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Early Prediction of Biomass Production and Composition Based on the First Six Years of Cultivation

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Miscanthus is a promising feedstock for secondgeneration bioethanol production. This perennial crop produces its biomass in two phases: a yieldbuilding phase, where the biomass production increases gradually, and a plateau phase, where it is maintained. However, to target the breeding of Miscanthus for second-generation bioethanol production, the early selection of interesting traits is critical. We therefore investigated the interannual correlations within and among the traits related to biomass production and composition. We studied 21 clones belonging to M. × giganteus J. M. Greef & Deuter ex Hodk. & Renvoize, M. sacchariflorus (Maxim.) Benth. & Hook. f. ex Franch., and M. sinensis Andersson species cultivated on plots from the second to the sixth year at two harvest dates. The biomass production, canopy height, plant stem number, and aboveground plant volume index were better predicted from the third year than from the second year (minimum correlation coefficients of 0.76 and 0.67 respectively). The stem diameter was well predicted from the second year (correlations above 0.93). The canopy height and the aboveground plant volume index determined in the second and third year were the best predictors of the biomass produced in the second, third, and fourth year (minimum correlations of 0.77 against 0.52 for flowering date or 0.64 for stem diameter). For older crops, the canopy height measured in the second and third year was the best predictor of the biomass production (correlations above 0.70). The interannual correlations were lower for the biomass composition-related traits than for the production-related traits and fluctuated over time. These results showed that early prediction of interesting traits is feasible to breed varieties tailored for biofuel production.
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crop science, vol. 55, m ayjune 2015 www.crops.org 1
RESEARCH
Miscant hus is a perennial crop that can be cultivated for up
to 25 yr (Lewandowski et al., 2003b). Its biomass is pro-
duced in two phases: a yield-building phase, where the biomass
production gradually increases, and a plateau phase, where the
biomass production is maintained (Clifton-Brown et al., 2001a;
Clifton-Brown et al., 2008; Zub and Brancourt-Hulmel, 2010).
The plateau phase of biomass production, which corresponds
to the adult phase, can be attained at various ages according to
Clifton-Brown et al. (2008) and Miguez et al. (2008). Miscanthus
giganteus, the species most studied in long-term experiments,
can take up to 5 yr to reach the plateau phase of biomass produc-
tion depending on the environmental conditions and crop man-
agement practices.
Miscanthus biomass production is a complex trait involving
earliness and morphological traits such as canopy height, number
of stems per plant, and stem diameter (Robson et al., 2013; Zub
et al., 2011). During the yield-building phase, the canopy height,
stem number, and stem diameter, to a lesser extent, increase
Early Prediction of Miscanthus Biomass
Production and Composition Based on
the First Six Years of Cultivation
Stéphanie Arnoult,* Marie-Chantal Mansard, and Maryse Brancourt-Hulmel
ABSTRACT
Miscanthus is a promising feedstock for second-
generation bioethanol production. This perennial
crop produces its biomass in two phases: a yield-
building phase, where the biomass production
increases gradually, and a plateau phase, where
it is maintained. However, to target the breeding
of Miscanthus for second-generation bioethanol
production, the early selection of interesting traits
is critical. We therefore investigated the interan-
nual correlations within and among the traits
related to biomass production and composition.
We studied 21 clones belonging to M. gigan-
teus J. M. Greef & Deuter ex Hodk. & Renvoize,
M. sacchariflorus (Maxim.) Benth. & Hook. f. ex
Franch., and M. sinensis Andersson species cul-
tivated on plots from the second to the sixth year
at two harvest dates. The biomass production,
canopy height, plant stem number, and aboveg-
round plant volume index were better predicted
from the third year than from the second year
(minimum correlation coefcients of 0.76 and
0.67 respectively). The stem diameter was well
predicted from the second year (correlations
above 0.93). The canopy height and the aboveg-
round plant volume index determined in the sec-
ond and third year were the best predictors of
the biomass produced in the second, third, and
fourth year (minimum correlations of 0.77 against
0.52 for owering date or 0.64 for stem diameter).
For older crops, the canopy height measured in
the second and third year was the best predic-
tor of the biomass production (correlations above
0.70). The interannual correlations were lower for
the biomass composition-related traits than for
the production-related traits and uctuated over
time. These results showed that early prediction
of interesting traits is feasible to breed varieties
tailored for biofuel production.
S. Arnoult, INRA, UMR1281 SADV, 2 Chaussée Brunehaut, Estrées-
Mons, BP 50136, F-80203 Péronne Cedex, France; S. Arnoult (cur-
rent address), and M.C. Mansard, INRA, UE0972 GCIE Picardie,
2 Chaussée Brunehaut, Estrées-Mons, BP 50136, F-80203 Péronne
Cedex, France; M. Brancourt-Hulmel, INRA, UR1158 AgroImpact,
Site d’Estrées-Mons, 2 Chaussée Brunehaut, Estrées-Mons, BP 50136,
F-80203 Péronne Cedex, France. Received 14 July 2014. Accepted 24
Nov. 2014. *Corresponding author (Stephanie.Arnoult@mons.inra.fr).
Abbreviations: ADF, acid detergent ber; ADL, acid detergent lignin;
DM, dry matter; NDF, neutral detergent ber.
Published in Crop Sci. 55:1–13 (2015).
doi: 10.2135/cropsci2014.07.0493
© Crop Science Societ y of America | 5585 Guilford Rd., Madison, WI 53711 USA
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form or by a ny means, electronic or mechanical, includ ing photocopying, recording,
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the publisher. Per mission for printing and for reprinting the material contai ned herein
has been obta ined by the publisher.
2 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
gradually, similar to the biomass production ( Jezowski et
al., 2011; Zub et al., 2011). In addition to the eect of
the year of cultivation, the biomass production, ower-
ing date, canopy height, stem number, and stem diameter
vary according to the clone and the harvest date (Clif-
ton-Brown and Lewandowski, 2002; Gauder et al., 2012;
Larsen et al., 2014; Lewandowski and Kicherer, 1997).
Furthermore, biomass production is highly and positively
correlated with the owering date, canopy height, and
stem diameter (Zub et al., 2011). In addition, the aboveg-
round volume of the plant has been identied as a reliable
predictor of biomass production for the second and the
third years of cultivation (Zub et al., 2012a).
Moreover, the traits related to the biomass composi-
tion are more consistent throughout the years of cultivation
than the traits related to the biomass production (Allison et
al., 2011). The traits related to the biomass composition are
inuenced mainly by the harvest date and the Miscanthus
clone (Allison et al., 2011; Qin et al., 2012). The aboveg-
round biomass production is highly and positively associ-
ated with cellulose and lignin contents. It is negatively asso-
ciated with the contents of hemicellulose, soluble, and ash.
The second-generation bioethanol production indus-
try needs crops displaying high aboveground biomass pro-
duction as well as high cellulose and hemicellulose con-
tents and low lignin, soluble, and ash contents (van der
Weijde et al., 2013; Dumas and Navard, personal com-
munication, 2014).
To breed Miscanthus clones that are tailored for sec-
ond-generation bioethanol production through an e-
cient breeding strategy, the early selection of traits that
are related to the biomass production and composition in
the rst few years of cultivation is essential for this peren-
nial crop, that is, without having to wait for the adult
phase. For this purpose, biomass production and composi-
tion predictions are needed. Moreover, as a complex trait,
biomass production needs to be predicted with reliability
using nondestructive and easy-to-measure traits.
We hypothesized that (i) the traits that are related to
the biomass production and composition of a mature crop
can be predicted in the early stages, and (ii) an index com-
bining several simple traits can improve the reliability of
the predicted biomass production.
Therefore, for breeding purpose, the aims of this study
were (i) to investigate the potential to predict the traits of
interest that are related to biomass production and compo-
sition in the early stages of the crop and (ii) to determine
reliable predictors using simple traits or an index to esti-
mate biomass production.
To meet these objectives, we studied 21 Miscanthus
clones that were cultivated for ve consecutive years
with two harvest dates (autumn and winter har vests).
These two harvest dates are potentially interesting for
diverse end uses. We studied the interannual correlations
involving the biomass production, the traits related to bio-
mass production (i.e., the owering date, canopy height,
number of stems per plant, and stem diameter), and the
traits related to the biomass composition (i.e., the cellu-
lose, hemicellulose, lignin, soluble, and ash contents in the
aboveground biomass). This paper will provide guidelines
for the early selection of Miscanthus clones that are tailored
for second-generation bioethanol production.
MATERIALS AND METHODS
Experimental Site and Climatic Conditions
The experimental site is located in the Picardie region of
Northern France (4953 N, 300 E) at the French National
Institute for Agricultural Research (IN RA) experimental unit
in Estrées-Mons, France. The soil is a deep loam soil (Ortic
Luvisol, FAO classication) and the climate is oceanic. The
rainfall and temperature data were collected for the duration of
the trial by a local meteorological station located at a distance
of 1 km from the experimental site.
Experimental Design
The experiment was designed as a randomized complete block
comprised of six blocks, each containing 21 clones. The trial
contained a total of 126 plots, each plot measuring 16 m2.
Among the 21 Miscanthus clones planted, four were identied
as M. giganteus clones, 15 as M. sinensis clones, and two as M.
sacchariorus clones (Table 1). Among the four M. giganteus
clones, H8 was considered as a M. giganteus clone as it was
a hybrid between M. sacchariorus and M. sinensis. The clone
named Flo was identied as belonging to the M. giganteus
species using nuclear DNA analysis with amplied fragment
length polymorphism markers (Rambaud, personal communi-
cation, 2013) and cpDNA analysis (Feng et al., 2014).
