ARTICLE IN PRESS

Available at www.sciencedirect.com

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4

0961-9534/$ - see frodoi:10.1016/j.biomb

�Corresponding autE-mail addresses

(E. Bonari).

http://www.elsevier.com/locate/biombioe

Bark content estimation in poplar (Populus deltoides L.)short-rotation coppice in Central Italy

Werther Guidia,�, Emiliano Piccionia, Marco Ginannib, Enrico Bonaria

aLand Lab, Scuola Superiore Sant’Anna, via S. Cecilia 3, 56127 Pisa, ItalybCentro Interdipartimentale Enrico Avanzi, Via Vecchia di Marina 6, 56010 San Piero a Grado, Pisa, Italy

a r t i c l e i n f o

Article history:

Received 8 December 2005

Received in revised form

23 November 2007

Accepted 26 November 2007

Available online 4 January 2008

Keywords:

Energy crops

Populus

Short-rotation coppice

Wood fuels

Prediction equations

Bark proportion

nt matter & 2007 Elsevieioe.2007.11.012

hor. Tel.: +39 50 883521; fa: guidiw@sssup.it (W. Gu

a b s t r a c t

Differences in bark and wood content in woody biomass directly affect its quality and

economic value as an energy source. In order to estimate the quality of biomass before

harvesting, an allometric regression of bark percentage of total aboveground biomass and

DHB (diameter at 1.30 m height) was developed in a 2-year poplar short-rotation coppice

system in Central Italy. Firstly, a relationship between mean diameter and bark content

percentage was established in 1 cm-wide sections belonging to all diametric classes. The

model of best fit for these stem cylindrical sections was an equation y ¼ ax�b. Following

this, sample stems (of which we measured DHB) were collected and divided into sections

belonging to a diameter class. Fresh and dry matter were determined for each class. Using

the first equation, bark content was calculated separately for all classes. Thereafter, a

second equation between bark content in the whole stem and DHB was developed. The best

fitting equation for the whole stem was y ¼ cx�d. Bark content in the whole stem ranged

from 33.9–31.4% in large-sized DHB stems to 15.1–12.5% in smallest stems, depending on

their moisture content. Bark content decreased rapidly in the small diametric classes until

DHB reached 4 cm. Thereafter, the ratio of reduction of bark percentage dropped.

& 2007 Elsevier Ltd. All rights reserved.

1. Introduction

Many experiments have been undertaken on the main

forestry species regarding aboveground biomass yield, both

in temperate environments [1–7] and in the tropics [8,9]. Most

of those experiments are related to wood production, and

only a small number of them estimate biomass of sub-

products like cork, charcoal, etc. [10,11]. The quite small

number of studies concerning short-rotation coppice (SRC)

crops has focused mainly on biomass production or on

ecological aspects of trees [12–15].

Interest in the qualitative characteristics of biomass feed-

stock is increasing as use of specialized crops as alternative

energy sources is expanding in many countries. Among the

r Ltd. All rights reserved.

x: +39 50 883512.idi), e.piccioni@sssup.it (E

parameters that are used to classify biomass for energy

purposes, humidity, density, heating value and ash content

are the most common [16,17]. Related to this, it is now quite

well accepted that one of the main characteristics that

differentiates woody and herbaceous biomass is the quantity

and quality of ash content produced through combustion

[18–23]. Woody biomass contains a very low amount of ash

compared with herbaceous biomass and, furthermore, sig-

nificant differences have been registered in the ash from a

quality point of view. On average, compared with woody

biomass, herbaceous ashes contain a very high level of silicon

oxide (SiO2) and alkali metals (K, Ca, Na, Mg). These

characteristics may negatively affect the use of biomass as

an energy source in common boilers. Such elements play a

. Piccioni), ginanni@tiscali.it (M. Ginanni), bonari@sssup.it

ARTICLE IN PRESS

Table 1 – Main soil characteristics

Soil parameter Value

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4 519

key role in determining the melting properties of a biomass.

