0.012b
11 Alternaria 0.675b 1a 0.008b 1b 0.03b 1b 0.679b 0.675b
12 Candida spp. 0.241b 0.025 0.025b 1b 0.087b 0.073b 1b 0.241b
13 Trichosporon 0.949 0.330 0.075a 0.078a 1a 0.531a 0.189a 1a 0.949 0.33

χ 2 value denotes the Pearson chi-square value with degree of freedom (p)=1. a25%, b50%, and c75% of cells have expected count less than 5, respectively. Tested by Fisher's exact test with the level of significance at p ≤ 0.05.

Table 10.

Independent sample T-test of mean of different types of isolates in meat against several sanitation parameters and meat type.

Parameters/Factors Conditions N Mean S.D. S.E. T score df p CI lower CI upper
Outlets Tiled 40 2.78 1.230 0.194 −3.160 78 0.002 −1.589 −0.361
Cemented 40 3.75 1.515 0.240

Slaughter wash Wash 72 3.19 3.19 0.175 −1.259 78 0.212 −1.757 0.396
Improper Wash 8 3.88 3.88 0.350

Apron wash Wash 56 3.00 1.348 0.180 −2.547 78 0.013 −1.559 −0.191
Unwashed 24 3.88 1.541 0.315

Chopping box wash Wash 64 3.25 1.469 0.184 −0.153 78 0.879 −0.878 0.753
Unwashed 16 3.31 1.448 0.362

Showcase Covered 44 2.77 1.097 0.165 −3.564 78 0.001 −1.696 −0.480
Uncovered 36 3.86 1.624 0.271

Water supply Properly cleaned 46 2.54 1.130 0.167 −6.256 78 ≤0.001 −2.230 −1.153
Improperly cleaned 34 4.24 1.281 0.220

Drainage Proper 48 3.00 1.337 0.193 −2.013 78 0.048 −1.305 −0.007
Improper 32 3.66 1.558 0.275

Meat sanitation Good 40 2.38 0.868 0.137 −6.859 78 ≤0.001 −2.290 −1.260
Poor 40 4.15 1.388 0.219

Meat type Chicken 40 3.30 1.265 0.2 0.229 78 0.819 −0.577 0.727
Mutton 40 3.23 1.641 0.259

df, degree of Freedom. The level of significance at p ≤ 0.05.

Mucor and Penicillium were among the highly found fungal contaminants in meat samples. Improper cleaning and maintenance of water supply area (32.4%) and drainage (18.8%) and poorly kept meat (27.5%) showed high amount of Mucor which decreased sharply with proper sanitation measures (Tables 46). Surprisingly in few cases, Mucor contamination was found to be higher after proper measures such as slaughter house wash (16.7%), apron wash (17.9%), and chopping box wash (20.3%). In the same manner, Penicillium increase was observed in showcased meat (27.3%), properly cleaned water supply (21.7%), proper drainage (22.9%), and good sanitation meat (25%). Trichosporon spp. was also found in greater number next to Mucor and Penicillium.

