Modelling the effect of essential oil of betel leaf (Piper betle L.) on germination, growth, and apparent lag time of Penicillium expansum on semi-synthetic media

Modelling the effect of essential oil of betel leaf (Piper betle L.) on germination, growth, and apparent lag time of Penicillium expansum on semi-synthetic media

International Journal of Food Microbiology 215 (2015) 171–178 Contents lists available at ScienceDirect International Journal of Food Microbiology j...

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International Journal of Food Microbiology 215 (2015) 171–178

Contents lists available at ScienceDirect

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Modelling the effect of essential oil of betel leaf (Piper betle L.) on germination, growth, and apparent lag time of Penicillium expansum on semi-synthetic media Suradeep Basak ⁎, Proshanta Guha Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

a r t i c l e

i n f o

Article history: Received 26 December 2014 Received in revised form 23 July 2015 Accepted 27 September 2015 Available online xxxx Keywords: antifungal activity spore germination kinetics Monod-type equation Predictive mycology

a b s t r a c t The current study aimed at characterizing the chemical components of betel leaf (Piper betle L. var. Tamluk Mitha) essential oil (BLEO) and modelling its effect on growth of Penicillium expansum on semi-synthetic medium. Gas chromatography-mass spectrophotometry (GC-MS) analysis of BLEO revealed the presence of different bioactive phenolic compounds in significant amounts. Among 46 different components identified, chavibetol (22.0%), estragole (15.8%), β-cubebene (13.6%), chavicol (11.8%), and caryophyllene (11.3%) were found to be the major compounds of BLEO. A disc diffusion and disc volatilization method were used to evaluate antifungal activity of the oil against a selected food spoilage mould. The logistic model was used to study the kinetics of spore germination. Prediction and validation of antifungal effect of BLEO was performed on semi-synthetic medium (apple juice agar) using predictive microbiological tools. The Baranyi and Roberts model was used to estimate maximum growth rate (μmax in mm/day) and apparent lag time (λ in days) of the mould. Secondary modelling was performed using a re-parameterized Monod-type equation based on cardinal values to study the effect of different BLEO concentration on estimated growth parameters. Emax (minimum concentration of oil at which mould growth was inhibited) and MIC (minimum inhibitory concentration of BLEO at which lag time is infinite) value of BLEO against P. expansum was estimated to be 0.56 and 0.74 μl/ml, respectively, which was found to be similar on potato dextrose agar (PDA) as well as apple juice agar (AJA) medium. The correlation between estimated growth parameters of the mould on both the media was obtained with satisfactory statistical indices (R2 and RMSE). This study revealed inhibitory efficacy of BLEO on spore germination, mycelial growth and apparent lag time of P. expansum in a dose-dependent manner. Hence, BLEO has potential to be used as a natural food preservative. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Essential oils have gained its niche as antimicrobials in food preservation with increasing trend of green-consumerism. Presence of bioactive phenolic compounds in essential oils provides antimicrobial properties (Tepe et al., 2005). Most of the phenolic compounds in essential oils have GRAS (Generally Recognized as Safe) status (Burt, 2004) as they originated from plants. Minimum alteration in sensory qualities while retaining its maximum activity is the most sought after criteria for food preservation with essential oils (Nazer et al., 2005). Deep green heart shaped leaves of betel vine are popularly known as Paan (Piper betle L.) in India possess essential oil which can be used as antimicrobial agent in food. The quantity of betel leaf essential oil (BLEO) varies with different cultivars, whereas qualitative attributes of most of the varieties showed a comparable trend in terms of number of biochemical components which determines the bioactive spectrum of BLEO (Guha, 2006). ⁎ Corresponding author. E-mail address: [email protected] (S. Basak). 0168-1605/© 2015 Elsevier B.V. All rights reserved.

Apple juice is a rich and popular source of various components that are beneficial to health around the world with huge consumer demand. But toxicogenic and spoilage microorganism like Penicillium expansum poses a major threat to this juice industry (Liewen and Bullerman, 1992). P. expansum is a psychrotrophic food spoilage mould which causes blue mould rot on fruits, predominantly apples and produces a toxin called patulin (Welke et al., 2011). Predictive microbiology is a useful tool to estimate microbial growth parameters under experimental as well as in food system. For fungi a simple and direct method to evaluate mycelium growth on the surface of solid substrate is to measure colony diameter over period of time (Dantigny et al., 2005b). There are detailed reports about different models for predicting fungal growth and toxin production under different treatment conditions (Garcia et al., 2009). Modelling the effect of water activity, pH, temperature, NaCl, sorbitol on the growth of moulds has been reported previously (Dantigny, 2003; Gibson and Hocking, 1997). However, reports on modelling the effect of essential oils, preferably BLEO on growth of food spoilage moulds were not found in current literature. Till date, many studies have been made on antimicrobial properties of essential oils from different plant sources (Burt, 2004; Da Cruz


