Inactivation kinetics of Bacillus cereus spores by Plasma activated water (PAW)

Journal Pre-proofs Inactivation kinetics of Bacillus cereus spores by Plasma activated water (PAW) Yan Bai, Aliyu Idris Muhammad, Yaqin Hu, Shigenobu Koseki, Xinyu liao, Shiguo chen, Xingqian Ye, Donghong Liu, Tian Ding PII: DOI: Reference:

S0963-9969(20)30066-1 https://doi.org/10.1016/j.foodres.2020.109041 FRIN 109041

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Food Research International

Received Date: Revised Date: Accepted Date:

9 October 2019 27 December 2019 26 January 2020

Please cite this article as: Bai, Y., Idris Muhammad, A., Hu, Y., Koseki, S., liao, X., chen, S., Ye, X., Liu, D., Ding, T., Inactivation kinetics of Bacillus cereus spores by Plasma activated water (PAW), Food Research International (2020), doi: https://doi.org/10.1016/j.foodres.2020.109041

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Inactivation kinetics of Bacillus cereus spores by Plasma activated water (PAW) Yan Baia,b, Aliyu Idris Muhammada,b, Yaqin Hua,b,*, Shigenobu Kosekic, Xinyu liaoa,b, Shiguo chena,b, Xingqian

Yea,b, Donghong Liua,b, Tian Dinga,b,*

aDepartment

of Food Science and Nutrition, National Engineering Laboratory of Intelligent Food Technology and

Equipment, Zhejiang University, Hangzhou, Zhejiang, 310058, China

bKey

Laboratory for Agro-Products Postharvest Handling of Ministry of Agriculture, Zhejiang Key Laboratory for

Agro-Food Processing, Hangzhou, Zhejiang, 310058, China

cResearch

Faculty of Agriculture, Hokkaido University, Kita 9 Nishi 9, Kita-ku, Sapporo, Hokkaido, 060-8589,

Japan

ABSTRACT In recent years, plasma activated water has attracted more attention as a new disinfectant. The purpose of this study was to explore impact of variation of different treatment conditions on the inactivation kinetics of Bacillus cereus spores by PAW. All survival curves showed that the number of spores has decreased rapidly at first, followed by tailing results from the reduction inactivation rate. A linear and two nonlinear models (Weibull and Log-logistic model) were fitted to these data, and

*Corresponding author at: Department of Food Science and Nutrition, National Engineering Laboratory of

Intelligent Food Technology and Equipment, Zhejiang University, Hangzhou, Zhejiang, 310058, China. E-mail address: [email protected] (YQ. Hu). Tel. +86 15868109010 [email protected] (T. Ding). Tel. +86 18758865789

Log-logistic model fitted the inactivation of the B. cereus spores best. B. cereus spores in 106 CFU/mL was reduced by 1.62–2.96 log CFU/mL by PAW at 55℃ due to the reactive species generated in PAW. Elevated temperature, lower initial spore concentration, lower bovine serum albumin content, and smaller activation volume of PAW considerably enhanced PAW inactivation of B. cereus spores. These results provide an approach to evaluate the inactivation efficacy of different treatment conditions for PAW. Keywords: Plasma activated water; B cereus spore; mathematics model; inactivation 1. Introduction Bacillus cereus is Gram-positive aerobe or facultative anaerobe, which is capable of causing food poisoning and form spores under poor conditions (Ceuppens et al., 2011; Soni, Oey, Silcock, & Bremer, 2018). Spores could survive for a long time and compared with vegetative cells, spores are more resistant to severe environment such as drying, heating, radiation and chemical treatments (Bhunia, 2018; Driks, 2002). The outermost structure of spores consists of two layers of protein, which could provide protection against chemicals such as acids and alkalis, and the cortex composed of peptidoglycan of spores could resist the small hydrophilic molecules in antimicrobial components effectively (Cho & Chung, 2017). Bacillus cereus mainly exists in the rhizosphere and is frequently isolated from soil (Schoeni & Wong, 2005) and can be found in various kinds of food such as meat (Schoeni & Wong, 2005), rice 2

(Chang et al., 2011), vegetables (Samapundo, Heyndrickx, Xhaferi, & Devlieghere, 2011), dairy products, and raw milk (Kumari & Sarkar, 2016). B. cereus is the pathogen of the emetic and diarrheal syndromes. The emetic syndrome is caused by absorption of a emetic toxin preformed in the food, while the diarrheal syndrome results from diverse toxins that may be formed in food and the small intestine (Bursova, Necidova, & Harustiakova, 2018). In the United States, B. cereus is one of the main microorganisms responsible for about 63,400 episodes of food-borne diseases every year (Scallan et al., 2011). In 2013, a risk assessment carried out in Shanghai, China stated that about 3.1% of the cooked rice contaminated by over 4.0 log CFU/g of B. cereus, which indicating a high potential risk for consumers (Dong, 2013). Low acidic liquid food products can be thermally sterilized at very high temperatures to inactivate microbial spores, which can be preserved. For many decades, 121 ℃ has been used as reference for spore destruction in food thermal sterilization (Silva, Tan, & Farid, 2012), however, prolonged exposure to high temperatures (120-140℃) causes deterioration of nutritional value, flavor, color and texture of these foods (Ansari, Ismail, & Farid, 2017). In order to overcome the disadvantages of thermal processing, various non-thermal microbial inactivation technologies, such as supercritical carbon dioxide (Zhang et al., 2006), high-pressure processing

