# Modelling the Ozone-Based Treatments for Inactivation of Microorganisms

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

_{3}/m

^{3}O

_{2}, with a flow rate of 0.4 L/min) and contact time (up to 20 min). The results demonstrated that a linear correlation between parameters p and k in Weibull distribution, providing an opportunity to calculate a fitted equation of the process.

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Plant Material Matrix

#### 2.2. Microorganisms

#### 2.3. Ozone Treatment in Dynamic Bed

_{3}/m

^{3}O

_{2}) stimulated with different flow rate values (1.2, 0.8, 0.6, 0.4 L/min, respectively) during different contact times (5, 10, 20, 30, 40 min), which gave 80 different measurement conditions. The pressure was kept constant at 0.5 atm. After treatment, each sample was transferred to sterile packaging (Merck, Darmstadt, Germany). Moreover, an ozone sensor (Eco Sensors Model A-21ZX, Newark, NJ, USA) was installed to be able to keep track of ozone concentration in the laboratory.

#### 2.4. Inoculation of Plant Material

^{8}cfu/mL) were done in a peptone salt solution (Sigma-Aldrich, St. Louis, MO, USA), and fungal suspensions (10

^{7}conidia per mL) were done in pepton salt with Tween 80 (Sigma-Aldrich, St. Louis, MO, USA) (1%, v/v). Tween 80 minimizes clumping of spores and improves the accuracy of spore counts [23]. Thermally sterilized (121 °C, 15 min) samples of plant material (10 g) were inoculated with 0.2 mL of the appropriate microorganism suspensions in the sterile bags (ChemLand, Stargard, Poland). The samples were mixed to facilitate adherence of the strains to the plant material and were left for 1 h prior to ozone treatment. Inoculated samples were placed into the reactor chamber and treated with ozone. Before and after the decontamination process, the number of bacteria (PCA medium (Merck, Darmstadt, Germany), 30 °C, 72 h) and fungi (YGC medium, 25 °C, 120 h) was determined. The obtained results were expressed as log cfu per gram of sample. All experiments were carried out in triplicate.

#### 2.5. Mathematical Model

_{0}is its initial value at time 0, k is the scale parameter of the model, p is the shape parameter of the model, and t is the time of exposure to ozone. Such equation can demonstrate different shapes of survival curves depending on the p value. Thus, there may be cases showing a concave downward survival curve if p > 1, which informs us that the hazard increases, or a convex shape of the survival curve if p < 1, reporting that the hazard is constant, and a linear function if p = 1, which means that the hazard decreases [2,25]. Additionally, shape parameter can be described as an indicator of the resistance of the microbial population. Also, knowing the values of scale and shape parameter, the reliable life t

_{R}can be calculated, or the 90% of the failure time distribution, which is analogous to the D-value (egn 2) [15].

## 3. Results and Discussion

^{2}), and the root mean square error (RMSE) was used as a measure of goodness-of-fit (Table 1 and Table 2).

_{3}/m

^{3}O

_{2}with the flow rate of 1.2, 0.8, 0.6, and 0.4 L/min, respectively, and for the cardamom seed matrix, the RMSE values were 0.04, 0.01, 0.03 and 0.02 for ozone doses of 5.0, 10.0, 15.0, and 20.0 g O

_{3}/m

^{3}O

_{2}with the flow rate of 1.2, 0.8, 0.6, and 0.4 L/min, respectively. Concerning the Weibull model inactivation of B. subtilis inoculated on the juniper berry and cardamom seed matrix, it can be observed that the failure of the model to accurately estimate log values was higher than in B. cereus model reaching 0.20, 0.22, 0.05, and 0.03 RMSE values for juniper berries and 0.05, 0.18, 0.21, and 0.22 for cardamom seeds treated with ozone doses of 5.0, 10.0, 15.0, and 20.0 g O

_{3}/m

^{3}O

_{2}with the flow rate of 1.2, 0.8, 0.6, and 0.4 L/min, respectively. RMSE values for B. pumilus Weibull model were recorded at the same level as B. subtilis, but slightly lower values were observed for juniper berry matrix.

