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Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population
Accepted Manuscript Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population Suradeep Basak PII:
S0023-6438(18)30429-8
DOI:
10.1016/j.lwt.2018.05.015
Reference:
YFSTL 7125
To appear in:
LWT - Food Science and Technology
Received Date: 16 April 2018 Revised Date:
3 May 2018
Accepted Date: 4 May 2018
Please cite this article as: Basak, S., Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population, LWT - Food Science and Technology (2018), doi: 10.1016/j.lwt.2018.05.015. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population Author name
:
Author’s Affiliation address:
Suradeep Basak∗ Indian Institute of Technology Kharagpur
West Bengal
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India.
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Kharagpur - 721302
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Agricultural and Food Engineering Department,
∗
Corresponding author’s Telephone: e-mail address:
+91-9476481537 [email protected]
ACCEPTED MANUSCRIPT Abstract The objective of this study was to model the efficacy of betel leaf (Piper betle L.) essential oil (BLEO) on germination of Aspergillus flavus and Penicillium expansum spore population. Experimental data of rate of spore germination under the influence of the range (0.1 to 1.5
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µl/ml) of BLEO concentration were fitted to the asymmetric model, and the germination time parameter was estimated with satisfactory statistical indices (RMSE and R2). The secondary modelling of germination time as a function of BLEO using the reciprocal of re-
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parameterized Monod-type equation estimated minimum inhibitory concentration 0.65 and 0.54 µl/ml of BLEO for spore germination of A. flavus and P. expansum, respectively. The
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accuracy and bias factor of the fitted secondary model suggested good similarity between observed and estimated germination time values under the influence of BLEO for both selected moulds. It can be concluded that the asymmetric model and the re-parameterized Monod-type model could describe the inhibitory pattern of the essential oil against two
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selected predominant food spoilage moulds. The antifungal activity also suggests the potential of BLEO as natural antimicrobials.
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Keywords: Food spoilage moulds; Spore germination; Predictive microbiology; Modelling;
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1. Introduction The demand for minimally processed fresh food products poses major challenges for
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food safety and quality. About 25% of total annual production of various crops is affected by
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mycotoxins, especially those produced by Aspergillus, Penicillium and Fusarium species
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(FAO, 2004), resulting in annual losses of about 1 billion metric tons of food and feed
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products (Maestroni & Cannavan, 2011). The use of naturally occurring antimicrobials like
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EOs is getting prominence as food preservatives (Juneja, Dwivedi, & Yan, 2012). Essential
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oils (EOs) are secondary metabolites of plants, which reportedly possess antimicrobial
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activities (Bakkali, Averbeck, Averbeck, & Idaomar, 2008; Basak & Guha, 2017b). The
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leaves of betel vine (Piper betle L.) contain essential oil, which can be used as an
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antimicrobial agent in food (Basak, 2018). Basak & Guha (2015) have identified chavibetol,
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estragole, β-cubebene, chavicol, and caryophyllene as the major chemical compounds of betel
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leaf essential oil (BLEO) of the cultivar Tamluk Mitha.
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Spore germination is an essential developmental stage in life cycle of all filamentous
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fungi, and it is mandatory to restrict germination of spores to prevent fungal infection and
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mycotoxin production in food (D’Enfert, 1997). The dormancy of spore is controlled by the
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metabolic activities, low water content, nutrient penetration barriers, self-inhibitors and
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defective genes. Mould spore germination involves series of physiological reactions that
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involve activation of the resting spore in response to modifications of the environmental
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conditions followed by isotoropic growth that results in swelling of spores and the
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resumption of numerous metabolic activities, and finally polarized growth that results in the
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formation of a germ tube which will convert into an elongating and branching mycelium
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(Osherov & May, 2001).
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The product is considered to be spoilt, as soon as fungal hyphae become apparent and
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hence, germination is the primary step to be focused from food quality point of view
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ACCEPTED MANUSCRIPT (Gougouli & Koutsoumanis, 2010). If the length of germ tube is twice the diameter of spore
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then the spore is considered to have germinated (Dantigny et al., 2006). Time required for
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germination is usually very short and vary with moulds. However, in most cases the food
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products are contaminated with low initial level of fungal spores (Dantigny, Marín, Beyer, &
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Magan, 2007), and the probability of spoiling the food product depends on the ability of the
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contaminating spores to survive and germinate under real time situation as well as on their
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germination kinetics (Gougouli & Koutsoumanis, 2012). Therefore, development of models
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to predict spore germination and mould growth is of great importance (Dantigny, 2016).
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However, significant efforts were made to develop predictive models for mycelial radial
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growth of food spoilage fungi (Garcia, Ramos, Sanchis, & Marín, 2013; Dantigny, Burgain,
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Deniel, & Bensoussan, 2014; Burgain, Bensoussan, & Dantigny, 2015; Aldars-García,
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Sanchis, Ramos, & Marín, 2017) in contrast to the studies on germination kinetics of spores,
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which are limited (Kalai, Bensoussan, & Dantigny, 2014; Basak & Guha, 2015; Kalai,
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Anzala, Bensoussan, & Dantigny, 2017; Nguyen Van Long et al., 2017). The most frequently
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used primary models for germination are the Gompertz equation and Logistic function (Marín
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et al., 1996, 1998; Plaza, Usall, Teixidó, & Viñas, 2003; Pardo, Ramos, Sanchis, & Marín,
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2005; Pardo, Malet, Marín, Sanchis, & Ramos, 2006; Gougouli & Koutsoumanis, 2012), and
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the logistic function (Dantigny, Soares Mansur, Sautour, Tchobanov, & Bensoussan, 2002;
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Dantigny, Tchobanov, Bensoussan, & Zwietering, 2005; Dantigny et al., 2006). However,
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asymmetric model for predicting spore germination of moulds was suggested to be consistent
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with skewness in distributions of the individual germination time of spores (Dantigny,
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Nanguy, Judet-Correia, & Bensoussan, 2011). Primary models quantify the percentage of
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germination of spores in a given population with respect to time at steady-state conditions.
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Such models provide information about the variation in germination time of individual spores
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in terms of slope and inflection point of the slope. Germination of individual spores is
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affected by the existence of self inhibitors that prevent premature and rapid germination
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(Barrios-González, Martínez, Aguilera, & Raimbault, 1989) as well as by various abiotic
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factors. The effect of abiotic factors on germination time can be quantified by secondary
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models. Although, previous studies have suggested the significant influence of environmental
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conditions (such as temperature, water activity and pH) on germination time and on other
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kinetic parameters, only a few studies have attempted to express this influence with
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mathematical models (El Halouat & Debevere, 1997; Sautour, Rouget, Dantigny, Divies, &
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Bensoussan, 2001; Pardo et al., 2006; Schubert, Mourad, & Schwarze, 2010; Gougouli &
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Koutsoumanis, 2012; Dagnas, Gougouli, Onno, Koutsoumanis, & Membré, 2017). Most of
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the previous research studies have demonstrated the impact of essential oils (EOs) on
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germination of mould spores (Soylu, Kurt, & Soylu, 2010; Jing et al., 2014; Ribes et al.,
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2017), but investigation on modelling the inhibitory effect of EOs on mould spore
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germination is very scarce in present literature (Basak & Guha, 2015). This study was taken
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up to describe the germination of mould spores on PDA medium under the influence of
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BLEO using the asymmetric model.
