SciELO - Scientific Electronic Library Online

 
vol.61 número2NANOSTRUCTURAL CHARACTERIZATION AND LATTICE STRAIN OF TiO2-Al2O3-SiO2 COATING ON GLASS AND SI (100) SUBSTRATESVARIATION IN ANTIOXIDANT ATTRIBUTES AND INDIVIDUAL PHENOLICS OF CITRUS FRUIT PEELS IN RELATION TO DIFFERENT SPECIES AND EXTRACTION SOLVENTS índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • En proceso de indezaciónCitado por Google
  • No hay articulos similaresSimilares en SciELO
  • En proceso de indezaciónSimilares en Google

Compartir


Journal of the Chilean Chemical Society

versión On-line ISSN 0717-9707

J. Chil. Chem. Soc. vol.61 no.2 Concepción jun. 2016

http://dx.doi.org/10.4067/S0717-97072016000200006 

 

CHARACTERIZATION OF TEMPORAL BIODEGRADATION OF RADIATA PINE BY GLOEOPHYLLUM TRABEUM THROUGH PRINCIPAL COMPONENT ANALYSIS-BASED TWO-DIMENSIONAL CORRELATION FTIR SPECTROSCOPY

 

CLAUDIO POZO1, JUDITH DÍAZ-VISURRAGA1, DAVID CONTRERAS2,4, JUANITA FREER2,4, JAIME RODRÍGUEZ2,3

1 Centro de Investigación de Polímeros Avanzados (CIPA) CONICYT- REGIONAL R08C1002. Av. Collao №1202 Edificio Lab. CIPA, Concepción, Chile
2
Centro de Biotecnología, Universidad de Concepción. Barrio Universitario s/n, Casilla 160-C, Concepción, Chile
3
Facultad de Ciencias Forestales, Universidad de Concepción. Victoria 631, Casilla 160-C, Concepción, Chile
4
Facultad de Ciencias Químicas, Universidad de Concepción. Edmundo Larenas 129, Casilla 160-C, Concepción, Chile
* e-mail: c.pozo@cipachile.cl


ABSTRACT

Brown rot fungi produce a special pattern of wood decay. In the first stages of biodegradation, fast depolymerisation of holocellulose causes a rapid loss of wood strength while lignin is not substantially depolymerized. Fourier Transform Infrared Spectroscopy (FTIR) is a powerful tool for examining changes in wood chemistry. FTIR is an accurate, non-destructive technique, which usually requires a minimum of sample preparation and sample size. Principal component analysis-based two-dimensional (PCA2D) correlation spectroscopy of a spectral data set was applied to assess temporal brown-rot wood decay. Pinus radiata with soil support was degraded by brown rot fungi Gloeophyllum trabeum for a period of 0, 1, 2, 3, 4, 8, 12 and 16 weeks simulating the natural process of biodegradation. Decayed samples were monitored and analyzed periodically by FTIR. Most of the autopeaks had contributions from lignin, cellulose, and hemicelluloses. The main effect observed by PCA2D correlation was the significant decrease in the intensities of bands predominantly in the region of 2000-1000 cm-1, associated with polysaccharides in the biodegraded wood. An increase in the intensities of bands at 1698 and 1664 cm-1 associated with the oxidation of wood components, mostly lignin, was also observed. Detailed analysis of asynchronous map showed that the wood oxidation began after the depolymerisation of polysaccharides.

Keywords: FTIR-PCA2D correlation spectroscopy, Brown rot, Gloeophyllum trabeum.


 

1. INTRODUCTION

Brown rot fungi produce a special pattern of wood decay characterized by the oxidative degradation of wood cell wall components causing a rapid loss of wood strength 1. The degradation mechanism is based on iron reducing compounds of low molar mass which promote Fenton reactions 2-7.

The Fenton reaction (Fe(II) + H2O2 — Fe(III) + -OH + •OH) generates hydroxyl radicals from hydrogen peroxide which oxidize organic molecules 3, 8. Low molar mass dihydroxybenzenes (DHBs) and demethylated lignin, produced during brown rot degradation of wood, promote Fenton reactions by iron chelation and reduction 9. The first biodegradation stage consists of holocellulose depolymerisation 10. Brown rot fungi always remove hemicelluloses prior to amorphous and crystalline cellulose 1 and modify lignin through a demethylations process 11, 12. They also oxidize lignin side chains to a lesser extent without substantial depolymerisation 13.