In addition to the various clones, the harvest date was
studied in this experiment. Two harvest dates were tested: an
autumn harvest and a winter harvest. The autumn harvest was
performed at the end of the growing period according to the
earliness of each clone, that is, 200 degree-days after the ow-
ering time of each clone. The winter harvest was performed at
the end of winter at overmaturit y (in February). This harvest
date appeared to be more suitable for second-generation bio-
ethanol production (Cadoux et al., 2014).
Within the six blocks, the autumn harvest was consistently
assigned to the same three blocks and the winter harvest was
always performed on the three remaining blocks.
Each 16-m2 plot consisted of four rows of eight plants. A
border row that surrounded the plots was planted with the same
clone, that is, M. sinensisM a le par t us’.
Trial Management
The trial was planted by hand in spring 2007 at a density of two
plants per square meter. The plants were watered immediately
after planting to ensure good root contact with the soil. No
irrigation was applied during the following years of cultivation.
No fertilizer was applied during the entire experiment. The
weeds were controlled by hand during the two rst years and
by machine hoeing for the subsequent years.
crop science, vol. 55, mayjun e 2015 www.crops.org 3
sample of approximately 500 g of fresh matter was randomly
selected from each plot and weighed. Each sample was dried at
65C for 4 d in a well-ventilated oven. The moisture content
of each sample was determined and used to calculate the dry
weight and moisture content of the total plot biomass. The dry
weight (referred to as the aboveground biomass production) was
expressed as tons of dr y matter (DM) per hectare (t DM ha−1).
Biomass Components
The canopy height, stem number per plant, and stem diameter
were recorded in each plot before each har vest. The canopy
height corresponded to the distance from the ground to the
ligule of the last ligulated leaf. In each plot, the canopy height
and the stem number per plant were measured on three median
plants. These three plants were chosen as they reected the
median values of the canopy height and the stem number per
plant. These median values were based on the measures of all
the plants of each plot. The average canopy height and stem
number per plant were calculated from these three individual
values. The stem diameter was measured at a height of 5 cm
above the ground on 12 randomly selected stems per plot and
the average stem diameter was calculated.
Calculation of the Aboveground Plant
Volume Index
The aboveground plant volume index (expressed in cm3) was
calculated as a function of the canopy height, stem number per
plant, and stem diameter according to Zub et al. (2012a):
Measurements and Calculations
The owering date and the aboveground biomass production and
its components (i.e., canopy height, stem number per plant, and
stem diameter) were measured each year from the second to the
sixth year after planting (2008–2012) and for each harvest date.
Flowering Date
The owering date corresponded to the date on which 50% of
the plants in each plot had their owers open and when anthers
were rst extruded. This date was recorded for each plot by
counting the number of plants for which at least one single
ower was open. This count was performed each year during
July, August, September, and October, corresponding to the
owering period as a function of the earliness of the clones. The
record was performed every 2 d. Some clones (Flo, GiB, GiD,
and H5) did not ower in the Picardie region because the ow-
ering stage was not reached. These clones were of particular
interest in our study because of their high aboveground biomass
production. Therefore, in the absence of visible owering, the
owering date was recorded as the rst frost day of each year so
all clones could be included in the analysis. The rst frost day
was based on the average daily temperature below 0C. The
owering date was expressed in degree-days using the same
base temperature of 10C as Jensen et al. (2013).
Aboveground Biomass Production
Each plot was harvested using a reed harvester. The plants were
cut at a height of approximately 5 cm above the ground. The
total aboveground fresh matter of each plot was weighed. A
Table 1. Description of the 21 Miscanthus clones studied in the experiment, including the species, ploidy level, name, code,
and acquisition.
Species Name Code Ploidy levelAcquired from
M. giganteus M. giganteus UK GiB 3xUnited Kingdom, ADAS
M. giganteus DK GiD 4xDenmark, Nordic Biomass
M. giganteus Floridulus Flo3x France, Nursery Chombart
M. sacchariflorus x M. sinensis Hybrid 8 H8§2xDanish Institute Of Agricultural Science, Aarhus
M. sacchariflorus M. sacchariflorus Sac 2xFrance, Nursery Chombart
M. sacchariflorus Hybrid 5 H5§4xDanish Institute Of Agricultural Science, Aarhus
M. sinensis M. sinensis August Feder Aug 2xFrance, Nursery Chombart
M. sinensis Ferner Osten Fer 2xBelgium, Nursery Bruckeveld
M. sinensis Flamingo Fla 2xFrance, Nursery Chombart
M. sinensis Goliath Gol 4xFrance, Nursery Chombart
M. sinensis Goliath DK GoD 4xDenmark, Nordic Biomass
M. sinensis Graziella Grz 2xFrance, Nursery Chombart
M. sinensis Herman Müssel Her 2xBelgium, Nursery Bruckeveld
M. sinensis Hybrid 6 H6§4x Danish Institute Of Agricultural Science, Aarhus
M. sinensis Malepartus Mal 2xFrance, Nursery Chombart
M. sinensis Punktchen Pun 2xBelgium, Nursery Bruckeveld
M. sinensis Purpurescens Pur 2xBelgium, Nursery Bruckeveld
M. sinensis Rotsilber Rot 2xFrance, Nursery Chombart
M. sinensis Silberspinne Sil 2xFrance, Nursery Chombart
M. sinensis Strictus Str 2xFrance, Nursery Chombart
M. sinensis Yak u Ji m a Yak 2xBelgium, Nursery Bruckeveld
From Zub et al. (2012b).
The clon e named “Flo” was determined as a clone be longin g to the M. giganteus species (Feng et al., 2014; Rambaud, personal communication, 2013).
§ Clones p revious ly studied by Clif ton-Brown et al. (2001b) and Lewand owski et al. (2003a).
The H6 clo ne was determined a s a tetraplo id clone (4x) (Rambaud, personal communication, 2013).
4 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
Aboveground plant
volume index = canopy height
stem number per plant
(stem diameter/2)2
Chemical Analyses
of the Biomass Composition
The biomass composition of the total aboveground biomass was
determined using chemical analyses from samples harvested in
the third, fourth, and fth years (i.e., 2009–2011).
Sample Preparation
Dried aboveground biomass samples were coarsely ground
using a crusher mill (Viking, GE 220 model) and then ground
using a hammer crusher (Gondard Productions) to pass through
a 1-mm screen as recommended for subsequent ber analysis by
Van Soest and Wine (1967).
Determination of the Cellulose, Hemicellulose,
Lignin, and Soluble Contents
The ground samples were analyzed by the LANO laboratory
(Laboratoire Agronomique de Normandie, France) for soluble,
neutral detergent ber (NDF), acid detergent ber (ADF), and
acid detergent lignin (ADL) according to a protocol adapted
from the Van Soest method (Van Soest and Wine, 1967).
Briey, the NDF fraction corresponded to the ash-corrected
residue remaining after reuxing for 60 min in a neutral-bu-
ered detergent solution. The ADF fraction corresponded to the
ash-corrected residue remaining after reuxing the samples in a
solution of hexadecyltrimethylammonium bromide in 0.5 mol
L−1 sulfuric acid. The ADL fraction was obtained by treating
the ADF with 72% sulfuric acid.
The cellulose, hemicellulose, and lignin contents of each
sample were calculated by subtracting the corresponding values
from the NDF, ADF, and ADL fractions (expressed as % DM):
(i) the NDF consists of cellulose, hemicelluloses, and lignins;
(ii) the ADF consists of cellulose and lignin, and (iii) the ADL
consists of lignin. The cellulose, hemicellulose, and lignin con-
tents of each sample were calculated according to Eq. [1–3]:
Cellulose content (cellulose) = ADF − ADL [1]
Hemicellulose content
(hemicellulose) = NDF − ADF [2]
Lignin content (lignin) = ADL [3]
The soluble content (soluble) was expressed as percentage
dry matter (% DM), calculated according to Eq. [4], which cor-
responds to the NDF soluble fraction as follows:
Soluble = 100 − NDF [4]
Determination of the Ash Content
The ash content was expressed as percentage dry matter (%
DM) and corresponds to the dry matter remaining after calci-
nation of the samples at 550C for 12 h.
Statistical Analysis
The experimental dataset was analyzed through correlations
between the traits using the Pearson correlation coecients of
the CORR procedure (SAS Institute Inc., 2000). In addition,
simple linear regression was performed for the analysis of the
aboveground biomass production, the log (aboveground plant
volume index), and the cellulose content.
For the traits related to aboveground biomass production,
we used 19 clones corresponding to the 21 clones that were
used in our experiment except for clones H5 and Sac, for which
data were not available for the stem number, stem diameter,
and aboveground volume. For the traits that are related to the
biomass composition, we used 19 clones corresponding to the
21 clones that were used in our experiment except for clones
Her and Pun, for which data were not available.
We calculated the correlations for each year and each har-
vest date separately, considering each of the three blocks.
RESULTS
Evolution of Biomass Production-
and Composition-Related Traits
The average values for the aboveground biomass produc-
tion increased gradually from the second to the fourth year
of cultivation, and subsequently, were more consistent up
to the sixth year (Table 2a). Additionally, the average values
for the aboveground biomass production from the winter
harvest of the fourth year were particularly high (Table 2a);
this was attributed to more favorable climatic conditions in
this year (data not shown). A peak in the biomass produc-
tion was clearly visible for the two harvest dates during
the fourth year. It appeared that the biomass production
plateau was attained in this year in the autumn harvest,
whereas the winter yields were more variable (Fig. 1).
