Effects of Organic Acid Catalysts on the Ethanol Organosolv Treatment of Wheat Bran to Produce Ferulate-Enriched Extracts

Abstract

Wheat bran (WB) is a major wheat processing byproduct, and it is characterized by significant ferulic acid content and ferulate derivatives, which are biologically important polyphenols. These phytochemicals occur in WB in bound form, and their recovery requires acid- and/or alkali-catalyzed hydrolysis. In the work described herein, ethanol organosolv treatment was employed, catalyzed by organic acids (oxalic, citric), to investigate their catalytic potency in releasing ferulates. Sulfuric acid was also included to compare the effects of mild and strong catalysis. Treatment assessment based on severity showed that the yield of total polyphenols was related to the combined severity factor in an exponential manner, while kinetics revealed that increases in temperature resulted in lower recovery rates but higher yields. Response surface optimization suggested 80 °C and 300 min to be the ideal conditions, where both oxalic acid- and sulfuric acid-catalyzed treatments yielded 11.6 mg ferulic acid equivalents per g dry WB weight; citric acid-catalyzed treatment was significantly less efficient (p < 0.05), giving a yield of 9.2 mg ferulic acid equivalents per g dry WB weight. Liquid chromatography–diode array–tandem mass spectrometry analyses showed that both sulfuric acid and oxalic acid catalysis was pivotal in the generation of certain ferulate derivatives, whereas the effect of citric acid was very weak. Some of the major derivatives tentatively identified were ferulate pentose esters and related compounds, in line with earlier findings. The differences in the compositions of the extracts obtained were reflected in their antioxidant properties, where important differentiation was observed. It was concluded that oxalic acid-catalyzed treatment might be an effective replacement for corrosive sulfuric acid in processes that are aimed at harnessing WB as a raw material for the generation of bioactive ferulate derivatives.

1. Introduction

The major challenge brought about by the ever-increasing world population is the assurance of sufficient and nutritious food, as well as sustainable agricultural and food production, to avoid uncontrolled resource utilization and maintain ecosystem equilibrium. However, it is irrefutable that the agrifood sector’s production has reached unprecedently high rates, with a concomitant increase in rejected materials and processing side streams. These biowastes require proper handling and disposal, with otherwise severe consequences for the environment, which pertain to pollution and aggravation [1,2]. Arguably, the higher-value option in establishing sustainable routes of development is food waste valorization, which is a solution with great potential, as an alternative to waste disposal at landfills. The intriguing concept of harnessing agrifood processing waste is largely based on the recognition that such biomaterials are in fact a low-cost and abundant resource, loaded with bioactive phytochemicals, which could be exploited in producing high-value-added products, such as nutritional supplements, food additives, pharmaceuticals, and cosmetics [3,4]. Although agricultural and food wastes may contain a diversity of biologically important substances, particular emphasis has been placed on polyphenolic compounds, which have been evidenced to display an array of beneficial properties, such as anti-inflammatory, antioxidant, anticarcinogenic, and cardioprotective effects [5,6].

Wheat is one of the largest crops worldwide, and it is largely processed into flour, with yields usually ranging from 73 to 77%. The residual 23–27% is constituted mainly by bran and lower amounts of wheat endosperm and germ. Wheat bran (WB) constitutes almost 25% of the grain weight, and it is the principal side stream of wheat processing, with the global annual production being 120 million tons [7]. WB may be regarded as an important source of value-added products, such as antioxidant polyphenols [8,9], represented primarily by ferulic acid (FA). Polyphenol recovery from WB is very low compared to other food processing wastes, since a major number of these substances are in bound, non-extractable forms, attached to arabinoxylan chains via ether or ester linkages [10,11]. Nonetheless, polyphenol recovery yields can be greatly improved through alkaline- or acid-catalyzed hydrolysis [12].

Several studies have indicated that polyphenol recovery from WB may be improved by thermal treatments, such as steam explosion [13], pressurized aqueous extraction [14], and hydrothermal treatment [15]. However, requirements for expensive equipment or the use of high temperatures (above 100 °C), which might be detrimental for the extraction of thermally sensitive molecules such as polyphenols, are serious drawbacks for these techniques. Therefore, there is a strong need for the development of alternative methodologies that are aimed at providing high polyphenol yields without compromising their sustainable nature because of the use of corrosive, strongly alkaline and/or acid catalysts and the application of high temperatures. Recently reported information shows that acid-catalyzed organosolv treatments (treatments involving organic solvents) of WB may generate extracts with different compositions compared to those obtained with alkaline catalysis [16], affecting the antioxidant attributes. Moreover, it was demonstrated that weak organic acids, such as citric acid, may serve as efficient acid catalysts in liberating hydroxycinnamate-derived substances from WB using hydrothermal treatments [17].

