Valorisation Potential of Invasive Acacia dealbata, A. longifolia and A. melanoxylon from Land Clearings

Abstract

Acacia spp. are invasive in Southern Europe, and their high propagation rates produce excessive biomass, exacerbating wildfire risk. However, lignocellulosic biomass from Acacia spp. may be utilised for diverse biorefinery applications. In this study, attenuated total reflectance Fourier transform infrared spectroscopy (FTIR-ATR), high-performance anion-exchange chromatography pulsed amperometric detection (HPAEC-PAD) and lignin content determinations were used for a comparative compositional characterisation of A. dealbata, A. longifolia and A. melanoxylon. Additionally, biomass was treated with three white-rot fungi species (Ganoderma lucidum, Pleurotus ostreatus and Trametes versicolor), which preferentially degrade lignin. Our results showed that the pre-treatments do not significantly alter neutral sugar composition while reducing lignin content. Sugar release from enzymatic saccharification was enhanced, in some cases possibly due to a synergy between white-rot fungi and mild alkali pretreatments. For example, in A. dealbata stems treated with alkali and P. ostreatus, saccharification yield was 702.3 nmol mg⁻¹, which is higher than the samples treated only with alkali (608.1 nmol mg⁻¹), and 2.9-fold higher than the non-pretreated controls (243.9 nmol mg⁻¹). By characterising biomass and pretreatments, generated data creates value for unused biomass resources, contributing to the implementation of sustainable biorefining systems. In due course, the generated value will lead to economic incentives for landowners to cut back invasive Acacia spp. more frequently, thus reducing excess biomass, which exacerbates wildfire risk.

1. Introduction

Trees and shrubs of the Acacia genus originate in Australia and belong to the Fabaceae, subfamily Mimosoideae, comprising more than 1350 species [1]. In Europe, particularly in Portugal, Acacia dealbata Link, Acacia longifolia (Andrews) Willd, and Acacia melanoxylon R.Br. are considered invasive species, having been brought as ornamentals to stabilise dunes and for timber and tanning applications [2]. These Acacia are highly adaptable to a wide range of soils with low fertility and have high growth rates, thus reducing the development of autochthonous species. Furthermore, they produce high amounts of biomass with high latent combustibility, which exacerbates wildfires. For this reason, there have been several studies focusing on the potential of Acacia spp. biomass for various applications [3,4], or the use of these species for the capture and sequestration of carbon [5], while reducing their impact on wildfires in Portugal [6].

Lignin content is positively correlated with the heat of combustion of wood [7]. Therefore, abundant lignin in the environment increases the risk of wildfires. Nonetheless, the high amounts of lignocellulosic biomass contained in these species can be used for various fermentation-based applications, from cellulosic ethanol [8] to biogas [9], or even for the production of lactic [10], citric [11], acetic [12], and succinic acids [13], via lignocellulose fermentation. Alternatively, there is also a range of products that may be derived from hemicelluloses and lignin fractions. A few examples include the use of pentoses in hemicellulose hydrolysates for ethanol fermentation [14], xylitol and xylonate production via fermentation of xylose [15], or the use of lignin building blocks for the production of plastics, industrial additives or biomedical applications [16].

The present work focused mainly on the conversion of Acacia spp. cell wall glycans into fermentable sugars via enzymatic saccharification. Lignocellulosic biomass is highly recalcitrant to enzymatic deconstruction; hence pretreatments are usually employed to reduce recalcitrance. Pretreatments have the purpose of altering the biomass structure by disrupting their inter-unit covalent and non-covalent interactions [17]. Alkaline pretreatments have been considered particularly promising procedures to increase the biodegradability of lignocellulosic feedstocks [18]. In contrast to acid pretreatments, mild alkali does not cause a significant release of individual monosaccharide components, as these pretreatments primarily lead to solvation and saponification of the cell wall, thereby making cellulose more accessible to hydrolytic enzymes [19,20,21,22]. Mild alkali pretreatment has been proven to significantly increase enzymatic saccharification yields [23,24], and consequently, we employed it here.

Biological pretreatments, namely by fungi, are another promising biomass pretreatment method [25,26]. Here, we hypothesise that biological pretreatment of wood with white-rot fungi (WRF) could significantly improve the results obtained by a mild alkali pretreatment. The capacity of WRF to selectively degrade lignin without extensive cellulose degradation is a characteristic that makes them ideally suited for biodelignification applications, where lignin or various phenolic compounds must be altered or removed [27,28]. WRF have developed ligninolytic enzymatic machinery, including a wide range of peroxidases and laccases [29,30,31]. These diverse enzymatic pools allow WRF to deal with different compositional and structural aspects and depolymerise lignin. In the wild, WRF might have a beneficial effect on wildfire prevention, as they reduce lignin content and thus reduce the calorific value of the biomass. From a biorefinery perspective, biological pretreatments have been less considered than thermochemical ones, possibly because the industry often finds slower processing rates unattractive. However, this problem can be addressed by continuous flow processing systems [32]. Furthermore, although compared to other pretreatments, WRF involve longer processes, the energy requirements are low, and treatment conditions are mild and more environment-friendly [33,34]. In this study, we aim to evaluate a bio-alkali pretreatment process (fungal pretreatment combined with 0.1 M NaOH) for the bioconversion of Acacia dealbata, A. longifolia and A. melanoxylon into fermentable sugars. The studied Acacia spp. have high fire tolerance, and their spread is promoted in post-fire conditions. Creating applications for acacia biomass will generate an economic incentive for landowners to more frequently cut back these invasive species, thus preventing wildfires and reducing their severity.

2. Results

2.1. Acacia Cell Wall Compositional Characterisation and Pretreatment Effects

FTIR-ATR was used for the characterisation of alcohol-insoluble residues (AIR) from A. dealbata, A. longifolia and A. melanoxylon. The most noticeable distinct spectral regions between the species are highlighted (Figure 1). For leaf and stem biomass, eight distinct regions were identified, centred at (cm⁻¹): 1728 (a), 1640 (b), 1612 (c), 1314 (d), 1238 (e), 1166 (f), 1055 (g) and 1030 (h) (Table 1).

There was a predominance of bands ascribed to polysaccharides, with spectral regions a and e having been assigned to xylan structural features (Table 1). Bands g and h have been attributed to vibration in cellulose. Regarding lignin, band c was ascribed to aromatic skeletal vibrations and d was assigned to syringyl monomer vibrations. The spectral data show that leaf biomass has a more divergent composition than stem biomass in Acacia spp. For the latter, the most prominent difference was higher intensities of lignin signals (band c, 1612 cm⁻¹) in A. longifolia.

To assess the effect of a mild alkali pretreatment on the cell wall from A. dealbata, A. longifolia, and A. melanoxylon, AIR samples were treated with 0.1 M NaOH for 24 h at 21 °C (AIK). FTIR-ATR was subsequently employed to assess the main compositional changes effected by the alkali. For stem, of the three examined species, pretreated biomass showed a reduction in the a (1728 cm⁻¹) and e (1238 cm⁻¹) spectral regions (Figure 2). For leaf, a reduction in the intensities was additionally observed in region f (1166 cm⁻¹). Band a was assigned to C=O stretching in xylans, band e is associated with C-O vibrations of acetyl, and band f was ascribed to glycosidic stretching in polysaccharides.

In addition to the mild-alkali pretreatment, the samples were pretreated with white-rot fungi (WRF). To assess the effect of these pretreatments on composition, FTIR-ATR was employed (Figure 3). Interestingly, the effect of a given WRF species varies between different biomass species. Similarly, the same biomass is differently affected by each WRF species. In leaf treated only with WRF, most of the variation was observed in the b and c spectral regions, where both showed higher intensities in relation to the non-WRF treated (NF) control samples. In stems, the most affected regions when only WRF pretreatment was employed also are b and c bands, showing higher intensities than NF, particularly in A. dealbata and A. melanoxylon. When the combined WRF-ALK pretreatments were employed, the effect of the fungi is once again seen in regions b and c of the spectra of leaves. For stems, the WRF-ALK-treated samples were less altered in relation to the biomass treated only with the mild alkali pretreatment.

2.2. Saccharification Yields of Acacia Biomass

An enzymatic saccharification assay was performed on all samples to compare biorefining potentials between the different acacia species and to investigate the effect of the applied pretreatments. AIR prepared from A. dealbata biomass showed the highest saccharification yields in leaves and in stems: 125.5 and 197.9 nmol mg⁻¹ after 8 h incubation, respectively (Figure 4 and Table 2). The AIR samples were also treated with a mild alkali pretreatment (AIK) 0.1 M NaOH (24 h at 21 °C). In these samples, A. dealbata also showed the highest saccharification yield in leaf and stem samples: 243.3 nmol mg⁻¹ and 690.0 nmol mg⁻¹. Saccharification yields were typically higher from stems than leaves.

