A Study on the Antimicrobial Activity of Thymol Intended As a Natural Preservative

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Journal of Food Protection, Vol. 68, No. 8, 2005, Pages 1664±1670 Copyright ᮊ, International Association for Food Protection

A Study on the Antimicrobial Activity of Thymol Intended as a Natural Preservative

P. FALCONE, B. SPERANZA, M. A. DEL NOBILE, M. R. CORBO, AND M. SINIGAGLIA*

Department of Food Science and Istituto per la Ricerca e le Applicazioni Biotecnologiche per la Sicurezza e la Valorizzazione dei Prodotti Tipici e di QualitaÁ, University of Foggia, Via Napoli, 25-71100 Foggia, Italy

MS 04-574: Received 15 December 2004/Accepted 26 March 2005 Downloaded from http://meridian.allenpress.com/jfp/article-pdf/68/8/1664/1680426/0362-028x-68_8_1664.pdf by guest on 29 September 2021 ABSTRACT

A quantitative investigation on the inhibitory activity of thymol against some microorganisms that could represent a potential spoilage risk both in acid and mild thermally treated foods is presented in this work. In order to assess potential biostatic or biocidal activity of thymol, both the growth kinetics and dose-response pro®les were obtained and analyzed. A suitable macrodilution methodology based on a turbidimetric technique was adopted to produce inhibitory data used for characterizing microbial susceptibility against thymol at sub-MIC levels. Microbial growth was monitored through absorbance measurements at 420 nm as a function of contact time with the active compound. Moreover, for each tested microorganism, the noninhibitory concentration (NIC) and the MIC were quanti®ed. Results prove that thymol can exert a signi®cant antimicrobial effect on each phase of the growth cycle. The microbial susceptibility and resistance were found to be nonlinearly dose related. It is worth noting that signi®cant biostatic effects were observed at sub-MIC levels.

Because of their ¯avoring and antimicrobial properties, tibility. Thymol (or isopropylmetacresol, 2-isopropil-5- herbs and spices historically have been used either to en- methylphenol) has been reported by many authors as one hance the aroma of foods or to increase the shelf life of of the most active antimicrobials among the essential oil packed foods (3, 10, 17). Most of the antimicrobial activ- constituents (8, 15, 28). This is a constituent of thyme es- ities of the above substances have been attributed to their sential oil (up to 50%), a naturally occurring mixture of volatile oil fraction (2, 9, 16, 29, 31, 35, 36). Recently, the potentially active compounds in plants such as T. vulgaris antifungal properties of oregano oil have been demonstrated L. (or thyme). Thymol also is found in oregano essential against Candida albicans (24). Oregano oil (Oreganum vul- oil and in other natural sources such as in mandarin and gare), thyme (Thymus vulgaris), bay (Pimenta racemosa), tangerine oils (0.1 to 0.05%) widely used in soft drinks and and clove (Eugenia caryophyllata) are very effective confectionery. against Escherichia coli (9, 11, 33). Authors have shown According to the Code of Federal Regulations, the U.S. that essential oils of oregano and thyme, which contain Food and Drug Administration lists thymol, thyme essential principally carvacrol and thymol, are effective as fumigants oil, and thyme spice as food for human consumption, as against fungi on storage grains, and they have proposed that well as food additives (http://www.cfsan.fda.gov/dms/ these essential oils be used as an alternative to chemicals eafus.html, date consulted: 16 September 2004). In partic- for preserving stored grains (30). ular, thyme essential oil and thyme spice are considered Essential oils from edible plants are claimed to possess generally recognized as safe (21 CFR 180.10 and 180.20), a broad spectrum of antimicrobial activity due to their high while thymol is recognized as a synthetic food additive (21 content of phenolic derivatives such as thymol, carvacrol, CFR 172.515). On the other hand, according to Annex II etc. Moreover, there is evidence that minor components of Council Regulation 2377/90, the Committee of Experts play a signi®cant role in the whole antimicrobial effect (11, on Flavoring Substances of the European Council registered 22, 25, 27, 30, 31). Differences in concentration of active thymol in the ¯avorings in foodstuff list. An upper limit constituents are strictly related to factors such as variety, agronomic practice, seasons, and processing conditions (1, for inclusion of thymol in food was established at 50 mg/ 6, 14, 23, 26). However, because of high variability both kg and in beverages at 10 mg/kg. Moreover, according to in composition and antimicrobial activity, there are limita- Joint Food and Agriculture Organization of the World tions in the use of essential oils as food preservatives, es- Health Organization Expert Committee on Food Additives, pecially when the foodstuff shelf life or safety critically latest evaluation at 2000, thymol is not expected to be nox- depends on the antimicrobial effectiveness. ious to human health at the current levels of intake when In this work, thymol was used as puri®ed active com- used as a ¯avoring agent. These reasons, together with the pound in characterizing different microorganisms' suscep- high antimicrobial activity of this natural compound at ppm levels and its renewable resource origin, suggest opportu- * Author for correspondence. Tel: (ϩ39) 0881 589 233; Fax: (ϩ39) 0881 nities for sustainability and low disposal costs for the use 740 211; E-mail: [email protected]. in food industry. J. Food Prot., Vol. 68, No. 8 ADVANCES IN MICROBIAL INACTIVATION TESTING AND MODELING 1665