(Yamamoto, 2017), high electric field pulses (Uemura, Kobayashi, &

Inoue, 2010), ultra-sonication (Li et al., 2019), electrolyzed water (Xuan et al., 2017), 3

and plasma (Liao et al., 2017a,b) have been developed. Chemical agents such as sodium hypochlorite, peracetic acid and hydrogen peroxide were also used to inactivate spores (Setlow, Yu, Li, & Setlow, 2013; Sudhaus et al., 2014; Tremarin, Brandao, & Silva, 2017), but it has now been clearly confirmed that some of these chemicals or their related inorganic byproducts might be toxic which could bring physical and health harm to people (Zhang et al., 2016). Therefore, it is necessary to develop effective, nontoxic, and environmentally friendly sterilization methods to diminish or inactivate bacterial spores. Plasma is the fourth state of matter and could generate an electric field, a magnetic field, UV rays, electrons, charged particles, and chemical species, such as reactive oxygen species (ROS) and reactive nitrogen species (RNS) (Scholtz et al., 2015). The oxygen and nitrogen will be discharged and excited, and various ROS (H2O2, hydrogen oxide radicals (OH∙), ozone) and RNS such as nitric oxide radicals (NO∙), will be generated (Xu, Garner, Tao, & Keener, 2017). Plasma is widely regarded as an effective decontamination method and increasingly used for food industry application (Liao et al., 2018; Liao et al., 2019). The preparation of PAW is based on treatment of distilled water with plasma for a specific time. PAW has attracted more and more attention as an aqueous disinfectant (Shen et al., 2016). Chemical compounds such as hydrogen peroxide (H2O2), nitrite (NO2−), and nitrate (NO3−) could be generated by the plasma treatment of water (Ercan et al., 2016). Furthermore, transient reactive species such 4

as ·OOH, ·OH and ·H radicals, and stable nitric acid could be generated by detailed interactions between plasma derived species and water (Xu et al., 2017; Zhou et al., 2018). The bactericidal activity of PAW is due to the synergistic effects of a high positive oxidation reduction potential (ORP) and low pH which are induced by those compounds above mentioned (Liao et al., 2020a; Zhang et al., 2016). PAW can effectively inactivate a variety of microorganisms such as Escherichia coli (Traylor et al., 2011), Hafnia alvei (Kamgang-Youbi et al., 2008; Naitali et al., 2010), Pseudomonas deceptionensis (Xiang et al., 2018) and Staphylococcus aureus (Oehmigen et al., 2010). Compared with direct plasma treatment, PAW is easy to use, and has the ability to kill microorganisms that cannot be destroyed by direct plasma treatment (i.e., areas not directly exposed or difficult to reach to plasma discharge in the device (Balan et al., 2018). Besides, compared with other chemicals (unlike other disinfectants), PAW has less adverse impact on the environment, and does not need to transport and store potentially hazardous chemicals (Shen et al., 2016). Indeed, chemical disinfectants may cause the risk of carcinogenic chlorinated byproducts, especially chlorine-based chemicals, which are public health concerns in food industry (Olmez & Kretzschmar, 2009). Inactivation kinetics can describe and forecast the inactivation behaviors of microorganisms under specific treatment conditions by combining with microbiology, experimental data, and mathematics to build mathematical models (Zimmermann, Schaffner, & Aragao, 2013). There are several models to fit the data of inactivation of 5

B. cereus spores by physical and chemical reagents. In this study, three models which have already been proven to be successful in describing the inactivation of microorganisms during processing were selected: Linear, Weibull, and Log-logistic models (Chen, 2007; Ngnitcho et al., 2018; Rezaeimotlagh et al., 2018). The linear model is a classical model which is used to provide a linear inactivation curve that is related only to time (Chick, 1908). When the inactivation kinetics of microorganisms could not be linearly fitted, that is to say the microbial inactivation curves show nonlinear state such as tailing, shoulder, and sigmoid effects (Pottage et al., 2012), non-linear models could be applied to these inactivation curves. Weibull model is the simplest non-linear model, and it has been successfully used to fit the nonlinear inactivation curves of many microorganisms under different sterilization conditions (Wang et al., 2016), such as pressure inactivation kinetics of Yersinia enterocolitica (Chen & Hoover, 2003), UV-C irradiation inactivation of Escherichia coli, Salmonella Enteritidis and L. monocytogenes (Martínez-Hernández et al., 2015), and high-power pulsed light inactivation of Salmonella Typhimurium (Luksiene, Gudelis, Buchovec, & Raudeliuniene, 2007). The Log-logistic model assumes that all microorganisms could be divided into three different bacterial subpopulations, one is composed of spore resistant to the treatment, the other is composed of spore that could repair themselves and survive after treatment, and the third one is composed of very sensitive spore generated by the absence or loss of repairing systems. This model is especially useful for modelling PAW-based 6

