Variability in the properties of triticale and rye biomass due to different varieties and growing conditions

1. VARIABILITY IN THE PROPERTIES OF TRITICALE AND RYE BIOMASS DUE TO THE DIFFERENT
VARIETIES AND GROWING CONDITIONS
Ruth Barro*, Pilar Ciria, Emiliano Maletta, Miguel Fernández, Javier Pérez, Jaime Losada, and Juan E. Carrasco
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CEDER -CIEMAT)
Autovía de Navarra A15, salida 56, 42290 Lubia (Soria), Spain
*Corresponding author: ruth.barro@ciemat.es, phone: +34 975281013, fax: +34 975281051
ABSTRACT: There is a large interest in Spain surrounding the maximum variability that can be obtained in the main
physico-chemical properties of biomass, when it is produced or used for energy purposes. Multiple sources could
cause that expected variability. Winter cereals might be considered as a potential biomass source for energy purposes,
particularly triticale and rye. On the one hand, a statistical study was carried out, and differences between varieties
cultivated in the same location and cereal development states were evaluated. On the other hand, different varieties of
cereals were cultivated in 11 different locations around the north and central part of the country under multiple
conditions. A Cochran´s test was run to check up on variances (variance of same location vs. variance of different
locations) and compare the variability originated by the genetics of cereals, and that caused by the different growing
conditions. Some parameters as carbon or heating values seem to be dependent on the variety cultivated, while the
variability associated to some others like ash, nitrogen, sulphur, and chlorine contents increases significantly by being
directly influenced by some other factors like the different growing and farming conditions.
Keywords: biomass, composition, characterization, grain, sampling, quality
1 INTRODUCTION their rusticity, tolerating adverse edafoclimatic conditions
(dryness, freezing, different soils, etc.). In addition, these
There is a large interest in Spain among biofuel two species, triticale and rye, were previously found to
producers, professionals, and final consumers, have better yield and quality demands than other grown
surrounding the maximum variability that can be cereals like wheat or oat for energy use [12,13].
obtained in the main physico-chemical properties of This paper deals with the task of obtaining a
biomass, when it is produced or used for energy variability range that can be found in Spain for the main
purposes. A full discussion brought up not only about the properties of triticale and rye biomass, but it only
source of variability, but also the range of values that pretends to be a first approach to this problem.
could be found from a real point of view. In such a long Preliminary results are presented in the frame of a much
process since biomass is grown until it is converted in a more ambitious comprehensive study that it is performing
solid biofuel and finally transformed into energy, many in Spain, supported by the national project for energy
steps are involved, and thus multiple sources could cause crops development: “PSE – On crops” Project, and where
that expected variability. For example, main sources other additional variability sources such as the collection
involving the first step of the process are e.g. the genetics process (which is a potential source of pollution with
of the plant (species, variety, clon...), the growing soil) are going to be added as this project gets developed.
conditions (type of soil, fertilizers...) or the collecting The aim of this study is to estimate the variability
step, transportation and storage, which could easily ranges in the properties of triticale and rye biomass and
pollute biomass by adding particles from soil. how it is affected by the different varieties and growing
With regard to the utilization of biomass as an energy conditions.
source, the investigation of characteristics of biomass
fuels is beneficial for biomass fuels to find suitable
energy conversion technologies and for various energy 2 MATERIALS AND METHODS
conversion processes to utilize favorable biomass
feedstock [1]. Researches in several countries have 2.1 Biomass
carried out extensive studies to determine the quality In this work, two different cereal species were
properties of their own available biomass resources [1-6]. considered: triticale (Triticosecale) and rye (Secale
In addition, several comprehensive reviews have been cereale). Four triticale varieties (Bienvenue, Trimour,
published regarding physical characterization and Trujillo and Collegial) and rye varieties (Askari and
chemical composition of different biomass fuels [7-11]. Petkus) were evaluated.
Spain is a country with a marked tradition and
expertise on cereal crops, which are cultivated in dry land 2.2 Locations and agronomic practices
for alimentary purposes, but suffering as a consequence This study was performed during 2009-2010. Plots
problems derived from a surplus of production. 81 % of were sown in November 2009 and sampling of plants was
the total existing growing surface is non-irrigated land, carried out between May and July 2010.
and around 37 % is dedicated to cereal grain farming. On the one hand, the four above-mentioned triticale
There is a conspicuous lack of knowledge with regard to varieties and the two rye varieties were cultivated in 6
the varibiality of physico-chemical properties of cereal small plots of the same location (see Fig. 1): Escobosa de
fuels in Spain, which is very important for their use as Almazan (EDA), a village in the province of Soria, in the
energy sources. Winter cereals might be considered as a region of Castilla y León (central-northern Spain),
potential biomass source for energy purposes, particularly characterizaed by a continental mediterranean climate
triticale (Triticosecale) and rye (Secale cereale), due to

2. with cold winters. EDA can be located in the Spanish
map of Fig. 2.
Different triticale varieties were sown in plots
between 2700 and 3000 m2, while Petkus and Askari ryes
were sown in 2500 and 900 m2, respectively.
Biomass grown in this location was carefully
controlled by our organization. It was cultivated strictly
applying the same farming techniques and sampled
manually to avoid biomass contamination. Therefore,
hypothetical differences between samples of the same
species should be attributed to the inherent variability of
each variety, and so to the genetics of plants.
