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Characterization by pyrolysis-gas chromatography of wheat straw fermented with white rot fungus Stropharia rugosoannulata
129
Journal of Analytical and Applied Pyrolysis, 15 (1989) 129-136 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
CHARACTERIZATION BY PYROLYSIS-GAS CHROMATOGRAPHY OF WHEAT STRAW FERMENTED WITH WHITE ROT FUNGUS STROPHARIA RUGOSOANNULATA
G. CHIAVARI
* and 0. FRANCIOSO
Dipartimento di Chimica “G. Ciamician”, 40126 Bologna (Italy) G.C. GALLETTI
Universitci di Bologna,
Via Selmi, 2,
and R. PICCAGLIA
Centro di Studio per la Conservazione dei Foraggi, C. N.R., 40126 Bologna (Itab)
Via Fihppo Re, 8,
F. ZADRAiIL Institut fur Bodenbiologie, Bundesforschungsanstalt D-3300 Braunschweig (I? R. G.)
fur Landwirtschaft,
Bundesallee
50,
ABSTRACT Pyrolysis-gas chromatography was applied to a study of the changes in organic material during fungal fermentation processing of wheat straw. Native straw samples were subjected to pyrolysis using a 100 CDS Pyroprobe heated filament pyrolyser coupled directly to the injector of the gas chromatograph. Twenty-one pyrolytic fragments were identified by retention times and mass spectrometry using an on-line gas chromatography/ion trap detector instrument. Pyrograms are reported, as well as quantitative and statistical analyses of fifteen compounds, showing significant changes for six compounds. Biomass;
gas chromatography;
lignin; pyrolysis;
straw.
INTRODUCTION
The production of cereal straw in the European Community countries (excluding Portugal and Spain) currently exceeds 85 million tons year [l]. The straw consumption for feeding, bedding, composting and other uses leads to a surplus of about 23.8 million tons. The accumulation of such a large amount of organic waste points to the need for research aimed at finding solutions to the problem of the reutilization of such materials. A better utilization of straw surpluses can be found in such areas as fuel, feed, fiber and chemical compound production. 0165-2370/89/$03.50
0 1989 Elsevier Science Publishers
B.V.
130
For straw to be fully exploited as an animal feed, physical, chemical and/or microbiological treatments are required to upgrade the nutritional value of such agricultural by-products. A better characterization of the chemical compounds that affect the value of lignocellulosic materials is necessary. Lignin is of fundamental importance when considering the poor quality of straw as an animal feed [2] due to its well known antinutritional effect. Classical methods of lignin investigation have included oxidative chemical degradation followed by chromatographic separation (high-performance liquid chromatography and gas chromatography) of the lignin components [3]. There is a definite need for rapid and accurate methods applicable to the routine analysis of lignin-containing materials. Pyrolysis-gas chromatography (Py-GC) is advantageous in the rapid analysis of matrixes where the complexity of the natural macromolecules makes traditional analytical techniques difficult to use [4]. In particular, Py-GC studies of lignin- and cellulose-related substances have been carried out recently by Boon [5], Se&-Aspax et al. [6] and Schulten [7]. This work reports the application of Py-GC to the study of wheat straw fermented with white rot fungi in order to increase its digestibility. An attempt will be made to differentiate samples subjected to different fungal activity in terms of their Py-GC patterns. Mass spectra obtained with the ion trap detector (ITD) will also be shown and discussed.
MATERIALS
AND METHODS
The straw samples were prepared as described elsewhere [8]. Oxygen (2 l/day) was passed through a chain of 30 Erlenmayer flasks containing sterile
TABLE
1
Content and loss of lignin and in vitro digestibility of wheat straw samples white rot fungus Stropharia rugosoannulata (after Zadraiil and Karma [8]) Sample 1 3 5 7 9 13 21 30 l
Lignin content 16.97 19.11 20.64 21.38 24.08 24.96 25.07 23.61
s& of dry matter.
