Adsorption and desorption characteristics of epigallocatechin-3-gallate from discarded green tea leaves on macroporous resin

doi:10.21203/rs.3.rs-4353625/v1

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Adsorption and desorption characteristics of epigallocatechin-3-gallate from discarded green tea leaves on macroporous resin

https://doi.org/10.21203/rs.3.rs-4353625/v1

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Green tea (Camellia sinensis) is intensely consumed all over the world and tea leaves discarded from production are a rich source of catechins, especially epigallocatechin-3-gallate (EGCG). This study aimed to perform preparative separation of EGCG from green tea waste by using macroporous resin and to reveal adsorption and desorption characteristics. Nine types of resins were compared for their adsorption and desorption capacities and desorption rate of EGCG, and NKA-2 was found the most suitable resin for the purpose. Adsorption isotherms were evaluated at 25°C, 35°C and 45°C. Experimental data was well described with pseudo-second order kinetics model and fitted best to the Langmuir model in tested temperatures. In dynamic separation process, 83% of adsorbed EGCG was recovered from the resin by using 70% ethanol. It has been thought that using macroporous resin can be an effective way of EGCG separation from green tea waste for commercial purposes.

Epigallocatechin-3-gallate

Green tea

Macroporous resin

Adsorption

Kinetics

Tea (Camellia sinensis L.) is one of the most popular beverages in the world (Deka et al. 2021). It is widely used in food, beverage and nutraceuticals due to its versatility in use (Xu et al. 2021). There are many reports on green tea ingredients and their health-promoting effects, particularly with antioxidant, antimutagenic, anticarcinogenic and antiviral activities (Jin et al. 2015; Sun et al. 2018; Meneses et al. 2021; Ahammed et al. 2023). This significant contribution to health is attributed to compounds called catechins, and they are recommended to be taken with daily diet (Musial et al. 2020; Meneses et al. 2021). The main role of catechins in the plant is providing it against to UV radiation of sunlight (Wei et al. 2011). In past studies based on this point, they were found bioavailable in the skin by green tea consumption and provide a protection against to UV radiation-induced inflammation (Clarke et al. 2016; Kapoor et al. 2021). In addition to all, some beneficial effects of catechins were reported on the protection of cognitive function against to neurodegenerative diseases (Gu et al. 2018). The catechins constitute in the ratio of 60–80% of tea polyphenols as major bioactive group (Deka et al. 2021; Sun et al. 2018). Among these compounds, epigallocatechin-3-gallate (EGCG) is one of the most important tea catechins (Musial et al. 2020; Ahammed et al. 2023), besides being the most abundant (Sun et al. 2018). In recent years, healthy foods have been promoted to greater interest, and food formulas are fortified with bioactive compounds to satisfy growing demand. It has been showed that catechins led by EGCG can be utilized in food systems such as bread (Pan et al. 2022), cakes, biscuits, ice cream, sausages, and soft drinks in order to increase the functionality of the product (Lee et al. 2013). However, the pharmaceutical industry is also interested in EGCG due to its high potential in preventing diseases. A feasible EGCG separation process is needed for industrial operations due to its low availability in plants and high production cost (Jin et al. 2015). Availability and ease-in-supply of pure EGCG could expedite clinical trials on its health-promoting effects (Wang et al. 2012a).