Key: CDR = Cabreros del Río, Fu = Fuentesaúco, PDN = Palencia de
Negrilla, Za = Valladolid, SL = San Llorente, Ce = Cerratón de Juarros,
Go = Golmayo, EDA = Escobosa de Almazán, Al = Aldealafuente, Ga =
Galar, VDO = Vilobi D´Onyar, LTE = La Tallada D´Empordà
Figure 2: Sampling locations
Table I: Studied varieties per location
Species Variety Location Province
Cabreros del Río León
Galar Navarra
Vilobi D´Onyar Girona
La Tallada D´Empordà Girona
Trujillo Fuentesaúco Zamora
Valladolid Valladolid
San Llorente Valladolid
Cerratón de Juarros Burgos
Palencia de Negrilla Salamanca
Triticale Vilobi D´Onyar Girona
La Tallada D´Empordà Girona
Figure 1: Sown plots in Escobosa de Almazán Collegial Fuentesaúco Zamora
Valladolid Valladolid
Cerratón de Juarros Burgos
Before sowing, soil was prepared and a basal dose Vilobi D´Onyar Girona
(300 kg ha-1) of N-P2O5-K2O (8-24-8) fertilizer was La Tallada D´Empordà Girona
Trimour Fuentesaúco Zamora
applied. In November 2009, sowing was done by
Valladolid Valladolid
broadcasting the seed at the rate of 250, 120 and 60 kg Cerratón de Juarros Burgos
ha-1 for triticales, Petkus rye and Askari rye, respectively. Aldealafuente Soria
Four months after sowing (March 2010), calcium Golmayo Soria
Fuentesaúco Zamora
ammonium nitrate (27 wt %) was applied at a 270 kg ha-1 Rye Petkus Valladolid Valladolid
dose. A month later, two herbicides were applied: 2,4- Cerratón de Juarros Burgos
dichlorophenoxyacetic acid and tribenuron-methyl 75 % San Llorente Valladolid
(granulated) at 0.25 L ha-1 and 16 g ha-1 dosages, Palencia de Negrilla Salamanca
respectively.
On the other hand, three triticale varieties (Trujillo, Such huge differences among the sampling locations
Collegial and Trimour) and a rye variety (Petkus) were are desireable in order to get a wide range of samples that
cultivated in 11 locations randomly distributed in 8 could be considered representative of the different
Spanish provinces all around the north and central part of scenarios that could occur around a country marked by
the country (colored in Fig. 2). Exact locations are different climates, orography and agricultural practices.
marked in Fig. 2, as well. Table I shows all the varieties
cultivated in the different locations all around the 2.3 Sampling
country. Sampling was carried out between May and July
All the locations are characterized by a continental 2010. Whole plants (straw + grains) were manually
mediterranean climate with cold winters or by a sub- collected to prevent biomass pollution, e.g. soil particles,
humid continental mediterranean climate, except the and add an additional source of variability derived from
coastal mediterranean climate of VDO and LTE. the increase of the ash content.
Biomass was grown by 6 different companies, and so Six samples from the positions shown in Fig. 3 were
multiple conditions (fertilizers, herbicides, seed rate, collected per each plot located in Escobosa de Almazán.
soils, etc.) were applied, following their own local Each sample was obtained by collecting all the available
traditional agricultural methods. biomass in 1.66 lineal meters, which is equivalent to the
Surface of plots varied remarkably in a range from 8 biomass produced in 0.25 m2. Therefore, 24 samples of
to 10000 m2. Fertilizers (NPK and urea), herbicides, and triticale and 12 samples of rye where collected from this
seed-rates were applied at different doses.

3. location for their further characterization and to evaluate calorimetric bomb followed by lixiviation of the ashes
their associated variabilities. with an aqueous solution, a procedure derived from EN
In addition, half of the samples collected in EDA 15289.
were sampled when the grains were in a different To determine the gross calorific value, 1 g-sample
development state according to Zadoks growth scale: 7 was burnt in an IKA C-5000 calorimetric bomb following
and 8, which are corresponded to milk and dough the norm EN 14918. Gross calorific value at constant
development, respectively. In a milk development state, volume in dry basis (GCVv,0) and net calorific value at
the grain is squeezed, and a milky solution is apparent, constant pressure in dry basis (NCVp,0) were calculated.
while in the dough development state, the grain will still Biomass ashes (obtained at 550 ºC) were digested in
deform slightly, but no liquid is apparent. Samples with a microwave oven using HNO3, H2O2 and HF in a first
grains in a 7 development state were collected at the end step and H3BO3 in a second step, and inorganic elements
of June 2010, and those with their grains in the dough were analyzed accordingly to EN 15290 by inductively
state were collected 20 days later. coupled plasma with atomic emission spectroscopy (ICP-
AES) using a Thermo Jarrell Ash simultaneous
spectrometer.
The ash fusibility test was based on the shape
md
m =2m
2 md
m =2m
2 md
m =2m
2
d m d m d m changes detected during the heating of a cylindrical ash
pellet (ashes produced at 550 ºC) from room temperature
to 1400 ºC in an air atmosphere. Four characteristic
temperatures were measured by an optical heating
microscope (LEICA) following CEN/TS 15370-1: initial
deformation (IDT), sphere (ST), hemisphere (HT), and
a) md
m =2m
2
b) fluid (FT) temperatures.