*
Loss of lignin *
In vitro digestibility
42.01 34.05 24.84 16.04 2.31 0.00 0.00 0.00
54.69 49.10 39.29 31.74 20.06 10.18 8.54 14.56
fermented
*
by
131
wheat straw and the white rot fungus (Stropharia rugosoannufata) to study the effect of oxygen on fungal degradation of lignin. Table 1 reports the lignin contents and in vitro digestibility [8] of the samples studied. Triplicate samples of straw, finely pulverized, were subjected to pyrolysis in a quartz holder. A CDS Pyroprobe 100 heated filament pyrolyser was used, fitted with a platinum coil probe. Pyrolysis was carried out at 600 o C for 5 seconds. The probe was coupled directly to a Carlo Erba HRGC with a flame ionization detector. An SE 54 capillary column (25 m X 0.32 mm I.D., film thickness 0.25 pm) was operated at a temperature programmed from 50 o C (10 min) to 250 o C at 5 o C/mm. An ITD (Finnigan MAT) model 600 set at 70 eV and equipped with the software Release 3.0 was employed for mass spectral analyses. Variance analysis was employed to check the variability of each of fifteen compounds in eight samples. When significant differences were found, a Duncan test was performed.
RESULTS AND DISCUSSION
Eight samples were selected from the chain of flasks in order to better represent the different stages of lignin degradation afforded by the fungi. Fungal activity has been shown to be high in the first flasks, where oxygen concentration is high, and low in the last flasks, where oxygen concentration is low [3]. Py-GC of the straw samples resulted in chromatographic profiles such as those reported in Figs. 1 and 2 for the first and last flask, respectively. The pyrolytic fragments were identified by mass spectrometry. Fig. 3 shows a reconstructed total ion chromatogram obtained with the ITD, while the results of the identification are summarized in Table 2. Identification of the mass spectra was performed on the basis of logical comparison with known spectra and by analogical interpretation of the Finnigan library software. Protonated molecular ions (M + H)+ were frequently found in the
0
10
20
Fig. 1. Pyrogram of sample 1. Peak letters as in Table 2.
30
mm
24
Q
C,H,ON
C,%O, C,H,% C,KP
122 138 120 154 152 164 166 180 194
84 86 86 96 98 98 84 99 _ 112 108 124 -
G W’ C,H,oO C,H,d’
4-Methyl-2,3_dihydrofuran Vinyl isopropyl ether (?) Methyl isopropyl ketone Furfural Furfuryl alcohol Furfuryl alcohol Dihydroxypyran Piperidone Unknown Methylcyclohexanone o-Cresol Guaiacol Unknown Unknown 2,4_DimethylphenoI Decahydronaphthalene Dihydrobenzofuran Unknown 3,CDimethoxyphenol Vanillin Eugenol Acetovanillone (?) Conyferyl alcohol 4-Allyl-2,6-dimethoxyphenol
74 140 144 188 229 248 363 380 515 562 596 636 679 705 711 757 794 883 920 968 1004 1043 1102 1206
1A 2 3B 4c 5 6 7D SE 9F 10 G 11 12 H 13 I 14 15 16 17 L 18 M 19 N 20 0 21 P 22 23
‘4HJb
MW
Formula
Compound
Scan
fragments
Peak
of the main pyrolytic
identification
Proposed
TABLE 2
45 43 43 39 43 43 55 99 114 113 108 124 126 42 43 138 120 150 154 151 164 151 180 194
m/t (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
(s)
55 39 39 55 39 39 125 127 43 122 67 110 151 155 153 103 43 137 91
44 (35) 95 (75) 81 (70) 44 85 43 115 112 43 109 43 56 107 123 39 107 39 152 39 66 165 119
(25) (35) (98) (90) (98) (92) (43) (98) (95) (88) (67) (41) (20) (18) (85) (35) (48) (22) (21)
57 69 75 97 39
44 (27) 87 (60)
(7) (32) (98) (30) (65) (87) (32) (95) (70) (70) (43) (40) (20) (18) (45) (28) (48) (22) (21)
(5) (23) (15) (50) (47) 98 84 42 58 41 107 53 39 115 39 39 91 135 111 39 55 123 91 195
(3) (25) (88) (25) (65) (85) (20) (87) (55) (70) (35) (40) (16) (15) (32) (25) (30) (17) (20)
87 (8) 96 (35) 41 (35)
71 (4) 44 (22)
(3) (13) (60) (18) (55) (60) (15) (85) (52) (60) (25) (30) (8) (14) (28) (20) (28) (17) (18)
81 54 98 39 55 55 81 55 114 42 95 69 39 139 53 149 39 181 39
69 (3) 43 (15) 98 (30)
85 (4) 57 (18)
E
133
10 Fig. 2. Pyrogram
Fig. 3. Typical
TABLE
min
800
1200
total ion chromatogram
obtained
1600
1
2000
by Py-GC-ITD
scan number of straw samples.