Tea is basically produced from young green shoots of the plant (Liu et al. 2020). Old leaves and pruned parts turn into soil despite their rich bioactive content (Arafat et al. 2020; Liu et al. 2020). Hence, only a miserable amount of the leaves has commercial importance while tons of them are discarded as "green waste" (Zhang et al. 2019a). According to 2022 report of Food and Agriculture Organization of the United Nations (FAO), worldwide tea leaves production was estimated more than 44 million tons (FAO, 2024). Considering the massive production volume, discarded tea leaves give a problem for economic sustainability. Utilization of the leaves may help saving on food sources while protecting the ecological environment (Liu et al. 2014). There are various methods used in the separation of the phenolics, including EGCG. Inorganic ion precipitation and solvent extraction are long-established techniques used in EGCG separation but they require using high amount of solvent or inorganic salts (Jin et al. 2015). Eco-friendly and greener practices are needed in ECG purification since organic solvents are toxic chemicals (Zhao et al. 2008). Additionally, these methods present low efficiency in the process (Jin et al. 2015) and low purity product (Yang et al. 2015). In previous reports, gel chromatography and preparative HPLC techniques were also used to extract the epicatechins from peanuts and fresh apple. However, their application was not suitable for EGCG separation from persimmon due to irreversible absorption and poor resolution (Peng et al. 2018). Supercritical CO₂ extraction (Sökmen et al. 2018) and high-speed counter-current chromatography (Peng et al. 2018) are commonly used methods to extract bioactive compounds from tea in recent years. Unfortunately, high equipment and production costs limit their application to industrial operations (Wang et al. 2012b; Jin et al. 2015). In recent years, adsorbent resins have attracted researchers' attention to recovering bioactive compounds from plant extracts (Yang et al. 2015). The use of resins stands out with ease-in-recovery, being economical and non-toxic process (Sevillano et al. 2014). Besides exhibiting high adsorption capacity, they have a stable structure which makes them a convenient equipment for long-term and multiple uses (Yang et al. 2015).

Considering the tremendous amount of tea waste, discarded leaves may be a good source for feasible EGCG separation. The main objective of this study was to investigate the adsorption and desorption characteristics of EGCG from discarded green tea leaves on macroporous resins. The most suitable resin was selected between nine kinds of macroporous resins for EGCG separation. Adsorption capacity, desorption rates and isotherms were evaluated according to results obtained by kinetic and thermodynamic calculations. It is expected to provide a guidance to the food and pharmaceutical industry for the separation of EGCG from discarded green tea leaves.

Materials and reagents

Green tea leaves (Camellia sinensis L.) pruned below the two leaves following the apical bud were used as discarded leaves in the study. They were harvested from gardens in Rize province (Turkey), in October and transferred to the laboratory immediately. Ethanol (99.5%) was obtained from Tekkim (Bursa, Turkey). Analytical grade methanol (99.9%) was purchased from Sigma-Aldrich Co. (St. Louis, MO, USA) while acetic acid (99.5%) was from Carlo-Erba (Milano, Italy). Analytical standards of (–)-epigallocatechin-3-gallate (EGCG), (–)-epicatechin gallate (ECG), (–)-epigallocatechin (EGC), (–)-epicatechin (EC) and caffeine (CAF) were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA).

The macroporous resins of AB-8, H-103, NKA-2, NKA-9 and X-5 were purchased from Chemical Plant affiliated to Nankai University (Tianjin, China). Other adsorbents (XAD7HP, XAD16N, DAX-8 and HP2-MG) were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA). The properties of the adsorbent resins were specified by manufacturers and summarized in Table 1.

Table 1

Physical properties of macroporous resins used.
Resins	Polarity	Matrix material	Particle diameter (mm)	Surface area (m²/g)	Average pore diameter (A°)
HP2-MG	Polar	Polymethacrylate	0.56–0.71	≈ 500	170
NKA-2	Polar	Acrylamide	0.30–1.25	160–200	145–155
NKA-9	Polar	Acrylamide	0.30–1.25	250–290	155–165
DAX-8	Semi-polar	Acrylic ester	0.56–0.71	140	225
XAD7HP	Semi-polar	Acrylic	0.56–0.71	380	300–400
AB-8	Weak-polar	Styrene-divinylbenzene	0.30–1.25	480–520	130–140
XAD16N	Non-polar	Styrene-divinylbenzene	0.56–0.71	800	200
X-5	Non-polar	Styrene-divinylbenzene	0.30–1.25	500–600	290–300
H-103	Non-polar	Styrene-divinylbenzene	0.30–1.25	1000–1100	85–95

Instruments and equipment

The extracts were clarified using Thermo Scientific SL 16R centrifuge (Waltham, WA, USA). Caffeine, EGCG and other catechins found in green tea extract were determined by using high-performance liquid chromatography (HPLC) system (Shimadzu, Kyoto, Japan) directly equipped with a Lichrospher RP18 reverse-phase column (250 mm × 4.6 mm, 5 µm), an autosampler (SIL-20A HT), a column oven (CTO-20A), a degasser system (DGU-20A5), a gradient pump (LC-20AD), a UV-visible detector (SPD-M20A) and a software package (LC solution). A Sartorius orbital shaker incubator (Darmstadt, Germany) was used for mixing resins well with the solution in adsorption and desorption trials.