Key: md = minimum distance
2.5 Statistical analysis
Figure 3: Sampling positions per plot in a) EDA, and b) To evaluate the effect of the different studied
rest of locations conditions on the biomass composition, different
statistical tests were carried out by using the software
In the rest of locations, samples were collected after Statgraphics Plus [14].
the reaping season between May and June 2010. All the First of all, a one-way analysis of variance (ANOVA)
cut biomass was left laid on the ground and a V sampling was performed on the species factor for the whole data
was performed (extracting samples from positions set obtained in Escobosa de Almazán (36 samples, i.e. 36
forming a V shape, see Fig. 3), paying special attention observations for each biomass property). Results obtained
not to introduce particles from soil (sand, stones, clays, from this test allow identifying statistical differences of
earth) into the bags and pollute biomass samples. each independent variable (each analyzed biomass
A minimum of 5 samples were extracted from each property) for the 2 different levels of the species factor
plot, and combined to form a 3-5 kg final sample, (triticale and rye). The F-test in the ANOVA table will
representative of the plot. 26 final samples were formed, test whether there are any significant differences amongst
meaning more than 130 subsamples were collected. Each the obtained means of each evaluated parameter for
final sample was considered representative of the overall triticale and rye. ANOVA table decomposes the variance
composition of the biomass grown in every plot. of each biomass property into two components: a
After sampling, collected samples were dried between-group component and a within-group
naturally or at 45 ºC, and sent to the laboratory to be component. If the P-value of the F-test is less than 0.05,
conveniently analyzed. All the analyzed aliquots were there is a statistically significant difference between the
taken out from each sample after following a cone and mean of the property from one level of the species factor
quartering sampling procedure. (triticale) to another (rye) at the 95.0 % confidence level.
Secondly, a two-way multifactor ANOVA was
2.4 Characterization methods performed on each species (first triticale and then rye) by
Samples were analyzed to determine volatile matter, separate. The considered factors for each species were the
ash, carbon, hydrogen, nitrogen, sulpur, and chlorine variety and the grain development state. Four varieties
contents, heating values, as well as major elements were studied (Trujillo, Collegial, Bienvenue and
constituting the ashes and their fusibility temperatures. Trimour) for triticale, and two (Petkus and Askari) for
Moisture was determined following the norm UNE-EN rye. Regarding the grain development state, as it was
14774-2. To determine ash content, a portion of a sample previously explained, it was studied at two growth stages:
was calcinated at 550 ºC following UNE-EN 14775. The milk (7) and dough (8) development. The 24 and 12
volatile matter (VM) was calculated as the loss of weight triticale and rye samples, respectively, cultivated in EDA
in a sample placed in a closed crucible at a temperature of were included in this study.
900 ºC for 7 minutes. Norm UNE-EN 15148 was Finally, a Cochran´s test was run to check up on
followed to carry out the analysis. variances in EDA and those obtained for different
Carbon, hydrogen, and nitrogen where directly locations. This test was run for each species by separate.
determined using a LECO elemental analyzer equipped It is a statistical test for homogeneity of variance. The
with an infrared cell to quantify the carbon and hydrogen hypothesis is that the variances across the two included
contents and with a thermal conductivity detector to levels (same location/farming conditions vs. different
quantify nitrogen by following EN 15104. locations/farming conditions) of each biomass property
Chlorine and sulphur determinations were carried out are equal. A reported significance level (P-value) greater
by ion chromatography after sample combustion in a than or equal to 0.05 means that hypotheris shall be

4. accepted; meaning that variances are not significantly 3.1 Variability in the same location
different (they are equal). Such approach allows As it was previously commented, four triticale
comparing the variability for each biomass property when varieties and two rye varieties were cultivated in the same
biomass is cultivated in the same location and conditions location (EDA), and collected when the grains were in a
