Agronomía Colombiana

Preparation of the samples

Fresh chicory roots (Cichorium intybus L.) were obtained from a local farmer from Rosario, Santa Fe, Argentina, during the autumn. The samples were subjected to drying using a convective drying oven (Tecno Dalvo, Model CHC/F/I, Argentina) and a vacuum dryer (ORL, Argentina). Each subsequently dried sample was ground using a dry blade mill (IKA, Germany) and stored under refrigeration in vacuum-sealed packaging. The resultant powdered samples were subjected to sieving to segregate particles that passed through an ASTM 40 sieve, utilizing a Ro-Tap sieve shaker (Tyler, USA). A particle diameter statistic was computed, with 0.26 mm as the mean.

The drying process was carried out in a convective oven and under vacuum. A mathematical model was used to represent the extraction process, incorporating considerations for the drying method and its associated parameters (drying temperature and air velocity or vacuum pressure) and the extraction variables (temperature, hydroalcoholic solvent composition, solid-liquid ratio, and agitation velocity). Consequently, the model established a connection between the operational parameters of both primary unit operations to attain polyphenol-enriched extracts. A series of experimental runs were conducted to determine the mass transfer coefficients. Subsequently, an independent set of experimental runs was employed to validate the proposed model and the calculated mass transfer coefficients. Lastly, the model was optimized to maximize extraction yield. This optimization process yielded potential operating conditions suitable for scaling up the drying and extraction unit operations.

Extraction of phenolic compounds

An experimental design was carried out to study the influence of various drying and extraction variables on the yields of extractions rich in polyphenols. A fractional factorial design was chosen, considering 6 factors and 2 levels for each factor. Consequently, each design comprised 16 individual experimental runs, elucidated in Table 1.

The ranges of the selected variables for the extraction process were aligned with prior studies conducted by other researchers who had extracted polyphenolic compounds from diverse vegetable sources (Jokić et al., 2010; Pinelo et al., 2005; Teffane et al., 2021). The drying temperature range of 60-80°C is reported by Figueira et al. (2004) as suitable for retaining bioactive compounds in chicory roots, further validated in a previous study by Balzarini et al. (2018). The levels of extraction temperature were set at 25°C and 50°C to ensure the stability of polyphenols (Bouchez et al., 2020; Cissé et al., 2012), while the ratios of solvent to flour and the concentrations of ethanol were determined based on those yielding superior extraction efficiencies (Bouchez et al., 2020; Carciochi et al., 2018; Das & Bera, 2013; Dzharov et al., 2016).

Table 1.: Fractional factorial experimental design for air forced drying.

All extraction runs were executed employing the precise weight of dried chicory root flour dictated by the experimental design, accompanied by 600 ml of the hydroalcoholic ethanol mixture. A batch extractor within a thermostatic bath (Lauda, Alpha A6, Germany) was equipped with continuous agitation using a propeller agitator with an extraction duration of 90 min. Samples of 5 ml were taken at previously defined time intervals. They were filtered and stored in opaque containers at 3°C ± 1°C.

Total phenolic content (TPC) determination

The Folin-Ciocalteu method with modifications (Boroski et al., 2015) was used to determine polyphenolic compounds in samples of hydroethanolic extract of chicory roots. A 250 µl aliquot of the sample was combined with 250 µl of the Folin-Ciocalteu reagent. After 3 min, 500 µl of a saturated Na₂CO₃ solution (20%) was added. The reaction was allowed to proceed in the dark for 120 min, and the absorbance was subsequently measured at 725 nm. The results were expressed as mg of gallic acid equivalent (GAE) per 100 g of dry sample (mg 100 g^-1 db), using a calibration curve (R²=0.998). Total phenolic content was reported as the mean ± standard deviation, and measurements were performed in triplicate.

Initial phenolic content (TPC_o) determination

The initial polyphenol content within the chicory root flours (C_p0) was evaluated following the approach presented by Tao et al. (2014), which included specific changes. According to tests, a 50% hydroalcoholic mixture of ethanol was selected as the extraction solvent due to its high efficiency. To initiate the process, 10 g of chicory root flour sample was combined with 400 ml of the aqueous ethanol solution in a 600 ml beaker. The exhaustive extraction of polyphenols was conducted at 50°C with continuous agitation for 48 h. Subsequently, the resulting extract was filtered. Then, the chicory root flours were added to the beaker, and an additional 100 ml of 50% ethanolic solution was introduced. The mixture was treated at 50°C while being agitated for 4 h, followed by another round of filtration. Ultimately, the two filtrates were combined, and the TPC was ascertained utilizing the methodology elaborated in the preceding section.