In addition, the range in the clonal variation for the
aboveground biomass production increased with the
number of years of cultivation for each harvest date; the
minimum values were especially consistent for this trait,
while the maximum values increased with the number of
years of cultivation (Table 2a).
The canopy height, stem number per plant, and aboveg-
round plant volume index followed the same trend as the
aboveground biomass production over the years of cultiva-
tion (Table 2a). In contrast, the average of the stem diameter
and owering date were consistent over time (Table 2a).
Regarding the clonal variation, the observation of the
minimum and maximum values showed that the range in
the canopy height, stem number per plant, and aboveg-
round plant volume index increased with the number
of years of cultivation for each harvest date (Table 2a).
However, the ranges corresponding to the owering date
crop science, vol. 55, mayjun e 2015 www.crops.org 5
Table 2. Description of the dataset of the Miscanthus clones grown in northern France and harvested on two harvest dates
(autumn and winter) from the second to the sixth year of cultivation for the traits related to the biomass production (a) and
composition (b).
(a)
Variable
(Unit)
(Number of
clones)
Year of
cultivation 2 3 4 5 6
Harvest
date Autumn Winter Autumn Winter Autumn Winter Autumn Winter Autumn Winter
Aboveground
biomass
production
(t DM ha−1)
(19 clones)
Mean SE§2.7 0.3 2.2 0.2 8.0 0.9 8.7 0.7 14. 2 1.2 24.7 1. 8 12. 8 1.3 14. 5 1.1 14.4 1. 3 17. 3 1. 2
Min 0.1 0 .1 0.3 0.6 1.2 4.7 0.9 3.4 0.0 2.4
Max 10.6 5.8 22.7 1 7. 2 36.4 52.0 44.9 32.4 38.2 36.9
Flowering date
(DD ba se 10)
(19 clones)
Mean SE 864 17 NA934 21 888 25 888 16 891 17 880 23 869 25 904 14 886 14
Min 535 NA 635 639 724 726 603 586 718 74 4
Max 1061 NA 118 7 118 7 108 9 1089 12 08 12 08 103 8 103 8
Canopy
height (cm)
(19 clones)
Mean SE 96 4 100 5 130 7 144 8 148 8 161 9 132 9 156 10 15 5 10 180 8
Min 45 36 58 68 72 85 53 72 77 90
Max 190 166 229 24 3 273 292 295 310 320 328
Stem number
per plant
(19 clones)
Mean SE 23 2 19 2 49 5 57 6 118 13 109 10 10 9 12 104 10 NA NA
Min 6 4 13 11 36 28 41 29 NA NA
Max 73 90 198 208 425 330 410 347 NA NA
Stem diameter
(mm)
(19 clones)
Mean SE NA 5.8 0.3 5.0 0.3 5.3 0.3 5.2 0.3 5.6 0.3 5.1 0.3 6.0 0.4 5.4 0.3 5.9 0.4
Min NA 2.8 1.4 2.6 2.3 2.5 2. 2 3.0 2.1 2.5
Max NA 9.5 10.0 9.8 10.3 10.0 10.7 12.0 10 .9 11.7
Aboveground
plant volume
index
(cm3)
(19 clones)
Mean SE NA 588 72 1291 181 1784 212 32 51 409 3792 366 2758 408 4221 575 NA NA
Min NA 14 30 161 656 656 308 669 NA NA
Max NA 195 5 6 416 6 612 13 86 1 9910 1175 2 19 605 NA NA
DM, dry matter.
DD, degree-days.
§ SE, standa rd error.
NA, data not available.
Table 2. Continued.
(b)
Variable
(Unit)
(Number of clones)
Year of
cultivation 345
Harvest date Autumn Winter Autumn Winter Autumn Winter
Cellulose
(% DM)
(19 clones)
Mean SE35.7 0.3 43.4 0.5 35.8 0.4 42.3 0.4 34.3 0.3 41.0 0.5
Min 31.3 34.2 26.2 3 7.1 30.3 33.6
Max 40.6 49.5 41. 4 4 8 .1 39.3 48.0
Hemicelluloses
(% DM)
(19 clones)
Mean SE 34.2 0.3 35.4 0.5 31.9 0.3 33.9 0.4 35.6 0.3 36.2 0.4
Min 29.4 2 7.7 26.6 2 7. 3 31.5 29.8
Max 38.4 40.4 35.9 39.2 39.3 40.6
Lignins
(% DM)
(19 clones)
Mean SE 5.3 0.2 7.7 0.3 5.5 0.2 7. 9 0.2 4.0 0.2 5.8 0.2
Min 3.5 4.0 3.0 5.7 2.2 4.2
Max 9.2 12 .1 9.1 11. 5 6.3 8.4
Solubles
(% DM)
(19 clones)
Mean SE 24. 8 0.3 13.6 0.3 26.9 0.4 16 .0 0.3 26.2 0.2 17.0 0.3
Min 19.8 9.8 21.9 11. 6 23.0 13. 2
Max 29.5 20.6 35.3 2 1.9 29.9 25.8
Ash
(% DM)
(19 clones)
Mean SE 4.3 0 .1 3.0 0.1 4.7 0.1 3.4 0 .1 5.0 0 .1 3.5 0.2
Min 1.8 1. 2 2.6 1. 5 2.8 1. 5
Max 5.9 5.5 6.2 5.2 6.4 10 .3
DM, dry matter.
SE, standa rd error.
6 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
and stem diameter remained relatively consistent over the
years of cultivation (Table 2a).
The average values of the traits related to the biomass
composition were more consistent than the aboveground
biomass production-related traits; for each harvest date,
the average values of the cellulose, hemicellulose, lignin,
soluble, and ash contents in the total aboveground biomass
were consistent from the third to the fth year of cultivation
(Table 2b). In contrast with the traits related to the biomass
production, the range in the clonal variation for all the traits
related to biomass composition were consistent throughout
the years of cultivation for each harvest date (Table 2b).
Interannual Correlations for Aboveground
Biomass Production and Related Traits
The aboveground biomass production in the winter har-
vest was highly and signicantly correlated between the
years of cultivation, with correlation coecients ranging
from 0.69 to 0.95 (Table 3a). Interestingly, the aboveg-
round biomass production was highly and signicantly
correlated between two subsequent years (in the diago-
nal of the matrix), with correlation coecients ranging
from 0.87 to 0.95 (Table 3a). In contrast, the correlations
between nonsequential years were lower and a mini-
mum correlation coecient of 0.69 was observed (Table
3a). In addition, the correlation coecients gradually
decreased when the interval between the years increased;
the aboveground biomass harvested in the sixth year was
highly correlated with the aboveground biomass produced
in the fourth and fth year (correlation coecients above
0.85), whereas it was less correlated with the aboveground
biomass produced in the second and third year (Table 3a).
Interestingly, the relative contribution of the indi-
vidual genotypes was similar throughout the years for
these correlations as illustrated in Fig. 2. In particular, the
clones Flo, GiB, and GiD, which clearly stood out on the
plots, maintained their relative contribution (Fig. 2).
Regarding the traits related to the biomass produc-
tion, they were always correlated between the years of
cultivation, with correlation coecients ranging from
0.59 to 0.99 in the winter harvest (Tables 3b–f ). The
owering date generally displayed the highest correlation
coecients between years followed by the stem diame-
ter, canopy height, aboveground plant volume index, and
stem number per plant (Tables 3b–f ).
Nevertheless, these traits were more or less correlated
depending on the interval between the years under con-
sideration. The correlation coecients decreased when the
interval between the years increased for the canopy height
and stem number per plant (Tables 3c, e). In contrast, the
owering date and stem diameter displayed consistent
Table 3. Interannual correlations between the second, third,
fourth, fifth, and sixth years of cultivation in the winter harvest
for (a) the aboveground biomass production and its related
traits: (b) the flowering date, (c) canopy height, (d) stem diam-
eter, (e) stem number per plant, and (f) aboveground plant
volume index of 19 Miscanthus clones. All correlation coef-
ficient values significant at the 0.05 probability level.
Pearson correlation coefficient
Yea r 2 Year 3 Yea r 4 Yea r 5 Year 6
(a) Aboveground biomass production (t DM ha−1)
Yea r 2 0.88 0.78 0.72 0.69
Yea r 3 0.87 0.81 0.76
Yea r 4 0.90 0.85
Yea r 5 0.95
(b) Flowering date (DD base 10)
Yea r 2 NA§NA NA NA
Yea r 3 0.99 0.97 0.96
Yea r 4 0.98 0.96
Yea r 5 0.94
(c) Canopy height (cm)
Yea r 2 0.90 0.79 0.72 0.67
Yea r 3 0.95 0.91 0.83
Yea r 4 0.97 0.93
Yea r 5 0.93
(d) Stem diameter (mm)
Yea r 2 0.94 0.95 0.94 0.93
Yea r 3 0.93 0.93 0.95
Yea r 4 0.93 0.94
Yea r 5 0.96
(e) Stem number per plant
Yea r 2 0.84 0.68 0.59 NA
Yea r 3 0.92 0.86 NA
Yea r 4 0.89 NA
Yea r 5 NA
(f) Aboveground plant volume index (cm3)
Yea r 2 0.80 0.70 0.65 NA
Yea r 3 0.79 0.88 NA
Yea r 4 0.67 NA
Yea r 5 NA
DM, dry matter.
DD, degree-days.
§ NA, data not available.
Figure 1. Average aboveground biomass production of 19 Miscan-
thus clones har vested in autumn and winter of the second to the
sixth year of cultivation. The errors bars represent the standard error.
crop science, vol. 55, mayjun e 2015 www.crops.org 7
correlation coecients between the years of cultivation
(Tables 3b, d). Lastly, the coecients were more variable
for the aboveground plant volume index (Table 3f).
