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Effect of air temperature and velocity on drying kinetics and essential oil composition of Piper umbellatum L. leaves
Industrial Crops & Products 142 (2019) 111846
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Effect of air temperature and velocity on drying kinetics and essential oil composition of Piper umbellatum L. leaves
T
Luana do Nascimento Silveira Dornelesa, André Luís Duarte Gonelia,⁎, Claudia Andrea Lima Cardosob, Cristiane Bezerra da Silvaa, Michele Rosemari Hautha, Guilherme Cardoso Obaa, Vanderleia Schoeningera a b
Faculty of Agricultural Ciences, Federal University of Grande Dourados, PO Box: 533, 79.804-970, Dourados, MS, Brazil Natural Resources Study Center, Mato Grosso do Sul State University, Dourados, MS, Brazil
ARTICLE INFO
ABSTRACT
Keywords: Essential oil GC–MS Midilli model Medicinal plants
Piper umbellatum L. possesses diuretic, antimalarial, vermifuge, and anti-inflammatory properties, in addition to having essential oil in its leaves. Presuming that substances and essential oils in medicinal plants can be altered when they are subjected to various drying conditions, this study aimed to evaluate kinetic drying as well as the composition of essential oil from P. umbellatum L. leaves. The drying process was completed using four temperatures (40 °C, 50 °C, 60 °C, and 70 °C) and two drying air velocities (0.4 and 0.7 m s−1), being the drying process stopped when the moisture content of leaves was equal to 0.11 ± 0.01 dry basis (d.b.). The essential oil of the leaves was determined by hydrodistillation. The chemical components were analyzed by GC–MS. The Midilli model was the only one who represented satisfactorily product drying curves and the rise of temperature and drying air velocity resulted in the increase of the drying rate and in decreasing the content of essential oil from leaves. In total, 28 chemical substances were identified in the essential oil, with piperitone, dillapiole, and myrcene being the majorities. The obtained data indicated that the drying process maintain the quality patterns of the essential oils from the leaves; a slight alteration in the compound percentage was also observed.
1. Introduction Piper umbellatum L. is a perennial shrub native to the Americas and is widely used in traditional medicine in several countries. This is because several parts of this plant possess pharmacological properties, including antibacterial, antifungal, antioxidant, antimalarial, anti-inflammatory, analgesic, and antithermogenic features (Roersch, 2010; Agbor et al., 2012). Phytochemical studies on P. umbellatum L. confirm the presence of terpenes (mainly found in essential oils), alkaloids, flavonoids, sterols, and other classes of secondary metabolites (François et al., 2019). The physico-chemical attributes of aromatic and medicinal plants are determined in accordance with their moisture content. In general, after harvest, these plants display a moisture content of around 60–80%, a relatively high value that enables the development of harmful biological processes (Poós and Varju, 2017). Therefore, the aromatic and medicinal plants must be commercialized, consumed, or dried shortly after harvest. This is in order to minimize the loss of content and composition of the plant active ingredients. These losses
⁎
occur because harvesting initiates a degradation process due to the increase in moisture activity (Coradi et al., 2014). In this way, the drying process is an extremely vital step, since it consists in the removal of available water to safe levels, so that the enzymatic and microbial activities are interrupted. This consequently preserves the quality of the culture, which also results in an increase in the shelf life. Moreover, the drying process can contribute to the commercialization step, since drying results in the reduction in the weight and volume of medicinal plants, with positive effects on transport and storage (Prusinowska and Śmigielski, 2015; Karam et al., 2016). Conventional drying, also known as convective hot air drying, is a widely adopted technique in the food and pharmaceutical industry; however, this process can change the structure of the plants, affecting the phytochemicals due to thermal degradation (Martínez-Las Heras et al., 2014). The temperature of the drying air depends on the sensitivity of the plant active ingredients to heat as well as the moisture migration rate; that is, the higher the temperature used, the faster the drying process. However, the choice of the temperature must be performed very carefully, because if it is too high it can cause leaf surfaces
Corresponding author. E-mail address: [email protected] (A. Luís Duarte Goneli).
https://doi.org/10.1016/j.indcrop.2019.111846 Received 30 July 2019; Received in revised form 2 October 2019; Accepted 4 October 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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to burn (Poós and Varju, 2017). In addition, air drying temperature is also a determinant in the volatile substances loss that are part of the essential oil. This also influences the vapor pressure of the drying air, and consequently, the process itself. Therefore, it is an expected that particular temperature range allows smaller losses of essential oil at the end of the drying process (Borsato et al., 2005). Drying at low temperatures protects against the degradation of active ingredients; however, it is slow and the metabolic processes can continue for a longer duration. This can lead to the loss of quality of the aromatic plants and, subsequently, of the added value products. Therefore, the use of appropriate dryers, working with adequate values of temperature and velocity, contributes to preserving the quality of the final product. In contrast, while observing various methods used in the phytotherapeutic industries, it is evident that several quality control approaches are available for the medicinal plants. This makes it difficult to standardize the type of drying, being one of the main reasons for the heterogeneous quality of final products (Chao et al., 2017; Rocha et al., 2011). Specifically, the development of efficient drying techniques is essential in order to use the biomass produced by the plant and its properties in an ideal and effective manner, particularly considering the increasing demand and supply for medicinal plants (Tabaldi et al., 2012). Nevertheless, because each product has specific characteristics, it is necessary to obtain theoretical information regarding the drying methods and conditions for each product (Silva et al., 2015). This information is obtained by simulating drying kinetics, which is based on the definition of a mathematical equation that can effectively describe the system. The solution of these mathematical equations is presumed to allow the prediction of process parameters as a function of time at any point in the drying equipment (Avhad and Marchetti, 2016). Studying the drying kinetics is very important to get the best conditions of the drying process and to promote a better product quality after its completion. In addition, mathematical model adjustment for the drying process allows design engineers choose the most appropriate operating conditions and a better design of the dryers. (Perea-Flores et al., 2012). Thus, this study aims to evaluate the drying kinetics and the effects of various drying air temperatures and velocities on the chemical composition of essential oil from P. umbellatum L. leaves.
2.2. Sample drying
2. Materials and methods
2.3. Drying kinetics
2.1. Sample collection and preparation
During the drying process, the mass of the trays containing the samples was periodically checked. A digital scale with a resolution of 0.01 g was used. The time between the readings was controlled based on the differences in mass (gravimetric method, by knowing the initial mass and moisture content of the leaves), aiming to avoid significant variations in the moisture content between the readings. From previously defined moisture content, it was possible to control the time required to reach a product mass that corresponded to the stipulated moisture content, in order to achieve satisfactory observations during drying. The moisture ratio (MR) of the P. umbellatum L. leaves, while drying at different air conditions, was determined using Eq. 2.
The drying process was realized carried out in an experimental dryer comprising fixed bed (Goneli et al., 2016), which feature a heating source containing a set of electrical resistances (totaling 12 kW of power) and a Sirocco fan (Ibraum brand, model VSI-160, with a motor of 1 hp). The temperature was controlled using a process universal controller (Novus brand, model N1200), working with proportional-integral-derivative (PID) control, and the airflow was selected by means of a frequency inverter connected to the fan motor. The dryer is equipped with a system that precisely controlled the flow and temperature of the drying air and had a series of sensors connected to the control panel. The purpose here was to obtain a fine adjustment and to monitor drying air conditions. The drying bed consisted of four trays allocated in an experimental dryer preheated to the specific temperature of each drying treatment. Each of the trays contained 50 g of sheets with a 0.25 mm layer height. The drying air velocity was adjusted by the rotation of the motor fan, frequency inverter, until it reached the desired speed, being determined with the aid of a rotary blade thermo-anemometer (Instrutherm brand, model TAD 500), with resolution of ±0.1 ms−1. The P. umbellatum L. leaves were dried using air temperatures of 40 °C, 50 °C, 60 °C, and 70 °C and drying air velocities of 0.4 and 0.7 m s −1 . The drying process was carried out until the product attained the equilibrium moisture content. The initial dry basis (d.b.) moisture content of the leaves was 3.87 ± 0.30. In addition, for the mathematical modeling, the final moisture content of 0.11 ± 0.01 (d.b.). The moisture content of the samples was determined, in accordance with the gravimetric method recommended by ASABE (2007) for forage and other similar plants, using a kiln with forced air circulation at 103 ± 1 °C, for 24 h. The drying rate (DR) of the leaves during drying was determined by Eq. 1 and refers to the amount of water that a given product loses per unit of dry matter per unit of time.
DR = Ma 0
Mai
Dm (ti
t0 )
(1)
where Ma0 is the previous total moisture mass (kg); Mai is the present total moisture mass (kg), Dm is the dry matter mass (kg), t0 is the total previous drying time (h), and ti is the total present drying time (h).