DPPH radical scavenging activity determination

The 2,2-diphenyl-1-picrylhydrazyl (DPPH) method described by Shimada et al. (1992) was used. One ml extract was added to 5 ml of DPPH solution of 0.1 mM. The mixture was shaken for 30 s and allowed to stand for 50 min. Absorbance was measured at 517 nm using a spectrophotometer (UV-1800, Shimadzu, Japan). All samples were tested in triplicate. The results were expressed as the average value ± the standard deviation. The DPPH scavenging activity was determined using Equation 1.

Statistical analysis

An analysis of variance (ANOVA) was performed, and Duncan's New Multiple Range test was used (P≤0.05). The SPSS Statistical Analysis Program for Windows (SPSS Inc., Chicago, IL, USA) was used.

Mathematical model

The phenomenological description of the extraction process has undergone extensive discourse in the literature (Crossley & Aguilera, 2007; Garcia-Perez et al., 2010; Kostic et al., 2019; Popescu et al., 2013). In our research, the extraction model was initially employed to compute mass transfer parameters. Subsequently, they were subjected to experimental validation. Subsequently, the mathematical model was integrated with the preceding drying phase to optimize extraction yield while accounting for both drying alternatives. It is worth noting that this model does not aim to determine the superior alternative. Such a determination will be addressed in subsequent research endeavors involving assessing cost functions. Specifically, regarding extraction modeling, it is posited that the solvent permeates the solid to dissolve the extractable components, which diffuse from within the solid into the surrounding bulk liquid. This model considers the diffusion process limiting (Cheung et al., 2013). The model considers the following assumptions based on Fick's second law:

• Every particle was considered spherical, symmetrical, and homogeneous. So, the uniform initial distribution of the active compounds in the matrix was taken;

• The polyphenolic diffusion path was assumed only in the radial direction;

• Only the diffusion of polyphenolics was taken under study;

• The rate of diffusion of polyphenolics from the solid was independent of the time, but it depended on the temperature, explained by Arrhenius equation;

• A perfect mixing between flour and solvent was considered;

• The convective mechanism of transfer was considered from the particle surface to the solvent bulk phase;

• There are no chemical reactions or thermal degradation of the bioactive compounds in the working temperature range.

Equations

Fick's law was implemented to explain the mass transfer of polyphenols within particles using spherical coordinates in one direction and considering the assumptions:

where (mg ml^-1) is the polyphenol concentration inside the particle and (m² s^-1) is the diffusivity coefficient of polyphenols within each particle. is the solvent volume fraction; is the spherical radial coordinate (m), is the time(s), and is the particle radius (m).

In this model, the diffusion coefficient of polyphenols within each particle, D_p,β, was obtained with the Arrhenius functionality:

where D₀ is the Arrhenius factor in m² s^-1, R represents the universal gas constant in kJ mol ^-1K^-1, T_e is the absolute extraction temperature in K, and E_a is the activation energy of the polyphenol diffusion in kJ mol^-1.

The fraction of solvent volume, denoted as ε, was defined according to Equation 4, in which were the volumes of the solid particle and the solvent phase, respectively.

The initial condition was represented by Equation 5, assuming homogeneous initial polyphenol concentration within the particles.

The drying process impacts the concentration of polyphenols due to thermal degradation (Shad et al., 2013). Consequently, distinct initial concentrations were attained based on the drying method and conditions elucidated in Table 2.

Equation 6 expressed the boundary condition for the particle center considering no mass transfer. The other necessary boundary condition was represented by Equation 7 for the interfacial polyphenols flux, where was the mass transfer coefficient in the solvent phase, was the interfacial polyphenol concentration and was the concentration in the bulk solvent.

The equilibrium correlation between polyphenolic concentrations in both phases was depicted by Equation 8, assuming a diluted solution:

where K was the distribution constant.

The mass transfer coefficient k_p,γ was computed using Equations 9 to 12, which are correlations applicable to fluidized beds of spheres within the Reynolds number range of 2-2,000 (Geankoplis, 1993).

where S_h, S_c and R_e are Sherwood, Schmit, and Reynolds numbers, respectively.