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Cabral et al., 2013; Kuorwel et al., 2011; Manso et al., 2014; Sivakumar and Bautista-Baños, 2014; Tiwari et al., 2009), but a few (Prakash et al., 2010) have explored antimicrobial activity of BLEO extracted from major commercial variety of betel leaf found in India. In view of the above research gap, this study was taken up to characterize chemical components and modelling the antifungal efficacy of BLEO on germination, growth and apparent lag time of P. expansum on semi-synthetic medium (apple juice agar). 2. Material and methods 2.1. Extraction and chemical composition of essential oil Betel leaves (Piper betle L.) var. Tamluk Mitha was purchased from the local market of Kharagpur and hydro-distillation of leaves were done using Betel Leaf Oil Extractor designed and developed at IIT Kharagpur (Guha, 2007). Essential oil was eluted in dark sterile glass vial and stored at 4 °C for experimental purpose. The essential oil (10 μl) was dissolved in methyl alcohol (240 μl), and 1 μl of the solution was injected into GS-MS system. Chemical composition of BLEO was evaluated using Gas Chromatography-Mass Spectroscopy (GC-MS) (Thermo Scientific GC (CERES 800 Plus) and MS (DSQ II). A fused silica DB wax column (length = 50 m, ID =0.25 mm, thickness = 0.25 μm) coated with Polyethylene glycol (PEG) was used. Helium was used as carrier gas at a flow rate of 1 ml/min. The injector port temperature was 225 °C and the detector temperature was 250 °C.The oven temperature was initially maintained at 40 °C for 3 min and then increased to 200 °C at rate of 4 °C/min and maintained for 5 min. The temperature was further increased to 250 °C at the rate of 4 °C/min. The split ratio was 1:25 and 70 eV was the ionization voltage. The mass spectrometer was operated in the full scan mode with mass range from 10 to 1000 amu. The ion source temperature was maintained at 200 °C. The obtained mass spectra were thoroughly screened and individual components of essential oils were quantified by relative peak percent area. Identification of each quantified components were done by comparing their mass fragmentation pattern with components stored in spectrometer database using NIST mass spectral library (Version 05, 2005) (Adams, 2007). 2.2. Fungal strains used Filamentous fungal strain P. expansum (MTCC 4485) was obtained from Microbial Type Culture collection and Gene Bank (MTCC), India. It was maintained on potato dextrose agar (PDA; HiMedia, India) at 4 °C and sub-cultured at regular interval. 2.3. Spore suspension Spores from seven days old culture of P. expansum obtained on PDA at 25 °C were harvested with 10 ml of potato dextrose broth (PDB, HiMedia, India) by scraping the mycelial surface gently with L-shaped glass spreader. The spore suspension obtained was counted using a Neubauer's Chamber (depth 0.1 mm, 0.0025 mm2) under biological microscope (Olympus CX31, Tokyo, Japan) and expressed as spores per millilitre. PDB was used to adjust the final spore concentration of 108 spores/ml and was used on the same day of experiment. 2.4. Antifungal efficacy of BLEO in liquid and vapour phase 2.4.1. Disc diffusion method Antifungal activity of BLEO in liquid phase was examined according to disc diffusion method reported by Lopez et al. (2005). Briefly, 100 μl of tested fungal spore suspension (108 spores/ml) was spread over Petri plates (90 mm diameter) containing solidified PDA medium. Desired volume (10, 20, 30 μl) of undiluted oil was pre-soaked in sterile filter paper disc (Whatman filter paper no.1, GE Healthcare co., UK) of

6 mm diameter and placed on the top of inoculated plates. Control plates contained distilled water to the disc, instead of essential oil. The plates were incubated at 25 ± 0.5 °C, and the mean of two perpendicular diameter of inhibition zone was measured after 72 h of incubation. 2.4.2. Disc volatilization method Antifungal activity of BLEO in vapour phase was examined by disc volatilization method using standard experimental set-up described by Tyagi et al. (2012). Briefly, 100 μl fungal spore suspension (108 spores/ml) was spread over the solidified PDA medium. Filter paper disc (Whatman No.1) of 6 mm diameter containing desired volume (10, 20, 30 μl) of undiluted oil was placed at centre of inside portion of upper lid. Inoculated plates were immediately inverted on top of the lid containing disc and were sealed with parafilm to avoid leakage of oil vapours. No hermetic sealing was done as this experiment was designed to mimic worst case situation. Plates were incubated at 25 ± 0.5 °C and mean of two perpendicular diameter of inhibition zone was measured after 72 h of incubation. 2.5. Growth medium Growth of P. expansum on the PDA under influence of BLEO was studied using poisoned food technique (Tripathi et al., 2007). Briefly, Table 1 Chemical composition of Piper betle L. var. Tamluk Mitha essential oil (BLEO). Sn.

Rt. (min)



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

6.8 7.83 8.52 8.95 9.29 10.48 11.68 12.11 12.79 13.23 14.08 14.53 20.95 21.44 21.76 22.64 23.24 23.39 24.93 25.28 25.54 27.13 27.4 28.02 28.23 28.71 29.4 30.01 30.74 31.03 31.94 32.15 33.3 35.39 36.85 38.19 38.39 38.65 39.14 39.77 40.71 40.86 41.39 42.34 42.66 44.57

α-Pinene Camphene Undecane β-Terpinene β-Phellandrene L-β-pinene D-Limonene Eucalyptol β-trans-ocimene γ-Terpinene m-xylene Allo-Ocimene δ-elemene Ylangene α-Cubebene β-Bourbonene (+)epi-bicyclosesquiphellandrene Linalool β-elemene Caryophyllene Aciphyllene Epizonarene Estragole γ-Muurolene Virdiflorene β-Cubebene Elixene δ-Cadinene 4-Isopropyl-1,6-dimethyl-1,2,3,4,4a,7-hexahydronaphthalene α-Cadinene Anethole Seychellene Isosafrole 4-Allylphenyl acetate Methyleugenol Carotol Cubenol (−)-Globulol Hexadecamethyl-cyclooctasioxane Spathulenol Pyridine-3-carbonitrile Epizonarene Chavibetol α-cadinol Octadeamethyl-cyclononasiloxane Chavicol

0.21 0.31 0.02 0.05 0.04 0.14 0.15 1.10 0.12 0.03 0.02 0.05 0.42 0.16 2.0 0.36 0.15 0.28 2.7 11.3 0.51 0.34 15.8 6.00 0.53 13.6 3.2 2.1 0.14 0.11 0.08 0.41 0.13 1.2 0.4 0.1 0.15 0.21 0.37 0.16 0.21 0.14 22.0 0.38 0.32 11.8

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1 ml of PDB containing 5% (v/v) Tween-20 and BLEO were dissolved separately in Petri plates (9 × 1.4 cm) containing 9 ml of warm sterilized PDA medium (aw 0.99, pH 5.6 ± 0.2 at 25 °C) to produce concentration range of 0.1–1.5 μl/ml of BLEO. Semi-synthetic media includes preparation of apple juice agar (AJA) supplemented with varied concentration of BLEO. Briefly, apples (cv. Red delicious) at commercial maturity were purchase from local market of IIT Kharagpur. After being cleaned with distilled water, each apple was cut and made into juices (TSS 14 0Brix, aw 0.99, pH 4.5 ± 0.2 at 25 °C) using mixer grinder. According to Tremarin et al. (2014), 1.5 g of agar was added to 100 ml of apple juice and heated at 115 °C (centre temperature) for 1 min to obtain AJA. Similar to PDA plates, poisoned food technique (Tripathi et al., 2007) was also used to prepare AJA plates containing different concentration of BLEO (0.1–1.5 μl/ml). 10 μl spore suspension (108 spores/ml) was aseptically inoculated at the centre of each PDA and AJA plates including control sets (without BLEO) and incubated at 25 ± 0.5 °C. The mould growth was evaluated by measuring the mean of two perpendicular diameters using ruler at regular interval for 60 days.