Fourier transform infrared (FTIR) spectroscopy is a powerful tool for characterizing lignocellulosics and for examining changes in wood chemistry of materials subjected to chemical treatments and different environmental conditions 14. This technique is accurate, non-destructive and usually requires a minimum of sample preparation and sample size. Only few milligrams are required compared with conventional gravimetric techniques where several grams are required. Studies of fungal wood decay using mid infrared (MIR) techniques have been developed by several authors 15-18.

Two-dimensional correlation spectroscopy (2DCOS) is a technique for evaluating the relationships among different functional groups in the molecules 19. The concept has evolved into the so-called generalized two-dimensional correlation spectroscopy for the detailed analysis of various spectral data 20. The construction of 2DCOS is based on the detection of dynamic changes of a system under an external perturbation. Perturbation methods can include both static (e.g., temperature, composition, pressure and stress, spatial distribution and orientation) and dynamic types (e.g., rheo-optical and acoustic, chemical reactions and kinetics, H/D exchange, sorption and diffusion) 21. 2DCOS has been employed in the study of wood biodegradation by soft rot fungi 22.

2DCOS consists of two kinds of spectra, a synchronous and asynchronous map. The former represents coupled or related changes in spectral intensity, while the latter represents independent spectral variations 19, 20. The positive or negative signs of the synchronous and asynchronous correlation peaks can help to identify the sequence of the responses of various components induced by a specific external stimulus applied to the system 20. 2DCOS, including synchronous and asynchronous map, has been certainly one of the most sensitive techniques for interpreting spectral data sets obtained during the observation of a system under some external perturbation 23. However, for very noisy spectra it is difficult to separate completely the real signals from noise in 2D correlation spectra.

Principal component analysis-based two-dimensional (PCA2D) correlation spectroscopy is one of the most effective methods to improve the data quality for 2D correlation analysis. This processing implies a great advantage in terms of noise suppression for the generalized 2DCOS 24.

In this work, PCA2D correlation spectroscopy was applied to the analysis of the chemical changes occurring in brown-rotted wood (BRW), considering the spectral features observed as the result of the perturbation produced by the temporal wood biodegradation.

2. EXPERIMENTAL

2.1 Chemicals

Nanopure water (NPW) was used in all experiments and analyses. Soy protein acid hydrolysate (Sigma); Agar-agar for microbiology (Merck); Malt extract for microbiology (Merck) were used for culture medium. Potassium bromide (Merck) for IR spectroscopy was employed for FTIR characterization. For chemical analysis (unless otherwise stated, all reagents were p.a. grade): Sodium chloride 80% (Fluka); Copper(II) ethylenediamine solution (Merck); Sulphuric acid 98% (Merck); Acetone 99% (Merck).

2.2 Fungus inoculum preparation

Wood chips (heartwood and sapwood mixtures) were incubated on soil for 0, 1, 2, 3, 4, 8, 12 and 16 weeks. All the experiments were carried out in triplicate. It is noteworthy that the amount of heartwood is negligible in this wood.

Wood of radiata pine trees (20 year old) was chipped and screened to approximately 2.0 cm×2.5 cm×0.5 cm. The wood chips were immersed in water for 24 h, and then the residual water was drained off before autoclaving for 20 minutes at 121°C.

A stationary tray bioreactor, consisting of a 30 cm (length) × 20 cm (width) × 7 cm (height) plastic tray, was used in this experiment according to the method proposed by Akhtar et al. (1992) 25. Two hundred fifty cm3 of sieved soil (mesh 5), obtained from the forest reserves in Concepcion, Chile (36° 50' 29'' S, 73° 1' 33'' O), was autoclaved for 20 min at 121 °C. Three hundred g (on dry basis) of autoclaved chips were put in the tray bioreactor along with the soil.

Materials were autoclaved separately in order to avoid the diffusion of metals from soil to wood. The final moisture of wood was 60% and 37% for soil.

