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Revista mexicana de fitopatología

versión On-line ISSN 2007-8080versión impresa ISSN 0185-3309

Rev. mex. fitopatol vol.35 no.2 Texcoco may. 2017 

Scientific articles

Chemical characterization, compositional variability and mathematical modelling of the effect of essential oils in Alternaria alternata

Jaime Black-Solis1 

Rosa Isela Ventura-Aguilar1 

Laura L. Barrera-Necha1 

Silvia Bautista-Baños1  * 

1Centro de Desarrollo de Productos Bióticos, Instituto Politécnico Nacional, Carretera Yautepec-Jojutla, Km. 6, calle Ceprobi No. 8, CP 62731, Yautepec, Morelos, México.


Mathematical models of in vitro growth and germination of Alternaria alternata in the presence of essential oils were developed. By using principal component analysis, similarities were found among the oils in terms of their volatile composition. The mycelial growth and conidial germination of A. alternata was evaluated in PDA with cinnamon, epazote and lime oils (0.25, 0.5 and 1.0 μL mL-1). The oils used were obtained by hydrodistillation and commercially and were characterized by gas chromatographymass spectrometry. The Baranyi and Roberts and logistics equations were used to fit the experimental data and to predict its behavior. Due to their chemical composition, the oils were grouped into: 1) cinnamon (commercial and non-commercial), in which cis-cinnamaldehyde predominated, 2) commercial lime (D-limonene) and epazote (commercial and non-commercial) with ascaridole and ρ-cimene, and 3) non-commercial lime. Cinnamon oil (0.5 and 1.0 μL mL-1) inhibited mycelial growth of A. alternata, whereas germination was 100 % inhibited with the presence of lime and epazote oils (0.25 and 0.5 μL mL-1). Mathematical models and principal component analyses are effective tools for understanding the effect of essential oils on A. alternata.

Key words: fungal development; Baranyi and Roberts; lime; epazote; cinnamon


Se desarrollaron modelos matemáticos del crecimiento y germinación in vitro de Alternaria alternata en presencia de aceites esenciales. Mediante el análisis de componentes principales, se encontraron similitudes entre ellos considerando su composición volátil. El crecimiento micelial y germinación de conidios de A. alternata se evaluó en PDA con aceites de canela, epazote y limón (0.25, 0.5, 1.0 μL mL-1). Los aceites se obtuvieron por hidrodestilación y comercialmente. Se caracterizaron por cromatografía de gases acoplada a espectrometría de masas. Para ajustar los datos experimentales y predecir su comportamiento se emplearon las ecuaciones de Baranyi y Roberts y logística. Por su composición química los aceites se agruparon en: 1) canela (comercial y no-comercial), en el que predominó el cis-Cinamaldehído, 2) limón comercial (D-Limoneno), y epazote (comercial y no-comercial), con Ascaridol y ρ-Cimeno y 3) limón no-comercial. El aceite de canela (0.5 y 1.0 μL∙ mL-1) inhibió el crecimiento micelial de A. alternata, mientras que, la germinación se inhibió 100 % con la presencia de aceites de limón y epazote (0.25 y 0.5 μL∙ mL-1). Los modelos matemáticos y el análisis de componente principales, son herramientas eficaces para entender el efecto de los aceites esenciales en A. alternata.

Palabras clave: desarrollo fúngico; Baranyi y Roberts; limón; epazote; canela


Fungi of Alternaria genus are responsible for diseases in a large number of vegetable and fruit products which may appear during crop development or postharvest, and cause widespread destruction of crops and production losses (Mamgain et al., 2013).

During postharvest, Alternaria is able to maintain a quiescent infection and grow under favorable conditions, mostly at the maturity stage of horticultural products. At this stage, the main species identified is A. alternata, which produces black mold in Solanaceae mainly (Troncoso-Rojas and Tiznado-Hernández, 2014).

Synthetic fungicides have been traditionally used to control diseases on fruit and vegetables, but due to inappropriate management and presence of residues, they have affected the human health and caused in fungal strains, resistant (McCarroll et al., 2002). For these reasons, over the last decades, the use of natural products, such as essential oils, has been studied as an option to control phytopathogenic fungi (Sivakumar and Bautista-Baños, 2014).

Essential oils (AE) are volatile aromatic compounds that contain the characteristic fragrance of the plants from which they are extracted (Krisch et al., 2011). In plants, they act as messengers, attract pollinators, and protect against herbivores and microorganisms that cause plant diseases (Baser and Buchbauer, 2009). These characteristics make them suitable for controlling fungal phytopathogenic.

EOs compounds content and their effectiveness to control phytopathogenic fungi depend on various factors, e. g., the part of the plant from which oil is extracted, concentration and environment conditions (Schmidt, 2009; Sánchez-González et al., 2011; Raut and Karuppayil, 2014).

