Inactivation of Salmonella during dry co-digestion of food waste and pig manure

Waste Management 82 (2018) 231–240

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Inactivation of Salmonella during dry co-digestion of food waste and pig manure Yan Jiang a, Conor Dennehy a, Peadar G. Lawlor b, Zhenhu Hu c, Qingfeng Yang a, Gemma McCarthy d, Shiau Pin Tan d, Xinmin Zhan a,e,⇑, Gillian E. Gardiner d a

Civil Engineering, College of Engineering & Informatics, National University of Ireland, Galway, Ireland Teagasc, Pig Development Department, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, Ireland School of Civil Engineering, Hefei University of Technology, Hefei 230009, Anhui Province, China d Department of Science, Waterford Institute of Technology, Waterford, Ireland e Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, China b c

a r t i c l e

i n f o

Article history: Received 14 July 2018 Revised 21 October 2018 Accepted 22 October 2018 Available online 28 October 2018 Keywords: Salmonella inactivation Minimum inhibitory concentration Volatile fatty acids Ammonia Dry co-digestion Modified Weibull distribution

a b s t r a c t Extremely high volatile fatty acids (VFAs) and ammonia concentrations can accumulate during dry codigestion of organic wastes, which may inactivate pathogenic microorganisms. In this study, inactivation of Salmonella during dry co-digestion of pig manure (PM) and food waste (FW), which are both reservoirs of zoonotic pathogens, was examined. The effects of pH, VFAs, ammonia and their interactions were assessed on three inoculated Salmonella serotypes. The results show that dry co-digestion significantly decreased the Salmonella inactivation time from several months (in wet digestion) to as short as 6–7 days. A modified Weibull distribution was proposed to simulate Salmonella reduction and to calculate or predict the minimum inhibitory concentrations (MIC) of VFAs and ammonia. Statistical analysis showed that all the factors (pH, VFA type, VFA/ammonia concentration and Salmonella serotype) significantly impacted Salmonella inactivation (P < 0.01). The inhibitory effect sequence was pH > VFA concentration > VFA type > Salmonella serotype in VFA MIC tests, and ammonia concentration > pH > Salmonella serotype in ammonia MIC tests. The toxicity of VFAs was much greater than that of ammonia, and an antagonistic effect was found between VFAs and ammonia on Salmonella inactivation. Apart from the toxicity of free VFAs and free ammonia, the inhibitory effects of pH alone, ionized VFAs and ammonium were also observed. Ó 2018 Elsevier Ltd. All rights reserved.

1. Introduction Land spreading for its fertilizer value is the most common and economic approach for pig manure (PM) management in Ireland, as manure is rich in nutrients including nitrogen, phosphorous, potassium and organic matter (Nolan et al., 2012). However, untreated PM is also considered a reservoir of pathogens, most notably Salmonella (Guan and Holley, 2003). A previous study reported that Salmonella was detected in the manure from half of 30 Irish pig farms surveyed, and most isolates were multi-drug resistant Salmonella Typhimurium (McCarthy et al., 2013). Salmonella can survive for a considerable length of time in PM. For example, McCarthy et al. (2015) found that Salmonella was detectable for as long as 84 days during storage of PM at 10.5 °C. Salmonella can also survive in soil for 16–120 days and in water for ⇑ Corresponding author. E-mail address: [email protected] (X. Zhan). https://doi.org/10.1016/j.wasman.2018.10.037 0956-053X/Ó 2018 Elsevier Ltd. All rights reserved.

5–21 weeks after land application of manure (Ziemer et al., 2010), posing potential risks to humans and animals. Therefore, PM should ideally be treated to eliminate Salmonella and other pathogens prior to land spreading. Salmonella is a major foodborne pathogen, which is a significant public health concern (Hendriksen et al., 2011). Apart from gastroenteritis, it can cause a number of illnesses and long-term sequelae, such as septicemia, reactive arthritis and postinfectious irritable bowel syndrome (Scallan et al., 2015; Soobhany et al., 2017). Salmonellosis is the second most commonly reported gastrointestinal infection and an important cause of foodborne outbreaks in the European Union (EU)/European Economic Area (EEA). In 2015, 95,595 laboratory-confirmed cases were reported in EU/EEA, representing a notification rate of 22.9 cases per 100,000 population (European Centre for Disease Prevention and Control, 2018). As Salmonella is a common contaminant of food products, biosafety and effective inactivation of Salmonella must be considered during management of food waste (FW).

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Anaerobic digestion is a preferable method for treating organic waste such as FW and PM. It yields biogas, mitigates greenhouse gas (GHG) emissions and produces nutrient-rich digestate with a high fertilizer value (Dennehy et al., 2017b, 2017c; Xie et al., 2012; Sheets et al., 2015). Co-digestion of FW and PM can have synergistic effects due to the balanced C/N ratio and buffering effect between volatile fatty acids (VFAs) and ammonia (Borowski et al., 2014; Dennehy et al., 2016; Xie et al., 2011). Biosafety of digestate is strictly controlled before land spreading and Salmonella is required to be absent in 25 g fresh matter according to EU Commission Regulation No 142/2011. However, the widely applied practice of wet digestion at mesophilic temperatures does not completely eliminate Salmonella as 37 °C is its optimum growth temperature (Salsali et al., 2006). Manyi-Loh et al. (2014) showed that it took as long as 133 days for Salmonella counts to reduce from 7.4
103 colony forming units (CFU)/mL to below the limit of detection (LOD; 102 CFU/mL) during mesophilic wet digestion of dairy manure. Smith et al. (2005) observed only a 1.5–2.0 log10 reduction of Salmonella from an initial concentration of 108–109 CFU/mL during mesophilic digestion of biowaste. Similarly, negligible Salmonella reduction (from 1.6
104 CFU/100 mL to 1.1
104 CFU/100 mL) was observed after mesophilic wet digestion of sludge (Salsali et al., 2006). The inactivation of Salmonella during anaerobic digestion may be affected by various operational parameters, such as pH, total solids (TS) content, as well as VFA and ammonia concentrations (Henry et al., 1983). A high VFA concentration at low pH (5,000 mg/L and 5.5, respectively) and a high total ammonia concentration at high pH (6,900 mg/L and 7.9, respectively) are reported to inactivate Salmonella effectively (Kunte et al., 1998; Ottoson et al., 2008). Compared to wetdigestion (TS content < 15%), dry co-digestion (TS content  15%) has advantages such as a smaller reactor volume and a reduced energy consumption for heating (Dennehy et al., 2017a). Extremely high VFA and ammonia concentrations (up to 48.4 g/L and 7.3 g/L, respectively) were observed during the hydrolysis and fermentation stages in FW/PM dry co-digestion systems employed by our group (Jiang et al., 2018), and these high VFA concentrations were found to be the main factor responsible for effective inactivation of pathogenic indicator microorganisms. It was hypothesized that the high VFA and ammonia concentrations generated during dry AD would be effective in killing Salmonella. However, to our knowledge, no such studies have been conducted in this area to date. Besides, the detailed effects of pH, VFAs, ammonia and their interactions on Salmonella inactivation have not been clearly described. Therefore, the objectives of this research were to (1) study the inactivation of Salmonella in dry co-digestion systems for FW and PM; and (2) study the main factors responsible for Salmonella inactivation, including pH, VFA type, VFA/ammonia concentration and Salmonella serotype.

