Food-Borne Intestinal Bacterial Pathogens

Bezirtzoglou, Eugenia; Maipa, V.; Voidarou, C.; Tsiotsias, Arsenis; Papapetropoulou, M.

doi:10.3402/mehd.v12i2.8073

Cited by 12 publications

(15 citation statements)

References 25 publications

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“…Foods hold microbial loads, the composition of which varies highly. Microorganisms originate from the commensal microflora of raw materials but are also introduced during animal slaughtering and food harvesting, processing, storage, and distribution [8,9]. In most cases, the food is consumed without problematic issues and secondary health effects [9].…”

Section: Microorganisms and Foodmentioning

confidence: 99%

“…Nevertheless, food is usually consumed without major health consequences ensuing. However, occasionally, microorganisms show their presence by spoiling food or causing foodborne-related diseases in humans [9,10].…”

Section: Microorganisms and Foodmentioning

confidence: 99%

“…It is worth mentioning that some microorganisms are capable of transforming foods beneficially; this is called food fermentation [9,10]. Foods derived after microbial fermentation seem to be beneficial to human health, in particular when lactic acid is present.…”

Section: Microorganisms and Foodmentioning

confidence: 99%

“…Fecal contamination of foods and waters from humans [7] or animals [3] is another possible source of food contamination, as well as untreated water supplies, flies, and human fingers. In this way, food that has been inadequately cooked, refrigerated, or stored may be heavily infected by microorganisms [9].…”

Section: Microorganisms and Foodmentioning

confidence: 99%

“…Two main categories of food-related diseases are (a) foodborne infections and (b) foodborne intoxications [2,9].…”

Section: Microorganisms and Foodmentioning

confidence: 99%

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Predictive Modeling of Microbial Behavior in Food

STAVROPOULOU

Bezirtzoglou

2019

Foods

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Microorganisms can contaminate food, thus causing food spoilage and health risks when the food is consumed. Foods are not sterile; they have a natural flora and a transient flora reflecting their environment. To ensure food is safe, we must destroy these microorganisms or prevent their growth. Recurring hazards due to lapses in the handling, processing, and distribution of foods cannot be solved by obsolete methods and inadequate proposals. They require positive approach and resolution through the pooling of accumulated knowledge. As the industrial domain evolves rapidly and we are faced with pressures to continually improve both products and processes, a considerable competitive advantage can be gained by the introduction of predictive modeling in the food industry. Research and development capital concerns of the industry have been preserved by investigating the plethora of factors able to react on the final product. The presence of microorganisms in foods is critical for the quality of the food. However, microbial behavior is closely related to the properties of food itself such as water activity, pH, storage conditions, temperature, and relative humidity. The effect of these factors together contributing to permitting growth of microorganisms in foods can be predicted by mathematical modeling issued from quantitative studies on microbial populations. The use of predictive models permits us to evaluate shifts in microbial numbers in foods from harvesting to production, thus having a permanent and objective evaluation of the involving parameters. In this vein, predictive microbiology is the study of the microbial behavior in relation to certain environmental conditions, which assure food quality and safety. Microbial responses are evaluated through developed mathematical models, which must be validated for the specific case. As a result, predictive microbiology modeling is a useful tool to be applied for quantitative risk assessment. Herein, we review the predictive models that have been adapted for improvement of the food industry chain through a built virtual prototype of the final product or a process reflecting real-world conditions. It is then expected that predictive models are, nowadays, a useful and valuable tool in research as well as in industrial food conservation processes.

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Section: Microorganisms and Foodmentioning

confidence: 99%

Section: Microorganisms and Foodmentioning

confidence: 99%

Section: Microorganisms and Foodmentioning

confidence: 99%

Section: Microorganisms and Foodmentioning

confidence: 99%

“…Two main categories of food-related diseases are (a) foodborne infections and (b) foodborne intoxications [2,9].…”

Section: Microorganisms and Foodmentioning

confidence: 99%

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Predictive Modeling of Microbial Behavior in Food

STAVROPOULOU

Bezirtzoglou

2019

Foods

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Predictive Modeling for Spoilage Microorganisms

Pınarlı,

Tarlak

2023

Methods and Protocols in Food Science

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Evaluation of sanitary risks associated with the consumption of street food in the city of Yaoundé (Cameroon): case of braised fish from Mvog-Ada, Ngoa Ekélé, Simbock, Ahala and Olézoa

Maffouo

Mouafo

Mouokeu

et al. 2021

Heliyon

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An investigation was performed to evaluate the braising fish practices and the level of hygiene of the sellers in the city of Yaoundé. Thereafter, five braised carp samples were collected from each of the five selected sites and their microbiological quality assessed. The results showed that all the braising sites do not satisfy the Good Hygiene and Manufacturing Practices. Pathogenic microorganisms such as coliforms (2.17 ± 0.08 to 5.94 ± 0.38 Log cfu/g), E. coli (3.71 ± 0.20 to 6.21 ± 0.48 Log cfu/g) and Salmonella spp. were found in braised carp samples at levels higher than the microbiological criteria of the European Commission which are 1, 1 and 0 Log cfu/g, respectively. Spoilage microorganisms such as yeasts (2.39 ± 0.18 to 3.09 ± 0.23 Log cfu/g) and moulds (2.30 ± 0.10 to 2.92 ± 0.18 Log cfu/g) as well as spore-forming (3.02 ± 0.18 to 4.86 ± 0.35 Log cfu/g) and anaerobic (3.74 ± 0.28 to 4.52 ± 0.38 Log cfu/g) bacteria were also found at higher levels. The study highlights the poor microbiological quality of braised fish sold in the city of Yaoundé.

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Food-Borne Intestinal Bacterial Pathogens

Cited by 12 publications

References 25 publications

Predictive Modeling of Microbial Behavior in Food

Predictive Modeling of Microbial Behavior in Food

Predictive Modeling for Spoilage Microorganisms

Evaluation of sanitary risks associated with the consumption of street food in the city of Yaoundé (Cameroon): case of braised fish from Mvog-Ada, Ngoa Ekélé, Simbock, Ahala and Olézoa

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