with the variability when biomass is cultivated in different development state (7 and 8 in the cereal
different locations by using multiple agricultural development Zadoks scale).
techniques. Results were confirmed by applying also Obtained results from biomass characterization, the
other variance check tests such as Bartlett´s, Hartley´s composition of ashes obtained from biomass by
and Levene´s test. 50 samples were included in this calcination at 550 ºC, and ash fusibilities were found to
study; 30 cultivated in EDA and 20 in other locations. be in the typical range for these species [7,8,12,14], and
they are shown in Tables II-IV. The number of analyzed
samples (n) for each condition is also included in all
3 RESULTS AND DISCUSSION tables.
Table II: Composition and variability of the biomass cultivated in Escobosa de Almazán
Ash VM C H N S Cl O GCVv,0 NCVp,0
Species Variety
(wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (MJ kg-1) -1
(MJ kg )
Mean (n=6) 4.6 78.8 44.1 6.1 0.87 0.08 0.07 44.1 17.78 16.45
Range 1.7 1.6 2.0 0.2 0.54 0.05 0.08 1.9 0.94 0.95
Collegial Min. Val. 3.9 78.2 43.1 6.0 0.73 0.06 0.04 43.1 17.36 16.02
Max. Val. 5.6 79.8 45.1 6.2 1.27 0.11 0.12 45.1 18.30 16.97
Std. Dev. 0.7 0.6 0.8 0.06 0.2 0.02 0.03 0.7 0.38 0.38
Mean (n=6) 5.1 78.1 44.1 6.1 0.77 0.07 0.08 43.7 17.68 16.35
Range 1.1 2.6 2.1 0.1 0.40 0.03 0.06 2.5 0.91 0.89
Trujillo Min. Val. 4.6 77.1 43.2 6.1 0.56 0.06 0.04 42.4 17.32 15.99
Max. Val. 5.7 79.7 45.3 6.2 0.96 0.09 0.10 44.9 18.23 16.88
Std. Dev. 0.4 1.0 0.9 0.05 0.1 0.01 0.03 1.0 0.42 0.42
Triticale
Mean (n=6) 5.2 77.1 45.4 6.1 0.76 0.08 0.08 42.5 18.22 16.90
Range 1.1 3.7 1.2 0.2 0.33 0.07 0.07 1.4 0.47 0.47
Bienvenue Min. Val. 4.6 75.2 44.8 5.9 0.60 0.06 0.04 41.9 17.99 16.66
Max. Val. 5.7 78.9 46.0 6.1 0.93 0.13 0.11 43.3 18.46 17.13
Std. Dev. 0.4 1.3 0.4 0.08 0.1 0.03 0.03 0.5 0.17 0.16
Mean (n=6) 5.3 77.2 45.0 6.0 0.76 0.07 0.06 42.8 18.05 16.75
Range 0.6 4.2 0.5 0.1 0.20 0.02 0.04 0.4 0.24 0.24
Trimour Min. Val. 4.9 75.4 44.8 5.9 0.67 0.06 0.04 42.6 17.96 16.66
Max. Val. 5.5 79.6 45.3 6.0 0.87 0.08 0.08 43.0 18.20 16.90
Std. Dev. 0.2 1.9 0.2 0.04 0.1 0.01 0.01 0.2 0.09 0.09
Mean (n=6) 4.4 77.7 45.7 6.1 0.72 0.08 0.08 43.0 18.28 16.96
Range 0.6 3.0 1.0 0.1 0.19 0.01 0.05 1.0 0.48 0.51
Petkus Min. Val. 4.1 76.5 45.1 6.0 0.61 0.07 0.06 42.5 18.04 16.71
Max. Val. 4.7 79.5 46.1 6.1 0.80 0.08 0.11 43.6 18.52 17.22
Std. Dev. 0.3 1.0 0.4 0.05 0.1 0.01 0.02 0.4 0.19 0.20
Rye
Mean (n=6) 4.2 77.2 46.2 6.1 1.04 0.10 0.06 42.3 18.51 17.19
Range 1.2 2.1 0.7 0.1 0.74 0.05 0.03 2.1 0.34 0.34
Askari Min. Val. 3.5 76.2 45.8 6.0 0.82 0.08 0.05 40.9 18.28 16.95
Max. Val. 4.7 78.3 46.5 6.1 1.56 0.13 0.08 43.1 18.62 17.29
Std. Dev. 0.4 0.7 0.2 0.04 0.3 0.02 0.01 0.8 0.13 0.13
Table III: Composition of the major components (expressed as oxides) of ashes from biomass cultivated in Escobosa de
Almazán
CaO MgO Na2O K2O P 2 O5 Al2O3 SiO2
Species Variety
(wt%, d.b.) (wt%, d.b.) (% b.s.) (% b.s.) (% b.s.) (% b.s.) (% b.s.)
Mean (n=2) 5.6 2.4 0.23 18 9.2 0.26 47
Range 1.8 0.7 0.01 5 1.6 0.00 11
Collegial
Min. Val. 4.7 2.0 0.22 15 8.4 0.26 41
Max. Val. 6.5 2.7 0.23 20 10.0 0.26 52
Mean (n=2) 5.1 1.8 0.25 16 6.7 0.36 49
Range 0.6 0.1 0.15 4 0.0 0.32 2
Trujillo
Min. Val. 4.8 1.7 0.17 14 6.7 0.20 48
Max. Val. 5.4 1.8 0.32 18 6.7 0.52 50
Triticale
Mean (n=2) 5.1 2.0 0.16 15 7.6 0.44 54
Range 1.1 0.6 0.08 1 0.2 0.42 0
Bienvenue
Min. Val. 4.5 1.7 0.12 14 7.5 0.23 54
Max. Val. 5.6 2.3 0.20 15 7.7 0.65 54
Mean (n=2) 5.5 2.0 0.28 17 8.0 0.63 45
Range 1.7 0.3 0.27 4 1.8 0.95 6
Trimour
Min. Val. 4.6 1.8 0.14 15 7.1 0.15 42
Max. Val. 6.3 2.1 0.41 19 8.9 1.10 48
Mean (n=2) 7.1 2.0 0.39 23 8.2 0.22 42
Range 0.4 0.1 0.03 5 0.6 0.04 6
Petkus
Min. Val. 6.9 1.9 0.37 20 7.9 0.20 39
Max. Val. 7.3 2.0 0.40 25 8.5 0.24 45
Rye
Mean (n=2) 8.3 2.3 0.18 30 8.8 0.30 30
Range 1.0 0.0 0.19 5 0.3 0.05 8
Askari
Min. Val. 7.8 2.3 0.09 27 8.6 0.27 26
Max. Val. 8.8 2.3 0.27 32 8.9 0.32 34

5. Table IV: Fusibility of the ashes obtained from the being more noticeable for Collegial samples with doughy
biomass cultivated in Escobosa de Almazán grains (5.3 wt% for doughy grains vs. 4.0 wt% for milky
grains), as it can be seen in the screening plot of Fig. 4.
IDT ST HT FT
Species Variety
(oC) (oC) (oC) (oC)
Mean (n=2)
Range
855
90
970
40
1100
100
1180
40
Ashes
Collegial
Min. Val. 810 950 1050 1160
Max. Val. 900 990 1150 1200 6.3
Mean (n=2) 890 1015 1125 1225
Range 160 70 110 10 6.0
Trujillo
Min. Val. 810 980 1070 1220 Doughy grains
Max. Val. 970 1050 1180 1230
Triticale 5.7
Mean (n=2) 865 1055 1155 1215
Range 50 90 50 70
Bienvenue 5.4
wt%, d.b.