All these interannual correlations observed in the
winter harvest for the aboveground biomass production
and its related traits were similar to those observed in the
autumn harvest (Supplemental Table S1a–f ). In addition,
these correlations showed a certain predictive capabil-
ity, which was assessed by a cross-validation. Compar-
ing the correlations obtained from one block of the trial
to the correlations of the two remaining blocks, a high
consistency of the correlations was found between the two
groups (Supplemental Table S2).
These results indicate that the aboveground biomass
production and its related traits observed in the sixth year,
which is considered as an adult age of the crop, were better
predicted from the third year than from the second year.
Correlations Between Autumn and Winter
Harvest Dates for Aboveground Biomass
Production and Related Traits
The aboveground biomass production and its related traits
were signicantly correlated between the autumn and
winter harvests, with correlation coecients ranging from
0.52 to 0.99 (Tables 4a–f ). The stem diameter and owering
date generally displayed the highest correlation coecients
between the harvest dates; the coecients varied from 0.84
to 0.99. These traits were followed by the canopy height,
aboveground biomass production, aboveground plant
volume index, and stem number per plant (Tables 4a–f ).
The correlation coecients between the second and
other years were generally lower than those from the third
year (Tables 4a–f ).
These results indicate that the aboveground biomass
production and its related traits were well correlated
between the autumn and winter harvests, especially from
the third year of growth.
Reliable Predictors of Adult Aboveground
Biomass Production
The aboveground biomass production was highly and
positively correlated with the owering date, canopy
height, stem diameter, and aboveground plant volume
index, with correlation coecients varying from 0.52
to 0.94 in the winter harvest (Table 5). In contrast, the
correlations between the aboveground biomass produc-
tion and the stem number per plant were nonsignicant
or weakly negative (Table 5). Nevertheless, the values of
these coecients varied over time. The correlations of the
aboveground biomass production with the canopy height
and aboveground plant volume index decreased from the
second to the sixth year. In contrast, the correlations with
the owering date and stem diameter increased (Table 5).
As the aboveground biomass production was highly
correlated with the canopy height and aboveground plant
volume index, they appeared to be the best predictors of
the aboveground biomass production (Table 5). Neverthe-
less, the log (aboveground plant volume index) increased
the correlation coecients with the aboveground bio-
mass production mainly during the rst years (Fig. 3a–h).
Therefore, the canopy height and the log (aboveground
plant volume index) were the best predictors of the
aboveground biomass production.
The correlations between these two best predic-
tors and the aboveground biomass produced from the
Figure 2. Contribution of the individual Miscanthus clones to the
interannual correlations between (a) the third and fourth years
of cultivation, (b) the third and fifth years, and (c) the third and
sixth years for the aboveground biomass production in the winter
harvest. A total of 19 Miscanthus clones were used for these plots.
The filled squares represent the M. giganteus clones, and the
filled triangles represent the M. sinensis clones. For details on the
clones, see Table 1. An asterisk represents significant correlations
at the 0.05 probability level; r, Pearson correlation coefficient.
8 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
second to the sixth year were higher for the predictors
in the third and fourth years compared with the second
year (Table 5). The aboveground biomass produced in
the second to the fourth year was slightly more correlated
with the log (aboveground plant volume index) than with
the canopy height observed in the second or third year
(Table 5). The correlations between the canopy height and
the aboveground biomass produced in the fth and sixth
years were slightly higher than the log (aboveground plant
volume index) (Table 5). Similar trends were observed in
the autumn harvest (Supplemental Table S3).
Interannual Correlations for Biomass
Composition-Related Traits
The correlation coecients between the years of culti-
vation were positive and signicant for all the biomass
composition traits in the winter harvest (Tables 6a–e).
However, the correlation coecients ranged from 0.38 to
0.85 and were generally lower than those obtained for the
aboveground biomass production and its related traits.
The cellulose, hemicellulose, and lignin contents in
the aboveground biomass displayed generally high inter-
annual correlation coecients, with values ranging from
0.69 to 0.85 (Tables 6a–c). In contrast, the correlations
were lower for the soluble and ash contents (Tables 6d–e).
For a given trait, these coecients varied among the
years. They were low in some years, as was the case for
the cellulose content measured between the third and the
fth years (Table 6a) and for the lignin content measured
Table 5. Correlations between the aboveground biomass
production (predicted variable) of the second, third, fourth,
fifth, and sixth years of cultivation using the following predic-
tors: the flowering date, canopy height, stem diameter, stem
number, and aboveground plant volume index using untrans-
formed and log-transformation data observed in the second,
third, and fourth years of cultivation. These correlations were
performed using 19 Miscanthus clones observed during the
winter har vest. All correlation coefficient values significant at
the 0.05 probability level.
Predictor Year
Predicted variable: Aboveground
biomass production
Yea r 2 Yea r 3 Ye ar 4 Year 5 Year 6
Flowering date Year 2 NANA NA NA NA
Yea r 3 0.52 0.71 0.78 0.77
Yea r 4 0.75 0.79 0.79
Canopy height Ye a r 2 0.91 0.90 0.79 0.76 0 .70
Yea r 3 0.87 0.82 0.89 0.86
Yea r 4 0.84 0.94 0.93
Stem diameter Ye a r 2 0.72 0.72 0 .74 0.81 0.77
Yea r 3 0.64 0.72 0.84 0.83
Yea r 4 0.75 0.86 0.83
Stem number per
plant
Yea r 2 NSNS NS NS NS
Yea r 3 NS NS NS NS
Yea r 4 NS −0.33 −0.32
Aboveground
plant volume
index
Yea r 2 0.9 0 0.83 0.82 0.75 0.68
Yea r 3 0.77 0.85 0.91 0.90
Yea r 4 0.78 0.85 0.78
Log (Aboveground
plant volume
index)§
Yea r 2 0.95 0.92 0.86 0.72 0.63
Yea r 3 0.90 0.91 0.86 0.83
Yea r 4 0.83 0.90 0.82
NA, data not available.
NS, Not sign ificant at the 0.05 proba bilit y level.
§The correlations were calculated using the log (aboveground biomass production).
Table 4. Correlations between the autumn and winter harvest
dates within and between the second, third, fourth, fifth, and
sixth year of cultivation for the traits related to the aboveg-
round biomass production from 19 Miscanthus clones: (a)
aboveground biomass production, (b) flowering date, (c)
canopy height, (d) stem diameter, (e) stem number per plant,
and (f) aboveground plant volume index. All correlation coef-
ficient values significant at the 0.05 probability level.
Pearson correlation coefficient
Yea r 2 Yea r 3 Yea r 4 Yea r 5 Ye a r 6
Autumn harvest
(a) Aboveground biomass production (t DM ha−1)
Winter
harvest
Yea r 2 0.78 0.80 0.77 0.72 0. 74
Yea r 3 0.77 0.82 0.81 0 .76 0.76
Yea r 4 0.68 0.79 0.84 0.82 0.8 0
Yea r 5 0.68 0.85 0.92 0.91 0.87
Yea r 6 0.63 0.84 0.92 0.90 0.89
(b) Flowering date (DD base 10)
Winter
harvest
Yea r 2 NA§NA NA NA NA
Yea r 3 0.90 0.96 0.98 0.96 0.88
Yea r 4 0.91 0.96 0.99 0.97 0.90
Yea r 5 0.90 0.96 0.97 0.97 0.88
Yea r 6 0.87 0.94 0.95 0.94 0.87
(c) Canopy height (cm)
Winter
harvest
Yea r 2 0.83 0.85 0.78 0.70 0.72
Yea r 3 0.82 0.96 0.93 0.88 0.89
Yea r 4 0.73 0.95 0.97 0.9 6 0.95
Yea r 5 0.67 0.92 0.97 0.98 0.96
Yea r 6 0.63 0.88 0.93 0.95 0.94
(d) Stem diameter (mm)
Winter
harvest
Yea r 2 NA 0.91 0.84 0.92 0.93
Yea r 3 NA 0.93 0.91 0.95 0.95
Yea r 4 NA 0.91 0.86 0.93 0.94
Yea r 5 NA 0.95 0.90 0.95 0.95
Yea r 6 NA 0.94 0.92 0.97 0.97
(e) Stem number per plant
Winter
harvest
Yea r 2 0 .71 0.64 0.57 0.52 NA
Yea r 3 0.76 0.86 0.86 0.83 NA
Yea r 4 0.75 0.85 0.91 0.8 6 NA
Yea r 5 0.67 0.83 0.92 0.92 NA
Yea r 6 NA NA NA NA NA
(f) Aboveground plant volume index (cm3)
Winter
harvest
Yea r 2 NA 0.73 0.57 0.70 NA
Yea r 3 NA 0.85 0.80 0.90 NA
Yea r 4 NA 0.75 0.64 0.73 NA
Yea r 5 NA 0.73 0.77 0.87 NA
Yea r 6 NA NA NA NA NA
DM, dry matter.
DD, degree-days.
§ NA, data not available.
crop science, vol. 55, mayjun e 2015 www.crops.org 9
Figure 3. Pairwise plots of traits between the aboveground biomass production of the third, fourth, fifth, and sixth years and the aboveground plant volume index of the third year for
untransformed (a, b, c, d) and log-transformed (e, f, g, h) data; data collected in the winter harvest. A total of 19 Miscanthus clones were used for these plots. The filled squares represent
the M. giganteus clones, and the filled triangles represent the M. sinensis clones. For details on the clones, see Table 1. An asterisk represents significant correlations at the 0.05
probability level; r, Pearson correlation coefficient.