TABLE 1. List of the used microbial strains, source of isolates, and optimal growth conditions Strains Source of isolation Media and growth conditionsa

Lactobacillus curvatus ``Caciocavallo Calabrese'' cheese MRS broth 30ЊC, 24 h Lactobacillus plantarum Wine MRS broth 30ЊC, 24 h Pichia subpelliculosa Minimally processed apples Sabouraud dextrose agar 25ЊC, 48 h Candida lusitaniae Minimally processed apples Sabouraud dextrose agar 25ЊC, 48 h Saccharomyces cerevisiae DAL CIN S.p.A. (Milan, Italy) Sabouraud dextrose agar 25ЊC, 48 h Bacillus cereus ATCC 10876 Plate count agar 30ЊC, 24 h Bacillus subtilis ATCC 6633 Plate count agar 30ЊC, 24 h Bacillus licheniformis Mimimally processed apples Plate count agar 30ЊC, 24 h a MRS, deMan, Rogosa, Sharpe. Downloaded from http://meridian.allenpress.com/jfp/article-pdf/68/8/1664/1680426/0362-028x-68_8_1664.pdf by guest on 29 September 2021 The purpose of this study was to investigate the ef®- containing the active solution with an appropriate concentration cacy of puri®ed thymol as a natural preservative against of thymol, were inoculated (1:10) with standardized cultures with- some yeasts and lactic acid bacteria, typical acid juice spoil- in standard test tubes to yield one active test (AT) for each mi- age organisms (13). Moreover, considering that to extend croorganism under study. At the end of challenge test some col- shelf life of acid foods mild heat treatments are used, thy- onies among the survivors were microscopically examined. mol effectiveness against some spore-forming bacteria was Acquisition of inhibitory data. Turbidimetric experiments also evaluated. For the study we chose Bacillus cereus, a were conducted to produce growth data in the presence of thymol. well-known and ubiquitous foodborne pathogen, plus two Evidence of microbial growth was acquired after 10 s of shaking common spoilage organisms, Bacillus licheniformis and by reading the absorbance changes at 420 nm with a spectropho- Bacillus subtilis. tometer (Beckman DU 600, Fullerton, Calif.) at regular intervals. Each growth experiment was replicated twice and optical density/ MATERIALS AND METHODS time growth curves were built by plotting the optical density mea- sures against the speci®ed contact time. Inoculated media without Organisms, media, and chemicals. Microbial strains used thymol or ethyl alcohol were used as primary positive controls in this study and the source of isolation are listed in Table 1. (PPC) to evaluate the microbial growth under optimal conditions. Selected microorganisms were isolated from fresh and spoiled Inoculated media without active solution but containing an appro- foods and belonged to the Laboratory of Applied Microbiology priate amount of ethyl alcohol (1%, wt/wt) served as secondary (Department of Food Science±University of Foggia) culture col- positive controls (SPC) to test for a possible antagonist or syn- lection with the exception of B. cereus, B. subtilis, and Saccha- ergistic activity of the alcoholic solvent during each growth ex- romyces cerevisiae, which were purchased from public collection. periment. Moreover, uninoculated media containing active solu- Conditions for storage were the following: Lactobacillus cur- tion only was used as primary negative controls (PNC) in eval- vatus and Lactobacillus plantarum were maintained at Ϫ20ЊCin uating the absorbance changes due to the different thymol con- deMan Rogosa Sharpe broth (Oxoid, Milan, Italy) with the ad- centrations. Finally, uninoculated media without active solution dition of 30% glycerol; Pichia subpelliculosa, Candida lusitaniae, served as secondary negative controls (SNC) to take into account S. cerevisiae, B. cereus, B. subtilis, and B. licheniformis were any possible changes in liquid media during growth experiments. grown on slants of appropriate media (Table 1) and stored at 4ЊC as stock cultures. Modeling of inhibitory data for susceptibility testing. The Thymol was purchased from Sigma (Poole, UK), and used actual growth of microbial suspensions in the presence of thymol as received. In order to enhance its water solubility, this essential was evaluated according to Lambert (19), and a growth index (GI) oil was dissolved in ethyl alcohol (95%) and then diluted with was de®ned as follows: distilled water (50%, vol/vol). All stock solutions were freshly ϭ Ϫ Ϫ ϫ prepared before each use and sterilized by ®ltering through mem- GIt [(AAT APNC)/(APPC ASNC)] 100 (1) branes (Minisart model 16534-K with 0.20-␮m pore size; Sarto- rius, Goettingen, Germany). Finally, an aliquot of 150 ␮l of se- where t is the contact time; AAT is the area under growth curves lected stock solutions was added to microbial suspensions in order corresponding to the AT, i.e., the inoculated media containing the to obtain thymol concentrations of 50, 100, 150, 200, 250, 500, active solution; APPC, APNC, and ASNC represent the area under 750, 1,000 ppm (wt/vol). growth curves corresponding to the above de®ned controls, i.e., PPC, PNC, and SNC, respectively. Subtraction of absorbance rel- Growth conditions and cultural methods. Prior to use, ex- ative to negative controls, PNC and SNC, eliminates the interfer- ponentially growing cultures were obtained by allowing each ence of both the active compound and solvents from the active strain to grow in an appropriate liquid medium (Table 1) at its test behavior. optimal temperature. Inocula were prepared by diluting the ex- GIt is a time-dependent and dimensional parameter ranging ponentially growing cultures with physiological solution (0.9% from 0 to 100%. A GIt value of 0 indicates no cell growth during 5 6 NaCl) to obtain approximately 10 CFU/ml for bacteria and 10 experiments; whereas a GIt value of 100 indicates that there is not CFU/ml for yeasts, respectively. To ensure a good degree of re- any change in turbidity between AT and PPC. A GIt value greater producibility in the inocula preparation, the cell counts were stan- than 100 indicates that the active compound enhances microbial dardized through the direct plate count technique (12). growth. For the growth experiments, deMan Rogosa Sharpe broth, In order to assess the antimicrobial activity (biostatic or bio- Sabouraud broth (Biolife, Milan, Italy), and Plate Count broth cidal) of thymol, growth kinetics and dose-response curves were (tryptone, 5 g/liter; glucose, 1 g/liter; yeast extract, 2.5 g/liter), obtained, mathematically modeled, and analyzed. The former 1666 FALCONE ET AL. J. Food Prot., Vol. 68, No. 8