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In view of above, the objective of present study were to: 1) study and model the
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germination process of Aspergillus flavus and Penicillium expansum spores under the
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influence of varying concentration of BLEO using the asymmetric model; 2) investigate the
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effect of BLEO on germination of the mould spores using a re-parameterized Monod type
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model; 3) validate the secondary model for its ability to predict the germination of the spores
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under the influence of BLEO.
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2. Materials and methods
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2.1.
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Fungal strains used
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Toxigenic filamentous fungal strain Aspergillus flavus (MTCC 6750) and Penicillium
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expansum (MTCC 4485) were obtained from Microbial Type Culture collection and Gene
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Bank (MTCC), India. These were maintained on potato dextrose agar (PDA) at 4 ºC and sub-
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cultured at regular interval.
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2.2.
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Spores from seven days old culture of A. flavus and P. expansum obtained on PDA at
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25 ºC were harvested with 10 ml of potato dextrose broth (PDB, HiMedia, India) by scraping
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the mycelial surface gently with L-shaped glass spreader. The spore suspension obtained was
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counted using a Neubauer’s Chamber (depth 0.1 mm, 0.0025 mm2) under biological light
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microscope and expressed as spores per millilitre. PDB was used to adjust the desired final
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spore concentration and was used on the same day of experiment.
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2.3.
Spore germination kinetics
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The modified method of Gougouli & Koutsoumanis (2012) was used to study
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germination of A. flavus and P. expansum spores. Briefly, 1 ml of PDB containing 5% (v/v)
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Tween-20 and BLEO were dissolved separately in petri plates (9×1.4 cm) containing 9 ml of
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warm sterilized PDA medium (aw 0.99, pH 5.6±0.2 at 25 0C) to produce concentration range
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of 0.1- 1.5 µl/ml through 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0 µl/ml of BLEO. 100 µl of
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spore suspension (108 spores/ml) was spread to obtain a layer of single spores over PDA
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medium added with different concentration of BLEO. The plates were sealed with parafilm
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and incubated at 25 ± 1 ºC. No hermetic sealing was done so as to simulate a real time
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situation.
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To study spore germination percentage at a regular time interval (hours), three pieces of
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agar slab (10×10 mm) from each Petri plates were aseptically cut using the scalpel and
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transferred to microscopic slides, stained with lactophenol cotton blue (HiMedia, India). A
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coverslip was placed on each agar slab and observed under 40x magnification of biological
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ACCEPTED MANUSCRIPT light microscope (Olympus CX31, Tokyo, Japan). Total of 600 spores (200 spores per agar
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slab and 30-35 spores per microscopic field) were counted for an individual concentration of
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BLEO at regular time interval. Spores were considered germinated only when the length of
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germ tube was equal or exceeded spore diameter. For each treatment the germination
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percentage was calculated according to Eq. 1, and the data were fitted to the asymmetric
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model.:
× 100
(1)
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% =
Where Ngerminated spores is the number of spores germinated among the total number of
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spores (Ntotal spores) counted.
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2.4. Modelling mould germination
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2.4.1. Data treatment
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Prior to fit the primary model, the raw germination data were analysed for the
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homogeneity of variance. Accordingly, the correlation coefficient (r) was determined by
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performing linear regression between variance data, Variance [P] against the Mean [P]
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(Zwietering, Cuppers, de Witt, & van’t Riet, 1994). The student t-test was performed to
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examine any significant correlation.
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If the absolute value of tstud was found to be less than tabulated T value (Ttable) then the
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correlation was inferred to be not significant.
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2.4.2. Primary modelling
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The asymmetric model:
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=
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! # "
%
(2)
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Where P (%) is the percentage of germinated spores, Pmax (%) was the asymptotic P value at
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t→ +∞ (infinity), d is the design parameter, τ (h) is the time point where P = ½ Pmax.
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2.4.3. Secondary modelling 7
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According to section 2.4.1., the estimated germination time under different BLEO
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concentrations of the primary model was analysed for the homogeneity of variance. The
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germination time parameters were square-root transformed to homogenize the variance
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(Dantigny & Bensoussan, 2008). Estimated germination time (τ) data were transformed and fitted to the re-parameterized
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Monod-type equation (Judet-Correia, Charpentier, Bensoussan, & Dantigny, 2011) for
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secondary modelling of τ as function of BLEO (E) according to the following Eq. 3: *. ,-. /0*.1 1. ,-. * ,-./1
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τ = !τ'()
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(3)
where, τopt (h) is the germination time at E=0 µl/ml; k (µl/ml) is the BLEO concentration at
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which τ = 2τopt and MIC is minimum inhibitory concentration of BLEO at which germination
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time is infinite.
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2.4.4. Performance evaluation of the predictive models
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The performances of the re-parameterized Monod-type equation used for modelling the
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effect of BLEO on germination of A. flavus and P. expansum spores on PDA medium were
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assessed by accuracy factor (Af) and bias factor (Bf) according to Ross (1996).
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23 = 10 ∑56'7 89:;$<=>;$ ⁄8?@A;:B;$
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E3 = 10
5⁄D
∑6'7 89:;$<=>;$ ⁄8?@A;:B;$ ⁄D
(4) (5)
τpredicted is the germination time calculated based on estimated parameters of Eq. 3 and the
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respective BLEO concentration; τobserved is the germination time estimated using the Eq. 3.
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2.5. Statistical analysis
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ANOVA was performed, and means were sorted using Tukey’s test for all the data. The
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model parameters were estimated by the Levenberg-Marquardt algorithm for nonlinear least
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square minimization using GraphPad Prism version 5.0 for Windows (GraphPad Software,
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San Diego, CA, USA). The performance of models was assessed using root mean square
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ACCEPTED MANUSCRIPT error (RMSE) and coefficient of determination (R2). Models that are having RMSE values
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close to zero and R2 values close to one were considered as a good fit (Ratkowsky, 2003). All
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experiments were conducted in triplicates and repeated thrice to establish repeatability.
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Values presented here represents mean of these replicates with standard deviation or standard
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error.
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3. Results and discussion
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3.1.
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3.1.1. Homogeneity of variance for primary modelling
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Modelling of mould germination
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Homogeneity of variance for each raw germination data sets was analysed. The
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variance data are shown in Fig. 1. In four instances, the variance was found to be more than
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or equal to 100. The highest variance was obtained at different mean [P] values depending on
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concentration of BLEO (i.e. 40.5% germination for untreated A. flavus, and 28.3% and 85.3%
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germination for untreated P. expansum, 30% germination for 0.2 µl/ml BLEO treated P.
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expansum). As suggested by Zwietering et al. (1994), the linear correlation between mean
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and variance was found to be insignificant (at P= 0.05) for all data sets under varying
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concentration of BLEO for both A. flavus and P. expansum. Therefore, data were not
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transformed prior to fit in the primary model.
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3.1.2. Primary modelling
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All spores were germinated at BLEO concentrations less than 0.5 and 0.4 µl/ml for A.