Gloeophyllum trabeum (ATCC 11539) cultures were maintained in water at 4 °C and then grown on agar-agar plates for 7 days at 25 °C. Erlenmeyer flasks containing 200 mL of nutritive medium (2% malt extract and 0.5% soy protein) were inoculated with 20 discs (8 mm diameter) cut from the G. trabeum culture. These liquid cultures were maintained under static conditions for 15 days at 25 °C. The mycelial pellets were then removed by filtration and washed with 500 mL of sterilized water. The washed mycelia from several flasks were blended with 100 mL of sterilized water for 15 s (three cycles) and used to inoculate the wood chips.

Inoculation of wood chips was performed before putting the wood on soil. Mycelium mass/wood ratio was 1000 mg kg-1 (on dry basis). Each stationary tray bioreactor was placed inside a sterile polypropylene containment bag. All cultures were incubated under static conditions at 25 °C for 0, 1, 2, 3, 4, 8, 12 and 16 weeks. At the end of each incubation period, the wood chips were separated from the soil, dried at 45°C for 48 h and stored under dry conditions for further characterization. The mycelium on the wood surface was not removed.

From each tray approximately 75 g of chips were collected by random sampling. Each replicate (3) was pulverized using a Cyclotec 1093 sample mill (Foss NIR Systems Inc.). After that, the samples were dried at 105 °C for 1h for the spectra acquisition.

After biodegradation, the wood chips were separated from soil, dried at 45°C for 48 h and stored in dry conditions for further characterization. The mycelium on the wood surface was not removed. Weight loss was calculated based on the initial and final dry weights. All values were corrected by weight loss except where otherwise noted.

2.3 Chemical analysis of the wood chips

For chemical analysis, air-dried samples were milled in a knife mill (Manesco & Ranieri) and passed through an 18 mesh. To obtain a representative sample, each sample was mixed and partitioned using a quartering method 26. Approximately 1 g of sample was extracted with 99% acetone for 16 h in a Soxhlet apparatus following standard method (TAPPI Test Method T 280 pm-99).

Total lignin content was determined by the sum of Klason lignin and soluble lignin in aqueous fraction. Klason lignin was determined in extractive-free wood samples according to TAPPI Standard T 222 om-98, 1998 and TAPPI Standard T 222 om-98, 1998. Acid insoluble lignin in wood and pulp, TAPPI T222 om-98 (1998). Soluble lignin in the aqueous fraction was determined by measuring the absorbance at 205 nm and by using an absorptivity of 105 Lg-1cm-1 27.

Chlorite holocellulose was prepared following standard method TAPPI T-9m-54. The volume and weight used in this procedure were scaled in proportion to the mass of air-dried wood used in each preparation.

Correlation between one dimensional FTIR and chemical properties of biodegraded wood chips (percent of weight loss, total lignin and holocellulose) were obtained using Statgraphics Plus 3.1 software (Manugistics Inc., Rockville, USA).

2.4 FTIR and PCA2D correlation analysis

FTIR spectra were recorded in a Perkin Elmer FT-2000 FTIR spectrometer in the range of 4000-400 cm-1 with a resolution of 4 cm-1 using the KBr pellet technique. Background and sample spectra were obtained from 64 scans. About 25 mg of sample was ground with 275 mg of dry potassium bromide and a pellet was formed using a press at a pressure of about 103.4 MPa. All spectra were baseline corrected around the spectral regions of 3800, 1800 and 800 cm-1, offsetting to a zero absorbance value, and then normalized on the basis of the internal standard band nearest to 1510 cm-1. The three spectra of each sample (independent triplicate) were averaged and a data matrix was created.

Prior to principal component analysis (PCA) calculations, the mean centering operation was performed on the data matrix. The 1800-800 cm-1 spectral range was considered, while the rest of data were excluded from the analysis.

The PCA2D correlation spectroscopy, synchronous and asynchronous maps were calculated according to algorithms described by Noda et al 23 and Jung et al 24. Data processing and analysis were performed using MATLAB software 7.4.0.287 R2007a (The Math Works, Inc.). PCA was performed using Pirouette software 3.11 (Infometrix Co., Tulsa, OK, USA).

