Effect of Brassica napus cultivar on cellulosic ethanol yield
Wood et al. Biotechnology for Biofuels
Effect of Brassica napus cultivar on cellulosic ethanol yield
Ian P. Wood 0
Nikolaus Wellner 2
Adam Elliston 0
David R. Wilson 0
Ian Bancroft 1
Keith W. Waldron 0
0 The Biorefinery Centre, Institute of Food Research , Norwich Research Park, Colney, Norwich NR4 7UA , UK
1 Department of Biology, University of York , Heslington, York YO10 5DD , UK
2 Analytical Sciences Unit, Institute of Food Research , Norwich Research Park, Colney, Norwich NR4 7UA , UK
Background: Intraspecific variations in biomass composition are likely to influence their suitability for biorefining. This may be particularly important in species such as Brassica napus, which contain many different crop types bred for different purposes. Here, straw derived from 17 B. napus cultivars, of varying crop types, were steam exploded, saccharified and fermented to establish differences in biomass composition relevant to cellulosic ethanol production. Results: Despite being grown and processed in the same manner, straw from the various cultivars produced different saccharification and fermentation yields after processing. Fermentation inhibitor abundances released by steam explosion also varied between genotypes. Cultivars with glucan-rich straw did not necessarily produce higher saccharification or ethanol yields after processing. Instead, the compositions of non-cellulosic components were more reliable indicators of substrate quality. The abundance of pectins and arabinogalactans had the greatest influence on saccharification efficiency between straw genotypes. Conclusions: In dicotyledonous species, such as B. napus, variations in the abundance of pectins between crop cultivars are likely to influence processing efficiency for bioethanol production. Knowledge of these genotypic variants provides targets for plant breeding and could aid in the development of improved cellulase cocktails.
Bioethanol; Biomass saccharification; Crop cultivars; Cultivar variation; Dicot; Dicotyledonous; Oilseed rape; Fermentation; Pretreatment; Rapeseed straw
Variations in biomass composition are likely to influence
their suitability for exploitation. Therefore, if biomass is
to be used to create sustainable products, such as
ethanol, we must first understand the compositional variants
that determine substrate quality . If the chemical basis
of biomass usability can be identified, both feedstock
and processing conditions can be improved.
Substrate variation is an important consideration for
industry for many reasons. If sufficient variation exists
between cultivars, it could be exploited by crop breeders
to improve feedstock quality . On the other hand,
cultivar variation may be undesirable to biorefinery
operators who are likely to require uniform and predictable
yields regardless of the biomass source.
As highlighted by other researchers, biomass
composition can vary considerably , even between members of
the same species with similar plant architectures [2, 4],
such as wheat [2, 4–6], rice  and maize [8, 9].
Intraspecific variations in these monocotyledonous biomass
sources are likely to be determined by the abundance of
plant tissue types [4, 10], which vary depending on
agronomic conditions and genotype.
If commodity chemicals are to be produced from
biomass, agricultural residues from dicotyledonous plants,
such as Brassica napus straw, may also be used [11, 12].
These species have very different cell wall structures to
monocot plants . Unlike many crop species, B. napus
has been bred to produce a range of products from
vegetable oil (oilseed rape (OSR)) to animal fodder
(fodder rape). Consequently, considerable phenotypic
and genotypic variation exists within Brassica species .
It is therefore likely that these genetic and phenotypic
differences will also influence lignocellulose composition
through differences in cell wall (CW) chemistry and tissue
abundances. In a biorefinery context, where
(ligno)cellulose is converted to monomeric sugars and fermented to
produce chemicals and fuels [1, 11], it is likely that these
variations will influence process efficiency and yields.
Fermentable sugars can be released from lignocellulose
in a number of ways. However, one of the most
promising production routes currently available involves
pretreatment by steam explosion, followed by enzymatic
hydrolysis . Steam explosion modifies the chemical
composition  and polymeric structure of B. napus
straw . The resulting material is therefore more
amenable to enzymatic saccharification . Previous
studies have shown that steam explosion improves
methane yields during anaerobic digestion  and
fermentable sugar yields after enzymatic saccharification
[17, 18]. These studies revealed that retention of uronic
acid- and xylose-containing compounds were the
important process-specific factors limiting initial hydrolysis
rate and overall reducing sugar yield, respectively . It
would be interesting to see if intraspecific variations in
these components were also important determinants of
Although process-dependent differences have been
explored using B. napus straw from a single genotype
[16–18], little is known about the effect that variations
in straw composition have on saccharification yields
with this feedstock. Furthermore, although significant
differences in saccharification yields are known to exist
within members of the same species, the precise
chemical basis for these variations is not fully understood.