For each of the applied pretreatments, the percentage of recovered solids was calculated (Supplementary Table S1) for each species and organ. From WRF-treated leaf samples, typically 94% of the biomass is recovered after a 30-day incubation. In stems, the value is 96% for the same conditions. When the 0.1 M NaOH mild alkali pretreatment alone is employed, 93% of leaf and 96% of stem biomass is recovered. As for combined WRF-ALK pretreatments, recovered percentages drop to 90% from leaves and 94% from stems.

Biomass treated with WRF showed increased saccharification yields under selected conditions when compared with NF controls (Figure 4B,E; green bars). In leaves, the highest saccharification yield from samples treated with WRF alone was observed using T. versicolor on A. dealbata biomass (240.8 nmol mg⁻¹; Figure 4), 72.0% higher than NF controls (p ≤ 0.05; Figure 4). For stems, the highest value was 276.9 nmol mg⁻¹ obtained from treating A. dealbata with P. ostreatus.

A mild alkali pretreatment (0.1 M NaOH; 24 h; 21 °C) was also employed in sequence with the WRF pretreatment (Figure 4C,F; blue bars) to extract compounds which may have a negative effect on saccharification. This alkaline treatment substantially increased saccharification yields. The highest, significantly different (p ≤ 0.05) saccharification yield in relation to the controls was seen with A. dealbata stems treated with P. ostreatus and 0.1 M NaOH (702.3 nmol mg⁻¹; Figure 4 blue bars).

Given that most of the highest saccharification yields were obtained from biomasses treated with P. ostreatus, subsequent cell wall and pretreatment liquid fraction compositional analyses were performed only for samples treated with this ligninolytic fungal species.

2.3. Acacia Cell Wall Neutral Sugars and Lignin Composition

The major cell wall neutral sugars and lignin contents were determined for leaf and stem samples from the acacia species examined in this study. In non-pretreated control samples, the biomass from leaves contained (% AIR dry weight, DW): 14.5% glucose, 7.1% xylose, 2.7% arabinose and 16.7% lignin for A. dealbata; 15.8% glucose, 6.6% xylose, 1.8% arabinose and 13.8% lignin for A. longifolia; 18.3% glucose, 7.8% xylose, 3.3% arabinose, and 18.3% lignin for A. melanoxylon (Figure 5 and Table 3). For these four parameters measured in leaves, the values were typically higher in A. melanoxylon. In stem biomass, the corresponding values were: 37.1% glucose, 16.4% xylose, 1.3% arabinose, and 19.2% lignin for A. dealbata; 42.3% glucose, 14.5% xylose, 1.2% arabinose and 20.0% lignin for A. longifolia; 25.7% glucose, 11.8% xylose, 1.9% arabinose, and 19.7% lignin for A. melanoxylon (Table 3). Highest glucose and lignin content was found in A. longifolia, whereas the highest xylose was in A. dealbata and arabinose in A. melanoxylon.

In biomass treated with WRF, 0.1 M NaOH mild alkali or a combination of both, in most cases, neutral sugar composition did not change significantly in relation to the non-pretreated samples (p > 0.05). Despite not being significantly different, in some cases, samples with WRF or ALK showed slightly higher amounts of neutral sugars compared with non-pretreated biomass. These slight increases, particularly in alkali-pretreated samples, are likely to be related to the pretreatment effect, which improved acid hydrolysis efficiency. By contrast, statistically significant differences for lignin were found (p ≤ 0.05; Figure 5). There was a decrease in lignin content in relation to non-pretreated samples. These results demonstrate that the action of the employed pretreatments produces a decrease in lignin content without significantly affecting neutral sugar composition.

3. Discussion

3.1. Characterisation of the Biomass from Acacia Species

Acacia biomass has been considered for various applications, such as pulp manufacture, sawed wood or furniture. It may also be used as a raw material to obtain sugars and sugar oligomers from its polysaccharide components, namely from xylan, as acacias may be an interesting source of xylooligosaccharides [52]. A variety of analytical techniques was employed to determine the biomass composition and biorefining potential of A. dealbata, A. longifolia, and A. melanoxylon from marginal lands in Portugal. Leaf and stem were analysed separately in the present work instead of pooled total above-ground biomass, as each of these types of biomass have very distinct properties in a biorefinery context, namely because leaves are, to a large extent, composed of cells lacking secondary cell walls, which means less lignin content.

Alcohol insoluble residues (AIR) were prepared from non-pretreated biomass samples from leaf and stem from the acacia species under study. From this material, neutral sugars, and acetyl bromide soluble lignin contents were determined. The main neutral monosaccharides in all three acacia species were glucose, xylose, and arabinose, with a respectively overall mean of 16.2%, 7.2% and 2.6% for leaves, and 35.0%, 14.2% and 1.5% for stems. These values agree with data reported elsewhere for acacia stems [53,54]. As for leaves, no reports could be found in the literature about the composition of this organ’s biomass in these acacia species. Therefore, the present work may be the first to report such values. In all species, glucose and xylose content was higher in stems than in leaves, whereas for arabinose, the amounts were higher in leaves (Figure 5 and Table 3). Lignin was determined using the acetyl bromide method, showing an overall mean of 16.3% for leaves and 19.6% for stems of the studied species. Once again, these values agree with those reported elsewhere for the acacia stems [53,54].

FTIR-ATR analysis showed that in stems, the main difference between species is in band c (1612 cm⁻¹), which has been ascribed to aromatic skeletal vibration. FTIR-ATR results also suggest that the wood from these three acacia species is less variable than leaf biomass. In leaves, presumably as a result of distinct leaf physiognomy between the species, there is more variability among the spectra and, thus, their composition. In stems, by contrast, despite the differences seen in glucose, xylose and arabinose, lignin content does not vary much between the species. Given the similarity among the wood of the different species, they can be processed using similar biorefining processes.

3.2. Mild Alkali Pretreatment and Impact on Saccharification

Mild alkali pretreatments have the potential to cause de-esterification in the biomass, minimising lignin and carbohydrate losses [55,56,57], resulting in increased biodegradability of lignocellulosic feedstocks [58,59]. To further understand the potential of the studied acacia biomasses for applications in biorefining, AIR samples were treated with a mild alkali pretreatment followed by enzymatic saccharification. The alkali pretreatment had a significant effect on saccharification (p ≤ 0.05; Figure 4), as AIK yields were, on average, 2.4-fold higher than AIR., being 1.6-fold for leaves, and 3.2-fold for stems. However, the increase also varied between the species (Table 2). The most substantial effect of the alkali pretreatment was seen in A. longifolia, as AIK yields were 4-fold higher in stems treated with a mild alkali. A. dealbata stems showed an increase in saccharification around 3.5-fold in AIK yields.

FTIR-ATR analysis (Figure 2) showed differences between AIR and AIK samples, particularly at spectral regions a (1728 cm⁻¹; assigned to C=O stretching in acetyl-xylans) and e (1238 cm⁻¹; attributed to C-O vibrations of acetyl) (Table 1). The intensity of these bands is reduced in pretreated biomass and is observed across all species. Nonetheless, the deacetylation effect appears to be more complete in stem biomass than in leaves. This is presumably due to the presence of higher amounts of secondary metabolites in leaves, given their more diversified physiological roles when compared to stems. For other lignocellulosic biomasses, it has been reported that alkaline saponification during mild alkali pretreatment can release acetyl ester substituents from heteroxylans [60]. This concurs with our results that the most noticeable and consistent compositional differences between AIR and AIK samples are seen with bands associated with xylan and acetyl substituents. These differences are the result of the loss of acetyl groups in the biomass, specifically in xylans, as O-acetylated xylan is the main source of acetylesters in lignocellulosic biomass [61].

3.3. Effects of White-Rot Fungi Pretreatments in Acacia Biomass

Polysaccharide hydrolysis is enhanced by the formation of pores in the plant cell wall during biodelignification, increasing saccharification yields [62]. As their hyphae penetrate the biomass, WRF degrades lignin more readily than holocellulose [31,63,64,65], and this trait was assessed by pretreating acacia biomass with these fungi. By comparing the FTIR-ATR spectra of stem biomass treated with WRF with the spectra from NF controls, we observed that stems are less affected by the fungal pretreatment than leaves (Figure 4). According to the modifications in the FTIR-ATR spectra of leaves, it is in A. dealbata that the most noticeable effect of the WRF treatment is observed, particularly in spectral regions b (1640 cm⁻¹) and c (1612 cm⁻¹). These regions have been correlated with non-esterified carboxyl groups in polysaccharides and aromatic skeletal vibration (Table 1). This may result from WRF-mediated de-esterification and modification of ester-linked phenolic hydroxycinnamates involved in cross-linking of cell wall polymers, including lignin [66,67].