inactivation curves because it proposes a treatment time parameter specific to bacterial strain, which depends on the treatment time of PAW. Thus, the optimal treatment time for inactivation could be estimated (Dementavicius, Lukseviciute, Gomez-Lopez, & Luksiene, 2016). Therefore, the main objective of this study was to explore the effect of different treatment factors (temperature, initial spore concentration, organic matter, activation volume) on the inactivation of B. cereus spores by PAW and the inactivation curves were fitted in Linear, Weibull, Log-Logistic models to study the inactivation kinetics of B. cereus spores by PAW, providing theoretical support for the application of PAW. 2. Materials and methods 2.1. Preparation of plasma activated water An atmospheric plasma jet (Tonson Tech Automation Equipment Co., LTD, Shenzhen, Guangdong, China) was used in our study (Wang et al., 2016). As shown in Figure 1, the PAW was produced by placing the plasma jet above the water surface. The distance between the end of the plasma jet and the liquid surface was 80 mm. Distilled water (50, 75, 100 mL) were subjected to plasma treatment at input power of 650 W for 60 s. Air compressed at 0.2 MPa was used as the working gas at a flow rate of 39 L/min. 2.2. Measurement of physicochemical properties of PAW 7

To better understand the process mechanisms of PAW treatment, the physicochemical properties of PAW after different activation power, activation time and activation volume were measured immediately, including pH and oxidation reduction potential (ORP) of PAW. The pH of PAW was measured with a pH meter (FE28-TRIS, Mettler Toledo, Shanghai, China) at 25 ± 1°C. The ORP of each sample was determined using a redox sensitive electrode (PB-10pH-ORP, Startorius, USA) connected to a dual channel pH meter. 2.3. The preparation of spore suspension B. cereus ATCC 11778-3 was obtained from Hope Bio-Technology Co., Ltd., Qingdao, Shandong, China, and routinely grown for 12 h until stationary phase at 37℃ and 180 rpm using standard nutrient broth (Hope Bio-Technology Co., Ltd., Qingdao, Shandong, China). Spores were harvested by glass sheet until 95% of the field of vision is green with the observation under electron microscope and (UPH 203i Phase Microscope, Aopu Photoelectric Technology Co., Ltd., Chongqing, China) then the suspension was centrifugal for 10 min at 6000 r/min and 4 ℃ (TGL-20M centrifuge; Kaida Scientific Instruments Co., Ltd., Changsha, Hunan, China) for 5-6 times. Subsequently, the solution was heated at 80 ℃ for 20 min to kill all vegetative cells. Ultimately, B. cereus spores suspended in distilled water at 109 spores/mL was used(Lv et al., 2018). 2.4. Inactivation by plasma activated water 8

There was 5 min between PAW generation and the treatment with temporarily storage at 4℃ to ensure the effectiveness of PAW. For inactivation of B. cereus spore induced by PAW at different temperatures, 100μL Bacillus cereus spore suspension at 106 spores/mL was added into 9.9 mL PAW activated at 50 mL, and the final total volume was 10 mL for the treatment time of 60 min at the temperature of 25℃, 40℃, and 55℃. For inactivation of B. cereus spore induced by PAW at different initial spore concentrations, Bacillus cereus spore suspension (100μL) at 106, 107, 108 spores/mL was added into 9.9 mL PAW activated at 50 mL, and the final total volume was 10 mL for the treatment time of 60 min at the temperature of 55℃. For inactivation of B. cereus spore induced by PAW at different BSA contents, 0.1, 0.5 mg/mL BSA was added into 9.9 mL PAW activated at 50 mL separately and then 100 μL Bacillus cereus spore suspension at 106 spores/mL was added to the mixture. The final total volume was 10 mL for the treatment time of 60 min at the temperature of 55℃. For inactivation of B. cereus spore induced by PAW at activation volumes of PAW, 100μL Bacillus cereus spore suspension at 106 spores/mL was added into 9.9 mL PAW activated at 50 mL, 75 mL, 100 mL, and the final total volume was 10 mL for the treatment time of 60 min at the temperature of 55℃. After that, 1 mL of mixture was added to 9 mL of neutralization solution (containing 0.5% Na2S2O3 and 0.85% NaCl) to stop the inactivation (Ding et al.,

9

2016). Bacillus cereus spore suspension treated with sterile water was set as the control. All experiments were repeated three times for statistical analysis. 2.5. Enumeration of surviving cells Colony count assays were used to indicate the antimicrobial effects and kinetic inactivation curves of a given compound or device (Zhang et al., 2013). After the treatment, 100 μL tenfold serial dilutions of treated suspension were plated on nutrient agar culture medium containing 0.1% soluble starch and incubated at 37℃ for about 12 h for a subsequent colony-forming unit (CFU) count. The inactivation ability of PAW treatment was evaluated by the log reduction, which was further calculated by the formula in equation 1 (Tian et al., 2015):

log Reduction  log control  log treated

[1]

2.6. Data modeling methods 2.6.1. Linear model Linear model is widely accepted and used to fit the microbial inactivation caused by thermal and non-thermal processes. The linear model assumes that the spores in the population have the same resistance, and the relationship between the decrease in the number of surviving spores over the treatment time is linear (Unluturk, Atilgan, Baysal, & Unluturk, 2010). The linear model is shown in equation 2. log10 ( N t / N 0 )  

t D

[2]

10

N0 is the primary number of spores (CFU/mL), t is the treatment time (min), and Nt is the number of surviving spores after a specific period of time (CFU/mL), D indicates the time required to inactivate 90% of spores (Wang et al., 2016). 2.6.2. Weibull model The Weibull model was first applied to bacteria inactivation caused by thermal treatment (Peleg & Cole, 1998). It is assumed that all the spores consisted of several parts which are sensitive to heat differently and each part could be described by a specific time, tc, then treatment becomes infeasible, and tc is distributed according to Weibull’s distribution in equation 3: n d  bntcn 1e btc dt c