Min. Val. 840 1010 1130 1180
Max. Val. 890 1100 1180 1250
Mean (n=2) 830 1005 1095 1165 5.1
Range 140 190 130 130
Trimour
Min. Val. 760 910 1030 1100 4.8
Max. Val. 900 1100 1160 1230
Mean (n=6) 793 917 1055 1135 4.5
Range 120 140 40 60
Petkus Min. Val. 730 830 1040 1100 4.2
Max. Val. 850 970 1080 1160 Milky grains
Std. Dev. 40 52 16 24
Rye 3.9
Mean (n=6) 783 883 1080 1107
Range 80 160 120 150 Bienvenue Collegial Trimour Trujillo
Askari Min. Val. 750 820 1040 1060
Max. Val. 830 980 1160 1210
Std. Dev. 33 54 45 56 Figure 4: Screening plot for the triticale ashes cultivated
in EDA
Means and standard deviations (Std. Dev.) were
calculated, and ranges, minimum values (Min. Val.) and Carbon content, as well as calorific values
maximum values (Max. Val.) were established for each (differences of 0.46 MJ kg-1 between means) were found
property and studied variety, trying to be representative to be higher for rye samples, probably as a consequence
of the differences due to a genetic factor, since the of the higher ash contents found for triticale samples.
growing conditions were the same (soil, fertilization, Significant differences between ashes and net calorific
weather, seed rate, etc.). values for both species can be appreciated in Fig. 5.
In a first attempt to estimate the differences between Negative effect that high ash contents causes into
the two studied species, a one-way analysis of variance biomass calorific value and C content is well-known.
(ANOVA) was carried out, and results are shown in the Significant correlations have been found when plotting
first raw of Table V. Secondly, a two-way multifactor heating values as a function of the ash or carbon contents
ANOVA was performed over the entire data set, and [15]. Heating values decrease with the increase of ash
differences between varieties and cereal development content in biomass materials, and increase with the
states were evaluated. Results are also included in Table increase of C and H contents, which is consistent with
V. P-values below 0.05 denote a statistically significant commonsense that higher C and H contents mean a
difference between the mean of one level of the property higher energy content of a biomass [15,16].
to another, at the 95.0% confidence level. For a full
comprehension of results, trends between levels for
Ashes NCVp,0
significant properties were also included in the table. 5.4 17.5
They were obtained by running a multiple range test 5.2
17.3
which is a multiple comparison procedure to determine 5.0
wt%, d.b.
MJ kg-1
17.1
which means are significantly different from each others 4.8
4.6
at the same confidence level. Refer to the key below 4.4
16.9
Table V for abbreviations. 4.2
16.7
C, H, N, S, Cl, O contents and heating values were 4.0 16.5
Rye Triticale Rye Triticale
not found to be dependent on the grain development
state. Samples collected when their grains were in a Figure 5: Mean and 95.0 % low square differences
dough development state showed very slightly higher (LSD) intervals for the ash content and net calorific value
volatile matter (77 wt% for milky grains and 78-79 wt% of samples cultivated in EDA
for doughy grains). Ash content was also slightly higher
for triticales with doughy grains (5.3 wt% vs. 4.8 wt%),
Table V: ANOVA results for biomass cultivated in Escobosa de Almazán (P-values and trends between levels).
Ash VM C H N S Cl O GCVv,0 NCVp,0
Factor -1 -1
(wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (MJ kg ) (MJ kg )
Species n=36 0.0000 0.4321 0.0000 1.0000 0.1767 0.0725 0.9575 0.0460 0.0002 0.0002
T>R R>T R>T R>T
Triticale n=24
Variety 0.0381 0.0156 0.0065 0.0033 0.4626 0.5047 0.7623 0.0015 0.0260 0.0183
(B=Ti=Tu)>C C>(B=Ti) (B=Ti)>(C=Tu) (C=Tu)>Ti (C=Tu)>(B=Ti) (B=Ti) > Tu (B=Ti) > Tu
Co=Tu Co=Tu
Growth stage 0.0119 0.0005 0.8805 0.5236 0.0776 0.2443 0.5786 0.3460 0.9527 0.9209
D>M D>M
Rye n=12
Variety 0.4686 0.2735 0.0211 0.2861 0.0119 0.0350 0.0660 0.0740 0.0361 0.0480
A>P A>P A>P A>P A>P
Growth stage 0.7690 0.0258 0.2724 1.0000 0.1452 0.2887 0.3666 0.3922 0.5055 0.5240
D>M
Key: T = triticale, R = Rye, B = Bienvenue, Ti = Trimour, Tu = Trujillo, C = Collegial, D = Dough, M = Milk

6. Found differences regarding ashes, C and heating
values must be attributed to the genetics of the plant, and Initial deformation temperature Sphere temperature
not to the contamination of the biomass with external 1000
950
1200
1150
1100
particles because all samples were manually collected 900
850 1050
ºC
ºC
800
avoiding this kind of pollution. Additionally, no 750
1000
950
700 900
differences among varieties were found when analyzing 650 850
600 800
the ashes obtained from biomass, which clearly supports Collegial Trujillo Bienvenue Trimour Collegial Trujillo Bienvenue Trimour
the afore-mentioned hypothesis. For instance, Al is Hemisphere temperature Fluid temperature
usually considered as a marker for contamination of 1300
1250
1300
1250
biomass by soil inclusions (predominantly clays and 1200
1200
1150
ºC
ºC
oxides). When biomass is polluted with sand, clays and 1150
1100
1100
1050
soil components, other elements such as Si, Ti, Fe and Na 1050
1000
950
are also introduced [8]. It can not be attributed either to 1000
Collegial Trujillo Bienvenue Trimour
900
Collegial Trujillo Bienvenue Trimour
the different grain development state, due to the only very K2O
slight differences found for ash (only for the Collegial 22
20
variety) and volatile matter contents (differences of only 18 Milky grains
wt%, d.b.
