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Modelling of yeast inactivation in sonicated tomato juice
International Journal of Food Microbiology 137 (2010) 116–120
Contents lists available at ScienceDirect
International Journal of Food Microbiology j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / i j f o o d m i c r o
Short Communication
Modelling of yeast inactivation in sonicated tomato juice A. Adekunte a, B.K. Tiwari a,⁎, A. Scannell b, P.J. Cullen c, C. O'Donnell a a b c
Biosystems Engineering, UCD School of Agriculture, Food Science and Veterinary Medicine, University College, Belfield, Dublin 4, Ireland Food Science, UCD School of Agriculture, Food Science and Veterinary Medicine, University College, Belfield, Dublin 4, Ireland School of Food Science and Environmental Health, Dublin Institute of Technology, Dublin 1, Ireland
a r t i c l e
i n f o
Article history: Received 14 August 2009 Received in revised form 4 October 2009 Accepted 6 October 2009 Keywords: Yeast Tomato juice Ultrasound Weibull model
a b s t r a c t Power ultrasound is recognised as a potential non thermal technique to inactivate microorganisms pertinent to fruit juices. In this study, the effect of sonication on the resistance of yeast (Pichia fermentans) in tomato juice was investigated. Tomato juice samples were sonicated at amplitude levels ranging from 24.4 to 61.0 μm at a constant frequency of 20 kHz for different treatment times (2 to 10 min) and pulse durations of 5 s on and 5 s off. Significant reductions (p < 0.05) were observed at higher amplitudes and processing times. Yeast inactivation was found to follow the Weibull model with a high regression coefficient (R2 > 0.98) and low RMSE (< 0.51). The desired 5 log reductions (D5 value) and shape factors were found to correlate exponentially with amplitude level. Results presented in this study show that sonication alone is an effective process to achieve the desired level of yeast inactivation in tomato juice. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The tomato (Lycopersicon esculentum) is one of the most important and widely consumed vegetable crops in the world (Suárez et al., 2008). The consumption of tomatoes and tomato based products such as tomato juice is associated with a lower risk of cardiovascular diseases. This is mainly due to the presence of bioactive compounds e.g. lycopene and other antioxidant components (Shi et al., 2008). Fruits and vegetable products including tomato juice are commonly spoiled by the presence and growth of yeasts (Kurtzman, 2006) resulting in the loss of nutritive and organoleptic properties. Thermal pasteurisation is the traditional and most common method to prevent microbial spoilage of acidic juices (Gunes et al., 2005). Generally tomato juice is thermally processed at temperatures varying from 60 to 100 °C to destroy vegetative microorganisms including yeast cells. Thermal processing of tomato juice has been widely investigated (Anese et al., 1999; Goodman et al., 2002; Sánchez-Moreno et al., 2006). Thermal treatment often triggers unwanted reactions in food systems, leading to undesirable organoleptic and nutritional effects. With increased consumer demands for nutritious, safe and chemical free juice, food processors are investigating alternatives to conventional thermal preservation techniques. Power ultrasound has been identified as a potential technology to meet the US Food and Drug Administration's requirement for a 5 log reduction in pertinent microorganisms found in fruit juices (SallehMack and Roberts, 2007). Power ultrasound can also be used with other hurdles to achieve the desired inactivation effect (Guerrero et al., 2005).
It has been reported to have a minimal effect on quality of fruit juices such as orange juice (Valero et al., 2007; Tiwari et al., 2008a), blackberry juice (Tiwari et al., 2009) and strawberry juice (Tiwari et al., 2008b). The biocidal effect of ultrasound has been mainly attributed to physical (cavitation, mechanical effects, micro-mechanical shocks) and/or chemical (formation of free radicals due to sonochemical reaction) principles (Mason et al., 1996; Raso et al., 1998; Butz and Tauscher, 2002; Rae et al., 2005; Kadkhodaee and Povey, 2008). Recently Piyasena et al. (2004) and Jiranek et al. (2008) extensively reviewed the potential of ultrasound for inactivation of food spoilage and pathogenic microorganisms. However limited information is available on the effect of ultrasound processing parameters on yeast inactivation (Guerrero et al., 2001). The objective of this study was to investigate the efficacy of ultrasound on yeast inactivation and to model the inactivation kinetics observed. 2. Experimental 2.1. Preparation of tomato juice Fresh tomatoes were purchased from a local fruit market (Begley's Marketing Services Ltd., Dublin 7, Ireland) and subsequently stored at 3 ± 1 °C and crushed using a domestic juice extractor (Kenstar, Dublin, Ireland). The juice was filtered on a sterile double layer cheese cloth to remove seeds from the juice. 2.2. Inocula preparation and enumeration procedure
⁎ Corresponding author. E-mail address: [email protected] (B.K. Tiwari). 0168-1605/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.ijfoodmicro.2009.10.006
The yeast strain Pichia fermentans, DSM 70090 ( DSM, Derbyshire, UK) was propagated in Universal medium for yeast (YM; code no. 189,
A. Adekunte et al. / International Journal of Food Microbiology 137 (2010) 116–120