2. Materials and methods 2.1. Dry co-digestion of FW and PM To assess the inactivation of Salmonella during dry co-digestion of FW and PM, a laboratory-scale batch experiment was conducted. PM was collected from a local Salmonella category 1 farm, i.e. low Salmonella prevalence, in Co. Galway, Ireland and centrifuged at 1500
g for 5 min to obtain the solid fraction (MSE super minor centrifuge, London, UK). Fresh FW was collected from 10 local residences in Galway City, Ireland, and was mixed and ground to a particle size of <2 mm prior to use. The inoculum was dewatered anaerobic sludge taken from a local wastewater treatment plant in Galway. The TS of the FW, PM and sludge were 24.0%, 19.5% and 22.1%, respectively. Six 1 L glass digesters were used in the

experiment (3 for high Salmonella inoculation, and 3 for low Salmonella inoculation). In each digester, 130 g FW, 165 g PM and 505 g sludge (wet weight) were added to obtain a sludge inoculum rate of 50% and a FW/PM ratio of 50:50 based on volatile solids (VS) according to our previous study (Jiang et al., 2018). The TS content was adjusted to 20% by adding tap water. 2.2. Preparation of Salmonella cultures, inoculation of digesters and digestate analyses Three Salmonella serotypes were selected for use in this experiment as they are the ones most commonly found in PM in Ireland (Burns et al., 2016; McCarthy et al., 2013). They were Salmonella Derby (WIT 413), Salmonella Typhimurium DT104 (WIT 384) and a monophasic variant of Salmonella Typhimurium 4,[5],12:i:- (Ashtown No 2040). The procedures for preparation, spiking and analysis of Salmonella were previously described by McCarthy et al. (2015). Briefly, each Salmonella serotype was streaked from 80 °C stock onto nutrient agar (Oxoid, Hampshire, UK) and incubated overnight at 37 °C. A single colony of each serotype was inoculated into separate 5 mL brain heart infusion (BHI) broth (Oxoid, Hampshire, UK) and incubated overnight at 37 °C. The Salmonella broth cultures were centrifuged at 18,620
g for 2 min, and the cell pellets were washed twice and then re-suspended in maximum recovery diluent (MRD, Oxoid, Hampshire, UK). The concentration (CFU/mL) of Salmonella in each suspension was calculated using a standard curve of OD600nm versus CFU/mL, which was constructed for each serotype. The Salmonella cocktail was made up of 1/3 of each Salmonella serotype and diluted in MRD so as to obtain high (1
106 CFU/ mL) and low (1
104 CFU/mL) Salmonella concentrations in the suspensions. Unexpectedly, a high Salmonella count (4.4
103 CFU/g) was found in the sludge inoculum. After spiking, the initial concentrations of Salmonella in the high and low Salmonella inoculation digesters (in triplicate) were 8.2
105 and 5.9
103 CFU/g, respectively. The reactor contents were then mixed well using a sterile wooden spatula, incubated at 37 °C and shaken by hand every day before sampling. Samples (2 g) were taken every day for analysis of pH, TS, VS, VFAs and total ammonia nitrogen (TAN). The analysis methods and calculation of free VFAs and free ammonia were as previously detailed by Jiang et al. (2018). A 25 g sample was taken from each digester every day and homogenized in 225 mL buffered peptone water (BPW, Oxoid, Hampshire, UK) in order to obtain a 1 in 10 dilution. A 10-fold dilution series was then performed using MRD. Enumeration of Salmonella was as detailed by McCarthy et al. (2015). Briefly, 100 lL of the dilutions were spread-plated in duplicate onto tryptone soy agar (TSA; Oxoid) and incubated at 30 °C for 2 h. The plates were then overlaid with xylose lysine deoxycholate (XLD) agar (Oxoid) and incubated at 37 °C for a further 24 h. Colonies on plates with between 30 and 300 CFU were counted after the second incubation period. The counts were averaged and presented as CFU/g. If the counts on any of the plates were below the LOD, the presence/absence of Salmonella was determined using the standard method (ISO, 2007) with some modifications as previously described by McCarthy et al. (2015) as follows. Apart from XLD agar, modified Brilliant Green agar (BGA; Oxoid) was used for additional selective plating. Five suspect Salmonella colonies were taken from each XLD and BGA plate (in total 10 colonies) and streaked twice onto Nutrient Agar (NA, Oxoid) to purify. Colonies from the NA plates were then inoculated into Urea Agar slants (Oxoid), Triple Sugar Iron Agar Slants (Oxoid) and Lysine Decarboxylase Broth (Oxoid) and incubated at 37 °C for 24 h. Presumptive Salmonella colonies were tested using the Salmonella Latex Agglutination kit (Oxoid) to confirm identity. The enumeration method was continued in conjunction with the presence/absence