On the above conceptual basis, the current study was performed to test ethanol organosolv treatments for their efficacy in the recovery of bound hydroxycinnamates from WB. Strong (sulfuric acid) and mild (oxalic and citric acids) catalysis was used to examine the role of the acid type in both the polyphenol recovery yield and composition. To thoroughly assess the treatment performance, the extracts produced were examined for their polyphenolic profiles and antioxidant potency. To the best of the authors’ knowledge, a comparative assessment of strong and weak organic acids as catalysts for such a task has never been performed in the past. Thus, such an approach to examine WB as a natural pool of antioxidant polyphenols is reported for the first time.

2. Materials and Methods

2.1. Chemicals

Sodium carbonate (>99.8%), iron(III) chloride hexahydrate, and 2,4,6-tripyridyl-s-triazine (TPTZ) were from Honeywell/Fluka (Steinheim, Germany). Ascorbic acid, oxalic acid (98%), 2,2-diphenylpicrylhydrazyl (DPPH), and trans-ferulic acid (99%) were from Sigma-Aldrich (Darmstadt, Germany). Folin–Ciocalteu reagent and citric acid (99%) were from Merck (Darmstadt, Germany). For chromatographic analyses, solvents of high-performance liquid chromatography (HPLC) purity were used.

2.2. Wheat Bran Procurement

Hard wheat (Triticum aestivum) bran (WB) was kindly donated by Mills of Crete (Chania, Greece). The bran was freshly produced (24 h), and it was delivered in airtight plastic bags. Upon receipt, WB was milled in a laboratory mill and then sieved to obtain material with a mean particle diameter <300 μm. This feed was maintained in plastic containers, in the fridge, for no longer than seven days until use.

2.3. Treatments

An exact mass of 1 g of WB was transferred into a 20 mL glass vial and mixed with 15 mL of 60% (v/v) ethanol (control extraction) or solutions of 60% ethanol with sulfuric acid (SuAc), oxalic acid (OxAc), and citric acid (CiAc). The testing of the effects of the acid type and concentration was accomplished within a range of 0.5 to 2% (w/v) for SuAc and within 3–12% (w/v) for OxAc and CiAc. These ranges were chosen on the basis of previous works [16,17], and the pH for all solvent systems used is given in Table S1. Treatments were carried out under stirring at 500 rpm and at 80 °C for 300 min. Both heating and stirring were accomplished using a hotplate/magnetic stirrer (AREC.X, Velp Scientifica, Usmate, Italy), with the aid of a paraffin bath. After the treatment, mixtures were centrifuged at 11,500× g for 10 min to remove cell debris and obtain a clear extract.

2.4. Examination of Extraction Kinetics

Following preliminary testing, the kinetic model that exhibited the best fit to the experimental data was a single rectangular, 2-parameter hyperbola, as used in earlier studies [18,19]:

$${\mathrm{Y}}_{\mathrm{T}\mathrm{P}\left(t\right)}= {\displaystyle \frac{{\mathrm{Y}}_{\mathrm{T}\mathrm{P}\left(\mathrm{s}\right)}t}{t_{0.5}+ t}}$$

(1)

The terms Y_TP(t), t, and Y_TP(s) correspond to the yield of total polyphenols at any residence time, the residence time, and the yield of total polyphenols at equilibrium (saturation). When t = t_0.5, then Y_TP(t) = Y_TP(s)/2; therefore, the term t_0.5 may be regarded as the time to attain Y_TP(s)/2 [19]. Thus, 2 × t_0.5 could be considered the residence time required to approach Y_TP(s). The initial rate of extraction, h, and the second-order extraction rate, k, are determined as shown below:

$$h= {\displaystyle \frac{{\mathrm{Y}}_{TP\left(s\right)}}{t_{0.5}}}$$

(2)

$$k={\displaystyle \frac{1}{{\mathrm{Y}}_{\mathrm{T}\mathrm{P}\left(s\right) }{t}_{0.5}}}$$

(3)

2.5. Treatment Severity Determination

The appraisal of the treatment severity was carried out as previously proposed [20]:

$$R_{\mathrm{o}} = t \times e^{\left({\displaystyle \frac{T-100}{14.75}}\right)}$$

(4)

Using Equation (4), the severity factor (SF) can be computed:

SF = logR_o

(5)

where R_o is the treatment severity, the value 100 °C is the reference temperature, and the value 14.75 is an empirical factor associated with the temperature of the treatment and the activation energy. The combined severity factor (CSF) can be determined using the following equations [21]:

$${R_{\mathrm{o}}}^{\prime } = {10}^{-\mathrm{pH}} \times t \times e^{\left({\displaystyle \frac{T-100}{14.75}}\right)}$$

(6)

CSF = logR_o′ − pH

(7)

Finally, the so-called “alternative combined severity factor” (CSF′) was also determined [21]:

CSF′ = logR_o + |pH − 7|

(8)

2.6. Experimental Design and Response Surface Methodology

Treatment examination was based on a design of experiments, which considered the two most significant treatment variables: the temperature (T) and residence time (t). The upper limit used for the temperature was 80 °C to eliminate excessive vapor pressure in the treatment vial due to the use of ethanol. Taking into consideration the information obtained from the kinetics study, a central composite design was used, with 8 design points and 3 central ones (11 points in total). The actual values of both variables were codified at 3 levels, −1, 0, and 1, as previously described [22].