3 values of 15 major fragments
from the pyrograms
of eight selected straw samples
Sample 1
3
5
7
9
13
21
30
A
22.38
21.24
20.34
21.28
19.54
20.66
22.28
20.43
B
9.41
9.77
9.18
8.50
9.02
8.77
9.32
9.60
C
7.69
6.61
6.26
6.79
5.93
5.54
5.71
5.69
D
4.54
3.93
4.19
3.50
3.60
3.58
1.70
3.10
E
13.41
10.52
8.90
8.42
10.38
8.52
9.65
8.40
F
3.74
2.41
4.29
2.90
3.32
2.63
2.41
1.30
G
5.60
5.78
5.33
5.80
5.08
4.87
4.83
5.37
H
7.59
7.33
7.58
6.46
6.18
6.09
5.73
6.48
I
6.34
6.19
6.08
5.92
5.17
5.70
5.42
6.01
L
5.09
6.06
6.75
8.12
9.71
10.01
10.25
9.68
M
5.74
8.45
8.34
8.78
9.69
10.14
10.23
11.07
N
4.80
5.59
5.56
5.53
5.42
6.05
4.94
4.99
0
1.67
1.80
2.29
2.07
2.16
2.04
1.67
1.76
1.75
2.44
2.65
2.37
2.59
2.60
2.63
2.46
1.34
1.88
1.95
2.66
2.68
2.80
3.22
3.84
:
Peak
as in Table 2.
Normalized Peak
30
of sample 30. Peak letters as in Table 2.
400 numbers
20
134 TABLE 4 Variance
analysis and Duncan
test of the six significantly
Variance analysis: * * Significant differences ent letters are different at P < 0.01. Peak
at
different
pyrolytic
fragments
P < 0.01. Duncan test: samples with differ-
Sample
c ** D ** H ** L** M ** ** Q
1
3
5
7
9
13
21
30
A A A C C D
AB A AB C B D
AB A A BC B CD
AB A ABC ABC B BC
B A BC AB AB BC
B A BC AB AB B
B B C A AB AB
B AB ABC AB A A
spectra. This can be attributed to proton exchange during the residence of the ions in the ITD. The eight selected straw samples did not show qualitative differences in the composition of the major components of the pyrograms. The normalized areas of the fifteen main peaks are reported in Table 3. The results of
lo--
3
Z >
B .-
.z
E.c
5--
flask
. 1
3
5
t
9
T--z
30
Fig. 4. Trends of the normalized values of three selected samples. (x): peak H; (0): peak L; (m): peak Q.
pyro-fragments
in the eight straw
135
400
200
9.
-100.
I
3
5
7
9
13
a ,
flark_@
2l
30
Fig. 5. Percentage variation of the sum of peaks A-G (0) and H-Q (m) relative to sample 1.
statistical analysis are reported in Table 4, along with the Duncan test. Variance analysis showed significant differences for compounds C, D, H, L, M and Q (P G 0.01). The Duncan test allows the identification of groups of samples, which might be correlated with the degree of fungal activity. Fig. 4 shows the quantitation of three typical components that may be taken as markers of fungal activity. The changes of some pyrolysis fragments in the eight samples are reported in Table 5 as percentage difference relative to the first flask. It is interesting to note (Fig. 5) that the sum of the relative change of aromatic compounds (H, L, M, N, 0, P and Q) increases from the first to the last flask ( + 399%) (r = 0.99) whereas fragments possibly originating from carbohydrates (A, B, C, D, E, F and G) present an opposing, but less-marked trend ( - 171%) (r = 0.75).