In the saccharification assay performed in this study, an increase in saccharification yields in relation to the NF controls was observed in leaf biomass from A. dealbata treated with the three fungal species, and in A. longifolia treated with G. lucidum and P. ostreatus. For stems, yield increases were seen with A. dealbata treated with P. ostreatus, T. versicolor, and with A. melanoxylon treated with P. ostreatus. However, in other cases, when samples were treated with WRF, the saccharification yields were lower than the controls (Figure 4 and Table 2). This is presumably due to the release of enzyme-inhibitory compounds during fungal action. It is known that pretreatment-derived soluble compounds can inhibit saccharification by binding the hydrolytic enzymes [68,69,70]. To address this issue and enhance pretreatment efficiency, a mild alkali pretreatment was employed (0.1 M NaOH; 24 h; 21 °C), which substantially increased saccharification yields in relation to non-alkali treated samples. Our results suggest that a synergistic effect does occur when the WRF and mild alkali pretreatments are combined. In A. dealbata stems treated with alkali and P. ostreatus, the saccharification yield was 702.3 nmol mg⁻¹, which is higher than the samples treated only with alkali (608.1 nmol mg⁻¹), and 2.9-fold higher than the non-pretreated controls (243.9 nmol mg⁻¹) (Figure 4 and Table 2). Furthermore, lignin content in the pretreated samples is lower than in non-pretreated controls (Table 3 and Figure 5). It is likely that some lignin loss or structural alteration is responsible for the increase seen in saccharification yield. These modifications are likely to be in cell wall polymers, such as lignin, and ester-bound substituents, such as ferulic acid. A structurally compromised cell wall would be more susceptible to hydrolysis by cellulolytic enzymes, leading to increased saccharification yields.

4. Materials and Methods

4.1. Acacia Lignocellulosic Biomass

Biomass from wild-grown Acacia dealbata (ACD), A. longifolia (ACL) and A. melanoxylon (ACM) was collected at a location in Central Portugal, Serra da Boa Viagem (40.186115° N, 8.903903° W) replicating the biomass that would result from biomass clearings. Sampling was performed during late summer (September). All samples consisted of whole branches cut at trunk level from non-senesced, field-growing plants. For each species, two biological replicates were collected, discarding any seeds, fruits, or flowers, when present. Within a maximum of 5 h from the collection, all samples were stored at −80 °C until freeze-drying. Once dry, stems were separated from leaves, and individual organs were ground using a Retsch SR3 Rotor Beater Mill (Retsch, Haan, Germany) and passed through a perforated plate screen with 2 mm diameter holes.

4.2. Preparation of Alcohol Insoluble Residue

A procedure based on a protocol reported by da Costa et al. 2020 [71] was carried out to produce the alcohol-insoluble residue (AIR) used in the subsequent analyses. For each sample, approximately 1 g of ground plant biomass was extracted sequentially as follows: 30 mL 70% (v/v) aqueous ethanol (first for 12 h and then twice for 30 min in a shaking incubator set at 40 °C/150 rpm), three times with 20 mL chloroform/methanol (1:1 v/v) (30 min incubation at 25 °C and 150 rpm), and finally, three times with 15 mL acetone (30 min, at 25 °C/150 rpm). Between each extraction step, the material was collected by centrifugation at 2000× g for 10 min and the supernatants were discarded. Following the third acetone step, the samples were left to dry overnight in a fume hood.

4.3. Inoculum Preparation and Fungal Pretreatment

Ganoderma lucidum (GAN), Pleurotus ostreatus (PLE) and Trametes versicolor (TRA) were used as white-rot fungi (WRF) for biological pretreatments. As described elsewhere [72], morphological examination and molecular analysis targeting internally transcribed spacer (ITS) regions allowed the identification of the fungal species used in this study. Fungal inocula were prepared by culturing the individual WRF strains at 23 °C on 2.9% potato dextrose agar (PDA, Oxoid CM0139, Basingstoke, UK). After 10 days of growth, for each of the three WRF strains, inoculation disks (Ø = 10 mm) were taken from actively growing mycelium on the PDA plates and used to inoculate each sample of the lignocellulosic feedstocks (2 disks per sample), under solid state fermentation (SSF) conditions. To serve as solid media for WRF growth, the biomass was prepared as follows: approximately 1.5 g of previously dried and milled but not organic solvent-washed biomass was added to 5 mL deionised water and autoclaved in glass culture tubes capped with hydrophobic cotton. This was performed for each combination of the 3 WRF species and leaf or stem from the 3 acacia species. Additionally, non-inoculated biomass samples (non-WRF treated, NF controls) with an equal volume of deionised water added were included as negative controls. All cultures were incubated statically at 23 °C in the dark for 30 days, with a total of 48 duplicated samples: 3 acacia species × 2 organs (leaf or stem) × 4 treatments (3 WRF species plus control). WRF-pretreatment methodologies were adapted from procedures reported elsewhere [73,74]. After incubation, the inoculation disks were removed, 5 mL of deionised water was added, and the samples were thoroughly mixed and incubated at 30 °C for 24 h with constant mixing. Samples were then centrifuged (2000× g for 10 min), and supernatants were removed. The solid pretreated biomasses were washed twice with deionised water, dried at 60 °C, and stored for subsequent analyses and alkali pretreatment. For neutral sugars and lignin determinations, AIR samples were produced from this WRF-treated biomass (as described above).

4.4. Mild Alkali Pretreatment

A portion of the non-WRF treated (NF) and WRF-treated solid fractions (approximately 250 mg, dry weight) were subjected to a mild alkali treatment with 2.5 mL 0.1 M NaOH for 24 h at 150 rpm shaking at 21 °C. This step was performed with the aim of achieving biomass saponification and determining if combined WRF and mild alkali (WRF-ALK) pretreatments would act synergistically on the biomass, break ester-linkages, and release potentially valuable molecules. After the pretreatment, the samples were centrifuged (2000× g for 10 min), and the supernatants were discarded. The pretreated solids were washed 3 times in 5 mL of 0.025 M potassium acetate buffer (pH = 5.6) and twice with deionised water, dried at 60 °C, and stored for subsequent assays. For neutral sugars and lignin determinations, AIR samples were produced as described above from this alkali (ALK)-treated biomass. Furthermore, the alkali pretreatment was also employed on AIR samples prepared from non-WRF pretreated samples to assess the effect of 0.1 M NaOH on structural compounds. These samples are subsequently referred to as AIK.

4.5. Fourier-Transform Infrared Spectroscopy

Attenuated total reflectance Fourier transform mid-infrared (FTIR-ATR) spectroscopy was performed on all samples included in this study (AIR, AIK, WRF, ALK and WRF-ALK samples), as reported elsewhere [24]. Duplicate spectra were collected in the range 4000–400 cm⁻¹ using a Bruker Optics Vertex 70 FTIR spectrometer purged by CO₂-free dry air and equipped with a Brucker Platinum ATR single reflection diamond accessory. A Ge on KBr substrate beamsplitter and a liquid nitrogen-cooled wide-band mercury cadmium telluride (MCT) detector were used. Spectra were averaged over 32 scans at a resolution of 4 cm⁻¹, and the 3-term Blackman-Harris apodization function was applied. The Bruker Opus 8.1 software (Bruker Optics GmbH, Ettlingen, Germany) was also used to: (i) remove eventual H₂O and CO₂ contributions and (ii) spectral smoothing using the Savitzky-Golay algorithm (window: 17 pt.). Absorbance spectra were converted to text files, imported into MatLab (v. R2021b; MathWorks, Natick, MA, USA) and averaged. Full spectra, or fingerprint region spectra (1800–800 cm⁻¹), were vector normalised to unit length and the baseline was removed according to the automatic weighted least squares algorithm (polynomial order = 2) prior to statistical analysis using the Eigenvector PLS Toolbox (v. 9.0; Eigenvector Research, Wenatchee, WA, USA).