Fig. 2. Germination kinetics of P. expansum under different BLEO concentration that includes 0.0 μl/ml (●), 0.1 μl/ml (■), 0.2 μl/ml (♦), 0.3 μl/ml (○), 0.4 μl/ml (□) on potato dextrose agar. Each point represents germination percentage of 600 spores and (—) indicates fitted logistic model. Values are mean ± S.D.

slope term for the rate of increasing germinated spores (Dantigny et al., 2002).

2.6. Spore germination kinetic 2.7. Modelling mould growth The modified method of Gougouli and Koutsoumanis (2012) was used to study germination of P. expansum spores. Briefly, 100 μl of spore suspension (108 spores/ml) was spread to obtain a layer of single spores over PDA medium added with BLEO (0.1–1.5 μl/ml), plates were sealed with parafilm and incubated at 26 ± 1 °C. No hermetic sealing was done so as to simulate a real time situation. To study spore germination percentage at regular time interval, three pieces of agar slab (10× 10 mm) from each Petri plates were aseptically cut using scalpel and transferred to microscopic slides, stained with lactophenol cotton blue (HiMedia, India). A coverslips was placed on each agar slab and observed under 40× resolution of biological microscope (Olympus CX31, Tokyo, Japan). Total of 600 spores (200 spores per agar slab and 30–35 spores per microscopic field) were counted for individual concentration of BLEO at regular time interval. Spores were considered germinated only when the length of germ tube was equal or exceeded spore diameter. For each treatment the germination percentage was calculated as P (%) = (Ngerminated spores/Ntotal spores)*100 and the data was fitted to logistic model to estimate germination parameters k (h−1) and τ (h): P max  1 þ ekðτ−tÞ

2.7.1. Primary modelling The experimental data of colony diameter over time was fitted to the Baranyi and Roberts model to estimate maximum growth rate and apparent lag time of P. expansum grown on PDA and AJA medium. Avoiding upper asymptotic part, the lag-linear portion of the each growth curves were fitted to the primary growth model (Baranyi and Roberts, 1994) using the following equation: "

n : ln expð−μ max t Þ þ expð−μ max λÞ # o − expð−μ max t−μ max λÞ

Dðt Þ ¼ Do þ μ max t þ


μ max


Where D(t) is the colony diameter (mm) at any time t (days), Do is colony diameter (mm) when t = 0, μmax (mm/day) is maximum growth rate and λ (days) is apparent lag time of the mould growth.

Where, P (%) is the percentage of germinated spores, Pmax (%) is maximum percentage of germination set to 100, τ (h) is time of inflexion point where P become half of Pmax, t is the time (h) and k (h−1) is the

2.7.2. Data treatment Prior to fit the secondary model to the estimated growth parameters, raw data were transformed to homogenize the variance. Accordingly, raw μmax and λ data were square-root transformed (Dantigny and Bensoussan, 2008) as square root transformation showed better stability of variance than natural logarithmic transformation.

Fig. 1. Antifungal activity of BLEO in liquid phase (Δ) and vapour phase (□) against P. expansum: zone of inhibition under different volume of oil: 10 μl ( ), 20 μl ( ), 30 μl ( ). Values are mean ± S.D.

Fig. 3. Effect of BLEO on germination model parameters: (▲) represents time (h) for 50% germination.




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Table 2 Parameter estimates and 95% confidence interval of the logistic model for the in vitro spore germination data of P. expansum under different BLEO concentration. BLEO (μl/ml) 0 0.1 0.2 0.3 0.4 0.5

k (h−1)

τ (h)


0.664 (0.570, 0.757) 0.782 (0.714, 0.850) 0.773 (0.701, 0.844) 0.677 (0.633, 0.722) 0.407 (0.369, 0.445) No germination

12.6 (12.4, 12.8) 17.8 (17.7, 17.9) 22.4 (22.3, 22.6) 39.4 (39.3, 39.5) 93.9 (93.7, 94.2)

0.981 0.988 0.985 0.991 0.980

RMSE 5.3 3.8 4.1 3.2 3.9

2.7.3. Secondary modelling Estimated maximum growth rate (μmax) data were modelled as function of BLEO (E) using a re-parameterized Monod-type equation based on cardinal values as described by Dantigny et al. (2005a) using the following equation:

2.8. Statistical analysis One way ANOVA was performed and means were sorted using Tukey's test (P = 0.05) for all the data. Primary and secondary model was fitted to individual experimental raw data and transformed data, respectively. The model parameters were estimated by LevenbergMarquardt algorithm for nonlinear least square minimization using Graphpad Prism version 5.0 for Windows (GraphPad Software, San Diego, CA, USA). The performance of models was assessed using Root Mean Square Error (RMSE) and coefficient of determination (R2). Models having RMSE values close to zero and R2 values close to one were considered as good fit (Ratkowsky, 2003). All experiments were conducted in triplicates and repeated thrice to establish repeatability. Values presented here represents mean of these replicates with standard deviation or standard error. 3. Results and discussion

√μ ¼

 μ opt

K ðE max −EÞ KE max −2KE þ EE max

1=2 ð3Þ

Optimum growth rate (μopt), minimum concentration of oil at which mould growth was inhibited (Emax) and oil concentration at which growth rate reduces to half (K) are model parameters to be estimated. Similarly, estimated apparent lag time (λ) data were transformed and fitted to reciprocal of re-parameterized Monod-type equation (Judet-Correia et al., 2011) for secondary modelling of λ as function of BLEO (E) according to the following equation:

√λ ¼

  K λ :ðMIC Þ−2K λ :E þ E:ðMIC Þ 1=2 λopt K λ ðMIC−EÞ


where, λopt (days) is the apparent lag time at E = 0 μl/ml; Kλ (μl/ml) is the BLEO concentration at which λ = 2λopt; and MIC is minimum inhibitory concentration of BLEO at which lag time is infinite.