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2.3. MIC experiments Minimum inhibitory concentration (MIC) experiments were conducted to further investigate the inactivation mechanisms of Salmonella in FW/PM dry co-digestion systems. They were conducted in 96-well microtiter plates (Sarstedt, Hildesheim, Germany) according to the standard protocol described by Wiegand et al. (2008). The antimicrobial activities of VFAs, ammonia and pH were assessed against each Salmonella serotype. The tested VFAs were obtained from Sigma-Aldrich (St. Louis, MO, USA) and included acetic acid (HAC), propionic acid (HPR), butyric acid (HB), isobutyric acid (HIB), valeric acid (HV), isovaleric acid (HIV) and an equimolar mixture of these individual VFAs (MVFA). Ammonia was diluted from a 35% ammonia solution (Fisher Scientific, Ballycoolen, Dublin, Ireland). The stock solutions of VFAs and ammonia were prepared at concentrations ranging from 100 to 1,000 mmol/L (in increments of 100 mmol/L) using sterile distilled water and adjusted to pH 6.0, 7.0, 8.0 and 9.0 with 2 mol/L HCl or NaOH using a pH meter (pH 3210, WTW, Weilheim, Germany). The stock solutions were then filter-sterilised through 0.45 lm cellulose nitrate membrane filter paper (Whatman, Maidstone, UK) and stored at 4 °C until use. The BHI broth was adjusted to pH 6.0, 7.0, 8.0 and 9.0 using the method outlined above. The pH probe was sterilized with 70% ethanol solution and Virkon disinfectant (VWR, Lutterworth, Leicestershire, UK) and rinsed thoroughly with sterile distilled water between samples. Each Salmonella culture was diluted using BHI broth to obtain a suspension of 1
106 CFU/mL according to the standard curve, and all suspensions were used within 30 min. The sample wells contained 100 lL Salmonella suspension and 100 lL VFA or ammonia solution, resulting in a Salmonella concentration of 5
105 CFU/mL and VFA or ammonia concentrations of 50–500 mmol/L (in increments of 50 mmol/L). These VFA and ammonia concentrations were selected based on the maximum concentrations observed in previous FW/PM dry co-digestion systems (Jiang et al., 2018). Three control wells were used for each test: sterility control (SC; 200 lL BHI broth), growth control (GC; 100 lL Salmonella suspension and 100 lL BHI broth) and antimicrobial agent control (AC; 100 lL VFA/ammonia solution and 100 lL BHI broth). As a result, 960 conditions in total (3 Salmonella serotypes
8 VFA or ammonia solutions
10 concentrations
4 pH’s) were assessed, each in triplicate. The OD600nm of each well was recorded at time 0 h using an EL
808 Ultra Microplate Reader (Bio Tek, Bad Friedrichshall, Germany), the microtiter plates were then covered with lids and incubated at 37 °C. The OD600nm of each well was read hourly during the first 7 h and then the final value was read after 20 h. At each time point, the triplicate readings for each condition were averaged for analysis. The MIC is defined as the lowest concentration of the antimicrobial agent that visibly inhibits growth of the bacteria as observed with the unaided eye (Wiegand et al., 2008). In this study, no visible growth was observed with the unaided eye when the total Salmonella reduction (RT) was 80% compared with the control (CLSI, 2012; ESCMID, 2003; Kunte et al., 2000). To quantify it, the MIC was calculated at the RT of 80% as described in Eq. (1), which is more accurate and less prone to experimental or subjective error than the unaided eye observation method.

RT ð%Þ ¼

ðODGC  ODSC ÞpH¼7:0  ðODSample  ODAC ÞpH¼i ðODGC  ODSC ÞpH¼7:0

ð1Þ

where RT is the total Salmonella reduction, %; ODGC, ODSC, ODSample and ODAC are the OD600nm readings of GC, SC, sample and AC wells after 20 h, respectively, and i represents the assessed pH value (6.0, 7.0, 8.0 and 9.0). It has been reported that pH plays an indirect role in bacterial inactivation by affecting concentrations of free VFAs and free ammonia (Himathongkham et al., 2000; Sahlström, 2003), but the effect of pH itself on Salmonella inactivation is not clear. In this study, the effect of pH was assessed and the Salmonella reductions caused by pH (RpH) were calculated by Eq. (2).

RpH ð%Þ ¼

ðODGC  ODSC ÞpH¼7:0  ðODGC  ODSC ÞpH¼i

ð2Þ

ðODGC  ODSC ÞpH¼7:0

where RpH is the Salmonella reductions only caused by pH, %. 2.4. Models As shown in Fig. 1, five types of curves were observed in the MIC experiment when describing the effects of VFA and ammonia concentrations on Salmonella reduction; they were exponential curves (A), convex curves (B), linear curves (C), S-shaped curves (D) and concave curves with a lag phase (E). The Weibull distribution was selected to simulate these curves because of its diverse patterns, which can indicate concave, linear and convex curves (Van Boekel, 2002). While considering the effect of VFA/ammonia concentration on Salmonella reduction, the traditional Weibull distribution can be described as Eqs. (3) and (4).

dN=dc a c b1 c b ¼ f ðcÞ ¼  ð Þ eðaÞ N0 b a

ð3Þ

N  N0 c b ¼ 1  eðaÞ N0

ð4Þ

R¼

where N0 and N are the Salmonella concentrations at VFA/ammonia concentrations of zero and c, respectively, which were described by OD600 in this study; c is the VFA/ammonia concentration, mmol/L; a is the scale parameter and b is the shape parameter. However, the traditional Weibull distribution can only simulate curve types A, B and C, but not curves D and E. Both curves D and E contain a lag Salmonella reduction (R0) at low VFA/ammonia concentrations. This means that a non-inhibition concentration (NIC) exists (Lambert and Pearson, 2000), below which the growth of Salmonella was not affected by VFAs/ammonia. Only when the concentration was above NIC, did the VFA/ammonia inhibit the growth of Salmonella. Apart from R0, curve D also contains a sta-

100%

Salmonella reduction

method for a further 3 days after obtaining a negative result in case of uneven distribution or revival of Salmonella. Reactors were considered negative for Salmonella when 3 consecutive time point tests were negative.

80% A 60%

B C

40%

D 20%

E

0% 0

100

200 300 400 500 600 Concentration (mmol/L)

700

Fig. 1. Salmonella inactivation curves. Graphic representations of five types of curves indicating the effects of VFA and ammonia concentrations on Salmonella reduction in Brain Heart Infusion broth (A: exponential curves; B: convex curves; C: linear curves; D: S-shaped curves; and E: concave curves with a lag phase).