High concentrations of these elements can damage boilers

through corrosion or deposits on the burner gate. Further-

more, high quantities of chlorinated compounds that are

usually formed when firing herbaceous biomass may repre-

sent a potential problem for the environment [24]. Although

some experiments have shown that the heating value of bark

is quite similar to that of wood [25], in woody SRC biomass,

bark content of the whole harvested biomass is, nevertheless,

considered to be a negative characteristic. Since most

minerals taken up by trees are accumulated within the bark,

ash content in the whole tree is largely related to bark

amount [26,27]. In addition, high bark content is considered a

problem for direct combustion since high moisture content in

this tissue may decrease its heating value [28]. It is well

known that, although the extent of bark varies depending on

the species and clone [27], as the stem diameter of a tree

increases the total bark content also increases but relative

amount of bark decreases [29]. In addition, in some species

the ash content in the bark increases with age, since age and

diameter dimensions are strictly related to each other [30].

Since one of the main characteristics of a SRC plantation is

represented by diameter distribution [31], a simple regression

that uses this as an independent variable to estimate bark

(or wood) percentages of a biomass is both accurate and

useful when we want to predict qualitative aspects of

biomass before harvesting.

The aim of this work was to elaborate an allometric relation

that may predict poplar SRC biomass quality before harvest-

ing using DHB of the stems as an independent variable.

Clay (%) 8.43

Silt (%) 51.50

Sand (%) 40.07

pH 8.2

Organic matter 2.29

Total (N g kg�1) 1.73

Total P (Olsen) (ppm) 10.10

K (mg kg�1) 138.20

CEC (meq 100 g�1) 24.42

CaCO3 (%) 1.77

2. Materials and methods

2.1. Description of the experimental site

The experiment was carried out in San Piero a Grado (Pisa) in

the Arno valley (431400 long. N, 101210 lat. E, 5 m a.s.l.). The

region has a Mediterranean climate, with rainfall mainly

0

10

20

30

40

50

60

J M M J

Rain

fall (

mm

)

Rainfall T min T max

F A J

Fig. 1 – Average climatic condition a

concentrated in the autumn and spring (mean 900 mm yr�1).

Mean minimum temperature is 9.3 1C, and mean maximum

temperature is 20.1 1C. Temperature and rainfall patterns for

the site are shown in Fig. 1. The morphology of the region is

flat and main soil characteristics are shown in Table 1. An SRC

plantation was established on the experimental site in winter

2000. Unrooted 20 cm long 1-year old cuttings of Populus

deltoides L. (clone Lux) were planted in five square fields of ca.

50�50 m2. Initially, plant density in each plot was

10,000 p ha�1 with a distance of 2 m between rows and 0.5 m

within rows. Chemical weed control was performed before

planting by applying ‘‘Panter’’ (pendimetalin+linuron) 5 l ha�1.

In addition, during the first year and in the following growing

seasons, weeds were controlled mechanically by hoeing in

order to minimize competition for light, nutrients and water.

Before planting, 48 kg ha�1 N, 144 kg ha�1 P2O5 and 144 kg ha�1

K2O were incorporated into the soil. After each harvesting

operation, 126 kg ha�1 N was applied in order to stimulate

growth of new shoots. At the end of the second growing

season (2002) all the plants were harvested. Resprouting

shoots were then grown for a further 2 years, and during the

winter 2004 stems were collected. Results of this latter

harvest are presented in this paper. Characteristics of the

experimental SRC plantation are shown in Table 2.

S N

0

5

10

15

20

25

30

35

Tem

pera

ture

(°C

)

A O D

t experimental site (1986–2003).

ARTICLE IN PRESS

Table 2 – Main characteristics of 2-year-old poplar SRC during the experiment year

Species Age(years)

Density(plants ha�1)

Inter row(m)

Mean DHB(cm)

Mean height(m)

Mean stems perstool (n)

Populus deltoides L.

clone Lux

Stems 2

Roots 4

10.000 2 3.9 6 3

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4520

2.2. Plant material and laboratory procedures

2.2.1. Bark percentages in cross sectionsFrom each plot, nine stools within the central row were

chosen in order to avoid stems with a non-representative

shape. Two stems per stool were collected to represent the

whole range of diameters (from 1 to 9 cm) found after a

previous sampling performed at the beginning of the experi-

ment. From each stem, a cylindrical woody cross section 5 cm

long was collected. In total, 90 sections were obtained. The

mid-length (H/2) diameter of each cylinder was measured

(above the bark) in two perpendicular directions with a digital

calliper Mitutoyo 500-181 and the mean diameter was

determined. All the cross sections were arranged into

diametric classes 1 cm wide. Since nine was the largest DHB

class found in the experimental plantation, nine classes

ranging from 1 to 9 cm were established. The numeric value of

each class represented the central value (i.e. class 1 included

all sections whose diameter ranged from 0.5 to 1.5 cm). In

total, 10 cylindrical sample sections per class were collected

and measured. The fresh weight (FWcyl) of each section was

determined. Subsequently, bark was removed from the wood

using a peeler knife and weighed separately. Both wood and

bark samples were oven dried at 65 1C until constant weight

and then the dry weight (DWcyl) was determined. Bark

content in each section was calculated as percentage of the

total weight of the cylinder for fresh and dry weight. Data

were arranged in nine classes. A non-linear regression model

was used to study the relationship between mean diameter of

the class (Dcyl) and bark percentage (B%cyl).