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flavus and P. expansum, respectively. The germinating curve shown in Fig. 2, suggested the
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ability of the model to describe the mould spore germination under the influence of BLEO
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with satisfactory statistical indices (R2 and RMSE). Time required to achieve 50%
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germination (τ) was estimated to have increased with increasing concentration of BLEO
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(Table 1). All spores of both selected moulds were able to germinate at every concentration
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of BLEO. However, the asymptotic estimated values, Pmax were significantly different from
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ACCEPTED MANUSCRIPT 100% for A. flavus spores. Similar overestimation of Pmax values was observed by Dantigny et
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al. (2011) for the asymmetric model for germination data of P. chrysogenum exposed to
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ethanol vapours. This overestimation could possibly be due to the sampled experimental data,
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and this could be corrected by setting the maximum percentage germination to 100% (Marín
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et al., 1996). In case of P. expansum, confidence interval was not wide, and overestimation
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was also not observed for Pmax values.
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The higher value (2 ≤ d < 37) of the design parameter suggested the presence of
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swelling period of the mould spores before forming germination tube and eventually
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germinated spores (Dantigny et al., 2011). Except A. flavus spores under no BLEO, the
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remaining value of d was shown to have increased with increase in concentration of the
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essential oil. However, the mean d value of A. flavus spores under no BLEO was significantly
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similar to 0.2 µl/ml of BLEO. Also, the mean d value of 0.1 µl/ml of BLEO lies within the
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confidence interval for both no BLEO and 0.2 µl/ml of BLEO. As suggested by Dantigny et
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al. (2011) the value of design parameter is depended on the experimental conditions and
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microorganisms. The germination time (τ) represents the time required to achieve 50% of the
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viable spores germinated, and increase in τ (h) value with increase in concentration of BLEO
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suggest the inefficiency of viable spores to germinate under such extreme conditions. The P
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(τ) value showed the percentage of germination when all spores were viable and was at least
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50% at the inflection point for the asymmetric model (Table 1). P (τ) validates the reliability
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of the model parameter τ (h). It can be hypothesised that fungitoxicity of BLEO increased
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with increasing concentration, which made it difficult for single spores to detoxify essential
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oil present on their surface. Hence, the germination process gets delayed or inhibited at a
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given concentration. Efficacy of BLEO against spore germination was found to be promising
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as compared to earlier studies on the inhibitory effect of essential oil from different plant
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sources on spore germination (Tao, Jia, & Zhou, 2014; He et al., 2016). No spore germination
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was observed at and beyond 0.6 µl/ml and 0.5 µl/ml of BLEO for A. flavus and P. expansum,
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respectively after 4 weeks of incubation.
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3.1.3. Data transformation The estimated germination time (τ) data were analysed for homogeneity of variance.
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The variance [P] and mean [P] of untransformed data were found to be positively correlated
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for both moulds, and the tstud values were reportedly higher than ttable value in case of A. flavus
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(Table 2). While, transformation of the τ (h) data led to stabilized variance with lower tstud
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values (< ttable) for A. flavus, the transformation of P. expansum germination time data
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resulted in negative correlation between variance [P] and mean [P]. The square-root
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transformation of the data for both mould showed reduced tstud value than logarithmic
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transformation. Therefore, the estimated germination time (τ) data was square-root
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transformed prior to fit the secondary model.
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3.1.4. Secondary modelling
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The germination time (τ) was modelled as a function of BLEO concentration. The
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estimated parameters (Table 3) are having narrow confidence interval for both the selected
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moulds. The value of τopt for A. flavus and P. expansum were not significantly different (P=
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0.082 and P = 0.210) with the value obtained under optimal condition (E0 = no BLEO),
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respectively. A four-fold increase in the germination time was observed with increase in
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BLEO concentration from E0 to k (i.e. ,-. = 74% and 63% of the BLEO range) for A. flavus
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and P. expansum, respectively. However, the effect of BLEO was strong (i.e. increase in
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more than two-fold increase) from k to MIC (26% and 37% of BLEO range) in case of A.
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flavus and P. expansum, respectively. An increase in germination time (τ) occurred at 0.4 to
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0.5 µl/ml, and 0.3 to 0.4 µl/ml of BLEO in case of A. flavus and P. expansum, respectively
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(Fig. 3). Also, lower MIC value of BLEO for P. expansum suggests its higher susceptibility
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to BLEO as compared to A. flavus, which was shown to have higher estimated MIC as well
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as k value (Table 3). The MIC of BLEO for A. flavus and P. expansum based on modelling apparent lag time
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as a function of BLEO on PDA medium was estimated to be 0.75 ± 0.03 µl/ml (Basak &
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Guha, 2017a) and 0.74 ± 0.06 µl/ml (Basak & Guha, 2015) in previous studies. However, in
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the present study, MIC was estimated to be 0.65 ± 0.01 and 0.54 ± 0.01 µl/ml of BLEO for A.
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flavus and P. expansum, respectively. The disparity in MIC values can be attributed to the
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fact that this study was based on germination of single spores in a population under varying
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concentration of BLEO, whereas previous studies were based on apparent lag time of point
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inoculum (10 µl) of spores (<106 spores/ml) as a function of BLEO. As discussed by Basak
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(2017), single spores have more surface area exposed to the BLEO present in the PDA
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medium. Hence, the probability is less for single spore to detoxify BLEO and germinate
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under similar condition as compared to point inoculum.
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3.1.5. Performance evaluation of the predictive models
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The Bf and Af are the tools for evaluating the performance of predictive models (Ross,
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1996). The bias and accuracy factors of the secondary model for germination time of A.
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flavus and P. expansum in the PDA medium are reported in Table 4. According to Ross
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(1999), bias factor (0.9
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Tienungoon, 2000) are within the permissible limits for both the selected moulds. Therefore,
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the model can be suggested to be in good performance. The plot between observed and
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predicted values of the selected moulds (Fig. 4) indicated that average predicted and observed
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values of germination time under varying BLEO concentration differ by 4.4% and 1.6% for
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A. flavus and P. expansum, respectively. This suggest the palusibility of the secondary model
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at predicting germination time of A. flavus and P. expansum under the influence of BLEO.
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4. Conclusion
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ACCEPTED MANUSCRIPT The mould spore germination under the influence of BLEO can be described by the
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asymmetric model. Square-root transformation of germination time data provided more
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stabilization and homogeneity to the variance. The efficacy of BLEO on germination time
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parameter could estimate the MIC values using the re-parameterized Monod type model.
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Satisfactory statistical indices (R2 and RMSE) alongside narrow 95% confidence interval of
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estimated MIC of BLEO suggested the reliability of the estimated parameter. The accuracy of
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the secondary model based on Af and Bf further cemented the faith in the goodness of the
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estimated parameters. This study provided an insight of germination of single spore in a
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population under the influence of essential oil of betel leaf using available predictive
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mycological tools. Further study on potential of individual mould spores to germinate under
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dynamic temperature conditions is warranted.
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Acknowledgements
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The author is grateful to Indian Institute of Technology Kharagpur for financial
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assistance, infrastructure and facilities to conduct the research. The author is thankful to Prof.
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P. Guha, Prof. S. L. Shrivastava, Prof. P. B. S. Bhadoria, Dr. Jayeeta Mitra, and Ms. Ruby
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Pandey of Agricultural and Food Engineering Department for their support.