3.1. Statistical Analysis

The chi-square test indicated that there is a strong evidence that Pseudomonas contamination was significantly dependent on types of outlet (χ2 value = 8.455, df = 1, p=0.004), showcase use (χ2 = 11.22, df = 1, p ≤ 0.001), water supply area (χ2 = 14.532, df = 1, p ≤ 0.001), and meat sanitation type (χ2 = 18.061, df = 1, p ≤ 0.001) (Table 9). E. coli contamination was significantly dependent on types of outlet (χ2 value = 8.901, df = 1, p ≤ 0.001), water supply area (χ2 = 14.403, df = 1, p ≤ 0.001), and meat sanitation type (χ2 = 19.013, df = 1, p ≤ 0.001). Staphylococcus aureus contamination was significantly dependent on showcase use (χ2 = 8.41, df = 1, p ≤ 0.004) and meat sanitation type (χ2 = 6.054, df = 1, p=0.014). Staphylococcusepidermidis was significantly dependent on water supply area (χ2 = 7.216, df = 1, p=0.007) and meat sanitation type (χ2 = 18.061, df = 1, p ≤ 0.001). Salmonella contamination was significantly dependent on types of outlet (χ2 = 8.717, df = 1, p=0.003), washing of apron (χ2 = 4.129, df = 1, p=0.042), water supply area (χ2 = 10.269, df = 1, p=0.001), drainage (χ2 = 13.075, df = 1, p ≤ 0.001), and meat sanitation type (χ2 = 8.717, df = 1, p=0.003). Vibrio spp. and several fungi in study such as Trichosporon, Aspergillus, Sporotrichum, Alternaria, and Candida were independent of any of the sanitation parameters. Mucor contamination was significantly dependent on types of outlet (χ2 = 4.501, df = 1, p=0.034), showcase use (χ2 = 9.843, df = 1, p=0.002), water supply area (χ2 = 11.266, df = 1, p=0.001), and meat sanitation type (χ2 = 7.44, df = 1, p=0.006). Penicillium contamination was significantly dependent on types of outlet (χ2 value = 9.038, df = 1, p=0.33). Tables 7 and 8 present the chi-square test of different microbial isolates of chicken and mutton meat against several sanitation parameters, respectively.

Pearson correlation between TVC of meat and the number of isolate types of meat was highly significant (r = 0.719, p ≤ 0.001). Pearson correlation between the number of isolate types of chicken and mutton was highly significant (r = 0.745, p ≤ 0.001). Pearson correlation between the TVC of chicken and mutton was highly significant (r = 0.816, p ≤ 0.001). The relationship of the number of isolates of chicken with TVC of chicken was significant (r = 0.701, p ≤ 0.001) like the number of isolates of mutton with TVC of mutton (r = 0.797, p ≤ 0.001).

The independent T-test illustrated that the mean of isolates from tiled outlet is significantly different from the cemented outlet (t = −3.160, d.f. = 78, p ≤ 0.002). Similarly, washed apron, covered meat, properly cleaned water supply area, proper drainage, and good meat sanitation showed significant difference of microbe type and number against improperly washed apron, uncovered meat, improperly cleaned water supply area, improper drainage, and bad meat sanitation, respectively (Table 10). The independent T-test proved that the mean TVC from tiled outlet is significantly different from the cemented outlet (t = −2.736, d.f. = 78, p=0.008). Similarly, covered meat, properly cleaned water supply area, and good meat sanitation showed significant difference of TVC against uncovered meat, improperly cleaned water supply area, and bad meat sanitation, respectively (Table 11). Mean TVC of chicken is significantly different from mean TVC of mutton (t = 2.43, d.f. = 78, p=0.017).

Table 11.

Independent sample T-test of mean of TVC in meat against several sanitation parameters and meat type.

Parameters/factors Conditions N Mean S.D. S.E. T score df p CI lower CI upper
Outlets Tiled 40 6.057 1.477 0.233 −2.736 78 0.008 −1.547 −0.244
Cemented 40 6.952 1.449 0.229

Slaughter wash Wash 72 6.460 1.581 0.186 −1.362 78 0.193 −1.151 0.254
Improper wash 8 6.909 0.768 0.272

Apron wash Wash 56 6.37 1.542 0.206 −1.216 78 0.228 −1.188 0.287
Unwashed 24 6.82 1.459 0.297

Chopping box wash Wash 64 6.35 1.504 0.188 −1.853 78 0.068 −1.611 0.058
Unwashed 16 7.126 1.478 0.37

Showcase Covered 44 6.048 1.5 0.226 −3.131 78 0.002 −1.662 −0.37
Uncovered 36 7.064 1.373 0.229

Water supply Properly cleaned 46 5.892 1.509 0.222 −4.934 78 ≤0.001 −2.021 −0.859
Improperly cleaned 34 7.333 1.102 0.189

Drainage Proper 48 6.262 1.589 0.229 1.773 73.1 0.72 −0.055 1.27
Improper 32 6.87 1.362 0.24

Meat sanitation Good 40 5.6 1.35 0.213 −6.62 78 ≤0.001 −2.361 −1.269
Poor 40 7.412 1.088 0.172

Meat type Chicken 40 6.91 1.562 0.247 2.43 78 0.017 0.145 1.46
Mutton 40 6.103 1.388 0.219

df, degree of Freedom. The level of significance at p ≤ 0.05.

