Next Article in Journal
Establishment of an In Vitro System of the Human Intestinal Microbiota: Effect of Cultivation Conditions and Influence of Three Donor Stool Samples
Next Article in Special Issue
Salmonella Bacterin Vaccination Decreases Shedding and Colonization of Salmonella Typhimurium in Pigs
Previous Article in Journal
CesL Regulates Type III Secretion Substrate Specificity of the Enteropathogenic E. coli Injectisome
Previous Article in Special Issue
Salmonella in Captive Reptiles and Their Environment—Can We Tame the Dragon?
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Characterization of Salmonella Isolates Recovered from Stages of the Processing Lines at Four Broiler Processing Plants in Trinidad and Tobago

1
School of Veterinary Medicine, Faculty of Medical Sciences, University of the West Indies, St. Augustine, Trinidad and Tobago
2
Veterinary Public Health Unit, Ministry of Health, Port of Spain, Trinidad and Tobago
3
Department of Pathobiology, Tuskegee University College of Veterinary Medicine, Tuskegee, 201 Frederick D Patterson Dr, Tuskegee, AL 36088, USA
4
Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, Onderstepoort, Pretoria 0110, South Africa
*
Author to whom correspondence should be addressed.
Microorganisms 2021, 9(5), 1048; https://doi.org/10.3390/microorganisms9051048
Submission received: 12 April 2021 / Revised: 6 May 2021 / Accepted: 10 May 2021 / Published: 13 May 2021
(This article belongs to the Special Issue Salmonella and Salmonellosis)

Abstract

:
This cross-sectional study determined the prevalence, characteristics, and risk factors for contamination of chicken with Salmonella at four operating broiler processing plants in Trinidad. Standard methods were used to isolate and characterize the Salmonella isolates. The overall prevalence of Salmonella at the four processing plants was 27.0% (107/396). The whole carcass enrichment (WCE) method yielded a statistically significantly (p = 0.0014) higher frequency of isolation (53.9%; 97/180) than the whole carcass rinse (35.0%; 63/180) and neck skin methods (42.2%; 38/90). S. enterica serotypes Enteritidis, Javiana, and Infantis were the predominant serotypes isolated accounting for 20.8%, 16.7% and 12.5%, respectively, of the serotyped isolates. Risk factors included the use of over 100 contract farmers (OR 4.4), pre-chiller (OR 2.3), addition of chlorine to chiller (OR 3.2), slaughtering sick broilers (OR 4.4), and flocks with >50% mortality. Multi-drug resistance was detected in 12.3% (14/114) of the isolates of Salmonella. Resistance was high to kanamycin (85.7%) and doxycycline (74.6%) but low to amoxicillin-clavulanic acid (2.4%) and sulphamethoxazole-trimethoprim (0.8%). The occurrence of resistant Salmonella in chickens processed at commercial broiler processing plants has implications for salmonellosis and therapeutic failure in consumers of improperly cooked contaminated chickens from these plants in the country.

1. Introduction

Salmonellosis is the third leading cause of death among food transmitted diseases [1] with an estimated global Salmonella enterocolitis incidence of 95.1 million cases [2], accounting for 50,771 deaths in 2017 [3]. In the Caribbean, Salmonella is the most common laboratory-confirmed cause of foodborne diseases since 2005 [4]. Poultry has been reported to be the main carrier of Salmonella infections to humans [5], more common than any other animal species [6]. Broiler meat is an economical source of protein and estimated to be the most widely consumed meat, globally.
The human population of the twin-island Republic of Trinidad and Tobago is 1,366,725 [7] with a reported 58.3 kg per capita poultry consumption rate; 800,000 broilers are produced weekly, of which 20% are imported [8]. Consumers purchase chicken from cottage poultry processors, where they are freshly slaughtered and from supermarkets, which offer both chilled and frozen locally processed or imported frozen chicken. Broiler processing plants are responsible for 50% of local broiler processing [9] where supermarkets and the franchised foodservice sector are supplied with chilled chickens as well as further-processed products [9].
Several studies have reported the high frequency of contamination with Salmonella of chicken meat sold at the informal and formal outlets in developed and developing countries [10,11]. It has also been reported that the processing of chicken at commercial processing plants contributes significantly to the contamination of dressed chicken carcasses with Salmonella before they reach the retail outlets [12,13]. Unhygienic carcass handling, soiled slaughter equipment [14,15], contaminated water (scalding and immersion chiller water), and waste generated from evisceration and the de-feathering processes have been implicated as major sources of Salmonella contamination during broiler processing [16,17,18]. Salmonella-free broilers leaving farms may potentially become contaminated by the pathogen during processing through contact with immersion chiller water contaminated with Salmonella originating from the positive broilers [19,20]. This can occur, should there be improper pH and chemical agents’ concentrations, as well as a failure to maintain good sanitary practices throughout processing [21].
With the increase in production and consumption of broiler meat over the years, the use, misuse, and overuse of veterinary drugs for prophylaxis, therapeutic, and growth promotion purposes [22,23] are common in countries such as Trinidad and Tobago. In the country, although regulations on the use of veterinary drugs in livestock exist, they are not routinely enforced. The increase in the isolation of Salmonella in humans, and the resistance of Salmonella strains to antimicrobial agents commonly used in food-producing animals is a major health concern [24,25]. Worldwide, of a greater concern is the emergence of multidrug-resistant (MDR) Salmonella [26], which has been implicated in foodborne outbreaks due to contaminated meat [27,28].
To isolate Salmonella from poultry processing plants, different approaches have been reported and recommended. In the European Union, the use of neck skin (NS) maceration [29] is most frequent whereas, in the United States, the U.S. Department of Agriculture Food Safety and Inspection Service (USDA-FSIS) [30] recommends the use of whole carcass rinse (WCR) method. Whilst the WCR is the most commonly used method for isolation of Salmonella in broiler carcasses [31,32,33], the whole carcass enrichment (WCE) and neck skin (NS) methods have been shown to be just as effective [34] or even more than the WCR [35]. However, the large space required for incubating whole carcasses makes the WCE method impractical for routine testing, but it is valuable for research purposes [36].
In Trinidad and Tobago and the Caribbean, there is a dearth of comprehensive up-to-date data on the role played by the commercial broiler processing plants in the contamination of processed chicken carcasses with Salmonella. The only available recent published data were from studies conducted at the outlets of cottage poultry processors (‘wet market’) where the slaughtering and retailing of dressed chicken were practiced [37] and at supermarkets where retailing of chicken from the commercial processing plants occurs [38] and the antimicrobial resistance profiles of Salmonella isolates from both sources were determined [39].
Considering the limited current information on the status and dynamics of Salmonella contamination of chicken carcasses at the commercial broiler processing plants, the present study with the following objectives was conducted: (i) to determine the frequency of isolation of Salmonella longitudinally from the different stages of processing, from pre-slaughter broilers to chilled carcasses, (ii) to evaluate the efficacy of three isolation methods for Salmonella, (iii) to identify the risk factors associated with Salmonella contamination of chicken carcasses at the plants and finally, (iv) to determine the serotypes and antimicrobial resistance profiles of the isolates of the pathogen recovered from the four plants operating in Trinidad.

2. Materials and Methods

2.1. Sampling Site

The study was conducted in Trinidad and Tobago, the twin-island Caribbean country located in the southern Caribbean, north-east of the South American country of Venezuela, northwest of Guyana, and south of Grenada in the Lesser Antilles. There are currently four commercial broiler processing plants in Trinidad. These plants process only broiler chickens and supply supermarkets and food outlets with dressed chilled and/or frozen chicken. Each processing plant packages whole dressed chickens, various packaged chicken parts (legs, thighs, breasts, wings, and mixed parts), offal (liver, gizzard), feet, and necks all of which are available for sale at their retail outlet (at the respective plant) or supplied to supermarkets or food outlets. The similarities and differences in the operations that may impact on the bacteriological quality of broilers at the four processing plants studied are shown in a flow chart (Supplementary data: S1, A–D).
The number of samples to be collected for this study was estimated using the formula [40]:
Estimated sample size for an infinite population,
n o = Z u 2 P ex   ( 1 P ex ) / d 2  
where:
n o = Estimated sample size; Zu = Degree of confidence= 1.96;
Pex = Expected prevalence = 50%; d = Desired absolute precision = 5%;
n o = [1.962 × 0.5(1 − 0.5)]/0.052 = 384.
A total of 396 samples were collected comprising swabs of pre-slaughter cloacae, pre-evisceration carcasses, post-evisceration carcasses, chilled whole chickens (dressed), and chilled chicken parts (dressed), as well as neck skins and chiller water. Sample collection was conducted during the period from January to September 2019. The total number of samples collected at each plant was determined using proportional sampling based on their throughputs. Therefore, two, four, one, and two sampling visits were made to plants A, B, C, and D, respectively. Plant A and D received chicken from their 210 and 98 contract farms, respectively, whereas Plants B and C were owned by the same parent company that controlled 32 farms. Samples were collected in individual sterile bags and bottles and transported on ice to the laboratory of the Veterinary Public Health Unit, School of Veterinary Medicine for processing within 4–6 h after collection. Standardized, pre-tested questionnaires were administered at each broiler processing plant to obtain information about demography, operational information, and risk factors for carcass contamination with Salmonella. Some of the questions were designed to elicit information on the average number of contract farmers, the average waiting period between arrival of chickens to slaughter, disposal of waste material, and source of water supply (Supplementary data: S2).

