Variations in ash content, pulp yield, and fibre properties of reed canary-grass

Industrial Crops and Products 22 (2005) 157–167

Variations in ash content, pulp yield, and fibre properties ofreed canary-grass

Michael Finell∗, Calle Nilsson1

Swedish University of Agricultural Sciences (SLU), Unit of Biomass Technology and Chemistry (BTK),P.O. Box 4097, SE-904 03 Ume˚a, Sweden

Received 25 September 2003; accepted 26 August 2004

Abstract

This study examines the effect of the variety of reed canary-grass (RCG), location, soil type, and yearly variation on the ashcontent of the stem, the RCG’s pulp yield, and the RCG’s fibre properties. Thirteen RCG varieties were grown in 11 locations innorthern Europe. The RCGs were harvested using the delayed harvesting method. Two years (1997 and 1998) were included toobtain information of the yearly variation. The yearly variation had the greatest influence on the pulp properties. The ash contentof the stem fraction of RCG mainly depends on location and soil type. The overall variation in the measured properties, however,was within reasonable limits, and a substantial reduction of the variation could be achieved by selecting varieties suitable to theclimatic and soil conditions of the location.© 2004 Elsevier B.V. All rights reserved.

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eywords: Phalaris arundinacea; Reed canary-grass; Non-wood pulping; Pulp properties; Variation; Multivariate data analysis; PLS; S

. Introduction

Reed canary-grass (RCG) (Phalaris arundinacea.) is a perennial cool-season rhizomatous grass thatupplements birch as a short fibre raw material in theordic countries (Paavilainen and Torgilsson, 1994). In

his study, delayed harvest was used. This method har-

∗ Corresponding author. Tel.: +46 90 786 87 96;ax: +46 90 786 87 99.

E-mail address:[email protected] (M. Finell).1 Present address: The Swedish Defence Research Agency, NBCefence, SE-901 82, Umea, Sweden.

vests the grass in the spring when it is wilted, resuin drier material. Using this method makes handlinthe grass easier and improves the quality of the g(Landstrom et al., 1996). Dry fractionation, which removes undesirable parts of the grass, can furtheprove the quality of the grass when used for shortproduction (Finell et al., 2000). Compression of thfractionated grass by briquetting improves handltransport, and storage (Finell et al., 2002).

The use of RCG as a short fibre raw materialbeen demonstrated in full-scale projects that usedelayed harvesting method, dry fractionation, andquetting (Paavilainen et al., 1999). Pulp was produce

926-6690/$ – see front matter © 2004 Elsevier B.V. All rights reserved.doi:10.1016/j.indcrop.2004.08.003

158 M. Finell, C. Nilsson / Industrial Crops and Products 22 (2005) 157–167

with the kraft method in a sawdust digester. The pro-duced pulp was bleached and tested as a short fibrecomponent in white top liner paper (Finell, 2003). Thetests showed that RCG had the potential to competewith birch as an effective short fibre material. RCGkraft pulp has also been shown to compete with birchpulp in the production of fine paper (Paavilainen andTulppala, 1996).

An important aspect of annually harvested plants,when used as raw material for paper making, is thehomogeneity of the raw material. A large variation infibre properties makes it difficult to use the raw materialin high quality products such as fine paper or white topliner paper. Variation in the ash content of grasses canmake it difficult to control the chemical recovery of thespent cooking liquors.

The soil type of the growing location influencesthe ash content of reed canary-grass. Plants grown inheavy clay soils produce the highest ash content. Plantsgrown in humus rich soils have the lowest ash content.The major component of RCG ash is silica (Burvall,1997; Burvall et al., 1997). The ash content is lowestin the stem and highest in the leaf sheaths and leafblades. The fibre content is lowest in the leaf sheathsand blades and highest in the stem (Pahkala and Pihala,2000).

For other annually harvested plants such as wheatstraw and kenaf, the yearly variation, location, andplant variety significantly influenced fibre properties(Jacobs et al., 1998; Cook et al., 1998). The lo-c cep dJ at-t andR -s af-f kraftp der-ay per-th ithd vari-a time( buto va-r rep

Table 1Some data found in the literature on RCG kraft pulp compared tobirch kraft pulp

Property RCGa RCGb RCGc Bircha Birchc

Screened pulp yield (%) 37.7 54.0 54.5 52.2 53.2Kappa no. 36.7 9.30 9.70 19.3 18.0Drainage (◦SR) 65 25 23 12 14Fibre length, weighted

(mm)0.80 0.71 0.85 0.90 1.00

a Thykesson et al. (1998).b Paavilainen et al. (1999).c Finell et al. (2000).