_{3}/m

^{3}O

_{2}with the flow rate of 1.2, 0.8, 0.6, and 0.4 L/min, respectively) and B. pumilus (0.91, 0.84, 0.89, and 0.92 for juniper berries and 0.99, 0.91, 0.84, and 0.93 for cardamom seeds treated with ozone doses of 5.0, 10.0, 15.0, and 20.0 g O

_{3}/m

^{3}O

_{2}with the flow rate of 1.2, 0.8, 0.6, and 0.4 L/min, respectively) in Weibull model, most of them varied among the ozone parameters, but were at acceptable range (R

^{2}= 0.80–0.99) for juniper berry and cardamom seed matrix (Table 1 and Table 2). The Weibull model of microbial inactivation of E. coli and P. fluorescens demonstrated similar fitting parameters as B. cereus comparing RMSE and R

^{2}values. Concerning the Weibull model for E. cinnamopurpureum and A. niger inactivation, it can be concluded that it has a comparable goodness-of-fit of Weibull model as B. cereus as well as gram-negative bacteria (E. coli and P. fluorescens) (Table 1 and Table 2).

_{R}in which a 1-log reduction occurs may be determined. According to the t

_{R}values, the susceptibility of microorganisms was in the following order: A. niger > E. cinnamopurpureum > P. fluorescens > B. cereus > E. coli > B. subtilis > B. pumilus and A. niger > E. cinnamopurpureum > P. fluorescens > E. coli > B. cereus > B. pumilus > B. subtilis for juniper berry and cardamom seed matrix, respectively. Comparing two kind of matrices, the reductions of A. niger and E. cinnamopurpureum occurred the fastest among the studied strains on both juniper berries and cardamom seeds, with slightly lower t

_{R}values of 3 × 10

^{−9}min, 8 × 10

^{−10}min, 1 × 10

^{−4}min, and 6 × 10

^{−7}min for cardamom seeds, whereas t

_{R}values for juniper berries were 6 × 10

^{−5}min, 9 × 10

^{−6}min, 4 × 10

^{−4}min, and 7 × 10

^{−6}min. In addition, it can be observed that k increases with decreasing p and suggests a good correlation between the two parameters. This is due to a monotonic correlation between parameters p and k, which makes it possible to calculate a fitted equation of the process. Our observations were confirmed by Figure 2 and Figure 3, which clearly show a linear correlation between ln (p) and sqrt (k) for B. cereus on the juniper berry and cardamom seed matrix. These results agree with the work conducted by Couvert et al. 2005 [31], who evaluated a structural correlation between p and k in their study on the thermal resistance of B. pumilus. Similarly, Le Marc et al. 2009 [2] developed the model for the photo-destruction of the foodborne pathogen B. cereus, initially treated with a precursor of endogenous photosensitizers, reporting a strong correlation between parameters k and p. The final equation was estimated for Bacillus strains as critical strains inoculated on juniper berry and cardamom seed matrix.

^{2}= 0.90, R

^{2}= 0.92 for juniper berry and cardamom seed matrix, respectively, Equations (4) and (5)), B. subtilis (R

^{2}= 0.90, R

^{2}= 0.92 for juniper berry and cardamom seed matrix, respectively, Equations (6) and (7)) and B. pumilus inactivation (R

^{2}= 0.98, R

^{2}= 0.98 for juniper berry and cardamom seed matrix, respectively, Equations (8 ) and (9)) were written as:

_{3}/m

^{3}O

_{2}) (Figure 4). Concerning other conditions, namely lower ozone concentrations and longer times of exposure, similar reductions were obtained as previous described. Our results are in disagreement with those obtained by Akbas and Ozdemir 2008 [32], who reported that ozone concentrations of 0.0002 and 0.001 g O