4. Discussion

Presence of nearly equal number of isolates, i.e., 132 isolates (100 bacteria and 32 fungi) from 40 chicken samples and 129 (92 bacteria and 37 fungi) isolates from 40 mutton samples and from two different types of meat, namely, mutton and chicken from the same outlet clearly indicated the cross contamination of microbes [26]. This can be because of using same chopping board, chopping knife, and unwashed hand for both types of meat [26]. Nearly, 36.4% microbial isolates from good sanitation and 63.6% isolates from poor sanitation type meat highlight the importance of proper hygiene and sanitation parameters for reducing microbial contamination.

TVC is a broadly accepted measure of the general degree of microbial contamination and hygienic conditions of processing plants or outlets [27]. The TVC of meat was 8.2 log CFU/g. There were no significant differences (t (78) = 2.43, p ≤ 0.05) between the TVC of mutton and chicken meat. TVC of mutton and chicken (7.6 log CFU/g and 8.5 log CFU/g) was higher (6.62 log CFU/g and 7.22 log CFU/g) than the findings in Lahore, Pakistan [28], and by Selvan et al. [29] for mutton (5.35 log CFU/g) and chicken (4.52 log CFU/g).

E. coli in mutton and chicken was higher than Lahore, Pakistan [28], while much lower than Kolkata, India [30]. E. coli was the foremost bacteria found in most of the sanitation parameters such as improperly washed slaughter house, unwashed apron, unwashed chopping box, improper drainage, cemented outlets, improperly cleaned water supply area, and poor sanitation meat. E. coli contamination was significantly dependent on types of outlet (χ2 = 8.901, p ≤ 0.003), water supply area (χ2 = 14.403, p ≤ 0.001), and meat sanitation type (χ2 = 19.013, p=0.001). The high level of E. coli contamination could be due to poor handling by retailers, exposure to direct air and flies, transport vehicle used, and ineffective washing activities. A potential cause of foodborne diseases, i.e., E. coli, shows higher levels of contamination in meat which could be attributed to the fact that meat offers a rich nutrient media for microbial growth [31]. Not only as an indicator organism of sanitary quality, E. coli is also used as an index organism of pathogens. E. coli originates primarily from the intestines of birds and animals, and to a lesser extent, from workers or environment of the processing plant [32]. The growth of these organisms can be controlled by minimizing contamination of slaughtered meat from intestinal contents, following good sanitary practices, and considering time-temperature control of product at retail.

Staphylococcus aureus in chicken and mutton was 52.5% and 45% which was much higher than Kolkata, India (22% and 18%) [30], and comparatively lower than Lahore [28]. Not only Pseudomonas, but also Staphylococcus epidermidis in chicken and mutton (40% and 35%) also was higher than the study (17% and 23%) of Sharma and Chattopadhyay in 2015 [30].

Staphylococcus aureus contamination was significantly dependent on showcase use ((χ2 = 8.41, p=0.004) and meat sanitation type ((χ2 = 6.054, p=0.014) while Staphylococcus epidermidis was significantly dependent on water supply area ((χ2 = 7.216, p=0.007). Staphylococcus aureus is a normal resident of the chickens, located on the skin and feathers and in the respiratory and intestinal tracts (Bennett, 1996). Staphylococcal contamination inconveniently reduced/increased in proper sanitation measures taken. During slaughtering, Staphylococcus aureus contamination could gain entry from high poultry concentration, slaughtering and processing equipment, and business devices, through sneezing, coughing, breathing, or talking [32], and from the processes of scalding and evisceration, due to cross contamination, are responsible for increased Staphylococcus aureus contamination [20]. The load of Staphylococcus aureus in poultry and meat reflects the level of hygiene of the handler [27].