Table 2.: Mass transfer parameters root mean square error and R2 values.

The diffusion coefficient of polyphenols in the hydroalcoholic phase, denoted as D_p,γ was evaluated employing the correlation introduced by Wilke and Chang (1955), as depicted by Equation 13:

where φ, MW_Y, µ_Y, V_m,p were solvent association parameters, molecular weight (kDa) and viscosity (kg m^-1 s^-2) of the solvent phase, and molar volume of polyphenols (m³ kmol^-1).

Finally, Equation 14 resumes the mass transfer balance for the whole system:

The extraction yield, denoted as Y, depended on the liquid-solid ratio, the ethanol concentration used as the extracting solvent, and the initial polyphenol concentration. This efficiency is characterized by Equation 15 for the concluding extraction duration, t_e, quantifying the mass of extracted polyphenols from the mass of polyphenols initially present in the chicory root flour:

The partial differential equations were discretized using the central finite difference method (CFDM) and an implicit scheme. Equations 16 and 17 defined the interval width for the radial (Δr) and temporal grids (Δt) with M = 7 and N = 10.

where G_R and G_t were the number of grid intervals in the radial coordinate and intervals in the temporal grid.

The resolution of the partial differential equations gave the local value of the polyphenol concentration. Local concentrations within the particles were integrated using Simpson's rule to calculate average polyphenol concentrations, according to Equation 18:

The root mean square error (RMSE) minimization function was used as an objective function to solve the model. It corresponds to the sum of the differences between experimental and theoretical data.

The GAMS (General Algebraic Modeling System) program and the CONOPT tool were used to implement and solve the model. We obtained 2,283 variables and 2,269 restrictions.

Estimation of mass transfer parameters

Table 2 presents mass transfer parameter values. D_p,β, k_p,γ and D_p,γ were calculated by Equations 4, 10, and 13, respectively, and K was estimated as a model parameter.

Figure 1: Description of the mathematical model of extracting polyphenolic compounds from chicory root flour

The diverse microstructures generated by the drying treatments lead to distinct internal diffusion pathways within the particles. These differences are evident in the variations observed in the internal diffusion coefficients. Remarkably, during the extraction process, polyphenolic compounds exhibited more rapid diffusion from vacuum-dried samples than from air-forced dried samples, even when subjected to the same extraction conditions (Aravindakshan et al., 2021). A lower diffusion coefficient was obtained for convective drying.

The diffusion coefficient of polyphenols, D_p,β, exhibits an increment with rising extraction temperatures (Chaiklahan et al., 2014; Nova et al., 2023; Thaisamak et al., 2019; Vallejo-Castillo et al., 2021). This augmentation was attributed to the molecule enhanced internal energy and increased mobility, leading to a reduction in dynamic viscosity. The activation energy values yielded by the model ranged from 20.3 to 22.4 kJ mol^-1 for extractions from air-forced convection-dried samples and from 0.7 to 3.5 kJ mol^-1 for vacuum-dried samples. As presented in Table 2, the highest D_p,β values were observed for a bath temperature of 50°C and with an ethanol concentration of 50% in the extraction solvent (P≤0.05), regardless of the drying method. Notably, the distribution constant exhibited higher values for samples dried within the vacuum chamber, indicating a heightened extent of polyphenol extraction under these conditions. The polyphenol diffusion coefficients obtained in this study were similar to those reported by other authors for plant matrices. Chaiklahan et al. (2014) conducted extractions of bioactive compounds at different temperatures, with values that range from 1.07 × 10⁻¹² m² s^-1 at 50°C to 3.02 × 10⁻¹² m² s^-1 at 90°C. Aramburu et al. (2020) report diffusivity values of the same order (6.97 × 10⁻¹² m² s^-1 at 25°C).

Regarding the mass transfer coefficients of the solvent phase of Equation 10, the model provides consistent operational conditions for the extraction phase, regardless of the drying technique applied. Thus, k_p,γ is affected by agitation velocity, temperature, and the hydroalcoholic extraction mixture, while the diffusion coefficient, D_p,γ hinges on the latter two factors, as evaluated in Equation 13. These associations are detailed in Table 2.