2.2.2. Bark percentages in the stemOne stem was harvested from each of nine stools within the

central row of each field representative of the whole DHB

distribution in the stand. In total, 45 stems were collected.

Mean DHB and fresh weight were determined for each sample

stem. Thereafter, using the digital calliper from bottom to top,

each stem and its branches were marked and then divided

into segments belonging to the same diametric class. Stems

and branches were cut using either a handsaw or pruning

scissors depending on the size of the sample. Fresh weight

(FWstem) was determined separately for each class. All

samples were then chopped and dried at 65 1C until constant

weight and the oven dry weight (DWstem) was determined.

Distribution in weight of the nine classes for different stem

sizes was determined. Combining these data with the results

obtained from the cylindrical sections, a new non-linear

regression between mean DHB and bark percentage of the

whole stem (B%stem), respectively for the fresh and dry

weight, was established respectively for fresh and dry matter.

2.3. Statistical analysis

Both ANOVA and non-linear regressions were performed

using STATGRAPHIC Plus 5.0 software (Manugistics, Rockville,

MD, USA). One-way ANOVA was used to test whether or not

there were differences between mean bark percentages in the

samples. For both cylindrical sections and stems samples, the

test was firstly used to assess differences in bark percentages

amongst the diametric classes. Subsequently, differences in

fresh and dry bark content within each diametric class were

compared using the same procedure. Least significant differ-

ences test (LSD) at po0.05 was used to determine significant

differences between mean bark content within samples.

3. Results and discussion

3.1. Bark percentage in cylindrical cross sections

On the basis of 90 cylindrical cross sections, a non-linear

regression between mean diameter of any cylindrical section

(Dcyl) and bark percentage (B%cyl) expressed as weight was

established, respectively, for fresh (moisture ¼ 54.4%) and dry

matter:

B%cyl ¼ a�Dbcyl, (1)

where a and b are estimated coefficients whose values are

shown in Table 3.

Bark percentages within the cylindrical sections grouped

per 1 cm wide diameter classes are shown in Table 4.

According to recent experiments on willow and poplar SRC

conducted in Sweden and the USA [25,27], B%cyl decreases

rapidly with increasing Dcyl. Once Dcyl reaches 6 cm, bark

percentage values stabilize around 6% and 7%, respectively, in

the fresh and dry matter. Due to a less homogenous material

used (i.e. small twigs cross sections), standard deviation tends

to decrease as diameter of the sections increases. The most

significant differences occur within the smaller diametric

classes. Classes ranging from 1 to 6 cm in the fresh and from 1

to 5 cm in the dry matter are all different from each other.

This shows that the change in bark content amongst smaller

classes is quite well defined in smaller woody sections. After

class 6 and 5 cm for both fresh and dry conditions differences

amongst bark content within classes decrease. Therefore,

significant differences occur only amongst class 9 cm, which

is different from 6 (fresh) and 5 (dry).

LSD test results concerning B%cyl of each diameter class for

both fresh and dry matter are shown in Fig. 2. Due to a high

water content inside the tissue, significant differences

between fresh and dry bark percentage occur within the first

ARTICLE IN PRESS

15

y = 0.0914737 x2.30334

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4 521

class as well as class 7 up to 9 cm (Fig. 2). No differences occur

amongst central classes (2–6 cm).