2.2. Processing of Samples Collected from Processing Plants

During each visit to the broiler processing plant the following samples were collected in sterile bottles/bags: 10 cloacal swabs, 5 pre-evisceration carcasses (post-defeathering), 5 post-evisceration carcasses, 10 neck skins, 4 immersion chiller water samples, 5 chilled whole carcasses (after removal from immersion chiller), and 5 packs of chilled chicken parts each of legs, thighs, breast, wings, and mixed parts.
The WCR method, described by the USDA-FSIS [30] for Salmonella isolation was used. Each carcass was rinsed in 430 mL of buffered peptone water (BPW) (Oxoid, Hampshire, UK), rotated for no less than 30 times and 30 mL of the rinsate was removed and incubated.
Each carcass with the remaining 400 mL BPW in the WCR process above, was incubated in accordance with the WCE method as described by Cox et al. [41] and constituted the WCE sample. Neck skin (NS) samples were processed as recommended by the Commission Regulation (EC) No 2073/2005 [42] with the following modification. Each neck skin was collected in a sterile bag from which approximately 10–15 g was aseptically excised and added to BPW in a 1:9 ratio and incubated at 37 °C for 18–24 h. Each excised neck skin was treated as one (1) sample as performed in other studies [34,43].
Each cloacal swab sample was added to 9 mL BPW and subsequently incubated [44]. During each sampling visit to the plants, 400 mL of immersion chiller water was collected four (4) times, at an interval of 1.5 h to provide representative samples of potential contamination over a 6 h period. In the laboratory, 100 mL were aseptically removed from each 400 mL sample and centrifuged at 4470× g for 20 min after which 1 mL of sediment was removed and transferred to 9 mL BPW and incubated [45].
All pre-enriched BPW samples were incubated at 37 °C for 18–24 h. Samples were then selectively enriched in 9 mL tetrathionate (TT) broth (Oxoid, Hampshire, UK) and 9 mL Rappaport-Vassiliadis Soya (RVS) broth (Oxoid, Hampshire, UK) and incubated at 37 and 42 °C, respectively.

2.3. Isolation and Identification of Salmonella

Samples enriched in selective broths were sub-cultured onto Xylose–lysine–tergitol 4 (XLT-4; Oxoid, Hampshire, UK) and Brilliant green agar (BGA; Oxoid) and incubated at 37 °C for 18–24 h. Suspected Salmonella colonies that displayed characteristic colonies on both selective agar plates were then purified on blood agar plates (Oxoid) and incubated at 37 °C for 18–24 h. Pure cultures were subjected to a panel of biochemical tests that included triple sugar iron agar, lysine iron agar, urea, citrate, methyl red, sulfide-indole-motility medium, and o-nitrophenyl-b-D-galactopyranoside (Oxoid) [39,46]. Isolates biochemically confirmed as Salmonella were then subjected to a slide agglutination test using Salmonella polyvalent antiserum (A-I & Vi, Difco, Detroit, MI). Complete confirmation and serotyping of Salmonella isolates representative of those recovered by the WCR/WCE/NS, RVS/TT, and BGA/XLT-4 methods were performed using the phase reversal technique, and the results interpreted according to the Kauffman–White scheme [47] at the Public Health Laboratory, Ministry of Health, St. Michael, Barbados. Molecular confirmation of tentatively identified Salmonella was conducted using conventional polymerase chain reaction (PCR). Initially, DNA was extracted from the Salmonella isolates by the boiling method [37,48], followed by the use of conventional PCR to detect the invA gene as described earlier [37,48]. The following primer sequences were used to amplify a 284 bp fragment of the invA gene, Forward: 5′ GTGAAATTATCGCCACGTTCGGGCAA 3′ and Reverse: 5′ TCATCGCACCGTCAAAGGAACC 3′ as described by Oliviera et al. [49].

2.4. Determination of Antimicrobial Resistance

The antimicrobial resistance of 126 Salmonella isolates recovered from the samples obtained at the four broiler processing plants was determined using the disk diffusion method according to the Clinical and Laboratory Standards Institute [50,51] guidelines. Eight antimicrobial agents commonly available in the local market and frequently used in the poultry industry in Trinidad formed the panel of antimicrobial agents. The antimicrobial agents, concentrations, and classes (Difco, Becton Dickinson, Sparks, MD, USA) used comprised the following: amoxicillin-clavulanic acid (AMC, 30 µg, β-lactam); doxycycline (DO, 30 µg, Tetracycline); ceftriaxone (CRO, 30 µg, Cephalosporin); gentamicin (CN, 10 µg, Aminoglycosides); kanamycin (K, 30 µg, Aminoglycosides); chloramphenicol (C, 30 µg, Phenicol); sulphamethoxazole–trimethoprim (SXT, 23.75 and 1.25 µg, Sulphonamides); and ciprofloxacin (CIP, 5 µg, Fluoroquinolones). The tests were performed on Mueller–Hinton agar (Difco), followed by aerobic incubation at 37 °C for 24 h. The zones of inhibition were interpreted as recommended by the disk manufacturer and Clinical and Laboratory Standards Institute [50].

2.5. Statistical Analysis of Data

Chi-square analyses were conducted using the Statistical Package for Social Sciences, SPSS (version 27, IBM Corp., Somers, NY, USA) to determine statistically significant associations in the frequency of isolation of Salmonella amongst (i) the three different sampling methods, (ii) the risk factors associated with Salmonella contamination, (iii) the types of samples collected, and iv) the plants sampled. The Fisher’s exact test was used for 2 × 2 contingency tables with expected frequencies of <5. The level of significance was set at an alpha = 0.05. Univariate analysis of associations was conducted using the Salmonella status of the sample as a binary outcome (positive or negative). The predictor variables were the average number of farmers, number of workers directly involved in processing, waiting period, the mortality rate on arrival, treatment of diseased birds, use of a pre-chiller, agents used in chiller, temperature of chiller water, and segregation of workers. Each predictor variable was tested for significant associations with the Salmonella status using the chi-square test of association. Significant variables (p < 0.05) in the univariate analysis were assessed for collinearity using the chi-square statistic and were considered collinear if p < 0.05. A forward stepwise regression model where entry of p < 0.5 and removal of p < 0.10 was used in the regression analysis. Hosmer–Lemeshow chi-square was used as a goodness of fit test. Statistical analysis was done using SPSS (version 27) at an alpha level of 0.05.

3. Results

3.1. Overview of Management and Production Data

In Trinidad, the poultry industry is vertically integrated, where each company controls its respective hatcheries, contracted farms, feed mills, and processing plant. However, because of the limited supply of broilers to the smaller integrated companies, broilers often originated from competitor farms. A summary of the management and production data on the four processing plants is shown in Table 1.

3.2. Comparison of Sampling Methods

Salmonella was isolated from 35.0%, 53.9%, and 42.2% of samples subjected to the WCR, WCE, and neck skin methods, respectively (p = 0.0013) (Figure 1). Significant differences in the frequency of isolation of Salmonella by sampling method were found in pre-evisceration carcasses (p < 0.001), post-evisceration carcasses (p < 0.001), and all samples (p < 0.001). Chilled whole carcasses subjected to the WCE method yielded a higher frequency of isolation (60%; 27/45) when compared to the WCR method (31.1%; 14/45) (p = 0.01). Selective enrichment in tetrathionate broth plated onto XLT-4 agar yielded the highest frequency of Salmonella positive samples among the three methods (p < 0.001). Overall, 8.9% (40/450), 29.8% (134/450), 1.8% (8/450), and 3.6% (16/450) of the samples were isolated on RVS/XLT-4, TT/XLT-4, RVS/BGA, and TT/BGA, respectively (p < 0.001).

3.3. Risk Factors Associated with Salmonella Contamination during Broiler Processing

The association of risk factors with the frequency of contamination of chickens processed is shown in Table 2. Of the 14 risk factors investigated, 10 (71.4%) were determined to be statistically significantly associated with the contamination with Salmonella during processing.

3.4. Multivariate Logistic Regression of Risk Factors for Isolation of Salmonella

Of the nine variables included in the initial logistic regression model, only the average number of contract farmers, the number of workers directly involved in the processing, and the waiting period were retained in the final model. Processing plants with more than 100 contract farms were significantly associated with increased odds of Salmonella isolation (OR = 8.5; χ2 = 16.968, p < 0.001) (Table 3). Similarly, plants where the waiting period between arrival and slaughter was more than 10 h were significantly associated with Salmonella isolation (OR = 2.9; χ2 = 4.072, p = 0.044). Plants, where there were more than 150 workers directly involved in processing, were included in the model but were not a significant predictor in the equation (p = 0.284). The Hosmer–Lemeshow test of goodness-of-fit test was not significant (χ2 = 0.00, p = 1), showing that the final logistic regression model fitted the data well.

3.5. Isolation from Different Broiler Processing Plants and Types of Samples

Overall, the isolation rate of Salmonella in carcasses sampled at broiler processing plants was 27.0% (107/396) (Table 4). Among all the samples collected during broiler processing, the isolation rate of Salmonella was highest in pre-evisceration carcasses (51.1%; 23/45) followed by chilled whole carcasses (44.4%; 20/45), chilled chicken parts (40.0%; 18/45), and post-evisceration carcasses (37.8%; 17/45) (Table 4). Salmonella was detected only in 2.2% (2/90) and 5.6% (2/36) cloacal swabs and immersion chiller water samples, respectively.

3.6. Serotypes of Salmonella Isolates

S. enterica serotype Enteritidis (20.8%; 15/72), Javiana (16.7%; 12/72), and Infantis (12.5%; 9/72) were the most prevalent among a total of 16 different serotypes isolated at broiler processing plants (Table 5). Serotypes Kentucky, Anatum, Schwarzengrund, and Albany were found in less than 10% of the isolates. Only one isolate each of serotypes Hindmarsh, Madjorio, Mbandaka, S. enterica subspecies Houtenae, Virchow, Weltevrden, Aberdeen, Alachua, and Ayinde were detected among all the isolates. Serotype Enteritidis was found primarily (14/15 samples: 93.3%) in chilled whole and chicken parts as well as neck skins.