[3]

 represents the fraction of microbes, which expires after tc, b and n are

constants. For the case of n<1 the equation allows the fitting of the tailing portion (inward concavity) of the inactivation curve, and for n>1, the shoulder portion (outward convexity) can be predicted (Marugan, van Grieken, Sordo, & Cruz, 2008).The relative proportion of bacteria surviving after treatment is expressed in a semi-logarithmic manner, as in equation 4: log10 ( N t / N 0 )  bt n

[4]

2.6.3. Log-logistic model The original Log-logistic model was proposed by Cole et al.(Cole et al., 1993) to fit the nonlinear equation of microbial thermal inactivation. The parameters of 11

Log-logistic model in this work was reduced from 4 to 3 in the equation, as shown in equation 5 (Chen, 2007): log10 ( N t / N 0 ) 

A 1 e

4 (  log t ) / A



A 1 e

4 (  6 ) / A

[5]

A represents the difference between the upper and lower asymptotes (log10 CFU/mL), and σ is the maximum inactivation rate log (CFU/mL)/log min; τ is the log10 time of the maximum inactivation rate (Lee et al, 2013). 2.7. Data analysis and model evaluation Statistical Package for the Social Sciences (SPSS) 20.0 (SPSS Statistical Software, Inc., Chicago, IL, USA) was used for data variance analysis and the significant differences between mean values were determined by Duncan's honest significant difference (HSD) test at a significance level of P<0.05. Origin 9.1 software (OriginLab Inc., U.S.A.) was used for linear and nonlinear analysis. All measured values for each experiment were taken in triplicate. 3. Results and discussion 3.1. Physicochemical properties of PAW The physicochemical properties of PAW such as pH and ORP value were measured in the course of different activation power, activation time and activation volume, as shown in table 1-3, the pH value of PAW (activated at 650W, 50 mL) decreased significantly from 6.71 to 3.35 after being activated by plasma for 30s, and the pH decreased with the longer activation time and smaller activation volume. Similar results have been reported previously for PAW samples prepared by 12

atmospheric pressure plasma jet (Xiang et al., 2019). It is speculated that the acidic pH plays an important role for the inactivation effect of PAW (Lukes, Dolezalova, Sisrova, & Clupek, 2014) since the structure and function of the biological macromolecules might be affected by high level of H+ (Ferreira, Pinto, Soares, & Soares, 2015; Xiang et al., 2019). ORP could represent the activity or intensity of oxidizers or reducers related to their concentrations, and is generally considered to be the main factor influencing the efficiency of microbial inactivation of a solution (Kim, Hung, & Brackett, 2000). It has been reported that a high ORP could destroy the outer membrane and inner membrane of E. coli O157:H7, and lead to the release of intracellular components (Liao, Chen, & Xiao, 2007). As depicted in Table 1-3, the ORP value of PAW (activated at 650W, 50 mL) significantly increased after being activated by plasma for 30s, which tended to be stable after the activation time of 60s. These findings are consistent with the results from previous reports (Guo et al., 2017; Xu et al., 2016). The increase of the ORP may be associated with the production of highly reactive species, such as nitrates, nitrites, and hydrogen peroxide (Guo et al., 2017). 3.2. Inactivation kinetics of B. cereus spore induced by PAW at different temperatures The experimental data and survival curves of B. cereus spore inactivation induced by PAW at different treatment temperatures are shown in Figure 2. B. cereus spore in 6 log CFU/mL was reduced by 1.62–2.96 log CFU/mL by PAW at 55℃. Nevertheless, when the treatment time was the same, the reduction of Alicyclobacillus 13

acidoterrestris spore in orange juice by thermosonication at 75 °C was lower than 2 log CFU/mL(Evelyn & Silva, 2016), and even thermal processes in the range of 70– 78°C almost did not affect spores of Clostridium perfringens, Neosartorya fischeri, B. cereus (Evelyn & Silva, 2018), which indicated that single PAW treatment had potentials to apply to inactivation of spores. This is because PAW could cause damages on the multilayered structure and leakage of intracellular components of B. cereus spores, and this disruption could be intensified with the increase of temperature (Liao et al., 2020b). As shown in Figure 2, at the same temperature, the survival level of B. cereus spores decreased with the extension of treatment time. Temperature plays a significant role in spore inactivation of PAW, with greater spore inactivation at higher temperatures, which are in agreement with the result of Evelyn & Silva (2015)with Bacillus cereus spores in skim milk. RMSE measures the average deviation between the observed and fitted values. The smaller the RMSE value of the model, the more suitable the data of the model (Buzrul & Alpas, 2007). By comparing the goodness of fit of the linear and nonlinear models using RMSE values (Table 4), the nonlinear models described the survival curves better than the linear model. The mean RMSE values for the linear, Weibull, and Log-logistic models were 0.20, 0.13, and 0.02, respectively. The parameters of the three fitted models are exhibited in Table 5. For Weibull model, the shape parameters of the inactivation of spores by PAW were all less than 1 14