Therefore, this work aimed not only to determine
differences in straw quality between cultivars using
pilotscale processing but also to relate those differences to
straw composition. To do this, straw derived from a
selection of OSR cultivars and other crop types of the
same species (B. napus) was pretreated at near-optimal
conditions  using pilot-scale steam explosion. The
chemical composition of the original material,
pretreated substrates and products released during
processing were established. IR spectra were also taken
from these materials which gave an insight into their
polymeric structure. Monomeric glucose (Glc) and
ethanol yields were quantified after hydrolysis and
simultaneous saccharification and fermentation (SSF),
respectively. This data allowed differences in product
yields between cultivars to be related to differences in
Results and discussion
The carbohydrate composition of B. napus straw differed
Despite being grown, harvested, stored and analysed
under the same conditions, significant variations in the
abundance of constituent sugars were observed between
B. napus straw from different cultivars (Table 1). The
mean moisture content of the straw was ca. 9.5 % and
did not differ significantly between cultivars (Table 1).
After pretreatment, the compositions of the
water-insoluble residues were more uniform but still
varied between cultivars
Straw derived from each cultivar (1 kg) was steam
exploded into hot water at near-optimal conditions (210 °C,
10 min). The sugar compositions of the steam-exploded
water-insoluble solids were then established to see if
genotypic variation in composition observed between the
untreated straw of different cultivars was retained after
pretreatment (Table 2).
The yields of washed, steam-exploded material on a
dry-weight basis as a function of the original material
are shown in Table 2. These show that approximately
half of the dry matter was lost from the biomass during
the pretreatment. The most likely explanation for this is
the breakdown and solubilisation of non-cellulosic
polysaccharides and other low-molecular-weight substances,
as well as the loss of small particulate matter during the
cyclone and washing stages (e.g. ).
Nevertheless, biomasses from different cultivars were
treated identically and processed in a random order in
relationship to their CW compositions. Therefore, the
relative differences in chemistry of the pretreated
material and saccharification yields are likely to reflect the
genotypic differences in biomass composition. After
steam explosion, mannose (Man), galactose (Gal) and
fucose (Fuc) were almost completely removed from the
water insoluble fraction (<5 % of the original remained)
(Table 2). Likewise, other non-cellulosic sugars (xylose
(Xyl), uronic acids (UA), arabinose (Ara) and rhamnose
(Rha)) were also removed but retained a higher
proportion of their sugars in the pretreated residue (10–20 %
of the original). By contrast, up to 80 % of the original
Glc present in the original material was retained in the
After steam explosion, the largest quantitative
difference between substrates produced from different
cultivars was in the abundance of glucan retained in the
water-insoluble material (Table 2). The glucan content
broadly correlated with that of the original straw.
Although present in much smaller quantities, larger
proportional variations were observed in the reduced
retention of non-cellulosic carbohydrates containing
Xyl, Ara and Rha between cultivars. Straw from
particular cultivars, such as Canard, retained small
quantities of arabinan after steam explosion (≈5 g/kg), as
others, such as York, retained almost none (Table 2).
These results indicated considerable varietal
differences in the pretreatment lability of non-cellulosic
Canberra x Courage
Hansen x Gaspard
Licrown x Express
Madrical x Recital
Shannon x Winner
Slapka Slapy S3
Range (% mean)
ANOVA (p value)
Table 1 Sugar composition of untreated B. napus straw derived from different cultivars
Values were calculated with a relative standard deviation (RSD) of 3.9, 3.2, 7.3, 2.6, 4.8, 4.8, 6.8, 12.1 and 8.1 % for Glc, Xyl, UA, Man, Gal, Ara, Rha, Fuc and
Glc glucose, Xyl xylose, UA uronic acids, Man mannose, Gal galactose, Ara arabinose, Rha rhamnose, Fuc fucose, MC moisture content, Other other
non-carbohydrate matter by difference, ANOVA one-way analysis of variance
Polymeric differences in biomass composition between
cultivars revealed using Fourier transform infrared
Fourier transform infrared (FT-IR) spectroscopy has been
used extensively to probe the structure of plant CWs
[20, 21]. Here, spectra for OSR straw from different
cultivars before and after steam explosion were used to assess
cultivar-specific differences at a polymeric level (Fig. 1).