3.1. Chemical composition of BLEO After analysing BLEO using GC-MS, 46 different components, comprising 99.7% of total oil composition were identified. Table 1 shows the identified chemical compounds, its retention time (Rt.) and percentage of the component in total oil. Five major compounds were found to be chavibetol (22.0%), estragole (15.8%), β-cubebene (13.6%), chavicol (11.8%), and caryophyllene (11.3%). Components like eucalyptol (1.1%), α-Cubebene (2.0%), β-elemene (2.7%), γ-Muurolene (6.0%), Elixene (3.2%), δ-Cadinene (2.1%), 4-Allylphenyl acetate (1.2%) were also present in trace amount. A few reports suggested dietary and other health benefits of individual chemical components found in BLEO but reports on antimicrobial activity of total oil is rare. Chavibetol is a distinct allylbenzene compound usually found in essential oils of betel leaves and may be responsible for its unique aroma. Earlier works on essential oil from different varieties of betel leaves revealed the existence of 4-allyl-2-methoxyphenolacetate (31.47%) and 3-allyl-6-methoxyphenol (25.96%) (Tawatsin et al., 2006), chavibetol (53.1%) and chavibetol acetate (15.5%) (Rimando et al., 1986) and eugenol (11.73%), allylpyrocatechol

Fig. 4. Primary modelling (—) of colony diameter of mould grown on (a) PDA: 0.0 μl/ml (○), 0.1 μl/ml (□), 0.2 μl/ml (×), 0.3 μl/ml (∇), 0.4 μl/ml (⨀); (b) AJA: 0.0 μl/ml (Δ), 0.1 μl/ml (∇), 0.2 μl/ml (×), 0.3 μl/ml (□) and (c) AJA: 0.4 μl/ml (◊), 0.5 μl/ml (+) treated with different dose of BLEO (μl/ml) using the Baranyi and Roberts model. Values are mean ± S.D.

S. Basak, P. Guha / International Journal of Food Microbiology 215 (2015) 171–178 Table 3 Estimated parameters (with 95% confidence interval) of the Baranyi and Roberts model fitted to obtained colony diameter (mm) of P. expansum grown on PDA and AJA treated with BLEO. BLEO (μl/ml)

μmax (mm/day)

λ (days)


0.2d (0.1, 0.3) 0.5d (0.2,1.0) 0.5d (0.2, 0.8) 4cd (3.5, 4.0) 5.6bcd (4.7, 6.5) 17bc (16.3,17.9)

0.999 0.982 0.992 0.991 0.864 0.820

0.6 2.6 1.6 1.5 4.1 0.9

0.8d (0.6, 1.0) 1.5cde (1.1, 1.9) 2cde (1.5, 2.3) 4cd (2.3, 5.1) 19b (18.4, 19.2) 44a (43.4, 44.1)

0.997 0.976 0.971 0.866 0.957 0.988

1.0 2.6 2.5 1.4 0.2 0.2


PDA medium 0.0 0.1 0.2 0.3 0.4 0.5 0.6

7.3a (7.23, 7.35) 7.0a (6.6, 7.2) 6.4ab (6.24, 6.6) 4.0bc (3.84, 4.1) 3.0cd (2.75, 3.55) 1.0d (0.72, 0.97) No growth

0.0 0.1 0.2 0.3 0.4 0.5 0.6

AJA medium 7.0a (7.0, 7.23) 6.5ab (6.18, 6.88) 6.0abc (5.48, 6.21) 1.0d (0.85, 1.1) 0.4d (0.42, 0.48) 0.3d (0.25, 0.27) No growth

The means followed by same letter in same column are not significantly different according to ANOVA and Tukey's multiple comparison tests.

diacetate (11.34%) and chavibetol acetate (12.55%) (Arambewela et al., 2005). Such variation of chemical profile of many essential oils has been reported due to change in geographical locations, climate, growth stage and harvesting time of leaves (Bagamboula et al., 2004). Among all major chemical components identified in BLEO, estragole is the only component which has restricted use in European Union, whereas all chemical compounds of BLEO have GRAS status in United States Food and Drug Administration (FDA). Prakash et al. (2010) reported eugenol (63.39%) and acetyleugenol (14.05%) as main components responsible for antifungal activity of Piper betle L. (cv. Magahi) essential oil. Due to narrow variation in percentage of major chemical components, it is difficult to judge the key component responsible for antifungal properties of BLEO (cv. Tamluk Mitha) in the current study. However, synergy between major and minor chemical components of BLEO may be responsible for its higher antifungal activity as compared to its single components like hydroxychavicol (Ali et al., 2010). 3.2. Antifungal efficacy of BLEO in liquid and vapour phase Antifungal effect of different concentration of BLEO against P. expansum culture in liquid phase and vapour phase was observed in terms of inhibition zone generated due to diffusion of phenolic components of essential oil into fungal strain inoculated PDA medium. As shown in Fig. 1, diameter (mm) of inhibition zone increases from 42.8 ± 1 mm to 53.8 ± 2 mm for 10 and 30 μl of BLEO in liquid phase, respectively, whereas in vapour phase diameter of clear zone increased from 28.7 ± 1 mm to 38.5 ± 1 mm for 10 and 30 μl of BLEO, respectively. Although, complete growth inhibition was not observed at highest concentration of BLEO (30 μl) in any of the phases and inhibition zone was absent in both phases for untreated plates. Essential oil from different plant origin have been tried and tested for its antimicrobial activity, but most of them have showed higher activity in vapour phase (Becerril et al., 2007; Tyagi and Malik, 2010). On the contrary, Doran