According to Noda's rule 23 the intensity peaks located at diagonal positions v1 = v2 of the synchronous map are called autopeaks. These peaks are always positive and appear when there are changes in the region of interest in terms of intensity under a given perturbation. The off-diagonal peaks are called crosspeaks. They reflect changes at the same time but not necessarily in the same direction of the variations of two spectral intensities measured at v1 and v2. A positive synchronous crosspeak indicates that the variations in intensity of the two peaks at v1 and v2 proceed in the same direction during the observation period (both increases or both decreases), while a negative synchronous cros-speak of the two peaks at v1 and v2 shows that the changes are in the opposite directions (one increases, while the other one decreases). An asynchronous map has only off-diagonal peaks. In the synchronous map, the function between two wavenumbers (v1/v2) is defined by φ(v1, v2), while in the asynchronous map it is defined by ψ(v1,v2). According to the sequence rules proposed by Noda 23, if a crosspeak in the synchronous map φ(1, v2)> 0 and the crosspeak at the same position in the asynchronous map ψ(v1, v2)>0, the change at v1 occurs prior to that at v2. If the crosspeak in the asynchronous map is negative, the change at v2 occurs prior to that at v1. The rule is inverted for φ(v1, v2) < 0. All crosspeaks are represented as (v1/v2).

3. RESULTS AND DISCUSSION

3.1 One dimensional FTIR analysis

Fig. 1 shows the reconstructed FTIR spectra of decayed wood measured during the degradation process over a 16-week period. The reconstructed data matrix from the three principal components was used instead of the original raw spectral data matrix for the subsequent 2D correlation analysis. PCA factor 1 (PC1), factor 2 (PC2), and factor 3 (PC3) accounted for 96.1%, 2.8%, and 1.0%, of the total variance of spectral intensities, respectively. The spectral region between 1800-800 cm-1 is known as the fingerprint region of wood; this region is very complex because many bands have contributions from all components of wood (cellulose, hemicelluloses, and lignin) 28, 29. All FTIR spectra were normalized at 1510 cm-1 since this band is considered a 'pure' band related to the aromatic groups present in lignin 15. The observed changes in the FTIR spectrum of BRW in this study were consistent with previous reports 15, 17, 30. The intensity of principal bands studied within this spectral range is summarized in Table 1.

 

Figure 1. Reconstructed data of the FTIR spectra of the wood
sample studied from loading vectors and scores of PC1, PC2 and PC3
in 1800-800 cm-1. Arrows indicate the directions of the changes in
the intensity bands with increasing of biodegradation time.

 

Table 1. Assignment of principal infrared bands identified in radiata pine wood chips
biotreated by G. trabeum.

aG: guaiacyl, S: syringyl

 

The observed changes in the one dimensional FTIR spectra of biodegraded wood (Fig. 1), are reflected in the decreases in bands at 1205, 1161, 1108, 1058 and 997 cm-1, which are related to the strong absorption of -C-O- present in the polysaccharides 15. This decrease is due to the selective consumption of polysaccharides by brown rot fungi (Fig. 4). Another effect of the biodegradation process by brown rot fungi is reduced cellulose crystallinity 1. The -C-O-C- band at 1161 cm-1 is sensitive to changes in cellulose crystallinity, with the band decreasing with decreasing crystallinity 31.

 

Figure 2. Power spectrum of BRW in the region of
1800-800 cm-1 and main peaks.

 

Figure 3. Two dimensional FTIR correlation analysis in the 1800-800 cm-1 × 1800-800 cm-1
region divided into quadrants, for synchronous (a-c) and asynchronous maps (d-f). Dark
and light color represent positive and negative cross peaks, respectively.

 

Figure 4. Temporal variation of weight loss and components
losses of radiate pine wood chips biotreated by G. trabeum.
Symbols: weight loss (squares), holocellulose (circles), lignin
(triangles). Standard deviations from triplicate experiments
are smaller than size of symbols.

 

The major softwood hemicelluloses are composed of partially acetylated galactoglucomannans and a small amount of arabino-4-O-methyglucoronoxylans 28. The decreases in bands at 1269 and 1229 cm-1 could be related to hemicelluloses biodegradation, since these bands result partially from acetyl and carboxylic vibration in xylan 32.