4.6. Saccharification

Non-pretreated, WRF-treated (30-day incubation with G. lucidum, T. versicolor or P. ostreatus) and mild alkali-treated biomass samples (ALK and WRF-ALK) were included in a saccharification assay, with four technical replicates for each sample, using an automatic platform as described elsewhere [75,76]. Briefly, 96-well plates containing biomass underwent saccharification analysis using a liquid handling platform (Tecan Evo 200; Tecan Group Ltd., Mannedorf, Switzerland) using enzymatic hydrolysis at 50 °C for 8 h. The enzyme cocktail contained commercially available Cellic CTec2 (Novozymes, Bagsvaerd, Denmark) in Na-Acetate buffer (25 mM; pH = 4.5) at 50 °C. The saccharification was performed in the liquid handling platform using a shaking Tecan reactor at an enzyme loading of 8 Filter Paper Units (FPU)/g. The reducing sugars released during hydrolysis were determined using a colorimetric assay involving 3-methyl-2-benzothiazolinone hydrozone (MTBH). Each plate contained standard reactions of 50 nmol, 100 nmol, and 150 nmol of glucose. Change in colour was read with a Tecan Sunrise microplate absorbance reader at 620 nm.

4.7. Neutral Monosaccharides

Acid hydrolysis and neutral monosaccharide determinations were performed as previously described [60], on non-pretreated, WRF-treated (30-day incubation with P. ostreatus) and mild alkali-treated (ALK and WRF-ALK) AIR samples. Briefly, 10 mg of each sample was weighed into 10 mL Pyrex glass tubes, and 100 μL H₂SO₄ (72% w/w) was added. Sealed tubes were left at 30 °C for 1 h. Samples were diluted to 4% H₂SO₄ (w/w) and autoclaved at 121 °C for 1 h. Once at room temperature, hydrolysates were neutralised using CaCO₃, and the tubes were centrifuged (2000× g for 10 min) to obtain a clear supernatant. Carbohydrate separation and detection were achieved using high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). The ICS-5000 ion chromatography system (Dionex, Sunnyvale, CA, USA) was operated at 45 °C using a CarboPac SA10 column with a CarboPac SA10G guard column. An eluent generator prepared 1 mM KOH for 14 min isocratic elution at 1.5 mL min⁻¹. Calibration standards (glucose, xylose and arabinose) were used for monosaccharide identification and quantitation.

4.8. Lignin Measurement

Acetyl bromide soluble lignin percentages were determined in duplicate for non-pretreated, WRF-treated (30-day incubation with P. ostreatus) and mild alkali-treated (ALK and WRF-ALK) AIR samples, as previously reported [77]. To approximately 10 mg of each sample, 500 μL of freshly prepared 25 % (v/v) acetyl bromide solution in glacial acetic acid was added, and the tubes were capped and left at 50 °C for a total of 3 h. Following lignin solubilisation, the tubes were cooled, and their contents were diluted by the addition of 2 mL of 2 M NaOH. A further addition of 350 μL of 0.5 M hydroxylamine hydrochloride to each tube ensured the decomposition of polybromide ions [78]. Final volumes were adjusted to 10 mL with glacial acetic acid and centrifuged (2000× g for 10 min) to produce particulate-free supernatants. From there, 200 μL of each sample was transferred to UV-transparent 96-well plates (UV-Star, Greiner Bio-One, Frickenhausen, Germany). Absorbance at 280 nm was measured with a plate reader (Perkin Elmer, Multimode Plate Reader 2300 EnSpire, Waltham, MA, USA). Blank negative controls were included, and their absorbance at 280 nm was set as the absorbance baseline. Lignin dry weight percentages were calculated according to Equation (1):

ABSL% = (A₂₈₀/(SAC × PL)) × (V_R/W_S) × 100%(1)

) where ABSL% is the acetyl bromide-soluble lignin percentage content; A₂₈₀ is the absorption reading at 280 nm; PL is the pathlength determined for the 96-well microplates with a volume of 200 μL per well used during the analysis (0.556 cm); V_R is the reaction volume (litres); W_S is the sample weight (g); and SAC is the specific absorption coefficient of 23.0772 g⁻¹ L cm⁻¹, as reported elsewhere [79].

4.9. Statistical Analysis

All univariate descriptive statistics, analyses of variance and Tukey’s range tests were performed using Statistica (v. 8.0; StatSoft, Tulsa, OK, USA). For the t-tests on spectral data to unveil the underlying chemometric relationships between FTIR-ATR spectra, an R-based data analysis platform was used [80].

5. Conclusions

This study focused on the assessment of the saccharification and valorisation potential of invasive vegetation. Under our experimental conditions, an increase in saccharification potential was observed when mild alkali pretreatment was employed, and a potential synergistic effect occurs when combined with WRF pretreatments. Moreover, the compositional characterisation and pretreatment mechanisms contribute to a better understanding of the potential routes for the valorisation of Acacia spp., thus advancing the research into novel lignocellulosic crops. The utilisation of lignocellulose for more sustainable production of biofuels and other biomaterials depends on a deep understanding of the feedstock composition and the mechanisms of action of the employed processing methodologies. Given their vigorous and spontaneous growth, biomass from the studied invasive Acacia spp. often accumulates excessively in unmanaged agroforestry areas, thus exacerbating wildfire risks. Open pile burning in the vicinity of biomass generation is frequently the only economic disposal option. By identifying economic opportunities for invasive vegetation valorisation, landowners would have a monetary incentive to cut back excessive vegetation more frequently and employ more efficient land management practices. As excessive vegetation can exacerbate wildfire risks, improved land management would help to control the spread of spontaneous high biomass-producing invasive species, mitigating the wildfire risk, which is a serious threat in Mediterranean-type climates.

Author Contributions

Conceptualization, R.M.F.d.C.; methodology, R.M.F.d.C. and R.S.; software, R.M.F.d.C. and R.S.; validation, M.B., L.D.G., J.M.C. and L.A.E.B.d.C.; formal analysis, R.M.F.d.C.; investigation, R.M.F.d.C.; resources, L.D.G., J.M.C. and L.A.E.B.d.C.; data curation, R.M.F.d.C.; writing—original draft preparation, R.M.F.d.C.; writing—review and editing, R.M.F.d.C., M.B., L.D.G., J.M.C. and L.A.E.B.d.C.; visualization, R.M.F.d.C.; supervision, M.B., L.D.G., J.M.C. and L.A.E.B.d.C.; project administration, R.M.F.d.C.; funding acquisition, M.B., L.D.G., J.M.C. and L.A.E.B.d.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Sample Availability

Samples of the compounds are not available from the authors.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Tables

Figure 1. Mean FTIR-ATR spectra of leaf and stem samples of three Acacia spp. in the range 1800–800 cm−1. Spectral bands: a, 1728 cm−1; b, 1640 cm−1; c, 1612 cm−1; d, 1314 cm−1; e, 1238 cm−1; f, 1166 cm−1; g, 1055 cm−1; h, 1030 cm−1.

Figure 2. Mean FTIR-ATR spectra of non-pretreated alcohol insoluble residue (AIR) and mild alkali-pretreated alcohol insoluble residue (AIK) Acacia spp. biomass. Spectral bands: a, 1728 cm−1; e, 1238 cm−1; f, 1166 cm−1.

Figure 3. Mean FTIR-ATR spectra of milled but not organic solvent-washed biomass samples from Acacia spp., treated with three white-rot fungi species (WRF; 30 days) and/or in combination with an alkali pretreatment. Spectral bands: b, 1640 cm−1; c, 1612 cm−1.

Figure 4. Saccharification of Acacia spp. biomass. Mean nmol of reducing sugar released per mg of biomass material (nmol mg−1) after 8 h incubation in a hydrolytic enzyme mixture. Red bars (A,D) refer to non-pretreated alcohol insoluble residue samples, without (AIR) or with (AIK), a mild alkali pretreatment. Green bars (B,E) refer to samples treated only with white rot fungi (WRF): G. lucidum, GAN; P. ostreatus, PLE; T. versicolor, TRA. Blue bars (C,F) designate treatments where the alkali treatment was employed subsequently to the WRF pretreatment. Pairwise t-tests were performed between each treatment and non-pretreated control samples (AIR; or NF, no fungi; striped bars) to evaluate the impact of the pretreatments. The treatments which are significantly different from the controls are marked with a “*” (p ≤ 0.05). Error bars represent the standard error of the sample replicates.

Figure 5. Mean percentage (%) composition of alcohol insoluble residues (AIR) prepared from pretreated biomass from three Acacia spp. Pretreatment acronyms: NP, non-pretreated control samples (striped bars); WRF, samples pretreated with P. ostreatus; ALK, alkali-pretreated samples; W + K, samples pretreated with P. ostreatus followed by alkali pretreatment. Pairwise t-tests were performed between each treatment and NP samples to evaluate the impact of the pretreatments; the treatments which are significantly different from the NP controls are marked with a “*” (p ≤ 0.05). Error bars represent the standard error of the sample replicates.

Table 1

Assignment of relevant FTIR-ATR absorption bands characteristic of cell wall biomass from Acacia spp.

Region	Band (cm−1)	Assignment	Cell Wall Feature
a	1728 [35,36,37]	C=O vibration	Xylan
b	1640 [38,39,40]	COO- vibrations	Non-esterified carboxyl groups
c	1612 [41,42,43]	Aromatic skeletal vibration	Lignin
d	1314 [37,42,44]	Syringyl monomer vibration	Lignin
e	1238 [37,45,46]	C-O vibrations of acetyl	Xylan
f	1166 [37,47,48,49]	O-C-O asymmetric stretching (glycosidic link) all residues	Polysaccharides
g	1055 [46,50,51]	C-O, C-C and O-C-H vibration	Cellulose
h	1030 [50,51]	C-O, C-C and C-C-O stretching	Cellulose

Table 2

Saccharification of leaf and stem biomass (nmol mg⁻¹) from Acacia spp. measured by a high-throughput saccharification assay after 8 h incubation in a hydrolytic enzyme mixture. Acronyms: AIR, alcohol insoluble residue; AIK, alcohol insoluble residue treated with a mild alkali pretreatment; NF, no fungi; GAN, G. lucidum; PLE, P. ostreatus; TRA, T. versicolor. Values are expressed as mean ± standard error.

	Leaf				Stem
	AIR	AIK			AIR	AIK
A. dealbata	125.5 ± 12.6	243.3 ± 7.7			197.9 ± 11.1	690.0 ± 16.7
A. longifolia	51.7 ± 5.6	79.2 ± 6.6			80.9 ± 9.1	324.0 ± 15.5
A. melanoxylon	81.8 ± 14.6	104.6 ± 12.4			195.6 ± 29.1	397.9 ± 71.2
	NF	GAN	PLE	TRA	NF	GAN	PLE	TRA	No alkali
A. dealbata	140.0 ± 18.2	208.0 ± 15.5	194.1 ± 16.9	240.8 ± 40.4	243.9 ± 21.7	200.1 ± 18.2	276.9 ± 27.0	265.9 ± 26.9
A. longifolia	115.1 ± 4.5	172.1 ± 12.8	172.1 ± 12.8	111.0 ± 16.2	230.7 ± 11.2	107.9 ± 5.3	162.5 ± 24.0	141.7 ± 2.6
A. melanoxylon	160.8 ± 17.8	129.3 ± 9.7	149.6 ± 3.4	138.9 ± 16.9	207.6 ± 16.3	133.6 ± 2.9	234.2 ± 20.9	162.5 ± 6.1
	NF	GAN	PLE	TRA	NF	GAN	PLE	TRA	Alkali
A. dealbata	243.4 ± 19.4	154.0 ± 10.8	179.6 ± 31.0	205.4 ± 38.8	608.1 ± 63.3	375.7 ± 7.5	702.3 ± 46.8	526.3 ± 80.5
A. longifolia	105.2 ± 13.9	81.6 ± 5.2	94.7 ± 3.2	107.4 ± 8.5	349.0 ± 50.0	258.8 ± 28.0	289.1 ± 24.8	254.7 ± 42.1
A. melanoxylon	166.7 ± 13.1	73.9 ± 10.9	70.6 ± 8.3	118.2 ± 18.9	236.4 ± 23.3	332.8 ± 52.4	369.8 ± 69.8	245.6 ± 17.1

Table 3

Mean percentage (%) composition of alcohol insoluble residues (AIR) prepared from pretreated biomass from three Acacia spp. Pretreatment acronyms: NP, non-pretreated control samples; WRF, samples pretreated with Pleurotus ostreatus; ALK, alkali-pretreated samples; WRF + ALK, samples pretreated with P. ostreatus followed by the alkali pretreatment. Values are the mean ± standard error of the sample replicates.

Leaf
	Glucose	Xylose	Arabinose	Lignin
NP	14.5 ± 0.6	7.1 ± 0.9	2.7 ± 0.4	16.7 ± 0.4	A. dealbata
WRF	15.8 ± 0.2	7.4 ± 0.3	2.4 ± 0.2	14.6 ± 0.8
ALK	19.3 ± 4.1	9.7 ± 1.6	2.8 ± 0.1	15.0 ± 0.7
WRF + ALK	18.3 ± 1.4	8.1 ± 0.8	2.8 ± 0.2	12.4 ± 0.6
NP	15.8 ± 1.0	6.6 ± 0.5	1.8 ± 0.3	13.8 ± 4.4	A. longifolia
WRF	14.3 ± 0.5	6.0 ± 0.8	1.6 ± 0.1	8.6 ± 0.7
ALK	17.8 ± 0.4	6.3 ± 0.3	1.9 ± 0.2	9.8 ± 2.6
WRF + ALK	17.5 ± 3.9	7.4 ± 1.8	2.0 ± 0.4	7.3 ± 0.2
NP	18.3 ± 0.6	7.8 ± 0.5	3.3 ± 0.3	18.3 ± 1.6	A. melanoxylon
WRF	19.3 ± 1.2	8.3 ± 1.3	3.2 ± 0.2	15.1 ± 0.4
ALK	20.4 ± 0.3	8.6 ± 0.5	3.4 ± 0.1	14.1 ± 2.4
WRF + ALK	20.6 ± 0.7	8.4 ± 0.3	3.7 ± 0.0	12.3 ± 0.9
Stem
	Glucose	Xylose	Arabinose	Lignin
NP	37.1 ± 0.4	16.4 ± 0.8	1.3 ± 0.1	19.2 ± 0.5	A. dealbata
WRF	39.7 ± 6.3	15.2 ± 0.1	1.1 ± 0.2	18.6 ± 0.6
ALK	39.3 ± 1.7	15.3 ± 0.3	1.5 ± 0.1	17.4 ± 0.4
WRF + ALK	43.1 ± 4.6	16.7 ± 1.5	1.3 ± 0.2	16.7 ± 0.6
NP	42.3 ± 0.1	14.5 ± 0.5	1.2 ± 0.0	20.0 ± 0.2	A. longifolia
WRF	36.0 ± 2.7	13.8 ± 1.5	1.4 ± 0.3	18.2 ± 0.1
ALK	40.0 ± 5.1	14.1 ± 1.2	1.5 ± 0.2	18.0 ± 0.5
WRF + ALK	40.5 ± 0.9	14.7 ± 0.1	1.6 ± 0.1	18.2 ± 1.3
NP	25.7 ± 0.3	11.8 ± 0.4	1.9 ± 0.0	19.7 ± 0.3	A. melanoxylon
WRF	29.9 ± 0.6	13.0 ± 1.3	1.9 ± 0.2	19.1 ± 0.1
ALK	34.6 ± 3.6	14.7 ± 1.2	1.8 ± 0.3	16.8 ± 0.4
WRF + ALK	32.4 ± 5.2	14.5 ± 2.4	1.9 ± 0.4	18.2 ± 0.4

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules27207006/s1, Table S1. Percentage of recovered biomass after white-rot fungi (WRF; 30-day incubation) and mild alkaline 0.1 M NaOH for 24 h at 21 °C (ALK) pretreatments.

References

1. Seigler, D.S. Phytochemistry of Acacia—Sensu lato. Biochem. Syst. Ecol.; 2003; 31, pp. 845-873. [DOI: https://dx.doi.org/10.1016/S0305-1978(03)00082-6]

2. Lourenço, A.; Baptista, I.; Gominho, J.; Pereira, H. The influence of heartwood on the pulping properties of Acacia melanoxylon wood. J. Wood Sci.; 2008; 54, pp. 464-469. [DOI: https://dx.doi.org/10.1007/s10086-008-0972-6]

3. Correia, R.; Quintela, J.C.; Duarte, M.P.; Gonçalves, M. Insights for the Valorization of Biomass from Portuguese Invasive Acacia spp. in a Biorefinery Perspective. Forests; 2020; 11, 1342. [DOI: https://dx.doi.org/10.3390/f11121342]

4. Nunes, L.J.R.; Raposo, M.A.M.; Meireles, C.I.R.; Pinto Gomes, C.J.; Ribeiro, N.M.C.A. Control of Invasive Forest Species through the Creation of a Value Chain: Acacia dealbata Biomass Recovery. Environments; 2020; 7, 39. [DOI: https://dx.doi.org/10.3390/environments7050039]

5. Nunes, L.J.R.; Raposo, M.A.M.; Meireles, C.I.R.; Pinto Gomes, C.J.; Almeida Ribeiro, N.M.C. Carbon Sequestration Potential of Forest Invasive Species: A Case Study with Acacia dealbata Link. Resources; 2021; 10, 51. [DOI: https://dx.doi.org/10.3390/resources10050051]

6. Nunes, L.J.R.; Raposo, M.A.M.; Meireles, C.I.R.; Gomes, C.J.P.; Ribeiro, N.M.C.A. The Impact of Rural Fires on the Development of Invasive Species: Analysis of a Case Study with Acacia dealbata Link. in Casal do Rei (Seia, Portugal). Environments; 2021; 8, 44. [DOI: https://dx.doi.org/10.3390/environments8050044]

7. White, R.H. Effect of lignin content and extractives on the higher heating value of wood. Wood Fiber Sci.; 1987; 19, pp. 446-452.

8. Liu, C.-G.; Xiao, Y.; Xia, X.-X.; Zhao, X.-Q.; Peng, L.; Srinophakun, P.; Bai, F.-W. Cellulosic ethanol production: Progress, challenges and strategies for solutions. Biotechnol. Adv.; 2019; 37, pp. 491-504. [DOI: https://dx.doi.org/10.1016/j.biotechadv.2019.03.002]

9. Mishra, A.; Kumar, M.; Bolan, N.S.; Kapley, A.; Kumar, R.; Singh, L. Multidimensional approaches of biogas production and up-gradation: Opportunities and challenges. Bioresour. Technol.; 2021; 338, 125514. [DOI: https://dx.doi.org/10.1016/j.biortech.2021.125514]

10. Ahmad, A.; Banat, F.; Taher, H. A review on the lactic acid fermentation from low-cost renewable materials: Recent developments and challenges. Environ. Technol. Innov.; 2020; 20, 101138. [DOI: https://dx.doi.org/10.1016/j.eti.2020.101138]

11. Mores, S.; Vandenberghe, L.P.d.S.; Magalhães Júnior, A.I.; de Carvalho, J.C.; de Mello, A.F.M.; Pandey, A.; Soccol, C.R. Citric acid bioproduction and downstream processing: Status, opportunities, and challenges. Bioresour. Technol.; 2021; 320, 124426. [DOI: https://dx.doi.org/10.1016/j.biortech.2020.124426] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33249260]

12. Ravinder, T.; Swamy, M.V.; Seenayya, G.; Reddy, G. Clostridium lentocellum SG6—A potential organism for fermentation of cellulose to acetic acid. Bioresour. Technol.; 2001; 80, pp. 171-177. [DOI: https://dx.doi.org/10.1016/S0960-8524(01)00094-3]

13. Mancini, E.; Mansouri, S.S.; Gernaey, K.V.; Luo, J.; Pinelo, M. From second generation feed-stocks to innovative fermentation and downstream techniques for succinic acid production. Crit. Rev. Environ. Sci. Technol.; 2020; 50, pp. 1829-1873. [DOI: https://dx.doi.org/10.1080/10643389.2019.1670530]

14. Silva, J.P.; Mussatto, S.I.; Roberto, I.C. The influence of initial xylose concentration, agitation, and aeration on ethanol production by Pichia stipitis from rice straw hemicellulosic hydrolysate. Appl. Biochem. Biotechnol.; 2010; 162, pp. 1306-1315. [DOI: https://dx.doi.org/10.1007/s12010-009-8867-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19946760]

15. Lekshmi Sundar, M.S.; Madhavan Nampoothiri, K. An overview of the metabolically engineered strains and innovative processes used for the value addition of biomass derived xylose to xylitol and xylonic acid. Bioresour. Technol.; 2022; 345, 126548. [DOI: https://dx.doi.org/10.1016/j.biortech.2021.126548]

16. Ragauskas, A.J.; Beckham, G.T.; Biddy, M.J.; Chandra, R.; Chen, F.; Davis, M.F. Lignin valorization: Improving lignin processing in the biorefinery. Science; 2014; 344, 709. [DOI: https://dx.doi.org/10.1126/science.1246843]

17. Muazzam, R.; Asim, A.M.; Uroos, M.; Muhammad, N.; Hallett, J.P. Evaluating the potential of a novel hardwood biomass using a superbase ionic liquid. RSC Adv.; 2021; 11, pp. 19095-19105. [DOI: https://dx.doi.org/10.1039/D1RA01328A]

18. Sheng, Y.; Lam, S.S.; Wu, Y.; Ge, S.; Wu, J.; Cai, L.; Huang, Z.; Le, Q.V.; Sonne, C.; Xia, C. Enzymatic conversion of pretreated lignocellulosic biomass: A review on influence of structural changes of lignin. Bioresour. Technol.; 2021; 324, 124631. [DOI: https://dx.doi.org/10.1016/j.biortech.2020.124631]

19. Hendriks, A.T.W.M.; Zeeman, G. Pretreatments to enhance the digestibility of lignocellulosic biomass. Bioresour. Technol.; 2009; 100, pp. 10-18. [DOI: https://dx.doi.org/10.1016/j.biortech.2008.05.027]

20. Xu, N.; Zhang, W.; Ren, S.; Liu, F.; Zhao, C.; Liao, H.; Xu, Z.; Huang, J.; Li, Q.; Tu, Y. et al. Hemicelluloses negatively affect lignocellulose crystallinity for high biomass digestibility under NaOH and H₂SO₄ pretreatments in Miscanthus. Biotechnol. Biofuels; 2012; 5, 58. [DOI: https://dx.doi.org/10.1186/1754-6834-5-58]

21. Li, C.; Sun, L.; Simmons, B.A.; Singh, S. Comparing the Recalcitrance of Eucalyptus, Pine, and Switchgrass Using Ionic Liquid and Dilute Acid Pretreatments. Bioenerg. Res.; 2013; 6, pp. 14-23. [DOI: https://dx.doi.org/10.1007/s12155-012-9220-4]

22. Wyman, C.E.; Dale, B.E.; Balan, V.; Elander, R.T.; Holtzapple, M.T.; Ramirez, R.S.; Ladisch, M.R.; Mosier, N.S.; Lee, Y.Y.; Gupta, R. et al. Comparative Performance of Leading Pretreatment Technologies for Biological Conversion of Corn Stover, Poplar Wood, and Switchgrass to Sugars. Aqueous Pretreatment of Plant Biomass for Biological and Chemical Conversion to Fuels and Chemicals; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2013; pp. 239-259.

23. Da Costa, R.M.F.; Pattathil, S.; Avci, U.; Winters, A.; Hahn, M.G.; Bosch, M. Desirable plant cell wall traits for higher-quality miscanthus lignocellulosic biomass. Biotechnol. Biofuels; 2019; 12, 85. [DOI: https://dx.doi.org/10.1186/s13068-019-1426-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31011368]

24. Da Costa, R.M.F.; Winters, A.; Hauck, B.; Martín, D.; Bosch, M.; Simister, R.; Gomez, L.D.; Batista de Carvalho, L.A.E.; Canhoto, J.M. Biorefining Potential of Wild-Grown Arundo donax, Cortaderia selloana and Phragmites australis and the Feasibility of White-Rot Fungi-Mediated Pretreatments. Front. Plant Sci.; 2021; 12, 679966. [DOI: https://dx.doi.org/10.3389/fpls.2021.679966] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34276732]

25. Intasit, R.; Khunrae, P.; Meeinkuirt, W.; Soontorngun, N. Fungal pretreatments of Napier grass and sugarcane leaves for high recovery of lignocellulosic enzymes and methane production. Ind. Crops Prod.; 2022; 180, 114706. [DOI: https://dx.doi.org/10.1016/j.indcrop.2022.114706]

26. Vyas, S.; Prajapati, P.; Shah, A.V.; Kumar Srivastava, V.; Varjani, S. Opportunities and knowledge gaps in biochemical interventions for mining of resources from solid waste: A special focus on anaerobic digestion. Fuel; 2022; 311, 122625. [DOI: https://dx.doi.org/10.1016/j.fuel.2021.122625]

27. Blanchette, R.A. Delignification by wood-decay fungi. Annu. Rev. Phytopathol.; 1991; 29, pp. 381-403. [DOI: https://dx.doi.org/10.1146/annurev.py.29.090191.002121]

28. Mahajan, S.; Jeremic, D.; Goacher, R.E.; Master, E.R. Mode of coniferous wood decay by the white rot fungus Phanerochaete carnosa as elucidated by FTIR and ToF-SIMS. Appl. Microbiol. Biotechnol.; 2012; 94, pp. 1303-1311. [DOI: https://dx.doi.org/10.1007/s00253-011-3830-1]

29. Ruiz-Dueñas, F.J.; Martínez, A.T. Microbial degradation of lignin: How a bulky recalcitrant polymer is efficiently recycled in nature and how we can take advantage of this. Microb. Biotechnol.; 2009; 2, pp. 164-177. [DOI: https://dx.doi.org/10.1111/j.1751-7915.2008.00078.x]

30. Dashtban, M.; Schraft, H.; Syed, T.A.; Qin, W. Fungal biodegradation and enzymatic modification of lignin. Int. J. Biochem. Mol. Biol.; 2010; 1, pp. 36-50.

31. López, A.M.Q.; Silva, A.L.d.S.; dos Santos, E.C.L. The Fungal Ability for Biobleaching/Biopulping/Bioremediation of Lignin-Like Compounds of Agro-Industrial Raw Material. Química Nova; 2017; 40, pp. 916-931. [DOI: https://dx.doi.org/10.21577/0100-4042.20170067]

32. Scott, G.M.; Akhtar, M.; Lentz, M.J.; Swaney, R.E. Engineering, scale-up, and economic aspects of fungal pretreatment of wood chips. Environ. Friendly Technol. Pulp Pap. Ind.; 1998; pp. 341-383.

33. Sun, Y.; Cheng, J. Hydrolysis of lignocellulosic materials for ethanol production: A review. Bioresour. Technol.; 2002; 83, pp. 1-11. [DOI: https://dx.doi.org/10.1016/S0960-8524(01)00212-7]

34. Suryadi, H.; Judono, J.J.; Putri, M.R.; Eclessia, A.D.; Ulhaq, J.M.; Agustina, D.N.; Sumiati, T. Biodelignification of lignocellulose using ligninolytic enzymes from white-rot fungi. Heliyon; 2022; 8, e08865. [DOI: https://dx.doi.org/10.1016/j.heliyon.2022.e08865] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35141441]

35. Gwon, J.G.; Lee, S.Y.; Doh, G.H.; Kim, J.H. Characterization of chemically modified wood fibers using FTIR spectroscopy for biocomposites. J. Appl. Polym. Sci.; 2010; 116, pp. 3212-3219. [DOI: https://dx.doi.org/10.1002/app.31746]

36. Sills, D.L.; Gossett, J.M. Using FTIR to predict saccharification from enzymatic hydrolysis of alkali-pretreated biomasses. Biotechnol. Bioeng.; 2012; 109, pp. 353-362. [DOI: https://dx.doi.org/10.1002/bit.23314]

37. Bekiaris, G.; Lindedam, J.; Peltre, C.; Decker, S.R.; Turner, G.B.; Magid, J.; Bruun, S. Rapid estimation of sugar release from winter wheat straw during bioethanol production using FTIR-photoacoustic spectroscopy. Biotechnol. Biofuels; 2015; 8, 85. [DOI: https://dx.doi.org/10.1186/s13068-015-0267-2] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26110018]

38. Chatjigakis, A.K.; Pappas, C.; Proxenia, N.; Kalantzi, O.; Rodis, P.; Polissiou, M. FT-IR spectroscopic determination of the degree of esterification of cell wall pectins from stored peaches and correlation to textural changes. Carbohydr. Polym.; 1998; 37, pp. 395-408. [DOI: https://dx.doi.org/10.1016/S0144-8617(98)00057-5]

39. Manrique, G.D.; Lajolo, F.M. FT-IR spectroscopy as a tool for measuring degree of methyl esterification in pectins isolated from ripening papaya fruit. Postharvest Biol. Technol.; 2002; 25, pp. 99-107. [DOI: https://dx.doi.org/10.1016/S0925-5214(01)00160-0]

40. Gannasin, S.P.; Ramakrishnan, Y.; Adzahan, N.M.; Muhammad, K. Functional and Preliminary Characterisation of Hydrocolloid from Tamarillo (Solanum betaceum Cav.) Puree. Molecules; 2012; 17, pp. 6869-6885. [DOI: https://dx.doi.org/10.3390/molecules17066869]

41. Ramirez, F.J.; Luque, P.; Heredia, A.; Bukovac, M.J. Fourier transform IR study of enzymatically isolated tomato fruit cuticular membrane. Biopolymers; 1992; 32, pp. 1425-1429. [DOI: https://dx.doi.org/10.1002/bip.360321102]

42. Pandey, K.K. A study of chemical structure of soft and hardwood and wood polymers by FTIR spectroscopy. J. Appl. Polym. Sci.; 1999; 71, pp. 1969-1975. [DOI: https://dx.doi.org/10.1002/(SICI)1097-4628(19990321)71:12<1969::AID-APP6>3.0.CO;2-D]

43. Nogales-Bueno, J.; Baca-Bocanegra, B.; Rooney, A.; Hernández-Hierro, J.M.; Byrne, H.J.; Heredia, F.J. Study of phenolic extractability in grape seeds by means of ATR-FTIR and Raman spectroscopy. Food Chem.; 2017; 232, pp. 602-609. [DOI: https://dx.doi.org/10.1016/j.foodchem.2017.04.049]

44. Chen, H.; Ferrari, C.; Angiuli, M.; Yao, J.; Raspi, C.; Bramanti, E. Qualitative and quantitative analysis of wood samples by Fourier transform infrared spectroscopy and multivariate analysis. Carbohydr. Polym.; 2010; 82, pp. 772-778. [DOI: https://dx.doi.org/10.1016/j.carbpol.2010.05.052]

45. Marchessault, R. Application of infra-red spectroscopy to cellulose and wood polysaccharides. Pure Appl. Chem.; 1962; 5, pp. 107-130. [DOI: https://dx.doi.org/10.1351/pac196205010107]

46. Harrington, K.; Higgins, H.; Michell, A. Infrared spectra of Eucalyptus regnans F. Muell. and Pinus radiata D. Don. Holzforsch.-Int. J. Biol. Chem. Phys. Technol. Wood; 1964; 18, pp. 108-113. [DOI: https://dx.doi.org/10.1515/hfsg.1964.18.4.108]

47. Kačuráková, M.; Capek, P.; Sasinková, V.; Wellner, N.; Ebringerová, A. FT-IR study of plant cell wall model compounds: Pectic polysaccharides and hemicelluloses. Carbohydr. Polym.; 2000; 43, pp. 195-203. [DOI: https://dx.doi.org/10.1016/S0144-8617(00)00151-X]

48. Szymanska-Chargot, M.; Zdunek, A. Use of FT-IR Spectra and PCA to the Bulk Characterization of Cell Wall Residues of Fruits and Vegetables Along a Fraction Process. Food Biophys.; 2013; 8, pp. 29-42. [DOI: https://dx.doi.org/10.1007/s11483-012-9279-7]

49. Abidi, N.; Cabrales, L.; Haigler, C.H. Changes in the cell wall and cellulose content of developing cotton fibers investigated by FTIR spectroscopy. Carbohydr. Polym.; 2014; 100, pp. 9-16. [DOI: https://dx.doi.org/10.1016/j.carbpol.2013.01.074]

50. Wilson, R.H.; Smith, A.C.; Kacurakova, M.; Saunders, P.K.; Wellner, N.; Waldron, K.W. The Mechanical Properties and Molecular Dynamics of Plant Cell Wall Polysaccharides Studied by Fourier-Transform Infrared Spectroscopy. Plant Physiol.; 2000; 124, pp. 397-406. [DOI: https://dx.doi.org/10.1104/pp.124.1.397]

51. Schulz, H.; Baranska, M. Identification and quantification of valuable plant substances by IR and Raman spectroscopy. Vib. Spectrosc.; 2007; 43, pp. 13-25. [DOI: https://dx.doi.org/10.1016/j.vibspec.2006.06.001]

52. Yáñez, R.; Romaní, A.; Garrote, G.; Alonso, J.L.; Parajó, J.C. Experimental evaluation of alkaline treatment as a method for enhancing the enzymatic digestibility of autohydrolysed Acacia dealbata. J. Chem. Technol. Biotechnol.; 2009; 84, pp. 1070-1077. [DOI: https://dx.doi.org/10.1002/jctb.2136]

53. Yáñez, R.; Romaní, A.; Garrote, G.; Alonso, J.L.; Parajó, J.C. Processing of Acacia dealbata in Aqueous Media: First Step of a Wood Biorefinery. Ind. Eng. Chem. Res.; 2009; 48, pp. 6618-6626. [DOI: https://dx.doi.org/10.1021/ie900233x]

54. López-Hortas, L.; Rodríguez-González, I.; Díaz-Reinoso, B.; Torres, M.D.; Moure, A.; Domínguez, H. Tools for a multiproduct biorefinery of Acacia dealbata biomass. Ind. Crops Prod.; 2021; 169, 113655. [DOI: https://dx.doi.org/10.1016/j.indcrop.2021.113655]