Spectra collected from untreated straw showed greater
variation between cultivars than those from the same
materials after SE. The largest spectral differences were
observed at wavenumbers typically associated with structural
carbohydrates—cellulose, hemicellulose and pectic
structures—875, 1020, 1240, 1315, 1420, 1600 and 1730 cm−1
. Particular cultivars showed above-average deviation in
absorbance at certain wavelengths. For example, Ramses
straw exhibited higher absorbance at 875 cm−1 (C1–H
bending in xyloglucan (XG) and cellulose) compared to
other cultivars. Similarly, Hansen x Gaspard showed
above-average absorbance at 1600 cm−1 (COO−
asymmetric stretching), suggesting differences in pectic
After pretreatment, spectra taken from the residues of
different cultivars were more uniform (Fig. 1). The largest
variation between cultivars was observed at wavenumbers
related to non-cellulosic polysaccharide abundances: 1020
cm−1 (C–O stretching, C–C stretching in XG and pectins)
and 1155 cm−1 (C–O–C glycosidic linkages in xylan) .
Spectral variations between cultivars identified at other
wavenumbers were diminished following steam explosion,
reflecting the extent of component removal from the
Variation in fermentation inhibitor release differed
We previously showed that significant quantities of
organic breakdown compounds are produced from B. napus
straw when steam exploded at severities required to
achieve reasonable saccharification yields (>60 %) .
Many of these have the capacity to inhibit downstream
processes—particularly fermentation . In the current
study, the abundance of four common inhibitory
compounds (furfural, hydroxymethylfurfural, acetic acid and
formic acid) released into the pretreatment liquor varied
Table 2 Matter recoveries and monomeric sugar composition of straw steam exploded at 210 °C, 10 min derived from different
Fig. 1 Average FT-IR spectra collected from straw, derived from different
cultivars before (a) and after (b) steam explosion at 210 °C, 10 min
significantly between cultivars (p < 0.001) (Table 3). This
variation in fermentation inhibitor production could be
exploited to limit the production of compounds that are
detrimental to downstream processes.
Straw from different cultivars obtained different
hydrolysis and fermentation yields
A portion of the steam exploded biomass derived from
each cultivar was converted to either Glc or ethanol by
enzymatic hydrolysis or SSF, respectively, using a
nearoptimum cellulase dose determined previously (36 FPU/
g substrate ) (Table 4). Although all 17 cultivars were
grown, processed and analysed in the same manner,
significant differences (p < 0.001) in product yields were
observed between cultivars (Table 4).
Here, two methods were used to quantify
saccharification products. Total reducing sugars in the hydrolysates
was estimated using dinitrosalicylic acid (DNS) reagent
and a Glc-specific assay (GOPOD) used for accurate
quantification of monomeric Glc release. Reducing sugar
assays typically overpredict sugar yields as other chemicals
created during pretreatment, such as furfural derivatives,
Table 3 Concentration of organic acids and furfural derivatives
retained in the pretreatment liquors of straw derived from
Volume (L) Concentration (g/L pretreated liquor)
Acetic Formic 2FA HMF
6.60 2.86 2.02 0.51 0.15
Canberra x Courage 7.08
Table 4 Estimated mass of reducing sugars (by DNS), glucose
and ethanol produced from pretreated straw derived from
different cultivars (5 % substrate, 37 FPU/g, 96 h) incubated at
50 or 40 °C, respectively
Canberra x Courage
Hansen x Gaspard
Licrown x Express
Madrical x Recital
Shannon x Winner
Slapka Slapy S3
Range (% mean)
Hansen x Gaspard
Licrown x Express
Madrical x Recital
Shannon x Winner
Slapka Slapy S3
Range (% mean)
The abundance of all compounds in the hydrolysis liquors differed significantly
between cultivars (ANOVA, p < 0.001). Values were calculated with a RSD of
1.9, 1.7, 1.9 and 5.4 % for acetic acid, formic acid, 2FA and HMF, respectively
Acetic acetic acid, Formic formic acid, 2FA 2-furfuraldehyde,
also contain reducing groups but have much lower mass
than Glc . This is particularly apparent when severe
pretreatment conditions are used. Nevertheless, reducing
sugar yields assayed using the DNS reagent correlated
strongly with Glc yields (p < 0.001, R = 0.920, n = 17),
demonstrating that the main variations in sugar release
between cultivars related to glucan digestibility.