136 TABLE
5
Percentage Peak
variation
of some pyrolysis
Compound
fragments
&
Methyldihydrofuran Methyl isopropyl ketone Furfural Dihydropyran Piperidone Unknown Methylcyclohexanone Guaiacol Unknown Dihydrobenzofuran Unknown Dimethoxyphenol Vanillin Eugenol 4-Allyl-2,5-dimethoxyphenol
I
Sample 30
A B C D E F G H I L M N 0
relative to sample
-9 2 -26 -32 -37 -65 -4 -15 -5 90 93 4 5 40 187
21
13
9
7
5
0 -1 -26 -63 -28 -36 -14 -25 -15 101 78 3 0 50 140
-8 -7 -28 -21 -36 -30 -13 -20 -10 97 77 26 22 49 109
-13 -4 -23 -21 -23 -11 -9 -19 -18 91 69 13 29 48 100
-5 -10 -12 -23 -37 -22
-9 -2 -19 -8 -34 15 -5 0 -4 33 45 16 37 51 46
4 -15 -7 60 53 15 24 35 99
3 -5 4 -12 -13 -22 -36 3 -3 -2 19 42 15 8 39 40
In conclusion, Py-GC affords the prospect of rapid checking of fungal processing of straw through the monitoring of a few selected chromatographic markers. The reliability and reproducibility of Py-GC applied to this analytical problem made this method of practical utility, even for statistical investigations.
REFERENCES Commission of the European Communities, rue de la Loi, Bruxelles. DGVI progrannne: energy in agriculture. Topic: straw as an energy source. Final report, August 1987, Lyon. H.G. Jung and G.C. Fahey, Jr., Nutritional implications of phenolic monomers and lignin: a review, J. Anim. Sci., 57 (1983) 206. G. Chiavari, V. Concialini and G.C. Galletti, Electrochemical detection in the high performance liquid chromatographic analysis of plant phenolics, Analyst (London), 113 (1988) 91. W.J. Irwin, Analytical Pyrolysis, Marcel Dekker, New York, Basel, 1982, p. 352. J.J. Boon, An introduction to pyrolysis (gas chromatography) mass spectrometry of lignocellulosic material with case studies on barley straw var. OECD, corn stem var. BM, ETA, IPHO and LG 11 and Agropyron species, Proceedings of the COST-84 bis Workshop, Aberdeen, 1988, Elsevier, in press. A. Serbs-Aspax, J.M. Alcaiiiz-Baldellou and M. Gassiot-Matas, Application of pyrolysis-gas chromatography to the study of the composting process of barley straw and pear-tree wood, J. Anal. Appl. Pyrolysis, 8 (1985) 415. H.-R. Schulten, Pyrolysis and soft ionization mass spectrometry of aquatic/terrestrial humic substances and soils, J. Anal. Appl. Pyrolysis, 12 (1987) 149. F. Zadrtil and D.N. Kamra, Influence of gaseous metabolites on lignin degradation and its relation with in vitro digestibility with white rot fungi, Mushroom J. for the Tropics, in press.
Journal of Analytical and Applied Pyrolysis, 15 (1989) 129-136 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
CHARACTERIZATION BY PYROLYSIS-GAS CHROMATOGRAPHY OF WHEAT STRAW FERMENTED WITH WHITE ROT FUNGUS STROPHARIA RUGOSOANNULATA
G. CHIAVARI
* and 0. FRANCIOSO
Dipartimento di Chimica “G. Ciamician”, 40126 Bologna (Italy) G.C. GALLETTI
Universitci di Bologna,
Via Selmi, 2,
and R. PICCAGLIA
Centro di Studio per la Conservazione dei Foraggi, C. N.R., 40126 Bologna (Itab)
Via Fihppo Re, 8,
F. ZADRAiIL Institut fur Bodenbiologie, Bundesforschungsanstalt D-3300 Braunschweig (I? R. G.)
fur Landwirtschaft,
Bundesallee
50,
ABSTRACT Pyrolysis-gas chromatography was applied to a study of the changes in organic material during fungal fermentation processing of wheat straw. Native straw samples were subjected to pyrolysis using a 100 CDS Pyroprobe heated filament pyrolyser coupled directly to the injector of the gas chromatograph. Twenty-one pyrolytic fragments were identified by retention times and mass spectrometry using an on-line gas chromatography/ion trap detector instrument. Pyrograms are reported, as well as quantitative and statistical analyses of fifteen compounds, showing significant changes for six compounds. Biomass;
gas chromatography;
lignin; pyrolysis;
straw.