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verrucosum isolates on barley meal extract agar. International Journal of Food
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Pardo, E., Ramos, A. J., Sanchis, V., & Marín, S. (2005). Modelling of effects of water
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activity and temperature on germination and growth of ochratoxigenic isolates of
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Aspergillus ochraceus on a green coffee-based medium. International Journal of Food
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Microbiology, 98(1), 1–9. Plaza, P., Usall, J., Teixidó, N., & Viñas, I. (2003). Effect of water activity and temperature
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candidum. Journal of Applied Microbiology, 94(4), 549–554.
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(Ed.), Modelling Microbial Responses in Foods (pp. 151-196). Boca Raton: CRC Press.
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Ribes, S., Fuentes, A., Talens, P., Barat, J. M., Ferrari, G., & Donsì, F. (2017). Influence of
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emulsifier type on the antifungal activity of cinnamon leaf, lemon and bergamot oil
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nanoemulsions against Aspergillus niger. Food Control, 73, 784–795.
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Sautour, M., Rouget, A, Dantigny, P., Divies, C., & Bensoussan, M. (2001). Prediction of
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conidial germination of Penicillium chrysogenum as influenced by temperature, water
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activity and pH. Letters in Applied Microbiology, 32(3), 131–4.
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Schubert, M., Mourad, S., & Schwarze, F. W. M. R. (2010). Statistical approach to determine
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the effect of combined environmental parameters on conidial development of
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Trichoderma atroviride (T-15603.1). Journal of Basic Microbiology, 50(6), 570–580.
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Soylu, E. M., Kurt, S., & Soylu, S. (2010). In vitro and in vivo antifungal activities of the
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essential oils of various plants against tomato grey mould disease agent Botrytis
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cinerea. International Journal of Food Microbiology, 143(3), 183–9. Tao, N., Jia, L., & Zhou, H. (2014). Anti-fungal activity of Citrus reticulata Blanco essential
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oil against Penicillium italicum and Penicillium digitatum. Food Chemistry, 153, 265–
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271.
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Zwietering, M. H., Cuppers, H. G. A. M., de Witt, J. C., & van’t Riet, K. (1994). Evaluation
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of data transformations and validation of a model for the effect of temperature on
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bacterial growth. Applied and Environmental Microbiology, 60(1), 195–203.
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ACCEPTED MANUSCRIPT Figure captions
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Figure 1: Variance of P, plotted against the mean of P for A. flavus under the influence of
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varying concentration of BLEO: (●) no BLEO; (■) 0.1 µl/ml; (▲) 0.2 µl/ml; (▼) 0.3 µl/ml;
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(♦) 0.4 µl/ml; (×) 0.5 µl/ml, and for P. expansum under the influence of varying concentration
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of BLEO: ( ) no BLEO; (∆) 0.1 µl/ml; ( ) 0.2 µl/ml; ( ) 0.3 µl/ml; ( ) 0.4 µl/ml.
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Figure 2: Parameter estimates and 95% confidence interval of the asymmetric model for the
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in vitro spore germination data of (a) A. flavus, and (b) P. expansum under varying
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concentration of BLEO. Each point represents germination percentage of 600 spores and ()
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indicates fitted asymmetric model. The conditions of no germination (i.e. BLEO
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concentration at and beyond 0.6 and 0.5 µl/ml for (a) and (b), respectively) are not shown in
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the plot.
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Figure 3: Effect of germination time versus BLEO concentration fitted by a re-parameterized
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Monod type model on (▲) A. flavus, and ( ) P. expansum spores.
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Figure 4: Performance evaluation of a re-parameterized Monod type model for the effect of
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BLEO on germination time (τ) of (▲) A. flavus, and ( ) P. expansum spores
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ACCEPTED MANUSCRIPT Table 1 Estimated parameters (with 95% confidence interval) of the asymmetric model fitted to obtained germination percentage of A. flavus and P. expansum spores under the influence of BLEO BLEO (µl/ml)
d (-)
τ (h)
R2
RMSE
P (τ) %
10.6de (8.1, 13.1)
13.8i (13.3, 14.3)
0.976
6.5
58.5
Pmax (%)
Parameter estimates for A. flavus 0.0
117ab (102, 132) ab
e
h
117.5 (106.3, 128.7)
7.9 (6.7, 9.1)
15.5 (15.0, 16.0)
0.986
4.7
58.8
0.2
138.6a (116.1, 161.2)
9.6de (8.0, 11.2)
18.6g (17.9, 19.4)
0.986
4.3
69.3
0.3
111.8b (105.8, 117.8)
14.6cd (13.1, 16.1)
23.9e (23.6, 24.1)
0.993
3.1
55.9
0.4
117.9ab (111, 124.8)
18.3c (16.7, 19.9)
32.5d (32.2, 32.7)
0.993
2.6
59.0
0.5
121.8ab (115.2, 128.3)
29.0b (26.5, 31.5)
62.8b (62.5, 63.1)
0.994
2.4
60.9
0.6
No germination
10.8de (9.1, 12.5)
12.4j (12.2, 12.5)
0.981
5.5
50.9
0.0
b
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101.8b (99.3, 104.2)
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Parameter estimates for P. expansum
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0.1
cd
g
0.1
101.4 (100.0, 102.7)
13.8 (12.8, 14.9)
17.8 (17.6, 17.9)
0.995
3.1
50.7
0.2
100.5b (99.2, 101.8)
17.1c (15.7, 18.42)
22.4f (22.3, 22.5)
0.995
3.4
50.3
0.3
101.9b (99.7, 104.1)
25.7b (23.7, 27.7)
39.4c (39.3, 39.6)
0.993
3.2
51.0
0.4
103.5b (101.1, 105.9)
36.6a (33.0, 40.2)
94.1a (93.8, 94.4)
0.987
3.8
51.8
0.5
No germination
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The values followed by same letter in same column are not significantly different according to ANOVA and
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Tukey’s multiple comparison tests
ACCEPTED MANUSCRIPT Table 2 Results of determination of correlation coefficient (r) by performing linear regression of the variance data as a function of mean of the germination time data over the range of BLEO Moulds
No transformation
Square-root transformation
Logarithmic transformation
tstud value
r (P-value)
tstud value
r (P-value)
tstud value
A. flavus
0.70 (0.121)
3.097
0.009 (0.986)
0.029
−0.15 (0.779)
0. 474
P. expansum
0.57 (0.311)
1.987
−0.43 (0.469)
1.349
−0.62 (0.269)
2.212
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r (P-value)
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The 95% critical Student’s t tabulated value (ttable) for 12 degree of freedom is 2.228 (A. flavus) and for 10 degree of freedom is 2.306 (P. expansum). Bold values indicates significant correlation
ACCEPTED MANUSCRIPT Table 3 Parameter estimates and 95% confidence interval of a re-parameterized Monod type model fitted to germination time (τ) of the selected moulds on PDA medium under the influence of BLEO Estimated parameters Moulds
k (µl/ml)
MIC (µl/ml)
R2
RMSE
A. flavus
3.73 (3.68, 3.78)
0.49 (0.48, 0.50)
0.65 (0.64, 0.67)
0.999
0.06
P. expansum
3.57 (3.47, 3.68)
0.34 (0.33, 0.35)
0.54 (0.52, 0.56)
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τopt (h)
0.998
0.10
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Moulds
Bf
A. flavus
1.01
0.99
P. expansum
1.02
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Af
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1.00
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ACCEPTED MANUSCRIPT Highlights Asymmetric model estimated spore germination time under the influence of BLEO Variance of estimated germination time was stabilized by square-root transformation Af and Bf showed the plausibility of the secondary model in estimating MIC of BLEO
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Predictive mycological tools can describe spore germination under influence of EOs
S0023-6438(18)30429-8
DOI:
10.1016/j.lwt.2018.05.015
Reference:
YFSTL 7125
To appear in:
LWT - Food Science and Technology
Received Date: 16 April 2018 Revised Date:
3 May 2018
Accepted Date: 4 May 2018
Please cite this article as: Basak, S., Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population, LWT - Food Science and Technology (2018), doi: 10.1016/j.lwt.2018.05.015. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Modelling the effect of betel leaf essential oil on germination time of Aspergillus flavus and Penicillium expansum spore population Author name
:
Author’s Affiliation address:
Suradeep Basak∗ Indian Institute of Technology Kharagpur
West Bengal
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India.