0 4 8 10

0

3

6

9

12

Stem

Dry

Bio

mas

s (k

g)

R2 = 0.98

2 6

3.2. Stem biomass grouped into diameter classes

Regarding the whole stem analysis, a first regression between

fresh biomass and DHB was established in order to test

variation in the biomass with increasing diameter. Grouping

collected data, a relationship between dry biomass and DHB

was obtained (Fig. 3). Biomass increases with diameter

dimension and it follows a power law. The shape of the curve

Table 3 – Estimated parameters for allometric relation-ship between mean diameter of the cylindrical sectionsand bark percentage

Biomass a b Adjusted R2

Fresh 39.3619 �0.8943 0.94

Dry 39.7170 �0.8386 0.94

Table 4 – Mean fresh and dry bark percentage(7SD; n ¼ 10) for the nine diameter classes of cylindricalsections

Diametric class (cm) Fresh Dry

1 31.1 (71.15)a 35.8 (74.06)a

2 22.2 (72.49)b 22.7 (71.65)b

3 17.0 (71.68)c 16.8 (71.73)c

4 11.9 (71.93)d 11.8 (72.40)d

5 9.2 (71.15)e 8.9 (71.29)e

6 7.1 (71.10)f 7.7 (71.14)ef

7 6.6 (70.60)fg 7.6 (70.56)ef

8 6.0 (70.46)fg 7.3 (70.54)ef

9 5.5 (70.55)g 7.1 (70.55)f

Note that mean values with the same letter are not significantly

different at po0.05 (LSD tests).

0

5

10

15

20

25

30

35

40

1 3 4 7 9

Bar

k %%

a

b

a a

aa

aa

aa a

aba aa b b

Diametric class (cm)2 5 6 8

FreshDry

Fig. 2 – Mean bark percentage in different diameter class

sections. Mean values with the same letter are not

significantly different at po0.05 (LSD tests).

DHB (cm)

Fig. 3 – Allometric power equation between stem DHB and

stem dry mass for 2-year-old Populus deltoides L. clone Lux.

is similar to that obtained in other experiments for poplar

SRC [32].

Fresh and dry biomass contents of each stem of DHB known

(separated into segment classes) were determined in samples

collected in the stand and are represented in Table 5. Since in

a poplar SRC plantation thinner plants are usually those with

small shoots and branches, most of their biomass is

concentrated in the small diameter classes. Obviously, as

DHB increases, the biomass of large stems is mainly located

into large classes. While DHB reaches the highest values

observed in the stand, small classes (i.e. 1st and 2nd) assume

a significant importance in the total weight of the stem. This

is mainly due to the fact that large-sized DHB stems are also

the highest and their crown is developing above the stand,

producing a large amount of fine lateral branches. This

behaviour has also been observed in other studies [33–35].

3.3. Bark percentage in the whole stem

By applying Eq. (1) for fresh and dry conditions to the results

shown in Table 5, a new relationship was established between

bark percentage and DHB in the whole stem (Tables 6 and 7).

The tables show fresh and dry bark content (expressed as

weight) for different diametric classes.

Using rough data (ungrouped), the best regression found

was a model expressed by Eq. (2) for both fresh and dry

conditions:

B%stem ¼ c�DHBd, (2)

where c and d are estimated coefficients whose values are

shown in Table 8.

As shown in Tables 6 and 7, as DHB increases total bark

amount of each stem also increases but relative amount of

bark (i.e. compared to the whole stem biomass) decreases.

This is mainly due to the fact that the biomass of large stems

is formed by a high amount of big diametric segments that

are constituted mostly by wood and by a low amount of bark.

In contrast, high bark content is found in the smallest classes

as registered in other experiments conducted on willow and

poplar SRC [25,27]. B%stem within the whole stems grouped

per 1 cm wide DHB classes are shown in Table 9. B%stem

decreases rapidly until DHB is 4 cm and then shows a slight

decrement until it reaches a relatively stable value. This result

ARTICLE IN PRESS

Table 5 – Fresh and dry matter for different diameter classes

Stem DHB (cm) Frequency (n) Diametric class of stem segments (kg)