3.7. Frequency of Resistance of Salmonella Isolates to Eight Antimicrobial Agents at Different Processing Plants

The prevalence of resistance to antimicrobial agents among Salmonella isolates tested was 90.5% (114/126) as resistance was exhibited to one or more of the eight antimicrobial agents tested (Figure 2). Overall, resistance was relatively high to K (85.7%) and DO (74.6%) but relatively low to SXT (0.8%), C (0.8%), and AMC (2.4%). The differences were statistically significant (p < 0.05). The overall prevalence of resistance to antimicrobial agents by Salmonella isolates was 96.7% (58/61), 97.1% (33/34), 50.0% (3/6), and 80.0% (20/25) at plant A, B, C, and D, respectively, and these differences were statistically significant (p < 0.05).

3.8. Frequency of Antimicrobial Resistance of Salmonella Isolates Based on the Type of Sample

The frequencies of resistance to antimicrobial agents (Table 6) were similar amongst the various types of samples, ranging from 86.2% to 100% in chilled chicken parts, post-evisceration carcasses, chilled whole carcasses, neck skins, pre-evisceration carcasses, chiller water, and cloacal swabs. The frequency of resistance to DO was significantly (p = 0.045) higher for isolates of Salmonella that originated from pre-evisceration carcasses (23/25, 92.0%) compared with isolates from other types of samples. The differences in the frequency of resistance were not statistically significant (p > 0.05) for Salmonella isolated from the other types of samples other than from chiller water samples.

3.9. Resistance of Salmonella Isolates Based on Serotype

Sixteen different serotypes of Salmonella were identified from the 72 isolates subjected to conventional serotyping. Serotypes Enteritidis and Javiana were the most prevalent serotypes with 60.0% (9/15) and 83.3% (10/12) exhibiting resistance to one or more agents, respectively (Table 7). All isolates (100.0%) belonging to serotypes Albany, Anatum, and Kentucky; 88.9% for Infantis, 83.3% for Javiana, and 83.3% for Schwarzengrund exhibited resistance to antimicrobial agents. Amongst the different serotypes, the differences in the resistance exhibited were only statistically significant to DO (p < 0.001).

3.10. Antimicrobial Resistance Patterns

A total of 14 (12.3%) of the 114 isolates of Salmonella exhibited multidrug resistance, i.e., resistance to antimicrobial agents belonging to three or more classes. Overall, a total of 12 different patterns were observed consisting of DO-K, which was the predominant pattern, with 54.4% isolates exhibiting the resistance pattern. Resistance to K alone was exhibited by 15 (13.2%) isolates, 12 (10.5%) isolates exhibited resistance to DO-CN-K, 8 (7.0%) exhibited resistance to DO-CRO-K, and 6 (5.3%) were resistant to DO alone. Other patterns observed ranged from 0.9% to 2.6% of resistant isolates.

4. Discussion

This is considered the first cross-sectional study conducted in the broiler processing plants in Trinidad and Tobago that documented the frequency of isolation of Salmonella along the processing lines. The study also characterized the isolates regarding their serotypes and antimicrobial resistance to currently used antimicrobial agents in the poultry industry. The food safety importance of the study cannot be underestimated because the four processing plants operational in the country supply the majority of local chickens and chicken products sold at supermarkets.
Of food safety concern, is the high level of contamination found in pre-packaged chilled whole carcasses (44.4%) and chilled chicken parts (40.0%) across the four processing plants. Salmonellosis has been reported in humans who consume inadequately cooked Salmonella-contaminated chicken meat [52,53]. Our findings agree with the prevalence of Salmonella found in chilled chicken carcasses in abattoirs elsewhere, where 48.0% [43], 45.2% [54], and 50.0% [55] were reported in the United States, China, and Brazil, respectively. These findings were higher than the 8.3% [56] and 3.75% [57] reported in Iran and the Czech Republic, respectively. It is interesting to note that the most recent study on the prevalence of Salmonella in chickens that originated from commercial processing plants in Trinidad was 8.3% [38]. The differences in the prevalence have been reported to be affected by the carriage of Salmonella during de-feathering [57], evisceration, and spray washing steps [58] as well as by contaminated chiller water [59].
The strategy used in our study which included the collection of samples from the time of reception of live chickens to the finished chilled chickens longitudinally, from the pre-evisceration samples to chilled carcasses during each visit provided evidence of statistically significant (p = 0.023) increased levels of contamination along the stages of processing. The differences in the frequencies of isolation of Salmonella in the samples between and within the four processing plants, could be due in part, to the different management, production, and risk factors at these plants. These findings were not surprising because other studies have reported progressive increases in the frequency of contamination with Salmonella during processing [60,61].
It is significant that the frequency of isolation of Salmonella from the cloacal swabs pre-slaughter across the four plants was 2.2% ranging from 0.0% to 10.0%. This is an indication that the prevalence of Salmonella was relatively low on the poultry farms from where the slaughtered birds originated. Our findings agree with the prevalence of Salmonella in cloacal swabs of broilers pre-slaughter reported in Trinidad and Tobago, 3.95% (3/76) [62]; Brazil, 7.0% (7/100) [20]; and Colombia, 12.5% (8/64) [63].
It was of epidemiological relevance to have detected that 71.4% of the 14 risk factors investigated demonstrated statistically significant association with the contamination of chicken carcasses during processing at the plants. Significantly higher frequencies of isolation of Salmonella were detected among the following factors including medium-sized plants, use of more than 100 contract farmers, employment of less than 150 workers directly involved in processing, the average mortality rate of over 0.5% in broilers on arrival at the plant, i.e., dead on arrival, the use of pre-chillers, and the use of sanitizers in chiller water, used sanitizers for general cleaning of plants, among other factors. Many of these risk factors have been documented to be associated with the isolation of Salmonella in processing plants by others [15,64,65,66,67]. Standardized sanitation protocols with surveillance to monitor the efficacy and the development of resistance is suggested. In addition, frequent training programs for processing plant workers and farmers to educate them on the current best-practices will be beneficial in reducing cross-contamination along the continuum. Interestingly, further regression analyses and the odds ratio (OR) revealed that Salmonella was 4.4 more likely (95% CI: 2.68–7.34) to be isolated from chickens in plants that received birds from more than 100 farmers. This risk could be attributed to the increased possibility of slaughtering broilers from Salmonella-infected farms. Similarly, it was detected that plants that allowed the slaughter of chickens from batches with mortality rates of over 0.5% on arrival at the plants were 2.3 times more likely (95% CI: 1.45–3.74) to lead to the isolation of Salmonella from chickens at those plants. Although the specific pathogens responsible for deaths experienced during transportation to the plant were not known, the possibility exists that Salmonella may be involved. The contamination of feathers of chickens from direct contact with feces of infected broilers shedding Salmonella and exposure to the pathogen in the transport vehicle on its way to the plant has been documented [68,69]. Similarly, the risk of contamination of chickens increased considerably by 4.4 times (95% CI: 2.68–7.34) in plants that permitted the slaughter of sick birds, albeit being processed last instead of being rejected at farms. The possibility of seeding the plant environment with pathogens, including Salmonella, is pertinent, if the cleaning of the plant is inadequate. Salmonella was isolated at a significantly higher frequency in plants that used chlorine (29.0%) than those that used hot water (11.4%). This is because Salmonella has been reported to develop resistance to sanitizers [70,71,72]. Additionally, our study noted that plants that used pre-chillers but did not add chemical agents were found to be 1.7 times more likely (95% CI: 0.94–3.02) to result in the recovery of Salmonella. The proper use of chillers and sanitizers in processing plants can therefore not be ignored [73,74].
In our study, the WCE method yielded a statistically significant higher (53.9%) frequency of isolation of Salmonella than either the WCR (35.0%) or the NS (42.2.%) methods, making it the most sensitive method for Salmonella detection as reported by others [43,75]. Berrang et al. [36] attributed this increased sensitivity to the ability of the WCE method to facilitate the proliferation of Salmonella in low quantities or those firmly attached to the skin of the chicken. However, the challenges associated with WCE method, particularly the considerably larger incubator space requirement compared with the use of WCR and NS methods, cannot be disregarded thereby making it an impractical method for routine surveillance testing but applicable as a research tool. It has been reported that the types of samples and the methods of enrichment affect their sensitivities to detect Salmonella in chickens [76,77].
The predominant serotypes of Salmonella isolated were Enteritidis, Javiana, and Infantis. These serotypes have similarly been isolated from chicken-associated samples in the country, such as chickens sampled from supermarkets that originated from broiler processing plants and outlets of cottage poultry processors [38] and chicken layers [78]. In the current study, it was found that the serotypes were detected at different frequencies from the types of samples tested in the processing plants, a finding that agrees with published reports [79,80]. Of food safety and public health, the significance is the fact that some of these predominant serotypes were determined in the Caribbean Public Health Agency (CARPHA) State of Public Health report [81], to be amongst the top 15 human Salmonella serotypes detected in the region. Similarly, the predominant serotypes in our study were also reported to be the most commonly Salmonella serotypes associated with human salmonellosis in Trinidad and Tobago between 2005–2012 [81]. It cannot be underestimated that serotype Enteritidis has globally been associated with poultry meat and eggs, and responsible for human cases and epidemics of salmonellosis [82,83].
The high prevalence of resistance (90.5%) to antimicrobial agents by the 126 isolates of Salmonella recovered from the four processing plants, has both zoonotic and therapeutic implications. It is important to have detected that the high prevalence of resistance was exhibited to antimicrobial agents routinely used in the poultry industry in the country. It has been reported that zoonotic spread of Salmonella to workers at the commercial processing plants may occur [84,85] and as well as therapeutic failure in consumers of improperly cooked chickens contaminated by antimicrobial resistant-Salmonella [80]. Similarly, a high prevalence of resistance to antimicrobial agents (100.0%) has been reported in chilled chickens from supermarkets and cottage poultry processors [39]. Although the current study was not farm-based, the prevalence of resistant Salmonella in chickens processed at the plants may be indicative of the level of resistance of Salmonella on the contract farms from where they originated. It has been documented that the misuse or over-use of antimicrobial agents by farmers may result in the development of resistance to antimicrobial agents [86]. This is a common practice particularly in developing countries, including Trinidad and Tobago, where although laws governing the type and use of antimicrobial agents for prophylaxis, growth promotion, and therapy exist, prevailing challenges limit or prevent their enforcement [87,88].
With regard to the eight antimicrobial agents tested, it was important that the overall prevalence of resistance was comparatively low (0.8–11.9%) to six (amoxicillin-clavulanic acid, ceftriaxone, gentamicin, chloramphenicol, sulphamethoxazole–trimethoprim, and ciprofloxacin) of the antimicrobial agents, while significantly higher prevalence was exhibited to doxycycline (74.6%) and kanamycin (85.7%). Furthermore, the study found that the prevalence of resistance to the antimicrobial agents varied significantly across the processing plants from where the Salmonella isolates originated. These findings reflect the differences in the types and the frequency of use of antimicrobial agents on the contract farms that supplied live broilers to the plants. The high prevalence of resistance exhibited to doxycycline and kanamycin has been documented in chickens in the country [39]. The detection of a high prevalence of resistance (60.0% to 88.9%) among the top three detected serotypes (Enteritidis, Javiana, and Infantis) may also be therapeutic significance to infected broilers or humans. Differences in the prevalence of resistance to antimicrobial agents by Salmonella have been reported to vary among serotypes of Salmonella from chickens by others [71,89]. Therefore, there is a need to monitor the use of the two antimicrobial agents on broiler farms in the country.
It is concluded that the high prevalence of Salmonella (27.0%) including antimicrobial-resistant strains (90.5%), along with the predominance of three serotypes (Enteritidis, Javiana, and Infantis) among the isolates has implications for human salmonellosis in the country. The relative risk of salmonellosis posed by consumption of under-cooked Salmonella-contaminated chicken meat from these plants needs to be emphasized. The fact that 10 of the 14 risk factors investigated were statistically significantly associated with the contamination of chicken in the processing lines along with the odds ratio (OR) generated provides critical control points where interventions may be successfully applied. Our study reveals that the WCE method, which is not used for routine surveillance of Salmonella in chickens, demonstrated its significantly higher sensitivity when compared with either the WCR or NS methods, a finding that may be indicative of the potential under-reporting of the prevalence of antimicrobial resistant Salmonella in chickens in the country. The high prevalence of antimicrobial resistance exhibited by Salmonella isolates in this study poses both zoonotic and therapeutic implications to humans exposed to infected chickens. It is imperative to control the use of antimicrobial agents on poultry farms to reduce the development of antimicrobial resistance among Salmonella.