et al. (2009) have suggested higher activity of geranium essential oil against Gram positive bacteria in direct contact than vapour phase, which supports the outcome of the current study. Hence, it can be suggested that BLEO is more effective in liquid phase as compared to vapour phase due to more lag time for dissolving BLEO in vapour phase to the medium. 3.3. Spore germination kinetics Germination percentage of spores over time was fitted to the logistic model to estimate germination kinetic parameters k (h−1) and τ (h). Due to symmetrical nature of the model, it was preferred over Gompertz model. Also, Pmax was fixed to 100 because 100% germination occurred under every BLEO concentration. The logistic model was able to describe percentage of germination of P. expansum over time under influence of BLEO (Fig. 2), with goodness of fit R2 ranging from 0.980 to 0.991 and RMSE ranging from 3.2 to 5.3 under BLEO concentration ranging from 0.0 to 0.4 μl/ml. BLEO has significant impact on germination time (Fig. 3). Increase in time for 50% germination (τ) was observed with increasing concentration of BLEO (Table 2). No spore germination occurred at and beyond 0.5 μl/ml of BLEO. It can be hypothesised that fungitoxicity of BLEO increased with increasing concentration, which makes it difficult for single spores to detoxify essential oil present on their surface. Hence, the germination process gets delayed or inhibited after a given concentration. Efficacy of BLEO against spore germination was found to be promising as compared to earlier reports on inhibitory effect of essential oil from different plant sources on spore germination (Soylu et al., 2010; Tzortzakis and Economakis, 2007; Tian et al., 2012). 3.4. Predictive modelling 3.4.1. Primary modelling Colony diameter of P. expansum on treated PDA and AJA plates over time and its primary modelling with the Baranyi and Roberts model are shown in Fig. 4. The curve showed typical mould growth with lag-linear phase without upper asymptote (stationary phase) part. Decline in maximum growth rate (μmax) and increase in apparent lag time (λ) of mould was observed with increase in BLEO concentration (μl/ml) in both media. Parameter estimates of primary model to the experimental colony diameter data of both studies are shown in Table 3. μmax of the mould on PDA and AJA plates containing no BLEO were not significantly different (P = 0.49), whereas effect of BLEO on rate of mould growth was more pronounced on AJA than PDA. Likewise, no significant difference in apparent lag time (λ) was found on both untreated medium, but treatment with 0.1–0.5 μl/ml of BLEO resulted in extension of apparent lag time from 0.2 to17 days and 0.8 to 44 days on PDA and AJA medium, respectively. Estimated μmax and λ of P. expansum on treated AJA were lower and longer, respectively as compared to those observed on PDA which can be the reason for higher efficacy of BLEO on the semi-synthetic medium. Gutierrez et al. (2009) have reported similar observation of lower growth rate and longer lag phase of bacteria in semisynthetic (lettuce leaf model media) media than in synthetic media (Tryptic soy broth and beef extract). Gutierrez et al. (2008) suggested that higher efficacy of thyme and oregano essential oil against Listeria monocytogenes grown in protein rich beef extract (BE) media was due to interaction of the EOs with hydrophobic peptone molecules of BE that facilitated the dissolution of the EOs in the medium. Based on the

Table 4 Parameter estimates and 95% confidence interval of secondary model fitted to obtained maximum growth rate (μmax) data of P. expansum grown on PDA and AJA containing BLEO. Estimated parameters Growth medium PDA AJA

μopt (mm/day)

K (μl/ml)

Emax (μl/ml)

2.72a (2.63, 2.81) 2.88a (2.54, 3.21)

0.46b (0.44, 0.47) 0.30b (0.24, 0.36)

0.56b (0.55, 0.57) 0.56b (0.50, 0.61)




1.62 1.07

0.988 0.919

0.1 0.3

The means followed by same letter in same column are not significantly different according to ANOVA and Tukey's multiple comparison tests.


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Fig. 5. Experimental plots (a) PDA and (b) AJA for secondary modelling (—) of maximum growth rate vs. BLEO using are-parameterized Monod type equation. Values are mean ± S.D.

report by Gill et al. (2002), it can be suggested that favourable nutrient composition of PDA enables P. expansum spore to germinate faster as compared to AJA under same BLEO treatment. Minimum dose that showed no visible mould growth on treated PDA and AJA during 60 days of incubation was found to be 0.6 μl/ml of BLEO. RMSE and R2 values were able to describe good fit of the model on PDA as well as AJA growth data of P. expansum. Complete inhibition of spore germination was observed at 0.5 μl/ml of BLEO, whereas minimum BLEO concentration at which no mycelial growth was found to be 0.6 μl/ml. Single spore on PDA medium treated with BLEO didn't show germination, whereas a drop of spore suspension (108 spores/ml) at centre on similar medium treated with same BLEO concentration resulted in visible mycelial growth. This can be attributed to the fact that probability of single spore to germinate after detoxification of BLEO present in media is very small, whereas in a point inoculum (108 spores) each and every spore have equal chance to germinate post detoxification of BLEO under same treatment condition and form a colony. Also, surface area of 108 spores spread on the surface of media will be more as compared to point inoculum of same spore concentration. Hence, with spread plate most of the spore surface is exposed to BLEO present in medium, whereas all spores in point inoculum are not as much exposed to the toxic oil. Darling and McArdle (1959) also suggested that single spore cannot germinate under stressed condition as compared to heavy inoculum. Sharma and Tripathi (2006) have also reported extreme toxicity of Citrus sinensis essential oil to spore germination of P. expansum at 500 ppm, whereas mycelial growth of same mould was inhibited at 600 ppm using similar technique.

3.4.2. Secondary modelling Secondary modelling of observed maximum growth rate (μmax) as function of BLEO for both studies was performed using a re-parameterized Monod type equation as given in Eq. (3). RMSE and R2 suggest good fit of the model to both PDA and AJA data sets (Table 4). Judet-Correia et al. (2010) reported optimum growth rate (μopt) of 2.86 mm/day for P. expansum on PDA at 25 °C and validation of predicted parameters on synthetic grape juice medium and grape juice agar. In current study, μopt of P. expansum on PDA and AJA were found to be 2.72 and 2.88 mm/day, respectively. This suggests that apple juice agar used in current study can mimic PDA to predict the growth of the mould. K values estimated the concentration of oil when μ becomes ½ μopt and this value determines shape of the curve. For PDA, convex shaped curve (Fig. 5) were obtained with K/(Emax/2) value greater than 1. The convex shaped curve suggests that P. expansum is less sensitive at lower BLEO concentrations and increase in dose higher than K value, increases the inhibition, whereas, curve obtained for AJA is almost linear in shape with K/(Emax/2) value of 1.07, which is close to 1. This suggests that inhibitory effect increases with every increasing concentration of BLEO. The present study showed that antifungal activity of BLEO in AJA is similar to PDA with same estimated Emax value of 0.56 μl/ml at 25 °C.