10 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
between the fth and fourth years (Table 6c). Similarly, the
ash content also displayed low correlation coecients, espe-
cially between the third and the fth years and between the
fourth and the fth years (Table 6e). Similar trends were
observed in the autumn harvest (Supplemental Table S4a–e).
Despite these low correlations, the most productive
clones were consistently ranked throughout the years with
respect to the cellulose, hemicellulose and lignin contents
(Fig. 4 for cellulose content).
DISCUSSION
This study of the prediction of the traits related to Mis-
canthus biomass production and composition in the young
growth stages of the crop partially addressed our hypoth-
eses: (i) The traits related to the biomass production were
predicted with robustness in the early growth stages of
the crop, but the traits related to the biomass composition
were not well predicted; moreover, (ii) the canopy height
and the log (aboveground plant volume index) were reli-
able predictors of the biomass production.
We therefore discuss two main points directly related
to our results: (i) the potential to predict Miscanthus biomass
production and its related traits from the young stages of the
crop, (ii) the traits that are reliable predictors of the biomass
production, and (iii) the signicance of our results for the
early selection of promising Miscanthus clones as feedstock
for second-generation bioethanol production.
Prediction of Biomass Production
and Related Traits in Miscanthus from
Young Crop Stages
Clifton-Brown et al. (2001b) reported that the third-year
biomass production of 15 Miscanthus clones at ve sites in
Europe was better correlated with the second-year bio-
mass production than with the biomass produced in the
rst year. In addition, Clifton-Brown and Lewandowski
(2002) studied the same clones in southern Germany
for the rst 3 yr of cultivation with autumn and winter
Figure 4. Contribution of the individual Miscanthus clones to the
interannual correlations between (a) the third and fourth years of
cultivation and (b) the third and fifth years of cultivation for the
cellulose content observed in the winter harvest. A total of 19 Mis-
canthus clones were used for these plots. The filled squares rep-
resent the M. giganteus clones, the filled circles represent the
M. sacchariflorus clones, and the filled triangles represent the M.
sinensis clones. For details on the clones, see Table 1. An aster-
isk represents significant correlations at the 0.05 probability level;
r, Pearson correlation coefficient.
Table 6. Interannual correlations between the third, four th,
and fifth years of cultivation in the winter har vest for the
traits related to the biomass composition from 19 Miscan-
thus clones: (a) the cellulose, (b) hemicellulose, (c) lignin, (d)
soluble, and (e) ash contents. All correlation coefficient val-
ues significant at the 0.05 probability level.
Pearson correlation coefficient
Yea r 3 Year 4 Year 5
(a) Cellulose (% DM)
Yea r 3 0.80 0.69
Yea r 4 0.85
(b) Hemicelluloses (% DM)
Yea r 3 0.83 0.83
Yea r 4 0.82
(c) Lignins (% DM)
Yea r 3 0.83 0.82
Yea r 4 0. 74
(d) Solubles (% DM)
Yea r 3 0.61 0.50
Yea r 4 0.68
(e) Ash (% DM)
Yea r 3 0.73 0.38
Yea r 4 0.47
DM, dry matter.
crop science, vol. 55, mayjun e 2015 www.crops.org 11
harvests and reported that the biomass production in the
rst year was not always related to the biomass produced
in subsequent years. These authors concluded that the
selection of Miscanthus clones showing optimal biomass
production should be based on at least 2 yr of eld trials.
Our results agree with these observations.
Similar trends have been described in the literature
for the traits related to the biomass production, particu-
larly for the plant height and number of stems per plant.
A moderate regression coecient (r = 0.67) was observed
between Miscanthus height in the rst and third year of
cultivation (Clifton-Brown and Lewandowski, 2002).
In addition, these authors showed that the shoot density
measured at the end of the rst growing season, which
could be associated with our measure of the stem number
per plant, was poorly correlated with the shoot density
measured at the end of the third growing season. We stud-
ied an extended time period, that is, longer than the three
rst years, and found lower correlations between traits
measured in the second year compared with subsequent
years. These results suggest that the plant height and stem
number per plant were predicted with more reliability
from the third year of cultivation than from the rst 2 yr.
In addition, our results indicated that the stem diameter
consistently displayed high correlation coecients between
the second to the sixth year, which was similar to the
results reported for poplar (Populus spp.), a woody perennial
crop of particular interest for the second-generation bio-
ethanol production (Kaczmarek et al., 2013). Furthermore,
the aboveground plant volume index was well correlated
between years, which is similar to the results reported for
poplar using a comparable index (Kaczmarek et al., 2013).
Reliable Predictors of Biomass Production
Jezowski (2008) reported that the biomass production of
six Miscanthus clones harvested in winter was highly cor-
related with the canopy height in the second and third
years of cultivation. In addition, Clifton-Brown et al.
(2001b) showed that the height of 15 Miscanthus clones was
well correlated with the biomass harvested in autumn of
the third year. Gauder et al. (2012) reported that the plant
height at senescence was a reliable parameter to estimate
the biomass harvested in winter. Furthermore, Robson
et al. (2013) observed that the canopy height of 244 Mis-
canthus clones was better correlated with the biomass
harvested in winter of the third year than the stem diam-
eter or the maximum canopy height. Our results veried
these observations and conrmed that the canopy height
was generally better correlated with the biomass produc-
tion than other morphological traits.
Clifton-Brown et al. (2001b) reported that the shoot
density, which is similar to our measurement of the number
of stems per plant, was poorly correlated with the aboveg-
round biomass harvested in autumn of the third year. In
contrast, Gauder et al. (2012) reported a relatively high and
negative correlation between the yield and the shoot den-
sity in a study performed on 14 consecutive years. Our
results agree with both studies; there were no correlations
between the second- and third-year data, whereas we
observed negative correlations in the fourth year irrespec-
tive of the harvest dates. These results showed that the cor-
relation between the stem number and the biomass pro-
duction increased over time and suggested that the stem
number did not contribute to the yield during the early
growth stages compared with the later stages. Moreover,
the contribution of the stem number to the biomass pro-
duction could be compensated by other variables such as
the height of the plants and the stem diameter. With a sim-
ilar height of the plants between all the genotypes, it would
be expected a better contribution of the stem number.
In addition, Zub et al. (2012a) reported that the aboveg-
round plant volume index of Miscanthus was a reliable pre-
dictor of the biomass produced in the second and third
years. Our results conrmed these ndings over a longer
time period (from the second to the sixth year). However,
we showed that the aboveground plant volume index was
a less reliable predictor of the biomass produced in the fth
and sixth years, compared with the canopy height. This
may be due to the diculty to determine the stem number
per plant for older plants in comparison to younger plants.
Therefore, we can suggest that this decreased the aboveg-
round plant volume index reliability to predict the biomass
production of older Miscanthus crops.
In a poplar study, Rae et al. (2004) found that the
stem volume index was the best predictor of the biomass
production, followed by the total basal area and the tree
height at harvest, which were used to calculate the stem
volume index. In addition, Scaracia-Mugnozza et al.
(1997) reported that the stem volume growth of poplar
well reected the increase in tree biomass. These observa-
tions conrmed our Miscanthus results.
Breeding Implications for the Early Selection
of Interesting Miscanthus Clones
Selecting clones based on the aboveground biomass pro-
duced in the rst and second years would be less eective
than a selection based on the third year data; however, an
initial screening of the most productive Miscanthus clones
from the rst and second years could be feasible because
Clifton-Brown and Lewandowski (2002) showed that
the most productive Miscanthus clones identied in the
rst year were generally also the most productive in the
subsequent years. However, our results showed that the
screening has to be continued for at least 3 yr.
Because of the high correlations between the two har-
vest dates, the clone selection can be performed using a
single harvest date. Under the tested conditions, this would
12 www.c rops .org crop scie nce, v ol. 55, mayjune 2015
allow the autumn harvest to be selected indirectly from the
winter harvest, which is the most common practice.
In addition, the canopy height and the aboveground
volume index were useful criteria to make an early selec-
tion of the most productive Miscanthus clones. Given the
very small dierences in predictive power between these
two predictors, breeders should use the canopy height to
accurately identify the most productive clones, as it is an
easy-to-measure trait. Nevertheless, we explored here a
great variability regarding the height of the plants in com-
parison to the other traits. For a lower variability, it should
be expected a greater impact of the stem number as found
in switchgrass (Panicum virgatum L.) (Price and Casler, 2014).
This would lead to a superiority of the aboveground plant
volume index to predict the subsequent years of production
in comparison to the plant height and this would require a
better assessment of the stem number per plant. This is par-
ticularly interesting as the canopy height and aboveground
plant volume index were nondestructive measurements.
Furthermore, the prediction of the traits related to the
biomass composition was less reliable when using the rst
years of cultivation in comparison with the aboveground
biomass production-related traits under the tested con-
ditions. However, an initial screening can be attempted
during the rst few years among the most productive
clones with respect to the cellulose, hemicellulose, and
lignin contents because we observed that the contribution
of the most productive clones were consistent over time.
CONCLUSIONS
This study investigated the possibility of early prediction
of the traits related to Miscanthus biomass production and
composition on a single-site testing.
The biomass production and its related traits, more
particularly, the stem diameter, owering date, and
canopy height, displayed high correlations between the
years. These traits were better predicted from the third
year of cultivation than from the second year. Moreover,
the correlations between the two harvest dates were high.
Therefore, to early select these traits in Miscanthus in the
rst few years of cultivation, it is more reliable to screen
the genotypes for at least 3 yr and it is possible to limit the
evaluation to a single harvest date.