Ϫ{e/[ln(ln NIC/ln MIC)]} GIt/time curves were built by plotting GIt data against time (in [T] the following they will be referred to as relative growth curves). ln MIC Growth kinetics were modeled by ®tting the Gompertz function  ϭ Ϫ as modi®ed by Zwietering et al. (37) to the GI data: GIt* exp ln NIC (6)  ln  ln MIC ␭Ϫt expϪ  ϭ Ϫ ␮ ϩ e GIt C expΆ exp ΂΃max2.7182 1· (2)  []C where [T] is the thymol concentration. Speci®ed contact time (t*) where C is the asymptotic growth index reached at the stationary is supposed to be long enough to reach the stationary phase of phase (equivalent to the upper asymptote of relative growth the growth cycle in the presence of the thymol solutions. So by ␮ curves, i.e., GItϭϱ); max is the maximal rate of growth index ®tting equation 6 to the GIt* data it was possible to directly es- change (de®ned as the tangent in the in¯exion point and expressed timate the NICs and MICs along with their con®dence intervals. in hourϪ1 units); ␭ is the delay time (hours) for microbial response (de®ned as the time-axis intercept of the tangent through the in- Statistical analysis of inhibitory data variance. According ¯exion point); and t is the time (hours). to equation 1, fractional area computation requires four indepen- Downloaded from http://meridian.allenpress.com/jfp/article-pdf/68/8/1664/1680426/0362-028x-68_8_1664.pdf by guest on 29 September 2021 Regarding the dose-response curves, a cumulative GIt value dent experimental measurements, each of which is subject to an at a speci®ed contact time was calculated. By using all inhibitory indeterminate uncertainty affecting the whole indeterminate error data, including those relative to the no-growth status, it was pos- (variance) of the ®nal result. A direct consequence is the nonhom- sible to obtain a speci®c inhibition pro®le for each test microor- ogeneity of GI data variance, which especially increases around ganisms under study. the in¯exion point of both the relative growth curves and inhi- Growth and no-growth status of microbial suspensions con- bition pro®les. Therefore, to improve the accuracy in estimating taining thymol were expressed as the noninhibitory concentration the kinetic parameters as well as the NIC and MIC levels, variance (NIC), representing a threshold value under which no effect on of GIt* data were taken into account. This was achieved by as- microbial growth can be observed, and the MIC, indicating a suming that the optical density measurements ¯uctuate in a ran- threshold concentration over which the active compound exerts dom way and performing a weighted ®tting procedure able to complete inhibition. When a turbidimetric technique is performed reduce the signi®cance related to highest uncertainty within to obtain inhibitory data, MICs indicate that there are no repro- growth data. All ®tting parameters were estimated by using Sta- ducing cells able to cause turbidity changes of microbial suspen- tistica 6.0 software (Stat Soft Inc., 1984 to 2001, Tulsa, Okla.). sions over time. A simple exponential decay model describing RESULTS AND DISCUSSION dose-response behavior of a microorganism against an inhibitor (20, 21) was used to evaluate both NIC and MIC levels. This With the aim of evaluating the potential biostatic or method estimates the Lambert parameters, P1 and P2, by ®tting biocidal activity of thymol, growth kinetics and dose-re- the following equation to the growth data: sponse pro®les were obtained and analyzed. Absorbance measurements have been used already to estimate microbial GI ϭ exp[Ϫ([C]/P1)P2] (3) t* growth; this technique has the advantages of being rapid