Doughy grains
1-2 wt%), regarding this factor. 16
14
No significant differences were found for N, S and Cl 12
among triticale varieties. However, differences were 10
Collegial Trujillo Bienvenue Trimour
found for heating values, as well as for ash, volatile, C,
H, and O contents. ANOVA found that mean ash content Figure 7: Fusibility temperatures and K2O content as a
for Collegial varieties was lower than for the rest of the function of grains growth stage
varieties, but it is only because of the low ash contents
found for samples of this variety containing milky grains The importance of the K content is due to its
(see Fig. 4). Plots were depicted in Fig. 6 for some of influence on the ash melting behaviour and on aerosol
these significant properties. It should be mentioned that formation. According to literature, potassium is relatively
Bienvenue and Trimour are the triticale varieties with the volatile, forming chlorides, hydroxides and sulfates,
highest C content and mean heating values. which play an important role in the corrosion
mechanisms relevant for boilers [17]. Increased K
Carbon NCVp,0 concentrations rise the amount of aerosols formed during
46.0 17.1 combustion, and thus fouling in boilers and fine
45.5 16.9 particulate emissions. Moreover, an increased K content
45.0
16.7
leads to a decreased ash melting point, which can cause
wt%, d.b.
MJ kg-1
44.5
16.5
slag and hard deposit formation in the furnace and boiler
44.0
16.3
[9]. Straw, cereal, grass, and grain ashes, which contain
43.5
low concentrations of Ca and high concentrations of Si
43.0 16.1
Bienvenue Collegial Trimour Trujillo Bienvenue Collegial Trimour Trujillo and K start to sinter and melt at significantly lower
temperatures than wood fuels [7]. Therefore, triticale
Figure 6: Mean and 95.0 % LSD intervals for C and net presents a lower tendency to fouling and slagging when it
calorific value for the triticale varieties cultivated in EDA is collected with doughy grains than with grains in a
milky development state.
Attending rye varieties, C and heating values were
slightly higher for the Askari variety (a difference of 0.24 3.2 Variability in different locations
MJ kg-1 between the means). Although N and S contents Three triticale varieties (Trujillo, Collegial and
were also found to be significant properties, this is not a Trimour) and one of rye (Petkus) were cultivated in 11
reliable result due to the presence of a likely outlier different locations around the north and central part of
sample, which exhibits disproportionate high contents of of Spain under multiple conditions (companies,
both elements, increasing thus the mean value and the fertilization, soil, etc.). More than 130 samples were
variability for this variety. manually collected to avoid the contamination of the
As it can be seen in Table IV, fusibility temperatures samples with stones, sand, etc. to form the 26 final
were found to be higher for triticale samples (e.g. IDT of samples that were characterized. Each final sample was
760-970 ºC) in comparison with those obtained for rye considered representative of the composition of the
samples (e.g. IDT of 730-850 ºC). It could be due to the biomass grown in its corresponding plot.
lower K2O contents (mean of 17 wt%) of triticale ashes Standard deviations and ranges were obtained for
compared to those found for rye samples (27 wt%). each variety and property, trying to be representative of
Fusibility or composition of ashes obtained from the differences due to an environment factor, given that
biomass does not depend on the variety of the studied this biomass was grown under multiple conditions and
species or the development state of rye grains. However, locations. Means, ranges, standard deviations as well as
ash fusibility temperatures for triticale samples were minimum and maximum found values are shown in
found to be dependent on the growth state of grains, Tables VI-VIII.
finding lower temperatures for milky grains (e.g. IDT of
760-840 for milky grains vs. 890-970 for doughy grains),
probably as a consequence of their higher K2O content
(15-20 for ashes from biomass containing milky grains
vs. 14-15 wt% for doughy grains, see Fig. 7).

7. Table VI: Composition and variability of the biomass cultivated in different locations around the north and central part of
Spain
Ash VM C H N S Cl O GCVv,0 NCVp,0
Species Variety
(wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (wt%, d.b.) (MJ kg-1) -1
(MJ kg )
Mean (n=5) 6.3 75.3 45.1 5.9 0.60 0.12 0.34 41.6 18.11 16.83
Range 1.9 2.2 1.2 0.2 0.89 0.10 0.69 2.4 0.18 0.21
Collegial Min. Val. 5.5 74.4 44.5 5.8 0.32 0.06 0.07 40.1 18.06 16.77
Max. Val. 7.4 76.6 45.7 6.0 1.21 0.16 0.76 42.4 18.24 16.98
Std. Dev. 0.8 0.9 0.4 0.1 0.37 0.04 0.27 0.9 0.07 0.09
Mean (n=9) 4.7 78.0 45.3 6.1 1.12 0.12 0.19 42.5 18.37 17.05
Range 3.0 3.1 1.3 0.3 0.55 0.09 0.53 2.9 0.46 0.50
Triticale Trujillo Min. Val. 3.4 76.8 44.7 6.0 0.89 0.07 0.05 40.7 18.18 16.81
Max. Val. 6.4 79.9 46.0 6.3 1.44 0.16 0.58 43.6 18.64 17.31
Std. Dev. 0.8 1.3 0.4 0.1 0.17 0.02 0.17 0.9 0.18 0.18
Mean (n=5) 5.1 76.3 45.6 6.0 0.75 0.10 0.22 42.2 18.54 17.24
Range 2.3 3.0 1.4 0.2 0.99 0.09 0.55 2.5 0.38 0.40
Trimour Min. Val. 4.0 74.9 44.8 5.9 0.35 0.06 0.05 40.8 18.41 17.08
Max. Val. 6.3 77.9 46.2 6.1 1.34 0.15 0.60 43.3 18.79 17.48
Std. Dev. 0.8 1.3 0.6 0.1 0.41 0.03 0.23 0.9 0.15 0.15
Mean (n=7) 4.1 78.0 46.0 6.0 0.88 0.09 0.19 42.7 18.51 17.20
Range 1.9 3.9 0.7 0.3 1.06 0.07 0.43 1.6 0.27 0.21
Rye Petkus Min. Val. 3.2 76.4 45.7 5.8 0.36 0.04 0.04 42.2 18.37 17.10
Max. Val. 5.1 80.3 46.4 6.1 1.42 0.11 0.47 43.8 18.64 17.31
Std. Dev. 0.7 1.5 0.3 0.1 0.36 0.03 0.15 0.6 0.09 0.07
Table VII: Composition of the major components (expressed as oxides) of ashes from the biomass cultivated in different
location
CaO MgO Na2O K2O P2O5 Al2O3 SiO2
Species Variety
(wt%, d.b.) (wt%, d.b.) (% b.s.) (% b.s.) (% b.s.) (% b.s.) (% b.s.)