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tionary Salmonella reduction (Rf) at high VFA/ammonia concentrations, indicating that after a threshold concentration (within the tested condition of 500 mmol/L used in this study), increasing VFA/ammonia concentration did not result in a greater Salmonella reduction. This may be because some Salmonella cells mutate or are intrinsically resistant to VFAs/ammonia, or during this period some cells can resynthesize some vital components to protect them from the toxicity of VFAs/ammonia (Xiong et al., 1999). R0 and Rf were introduced into the traditional Weibull distribution to form a modified Weibull distribution (Eq. (5)), which was used to simulate the reductions of Salmonella in this study (curves A-E). c b

R ¼ R0 þ ðRf  R0 Þð1  eðaÞ Þ

c0

ð5Þ

where R0 is the lag Salmonella reduction at low VFA/ammonia concentrations, %; and Rf is the stationary Salmonella reduction at high VFA/ammonia concentrations, %.

2.5. Statistical analysis Statistical analysis was performed using SPSS 22.0 (IBM, USA). Salmonella reductions across different pH values were compared using one-way analysis of variance (ANOVA) followed by the Bonferroni post hoc test for pairwise comparison. Multivariate analysis of variance (MANOVA) was performed to determine the effect of multi-factors (Salmonella serotype, pH, VFA type, VFA and ammonia concentrations) and their interactions on Salmonella reduction and MIC. The range analysis was performed to assess the effect sequence of the above factors. Post hoc multiple comparisons were conducted using the Bonferroni method to explore the effect sequence of different levels in each factor. A P value of less than 0.05 was considered statistically significant.

3. Results and discussion 3.1. Results of Salmonella inactivation during dry co-digestion of FW/ PM The Salmonella inactivation in dry co-digestion systems and variations of pH/TAN/VFAs in the digesters are shown in Fig. 2. No significant differences were observed between the pH/TAN/ VFAs in the high and low Salmonella inoculation digesters (P > 0.05). In both high (8.2
105 CFU/mL) and low (5.9
103 CFU/mL) inoculation digesters, Salmonella counts increased during the first day (Fig. 2a). Two factors could be responsible for this: firstly, there is likely a plentiful supply of nutrients at the beginning of digestion; secondly, the low initial VFA (237–402 mg/L) and TAN (1,423–1,627 mg/L) concentrations were not high enough to inhibit the growth of Salmonella (Manyi-Loh et al., 2014). Thereafter, Salmonella counts in both high and low inoculation digesters began to decrease on the second day. The serotypes of representative Salmonella isolates recovered on Day 4 are shown in Fig. S1. Salmonella was completely eliminated from all digesters within 6–7 days. The enumeration and presence/absence detection of Salmonella were continued for a further 3 days and the experiment finished after 9 days as all samples remained Salmonella-negative. The higher initial Salmonella concentration did not prolong the inactivation time. The VFA and TAN concentrations increased sharply on the first day but stabilized thereafter at 7077 ± 593 mg/L (118 ± 10 mmol/L) and 3241 ± 386 mg/L (232 ± 28 mmol/L), respectively, with the pH remaining stable at 7.1 ± 0.2 after an initial reduction from 8.4 at day 0 (Fig. 2b–d). HAC, HPR and HIB were the main VFAs detected, accounting for about 53.4%, 25.0% and 21.6% of the total VFA concentrations, respectively.

3.2. Effect of pH on Salmonella inactivation The effect of pH on the growth of the three Salmonella serotypes was determined using the OD600nm readings obtained from GC wells without VFA/ammonia addition. As shown in Fig. 3, for all serotypes, the best growth was observed at pH 7.0, indicating that neutral pH is optimal for Salmonella growth, in keeping with the results of Salsali et al. (2006). No significant differences were observed between pH 7.0 and 8.0, indicating that slightly alkaline conditions did not inhibit growth. Salmonella growth at pH 9.0 (P < 0.05) and 6.0 (P < 0.01) was significantly lower than those found at pH 7.0 and 8.0, indicating that both acid and alkaline conditions inhibit the growth of Salmonella. Salmonella reductions caused by pH were calculated according to Eq. (2); the reductions at pH 6.0 and 9.0 ranged from 50.6% to 60.3% and 12.4% to 20.4%, respectively. These demonstrated the direct inhibitory effect of pH on Salmonella growth. It is reasonably hypothesized that the inhibitory effect of H+ (106 mol/L at pH 6.0) is much higher than that of OH (105 mol/L at pH 9.0). The growth of different Salmonella serotypes at different pH values is shown in Fig. S2. 3.3. Effect of VFA on Salmonella The reductions of Salmonella at various VFA concentrations were simulated by the modified Weibull distribution (Eq. (5)), with the results shown in Fig. 4. The sums of square errors (SSE) were  0.023 and R2 were 0.942, indicating that the models can simulate the Salmonella reductions with a high degree of accuracy. The MIC values were calculated from the modified Weibull distribution at a Salmonella reduction of 80%, with the results shown in Table 1. Compared with observation by eye, calculation of the MIC from the modified Weibull distribution is more accurate, and can predict values beyond the experimental concentrations used. Some MIC values were not available (NA) due to stationary reduction phases, where the increase of VFAs did not result in additional reductions in Salmonella growth (Curve D in Fig. 1). Wood et al. (2001) reported that when exposed to high to medium osmolality, S. Typhimurium can accumulate compatible solutes, e.g. trehalose, through biosynthetic or transport systems to protect itself from high osmotic pressure. In addition, S. Typhimurium can change its membrane fatty acid composition under organic acid conditions, which makes it more resistant to stress. Alvarez-Ordonez et al. (2008) reported that at 37 °C, the unsaturated fatty acid/saturated fatty acid ratio of acid-adapted S. Typhimurium was very low (0.10–0.22) compared with non-acid adapted cells (0.41– 0.48), indicating that it had a low membrane fluidity and was more resistant to stress. Obviously, the Salmonella reductions increased with the increase of VFA concentrations. The VFAs at pH 6 posed greater harm to Salmonella than at the other pH values, with the reductions increasing sharply to  100% and the MIC ranging 31–76 mg/L. VFA types also impacted Salmonella inactivation; HV and HIV led to high reductions and low MIC values, and HAC seemed the least harmful. However, the detailed effects of pH, VFA type, VFA concentration and Salmonella serotype were complex and the statistical analysis was conducted for further in-depth study. A four-way ANOVA was conducted to assess the effects of Salmonella serotype, pH, VFA type and VFA concentration on Salmonella reduction, and the effects of the factors Salmonella serotype, pH and VFA type on MIC were assessed using a threeway ANOVA. The results showed that all of the factors analyzed had significant effects on Salmonella reduction and MIC (P < 0.01). Range analysis was then conducted to analyze the effect sequence of these factors on each dependent variable, and the Bonferroni post hoc test was performed to assess the effect sequence of the levels for each factor, with the results shown in Table 2.