Ethanol yields produced by SSF generally reflected Glc
yields saccharified from the material except for Hansen x
Gaspard and Canberra x Courage, which obtained good
saccharification yields but performed very poorly under
SSF conditions (Table 4). Typically, 95 % of the Glc
hydrolysed from the pretreated material was fermented to
ethanol under SSF conditions. It is therefore likely that ethanol
yields produced from ‘Hansen x Gaspard’ and ‘Canberra x
Courage’, which only produced ≈60 % of the expected
yield based on the saccharification results alone, were not
indicative of the general trend in product yields observed
between cultivars (Table 4). Such cultivars might provide
useful model systems for identifying mechanisms that
reduce fermentation efficiency. Without these outliers,
Significant differences in product yields were observed between cultivars
(ANOVA p < 0.001). Italicised values are atypically low when compared to
aGlucose equivalent reducing groups as assayed using DNS reagent
monomeric Glc and reducing sugar yields correlated
strongly with ethanol yields as one might expect (p < 0.01,
R = 0.755 and 0.704, respectively, n = 15).
Relationship between straw composition and product
To understand the potential relationship between
cultivar straw composition and product yields, the
abundance of each component sugar present in the untreated
and pretreated residues were correlated with monomeric
Glc and ethanol yields after processing (Table 5).
Cultivars with glucan-rich straws did not necessarily produce
higher monomeric Glc (p = 0.957, n = 17) or ethanol
yields after processing (p = 0.730, n = 15). These results
are similar to those observed in maize, where varietal
differences in ethanol yield were more closely related to
glucan convertibility rather than glucan content .
Cultivars that contained fewer Ara-containing
components in their original straw tended to produce higher
Glc yields after steam explosion and hydrolysis (p < 0.49,
n = 16) and ethanol after SSF (p < 0.05, n = 15).
0.691 n.s. −0.014 0.957 n.s. 0.098
0.837 n.s. 0.082
0.756 n.s. 0.291
−0.034 0.896 n.s. −0.090 0.732 n.s. −0.126 0.655 n.s.
−0.441 0.077 n.s. −0.530 0.029*
−0.353 0.196 n.s.
−0.239 0.355 n.s. −0.256 0.321 n.s. 0.202
−0.092 0.725 n.s. −0.073 0.780 n.s. 0.240
−0.210 0.418 n.s. −0.168 0.520 n.s. 0.222
−0.045 0.865 n.s. 0.002
0.994 n.s. −0.174 0.535 n.s.
−0.378 0.135 n.s. −0.243 0.384 n.s.
0.770 n.s. 0.199
0.443 n.s. −0.079 0.780 n.s.
0.405 n.s. 0.022
0.934 n.s. 0.063
0.425 n.s. 0.051
0.845 n.s. 0.195
0.937 n.s. −0.139 0.594 n.s. 0.204
0.567 n.s. 0.099
0.706 n.s. −0.012 0.966 n.s.
Pretreated straw composition (g/kg DW)
−0.131 0.616 n.s. −0.220 0.396 n.s. 0.053
Correlation coefficients (R) and significance values (p) are presented, with
significant correlations (p < 0.05) marked with an asterisk (*)
FW fresh weight, DW dry weight, ns not significant
Likewise, Gal composition of the original straws also
negatively correlated with Glc yields (p < 0.03, n = 17)
and (not significantly, n = 0.2) with ethanol yields.
Interestingly, a low-yielding cultivar, Ramses, contained
relatively high galactan and arabinan content compared to
other cultivars (Table 5). It is therefore possible that
particularly low saccharification yields were produced from
Ramses straw because of this difference in CW
In contrast, comparison of Glc and ethanol yields with
pretreated straw chemistry showed no such correlations
with non-cellulosic neutral sugars (Table 5). The most
likely reason for this is that the non cellulosic neutral
sugars were almost completely removed during the
pretreatment process. Nevertheless, the fact that the final
yields of Glc and ethanol maintained a correlation with
the original straw chemistry suggests that some physical
or chemical signatures still exist in the pretreated
material which has a negative impact on the digestibility and
These results suggest that polymers enriched in Ara
and Gal such as pectins (particularly
rhamnogalacturonan I (RG-I)) or arabinogalactans (AGs) are likely to
influence biomass recalcitrance between B. napus cultivars
after pilot-scale SE. Recent evidence has shown that AGs
can covalently link the hemicellulose-pectin network
. AGs are thermally resistant CW-associated
polymers ; therefore, it is possible that genotypic
differences in the abundance of these, or similarly Ara- and
Gal-rich polymers, could have a significant impact on
substrate recalcitrance after pretreatment. Similarly,
pectic side chains on RG-I are comprised mainly of Ara and
Gal sugars, which are likely to hinder
degradation—particularly when hydrolysing dicotyledonous biomass .