In addition, the biomass produced in the rst years (i.e.,
the second to fourth year) was reliably predicted using the
log (aboveground plant volume index) of the second and
third years; however, the biomass produced in later years
(i.e., in the fth and sixth years) was better predicted using
the canopy height of the second and third year.
Additionally, a rst screening of the cellulose, hemi-
cellulose, and lignin contents can be attempted among the
most productive genotypes during the early stages of the
crop as the most productive clones were consistently ranked
throughout the years with respect to these variables.
Acknowledgments
The authors would like to thank the FUTUROL project funded
by Oseo, which supported this study. Particular thanks to Benoit
Decaux and the sta of the UE GCIE for their valuable help in the
records, harvests, and maintenance of the trial. Thanks to Yves
Barrière, Jacques Le Gouis, and François-Xavier Oury for their
valuable recommendations during the preparation of this text.
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... The genus sensu stricto comprises about 12 species (Clifton-Brown et al., 2008), among which Miscanthus × giganteus and Miscanthus sinensis are the most cultivated in Europe. Morphological traits contribute to a high aboveground biomass production (Robson et al., 2013;Zub et al., 2011), and the aboveground biomass production itself is well predicted by a combination of morphological traits, such as aboveground volume or stand volume (Arnoult et al., 2015;Zub et al., 2012). In a comparison of 21 miscanthus clones, the most productive clones displayed high cellulose and lignin contents but low hemicellulose contents (Arnoult et al., 2015). ...
... Morphological traits contribute to a high aboveground biomass production (Robson et al., 2013;Zub et al., 2011), and the aboveground biomass production itself is well predicted by a combination of morphological traits, such as aboveground volume or stand volume (Arnoult et al., 2015;Zub et al., 2012). In a comparison of 21 miscanthus clones, the most productive clones displayed high cellulose and lignin contents but low hemicellulose contents (Arnoult et al., 2015). ...
... The stand volume yielded the best predictions of the biomass produced in the second and third years. Arnoult et al. (2015) confirmed these findings over a longer time period. Here, we confirmed the good predictability of aboveground biomass by stand volume over a larger number of genotypes. ...
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Abstract Miscanthus (Miscanthus Andersson) is a perennial grass that is attracting growing interest from the biomaterial industry. Our aim was to compare miscanthus genotypes varying in stem solidness, a measure of degree to which pith fills cavity between the outer walls of the stem, and analyze whether this trait influences the mechanical properties of polypropylene composites reinforced with miscanthus particles. Six contrasting genotypes were chosen from a Miscanthus sinensis population to determine morphological variables, stem solidness, and mechanical properties of polypropylene composites including 30% of milled miscanthus particles of two sizes of 100
... Miscanthus is a perennial crop that typically matures in 2-5 years, depending on the environmental conditions. During this process of maturation, miscanthus shows a pattern of increasing yields during the establishment phase, until at full maturity a plateau phase is reached, with relatively stable yields (Christian and Haase, 2001;Christian et al., 2008;Gauder et al., 2012;Hulle et al., 2012;Arnoult et al., 2015). Here we show that during this establishment phase, cell wall composition is changing as the crop matures. ...
... However, for all locations accession performance in CEY in the second cultivation year correlated reasonably well with that in the third cultivation year (r 2 = 0.42-0.83). Previously, Arnoult et al. (2015), already indicated that biomass quality in miscanthus harvested in the third cultivation year was reliably representative of that in the fourth and the fifth year in a single location. Here we validate that conclusion using data from multiple environments and even support that performance at full maturity can be estimated with reasonable accuracy from accession performance after two cultivation years. ...
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To investigate the potential effects of differences between growth locations on the cell wall composition and saccharification efficiency of the bioenergy crop miscanthus, a diverse set of 15 accessions were evaluated in six locations across Europe for the first 3 years following establishment. High-throughput quantification of cellulose, hemicellulose and lignin contents, as well as cellulose and hemicellulose conversion rates was achieved by combining near-infrared reflectance spectroscopy (NIRS) and biochemical analysis. Prediction models were developed and found to predict biomass quality characteristics with high accuracy. Location significantly affected biomass quality characteristics in all three cultivation years, but location-based differences decreased toward the third year as the plants reached maturity and the effect of location-dependent differences in the rate of establishment reduced. In all locations extensive variation in accession performance was observed for quality traits. The performance of the different accessions in the second and third cultivation year was strongly correlated, while accession performance in the first cultivation year did not correlate well with performance in later years. Significant genotype-by-environment (G × E) interactions were observed for most traits, revealing differences between accessions in environmental sensitivity. Stability analysis of accession performance for calculated ethanol yields suggested that selection for good and stable performance is a viable approach. Environmental influence on biomass quality is substantial and should be taken into account in order to match genotype, location and end-use of miscanthus as a lignocellulose feedstock.
... The same factors, albeit to different extents, determine photosynthesis, growth and biomass productivity. The yield-building phase of Miscanthus growth is considered to take three years, after which biomass supply is maintained relatively constantly for up to 20 years (Lewandowski et al., 2000;Clifton-Brown et al., 2008;Jeżowski, 2008;Jeżowski et al., 2011;Robson et al., 2013;Arnoult et al., 2015a;McCalmont et al., 2017;Nazli et al., 2018). Established plantations provide feedstock for pelleting, but increasingly they are being examined for biofuel production potential (Le Ngoc Huyen et al., 2010;Han et al., 2011;Brosse et al., 2012;Arnoult et al., 2015b). ...
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Production of bioethanol from Miscanthus biomass has been studied for years, yet many important aspects still remain to be evaluated and optimised. It may be assumed that the three-year yield-building phase of Miscanthus growth would be sufficient for stabilisation of biomass composition to provide suitable biomass as a bioethanol feedstock. Such early biomass harvesting could be important for the economics of newly established plantations. This study shows the gradual stabilisation of biomass production by genotypes of M. × giganteus, M. sinensis and M. sacchariflorus within the first three years of cultivation on moderately fertile soil, under the climatic conditions of west-central Poland. Photosynthesis, plant growth, biomass yield, and biochemical and elemental composition, simultaneously stabilised. The tested genotypes differed in their photosynthesis intensity and yield traits. There was little variation in the biochemical composition among genotypes; in comparison to Miscanthus cultivated in a more oceanic climate there was lower cellulose content, but higher lignin content. Aside from basal elements, the tested genotypes varied considerably in their accumulation of most macro- and especially microelements. The three-year old, winter-harvested technical biomass was used for pilot-scale bioethanol production including alkaline delignification and SSF technology. The particular biochemical components and elements in the biomass differently impacted the production process, yet for most genotypes the bioethanol produced was highly correlated with the cellulose:lignin ratio. The highest yield (g/kg DM) and efficiency (%) of raw bioethanol production were recorded for genotypes of M. sinensis (234–253 g/kg DM, 83–86%), followed by M. sacchariflorus (207–237 g/kg DM, 76–81%) and M. × giganteus (185–222 g/kg DM, 62–76%). However, biomass yield had a substantial effect on the estimated bioethanol production. The study pointed to the high potential for raw bioethanol production (4,400-5,600 L/ha) exploiting 3-year Miscanthus plantations, comparably for M. × giganteus and M. sinensis cultivated in a temperate transitional climate.
... Therefore, several studies report the interest of the ear and stem density as traits to be used in the selection process of wheat genotypes [4,5]. Further, plant height and stem diameter are highly correlated with the above-ground biomass in wheat [6][7][8][9][10]. Therefore, stem density, ear density, plant height, and stem diameter are thus highly desired to score the performances of a genotype in wheat crop breeding programs. ...
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Total above-ground biomass at harvest and ear density are two important traits that characterize wheat genotypes. Two experiments were carried out in two different sites where several genotypes were grown under contrasted irrigation and nitrogen treatments. A high spatial resolution RGB camera was used to capture the residual stems standing straight after the cutting by the combine machine during harvest. It provided a ground spatial resolution better than 0.2 mm. A Faster Regional Convolutional Neural Network (Faster-RCNN) deep-learning model was first trained to identify the stems cross section. Results showed that the identification provided precision and recall close to 95%. Further, the balance between precision and recall allowed getting accurate estimates of the stem density with a relative RMSE close to 7% and robustness across the two experimental sites. The estimated stem density was also compared with the ear density measured in the field with traditional methods. A very high correlation was found with almost no bias, indicating that the stem density could be a good proxy of the ear density. The heritability/repeatability evaluated over 16 genotypes in one of the two experiments was slightly higher (80%) than that of the ear density (78%). The diameter of each stem was computed from the profile of gray values in the extracts of the stem cross section. Results show that the stem diameters follow a gamma distribution over each microplot with an average diameter close to 2.0 mm. Finally, the biovolume computed as the product of the average stem diameter, the stem density, and plant height is closely related to the above-ground biomass at harvest with a relative RMSE of 6%. Possible limitations of the findings and future applications are finally discussed.
... Yield of perennial crops typically follows a trajectory with three main phases: a yield-building phase where yield increases, a maturity phase when the crop yield plateaus, and a gradual decrease associated with stand decline. This pattern has been documented in perennial C 3 and C 4 grasses [9][10][11][12], mixed grasslands and pastures [13][14][15], and forests [16,17]. Understanding when these phases are likely to occur, and what management or genetics can be used to influence their timing, is key to understanding the financial and carbon economy of perennial biomass crops [10,18]. ...