GmbH, Braunschweig, Germany) at 37 °C with continuous shaking at 130 rpm for 72 h. Short term cultures were maintained on YM agar (YM broth + 15% technical Agar, LP0013) and stored at 4 °C. Long term microbial stock cultures were prepared in 80% glycerol and stored at −20 °C. The initial inoculum was prepared by transferring a loopful of a stock culture maintained on universal yeast agar slants to 10 mL of yeast broth contained in 50 mL Erlenmeyer flasks. The yeast was grown to stationary phase for 72 h at 30 °C (±1 °C). The yeast growth was monitored by measuring the absorbance at 660 nm using a spectrophotometer (Unicam UV–VIS). A single yeast colony from a universal yeast agar stock plate was transferred to 10 ml of sterile yeast broth containing yeast extract (3 g) (Sigma-Aldrich, code Y1625, U.S.A), 3 g of malt extract (Fluka, SigmaAldrich, code 70167, U.S.A), 10 g of D-glucose (Fluka, Sigma-Aldrich, U.S.A) and 5 g of soy peptone (Oxoid Ltd, L0044, Hampshire, UK). The inoculated yeast broth was incubated at 25 °C on a rotatory shaker (200 rpm) for 72 h. The cells were harvested by centrifugation (10,000×g), 10 min at 4 °C and resuspended in sterile quarter-strength 20 mL ringer's solution (Oxoid Ltd, Hampshire) and resuspended in tomato juice at an initial concentration (N0) of approximately 108 CFU/mL. 2.3. Ultrasound treatment
2.5. Yeast inactivation kinetics 2.5.1. Weibull distribution model Yeast inactivation models were developed using a two-step procedure. Reaction rate constants were determined by fitting the experimental data to the Weibull model (Peleg and cole, 1998). In the second step the rate constants were modelled as a function of ultrasound amplitude level (μm). The Weibull distribution model is a flexible model with convenient functions to describe microbial survival (Peleg, 1999; Buzrul et al., 2005). The cumulative form of the Weibull distribution is as follows: −ðktÞβ
Nt = N 0 × e
2.4. Viable cell counts and expression of results Surviving yeast cells were plated on to universal yeast agar by spread plating with 0.1 mL sample suspension serially diluted (1:10) with sterile ringers solution. Plates of 6 serial dilutions were incubated at 30 °C for 2 days. Two plates were used for each dilution. Cell counts were carried out manually and expressed as CFU/mL.
Fig. 1. Experimental setup (1) ultrasound transducer; (2) ultrasonic generator; (3) ultrasound probe (19 mm); (4) data logger; (5) temperature probe; (6) jacketed beaker; (7) computer; (8) water inlet; (9) water outlet; (h) depth of probe in to the sample (2.5 cm).
ð1Þ
Rearranging Eq. (1), yields log
Nt β = −ðktÞ N0
ð2Þ
The numerical values of k and β were used to calculate a desired log reduction. The time required to obtain a 5 log reduction (Ddes) was calculated from model parameters by employing Eq. (3). 1=β
A 1500 W ultrasonic processor (VC 1500, Sonics and Materials Inc., Newtown, USA) with a 19 mm probe was used for sonication (Fig. 1). Tomato juice samples of 80 mL were placed in a 100 mL jacketed vessel through which water at 25 ± 1.0 °C and a flowrate of 0.5 L/min was circulated. Samples of 1 mL of yeast cell suspension were taken at interval of 2, 4, 6, 8 and 10 min at varying amplitude levels of 24.4, 30.5, 42.7, 54.9 and 61 μm respectively. At the 10-min treatment time, the maximum sample temperatures reached were 30.6, 31.6, 34.1, 37.2 and 39.9 °C for amplitude levels of 24.4, 30.5, 42.7, 54.9 and 61 μm. The acoustic energy density for each of amplitude level investigated was 0.33, 0.36, 0.47, 0.61 and 0.81 W/mL respectively. The ultrasound probe was submerged to a depth of 25 mm into the sample. All treatments were carried out in triplicate.
117
td = δ × ðDdes Þ
ð3Þ
where Nt represents the number of surviving cells at any given time (t, min), while N0 is the initial number of the surviving cells. β is shape factor, δ is decimal reduction time (min) and k is inactivation rate constant. 3. Results and discussion 3.1. Inactivation kinetics model The effect of sonication time (min) on yeast inactivation in tomato juice under the experimental conditions investigated are shown in Fig. 2. Extrinsic control parameters of amplitude level (μm) and processing time (min) had a significant effect (p < 0.05) on the inactivation of yeast in tomato juice but the effect was relatively small at lower amplitude levels and processing times. Yeast inactivation is reported to follow first order kinetics during sonication (Tsukamoto et al., 2004), however in this study, yeast inactivation was found to follow the Weibull model. Deviations from the conventional inactivation curve (first order kinetics) have been observed including sigmoidal curves, curves with a shoulder and especially with a tailing and correspondingly various models have been proposed to describe these non-linear curves (Baranyi and Roberts, 1994; Buchanan et al., 1994; Linton et al., 1995; Peleg and Cole, 2000; Peleg, 2000). Among these, the Weibull model has been successfully used in describing the non-linear inactivation of different microorganisms under various experimental conditions (Chen and Hoover, 2003; Chen and Hoover, 2004; Buzrul and Alpas, 2004). Many non-sigmoid semi-logarithmic survival curves can be described by power law relationships, which is only consistent with the existence of an underlying Weibull distribution of resistances within the treated population (Peleg, 1999; Buzrul et al., 2005). The Weibull model is sufficiently robust to describe a concave upward survival curve if β < 1 and a concave downward if β > 1 (van Boekel, 2002). The model includes the traditional case where the survival curve, originated from a first order, is linear (n = 1) (Mafart et al., 2002). In this study survival curves of P. fementans obtained by plotting Log (number of survivors/initial number) vs. treatment time (min) at varying amplitude levels (μm) were fitted to a Weibull inactivation model (Eq. (1)). The calculated Weibull model parameters (inactivation rate constants and shape factor) with corresponding regression coefficients (R2) and root mean square error (RMSE) are listed in Table 1.