INTRODUCTION
The production of cereal straw in the European Community countries (excluding Portugal and Spain) currently exceeds 85 million tons year [l]. The straw consumption for feeding, bedding, composting and other uses leads to a surplus of about 23.8 million tons. The accumulation of such a large amount of organic waste points to the need for research aimed at finding solutions to the problem of the reutilization of such materials. A better utilization of straw surpluses can be found in such areas as fuel, feed, fiber and chemical compound production. 0165-2370/89/$03.50
0 1989 Elsevier Science Publishers
B.V.
130
For straw to be fully exploited as an animal feed, physical, chemical and/or microbiological treatments are required to upgrade the nutritional value of such agricultural by-products. A better characterization of the chemical compounds that affect the value of lignocellulosic materials is necessary. Lignin is of fundamental importance when considering the poor quality of straw as an animal feed [2] due to its well known antinutritional effect. Classical methods of lignin investigation have included oxidative chemical degradation followed by chromatographic separation (high-performance liquid chromatography and gas chromatography) of the lignin components [3]. There is a definite need for rapid and accurate methods applicable to the routine analysis of lignin-containing materials. Pyrolysis-gas chromatography (Py-GC) is advantageous in the rapid analysis of matrixes where the complexity of the natural macromolecules makes traditional analytical techniques difficult to use [4]. In particular, Py-GC studies of lignin- and cellulose-related substances have been carried out recently by Boon [5], Se&-Aspax et al. [6] and Schulten [7]. This work reports the application of Py-GC to the study of wheat straw fermented with white rot fungi in order to increase its digestibility. An attempt will be made to differentiate samples subjected to different fungal activity in terms of their Py-GC patterns. Mass spectra obtained with the ion trap detector (ITD) will also be shown and discussed.
MATERIALS
AND METHODS
The straw samples were prepared as described elsewhere [8]. Oxygen (2 l/day) was passed through a chain of 30 Erlenmayer flasks containing sterile
TABLE
1
Content and loss of lignin and in vitro digestibility of wheat straw samples white rot fungus Stropharia rugosoannulata (after Zadraiil and Karma [8]) Sample 1 3 5 7 9 13 21 30 l
Lignin content 16.97 19.11 20.64 21.38 24.08 24.96 25.07 23.61
s& of dry matter.
*
Loss of lignin *
In vitro digestibility
42.01 34.05 24.84 16.04 2.31 0.00 0.00 0.00
54.69 49.10 39.29 31.74 20.06 10.18 8.54 14.56
fermented
*
by
131
wheat straw and the white rot fungus (Stropharia rugosoannufata) to study the effect of oxygen on fungal degradation of lignin. Table 1 reports the lignin contents and in vitro digestibility [8] of the samples studied. Triplicate samples of straw, finely pulverized, were subjected to pyrolysis in a quartz holder. A CDS Pyroprobe 100 heated filament pyrolyser was used, fitted with a platinum coil probe. Pyrolysis was carried out at 600 o C for 5 seconds. The probe was coupled directly to a Carlo Erba HRGC with a flame ionization detector. An SE 54 capillary column (25 m X 0.32 mm I.D., film thickness 0.25 pm) was operated at a temperature programmed from 50 o C (10 min) to 250 o C at 5 o C/mm. An ITD (Finnigan MAT) model 600 set at 70 eV and equipped with the software Release 3.0 was employed for mass spectral analyses. Variance analysis was employed to check the variability of each of fifteen compounds in eight samples. When significant differences were found, a Duncan test was performed.