The diffusion coefficient of total polyphenols in the phase of the solvent, the mass transfer coefficient in the solvent phase, k_p,γ, and the distribution constant, K, all exhibited similar upward trends. Similarly, elevated values for the mass transfer parameters were observed at a bath temperature of 50°C and when using an extraction solvent containing 50% ethanol concentration. The mass transfer coefficient demonstrated responsiveness to agitation velocity, with higher values observed as agitation velocity increased. Consequently, higher mass transfer rates are achieved using heightened agitation velocity during extraction, elevated temperatures, and utilization of a 50% ethanol concentration within the extraction solvent. This observation aligns with published studies concerning the extraction of bioactive compounds in soybeans and certain fruits (Jokić et al., 2010; Velić et al., 2011; Zhou et al., 2017).

Model validation

The polyphenol concentrations from a subset of 12 experimental runs were compared with the predicted values, employing the mass transfer parameters previously determined in the model. RMSE and R² were calculated to assess the model predictive efficacy, obtaining values ranging between 0.002-0.013 and 0.957-0.997.

Figure 2 shows the discrepancy in the polyphenol extraction contents for samples from different drying methods. Graphs A-B and C-D correspond to samples dried in their forced convection chamber and the vacuum chamber but submitted to the same extraction conditions.

The confidence band (CB) and prediction band (PB) for total phenol contents are also presented in Figure 2. It should be noted that PB is the area where 95% of the experimental data points are expected, where all the obtained observations lie within this area. Similarly, CB is the area where 95% of the regression line was expected, which contains more than 50% of the experimental values for all experiences reported here. The obtained CB and PB fit the experimental data points well, increasing the confidence in the model's predictions. Standard probability plots of the residuals for the different experimental runs were also shown in Figure 2 (E and F). The data points above and below the line are evenly distributed, ensuring that they are typically distributed and that there are no undesirable trends or correlations between them.

The initial phenolic content of the samples dried using the air-forced convection chamber was (451.03 - 645.04) mg GAE 100 g^-1 d.b., and for the vacuum dryer they were (805.05 - 1344.31) mg GAE 100 g^-1 d.b. The higher polyphenol content observed with vacuum drying can be attributed to the lower operational pressures, which reduce the boiling point of water and allow for drying at lower temperatures. This minimizes the thermal degradation of polyphenols, which are sensitive to heat, thus preserving a more significant amount of these bioactive compounds. The vacuum conditions create an environment where moisture can be removed efficiently without exposing the samples to high thermal stress, aligning with observations reported in the literature (Shad et al., 2013; Wang et al., 2003).

The effects of the extraction parameters (hydroalcoholic solvent mixture, temperature, agitation velocity, and solid-liquid ratio) at the final time were examined in Figure 3. For this analysis, the drying process conditions were maintained at the lowest air temperature, air velocity, and absolute vacuum pressure values (60°C, 0.2 m s^-1, and 25 mm Hg).

The influence of the ethanol content on TPC is depicted in Figure 3A. The outcomes proved to be statistically significant (P≤0.05). For extracts derived from chicory roots subjected to both conventional and vacuum drying, the highest values were 428.515 ± 7.059 and 745.909 ± 4.531 mg GAE 100 g^-1 d.b., employing a solvent concentration of 50% (v/v). Additionally, for an ethanol content of 70% (v/v), the corresponding values were 335.454 ± 2.349 and 698.518 ± 2.282 mg GAE 100 g^-1 d.b. These findings align with the data of Thach et al. (2017) and Zhou et al. (2017).

The effect of extraction temperature on TPC was examined at 25°C and 50°C (Fig. 3B). The greatest phenolic compound concentration was achieved at 50°C, with a significant difference observed (P≤0.05). The elevation of temperature contributed to an augmented TPC, possibly attributed to the heightened diffusion coefficient leading to enhanced solubility of polyphenols in the solvent (Sarkar & Ghosh, 2017).

Figure 2.: Experimental and predicted variation of the total polyphenols content (TPC) in the solvent phase for dehydrated samples using dried in the air-forced convection chamber (A and B) and vacuum chamber (C and D). Standard probability plots of residuals for different extraction operating conditions (E and F). C, convective; v, vacuum; Te, extraction temperature; ve, agitation velocity.

Figure 3C demonstrated a noteworthy effect of agitation velocity (P≤0.05) on the extracted TPC compounds within the hydroalcoholic bath. The results are consistent with those reported by Teffane et al. (2021). Agitation extraction techniques and velocity significantly influence total phenolic extraction (Sarkar & Ghosh, 2017; Teffane et al., 2021).