Results of effectiveness and specificity of different AE for controlling phytopathogenic fungi have been reported in earlier studies. For example, Badawy and Abdelgaleil (2014) and Dimić et al. (2014) reported that lime essential oil (Citrus limon) inhibited the development of Botrytis cinerea, Fusarium oxysporum, Aspergillus parasiticus and Penicillium chrysogenum. Manganyi et al. (2015) and Lu et al. (2013) also reported the effectiveness of (Cinnamomum zeylanicum) cinnamon bark essential oil in controlling mycelial growth and spore germination of Colletotrichum destructivum, Phytophthora parasitica var. nicotianae and F. oxysporum; epazote essential oil has also been reported to have inhibitory effects on Phyllosticta citricarpa (Lombardo et al., 2016), F. oxysporum (Jaramillo et al., 2012), A. flavus, A. niger and C. gloeosporioides (Jardim et al., 2010).

Essentials oils may contain over than 100 compounds (Dima and Dima, 2015), thus to analyze and compare them, it is necessary to use multivariate statistics, which would allow to describe and analyze multidimensional observations of information obtained from diverse variables in the same study unit (Di Rienzo et al., 2008).

Using EOs for controlling phytopathogenic fungi created the need to use mathematical models to understand and predict their development over time. In the beginning, models were developed to predict bacteria growth (Baranyi and Roberts, 1994). However, due to the importance of fungi as food contamination vectors, the models have been adapted to evaluate their growth (García et al., 2009).

Dantigny et al. (2007), García et al. (20109 and Longhi et al. (2013) reported three types of mathematical models that may be useful to analyze fungi. The first type represents fungal growth over time, given by a series of restrictive factors; the second type represents the influence of restrictive factors on the primary model; and the third type is a combination of the first and second model types, and allows to predict the influence of restrictive factors on fungal growth. Basak and Guha (2015) reported the use of mathematical models based on experimental data of P. expansum mycelial growth and spore germination. Tremarin et al. (2015) adjusted data of Byssochlamys fulva and Neosartorya fischeri growth to the model of Baranyi and Roberts. Similarly, García et al. (2009) modeled the impact of optimal/suboptimal environment conditions on A. carbonarius and P. expansum growth by using Baranyi’s function.

The objectives of this study were: 1 characterize chemically three essential oils; 2. evaluate their effectiveness in controlling in vitro A. alternata; 3. determine the variability of EOs by analyzing their main components, and 4. model the inhibitory effect of EOs on A. alternata mycelial growth and conidial germination.

Materials and methods

Vegetal material and essential oil extraction

We used lime peel (Citrus limon), epazote above-ground plant parts (Dysphania ambrosioides) and cinnamon bark (Cinnamomum zeylanicum). Limes were collected in orchards in Yautepec Morelos, Mexico (18° 53’ 09’’ north and 99° 03’ 38’’ west). Epazote above-ground parts and cinnamon barks were purchased at the Central de Abasto (wholesale market) in Cuautla, Morelos, Mexico (18° 48’ 44’’north and 98° 57’ 21’’ wet). The vegetal species were identified at the Universidad Autónoma del Estado de Morelos Herbarium (number of specimens 34057-lime and 34058-epazote).

Vegetal material was used to obtain EOs by hydrodistillation (Díaz-Cedillo et al., 2013). One kilogram of vegetal material was placed in an Italian-type distiller and kept on boiling (97 °C) for 2 h. The EOs obtained were stored in amber jars at 4 °C and then their yield was gravimetrically determined. Furthermore, lime EOs were purchased at the company Hersol (State of Mexico, Mexico), epazote AE at the company Aceites y Esencias (State of Mexico, Mexico) and cinnamon bark AE at the company dōTERRA (Mexico City, Mexico). According to the manufacturer’s specifications, the EOs were 99 % pure industrial-grade.

Chemical characterization of essential oils using CG-EM

The commercial EOs and the ones obtained by hydrodistillation were diluted in chloroform in a 1:10 v/v. Then, 1 µL of the dissolution was injected in a gas chromatograph (GC) SCION 456-GC (Bruker Daltonics, Billerica, USA) adapted to an EVOQ mass triple quadrupole detector and a PAL-COMBI xt automatic sample injector (Bruker Daltonics, Inc.). The mass spectrometer (EM) was set to a 50 to 500 mass-charge-1 range using the MS Workstation version 8.2 software (Bruker Daltonics, Inc.).

The GC-EM was equipped with a BR-1ms capillary column 30 m long, 0.25 mm internal diameter and 0.25 µm thick (Bruker Daltonics, Inc.). The injector and detector temperature was 220 °C and 280 °C, respectively. Helium (He) was used as carrier gas at a 1 mL min-1 flow rate. The initial oven temperature was 55 °C for 1 min and then increased to 155 °C at heat speed rate of 20 °C min-1; this rate was maintained for 2 min and then increased to 255 °C at heat speed rate of 10 °C min-1 and a total analysis period of 20.14 min per sample.

The detected compounds were identified by comparing their retention time and mass spectrum with data from standards included in NIST (National Institute of Standards and Technology, MD) team’s library.

Fungus isolate and crop conditions

The A. alternata isolate was obtained from the fungi collection of the Laboratory of Tecnología Postcosecha de Productos Agrícolas (Ceprobi, Morelos, Mexico). The species that had already been morphologically and molecularly identified was grown in potato-dextrose-agar culture (PDA, Bioxon, Mexico) for 14 days at 28 °C.

Inhibition test of mycelial growth

The EOs inhibitory effect was determined using the agar-dilution method reported by Chen et al. (2014) which involves mixing essential oil concentrations (0.25, 0.5, 1.0 µL mL-1) with 0.1 % (v/v) Tween 20 (Hycel, Mexico City, Mexico) in 150 mL of PDA medium. Then, Petri dishes 90 mm in diameter were filled with 25 ml of the mixture (6 replications per treatment) and left to cool at room temperature (25±2 °C). PDA and PDA-Tween were used as controls.

A PDA disk 100 mm in diameter containing A. alternata was grown in the center of a Petri dish and incubated at 28±2 °C. Mycelial growth was measured daily using a vernier caliper in order to evaluate the diameter reached by the mycelium over time. The test ended when the mycelium completely covered the Petri dish containing the control treatment. The results were reported as mycelial growth inhibition index (IM), according to the following equation (1), where CC denotes the control’s growth, and CT , the growth in the treatment.


Treatments reaching 100 % inhibition were regrown in PDA culture but without adding essential oil to evaluate the fungistatic or fungicide effect of the EOs used.

Inhibition test for conidial germination

The effect of EOs on conidial germination was evaluated using the technique described by Bautista-Baños et al. (2008). A conidial solution (105 conidia mL-1) of a 14-day old monosporic culture of A. alternata was prepared and added to six disks containing PDA (25 µL disk-1) which then were placed on glass slides. Later, 10 µL of EOs were added to each disk (0.25, 0.5, 1.0 µL mL-1) incubated at 28±2 °C within sealed Petri dishes. Germination was carried out after 2, 4, 6 and 8 h. A conidium was considered germinated when a germ tube was observed regardless of its length (Costa et al., 2015).

After the incubation period, a drop of lactophenol blue solution was added to each disk and 100 conidia per disk were observed under an optical microscope 40x objective (Nikon alphaphot-2 YS2-H, Japan). The percentage germination was calculated (G(%)) using the following equation (2), where EG denotes the number of germinated conidia, and TE the total conidia.


Adjusting experimental data to mathematical models

Experimental data of A. alternata mycelial growth in PDA culture in terms of time, with and without EOs, were adjusted to the model of Baranyi and Roberts (1994) to estimate the maximum growth rate and apparent lag phase time using the following equation (3). Where D(t) denotes the diameter of the mycelium (cm) at any time t (días); Do , the diameter at t=0, µmax (cm day-1), the maximum growth rate; and λ (days), the apparent lag phase time.


The model was developed using DMFit version 3.5 (Microsoft Excel add-in) (Institute of Food Research, Norwich, UK). To evaluate the model, it was estimated the Mean Square Root Error (MSRE) and the determination coefficient (R2). Models with MSRE values near to cero and R2 near to one were considered to be the best (Tremarin et al., 2015). Growth data (experimental and predicted by the model) were used to plot surface graphs using SigmaPlot 12.0 (Systat Sofware Inc., CA, USA).

The conidial percentage germination was adjusted to the logistic model (Equation 4) to estimate the parameters, the increase in the percentage germination and the time required to reach 50 % germination. Experimental units containing EOs that not allowed fungal germination were omitted in the analysis. For this purpose, we used the statistical software InfoStat version 2016 (Universidad Nacional de Córdoba, Argentina). Where P denotes the germination percentage; Pmax , the maximum percentage germination (100 %); k(h-1), the increase in the rate of percentage germination; r (h), the time required to reach 50 % germination; and t (h), the time (Dantigny et al., 2007).


Statistical analysis

Data of the volatile compounds of the six different EOs identified through GC-EM were analyzed using principal component analysis (PCA) to obtain the variability of the studied systems with the software package InfoStat version 2016; mycelial growth and conidial germination at the end of the growth period were analyzed using a completely randomized design in a factorial arrangement with 6 replications. The factors used were 1) type of essential oil (lime, epazote and cinnamon); 2) source (hydrodistilled or commercial); and 3) concentration (0.25, 0.5 and 1.0 µL mL-1). Tukey’s test (p≤0.05) to compare the medians, and the InfoStat version 2016 software for data analysis was used. The experiment was performed in duplicate.


Chemical composition of essential oils

Results show differences in the composition of the EOs evaluated regarding the vegetal material and the method used to extract them (by hydrodistillation or commercial). Cinnamon, lime and epazote EOs obtained by hydrodistillation yielded 0.49, 0.33 and 0.015 %, respectively.

Considering the type of vegetal material from which the EOs were extracted, it was observed that lime and epazote oils contained terpenes mainly (D-Limonene, ρ-Cymene and Ascaridole), while the predominant compounds in cinnamon oil were aldehydes (cis-Cinnamaldehyde) (Table 1). However, considering the method used, differences in the content of the detected compounds were noted.

Table 1. Summary of the main volatile organic compounds of three essential oils detected by CG-EM. 

AE-essential oil; AR-relative area; TR-retention time; GF-functional group; A-aldehyde, E-ester, T-terpene

As for D-Limonene, it was observed 7.26 % more content in the lime AE obtained by hydrodistillation compared with the commercial AE. In epazote AE, two main components were identified: ρ-Cymene in non-commercial oil (22.40 %) and Ascaridole in commercial oil (27.30 %). Finally, the content of cis- Cinnamaldehyde in commercial cinnamon oil was 4.20 % higher than that obtained by hydrodistillation; this compound was the highest in both EOs.

Principal component analysis (PCA)

For PCA, compounds representing an area greater than 1 % were used in the chromatographic analysis. According to Terrádez (2002) there is no denifite rule regarding the number of principal components (PC) to be used, but it is important to keep in mind that one of the objectives of the analysis was to reduce the number of variables. In this regard, we selected the PCs that contributed at least 5 % of the total variance and whose proportion of accumulated variance explained at least 70 % of the same (Mora-Aguilera and Campbell, 1997). The results were grouped in five PCs that explain 100 % of the variability in the chemical composition of the EOs used (Table 2). However, given that PC1 and PC2 explained 74.0 % of the variability, the results were described in PC1 and PC2 terms.

Table 2. Principal Component Analysis (eigenvalues) among the compounds of three different essential oils. 

Figure 1A, shows the three groups formed considering the type of vegetal material. The first group corresponds to lime oil obtained by hydrodistillation; the second group, to cinnamon oils (commercial and non-commercial); and the third group, to lime (commercial) and epazote (commercial and non-comercial) oils. In PC1 we observed that essential cinnamon oil was different from epazote and lime oils. In PC2, differences were found among epazote (comercial and non-comercial) and lime (commercial) oils, and cinnamon (commercial and non-commercial) lime oils obtained by hydrodistillation.

On the other hand, significant values were observed in PC1 due to the presence of monoterpenic compounds, while PC2 was positively correlated with aldehydes and esters (data not shown). This is clearly appreciated in Figure 1B with three groups formed: a) the first group included D-Limonene and L-β- Pinene, which correspond to lime oil composition; b) in the second group we observed aldehydes, esters and non-cyclic monoterpenes such as cis-Cinnamaldehyde, compounds that are present in cinnamon oil; and c) the third group, showed oxigenated monoterpenes as Ascaridole, compounds that are present in epazote oil.

Figure 1. Distribution of essential oils (A) and compounds identified (B) according to eigenvectors from principal component analysis calculated for PC1 and PC2 (74 % variance). 

Mycelial growth inhibition

Statistically significant differences were observed (p<0.0001) in A. alternata in vitro mycelial growth (at day 9-time when the control treatment reached its maximum growth) by the effect of the essential oil type, source and concentration (Table 3). Results showed that A. alternata did not grow on the PDA medium to which cinnamon essential oil (commercial and non-commercial) was added at concentrations of 0.5 and 1.0 µL mL-1, and which had a fungicidal effect on the fungus. In contrast, commercial lime essential oil at 0.25 µL mL-1 concentration did not inhibit A. alternata growth, while, at the same concentration, comercial lime and epazote oils showed limited inhibition (4.06 and 3.42 %, respectively). A similar effect was observed with commercial lime oil at a concentration of 0.5 µL mL-1 (3.18 % inhibition).

Table 3. Mycelial growth and percentage inhibition of A. alternata incubated for 9 days in PDA medium to which AEs were added. 

CM-Mycelial growth; DE-standard deviation; medians with the same letter are significantly different (p > 0.05) by Tukey’s test.

Inhibition of conidial germination

The percentage germination of A. alternata conidia to which EOs were directly applied showed statistically significant differences (p<0.0001), as a result of the treatments, when they were evaluated after 8 h (data not shown). No germination was observed in treatments containing cinnamon essential oil (0.25, 0.5 and 1.0 ml-1), non-commercial lime and epazote oils (0.5 and 1.0 µL mL-1) and commercial lime and epazote oils (1.0 µL mL-1).

Treatments showing the highest germination inhibition percentage were non-commercial lime (92.50 %) and epazote oils (93.33 %) at a concentration of 0.25 µL mL-1, while at a concentration of 0.5 µL mL-1 it was the commercial lime and epazote oils (91.0 % and 94.17 %, respectively) that showed the highest percentage germination inhibition; this suggests that the results depend on the oil concentration used.

Mycelial growth model

Experimental data of A. alternata mycelial growth on PDA at different concentrations of EOs, in terms of time were adjusted to the model of Baranyi and Roberts. Mycelial growth tended to decrease as the concentration of EOs in the culture medium increased (Figure 2).

Figure 2. Surface graph of the effect of different concentrations of essential oils on A. alternata mycelial growth. Essential oils obtained by hydrodistillation. a. lime. b. epazote. c. cinnamon. Commercial essential oils. d. lime. e. epazote. f. cinnamon. Experimental data (), data predicted by the model (). 

Based on data of the evaluated treatments, we developed 14 models (Table 4). The average determination coefficient (R2) was 0.97, while the root-mean-square error (RMSE) was 0.15. In the models developed, we observed that as the concentration of essential oil increased, the maximum growth rate decreased (µmax) and the time of the apparent lag phase increased (λ).

Table 4. Parameters obtained by adjusting experimental data of mycelial growth of A. alternata incubated in PDA and AEs to the model of Baranyi and Roberts. 

O-AE obtained;C-AE commercial;µmax -maximum growth rate; λ- apparent lag phase time; SE-standard error; R2-determination coefficient; RMSE- square root mean error

Conidial germination model

Experiment data of conidial germination were adjusted to the Logistic model. Using the evaluated treatments 5 models were developed (Table 5). The average RMSE was 1.98. The increase in EOs concentration affected germination, and as the concentration of essential oil increased, there was a lower rate of germination increase k (h-1) and more time was required to reach 50 % germination r(h).

Table 5. Parameters obtained by adjusting experimental data of conidial germination of A. alternata incubated in direct contact with AEs to the logistic model. 

O-AE obtained;C-AE commercial; k-rate of increase in percentage germination; r-time required to reach 50 % germination; SE-standard error; RMSE-square root mean error


Yields of EOs obtained by hydrodistillation were lower than those reported in the literature. For essential epazote oil, Jaramillo et al. (2012) reported yields of 0.4 %. For cinnamon oil, Golmohammad et al. (2012) reported yields of 3.6 %, and Saleem et al. (2015) and Unlu et al. (2010) reported yields of 0.93 %. Differences in yields of the EOs evaluated, compared with yields reported in literature, may be attributed to factors such as the methology used during essential oil extraction, as well as its effectiveness (Schmidt, 2009; Golmakani and Moayyedi, 2015).

For example, Hamdani and Allem (2015), and Sharma and Vashist (2015), extracted lime essential oil by hydrodistillation using a Clevenger-type distiller and obtained yields of 1.0-1.5 %, which were 3 to 5 times higher than the yield obtained in this research using an Italian-type distiller. Similarly, the condition of the plant material (fresh or dry) and the variety, influence yield and their fungicidal/fungistatic effect, which can explain the variation cited in literature (Schmidt, 2009).

Although there are several reports associated with AE composition, the effect of a commercial product has not been compared to that of regional species, such as the ones used in this research. Using these species to obtain EOs, and evaluate their control on A. alternata can be a viable alternative for effectively using them.

On the other hand, the limited capacity of essential lime oil to inhibt A. alternata growth may be attributed to its high concentration of D-Limonene, the most abundant component, which has insecticidal but not antimocrobial activity, as reported by Guo et al. (2016).

Regarding essential epazote oil, there are no studies about their application to control A. alternata. However, its effect has already been evaluated on other microorganisms. Lombardo et al. (2016) found limited growth inhibition in vitro of P. citricarpa at a concentration of 1 mg mL-1, and Jardim et al. (2008) reported total inhibition, among others, of A. niger, C. gloeosporioides and F. oxysporum, at 0.3 % concentration. The effectivenes of epazote oil to control phytopathogenic fungi is attributed to the presence of Ascaridole (Jardim et al. 2010). However, in this study, we did not identify this compound in epazote oil obtained by hydrodistillation, but we identified it in commercial oil (27.29 %). This result could explain the higher antifungal activity of the commercial oil (76.6 % inhibition at a concentration of 1.0 µL mL-1).

As for essential cinnamon oil, it completely inhibited in vitro growth of A. alternata; a similar effect was reported by Lu et al. (2013) at a concentration of 240 mg mL-1. Its effect has also been evaluated in other fungi. Nasir et al. (2015) reported growth inhibition of A. niger (100 %) at a concentration of 0.08 µL mL-1, while Saleem et al. (2015) reported 50 % more inhibiton in A. niger and A. flavus at 2 mg mL-1. In all reports, Cynamaldehyde was found to be the main compound and responsible for the antifungal activity (Schwab et al., 2008).

Regarding inhibition of the conidial germination, we observed an effect depending on oil concentration. This means that as more essential oil was applied, germination decreased. This phenomenon may have been produced by EOs by delaying the development of the germ tube or causing rupture of conidia cell membrane, which in turn caused disorganization of the conidia cytoplasm and destroyed organelles (Perina et al., 2014). Lu et al. (2013) reported the same effect, with an increased concentration of essential cinnamon oil (20 to 80 μg∙mL-1), increased A. alternata the inhibition of conidial germination from 30 to 100 %.

In this study PCAs facilitated the analysis and grouping of the evaluated EOs according to their chemical composition and source (hydrodistillation or commercial), and allowed to explain their effect on A. alternata growth. It was confirmed that essential cinnamon oil (commercial and non-commercial) had different composition compared with the remaining oils. Similarly, Petretto et al. (2016) used PCAs based on data of the composition of essential Myrtus communis oil and classified diffferent specimens and wild varieties, finding the more representative compounds of each variety. Furthermore, in a study conducted by Méndez-Tovar et al. (2016) PCA allowed to analyze the influence of the harvest year on the chemical composition of EOs from Thymus mastichina, Salvia lavandulifolia and Lavandula latifolia populations.

Given the extent of the study and data obtained about mycelial growth and conidial germination, the use of mathematical tools is useful to appreciate the combined effect of different doses and essential oils during time. The use of mathematical modeling in A. alternata is innovative, so it can allow us to reduce analysis time, estimate its behavior considering diverse factors and optimize processes associated with fungal control.

There are already reports on the use of mathematical models based on Baranyi and Roberts function to model P. expansum data of mycelial growth on PDA, adding betel leaf oil (Piper betle). Results from this experiment showed that higher concentrations of essential oil in the medium culture decreased the maximum growth rate (µmax) and increased the apparent lag phase time (λ) (Basak and Guha, 2015). Similarly, Marín et al. (2008) and Tremarin et al. (2015) used fungal growth models based on Baranyi and Roberts equation but without a restrictive agent (essential oil) in the culture medium. Instead, they modified the parameters of the culture medium (temperature and pH). The study showed an effect of the modification to the parameters of the culture, on the parameters of the maximum growth rate (µmax) and apparent lag phase time (λ). Dantigny et al. (2007) and Basak and Guha (2015) also used mathematical modeling (logistics model) in spore germination of phytopathogens such as P. expansum and P. verrucosum.


Mycelial growth and conidial germination of A. alternata was affected by the use of cinnamon oil at concentrations of 0.5 and 1 µL∙mL-1 regardless of its source (commercial and non-commercial). On the other hand, data analysis using principal components resulted to be an appropriate methodology to group the EOs, that were evaluated according to their chemical composition, and thereby explaining their fungicidal or fungisticatic effect. Finally, by using mathematical modeling it was established that as the concentrations of essential oil increased in the culture medium, the maximum growth rate (µmax) decreased and the apparent lag phase time (λ) increased.


The authors wish to thank M.S. Gabriel Flores Franco, curator at UAEM’s Herbarium for his support to identify the vegetal species used in this study, and to Dra. Mayra Beatriz Gómez Patiño from IPN’s Centro de Nanociencias y Micro y Nanotecnologías for her support to analyze the chemical composition of the EOs used.


Badawy M and Abdelgaleil S. 2014. Composition and antimicrobial activity of essential oils isolated from Egyptian plants against plant pathogenic bacteria and fungi. Industrial Crops and Products 52:776-782. ]

Baranyi J and Roberts T. 1994. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23:277-294. DOI: 10.1016/0168-1605(94)90157-0 [ Links ]

Basak S and Guha P. 2015. 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 215:171-178. ]

Baser K and Buchbauer G. eds. 2009. Handbook of essential oils: science, technology, and applications. CRC Press. NW-USA, 975p. ]

Bautista-Baños S, Barrera-Necha L, Hernandez-Lauzardo A, Velázquez-Del Valle M, Alia-Tejacal I y Guillén-Sánchez D. 2008. Polvos, extractos y fracciones de hojas de Cestrum nocturnum L. y su actividad antifúngica en dos aislamientos de Fusarium spp. Revista UDO Agrícola 8:42-51. ]

Chen Q, Xu S, Wu T, Guo J, Sha S, Zheng X and Yu T. 2014. Effect of citronella essential oil on the inhibition of postharvest Alternaria alternata in cherry tomato. Journal of the Science of Food and Agriculture 94:2441-2447. DOI: 10.1002/jsfa.6576 [ Links ]

Costa L, Pinto J, Bertolucci S, Costa J, Alves P and Niculau E. 2015. antifungal activity of Ocimum selloi essential oil and methylchavicol against phytopathogenic fungi. Revista Ciência Agronômica 46:428-435. ]

Dantigny P, Marín S, Beyer M and Magan N. 2007. Mould germination: data treatment and modelling. International Journal of Food Microbiology 114:17-24. DOI: 10.1016/j.ijfoodmicro.2006.11.002 [ Links ]

Di Rienzo J, Casanoves F, Balzarini M, González L, Tablada M y Robledo C. 2008. InfoStat manual de usuario. Grupo InfoStat, FCA. 333p. [ Links ]

Díaz-Cedillo F, Serrato-Cruz M, de la Cruz-Marcial J, Sánchez-Alonso M y López-Morales V. 2013. Compuestos mayoritarios del aceite esencial en órganos de una población de Tagetes coronopifolia Willd. Revista Fitotecnia Mexicana 36:405-411. ]

Dima C and Dima S. 2015. Essential oils in foods: extraction, stabilization, and toxicity. Current Opinion in Food Science 5:29-35. ]

Dimić G, Kocić-Tanackov S, Mojović L and Pejin J. 2014. Antifungal activity of lemon essential oil, coriander and cinnamon extracts on foodborne molds in direct contact and the vapor phase. Journal of Food Processing and Preservation 1-10. DOI:10.1111/jfpp.12410 [ Links ]

García D, Ramos A, Sanchis V and Marín S. 2009. Predicting mycotoxins in foods: a review. Food Microbiology 26:757-769. ]

Garcia D, Ramos A, Sanchis V and Marín S. 2010. Modelling mould growth under suboptimal environmental conditions and inoculum size. Food Microbiology 27:909-917. DOI:10.1016/ [ Links ]

Golmakani M and Moayyedi M. 2015. Comparison of heat and mass transfer of different microwave-assisted extraction methods of essential oil from Citrus limon (Lisbon variety) peel. Food Science & Nutrition 3:506-518. DOI: 10.1002/fsn3.240 [ Links ]

Golmohammad F, Eikani M and Maymandi H. 2012. Cinnamon bark volatile oils separation and determination using solidphase extraction and gas chromatography. Procedia Engineering 42:247-260. DOI: 10.1016/j.proeng.2012.07.416 [ Links ]

Guo S, Zhang W, Liang J, You C, Geng Z, Wang C and Du S. 2016. Contact and repellent activities of the essential oil from Juniperus formosana against two stored product insects. Molecules 21:504. DOI: 10.3390/molecules21040504 [ Links ]

Hamdani F and Allem R. 2015. Propriétés antifongiques des huiles essentielles des feuilles de Citrus vis-à-vis d’Alternaria alternata et Penicillium sp in vitro. Phytothérapie 1-4. DOI: 10.1007/s10298-015-0978-3 [ Links ]

Jaramillo B, Duarte E y Delgado W. 2012. Bioactividad del aceite esencial de Chenopodium ambrosioides colombiano. Revista Cubana de Plantas Medicinales 17:54-64. ]

Jardim C, Jham G, Dhingra O and Freire M. 2008. Composition and antifungal activity of the essential oil of the brazilian Chenopodium ambrosioides L. Journal of Chemical Ecology 34:1213-1218. DOI: 10.1007/s10886-008-9526-z [ Links ]

Jardim C, Jham G, Dhingra O and Freire M. 2010. Chemical composition and antifungal activity of the hexane extract of the brazilian Chenopodium ambrosioides L. Journal of the Brazilian Chemical Society 21:1814-1818. ]

Krisch J, Rentsenkhand T and Vágvölgyi C. 2011. Essential oils against yeasts and moulds causing food spoilage. Formatex research center. Science Against Microbial Pathogens: Communicating Current Research and Technological Advances Microbiology 1135-1142. [ Links ]

Lombardo P, Guimaraens A, Franco J, Dellacassa E and Faggiani E. 2016. Effectiveness of essential oils for postharvest control of Phyllosticta citricarpa (citrus black spot) on citrus fruit. Postharvest Biology and Technology 121:1-8. ]

Longhi D, Dalcanton F, Fãlcao G, Mattar B and Borges J. 2013. Assessing the prediction ability of different mathematical models for the growth of Lactobacillus plantarum under non-isothermal conditions. Journal of Theoretical Biology 335:88-96. DOI: 10.1016/j.jtbi.2013.06.030 [ Links ]

Lu M, Han Z, Xu Y and Yao L. 2013. Effects of essential oils from chinese indigenous aromatic plants on mycelial growth and morphogenesis of three phytopathogens. Flavour and Fragrance Journal 28:84-92. DOI: 10.1002/ffj.3132 [ Links ]

Mamgain A, Roychowdhury R and Tah J. 2013. Alternaria pathogenicity and its strategic controls. Research Journal of Biology 1:1-9. ]

Manganyi M, Regnier T and Olivier E. 2015. Antimicrobial activities of selected essential oils against Fusarium oxysporum isolates and their biofilms. South African Journal of Botany 99:115-121. ]

Marín S, Cuevas D, Ramos A and Sanchis V. 2008. Fitting of colony diameter and ergosterol as indicators of food borne mould growth to known growth models in solid medium. International Journal of Food Microbiology 121:139-149. ]

McCarroll N, Protzel A, Ioannou Y, Stack F, Jackson M, Waters M and Dearfield K. 2002. A survey of EPA/OPP and open literatura on selected pesticide chemicals III. Mutagenicity and carcinogenicity of benomyl and carbendazim. Review. Mutation Research 512:1-35. ]

Méndez-Tovar I, Novak J, Sponza S, Herrero B and AsensioS-Manzanera M. 2016. Variability in essential oil composition of wild populations of Labiatae species collected in Spain. Industrial Crops and Products 79:18-28. ]

Mora-Aguilera G and Campbell C. 1997. Multivariate techniques for selection of epidemiological variables. In Francl L and Neher D. eds. Exercises in plant disease epidemiology. APS Press 51-58 [ Links ]

Nasir M, Tafess K and Abate D. 2015. Antimicrobial potential of the ethiopian Thymus schimperi essential oil in comparison with others against certain fungal and bacterial species. BMC Complementary and Alternative Medicine 15:1. DOI: 10.1186/s12906-015-0784-3 [ Links ]

Perina F, Amaral D, Fernandes R, Labory C, Teixeira G and Alves E. 2014. Thymus vulgaris essential oil and thymol against Alternaria alternata (Fr.) Keissler: effects on growth, viability, early infection and cellular mode of action. Pest Management Science 71:1371-1378 DOI: 10.1002/ps.3933 [ Links ]

Petretto G, Maldini M, Addis R, Chessa M, Foddai M, Rourke J and Pintore G. 2016. Variability of chemical composition and antioxidant activity of essential oils between Myrtus communis var. Leucocarpa DC and var. Melanocarpa DC. Food Chemistry 197:124-131. ]

Raut J and Karuppayil S. 2014. A status review on the medicinal properties of essential oils. Industrial Crops and Products 62:250-264. ]

Saleem M, Bhatti H, Jilani M and Hanif M. 2015. Bioanalytical evaluation of Cinnamomum zeylanicum essential oil. Natural Product Research 29:1857-1859. ]

Sánchez-González L, Vargas M, González-Martínez C, Chiralt A and Cháfer M. 2011. Use of essential oils in bioactive edible coatings: a review.Food Engineering Reviews 3:1-16. DOI 10.1007/s12393-010-9031-3 [ Links ]

Schmidt E. 2009. Production of essential oils. In Baser K and Buchbauer G. eds. Handbook of essential oils: science, technology, and applications. CRC Press 83-119. DOI: 10.1201/b19393-6 [ Links ]

Schwab W, Davidovich-Rikanati R and Lewinsohn E. 2008. Biosynthesis of plant-derived flavor compounds. The Plant Journal 54:712-732. DOI: 10.1111/j.1365-313X.2008.03446.x [ Links ]

Sharma D and Vashist H. 2015. Hydrodistillation and comparative report of percentage yield on leaves and fruit peels from different citrus plants of rutaceae family. Journal of Plant Sciences 10:75-78. DOI: 10.3923/jps.2015.75.78 [ Links ]

Sivakumar D and Bautista-Baños S. 2014. A review on the use of essential oils for postharvest decay control and maintenance of fruit quality during storage. Review. Crop Protection 64:27-37. ]

Terrádez M. 2002. Análisis de componentes principales. Proyecto e-Math. Universitat Oberta de Catalunya. (consulta, febrero 2017) [ Links ]

Tremarin A, Longhi D, Martins B and Falcão G. 2015. Modeling the growth of Byssochlamys fulva and Neosartorya fischeri on solidified apple juice by measuring colony diameter and ergosterol content. International Journal of Food Microbiology 193:23-28. ]

Troncoso-Rojas R and Tiznado-Hernández M. 2014. Alternaria alternata (black rot, black spot). In Bautista-Baños S. ed. Postharvest decay: control strategies. Elsevier 87-147. ]

Unlu M, Ergene E, Unlu G, Zeytinoglu H and Vural N. 2010. Composition, antimicrobial activity and in vitro cytotoxicity of essential oil from Cinnamomum zeylanicum Blume (Lauraceae). Food and Chemical Toxicology 48:3274-3280. [ Links ]

Received: December 11, 2016; Accepted: February 14, 2017

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