55. Kong, F.; Engler, C.; Soltes, E. Effects of cell-wall acetate, xylan backbone, and lignin on enzymatic hydrolysis of aspen wood. Appl. Biochem. Biotechnol.; 1992; 34–35, pp. 23-35. [DOI: https://dx.doi.org/10.1007/BF02920531]

56. Chen, Y.; Stevens, M.; Zhu, Y.; Holmes, J.; Xu, H. Understanding of alkaline pretreatment parameters for corn stover enzymatic saccharification. Biotechnol. Biofuels; 2013; 6, 8. [DOI: https://dx.doi.org/10.1186/1754-6834-6-8]

57. Chen, X.; Shekiro, J.; Pschorn, T.; Sabourin, M.; Tao, L.; Elander, R.; Park, S.; Jennings, E.; Nelson, R.; Trass, O. et al. A highly efficient dilute alkali deacetylation and mechanical (disc) refining process for the conversion of renewable biomass to lower cost sugars. Biotechnol. Biofuels; 2014; 7, 98. [DOI: https://dx.doi.org/10.1186/1754-6834-7-98]

58. Jackson, M.G. Review article: The alkali treatment of straws. Anim. Feed Sci. Technol.; 1977; 2, pp. 105-130. [DOI: https://dx.doi.org/10.1016/0377-8401(77)90013-X]

59. Sharma, R.; Palled, V.; Sharma-Shivappa, R.; Osborne, J. Potential of Potassium Hydroxide Pretreatment of Switchgrass for Fermentable Sugar Production. Appl. Biochem. Biotechnol.; 2013; 169, pp. 761-772. [DOI: https://dx.doi.org/10.1007/s12010-012-0009-x]

60. Da Costa, R.M.F.; Pattathil, S.; Avci, U.; Lee, S.J.; Hazen, S.P.; Winters, A.; Hahn, M.G.; Bosch, M. A cell wall reference profile for Miscanthus bioenergy crops highlights compositional and structural variations associated with development and organ origin. New Phytol.; 2017; 213, pp. 1710-1725. [DOI: https://dx.doi.org/10.1111/nph.14306]

61. Pauly, M.; Scheller, H.V. O-Acetylation of plant cell wall polysaccharides: Identification and partial characterization of a rhamnogalacturonan O-acetyl-transferase from potato suspension-cultured cells. Planta; 2000; 210, pp. 659-667. [DOI: https://dx.doi.org/10.1007/s004250050057]

62. Chandel, A.K.; Gonçalves, B.C.M.; Strap, J.L.; da Silva, S.S. Biodelignification of lignocellulose substrates: An intrinsic and sustainable pretreatment strategy for clean energy production. Crit. Rev. Biotechnol.; 2015; 35, pp. 281-293. [DOI: https://dx.doi.org/10.3109/07388551.2013.841638] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24156399]

63. Valmaseda, M.; Martínez, M.J.; Martínez, A.T. Kinetics of wheat straw solid-state fermentation with Trametes versicolor and Pleurotus ostreatus—Lignin and polysaccharide alteration and production of related enzymatic activities. Appl. Microbiol. Biotechnol.; 1991; 35, pp. 817-823. [DOI: https://dx.doi.org/10.1007/BF00169902]

64. Taniguchi, M.; Suzuki, H.; Watanabe, D.; Sakai, K.; Hoshino, K.; Tanaka, T. Evaluation of pretreatment with Pleurotus ostreatus for enzymatic hydrolysis of rice straw. J. Biosci. Bioeng.; 2005; 100, pp. 637-643. [DOI: https://dx.doi.org/10.1263/jbb.100.637] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16473773]

65. Abdel-Hamid, A.M.; Solbiati, J.O.; Cann, I.K.O. Chapter One—Insights into Lignin Degradation and its Potential Industrial Applications. Advances in Applied Microbiology; Sariaslani, S.; Gadd, G.M. Academic Press: Cambridge, MA, USA, 2013; 82, pp. 1-28.

66. Ishii, T. Structure and functions of feruloylated polysaccharides. Plant Sci.; 1997; 127, pp. 111-127. [DOI: https://dx.doi.org/10.1016/S0168-9452(97)00130-1]

67. Ralph, J. Hydroxycinnamates in lignification. Phytochem. Rev.; 2010; 9, pp. 65-83. [DOI: https://dx.doi.org/10.1007/s11101-009-9141-9]

68. Biely, P. Microbial carbohydrate esterases deacetylating plant polysaccharides. Biotechnol. Adv.; 2012; 30, pp. 1575-1588. [DOI: https://dx.doi.org/10.1016/j.biotechadv.2012.04.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22580218]

69. Pawar, P.M.-A.; Koutaniemi, S.; Tenkanen, M.; Mellerowicz, E.J. Acetylation of woody lignocellulose: Significance and regulation. Front. Plant Sci.; 2013; 4, 118. [DOI: https://dx.doi.org/10.3389/fpls.2013.00118]

70. Zhai, R.; Hu, J.; Saddler, J.N. Minimizing cellulase inhibition of whole slurry biomass hydrolysis through the addition of carbocation scavengers during acid-catalyzed pretreatment. Bioresour. Technol.; 2018; 258, pp. 12-17. [DOI: https://dx.doi.org/10.1016/j.biortech.2018.02.124]

71. Da Costa, R.M.F.; Barrett, W.; Carli, J.; Allison, G.G. Analysis of Plant Cell Walls by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy. The Plant Cell Wall: Methods and Protocols; Popper, Z.A. Springer: New York, NY, USA, 2020; pp. 297-313.

72. Paiva de Carvalho, H.; Sequeira, S.O.; Pinho, D.; Trovão, J.; da Costa, R.M.F.; Egas, C.; Macedo, M.F.; Portugal, A. Combining an innovative non-invasive sampling method and high-throughput sequencing to characterize fungal communities on a canvas painting. Int. Biodeterior. Biodegrad.; 2019; 145, 104816. [DOI: https://dx.doi.org/10.1016/j.ibiod.2019.104816]

73. Salvachúa, D.; Prieto, A.; Lopez-Abelairas, M.; Lú-Chau, T.; Martínez, A.T.; Martínez, M.J. Fungal pretreatment: An alternative in second-generation ethanol from wheat straw. Bioresour. Technol.; 2011; 102, pp. 7500-7506. [DOI: https://dx.doi.org/10.1016/j.biortech.2011.05.027]

74. Sun, F.-h.; Li, J.; Yuan, Y.-x.; Yan, Z.-y.; Liu, X.-f. Effect of biological pretreatment with Trametes hirsuta yj9 on enzymatic hydrolysis of corn stover. Int. Biodeterior. Biodegrad.; 2011; 65, pp. 931-938. [DOI: https://dx.doi.org/10.1016/j.ibiod.2011.07.001]

75. Gomez, L.D.; Whitehead, C.; Barakate, A.; Halpin, C.; McQueen-Mason, S. Automated saccharification assay for determination of digestibility in plant materials. Biotechnol. Biofuels; 2010; 3, 23. [DOI: https://dx.doi.org/10.1186/1754-6834-3-23]

76. Whitehead, C.; Gomez, L.D.; McQueen-Mason, S.J. The Analysis of Saccharification in Biomass Using an Automated High-Throughput Method. Methods Enzymol.; 2012; 510, pp. 37-50. [DOI: https://dx.doi.org/10.1016/B978-0-12-415931-0.00003-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22608720]

77. Da Costa, R.M.F.; Lee, S.J.; Allison, G.G.; Hazen, S.P.; Winters, A.; Bosch, M. Genotype, development and tissue-derived variation of cell-wall properties in the lignocellulosic energy crop Miscanthus. Ann. Bot.; 2014; 114, pp. 1265-1277. [DOI: https://dx.doi.org/10.1093/aob/mcu054] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24737720]

78. Monties, B. Lignins. Methods in Plant Biochemistry; Dey, P.M.; Harborne, J.B. Academic Press: New York, NY, USA, 1989; Volume 1, pp. 113-158.

79. Fukushima, R.S.; Kerley, M.S. Use of Lignin Extracted from Different Plant Sources as Standards in the Spectrophotometric Acetyl Bromide Lignin Method. J. Agric. Food Chem.; 2011; 59, pp. 3505-3509. [DOI: https://dx.doi.org/10.1021/jf104826n]

80. Chong, J.; Soufan, O.; Li, C.; Caraus, I.; Li, S.; Bourque, G.; Wishart, D.S.; Xia, J. MetaboAnalyst 4.0: Towards more transparent and integrative metabolomics analysis. Nucleic Acids Res.; 2018; 46, pp. W486-W494. [DOI: https://dx.doi.org/10.1093/nar/gky310]