Methods

Extraction of catechins from green tea leaves

Extraction was performed according to directions stated by Vuong et al. (2013). Briefly, tea leaves were subjected to water steam for 30 s to inactivate oxidizing enzymes. They were dried in a vacuum oven at 70°C until reaching a constant weight. All fragments were grounded and downscaled by using a blender and then sieved into < 1 mm particle size with a stainless-steel sieve (Endocotts; London, England). Grounded leaves (100 g) were placed into a beaker containing 1.2 L of water, and held at 80°C for 30 min. It was filtered through Whatman no.1 filter paper, and the sediment was brewed in 800 mL of water once again. The extracts were combined right after the brewing and filtering process. It was clarified with centrifugation at 3000 xg, at 4°C for 5 min. The extracts were filtered through by the filter paper and stored in the dark at + 4°C until use. Samples taken for polyphenol and caffeine analysis were passed through 0.45 µm nylon syringe filter and transferred to amber-colored HPLC vials for further analysis.

Determination of catechins in the extract

A volume of 20 µL sample was injected into the HPLC column and compounds were monitored at 278 nm using UV-visible detector. 0.5% (v:v) acetic acid in ultrapure water (A) and analytical grade methanol (B) were applied for compound separation at 30°C. Gradient elution was set according to phase (B) as following: linear gradient from 80–70% in 0–15 min, from 70–65% in 15–27 min, from 65–80% in 27–35 min, and isocratic flow at 80% of B for 5 min; at a constant flow rate of 1 mL min^–1. Quantification was achieved by using a calibration curve obtained from five-point serial dilutions of the analytical standards.

Pretreatment of adsorbent resins

The resins were soaked in 99.5% ethanol for 24 h and washed with distilled water to remove impurities. They were dried in oven at 70°C and stored at + 4°C by tightly sealed boxes until use. All resins were dipped in ethanol for overnight and rinsed with distilled water once again before using (Jin et al. 2015).

Adsorption and desorption capacities

0.5 g (dry weight, dw) of pretreated resins were weighed into 250-mL Erlenmeyer flasks and 100 mL of green tea extract (827.3 µg mL^–1 EGCG) was added over. The flasks were sealed with cotton plugs and left to orbital shaker incubator at 25°C and 120 rpm for 24 h. At the end of time, resins were separated by filtration and washed with distilled water. Subsequently, resins were dipped into 100 mL of ethanol (70%) and left for desorption in the same conditions as adsorption (Jin et al. 2015).

Selectivity of the resins was determined according to adsorption capacity (Q_e, mg g^–1 dry resin) (Eq. 1) and desorption capacity (Q_d, mg g^–1 dry resin) (Eq. 2) at equilibrium, and desorption rate (D, %) (Eq. 3) obtained by following equations:

Q _e = $\frac{\left({C}_{0}- {C}_{e}\right)}{W} \times {V}_{e}$ (1)

Q _d = $\frac{{C}_{d} \times {V}_{d}}{W}$ (2)

D = $\frac{{C}_{d} \times {V}_{d}}{({C}_{0}- {C}_{e}) \times {V}_{e}} \times 100$ (3)

where C₀ and C_e are initial and equilibrium concentrations of EGCG (mg mL^–1), respectively. W indicates the weight of dry resin (g). V_d refers to the volume of desorption solution while V_e is the volume of the extract (mL). C_d indicates EGCG concentration (mg mL^–1) in the desorption solution.