Table 1. The coded and actual values for both treatment variables used to build the experimental design.

Treatment Variable	Code	Coded and Actual Variable Level
		−1	0	1
T (°C)	X2	40	60	80
t (min)	X1	120	210	300

illustrates these data in detail.

Model significance (R², p) and the significance of each model coefficient were assessed using pertinent statistical tests (lack-of-fit and ANOVA tests), with 95% representing the minimum level of significance.

2.7. Determination of Total Polyphenol Yield and Antioxidant Activity

Total polyphenols were measured with a previously described assay based on the Folin–Ciocalteu reagent [23]. The yield of total polyphenols (Y_TP) was given as ferulic acid equivalents (FAE) per g of dry WB mass (DM). To evaluate the antiradical activity (A_AR), the radical probe DPPH was employed, using a protocol described elsewhere [24]. Results were expressed as μmol DPPH per g DM. The ferric-reducing power (P_R) determination was carried out with TPTZ chromophore reagent, and the results were expressed as μmol ascorbic acid equivalents (AAE) per g DM [24].

2.8. Liquid Chromatography–Tandem Mass Spectrometry (LC-MS/MS)

For all chromatographic and mass spectrometry examinations, the device employed was a TSQ Quantum Access LC-MS/MS instrument, equipped with a Surveyor pump (Thermo Scientific, Walltham, MA, USA), and an Acquity PDA detector (Waters, Milford, MT, USA). The system was interfaced with the XCalibur 2.1, TSQ 2.1 software. Chromatographic separations were accomplished with a Fortis RP-18 column, 150 mm × 2.1 mm, 3 μm, at 40 °C. The injection volume was 10 μL and the flow rate 0.3 mL min⁻¹. The eluents used were A—1% aqueous acetic and B—99% acetonitrile/1% acetic acid. The elution program deployed was as follows: 0–2 min, 5% B; 2–27 min, 50% B; 27–29 min, 100% B. The settings used for mass spectrum acquisition were the following: spray voltage—3000 V, sheath gas pressure—30 (arbitrary units), auxiliary gas pressure—10 (arbitrary units), and capillary temperature—350 °C. Quantification was accomplished with an external standard methodology. The calibration curve of ferulic acid was created with a commercial standard (R² = 0.9981, concentration range 0–50 μg mL⁻¹), prepared freshly in HPLC-grade methanol.

2.9. Data Elaboration and Statistics

JMP™ Pro 16 (SAS, Cary, NC, USA) was used to set up the experimental design and carry out response surface methodology optimization, as well as to obtain all pertinent statistics (analysis of variance (ANOVA) and lack-of-fit test). Kinetic assays and non-linear and linear regressions were accomplished with SigmaPlot™ 15.0 (Systat Software Inc., San Jose, CA, USA). Statistically significant differences were revealed by the Kruskal–Wallis test, using IBM SPSS Statistics™ 29 (SPSS Inc., Chicago, IL, USA), considering that the data used did not show a normal distribution in the Shapiro–Wilk test. At least two runs were carried out on each treatment, while spectrophotometric and chromatographic determinations were performed in triplicate. Values are presented as the average ± standard deviation (SD).

3. Results and Discussion

3.1. The Effects of the Acid Type and Concentration

Treatment with 60% ethanol, without the addition of any acid catalyst, afforded a total polyphenol yield of 4.3 mg FAE g⁻¹ DM (Figure 1). On the other hand, when the treatment was performed in the presence of 2% (w/v) SuAc, the yield increased by almost 42%, reaching 6.1 mg FAE g⁻¹ DM. These two levels were used as controls to assess the effects of OxAc and CiAc in catalyzing polyphenol release from WB.

At a concentration of 3%, both OxAc and CiAc were inefficient in boosting Y_TP (p > 0.05), and the same effect was observed at 6%. However, at 12%, the effects of both OxAc and CiAc equaled that of 2% SuAc. Therefore, the most efficacious solvents were 60% ethanol containing 2% SuAc (used as a control), 12% OxAc, and 12% CiAc. On the basis of this outcome, severity-based trials were considered for further acid catalyst appraisal.

3.2. Treatment Severity-Based Trials

Treatment severity represents the harshness of the conditions used and can be determined by the severity factor. Along with the residence time and temperature, acidity or alkalinity also affects the treatment severity. Therefore, the combined severity factor (CSF) or the alternative combined severity factor (CSF′), which take into consideration the pH of the solvent used, may be more descriptive [21]. To examine the severity effects, the above-selected solvent systems were tested under various combinations of time and temperature, and the efficiency evaluation was based on the yield of total polyphenols (Y_TP).