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Much field research on perennial bioenergy crops confounds effects of plant age with those of the growing season, which increases uncertainty and the potential for erroneous conclusions, particularly in maturing stands. Most studies rely on stands planted in a single year and measured across multiple subsequent seasons. These “single-start” designs lack statistical power to separate temporal from environment effects. We used a staggered start experimental design to learn if increased statistical power clarified understanding of Miscanthus × giganteus nitrogen (N) needs. We conducted a staggered start experiment with three planting years and five N rates during the M. × giganteus yield-building phase at three sites across IA, USA. Third-year yields were 21.0, 25.0, and 27.1 Mg dry matter (DM) ha⁻¹ at the northwest (NW), central, and southeast (SE) sites, respectively. Nitrogen fertilization effects changed with establishment conditions, but not with plant age. At the most N responsive site, N fertilizer changed yields at all stand ages, but not in every year. Yield increases of 150%, 36%, and 40% were observed in 1-, 2-, and 3-year-old stands, respectively, with N addition. Nitrogen effects on 1-year-old stands were positive in SE IA (2.7 kg DM kg⁻¹ N added), negative (− 2.3 kg DM kg⁻¹ N) in NW IA, and variable in central IA (− 2.2–9.6 kg DM kg⁻¹ N), suggesting a site–year-specific response. Yield increases between the first and second years varied by > 100% depending on establishment conditions, highlighting the need for repeated planting before determining economic and agronomic crop viability.
... Compared to annual crops, progress in breeding of perennials, such as miscanthus, is slowed-down by the need to evaluate genotype performance in multi-year field trials. Miscanthus typically matures in 3 years and selection at a premature stage, specifically during its first year of establishment, has proven unreliable [24]. Therefore, the application of marker-assisted selection could substantially increase the efficiency of breeding in miscanthus, as selections could be done at the seedling stage using marker data. ...
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Background Miscanthus sinensis is a high yielding perennial grass species with great potential as a bioenergy feedstock. One of the challenges that currently impedes commercial cellulosic biofuel production is the technical difficulty to efficiently convert lignocellulosic biomass into biofuel. The development of feedstocks with better biomass quality will improve conversion efficiency and the sustainability of the value-chain. Progress in the genetic improvement of biomass quality may be substantially expedited by the development of genetic markers associated to quality traits, which can be used in a marker-assisted selection program. Results To this end, a mapping population was developed by crossing two parents of contrasting cell wall composition. The performance of 182 F1 offspring individuals along with the parents was evaluated in a field trial with a randomized block design with three replicates. Plants were phenotyped for cell wall composition and conversion efficiency characters in the second and third growth season after establishment. A new SNP-based genetic map for M. sinensis was built using a genotyping-by-sequencing (GBS) approach, which resulted in 464 short-sequence uniparental markers that formed 16 linkage groups in the male map and 17 linkage groups in the female map. A total of 86 QTLs for a variety of biomass quality characteristics were identified, 20 of which were detected in both growth seasons. Twenty QTLs were directly associated to different conversion efficiency characters. Marker sequences were aligned to the sorghum reference genome to facilitate cross-species comparisons. Analyses revealed that for some traits previously identified QTLs in sorghum occurred in homologous regions on the same chromosome. Conclusion In this work we report for the first time the genetic mapping of cell wall composition and bioconversion traits in the bioenergy crop miscanthus. These results are a first step towards the development of marker-assisted selection programs in miscanthus to improve biomass quality and facilitate its use as feedstock for biofuel production. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3802-7) contains supplementary material, which is available to authorized users.
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In the context of bioenergy production, sorghum and miscanthus are relevant candidates for biogas production. As for many lignocellulosic biomasses, pretreatments can improve the accessibility of carbohydrates for microorganisms during anaerobic digestion. The objectives of this study were (1) to assess environmental impacts of lime and soda pretreatments of both biomasses in co-digestion with manure and (2) to compare the heat produced from natural gas with heat produced from biomethane generated from whole plants of sorghum and miscanthus under different studied scenarios. A comprehensive attributional life cycle analysis (LCA) was performed on 21 sorghum scenarios and 12 miscanthus scenarios. Certain scenarios explored direct and indirect land use change (dLUC and iLUC). An environmental evaluation highlighted that most of the impacts are generated by crop production and by the purification and injection step for both sorghum and miscanthus. Compared to natural gas, the study emphasized that, unlike lime treatment, soda treatment does not provide an added value. Although most impacts are favourable towards natural gas, sorghum-based methane presents very good results (below 0) for six impact categories. The reduction of climate change ranges from − 90 to − 105%. Miscanthus can reduce climate change by − 60 to − 80%, but almost all other impact categories are in favour of natural gas. Lime pretreatment always presents best results. For both sorghum and miscanthus, it is crucial that crops are not cultivated on a land in competition with food production.
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Genetic progress is one of the major leverage used to increase food production and satisfy the needs for the increasing human population under global change issues. Selecting or creating the optimal cultivar for a given location is quite challenging considering the very large spatial and temporal variability of the environmental conditions. Field phenotyping, i.e. the quantitative monitoring of crop state variables and canopy functioning, was recognized as the bottleneck to accelerate genetic progress and increase crop yield. This multidisciplinary study develops statistical and image processing methods to estimate the several structural traits of wheat to be applied to crop breeding. Further, this thesis was undertaken in the context of rapid hardware and software technological advancements illustrated by the increasing accessibility to UAV (Unmanned Aerial Vehicle) and UGV (Unmanned Ground Vehicle) platforms, the decreasing cost of processing units (GPUs, cloud computing) and the boom in the development of deep learning algorithms. This manuscript is divided into five chapters: The first chapter introduces the motivation behind the study as well as the current needs for high throughput phenotyping. A state of the art on phenotyping is also achieved by drawing attention to image processing methods and convolutional neural networks. The second chapter presents the development of methodologies for estimating the crop height. The feasibility of two main technologies and platforms were compared and proven: LiDAR mounted on a UGV and RGB (Red Green Blue) images acquired by a UAV. The next two chapters address the problem of estimating the density of wheat ears and stems from spatial high-resolution images. The results show the potential and limitations of deep learning for this application. Emphasis is also put on the study of the different possible acquisition configurations and the throughput of the method. The last chapter summarizes the pipelines developed and draws different perspectives of high throughput phenotyping to replace or supplement in-situ measurements as well as the improvement facilitated by the methods developed.
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HIGHLIGHTSBiomass production and cell wall composition are differentially impacted by harvesting year and genotypes, influencing then cellulose conversion in miniaturized assay. Using a high-throughput miniaturized and semi-automated method for performing the pretreatment and saccharification steps at laboratory scale allows for the assessment of these factors on the biomass potential for producing bioethanol before moving to the industrial scale. The large genetic diversity of the perennial grass miscanthus makes it suitable for producing cellulosic ethanol in biorefineries. The saccharification potential and year variability of five genotypes belonging to Miscanthus × giganteus and Miscanthus sinensis were explored using a miniaturized and semi-automated method, allowing the application of a hot water treatment followed by an enzymatic hydrolysis. The studied genotypes highlighted distinct cellulose conversion yields due to their distinct cell wall compositions. An inter-year comparison revealed significant variations in the biomass productivity and cell wall compositions. Compared to the recalcitrant genotypes, more digestible genotypes contained higher amounts of hemicellulosic carbohydrates and lower amounts of cellulose and lignin. In contrast to hemicellulosic carbohydrates, the relationships analysis between the biomass traits and cellulose conversion clearly showed the same negative effect of cellulose and lignin on cellulose digestion. The miniaturized and semi-automated method we developed was usable at the laboratory scale and was reliable for mimicking the saccharification at the pilot scale using a steam explosion pretreatment and enzymatic hydrolysis. Therefore, this miniaturized method will allow the reliable screening of many genotypes for saccharification potential. These findings provide valuable information and tools for breeders to create genotypes combining high yield, suitable biomass composition, and high saccharification yields.
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Miscanthus is a perennial grass rich in lignocellulose that has attracted interest as a non-food crop for renewable bioenergy with major environmental and economic benefits for China. The lignocellulose composition of whole stems of four major species of Miscanthus was assessed. The average values of total moisture content (TMC) (61.90%) and hemicelluloses (34.86%) were the highest while cellulose (32.71%) and acid detergent lignin (ADL) (8.90%) were the lowest in Miscanthus floridulus. On the contrary, the contents of cellulose (42.11%) and ADL (13.64%) were the highest and total ash (TA) (2.89%) was the lowest in Miscanthus lutarioriparius. The Shannon–Weaver diversity indices of components for the four species showed that hemicellulose content (H'= 2.00±0.11) was the most variable trait followed by cellulose (H'= 1.84±0.07), then ADL (H'= 1.84±0.07). The variational range of each component was relatively higher in Miscanthus sacchariflorus. In M. lutarioriparius, the diversity indices of each component were moderate. The diversity of cellulose was the highest and hemicellulose, ADL, TA and TMC were low in Miscanthus sinensis. By correlation analysis, neutral detergent fiber (NDF) significantly and positively correlated with ADF, cellulose and ADL at P<0.01 as well as the relationship of cellulose and ADL in the four species. Hemicellulose showed significant (P<0.01) but negative correlation with cellulose and ADL in M. floridulus, M. lutarioriparius and M. sacchariflorus. By principal component analysis (PCA), the components ADF and cellulose were the PC1 that were considered the foremost for the evaluation and selection of resource in the four species. The conclusions show that lignocellulose composition contents of Miscanthus culms were different. M. floridulus was more fit to ethanol fermentation. Though the components contents in M. sinensis and M. sacchariflorus were moderate, the range of choice was large. It provided a possible means to screen the appropriate materials according to different utilization. M. lutarioriparius had more superiorities relatively. So the four species of Miscanthus were appropriate for extension as excellent herbaceous energy plants, though, reasonable species choice should be employed according to the conversion approach and the growth characteristics, productivity levels and biomass quality characteristics of these tall grasses.