This study examines the yearly variation and effectof growing location, soil type, and RCG variety on ashcontent, pulp yield, and fibre properties. Although theyare not included in this study, variables such as weather,water, nutrient availability, and soil pH probably havea significant influence on the measured properties. Themain purpose of this study is to show the variation inthe above-mentioned properties for some varieties ofRCG grown in northern Europe.

2. Materials and methods

2.1. Reed canary-grass

Thirteen varieties of RCG (Table 2) were grownat 11 locations in northern Europe. The plants were

Table 2Name, code, and supplier of the tested reed canary-grass varieties

RCG varietya Code(VAR)

Delivered by

Jo0510 JO01 Agrifood Research, MTT, FinlandLEU94101 LE01 Federal Agricultural Research Centre,

FAL, GermanyLEU94201 LE02 Federal Agricultural Research Centre,

FAL, GermanyPalaton PALA Svalof Weibull AB, SwedenSWRF5001 SW01 Svalof Weibull AB, SwedenSWRF5002 SW02 Svalof Weibull AB, SwedenSWRF5003 SW03 Svalof Weibull AB, SwedenSWRF5004 SW04 Svalof Weibull AB, SwedenSSSSS

ties.

ation and RCG variety also significantly influenlant height and plant development (Sahramaa anauhiainen, 2003). Substantial differences in dry mer yield were found for locations, harvest year,CG varieties (Saijonkari-Pahkala, 2001). It can be asumed that also the fibre properties of RCG will beected by these variables. Other studies on RCGulp properties indicate that quality varies consibly (Table 1). Thykesson et al. (1998)report low pulpield, high kappa number, and poor drainage proies.Paavilainen et al. (1999)andFinell et al. (2000),owever, report high yield and low kappa number wecent drainage properties. To some extent, thesetions can be explained by differences in harvestautumn/spring) and fractionation before pulping,ther factors such as soil type, location, and RCGiety will probably contribute to the variation in fibroperties.

WRF8701 SW05 Svalof Weibull AB, SwedenWNRF9208 SW06 Svalof Weibull AB, SwedenWNRF9214 SW07 Svalof Weibull AB, SwedenWNRF9406 SW08 Svalof Weibull AB, SwedenWNRF9407 SW09 Svalof Weibull AB, Sweden

a Palaton is the only real variety, all other are candidate varie

M. Finell, C. Nilsson / Industrial Crops and Products 22 (2005) 157–167 159

Fig. 1. The RCG growing locations in northern Europe.

raised in greenhouses and planted in the field byhand in the early summer of 1995. Fertilisation ofthe field trials varied between different sites due todifferent soil fertility. On average, the yearly nitro-gen supply was about 90 kg/ha. Phosphorus and potas-sium fertilisation was adjusted to meet the need ofeach site. All 13 RCG varieties were harvested inearly spring (delayed harvest) in 1997 and 1998.Fig. 1 identifies the location of the 11 trial sites, andTable 3lists the soil type and composition at the loca-tions.

Table 3The RCG growing locations, code, and soil type

Location Code (LOC) Soil type Organic (%) Clay (%) Silt (%) Sand (%) Gravel (%)

Aberystwyth, GB ABER Clay loam 8 26 36 24 6Braunschweig, DE BRAU Sandy loam 1 6 31 60 2Dundee, GB DUND Loam 9 10 23 47 11Foulum, DK FOUL Sandy loam 4 8 21 67 0Jokioinen, Fl JOKI Heavy clay 6 41 33 20 0Rothamstead, GB ROTH Silt loam 6 23 50 18 3Sotkamo, Fl SOTK Silt loam 5 13 69 12 1Svalof, SE SVAL Sandy clay loam 2 15 26 51 6Tipperary, IE TIPP Loam 4 14 29 44 9Umea, SE UMEA Silt loam 5 8 72 15 0Ylistaro, Fl YLIS Silt loam 4 21 55 20 0