RESULTS AND DISCUSSION
Eight samples were selected from the chain of flasks in order to better represent the different stages of lignin degradation afforded by the fungi. Fungal activity has been shown to be high in the first flasks, where oxygen concentration is high, and low in the last flasks, where oxygen concentration is low [3]. Py-GC of the straw samples resulted in chromatographic profiles such as those reported in Figs. 1 and 2 for the first and last flask, respectively. The pyrolytic fragments were identified by mass spectrometry. Fig. 3 shows a reconstructed total ion chromatogram obtained with the ITD, while the results of the identification are summarized in Table 2. Identification of the mass spectra was performed on the basis of logical comparison with known spectra and by analogical interpretation of the Finnigan library software. Protonated molecular ions (M + H)+ were frequently found in the
0
10
20
Fig. 1. Pyrogram of sample 1. Peak letters as in Table 2.
30
mm
24
Q
C,H,ON
C,%O, C,H,% C,KP
122 138 120 154 152 164 166 180 194
84 86 86 96 98 98 84 99 _ 112 108 124 -
G W’ C,H,oO C,H,d’
4-Methyl-2,3_dihydrofuran Vinyl isopropyl ether (?) Methyl isopropyl ketone Furfural Furfuryl alcohol Furfuryl alcohol Dihydroxypyran Piperidone Unknown Methylcyclohexanone o-Cresol Guaiacol Unknown Unknown 2,4_DimethylphenoI Decahydronaphthalene Dihydrobenzofuran Unknown 3,CDimethoxyphenol Vanillin Eugenol Acetovanillone (?) Conyferyl alcohol 4-Allyl-2,6-dimethoxyphenol
74 140 144 188 229 248 363 380 515 562 596 636 679 705 711 757 794 883 920 968 1004 1043 1102 1206
1A 2 3B 4c 5 6 7D SE 9F 10 G 11 12 H 13 I 14 15 16 17 L 18 M 19 N 20 0 21 P 22 23
‘4HJb
MW
Formula
Compound
Scan
fragments
Peak
of the main pyrolytic
identification
Proposed
TABLE 2
45 43 43 39 43 43 55 99 114 113 108 124 126 42 43 138 120 150 154 151 164 151 180 194
m/t (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
(s)
55 39 39 55 39 39 125 127 43 122 67 110 151 155 153 103 43 137 91
44 (35) 95 (75) 81 (70) 44 85 43 115 112 43 109 43 56 107 123 39 107 39 152 39 66 165 119
(25) (35) (98) (90) (98) (92) (43) (98) (95) (88) (67) (41) (20) (18) (85) (35) (48) (22) (21)
57 69 75 97 39
44 (27) 87 (60)
(7) (32) (98) (30) (65) (87) (32) (95) (70) (70) (43) (40) (20) (18) (45) (28) (48) (22) (21)
(5) (23) (15) (50) (47) 98 84 42 58 41 107 53 39 115 39 39 91 135 111 39 55 123 91 195
(3) (25) (88) (25) (65) (85) (20) (87) (55) (70) (35) (40) (16) (15) (32) (25) (30) (17) (20)
87 (8) 96 (35) 41 (35)
71 (4) 44 (22)
(3) (13) (60) (18) (55) (60) (15) (85) (52) (60) (25) (30) (8) (14) (28) (20) (28) (17) (18)
81 54 98 39 55 55 81 55 114 42 95 69 39 139 53 149 39 181 39
69 (3) 43 (15) 98 (30)
85 (4) 57 (18)
E
133
10 Fig. 2. Pyrogram
Fig. 3. Typical
TABLE
min
800
1200
total ion chromatogram
obtained
1600
1
2000
by Py-GC-ITD
scan number of straw samples.
3 values of 15 major fragments
from the pyrograms
of eight selected straw samples
Sample 1
3
5
7
9
13
21
30
A
22.38
21.24
20.34
21.28
19.54
20.66
22.28
20.43
B
9.41
9.77
9.18
8.50
9.02
8.77
9.32
9.60
C
7.69
6.61
6.26
6.79
5.93
5.54
5.71
5.69
D
4.54
3.93
4.19
3.50
3.60
3.58
1.70
3.10
E
13.41
10.52
8.90
8.42
10.38
8.52
9.65
8.40
F
3.74
2.41
4.29
2.90
3.32
2.63
2.41
1.30
G
5.60
5.78
5.33
5.80
5.08
4.87
4.83
5.37
H
7.59
7.33
7.58
6.46
6.18
6.09
5.73
6.48
I
6.34
6.19
6.08
5.92
5.17
5.70
5.42
6.01
L
5.09
6.06
6.75
8.12
9.71
10.01
10.25
9.68
M
5.74
8.45
8.34
8.78
9.69
10.14
10.23
11.07
N
4.80
5.59
5.56
5.53
5.42
6.05
4.94
4.99
0
1.67
1.80
2.29
2.07
2.16
2.04
1.67
1.76
1.75
2.44
2.65
2.37
2.59
2.60
2.63
2.46
1.34
1.88
1.95
2.66
2.68
2.80
3.22
3.84
:
Peak
as in Table 2.