Further work, involving the more detailed
characterisation of biomass, would be needed to ascertain the effect
that these carbohydrates may have on CW recalcitrance.
Interestingly, variations in UA abundance retained in
the pretreated solid between cultivars correlated
negatively with reducing sugar yields after pretreatment and
enzymatic hydrolysis (Table 5). This observation is
consistent with previous work where saccharification
performance of straw steam exploded from a single B.
napus genotype was limited by severity-dependent UA
retention . Together, these results suggest that
variations in UA retained in the pretreated material, brought
about by either changes in pretreatment severity  or
straw composition (this work), are particularly important
components influencing the saccharification of OSR
straw. These results also mirror those collected from
other herbaceous, dicotyledonous plants such as hemp,
where galacturonic acid content correlates negatively
with saccharification yield, irrespective of the
pretreatment technique used .
Relating genotypic variation in IR spectra with variation
in ethanol yields using partial least squares regression
Partial least squares (PLS) regression is a convenient
way of correlating quantitative measurements with
spectral data. As mentioned previously, FT-IR spectra give
an overview of the constituent bonds present in the
material—thereby giving information as to its polymeric
structure. This can make spectral interpretations of
biological material difficult, as many infrared absorbance
peaks overlap. Splitting the spectral variation into
successive, principal components, using multivariate
analysis, makes the data more accessible: highlighting areas
of the spectra that correlate with variances in
Previously, this methodology has been used to provide
information on the main polymeric changes that occur
in OSR straw following steam explosion at varying
pretreatment severities . The crucial effects that these
changes in severity had on subsequent Glc (via
enzymatic hydrolysis)  and methane generation (after
anaerobic digestion) were also identified .
Here, PLS modelling was used to match spectral
variations between cultivars to variations in ethanol yields
after processing—summarising them into six PLS
components (PLS 1–6). Spectra taken from the untreated
straw samples were correlated with ethanol yields
obtained from the same cultivar in grams per kilogram
original straw (Fig. 2a). Likewise, spectra taken from
pretreated cultivar straw samples were correlated with
ethanol yields expressed as grams per kilogram
steamexploded straw (Fig. 2b).
This showed that variations in FT-IR spectra collected
from both untreated and pretreated straw accessions
could provide reasonable estimations of the ethanol
yields obtained after processing (Fig. 2). In total, the first
six PLS components could describe 97–98 % of
intraspecific variation in ethanol yields utilising 78–83 % of the
spectral variations observed between cultivars. These
models show that variations in the chemistry of the
untreated and pretreated material, detected as spectral
differences, can be matched to the different ethanol yields
between straw accessions. The cause of these differences
can be interrogated further by examining the loadings
for each PLS component (Fig. 3).
The loadings for each component were therefore
examined to identify what differences in polymeric
associations between cultivars are likely to influence
ethanol yields (Fig. 3). The majority of variation in
ethanol yields observed between cultivars after steam
explosion (76.83 %) could be explained by a single PLS
component (PLS 1)—utilising 29.6 % of the variation
in spectra collected from the pretreated residues
(Fig. 3, RHS). This spectral variation was mostly
isolated to the 1020–1025 cm−1 region (C–O stretching,
C–C stretching in xylans and pectins), suggesting that
residual non-cellulosic carbohydrates were the main
spectral differences between cultivars related to
ethanol yields (Fig. 3, RHS) [20, 21].
Other spectral variations between pretreated residues
derived from different cultivars (identified in PLS
components 2–6) explained much less of the variance in
ethanol yield. PLS 2 could explain a further 6.5 % of the
variation in ethanol yields—primarily using variation in
absorbance at cellulose-associated wavenumbers (1000,
1030, 1103, and 1160 cm−1). PLS 3 described a further
7.7 % of the variation in ethanol yields, attributed
mostly to residual pectin, (1600 cm−1, COO−
asymmetric stretching) (Fig. 3, RHS). The remaining
components (4–6) explained less than 7 % of the remaining
variation combined, highlighting subtle differences in
spectral regions previously identified by higher
components (Fig. 3, RHS).