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Kharagpur - 721302
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Agricultural and Food Engineering Department,
∗
Corresponding author’s Telephone: e-mail address:
+91-9476481537 [email protected]
ACCEPTED MANUSCRIPT Abstract The objective of this study was to model the efficacy of betel leaf (Piper betle L.) essential oil (BLEO) on germination of Aspergillus flavus and Penicillium expansum spore population. Experimental data of rate of spore germination under the influence of the range (0.1 to 1.5
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µl/ml) of BLEO concentration were fitted to the asymmetric model, and the germination time parameter was estimated with satisfactory statistical indices (RMSE and R2). The secondary modelling of germination time as a function of BLEO using the reciprocal of re-
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parameterized Monod-type equation estimated minimum inhibitory concentration 0.65 and 0.54 µl/ml of BLEO for spore germination of A. flavus and P. expansum, respectively. The
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accuracy and bias factor of the fitted secondary model suggested good similarity between observed and estimated germination time values under the influence of BLEO for both selected moulds. It can be concluded that the asymmetric model and the re-parameterized Monod-type model could describe the inhibitory pattern of the essential oil against two
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selected predominant food spoilage moulds. The antifungal activity also suggests the potential of BLEO as natural antimicrobials.
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Essential oil
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Keywords: Food spoilage moulds; Spore germination; Predictive microbiology; Modelling;
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1. Introduction The demand for minimally processed fresh food products poses major challenges for
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food safety and quality. About 25% of total annual production of various crops is affected by
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mycotoxins, especially those produced by Aspergillus, Penicillium and Fusarium species
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(FAO, 2004), resulting in annual losses of about 1 billion metric tons of food and feed
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products (Maestroni & Cannavan, 2011). The use of naturally occurring antimicrobials like
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EOs is getting prominence as food preservatives (Juneja, Dwivedi, & Yan, 2012). Essential
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oils (EOs) are secondary metabolites of plants, which reportedly possess antimicrobial
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activities (Bakkali, Averbeck, Averbeck, & Idaomar, 2008; Basak & Guha, 2017b). The
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leaves of betel vine (Piper betle L.) contain essential oil, which can be used as an
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antimicrobial agent in food (Basak, 2018). Basak & Guha (2015) have identified chavibetol,
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estragole, β-cubebene, chavicol, and caryophyllene as the major chemical compounds of betel
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leaf essential oil (BLEO) of the cultivar Tamluk Mitha.
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Spore germination is an essential developmental stage in life cycle of all filamentous
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fungi, and it is mandatory to restrict germination of spores to prevent fungal infection and
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mycotoxin production in food (D’Enfert, 1997). The dormancy of spore is controlled by the
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metabolic activities, low water content, nutrient penetration barriers, self-inhibitors and
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defective genes. Mould spore germination involves series of physiological reactions that
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involve activation of the resting spore in response to modifications of the environmental
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conditions followed by isotoropic growth that results in swelling of spores and the
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resumption of numerous metabolic activities, and finally polarized growth that results in the
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formation of a germ tube which will convert into an elongating and branching mycelium
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(Osherov & May, 2001).
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The product is considered to be spoilt, as soon as fungal hyphae become apparent and
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hence, germination is the primary step to be focused from food quality point of view
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ACCEPTED MANUSCRIPT (Gougouli & Koutsoumanis, 2010). If the length of germ tube is twice the diameter of spore
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then the spore is considered to have germinated (Dantigny et al., 2006). Time required for
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germination is usually very short and vary with moulds. However, in most cases the food
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products are contaminated with low initial level of fungal spores (Dantigny, Marín, Beyer, &
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Magan, 2007), and the probability of spoiling the food product depends on the ability of the
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contaminating spores to survive and germinate under real time situation as well as on their
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germination kinetics (Gougouli & Koutsoumanis, 2012). Therefore, development of models
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to predict spore germination and mould growth is of great importance (Dantigny, 2016).
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However, significant efforts were made to develop predictive models for mycelial radial
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growth of food spoilage fungi (Garcia, Ramos, Sanchis, & Marín, 2013; Dantigny, Burgain,
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Deniel, & Bensoussan, 2014; Burgain, Bensoussan, & Dantigny, 2015; Aldars-García,
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Sanchis, Ramos, & Marín, 2017) in contrast to the studies on germination kinetics of spores,
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which are limited (Kalai, Bensoussan, & Dantigny, 2014; Basak & Guha, 2015; Kalai,
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Anzala, Bensoussan, & Dantigny, 2017; Nguyen Van Long et al., 2017). The most frequently
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used primary models for germination are the Gompertz equation and Logistic function (Marín
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et al., 1996, 1998; Plaza, Usall, Teixidó, & Viñas, 2003; Pardo, Ramos, Sanchis, & Marín,
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2005; Pardo, Malet, Marín, Sanchis, & Ramos, 2006; Gougouli & Koutsoumanis, 2012), and
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the logistic function (Dantigny, Soares Mansur, Sautour, Tchobanov, & Bensoussan, 2002;
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Dantigny, Tchobanov, Bensoussan, & Zwietering, 2005; Dantigny et al., 2006). However,
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asymmetric model for predicting spore germination of moulds was suggested to be consistent
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with skewness in distributions of the individual germination time of spores (Dantigny,
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Nanguy, Judet-Correia, & Bensoussan, 2011). Primary models quantify the percentage of
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germination of spores in a given population with respect to time at steady-state conditions.
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Such models provide information about the variation in germination time of individual spores
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in terms of slope and inflection point of the slope. Germination of individual spores is
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affected by the existence of self inhibitors that prevent premature and rapid germination
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(Barrios-González, Martínez, Aguilera, & Raimbault, 1989) as well as by various abiotic
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factors. The effect of abiotic factors on germination time can be quantified by secondary
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models. Although, previous studies have suggested the significant influence of environmental
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conditions (such as temperature, water activity and pH) on germination time and on other
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kinetic parameters, only a few studies have attempted to express this influence with
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mathematical models (El Halouat & Debevere, 1997; Sautour, Rouget, Dantigny, Divies, &
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Bensoussan, 2001; Pardo et al., 2006; Schubert, Mourad, & Schwarze, 2010; Gougouli &
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Koutsoumanis, 2012; Dagnas, Gougouli, Onno, Koutsoumanis, & Membré, 2017). Most of
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the previous research studies have demonstrated the impact of essential oils (EOs) on
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germination of mould spores (Soylu, Kurt, & Soylu, 2010; Jing et al., 2014; Ribes et al.,
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2017), but investigation on modelling the inhibitory effect of EOs on mould spore
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germination is very scarce in present literature (Basak & Guha, 2015). This study was taken
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up to describe the germination of mould spores on PDA medium under the influence of
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BLEO using the asymmetric model.