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Fig. 2. Survival curves for yeast inactivation as a function of time at varying amplitude levels of A (24.4 μm), B (30.5 μm), C (42.7 μm), D (54.9 μm), E (61.0 μm) respectively (Error bars represents standard deviation).
Yeast inactivation in sonicated tomato juice samples can be adequately described by the Weibull frequency distribution model, with good measures of fit (R2 > 0.97 and RMSE < 0.519). The yeast inactivation rate constant increased from 3.23 × 10− 2 (R2 = 0.997, RMSE = 0.031) to 6.67 × 10− 2/min (R2 = 0.986, RMSE = 0.488), with an increase in amplitude level from 24.4 to 61 μm. The Weibull model shape factors listed in Table 1, indicate that the yeast survival curves were concave downward (β > 1), which can also be seen from Fig. 3B. β values of >1 indicate the susceptibility of remaining cells to the treatment (van Boekel, 2002). The Weibull model provided estimations of yeast inactivation in terms of processing times required. Ultrasound inactivation of yeast in this study showed a > 5 log reduction with increasing amplitude (μm) level in 10 min or less. Ultrasound treatment has been reported to be most effective in combination with mild heat or pressure treatment for microbial inactivation for E coli (Villamiel and de Jong, 2000; Furuta et al., 2004; Baumann et al., 2005) and Listeria monocytogenes (D'Amico et al., 2006). In the case of yeasts, Lopez-Malo et al. (1999) reported significant reductions in the D-values for S. cerevisiae at 45 °C from 739 min (heat treatment alone) to 22.3 min, when ultrasound was combined with heat treatment. Similarly, Guerrero et al. (2001) reported that at moderate temperatures, decimal reduction time values of S. cervisiae in Sabouroud broth were reduced by the simultaneous effect of ultrasound but at a
higher temperature (55 °C), no advantages was observed by additional sonication. They observed a D-value for S. cerevisiae at treatment times of 30.9 to 19.5 min in Sabouroud broth at pH 3 and a temperature of 35 °C. During sonication the temperature of the juice sample was in range of 32– 5 °C. The desired 5 log reduction (D5) value at moderate processing temperature which can be calculated using Eq. (4) was found to decrease from 21.85± 1.79 min to 7.51 ± 0.01 min with an increase in amplitude level (μm) from 24.4 to 61 μm (Fig. 4). Inactivation rate constants (k) and shape factor (β) for the Weibull model increased exponentially as a function of amplitude (μm). The
Table 1 Effect of amplitude level (μm) on the inactivation rate constants, min− 1 (± SD) and shape factor (± SD). Amplitude
k × 10− 2
β (shape factor)
R2
RMSE
24.4 30.5 42.7 54.9 61.0
3.234 ± 0.477 3.494 ± 0.429 5.400 ± 0.499 5.437 ± 0.835 6.672 ± 0.434
1.46 ± 0.792 1.44 ± 0.118 2.05 ± 0.491 3.62 ± 1.043 4.95 ± 0.600
0.997 0.990 0.994 0.977 0.986
0.031 0.086 0.087 0.519 0.488
Fig. 3. Changes in A) inactivation rate constant (k × 10 −2) and B) shape factor (β) as a function of amplitude level (μm).
A. Adekunte et al. / International Journal of Food Microbiology 137 (2010) 116–120
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an internal cavitation as well as internal microstreaming, modifying the cellular structure. Alliger (1975) also mentioned that disruption of subcellular particles during sonication was often faster than disruption of cell walls and that ultrasound rapidly disrupted mitochondria with fine membrane fragmentation. Bactericidal effects on yeast cells were reported during the initial stages of sonication, with the bactericidal and bacteriostatic effects gradually increasing with time and intensity of sonication (Tsukamoto et al., 2004). 4. Conclusions Fig. 4. Changes in desired 5 log reduction (D5, min) as a function of amplitude level (μm).