Adsorption kinetics

The selected resin (0.5 g, dw) was pretreated and placed into 250-mL flask which included 100 mL of tea extract (containing 567.5 µg mL^–1 EGCG). It was incubated at 25°C, for 5 h with 120 rpm orbital shaking (Jin et al. 2015). Aliquot (1 mL) samples were taken from flask at different time intervals and EGCG amounts were monitored by HPLC. Results were evaluated according to pseudo-first (Eq. 4) and pseudo-second order models (Eq. 5) to reveal static adsorption kinetics (Shin and Kim 2016).

$${ln} \left({Q}_{e}-{Q}_{t}\right)= {ln}{Q}_{e}- {k}_{1}t$$

$$\frac{t}{{Q}_{t}}=\frac{1}{{k}_{2} {Q}_{e}^{2} }+ \frac{1}{{Q}_{e}} t$$

where, Q_e and Q_t are amount of EGCG adsorbed (mg g^–1) at equilibrium and any time (t, min), respectively. k₁ and k₂ are the rate constants of pseudo-first and pseudo-second order models, respectively.

Adsorption isotherms

EGCG concentrations ranging between 149.8-827.3 µg mL^–1 were used for plotting adsorption isotherm curves at 25°C, 35°C and 45°C. The activated resins (0.5 g, dw) and six aliquots of 100 mL extract solutions were mixed in 250-mL flasks. They were left to incubation for 3 h, at 120 rpm shaking. Initial and equilibrium concentrations of EGCG were determined by using HPLC. The obtained results were examined according to Langmuir (1918) and Freundlich (1907) models to reveal adsorption characteristics in given temperatures.

The Langmuir model can be figured as given formula:

$${Q}_{e}=\frac{{Q}_{m}.{K}_{L}.{C}_{e}}{1+ {K}_{L}.{C}_{e}}$$

The equilibrium value (R_L) can be stated by the following equation:

$${R}_{L}=\frac{1}{1+{K}_{L}.{C}_{0}}$$

The Freundlich model can be calculated through the following formula:

$${Q}_{e}= {K}_{F}.{C}_{e}^{1/n}$$

where, Q_e denotes adsorption capacity (mg g^–1) and C_e refers to EGCG concentration (mg mL^–1) at equilibrium. K_L and K_F are the constants of each model, respectively. C₀ is the highest initial EGCG concentration (mg mL^–1) used in kinetic trials. 1/n is the empirical constant related to adsorption driving force; Q_m is the empirical constant defining maximum adsorption capacity (mg g^–1 dry resin).

The evaluation of R_L is done as follows: irreversible (= 0), favorable adsorption (between 0–1), linear (= 1), unfavorable adsorption (> 1). Similarly, 1/n value can be expressed as follows: irreversible (= 0), favorable adsorption (between 0–1), unfavorable adsorption (> 1) (Park et al. 2021).

Thermodynamic parameters

Thermodynamic parameters were evaluated by estimating the change in Gibbs free energy (∆G), enthalpy (∆H) and entropy (∆S). ∆G (kj mol^–1) was calculated by using Eq. 9, while ∆H (kj mol^–1) and ∆S [j (mol.K) ^–1] were obtained from Van't Hoff equation (Eq. 10) (Shin and Kim 2016):

$$\varDelta G=-RT{ln}{K}_{L}$$

$${ln}{K}_{L}=\frac{\varDelta S}{R}-\frac{\varDelta H}{RT}$$

where, K_L is the constant of Langmuir model (Eq. 6). R refers to universal gas constant [8.314 j (mol.K) ^–1] whereas T indicates the absolute temperature (K).

Dynamic adsorption and desorption

Dynamic adsorption and desorption trials were carried out on a lab-scale glass column (15 mm i.d. × 200 mm height). The column was packed with 15 g (dw) of the selected resin. Bed volume (BV) was approximately 19 mL and a total of 30 BV tea extract (567.5 µg mL^–1 EGCG) flowed through the column at a flow rate of 2.38 mL min^–1. Elution coming from column-out was collected into tubes at time intervals of 8 min. The adsorbate-laden column was rinsed with 3 BV of distilled water before desorption process. Desorption was performed by using 20 BV of 70% ethanol. The flow rate and sampling time intervals were kept same as for the adsorption process. Non-adsorbed and desorbed EGCG contents were monitored by HPLC system.