2.2. Sampling

Representative soil samples were collected at eachgrowing location. The samples were sent to our lab-oratory for classification. Near infrared spectroscopy(NIR) was used to select the varieties for analysis. In1997, five samples from each location were selectedto obtain the largest possible variation in the composi-tion of RCG as reflected by NIR. Principal componentanalysis (PCA) was used to model the variation of therecorded NIR spectral data (unpublished data). In the


Table 4The RCG varieties collected at the different growing locations year 1997 and 1998

ABER BRAU DUND FOUL JOKI ROTH SOTK SVAL TIPP UMEA YLIS

1997 LE02 LE02 (3) LE01 PALA JO01 LE01 JO01 JO01 PALA LE02 PALAPALA PALA (3) PALA SW03 PALA LE02 PALA (2) PALA SW01 JO01 (2) SW02SW04 SW01 (3) SW01 SW06 SW05 PALA SW01 SW02 SW04 PALA SW04SW06 SW03 (3) SW04 SW08 SW08 SW02 SW02 SW03 SW06 SW01 SW05SW07 SW08 (3) SW07 SW09 SW09 SW07 SW05 SW06 SW07 SW09 SW07 (2)

1998 LE01 LE02 PALA LE01 JO01 LE01 PALA PALA PALA LE02 LE01PALA PALA SW01 LE02 PALA LE02 SW03 SW03 SW01 JO01 PALASW02 SW02 SW02 JO01 SW05 PALA SW04 SW04 SW02 PALA SW02SW04 SW03 SW03 PALA SW08 SW02 SW05 SW05 SW04 SW08 SW05SW06 SW04 SW06 SW04 SW09 SW04 SW07 SW07 SW06 SW07

SW05SW07

The number in parenthesis indicates duplicate (2) or triplicate (3) samples.

second year (1998), five RCG varieties from each sitewere chosen based on the highest dry matter yield. ThevarietyPhalaris, however, was included from all sitesfor both years. Duplicates and triplicates of some va-rieties were also collected at some growing locations.Table 4shows the varieties collected at each growinglocation. From these samples, analysis was done on thestem fraction. Leaves and leaf sheaths were removedby hand.

2.3. Pulping conditions

About 60 g of each RCG sample was cooked in0.5 l autoclave digesters (Chemical Autoclave Sys-tem, CRS 405, Reactor Engineering AB, Sweden).The alkali charge (effective alkali, EA) was kept at18%, the sulphidity was kept at 38%, the liquor-to-grass ratio was 5:1, time to cooking temperature was1 h, and the cooking time at 165◦C was 15 min. Im-mersing the reactors in cold water ended the cook-ing.

2.4. Analysis

Weight percentage of soil fractions (based onSwedish standards KLK Nr 1,1965 and SLL Nr 8,1981)and soil type (USDA, Soil survey staff, 1975) at thegrowing locations were determined. The organic con-tent of the soil was calculated as dry matter. Thea sed

(Swedish standard SS 18 71 71). After cooking, thepulps were washed with tap water on a 150-mesh wire,and disintegrated in a laboratory defibrator (L&W No-ram), using 20,000 revolutions. The pulps were dilutedto about 3 l. Samples were taken, collected on a fil-ter paper, dried, and used for pulp yield determina-tion. The remaining pulp was analysed for screeningreject (0.15 mm slots, L&W Noram CA 328 Fraction-ator, Somerville type). The reject fraction was calcu-lated on weight basis of raw material, and the screenedpulp yield was obtained by subtracting the screeningreject from the pulp yield. The accept fraction was col-lected in polyester filter bags and dewatered in a spin-dryer. Kappa number (SCAN-C 1:77), drainage resis-tance (SCAN-C 19:65), fibre length, fines, and coarse-ness (Kajaani FS-200) were determined for the acceptfraction.

2.5. Data analysis

A regression model based on partial least squares(PLS) was used to relate the variables (year, location,soil type, and variety) to the responses (the measuredproperties) (Eriksson et al., 2001). The variables ‘year’,‘location’, and ‘variety’ are qualitative variables, andthe variable ‘soil type’ is split in quantitative variables,representing the weight percentage of the soil compo-nents (organic, clay, silt, sand, and gravel) (Table 3).The software used for the data analysis was SIMCA-P1
sh content of the RCG stem fraction was analy 0.0 (Umetrics AB, Sweden).