relationship between the rate constants and amplitude (Fig. 3A,B) were found to fit the equations below with R2 values of 0.92 and 0.95 for k and β respectively. 0:0196 A
ð4Þ
0:0353 A
ð5Þ
k = 0:0205 × e
β = 0:5408 × e
As with k and β, D5 was exponentially related to the ultrasonic amplitude (μm). The relationship between D5 values and amplitude (Fig. 4) were found to fit the following equation with coefficient of regression (R2 = 0.92). −0:0276 A
k = 46:373 × e
ð6Þ
The experimental yeast log reduction (CFU/mL) was plotted against the predicted values from Eq. (1) for the Weibull model. Predicted values were observed to be in good agreement with experimental values with R2 = 0.983 for the Weibull model. 3.2. Effect of ultrasound on yeast inactivation The mechanism of microbial inactivation by power ultrasound is through cavitation, the generation and collapse of micro-bubbles. Bubble collapse within a liquid medium results in localised temperatures of up to 5500 °C and pressures of up to 100 MPa. Consequently the intense local energy and high pressure bring about a localised inactivation effect. The pressure changes that occur from these implosions are the main mechanism for microbial cell disruption (Piyasena et al., 2004). A number of parameters such as frequency and amplitude of ultrasound waves, as well as temperature and viscosity of the liquid medium influence the degree of cavitation (Sala et al. 1995; Mason et al., 1996). At higher amplitude levels which corresponds to higher ultrasound intensities, the inactivation rate was enhanced for yeast (Fig. 2), in accordance with previous studies (Lopez-Malo et al., 1999; Guerrero et al., 2001). The measurement of amplitude instead of power as an indication of the ultrasonic cavitation is reported to be a reliable method for indication of the ultrasound power (Tsukamoto et al., 2004). The presented yeast inactivation could be from a combination of physical and chemical mechanisms which occur during cavitation. The physical effects of sonication may not result in yeast inactivation due to the fact that yeast cells are relatively rigid and may not be disrupted by the action of microstreaming (Iida et al., 2008). However, Iida et al. (2008) emphasised that the rupture of yeast cells due to cavitation bubbles and the release of intercellular protein from yeast cells by ultrasonic action could be proposed as a method for evaluating the physical (mechanical) effects of the ultrasonic field. Koda et al. (2009) studied the effect of sonication on microbial inactivation (E. coli and S. mutans) and concluded that the inactivation mechanism relies mainly on chemical effects. Similarly, Ciccolini et al. (1997) suggested that yeast cells could contain cavitation nuclei and sonication could cause
The results presented in this study indicate that power ultrasound treatment may be employed for inactivation of key spoilage microorganisms of concern in fruit juice processing. Sonication alone at moderate temperature can achieve the desired 5 log reduction in yeast cells. The Weibull model adequately describes yeast inactivation. This study is relevant to the processing of tomato juice as it is desirable to maintain low processing temperature to retain the quality characteristics of fresh juice. Acknowledgement Funding for this research was provided under the National Development Plan, through the Food Institutional Research Measure, administered by the Department of Agriculture, Fisheries and Food, Ireland. References Alliger, H., 1975. Ultrasonic disruption. Am. Lab. 10, 75–85. Anese, M., Manzocco, L., Nicoli, M.C., Lerici, C.R., 1999. Antioxidant properties of tomato juice as affected by heating. J. Sci. Food Agric. 79, 750–754. Baranyi, J., Roberts, T.A., 1994. A dynamic approach to predicting bacterial growth in foods. Int. J. Food Microbiol. 23, 277–294. Baumann, A.R., Martin, S.E., Feng, H., 2005. Power ultrasound treatment of Listeria monocytogenes in apple cider. J. Food Prot. 68, 2333–2340. Buchanan, R.L., Golden, M.H., Whiting, R.C., Philips, J.G., Smith, J.L., 1994. Non-thermal inactivation models for Listeria monocytogenes. J. Food Sci. 59, 179–188. Butz, P., Tauscher, B., 2002. Emerging technologies: chemical aspects. Food Res. Int. 35, 279–284. Buzrul, S., Alpas, H., 2004. Modeling the synergistic effect of high pressure and heat on the inactivation kinetics of Listeria innocua: a preliminary study. FEMS Microbiol. Lett. 238, 29–36. Buzrul, S., Alpas, S., Bozoglu, F., 2005. Use of Weibull frequency distribution model to describe the inactivation of Alicyclobacillus acidoterrestris by high pressure at different temperatures. Food Res. Int. 38, 151–157. Chen, H., Hoover, D.G., 2003. Pressure inactivation kinetics of Yersinia enterocolitica ATCC 35669. Int. J. Food Microbiol. 87, 161–171. Chen, H., Hoover, D.G., 2004. Use of Weibull model to describe and predict pressure inactivation of Listeria monocytogenes Scott A in whole milk. Innovative Food Science and Emerging Technologies 5, 269–276. Ciccolini, L., Taillandier, P., Wilhem, A.M., Delmas, H., Strehaiano, P., 1997. Low frequency thermo-ultrasonication of Saccharomyces cerevisiae suspensions: effect of temperature and of ultrasonic power. Chem. Eng. J. 65, 145–149. D'Amico, D.J., Silk, T.M., Wu, J.R., Guo, M.R., 2006. Inactivation of microorganisms in milk and apple cider treated with ultrasound. J. Food Prot. 69, 556–563. Goodman, C.L., Fawcett, S., Barringer, S.A., 2002. Flavor, viscosity, and color analyses of hot and cold break tomato juices. J. Food Sci. 67 (1), 404–408. Guerrero, S., Lopez-Malo, A., Alzamora, S.M., 2001. Effect of ultrasound on the survival of Saccharomyces cerevisiae: influence of temperature pH and amplitude. Innovative Food Science and Emerging Technologies 2, 31–39. Guerrero, S., Tognon, M., Alzamora, S.M., 2005. Response of Saccharomyces cerevisiae to the combined action of ultrasound and low weight chitosan. Food Control 162, 131–139. Gunes, G., Blum, L.K., Hotchkiss, J.H., 2005. Inactivation of yeasts in grape juice using a continuous dense phase carbon dioxide processing system. J. Sci. Food Agric. 85, 2362–2368. Iida, Y., Tuziuti, T., Yasui, K., Kozuka, T., Towata, A., 2008. Protein release from yeast cells as an evaluation method of physical effects in ultrasonic field. Ultrason. Sonochem. 156, 995–1000. Jiranek, V., Grbin, P., Yap, A., Barnes, M., Bates, D., 2008. High power ultrasonics as a novel tool offering new opportunities for managing wine microbiology. Biotechnol. Lett. 30, 1–6. Kadkhodaee, R., Povey, M.J.W., 2008. Ultrasonic inactivation of Bacillus α-amylase I effect of gas content and emitting face of probe. Ultrason. Sonochem. 15, 133–142. Koda, S., Miyamoto, M., Toma, M., Matsuoka, T., Maebayashi, M., 2009. Inactivation of Escherichia coli and Streptococcus mutans by ultrasound at 500 kHz. Ultrason. Sonochem. 16 (5), 655–659.