at all temperatures, which indicated that the remaining survivors of B. cereus spores can adapt to the PAW treatments and showed that their resistance to PAW increased gradually. Similarly, Hertwig et al. (Hertwig, Reineke, Rauh, & Schluter, 2017) used the Weibull model to fit the inactivation data of Bacillus subtilis by cold plasma, and the shape parameters for inactivation kinetic by air, O2, N2 and CO2 plasma were all less than 1. Furthermore, the data indicated that the Log-logistic model was most suitable for evaluating inactivation curves of B. cereus spores induced by PAW at different temperatures. The shapes of the survival curves of the three temperatures were very similar, which are characterized by a rapid decrease in bacterial count at first, followed by tailing due to a falling inactivation rate (Figure 2c), and tailing started after about 40 min. This phenomenon indicated that it is inappropriate to prolong the treatment time to improve the sporicidal efficiency of PAW on B. cereus spores. The higher the temperature, the greater the maximum inactivation rate σ value (Table 5). To improve the inactivation of bacillus cereus spores, it is preferable to increase the temperature and shorten the time of treatment. 3.3. Inactivation kinetics of B. cereus spore by PAW at different initial spore concentrations Survival curves of B. cereus spore inactivation induced by PAW at different initial spore concentrations are shown in Figure 3. The result indicated that the 15

Log-logistic model exhibited the best fit for all the survival curves at different initial spore concentrations. The goodness of fit of these three models were compared using RMSE values in Table 6. The results revealed that the mean RMSE value for the linear, Weibull, and Log-logistic models were 0.29, 0.15, and 0.03, respectively. The survival curves of the three initial spore concentrations were very similar in shape, and characterized by a rapid drop in bacterial counts at first, followed by tailing due to a decrease in inactivation rate (Figure 3c). The lower the initial spore concentration, the higher the inactivation rate σ value (Table 7). Deng et al. (2005) also found that microbial load (spore initial density) significantly affect the resistance of microorganisms to atmospheric plasma,

result in a stacking structure as a

protective cover . Fernandez et al. (2012) studied the effects of primary microbial concentration on the inactivation of S. Typhimurium with cold atmospheric plasma (CAP), they found that the inactivation efficacy of CAP is related to the bacterial concentration . These results could explain the reduced inactivation by the plasma, since the top or outer layer may present a physical barrier that protects underlying or inner cells. 3.4. Inactivation kinetics of B. cereus spore by PAW at different BSA contents In the process of inactivation, there are usually many organic substances in the food environment, such as protein, grease, and food fragments. These substances usually reduce the disinfection efficacy of the oxidizing water (Fang, Cannon, & 16

Hung, 2016). Therefore, bovine serum albumin (BSA) (Park et al., 2009) was used as an organic interfering substance in this study, and the effects of the cleaning conditions (no interfering substance) as well at different concentrations of organic interfering substance on the inactivation effect of PAW were prepared. This method could provide a guidance for process parameters (temperature, treatment time, organic interfering substance content, etc.) in practical application of PAW. The experimental data and survival curves of inactivation of B. cereus spores induced by PAW at different BSA contents are shown in Figure 4. It can be observed that the sporicidal efficacy of PAW was significantly decreased as the BSA concentration is increased. The inactivation curves showed that the nonlinear models were more suitable to describe the survival curves compared to the linear model, which was confirmed by comparing the goodness of fit of the linear and nonlinear models using RMSE values (Table 8). Among the three models, the Log-logistic model with RMSE of 0.02 has the best fit for all the survival curves. Also, we noticed that the B. cereus spores suspended in PAW containing BSA were more resistant to the PAW than those suspended in PAW only. Park et al. (2009) reported similar results. Additionally, Klampfl et al. (2014) found that when the content of BSA was 0.03%, there were still viable Clostridium difficile spores even after 10 min of cold plasma treatment, while the treatment time of 5 min was sufficient for completed inactivation of spores in the absence of BSA. And when spores were surrounded by organic matter such as BSA or cell debris, there was no alteration on spores (Connor 17

et al., 2017; Klampfl et al., 2014), which showed that the addition of organic matters may increase the resistance to plasma and PAW. Considering the mentioned effect of BSA above, it’s necessary to reduce the amount of organic interfering substances during PAW processing. 3.5. Inactivation kinetics of B. cereus spores using different activation volumes of PAW The experimental data and survival curves of B. cereus spores inactivated by PAW prepared at different activation volumes are depicted in Figure 5. Compared with linear and Weibull models, the Log-logistic model could fit better the inactivation kinetics of B. cereus spores by different activation volumes of PAW. As presented in Table 10, the goodness of fit of the models were compared by RMSE. The average RMSE value of the Log-logistic model was 0.03, which was less than those of the linear (0.25) and Weibull (0.17) models. The inactivation rate, σ was influenced by PAW activated volume, with the maximum σ recorded at the smallest activation volume (Table 11). The differences for various volumes and time might be explained by considerable variations in the physical and chemical properties of PAW at these conditions. The activation volume significantly affected the ORP of PAW (Zhou et al., 2018). That was consistent with the results in Table 3, which showed that after the PAW activation, the ORP values of the PAW remained relatively high levels (531-573 mV) compared with that of distilled water (342 mV), with the increase in 18