_{3}/m

^{3}O

_{2}after a 360-min treatment resulted in 2.7 and 2.9-log reductions in population of B. cereus, respectively. The same authors also noticed that using higher ozone doses, such as 0.011, 0.015, and 0.019 g O

_{3}/m

^{3}O

_{2}, were needed to achieve significant reductions in B. cereus spores in dried fig samples, 1.5, 2.0, and 2.0-log reductions were observed, respectively [32]. In another study the same authors found ozone to be effective in inactivation B. cereus in pistachios, reporting that the effectiveness of ozone increased with increasing exposure time and ozone dose. At low ozone concentrations (0.0002 and 0.001 g O

_{3}/m

^{3}O

_{2}, 360 min), B. cereus counts were decreased by 1.5–2.0 log numbers [33].

_{3}/m

^{3}O

_{2}for 360 min, whereas 3.5-log reduction was recorded in kernels and shelled pistachios under the same processing conditions. It means that in their study 6 h and a much lower ozone concentration (1000 times) were needed for achieving the same level of reduction of B. cereus, while in our study 5 min with using higher ozone dose was sufficient. Undeniably, the longer time of the process is associated with a higher cost for whole process, whereas the aim of development of each new technology is to reduce the cost of the process as much as possible.

_{3}/m

^{3}O

_{2}with the flow rate of 1.2 and 0.8 L/min, respectively, whereas a similar level of reduction in matrix consisted of cardamom seeds was obtained for higher ozone doses of 15.0 and 20.0 g O

_{3}/m

^{3}O

_{2}with the flow rate of 0.6 and 0.4 L/min, respectively.

_{3}/m

^{3}O

_{2}with the flow rate of 0.6 and 0.4 L/min, respectively) after a 5-min treatment on juniper berry matrix, whereas the same results were achieved on cardamom seed matrix over the whole ozone concentration range during the same time.

_{3}/m

^{3}O

_{2}stimulated with the flow rate of 0.8 and 0.6 L/min, respectively, after 5 min, achieved a 2.9 and 3.5 log decrease in E. cinnamopurpureum counts, respectively, whereas treatment of cardamom seeds under the same conditions resulted in a lower reduction—2.7 and 1.9 log numbers, respectively (Figure 9). The obtained results showed that E. cinnamopurpureum is more sensitive to ozone than B. cereus.

## 4. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**Ozone treatment system in dynamic bed for gaseous phase used for laboratory purposes; 1—oxygen bottle, 2—ozone generator, 3—ozone analyzer, 4—surplus gas elimination unit, 5—inlet of ozone, 6—outlet of ozone, 7—reactor, 8—control system with jolting and rotating mechanism, 9—supply and disposal of plant material treated with ozone [22].

**Figure 2.**Linear relationship between ln (p) and sqrt (k) for B. cereus on the juniper berry matrix, where p and k are the scale and shape parameters of the Weibull model (Equation (4)).

**Figure 3.**Linear relationship between ln (p) and sqrt (k) for B. cereus on the cardamom seed matrix, where p and k are the scale and shape parameters of the Weibull model (Equation (5)).

**Figure 4.**Survival of B. cereus on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6 and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: prediction of the Weibull model (egns 4–5), dotted line: bacterial log counts.

**Figure 5.**Survival of B. subtilis on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: prediction of the Weibull model (egns 6–7), dotted line: bacterial log counts.

**Figure 6.**Survival of B. pumilus on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: prediction of the Weibull model (egns 8–9), dotted line: bacterial log counts.

**Figure 7.**Survival of E. coli on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: fit of the Weibull model (egn 1), dotted line: bacterial log counts.

**Figure 8.**Survival of P. fluorescens on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: fit of the Weibull model (egn 1), dotted line: bacterial log counts.

**Figure 9.**Survival of E. cinnamopurpureum on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: fit of the Weibull model (egn 1), dotted line: bacterial log counts.

**Figure 10.**Survival of A. niger on the cardamom seed (

**left**) and juniper berry (

**right**) matrix treated with ozone doses stimulated with flow rate of 1.2, 0.8, 0.6, and 0.4 L/min after 5, 10, 20, 30, and 40 min. Solid line: fit of the Weibull model (egn 1), dotted line: bacterial log counts.

**Table 1.**Weibull model and fitted parameters for reductions of B. cereus, B. subtilis, B. pumilus, E. coli, P. fluorescens, E. cinnamopurpureum, and A. niger on the juniper berry matrix after ozone treatment in a dynamic bed.

Research Matrix | Microorganism | Ozone Flow Rate (L/min) | Weibull Model Parameters | Fitted Parameters | |||
---|---|---|---|---|---|---|---|

k | p | t_{R} (min) | RMSE | R^{2} | |||

Juniper berries | B. cereus | 1.2 | 3.60 | 0.11 | 0.02 | 0.01 | 0.99 |

0.8 | 4.35 | 0.08 | 0.00 | 0.02 | 0.93 | ||

0.6 | 3.88 | 0.11 | 0.01 | 0.02 | 0.97 | ||

0.4 | 3.95 | 0.10 | 0.01 | 0.01 | 0.98 | ||

B. subtilis | 1.2 | 1.20 | 0.35 | 6.62 | 0.20 | 0.73 | |

0.8 | 1.07 | 0.36 | 8.25 | 0.22 | 0.73 | ||

0.6 | 2.01 | 0.16 | 2.37 | 0.05 | 0.92 | ||

0.4 | 1.74 | 0.22 | 3.69 | 0.03 | 0.98 | ||

B. pumilus | 1.2 | 1.28 | 0.37 | 5.03 | 0.11 | 0.91 | |

0.8 | 2.87 | 0.11 | 0.12 | 0.04 | 0.84 | ||

0.6 | 1.12 | 0.28 | 13.62 | 0.10 | 0.89 | ||

0.4 | 0.36 | 0.66 | 17.04 | 0.18 | 0.92 | ||

E. coli | 1.2 | 3.50 | 0.12 | 0.03 | 0.04 | 0.90 | |

0.8 | 2.68 | 0.18 | 0.44 | 0.05 | 0.93 | ||

0.6 | 5.67 | 0.09 | 0.00 | 0.02 | 0.97 | ||

0.4 | 5.46 | 0.10 | 0.00 | 0.02 | 0.95 | ||

P. fluorescens | 1.2 | 6.30 | 0.07 | 0.00 | 0.01 | 0.99 | |

0.8 | 3.56 | 0.22 | 0.14 | 0.06 | 0.93 | ||

0.6 | 5.42 | 0.11 | 0.00 | 0.01 | 0.98 | ||

0.4 | 5.81 | 0.10 | 0.00 | 0.03 | 0.91 | ||

E. cinnamopurpureum | 1.2 | 4.08 | 0.17 | 0.03 | 0.06 | 0.90 | |

0.8 | 4.91 | 0.17 | 0.01 | 0.06 | 0.90 | ||

0.6 | 6.93 | 0.09 | 0.00 | 0.03 | 0.91 | ||

0.4 | 4.16 | 0.16 | 0.02 | 0.06 | 0.88 | ||

A. niger | 1.2 | 6.03 | 0.10 | 0.00 | 0.03 | 0.91 | |

0.8 | 6.36 | 0.09 | 0.00 | 0.02 | 0.95 | ||

0.6 | 5.58 | 0.12 | 0.00 | 0.04 | 0.87 | ||

0.4 | 6.36 | 0.09 | 0.00 | 0.03 | 0.86 |

**Table 2.**Weibull model and fitted parameters for reductions of B. cereus, B. subtilis, B. pumilus, E. coli, P. fluorescens, E. cinnamopurpureum, and A. niger on the cardamom seed matrix after ozone treatment in a dynamic bed.

Research Matrix | Microorganism | Ozone Flow Rate (L/min) | Weibull Model Parameters | Fitted Parameters | |||
---|---|---|---|---|---|---|---|

k | p | t_{R} (min) | RMSE | R^{2} | |||

Cardamom seeds | B. cereus | 1.2 | 3.74 | 0.11 | 0.01 | 0.04 | 0.90 |

0.8 | 4.22 | 0.08 | 0.00 | 0.01 | 0.98 | ||

0.6 | 4.09 | 0.09 | 0.00 | 0.03 | 0.91 | ||

0.4 | 4.27 | 0.07 | 0.00 | 0.02 | 0.89 | ||

B. subtilis | 1.2 | 0.59 | 0.52 | 13.75 | 0.05 | 0.99 | |

0.8 | 0.92 | 0.45 | 7.59 | 0.18 | 0.86 | ||

0.6 | 0.94 | 0.46 | 7.12 | 0.21 | 0.82 | ||

0.4 | 0.79 | 0.48 | 9.34 | 0.22 | 0.81 | ||

B. pumilus | 1.2 | 0.30 | 0.73 | 16.89 | 0.05 | 0.99 | |

0.8 | 0.96 | 0.39 | 9.37 | 0.12 | 0.91 | ||

0.6 | 0.98 | 0.52 | 5.18 | 0.22 | 0.84 | ||

0.4 | 1.48 | 0.39 | 3.12 | 0.11 | 0.93 | ||

E. coli | 1.2 | 4.82 | 0.14 | 0.00 | 0.05 | 0.87 | |

0.8 | 5.40 | 0.11 | 0.00 | 0.01 | 0.99 | ||

0.6 | 5.32 | 0.11 | 0.00 | 0.03 | 0.93 | ||

0.4 | 4.62 | 0.15 | 0.00 | 0.02 | 0.97 | ||

P. fluorescens | 1.2 | 6.44 | 0.10 | 0.00 | 0.05 | 0.80 | |

0.8 | 6.25 | 0.14 | 0.00 | 0.01 | 0.99 | ||

0.6 | 8.20 | 0.06 | 0.00 | 0.01 | 0.96 | ||

0.4 | 7.06 | 0.11 | 0.00 | 0.02 | 0.95 | ||

E. cinnamopurpureum | 1.2 | 5.37 | 0.07 | 0.00 | 0.02 | 0.91 | |

0.8 | 5.71 | 0.06 | 0.00 | 0.02 | 0.90 | ||

0.6 | 3.84 | 0.10 | 0.01 | 0.04 | 0.88 | ||

0.4 | 3.57 | 0.14 | 0.05 | 0.03 | 0.95 | ||

A. niger | 1.2 | 6.96 | 0.06 | 0.00 | 0.02 | 0.86 | |

0.8 | 6.95 | 0.05 | 0.00 | 0.01 | 0.97 | ||

0.6 | 4.78 | 0.08 | 0.00 | 0.02 | 0.91 | ||

0.4 | 5.51 | 0.06 | 0.00 | 0.03 | 0.78 |

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Brodowska, A.J.; Nowak, A.; Kondratiuk-Janyska, A.; Piątkowski, M.; Śmigielski, K. Modelling the Ozone-Based Treatments for Inactivation of Microorganisms. *Int. J. Environ. Res. Public Health* **2017**, *14*, 1196.
https://doi.org/10.3390/ijerph14101196

**AMA Style**

Brodowska AJ, Nowak A, Kondratiuk-Janyska A, Piątkowski M, Śmigielski K. Modelling the Ozone-Based Treatments for Inactivation of Microorganisms. *International Journal of Environmental Research and Public Health*. 2017; 14(10):1196.
https://doi.org/10.3390/ijerph14101196

**Chicago/Turabian Style**

Brodowska, Agnieszka Joanna, Agnieszka Nowak, Alina Kondratiuk-Janyska, Marcin Piątkowski, and Krzysztof Śmigielski. 2017. "Modelling the Ozone-Based Treatments for Inactivation of Microorganisms" *International Journal of Environmental Research and Public Health* 14, no. 10: 1196.
https://doi.org/10.3390/ijerph14101196