More PLS components were needed to explain the
variation in ethanol yields (grams per kilogram untreated
straw) when correlating them against spectra collected
from the original straw (Fig. 3, LHS). The majority
variation in ethanol yields between cultivars (52.4 %)
can be explained by 15.8 % of the intraspecific spectral
variation between the untreated straw (PLS 1). The
PLS loadings for PLS 1 identified this spectral variation
was found at XG- and pectin-related absorbances:
1020 cm−1 (C–O stretching, C–C stretching in XG and
pectins), 875 cm−1 (C1–H bending in XG and
cellulose), 1600 cm−1 (COO− asymmetric stretching in
pectins) and 1730/40 cm−1 (C=O stretching vibration of
alkyl ester in pectins) [20, 21].
The variation in spectra at 1600 and 1730/40 cm−1 in
PLS 1 are particularly interesting as they suggest that
straw containing a greater abundance of methylesters
obtain higher ethanol yields . The abundance of
methylesters implicates homogalacturonans as important
cell wall components in determining saccharification
efficiency in this species. Unlike most cereal crop residues,
Fig. 2 Ethanol yields predicted from FT-IR spectra compared to actual data collected from untreated (a) and pretreated (b) materials. Data predicted
by fitting to six PLS components are shown
Ethanol (g/kg original)
Ethanol (g/kg PT material)
1800 1600 1400 1200 1000 800
1800 1600 1400 1200 1000 800
Fig. 3 PLS loadings showing spectral variations correlated with ethanol yields in untreated (LHS) and pretreated (RHS) straw produced from different
cultivars. The first four PLS components are displayed (PLS 1–4)
B. napus is a dicotyledonous plant—with pectin-rich,
type I CWs similar to the model plant Arabidopsis .
Genetic manipulation in other species, including
Arabidopsis, has independently revealed that saccharification
yields produced from CW material is related to
pectinmethyl esterification [29, 30]. It is therefore interesting
to see that these changes may also influence genotypic
variation in saccharification quality between B. napus
cultivars after pilot-scale processing.
The loadings for the second PLS component (PLS 2),
which explained a further 26.4 % of the variation in
ethanol yields, can also show variation in pectin-associated
peaks—the largest being at 1115 cm−1 (C–O, C–C
stretching in pectin). Minor cellulose-associated peaks also
contribute to PLS 2: 1415 cm−1 (C–O, C–C stretching in
cellulose) and 1160 cm−1 (O–C–O asymmetric stretching
of the glycosidic bond in cellulose) (Fig. 3, LHS).
The main spectral differences in lower PLS
components, for example PLS 3, explaining a further 7.0 % of
variation in ethanol yield, included 1034 cm−1 (glucan/
glucomannan ring vibrations) and 1580 cm−1 (CW
proteins) [18, 19]. PLS 4 explained a further 9.2 % of the
variation in ethanol yields, primarily from the variation
in absorbance at 1408 cm−1 (COO− symmetric
stretching in pectins) (Fig. 3, LHS).
Although not shown, similar conclusions could be
drawn from the PLS analysis of FT-IR spectra in relation
to glucose release after saccharification, which were
almost identical to those associated with ethanol yield.
Significant variation in Glc, ethanol and fermentation
inhibitor yields were observed between
cultivars—despite being grown, harvested and analysed under
identical conditions. Genotypic differences in straw quality
were not simply governed by Glc concentration in the
original material but by the integrity of the
noncellulosic components. Arabinose- and galactose-rich
polymers contained within the original straw were
implicated as limiting saccharification yields between
cultivars. PLS regression modelling revealed additional
cultivar-specific properties, such as homogalacturonan
abundance, which are likely to alter ethanol yields
between cultivars. These observations are important to
those wishing to breed agricultural residues as a feedstock
for biorefining—highlighting key targets for improvement
already present in cultivars of the same species.