where GIt* is GIt calculated at a given level of exposure time (t*), and inexpensive and has been used to determine the anti- [C] is the inhibitor concentration. P1 determines the position of microbial activity of essential oils (5, 20). However, Dal- the in¯exion point of the inhibition pro®le and is de®ned as the gaard and Koutsoumanis (7) have demonstrated that the log of the inhibitor concentration for which GIt* is numerically Gompertz parameters estimated from absorbance data often equal to 1/e. Low P1 values indicate high microbial sensitivity to can be of insuf®cient precision for use in practice, above the active compound, whereas P2 represents a shape parameter all when different factors substantially in¯uencing growth describing the abruptness in the growth index change of the dose- yields, such as pH, carbon substrates, incubation conditions, response curve. In particular, high P2 values prove a very steep etc., have to be studied and compared. In the present study, decline, indicating that a small increase in the inhibitor concen- Gompertz parameters were used only to compare sensitivity tration around P1 level leads to very high change in the microbial to thymol of different microorganisms grown under optimal growth index. Generally, high microbial susceptibility involves conditions. Results on the antimicrobial activity of thymol both low values of P1 and high values of P2. This methodology ␮ ␭ allows one to indirectly de®ne new characteristic parameters such are discussed in terms of C, max, , NIC, and MIC. The as NIC and MIC as the intercept of the line tangential to the results obtained for B. cereus are presented ®rst; afterwards, ϭ ϭ results relative to the other investigated microorganisms are in¯exion point with GIt* 1 and GIt* 0 boundaries, respectively. Once the Lambert parameters are estimated, NIC and MIC discussed. parameters are evaluated with the following formulas: Growth kinetics. GIt data of B. cereus in relation to 1 thymol concentration and contact time are reported in Fig- NIC ϭ P1 exp and (4) ΂΃P2 ure 1. The curves were obtained by ®tting equation 2 to the experimental data. The goodness of ®t was evaluated 1 Ϫ e MIC ϭ P1 exp΂΃ (5) by means of the mean absolute relative error, EÅ % (4), and P2 it was found to be close to 5%. As can be inferred from Å The main disadvantage to using the above approach in a suscep- the data in Figure 1 and from the values of E%, the Gom- tibility study is the impossibility of estimating the con®dence in- pertz equation, as modi®ed by Zwietering (37), satisfacto- terval of both NIC and MIC, since they do not compare explicitly rily ®ts the experimental data. As expected, bacterial in equation 3. In this work, an advance in the Lambert and Pear- growth followed a sigmoidal trend and growth index in- son model (20) was done by rearranging equation 3 as follows: creased with time. It is worth noting that, at a ®xed contact J. Food Prot., Vol. 68, No. 8 ADVANCES IN MICROBIAL INACTIVATION TESTING AND MODELING 1667