1 2 3 4 5 6 7 8 9 Total

Fresh weight

1 3 0.10 0.09 – – – – – – – 0.19

2 11 0.14 0.38 0.10 – – – – – – 0.62

3 5 0.29 0.66 1.05 0.18 – – – – – 2.18

4 4 0.64 0.46 1.13 1.48 1.49 0.12 – – – 5.32

5 7 1.21 0.37 1.03 1.87 2.19 0.84 – – – 7.51

6 2 1.93 0.44 0.67 1.49 2.16 2.25 1.75 – – 10.69

7 7 1.94 1.08 0.66 1.44 2.35 3.05 2.48 1.32 0.13 14.45

8 4 2.26 0.87 0.57 1.43 1.96 3.15 2.79 3.50 1.93 18.46

9 2 3.54 0.74 0.68 1.12 2.35 2.45 3.61 4.18 5.27 23.94

Dry weight

1 3 0.05 0.05 – – – – – – – 0.10

2 11 0.08 0.20 0.05 – – – – – – 0.33

3 5 0.16 0.35 0.57 0.10 – – – – – 1.16

4 4 0.34 0.24 0.61 0.79 0.82 0.07 – – – 2.88

5 7 0.65 0.19 0.56 1.00 1.21 0.48 – – – 4.09

6 2 1.04 0.23 0.36 0.80 1.19 1.29 0.97 – – 5.88

7 7 1.04 0.56 0.36 0.77 1.30 1.75 1.38 0.74 0.07 7.97

8 4 1.22 0.46 0.31 0.77 1.08 1.81 1.55 1.97 1.08 10.23

9 2 1.90 0.39 0.37 0.60 1.30 1.41 2.00 2.35 2.95 13.27

Table 6 – Fresh bark content within the segments for different DHB classes of stem

Stem DHB(cm)

Frequency(n)

Diametric class of stem segments (kg) Total bark(kg)

Total biomass(kg)

1 2 3 4 5 6 7 8 9

1 3 0.04 0.02 – – – – – – – 0.06 0.20

2 11 0.05 0.08 0.01 – – – – – – 0.15 0.61

3 5 0.11 0.14 0.15 0.02 – – – – – 0.43 2.18

4 4 0.25 0.10 0.17 0.16 0.14 0.01 – – – 0.82 5.31

5 7 0.48 0.08 0.15 0.21 0.20 0.07 – – – 1.19 7.51

6 2 0.76 0.09 0.10 0.16 0.20 0.18 0.12 – – 1.61 10.68

7 7 0.76 0.23 0.10 0.16 0.22 0.24 0.17 0.08 0.01 1.98 14.45

8 4 0.89 0.18 0.08 0.16 0.18 0.25 0.19 0.21 0.11 2.27 18.45

9 2 1.39 0.16 0.10 0.13 0.22 0.19 0.25 0.26 0.29 2.99 23.94

Table 7 – Dry bark content within the segments for different DHB classes of stem

Stem DHB(cm)

Frequency(n)

Diametric class of stem segments (kg) Total bark(kg)

Totalbiomass (kg)

1 2 3 4 5 6 7 8 9

1 3 0.02 0.01 – – – – – – – 0.03 0.10

2 11 0.03 0.04 0.01 – – – – – – 0.08 0.33

3 5 0.06 0.08 0.09 0.01 – – – – – 0.24 1.18

4 4 0.13 0.05 0.10 0.10 0.08 0.01 – – – 0.47 2.87

5 7 0.23 0.04 0.09 0.12 0.12 0.04 – – – 0.65 4.09

6 2 0.37 0.05 0.06 0.10 0.12 0.11 0.08 – – 0.89 5.88

7 7 0.37 0.12 0.06 0.10 0.13 0.15 0.11 0.05 0.005 1.10 7.97

8 4 0.43 0.10 0.05 0.10 0.11 0.16 0.12 0.14 0.07 1.27 10.24

9 2 0.68 0.09 0.06 0.07 0.13 0.12 0.16 0.16 0.19 1.66 13.27

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4522

ARTICLE IN PRESS

Table 8 – Estimated parameters for allometric relation-ship between DHB of the stem and bark percentage

Humidity c d Adjusted R2

Fresh 35.4587 �0.511018 0.97

Dry 35.6402 �0.515734 0.96

Table 9 – Mean fresh and dry bark percentage (7SD) forthe whole 2-year-old Populus deltoides L. (clone Lux)stems

Stem DHB (cm) Fresh Dry

1 31.4 (73.87)a 33.9 (75.05)a

2 25.8 (72.85)b 27.8 (73.85)b

3 20.8 (71.54)c 21.4 (71.20)c

4 16.1 (72.05)d 17.5 (71.21)d

5 15.3 (71.04)d 16.8 (70.65)d

6 15.0 (70.55)d 16.5 (70.22)d

7 13.6 (71.46)d 15.6 (70.63)d

8 12.5 (70.75)d 15.2 (70.22)d

9 12.5 (70.44)d 15.1 (70.11)d

Note that mean values with the same letter are not significantly

different at po0.05 (LSD tests).