3. Results and discussion

3.1. Raw data

Table 5shows the mean value, arithmetic standarddeviation, number of samples, and maximum and min-imum values of the measured properties. The screeningreject was low for all samples (mean value 0.39 with astandard deviation of 0.10 for all 111 samples), and isnot reported in the table or used in the multivariate anal-ysis. The upper part ofTable 5shows data for all sam-ples. Because different RCG varieties were collectedin 1997 and 1998 at the growing locations, statisticaltesting for difference between the two years would bemisleading. The middle part of the table shows data forthe variety ‘Palaton’, which was grown at all locationsboth years. For these samples, statistical testing showsa significant difference between year 1997 and 1998for the properties ‘Pulp yield’, ‘Kappa no.’, and ‘Fibrecoarseness’. The lower part of the table shows data fromtriplicates of the variety ‘Palaton’ grown at the location‘Braunschweig’ in 1997. This gives some informationabout the repeatability of the experiments. The vari-ety ‘Palaton’ grown at the location ‘Braunschweig’ in1997 was also the sample that gave the highest pulpyield. The results in this table for RCG pulp propertiescan be compared to typical values for birch pulp thatare presented inTable 1.

Table 5shows that the variations in pulp proper-ties are considerable for two years. This indicates thatu vail-a a-s

3

entP er.T orem ibet (byc low-em ses.N thel e-d Thea plots

(Fig. 3a and b) are in parenthesis. For the variable‘Ash’, the model is good and can be used for pre-diction. For the other responses, the model can onlybe used to show the main effects of the investigatedvariables.

3.3. Variable importance

The overall importance of the investigated variablesfor the seven-component model is shown inFig. 2.Terms with a VIP > 1 have an above average influ-ence on the responses. The 95% confidence intervalsare derived from jack knifing (Eriksson et al., 2001).It can be seen that the factors year 1997 and year1998 have the greatest influence of all the factors.Of the varieties investigated, the variety SW02 is theonly one with an above average influence. The lo-cations Rothamsted, Sotkamo, Braunschweig, Umea,Jokioinen, and Foulum all have above average influ-ence on the responses. In addition, the soil componentsgravel, clay, sand, and organic have an above averageinfluence.

3.4. Interpretation of the scatter plots

Fig. 3a and b show the scores scatter plot and thePLS weights plot for the first two components of thePLS model. The first two components describe 27.8and 10.3% of the variation in the response matrix. Theeffect of yearly variation can be seen as a separationo plot.D ir-c LSw gestv Sw pos-i es,a withp ela-t 02i nsesa asha woc n andU bes orre-l po-n

ncontrollable factors such as weather and water ability play a significant role in controlling the meured properties.

.2. PLS model

Table 6shows a summary of the seven-componLS model. All Y-variables were modelled togethhe Y-variable ‘Drainage’ was log-transformed befodelling. TheR2 andQ2 values are used to descr

he explained variation and the predicted variationross validation). More than seven componentsred theQ2 value of the model. As seen inTable 6, theodel explains 63% of the variation of the respono interaction terms were included in the model. In

ower part ofTable 6, the explained variation and pricted variation of individual responses are listed.bbreviated variable names used in the scatter

f data from 1997 and 1998 in the scores scatterata from 1998 is located to the left of the plot (cles) and data from 1997 to the right (dots). In the Peights plot, year 1997 and year 1998 are the stronariables in the first component (x-axis). From the PLeights plot, it can also be seen that year 1998 is

tively correlated with drainage, kappa number, finnd coarseness. Year 1998 is negatively correlatedulp yield and fibre length. For year 1997, the corr

ions are the opposite of year 1998. The variety SWs to a high degree correlated with the same respos year 1998 but also negatively correlated withnd fibre length. The PLS weights plot for the first tomponents also shows that the locations Jokioinemea are positively correlated with ash. It can alsoeen that the soil component sand is negatively cated with ash in the raw material and the soil coment clay is positively correlated with ash.