Table 2. The combination of residence time and temperature used to assess the effects of treatment severity on the total polyphenol yield. CSF and CSF′ correspond to combined and alternative severity factors.

T (°C)	t (min)	CSF			CSF′			YTP (mg FAE g−1 DM)
		Catalyst			Catalyst			Catalyst
		2% SuAc	12% OxAc	12% CiAc	2% SuAc	12% OxAc	12% CiAc	2% SuAc	12% OxAc	12% CiAc
40	120	−0.60	−0.39	−1.81	6.40	6.61	5.19	3.4 ± 0.2 a	3.6 ± 0.2 a	3.3 ± 0.1 a
	210	−0.35	−0.14	−1.56	6.65	6.86	5.44	3.6 ± 0.3 a,b	3.9 ± 0.3 a	3.4 ± 0.2 a
	300	−0.20	0.01	−1.41	6.80	7.01	5.59	3.9 ± 0.3 b	3.9 ± 0.2 a	3.6 ± 0.2 a
60	120	−0.01	0.20	−1.22	6.99	7.20	5.78	4.3 ± 0.3 b	4.6 ± 0.3 b	3.6 ± 0.2 a
	210	0.23	0.44	−0.98	7.23	7.44	6.02	4.5 ± 0.3 b	4.6 ± 0.3 b	4.0 ± 0.1 b
	300	0.39	0.60	−0.82	7.39	7.60	6.18	4.6 ± 0.4 b	4.8 ± 0.4 b	4.0 ± 0.1 b
80	120	0.58	0.79	−0.63	7.58	7.79	6.37	10.5 ± 0.4 c	10.2 ± 0.5 c	8.6 ± 0.3 c
	210	0.82	1.03	−0.39	7.82	8.03	6.61	11.4 ± 0.4 d	11.3 ± 0.5 d	9.1 ± 0.3 c,d
	300	0.98	1.19	−0.23	7.98	8.19	6.77	11.6 ± 0.6 d	11.6 ± 0.7 d	9.2 ± 0.2 d

Values indicated by different lowercase letters (a, b, c, d) are statistically different (p < 0.05).

shows all combinations used and the corresponding CSF, CSF′, and Y_TP values. For the SuAc-catalyzed treatment, the smallest CSF required for the maximum Y_TP was 0.82 (CSF′ = 7.82). For the OxAc- and CiAc-catalyzed treatments, the smallest CSFs required were 1.03 (CSF′ = 8.03) and −0.39 (CSF′ = 6.61), respectively.

Previous studies showed that a maximum Y_TP of 11 mg FAE g⁻¹ DM could be achieved by treating WB with 1.5% SuAc at a CSF of 0.93 (CSF′ = 7.93) [16]. On the other hand, a significantly higher Y_TP of 18.8 mg FAE g⁻¹ DM was attained using 10% CiAc at a CSF of 0.67 (CSF′ = 7.67) [17]. A critical assessment of these data suggests that the polyphenol recovery yield might depend on the type of acid catalyst used, its concentration (and thus the pH), and the combined effects of the time and temperature (severity). This argument is further supported by findings from a pertinent investigation on polyphenol recovery from coffee silverskin using SuAc- and OxAc-catalyzed ethanol organosolv treatments [25]. In that case, it was clearly revealed that Y_TP may be linearly linked with CSF (or CSF′), a strong indication that increasing severities could afford higher polyphenol yields. Similar results have also been reported for the non-catalyzed ethanol organosolv treatment of WB [26]. However, evidence derived from another work on polyphenol recovery from potato peels showed that the dependence of Y_TP on CSF does not always obey a linear function, and the correlation between Y_TP and CSF may also depend on the solvent used [27].

Thus, to scrutinize the dependence of the polyphenol yield on the treatment severity, Y_TP was plotted as a function of CSF (Figure 2). By carrying out a non-linear regression, the model that best fitted the experimental measurements was, in all cases, a two-parameter exponential growth model, described by Equations (9)–(11), as shown below:

Y_TP(SuAc) = 4.52e^1.03CSF (R² = 0.87, p = 0.0003)

(9)

Y_TP(OxAc) = 3.84e^0.97CSF (R² = 0.87, p = 0.0002)

(10)

Y_TP(CiAc) = 11.83e^0.88CSF (R² = 0.84, p = 0.0005)

(11)

Such a correlation has not been heretofore reported and provides novel insights into the association between the treatment severity and polyphenol yield. The fact that the correlations obeyed the same model irrespective of the catalyst used could indicate wide applicability, offering a valuable tool for treatment evaluation. However, further trials are required to examine model suitability over wider severity ranges and under diversified conditions (e.g., high pressure).