Seventeen B. napus cultivars were grown under field
conditions at KWS UK Ltd., Cambridge, UK (+52°, 8′,
32.40″, −1°, 6′, 19.66″), in a randomised order, in adjacent
3 × 12 m plots. The cultivars selected were a genetically
diverse selection of B. napus genotypes, representative of
the most common sub-groups—winter OSR (WR), spring
OSR (SR), fodder rapes (FR) and swede (SW) . The
cultivars analysed in this study were as follows: Canard
(FR), Canberra x Courage (WR), Darmor (WR), Erglu
(SR), Hansen x Gaspard (WR), Judzae (SW), Lincrown x
Express (WR), Madrical x Recital (WR), Major (WR),
POH285 Bolko (WR), Quinta (WR), Ramses (WR),
Sensation NZ (SW), Shannon x Winner (WR), Slapka Slapy
(unspecified), Slovenska Krajova (WR) and York (SW).
All cultivars were harvested at maturity (8 Aug. 2012).
Approximately 3kg OSR straw was collected upon
ejection from a combine harvester which directly threshed
and chipped the straw from a single cultivar into 2–3
cm pieces. The straw sample was taken from the centre
of each 3m strip to prevent contamination from adjacent
cultivars. The straw was then stored in woven
polypropylene bags in a dry, unheated room before analysis.
Cellulase and chemicals
The cellulase cocktail used in this study was Cellic®
CTec2 (Novozymes, Denmark) with a stock cellulase
activity of 180 FPU/mL determined following Ghose .
Unless otherwise stated, all chemicals used were
analytical grade, purchased from Sigma-Aldrich, UK.
Steam explosion of OSR straw
A sample of OSR straw (1 kg FW) from each cultivar
was steam exploded into hot water (6.6 L) at a
nearoptimum pretreatment severity (210 °C, 10 min) using a
Cambi™ Steam Explosion Pilot Plant . After steam
explosion, the heating chamber was then cleared twice
by applying 2–3 bars of pressure to dislodge the majority
of residual material. The pretreated biomass was filtered
immediately through a 100μm nylon mesh bag in a
low-speed centrifuge. The solid and liquid products were
measured, and a representative sample of each fraction
was taken for analysis. The steam explosion unit was
extensively rinsed between each pretreatment to prevent
cross contamination between cultivars.
Analysis of steam explosion liquors
The concentration of fermentation inhibitors (organic
acids and furfural derivatives) retained in each liquor
(water-soluble fraction created after steam explosion)
was quantified by HPLC after filtration (96-well filter
plate, 0.2 μm). A Flexar® FX-10 UHPLC instrument
(PerkinElmer, UK) equipped with a refractive index (RI)
and photodiode array (PDA) detector was used,
separating samples using an Aminex HPX-87H organic acid
analysis column (Bio-Rad Laboratories Ltd., UK) (65 °C,
mobile phase 5 mM H2SO4, flow rate 0.5 mL/min).
Chemical composition of the untreated and pretreated
The matter content of the pretreated solid produced from
each cultivar was established using an infrared drying
balance (Mettler LP16, Mettler-Toledo, Belgium) drying
duplicate samples (0.5 g) at 105 °C, to constant mass. A
sample of each steam-exploded solid and untreated
material was frozen in liquid nitrogen and freeze-milled into a
fine powder to gain a homogenous sample for chemical
analysis (3 min, SPEX 6700 freezer/mill, Spex Industries,
NJ) and dried to constant mass (40 °C, overnight).
Samples of the dried steam exploded residue and untreated
material were then acid-hydrolysed (72 % H2SO4, 20 °C,
3 h followed by dilution to 1 M, 100 °C, 2.5 h). The sugar
composition of the solid was established by converting the
monomeric sugars released into their aditol acetate
derivatives and quantifying their abundance by gas
chromatography . 2-Deoxy-Glc was used as an internal standard.
Uronic acid content of the same materials were
established colorimetrically after a milder hydrolysis regime
(72 % H2SO4, 20 °C, 3 h followed by dilution to 1 M,
100 °C, 1 h) following .
Fourier transform infrared (FT-IR) spectroscopy
FT-IR spectra were collected in the 800–4000 cm−1
region for each freeze-milled sample using a dynamic
alignment FT-IR spectrophotometer (Bio-Rad FTS 175C,
Bio-Rad Laboratories, Cambridge, USA), resolution 2 cm−1,
64 scans. The sample was trapped in a Golden Gate™
diamond attenuated total reflectance (ATR) accessory (Specac,
Slough, UK) before collection. Triplicate spectra were taken
for each material, truncated (800–1800 cm−1), baseline
corrected (to 1800 cm−1) and area normalised before analysis.