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In view of above, the objective of present study were to: 1) study and model the
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germination process of Aspergillus flavus and Penicillium expansum spores under the
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influence of varying concentration of BLEO using the asymmetric model; 2) investigate the
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effect of BLEO on germination of the mould spores using a re-parameterized Monod type
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model; 3) validate the secondary model for its ability to predict the germination of the spores
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under the influence of BLEO.
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2. Materials and methods
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2.1.
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Fungal strains used
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Toxigenic filamentous fungal strain Aspergillus flavus (MTCC 6750) and Penicillium
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expansum (MTCC 4485) were obtained from Microbial Type Culture collection and Gene
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Bank (MTCC), India. These were maintained on potato dextrose agar (PDA) at 4 ºC and sub-
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cultured at regular interval.
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2.2.
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Spore suspension
Spores from seven days old culture of A. flavus and P. expansum obtained on PDA at
81
25 ºC were harvested with 10 ml of potato dextrose broth (PDB, HiMedia, India) by scraping
82
the mycelial surface gently with L-shaped glass spreader. The spore suspension obtained was
83
counted using a Neubauer’s Chamber (depth 0.1 mm, 0.0025 mm2) under biological light
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microscope and expressed as spores per millilitre. PDB was used to adjust the desired final
85
spore concentration and was used on the same day of experiment.
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2.3.
Spore germination kinetics
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The modified method of Gougouli & Koutsoumanis (2012) was used to study
88
germination of A. flavus and P. expansum spores. Briefly, 1 ml of PDB containing 5% (v/v)
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Tween-20 and BLEO were dissolved separately in petri plates (9×1.4 cm) containing 9 ml of
90
warm sterilized PDA medium (aw 0.99, pH 5.6±0.2 at 25 0C) to produce concentration range
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of 0.1- 1.5 µl/ml through 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0 µl/ml of BLEO. 100 µl of
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spore suspension (108 spores/ml) was spread to obtain a layer of single spores over PDA
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medium added with different concentration of BLEO. The plates were sealed with parafilm
94
and incubated at 25 ± 1 ºC. No hermetic sealing was done so as to simulate a real time
95
situation.
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To study spore germination percentage at a regular time interval (hours), three pieces of
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agar slab (10×10 mm) from each Petri plates were aseptically cut using the scalpel and
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transferred to microscopic slides, stained with lactophenol cotton blue (HiMedia, India). A
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coverslip was placed on each agar slab and observed under 40x magnification of biological
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ACCEPTED MANUSCRIPT light microscope (Olympus CX31, Tokyo, Japan). Total of 600 spores (200 spores per agar
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slab and 30-35 spores per microscopic field) were counted for an individual concentration of
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BLEO at regular time interval. Spores were considered germinated only when the length of
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germ tube was equal or exceeded spore diameter. For each treatment the germination
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percentage was calculated according to Eq. 1, and the data were fitted to the asymmetric
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model.:
× 100
(1)
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% =
Where Ngerminated spores is the number of spores germinated among the total number of
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spores (Ntotal spores) counted.
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2.4. Modelling mould germination
110
2.4.1. Data treatment
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Prior to fit the primary model, the raw germination data were analysed for the
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homogeneity of variance. Accordingly, the correlation coefficient (r) was determined by
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performing linear regression between variance data, Variance [P] against the Mean [P]
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(Zwietering, Cuppers, de Witt, & van’t Riet, 1994). The student t-test was performed to
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examine any significant correlation.
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If the absolute value of tstud was found to be less than tabulated T value (Ttable) then the
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correlation was inferred to be not significant.
118
2.4.2. Primary modelling
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The asymmetric model:
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=
1−
$
! # "
%
(2)
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Where P (%) is the percentage of germinated spores, Pmax (%) was the asymptotic P value at
122
t→ +∞ (infinity), d is the design parameter, τ (h) is the time point where P = ½ Pmax.
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2.4.3. Secondary modelling 7
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According to section 2.4.1., the estimated germination time under different BLEO
125
concentrations of the primary model was analysed for the homogeneity of variance. The
126
germination time parameters were square-root transformed to homogenize the variance
127
(Dantigny & Bensoussan, 2008). Estimated germination time (τ) data were transformed and fitted to the re-parameterized
129
Monod-type equation (Judet-Correia, Charpentier, Bensoussan, & Dantigny, 2011) for
130
secondary modelling of τ as function of BLEO (E) according to the following Eq. 3: *. ,-. /0*.1 1. ,-. * ,-./1
#
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τ = !τ'()
131
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(3)
where, τopt (h) is the germination time at E=0 µl/ml; k (µl/ml) is the BLEO concentration at
133
which τ = 2τopt and MIC is minimum inhibitory concentration of BLEO at which germination
134
time is infinite.
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2.4.4. Performance evaluation of the predictive models
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The performances of the re-parameterized Monod-type equation used for modelling the
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effect of BLEO on germination of A. flavus and P. expansum spores on PDA medium were
138
assessed by accuracy factor (Af) and bias factor (Bf) according to Ross (1996).
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23 = 10 ∑56'7 89:;$<=>;$ ⁄8?@A;:B;$
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E3 = 10
5⁄D
∑6'7 89:;$<=>;$ ⁄8?@A;:B;$ ⁄D
(4) (5)
τpredicted is the germination time calculated based on estimated parameters of Eq. 3 and the
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respective BLEO concentration; τobserved is the germination time estimated using the Eq. 3.
143
2.5. Statistical analysis
144
ANOVA was performed, and means were sorted using Tukey’s test for all the data. The
145
model parameters were estimated by the Levenberg-Marquardt algorithm for nonlinear least
146
square minimization using GraphPad Prism version 5.0 for Windows (GraphPad Software,
147
San Diego, CA, USA). The performance of models was assessed using root mean square
8
ACCEPTED MANUSCRIPT error (RMSE) and coefficient of determination (R2). Models that are having RMSE values
149
close to zero and R2 values close to one were considered as a good fit (Ratkowsky, 2003). All
150
experiments were conducted in triplicates and repeated thrice to establish repeatability.
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Values presented here represents mean of these replicates with standard deviation or standard
152
error.
153
3. Results and discussion
154
3.1.
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3.1.1. Homogeneity of variance for primary modelling
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Homogeneity of variance for each raw germination data sets was analysed. The
157
variance data are shown in Fig. 1. In four instances, the variance was found to be more than
158
or equal to 100. The highest variance was obtained at different mean [P] values depending on
159
concentration of BLEO (i.e. 40.5% germination for untreated A. flavus, and 28.3% and 85.3%
160
germination for untreated P. expansum, 30% germination for 0.2 µl/ml BLEO treated P.