Statistical analysis

Results were expressed as means followed by standard deviation. Statistical analysis was performed by using IBM SPSS 16.0 package program (SPSS Inc., Chicago, IL, USA). Comparison between test units was carried out using one-way analysis of variance (ANOVA), and Tukey’s test was used for comparison of the means at a significance level of p < 0.05.

Polyphenolic and caffeine contents

Green tea extract was analyzed for its caffeine and polyphenolic content. Caffeine was found at the level of 848.0 ± 23.3 mg L^–1 in green tea extract (which was equal to 1695.9 mg 100 g^–1 green tea, dw). EGCG was determined as major bioactive compound in the extract with an amount of 1654.5 ± 130.8 mg L^–1 (equal to 3309.0 mg 100 g^–1 green tea, dw). EGC, EC and ECG content of the extract were at levels of 854.7 ± 24.2, 299.5 ± 7.9 and 213.2 ± 6.8 mg L^–1, respectively. In past studies, EGCG was stated as the most abundant catechin type in green tea while EC was the least between those of catechins (Ayyildiz et al. 2018; El-Shahawi et al. 2012). EGCG content of green tea, which was harvested from Rize (Turkey) province in the summer season, was found 3.46 g 100 g^–1 in a past study (Ayyildiz et al. 2018). Results were compatible with those of previous literature reports.

Approximately 30% of commercially harvested tea is discarded from the processing due to being low quality. Its bioactive compounds are almost the same with commercial ones, in fact (Wang et al. 2012b). However, El-Shahawi et al. (2012) emphasized that EGCG amount in various tea samples showed a wide range distribution from 101 to 4330 mg 100 g^–1, dw. Catechin composition of the tea leaves may differ depending on leaf age (Liu et al. 2020), harvest season (Xu et al. 2012; Deka et al. 2021), climatic conditions and soil specifications (Ahammed et al. 2023). Further, non-prime green teas which are picked in summer and fall have higher EGCG content than spring flush (Xu et al. 2012; He et al. 2022). One or more factors mentioned above may be the reason of high EGCG content of the autumn tea used in the present study. The leaf samples were found suitable for waste valorization with their substantial EGCG content.

Selection of macroporous resin

Adsorption and desorption characteristics of phenolics depend on the interactions between the resin, target molecule and solvent (Wang et al. 2020). "Like dissolves like" is a well-known phenomenon in organic chemistry (Wan et al. 2014; Liu et al. 2016). EGCG has a versatile chemical structure that includes non-polar benzene rings, polar hydroxyl and carboxyl groups (Jin et al. 2015). This makes it a convenient compound that allows the use of many types of resins. Therefore, nine macroporous resins with different physical and chemical structures were investigated for EGCG separation from tea extract.

The adsorption capacity of NKA-2 resin (71.6 ± 1.7 mg g^–1 dry resin) was significantly (p < 0.05) higher than the others (Fig. 1a). Resins with high surface area are expected to perform higher adsorption capacity as they provide more space to be adsorbed (Liu et al. 2016). Nevertheless, H-103, X-5 and XAD16N, which are all non-polar resins, conversely adsorbed moderate or low amounts of EGCG. Thus, it can be noted that polar interactions play a significant role in EGCG adsorption. Phenolic compounds are adsorbed onto macroporous resin via hydrogen bonding or physical Van der Waals force (Wang et al. 2020). The abundance of hydroxyl groups in EGCG can simplify hydrogen bonding with resin (Wan et al. 2014; Jin et al. 2015). On the other hand, XAD7HP performed well-adsorption capacity following after NKA-2. Affinity of EGCG on non-polar resins may be attributed to π-π conjugation via benzene rings and relatively bigger pore size of the resins. It is worth noting that small pore diameter may be a restrictive factor in adsorption process. Limited adsorption capacity on H-103 resin may be due to blockage of the pores by target molecules.

Desorption rates were found satisfactory (> 85%) in all types of resins. 70% ethanol may have simplified the desorption of EGCG from the resins as Park and Lee (2021) stated. The highest desorption rates were obtained from HP2-MG (98.1%), NKA-9 (97.2%) and NKA-2 (96.2%) resins. Although it was slightly higher in HP2-MG and NKA-9, the difference was not significant (p > 0.05). Moreover, using NKA-9 resin would cause wasting of EGCG due to low adsorption capacity. Considering the both adsorption and desorption trials, NKA-2 was found the most suitable resin for the purpose and thus, further experiments were carried out on this resin.

Adsorption kinetics

Besides determining the highest level of product adsorbed, it is very important when EGCG concentration reaches at equilibrium between the resin and extract solution. Adsorption rates were examined at 25°C for 5 h and it showed a rapid increase within first 10 min (Fig. 1b). The complete surface of the resin must have contained many spaces for adsorption at the beginning which provided a sharp increase in adsorption amount. However, increase in adsorption was almost linear between the 10th and 180th minutes. In resin-based processes, adsorbable surface area decreases by the time progresses. Repulsive molecular charge makes it difficult to adsorb and it causes a slowing down in the adsorption rate (Limwachiranon et al. 2019). EGCG amount reached to equilibrium in 180 min which indicated resin was saturated with this catechin. Even as the time flowed, changes in adsorption capacity were no more significant (p > 0.05). It can be classified as slow type adsorption due to time-consuming process until reaching equilibrium (Liu et al. 2011). Since the 180 min was sufficient to reach equilibrium state, further analysis was set over that time.

Kinetic modeling is a good way to elucidate adsorption behaviors in various resin types (Park and Lee 2021). Pseudo-first and pseudo-second order models were used to illustrate the adsorption mechanism of EGCG on NKA-2 resin (Table 2). In general, pseudo-first model is more convenient to describe rapid adsorption which occurs at the beginning of the process. On the other hand, pseudo-second order model applies a prediction on the entire process including the slowing down stage (Wang et al. 2020). A smaller k value is favorable since it indicates higher efficiency (Wang et al. 2014). Pseudo-second order model offered a lower k value (0.0005). Moreover, the equation obtained from pseudo-second order model provided a higher correlation coefficient (0.981) compared to the pseudo-first (0.978). Theoretical calculation for adsorption capacity was very close to experimental data (70.4 mg g^–1 dry resin) at the equilibrium. According to the findings, pseudo-second order model was more convenient for describing the adsorption kinetics of EGCG on NKA-2 resin.

Table 2

Kinetic modeling of EGCG adsorption on NKA-2 resin.
	Equations	Constants
Pseudo-first order model	${ln} \left({Q}_{e}-{Q}_{t}\right)=-0.0127t+4.0561$	k₁	0.0127
		Q_e	57.75
		R²	0.978
Pseudo-second order model	$t/{Qt}=0.0135t+0.3888$	k₂	0.0005
		Q_e	74.07
		R²	0.981

Adsorption isotherms

It is important to determine the appropriate initial EGCG concentration in order to minimize the repulsive force that may obstruct the process (Liu et al. 2011). Adsorption isotherms were constructed at three different temperatures of 25°C, 35°C and 45°C. As shown Fig. 2a, the equilibrium concentration was increased by increasing the initial EGCG concentration and then, began forming a saturation plateau when the initial concentration was set of 567.5 µg mL^–1. Adsorption capacity showed a decrease by increasing temperature from 25 to 45°C. Based on the experimental data, it was determined using 567.5 µg mL^–1 EGCG and 25°C as the initial concentration and operation temperature in the dynamic adsorption experiment, respectively.

