Genetic Potential of Loblolly Pine for
Hydrolytic Conversion to Ethanol
David Barker, Steve McKeand, Fikret Isik, Ross Whetten, and Sunkyu Park
This study focuses on the use of loblolly pine in
hydrolytic conversion processes, following this general
schematic:
Woody
biomass
pretreatment
Carbohydrates
(cellulose)
released from lignin
hydrolysis
fermentation
Sugars
Ethanol
 Using loblolly pine for cellulosic ethanol is a
challenge given the strong chemical bonds within
the wood
 However, loblolly pine is the most productive and
widely-planted tree species in the southeastern U.S.
 The ability to use this species for biofuel production
will have great value in the push for renewable fuels
Rationale
Wood properties are highly heritable traits and are
thought to have significant impacts on conversion
yields.
 Different genotypes of loblolly pine should
therefore have varying ethanol yields
 Testing different varieties should enable the
selection of those well-suited to conversion
Methods
41.8
Ethanol yield should improve
with increasing cellulose and
decreasing lignin content
41.4
C1
C2
41.0
C3
C4
40.6
C5
C6
40.2
25.5
26.0
26.5
27.0
27.5
28.0
28.5
Predicted % Lignin Content
Figure 1. Means of 23 clones for predicted lignin and
cellulose content. The clones selected for conversion to
ethanol represent all six clusters as well as a good crosssection of available variation in lignin and cellulose content.
C1 indicates cluster 1, C2 indicates cluster 2, etc…
Total Sugar Yield in mg/g Wood
Determine the feasibility of using loblolly pine (Pinus
taeda L.) as a feedstock for ethanol-based biofuels.
Predicted % Cellulose Content
Purpose
 Approximately 1700 wood core samples were
taken from 187 clonal varieties of loblolly pine
 Cores were dried, ground, and subjected to NearInfrared Spectroscopy (NIR)
 A subset consisting of 23 clones was selected for
conversion to ethanol
 This subset was selected based on: (1) a cluster
analysis of the NIR spectra which divided the
clones into six different clusters (on the basis that
differences between NIR spectra represent
differences in wood chemistry) and (2) lignin and
cellulose content predictions that were also
derived from the NIR spectra (Figure 1)
 The selection of clones for conversion aimed to
capture as much of the available genetic variation
as possible
Sampled clones are still being tested. The conversion
work is being done by associates in the Department of
Forest Biomaterials at NCSU.
230
210
Preliminary Results
190
170
150
1
2
3
4
5
6
Clones
7
8
9
10
Figure 2. Sugar yields for 10 clones tested to date using a
dilute acid pretreatment.
For 10 clones already processed using a dilute acid
pretreatment, sugar yields did show substantial
variation. The lowest- and highest-yield clones were
approximately 13% below and above the mean,
respectively. (Figure 2) This variation in sugar yield
translates directly into variation in ethanol yield.
Acknowledgements
Department of Forestry and Environmental Resources, NCSU
Department of Forest Biomaterials, NCSU
Tree Improvement Program; students, faculty and staff
Dr. Gary Hodge, DFER, NCSU