Supplementary Materials

Available online at https://www.mdpi.com/article/10.3390/microorganisms9051048/s1: S1: Flow chart of activities that take place at the four processing plants, S2: Broiler processing plant questionnaire.

Author Contributions

Conceptualization: A.A.A. and K.G.; methodology: A.S.K., A.A.A., W.A., S.R., and K.G.; validation: A.A.A., K.G., A.S.K., and W.A.; formal analysis: K.G., A.S.K., and A.A.A.; investigation: S.R., A.S.K., and A.A.A.; resources: A.A.A., K.G., W.A., A.S.K., and S.R.; data curation: A.A.A., K.G., A.S.K., W.A., and S.R.; writing—original draft preparation: A.S.K., A.A.A., and W.A.; writing—review and editing: A.A.A., A.S.K., and W.A.; supervision: A.A.A. and K.G.; project administration: A.A.A., K.G., A.S.K., and S.R.; funding acquisition: A.A.A. All authors have read and agreed to the published version of the manuscript.

Funding

The University of the West Indies, St. Augustine Campus Research and Publication Fund Committee approved the funding for the project (Research grant #2660-457522 on 3 July 2017). The Tuskegee University, U.S.A. funded the APC.

Institutional Review Board Statement

The study was approved and conducted under terms approved by the University of the West Indies, St. Augustine Campus Research Committee (Research grant #2660-457522 on 13 April 2016). The UWI St. Augustine Campus Ethics Committee granted the project an exemption from ethical review after assessing the research proposal.

Informed Consent Statement

The investigators obtained the consent of the managers of the four processing plants before they completed the questionnaires (Supplemental data: S2) and before visits were made to the plants to collect samples by the investigators.

Data Availability Statement

All the data are contained within the article and the Supplementary Materials.

Acknowledgments

The technical assistance of Alva Marie Stewart-Johnson and Sannandan Samlal is appreciated. We also thank Joanne Singh and Shayne Ramsubeik for their assistance, as well as the processing plant managers and staff of the four processing plants who participated in the study. We also wish to thank the managers and workers at the four processing plants for facilitating visits to the plants, completion of the questionnaires, and sample collection at the processing plants.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Ferrari, R.G.; Rosario, D.K.A.; Cunha-Neto, A.; Mano, S.B.; Figueiredo, E.E.S.; Conte-Junior, C.A. Worldwide epidemiology of salmonella serovars in animal-based foods: A meta-analysis. Appl. Environ. Microbiol. 2019, 85, e00591-19. [Google Scholar] [CrossRef] [Green Version]
  2. James, S.L.; Abate, D.; Abate, K.H.; Abay, S.M.; Abbafati, C.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdela, J.; Abdelalim, A.; et al. GBD 2017 disease and injury incidence and prevalence collaborators. global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analy-sis for the global burden of disease study 2017. Lancet 2018, 392, 1789–1858. [Google Scholar] [CrossRef] [Green Version]
  3. GBD Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the global burden of disease study 2017. Lancet 2018, 392, 1736–1788. [Google Scholar] [CrossRef] [Green Version]
  4. Caribbean Public Health Agency. State of Public Health in the Caribbean Report 2017–2018 Climate and Health: Averting and Responding to an Unfolding Health Crisis; Caribbean Public Health Agency: Port of Spain, Trinidad and Tobago, 2018. [Google Scholar]
  5. Velasquez, C.; Macklin, K.; Kumar, S.; Bailey, M.; Ebner, P.; Oliver, H.; Martin-Gonzalez, F.; Singh, M. Prevalence and antimicrobial resistance patterns of salmonella isolated from poultry farms in southeastern United States. Poult. Sci. 2018, 97, 2144–2152. [Google Scholar] [CrossRef]
  6. Foley, S.L.; Nayak, R.; Hanning, I.B.; Johnson, T.J.; Han, J.; Ricke, S.C. Population dynamics of salmonella enterica serotypes in commercial egg and poultry production. Appl. Environ. Microbiol. 2011, 77, 4273–4279. [Google Scholar] [CrossRef] [Green Version]
  7. Central Statistical Office (CSO)—Government of Trinidad and Tobago. Core Statistics. Available online: https://cso.gov.tt/ (accessed on 21 February 2021).
  8. Wright, S. Poultry Production in the Caribbean. Available online: https://www.inciner8.com/blog/animal-incineration/poultry/poultry-production-in-the-caribbean/ (accessed on 21 February 2021).
  9. Johnson, R. Checking in on Caribbean Poultry: Insight from an Expert. Available online: https://www.thepoultrysite.com/news/2018/09/checking-in-on-caribbean-poultry-insight-from-an-expert (accessed on 21 February 2021).
  10. Li, Y.; Yang, Q.; Cao, C.; Cui, S.; Wu, Y.; Yang, H.; Xiao, Y.; Yang, B. Prevalence and characteristics of Salmonella isolates recovered from retail raw chickens in Shaanxi province, China. Poult. Sci. 2020, 99, 6031–6044. [Google Scholar] [CrossRef]
  11. Mokgophi, T.; Gcebe, N.; Fasina, F.; Adesiyun, A. Antimicrobial resistance profiles of salmonella isolates on chickens processed and retailed at outlets of the informal market in Gauteng province, South Africa. Pathogens 2021, 10, 273. [Google Scholar] [CrossRef]
  12. Álvarez-Fernández, E.; Alonso-Calleja, C.; García-Fernández, C.; Capita, R. Prevalence and antimicrobial resistance of Salmonella serotypes isolated from poultry in Spain: Comparison between 1993 and 2006. Int. J. Food Microbiol. 2012, 153, 281–287. [Google Scholar] [CrossRef]
  13. Lamas, A.; Fernandez-No, I.C.; Miranda, J.M.; Vazquez, B.; Cepeda, A.; Franco, C.M. Prevalence, molecular characterization and antimicrobial resistance of Salmonella serovars isolated from northwestern Spanish broiler flocks (2011–2015). Poult. Sci. 2016, 95, 2097–2105. [Google Scholar] [CrossRef]
  14. Folk, M.K. Identifying Production Facility Characteristics in Small and Very Small Meat Processing Plants with Reference to FSIS Salmonella Test Results. Ph.D. Thesis, The Ohio State University, Columbus, OH, USA, 2008. [Google Scholar]
  15. Henry, I.; Granier, S.; Courtillon, C.; Lalande, F.; Chemaly, M.; Salvat, G.; Cardinale, E. Salmonella enterica subsp. enterica isolated from chicken carcasses and environment at slaughter in Reunion Island: Prevalence, genetic characterization and antibiotic susceptibility. Trop. Anim. Health Prod. 2012, 45, 317–326. [Google Scholar] [CrossRef]
  16. Hamidi, A.; Irsigler, H.; Jaeger, D.; Muschaller, A.; Fries, R. Quantification of water as a potential risk factor for cross-contamination with salmonella, campylobacter and listeriain a poultry abattoir. Br. Poult. Sci. 2014, 55, 585–591. [Google Scholar] [CrossRef] [PubMed]
  17. Schambach, B.T.; Berrang, M.E.; Harrison, M.A.; Meinersmann, R.J. Chemical additive to enhance antimicrobial efficacy of chlorine and control cross-contamination during immersion chill of broiler carcasses. J. Food Prot. 2014, 77, 1583–1587. [Google Scholar] [CrossRef] [PubMed]
  18. Wang, H.; Shu, R.; Zhao, Y.; Zhang, Q.; Xu, X.; Zhou, G. Analysis of ERIC-PCR genomic polymorphism of salmonella isolates from chicken slaughter line. Eur. Food Res. Technol. 2014, 239, 543–548. [Google Scholar] [CrossRef]
  19. Cardoso, A.; Tessari, E. Salmonella in food safety. Biológicol 2008, 70, 11–13. (In Portuguese) [Google Scholar]
  20. Brito, D.A.P.; Sousa, G.L.A.; De Souza, Y.L.; Reis, V.; de Sousa Silva, J.R.; Reis, A.; Oba, A. Sources of paratyphoid salmonella in the production chain of broilers in the northern mesoregion of Maranhão state, Brazil. Semin. Ciências Agrárias 2019, 40, 3021–3034. [Google Scholar] [CrossRef]
  21. Xiao, X.; Wang, W.; Zhang, J.; Liao, M.; Yang, H.; Fang, W.; Li, Y. Modeling the reduction and cross-contamination of salmonella in poultry chilling process in China. Microorganisms 2019, 7, 448. [Google Scholar] [CrossRef] [Green Version]
  22. Durso, L.M.; Cook, K.L. Impacts of antibiotic use in agriculture: What are the benefits and risks? Curr. Opin. Microbiol. 2014, 19, 37–44. [Google Scholar] [CrossRef]
  23. Finley, R.L.; Collignon, P.; Larsson, D.G.J.; McEwen, S.A.; Li, X.-Z.; Gaze, W.H.; Reid-Smith, R.; Timinouni, M.; Graham, D.W.; Topp, E. The scourge of antibiotic resistance: The important role of the environment. Clin. Infect. Dis. 2013, 57, 704–710. [Google Scholar] [CrossRef] [Green Version]
  24. Ziech, R.E.; Lampugnani, C.; Perin, A.P.; Sereno, M.J.; Sfaciotte, R.A.P.; Viana, C.; Soares, V.M.; Pinto, J.P.D.A.N.; Bersot, L.D.S. Multidrug resistance and ESBL-producing salmonella spp. isolated from broiler processing plants. Braz. J. Microbiol. 2016, 47, 191–195. [Google Scholar] [CrossRef] [Green Version]
  25. Dan, S.D.; Tăbăran, A.; Mihaiu, L.; Mihaiu, M. Antibiotic susceptibility and prevalence of foodborne pathogens in poultry meat in Romania. J. Infect. Dev. Ctries. 2015, 9, 35–41. [Google Scholar] [CrossRef] [Green Version]
  26. Chon, J.-W.; Jung, H.-I.; Kuk, M.; Kim, Y.-J.; Seo, K.-H.; Kim, S.-K. High occurrence of extended-spectrum β-lactamase-producing salmonellain broiler carcasses from poultry slaughterhouses in south Korea. Foodborne Pathog. Dis. 2015, 12, 190–196. [Google Scholar] [CrossRef] [PubMed]
  27. Brown, A.C.; Grass, J.E.; Richardson, L.C.; Nisler, A.L.; Bicknese, A.S.; Gould, L.H. Antimicrobial resistance in salmonella that caused foodborne disease outbreaks: United States, 2003–2012. Epidemiol. Infect. 2017, 145, 766–774. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Bearson, B.L.; Bearson, S.M.D.; Looft, T.; Cai, G.; Shippy, D.C. Characterization of a multidrug-resistant salmonella enterica serovar heidelberg outbreak strain in commercial Turkeys: Colonization, transmission, and host transcriptional response. Front. Veter. Sci. 2017, 4, 156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. International Organization for Standardization. ISO 6579-1: 2017 Microbiology of the Food Chain. Horizontal Method for the Detection, Enumeration and Serotyping of Salmonella—Part 1: Detection of Salmonella spp.; International Organization for Standardization: Geneva, Switzerland, 2017. [Google Scholar]
  30. US Department of Agriculture Food Safety and Inspection Service. Isolation and Identification of Salmonella from Meat, Poultry, Pasteurized Egg and Siluriformes(Fish) Products and Carcass and Environmental Sponges; U.S Department of Agriculture: Washington, DC, USA, 2013.
  31. Jimenez, S.M.; Salsi, M.S.; Tiburzi, M.C.; Pirovani, M.E. A comparison between broiler chicken carcasses with and without visible faecal contamination during the slaughtering process on hazard identification of Salmonella spp. J. Appl. Microbiol. 2002, 93, 593–598. [Google Scholar] [CrossRef]
  32. Jetton, J.P.; Bilgili, S.F.; Conner, D.E.; Kotrola, J.S.; Reiber, M.A. Recovery of salmonellae from chilled broiler carcasses as affected by rinse media and enumeration method. J. Food Prot. 1992, 55, 329–332. [Google Scholar] [CrossRef]