Softwood lignin is mainly composed of guaiacyl (G) units with small amounts of syringyl (S) and only traces of p-hydroxyphenyl type units 28. The FTIR spectrum of BRW revealed a predominance of G bands with higher intensities at 1269, 1229, and a shoulder around 855 cm-1. Softwood lignin absorbs near 1269 and 1229 cm-1 and hardwood lignin only absorbs at 1229 cm-1 35. Although the content of phenolic OH in BRW tends to increase over time 36, it is likely that this effect at 1371 and 1327 cm-1 was offset by the polysaccharide biodegradation.

The intensities of bands assigned to lignin at 1597 cm-1 showed an important increase; however, the bands in the fingerprint region contained further information about lignin and polysaccharide content. Bands at 1426, 1371, 1327, 1269 and 1229 cm-1 revealed an important decrease in the intensities that could be mainly attributed to biodegradation of polysaccharides.

The FTIR spectrum of all BRW samples displayed bands at 1597, 1510, and 1426 cm-1 corresponding to the aromatic ring vibrations of the phenyl propane skeleton 37, with weaker changes at 1597 cm-1 than carbohydrates bands (Table 1). This confirms that the "core" of the lignin structure did not change dramatically during the biodegradation process, showing a low rate of mass loss (Fig. 4). The intensity of the band at 1426 cm-1 decreased due to degradation of associated polysaccharides.

Bands at 1738, 1698 and 1664 cm-1 could be related to oxidative processes produced by brown rot fungi. The small change in intensities of the band at 1738 cm-1 can be explained because the changes caused by oxidation were offset by depolymerization of xylan, which absorbs at this band 17.

Peaks at 1161, 1108, 1058 and 997 cm-1 were obviously stronger than other prominent peaks at 1738, 1698, 1664, 1464, 1426, 1371, 1327, 1229 and 895 cm-1 (Fig. 2). The strong peaks indicated that polysaccharides were highly susceptible to biodegradation by brown rot fungi (Fig. 4). Bands associated with C-O, C-C and C-O-C stretching vibrations of cellulose and hemicelluloses showed greater changes in intensity; this is consistent with the known wood decay pathway of brown rot fungi which preferably degrade hemicellulose and cellulose, leaving a chemically modified, depolymerised lignin residue 11, 12.

3.2 Two dimensional FTIR correlation analysis

The range 1800-800 cm-1 × 1800-800 cm-1 was divided into four quadrants for better interpretation of the synchronous and asynchronous map. The 18001200 cm-1 × 1800-1200 cm-1 and 1200-800 cm-1 × 1200-800 cm-1 quadrants were used for autopeak analysis. The 1800-1200 cm-1 × 1200-800 cm-1 quadrant was used for crosspeak analysis (Fig. 3). A power spectrum, corresponding to the synchronous correlation intensity along the diagonal line, illustrates the extent of the intensity changes (Fig. 2).

The synchronous map in the 1800-1200 cm-1 region (Fig. 3a) showed seven weak autopeaks on the diagonal at approximately 1698, 1664, 1426, 1371, 1327 and 1229 cm-1. Four strong autopeaks on the diagonal at approximately 1161, 1108, 1058, 997 cm-1 and a weak autopeak at approximately 895 cm-1 were observed in the region 1200-800 cm-1 (Fig. 3b). The absence of the band at 1033 cm-1 can be explained by the overlapping with the band at 1058 cm-1. Bands at 1738, 1597, 1510, 1464, 1269, 1205, 855 and 805 cm-1 showed no or very weak synchronous autopeaks.

The strong synchronous crosspeak 1698/1664 was positive, because both peaks changed in the same direction (both increased) (Fig. 3c). The band at 1698 cm-1 corresponded to unconjugated carbonyl groups, possibly due to the side chain oxidation of lignin 11 and carbonyl and carboxylic acid groups formed by free radical attack on cellulose during the biodegradation process 38. On the other hand, the band at 1664 cm-1 correspond to conjugated carbonyl groups, possibly orto-quinone structures resulting from the lignin modification by brown rot fungi 39.