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(b)

8.0

Total ammonia nitrogen (mg/L)

Salmonella (Log CFU/g)

High inoculation Low inoculation 6.0

4.0

2.0

0.0

9.0

7.5 4500 6.0 4.5

3000 TAN - High inoculation TAN - Low inoculation pH - High inoculation pH - Low inoculation

1500

3.0 1.5 0.0

0 0

1

2

3

4 5 6 Time (d)

7

8

9

0

1

2

3

4 5 6 Time (d)

7

8

9

(d) 10000 High inoculation HAC HPR

HIB

TVFA

8000 6000 4000 2000 0

Volatile fatty acids (mg/L)

(c) 10000 Volatile fatty acids (mg/L)

6000

pH

(a)

Low inoculation HAC HPR

8000

HIB

TVFA

6000 4000 2000 0

0

1

2

3

4 5 Time (d)

6

7

8

9

0

1

2

3

4 5 Time (d)

6

7

8

9

Fig. 2. Performance in digesters. Inactivation of Salmonella (a), pH and total ammonia nitrogen variations (b) and volatile fatty acid compositions (c, d) during a 9 - day dry codigestion of food waste and pig manure. (HAC: acetic acid; HPR: propionic acid; HIB: isobutyric acid; TVFA: total volatile fatty acids; High inoculation: initial Salmonella concentration = 8.2
105 CFU/g; Low inoculation: initial Salmonella concentration = 5.9
103 CFU/g).

1.8 Salmonella growth (OD600)

pH=6.0

pH=7.0

pH=8.0

pH=9.0

1.5 A A

A A

1.2

B

0.9 0.6

Aa

B

C

C

Aa

Ab

Bc

0.3 0.0

S. Derby

S. Typhimurium S. Typhimurium DT104 4,[5],12:i:-

Fig. 3. Effect of pH on Salmonella. Effect of pH on the growth of different Salmonella serotypes (Retention time = 20 h, initial Salmonella concentration  5
105 CFU/g. Values that do not share a common capital letter are significantly different at P < 0.01. Values that do not share a common lowercase letter are significantly different at P < 0.05).

The higher inhibitory effect of VFAs is evidenced by a higher Salmonella reduction and a lower MIC. Range analysis showed that the inhibitory effect sequence of these factors was: pH > VFA concentration > VFA type > Salmonella serotype. However, the ranges of the first three factors were almost one order of magnitude larger than that of the Salmonella serotype, therefore the effects of pH, VFAs and their interactions will be highlighted in the following analysis. Bonferroni post hoc test showed that the inhibitory effect sequence of pH was 6.0 > 7.0 > 8.0 > 9.0 (P < 0.01), which differed

from that of pH alone (6.0 > 9.0 > 8.0 & 7.0), indicating the interactions between pH and VFA. The inhibitory effect of VFAs is pH dependent because pH affects the conversion of ionized VFA to free VFA (Sahlström, 2003). Free VFAs are usually considered the real toxic factor for bacteria, as free VFAs can pass through the cell membrane easily and dissociate within the cell, resulting in a lower intracellular pH (Puchajda and Oleszkiewicz, 2006). This in turn decreases the proton motive force (PMF) across the cell membrane, which inhibits the bacterium by impacting metabolism and electrophysiology of the cell, acidifying the cytoplasm and causing osmotic problems (Kashket, 1987, 1985; Roe et al., 1998; Sheu and Freese, 1972). Although pH values of 7.0 and 8.0 themselves did not cause significant Salmonella reductions (Section 3.2), higher free VFA concentrations were induced at these pH values compared with at pH 9.0. A significant positive correlation was observed between VFA concentrations and Salmonella reductions (P < 0.01). High VFA concentrations meant highly available acid molecules and a high osmotic gradient across cell membranes, resulting in increased toxicity to Salmonella. For VFA type, the inhibitory sequence observed in this study was: HV > HIV  HPR  MVFA > HB  HIB > HAC (P < 0.05). In general, this was in agreement with the fact that the inhibitory effect of VFAs increases with increasing chain length. Sheu and Freese (1972) reported inhibitory sequence of VFAs on Bacillus subtilis as follows: n-hexanoic acid > n-pentanoic acid > HB > HPR > HAC > formic acid. Back et al. (2009) indicated that HPR > HAC > formic acid in terms of inhibitory effects against Enterobacter sakazakii. However, Salsali et al. (2006) reported that HAC > HPR > HB during Salmonella inactivation, which contradicts the results obtained in this study. But Salsali et al. (2006) compared the effect of different VFAs at the same mass concentration, e.g., at 6,000 mg/L, the molar concentra-

Y. Jiang et al. / Waste Management 82 (2018) 231–240

40% 20%

S. Typhimurium 4,[5],12:i:- reduction

HPR

HB

HIB

HV

HIV

VFA MVFA

0% 100% 0 80%

60%

40%

20%

20%

0% 0% 0% 100 200 300 400 100% 500 0 100 200 300 400 100% 500 0 100 200 300 400 100% 500 0 100 200 300 400 500 pH=7.0 pH=8.0 pH=9.0 pH=6.0 80% 80% 80% 60%

40%

40%

20%

20%

80%

60%

40%

20%

0% 100 200 300 400 100% 500 0 100 pH=7.0 pH=6.0 80%

200

300

60%

60%

40%

40%

20%

20%

0% 400 100% 500 0

100 200 pH=8.0

0% 400 100% 500 0

300

80%

80%

60%

60%

60%

60%

40%

40%

40%

40%

20%

20%

20%

20%

0%

pH=9.0

80%

60%

40%

60%

0% 100% 0 S. Typhimurium DT104 reduction

HAC

100% pH=8.0

80%

S. Typhimurium 4,[5],12:i:-…

60%

100%

S. Derby reduction (%)

100% pH=7.0 pH=6.0 80%

80%

S. Derby reduction (%)

S. Derby reduction

100%

S. Derby reduction (%)

236

100 200 pH=9.0

300 400

500

0% 0% 0% 0 100 200 300 400 500 0 100 200 300 400 500 0 100 200 300 400 500 0 100 200 300 400 500 Concentration (mmol/L) Concentration (mmol/L) Concentration (mmol/L) Concentration (mmol/L)

Fig. 4. Effects of pH and VFAs on Salmonella. Simulation of Salmonella reductions due to variations in different VFAs at four different pH’s. (Retention time = 20 h, initial Salmonella concentration  5
105 CFU/g. The scatter plots are the experimental data, and the solid lines represent the responses predicted by the modified Weibull distribution. HAC: acetic acid; HPR: propionic acid; HB: butyric acid; HIB: isobutyric acid; HV: valeric acid; HIV: isovaleric acid; MVFA: equimolar mixture of the above individual VFAs).