Table 5Summary of the measured properties

Ash instem (%)

Pulp yield,screened (%)

Drainageresistancec

(◦SR)

Kappa no. Fibre length,weighted (mm)

Fibrecoarseness(mg/m)

Fines,arithm. (%)

All varieties, all locationsa

Mean (1997 + 1998) 3.37 52.7 26.0 12.5 0.90 0.074 39.2S.D. 1.69 2.28 5.30 1.68 0.10 0.009 3.38N 100 111 111 111 111 111 111Max 7.50 57.3 46.5 21.3 1.09 0.102 48.2Min 0.77 47.6 18.0 9.71 0.65 0.056 32.5

Mean (1997) 3.18 53.9 24.0 11.8 0.92 0.068 39.2S.D. 1.68 2.15 4.65 1.30 0.08 0.006 3.48N 49 55 55 55 55 55 55Max 7.42 57.3 39.0 15.2 1.09 0.085 46.6Min 0.77 47.6 18.0 9.71 0.74 0.057 32.5

Mean (1998) 3.56 51.5 28.0 13.3 0.88 0.080 39.3S.D. 1.71 1.72 5.19 1.68 0.10 0.008 3.31N 51 56 56 56 56 56 56Max 7.50 55.9 46.5 21.3 1.07 0.102 48.2Min 0.93 47.8 20.0 10.6 0.65 0.056 32.9

Only variety Palaton, all locationsa,b

Mean (1997 + 1998) 2.99 53.3 25.1 12.8 0.93 0.072 38.2S.D. 1.50 2.40 5.49 1.82 0.09 0.012 3.26N 20 22 22 22 22 22 22Max 5.99 57.0 38.0 17.3 1.05 0.101 45.1Min 0.77 48.6 18.0 10.4 0.74 0.056 32.5

Mean (1997) 2.69 54.6 23.0 11.6 0.96 0.066 37.8S.D. 1.46 2.40 3.76 1.24 0.09 0.007 3.41N 10 11 11 11 11 11 11Max 5.80 57.0 31.0 15.0 1.05 0.080 43.3Min 0.77 48.6 18.0 10.4 0.75 0.057 32.5

Mean (1998) 3.30 52.0* 27.2 13.9* 0.91 0.079* 38.5S.D. 1.56 1.62 6.27 1.63 0.09 0.013 3.22N 10 11 11 11 11 11 11Max 5.99 54.1 38.0 17.3 1.03 0.101 45.1Min 0.93 49.4 20.0 12.1 0.74 0.056 34.7

Only variety Palaton, location Braunschweig, year 1997Mean (1997) 2.12 57.0 20.3 10.4 0.92 0.063 32.5S.D. 0.10 0.13 0.52 0.39 0.01 0.001 1.19N 3 3 3 3 3 3 3Max 2.21 57.1 20.0 10.7 0.94 0.064 33.6Min 2.01 56.8 21.0 10.0 0.92 0.062 31.2

* Significant difference between 1997 and 1998 for the variety ‘Palaton’ at 95% confidence level.a Mean value used in case of replicates.b Data for ‘Ash in stem’ missing for location ‘TIPP’ year 1997, corresponding data for 1998 removed to make comparison between the years

possible.c Arithmetic mean and standard deviation is given for this property, however, in PLS modelling log transformation was used because of skewed

distribution.


Table 6PLS model overview: the explained variation (R2) and the predictedvariation (Q2) for the model and for the individual responses

Component no. R2 (cumulative) Q2 (cumulative)

1 0.278 0.2462 0.381 0.3293 0.469 0.3894 0.556 0.4625 0.586 0.4716 0.611 0.4747 0.63 0.476

Response Id.Ash [ASH] 0.916 0.837Yield [YIELD] 0 .524 0.34Log drainage [DRAIN] 0.583 0.475Kappa no. [KAPPA] 0.55 0.393Fibre length [FLW] 0.646 0.445Coarseness [COAR] 0.654 0.498Fines [FINA] 0.563 0.365

3.5. Significance of the coefficients

In Table 7, the coefficients of the seven-componentmodel are shown. The coefficients are scaled to makethem comparable. The significance of the coefficientsis derived from jack knifing, and the significance levelis chosen to 95%. Significant factors are marked withbold text and an asterisk (*).

Fig. 2. Variable importance, includ

3.6. Ash content of the stem

The response ‘Ash’ is significantly higher than av-erage when RCG is grown in Jokioinen, Svalof, andUmea. The variety JO01 and clay rich soils also givehigher ash content of the stem. Ash is significantlylower if the RCG is gown in Abeystwyth, Foulum,Rothamsted, or Sotkamo. Sand rich soil also signifi-cantly lowers the ash content of the grass. The growinglocations associated with high ash content of the RCGstem is not always correlated to high clay content ofthe soil. Other factors seem to influence the uptake ofsilica (the main ash component) in RCG. These factorscould be soil, pH, and water accessibility. The fact thatone variety of RCG (JO01) gave significantly higherash content indicates that plant breeding might be usedto control the silica uptake in the grass.