The use of treatment severity as a criterion for the appraisal of the polyphenol recovery efficiency from WB has been so far well documented [14,16,17,26], and it may be considered a valuable tool for the critical comparison of organosolv treatments involving either acid or alkaline catalysis. The expression of severity, including the pH of the treatment medium, can certainly provide a more integrated image of the actual effect [28] over an extended range of pH values [21,29]. Nevertheless, the determination of CSF (or CSF′) is merely indicative, because other factors may also significantly affect the treatment performance, such as the structural attributes of the treated biomass (e.g., its recalcitrance), the nature of the polyphenols extracted, their thermal stability, etc. Although regression between Y_TP and CSF cannot detect cross (synergistic) effects between the residence time and temperature, the severity could be pivotal in selecting the ranges of these variables when setting up organosolv treatments.

3.3. Polyphenol Release Kinetics

The testing of various catalysts by assessing the treatment severity strongly indicated that the temperature might play an instrumental role in boosting the treatment performance (Table 2). Thus, to gain a more thorough understanding of the temperature effects, a kinetic assay was applied, using the same temperature and timeframe (Figure 3).

A single rectangular, two-parameter hyperbola model, which has been previously deployed to trace polyphenol extraction kinetics [19], gave very satisfactory fitting to the experimental measurements, and, in all cases, it was found that R² ≥ 0.97 and p < 0.0001. The kinetic assay revealed that the second-order extraction rate, k, declined when raising the treatment temperature from 40 to 80 °C, and this finding was common across all acid catalysts tested (

Table 3. Kinetic data and total polyphenol yields obtained when treating WB with 2% (w/v) sulfuric acid (SuAc), 12% oxalic acid (OxAc), and 12% citric acid (CiAc).

Catalyst	T (°C)	k (×10−3) (g mg−1 min−1)	t0.5 (min)	h (mg g−1 min−1)	YTP(s) (mg FAE g−1 DM)
SuAc	40	87.1	3.19	1.1	3.6 ± 0.2 a
	60	26.8	8.12	0.6	4.6 ± 0.3 b
	80	1.5	47.29	0.3	13.9 ± 1.0 c
OxAc	40	56.6	4.53	0.9	3.9 ± 0.4 a
	60	40.8	5.22	0.9	4.7 ± 0.3 b
	80	2.0	37.64	0.4	13.3 ± 0.9 c
CiAc	40	89.1	3.30	1.0	3.4 ± 0.2 a
	60	38.3	6.70	0.6	3.9 ± 0.2 a
	80	3.7	26.36	0.4	10.3 ± 0.8 d

Values indicated by different lowercase letters (a, b, c, and d) are statistically different (p < 0.05).

). Such behavior did not concur with the Arrhenius model for the relation between the rate and temperature [30,31], where it would be anticipated to observed an increased k as a response to increasing temperatures.

Although this phenomenon has been previously reported for polyphenol extraction using deep eutectic solvents [24,32], no explanation has been provided to justify such behavior. In the case examined herein, it could be argued that the readily extracted polyphenols, which represented a small fraction of the total amount, were rapidly entrained into the liquid phase (solvent) at any temperature tested; this could not be the rate-limiting step, as it represented the washing phase of the extraction. During this phase, and owing to relatively low temperature, the liberation of bound polyphenols might be slow. On the other hand, as the temperature increased, progressive bound polyphenol liberation could take place due to reactions leading to bound polyphenol release, but also to cell wall deconstruction, which would facilitate the entrainment of “trapped” polyphenols into the liquid phase. Thus, both liberation and diffusion could be the rate-determining steps—hence the lower k and h and the higher t_0.5 (Table 3).

In brief, the assumption that can be made is that, at low temperatures (<60 °C), k might represent almost exclusively the recovery of free polyphenols, whereas, at elevated temperatures, the reactions leading to polyphenol release predominate. Due to the multitude of reactions involved in polyphenol release, the reduction in k might indicate that polyphenols were liberated through more than one pathway. Eventually, treatment at a higher temperature gave a much higher Y_TP(s) due to both the washing of the free polyphenols and extended bound polyphenol release. At this point, the initial observation regarding the critical role of the temperature was affirmed. Specifically, raising the temperature from 40 to 60 °C provoked a rather low to moderate Y_TP increase, but, when the temperature was changed from 60 to 80 °C, Y_TP was boosted. This outcome probably explains the exponential dependence of Y_TP on CSF, as shown above.

3.4. Design of Experiments and Treatment Optimization

Although severity-based and kinetic modeling was informative regarding the influence of the treatment temperature and residence time, synergistic (cross-) effects between these two crucial variables could not be revealed. Such effects can only be seen when deploying the response surface methodology, which is specifically designed to identify such functions. Treatment modeling through the response surface methodology was evaluated by analysis of variance (ANOVA) and lack-of-fit tests (Figures S1–S3), taking into consideration the closeness of the actual (measured) response (Y_TP) values (

Table 4. Analytical presentation of all design points (1–11) used for the experimental design, along with the corresponding coded variable values and the responses (Y_TP).