Table 1 Minimum inhibitory concentrations of VFA for three different Salmonella serotypes at four different pH’s. MIC (mmol/L)

a b c d e f g h

HAC

a

HPR

b

HB

c

d

HIB

HV

e

HIV

f

MVFA

pH = 6

S. Derby S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

71 55 76

49 44 50

53 50 61

53 59 76

31 33 35

35 37 42

42 40 49

pH = 7

S. Derby S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

522 426 640

190 208 236

345 274 338

396 316 327

93 104 109

176 184 211

233 236 276

pH = 8

S. Derby S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

627 NA 973

416 523 381

559 NA 629

NA NA NA

232 244 254

322 341 362

NA NA NA

pH = 9

S. Derby S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

605 685 908

454 502 584

653 675 934

676 711 815

302 287 329

458 442 484

596 642 792

h

g

HAC: acetic acid. HPR: propionic acid. HB: butyric acid. HIB: isobutyric acid. HV: valeric acid. HIV: isovaleric acid. MVFA: equimolar mixture of the above individual VFAs. NA: not available.

tion of HAC (100 mmol/L) > HPR (81 mmol/L) > HB (68 mmol/L). Thus, the high inhibitory effect of HAC on Salmonella may not be simply because of its short chain length as explained in the paper. As regards VFA structure, it was noted that the inhibitory effect of linear chain VFAs was greater than that of branched chain VFAs (e.g. HV > HIV and HB  HIB), probably because linear chain VFAs could cross the cell membrane more readily. Ionized VFAs also affect the inactivation of pathogens because they may change the osmotic pressure of the cell (Roe et al., 1998). As shown in Table S2, the effect of free VFA concentrations

at pH 9.0 and a total VFA concentration of 50 mmol/L were negligible (free VFA = 0.003–0.004 mmol/L), which can be considered similar to those at pH 9.0 without the addition of VFA. As shown in Fig. 5 a, Salmonella reductions at pH 9.0 and a total VFA concentration of 50 mmol/L were 12.1% – 23.0% higher than those at pH 9.0 and a total VFA concentration of 0 mmol/L, which could be attributed to 50 mmol/L ionized VFAs. On the other hand, the free VFA concentrations at pH 7.0 and a total VFA concentration of 50 mmol/L (free VFA = 0.28–0.37 mmol/L) were similar to those at pH 8.0 and a total VFA concentration of 500 mmol/L (free

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Y. Jiang et al. / Waste Management 82 (2018) 231–240 Table 2 Range analysis and Bonferroni post hoc test for the effects of volatile fatty acids on Salmonella reduction (%) and minimum inhibitory concentration (mmol/L). TSalma

Reduction A

MIC

b A

S. Typhimurium DT104 S. Derby S. Typhimurium 4,[5],12:i:-

69.61 66.97B 66.20C

326 315 A 384B

Range

3.41

69

pH 6.0 7.0 8.0 9.0

Reduction A

MIC A

96.86 72.60B 51.24C 49.67 D

50 278B 481C 597 D

47.19

547

TVFAc e

HV HIVf HPRg MVFAh HBi HIBj HACk

Reduction A

MIC A a

84.52 76.06B 69.25C 68.87C 62.06D 59.65E 52.74F

171 258B b 303B bc 323BCE c 429C d 381C d 530D e

31.78

359

CVFA 0 50 100 150 200 250 300 350 400 450 500

d

Reduction 40.63A 51.05B 58.04C 62.87D 67.82E 71.91F 75.53G 79.18H 82.85I 86.06G 45.43

Within a column, values that do not share a common capital letter superscript are significantly different at P < 0.01; and values that do not share a common lowercase letter superscript are significantly different at P < 0.05. a TSalm: Salmonella serotype. b MIC: minimum inhibitory concentration. c TVFA: volatile fatty acid (VFA) type. d CVFA: VFA concentration. e HV: valeric acid. f HIV: isovaleric acid. g HPR: propionic acid. h MVFA: mixed volatile fatty acid. i HB: butyric acid. j HIB: isobutyric acid. k HAC: acetic acid.

pH=9.0, total VFA = 0 mmol/L

(a)

Salmonella reduction

50.0%

S. Derby

pH=9.0, total VFA = 50 mmol/L

S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

40.0% 30.0% 20.0% 10.0%

pH=7.0, total VFA = 50 mmol/L

(b) 100.0% Salmonella reduction

S. Derby

HAC HPR HB HIB HV HIV MVFA

HAC HPR HB HIB HV HIV MVFA

HAC HPR HB HIB HV HIV MVFA

0.0%

pH=8.0, total VFA = 500 mmol/L

S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

80.0% 60.0% 40.0% 20.0%

HAC HPR HB HIB HV HIV MVFA

HAC HPR HB HIB HV HIV MVFA

HAC HPR HB HIB HV HIV MVFA

0.0%

Fig. 5. Salmonella reductions at similar free VFAs. Salmonella reductions at (a) pH = 9.0, VFA = 0 mmol and pH = 9.0, VFA = 50 mmol/L; and (b) pH = 7.0, VFA = 50 mmol/L and pH = 8.0, VFA = 500 mmol/L. (Retention time = 20 h, initial Salmonella concentration  5
105 CFU/g. HAC: acetic acid; HPR: propionic acid; HB: butyric acid; HIB: isobutyric acid; HV: valeric acid; HIV: isovaleric acid; MVFA: equimolar mixture of the above individual VFAs).