3.7. Pulp yield

Pulp yield mainly depends on the yearly variation.On average, year 1998 gave lower pulp yield than year1997. The slightly higher ash content in the materialcollected in 1998 might also contribute to the lowerpulp yield, because silica is removed with the cookingliquor. The location Dundee gives higher pulp yield,and the location Svalof gives lower pulp yield. Of the

ing the 95% confidence interval.


Fig. 3. (a) Scores scatter plot for component 1 and 2. The dots represent date from 1997 and the circles represent data from 1998. (b) PLSweights plot for component 1 and 2. The black triangles represent the variables and the grey dots represent the responses. Component 1 describes27.8% and component 2 describes 10.3% of the variation in the Y-matrix.


Table 7Coefficient list: scaled coefficients for the seven-component model

VARIABLE ID Ash Pulp yield Drainage Kappa no Fibre length Fibre coarseness Fines

YEAR (1997) −0.1 0.26* −0.18* −0.22* 0.093 −0.32* −0.028YEAR (1998) 0.1 −0.26* 0.18* 0.22* −0.093 0.32* 0.028LOC (ABER) −0.19* −0.045 0.055 0.15 −0.013 0.018 0.079LOC (BRAU) −0.077 0.067 −0.028 −0.12 −0.12* −9.1E-5 −0.031LOC (DUND) 0.093 0.11* −0.049 −0.1 0.049 0.11 0.028LOC (FOUL) −0.29* 0.074 −0.074 0.027 0.13* 0.035 −0.13*

LOC (JOKI) 0.33* 0.03 −0.058 −0.12 0.12* −0.032 −0.095*

LOC (ROTH) −0.21* −0.012 0.25* 0.00088 −0.27* −0.023 0.24*

LOC (SOTK) −0.21* 0.047 −0.16* 0.13* 0.26* −0.018 −0.18*

LOC (SVAL) 0.19* −0.1* −0.019 0.057 −0.0087 0.02 0.013LOC (TIPP) 0.026 −0.15 0.041 0.098 −0.093 −0.059 0.08LOC (UMEA) 0.36* 0.029 −0.096* −0.03 0.09 0.14 −0.056LOC (YLIS) 0.026 −0.075 0.13* −0.034 −0.088 −0.18* 0.052VAR (JO01) 0.15* 0.049 −0.04 −0.065 0.037 0.0069 −0.032VAR (LE01) −0.072 −0.0084 0.099 −0.059 −0.064 −0.068 0.039VAR (LE02) 0.08 −0.052 0.00023 0.12* −0.089 0.2* 0.087VAR (PALA) −0.096 0.049 −0.087 0.0051 0.14 −0.066 −0.1VAR (SW01) 0.0055 0.078* −0.07* −0.076 0.038 −0.0083 −0.04VAR (SW02) −0.023 −0.11 0.2* 0.12 −0.3* 0.11 0.28*

VAR (SW03) −0.0043 −0.018 −0.059* 0.016 0.03 0.0021 −0.059VAR (SW04) −0.032 −0.088 0.01 0.077 0.036 −0.0058 −0.035VAR (SW05) −0.018 0.081 −0.062 −0.061 0.17 −0.0039 −0.13VAR (SW06) −0.054 0.015 0.042 −0.063 −0.031 −0.057 0.019VAR (SW07) −0.0096 −0.1 0.058 0.11 −0.06 −0.082 0.088VAR (SW08) 0.048 0.061 −0.021 −0.16* 0.034 −0.073 −0.12VAR (SW09) 0.11 0.079 −0.023 −0.041 0.0066 0.071 0.036ORGANIC −0.0026 0.049 0.033 0.038 0.083 0.065 0.074CLAY 0.14* −0.065 0.11* 5.9e−005 −0.018 −0.1* 0.073SILT 0.061 −0.00049 −0.009 0.057* 0.081* −0.015 −0.033SAND −0.13* 0.038 −0.062* −0.064* −0.053* 0.045 −0.047GRAVEL 0.0095 −0.059 0.046 0.057 −0.1 0.057 0.16*

* Significant at 95% confidence level.

RCG varieties, only SW01 was found to have a signif-icant (positive) effect on pulp yield. None of the soilcomponents were found to have a significant effect onpulp yield.

3.8. Drainage resistance

Largely, drainage depends on yearly variation. Year1997 gave lower drainage resistance than year 1998.The locations Sotkamo and Umea and the varietiesSW01 and SW03 lower the drainage resistance, andthe locations Rothamsted and Ylistaro and the vari-eties SW02 significantly give higher drainage resis-tance. All four locations, however, have similar soiltype, ‘silt loam’, which indicates that uncontrollable

factors such as weather and water are important forthis property. Of the soil components, clay gives higherdrainage resistance, and sand gives lower drainageresistance.

3.9. Kappa number

The kappa number of the pulps depends on yearlyvariation. Year 1997 gave pulps with lower kappa num-ber than year 1998. This indicates that the samples col-lected in 1998 contained more lignin than the samplescollected in 1997. The cooking liquor removes lignin,and this could also explain the differences in pulp yield.The location Sotkamo, the variety LE02, and silt richsoil type gives significantly higher kappa number, while


the variety SW08 and sand rich soil types lower thekappa number.

3.10. Fibre properties

The fibre length of the pulp is higher if the grass isgrown in Foulum or Sotkamo and on silt rich soils. Thefibre length will be reduced if RCG is grown in Braun-schweig or Rothamsted and if the variety SW02 is used.A sand rich soil also lowers the fibre length. The fi-bre coarseness mainly depends on the yearly variation.Year 1997 gave lower fibre coarseness than year 1998.The location Ylistaro and a clay rich soil also lower thefibre coarseness. The variety LE02 gives higher fibrecoarseness. The amount of fines in the pulp is increasedif RCG is grown in Rothamsted, if the variety SW02 isused, or if grown in a gravel rich soil. The amount offines is reduced if RCG is grown in Foulum, Jokioinen,or Sotkamo. Because there is no clear connection be-tween growing location, soil type, and fibre properties,uncontrollable weather variables seem to be importantfor these properties.

In this study, the findings on the ash variation agreewith the results published byBurvall (1997). However,as published byStewart et al. (1997), it was not con-firmed that the location Jokioinen was unsuitable forRCG production. The variety ‘SW02’ was found ingeneral to give poor fibre properties. It should also bekept in mind that the PLS model presented in this in-v n oft . Them usedf utri-e thiss ea-s thes ctedb

4

notr thatd d too uredp tioni e in-

vestigated properties. This study only included 2 years(1997 and 1998), and it is not possible to tell if inclusionof additional years would have given larger variation.

Year 1997 gave on average higher pulp yield, lowerkappa number, better dewatering properties and longerfibres compared to year 1998. The ash content of theRCG was mainly dependent on the growing location.

This study, however, shows that if using the delayedharvesting method and if the grass is well fractionated(fractionation by hand in this case), then the variationin the measured properties is within reasonable limitsfrom an industrial point of view. If RCG is going to beused as raw material for short fibre pulp production, asubstantial reduction of the variation can be achievedby selecting varieties suitable to the climate and soilconditions at the growing location. A high dry matterstem yield, however, should be one of the most impor-tant factors when selecting a suitable RCG variety andgrowing location for short fibre production.

Acknowledgements

Financial support from the European Commission(Project AIR3-CT94-2465), Kempe Foundations, Stif-telsen Lantbruksforskning, and the Swedish Univer-sity of Agricultural Sciences (SLU) are gratefully ac-knowledged. Many thanks to Bjorn Hedman (SLU)for his skilled laboratory assistance and Paul Geladi(SLU) for his comments on the data analysis. A specialt ion’o awm

R

C , D.,ent,140.

B fuel

B non

E ,and

estigation only describes 55–65% of the variatiohe measured properties with the exception of ashodel for ash, however, was good and can be

or prediction. Factors such as weather, water, nnt availability, and soil pH were not considered intudy, and probably have a significant effect on the mured pulp properties; however, the ash content intem fraction of RCG seems to be relatively unaffey these factors.

. Conclusions

The dry matter yield and plant development areeported in this paper. In this study, RCG varietiesid develop poorly at some locations are includebtain a variation as large as possible in the measroperties. The study shows that the yearly varia

s the factor that has the greatest influence on th

hanks to the participants of ‘Task 1—Crop Productf the project AIR3-CT94-2465 for supplying the raterial.

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Variations in ash content, pulp yield, and fibre properties of reed canary-grass

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