Mean (n=5) 7.2 2.4 0.35 29 6.5 0.50 39
Range 3.6 1.8 0.61 10 10.0 0.63 20
Collegial Min. Val. 5.1 1.6 0.15 24 2.0 0.17 31
Max. Val. 8.7 3.4 0.76 34 12.0 0.80 51
Std. Dev. 1.4 0.7 0.26 4 4.3 0.25 8
Mean (n=9) 6.7 3.5 0.43 24 8.4 0.54 37
Range 4.0 3.8 0.51 14 10.3 0.81 28
Triticale Trujillo Min. Val. 4.6 2.4 0.15 19 4.7 0.19 21
Max. Val. 8.6 6.2 0.66 33 15.0 1.00 49
Std. Dev. 1.2 1.4 0.18 4 3.4 0.30 8
Mean (n=5) 7.4 2.7 0.41 26 5.5 0.71 41
Range 4.0 2.3 0.52 12 9.0 1.01 25
Trimour Min. Val. 5.4 1.9 0.17 21 2.0 0.29 29
Max. Val. 9.4 4.2 0.69 33 11.0 1.30 54
Std. Dev. 2.0 0.9 0.20 5 3.8 0.46 10
Mean (n=7) 7.7 3.9 0.16 29 8.9 0.29 32
Range 2.8 1.7 0.09 9 8.4 0.46 21
Rye Petkus Min. Val. 6.4 2.9 0.11 23 5.6 0.13 21
Max. Val. 9.2 4.6 0.20 32 14.0 0.59 42
Std. Dev. 1.0 0.5 0.04 3 2.7 0.14 8
Table VIII: Fusibility of the ashes obtained from the 3.3 Comparison of variabilities
biomass cultivated in different locations Finally, a Cochran´s test was run for each biomass
property to check up on variances (variance of same
IDT ST HT FT
location vs. variance of different locations). Variance of
Species Variety
(oC) (oC) (oC) (oC) same location can be equivalent to the variability
Mean (n=5) 766 940 1024 1126
Range 110 140 30 250 originated by the genetics of the grown variety, while
Collegial Min. Val. 720 850 1010 1050
Max. Val. 830 990 1040 1300
variance of different locations includes the variability
Std. Dev. 50 78 11 101 originated by the different grown varieties plus that
Mean (n=9) 868 955 1082 1146
Range 280 340 150 140 caused by the multiple growing and farming conditions
Triticale Trujillo Min. Val. 780 830 1040 1070
Max. Val. 1060 1170 1190 1210
applied.
Std. Dev. 85 105 45 48 Cochran´s test results for triticale samples (including
Mean (n=5) 836 923 1088 1128
Range 200 180 230 270 Collegial, Trujillo and Trimour varieties) and rye
Trimour Min. Val. 740 840 1030 1040
Max. Val. 940 1020 1260 1310
samples (including Petkus variety) are shown in Tables
Std. Dev.
Mean (n=7) 876
86
861
74
967
97
1040
108 IX and X, respectively. Standard deviations (SD) and
Range 400 300 290 220 ranges (R) were also included in tables.