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Y. Jiang et al. / Waste Management 82 (2018) 231–240

VFAs (31–973 mmol/L). These indicated that the inhibitory effect of VFAs on Salmonella was much greater than that of ammonia. The effect of pH on Salmonella reductions varied with different Salmonella serotypes, and pH 9.0 did not show dominant advantages over pH 6.0. The detailed effects of pH, ammonia concentration and Salmonella serotype were further assessed by statistical analysis. A three-way ANOVA was conducted to assess the effects of Salmonella serotype, pH, and total ammonia concentration on Salmonella reduction, and a two-way ANOVA was performed to assess the effects of Salmonella serotype and pH on MIC. The results showed that Salmonella serotype, pH and total ammonia concentration were all significant factors for Salmonella reduction (P < 0.01), while pH was the only significant factor for MIC (P < 0.01). Range analysis and Bonferroni post hoc tests were used to analyze the effect sequence of the factors and their respective levels on each dependent variable, with the results shown in Table 4. The range analysis showed that the inhibitory effect sequence of the factors was: total ammonia concentration > pH > Salmonella serotype. The Salmonella reductions at pH 9.0 and 6.0 were

VFA = 0.29–0.37 mmol/L), but the ionized VFA concentrations at pH 8.0 were 450 mmol/L higher than those at pH 7.0 (Table S2). As indicated in Section 3.2, pH 7.0 and 8.0 themselves did not cause Salmonella reductions; therefore, the higher Salmonella reductions (23.0% – 82.3%) at pH 8.0 than at pH 7.0 might be due to the contribution of 450 mmol/L ionized VFAs (Fig. 5b). All of these demonstrate the inhibitory effect of ionized VFAs on Salmonella; however, the detailed inactivation mechanism is not clear and needs further study. 3.4. Effect of ammonia on Salmonella The effect of ammonia on Salmonella was also simulated by the modified Weibull distribution (Fig. 6), and the MIC was calculated at the Salmonella reduction of 80% (Table 3). The Salmonella reductions increased slowly with the increase of total ammonia concentration. Besides, the Salmonella reductions caused by ammonia (25.0% – 65.4%) were much lower than those caused by similar VFA concentrations (40.63% – 86.06%), and the MIC values for ammonia (588–2,284 mmol/L) were much higher than those of

S. Derby reduction

80%

pH=7.0

pH=8.0

pH=9.0

60% 40% 20% 0%

100% S. Typhimurium 4,[5],12:i:- reduction

100% pH=6.0

S. Typhimurium DT104 reduction

100%

80%

60% 40% 20% 0%

0

100 200 300 400 Ammonia (mmol/L)

500

80%

60% 40% 20% 0%

0

100 200 300 400 Ammonia (mmol/L)

500

0

100 200 300 400 Ammonia (mmol/L)

500

Fig. 6. Effects of pH and ammonia on Salmonella. Simulation of Salmonella reduction caused by ammonia at four different pHs. (Retention time = 20 h, initial Salmonella concentration  5
105 CFU/g. The scatter plots are the experimental data, and the solid lines represent the responses predicted by the modified Weibull distribution).

Table 3 Minimum inhibitory concentrations of total ammonia on Salmonella at four different pH’s.

a

MIC (mmol/L)

pH = 6.0

pH = 7.0

pH = 8.0

pH = 9.0

S. Derby S. Typhimurium DT104 S. Typhimurium 4,[5],12:i:-

781 588 697

758 646 841

988 690 720

NAa 2284 2181

NA: Not available.

Table 4 Range analysis and Bonferroni post hoc test for the effect of ammonia on Salmonella reduction (%) and minimum inhibitory concentration (mmol/L). TSalma

Reduction A

MICb

pH A

S. Derby S. Typhimurium 4,[5],12:i:S. Typhimurium DT104

50.93 43.87B 41.31C

1226 1110A 1052A

Range

9.63

174

6.0 7.0 8.0 9.0

Reduction A

MIC A

50.86 40.59B 39.55B 50.47 A

689 748A 799A 2281B

11.31

1592

CAmc 0 50 100 150 200 250 300 350 400 450 500

Reduction 37.75Aa 38.18Aa 38.76ABa 39.63ABab 42.40Bb 45.03BCbc 47.65Cc 51.23CDd 55.14De 57.91De 20.16

Within a column, values that do not share a common capital letter superscript are significantly different at P < 0.01; and values that do not share a common lowercase letter superscript are significantly different at P < 0.05. a TSalm: Salmonella serotype. b MIC: minimum inhibitory concentration. c CAm: Total ammonia concentration.

Y. Jiang et al. / Waste Management 82 (2018) 231–240

significantly higher than those at pH 7.0 and 8.0 (P < 0.01). Similar to VFA, the effect of ammonia on bacterial inactivation has been reported to be pH-dependent, as pH affects the conversion of free ammonia and ammonium (Himathongkham et al., 2000). Free ammonia is considered more toxic because it can cross the cell membrane by simple diffusion, and dissociate to alkalinize the cytoplasm (Ottoson et al., 2008). Park and Diez-Gonzalez (2003) reported that a free ammonia concentration of 5 mmol/L was the threshold inhibitory concentration for Salmonella, as Salmonella grew at 5 mmol/L. In this experiment, the free ammonia concentrations of 0.06–0.64 mmol/L at pH 6.0 were much lower than the threshold inhibitory concentration reported. The average Salmonella reduction at pH 6.0 was 50.9%, equivalent to a Salmonella reduction of 50.6% – 60.3% with no addition of ammonia (GC tests; Section 3.2), so H+ should be the main inhibitory factor at pH 6.0. At pH 7.0, the free ammonia concentration ranged 0.6–4.4 mmol/L (<5 mmol/L) at the total ammonia concentration of 50– 350 mmol/L, and the Salmonella reduction ranged 25.0% – 43.4%. As pH 7.0 did not cause Salmonella reduction itself, it was assumed that ammonium contributed to the reduction. The free ammonia concentration at pH 8.0 ranged 5.7–56.8 mmol/L and caused the Salmonella reduction of 29.8% – 56.2%. At pH 9.0, the free ammonia concentration ranged 28.1–281 mmol/L, which increased the Salmonella reduction to 39.9% – 59.3%. However, the increase of Salmonella reduction rate at pH 9.0 was minor due to the increase in total ammonia concentration, and because of this resulted in a significantly higher MIC. This is possibly because the remaining live Salmonella had adapted to the high free ammonia environment. A similar phenomenon occurred during the VFA tests, in which the increase in VFAs did not always increase the inactivation of Salmonella, and Curve D in Fig. 1 indicated the adaptation and resistance of Salmonella to stress. The resistance of Salmonella to ammonia, together with its complex inactivation mechanism, requires further study. 3.5. Inhibitory effects of VFA/ammonia on Salmonella in the reactors As shown in Fig. 2, after the first day, the concentration of HAC, HPR and HIB in the reactors remained at 63 ± 6 mmol/L, 29 ± 2 mmol/L and 25 ± 1 mmol/L, respectively, with a pH of 7.1 ± 0.2. These values were far below the MIC obtained at pH 7.0, but the Salmonella reductions caused by these VFA concentrations within 20 h can be calculated from the modified Weibull distribution. The average Salmonella reductions due to HAC, HPR and HIB within 20 h were 21.3%, 16.7% and 8.7%, respectively (totally 46.7%). The average total ammonia concentration was 232 ± 28 mmol/L and the associated average Salmonella reduction calculated from the modified Weibull distribution was 32.8%. Supposing the antagonistic effect exists between VFAs and ammonia due to their buffering effect, the total Salmonella reduction in 20 h might be 13.9% (46.7% – 32.8%), and a complete Salmonella inactivation could be expected within 6 days (100%/13.9%*20/24). This is consistent with the experimental data of 6–7 days, thereby proving the assumption. Thus, the concentrations of VFAs and ammonia should be properly controlled in order to inactivate pathogens effectively in dry co-digestion systems. 4. Conclusions Salmonella was completely eliminated within 6–7 days during dry co-digestion of FW and PM due to the accumulation of high VFA and ammonia concentrations. This rapid inactivation could prevent pathogen contamination of soil/water and human/animal infection after land application of digestated wastes. A modified Weibull distribution was established to simulate Salmonella reduc-