Determining saccharification yields for each cultivar
A 1g (DW equivalent) sample of each pretreated solid was
suspended in 20mL sodium acetate/acetic acid buffer (5 %
substrate, 0.1 M, pH 5, 0.01 % thiomersal) in 30mL
screwtopped vials (Sterilin, UK), held in a shaker plate incubator
(50 °C, 150 RPM). Cellic® CTec2 was added to the
equilibrated solutions at a cellulase dose of 0.2 mL/g substrate
(ca. 36 FPU/g). Digestions were conducted in triplicate and
the amount of Glc quantified after 96 h of incubation. The
amount of cellulase-derived Glc was also quantified and
subtracted from the total.
Quantification of sugars in biomass hydrolysates
(reducing sugars and Glc)
The concentration of reducing sugars in undiluted
biomass hydrolysates was estimated using a multiplexed
DNS assay, optimised for this purpose . The precise
concentration of Glc released during hydrolysis was
determined using GOPOD reagent as follows. A 100μL
sample of each supernatant was heated in a sealed PCR
plate to denature the cellulase (100 °C, 5 min), diluted to
within a readable range (0–2 g/L). A 5μL sample of the
diluted solutions was then dispersed in 195 μL of
GOPOD reagent (Megazyme International Ltd., Ireland)
in a microtitre plate. The amount of Glc in each
hydrolysate was quantified after 20 min of incubation (50 °C)
by comparing the absorbance of the products (510 nm)
against a set of Glc calibration standards. Plates were
covered during incubation to minimise evaporation.
Simultaneous saccharification and fermentation (SSF) of
A sample of each pretreated substrate was suspended in
10 mL solution with a final concentration of 5 %
substrate in nitrogen base (Formedium, Hunstanton, UK)
and held in 20mL screw-topped glass vials. Both
cellulases (36 FPU cellulase/g substrate) and a concentrated
yeast inoculum were added to each vial and incubated
for 96 h, 40 °C.
The yeast inoculum used was a robust thermo-tolerant
yeast (Saccharomyces cerevisiae, strain NCYC 2826,
National Collection of Yeast Cultures, Norwich, UK) grown
from a slope culture, inoculating 1 L of yeast mould
(YM) broth (3 d, 25 °C) before centrifuging, discarding
the supernatant and partially reconstituting the yeast in
nitrogen base. The final solutions contained 3.83 × 107
viable cells/mL when inoculated—assayed using a
NucleoCounter® YC-100™ (ChemoMetec, Denmark). SSFs were
conducted as three independent replicates, and the
ethanol released from a cellulase + yeast control was
subtracted from each sample.
Ethanol concentrations were quantified using HPLC
using a Series 200 LC instrument (PerkinElmer, UK)
equipped with an Aminex HPX-87P carbohydrate
analysis column (Bio-Rad Laboratories Ltd., Hemel
Hempstead, UK). The mobile phase used was ultrapure water
(0.6 mL/min) and concentration quantified using a
refractive index (RI) detector, comparing absorbance to a
set of ethanol standards.
All descriptive statistics were calculated using Microsoft
Excel and one-way ANOVAs conducted using GenStat v. 13
(VSN International, Ltd.). PLS regression (plsregress) was
conducted in Matlab® (MathWorks, USA) .
Ara: arabinose; CW: cell wall; DW: dry weight; FR: fodder rapes; FT-IR: Fourier
transform infrared; Fuc: fucose; FW: fresh weight; Gal: galactose; Glc: glucose;
Man: mannose; OSR: oilseed rape; PLS: partial least squares; Rha: rhamnose;
RSD: relative standard deviation; SR: spring OSR; SW: swede; UA: uronic acids;
WR: winter OSR; XG: xyloglucan; Xyl: xylose.
The authors declare that they have no competing interests.
IW conducted the experiments in this study and drafted the manuscript. NW
conducted the PLS modelling. DW and AE assisted with the steam explosion
and HPLC, respectively. KW and IB conceived of the study, participated in its
design and coordination and helped draft and finalise the manuscript. All
authors read and approved the final manuscript.
The authors receive financial support from the Biotechnology and Biological
Sciences Research Council (BBSRC) via the Integrated Biorefining Research
and Technology Club (IBTI Club; grant number BB/H004351/1) and Institute
Strategic Programme ‘Food and Health’ (grant number BB/J004545/1). The
authors would also like to thank Peter Werner and colleagues at KWS, UK, for
providing the OSR straw used in this study, Andrea Harper and Charlotte
Miller for the assistance with the straw collection and Nicola Cook for the
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