Design Point	Variable		Response (YTP—mg FAE g−1 DM)
	X1 (T, °C)	X2 (t, min)	SuAc		OxAc		CiAc
			Measured	Predicted	Measured	Predicted	Measured	Predicted
1	−1 (40)	−1 (120)	3.4	3.4	3.6	3.8	3.3	3.3
2	−1 (40)	1 (300)	3.9	3.7	3.9	3.9	3.6	3.5
3	1 (80)	−1 (120)	10.5	10.6	10.3	10.5	8.6	8.6
4	1 (80)	1 (300)	11.6	11.6	11.7	11.6	9.2	9.2
5	−1 (40)	0 (210)	3.6	3.6	4.0	3.9	3.4	3.5
6	1 (80)	0 (210)	11.4	11.2	11.3	11.1	9.1	9.0
7	0 (60)	−1 (120)	4.3	4.1	4.6	4.2	3.6	3.6
8	0 (60)	1 (300)	4.6	4.7	4.8	4.9	4.0	4.0
9	0 (60)	0 (210)	4.5	4.5	4.6	4.6	4.0	3.9
10	0 (60)	0 (210)	4.4	4.5	4.8	4.6	4.0	3.9
11	0 (60)	0 (210)	4.5	4.5	4.1	4.6	3.8	3.9

). Non-significant terms of the mathematical equations (models) derived were excluded, and the resulting second-degree polynomial equations are illustrated in

Table 5. Models (mathematical equations) derived after implementing response surface methodology. Non-significant equation terms have been omitted.

Catalyst	Equation (Model)	R2	p
2% SuAc	YTP = 4.5 + 3.8X1 + 0.3X2 + 2.9X12	1.00	<0.0001
12% OxAc	YTP = 4.7 + 3.6X1 + 0.3X2 + 2.9X12	1.00	<0.0001
12% CiAc	YTP = 3.9 + 2.8X1 + 0.2X2 + 2.3X12	1.00	<0.0001

, along with the pertinent statistical quantities (overall model square correlation coefficients (R²) and p values). Since R² ≥ 0.95 and p < 0.005, it could be concluded that the models displayed very satisfactory fitting to the experimental data. An at-a-glance depiction of the simultaneous effects of the independent variables on Y_TP was observed in the 3D plots (Figure 4) produced on the basis of the models.

For all three catalysts tested, both variables T and t, as well as the quadratic term of T (X₁²), were highly significant (p < 0.005). The dependence of Y_TP on X₁² was further confirmation that the extraction yield was related to the temperature by an exponential function, as shown for CSF and suggested by the kinetic data. On the other hand, the lack of significance for the quadratic term related to time would indicate that time affected the treatments in a linear manner, as suggested by the models. The desirability function (Figures S1–S3) allowed for the determination of the optimum T and t settings to maximize Y_TP (

Table 6. Values of maximum responses and optimum variable settings, as predicted by the desirability function (Figures S1–S3).

Catalyst	Maximum Predicted Response (mg GAE g−1 DM)	Optimal Conditions
		t (min)	T (°C)
2% SuAc	11.6 ± 0.4 a	300	80
12% OxAc	11.6 ± 0.8 a	300	80
12% CiAc	9.2 ± 0.2 b	300	80

Values indicated by different lowercase letters (a, b) are statistically different (p < 0.05).

), which perfectly matched those determined experimentally (Table 2), showcasing the validity of the derived models.

Under identical conditions, the OxAc-catalyzed treatment afforded 11.6 ± 0.4 mg FAE g⁻¹ DM, which was equal to the level attained with the SuAc-catalyzed treatment and significantly higher than the level achieved with the CiAc-catalyzed treatment. Previous studies on SuAc-catalyzed ethanol organosolv treatment reported a maximum Y_TP of 10.9 mg FAE g⁻¹ DM [16], which is essentially equal to the 11.6 mg FAE g⁻¹ DM found in this study. However, Y_TP as high as 23.8 mg FAE g⁻¹ DM was achieved using 10% CiAc for an extended residence time of 1440 min (24 h) [17]. On the basis of these results, it would appear that the combination of the treatment temperature and time is the major determinant of Y_TP, but the selection of an appropriate catalyst might significantly accelerate the treatment. Thus, additional work is needed to fully elucidate the actual potential of either OxAc or CiAc in enhancing polyphenol recovery from WB, employing higher temperatures and more extended residence times. However, it should be noted that harsher conditions might raise issues pertaining to polyphenol stability; thus, a thorough investigation would be required to clearly set appropriate limits for these two variables.