Normalized Peak
30
of sample 30. Peak letters as in Table 2.
400 numbers
20
134 TABLE 4 Variance
analysis and Duncan
test of the six significantly
Variance analysis: * * Significant differences ent letters are different at P < 0.01. Peak
at
different
pyrolytic
fragments
P < 0.01. Duncan test: samples with differ-
Sample
c ** D ** H ** L** M ** ** Q
1
3
5
7
9
13
21
30
A A A C C D
AB A AB C B D
AB A A BC B CD
AB A ABC ABC B BC
B A BC AB AB BC
B A BC AB AB B
B B C A AB AB
B AB ABC AB A A
spectra. This can be attributed to proton exchange during the residence of the ions in the ITD. The eight selected straw samples did not show qualitative differences in the composition of the major components of the pyrograms. The normalized areas of the fifteen main peaks are reported in Table 3. The results of
lo--
3
Z >
B .-
.z
E.c
5--
flask
. 1
3
5
t
9
T--z
30
Fig. 4. Trends of the normalized values of three selected samples. (x): peak H; (0): peak L; (m): peak Q.
pyro-fragments
in the eight straw
135
400
200
9.
-100.
I
3
5
7
9
13
a ,
flark_@
2l
30
Fig. 5. Percentage variation of the sum of peaks A-G (0) and H-Q (m) relative to sample 1.
statistical analysis are reported in Table 4, along with the Duncan test. Variance analysis showed significant differences for compounds C, D, H, L, M and Q (P G 0.01). The Duncan test allows the identification of groups of samples, which might be correlated with the degree of fungal activity. Fig. 4 shows the quantitation of three typical components that may be taken as markers of fungal activity. The changes of some pyrolysis fragments in the eight samples are reported in Table 5 as percentage difference relative to the first flask. It is interesting to note (Fig. 5) that the sum of the relative change of aromatic compounds (H, L, M, N, 0, P and Q) increases from the first to the last flask ( + 399%) (r = 0.99) whereas fragments possibly originating from carbohydrates (A, B, C, D, E, F and G) present an opposing, but less-marked trend ( - 171%) (r = 0.75).
136 TABLE
5
Percentage Peak
variation
of some pyrolysis
Compound
fragments
&
Methyldihydrofuran Methyl isopropyl ketone Furfural Dihydropyran Piperidone Unknown Methylcyclohexanone Guaiacol Unknown Dihydrobenzofuran Unknown Dimethoxyphenol Vanillin Eugenol 4-Allyl-2,5-dimethoxyphenol
I
Sample 30
A B C D E F G H I L M N 0
relative to sample
-9 2 -26 -32 -37 -65 -4 -15 -5 90 93 4 5 40 187
21
13
9
7
5
0 -1 -26 -63 -28 -36 -14 -25 -15 101 78 3 0 50 140
-8 -7 -28 -21 -36 -30 -13 -20 -10 97 77 26 22 49 109
-13 -4 -23 -21 -23 -11 -9 -19 -18 91 69 13 29 48 100
-5 -10 -12 -23 -37 -22
-9 -2 -19 -8 -34 15 -5 0 -4 33 45 16 37 51 46
4 -15 -7 60 53 15 24 35 99
3 -5 4 -12 -13 -22 -36 3 -3 -2 19 42 15 8 39 40
In conclusion, Py-GC affords the prospect of rapid checking of fungal processing of straw through the monitoring of a few selected chromatographic markers. The reliability and reproducibility of Py-GC applied to this analytical problem made this method of practical utility, even for statistical investigations.
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