Two equations, namely Langmuir and Freundlich, are generally used to better understand the adsorption characteristics of resins because of their simplicity and accuracy (Wang and Wang 2019; Zhang et al. 2019b; Wang et al. 2020). The Langmuir equation is mostly suitable for adsorption occurring on monolayer and homogenous surfaces, while the Freundlich equation is mostly appropriate for physical and chemical processes in non-ideal and heterogeneous systems (Kim et al. 2014; Wang and Wang 2019; Zhang et al. 2019b). Adsorption behaviors of EGCG on NKA-2 resin were evaluated by plotting C_e vs. C_e/Q_e and log C_e vs. log Q_e in Langmuir and Freundlich models, respectively (Fig. 2b and 2c). Adsorption isotherm was interpreted by evaluating R_L and 1/n values. The process was found favorable in both models according to these constants (0 < R_L<1 and 0 < 1/n < 1) (Table 3). Adsorption goes easier when it is 0.1 < 1/n < 0.5 (Wan et al. 2014), and goes difficult when 1/n is higher than 2 (Lv et al. 2018). 1/n value decreased related with temperature increase which indicates adsorption can be realized more easily at lower temperatures. Higher Q_m values indicate a strong interest of the target compound to the resin (Wang and Wang 2019). Q_m value was adversely affected by temperature rise. Similar results were reported in previous studies (Xi et al. 2015; Park and Lee 2021). This was due to the fact that EGCG adsorption was an exothermic process. Moreover, the Langmuir equation represented a higher correlation coefficient (R²) than the Freundlich equation in given temperatures. When the results were evaluated, Langmuir equation better described the adsorption behaviors of EGCG.

Table 3

Isotherm and thermodynamic parameters of EGCG adsorption on NKA-2 resin at different temperatures.
	Langmuir equation
	Equation	R²	Q_m	K_L	R_L
25°C	C_e/Q_e = 0.0126 C_e + 0.0006	0.9949	79.37	21.00	0.054
35°C	C_e/Q_e = 0.0127 C_e + 0.0008	0.9910	78.74	15.88	0.071
45°C	C_e/Q_e = 0.0128 C_e + 0.0012	0.9857	78.13	10.57	0.102
	Freundlich equation
	Equation	R²	1/n	K_F
25°C	Q_e = 104.93 ${C}_{e}^{0.346}$	0.8467	0.346	104.93
35°C	Q_e = 104.09 ${C}_{e}^{0.397}$	0.8755	0.397	104.09
45°C	Q_e = 98.49 ${C}_{e}^{0.440}$	0.9022	0.440	98.49
	Thermodynamic parameters
	ΔG (kj mol^–1)	ΔH (kj mol^–1)	ΔS [j (mol.K) ^–1]
25°C	–7.55	–26.64	–63.85
35°C	–7.08
45°C	–6.26

Thermodynamic parameters

Thermodynamic parameters can provide valuable information on structural and inherent energy changes of the resin after adsorption (Lv et al. 2018). ΔG defines the amount of energy for holding molecules on the resin at a specified temperature (Park and Lee 2021). Therefore, lower ΔG is more favorable due to making the process easier. Negative ΔG values were obtained at all three temperatures (Table 3), and it was concluded that the adsorption process could run spontaneously. According to the results, ΔG was increased by increasing temperature. That means adsorption was getting more difficult with the temperature rise. On the other hand, adsorption type can be classified according to ΔG values (Ye et al. 2011). It was predominantly physical adsorption (–20 < ΔG < 0) rather than chemisorption (–400 < ΔG<–80). The process was exothermic with regard to negative ΔH value. It can be shown as an evidence of decrease in Q_m by temperature rise as stated before. Since ΔH value was − 26.64 kj mol^–1, hydrogen bonding was thought as predominant interaction in the process (Lv et al. 2018). In addition, adsorption isotherms serve to understand how target compound is distributed between liquid and solid phases at equilibrium (Shin and Kim 2016). Randomness is decreased when ΔS value is lower than 0, or vice versa (Jin et al. 2015; Park and Lee 2021). Obtained result suggested that distribution of the particles was uniform on the resin/solution interface.