  33. Cason, J.A.; Bailey, J.S.; Stern, N.J.; Whittemore, A.D.; Cox, N.A. Relationship between aerobic bacteria, salmonellae and Campylobacter on broiler carcasses. Poult. Sci. 1997, 76, 1037–1041. [Google Scholar] [CrossRef]
  34. Cox, N.A.; Richardson, L.J.; Cason, J.A.; Buhr, R.J.; Vizzier-Thaxton, Y.; Smith, D.P.; Fedorka-Cray, P.J.; Romanenghi, C.P.; Pereira, L.V.B.; Doyle, M.P. Comparison of neck skin excision and whole carcass rinse sampling methods for microbiological evaluation of broiler carcasses before and after immersion chilling. J. Food Prot. 2010, 73, 976–980. [Google Scholar] [CrossRef]
  35. Bourassa, D.V.; Holmes, J.M.; Cason, J.A.; Cox, N.A.; Rigsby, L.L.; Buhr, R.J. Prevalence and serogroup diversity of salmonella for broiler neck skin, whole carcass rinse, and whole carcass enrichment sampling methodologies following air or immersion chilling. J. Food Prot. 2015, 78, 1938–1944. [Google Scholar] [CrossRef]
  36. Berrang, M.E.; Cox, N.A.; Cosby, D.E.; Frye, J.; Jackson, C.R. Detection of salmonella serotypes by overnight incubation of entire broiler carcass. J. Food Saf. 2017, 37, e12298. [Google Scholar] [CrossRef]
  37. Kumar, N.; Mohan, K.; Georges, K.; Dziva, F.; Adesiyun, A.A. Prevalence, serovars, and antimicrobial resistance of salmonella in cecal samples of chickens slaughtered in pluck shops in Trinidad. J. Food Prot. 2019, 82, 1560–1567. [Google Scholar] [CrossRef]
  38. Khan, A.S.; Georges, K.; Rahaman, S.; Abdela, W.; Adesiyun, A.A. Prevalence and serotypes of Salmonella spp. on chickens sold at retail outlets in Trinidad. PLoS ONE 2018, 13, e0202108. [Google Scholar] [CrossRef] [PubMed]
  39. Khan, A.S.; Georges, K.; Rahaman, S.; Abdela, W.; Adesiyun, A.A. Antimicrobial resistance of Salmonella isolates recovered from chickens sold at retail outlets in Trinidad. J. Food Prot. 2018, 81, 1880–1889. [Google Scholar] [CrossRef]
  40. Thrusfield, M. Veterinary Epidemiology, 2nd ed.; Blackwell Publishing: Oxford, UK, 1995; p. 339. [Google Scholar]
  41. Cox, N.A.; Blankenship, L.C. Comparison of rinse sampling methods for detection of salmonellae on eviscerated broiler carcasses. J. Food Sci. 1975, 40, 1333–1334. [Google Scholar] [CrossRef]
  42. European Commission. Commission Regulation (EC) No 2073/2005 of 15 November 2005 on Microbial Criteria for Food Stuffs; L 338; European Commission: Brussels, Belgium, 2005; pp. 1–26. ISSN 1725-2555. [Google Scholar]
  43. Cox, N.A.; Buhr, R.J.; Smith, D.P.; Cason, J.A.; Rigsby, L.L.; Bourassa, D.V.; Fedorka-Cray, P.J.; Cosby, D.E. Sampling naturally contaminated broiler carcasses for salmonella by three different methods. J. Food Prot. 2014, 77, 493–495. [Google Scholar] [CrossRef]
  44. Olovo, C.V.; Reward, E.E.; Obi, S.N.; Ike, A.C. Isolation, identification and antibiogram of salmonella from cloacal swabs of free range poultry in Nsukka, Nigeria. J. Adv. Microbiol. 2019, 2019, 1–9. [Google Scholar] [CrossRef] [Green Version]
  45. Public Health England. Detection of Salmonella Species. National Infection Service, Food, Water & Environmental Microbiology Standard Method; Public Health England: London, UK, 2017; p. 13. [Google Scholar]
  46. Andrews, W. Manual of food quality control. 4. Rev. 1. Microbiological analysis. Food and drug administration. FAO Food Nutr. Pap. 1992, 14, 1–338. [Google Scholar]
  47. Grimont, P.A.D.; Weill, F.X. Antigenic Formulae of the Salmonella Serovars; World Health Organization and Institut Pasteur: Paris, France, 2007; pp. 1–166. [Google Scholar]
  48. Eijkelkamp, J.M.; Aarts, H.J.M.; van der Fels-Klerx, H.J. Suitability of rapid detection methods for salmonella in poultry slaughterhouses. Food Anal. Methods 2009, 2, 1–13. [Google Scholar] [CrossRef] [Green Version]
  49. Oliveira, S.; Santos, L.; Schuch, D.; Silva, A.; Salle, C.; Canal, C. Detection and identification of salmonellas from poultry-related samples by PCR. Veter. Microbiol. 2002, 87, 25–35. [Google Scholar] [CrossRef]
  50. Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing; CLSI supplement M100; Clinical and Laboratory Standards Institute: Wayne, PA, USA, 2017. [Google Scholar]
  51. Jacob, J.J.; Solaimalai, D.; Sethuvel, D.P.M.; Rachel, T.; Jeslin, P.; Anandan, S.; Veeraraghavan, B. A nineteen-year report of serotype and antimicrobial susceptibility of enteric non-typhoidal salmonella from humans in southern India: Changing facades of taxonomy and resistance trend. Gut Pathog. 2020, 12, 49. [Google Scholar] [CrossRef] [PubMed]
  52. Chai, S.J.; Cole, D.; Nisler, A.; Mahon, B.E. Poultry: The most common food in outbreaks with known pathogens, United States, 1998–2012. Epidemiol. Infect. 2016, 145, 316–325. [Google Scholar] [CrossRef] [Green Version]
  53. Lanier, W.A.; Hale, K.R.; Geissler, A.L.; Dewey-Mattia, D. Chicken liver–Associated outbreaks of campylobacteriosis and salmonellosis, united states, 2000–2016: Identifying opportunities for prevention. Foodborne Pathog. Dis. 2018, 15, 726–733. [Google Scholar] [CrossRef]
  54. Bai, L.; Lan, R.; Zhang, X.; Cui, S.; Xu, J.; Guo, Y.; Li, F.; Zhang, D. Prevalence of salmonella isolates from chicken and pig slaughterhouses and emergence of ciprofloxacin and cefotaxime co-resistant S. enterica serovar indiana in Henan, China. PLoS ONE 2015, 10, e0144532. [Google Scholar] [CrossRef] [Green Version]
  55. Borges, K.; Furian, T.; Souza, S.; Salle, C.; Moraes, H.; Nascimento, V. Antimicrobial resistance and molecular characterization of salmonella enterica serotypes isolated from poultry sources in Brazil. Braz. J. Poult. Sci. 2019, 21, 21. [Google Scholar] [CrossRef]
  56. Jamshidi, A.; Bassami, M.R.; Nik, S. Identification of salmonella spp. and salmonella typhimurium by a multiplex PCR-based assay from poultry carcasses in Mashhad-Iran. Int. J. Vet. Res. 2009, 3. [Google Scholar] [CrossRef]
  57. Svobodova, I.; Borilova, G.; Hulankova, R.; Steinhauserova, I. Microbiological quality of broiler carcasses during slaughter processing. Acta. Vet. 2012, 81. [Google Scholar] [CrossRef] [Green Version]
  58. Rivera-Pérez, W.; Barquero-Calvo, E.; Zamora-Sanabria, R. Salmonella contamination risk points in broiler carcasses during slaughter line processing. J. Food Prot. 2014, 77, 2031–2034. [Google Scholar] [CrossRef]
  59. Jamshidi, A.; Naghdipour, D. Contamination of water used for chilling of poultry carcasses to salmonella typhimurium and salmonella enteritidis using multiplex-PCR method. J. Vet. Res. 2011, 66, 149–152. [Google Scholar]
  60. Monte, D.F.M.; Andrigheto, C.; Ribeiro, V.B.; Landgraf, M.; Destro, M.T. Highly clonal relationship among Salmonella Enteritidis isolates in a commercial chicken production chain, Brazil. Braz. J. Microbiol. 2020, 51, 2049–2056. [Google Scholar] [CrossRef]
  61. Lin, C.-H.; Huang, J.-F.; Sun, Y.-F.; Adams, P.J.; Lin, J.-H.; Robertson, I.D. Detection of chicken carcasses contaminated with Salmonella enterica serovar in the abattoir environment of Taiwan. Int. J. Food Microbiol. 2020, 325, 108640. [Google Scholar] [CrossRef]
  62. Dookeran, M.M.; Baccus-Taylor, G.S.; Akingbala, J.O.; Tameru, B.; Lammerding, A.M. Transmission of salmonella on broiler chickens and carcasses from production to retail in trinidad and tobago. J. Agric. Biodivers. Res. 2012, 1, 78–84. [Google Scholar]
  63. Ramírez-Hernández, A.; Varón-García, A.; Sánchez-Plata, M.X. Microbiological profile of three commercial poultry processing plants in Colombia. J. Food Prot. 2017, 80, 1980–1986. [Google Scholar] [CrossRef]
  64. Yang, H.; Wang, S.; Li, Y.; Johnson, M. Predictive models for the survival/death of campylobacter jejuni and salmonella typhimurium in poultry scalding and chilling. J. Food Sci. 2002, 67, 1836–1843. [Google Scholar] [CrossRef]
  65. Mead, G.C.; Hudson, W.R.; Hinton, M.H. Use of a marker organism in poultry processing to identify sites of cross-contamination and evaluate possible control measures. Br. Poult. Sci. 1994, 35, 345–354. [Google Scholar] [CrossRef]
  66. Wu, D.; Alali, W.Q.; Harrison, M.A.; Hofacre, C.L. Prevalence of salmonella in neck skin and bone of chickens. J. Food Prot. 2014, 77, 1193–1197. [Google Scholar] [CrossRef]
  67. Mezali, L.; Mebkhout, F.; Nouichi, S.; Boudjellaba, S.; Hamdi, T.-M. Serotype diversity and slaughterhouse-level risk factors related to salmonella contamination on poultry carcasses in Algiers. J. Infect. Dev. Ctries. 2019, 13, 384–393. [Google Scholar] [CrossRef]
  68. Marin, C.; Lainez, M. Salmonella detection in feces during broiler rearing and after live transport to the slaughterhouse. Poult. Sci. 2009, 88, 1999–2005. [Google Scholar] [CrossRef] [PubMed]
  69. NidaUllah, H.; Abirami, N.; Shamila-Syuhada, A.K.; Chuah, L.-O.; Nurul, H.; Tan, T.P.; Abidin, F.W.Z.; Rusul, G. Prevalence of Salmonella in poultry processing environments in wet markets in Penang and Perlis, Malaysia. Veter. World 2017, 10, 286–292. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Joseph, B.; Otta, S.; Karunasagar, I. Biofilm formation by salmonella spp. on food contact surfaces and their sensitivity to sanitizers. Int. J. Food Microbiol. 2001, 64, 367–372. [Google Scholar] [CrossRef]
  71. Youn, S.Y.; Jeong, O.M.; Choi, B.K.; Jung, S.C.; Kang, M.S. Comparison of the antimicrobial and sanitizer resistance of salmonellaisolates from chicken slaughter processes in Korea. J. Food Sci. 2017, 82, 711–717. [Google Scholar] [CrossRef]
  72. Berghaus, R.D.; Thayer, S.G.; Law, B.F.; Mild, R.M.; Hofacre, C.L.; Singer, R.S. Enumeration of salmonella and campylobacter spp. in environmental farm samples and processing plant carcass rinses from commercial broiler chicken flocks. Appl. Environ. Microbiol. 2013, 79, 4106–4114. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Moore, A.; Nannapaneni, R.; Kiess, A.; Sharma, C.S. Evaluation of USDA approved antimicrobials on the reduction of salmonella and campylobacter in ground chicken frames and their effect on meat quality. Poult. Sci. 2017, 96, 2385–2392. [Google Scholar] [CrossRef] [PubMed]
  74. Lee, N.Y.; Park, S.Y.; Kang, I.S.; Ha, S.D. The evaluation of combined chemical and physical treatments on the reduction of resident microorganisms and salmonella typhimurium attached to chicken skin. Poult. Sci. 2014, 93, 208–215. [Google Scholar] [CrossRef]
  75. Simmons, M.; Fletcher, D.L.; Cason, J.A.; Berrang, M.E. Recovery of salmonella from retail broilers by a whole-carcass enrichment procedure. J. Food Prot. 2003, 66, 446–450. [Google Scholar] [CrossRef]
  76. Cox, N.A.; Berrang, M.E.; House, S.L.; Medina, D.; Cook, K.L.; Shariat, N.W. Population analyses reveal preenrichment method and selective enrichment media affect salmonella serovars detected on broiler carcasses. J. Food Prot. 2019, 82, 1688–1696. [Google Scholar] [CrossRef] [PubMed]
  77. Giombelli, A.; Cavani, R.; Gloria, M.B.A. Evaluation of three sampling methods for the microbiological analysis of broiler carcasses after immersion chilling. J. Food Prot. 2013, 76, 1330–1335. [Google Scholar] [CrossRef] [PubMed]
  78. Adesiyun, A.; Webb, L.; Musai, L.; Louison, B.; Joseph, G.; Stewart-Johnson, A.; Samlal, S.; Rodrigo, S. Survey of salmonella contamination in chicken layer farms in three Caribbean countries. J. Food Prot. 2014, 77, 1471–1480. [Google Scholar] [CrossRef]
  79. Adesiyun, A.A.; Ojo, M.O.; Mohammed, K.; Garcia, G. Frequency of isolation of campylobacters and salmonellae from live broilers reared by contract farmers in Trinidad. Bull. Anim. Health Prod. Afr. 1994, 42, 167–172. [Google Scholar]
  80. EFSA-ECDC: European Food Safety Authority and European Centre for Disease Prevention and Control. The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018. EFSA J. 2020, 18, e6007. [Google Scholar] [CrossRef] [Green Version]
  81. Caribbean Public Health Agency. State of Public Health in the Caribbean Region Inaugural Report; Caribbean Public Health Agency: Port of Spain, Trinidad and Tobago, 2013. [Google Scholar]
  82. Whiley, H.; Ross, K. Salmonella and eggs: From production to plate. Int. J. Environ. Res. Public Health 2015, 12, 2543–2556. [Google Scholar] [CrossRef] [Green Version]
  83. Borges, K.A.; Furian, T.Q.; De Souza, S.N.; Tondo, E.C.; Streck, A.F.; Salle, C.T.P.; Moraes, H.L.D.S.; Nascimento, V.P.D. Spread of a major clone of salmonella enterica serotype enteritidis in poultry and in salmonellosis outbreaks in southern brazil. J. Food Prot. 2016, 80, 158–163. [Google Scholar] [CrossRef]
  84. Su, C.-P.; De Perio, M.A.; Fagan, K.; Smith, M.L.; Salehi, E.; Levine, S.; Gruszynski, K.; Luckhaupt, S.E. Occupational distribution of campylobacteriosis and salmonellosis cases—Maryland, Ohio, and Virginia, 2014. Morb. Mortal. Wkly. Rep. 2017, 66, 850–853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  85. Thames, H.T.; Sukumaran, A.T. A Review of Salmonella and Campylobacter in broiler meat: Emerging challenges and food safety measures. Foods 2020, 9, 776. [Google Scholar] [CrossRef]
  86. Mellon, M.G.; Benbrook, C.; Benbrook, K.L. Hogging It: Estimates of Antimicrobial Abuse in Livestock; Union of Concerned Scientists: Cambridge, MA, USA, 2001. [Google Scholar]
  87. Masud, A.A.; Rousham, E.K.; Islam, M.A.; Alam, M.-U.; Rahman, M.; Mamun, A.A.; Sarker, S.; Asaduzzaman, M.; Unicomb, L. Drivers of antibiotic use in poultry production in Bangladesh: Dependencies and dynamics of a patron-client relationship. Front. Veter. Sci. 2020, 7. [Google Scholar] [CrossRef] [PubMed]
  88. Xu, J.; Sangthong, R.; McNeil, E.; Tang, R.; Chongsuvivatwong, V. Antibiotic use in chicken farms in northwestern China. Antimicrob. Resist. Infect. Control 2020, 9, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Romero-Barrios, P.; Deckert, A.; Parmley, E.J.; LeClair, D. Antimicrobial resistance profiles of escherichia coli and salmonella isolates in Canadian broiler chickens and their products. Foodborne Pathog. Dis. 2020, 17, 672–678. [Google Scholar] [CrossRef]
Figure 1. Recovery of Salmonella based on the method used.
Figure 1. Recovery of Salmonella based on the method used.
Microorganisms 09 01048 g001
Figure 2. Antimicrobial resistance of Salmonella isolates isolated from four processing plants. * AMC, amoxicillin-clavulanic acid (30 µg); DO, doxycycline (30 µg); CRO, ceftriaxone (30 µg); CN, gentamicin (10 µg); K, kanamycin (30 µg); C, chloramphenicol (30 µg); SXT, sulfamethoxazole-trimethoprim (23.75 and 1.25 µg); CIP, ciprofloxacin (5 µg).
Figure 2. Antimicrobial resistance of Salmonella isolates isolated from four processing plants. * AMC, amoxicillin-clavulanic acid (30 µg); DO, doxycycline (30 µg); CRO, ceftriaxone (30 µg); CN, gentamicin (10 µg); K, kanamycin (30 µg); C, chloramphenicol (30 µg); SXT, sulfamethoxazole-trimethoprim (23.75 and 1.25 µg); CIP, ciprofloxacin (5 µg).
Microorganisms 09 01048 g002
Table 1. Management and production data from four broiler processing plants in Trinidad.
Table 1. Management and production data from four broiler processing plants in Trinidad.
ParameterProcessing Plant:
Plant APlant BPlant CPlant D
Total installed capacity of the processing plant (birds/week)160,000250,000<100,000100,000
Average number of broilers processed daily32,00050,00015,00020,000
Number of days operational weekly5545
Average number of contract farmers used2103232100
Number of workers directly involved in Processing a15040075150
Number of workers indirectly involved in Processing b1001000100075
Waiting period (h) between arrival of birds at plant and slaughter2–60.5–31–312
Average mortalities (%) or broilers dead on arrival at plant0.70.020.940.50
Disposal of solid waste (fecal materials) from broilersRendered cExternal CompanyRenderedRendered
Disposal of waste-waterRiverSettling pondsSettling pondsSettling ponds
Treatment of water at the plant dNoYesNoNo
a Workers who have contact with the birds/carcass at one point during processing; b Workers involved in the management of the plant but not having contact with the birds/carcass during processing; c Rendering (in-house) to convert animal tissue waste to useable by-product meal; d All plants utilized municipal water supply as their source.
Table 2. Risk factors associated with Salmonella contamination of carcasses.
Table 2. Risk factors associated with Salmonella contamination of carcasses.
Risk FactorTotal No. Samples TestedTotal No. (%) Positive for Salmonellap-ValueOdds RatioCI (95%)
Size of plant ap < 0.001
Small445 (11.4) Ref
Medium17670 (39.8) 5.11.94–13.71
Large17632 (18.2) 1.70.63–4.74
Average number of contract farmersp < 0.001
≤100 farmers30861 (19.8) Ref
>100 farmers8846 (52.3) 4.432.68–7.34
Number of workers directly involved in processing operationp = 0.001
≤150 workers22075 (34.1) Ref
>150 workers17632 (18.2) 0.430.27–0.70
Average waiting period from arrival at plant to processingp = 0.95
≤10 h30883 (26.9) Ref
>10 h8824 (27.3) 1.010.60–1.73
Average mortality rate (%) of birds on arrival at plantp = 0.001
<0.5017632 (18.2) Ref
≥0.5022075 (34.1) 2.321.45–3.74
Handling of sick/diseased birdsp < 0.001
Rejected at farm30861 (19.8) Ref
Processed last8846 (52.3) 4.432.68–7.34
Use of pre-chillerp = 0.001
Yes22075 (34.1) Ref
No17632 (18.2) 2.321.45–3.74
Agents used in pre-chiller bp = 0.11
Citric acid + chlorine8824 (27.3) Ref
No agents added13251 (38.6) 1.670.94–3.02
Temperature of pre-chiller bp < 0.001
Room temperature8846 (52.3) Ref
10 °C445 (11.4) 0.110.04–0.33
20 °C8824 (27.3) 0.340.18–0.64
Agents used in chillerp = 0.01
Chlorine352102 (29.0) 3.181.22–8.30
No agents added c445 (11.4) Ref
Concentration of chlorine used in chiller cp = 0.79
20 ppm8824 (27.3) Ref
21–50 ppm26478 (29.5) 1.110.65–1.92
Temperature of chillerp = 0.14
<1 °C13229 (22.0) Ref
1–4 °C26478 (29.5) 1.490.91–2.43
Agents used for general cleaning of plant during processingp = 0.01
Sanitizer352102 (29.0) Ref