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Biomass from dedicated crops is expected to contribute significantly to the replacement of fossil resources. However, sustainable bioenergy cropping systems must provide high biomass production and low environmental impacts. This study aimed at quantifying biomass production, nutrient removal, expected ethanol production, and greenhouse gas (GHG) balance of six bioenergy crops: Miscanthus × giganteus, switchgrass, fescue, alfalfa, triticale, and fiber sorghum. Biomass production and N, P, K balances (input-output) were measured during 4 years in a long-term experiment, which included two nitrogen fertilization treatments. These results were used to calculate a posteriori ‘optimized’ fertilization practices, which would ensure a sustainable production with a nil balance of nutrients. A modified version of the cost/benefit approach proposed by Crutzen et al. (2008), comparing the GHG emissions resulting from N-P-K fertilization of bioenergy crops and the GHG emissions saved by replacing fossil fuel, was applied to these ‘optimized’ situations. Biomass production varied among crops between 10.0 (fescue) and 26.9 t DM ha−1 yr−1 (miscanthus harvested early) and the expected ethanol production between 1.3 (alfalfa) and 6.1 t ha−1 yr−1 (miscanthus harvested early). The cost/benefit ratio ranged from 0.10 (miscanthus harvested late) to 0.71 (fescue); it was closely correlated with the N/C ratio of the harvested biomass, except for alfalfa. The amount of saved CO2 emissions varied from 1.0 (fescue) to 8.6 t CO2eq ha−1 yr−1 (miscanthus harvested early or late). Due to its high biomass production, miscanthus was able to combine a high production of ethanol and a large saving of CO2 emissions. Miscanthus and switchgrass harvested late gave the best compromise between low N-P-K requirements, high GHG saving per unit of biomass, and high productivity per hectare.
A rapid procedure for determining cellwall constituents of plants consists of the determination of the fiber insoluble in neutral detergent and is applicable to all feedstuffs. The standardization of the method is based on a nutritional concept which defines fiber as insoluble vegetable matter which is indigestible by proteolytic and diastatic enzymes and which cannot be utilized except by microbial fermentation in the digestive tracts of animals.
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Miscanthus is a perennial grass rich in lignocellulose that has attracted interest as a non-food crop for renewable bioenergy with major environmental and economic benefits for China. The lignocellulose composition of whole stems of four major species of Miscanthus was assessed. The average values of total moisture content (TMC) (61.90%) and hemicelluloses (34.86%) were the highest while cellulose (32.71%) and acid detergent lignin (ADL) (8.90%) were the lowest in Miscanthus floridulus . On the contrary, the contents of cellulose (42.11%) and ADL (13.64%) were the highest and total ash (TA) (2.89%) was the lowest in Miscanthus lutarioriparius . The Shannon–Weaver diversity indices of components for the four species showed that hemicellulose content (H’= 2.00±0.11) was the most variable trait followed by cellulose (H’= 1.84±0.07), then ADL (H’= 1.84±0.07). The variational range of each component was relatively higher in Miscanthus sacchariflorus . In M. lutarioriparius , the diversity indices of each component were moderate. The diversity of cellulose was the highest and hemicellulose, ADL, TA and TMC were low in Miscanthus sinensis . By correlation analysis, neutral detergent fiber (NDF) significantly and positively correlated with ADF, cellulose and ADL at P<0.01 as well as the relationship of cellulose and ADL in the four species. Hemicellulose showed significant (P<0.01) but negative correlation with cellulose and ADL in M. floridulus , M. lutarioriparius and M. sacchariflorus . By principal component analysis (PCA), the components ADF and cellulose were the PC1 that were considered the foremost for the evaluation and selection of resource in the four species. The conclusions show that lignocellulose composition contents of Miscanthus culms were different. M. floridulus was more fit to ethanol fermentation. Though the components contents in M. sinensis and M. sacchariflorus were moderate, the range of choice was large. It provided a possible means to screen the appropriate materials according to different utilization. M. lutarioriparius had more superiorities relatively. So the four species of Miscanthus were appropriate for extension as excellent herbaceous energy plants, though, reasonable species choice should be employed according to the conversion approach and the growth characteristics, productivity levels and biomass quality characteristics of these tall grasses. Keywords: Miscanthus , bioenergy, lignocellulose compositions, detergent fiber, diversity analysis, PCA
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It is essential to enlarge the pool of varieties of the biomass crop Miscanthus to support the increase in its cultivation area, and several natural species from eastern or southeastern Asia could be of interest. Our main study objectives were: (i) to investigate the frequency spectrum of the haplotypes of natural Chinese accessions and their geographic distribution in China, and (ii) to identify the Chinese chloroplast genomes related to the maternal genomes of cultivated European varieties. We studied 21 clones cultivated in Europe and 44 wild Chinese accessions from 10 Chinese provinces covering four species of Miscanthus: M. sacchariflorus (Maxim.) Hack., M. sinensis Andersson, M. floridulus (Labill.) Warb. ex K. Schum. & Lauterb., and M. x giganteus J.M. Greef & Deuter ex Hodkinson & Renvoize. We used chloroplast DNA from sugarcane (Saccharum officinarum L.) due to its taxonomic relationship with Miscanthus and designed primers using the large single-copy region of the chloroplast genome. The polymorphisms belonged to noncoding and coding regions and were substitutions that corresponded to single nucleotide polymorphisms. Haplotypes were then determined, enabling the investigation of the haplotype frequency spectrum and the geographic distribution of the accessions in China. Furthermore, the maternal genome of M. ' giganteus appears related to some Chinese M. sacchariflorus clones. The corresponding geographic native area of these wild clones could be of interest to enlarge the genetic variability for the breeding of new interspecific hybrids.
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Commercial viability of switchgrass (Panicum virgatum) as a biofuel will require further improvements of biomass yield to improve sustainability. Direct selection for biomass yield in switchgrass has proven difficult due to the many factors influencing biomass yield. The identification of morphological traits associated with biomass yield could increase the efficiency of breeding efforts if these traits can be used as indirect selection criteria. By allowing increased screening and greater intensity of selection for biomass yield within spaced-plant nurseries, these results may impact how phenotypic selection is used for switchgrass cultivar development. The objective of this research was to identify morphological traits in parental plants that are predictive of biomass yield in progeny swards. Results of this research demonstrate the challenges of selecting for increased biomass yield in switchgrass within spacedplant nurseries. Limited predictive ability was observed using individual and combinations of plant morphological traits. Comparisons of models with varying subsets of traits revealed common traits among the best predictive models including plant height, single-plant dry biomass, and second leaf width. Predictions of single- plant biomass, using the same set of morphological traits, revealed a large effect for tillering related traits. The observation that different traits affect biomass yield differently in the two planting types may indicate an effect of plant competition on the relationship of these traits with biomass yield. While these traits can help guide selections for a preferred plant ideotype, additional efforts to improve selection schemes for increasing biomass yield will be necessary for sustained genetic gain in switchgrass.
Article
Long-term yield studies in perennial crops like miscanthus are important to determine mean annual energy yield and the farmer’s economy. In two Danish field trials, annual yield of two miscanthus genotypes was followed over a 20-year period. The trials were established in 1993 on loamy sand in Foulum and on coarse sand in Jyndevad. Effects of genotype, row distance and fertilization were investigated. In both trials, yield development over time was characterized by an increase during the first years, optimum yields after 7–8 years and a decrease to a lower level which remained relatively constant from year 11 to 20. Spring harvest reduced the yield by 34–42 % compared to autumn harvest. In Foulum annual fertilization with 75 kg ha−1 N increased the yield of the genotype Goliath (Miscanthus sinensis) by 26 %. Additional N fertilization only increased the yield of Goliath little, and the genotype Giganteus (Miscanthus × giganteus) did not respond to fertilization at all. The highest mean yield in Foulum for the period 1997–2012 was obtained with the shortest row distance (∼18,000 rather than ∼12,000 plants ha−1) and harvested in late autumn, namely 13.1 and 12.0 Mg ha−1 DM annually for Giganteus and Goliath, respectively. In Jyndevad, where only Goliath was studied, the highest yield during 1995–2001 was obtained by short row distance, autumn harvest and annual fertilization with 75 kg ha−1 N, with yield increasing up to 116 % in response to fertilization. A mean yield of 14.4 Mg ha−1 DM was achieved over the period 1995–2012.
Article
To develop the perennial grass Miscanthus x giganteus as a highly productive crop for biomass production, new varieties need to be bred, and more knowledge about its growth behaviour has to be collected. Our aim was to identify an efficient function for assessing and comparing emergence date and canopy height growth (rate, duration, and final maximal height) of 21 clones of Miscanthus in Northern France. Flow cytometry made it possible to classify the clones into three clusters corresponding to 2x, 3x, and 4x ploidy levels. Three functions, 3- and 4-parameter logistic functions and Gompertz function, were tested to best describe the dynamics of crop emergence and of plant growth. The best functions were used to estimate emergence dynamics (Gompertz function), and growth dynamics (4-parameter logistic). All these traits showed a significant year, clone, and corresponding interaction effects (but not for harvest date). Species and ploidy level explained the clone and clone × year interaction effects. M. x giganteus and M. floridulus clones were among the latest to emerge, and the tallest. M. sinensis clones showed the lowest height and growth rates. Higher final canopy height was correlated to late emergence and high growth rate. These findings could help early selection of interesting clones within M. sinensis populations, in order to breed new inter-species hybrids of giganteus type.