Bands at 1698 and 1664 cm-1 show the following crosspeaks in the spectral range of 1800-800: negative strong synchronous crosspeaks at 1698/1426, 1698/1371, 1698/1229, 1664/1426, 1664/1371 and 1664/1327; negative weak synchronous crosspeaks at 1698/1464, 1698/1327, 1698/1161, 1698/1108, 1698/1058, 1698/997, 1664/1161, 1664/1108, 1664/1058, 1664/997 and 1664/895 (Fig. 3a, c); positive strong asynchronous crosspeaks at 1698/1426, 1698/1371, 1698/1327, 1698/1161, 1698/1108 and 1698/1058; and positive weak asynchronous crosspeaks at 1698/1464, 1698/1229 and 1698/997 (Fig. 3d, f).

According to Noda's rule, the bands associated with wood oxidation at 1698 and 1664 cm-1 were negatively correlated with bands of polysaccharides: 1464, 1426, 1371, 1327, 1229, 1161, 1108, 1058 and 997 cm-1. While the bands 1058 and 1229 cm-1 decreased in intensity with the decrease of the content of residual lignin and holocellulose (Fig. 5), the intensity of band 1698 cm-1 increased with increasing mass loss. This can be explained because the brown rot fungi selectively degraded polysaccharides, causing a decrease in absorbance of the bands associated with these polymers. At the same time, oxidized lignin and carbohydrates increased the absorbance of the bands associated with carbonyl and carboxylic acid groups 1.

 

Figure 5. Correlation between one dimensional FTIR and chemical properties of biodegraded
wood chips (percent of weight loss, total lignin and holocellulose).

 

Based on the rule of an asynchronous maps (Fig. 3d-f), the spectral intensity change at 1698 and 1664 cm-1 occurred after those at 1464, 1426, 1371, 1327, 1229, 1161, 1108, 1058 and 997 cm-1. This can be explained because the brown rot fungi mainly employ a non-enzymatic oxidative process at the beginning of the degradation process based on the Fenton reaction. The hydroxyl radicals involved are nonselective oxidants that attack all wood components 3. Polysaccharides are rapidly depolymerised in the early stages of biodegradation 10 producing smaller soluble oligosaccharides or monosaccharides that are used by the fungus in its metabolism 1, 11. In addition, brown rot fungi preferably degrade the S2 layer of the cell wall which contains more polysaccharides 1, 40.

Bands at 1161, 1108 and 1058 cm-1 corresponding to polysaccharides showed the following positive strong synchronous crosspeaks with mixed bands corresponding to polysaccharide and lignin at 1426/1161, 1426/1108, 1426/1058, 1371/1108, 1371/1058, 1327/1108, 1327/1058, 1229/1161, 1229/1108 and 1229/1058 (Fig. 3b, c); and negative strong asynchronous crosspeaks at 1426/1161, 1426/1108, 1426/1058, 1371/1108, 1371/1058, 1327/1108, 1327/1058, 1229/1161, 1229/1108 and 1229/1058 (Fig. 3e, f). Based on the rule of an asynchronous map, the spectral intensity change at 1161, 1108 and 1058 cm-1 occurred before those at 1464, 1426, 1371, 1327, 1229, 1161, 1108, 1058 and 997 cm-1. These bands are highly sensitive to the brown rot fungi biodegradation compared with mixed bands, possibly due to the C-O stretching vibration associated with hemicellulose, which is removed prior to amorphous and crystalline cellulose1. Bands at 1161, 1108 and 1058 cm-1 did not show asynchronous crosspeaks between them and according to Noda's rule, these bands vary together.

3.3 Correlation between standard methods of biodegradation and one dimensional FTIR analysis for wood biodegradation

Decayed wood chips exhibited a progressive weight loss reaching values of 38.5% after 16 weeks (Fig. 4). At the end of the period of biodegradation the wood progressively turned dark brown and became brittle to the touch, which are typical characteristics of the process of biodegradation by brown rot fungi.

Lignin loss reached values of 5.1% after 16 weeks of incubation. The low value of lignin loss is due to brown rot fungi do not degrade lignin extensively 41-44. However, lignin is chemically modified 11, 45. In contrast, mass loss of holocellulose reached values of 40.8% after 16 weeks (Fig. 4), which is consistent with the known wood decay pathway of brown rot fungi 1. The degree of holocellulose depolymerisation is consistent with previous studies that have shown that brown rot fungi rapidly depolymerise holocellulose in the early stages of biodegradation 10.