Hot water only445 (11.4) 0.310.12–0.82
Worker segregation dp = 0.01
Yes352102 (29.0) 3.181.22–8.30
No445 (11.4) Ref
a Based on weekly throughput, small <100,000 birds; medium 101,000–160,000 birds; large >161,000 birds. b Only 3 plants use pre-chillers. c Only 3 plants add additional chlorine to chiller water. Chlorine concentration ranged from 1–5 ppm in the municipal water supply. d Colour coding of workers was done to limit movement of workers to prevent cross contamination of dirty and clean work areas.
Table 3. Results of a multivariate logistic regression of risk factors for Salmonella isolation from carcasses sampled at broiler processing plants in Trinidad.
Table 3. Results of a multivariate logistic regression of risk factors for Salmonella isolation from carcasses sampled at broiler processing plants in Trinidad.
VariableCoef.Standard Error aChi-Squarep-ValueOdds Ratio95.0% CI
LowerUpper
>100 versus ≤100 farmers2.1450.52116.968<0.0018.5433.07823.707
>150 versus ≤150 workers0.550.5141.1470.2841.7330.6334.744
>10 h versus ≤10 h waiting period1.0730.5324.0720.0442.9251.0318.296
Constant−2.0540.47518.7<0.0010.128
a Standard error of the coefficient.
Table 4. Frequency of isolation of Salmonella by type of samples tested at each plant.
Table 4. Frequency of isolation of Salmonella by type of samples tested at each plant.
Stage in ProcessingType of Sample CollectedPlant APlant BPlant CPlant DTotal No. TestedTotal No. (%) Positive for Salmonella
No. of Samples TestedNo. (%) PositiveNo. of Samples TestedNo. (%) PositiveNo. of Samples TestedNo. (%) PositiveNo. of Samples TestedNo. (%) Positive
Pre-eviscerationCloacal swab202 (10.0)400 (0.0)100 (0.0)200 (0.0)902 (2.2)
De-feathered carcass107 (70.0)209 (45.0)51 (20.0)106 (60.0)4523 (51.1)
p-value 0.002 <0.001 0.333 0.0004 <0.001
Subtotal309 (30.0)609 (30.0)151 (6.7)306 (20.0)13525 (18.5)
Post-eviscerationEviscerated carcass107 (70.0)205 (25.0)50 (0.0)105 (50.0)4517 (37.8)
Neck skin2014 (70.0)409 (22.5)100 (0.0)202 (10.0)9025 (27.8)
p-value 0.656 0.535 NA 0.026 0.972
Subtotal3021 (70.0)6014 (23.3)150 (0.0)307 (23.3)13542 (31.1)
Chiller water and carcassesChilled water80 (0.0)162 (12.5)40 (0.0)80 (0.0)362 (5.6)
Chilled-whole carcass107 (70.0)205 (25.0)53 (60.0)105 (50.0)4520 (44.4)
Chilled-parts109 (90.0)202 (10.0)51 (20.0)106 (60.0)4518 (40.0)
p-value 0.0004 0.391 0.123 0.024 0.0003
Subtotal2816 (57.1)569 (16.1)144 (28.6)2811 (39.3)12640 (31.7)
Total 8846 (52.3)17632 (18.2)445 (11.4)8824 (27.3)396107 (27.0)
p-value <0.001
Pre-evisceration 309 (30.0)609 (30.0)151 (6.7)306 (20.0)13525 (18.5)
Post-evisceration 3021 (70.0)6014 (23.3)150 (0.0)307 (23.3)13542 (31.1)
Chiller water and carcasses 2816 (57.1)569 (16.1)144 (28.6)2811 (39.3)12640 (31.7)
p-value 0.007 0.439 0.041 0.215 0.023
Table 5. Salmonella serotypes isolated from different types of samples.
Table 5. Salmonella serotypes isolated from different types of samples.
Stage of ProcessingNo. of Samples Positive for Salmonella No. (%) a of Isolates SerotypedSerotypes (No., %)
Cloacal swabs2 0 (0.0)Not applicable
Pre-evisceration carcass23 2 (8.7)Weltevreden (1, 50.0)
Enteritidis (1, 50.0)
Post-evisceration carcass17 5 (29.4)Javiana (3, 60.0)
Virchow (1, 20.0)
Infantis (1, 20.0)
Neck skins25 25 (100.0)Javiana (7, 28.0)
Schwarzengrund (5, 20.0)
Albany (4, 16.0)
Anatum (3, 12.0)
Infantis (2, 8.0)
Group C2 b (2, 8.0)
Madjorio (1, 4.0)
Enteritidis (1, 4.0)
Chiller water2 2 (100.0)Salmonella spp. (1, 50.0)
subspecies Houtenae IV (1, 50.0)
Chilled whole carcass20 20 (100.0)Enteritidis (7, 35.0)
Infantis (4, 20.0)
Anatum (2, 10.0)
Albany (1, 5.0)
Mbandaka (1, 5.0)
Schwarzengrund (1, 5.0)
Aberdeen (1, 5.0)
Javiana (1, 5.0)
Kentucky (1, 5.0)
Ayinde (1, 5.0)
Chilled chicken parts18 18 (100.0)Enteritidis (6, 33.3)
Kentucky (6, 33.3)
Infantis (2, 11.1)
Hindmarsh (1, 5.6)
Javiana (1, 5.6)
Anatum (1, 5.6)
Alachua (1, 5.6)
Total107 72 (67.3)
a Of the number of randomly selected Salmonella serotypes from each source; b Serogroup (Group C2) could not be determined to the serotype level.
Table 6. Antimicrobial resistance of Salmonella isolated from various stages of processing.
Table 6. Antimicrobial resistance of Salmonella isolated from various stages of processing.
Stage in ProcessingType of Sample CollectedNo. of Isolates TestedNo. (%) of Isolates Resistant aNo. (%) Resistant to b:
AMCDOCROCNKCSXTCIP
Pre-eviscerationCloacal swab33 (100.0)0 (0.0)1 (33.3)0 (0.0)1 (33.3)3 (100.0)0 (0.0)0 (0.0)0 (0.0)
Defeathered carcass2524 (96.0)0 (0.0)23 (92.0)1 (4.0)2 (8.0)23 (92.0)0 (0.0)0 (0.0)0 (0.0)
p-value 1NA0.04510.2981NANANA
Subtotal2827 (96.4)0 (0.0)24 (85.7)1 (3.6)3 (10.7)26 (92.9)0 (0.0)0 (0.0)0 (0.0)
Post-eviscerationEviscerated Carcass1715 (88.2)0 (0.0)12 (70.6)0 (0.0)2 (11.8)14 (82.4)0 (0.0)0 (0.0)0 (0.0)
Neck skin2523 (92.0)0 (0.0)18 (72.0)2 (8.0)6 (24.0)21 (84.0)0 (0.0)0 (0.0)3 (12.0)
p-value 1NA10.5060.4391NANA0.260
Subtotal4238 (90.5)0 (0.0)30 (71.4)2 (4.8)8 (19.0)35 (83.3)0 (0.0)0 (0.0)3 (7.1)
Chiller water and carcasses Chiller water22 (100.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (100.0)0 (0.0)0 (0.0)1 (50.0)
Chilled-whole carcass2925 (86.2)0 (0.0)20 (69.0)4 (13.8)4 (13.8)24 (82.8)0 (0.0)0 (0.0)2 (6.9)
Chilled-parts2522 (88.0)3 (12.0)20 (80.0)2 (8.0)0 (0.0)21 (84.0)1 (4.0)1 (4.0)0 (0.0)
p-value 0.8460.1400.0500.6980.1350.8140.5320.5320.009
Subtotal5649 (87.5)3 (5.4)40 (71.4)6 (10.7)4 (7.1)47 (83.9)1 (1.8)1 (1.8)3 (5.4)
Total 126c114 (90.5)3 (2.4)94 (74.6)9 (7.1)15 (11.9)108 (85.7)1 (0.8)1 (0.8)6 (4.8)
Pre-evisceration 2827 (96.4)0 (0.0)24 (85.7)1 (3.6)3 (10.7)26 (92.9)0 (0.0)0 (0.0)0 (0.0)
Post-evisceration 4238 (90.5)0 (0.0)30 (71.4)2 (4.8)8 (19.0)35 (83.3)0 (0.0)0 (0.0)3 (7.1)
Chiller water and carcasses 5649 (87.5)3 (5.4)40 (71.4)6 (10.7)4 (7.1)47 (83.9)1 (1.8)1 (1.8)3 (5.4)
p-value 0.4220.1470.3100.3730.1930.4710.5330.5330.374
a Resistance to one or more agents tested. b AMC, amoxicillin-clavulanic acid (30 µg); DO, doxycycline (30 µg); CRO, ceftriaxone (30 µg); CN, gentamicin (10 µg); K, kanamycin (30 µg); C, chloramphenicol (30 µg); SXT, sulfamethoxazole-trimethoprim (23.75 and 1.25 µg); CIP, ciprofloxacin (5 µg). c A total of 126 isolates may have included duplicates of isolates obtained from TT/XLT-4, TT/BGA, RVS/XLT-4, and RVS/BGA media, solely of phenotypes. NA: Not applicable.
Table 7. Resistance exhibited by different serotypes isolated at four processing plants.
Table 7. Resistance exhibited by different serotypes isolated at four processing plants.
Serotype aNo. of Isolates TestedNo. (%) of Isolates Resistant bNo. (%) Isolates Resistant to c:
AMCDOCROCNKCSXTCIP
Albany55 (100.0)0 (0.0)5 (100.0)2 (40.0)0 (0.0)4 (80.0)0 (0.0)0 (0.0)0 (0.0)
Anatum66 (100.0)0 (0.0)6 (100.0)2 (33.3)0 (0.0)4 (66.7)0 (0.0)0 (0.0)0 (0.0)
Enteritidis159 (60.0)1 (6.7)1 (6.7)0 (0.0)0 (0.0)9 (60.0)1 (6.7)0 (0.0)2 (13.3)
Infantis98 (88.9)0 (0.0)6 (66.7)0 (0.0)2 (22.2)8 (88.9)0 (0.0)0 (0.0)0 (0.0)
Javiana1210 (83.3)0 (0.0)10 (83.3)0 (0.0)4 (33.3)10 (83.3)0 (0.0)0 (0.0)3 (25.0)
Kentucky77 (100.0)2 (28.6)7 (100.0)1 (14.3)0 (0.0)6 (85.7)0 (0.0)1 (14.3)0 (0.0)
Schwarzengrund65 (83.3)0 (0.0)4 (66.7)0 (0.0)2 (33.3)5 (83.3)0 (0.0)0 (0.0)0 (0.0)
p-value 0.813<0.0010.2520.2380.74510.9960.192
Total6050 (83.3)3 (5.0)39 (65.0)5 (8.3)8 (13.3)46 (76.7)1 (1.7)1 (1.7)5 (8.3)
a In addition, 2 (100.0%) of 2 Group C2 isolates exhibited resistance to one or more of the eight antimicrobial agents tested; 1 (100.0%) of 1 of the following serotypes Aberdeen, Alachua, Ayinde, Hindmarsh, Madjorio, Mbandaka, Salmonella sp. (untypable), S. Houtenae, Virchow, and Weltevreden were resistant, i.e., a total of 12 isolates. b Exhibited resistance to one or more antimicrobial agents. c AMC, amoxicillin-clavulanic acid (30 µg); DO, doxycycline (30 µg); CRO, ceftriaxone (30 µg); CN, gentamicin (10 µg); K, kanamycin (30 µg); C, chloramphenicol (30 µg); SXT, sulfamethoxazole-trimethoprim (23.75 and 1.25 µg); CIP, ciprofloxacin (5 µg).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Khan, A.S.; Georges, K.; Rahaman, S.; Abebe, W.; Adesiyun, A.A. Characterization of Salmonella Isolates Recovered from Stages of the Processing Lines at Four Broiler Processing Plants in Trinidad and Tobago. Microorganisms 2021, 9, 1048. https://doi.org/10.3390/microorganisms9051048

AMA Style

Khan AS, Georges K, Rahaman S, Abebe W, Adesiyun AA. Characterization of Salmonella Isolates Recovered from Stages of the Processing Lines at Four Broiler Processing Plants in Trinidad and Tobago. Microorganisms. 2021; 9(5):1048. https://doi.org/10.3390/microorganisms9051048

Chicago/Turabian Style

Khan, Anisa Sarah, Karla Georges, Saed Rahaman, Woubit Abebe, and Abiodun Adewale Adesiyun. 2021. "Characterization of Salmonella Isolates Recovered from Stages of the Processing Lines at Four Broiler Processing Plants in Trinidad and Tobago" Microorganisms 9, no. 5: 1048. https://doi.org/10.3390/microorganisms9051048

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop