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Title: Antimicrobial efficacy of nisin, oregano and ultrasound treatments against foodborne pathogens in ready-to-eat vegetables
Authors: Takundwa, Brianmax Aubrey 
Issue Date: 2020
A marked increase in the prevalence of foodborne illnesses resulting in foodborne outbreaks
globally have been noticed, primarily due to the contamination of foods with bacterial pathogens.
Recently, there has been a growing interest in employing alternative decontamination methods
against bacterial pathogens, as a result of problems associated with the commonly used chemical
and thermal methods. Therefore, the current impetus is on employing decontamination techniques
involving green technology (physical, biological) and hurdle technology. In this study, oregano,
nisin and ultrasound treatments were employed on lettuce and cabbage at varying levels to
elucidate their antimicrobial efficacy and subsequent effect on the physical and sensory properties
of the vegetables.
Specifically, fresh cut lettuce and cabbage samples were inoculated with Escherichia coli O157:H7
and Listeria monocytogenes and were subjected to a series of combined treatment applications, of
nisin, oregano essential oil and ultrasound. The Box Behnken, response surface methodology
(RSM) technique was used in formulating the various combination treatments that would, in turn,
demonstrate the synergistic capabilities of the three factors, nisin, oregano and ultrasound when
combined. Results from the RSM were then used in the optimization of the combined treatment
parameters by maximizing the microbial log reduction in both ready-to-eat vegetables. The
physical properties studied on lettuce and cabbage subjected to combined treatments were colour
and texture, and their structural damage was investigated using electrolyte leakage. Sensory
properties were also analyzed on non-inoculated cabbage samples previously subjected to
combined antimicrobial treatments. The efficacy of nisin, oregano and ultrasound on the reduction of E. coli O157:H7 and L. monocytogenes
on lettuce studied using RSM/Box-Behnken model design, was found to be reliable (p<0.05). The
most effective treatment on both pathogens was a combination of 771.2 IU/g nisin, 0.185% v/v
oregano and 14.65 min ultrasound which showed log reductions of 3.43 and 9.20 CFU/mL for E. coli
O157:H7 and L. monocytogenes, respectively. Lettuce treatment with the combined antimicrobial
treatments resulted in no significant differences in textural properties, specifically hardness.
However, mild colour changes and a slight increase in the electrolyte leakage rate was observed,
though they were within the permissible limits.
The reduction of E. coli O157:H7 on cabbage was increased with the use of combined treatments
of nisin, oregano and ultrasound. Hence, the combination (comprising 607.85 IU/g nisin, 0.20%
v/v oregano and 14.98 min ultrasound) exhibited the highest log reduction of 3.66 CFU/mL. In
the samples inoculated with L. monocytogenes, 731.25 IU/g nisin, 0.12% v/v oregano and 13.21
min ultrasound treatments were found to be the best combination exhibiting the highest log
reduction of 8.27 CFU/mL. No significant colour and textural changes were observed between
untreated and treated cabbage. However, a slight increase in the electrolyte leakage rate was
observed after the application of the combined treatment. Sensory evaluation scores also had some
factors that were slightly below par.
Overall, results from the study demonstrated that a combination of nisin, oregano and ultrasound,
is a promising alternative to chemical treatments for the reduction of E. coliO157:H7 and L. monocytogenes
as well as retaining the quality characteristics of fresh produce. Prospectively, other studies could
explore the frontier field of artificial intelligence and machine learning, in the form of predictive
microbiology and mathematical modelling, in the fresh produce industry. This would present a better understanding of risk assessment that is powered by the technological advantage of data
Submitted in fulfillment of the academic requirements for the Master of Applied Sciences in Food Science and Technology degree at the Department of Biotechnology and Food Science, Faculty of Applied Sciences
Durban University of Technology, Durban, 2020.
Appears in Collections:Theses and dissertations (Applied Sciences)

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