161
expansum). As suggested by Zwietering et al. (1994), the linear correlation between mean
162
and variance was found to be insignificant (at P= 0.05) for all data sets under varying
163
concentration of BLEO for both A. flavus and P. expansum. Therefore, data were not
164
transformed prior to fit in the primary model.
165
3.1.2. Primary modelling
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All spores were germinated at BLEO concentrations less than 0.5 and 0.4 µl/ml for A.
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flavus and P. expansum, respectively. The germinating curve shown in Fig. 2, suggested the
168
ability of the model to describe the mould spore germination under the influence of BLEO
169
with satisfactory statistical indices (R2 and RMSE). Time required to achieve 50%
170
germination (τ) was estimated to have increased with increasing concentration of BLEO
171
(Table 1). All spores of both selected moulds were able to germinate at every concentration
172
of BLEO. However, the asymptotic estimated values, Pmax were significantly different from
9
ACCEPTED MANUSCRIPT 100% for A. flavus spores. Similar overestimation of Pmax values was observed by Dantigny et
174
al. (2011) for the asymmetric model for germination data of P. chrysogenum exposed to
175
ethanol vapours. This overestimation could possibly be due to the sampled experimental data,
176
and this could be corrected by setting the maximum percentage germination to 100% (Marín
177
et al., 1996). In case of P. expansum, confidence interval was not wide, and overestimation
178
was also not observed for Pmax values.
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The higher value (2 ≤ d < 37) of the design parameter suggested the presence of
180
swelling period of the mould spores before forming germination tube and eventually
181
germinated spores (Dantigny et al., 2011). Except A. flavus spores under no BLEO, the
182
remaining value of d was shown to have increased with increase in concentration of the
183
essential oil. However, the mean d value of A. flavus spores under no BLEO was significantly
184
similar to 0.2 µl/ml of BLEO. Also, the mean d value of 0.1 µl/ml of BLEO lies within the
185
confidence interval for both no BLEO and 0.2 µl/ml of BLEO. As suggested by Dantigny et
186
al. (2011) the value of design parameter is depended on the experimental conditions and
187
microorganisms. The germination time (τ) represents the time required to achieve 50% of the
188
viable spores germinated, and increase in τ (h) value with increase in concentration of BLEO
189
suggest the inefficiency of viable spores to germinate under such extreme conditions. The P
190
(τ) value showed the percentage of germination when all spores were viable and was at least
191
50% at the inflection point for the asymmetric model (Table 1). P (τ) validates the reliability
192
of the model parameter τ (h). It can be hypothesised that fungitoxicity of BLEO increased
193
with increasing concentration, which made it difficult for single spores to detoxify essential
194
oil present on their surface. Hence, the germination process gets delayed or inhibited at a
195
given concentration. Efficacy of BLEO against spore germination was found to be promising
196
as compared to earlier studies on the inhibitory effect of essential oil from different plant
197
sources on spore germination (Tao, Jia, & Zhou, 2014; He et al., 2016). No spore germination
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10
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was observed at and beyond 0.6 µl/ml and 0.5 µl/ml of BLEO for A. flavus and P. expansum,
199
respectively after 4 weeks of incubation.
200
3.1.3. Data transformation The estimated germination time (τ) data were analysed for homogeneity of variance.
202
The variance [P] and mean [P] of untransformed data were found to be positively correlated
203
for both moulds, and the tstud values were reportedly higher than ttable value in case of A. flavus
204
(Table 2). While, transformation of the τ (h) data led to stabilized variance with lower tstud
205
values (< ttable) for A. flavus, the transformation of P. expansum germination time data
206
resulted in negative correlation between variance [P] and mean [P]. The square-root
207
transformation of the data for both mould showed reduced tstud value than logarithmic
208
transformation. Therefore, the estimated germination time (τ) data was square-root
209
transformed prior to fit the secondary model.
210
3.1.4. Secondary modelling
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The germination time (τ) was modelled as a function of BLEO concentration. The
212
estimated parameters (Table 3) are having narrow confidence interval for both the selected
213
moulds. The value of τopt for A. flavus and P. expansum were not significantly different (P=
214
0.082 and P = 0.210) with the value obtained under optimal condition (E0 = no BLEO),
215
respectively. A four-fold increase in the germination time was observed with increase in
216
BLEO concentration from E0 to k (i.e. ,-. = 74% and 63% of the BLEO range) for A. flavus
217
and P. expansum, respectively. However, the effect of BLEO was strong (i.e. increase in
218
more than two-fold increase) from k to MIC (26% and 37% of BLEO range) in case of A.
219
flavus and P. expansum, respectively. An increase in germination time (τ) occurred at 0.4 to
220
0.5 µl/ml, and 0.3 to 0.4 µl/ml of BLEO in case of A. flavus and P. expansum, respectively
221
(Fig. 3). Also, lower MIC value of BLEO for P. expansum suggests its higher susceptibility
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*
11
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to BLEO as compared to A. flavus, which was shown to have higher estimated MIC as well
223
as k value (Table 3). The MIC of BLEO for A. flavus and P. expansum based on modelling apparent lag time
225
as a function of BLEO on PDA medium was estimated to be 0.75 ± 0.03 µl/ml (Basak &
226
Guha, 2017a) and 0.74 ± 0.06 µl/ml (Basak & Guha, 2015) in previous studies. However, in
227
the present study, MIC was estimated to be 0.65 ± 0.01 and 0.54 ± 0.01 µl/ml of BLEO for A.
228
flavus and P. expansum, respectively. The disparity in MIC values can be attributed to the
229
fact that this study was based on germination of single spores in a population under varying
230
concentration of BLEO, whereas previous studies were based on apparent lag time of point
231
inoculum (10 µl) of spores (<106 spores/ml) as a function of BLEO. As discussed by Basak
232
(2017), single spores have more surface area exposed to the BLEO present in the PDA
233
medium. Hence, the probability is less for single spore to detoxify BLEO and germinate
234
under similar condition as compared to point inoculum.
235
3.1.5. Performance evaluation of the predictive models
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The Bf and Af are the tools for evaluating the performance of predictive models (Ross,
237
1996). The bias and accuracy factors of the secondary model for germination time of A.
238
flavus and P. expansum in the PDA medium are reported in Table 4. According to Ross
239
(1999), bias factor (0.9
240
Tienungoon, 2000) are within the permissible limits for both the selected moulds. Therefore,
241
the model can be suggested to be in good performance. The plot between observed and
242
predicted values of the selected moulds (Fig. 4) indicated that average predicted and observed
243
values of germination time under varying BLEO concentration differ by 4.4% and 1.6% for
244
A. flavus and P. expansum, respectively. This suggest the palusibility of the secondary model
245
at predicting germination time of A. flavus and P. expansum under the influence of BLEO.
246
4. Conclusion
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ACCEPTED MANUSCRIPT The mould spore germination under the influence of BLEO can be described by the
248
asymmetric model. Square-root transformation of germination time data provided more
249
stabilization and homogeneity to the variance. The efficacy of BLEO on germination time
250
parameter could estimate the MIC values using the re-parameterized Monod type model.