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Kurtzman, C.P., 2006. Detection, identification and enumeration methods for spoilage yeasts. In: Blackburn, C.W. (Ed.), Food spoilage microorganisms. Woodhead Publishing, Cambridge, England, pp. 28–54. Linton, R.H., Carter, W.H., Pierson, M.D., Hackney, C.R., 1995. Use of modified Gompertz equation to model non-linear survival curves for Listeria monocytogenes Scott A. J. Food Prot. 59, 16–23. Lopez-Malo, A., Guerrero, S., Alzamora, S.M., 1999. Saccharomyces cerevisiae, thermal inactivation kinetics combined with ultrasound. J. Food Prot. 62 (10), 1215–1217. Mafart, P., Couvert, O., Gaillard, S., Leguerinel, I., 2002. On calculating sterility in thermal preservation methods: application of the Weibull frequency distribution model. Int. J. Food Microbiol. 72, 107–112. Mason, T.J., Paniwnyk, L., Lorimer, J.P., 1996. The uses of ultrasound in food technology. Ultrason. Sonochem. 33, 253–260. Peleg, M., 1999. On calculating sterility in thermal and non-thermal preservation methods. Food Res. Int. 32, 271–278. Peleg, M., 2000. Microbial survival curves-the reality of flat “shoulders” and absolute thermal death times. Food Res. Int. 33, 531–538. Peleg, M., Cole, M.B., 1998. Reinterpretation of microbial survival curves. Crit. Rev. Food Sci. Nutr. 38, 353–380. Peleg, M., Cole, M.B., 2000. Estimating the survival of Clostridium botulinum spores during heat treatments. J. Food Prot. 63, 190–195. Piyasena, P., Mohareb, E., McKellar, R.C., 2004. Inactivation of microbes using ultrasound: a review. Int. J. Food Microbiol. 87, 207–216. Rae, J., Ashokkumar, M., Eulaerts, O., von Sonntag, C., Reisse, J., Grieser, F., 2005. Estimation of ultrasound induced cavitation bubble temperatures in aqueous solutions. Ultrason. Sonochem. 125, 325–329. Raso, J., Pagan, R., Condon, S., Sala, J.F., 1998. Influence of the temperature and pressure on the lethality of ultrasound. Appl. Environ. Microbiol. 64, 465–471.
Salleh-Mack, S.Z., Roberts, J.S., 2007. Ultrasound pasteurization: the effects of temperature soluble solids organic acids and pH on the inactivation of Escherichia coli ATCC 25922. Ultrason. Sonochem. 14, 323–329. Sánchez-Moreno, C., Plaza, L., de Ancos, B., Cano, M.P., 2006. Nutritional characterisation of commercial traditional pasteurized tomato juices: carotenoids, vitamin C and radical-scavenging capacity. Food Chem. 98 (4), 749–756. Shi, J., Dai, Y., Kakuda, Y., Mittal, G., Xue, S.J., 2008. Effect of heating and exposure to light on the stability of lycopene in tomato purée. Food Control 19 (5), 514–520. Suárez, M.H., Rodríguez, E.M., Romero, C.D., 2008. Chemical composition of tomato Lycopersicon esculentum from Tenerife, the Canary Islands. Food Chem. 106 (3), 1046–1056. Tiwari, B.K., Muthukumarappan, K., O'Donnell, C.P., Cullen, P.J., 2008a. Effects of sonication on the kinetics of orange juice quality parameters. J. Agric. Food Chem. 56 (7), 2423–2428. Tiwari, B.K., O'Donnell, C.P., Cullen, P.J., 2009. Effect of sonication on retention of anthocyanins in blackberry juice. J. Food Eng. 93 (2), 166–171. Tiwari, B.K., O'Donnell, C.P., Patras, A., Cullen, P.J., 2008b. Anthocyanin and ascorbic acid degradation in sonicated strawberry juice. J. Agric. Food Chem. 56 (21), 10071–10077. Tsukamoto, I., Constantinoiu, E., Furuta, M., Nishimura, R., Maeda, Y., 2004. Inactivation effect of sonication and chlorination on Saccharomyces cerevisiae. Calorimetric Analysis. Ultrason. Sonochem. 11 (3–4), 167–172. Valero, M., Recrosio, N., Saura, D., Munoz, N., Martıc, N., Lizama, V., 2007. Effects of ultrasonic treatments in orange juice processing. J. Food Eng. 80, 509–516. van Boekel, M.A.J.S., 2002. On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells. Int. J. Food Microbiol. 74, 139–159. Villamiel, M., de Jong, P., 2000. Inactivation of Pseudomonas fluorescens and Streptococcus thermophilus in trypticase soy broth and total bacteria in milk by continuous-flow ultrasonic treatment and conventional heating. J. Food Eng. 45, 171–179.