Three FTIR bands were selected to verify correlation between standard method of biodegradation and one dimensional FTIR analysis of biodegraded wood chips (Fig. 5). The selected bands were 1698cm-1, associated with the weight loss of wood, 1229 cm-1, associated with the lignin loss, and 1058 cm-1, associated with the holocellulose loss. The three bands showed high correlation with their respective chemical properties (R>0.85).

4. CONCLUSION

In conclusion, principal component analysis-based two-dimensional correlation FTIR spectroscopy was used to qualitatively characterize the temporal biodegradation of wood by brown rot fungi G. trabeum. Bands more sensitive to biodegradation by brown rot fungi were those associated with polysaccharides, as evidenced by the greater extent of intensity changes in absorbance of the bands at 1161, 1108, 1058 and 997 cm-1. Oxidation of wood components was observed by changes of intensities in absorbance bands at 1698, associated to carbonyl and carboxylic groups formed from cellulose, and at 1664 cm-1, associated with the oxidation of the aliphatic chain of lignin. It was possible to correlate intensity changes of absorbances at the bands 1698, 1229 and 1058 cm-1 with mass loss, lignin and holocellulose degradation, respectively. The inspection of asynchronous map revealed that wood oxidation began after depolymerization of polysaccharides.

ACKNOWLEDGEMENT

This work was supported by FONDECYT 1131101 and FONDECYT 3110094. CIPA Conicyt-Regional R08C1002 and CONICYT (Claudio Pozo PhD fellowship) is gratefully acknowledged.

 

REFERENCES

1. B. Goodell, in Wood Deterioration and Preservation. ACS Symposium Series 845. Brown-rot fungal degradation of wood: our evolving view, B. Goodell et al. eds., Washington DC American Chemical Society, 2003; pp. 97-118.         [ Links ]

2. B. Goodell, J. Jellison, J. Liu, G. Daniel, A. Paszczynski, F. Fekete, S. Krishnamurthy, L. Jun, G. Xu, J. Biotechnol. 53, 133, (1997).         [ Links ]

3. K. E. Hammel, A. N. Kapich, J. K. A. Jensen, Z. C. Ryan, Enzyme Microb. Technol. 30, 445, (2002).         [ Links ]

4. S. M. Hyde, P. M. Wood, Microbiology 143, 259, (1997)        [ Links ]

5. K. A. Jensen, Jr., C. J. Houtman, Z. C. Ryan, K. E. Hammel, Appl. Environ. Microbiol. 67, 2705, (2001).         [ Links ]

6. Z. Kerem, K. A. Jensen, K. E. Hammel, FEBSLett. 446, 49, (1999)        [ Links ]

7. J. Rodriguez, A. Ferraz, M. P. Mello, in Wood Deterioration and Preservation. ACS Symposium Series 845. Role of metals in wood biodegradation, B. Goodell, et al. eds., Washington DC American Chemical Society, 2003; pp. 154-174.         [ Links ]

8. P. M. Wood, FEMSMicrobiol. Rev. 13, 313, (1994).         [ Links ]

9. B. Goodell, G. Daniel, J. Jellison, Y. Qian, Holzforschung 60, 630, (2006).         [ Links ]

10. M. R. Suzuki, C. G. Hunt, C. J. Houtman, Z. D. Dalebroux, K. E. Hammel, Environ. Microbiol. 8, 2214, (2006).         [ Links ]

11. T. R. Filley, G. D. Cody, B. Goodell, J. Jellison, C. Noser, A. Ostrofsky, Org. Geochem. 33, 111, (2002).         [ Links ]