BLEO concentration that reduced mould growth to half (K value) was found to be low on AJA (0.3 μl/ml) than on PDA (0.46 μl/ml). Neri et al. (2006) reported minimum inhibitory concentration (MIC) of trans2-hexenal vapours against P. expansum for in vitro and in vivo (Conference pears) system is 21.5 μl/L and 12.5 μl/L, respectively. Similarly, Busatta et al. (2007) also reported bacteriostatic effect of oregano essential oil at relatively low concentration on infected fresh sausage than in vitro inhibitory concentration against aerobic heterotrophic bacteria and Escherichia coli. Growth medium treated with BLEO concentration ≥ Emax value did not show any mould growth during the experimentation period of 60 days. Previous studies on antifungal efficacy of different essential oils against P. expansum on food system by incorporating EOs in active films and packaging have also been reported. Among a few includes the report of Montero-Prado et al. (2011) that reported reduced infection of P. expansum on active packaged “Calanda” peach fruit using cinnamon essential oil during storage at 20–25 °C for 12 days. Likewise, Balaguer et al. (2014) has shown effectiveness of gliadins based active films containing 0.5% natamycin and 5% cinnamaldehyde against P. expansum in soft-cheese slices active packaged with the film. Storage of apples with pullulan enriched sweet basil extract coating was reported to have better physical and chemical attributes and lower incidence of mesophilic bacterial infection as compared to control sets (Synowiec et al., 2014). Estimated parameters obtained from secondary modelling of apparent lag time of P. expansum on PDA and AJA medium as a function of BLEO using reciprocal of re-parameterized Monod-type equation are shown in Table 5. Optimum apparent lag time (λopt) was found to be 0.35 and 0.48 days on PDA and AJA, respectively. Estimated Kλ value was found to be less than K value. It was estimated that at 0.12 μl/ml of BLEO, λ becomes 2λopt on both PDA and AJA. MIC value for both PDA and AJA was not significantly different (P = 0.51). Estimated Emax value (0.56 μl/ml) was found to be lower than MIC value (0.74 μl/ml). Similar observation was made by Judet-Correia et al. (2011) on modelling the effect of copper sulphate on growth rate and apparent lag time of P. expansum. The secondary model fitted the data with satisfactory value of statistical indices (RMSE and R2). Fig. 6 shows the effect of BLEO on apparent lag time of the mould on PDA and AJA. Incubation time is important factor to estimate MIC value using the selected

Table 5 Parameter estimates and 95% confidence interval of secondary model fitted to obtained apparent lag time (λ) data of P. expansum grown on PDA and AJA containing BLEO. Growth medium PDA AJA

Estimated parameters λopt (days)

Kλ (μl/ml)



MIC (μl/ml)

0.35b (0.09, 0.61) 0.12c (0.02, 0.22) 0.74a (0.61, 0.87) 0.964 0.3 0.48b (0.07, 1.03) 0.12c (0.03, 0.25) 0.72a (0.59, 0.85) 0.973 0.4

The means followed by same letter in same column are not significantly different according to ANOVA and Tukey's multiple comparison tests.

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Fig. 6. Experimental plots (a) PDA and (b) AJA for secondary modelling (—) of detection time vs. BLEO using reciprocal of re-parameterized Monod type equation. Values are mean ± S.D.

secondary model. It is evident from the fact that lower incubation period cannot determine actual growth behaviour of P. expansum under BLEO treatment. Hence, maximum incubation time of 60 days was selected in the current study so as to avoid inappropriate MIC. 3.5. Correlation between growth parameters of PDA and AJA The correlation curves between μmax and λ of PDA and AJA are shown in Fig. 7. The developed correlation equations describe the relationship between μmax and λ of P. expansum on AJA with respect to PDA under influence of BLEO. μ AJA ¼ 0:244ðμ PDA Þ2 −0:853ðμ PDA Þ þ 0:748


λin vivo ¼ 2:588ðλin vitro Þ−0:22


Plot μAJA vs. μPDA with data points (0–0.4 μl/ml) except 0.5 μl/ml, followed linear distribution pattern with R2 = 0.99 and RMSE = 0.4. Whereas, same plot μAJA vs. μPDA with all data points (0–0.5 μl/ml) followed non-linear (quadratic) distribution (Eq. (5)) with R2 = 0.992 and RMSE =0.4. This is due to significant (P = 0.005) reduction in μmax of P. expansum on both PDA and AJA medium treated with 0.5 μl/ml of BLEO with respect to other treatments (0–0.4 μl/ml). On the contrary, all data points of plot λAJA vs. λPDA were fitted to linear regression model (Eq. (6)) with R2 = 0.962 and RMSE =3.7. According to Judet-Correia et al. (2011), it can be suggested that presence of BLEO in growth medium imparts toxicity at surface of spores which prevents them to germinate. Therefore, higher BLEO concentration would increase time to detoxify the medium to facilitate spore germination, hence longer lag phase would be observed. Similar reason can be suggested for discrepancy in λAJA vs. λPDA instead of μAJA vs. μPDA plot, because delay in germination extended the apparent lag time of P. expansum to a greater extent on AJA than PDA under same treatment condition, whereas correlation between growth rate of the mould on AJA and PDA under given BLEO concentration remained unaffected.

4. Conclusion It can be concluded from the present study that, BLEO has high antifungal properties against a selected predominant food spoilage mould. Chemical composition of BLEO cv. Tamluk Mitha revealed wide variety of bioactive phenolic compounds that are present in significant amount in total essential oil content, and are also responsible for antimicrobial properties of oil. Spore germination kinetic study revealed the efficacy of BLEO to inhibit germination of P. expansum spores at much lower concentration as compared to other essential oils reported. It was also found that increase in BLEO concentration delayed the germination time of spore up to a point, beyond that no germination occurred. The Baranyi and Roberts model can describe the experimental data of colony diameter on PDA as well as AJA with satisfactory RMSE and R2 values. Also, secondary modelling of μmax and λ with respect to BLEO defined the effect of oil on the mould growth with increase in BLEO to a point after which no growth occurred. Statistical indices suggested the goodness of fitted model at 95% level of confidence. The obtained correlation curves can be useful to compare the effect of BLEO on estimated growth parameters of P. expansum grown on PDA and AJA. After evaluating classical criteria for antifungal efficacy, BLEO was found to be a potent antifungal agent from plant source that can be used as natural food preservative in comparatively low doses. Further study on spore germination of mould on real food system and mode of action of BLEO on the mould is warranted.