Contents lists available at ScienceDirect
International Journal of Food Microbiology j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / i j f o o d m i c r o
Short Communication
Modelling of yeast inactivation in sonicated tomato juice A. Adekunte a, B.K. Tiwari a,⁎, A. Scannell b, P.J. Cullen c, C. O'Donnell a a b c
Biosystems Engineering, UCD School of Agriculture, Food Science and Veterinary Medicine, University College, Belfield, Dublin 4, Ireland Food Science, UCD School of Agriculture, Food Science and Veterinary Medicine, University College, Belfield, Dublin 4, Ireland School of Food Science and Environmental Health, Dublin Institute of Technology, Dublin 1, Ireland
a r t i c l e
i n f o
Article history: Received 14 August 2009 Received in revised form 4 October 2009 Accepted 6 October 2009 Keywords: Yeast Tomato juice Ultrasound Weibull model
a b s t r a c t Power ultrasound is recognised as a potential non thermal technique to inactivate microorganisms pertinent to fruit juices. In this study, the effect of sonication on the resistance of yeast (Pichia fermentans) in tomato juice was investigated. Tomato juice samples were sonicated at amplitude levels ranging from 24.4 to 61.0 μm at a constant frequency of 20 kHz for different treatment times (2 to 10 min) and pulse durations of 5 s on and 5 s off. Significant reductions (p < 0.05) were observed at higher amplitudes and processing times. Yeast inactivation was found to follow the Weibull model with a high regression coefficient (R2 > 0.98) and low RMSE (< 0.51). The desired 5 log reductions (D5 value) and shape factors were found to correlate exponentially with amplitude level. Results presented in this study show that sonication alone is an effective process to achieve the desired level of yeast inactivation in tomato juice. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The tomato (Lycopersicon esculentum) is one of the most important and widely consumed vegetable crops in the world (Suárez et al., 2008). The consumption of tomatoes and tomato based products such as tomato juice is associated with a lower risk of cardiovascular diseases. This is mainly due to the presence of bioactive compounds e.g. lycopene and other antioxidant components (Shi et al., 2008). Fruits and vegetable products including tomato juice are commonly spoiled by the presence and growth of yeasts (Kurtzman, 2006) resulting in the loss of nutritive and organoleptic properties. Thermal pasteurisation is the traditional and most common method to prevent microbial spoilage of acidic juices (Gunes et al., 2005). Generally tomato juice is thermally processed at temperatures varying from 60 to 100 °C to destroy vegetative microorganisms including yeast cells. Thermal processing of tomato juice has been widely investigated (Anese et al., 1999; Goodman et al., 2002; Sánchez-Moreno et al., 2006). Thermal treatment often triggers unwanted reactions in food systems, leading to undesirable organoleptic and nutritional effects. With increased consumer demands for nutritious, safe and chemical free juice, food processors are investigating alternatives to conventional thermal preservation techniques. Power ultrasound has been identified as a potential technology to meet the US Food and Drug Administration's requirement for a 5 log reduction in pertinent microorganisms found in fruit juices (SallehMack and Roberts, 2007). Power ultrasound can also be used with other hurdles to achieve the desired inactivation effect (Guerrero et al., 2005).
It has been reported to have a minimal effect on quality of fruit juices such as orange juice (Valero et al., 2007; Tiwari et al., 2008a), blackberry juice (Tiwari et al., 2009) and strawberry juice (Tiwari et al., 2008b). The biocidal effect of ultrasound has been mainly attributed to physical (cavitation, mechanical effects, micro-mechanical shocks) and/or chemical (formation of free radicals due to sonochemical reaction) principles (Mason et al., 1996; Raso et al., 1998; Butz and Tauscher, 2002; Rae et al., 2005; Kadkhodaee and Povey, 2008). Recently Piyasena et al. (2004) and Jiranek et al. (2008) extensively reviewed the potential of ultrasound for inactivation of food spoilage and pathogenic microorganisms. However limited information is available on the effect of ultrasound processing parameters on yeast inactivation (Guerrero et al., 2001). The objective of this study was to investigate the efficacy of ultrasound on yeast inactivation and to model the inactivation kinetics observed. 2. Experimental 2.1. Preparation of tomato juice Fresh tomatoes were purchased from a local fruit market (Begley's Marketing Services Ltd., Dublin 7, Ireland) and subsequently stored at 3 ± 1 °C and crushed using a domestic juice extractor (Kenstar, Dublin, Ireland). The juice was filtered on a sterile double layer cheese cloth to remove seeds from the juice. 2.2. Inocula preparation and enumeration procedure
⁎ Corresponding author. E-mail address: [email protected] (B.K. Tiwari). 0168-1605/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.ijfoodmicro.2009.10.006
The yeast strain Pichia fermentans, DSM 70090 ( DSM, Derbyshire, UK) was propagated in Universal medium for yeast (YM; code no. 189,
A. Adekunte et al. / International Journal of Food Microbiology 137 (2010) 116–120
GmbH, Braunschweig, Germany) at 37 °C with continuous shaking at 130 rpm for 72 h. Short term cultures were maintained on YM agar (YM broth + 15% technical Agar, LP0013) and stored at 4 °C. Long term microbial stock cultures were prepared in 80% glycerol and stored at −20 °C. The initial inoculum was prepared by transferring a loopful of a stock culture maintained on universal yeast agar slants to 10 mL of yeast broth contained in 50 mL Erlenmeyer flasks. The yeast was grown to stationary phase for 72 h at 30 °C (±1 °C). The yeast growth was monitored by measuring the absorbance at 660 nm using a spectrophotometer (Unicam UV–VIS). A single yeast colony from a universal yeast agar stock plate was transferred to 10 ml of sterile yeast broth containing yeast extract (3 g) (Sigma-Aldrich, code Y1625, U.S.A), 3 g of malt extract (Fluka, SigmaAldrich, code 70167, U.S.A), 10 g of D-glucose (Fluka, Sigma-Aldrich, U.S.A) and 5 g of soy peptone (Oxoid Ltd, L0044, Hampshire, UK). The inoculated yeast broth was incubated at 25 °C on a rotatory shaker (200 rpm) for 72 h. The cells were harvested by centrifugation (10,000×g), 10 min at 4 °C and resuspended in sterile quarter-strength 20 mL ringer's solution (Oxoid Ltd, Hampshire) and resuspended in tomato juice at an initial concentration (N0) of approximately 108 CFU/mL. 2.3. Ultrasound treatment
2.5. Yeast inactivation kinetics 2.5.1. Weibull distribution model Yeast inactivation models were developed using a two-step procedure. Reaction rate constants were determined by fitting the experimental data to the Weibull model (Peleg and cole, 1998). In the second step the rate constants were modelled as a function of ultrasound amplitude level (μm). The Weibull distribution model is a flexible model with convenient functions to describe microbial survival (Peleg, 1999; Buzrul et al., 2005). The cumulative form of the Weibull distribution is as follows: −ðktÞβ
Nt = N 0 × e
2.4. Viable cell counts and expression of results Surviving yeast cells were plated on to universal yeast agar by spread plating with 0.1 mL sample suspension serially diluted (1:10) with sterile ringers solution. Plates of 6 serial dilutions were incubated at 30 °C for 2 days. Two plates were used for each dilution. Cell counts were carried out manually and expressed as CFU/mL.