FIGURE 1. Relative growth curves of Ba- cillus cereus at thymol concentrations ranging between 50 and 500 ppm. Growth curve corresponding to the primary positive control (PPC) was reported with the solid rhombus. Downloaded from http://meridian.allenpress.com/jfp/article-pdf/68/8/1664/1680426/0362-028x-68_8_1664.pdf by guest on 29 September 2021

time, the growth index was a decreasing function of thymol that higher concentrations of essential oils were required to concentration. The above ®ndings suggest that thymol ex- suppress cell multiplication as compared with those nec- erts a signi®cant antimicrobial effect on each phase of the essary to inhibit germination. This is probably due to the B. cereus growth cycle. These results could be seen in the hydrophobic nature of the spores. Moreover, our results light of the results of Lambert and Hammond (18), who demonstrated that lactic acid bacteria are more resistant to showed that many essential oils, such as eugenol and thy- the action of thymol than spore-forming bacteria. mol, can change the membrane permeability of microbial Results also point out that B. cereus growth kinetics cells, leading to a leakage of chemical constituents that are seem to be a complex function of thymol concentration, as essential for their metabolism. These effects cause a lag proved by the kinetic parameters reported in Table 2. In phase increase as well as a maximum cell load decrease fact, for thymol concentration ranging between 50 and 250 (32, 34). ppm, the value of the growth index at the stationary phase It is reasonable to suppose that vegetative cells of (C) linearly decreased with thymol concentration. A similar spore-forming bacteria can sporulate and become more re- ␮ ␭ sistant to thymol; unfortunately our test procedure evalu- behavior was observed for max, whereas in the case of , ated only the total population and not population of vege- an exponential dependence on the active compound con- tative cells versus spores. In any case, Paster et al. (29) centration was observed. When the thymol concentration have already demonstrated inhibitory effects of oregano was equal to or higher than 500 ppm, the growth index and thyme essential oils on bacterial spores, and Chaibi et reached values close to zero, leading to the conclusion that al. (5) have con®rmed that many essential oils can inhibit at the higher concentration, thymol completely prevented one of several of the different processes involved in the detectable growth. However, since no-growing microbial spore-to-cell transition, namely germination, outgrowth, suspensions completely recovered their growth ability dur- and cell multiplication. In addition, Chaibi et al. observed ing the revitalization experiments (data not shown), it was

TABLE 2. Kinetic parameters related to Bacillus cereus growth at different thymol concentrationsa

␮ Ϫ1 ␭ Thymol (ppm) C max (h ) (h)

0 94.181 (93.111±95.146) 23.554 (18.374±28.735) 2.646 (2.385±2.808) 50 87.627 (87.253±87.999) 6.773 (6.136±7.401) 4.079 (3.548±4.613) 100 66.402 (66.205±66.598) 5.082 (4.867±5.297) 6.174 (5.674±6.670) 150 49.776 (49.257±50.294) 2.659 (2.432±2.885) 11.635 (10.814±12.456) 200 42.367 (41.685±43.048) 0.599 (0.122±0.130) 35.912 (35.142±36.682) 250 15.640 (15.402±15.876) 0.126 (0.122±0.130) 44.732 (43.485±45.979) 500 No growth No growth No growth 750 No growth No growth No growth 1,000 No growth No growth No growth

a Relative growth curves were modeled by means of equation 2; values in parentheses de®ne the con®dence interval. 1668 FALCONE ET AL. J. Food Prot., Vol. 68, No. 8

GI180 data, measurable bacterial growth was not detectable within a third region of the inhibition pro®le above the MIC (``No-Growth region'' in Fig. 2). To immediately compare microbial sensitivity and resistance to thymol, NIC and MIC levels for investigated microorganisms were calculated (Table 3). Microbial sensitivity to the active compound was related to the NICs, whereas the microbial resistance was related to MICs. As reported in Table 3, there are differences in microbial sensitivity to thymol among tested microorganisms; in general all microorganisms showed NIC levels under 100 ppm, ex- cept L. curvatus and L. plantarum, which were character-