Acknowledgements The authors are grateful to Indian Council of Agricultural Research (ICAR), New Delhi, for financial assistance and Indian Institute of Technology Kharagpur for providing the infrastructure and facilities to conduct the research. They also thank Dr. S. L. Shrivastava and Dr. Jayeeta Mitra, Agricultural and Food Engineering Department, IIT Kharagpur for continual support and suggestions throughout.

Fig. 7. Correlation curve (—) between: (a) maximum growth rate (μmax) and (b) apparent lag time (λ) of P. expansum on PDA and AJA.


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References Adams, R.P., 2007. Identification of Essential oil Components by gas Chromatography/ Mass Spectrometry. Allured Publishing Corporation, Carol Stream, IL. Ali, I., Khan, F.G., Suri, K., Gupta, B.D., Satti, N.K., Dutt, P., Afrin, F., Qazi, G.N., Khan, I., 2010. In vitro antifungal activity of hydroxychavicol isolated from Piper betle L. Ann. Clin. Microbiol. Antimicrob. 9, 1–9. Arambewela, L., Kumaratunga, K.G.A., Dias, K., 2005. Studies on Piper betle of Sri Lanka. J. Natl. Sci. Found. Sri Lanka 33, 133–139. Bagamboula, C.F., Uyttendaele, M., Debevere, J., 2004. Inhibitory effect of thyme and basil essential oils, carvacrol, thymol, estragol, linalool and p-cymene towards Shigella sonnei and S. flexneri. Food Microbiol. 21, 33–42. Balaguer, M.P., Fajardo, P., Gartner, H., Gomez-Estaca, J., Gavara, R., Almenar, E., Hernandez-Munoz, P., 2014. Functional properties and antifungal activity of films based on gliadins containing cinnamaldehyde and natamycin. Int. J. Food Microbiol. 173, 62–71. Baranyi, J., Roberts, T.A., 1994. A dynamic approach to predicting bacterial growth in food. Int. J. Food Microbiol. 23, 277–294. Becerril, R., Gomez-Lus, R., Goni, P., Lopez, P., Nerin, C., 2007. Combination of analytical and microbiological techniques to study the antimicrobial activity of a new active food packaging containing cinnamon or oregano against E. coli and S. aureus. Anal. Bioanal. Chem. 388, 1003–1011. Burt, S., 2004. Essential oils: their antibacterial properties and potential applications in foods a review. Int. J. Food Microbiol. 94, 223–253. Busatta, C., Mossi, A.J., Rodrigues, M.R.A., Cansian, R.L., Oliveira, J.V., 2007. Evaluation of Origanum vulgare essential oil as antimicrobial agent in sausage. Braz. J. Microbiol. 38, 610–616. Da Cruz Cabral, L., Fernández Pinto, V., Patriarca, A., 2013. Application of plant derived compounds to control fungal spoilage and mycotoxin production in foods. Int. J. Food Microbiol. 166, 1–14. Dantigny, P., 2003. Predictive mycology. In: McKellar, R.C., Lu, X. (Eds.), Modelling Microbial Responses in Foods. CRC Press, Boca Raton, Fl, USA, pp. 313–320. Dantigny, P., Bensoussan, M., 2008. The logarithmic transformation should be avoided for stabilising the variance of mould growth rate. Int. J. Food Microbiol. 121, 225–228. Dantigny, P., Soares Mansur, C., Sautour, M., Tchobanov, I., Bensoussan, M., 2002. Relationship between spore germination kinetics and lag time during growth of Mucor racemosus. Lett. Appl. Microbiol. 35, 395–398. Dantigny, P., Guilmart, A., Radoi, F., Bensoussan, M., Zwietering, M., 2005a. Modelling the effect of ethanol on growth rate of food spoilage moulds. Int. J. Food Microbiol. 98, 261–269. Dantigny, P., Guilmart, A., Bensoussan, M., 2005b. Basis of predictive mycology. Int. J. Food Microbiol. 100, 187–196. Darling, W.M., McArdle, M., 1959. Effect of inoculum dilution of spore germination and sporeling growth in a mutant strain of Aspergillus amstelodami. Trans. Br. Mycol. Soc. 42, 235–242. Doran, A.L., Morden, W.E., Dunn, K., Edwards-Jones, V., 2009. Vapour-phase activities of essential oils against antibiotic sensitive and resistant bacteria including MRSA. Lett. Appl. Microbiol. 48, 387–392. Garcia, D., Ramos, A.J., Sanchis, V., Marin, S., 2009. Predicting mycotoxins in foods: a review. Food Microbiol. 26, 757–769. Gibson, A.M., Hocking, A.D., 1997. Advances in predictive modelling of fungal growth. Trends Food Sci. Technol. 8, 353–358. Gill, A.O., Delaquis, P., Russo, P., Holley, R.A., 2002. Evaluation of antilisterial action of cilantro oil on vacuum packed ham. Int. J. Food Microbiol. 73, 83–92. Gougouli, M., Koutsoumanis, K., 2012. Modelling germination of fungal spores at constant and fluctuating temperature conditions. Int. J. Food Microbiol. 152, 153–161. Guha, P., 2006. Betel leaf: the neglected green gold of India. J. Hum. Ecol. 19, 87–93. Guha, P., 2007. Extraction of essential oil: an appropriate rural technology for minimizing wastage of surplus betel leaves. Agric. Mechanization Asia Afr. Lat. Am. 38, 44–47. Gutierrez, J., Barry-Ryan, C., Bourke, P., 2008. The antimicrobial efficacy of plant essential oil combinations and interactions with food ingredients. Int. J. Food Microbiol. 124, 91–97. Gutierrez, J., Barry-Ryan, C., Bourke, P., 2009. Antimicrobial activity of plant essential oils using food model media: efficacy, synergistic potential and interactions with food components. Food Microbiol. 26, 142–150. Judet-Correia, D., Bollaert, S., Duquenne, A., Charpentier, C., Bensoussan, M., Dantigny, P., 2010. Validation of a predictive model for the growth of Botrytis cinerea and Penicillium expansum on grape berries. Int. J. Food Microbiol. 142, 106–113. Judet-Correia, D., Charpentier, C., Bensoussan, M., Dantigny, P., 2011. Modelling the inhibitory effect of copper sulfate on the growth of Penicillium expansum and Botrytis cinerea. Lett. Appl. Microbiol. 53, 558–564.

Kuorwel, K.K., Sonneveld, M.J., Miltz, J., Bigger, S.W., 2011. Essential oils and their principal constituents as antimicrobial agents for synthetic packaging films. J. Food Sci. 76, R164–R177. Liewen, M.B., Bullerman, L.B., 1992. Toxigenic fungi and fungal toxins. In: Vanderzant, C., Splittstoesser, D.F. (Eds.), Compendium of Methods for the Microbiological Examination of Foods. American Public Health Association, Washington, D.C., pp. 811–819. Lopez, P., Sanchez, C., Batlle, R., Nerin, C., 2005. Solid- and vapour-phase antimicrobial activities of six essential oils: susceptibility of selected foodborne bacterial and fungal strains. J. Agric. Food Chem. 53, 6939–6946. Manso, S., Pezo, D., Gómez-Lus, R., Nerin, C., 2014. Diminution of aflatoxin B1 production caused by an active packaging containing cinnamon essential oil. Food Control 45, 101–108. Montero-Prado, P., Rodriguez-Lafuente, A., Nerin, C., 2011. Active label-based packaging to extend the shelf-life of "calanda" peach fruit: changes in fruit quality and enzymatic activity. Postharvest Biol. Technol. 60, 211–219. Nazer, A.I., Kobilinsky, A., Tholozana, J.L., Dubois-Brissonneta, F., 2005. Combinations of food antimicrobials at low levels to inhibit the growth of Salmonella sv. Typhimurium: a synergistic effect. Food Microbiol. 22, 391–398. Neri, F., Mari, M., Brigati, S., 2006. Control of Penicillium expansum by plant volatile compounds. Plant Pathol. 55, 100–105. Prakash, B., Shukla, R., Singh, P., Kumar, A., Mishra, P.K., Dubey, N.K., 2010. Efficacy of chemically characterized Piper betle L. essential oil against fungal and aflatoxin contamination of some edible commodities and its antioxidant activity. Int. J. Food Microbiol. 142, 114–119. Ratkowsky, D.A., 2003. Model fitting and uncertainty. In: McKellar, R.C., Lu, X. (Eds.), Modelling Microbial Responses in Foods. CRC Press, Boca Raton, FL, USA, pp. 151–196. Rimando, A.M., Han, B.H., Park, J.H., Cantoria, M.C., 1986. Studies on the constituents of Philippine Piper betle leaves. Arch. Pharm. Res. 9, 93–97. Sharma, N., Tripathi, A., 2006. Fungitoxicity of the essential oil of Citrus sinensis on postharvest pathogens. World J. Microbiol. Biotechnol. 22, 587–593. Sivakumar, D., Bautista-Baños, S., 2014. A review on the use of essential oils for postharvest decay control and maintenance of fruit quality during storage. Crop. Prot. 64, 27–37. Soylu, E.M., Kurt, S., Soylu, S., 2010. In vitro and in vivo antifungal activities of the essential oils of various plants against tomato grey mould disease agent Botrytis cinerea. Int. J. Food Microbiol. 143, 183–189. Synowiec, A., Gniewosz, M., Kraśniewka, K., Przybył, J.L., Baczek, K., Węglarz, Z., 2014. Antimicrobial and antioxidant properties of pullulan film containing sweet basil extract and an evaluation of coating effectiveness in the prolongation of the shelf life of apples stored at refrigeration conditions. Innov. Food Sci. Emerg. Technol. 23, 171–181. Tawatsin, A., Asavadachanukorn, P., Thavara, U., 2006. Repellency of essential oils extracted from plants in Thailand against four mosquito vectors (diptera: culicidae) and oviposition deterrent effects against Aedes aegypti (diptera: culicidae). Southeast Asian J. Trop. Med. Public Health 37, 915–931. Tepe, B., Daferera, D., Sokmen, A., Sokmen, M., Polissiou, M., 2005. Antimicrobial and antioxidant activities of the essential oils and various extracts of Salvia tomentosa miller (lamiaceae). Food Chem. 90, 333–340. Tian, J., Huang, B., Luo, X., Zeng, H., Ban, X., He, J., Wang, Y., 2012. The control of Aspergillus flavus with Cinnamomum jensenianum hand.-mazz essential oil and its potential use as a food preservative. Food Chem. 130, 520–527. Tiwari, B.K., Valdramidis, V.P., O'Donnell, C.P., Muthukumarappan, K., Bourke, P., Cullen, P.J., 2009. Application of natural antimicrobials for food preservation. J. Agric. Food Chem. 57, 5987–6000. Tremarin, A., Longhi, D.A., Salomão, B.C.M., Aragão, G.M.F., 2014. Modeling the growth of Byssochlamys fulva and Nessential oilsartorya fischeri on solidified apple juice by measuring colony diameter and ergosterol content. Int. J. Food Microbiol. 193, 23–28. Tripathi, P., Dubey, N.K., Shukla, A.K., 2007. Use of some essential oils as post-harvest botanical fungicides in the management of grey mould of grapes caused by Botrytis cinerea. World J. Microbiol. Biotechnol. 24, 39–46. Tyagi, A.K., Malik, A., 2010. Antimicrobial action of essential oil vapours and negative air ions against Pseudomonas fluorescens. Int. J. Food Microbiol. 143, 205–210. Tyagi, A.K., Malik, A., Gottardi, D., Guerzoni, M.E., 2012. Essential oil vapour and negative air ions: a novel tool for food preservation. Trends Food Sci. Technol. 26, 99–113. Tzortzakis, N.G., Economakis, C.D., 2007. Antifungal activity of lemongrass (Cympopogon citratus L.) essential oil against key postharvest pathogens. Innov. Food Sci. Emerg. Technol. 8, 253–258. Welke, J.E., Hoeltz, M., Dottori, H.A., Noll, I.B., 2011. Patulin accumulation in apples during storage by Penicillium expansum and Penicillium griseofulvum strains. Braz. J. Microbiol. 42, 172–180.