0

5

10

15

20

25

30

35

40

1 3 8

Bar

k %

aa

a

a

a

a

aa

ab a

a aa

ab b b

2 4 5 6 7 9

DHB class (cm)

FreshDry

Fig. 4 – Mean bark percentage in different DHB classes. Mean

values with the same letter are not significantly different at

po0.05 (LSD tests).

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4 523

validates the tendency observed in willow SRC stands in

Sweden in which bark proportion decreased rapidly with age

and dimensions until a relatively constant value in the aged

and large-sized samples shoots [25]. Obviously, compared

with the above-mentioned experiment, there are differences

in B%stem values due to a different stem architecture of the

two species. Particularly, compared with willow, poplar shows

higher B%stem in smaller classes. Fast reduction in B%stem in

poplar is registered for DHB classes ranging from 1 to 4 cm.

However as DHB increases, B%stem in poplar reaches lower

values than in willow. Significant differences (po0.05) were

registered in B%stem amongst the first four diametric classes

(1–4) for fresh and dry matter. No differences were registered

for the following five classes (4–9). In detail, B%stem ranges

from a maximum of 31.4–33.9% to a minimum of 12.5–15.1%,

respectively, for fresh and dry conditions. Most differences

between fresh and dry matter inside each DHB class occur in

larger classes as shown in Fig. 4.

4. Conclusions

The results of this experiment constitute a useful and easy

tool that can be used in order to predict biomass quality of a

poplar SRC plantation before harvesting. Obviously the

equation we developed can be used mainly in the same

conditions in which it has been created (i.e. species, clone,

environmental conditions). Nevertheless, once DHB distribu-

tion of the stems within the stand is known and biomass

production has properly been estimated, it is possible to

predict the amount of biomass that is represented by the

bark. In addition, the results show the same trend observed in

willow SRC stands in which bark proportion of the harvest-

able biomass is directly affected by DHB size. Furthermore,

the existence of substantial differences in bark percentage for

diverse DHB stems indicate the possibility to manage poplar

SRC plantation in order to obtain a better quality of biomass.

DHBs lower than 4 cm wide may be considered a threshold

under which it is not convenient, from a qualitative point of

view, to descend. Therefore, large DHB sized stems are

preferred in order to match the requirements of high quality

of feedstock biomass for energy purposes.

R E F E R E N C E S

[1] Ter-Mikaelian MT, Korzukhin MD. Biomass equations forsixty-five North American tree species. Forest Ecology andManagement 1997;97:1–24.

[2] Reed D, Tome M. Total aboveground biomass and net drymatter accumulation by plant component in young Eucalyp-tus globulus in response to irrigation. Forest Ecology andManagement 1998;103:21–32.

[3] Vann DR, Palmiotto PA, Strimbeck GR. Allometric equationfor two South American conifers: test of a non-destructivemethod. Forest Ecology and Management 1998;106:55–71.

[4] Ponette Q, Ranger J, Ottorini JM, Ulrich E. Abovegroundbiomass and nutrient content of five Douglas-fir stands inFrance. Forest Ecology and Management 2001;142:109–27.

[5] Son Y, Hwang JW, Kim ZS, Lee WK, Kim JS. Allometry andbiomass of Korean pine (Pinus koraiensis) in central Korea.Bioresource Technology 2001;78:251–5.

[6] Porte A, Trichet P, Didier B, Loustau D. Allometric relation-ships for branch and tree woody biomass of maritime pine(P. pinaster Ait.). Forest Ecology and Management 2002;158:71–83.

[7] Williams CJ, Le Page BA, Vann DR, Tange T, Ikeda H, Ando M.Structure, allometry and biomass of plantation Metasequoiaglyptostroboides in Japan. Forest Ecology and Management2003;180:287–301.

[8] Fuwape JA, Onyekwelu JC, Adekunle VAJ. Biomass equationsand estimation for Gmelina arborea and Nauclea diderrichiistands in Akure forest reserve. Biomass and Bioenergy2001;21:401–5.

[9] Onyekwelu JC. Above-ground biomass production and bio-mass equations for even-aged Gmelina arborea (ROXB)

ARTICLE IN PRESS

B I O M A S S A N D B I O E N E R G Y 3 2 ( 2 0 0 8 ) 5 1 8 – 5 2 4524

plantations in south-western Nigeria. Biomass and Bioenergy2004;26:39–46.