Pseudomonas spp. contamination sharply decreased with proper sanitation measures. Pseudomonas contamination was significantly dependent on types of outlet (χ2 = 8.455, p ≤ 0.004), showcase use (χ2 = 11.22, p ≤ 0.001), water supply area (χ2 = 14.532, p ≤ 0.001), and meat sanitation type (χ2 = 8.455, p=0.001). Pseudomonas spp. are recognized as major food spoilers [7], and they are psychrotrophic bacteria that easily develop in foods stored aerobically like meat, fish, milk, and dairy products [33]. Pseudomonas increases in levels from the environment to meat because the meat matrix provides more favorable conditions to grow and become the dominant population [34].

The prevalence of Salmonella spp. was 41.3% which is similar to the studies carried out in China and Colombia [35, 36]. On the contrary, the higher prevalence rate of Salmonella spp. was found in Southern Thailand (67.5%) [37]. Contamination of chicken meat with Salmonella spp. may occur during slaughtering process or evisceration [38]. It can be a cause of foodborne salmonellosis and meat spoilage [39, 40]. Salmonella spp. was present in improperly washed slaughter house, unwashed apron, unwashed chopping box, and improperly maintained drainage. Salmonella contamination was significantly dependent on types of outlet (χ2 = 8.717, p ≤ 0.003), washing of apron (χ2 = 4.129, p ≤ 0.042), water supply area (χ2 = 10.269, p ≤ 0.001), drainage (χ2 = 13.075, p=0.001), and meat sanitation type (χ2 = 8.717, p ≤ 0.003). Salmonella spp. might have contaminated the meats because of poor handling by meat sellers, contamination from the water used by the retailer in washing the produce, its exposure to direct air, and also from the tables of the retailers from which produce is displayed [41]. In addition, the size and structure of the market could also contribute to the increased incidence of Salmonella contamination. Highly populated area with compactness of sellers and consumers can upsurge microbial contamination by the skin, mouth, or nose of the handlers and consumers which might be introduced directly into the meat [42].

Vibrio spp. was absent in the mutton sample which was similar to the work done in Libya [43]. For chicken samples, the finding was very low (5%) compared to 55.5% [43]. Vibrio spp. was barely present in samples which were specific to cemented outlets, improperly cleaned slaughter, and water supply area.

The predominant mold pathogen isolated from meat was Penicillium spp. (21.3%), Mucor (16.3%), Aspergillus spp. (15%), Sporotrichum spp. (8.8%), and Alternaria spp. (7.5%) which were greater than the findings in Chennai, India [44]. The predominant yeast pathogen isolated was Trichosporon spp. (13.8%) and Candida spp. (3.8%) which were in agreement with Thanigaivel and Anandhan [44].

Molds such as Mucor and Penicillium and yeasts such as Trichosporon were highly found fungal contaminants in meat samples. Improper cleaning and maintenance of water supply area and drainage and poorly kept meat showed high amount of Mucor which decreased sharply with proper sanitation measures. Mucor contamination was significantly dependent on types of outlet (χ2 = 4.501, p ≤ 0.034), showcase use (χ2 = 9.843, p ≤ 0.002), water supply area (χ2 = 11.266, p ≤ 0.001), and meat sanitation type (χ2 = 7.44, p ≤ 0.006). Surprisingly, little Mucor contamination was found to be higher after proper measures such as slaughter house wash, apron wash, and chopping box wash. This could be better explained by the findings of Barnes et al. [45]. During slaughtering the feathers, feed and bodies of the birds, and outsides of cages have also been found to be contaminated with yeasts [46]. The air and soil of poultry breeding and rearing houses, old litter and litter containing water, wet feed, and bird droppings have been found to contain yeasts [47]. From the results, it would appear that yeasts are considerably represented in the total microbial ecology of poultry carcasses, although yeasts are rarely the direct cause for spoilage [48].