The leaves of P. umbellatum L. were collected in the Medicinal Plant Growing Area of the Federal University of Grande Dourados-UFGD (Dourados, Mato Grosso do Sul, Brazil) where it had already been cultivated over the years, during the months of August and september. To avoid variations in the leaves initial moisture content, they were always collected from the aerial part of the bushes during the early hours of the morning and never after rainfall or irrigation. The fresh samples were packed in polyethylene bags and sent to the Pre-processing and storage laboratory of agricultural products (LAPREP/UFGD). For each drying condition evaluated in this study, about 400 g of leaves were collected in the median region of the plants, where they were in a fully developed secondary growth stage. Due to heterogeneity in fresh leaves size, homogenization was performed after collection to avoid interference with results during drying, started soon after harvest. The leaves that showed any kind of physical damage or signs of disease were eliminated. Eventually, 3 g of the collected material was separated to determine its moisture content and another part, approximately 50 g per repetition, was dried immediately after collection.
MR = Mt
Me
Mi
Me
(2)
where Mt is the moisture content of the product at a given time, Me is the equilibrium moisture content of the product, and Mi is the initial moisture content of the product, all in dry basis moisture content. Four mathematical models, traditionally used to regress the phenomenon of drying of agricultural products (Table 1), were adjusted for moisture ratio data obtained experimentally during leaf drying. 2
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Aldrich, purity ≥ 90%), were used to analyze the mass spectra compared to Adams (2007) and the equipment library (NIST21 and WILEY229). The peak area of each compound was determined via manual integration of each total ion chromatogram (TIC). Eventually, all areas were transformed into relative percentage areas.This method is considered safe since the fragmentation patterns of each substance is demonstrated through the NIST library, and compared with each substance obtained in the generated chromatogram This method is considered safe since the fragmentation patterns of each substance is demonstrated through the NIST library, and compared with each substance obtained in the generated chromatogram.
Table 1 Mathematical models adjusted to the drying curves of the Piper umbellatum L. leaves. Models
Equations
Diffusion approximation Modified Henderson and Pabis
MR = a exp(-k θ) + (1 - a) exp(-k b θ) MR = a exp(-k θ) + b exp(-k0 θ)+c exp (-k1 θ) MR = a exp(-k θn) + b θ MR = exp(-k θn)
Midilli Page
(3) (4) (5) (6)
where θ is the drying time (h), k, ko, and k1 are the drying constants (h−1), and a, b, c, and n are the model coefficients.
2.6. Statistical analysis
2.4. Effective diffusivity and activation energy
The experimental data of drying kinetics were submitted to nonlinear regression analysis by the Gauss–Newton algorithm. To analyze the degree of fit of each model, the magnitudes of the adjusted coefficient of determination (R2), mean relative error (MRE), and standard error of estimate of moisture (SSE) were considered, and the behavior of the distribution of the residual, s, was verified. The values of the relative mean error (P) and standard deviation of the estimate (SE) were calculated according to:
The effective diffusion coefficient for the different drying air temperatures (40, 50, 60 and 70 °C) was calculated using Eq. 7, based on the theory of net diffusion. This equation is the analytical solution for Fick’s second law, considering the geometrical shape of the product approximately as a flat plate and with approximation of eight terms.
MR =
8 2
n =0
1 exp -(2n + 1)² ²Deff (2n+1) 2 4L²
(7)
2 −1
where Deff is the effective diffusivity (m s ), θ is the drying time (s), L is the product thickness, and (n) is the model term number. The thickness of the P. umbellatum L. leaves was measured using a digital caliper with a resolution of 0.01 mm. Fifty fresh leaves were measured, performing three measurements on each one of them in different areas, following which the mean measured value was calculated. In order to evaluate the influence of temperature on the effective diffusion coefficient, Arrhenius equation was used and described as follows:
Deff = Do exp
Ea RT
MRE = 100 N
SSE =
MRpre
N i=1
(MR exp
MRpre )
MRexp
(10)
2
Df
(11)
where N is the number of experimental observations, MRexp is the experimental moisture ratio, MRpre is the predicte moisture ratio, and Df is the degrees of freedom. The analysis of the main components was completed using Paretoscaled variables for statistical multivariate principal component analysis (PCA). Two chemometric matrices were evaluated for each activity: first, the yield values were interpreted to delineate the generic behavior of each drying curve against the air velocities used; second, the data from each parameter were evaluated to specify a better temperature for the drying air. Specifically, the PCA was completed by preprocessing the self-adjusted averages with varied scales, to which the same variant weight was assigned (Brandão et al., 2013; Monteiro et al., 2008).
−1
where Do is the Arrhenius factor for the drying process, (m s ), Ea is the activation energy (kJ mol−1), R is the universal gas constant (8.314 kJ kmol−1 K−1), and T is the absolute temperature (K). 2.5. Obtaining the essential oil and chemical analysis Fresh and dry leaves separately were subjected to hydrodistillation for 4 h in a Clevenger. The mass obtained of the essential oil was evaluated in relation mass of the plant. The essential oil (O) content of pariparoba leaves was calculated by the following equation:
O= om dm
MRexp
i=1
(8) 2
N
3. Results and discussion 3.1. Drying kinetics Table 2 presents the results obtained from the analysis of the models for drying the leaves of P. umbellatum L. leaves. It was observed that the models adjusted to the experimental data presented values for the coefficient of determination (R2) greater than 0.97, with the greatest values (0.99) obtained from the Modified Henderson and Pabis (4) and Midilli (5) models for all the evaluated drying conditions. It was observed that within the adjusted models, only the Midilli (5) model was able to satisfactorily represent the phenomenon of moisture removal from the product, considering that it presented appropriate values for SSE (estimated average error) and MRE (relative mean error). The lower the value of SSE, the greater the adjustment of the model to the observed data, since this index measures the error produced by the model in the same physical unit of the estimated variable (Botelho et al., 2018). Besides this, it is recommended that models able to represent the drying process present values for MRE less than 10%, considering that this value represents the deviation of the observed data due to the curve estimated by the model (Mohapatra and Rao, 2005). The fact that this model presents the best fit of the experimental data for the drying of the medicinal plants is presumably related to the
(9)
where O is the percentage of essential oil content on dry basis, om is the mass of oil extracted in grams, and dm is the dry mass of leaves used for the extraction of oil in grams. The oil obtained were solubilized in hexane for further analysis using gas chromatography coupled to mass spectrometry (SHIMADZU, model GCMS-QP 2010) equipped with a DB5-MS column (30.0 m long × 0.25 mm internal diameter ×0.25 μm thickness of film), heating ramp with initial temperature of 50 °C, reaching 280 °C at 3 °C min−1, and remaining at the final temperature for 10 min. Helium was used as a carrier gas in a flow of 1 mL min−1 and the injections were 1 μL in split mode (1:20). The temperatures of the injector, detector, and transfer line were 250 °C, 280 °C, and 200 °C, respectively. Scanning parameters of the mass spectrometer included a voltage electron impact ionization of 70 eV, mass ranging from 40 to 650 m z−1, and scanning interval of 0.3 s. In order to identify the analyzed substances, the retention indices, which were calculated using a series of linear alkanes (C14–C36, Sigma 3
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Table 2 Statistical parameters of the models adjusted to the drying curves of the Piper umbellatum L. leaves. 0.4 m s−¹ Models 40 °C 3 4 5 6 50 °C 3 4 5 6 60 °C 3 4 5 6 70 °C 3 4 5 6
0.7 m s−¹
SSE (decimal)
MRE (%)
R² (decimal)
SSE (decimal)
MRE (%)
R² (decimal)
0.026 0.009 0.010 0.029
26.309 6.912 8.744 27.578
0.992 0.999 0.998 0.990
0.031 0.007 0.007 0.029
9.668 2.126 2.227 8.474
0.984 0.999 0.999 0.986
0.022 0.009 0.011 0.023
20.154 2.857 9.982 20.960
0.994 0.999 0.998 0.993
0.060 0.024 0.018 0.048
31.277 21.796 7.785 37.897
0.948 0.994 0.996 0.974
0.033 0.010 0.008 0.024
46.155 17.571 6.695 35.273
0.987 0.998 0.999 0.993
0.012 0.010 0.010 0.028
7.592 3.148 6.247 22.901
0.998 0.999 0.999 0.991
0.061 0.015 0.025 0.046
64.656 12.147 3.642 41.962
0.962 0.998 0.997 0.977
0.037 0.012 0.026 0.042
12.317 8.548 8.259 33.482
0.987 0.999 0.994 0.981
rapid loss of moisture in the initial stages of the process for this type of product, generating a more pronounced drying curve better characterized mathematically by this model (Goneli et al., 2014). The Midilli model has been proposed by various investigators for representing the drying process of leaves among them (Alara et al., 2018; Babu et al., 2018; Nurafifah et al., 2018; Ashtiani et al., 2017, and Mghazli et al., 2017). The good fit of the model is evidenced by proximity of the experimental values with respect to the curve estimated by the model in all studied conditions (Figs. 1A and 2A), reinforcing its applicability in predicting drying data for P. umbellatum L. leaves for the studied data interval. It is observed that an increase in the temperature reduced the drying time, independently of the employed drying air velocity (Figs. 1A and 2A). To the leaves of P. umbellatum L. reached the moisture content of 0.11 (d.b.), it was necessary to use drying times of 12.5, 3.6, 3.0, and 1.5 h for temperatures of 40, 50, 60 and 70 °C, respectively, at drying air velocity of 0.4 m s−1, and drying times of 9.4, 3.1, 1.6, and 0.9 h for temperatures of 40, 50, 60 and 70 °C, respectively, at drying air velocity of 0.7 m s−1. This phenomenon has frequently been reported by various researchers for several agricultural products (Mghazli et al., 2018; Nurafifah et al., 2018; Ashtiani et al., 2017), and occurs due to the fact that an increase in the temperature of the drying air results in greater values of drying rate (Figs. 1B and 2B). It was observed that at the
beginning of the drying process, the removal of moisture from the leaves was more accentuated than that at the end of the process, independently of temperature and drying air velocity. This is presumably due to the fact that, during the drying process, superficial water evaporates first, given that it is affected more by the drying air velocity. Nevertheless, with the removal of superficial water, the evaporation front gradually moves to the innermost layers of the product, such that the effect of drying air velocity is minimized. This reinforces the process of liquid diffusion (Babalis et al., 2006), which is influenced more by the temperature of the drying air. The parameter “k” Midilli model presented in their values increase with increasing temperature of the drying air, which reflects the effect of the conditions external drying conditions, whereas the parameters “a,” “n,” and “b” did not indicate any defined trend (Table 3). The parameter "k" relates to the effective diffusivity in the process of drying kinetics in the descending period, in which liquid diffusion controls the process. Therefore, it can be used approximately to characterize the effect on the drying temperature (Babalis and Belessiotis, 2004). Therefore, as the magnitude of parameter “k” increases with an increase in the drying air temperature, the effective diffusivity also increases, that is, the larger the parameter “k”, the greater the effective diffusivity in the kinetic process for drying. The values for the effective diffusivity obtained during the drying of the P. umbellatum L. leaves, considering an average leaf thickness of 0.48 ± 0.02 mm, increased with the temperature (Table 3).
Fig. 1. Values for the moisture ratio, experimental and estimated by the Midilli (A) model; and drying rate (B) for the drying process of Piper umbellatum L. leaves at different temperatures and a drying air velocity of 0.4 m s−1. 4
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Fig. 2. Values for the moisture ratio, experimental and estimated by the Midilli (A) model; and drying rate (B) for the drying process of Piper umbellatum L. leaves at different temperatures and a drying air velocity of 0.7 m s−1.
the product, the faster should be the diffusion process in order to replace the lost moisture, which could be observed by an increase in values of the effective diffusion coefficient. The activation energy values, during the drying of medicinal plants, presented great variation, due to the fact that they were dependent on the temperature and velocities ranges of the air employed in the drying process. As a result, based on the studies of various authors (Doymaz and Karasu, 2018; Sousa et al., 2018; Ashtiani et al., 2017; Lamharrar et al., 2017; Mghazli et al., 2017), the activation energy values varied approximately from 20 to 80 kJ mol−1.
Table 3 Midilli model parameters and effective diffusion coefficient (Deff) for the different drying air velocity and temperatures for Piper umbellatum L. leaves. Temperature (ºC)
40 50 60 70 40 50 60 70
Deff x10−11 (m² s-¹)
Midilli model parameters a
k
n
b
0.955 0.979 0.982 1.619 1.001 0.981 0.990 0.993
0.157 0.344 0.780 0.864 0.021 0.621 1.099 1.391
1.060 0.899 1.011 0.833 0.601 1.032 0.985 0.903
−0.008 −0.129 −0.033 −0.725 −0.092 −0.025 −0.095 −0.209
0.468 1.616 2.000 2.617 0.291 1.365 3.061 4.505
3.2. Volatile substances in the essential oil The essential oil content in the dry leaves of P. umbellatum L. was greater for a temperature of 40 °C and an air velocity of 0.4 m s−1; as the drying air temperature increased, the essential oil content decreased (Fig. 3). An air velocity of 0.7 m s−1 presented a lower yield of essential oil content when compared to a velocity of 0.4 m s−1. This behavior was also observed by Karami et al. (2017) while evaluating the effect of the temperature and velocity of drying air on the essential oil content in the leaves of Mentha aquatica L. Argyropoulos and Müller (2014), study the effect of different drying air temperatures on the content of essential oil of Melissa officinalis L., suggest that high temperatures can break drying oil glands causing the rapid evaporation of the same. That way, as the increment of drying air temperature, occurs the reduction in the total content of essential oil of M. officinalis L. The analysis of essential oil helped to identify 28 substances
Nevertheless, it was observed that for a given temperature, the magnitude of the effective diffusion coefficient increased with an increase in the drying air velocity. This behavior can be attributed to the fact that an increase in this variable contributes to the rapid removal of superficial moisture on the product. The effective diffusivity is one of the most important indices used to evaluate the drying kinetics of agricultural products, considering that it allows for an evaluation and comparison of the drying velocity and its dependence on temperature (Botelho et al., 2018). The variations in this property imply changes during water diffusion in the capillaries of the agricultural products that, together with more intense vibration of the water molecules, contribute to a faster diffusion (Goneli et al., 2014). Eqs. 12 and 13 present the Arrhenius equation coefficients adjusted for the effective diffusion coefficients of pariparoba leaves, calculated according to Eq. 8.
Deff (0, 4 m s 1) = 7.62 × 10-4exp
Deff (0, 7 m s 1) = 134.038exp
48.519 RT
81.212 RT
(12) (13)
The activation energy for water diffusion during drying kinetics of the P. umbellatum L. leaves was 48.519 and 81.212 kJ mol−1 for velocities of 0.4 and 0.7 m s−1, respectively. It was observed that an elevation in the activation energy values with an increase in the drying air velocity, due to the ease with which the product moisture was evaporated with faster air velocity, consequently, increased the moisture diffusion process in the leaves. Moisture removal with increasing air drying velocity is a physical process that facilitate the removal of water vapor from the product surface. Thus, probably when air velocity is higher, moisture will be removed from the surface and the first layers of the product. The greater the removal of moisture from the surface and the first layers of
Fig. 3. Essential oil (Eo) content in the leaves of Piper umbellatum L. as a function of the temperature (T) and velocity of the drying air. 5
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Table 4 Chemical composition of the essential oils from fresh and dry leaves of Piper umbellatum L., obtained by GC–MS. R.T.
C.I.
L.I.
Substances
(%) fresh plant
Temperature (ºC) 40
7.09 7.58 9.04 9.54 9.76 10.32 10.49 12.94 13.43 15.35 21.63 27.63 28.13 29.69 29.85 30.50 30.65 31.19 31.56 33.10 33.57 33.66 33.90 35.48 36.10 36.39 36.56 37.89
920 946 986 1002 1003 1021 1024 1085 1095 1141 1248 1417 1430 1452 1462 1470 1481 1494 1510 1543 1550 1550 1563 1620 1626 1629 1638 1663
921 946 988 1.00 1.00 1.020 1.02 1.08 1.09 1.14 1.24 1.41 1.43 1.45 1.46 1.47 1.48 1.49 1.51 1.54 1.55 1.55 1.56 1.62 162 1.62 1.63 1.66
Tricyclene Camphene Myrcene α-phellandrene ρ-Mentha-1(7), 8-diene ρ-Cymene Sylvestrene Terpinolene Linalool Camphor Piperitone Caryophyllene β-Copaene α-Clovene Cadina-1(6),4-diene α-Macrocarpene α-Amorphene ϒ-Amorohene δ-Amorphene Sesquisabinene hydrate Muurol-5-em-4-β-ol Occidentalol E-Nerilidol Dill apoiole Cubenol Eremoligenol Cadinol Eudesmol
0.47 0.16 10.27 0.37 9.16 0.08 0.84 0.39 0.72 0.06 27.77 1.41 0.19 0.39 0.23 3.91 0.07 0.30 3.12 0.45 0.68 0.77 0.70 22.37 1.67 1.46 2.26 9.73
50
60
70
0.4
0.7
0.4
0.7
0.4
0.7
0.4
0.7
0.45 0.15 9.26 0.37 9.10 0.08 0.84 0.39 0.70 0.06 28.85 1.40 0.2 0.39 0.23 3.91 0.07 0.31 3.11 0.45 0.68 0.76 0.70 22.35 1.69 1.48 2.27 9.75
0.47 0.17 9.10 0.37 9.04 0.08 0.84 0.39 0.70 0.06 29.08 1.40 0.20 0.39 0.22 3.91 0.07 0.30 3.14 0.45 0.68 0.76 0.70 22.23 1.69 1.48 2.27 9.81
0.44 0.15 9.26 0.36 9.00 0.07 0.82 0.38 0.70 0.05 28.98 1.40 0.19 0.39 0.23 3.92 0.07 0.31 3.11 0.45 0.68 0.75 0.70 22.36 1.70 1.49 2.27 9.77
0.44 0.15 9.02 0.36 8.98 0.08 0.82 0.38 0.70 0.05 29.17 1.40 0.20 0.38 0.22 3.92 0.07 0.30 3.12 0.45 0.68 0.75 0.70 22.33 1.70 1.49 2.27 9.87
0.43 0.14 9.22 0.35 8.99 0.07 0.80 0.38 0.68 0.05 29.01 1.39 0.19 0.38 0.22 3.94 0.07 0.31 3.09 0.46 0.69 0.75 0.70 22.42 1.70 1.51 2.28 9.78
0.43 0.15 9.01 0.35 8.93 0.07 0.77 0.38 0.69 0.05 29.21 1.39 0.21 0.38 0.22 3.94 0.07 0.31 3.06 0.46 0.69 0.75 0.70 22.37 1.70 1.51 2.28 9.92
0.42 0.14 9.17 0.33 8.95 0.07 0.79 0.36 0.66 0.04 29.14 1.39 0.19 0.38 0.21 3.95 0.07 0.32 3.08 0.46 0.69 0.75 0.70 22.43 1.71 1.51 2.28 9.81
0.42 0.14 8.87 0.34 8.87 0.07 0.76 0.37 0.67 0.04 29.39 1.38 0.21 0.37 0.21 3.95 0.07 0.31 3.04 0.46 0,69 0.75 0.70 22.40 1.71 1.51 2.28 10.02
RT.: retention time in minutes, CI.: calculated index, and LI.: literature index.
Fig. 4. Multivariate analysis of the substances obtained from the essential oil for the Piper umbellatum L. leaves, both for the fresh and dry plant (A), and for the different drying conditions (B).
(Table 4), with piperitone, dill apiole, and myrcene being the three major substances, with contents of 27.7%, 22.7%, and 10.27%, respectively. Variation was observed in the percentage of constituents and the different drying conditions, with the greatest variation being for temperatures of 70 °C and air velocities equal to 0.7 m s−1. Moreover, it can be verified that the substances piperitone and eudesmol are increased with respect to the control (fresh plant), both for different temperatures and for various air drying velocity. Meanwhile, α-macrocarpene concentration increased at a speed of 0.7 m s−1, with α-macrocarpene showing this increase only at a temperature of 70 °C. Chao et al. (2017) suggested that the difference in performance (in yield) and isolated presence of substances could be significantly
improved by postharvest methods such as drying. During the evaluation of the composition of the essential oil of P. umbellatum L. in relation to drying, there was a decrease in the amount of monoterpenes found in the essential oil while there was an increase in the amount of sesquiterpenes. This change in composition may also be due to the loss of more volatile substances (monoterpenes) by volatilization due to the longer drying time. Sesquiterpenes increasing may probably be associated with the formation of new byproducts from the volatility of others (monoterpenes). Unsaturated substances can undergo photochemical addition cycle reactions, and these reactions are responsible for the formation of several products. These reactions are probably involved in the decomposition process of these substances, 6
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since they polymerize when there is exposure to air and light (Copolovici and Niinemets, 2015). The low variation in the content of these substances as a function of air temperature and velocity could be justified by the low intensity of tissue surface moisture evaporation that could be extremely weak with respect to an increase in the evacuation of these molecules to the surrounding air (Pirbalouti et al., 2013). It was observed that a group of substances obtained from the fresh leaves by steam distillation resembled the negative part of PC1 on the scoring chart, with a score of 78.03% (Fig. 4A). This marks a significant distance from the samples processed at different drying air velocities and temperatures. Furthermore, the differences could be separated in PC2 (score of 61.23%). This variation is primarily due to the differences in the quantity of metabolites present and in the increase in the levels of some metabolites, such as myrcene, considering that a difference exists when compared to the fresh plant; however, little difference was observed between the temperatures and drying methods. Regarding the use of different drying methods, a greater correlation was observed with air velocity at 0.7 m s−1, with the best temperatures identified at 40 °C and 50 °C (Fig. 4B). When analyzing the grouping of substances with respect to drying air velocity, temperature and oil content, it was confirmed that the fresh plant was found in the most negative portion of the PCA, with a score of 92.24% (Fig. 4A). and closer to the positive for PCA, with a score of 83.38% (Fig. 4B), demonstrating that, although the fresh plant has better conditions for oil extraction in terms of yield, the drying process analyzed in this study contributed. for maintaining P. umbellatum L. oil quality standards, confirming considerably that all temperature conditions were placed close to the positive axis (Fig. 4A and B). Therefore, the conditions of drying employed played important roles, and the concentrations of bioactive components can be improved from this study, since methods that improve the quality of herbs or functional foods are important to improve the consistency of the effect of the active principle.
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Influence of drying method and extraction variables on the antioxidant properties of persimmon leaves. Food Biosci. 6, 1–8. https://doi.org/10.1016/j.fbio.2014.01.002. Mghazli, S., Ouhammou, M., Hidar, N., Lahnine, L., Idlimam, A., Mahrouz, M., 2017. Drying characteristics and kinetics solar drying of Moroccan rosemary leaves. Renew. Energy 108, 303–310. https://doi.org/10.1016/j.renene.2017.02.022. Mohapatra, D., Rao, P.S., 2005. A thin layer drying model of parboiled wheat. J. Food Eng. 66, 513–518. https://doi.org/10.1016/j.jfoodeng.2004.04.023. Monteiro, M.R., Ambrozin, A.R.P., Lião, L.M., Boffo, E.F., Tavares, L.A., Ferreira, M.M.C., Ferreira, A.G., 2008. Study of brazilian gasoline quality using hydrogen nuclear magnetic resonance (1H NMR) spectroscopy and chemometrics. Energy Fuels 23, 272–279. https://doi.org/10.1021/ef800436p. Nurafifah, F., Chuah, L., Wahida, M.A.P.F., 2018. Drying of Plectranthus amboinicus (lour) spreng leaves by using oven dryer. Eng. Agric. Environ. Food 11, 239–244. https:// doi.org/10.1016/j.eaef.2018.08.002. Perea-Flores, M.J., Garibay-Febles, V., Chanona-Pérez, J.J., Calderón-Domínguez, G., Méndez-Méndez, J.V., Palacios-González, E., Gutiérrez-López, G.F., 2012. Mathematical modelling of castor oil seeds (Ricinus communis) drying kinetics in fluidized bed at high temperatures. Ind. Crops Prod. 38, 64–71. https://doi.org/10. 1016/j.indcrop.2012.01.008. Pirbalouti, A.G., Firoznezhad, M., Craker, M., Akbarzadeh, M., 2013. Essential oil compositions, antibacterial and antioxidant activities of various populations of Artemisia
4. Conclusions The mathematical model proposed by Midilli fits better with the experimental data, adequately representing the drying process of P. umbellatum L. leaves. The increase of drying air temperature and velocity promotes the amplification in the moisture reduction rate during the process as well as the effective values of the diffusion coefficient. The three main substances in the chemical composition of the essential oil of P. umbellatum L. leaves are piperitone, dill apiole and mircene. Lower the temperature and speed of the drying air, the higher the content of essential oils in the leaves. The different drying conditions used in this study did not influence the type of substances present in the essential oil of P. umbellatum L. Acknowledgments The authors thank the FUNDECT - Foundation to Support the Development of Education Science and Technology of Mato Grosso do Sul State, CNPq - National Council for Scientific and Technological Development and CAPES - Coordination for the Improvement of Higher Education Personnel, all funders of brazil, for the financial support the development and dissemination of this work. References Adams, R.P., 2007. Identification of Essential Oil Components by Gas Chromatography/ Mass Spectroscopy, 4th edition. Allured Publishing Corporation, Carol Stream 804 p. Alara, O.R., Abdurahman, N.R., Mudalip, S.K.A., Olalere, O.A., 2018. Mathematical modeling of thin layer drying using open sun and shade of Vernonia amygdalina leaves. Agric. Nat. Resour. 52, 53–58. https://doi.org/10.1016/j.anres.2018.05.013. Argyropoulos, D., Müller, J., 2014. Changes of essential oil content and composition during convective drying of lemon balm (Melissa officinalis L.). Ind. Crops Prod. 52,
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522–537. https://doi.org/10.1016/j.jep.2010.07.045. Silva, L.A., Resende, O., Virgolino, Z.Z., Bessa, J.F.V., Morais, W.A., Vidal, V.M., 2015. Drying kinetics and effective diffusivity in jenipapo sheets (Genipa Americana L.). Braz. J. Med. Plants 17https://doi.org/10.1590/1983-084X/14_106. 953-936. Sousa, A.D., Ribeiro, P.R.V., Canuto, K.M., Zocolo, G.J., Pereira, R.C.A., Fernandes, F.A.N., Brito, E.Sde., 2018. Drying kinetics and effect of air-drying temperature on chemical composition of Phyllanthus amarus and Phyllanthus niruri. Dry. Technol. 36, 609–616. https://doi.org/10.1080/07373937.2017.1351454. Tabaldi, L.A., Vieira, M.C., Zárate, N.A.H., Silva, L.Rda., Gonçalves, W.L.F., Pilecco, M., Formagio, A.S.N., Gassi, R.P., Padovan, M.P., 2012. Cover crops and their effects on the biomass yield of Serjania marginata plants. Ciência Rural 42, 614–620. https:// doi.org/10.1590/S0103-84782012000400006.
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Effect of air temperature and velocity on drying kinetics and essential oil composition of Piper umbellatum L. leaves
T
Luana do Nascimento Silveira Dornelesa, André Luís Duarte Gonelia,⁎, Claudia Andrea Lima Cardosob, Cristiane Bezerra da Silvaa, Michele Rosemari Hautha, Guilherme Cardoso Obaa, Vanderleia Schoeningera a b
Faculty of Agricultural Ciences, Federal University of Grande Dourados, PO Box: 533, 79.804-970, Dourados, MS, Brazil Natural Resources Study Center, Mato Grosso do Sul State University, Dourados, MS, Brazil
ARTICLE INFO
ABSTRACT
Keywords: Essential oil GC–MS Midilli model Medicinal plants
Piper umbellatum L. possesses diuretic, antimalarial, vermifuge, and anti-inflammatory properties, in addition to having essential oil in its leaves. Presuming that substances and essential oils in medicinal plants can be altered when they are subjected to various drying conditions, this study aimed to evaluate kinetic drying as well as the composition of essential oil from P. umbellatum L. leaves. The drying process was completed using four temperatures (40 °C, 50 °C, 60 °C, and 70 °C) and two drying air velocities (0.4 and 0.7 m s−1), being the drying process stopped when the moisture content of leaves was equal to 0.11 ± 0.01 dry basis (d.b.). The essential oil of the leaves was determined by hydrodistillation. The chemical components were analyzed by GC–MS. The Midilli model was the only one who represented satisfactorily product drying curves and the rise of temperature and drying air velocity resulted in the increase of the drying rate and in decreasing the content of essential oil from leaves. In total, 28 chemical substances were identified in the essential oil, with piperitone, dillapiole, and myrcene being the majorities. The obtained data indicated that the drying process maintain the quality patterns of the essential oils from the leaves; a slight alteration in the compound percentage was also observed.
1. Introduction Piper umbellatum L. is a perennial shrub native to the Americas and is widely used in traditional medicine in several countries. This is because several parts of this plant possess pharmacological properties, including antibacterial, antifungal, antioxidant, antimalarial, anti-inflammatory, analgesic, and antithermogenic features (Roersch, 2010; Agbor et al., 2012). Phytochemical studies on P. umbellatum L. confirm the presence of terpenes (mainly found in essential oils), alkaloids, flavonoids, sterols, and other classes of secondary metabolites (François et al., 2019). The physico-chemical attributes of aromatic and medicinal plants are determined in accordance with their moisture content. In general, after harvest, these plants display a moisture content of around 60–80%, a relatively high value that enables the development of harmful biological processes (Poós and Varju, 2017). Therefore, the aromatic and medicinal plants must be commercialized, consumed, or dried shortly after harvest. This is in order to minimize the loss of content and composition of the plant active ingredients. These losses
⁎
occur because harvesting initiates a degradation process due to the increase in moisture activity (Coradi et al., 2014). In this way, the drying process is an extremely vital step, since it consists in the removal of available water to safe levels, so that the enzymatic and microbial activities are interrupted. This consequently preserves the quality of the culture, which also results in an increase in the shelf life. Moreover, the drying process can contribute to the commercialization step, since drying results in the reduction in the weight and volume of medicinal plants, with positive effects on transport and storage (Prusinowska and Śmigielski, 2015; Karam et al., 2016). Conventional drying, also known as convective hot air drying, is a widely adopted technique in the food and pharmaceutical industry; however, this process can change the structure of the plants, affecting the phytochemicals due to thermal degradation (Martínez-Las Heras et al., 2014). The temperature of the drying air depends on the sensitivity of the plant active ingredients to heat as well as the moisture migration rate; that is, the higher the temperature used, the faster the drying process. However, the choice of the temperature must be performed very carefully, because if it is too high it can cause leaf surfaces
Corresponding author. E-mail address: [email protected] (A. Luís Duarte Goneli).
https://doi.org/10.1016/j.indcrop.2019.111846 Received 30 July 2019; Received in revised form 2 October 2019; Accepted 4 October 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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to burn (Poós and Varju, 2017). In addition, air drying temperature is also a determinant in the volatile substances loss that are part of the essential oil. This also influences the vapor pressure of the drying air, and consequently, the process itself. Therefore, it is an expected that particular temperature range allows smaller losses of essential oil at the end of the drying process (Borsato et al., 2005). Drying at low temperatures protects against the degradation of active ingredients; however, it is slow and the metabolic processes can continue for a longer duration. This can lead to the loss of quality of the aromatic plants and, subsequently, of the added value products. Therefore, the use of appropriate dryers, working with adequate values of temperature and velocity, contributes to preserving the quality of the final product. In contrast, while observing various methods used in the phytotherapeutic industries, it is evident that several quality control approaches are available for the medicinal plants. This makes it difficult to standardize the type of drying, being one of the main reasons for the heterogeneous quality of final products (Chao et al., 2017; Rocha et al., 2011). Specifically, the development of efficient drying techniques is essential in order to use the biomass produced by the plant and its properties in an ideal and effective manner, particularly considering the increasing demand and supply for medicinal plants (Tabaldi et al., 2012). Nevertheless, because each product has specific characteristics, it is necessary to obtain theoretical information regarding the drying methods and conditions for each product (Silva et al., 2015). This information is obtained by simulating drying kinetics, which is based on the definition of a mathematical equation that can effectively describe the system. The solution of these mathematical equations is presumed to allow the prediction of process parameters as a function of time at any point in the drying equipment (Avhad and Marchetti, 2016). Studying the drying kinetics is very important to get the best conditions of the drying process and to promote a better product quality after its completion. In addition, mathematical model adjustment for the drying process allows design engineers choose the most appropriate operating conditions and a better design of the dryers. (Perea-Flores et al., 2012). Thus, this study aims to evaluate the drying kinetics and the effects of various drying air temperatures and velocities on the chemical composition of essential oil from P. umbellatum L. leaves.
2.2. Sample drying
2. Materials and methods
2.3. Drying kinetics
2.1. Sample collection and preparation
During the drying process, the mass of the trays containing the samples was periodically checked. A digital scale with a resolution of 0.01 g was used. The time between the readings was controlled based on the differences in mass (gravimetric method, by knowing the initial mass and moisture content of the leaves), aiming to avoid significant variations in the moisture content between the readings. From previously defined moisture content, it was possible to control the time required to reach a product mass that corresponded to the stipulated moisture content, in order to achieve satisfactory observations during drying. The moisture ratio (MR) of the P. umbellatum L. leaves, while drying at different air conditions, was determined using Eq. 2.
The drying process was realized carried out in an experimental dryer comprising fixed bed (Goneli et al., 2016), which feature a heating source containing a set of electrical resistances (totaling 12 kW of power) and a Sirocco fan (Ibraum brand, model VSI-160, with a motor of 1 hp). The temperature was controlled using a process universal controller (Novus brand, model N1200), working with proportional-integral-derivative (PID) control, and the airflow was selected by means of a frequency inverter connected to the fan motor. The dryer is equipped with a system that precisely controlled the flow and temperature of the drying air and had a series of sensors connected to the control panel. The purpose here was to obtain a fine adjustment and to monitor drying air conditions. The drying bed consisted of four trays allocated in an experimental dryer preheated to the specific temperature of each drying treatment. Each of the trays contained 50 g of sheets with a 0.25 mm layer height. The drying air velocity was adjusted by the rotation of the motor fan, frequency inverter, until it reached the desired speed, being determined with the aid of a rotary blade thermo-anemometer (Instrutherm brand, model TAD 500), with resolution of ±0.1 ms−1. The P. umbellatum L. leaves were dried using air temperatures of 40 °C, 50 °C, 60 °C, and 70 °C and drying air velocities of 0.4 and 0.7 m s −1 . The drying process was carried out until the product attained the equilibrium moisture content. The initial dry basis (d.b.) moisture content of the leaves was 3.87 ± 0.30. In addition, for the mathematical modeling, the final moisture content of 0.11 ± 0.01 (d.b.). The moisture content of the samples was determined, in accordance with the gravimetric method recommended by ASABE (2007) for forage and other similar plants, using a kiln with forced air circulation at 103 ± 1 °C, for 24 h. The drying rate (DR) of the leaves during drying was determined by Eq. 1 and refers to the amount of water that a given product loses per unit of dry matter per unit of time.
DR = Ma 0
Mai
Dm (ti
t0 )
(1)
where Ma0 is the previous total moisture mass (kg); Mai is the present total moisture mass (kg), Dm is the dry matter mass (kg), t0 is the total previous drying time (h), and ti is the total present drying time (h).
The leaves of P. umbellatum L. were collected in the Medicinal Plant Growing Area of the Federal University of Grande Dourados-UFGD (Dourados, Mato Grosso do Sul, Brazil) where it had already been cultivated over the years, during the months of August and september. To avoid variations in the leaves initial moisture content, they were always collected from the aerial part of the bushes during the early hours of the morning and never after rainfall or irrigation. The fresh samples were packed in polyethylene bags and sent to the Pre-processing and storage laboratory of agricultural products (LAPREP/UFGD). For each drying condition evaluated in this study, about 400 g of leaves were collected in the median region of the plants, where they were in a fully developed secondary growth stage. Due to heterogeneity in fresh leaves size, homogenization was performed after collection to avoid interference with results during drying, started soon after harvest. The leaves that showed any kind of physical damage or signs of disease were eliminated. Eventually, 3 g of the collected material was separated to determine its moisture content and another part, approximately 50 g per repetition, was dried immediately after collection.
MR = Mt
Me
Mi
Me
(2)
where Mt is the moisture content of the product at a given time, Me is the equilibrium moisture content of the product, and Mi is the initial moisture content of the product, all in dry basis moisture content. Four mathematical models, traditionally used to regress the phenomenon of drying of agricultural products (Table 1), were adjusted for moisture ratio data obtained experimentally during leaf drying. 2
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Aldrich, purity ≥ 90%), were used to analyze the mass spectra compared to Adams (2007) and the equipment library (NIST21 and WILEY229). The peak area of each compound was determined via manual integration of each total ion chromatogram (TIC). Eventually, all areas were transformed into relative percentage areas.This method is considered safe since the fragmentation patterns of each substance is demonstrated through the NIST library, and compared with each substance obtained in the generated chromatogram This method is considered safe since the fragmentation patterns of each substance is demonstrated through the NIST library, and compared with each substance obtained in the generated chromatogram.
Table 1 Mathematical models adjusted to the drying curves of the Piper umbellatum L. leaves. Models
Equations
Diffusion approximation Modified Henderson and Pabis
MR = a exp(-k θ) + (1 - a) exp(-k b θ) MR = a exp(-k θ) + b exp(-k0 θ)+c exp (-k1 θ) MR = a exp(-k θn) + b θ MR = exp(-k θn)
Midilli Page
(3) (4) (5) (6)
where θ is the drying time (h), k, ko, and k1 are the drying constants (h−1), and a, b, c, and n are the model coefficients.
2.6. Statistical analysis
2.4. Effective diffusivity and activation energy
The experimental data of drying kinetics were submitted to nonlinear regression analysis by the Gauss–Newton algorithm. To analyze the degree of fit of each model, the magnitudes of the adjusted coefficient of determination (R2), mean relative error (MRE), and standard error of estimate of moisture (SSE) were considered, and the behavior of the distribution of the residual, s, was verified. The values of the relative mean error (P) and standard deviation of the estimate (SE) were calculated according to:
The effective diffusion coefficient for the different drying air temperatures (40, 50, 60 and 70 °C) was calculated using Eq. 7, based on the theory of net diffusion. This equation is the analytical solution for Fick’s second law, considering the geometrical shape of the product approximately as a flat plate and with approximation of eight terms.
MR =
8 2
n =0
1 exp -(2n + 1)² ²Deff (2n+1) 2 4L²
(7)
2 −1
where Deff is the effective diffusivity (m s ), θ is the drying time (s), L is the product thickness, and (n) is the model term number. The thickness of the P. umbellatum L. leaves was measured using a digital caliper with a resolution of 0.01 mm. Fifty fresh leaves were measured, performing three measurements on each one of them in different areas, following which the mean measured value was calculated. In order to evaluate the influence of temperature on the effective diffusion coefficient, Arrhenius equation was used and described as follows:
Deff = Do exp
Ea RT
MRE = 100 N
SSE =
MRpre
N i=1
(MR exp
MRpre )
MRexp
(10)
2
Df
(11)
where N is the number of experimental observations, MRexp is the experimental moisture ratio, MRpre is the predicte moisture ratio, and Df is the degrees of freedom. The analysis of the main components was completed using Paretoscaled variables for statistical multivariate principal component analysis (PCA). Two chemometric matrices were evaluated for each activity: first, the yield values were interpreted to delineate the generic behavior of each drying curve against the air velocities used; second, the data from each parameter were evaluated to specify a better temperature for the drying air. Specifically, the PCA was completed by preprocessing the self-adjusted averages with varied scales, to which the same variant weight was assigned (Brandão et al., 2013; Monteiro et al., 2008).
−1
where Do is the Arrhenius factor for the drying process, (m s ), Ea is the activation energy (kJ mol−1), R is the universal gas constant (8.314 kJ kmol−1 K−1), and T is the absolute temperature (K). 2.5. Obtaining the essential oil and chemical analysis Fresh and dry leaves separately were subjected to hydrodistillation for 4 h in a Clevenger. The mass obtained of the essential oil was evaluated in relation mass of the plant. The essential oil (O) content of pariparoba leaves was calculated by the following equation:
O= om dm
MRexp
i=1
(8) 2
N
3. Results and discussion 3.1. Drying kinetics Table 2 presents the results obtained from the analysis of the models for drying the leaves of P. umbellatum L. leaves. It was observed that the models adjusted to the experimental data presented values for the coefficient of determination (R2) greater than 0.97, with the greatest values (0.99) obtained from the Modified Henderson and Pabis (4) and Midilli (5) models for all the evaluated drying conditions. It was observed that within the adjusted models, only the Midilli (5) model was able to satisfactorily represent the phenomenon of moisture removal from the product, considering that it presented appropriate values for SSE (estimated average error) and MRE (relative mean error). The lower the value of SSE, the greater the adjustment of the model to the observed data, since this index measures the error produced by the model in the same physical unit of the estimated variable (Botelho et al., 2018). Besides this, it is recommended that models able to represent the drying process present values for MRE less than 10%, considering that this value represents the deviation of the observed data due to the curve estimated by the model (Mohapatra and Rao, 2005). The fact that this model presents the best fit of the experimental data for the drying of the medicinal plants is presumably related to the
(9)
where O is the percentage of essential oil content on dry basis, om is the mass of oil extracted in grams, and dm is the dry mass of leaves used for the extraction of oil in grams. The oil obtained were solubilized in hexane for further analysis using gas chromatography coupled to mass spectrometry (SHIMADZU, model GCMS-QP 2010) equipped with a DB5-MS column (30.0 m long × 0.25 mm internal diameter ×0.25 μm thickness of film), heating ramp with initial temperature of 50 °C, reaching 280 °C at 3 °C min−1, and remaining at the final temperature for 10 min. Helium was used as a carrier gas in a flow of 1 mL min−1 and the injections were 1 μL in split mode (1:20). The temperatures of the injector, detector, and transfer line were 250 °C, 280 °C, and 200 °C, respectively. Scanning parameters of the mass spectrometer included a voltage electron impact ionization of 70 eV, mass ranging from 40 to 650 m z−1, and scanning interval of 0.3 s. In order to identify the analyzed substances, the retention indices, which were calculated using a series of linear alkanes (C14–C36, Sigma 3
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Table 2 Statistical parameters of the models adjusted to the drying curves of the Piper umbellatum L. leaves. 0.4 m s−¹ Models 40 °C 3 4 5 6 50 °C 3 4 5 6 60 °C 3 4 5 6 70 °C 3 4 5 6
0.7 m s−¹
SSE (decimal)
MRE (%)
R² (decimal)
SSE (decimal)
MRE (%)
R² (decimal)
0.026 0.009 0.010 0.029
26.309 6.912 8.744 27.578
0.992 0.999 0.998 0.990
0.031 0.007 0.007 0.029
9.668 2.126 2.227 8.474
0.984 0.999 0.999 0.986
0.022 0.009 0.011 0.023
20.154 2.857 9.982 20.960
0.994 0.999 0.998 0.993
0.060 0.024 0.018 0.048
31.277 21.796 7.785 37.897
0.948 0.994 0.996 0.974
0.033 0.010 0.008 0.024
46.155 17.571 6.695 35.273
0.987 0.998 0.999 0.993
0.012 0.010 0.010 0.028
7.592 3.148 6.247 22.901
0.998 0.999 0.999 0.991
0.061 0.015 0.025 0.046
64.656 12.147 3.642 41.962
0.962 0.998 0.997 0.977
0.037 0.012 0.026 0.042
12.317 8.548 8.259 33.482
0.987 0.999 0.994 0.981
rapid loss of moisture in the initial stages of the process for this type of product, generating a more pronounced drying curve better characterized mathematically by this model (Goneli et al., 2014). The Midilli model has been proposed by various investigators for representing the drying process of leaves among them (Alara et al., 2018; Babu et al., 2018; Nurafifah et al., 2018; Ashtiani et al., 2017, and Mghazli et al., 2017). The good fit of the model is evidenced by proximity of the experimental values with respect to the curve estimated by the model in all studied conditions (Figs. 1A and 2A), reinforcing its applicability in predicting drying data for P. umbellatum L. leaves for the studied data interval. It is observed that an increase in the temperature reduced the drying time, independently of the employed drying air velocity (Figs. 1A and 2A). To the leaves of P. umbellatum L. reached the moisture content of 0.11 (d.b.), it was necessary to use drying times of 12.5, 3.6, 3.0, and 1.5 h for temperatures of 40, 50, 60 and 70 °C, respectively, at drying air velocity of 0.4 m s−1, and drying times of 9.4, 3.1, 1.6, and 0.9 h for temperatures of 40, 50, 60 and 70 °C, respectively, at drying air velocity of 0.7 m s−1. This phenomenon has frequently been reported by various researchers for several agricultural products (Mghazli et al., 2018; Nurafifah et al., 2018; Ashtiani et al., 2017), and occurs due to the fact that an increase in the temperature of the drying air results in greater values of drying rate (Figs. 1B and 2B). It was observed that at the
beginning of the drying process, the removal of moisture from the leaves was more accentuated than that at the end of the process, independently of temperature and drying air velocity. This is presumably due to the fact that, during the drying process, superficial water evaporates first, given that it is affected more by the drying air velocity. Nevertheless, with the removal of superficial water, the evaporation front gradually moves to the innermost layers of the product, such that the effect of drying air velocity is minimized. This reinforces the process of liquid diffusion (Babalis et al., 2006), which is influenced more by the temperature of the drying air. The parameter “k” Midilli model presented in their values increase with increasing temperature of the drying air, which reflects the effect of the conditions external drying conditions, whereas the parameters “a,” “n,” and “b” did not indicate any defined trend (Table 3). The parameter "k" relates to the effective diffusivity in the process of drying kinetics in the descending period, in which liquid diffusion controls the process. Therefore, it can be used approximately to characterize the effect on the drying temperature (Babalis and Belessiotis, 2004). Therefore, as the magnitude of parameter “k” increases with an increase in the drying air temperature, the effective diffusivity also increases, that is, the larger the parameter “k”, the greater the effective diffusivity in the kinetic process for drying. The values for the effective diffusivity obtained during the drying of the P. umbellatum L. leaves, considering an average leaf thickness of 0.48 ± 0.02 mm, increased with the temperature (Table 3).
Fig. 1. Values for the moisture ratio, experimental and estimated by the Midilli (A) model; and drying rate (B) for the drying process of Piper umbellatum L. leaves at different temperatures and a drying air velocity of 0.4 m s−1. 4
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Fig. 2. Values for the moisture ratio, experimental and estimated by the Midilli (A) model; and drying rate (B) for the drying process of Piper umbellatum L. leaves at different temperatures and a drying air velocity of 0.7 m s−1.
the product, the faster should be the diffusion process in order to replace the lost moisture, which could be observed by an increase in values of the effective diffusion coefficient. The activation energy values, during the drying of medicinal plants, presented great variation, due to the fact that they were dependent on the temperature and velocities ranges of the air employed in the drying process. As a result, based on the studies of various authors (Doymaz and Karasu, 2018; Sousa et al., 2018; Ashtiani et al., 2017; Lamharrar et al., 2017; Mghazli et al., 2017), the activation energy values varied approximately from 20 to 80 kJ mol−1.
Table 3 Midilli model parameters and effective diffusion coefficient (Deff) for the different drying air velocity and temperatures for Piper umbellatum L. leaves. Temperature (ºC)
40 50 60 70 40 50 60 70
Deff x10−11 (m² s-¹)
Midilli model parameters a
k
n
b
0.955 0.979 0.982 1.619 1.001 0.981 0.990 0.993
0.157 0.344 0.780 0.864 0.021 0.621 1.099 1.391
1.060 0.899 1.011 0.833 0.601 1.032 0.985 0.903
−0.008 −0.129 −0.033 −0.725 −0.092 −0.025 −0.095 −0.209
0.468 1.616 2.000 2.617 0.291 1.365 3.061 4.505
3.2. Volatile substances in the essential oil The essential oil content in the dry leaves of P. umbellatum L. was greater for a temperature of 40 °C and an air velocity of 0.4 m s−1; as the drying air temperature increased, the essential oil content decreased (Fig. 3). An air velocity of 0.7 m s−1 presented a lower yield of essential oil content when compared to a velocity of 0.4 m s−1. This behavior was also observed by Karami et al. (2017) while evaluating the effect of the temperature and velocity of drying air on the essential oil content in the leaves of Mentha aquatica L. Argyropoulos and Müller (2014), study the effect of different drying air temperatures on the content of essential oil of Melissa officinalis L., suggest that high temperatures can break drying oil glands causing the rapid evaporation of the same. That way, as the increment of drying air temperature, occurs the reduction in the total content of essential oil of M. officinalis L. The analysis of essential oil helped to identify 28 substances
Nevertheless, it was observed that for a given temperature, the magnitude of the effective diffusion coefficient increased with an increase in the drying air velocity. This behavior can be attributed to the fact that an increase in this variable contributes to the rapid removal of superficial moisture on the product. The effective diffusivity is one of the most important indices used to evaluate the drying kinetics of agricultural products, considering that it allows for an evaluation and comparison of the drying velocity and its dependence on temperature (Botelho et al., 2018). The variations in this property imply changes during water diffusion in the capillaries of the agricultural products that, together with more intense vibration of the water molecules, contribute to a faster diffusion (Goneli et al., 2014). Eqs. 12 and 13 present the Arrhenius equation coefficients adjusted for the effective diffusion coefficients of pariparoba leaves, calculated according to Eq. 8.
Deff (0, 4 m s 1) = 7.62 × 10-4exp
Deff (0, 7 m s 1) = 134.038exp
48.519 RT
81.212 RT
(12) (13)
The activation energy for water diffusion during drying kinetics of the P. umbellatum L. leaves was 48.519 and 81.212 kJ mol−1 for velocities of 0.4 and 0.7 m s−1, respectively. It was observed that an elevation in the activation energy values with an increase in the drying air velocity, due to the ease with which the product moisture was evaporated with faster air velocity, consequently, increased the moisture diffusion process in the leaves. Moisture removal with increasing air drying velocity is a physical process that facilitate the removal of water vapor from the product surface. Thus, probably when air velocity is higher, moisture will be removed from the surface and the first layers of the product. The greater the removal of moisture from the surface and the first layers of
Fig. 3. Essential oil (Eo) content in the leaves of Piper umbellatum L. as a function of the temperature (T) and velocity of the drying air. 5
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Table 4 Chemical composition of the essential oils from fresh and dry leaves of Piper umbellatum L., obtained by GC–MS. R.T.
C.I.
L.I.
Substances
(%) fresh plant
Temperature (ºC) 40
7.09 7.58 9.04 9.54 9.76 10.32 10.49 12.94 13.43 15.35 21.63 27.63 28.13 29.69 29.85 30.50 30.65 31.19 31.56 33.10 33.57 33.66 33.90 35.48 36.10 36.39 36.56 37.89
920 946 986 1002 1003 1021 1024 1085 1095 1141 1248 1417 1430 1452 1462 1470 1481 1494 1510 1543 1550 1550 1563 1620 1626 1629 1638 1663
921 946 988 1.00 1.00 1.020 1.02 1.08 1.09 1.14 1.24 1.41 1.43 1.45 1.46 1.47 1.48 1.49 1.51 1.54 1.55 1.55 1.56 1.62 162 1.62 1.63 1.66
Tricyclene Camphene Myrcene α-phellandrene ρ-Mentha-1(7), 8-diene ρ-Cymene Sylvestrene Terpinolene Linalool Camphor Piperitone Caryophyllene β-Copaene α-Clovene Cadina-1(6),4-diene α-Macrocarpene α-Amorphene ϒ-Amorohene δ-Amorphene Sesquisabinene hydrate Muurol-5-em-4-β-ol Occidentalol E-Nerilidol Dill apoiole Cubenol Eremoligenol Cadinol Eudesmol
0.47 0.16 10.27 0.37 9.16 0.08 0.84 0.39 0.72 0.06 27.77 1.41 0.19 0.39 0.23 3.91 0.07 0.30 3.12 0.45 0.68 0.77 0.70 22.37 1.67 1.46 2.26 9.73
50
60
70
0.4
0.7
0.4
0.7
0.4
0.7
0.4
0.7
0.45 0.15 9.26 0.37 9.10 0.08 0.84 0.39 0.70 0.06 28.85 1.40 0.2 0.39 0.23 3.91 0.07 0.31 3.11 0.45 0.68 0.76 0.70 22.35 1.69 1.48 2.27 9.75
0.47 0.17 9.10 0.37 9.04 0.08 0.84 0.39 0.70 0.06 29.08 1.40 0.20 0.39 0.22 3.91 0.07 0.30 3.14 0.45 0.68 0.76 0.70 22.23 1.69 1.48 2.27 9.81
0.44 0.15 9.26 0.36 9.00 0.07 0.82 0.38 0.70 0.05 28.98 1.40 0.19 0.39 0.23 3.92 0.07 0.31 3.11 0.45 0.68 0.75 0.70 22.36 1.70 1.49 2.27 9.77
0.44 0.15 9.02 0.36 8.98 0.08 0.82 0.38 0.70 0.05 29.17 1.40 0.20 0.38 0.22 3.92 0.07 0.30 3.12 0.45 0.68 0.75 0.70 22.33 1.70 1.49 2.27 9.87
0.43 0.14 9.22 0.35 8.99 0.07 0.80 0.38 0.68 0.05 29.01 1.39 0.19 0.38 0.22 3.94 0.07 0.31 3.09 0.46 0.69 0.75 0.70 22.42 1.70 1.51 2.28 9.78
0.43 0.15 9.01 0.35 8.93 0.07 0.77 0.38 0.69 0.05 29.21 1.39 0.21 0.38 0.22 3.94 0.07 0.31 3.06 0.46 0.69 0.75 0.70 22.37 1.70 1.51 2.28 9.92
0.42 0.14 9.17 0.33 8.95 0.07 0.79 0.36 0.66 0.04 29.14 1.39 0.19 0.38 0.21 3.95 0.07 0.32 3.08 0.46 0.69 0.75 0.70 22.43 1.71 1.51 2.28 9.81
0.42 0.14 8.87 0.34 8.87 0.07 0.76 0.37 0.67 0.04 29.39 1.38 0.21 0.37 0.21 3.95 0.07 0.31 3.04 0.46 0,69 0.75 0.70 22.40 1.71 1.51 2.28 10.02
RT.: retention time in minutes, CI.: calculated index, and LI.: literature index.
Fig. 4. Multivariate analysis of the substances obtained from the essential oil for the Piper umbellatum L. leaves, both for the fresh and dry plant (A), and for the different drying conditions (B).
(Table 4), with piperitone, dill apiole, and myrcene being the three major substances, with contents of 27.7%, 22.7%, and 10.27%, respectively. Variation was observed in the percentage of constituents and the different drying conditions, with the greatest variation being for temperatures of 70 °C and air velocities equal to 0.7 m s−1. Moreover, it can be verified that the substances piperitone and eudesmol are increased with respect to the control (fresh plant), both for different temperatures and for various air drying velocity. Meanwhile, α-macrocarpene concentration increased at a speed of 0.7 m s−1, with α-macrocarpene showing this increase only at a temperature of 70 °C. Chao et al. (2017) suggested that the difference in performance (in yield) and isolated presence of substances could be significantly
improved by postharvest methods such as drying. During the evaluation of the composition of the essential oil of P. umbellatum L. in relation to drying, there was a decrease in the amount of monoterpenes found in the essential oil while there was an increase in the amount of sesquiterpenes. This change in composition may also be due to the loss of more volatile substances (monoterpenes) by volatilization due to the longer drying time. Sesquiterpenes increasing may probably be associated with the formation of new byproducts from the volatility of others (monoterpenes). Unsaturated substances can undergo photochemical addition cycle reactions, and these reactions are responsible for the formation of several products. These reactions are probably involved in the decomposition process of these substances, 6
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since they polymerize when there is exposure to air and light (Copolovici and Niinemets, 2015). The low variation in the content of these substances as a function of air temperature and velocity could be justified by the low intensity of tissue surface moisture evaporation that could be extremely weak with respect to an increase in the evacuation of these molecules to the surrounding air (Pirbalouti et al., 2013). It was observed that a group of substances obtained from the fresh leaves by steam distillation resembled the negative part of PC1 on the scoring chart, with a score of 78.03% (Fig. 4A). This marks a significant distance from the samples processed at different drying air velocities and temperatures. Furthermore, the differences could be separated in PC2 (score of 61.23%). This variation is primarily due to the differences in the quantity of metabolites present and in the increase in the levels of some metabolites, such as myrcene, considering that a difference exists when compared to the fresh plant; however, little difference was observed between the temperatures and drying methods. Regarding the use of different drying methods, a greater correlation was observed with air velocity at 0.7 m s−1, with the best temperatures identified at 40 °C and 50 °C (Fig. 4B). When analyzing the grouping of substances with respect to drying air velocity, temperature and oil content, it was confirmed that the fresh plant was found in the most negative portion of the PCA, with a score of 92.24% (Fig. 4A). and closer to the positive for PCA, with a score of 83.38% (Fig. 4B), demonstrating that, although the fresh plant has better conditions for oil extraction in terms of yield, the drying process analyzed in this study contributed. for maintaining P. umbellatum L. oil quality standards, confirming considerably that all temperature conditions were placed close to the positive axis (Fig. 4A and B). Therefore, the conditions of drying employed played important roles, and the concentrations of bioactive components can be improved from this study, since methods that improve the quality of herbs or functional foods are important to improve the consistency of the effect of the active principle.
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4. Conclusions The mathematical model proposed by Midilli fits better with the experimental data, adequately representing the drying process of P. umbellatum L. leaves. The increase of drying air temperature and velocity promotes the amplification in the moisture reduction rate during the process as well as the effective values of the diffusion coefficient. The three main substances in the chemical composition of the essential oil of P. umbellatum L. leaves are piperitone, dill apiole and mircene. Lower the temperature and speed of the drying air, the higher the content of essential oils in the leaves. The different drying conditions used in this study did not influence the type of substances present in the essential oil of P. umbellatum L. Acknowledgments The authors thank the FUNDECT - Foundation to Support the Development of Education Science and Technology of Mato Grosso do Sul State, CNPq - National Council for Scientific and Technological Development and CAPES - Coordination for the Improvement of Higher Education Personnel, all funders of brazil, for the financial support the development and dissemination of this work. References Adams, R.P., 2007. Identification of Essential Oil Components by Gas Chromatography/ Mass Spectroscopy, 4th edition. Allured Publishing Corporation, Carol Stream 804 p. Alara, O.R., Abdurahman, N.R., Mudalip, S.K.A., Olalere, O.A., 2018. Mathematical modeling of thin layer drying using open sun and shade of Vernonia amygdalina leaves. Agric. Nat. Resour. 52, 53–58. https://doi.org/10.1016/j.anres.2018.05.013. Argyropoulos, D., Müller, J., 2014. Changes of essential oil content and composition during convective drying of lemon balm (Melissa officinalis L.). Ind. Crops Prod. 52,
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