activation volume, the ORP declined, and pH increased. These results showed that a large amount of reactive species was generated in PAW, such as O3, OH, 1O2, and H2O2 (Oehmigen et al., 2010; Pavlovich et al., 2013; Zhang et al., 2013). These reactive species could affect the oxidation-reduction state of antioxidants and damage the outer and inner membrane of spores (Guo et al., 2017; Liao et al., 2007; Ma et al., 2016), which may lead to the inactivation of B. cereus spores. 4. Conclusion This study provided novel and detailed data on the various factors influencing the inactivation B. cereus spores by PAW. The results confirmed that higher temperature( ≤ 55 ℃ ), lower initial spore concentration and BSA content, smaller activation volume could enhance the inactivation effect of PAW on B. cereus spores. In addition, the average R2 and RMSE values of the linear model were 0.94 and 0.24, and 0.97 and 0.16 for the Weibull model while the mean R2 and RMSE values were 0.99 and 0.02 for the Log-logistic model, these results showed that the spore inactivation curves of PAW under different conditions were adequately fitted by the Log-logistic model compared with Linear and Weibull model. The inactivation mechanism of PAW on B. cereus spores was the rupture of spore multilayer structure caused by ROS and RNS in PAW. The results of this study provide fundamental knowledge for the optimization of PAW treatment in order to achieve an efficient inactivation of B. cereus spores in the food industry. Acknowledgment 19

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33

FIGURE CAPTIONS Figure 1 Schematic diagram of plasma jet and generation of plasma-activated water Figure 2 Inactivation curves of B. cereus spores by PAW at different treatment temperatures of 55℃ (■), 40℃ (●), and 25℃ (▲). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 3 Inactivation curves of B. cereus spores by PAW at different initial spore concentrations (105(■); 106(●);107(▲)). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 4 Inactivation curves of B. cereus spores treated with PAW and different BSA contents (0 mg/mL (■); 0.1 mg/mL (●); 0.5 mg/mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 5 Inactivation curves of B. cereus spores treated with different activation volumes of PAW (50 mL (■); 75 mL (●); 100 mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

34

Working gas (air) Power supply

Plasma

Distilled water

Figure 1 Schematic diagram of plasma jet and generation of plasma-activated water 0.5

0.5

0.0

0.0

-0.5

log10(Nt/N0)

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0

-3.5

-1.5 -2.0 -2.5

-2.5 -3.0

-1.0

55℃ 40℃ 25℃

0

-3.0 -3.5 10

20

30

40

50

60

55℃ 40℃ 25℃

0

10

20

30

40

50

60

Time(min)

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5

55℃ 40℃ 25℃

0

10

20

30

40

50

60

Time(min)

Figure 2 Inactivation curves of B. cereus spores by PAW at different treatment temperatures of 55℃ (■), 40℃ (●), and 25℃ (▲). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5

0.0

0.0

-0.5

-0.5

-1.0

-1.0

log10(Nt/N0)

log10(Nt/N0)

0.5

-1.5 -2.0 -2.5

-1.5 -2.0 -2.5

-3.0

-3.0 105CFU 106CFU 107CFU

-3.5 -4.0 0

105CFU 106CFU 107CFU

-3.5 -4.0

10

20

30

40

50

60

0

10

20

Time(min)

30

40

50

60

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 105CFU 106CFU 107CFU

-3.5 -4.0 0

10

20

30

40

50

60

Time(min)

Figure 3 Inactivation curves of B. cereus spores by PAW at different initial spore concentrations (105(■); 106(●);107(▲)). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5

0.5

0.0

0.0 -0.5

-1.0

log10(Nt/N0)

log10(Nt/N0)

-0.5

-1.5 -2.0 -2.5 -3.0 -3.5

-1.0 -1.5 -2.0 -2.5

0 mg/mL 0.1 mg/mL 0.5 mg/mL

0

10

0 mg/mL 0.1 mg/mL 0.5 mg/mL

-3.0

20

30

40

50

-3.5

60

0

Time(min)

10

20

30

Time(min)

36

40

50

60

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 0 mg/mL 0.1 mg/mL 0.5 mg/mL

-3.0 -3.5

0

10

20

30

40

50

60

Time(min)

Figure 4 Inactivation curves of B. cereus spores treated with PAW and different BSA contents (0 mg/mL (■); 0.1 mg/mL (●); 0.5 mg/mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5 0.5

0.0 0.0

-0.5

log10(Nt/N0)

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0

-1.0 -1.5 -2.0 -2.5

-2.5 -3.0 -3.5 0

50 mL 75 mL 100 mL

-3.0

50 mL 75 mL 100 mL

-3.5 10

20

30

40

50

0

60

10

20

30

40

50

60

Time(min)

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5

50 mL 75 mL 100 mL

0

10

20

30

40

50

60

Time(min)

Figure 5 Inactivation curves of B. cereus spores treated with different activation volumes of PAW (50 mL (■); 75 mL (●); 100 mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

37

TABLE CAPTIONS Table 1 Physical and chemical properties of paw obtained by different activation power. Table 2 Physical and Chemical Properties of PAW Obtained at Different Activation Time. Table 3 Physical and Chemical Properties of PAW Obtained by Different Activation Volume. Table 4 Evaluation of different kinetic models for the inactivation of B. cereus spores by PAW at different temperature. Table 5 Different kinetic models’ parameters for the inactivation of B. cereus spores by PAW at different temperature. Table 6 Evaluation of different kinetic models for inactivation of B. cereus spores by PAW at different initial spore concentrations. Table 7 38

Parameters for different kinetic models for the inactivation of B. cereus spores by PAW at different initial spore concentration. Table 8 Evaluation of different kinetic models for the inactivation of B. cereus spores by PAW under different BSA contents. Table 9 Parameters of different kinetic models for the inactivation of B. cereus spores by PAW under different BSA contents. Table 10 Evaluation of different kinetic models for the inactivation of B. cereus spores by different activated volumes of PAW. Table 11 Parameters of different kinetic models for the inactivation of B. cereus spores by different activated volumes of PAW.