Fig. 1. Experimental setup (1) ultrasound transducer; (2) ultrasonic generator; (3) ultrasound probe (19 mm); (4) data logger; (5) temperature probe; (6) jacketed beaker; (7) computer; (8) water inlet; (9) water outlet; (h) depth of probe in to the sample (2.5 cm).
ð1Þ
Rearranging Eq. (1), yields log
Nt β = −ðktÞ N0
ð2Þ
The numerical values of k and β were used to calculate a desired log reduction. The time required to obtain a 5 log reduction (Ddes) was calculated from model parameters by employing Eq. (3). 1=β
A 1500 W ultrasonic processor (VC 1500, Sonics and Materials Inc., Newtown, USA) with a 19 mm probe was used for sonication (Fig. 1). Tomato juice samples of 80 mL were placed in a 100 mL jacketed vessel through which water at 25 ± 1.0 °C and a flowrate of 0.5 L/min was circulated. Samples of 1 mL of yeast cell suspension were taken at interval of 2, 4, 6, 8 and 10 min at varying amplitude levels of 24.4, 30.5, 42.7, 54.9 and 61 μm respectively. At the 10-min treatment time, the maximum sample temperatures reached were 30.6, 31.6, 34.1, 37.2 and 39.9 °C for amplitude levels of 24.4, 30.5, 42.7, 54.9 and 61 μm. The acoustic energy density for each of amplitude level investigated was 0.33, 0.36, 0.47, 0.61 and 0.81 W/mL respectively. The ultrasound probe was submerged to a depth of 25 mm into the sample. All treatments were carried out in triplicate.
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td = δ × ðDdes Þ
ð3Þ
where Nt represents the number of surviving cells at any given time (t, min), while N0 is the initial number of the surviving cells. β is shape factor, δ is decimal reduction time (min) and k is inactivation rate constant. 3. Results and discussion 3.1. Inactivation kinetics model The effect of sonication time (min) on yeast inactivation in tomato juice under the experimental conditions investigated are shown in Fig. 2. Extrinsic control parameters of amplitude level (μm) and processing time (min) had a significant effect (p < 0.05) on the inactivation of yeast in tomato juice but the effect was relatively small at lower amplitude levels and processing times. Yeast inactivation is reported to follow first order kinetics during sonication (Tsukamoto et al., 2004), however in this study, yeast inactivation was found to follow the Weibull model. Deviations from the conventional inactivation curve (first order kinetics) have been observed including sigmoidal curves, curves with a shoulder and especially with a tailing and correspondingly various models have been proposed to describe these non-linear curves (Baranyi and Roberts, 1994; Buchanan et al., 1994; Linton et al., 1995; Peleg and Cole, 2000; Peleg, 2000). Among these, the Weibull model has been successfully used in describing the non-linear inactivation of different microorganisms under various experimental conditions (Chen and Hoover, 2003; Chen and Hoover, 2004; Buzrul and Alpas, 2004). Many non-sigmoid semi-logarithmic survival curves can be described by power law relationships, which is only consistent with the existence of an underlying Weibull distribution of resistances within the treated population (Peleg, 1999; Buzrul et al., 2005). The Weibull model is sufficiently robust to describe a concave upward survival curve if β < 1 and a concave downward if β > 1 (van Boekel, 2002). The model includes the traditional case where the survival curve, originated from a first order, is linear (n = 1) (Mafart et al., 2002). In this study survival curves of P. fementans obtained by plotting Log (number of survivors/initial number) vs. treatment time (min) at varying amplitude levels (μm) were fitted to a Weibull inactivation model (Eq. (1)). The calculated Weibull model parameters (inactivation rate constants and shape factor) with corresponding regression coefficients (R2) and root mean square error (RMSE) are listed in Table 1.
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Fig. 2. Survival curves for yeast inactivation as a function of time at varying amplitude levels of A (24.4 μm), B (30.5 μm), C (42.7 μm), D (54.9 μm), E (61.0 μm) respectively (Error bars represents standard deviation).