ized by the greatest resistance against thymol. For these Downloaded from http://meridian.allenpress.com/jfp/article-pdf/68/8/1664/1680426/0362-028x-68_8_1664.pdf by guest on 29 September 2021 FIGURE 2. Inhibitory pro®le of Bacillus cereus against thymol. microorganisms, NIC levels reached 554 and 697 ppm, re- GI180 is the growth index calculated at the contact time of 180 h. spectively. For the other bacterial species, the susceptibility The error bars represent the standard deviation of the experi- to the thymol inhibitory effect was in the following order: Ϫ mental data. ( ) were obtained by ®tting equation 1 to the GI180 B. subtilis Ͻ B. cereus Ͻ B. licheniformis. As concerns data. yeasts, C. lusitaniae and S. cerevisiae appeared to be less sensitive to the action of thymol than P. subpelliculosa. possible to argue that the observed thymol antimicrobial The possibility of completely inhibiting microbial effect is based on a reversible inhibitory mechanism. growth is related to the use of thymol at the MIC level at least. The bacterial resistance was in the following order: Susceptibility testing. The wide range of thymol con- Ͻ ഠ Ͻ centrations allowed development of a dose-response curve. B. cereus B. subtilis B. licheniformis L. curvatus Ͻ t* was set to 180 h, time necessary to reach stationary L. plantarum. The order of yeast resistance was the fol- Ͻ Ͻ phase for all tested microorganisms. Equation 6 was ®tted lowing: C. lusitaniae S. cerevisiae P. subpelliculosa. As expected, lower MIC levels do not necessarily cor- to the GI180 data versus log of thymol concentration data. The inhibition pro®le corresponding to B. cereus is reported respond to lower NIC levels for the same microorganism. in Figure 2. The goodness of ®t was found to be equal to Thus, the difference between MIC and NIC levels could 0.219%. As also suggested above, results prove that the allow better understanding of microbial behavior in the Ϫ microbial susceptibility to thymol is nonlinearly dose relat- presence of thymol. This new parameter [MIC NIC] can ed. Furthermore, growing and no-growing status were ac- be used to quantify the differences in microbial suscepti- curately individuated by determining both the NIC and bility to thymol. As can be inferred from the data reported MIC parameters, respectively. in Figure 3, signi®cant differences appear both between the For the sake of clarity, the dose-response curve was same microbial group and between bacteria and yeasts. The subdivided in three primary regions to describe the B. ce- error bars represent the standard deviation of the experi- reus susceptibility to thymol. The ®rst region lying below mental data. the NIC (highlighted as ``Growth region'' in Fig. 2) de®nes Further work is needed to determine the effects of pre- a range of thymol concentration that did not signi®cantly vious growth conditions on microbial resistance or suscep- affect microbial growth. The nonlinear dose-dependent in- tibility to thymol; in fact, our work was developed with crease of the antimicrobial activity was proved within an microorganisms grown under optimal conditions of tem- intermediate region bounded by NICs and MICs where the perature and growth medium, which were different for each observed sigmoidal trend of the inhibitory pro®le allows microbial group. On the contrary, microorganisms that con- one to hypothesize a high order kinetics for the B. cereus taminate foods may derive from environments in which inhibition within this boundary. As can be inferred from their previous growth occurred under nonoptimal condi-

TABLE 3. Inhibition parameters for some foodborne microorganisms against thymola Microorganisms NIC (ppm) MIC (ppm)

Bacillus cereus 85.201 (84.512±85.895) C 327.581 (325.263±329.891) I Bacilus subtilis 88.182 (86.983±89.395) D 422.332 (417.784±426.892) H Bacillus licheniformis 43.793 (43.365±44.224) B 422.811 (418.221±427.401) H Lactobacillus curvatus 554.12 (552.85±555.39) E 723.45 (717.35±729.54) L Lactobacillus plantarum 696.87 (695.22±698.52) F 941.01 (932.76±949.26) M Candida lusitaniae 94.391 (93.501±95.273) A 307.901 (304.701±311.093) G Pichia subpelliculosa 43.791 (43.362±44.225) B 422.781 (418,181±427,372) H Saccharomyces cerevisiae 86.042 (85.211±86.847) C 337.761 (333.602±341.932) I a Growth experiments were carried out at the speci®c optimal temperature and with a contact time of 180 h. Values in parentheses de®ne the con®dence interval. Means with different letters in the same column are signi®cantly different (P Ͻ 0.05). J. Food Prot., Vol. 68, No. 8 ADVANCES IN MICROBIAL INACTIVATION TESTING AND MODELING 1669

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