Dynamic adsorption and desorption on the NKA-2 resin

Compatibility of the practice to batch processing was investigated by using a glass column packed with NKA-2. EGCG was almost fully adsorbed at first 3 BV feeding. After a certain point, the resin cannot manage to bind target molecules and it starts to leak. Leakage exceeding 10% of initial EGCG concentration is defined as breakthrough point (Jin et al. 2015; Zhang et al. 2019b). As shown in Fig. 3a, it was over 10% following 3 BV feeding and that was accepted as the maximum loading volume of the resin. As time progressed, EGCG concentration in the outlet solution was sharply raised up to 10 BV. In further loadings, 75% or more of EGCG was discarded from the column out in each BV. Thus, 3 BV loading was found sufficient for an efficient adsorption process. The breakthrough point can be delayed by slowing down the flow rate or extending bed length (Park and Lee 2021). In high flow rates, molecules do not have sufficient time to interact with resin and are discharged out from the column without adsorbed (Ma et al. 2009). On the other hand, increasing the flow rate can shorten the processing time (Yang et al. 2015; Park and Lee 2021). Since industrial purpose was considered preferential, slightly high flow rate of 2.38 mL min^–1 was applied in the dynamic adsorption/desorption experiment. As shown in Fig. 3b, a total of 112.0 mg EGCG was adsorbed by the resin in 30 BV feeding. Despite the high flow rate, a good adsorption performance was obtained because of using a long column size (20 cm). A total of 2.55 mg EGCG was lost in washing step by 3 BV distilled water. In the previous reports, 50–70% ethanol concentration was recommended for the desorption process of phenolics in both polar and non-polar resins (Sun et al. 2013; Park and Lee 2021). Desorption was carried out by using 20 BV of 70% ethanol, and EGCG was recovered from the column in the ratio of 83.0%. In fact, 90.5% of total desorbed EGCG was obtained at first 4 BV and the desorption curve formed a plateau in further elutions which indicates no dramatic change occurred in the total desorption rate.

EGCG was found as the most abundant catechin compound in green tea leaves. Among the resins with different physical and chemical properties, NKA-2 exhibited better adsorption/desorption rates for EGCG separation from the tea extract. It was determined that adsorption kinetics was well described with pseudo-second order kinetics and the Langmuir model. According to the findings obtained from thermodynamic calculations, EGCG adsorption onto the resin was a spontaneous and exothermic process. It was revealed that particle distribution at the solution/resin interface was uniform. Taking into consideration static adsorption trials, specified conditions were adapted to dynamic adsorption process. The breakthrough occurred following after 3 BV loading at 2.38 mL min^–1 flow rate. 83.0% of adsorbed EGCG was recovered from NKA-2 packed column. The method offered some advantages such as a good adsorption rate and high recovery yield besides the reusability of the resins. Therefore, this study has certified that using NKA-2 resin is an effective way of EGCG separation from green tea extract. The combined practice of adsorbent resin and column chromatography can be a cost-effective and eco-friendly processes for the utilization of waste green tea leaves.

Author contributions Basak Bilcanoglu Cagan: Resources, Formal analysis, Software, Validation, Investigation, Writing – review & editing. Huseyin Karakaya: Investigation, Data curation, Visualization, Writing – review & editing. Murat Yilmaztekin: Conceptualization, Methodology, Supervision, Project administration, Writing – original draft.

Funding This work was supported by Inonu University Scientific Research Projects Commission (Grant number 2015/21).

Conflict of interest The authors have no relevant financial or non-financial interests to disclose.

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Adsorption and desorption characteristics of epigallocatechin-3-gallate from discarded green tea leaves on macroporous resin

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Abstract

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Introduction

Experimental

Materials and reagents

Instruments and equipment

Methods

Extraction of catechins from green tea leaves

Determination of catechins in the extract

Pretreatment of adsorbent resins

Adsorption and desorption capacities

Adsorption kinetics

Adsorption isotherms

Thermodynamic parameters

Dynamic adsorption and desorption

Statistical analysis

Results and discussion

Polyphenolic and caffeine contents

Selection of macroporous resin

Adsorption kinetics

Adsorption isotherms

Thermodynamic parameters

Dynamic adsorption and desorption on the NKA-2 resin

Conclusions

Declarations

References

Supplementary Files

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	Equations	Constants
Pseudo-first order model	\({ln} \left({Q}_{e}-{Q}_{t}\right)=-0.0127t+4.0561\)	k₁	0.0127
		Q_e	57.75
		R²	0.978
Pseudo-second order model	\(t/{Qt}=0.0135t+0.3888\)	k₂	0.0005
		Q_e	74.07
		R²	0.981