Yeast inactivation in sonicated tomato juice samples can be adequately described by the Weibull frequency distribution model, with good measures of fit (R2 > 0.97 and RMSE < 0.519). The yeast inactivation rate constant increased from 3.23 × 10− 2 (R2 = 0.997, RMSE = 0.031) to 6.67 × 10− 2/min (R2 = 0.986, RMSE = 0.488), with an increase in amplitude level from 24.4 to 61 μm. The Weibull model shape factors listed in Table 1, indicate that the yeast survival curves were concave downward (β > 1), which can also be seen from Fig. 3B. β values of >1 indicate the susceptibility of remaining cells to the treatment (van Boekel, 2002). The Weibull model provided estimations of yeast inactivation in terms of processing times required. Ultrasound inactivation of yeast in this study showed a > 5 log reduction with increasing amplitude (μm) level in 10 min or less. Ultrasound treatment has been reported to be most effective in combination with mild heat or pressure treatment for microbial inactivation for E coli (Villamiel and de Jong, 2000; Furuta et al., 2004; Baumann et al., 2005) and Listeria monocytogenes (D'Amico et al., 2006). In the case of yeasts, Lopez-Malo et al. (1999) reported significant reductions in the D-values for S. cerevisiae at 45 °C from 739 min (heat treatment alone) to 22.3 min, when ultrasound was combined with heat treatment. Similarly, Guerrero et al. (2001) reported that at moderate temperatures, decimal reduction time values of S. cervisiae in Sabouroud broth were reduced by the simultaneous effect of ultrasound but at a
higher temperature (55 °C), no advantages was observed by additional sonication. They observed a D-value for S. cerevisiae at treatment times of 30.9 to 19.5 min in Sabouroud broth at pH 3 and a temperature of 35 °C. During sonication the temperature of the juice sample was in range of 32– 5 °C. The desired 5 log reduction (D5) value at moderate processing temperature which can be calculated using Eq. (4) was found to decrease from 21.85± 1.79 min to 7.51 ± 0.01 min with an increase in amplitude level (μm) from 24.4 to 61 μm (Fig. 4). Inactivation rate constants (k) and shape factor (β) for the Weibull model increased exponentially as a function of amplitude (μm). The
Table 1 Effect of amplitude level (μm) on the inactivation rate constants, min− 1 (± SD) and shape factor (± SD). Amplitude
k × 10− 2
β (shape factor)
R2
RMSE
24.4 30.5 42.7 54.9 61.0
3.234 ± 0.477 3.494 ± 0.429 5.400 ± 0.499 5.437 ± 0.835 6.672 ± 0.434
1.46 ± 0.792 1.44 ± 0.118 2.05 ± 0.491 3.62 ± 1.043 4.95 ± 0.600
0.997 0.990 0.994 0.977 0.986
0.031 0.086 0.087 0.519 0.488
Fig. 3. Changes in A) inactivation rate constant (k × 10 −2) and B) shape factor (β) as a function of amplitude level (μm).
A. Adekunte et al. / International Journal of Food Microbiology 137 (2010) 116–120
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an internal cavitation as well as internal microstreaming, modifying the cellular structure. Alliger (1975) also mentioned that disruption of subcellular particles during sonication was often faster than disruption of cell walls and that ultrasound rapidly disrupted mitochondria with fine membrane fragmentation. Bactericidal effects on yeast cells were reported during the initial stages of sonication, with the bactericidal and bacteriostatic effects gradually increasing with time and intensity of sonication (Tsukamoto et al., 2004). 4. Conclusions Fig. 4. Changes in desired 5 log reduction (D5, min) as a function of amplitude level (μm).
relationship between the rate constants and amplitude (Fig. 3A,B) were found to fit the equations below with R2 values of 0.92 and 0.95 for k and β respectively. 0:0196 A
ð4Þ
0:0353 A
ð5Þ
k = 0:0205 × e
β = 0:5408 × e
As with k and β, D5 was exponentially related to the ultrasonic amplitude (μm). The relationship between D5 values and amplitude (Fig. 4) were found to fit the following equation with coefficient of regression (R2 = 0.92). −0:0276 A
k = 46:373 × e
ð6Þ
The experimental yeast log reduction (CFU/mL) was plotted against the predicted values from Eq. (1) for the Weibull model. Predicted values were observed to be in good agreement with experimental values with R2 = 0.983 for the Weibull model. 3.2. Effect of ultrasound on yeast inactivation The mechanism of microbial inactivation by power ultrasound is through cavitation, the generation and collapse of micro-bubbles. Bubble collapse within a liquid medium results in localised temperatures of up to 5500 °C and pressures of up to 100 MPa. Consequently the intense local energy and high pressure bring about a localised inactivation effect. The pressure changes that occur from these implosions are the main mechanism for microbial cell disruption (Piyasena et al., 2004). A number of parameters such as frequency and amplitude of ultrasound waves, as well as temperature and viscosity of the liquid medium influence the degree of cavitation (Sala et al. 1995; Mason et al., 1996). At higher amplitude levels which corresponds to higher ultrasound intensities, the inactivation rate was enhanced for yeast (Fig. 2), in accordance with previous studies (Lopez-Malo et al., 1999; Guerrero et al., 2001). The measurement of amplitude instead of power as an indication of the ultrasonic cavitation is reported to be a reliable method for indication of the ultrasound power (Tsukamoto et al., 2004). The presented yeast inactivation could be from a combination of physical and chemical mechanisms which occur during cavitation. The physical effects of sonication may not result in yeast inactivation due to the fact that yeast cells are relatively rigid and may not be disrupted by the action of microstreaming (Iida et al., 2008). However, Iida et al. (2008) emphasised that the rupture of yeast cells due to cavitation bubbles and the release of intercellular protein from yeast cells by ultrasonic action could be proposed as a method for evaluating the physical (mechanical) effects of the ultrasonic field. Koda et al. (2009) studied the effect of sonication on microbial inactivation (E. coli and S. mutans) and concluded that the inactivation mechanism relies mainly on chemical effects. Similarly, Ciccolini et al. (1997) suggested that yeast cells could contain cavitation nuclei and sonication could cause
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