The effect of the liquid-to-solid ratio on the extraction of total polyphenolic compounds from ground chicory root is presented in Figure 3D, comparing ratios of 20:1 and 30:1. The highest TPC extraction was achieved with a ratio of 20:1 (P≤0.05). It is widely established that the interaction between the solvent and the solid matrix significantly influences extraction efficiency. Adequate solvent volume is essential to facilitate effective hydration and swelling of the solid phase, ultimately leading to improved recovery yield. Across all cases, parameter values were consistently higher for extracts obtained from chicory root flour subjected to vacuum drying.

Figure 3.: Effects of hydroalcoholic solvent mixture (A), temperature (B), agitation velocity (C), and solid-to-liquid ratio (D) on total polyphenol content (TPC) extraction from chicory roots floor. Values are expressed as mean ± SD. Different lower-case letters (a-d) represent significant differences between values according to Duncan's New Multiple Range test (P≤0.05). v v-1, volume volume-1; ve1, agitation velocity (0.55 m s-1); ve2, agitation velocity (1.10 m s-1).

The DPPH radical scavenging capacities are presented in Table 3. The maximum antioxidant activity (P≤0.05) was observed in samples subjected to vacuum drying at 60°C and 25 mm Hg absolute pressure. Elevated antioxidant activity was also evident at a dehydration temperature of 80°C. This phenomenon could be attributed to the development of Maillard reaction compounds, which enhance the antioxidant potential of chicory root flours dried at air temperatures of 80°C or above. Maillard reaction products contain electron donors and hydroxyl groups that function as reducing agents by providing hydrogen atoms to neutralize free radicals, thereby augmenting the overall antioxidant activity of the food (Vhangani & Van Wyk, 2016).

Table 3.: DPPH of hydroalcoholic extracts of chicory roots dehydrated at 60°C and 80°C by conventional and vacuum drying. Different letters indicate that the values are significantly different according to Duncan's New Multiple Range tests (P≤0.05).

DPPH (2,2-diphenyl-1-picrylhydrazyl).

Optimization model

The validated model maximized the extraction yield (% of dry weight or mg GAE g^-1 sample). This study facilitated a comparison of operational strategies between the two drying methods and an analysis of their impact on subsequent extraction stages.

The drying method and extraction operating conditions were considered optimization variables in the optimization model, enhancing the model degree of freedom compared to the validation model. Additionally, the initial concentrations of total polyphenols (C_p0) for the extraction using the drying method were integrated into the model using Equations 19 and 20. These equations represent response surfaces derived from experimental data as a function of the drying process operating conditions.

The appropriateness of the model linear response surfaces (Equations 19 and 20) was evaluated using the adjusted R² equations, yielding the subsequent values: Adj R² = 0.986 and R² = 0.977 for forced convection drying, and Adj R² = 0.999 and R² = 0.998 for vacuum drying. In this study, the ethanol concentration was maintained at 50%.

The optimization model was subjected to Equations 2 to 20, incorporating the objective function of maximizing the yield of total polyphenol extraction:

Under the objective function of Equation 21, the maximum extraction yields achieved are 63.48% and 71.19% for air-forced and vacuum drying, respectively. These optimal yields are attained by applying the same extraction operating conditions regardless of the drying method. These conditions encompass the highest extraction temperature (50°C), agitation velocity (1.1 m s^-1), solvent/flour ratio (30 ml g^-1), and maximum extraction time (90 min).

The optimal solution selected dried samples with a higher initial polyphenol concentration, obtained by employing lower air temperature, absolute vacuum pressure, or air velocity during the drying process (60°C and 25 mm Hg or 0.2 m s^-1). As a result, achieving maximum yields requires heightened requirements in the extraction stage, involving a higher agitation speed (1.1 m s^-1) and the maximum solvent-to-flour ratio (30 ml g^-1). The optimal extraction temperature was also consistently resolved at the upper limit (50°C), enhancing the mass transfer rate.

This outcome stems from the extraction efficiency being significantly improved with increased agitation velocity and temperature, both of which approached their upper bounds due to technological constraints.

The optimization results underscored the significant impact of several processing variables on polyphenol extraction yields from both the drying and extraction stages. Further analyses involving operational and investment costs are essential to establish a balanced solution that strikes a compromise between quality and costs.