39

Table 1 Physical and Chemical Properties of PAW Obtained by Different Activation Power Activation Power(W)

650

700

750

800

850

pH

3.09±0.012

3.08±0.017

3.04±0.009

3.03±0.009

3.04±0.012

ORP(mv)

566±0.8

560±0.8

557±0.5

566±1.3

564±0.8

Table 2 Physical and Chemical Properties of PAW Obtained at Different Activation Time Activation Time(s)

30

60

90

pH

3.35±0.005

3.09±0.012

2.94±0.017 2.94±0.005

2.84±0.008

ORP(mv)

550±1.3

566±0.8

569±0.8

573±1.3

120

150

569±1.3

Table 3 Physical and Chemical Properties of PAW Obtained by Different Activation Volume Activation Volume(mL)

50

pH ORP(mv)

75

125

150

3.09±0.012 3.12±0.012 3.29±0.005

3.32±0.025

3.56±0.036

566±0.8

550±0.8

531±1.6

560±1.2

100

551±0.8

Table 4 Evaluation of different kinetic models for the inactivation of B. cereus spores by PAW at different temperature Temperature (℃)

Linear

Weibull

Log-Logistic

RMSE

R2

RMSE

R2

RMSE

R2

55

0.27

0.96

0.14

0.99

0.03

0.99

40

0.19

0.90

0.13

0.96

0.02

0.99

25

0.13

0.96

0.11

0.98

0.01

0.99

Table 5 Different kinetic models’ parameters for the inactivation of B. cereus spores by PAW at different temperature Temperature (℃)

Linear

Weibull

Log-Logistic

D

b

55

20.180±1.335 0.201±0.033 0.676±0.044 -4.252±0.331 -3.035±0.072 1.480±0.060

40

35.770±3.730 0.174±0.058 0.688±0.085 -2.188±0.089 -2.105±0.097 1.347±0.027

25

35.006±2.209 0.080±0.031 0.753±0.100 -1.908±0.026 -2.084±0.030 1.385±0.008

n

A

σ

τ

Table 6 Evaluation of different kinetic models for inactivation of B. cereus spores by PAW at different initial spore concentrations Initial spore Linear concentration(CFU/mL) RMSE

Weibull

Log-Logistic

R2

RMSE

R2

RMSE

R2

105

0.30

0.96

0.18

0.99

0.03

0.99

106

0.27

0.97

0.14

0.99

0.03

0.99

107

0.29

0.95

0.22

0.97

0.02

0.99

Table 7 Parameters for different kinetic models for the inactivation of B. cereus spores by PAW at different initial spore concentration Initial spore Linear concentration D (CFU/mL) 105

Weibull b

Log-Logistic n

A

σ

15.057±0.987 0.149±0.016 0.801±0.034 -7.657±0.652 -5.355±0.367 41

τ 1.532±0.049

106

20.180±1.335 0.201±0.033 0.676±0.044 -3.761±0.536 -4.252±0.331

1.480±0.060

107

19.777±1.352 0.110±0.039 0.809±0.092 -1.948±0.016 -3.028±0.075

1.292±0.019

Table 8 Evaluation of different kinetic models for the inactivation of B. cereus spores by PAW under different BSA contents BSA content Linear (mg/mL) RMSE

Weibull

Log-Logistic

R2

RMSE

R2

RMSE

R2

0

0.27

0.96

0.14

0.99

0.03

0.99

0.1

0.28

0.85

0.20

0.94

0.01

0.99

0.5

0.14

0.96

0.12

0.96

0.01

0.99

Table 9 Parameters of different kinetic models for the inactivation of B. cereus spores by PAW under different BSA contents BSA content Linear (mg/mL) D

Weibull b

Log-Logistic n

A

σ

τ

0

20.180±1.335 0.201±0.033 0.676±0.044 -4.252±0.331 -3.035±0.072 1.480±0.060

0.5

28.367±3.631 0.206±0.065 0.604±0.084 -2.625±0.039 -2.910±0.067 1.342±0.008

1

33.268±2.193 0.040±0.017 0.922±0.112 -1.786±0.039 -2.047±0.037 1.376±0.013

Table 10 Evaluation of different kinetic models for the inactivation of B. cereus spores by different activated volumes of PAW Activation volume (mL)

Linear

Weibull

RMSE

R2

RMSE

R2

RMSE

R2

50

0.27

0.96

0.14

0.99

0.03

0.99

42

Log-Logistic

75

0.27

0.91

0.19

0.95

0.02

0.99

100

0.22

0.96

0.17

0.97

0.03

0.99

Table 11 Parameters of different kinetic models for the inactivation of B. cereus spores by different activated volumes of PAW Activation volume (mL)

Linear

Weibull

Log-Logistic

D

b

50

20.180±1.335 0.201±0.033 0.676±0.044 -4.252±0.331 -3.035±0.072 1.480±0.060

75

23.902±2.257 0.113±0.020 0.764±0.056 -2.439±0.096 -2.423±0.054 1.257±0.027

100

37.078±2.058 0.057±0.024 0.836±0.105 -1.949±0.029 -2.043±0.031 1.315±0.013

n

A

43

σ

τ

Graphical Abstract Working gas Power supply

Plasma

B. cereus spores PAW

Water

44

Highlights 1. PAW effectively reduced the spore loads at different conditions.
 2. Temperature, BSA content and other factors influenced the efficiency of PAW. 3. The inactivation curves of PAW were adequately fitted by the Log-logistic model.