3.5. Polyphenolic Profile and Antioxidant Activity

To shed more light on the actual effects of the various acid catalysts on the polyphenolic composition, the extracts produced under optimized conditions, along with the extract produced with no catalyst (only 60% ethanol), were subjected to LC-DAD-MS/MS analyses. The treatment performed without the presence of any catalyst (only 60% ethanol) yielded an extract with the chromatographic profile illustrated in Figure 5A. However, the extract generated from the treatment with 2% SuAc as a catalyst showed significant differentiation in composition, since the occurrence of two additional predominant peaks was observed (Figure 5B). These two peaks were present in the extracts produced from all acid-catalyzed treatments, irrespective of the catalyst used, evidencing the role of acid catalysis in their formation.

Peaks 1, 2, 3, 5, 6, and 7 had very similar UV–vis spectral characteristics to the original standard ferulic acid (peak 4), which suggests that these compounds could be ferulate derivatives (

Table 7. Details pertaining to the tentative identification of major peaks detected in WB extracts.

Peak Number	Retention Time (min)	UV–Vis Maxima (nm)	[M − H]− (m/z)	Other Ions	Tentative Identity
1	13.79	327	325	-	Feruloyl–pentose
2	13.84	325	325	-	Feruloyl–pentose
3	14.21	272, 334	247	219	Unknown
4	14.33	323	193		Ferulic acid
5	14.60	291, 323	193	-	Ferulic acid derivative
6	17.57	326	353	325, 249, 194	Ferulic acid derivative
7	17.81	326	355	194	Ferulic acid derivative

). The mass spectra obtained in negative ionization mode revealed a molecular ion at m/z = 325 for peaks 1 and 2, and, based on previous information [17], these compounds were tentatively identified as ferulic acid–pentose (arabinose or xylose) esters. Peak 6 gave a molecular ion at m/z = 353, and, considering the diagnostic fragments at m/z = 325 (ferulic acid–pentose ester) and 194 (ferulic acid), this compound was identified as a ferulate derivative. Likewise, peak 7 displayed a molecular ion at m/z = 355 and a diagnostic fragment at m/z = 194 (FA), and it was also identified as a ferulate derivative. For peak 3, no tentative identity could be assigned. The quantitative analysis showed that the SuAc-catalyzed treatment afforded the most enriched extracts in all compounds identified (

Table 8. Quantitative information for the major compounds detected in WB extracts, obtained with treatments with 2% (w/v) sulfuric acid (SuAc), 12% oxalic acid (OxAc), and 12% citric acid (CiAc), under optimized conditions (see Table 6).

Peak Number	Compound	Yield (μg g−1 DM)
		No Catalyst	2% SuAc	12% OxAc	12% CiAc
1	Feruloyl–pentose	8.0 ± 0.5 b	210.6 ± 12.3 e	179.4 ± 10.5 d	- a
2	Feruloyl–pentose	24.4 ± 1.8 a	212.8 ± 10.0 e	170.8 ± 9.8 d	74.8 ± 3.3 b
3	Unknown	141.8 ± 9.0 c	130.7 ± 8.4 c	113.1 ± 6.3 b	89.5 ± 4.4 a
4	Ferulic acid	15.6 ± 1.0 b	127.8 ± 9.6 e	59.7 ± 3.3 c	10.9 ± 0.4 a
5	Ferulic acid derivative	13.7 ± 0.7 c	21.5 ± 1.3 e	16.4 ± 0.6 d	9.4 ± 0.1 a
6	Ferulic acid derivative	- a	358.2 ± 12.5 e	281.2 ± 10.8 d	11.8 ± 0.7 b
7	Ferulic acid derivative	- a	416.7 ± 19.8 e	252.0 ± 11.4 d	2.5 ± 0.1 b
	Total	203.5	1475.9	1081.0	198.8

Values within columns indicated by different lowercase letters (a, b, c, d and e) are statistically different (p < 0.05).

). Furthermore, it was unequivocally demonstrated that acid catalysis was necessary to boost the formation of FA and its derivatives. However, in the case of CiAc catalysis, the extract obtained was very poor in terms of all compounds considered, an indication that this catalyst had a very weak effect.

In general, FA dominates among other polyphenols in WB extracts, but the relevant amounts are strictly dependent on the catalyst used. Recent data on both acid-catalyzed organosolv and hydrothermal treatments demonstrated that, under acidic conditions, a ferulate pentose was the major polyphenolic metabolite in WB extracts, accompanied by a significantly lower concentration of FA [16,17]. The results presented in Table 8 are in line with these findings, since the two feruloyl–pentose derivatives identified were among the most abundant metabolites, whereas FA occurred at much lower levels. Moreover, peaks 6 and 7 were the predominant ferulate derivatives.