251
Satisfactory statistical indices (R2 and RMSE) alongside narrow 95% confidence interval of
252
estimated MIC of BLEO suggested the reliability of the estimated parameter. The accuracy of
253
the secondary model based on Af and Bf further cemented the faith in the goodness of the
254
estimated parameters. This study provided an insight of germination of single spore in a
255
population under the influence of essential oil of betel leaf using available predictive
256
mycological tools. Further study on potential of individual mould spores to germinate under
257
dynamic temperature conditions is warranted.
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Acknowledgements
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The author is grateful to Indian Institute of Technology Kharagpur for financial
260
assistance, infrastructure and facilities to conduct the research. The author is thankful to Prof.
261
P. Guha, Prof. S. L. Shrivastava, Prof. P. B. S. Bhadoria, Dr. Jayeeta Mitra, and Ms. Ruby
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Pandey of Agricultural and Food Engineering Department for their support.
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Trichoderma atroviride (T-15603.1). Journal of Basic Microbiology, 50(6), 570–580.
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Soylu, E. M., Kurt, S., & Soylu, S. (2010). In vitro and in vivo antifungal activities of the
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essential oils of various plants against tomato grey mould disease agent Botrytis
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cinerea. International Journal of Food Microbiology, 143(3), 183–9. Tao, N., Jia, L., & Zhou, H. (2014). Anti-fungal activity of Citrus reticulata Blanco essential
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oil against Penicillium italicum and Penicillium digitatum. Food Chemistry, 153, 265–
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271.
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Zwietering, M. H., Cuppers, H. G. A. M., de Witt, J. C., & van’t Riet, K. (1994). Evaluation
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of data transformations and validation of a model for the effect of temperature on
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bacterial growth. Applied and Environmental Microbiology, 60(1), 195–203.
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ACCEPTED MANUSCRIPT Figure captions
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Figure 1: Variance of P, plotted against the mean of P for A. flavus under the influence of
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varying concentration of BLEO: (●) no BLEO; (■) 0.1 µl/ml; (▲) 0.2 µl/ml; (▼) 0.3 µl/ml;
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(♦) 0.4 µl/ml; (×) 0.5 µl/ml, and for P. expansum under the influence of varying concentration
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of BLEO: ( ) no BLEO; (∆) 0.1 µl/ml; ( ) 0.2 µl/ml; ( ) 0.3 µl/ml; ( ) 0.4 µl/ml.
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Figure 2: Parameter estimates and 95% confidence interval of the asymmetric model for the
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in vitro spore germination data of (a) A. flavus, and (b) P. expansum under varying
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concentration of BLEO. Each point represents germination percentage of 600 spores and ()
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indicates fitted asymmetric model. The conditions of no germination (i.e. BLEO
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concentration at and beyond 0.6 and 0.5 µl/ml for (a) and (b), respectively) are not shown in
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the plot.
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Figure 3: Effect of germination time versus BLEO concentration fitted by a re-parameterized
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Monod type model on (▲) A. flavus, and ( ) P. expansum spores.
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Figure 4: Performance evaluation of a re-parameterized Monod type model for the effect of
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BLEO on germination time (τ) of (▲) A. flavus, and ( ) P. expansum spores
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ACCEPTED MANUSCRIPT Table 1 Estimated parameters (with 95% confidence interval) of the asymmetric model fitted to obtained germination percentage of A. flavus and P. expansum spores under the influence of BLEO BLEO (µl/ml)
d (-)
τ (h)
R2
RMSE
P (τ) %
10.6de (8.1, 13.1)
13.8i (13.3, 14.3)
0.976
6.5
58.5
Pmax (%)
Parameter estimates for A. flavus 0.0
117ab (102, 132) ab
e
h
117.5 (106.3, 128.7)
7.9 (6.7, 9.1)
15.5 (15.0, 16.0)
0.986
4.7
58.8
0.2
138.6a (116.1, 161.2)
9.6de (8.0, 11.2)
18.6g (17.9, 19.4)
0.986
4.3
69.3
0.3
111.8b (105.8, 117.8)
14.6cd (13.1, 16.1)
23.9e (23.6, 24.1)
0.993
3.1
55.9
0.4
117.9ab (111, 124.8)
18.3c (16.7, 19.9)
32.5d (32.2, 32.7)
0.993
2.6
59.0
0.5
121.8ab (115.2, 128.3)
29.0b (26.5, 31.5)
62.8b (62.5, 63.1)
0.994
2.4
60.9
0.6
No germination
10.8de (9.1, 12.5)
12.4j (12.2, 12.5)
0.981
5.5
50.9
0.0
b
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0.1
cd
g
0.1
101.4 (100.0, 102.7)
13.8 (12.8, 14.9)
17.8 (17.6, 17.9)
0.995
3.1
50.7
0.2
100.5b (99.2, 101.8)
17.1c (15.7, 18.42)
22.4f (22.3, 22.5)
0.995
3.4
50.3
0.3
101.9b (99.7, 104.1)
25.7b (23.7, 27.7)
39.4c (39.3, 39.6)
0.993
3.2
51.0
0.4
103.5b (101.1, 105.9)
36.6a (33.0, 40.2)
94.1a (93.8, 94.4)
0.987
3.8
51.8
0.5
No germination
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ACCEPTED MANUSCRIPT Table 2 Results of determination of correlation coefficient (r) by performing linear regression of the variance data as a function of mean of the germination time data over the range of BLEO Moulds
No transformation
Square-root transformation
Logarithmic transformation
tstud value
r (P-value)
tstud value
r (P-value)
tstud value
A. flavus
0.70 (0.121)
3.097
0.009 (0.986)
0.029
−0.15 (0.779)
0. 474
P. expansum
0.57 (0.311)
1.987
−0.43 (0.469)
1.349
−0.62 (0.269)
2.212
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r (P-value)
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The 95% critical Student’s t tabulated value (ttable) for 12 degree of freedom is 2.228 (A. flavus) and for 10 degree of freedom is 2.306 (P. expansum). Bold values indicates significant correlation
ACCEPTED MANUSCRIPT Table 3 Parameter estimates and 95% confidence interval of a re-parameterized Monod type model fitted to germination time (τ) of the selected moulds on PDA medium under the influence of BLEO Estimated parameters Moulds
k (µl/ml)
MIC (µl/ml)
R2
RMSE
A. flavus
3.73 (3.68, 3.78)
0.49 (0.48, 0.50)
0.65 (0.64, 0.67)
0.999
0.06
P. expansum
3.57 (3.47, 3.68)
0.34 (0.33, 0.35)
0.54 (0.52, 0.56)
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τopt (h)
0.998
0.10
ACCEPTED MANUSCRIPT Table 4 Statistical validation factors (Af = accuracy factor; Bf = bias factor) calculated for a re-parameterized Monod type model for germination time (τ) of the mould spores on PDA medium under the influence of BLEO Index
Moulds
Bf
A. flavus
1.01
0.99
P. expansum
1.02
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Af
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1.00
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ACCEPTED MANUSCRIPT Highlights Asymmetric model estimated spore germination time under the influence of BLEO Variance of estimated germination time was stabilized by square-root transformation Af and Bf showed the plausibility of the secondary model in estimating MIC of BLEO
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Predictive mycological tools can describe spore germination under influence of EOs