239

tion and calculate or predict the MIC of VFAs and ammonia. The pH, VFA type, VFA/ammonia concentration and Salmonella serotype all had significant effects on Salmonella inactivation (P < 0.01). For VFA tests the inhibitory effect sequence was pH > VFA concentration > VFA type > Salmonella serotype; while for ammonia tests, the sequence was ammonia concentration > pH > Salmonella serotype. The VFAs were much more toxic to Salmonella than ammonia. Conflict of interest The authors declare no competing financial interest. Acknowledgements This work was funded by the Green Farm project supported by a Science Foundation Ireland Investigator Project Award (Ref: 12/ IP/1519). Xinmin is also grateful for the support of the Natural Science Foundation of China (Ref: 51728801). We would also like to thank Dr. Kavita Walia for her help in serotyping of Salmonella using O- and H-group antigens method. Appendix A. Supplementary material Supplementary data to this article can be found online at https://doi.org/10.1016/j.wasman.2018.10.037. References Alvarez-Ordonez, A., Fernandez, A., Lopez, M., Arenas, R., Bernardo, A., 2008. Modifications in membrane fatty acid composition of Salmonella typhimurium in response to growth conditions and their effect on heat resistance. Int. J. Food Microbiol. 123 (3), 212–219. Back, S.Y., Jin, H.H., Lee, S.Y., 2009. Inhibitory effect of organic acids against Enterobacter sakazakii in laboratory media and liquid foods. Food Control 20 (10), 867–872. Borowski, S., Doman´ski, J., Weatherley, L., 2014. Anaerobic co-digestion of swine and poultry manure with municipal sewage sludge. Waste Manag. 34 (2), 513– 521. Burns, A.M., Duffy, G., Walsh, D., Tiwari, B.K., Grant, J., Lawlor, P.G., Gardiner, G.E., 2016. Survival characteristics of monophasic Salmonella Typhimurium 4,[5],12: i:- strains derived from pig feed ingredients and compound feed. Food Control 64, 105–114. CLSI, 2012. Methods for dilution antimicrobial susceptibility tests for bacteria that grow aerobically; approved standard - ninth edition. Clinical and Laboratory Standards Institute. M07-A09, Vol.32 No. 02. Dennehy, C., Lawlor, P.G., Croize, T., Jiang, Y., Morrison, L., Gardiner, G.E., Zhan, X., 2016. Synergism and effect of high initial volatile fatty acid concentrations during food waste and pig manure anaerobic co-digestion. Waste Manag. 56, 173–180. Dennehy, C., Lawlor, P.G., Gardiner, G.E., Jiang, Y., Shalloo, L., Zhan, X., 2017a. Stochastic modelling of the economic viability of on-farm co-digestion of pig manure and food waste in Ireland. Appl. Energy 205, 1528–1537. Dennehy, C., Lawlor, P.G., Jiang, Y., Gardiner, G.E., Xie, S.H., Nghiem, L.D., Zhan, X.M., 2017b. Greenhouse gas emissions from different pig manure management techniques: a critical analysis. Front. Environ. Sci. Eng. 11 (3), 11. Dennehy, C., Lawlor, P.G., Gardiner, G.E., Jiang, Y., Cormican, P., McCabe, M.S., Zhan, X., 2017c. Process stability and microbial community composition in pig manure and food waste anaerobic co-digesters operated at low HRTs. Front. Environ. Sci. Eng. 11 (3), 4. European Centre for Disease Prevention and Control. Salmonellosis, 2018. In: ECDC. Annual epidemiological report for 2015. Stockholm: ECDC. Escmid, E.O., 2003. Determination of minimum inhibitory concentrations (MICs) of antibacterial. Clin. Microbiol. Infect. 9 (8), 1–7. Guan, T., Holley, R.A., 2003. Pathogen survival in swine manure environments and transmission of human enteric illness - a review. J. Environ. Qual. 32 (2), 383– 392. Hendriksen, R.S., Vieira, A.R., Karlsmose, S., Lo Fo Wong, D.M.A., Jensen, A.B., Wegener, H.C., Aarestrup, F.M., 2011. Global monitoring of Salmonella Serovar distribution from the world health organization global foodborne infections network country data bank: results of quality assured laboratories from 2001 to 2007. Foodborne Pathog. Dis. 8 (8), 887–900. Henry, D.P., Frost, A.J., Samuel, J.L., Oboyle, D.A., Thomson, R.H., 1983. Factors affecting the survival of Salmonella and Escherichia Coli in anaerobically fermented pig waste. J. Appl. Bacteriol. 55 (1), 89–95. Himathongkham, S., Riemann, H., Bahari, S., Nuanualsuwan, S., Kass, P., Cliver, D.O., 2000. Survival of Salmonella typhimurium and Escherichia coli O157 H7 in

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