African Journal of
Microbiology Research

  • Abbreviation: Afr. J. Microbiol. Res.
  • Language: English
  • ISSN: 1996-0808
  • DOI: 10.5897/AJMR
  • Start Year: 2007
  • Published Articles: 5233

Full Length Research Paper

Growth response and modeling the effects of Carum copticum essential oil, pH, inoculum level and temperature on Escherichia coli O157:H7

Tayebe Zeinali1, Saeid Khanzadi2*, Abdollah Jamshidi2 and Mohammad Azizzadeh3
  1Student of Veterinary Medicine, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad-Iran. 2Department of Food Hygiene and Aquaculture, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad-Iran. 3Department of Clinical Sciences, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad-Iran.
Email: [email protected]

  •  Accepted: 09 June 2012
  •  Published: 26 July 2012

Abstract

 

Enterohemorrhagic Escherichia coli O157:H7 (EHEC) is an important verotoxin producingE. coli (VTEC). It is associated with food and water borne infections. This study was designed to carefully examine the effects of four different factors on the growth of E. coliO157:H7 in the brain heart infusion broth. These factors included four concentrations ofCarum copticum (Zenyan in Persian) essential oil (0, 0.015, 0.03 and 0.06%), with the major components of thymol (57.18%), p-cymene (22.55%), and γ-terpinene (13.07%), two incubation temperatures (35 and 25°C), three levels of pH (5, 6 and 7) and two inoculum size (103 and 105 cfu ml-1). The experiment was carried out in triplicate. Growth was monitored by visible turbidity during a 30-day period. To evaluate the effects of explanatory variable on time to detection of bacterial growth, parametric survival model based on the weibull distribution was used. All explanatory variables had significant association with time to detection (P < 0.05). The models accurately predicted the growth initiation and inhibition of E. coli O157: H7.

 

Key words: Escherichia coli O157:H7, Carum copticum essential oil, modeling, predictive microbiology.