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Growth kinetics of Escherichia coli O157:H7 on the epicarp of fresh vegetables and fruits

Overview of attention for article published in Brazilian Journal of Microbiology, August 2017
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Title
Growth kinetics of Escherichia coli O157:H7 on the epicarp of fresh vegetables and fruits
Published in
Brazilian Journal of Microbiology, August 2017
DOI 10.1016/j.bjm.2017.08.001
Pubmed ID
Authors

Mariel Gullian-Klanian, Maria José Sánchez-Solis

Abstract

Despite the increasing reports on the incidence of fresh vegetables and fruits as a possible vehicle for human pathogens, there is currently limited knowledge on the growth potential of Escherichia coli O157:H7 on different plant substrates. This study analyzed the selective adhesion and growth of E. coli O157:H7 on chili habanero (Capsicum chinense L.), cucumber (Cucumis sativus), radish (Raphanus sativus), tomato (Lycopersicon esculentum), beet (Beta vulgaris subsp. vulgaris), and onion (Allium cepa L.) under laboratory conditions. The Gompertz parameters were used to determine the growth kinetics. Scanning electron microscopy was used to visualize the adhesion of E. coli O157:H7 on the epicarp of the samples. Predictive models were constructed to compare the growth of E. coli O157:H7 on the samples with different intrinsic factors and to demonstrate the low selectivity of the pathogen. No significant difference was observed in the lag-phase duration (LPD), generation time (GT), and exponential growth rate (EGR) of the pathogen adhered to the samples. The interaction between the microorganism and the substrate was less supportive to the growth of E. coli O157:H7 for onion, whereas for tomato and cucumber, the time for the microorganism to attain the maximum growth rate (M) was significantly longer than that recorded for other samples.

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Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 20%
Student > Master 11 17%
Student > Postgraduate 5 8%
Other 3 5%
Student > Ph. D. Student 3 5%
Other 8 12%
Unknown 23 35%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 21%
Engineering 6 9%
Biochemistry, Genetics and Molecular Biology 5 8%
Immunology and Microbiology 3 5%
Veterinary Science and Veterinary Medicine 2 3%
Other 12 18%
Unknown 24 36%