45

FIGURE CAPTIONS Figure 1 Schematic diagram of plasma jet and generation of plasma-activated water Figure 2 Inactivation curves of B. cereus spores by PAW at different treatment temperatures of 55℃ (■), 40℃ (●), and 25℃ (▲). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 3 Inactivation curves of B. cereus spores by PAW at different initial spore concentrations (105(■); 106(●);107(▲)). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 4 Inactivation curves of B. cereus spores treated with PAW and different BSA contents (0 mg/mL (■); 0.1 mg/mL (●); 0.5 mg/mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model. Figure 5 Inactivation curves of B. cereus spores treated with different activation volumes of PAW (50 mL (■); 75 mL (●); 100 mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

46

Working gas (air) Power supply

Plasma

Distilled water

Figure 1 Schematic diagram of plasma jet and generation of plasma-activated water

0.5

0.5

0.0

0.0

-0.5

log10(Nt/N0)

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0

-3.5

-1.5 -2.0 -2.5

-2.5 -3.0

-1.0

55℃ 40℃ 25℃

0

-3.0 -3.5 10

20

30

40

50

55℃ 40℃ 25℃

0

60

10

20

30

40

50

60

Time(min)

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5

55℃ 40℃ 25℃

0

10

20

30

40

50

60

Time(min)

Figure 2 Inactivation curves of B. cereus spores by PAW at different treatment temperatures of 55℃ (■), 40℃ (●), and 25℃ (▲). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5

0.0

0.0

-0.5

-0.5

-1.0

-1.0

log10(Nt/N0)

log10(Nt/N0)

0.5

-1.5 -2.0 -2.5

-1.5 -2.0 -2.5

-3.0

-3.0 105CFU 106CFU 107CFU

-3.5 -4.0 0

105CFU 106CFU 107CFU

-3.5 -4.0

10

20

30

40

50

60

0

10

20

Time(min)

30

40

50

60

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 105CFU 106CFU 107CFU

-3.5 -4.0 0

10

20

60

50

40

30

Time(min)

Figure 3 Inactivation curves of B. cereus spores by PAW at different initial spore concentrations (105(■); 106(●);107(▲)). Model curves were generated using (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5

0.5

0.0

0.0 -0.5

-1.0

log10(Nt/N0)

log10(Nt/N0)

-0.5

-1.5 -2.0 -2.5 -3.0 -3.5

-1.0 -1.5 -2.0 -2.5

0 mg/mL 0.1 mg/mL 0.5 mg/mL

0

10

0 mg/mL 0.1 mg/mL 0.5 mg/mL

-3.0

20

30

40

50

-3.5

60

0

Time(min)

10

20

30

Time(min)

48

40

50

60

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 0 mg/mL 0.1 mg/mL 0.5 mg/mL

-3.0 -3.5

0

10

20

30

40

50

60

Time(min)

Figure 4 Inactivation curves of B. cereus spores treated with PAW and different BSA contents (0 mg/mL (■); 0.1 mg/mL (●); 0.5 mg/mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

0.5 0.5

0.0 0.0

-0.5

log10(Nt/N0)

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0

-1.0 -1.5 -2.0 -2.5

-2.5 -3.0 -3.5 0

50 mL 75 mL 100 mL

-3.0

50 mL 75 mL 100 mL

-3.5 10

20

30

40

50

0

60

10

20

30

40

50

60

Time(min)

Time(min)

0.5 0.0

log10(Nt/N0)

-0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5

50 mL 75 mL 100 mL

0

10

20

30

40

50

60

Time(min)

Figure 5 Inactivation curves of B. cereus spores treated with different activation volumes of PAW (50 mL (■); 75 mL (●); 100 mL (▲)). Model curves were generated using the (a) Linear model, (b) Weibull model, and (c) Log-logistic model.

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Author contributions Yan Bai: Conceptualization, Methodology, Software, Investigation, Writing-Original Draft. Aliyu Idris Muhammad: Validation, Formal analysis, Visualization. Xinyu liao: Validation, Formal analysis, Visualization. Tian Ding: Resources, Writing - Review & Editing, Supervision, Data Curation. Yaqin Hu: Resources, Writing - Review & Editing, Supervision, Data Curation. Shigenobu Koseki: Writing: Review & Editing. Shiguo chen: Writing: Review & Editing. Xingqian Ye: Writing: Review & Editing Donghong Liu: Writing: Review & Editing

50

Declaration of interest We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted. The authors of this manuscript have directly participated in planning, execution, or analysis of this study. The contents of this manuscript have not been copyrighted or published previously, and are not now under consideration for publication elsewhere.

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