From the analysis of microbial isolates found in meat samples against sanitation parameters, it was evident that microbial load was higher in cemented outlets, improperly washed slaughter area and chopping box, meat handlers wearing unwashed apron, open meat, improperly cleaned water supply area, improper drainage facility, and poorly sanitated meat. Undoubtedly, the meat outlets in the Biratnagar city may carry high initial microbial contamination from the point of slaughtering process to the point of offering to consumers. Biomagnifications occur at all levels of handling, poor transport, and retailing conditions [49]. The mean of isolates from the tiled outlet is significantly different from the cemented outlet (t (78) = −3.16, p=0.002) which indicates that tiling of outlets is better than cemented outlets to reduce microbial load.

5. Conclusion

It is concluded that microbial load of raw meat from outlets in Biratnagar is high which insinuates its possible role in spoilage and foodborne illnesses. The exposure of meat products to unhygienic practices from the point of production to retail level increases the level of microbial contamination in the produce. To diminish microbiological load on meat carcasses sold in the Biratnagar Metropolitan City, standard operating methods should be practiced. Such methods include more stringent inspection, regular supervision and/or monitoring of hygiene practices, regular interval screening of butchers, meat sellers, and all people involved in handling of meat. In addition, properly tiled outlets, well-maintained meat chopping box, selling tables covered with nets, thoroughly cleaned and regularly sterilized knives, aprons, and all the equipment that meats encounter should be used. Further research should be done to assess the meat safety and hygiene knowledge levels of meat handlers, the bacterial load on meat at the abattoir and butchery levels.

Acknowledgments

The author is grateful to AASRA Research & Education Academy Counsel for providing a research platform and all the necessary technical support. No funding was received from any agency.

Data Availability

All the related data of this study have been included in this manuscript in the tabulated form. These data may help other researchers to replicate or analyze the result of this study.

Additional Points

Due to limitations of resource, few sanitation parameters, microbial load in outlets' environment and used apparatus, and molecular identifications of isolates could not be performed.

Conflicts of Interest

The author declares that there are no conflicts of interests regarding the publication of this paper.

References

  • 1.Heinz G., Hautzinger P. Meat Processing Technology for Small to Medium Scale Producers. Bangkok, Thailand: RAP Publication 2007/20-FAO; 2007. [Google Scholar]
  • 2.Dave D., Ghaly A. E. Meat spoilage mechanisms and preservation techniques: a critical review. American Journal of Agricultural and Biological Sciences. 2011;6(4):486–510. doi: 10.3844/ajabssp.2011.486.510. [DOI] [Google Scholar]
  • 3.Cerveny J., Meyer J. D., Hall P. A. Microbiological spoilage of meat and poultry products. In: Sperber W. H., Doyle M. P., editors. Compendium of the Microbiological Spoilage, of Foods and Beverages. Food Microbiology and Food Safety. New York, NY, USA: Springer Science and Business Media; 2009. [Google Scholar]
  • 4.Animal Slaughterhouse and Meat Inspection Act, 2055. 1999. [Google Scholar]
  • 5.Addis M. Major causes of meat spoilage and preservation techniques: a review. Food Science and Quality Management. 2015;41:101–114. [Google Scholar]
  • 6.Berkel B. M., Boogaard B. V., Heijnen C. Preservation of Fish and Meat. Wageningen, The Netherlands: Agromisa Foundation; 2004. ISBN: 90-72746-01-9. [Google Scholar]
  • 7.Marchand S., De Block J., De Jonghe V., Coorevits A., Heyndrickx M., Herman L. Biofilm formation in milk production and processing environments; influence on milk quality and safety. Comprehensive Reviews in Food Science and Food Safety. 2012;11(2):133–147. doi: 10.1111/j.1541-4337.2011.00183.x. [DOI] [Google Scholar]
  • 8.Chambers P. G., Grandin T. In: Guidelines for Humane Handling, Transport and Slaughter of Livestock. Heinz G., Srisuvan T., editors. 2001. http://www.fao.org/fileadmin/user_upload/animalwelfare/guidelines%20humane%20handling%20transport%20slaughter.pdf. [Google Scholar]
  • 9.Miller R. K. Factors affecting the quality of raw meat. In: Joseph K., John K., Ledward D., editors. Meat Processing Improving Quality. FL, USA: CRC Press; 2002. ISBN: 978-1-59124-484-4. [Google Scholar]
  • 10.Jay J. M., Loessner M. J., Golden D. A. Modern Food Microbiology. 7th. New York, NY, USA: Springer Science and Business Media; 2005. ISBN: 0387231803. [Google Scholar]
  • 11.Garcia-Lopez M. L., Prieto M., Otero A. The physiological attributes of Gram-negative bacteria associated with spoilage of meat and meat products. In: Davies A., Board R., editors. The microbiology of meat and poultry. London, UK: Blackie Academic and Professional; 1998. ISBN: 0-7514-0398-9. [Google Scholar]
  • 12.Lin M., Al-Holy M., Mousavi-Hesary M., et al. Rapid and quantitative detection of the microbial spoilage in chicken meat by diffuse reflectance spectroscopy (600-1100 nm) Letters in Applied Microbiology. 2004;39(2):148–155. doi: 10.1111/j.1472-765x.2004.01546.x. [DOI] [PubMed] [Google Scholar]
  • 13.Noori T. E., Alwan M. J. Isolation and Identification of zoonotic bacteria from poultry meat. International Journal of Advanced Research in Biological Sciences. 2016;3(8):57–66. [Google Scholar]
  • 14.Nychas G. J. E., Skandamis P. N., Tassou C. C., Koutsoumanis K. P. Meat spoilage during distribution. Meat Science. 2007;78:77–89. doi: 10.1016/j.meatsci.2007.06.020. [DOI] [PubMed] [Google Scholar]
  • 15.Adams M. R., Moss M. O. Food Microbiology. 3rd. Cambridge, UK: The Royal Society of Chemistry; 2008. [Google Scholar]
  • 16.Adeyanju G. T., Ishola O. Salmonella and Escherichia coli contamination of poultry meat from a processing plant and retail markets in Ibadan, Oyo State, Nigeria. SpringerPlus. 2014;3(1):p. 139. doi: 10.1186/2193-1801-3-139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Adetunji V. O., Isola T. O. Antibiotic resistance of Escherichia coli, Listeria and Salmonella isolates from retail meat tables in Ibadan municipal abattoir, Nigeria. African Journal of Biotechnology. 2011;10(30):5795–5799. doi: 10.3923/pjn.2011.224.228. [DOI] [Google Scholar]
  • 18.Akbar A., Anal K. A. Food safety concerns and food-borne pathogens, Salmonella, Escherichia coli and Campylobacter. FUUAST Journal of Biology. 2011;1(1):5–17. [Google Scholar]
  • 19.Faruque S. M., Nair B. G. Vibrio cholerae: Genomics and Molecular Biology. Wymondham, UK: Caister Academic; 2008. [Google Scholar]
  • 20.Shareef A. M., Mansour R. S., Ibrahim K. K. Staphylococcus aureus in commercial breeder layer flocks. Iraqi Journal of Veterinary Medicine. 2009;23:63–68. [Google Scholar]
  • 21.Panisello P. J., Rooney R., Quantick P. C., Stanwell-Smith R. Application of foodborne disease outbreak data in the development and maintenance of HACCP systems. International Journal of Food Microbiology. 2000;59(3):221–234. doi: 10.1016/s0168-1605(00)00376-7. [DOI] [PubMed] [Google Scholar]
  • 22.Taneja N., Mewara A. Shigellosis: epidemiology in India. Indian J Med Res. 2016;143(5):565–576. doi: 10.4103/0971-5916.187104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Haq I., Ashraf H., Abdullah R., Shah A. H. Isolation and screening of fungi for the biosynthesis of alpha amylase. Biotechnology. 2002;2:61–66. [Google Scholar]
  • 24.Whitman W. B., Goodfellow M., Kämpfer P., et al. Bergey’s Manual of Systematic Bacteriology. 2nd. Vol. 5. New York, NY, USA: Springer-Verlag; 2012. [Google Scholar]
  • 25.Cheesbrough M. District Laboratory Practice in Tropical Countries, Part II. 2nd. New York, NY, USA: Cambridge University Press; 2009. Biochemical tests to identify bacteria. [Google Scholar]
  • 26.Dang-Xuan S., Nguyen-Viet H., Pham-Duc P, et al. Simulating cross-contamination of cooked pork with Salmonella enterica from raw pork through home kitchen preparation in Vietnam. International Journal of Environmental Research and Public Health. 2018;15(10):p. 2324. doi: 10.3390/ijerph15102324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Cohen N., Ennaji H., Bouchrif B., Hassar M. H. Comparative study of microbiological quality of raw poultry meat at various seasons and for different slaughtering processes in Casablanca (Morocco) Journal of Applied Poultry Research. 2007;16(4):502–508. doi: 10.3382/japr.2006-00061. [DOI] [Google Scholar]
  • 28.Ahmad M. U. D., Sarwar A., Najeeb M. I, et al. Assessment of microbial load of raw meat at abattoirs and retail outlets. Journal of Animal and Plant Sciences. 2013;23(3):745–748. [Google Scholar]
  • 29.Selvan P., Narendra Babu R., Sureshkumar S., Venkataramanujam V. Microbial quality of retail meat products available in Chennai city. American Journal of Food Technology. 2007;2(1):55–59. doi: 10.3923/ajft.2007.55.59. [DOI] [Google Scholar]
  • 30.Sharma K. P., Chattopadhyay U. K. Assessment of Microbial load of raw meat Samples sold in the Open Markets of city of Kolkata. IOSR Journal of Agriculture and Veterinary Science. 2015;8(3):24–27. [Google Scholar]
  • 31.Phillips M. Analysis of Microbial Hazards related to time/temperature control of foods for safety Comprehensive Review in. Food Science and Food safety. 2003;2:33–35. [Google Scholar]
  • 32.Wabeck C. J. Microbiology of poultry meat products. In: Bell D. D., Weaver W. D., editors. Commercial Chicken Meat and Egg Production. Berlin, Germany: Springer Science & Business Media Inc.; 2002. [Google Scholar]
  • 33.Remenant B., Jaffrès E., Dousset X., Pilet M. F., Zagorec M. Bacterial spoilers of food: behavior, fitness and functional properties. Food Microbiology. 2015;45:45–53. doi: 10.1016/j.fm.2014.03.009. [DOI] [PubMed] [Google Scholar]
  • 34.Ercolini D., Casaburi A., Nasi A., et al. Different molecular types of Pseudomonas fragi have the same overall behaviour as meat spoilers. Int J Food Microbiol. 2010;142(1-2):120–131. doi: 10.1016/j.ijfoodmicro.2010.06.012. [DOI] [PubMed] [Google Scholar]
  • 35.Donado-Godoy P., Clavijo V., León M., et al. Counts, serovars, and antimicrobial resistance phenotypes of Salmonella on raw chicken meat at retail in Colombia. Journal of Food Protection. 2014;77(2):227–235. doi: 10.4315/0362-028x.jfp-13-276. [DOI] [PubMed] [Google Scholar]
  • 36.Yang B., Qu D., Zhang X., et al. Prevalence and characterization of Salmonella serovars in retail meats of marketplace in Shaanxi, China. International Journal of Food Microbiology. 2010;141(1-2):63–72. doi: 10.1016/j.ijfoodmicro.2010.04.015. [DOI] [PubMed] [Google Scholar]
  • 37.Lertworapreecha M., Sutthimusik S., Tontikapong K. Antimicrobial resistance in Salmonella enterica isolated from pork, chicken, and vegetables in southern Thailand. Jundishapur Journal of Microbiology. 2012;6(1):36–41. doi: 10.5812/jjm.4312. [DOI] [Google Scholar]
  • 38.Rouger A., Tresse O., Zagorec M. Bacterial contaminants of poultry meat: sources, species, and dynamics. Microorganisms. 2017;5(3):p. 50. doi: 10.3390/microorganisms5030050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Kim M. S., Lim T. H., Jang J. H., et al. Prevalence and antimicrobial resistance of Salmonella species isolated from chicken meats produced by different integrated broiler operations in Korea. Poultry Science. 2012;91(9):2370–2375. doi: 10.3382/ps.2012-02357. [DOI] [PubMed] [Google Scholar]
  • 40.Noori A. L., Al Ghamdi A., Ansari M. J., Al-Attal Y., Al-Mubarak A., Salom K. Differences in composition of honey samples and their impact on the antimicrobial activities against drug multiresistant bacteria and pathogenic fungi. Archives of Medical Research. 2013;44(4):307–316. doi: 10.1016/j.arcmed.2013.04.009. [DOI] [PubMed] [Google Scholar]
  • 41.Antwi-Agyei P., Maalekuu B. K. Determination of microbial contamination in meat and fish products sold in the Kumasi metropolis (A Case Study of Kumasi central market and the Bantama market) Merit Research Journal of Agricultural Science and Soil Sciences. 2014;2(3):38–46. [Google Scholar]
  • 42.Schroeder C. M., Naugle A. L., Schlosser W. D., Hogue A. T., Angulo F. J., Rose J. S. Estimate of illnesses from Salmonella enteritidis in eggs, United States, 2000. Emerging Infectious Diseases. 2005;8(10):2385–2388. doi: 10.3201/eid1101.040401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Azwai S. M., Alfallani E. A., Abolghait S. K., et al. Isolation and molecular identification of Vibrio spp. by sequencing of 16S rDNA from seafood, meat and meat products in Libya. Open Veterinary Journal. 2016;6(1):36–43. doi: 10.4314/ovj.v6i1.6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Thanigaivel G., Anandhan A. S. Isolation and characterization of microorganisms from raw meat obtained from different market places in and around Chennai. Journal of Pharmaceutical, Chemical and Biological Sciences. 2015;3(2):295–301. [Google Scholar]
  • 45.Hossain M., Hoda N., Hossen M. J., Hasan M. M., Rahman S. M. E., Kabir S. M. L. Assessment of bacterial load of poultry meat used at dining hall of Bangladesh Agricultural University campus. Asian Journal of Medical and Biological Research. 2015;1(1):9–16. doi: 10.3329/ajmbr.v1i1.25492. [DOI] [Google Scholar]
  • 46.Diasty E. M. E., Ibrahim M. A. E. H., Khalafawy G. K. E. Isolation and molecular characterization of medically important yeasts isolated from poultry slaughterhouses and workers. Pakistan Journal of Zoology. 2017;49(2):609–614. [Google Scholar]
  • 47.Dunlop M. W., Moss A. F., Groves P. J., Wilkinson S. J., Stuetz R. M., Selle P. H. The multidimensional causal factors of ‘wet litter’ in chicken meat production. Science of the Total Environment. 2016;562:766–776. doi: 10.1016/j.scitotenv.2016.03.147. [DOI] [PubMed] [Google Scholar]
  • 48.Rawat S. Food spoilage: microorganisms and their prevention. Asian Journal of Plant Science and Research. 2015;5(4):47–56. [Google Scholar]
  • 49.Shareef A. M., Farag R. A., Al-Ruthwani E. K. Evaluation of bacterial load of frozen chicken thighs in Mosul markets. Iraqi Journal of Veterinary Sciences. 2012;26(2):63–69. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

All the related data of this study have been included in this manuscript in the tabulated form. These data may help other researchers to replicate or analyze the result of this study.


Articles from International Journal of Microbiology are provided here courtesy of Wiley

RESOURCES