[10] Fonseca T, Parresol BR. A new model for cork weightestimation in Northern Portugal with methodology forconstruction of confidence intervals. Forest Ecology andManagement 2001;152:131–9.

[11] Okello BO, O’Connor TG, Young TP. Growth, biomass esti-mates and charcoal production of Acacia drepanolobium inLaikipia, Kenya. Forest Ecology and Management2001;142:143–53.

[12] Clendenen GW. Use of harmonized equations to estimateabove-ground woody biomass for two hybrid poplar clones inthe pacific northwest. Biomass and Bioenergy 1996;11:475–82.

[13] Pontailler J, Ceulemans R, Guittet J, Mau F. Linear and nonlinear functions of volume index to estimate woody biomassin high density young poplar stands. Annales des SciencesForestieres 1997;54:335–45.

[14] Ballard B, Stehman S, Briggs RD, Volk TA, Abrahamson LP,White EH. Aboveground biomass equation development forfive salix clones and one populus clone. Technical report of‘‘Biomass Power for Rural Development’’ project 1998.

[15] Verwijst T, Bjorn T. Biomass estimation procedures in shortrotation forestry. Forest Ecology and Management1999;121:137–46.

[16] Kenney WA, Sennerby-Forsse L, Layton P. A review ofbiomass quality research relevant to the use of poplar andwillow for energy conversion. Biomass 1990;21:163–88.

[17] CTI. Biocombustibili specifiche e classificazioni 2003/www.cti.itS.

[18] Olander B, Steenari B. Characterization of ashes from woodand strow. Biomass and Bioenergy 1995;8:105–15.

[19] Sander B. Properties of Danish biofuels and the requirementsfor power production. Biomass and Bioenergy 1997;12:177–83.

[20] Lehtikangas P. Quality properties of pelletised sawdust,logging residues and bark. Biomass and Bioenergy2000;20:351–60.

[21] Obernberger I, Gerold T. Physical characterization andchemical composition of densified biomass fuels withregard to their combustions behavior. Biomass and Bioenergy2004;27:653–69.

[22] Permchart W, Kouprianov V. Emission performances andcombustion efficiency of a conical fluidized-bed combustorfiring various biomass fuels. Bioresource Technology2004;92:83–91.

[23] Aho M, Ferrer E. Importance of coal ash composition inprotecting the boiler against chlorine deposition duringcombustion of chlorine-rich biomass. Fuel 2005;84:201–12.

[24] Miles RT, Baxter LL. Boiler deposit from firing biomass fuels.Biomass and Bioenergy 1996;10:125–38.

[25] Adler A, Verwijst T, Aronsson P. Estimation and relevance ofbark proportion in a willow stand. Biomass and Bioenergy2005;29:102–13.

[26] Steenari B, Lindqvist O. Stabilization of biofuel ashes forrecycling to forest soil. Biomass and Bioenergy 1997;13:39–50.

[27] Tharakan PJ, Volk TA, Abrahamson LP, White EH. Energyfeedstock characteristics of willow and hybrid poplar clonesat harvest age. Biomass and Bioenergy 2003;25:571–80.

[28] Goel VL, Behl HM. Fuelwood quality of promising tree speciesfor alkaline soils sites in relation to tree age. Biomass andBioenergy 1996;10:57–61.

[29] La Marca O. Elementi di dendrometria. Bologna: PatronEditore; 1999.

[30] Klasnja B, Kopitovic S, Orlovic S. Wood and bark of somepoplar willow clones as fuelwood. Biomass and Bioenergy2002;23:427–32.

[31] Laureysens I, Deraedt W, Cuelemans R. Population dynamicsin a 6 year old coppice culture of popular. I. Clonaldifferences in stool mortality, shoot dynamics and shootdiameter distribution in relation to biomass production.Biomass and Bioenergy 2003;24:81–95.

[32] Pellis A, Laureysens I, Cuelemans R. Growth and productionof a short rotation coppice culture of poplar I. Clonaldifferences in leaf characteristics in relation to biomassproduction. Biomass and Bioenergy 2004;27:9–19.

[33] Kimmins JP. Forest ecology. New York: Macmillan PublishingCompany; 1987.

[34] Piussi P. Selvicoltura generale. Torino: UTET; 1994.[35] Paci M. Ecologia Forestale: elementi di conoscenza dei

sistemi forestali. Bologna: Edagricole; 2004.