In WB, FA is attached to cell wall arabinoxylan via ester bonds [10,33], which can be effectively cleaved with alkaline hydrolysis. Moreover, FA may also be ester-bound between polysaccharides and lignin, acting as crosslinking compounds, but also within the lignin network [34]. On the other hand, ether-linked FA may be cleaved only upon acid catalysis, where hemicellulose fractions may be solubilized, but the ester-linked FA remains unaffected [35]. This might be the reason for the greater abundance of ferulate esters and other derivatives detected in the extracts generated in this study, with the exception of the CiAc-catalyzed treatment. It is also underlined that lignin decomposition and solubilization could further enhance the release of ferulate derivatives, because, during ethanol organosolv treatment, the breakdown of α-aryl and β-aryl ether linkages may contribute to lignin cleavage [33,35]. Such reactions result in lignin splitting into smaller fractions, thus permitting greater lignin solubilization, and may occur in the presence of an acid catalyst.

The differences seen among the various acid catalysts used in this study with regard to ferulate formation concerned quantitative aspects, whereas no differentiation in the polyphenolic profile was recorded. This finding indicates that the type of acid catalyst did not affect the polyphenolic composition, but it was rather the acidity (acid strength and concentration) that defined the extent of product formation, given that all treatments were performed at 80 °C for 300 min. Nevertheless, CiAc, which performed poorly in this study, was shown to be an effective catalyst for WB hydrothermal treatment, providing high ferulate pentose ester yields [17], when the residence time was extended to 24 h. Therefore, it could be argued that the actual effect exerted by a given catalyst might depend on the time/temperature combination.

To investigate the impact of the compositional differences on the antioxidant potency of the extracts produced, the radical-scavenging activity and the reducing power were determined. It can be seen in Figure 6A that the extracts produced using SuAc- and OxAc-catalyzed treatments were of equal radical-scavenging capacity. By contrast, the extracts generated with 60% ethanol and CiAc-catalyzed treatments exhibited significantly lower performance (p < 0.05). On the other hand, the highest ferric-reducing potency was exerted by the extract produced with the OxAc-catalyzed treatment (p < 0.05), whereas all other extracts were much weaker in this regard.

In the case of A_AR, the extracts with higher total ferulate concentrations (SuAc- and OxAc-catalyzed) were the most active, compared to the extracts with low concentrations (60% ethanol and CiAc-catalyzed). However, the extract from the SuAc-catalyzed treatment had an almost 1.4 times higher concentration than that obtained with the OxAc-catalyzed one. Therefore, the differences observed could not be interpreted solely on the grounds of the polyphenolic richness of the extracts. This phenomenon was even more pronounced when P_R was examined, where the extract from the OxAc-catalyzed treatment was found to be the most powerful. Thus, qualitative differences arising from the relative amounts of each constituent appear to dictate the actual antioxidant effect.

The antioxidant activity of a polyphenol-containing extract cannot be predicted, as it may depend both on the polyphenolic species and their relative amounts. The various interactions among all these substances could bring about antagonistic and/or synergistic effects; hence, the overall ferric-reducing power or antiradical activity would result from the integration of such interactions [36,37]. Nevertheless, A_AR in WB extracts has been correlated with the polyphenol concentration [38,39,40], and the liberation of bound polyphenols has also been demonstrated to greatly enhance antioxidant activity [41]. However, in recent studies, it was evidenced that WB extracts enriched in ferulate pentose esters were the most active on the basis of both A_AR and P_R [16,17], and it was suggested that this compound might be a stronger antioxidant compared to FA. Earlier investigations concurred with such an assumption, since it was shown that ferulate esters may be better antioxidants than FA itself [42]. Results from studies that compared ferulate glucose esters [43] and ferulate arabinose [44] with FA showed the same pattern. Considering that the exact nature of most of the compounds detected in the extracts is unknown, it would be impossible to interpret with certainty the antioxidant behavior observed. Nevertheless, it appears that the enrichment of the extracts with polyphenols as a result of acid hydrolysis enhanced their antioxidant activity, and this is an outcome that merits further examination.

4. Conclusions

A few recent works have highlighted the potency of weak organic acids, such as citric and oxalic, to catalyze hydrolytic reactions. Although the liberation of bound polyphenols in cereal tissues, such as WB, may require harsh conditions (e.g., strong acid catalysis) for high efficacy, the usefulness of the aforementioned natural acids should not be overlooked. In the investigation presented herein, it was demonstrated that the oxalic acid-catalyzed ethanol organosolv treatment of WB may have important prospects in the recovery of ferulates, although the sulfuric acid-catalyzed treatment was of significantly higher performance. However, further examination of the factors that affect such processes (time, temperature) may provide a highly productive treatment without the need to use corrosive catalysts such as sulfuric acid. This would enable the establishment of green technologies, which, when incorporated into wider biorefinery procedures, could contribute towards fully sustainable strategies of biowaste valorization. The undisputed abundance of WB would make it an ideal candidate as a bioresource for the retrieval of valuable phytochemicals; thus, more extended research should be directed towards WB, harnessing eco-friendly treatments. Furthermore, additional research is needed to fully characterize the ferulate derivatives detected in the extracts produced and clarify their biological attributes.