Rye Petkus Min. Val. 750 840 930 1040
Max. Val. 1150 1140 1220 1260
Std. Dev. 137 110 97 73

8. Table IX: Cochran´s test results for triticale samples (Collegial, Trujillo and Trimour varieties included)
Property Units n P-value SDDL SDSL RDL RSL
Ash wt%, d.b. 37 0.00646 1.1 0.5 4.0 1.8 not equal
VM wt%, d.b. 37 0.46920 1.7 1.4 5.5 4.4 equal
C wt%, d.b. 37 0.04081 0.48 0.80 1.70 2.20 not equal
H wt%, d.b. 37 0.27460 0.11 0.08 0.50 0.30 equal
N wt%, d.b. 37 0.00029 0.37 0.15 1.12 0.71 not equal
S wt%, d.b. 37 0.00103 0.03 0.01 0.10 0.05 not equal
Cl wt%, d.b. 37 0.00000 0.22 0.02 0.71 0.08 not equal
O wt%, d.b. 37 0.79582 0.95 0.90 3.51 2.65 equal
GCVv,0 MJ kg-1 37 0.06510 0.22 0.35 2.65 0.98 equal
NCVp,0 MJ kg-1 37 0.04481 0.22 0.36 0.71 0.98 not equal
Key: SD = satnadard deviation, R = range, DL = different locations, SL = same location
Table X: Cochran´s test results for rye samples (Petkus variety included)
Property Units n P-value SDDL SDSL RDL RSL
Ash wt%, d.b. 25 0.03914 0.7 0.3 1.9 0.6 not equal
VM wt%, d.b. 25 0.44961 1.5 1.0 3.9 3.0 equal
C wt%, d.b. 25 0.42253 0.28 0.39 0.70 1.00 equal
H wt%, d.b. 25 0.12559 0.11 0.06 0.30 0.10 equal
N wt%, d.b. 25 0.00149 0.36 0.07 1.06 0.19 not equal
S wt%, d.b. 25 0.00183 0.03 0.01 0.07 0.01 not equal
Cl wt%, d.b. 25 0.00013 0.15 0.02 0.43 0.05 not equal
O wt%, d.b. 25 0.25364 0.59 0.35 1.60 1.01 equal
GCVv,0 MJ kg-1 25 0.09821 0.09 0.19 0.27 0.48 equal
NCVp,0 MJ kg-1 25 0.02862 0.07 0.20 0.21 0.51 not equal
Key: SD = standard deviation, R = range, DL = different locations, SL = same location
This test assumes the hypothesis that both variances found variability by separate, e.g. factors like rainfall,
are equal and reports a significance level for each type of soil, physical conditions of the land, nutrients, or
evaluated property. P-values below 0.05 means that some others more related to the pollution during
variances are significantly different, which indicates in sampling and handling of the fuel, such as sawthing with
turn that the variability of that group of samples is windrowers or bailing.
originated by the condition exhibiting the highest
variance. It is worth mentioning that the same test was
performed for each individual variety, obtaining the 4 CONCLUSIONS
same results. Therefore, if variances can be considered
statistically different (raws labelled as “not equal”) , the This study constitutes a first approach to estimate the
variability of the results can be attributed to a genetic variability of cereals in Spain in terms of biomass quality.
factor (SDSL > SDDL) or, on the contrary, the different The variability among the properties of unpolluted raw
growing and farming conditions adds more variability to biomass (straw + grains) of triticale and rye due to the
the results (SDDL > SDSL). different varieties and growing conditions was evaluated.
Taking a thorough look at Table IX, it can be Variability ranges that can be expected for each variety
deduced that the variability of parameters such as C and and physico-chemical property of triticale and rye were
net calorific value can be associated with the cultivated set in north central Spain.
variety of triticale, while main differences in the ash, N, It is really worth mentioning that parameters such as
S, and Cl contents seem to be linked to the growing carbon or heating values seem to be somehow dependent
conditions. Dispersion plots for some triticale properties on the variety cultivated, while different growing and
are also presented in Figure 8. Regarding rye, it can be farming conditions seem to add a significant extra source
said from Table X that the variability of the net calorific of variability to some others like ash, nitrogen, sulphur,
value can be associated with the cultivated rye variety, or chlorine contents.
while differences in the growing conditions seem to add Of particular interest are some other conclusions that
a significant extra source of variability to the ash, N, S, can be extracted from this study. For instance, the rye
Cl contents. Bartlett´s, Hartley´s and Levene´s tests variety Askari is characterized by the highest mean
confirmed the obtained results. Higher variability for heating values among all the considered varieties.
e.g. Cl, and S was expected for samples cultivated under Attending triticale, Bienvenue and Trimour are
different conditions, since it was demonstrated that characterized by higher mean heating values than
precipitation removes substantial amounts of K, Cl and Collegial or Trujillo. Triticale presents a lower tendency
S from triticale and rye, or the use of K fertilizers to fouling and slagging than rye, particularly when
containing Cl and S resulted in a significantly increased triticale is collected with doughy grains instead of milky
concentration of these elements in the straw [12]. grains.
Future research could involve the study of how
different environmental conditions contribute to the

9. .
Ashes Volatile matter Carbon
8.0 84.0 47.0
7.0 82.0
46.0
80.0
6.0
wt%, d.b.
wt%, d.b.
78.0 45.0
wt%, d.b.
5.0
76.0
44.0
4.0
74.0
3.0 43.0
72.0
2.0 70.0 42.0
0 5 10 15 20 0 5 10 15 20 0 2 4 6 8 10 12 14 16 18 20
Sample Sample Sample
NCVp,0
Hydrogen Nitrogen
17.75
17.50 7.0 1.75
17.25 6.8 1.50
17.00 6.5
1.25
-1
MJ kg
16.75 6.3
1.00
wt%, d.b.
wt%, d.b.
16.50 6.0
0.75
16.25 5.8
0.50
16.00 5.5
15.75 5.3 0.25
0 5 10 15 20
5.0 0.00
Sample
0 5 10 15 20 0 2 4 6 8 10 12 14 16 18 20
Sample Sample
Sulphur Chlorine
0.20 0.20
Same location (EDA)
0.16 0.16
Rest of locations
wt%, d.b.
wt%, d.b.
0.12 0.12
0.08 0.08
0.04 0.04
0.00 0.00
0 5 10 15 20 0 5 10 15 20
Sample Sample
Figure 8: Dispersion plots for triticale samples as a function of the location: EDA/same growing conditions vs. the rest of
locations/different growing conditions
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6 ACKNOWLEDGEMENTS
This research has been performed in the frame of the
2R Subproject (PSE-120000-2009-15) from the Project
for Development, Demonstration and Evaluation of the
Viability of the Commercial Production of Energy from
Dedicated Crops in Spain “PSE – On crops”, which has
been recognized as a national singular and strategic
project. This project is being supported by the Spanish
Ministry of Science and Innovation.