12. M. Lopretti, D. Cabella, J. Morais, A. Rodrigues, Process Biochem. 33, 657, (1998).         [ Links ]

13. V. A. Demin, V. V. Shereshovets, J. B. Monakov, Russ. Chem. Rev. 68, 937, (1999)        [ Links ]

14. A. K. Moore, N. L. Owen, Appl. Spectrosc. Rev. 36, 65, (2001)        [ Links ]

15. A. Ferraz, J. Baeza, J. Rodriguez, J. Freer, Bioresour. Technol. 74, 201, (2000)        [ Links ]

16. K. K. Pandey, J. Appl. Polym. Sci. 71, 1969, (1999)        [ Links ]

17. K. K. Pandey, A. J. Pitman, Int. Biodeterior. Biodegrad. 52, 151, (2003)        [ Links ]

18. G.-Y. Li, L.-H. Huang, C.-Y. Hse, T.-F. Qin, Carbohydr. Polym. 85, 560, (2011)        [ Links ]

19. I. Noda, Appl. Spectrosc. 44, 550, (1990)        [ Links ]

20. I. Noda, Appl. Spectrosc. 47, 1329, (1993).         [ Links ]

21. I. Noda, Chin. Chem. Lett. 26, 167, (2015).         [ Links ]

22. C.-M. Popescu, M.-C. Popescu, C. Vasile, Microchem. J. 95, 377, (2010).         [ Links ]

23. I. Noda, Appl. Spectrosc. 54, 994, (2000)        [ Links ]

24. Y. M. Jung, H. S. Shin, S. B. Kim, I. Noda, Appl. Spectrosc. 56, 1562, (2002).         [ Links ]

25. M. Akhtar, C. Attridge, C. G. Myers, K. T. Kirk, R. A. Blanchette, Tappi J. 75, 105, (1992).         [ Links ]

26. D. Harvey Modern analytical chemistry, McGraw-Hill Higher Education a Division of the McGraw-Hill, New York, NY, USA, 2000.         [ Links ]

27. C. W. Dence, in Methods in Lignin Chemistry. The Determination of Lignin, S. Lin, et al. eds. Springer Berlin, Heidelberg, 1992; pp. 33-61.         [ Links ]

28. J. Baeza, J. Freer, in Wood and cellulosic chemistry. Chemical characterization of wood and its components, D. N.-S. Hon, et al. eds. Marcel Dekker, Inc., New York, 2001; pp. 275-384.         [ Links ]

29. O. Faix, Holzforschung, 45, 21, (1991).         [ Links ]

30. K. K. Pandey, A. J. Pitman, Journal of Polymer Science Part A: Polymer Chemistry, 42, 2340, (2004).         [ Links ]

31. M. Schwanninger, J. C. Rodrigues, H. Pereira, B. Hinterstoisser, Vib. Spectrosc. 36, 23, (2004).         [ Links ]

32. K. Pandey, K. Theagarajan, Holz Roh Werkst. 55, 383, (1997).         [ Links ]

33. M. Kacuráková, P. Capek, V. Sasinková, N. Wellner, A. Ebringerová, Carbohydr. Polym. 43, 195, (2000).         [ Links ]

34. R. H. Marchessault, Pure Appl. Chem. 5, 107, (1962).         [ Links ]

35. K. V. Sarkanen, C. H., E. B., Tappi J. 50, 572, (1967).         [ Links ]

36. K. T. Kirk, Holzforschung, 29, 99, (1975).         [ Links ]

37. G. Xu, B. Goodell, J. Biotechnol. 87, 43, (2001).         [ Links ]

38. T. K. Kirk, R. Ibach, M. D. Mozuch, A. H. Conner, T. L. Highley, Holzforschung 45, 239, (1991).         [ Links ]

39. K. Li, X. Geng, Macromol. Rapid Commun. 26, 529, (2005).         [ Links ]

40. E. Sjöström Wood chemistry: Fundamentals and applications, Academic Press, San Diego, USA, 1993.         [ Links ]

41. I. Irbe, I. Andersone, B. Andersons, J. Chirkova, Int. Biodeterior. Biodegrad. 47, 37, (2001).         [ Links ]

42. I. Irbe, B. Andersons, J. Chirkova, U. Kallavus, I. Andersone, O. Faix, Int. Biodeterior. Biodegrad. 57, 99, (2006).         [ Links ]

43. J. E. Winandy, J. J. Morrell, Wood Fiber Sci. 25, 278, (1992).         [ Links ]

44. A. Machuca, A. Ferraz, EnzymeMicrob. Technol. 29, 386, (2001).         [ Links ]

45. L. Jin, T. P. Schultz, D. D. Nicholas, Holzforschung 44, 133, (1990).         [ Links ]

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons