ISSN 2320 -5083 Journal of International · Dr. Vijay Pithadia, Ph.D, Director - Sri Aurobindo Institute of Management Rajkot, India. Er. R. Bhuvanewari Devi M. Tech, MCIHT Highway

Journal of International Academic Research for Multidisciplinary

ISSN 2320 -5083

A Scholarly, Peer Reviewed, Monthly, Open Access, Online Research Journal

Impact Factor – 1.393

VOLUME 1 ISSUE 12 JANUARY 2014

A GLOBAL SOCIETY FOR MULTIDISCIPLINARY RESEARCH

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Editorial Board

Dr. Kari Jabbour, Ph.D Curriculum Developer, American College of Technology, Missouri, USA.

Er.Chandramohan, M.S System Specialist - OGP ABB Australia Pvt. Ltd., Australia.

Dr. S.K. Singh Chief Scientist Advanced Materials Technology Department Institute of Minerals & Materials Technology Bhubaneswar, India

Dr. Jake M. Laguador Director, Research and Statistics Center, Lyceum of the Philippines University, Philippines.

Prof. Dr. Sharath Babu, LLM Ph.D Dean. Faculty of Law, Karnatak University Dharwad, Karnataka, India

Dr.S.M Kadri, MBBS, MPH/ICHD, FFP Fellow, Public Health Foundation of India Epidemiologist Division of Epidemiology and Public Health, Kashmir, India

Dr.Bhumika Talwar, BDS Research Officer State Institute of Health & Family Welfare Jaipur, India

Dr. Tej Pratap Mall Ph.D Head, Postgraduate Department of Botany, Kisan P.G. College, Bahraich, India.

Dr. Arup Kanti Konar, Ph.D Associate Professor of Economics Achhruram, Memorial College, SKB University, Jhalda,Purulia, West Bengal. India

Dr. S.Raja Ph.D Research Associate, Madras Research Center of CMFR , Indian Council of Agricultural Research, Chennai, India

Dr. Vijay Pithadia, Ph.D, Director - Sri Aurobindo Institute of Management Rajkot, India.

Er. R. Bhuvanewari Devi M. Tech, MCIHT Highway Engineer, Infrastructure, Ramboll, Abu Dhabi, UAE Sanda Maican, Ph.D. Senior Researcher, Department of Ecology, Taxonomy and Nature Conservation Institute of Biology of the Romanian Academy, Bucharest, Romania Dr. Reynalda B. Garcia Professor, Graduate School & College of Education, Arts and Sciences Lyceum of the Philippines University Philippines Dr.Damarla Bala Venkata Ramana Senior Scientist Central Research Institute for Dryland Agriculture (CRIDA) Hyderabad, A.P, India PROF. Dr.S.V.Kshirsagar, M.B.B.S,M.S Head - Department of Anatomy, Bidar Institute of Medical Sciences, Karnataka, India. Dr Asifa Nazir, M.B.B.S, MD, Assistant Professor, Dept of Microbiology Government Medical College, Srinagar, India. Dr.AmitaPuri, Ph.D Officiating Principal Army Inst. Of Education New Delhi, India Dr. Shobana Nelasco Ph.D Associate Professor, Fellow of Indian Council of Social Science Research (On Deputation}, Department of Economics, Bharathidasan University, Trichirappalli. India M. Suresh Kumar, PHD Assistant Manager, Godrej Security Solution, India. Dr.T.Chandrasekarayya,Ph.D Assistant Professor, Dept Of Population Studies & Social Work, S.V.University, Tirupati, India.

JOURNAL OF INTERNATIONAL ACADEMIC RESEARCH FOR MULTIDISCIPLINARY Impact Factor 1.393, ISSN: 2320-5083, Volume 1, Issue 12, January 2014

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GENETIC ESTIMATES ON GROWTH AND WOOD TRAITS OF EUCALYPTUS GENETIC RESOURCES

DR.S.VENNILA*

DR. S.UMESH KANNA** DR. K.T.PARTHIBAN***

*Senior Research Fellow, Forest College & Research Institute, Mettupalayam, Tamil Nadu, India

**Assistant Professor, Forest College & Research Institute Tamil Nadu Agricultural University, Mettupalyam, Tamil Nadu, India *** Professor, Forest College & Research Institute Tamil Nadu Agricultural University, Mettupalyam, Tamil Nadu, India

ABSTRACT

Studies were carried out to elicit genetic estimates on Eucalyptus genetic resources

with respect to heritability, phenotypic correlation coefficient, genotypic correlation

coefficient and Genetic advance. The study indicated that the maximum heritability was

recorded by total height (81.23%) followed by volume (74.39%) and Dbh (72.09%) with

respect to growth attributes. With respect to physical properties bulk density registered

maximum heritability (98.59%). Acid insoluble lignin (97.97%) followed by pentosans

(96.35%) exhibited maximum heritability with respect to chemical properties. In the present

study, higher genotypic correlation coefficient than phenotypic correlation coefficient was

evidenced for the growth attributes, physical and chemical properties of all the eucalyptus

genetic resources. Positive and significant phenotypic (0.679) and genotypic correlation

(0.740) with unbleached pulp yield was registered for holocellulose. Path analysis revealed

that, total height (0.259), dbh (1.578), bulk density (0.573), one per cent NaOH solubility

(0.316), alcohol benzene extractives (0.151) and holocellulose (0.530) exhibited positive

direct effect, while basal diameter (0.777), volume (0.892), basic density (0.351), ash content

(0.221), hot water solubility (0.175), acid insoluble lignin (0.300) and pentosans (0.084)

showed negative direct effect on unbleached pulp yield.

KEYWORDS: Eucalyptus, Heritability, PCV, GCV, Phenotypic and Genotypic Correlation

INTRODUCTION

Improvement of Eucalyptus for traits of commercial importance is relatively recent

development and linked to the increasing establishment of plantations. The earlier studies on

breeding of Eucalyptus concentrated mostly on tree growth and development (Raymond,

2002). As the breeding programme progressed, the range of traits assessed also increased to

include wood properties and wood quality traits. However, limited work on assessing the

wood quality traits in breeding programme had been under taken till the recent past due to


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expensive procedures coupled with large wood sample requirements (Malan and Arbuthnot,

1995). But with the development of clonal forestry, large number of clones needs to be

screened for their suitability for pulp and paper manufacture. Hence the current study.

Wood properties are known to vary between species, between genotypes and within

species. This variability is heritable and can be utilized in breeding programmes to obtain

varieties with improved wood properties, thus enhancing end-product quality. The ability to

assess wood quality is a critical challenge facing the forest industry. In intensively managed

forests such as clonal Eucalyptus plantations where the raw material is highly heterogeneous

(Downes et al., 1997), it is important to be able to predict wood properties of whole trees.

Moreover, in breeding programs, selection is generally focused on a narrow genetic base, so

there is low between-tree variability in selected traits in contrast with the high within-species

variations that can occur. Predicting the technological properties of interest is a real challenge

in these conditions. Against this backdrop, study was designed and included pulp wood traits

in the improvement programme in order to screen the clones with superior wood quality traits.

Materials and Methods

Twenty plus trees of Eucalyptus species have been selected from the seed source trial

at Forest College and Research Institute, Mettupalayam and seven potential clones and one

seed source were used in the current study. The morphometric traits like total height, basal

diameter and dbh were actually measured. From these primary data, volume was calculated

using the formula (Πd2/4) h and expressed in m3. After record of growth traits, the candidate

trees were felled at a stump height of 15-20 cm using axe and two men cross-cut saw and the

wood samples were subjected to pulp analysis. The genetic estimates for the selected plus

trees and wood traits are furnished hereunder.

Variability studies

These parameters were estimated as per the method described by Johnson

et al. (1955).

a) Heritability

Heritability in the broad sense (h2) was calculated using the formula suggested by

Lush (1940); Hanson et al., (1956) and expressed in percentage.

h2 (broad sense) = (2g/ 2p) x 100


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b) Genetic advance

The genetic advance was worked after Johnson et al., (1955).

Genotypic Variance Genetic Advence (GA) = -------------------------- x K (Phenotypic variance)1/2

Where,

K = Selection differential (2.06) at 5% level of significance.

Genetic advance as percentage of mean

This was calculated using the formula;

GA GA as percentage over mean = ------------- x 100 X Where,

X = Grand mean

Correlation studies

Genotypic and Phenotypic correlations coefficients were calculated according to the

method suggested by Goulden (1952).

a) Genotypic correlation

Genotypic covariance between X & Y rg(XY) = ------------------------------------------------------------------------------- [Genotypic variance of (X) x Genotypic variance of (Y)]½

b) Phenotypic correlation

Phenotypic covariance between X & Y rp(XY) = -------------------------------------------------------------------------- [Phenotypic variance of (X) x Phenotypic variance of (Y)]½

The genetic estimates for biometric attributes were classified as detailed below.

Genetic parameter Low Moderate High

GCV and PCV <20 20-30 >30 Heritability <30 30-60 >60 GA as % of mean <30 30-60 >60

Path coefficient analysis

Path co-efficient analysis was estimated as suggested by Dewey and

Lu (1959) to study the direct and indirect effects.


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Result and Discussion

Variability studies

The present study revealed that significant amount of variability existed among different

Eucalyptus species in growth and wood characters investigated viz., total height, basal

diameter, DBH, volume, basic density, bulk density, ash content, hot water solubility, one per

cent NaOH solubility, alcohol benzene extractives, acid insoluble lignin, pentosans,

holocellulose and pulp yield. The heritability values were high with only marginal difference.

To understand the causes of variation, apportioning of total phenotypic variance has more

utility. The genetic variance which is heritable could be exploited for future utility. In the

current study, volume recorded highest phenotypic and genotypic variance in different

identified and selected Eucalyptus plus trees. The traits total height, basal diameter and DBH

expressed moderate phenotypic and genotypic variances. Similar reports on high PCV and

GCV for volume, height and DBH was observed in Eucalyptus globulus (Paramathma and

Surendran, 1999); E. grandis (Pugazhendi et al., 1999; Jude Sudhagar, 1999); Eucalyptus

species (Balaji et al., 1999; Gokul et al., 1999); Madhuca latifolia (George Jenner et al.,

1999); Casuarina equisetifolia (Mohan Varghese et al., 1999; Maheshwar Hegde et al., 1999)

and also in teak (Arun Prasad, 1996, Parthiban, 2001). In the present study, the information

obtained from the clones of Eucalyptus showed that the phenotypic variance (Table 3) this

indicates that the traits were influenced by non-additive gene action.

Among the morphometric traits, highest heritability was recorded by height (81.23)

followed by volume (74.39), DBH (72.09) and basal diameter (62.68)

suggesting the role of additive gene action in the expression of these characters and could be

considered as reliable indices for selection. Similarly, high heritability estimates for volume

was earlier reported in Eucalyptus progeny trials (Balaji, 2000) and Rao et al. (2001) in C.

equisetifolia also reported high heritability for girth at breast height followed by girth at

ground level. Jambulingam (1990) observed consistency in heritability and genetic gain for

volume over growth stages in C. equisetifolia. Similarly, high heritability and genetic

advance were reported for height in Bambusa balcooa at early stages of growth (Singh and

Beniwal, 1993). Antony Joseph Raj (1999) and Satheesh (2000) recorded high heritability

for growth traits in Bambusa bambos and Dendrocalamus strictus, respectively.

High heritability coupled with higher genetic advance as percentage over mean indicates

predominance of additive gene action (Paramathma et al.,1997). In the present study, such

phenomenon was observed for plant height which recorded highest values for heritability and


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genetic advance as percentage. Hence, selection based on this character will be advantageous

for yield improvement and future breeding programme in Eucalyptus clones.

Among the wood traits investigated, high heritability estimates for bulk density (98.59 %),

acid insoluble lignin (97.97 %), pentosans (96.35 %), basic density (94.62 %), holocellulose

(93.57 %), alcohol benzene extractives (90.42 %), ash content (89.53 %), unbleached pulp

yield (89.02 %) and one per cent NaOH solubility (86.63 %) were obtained. Heritability

values for wood property traits were generally higher than that for growth traits, indicating

that wood properties are under stronger additive genetic control than growth. However,

average additive genetic coefficients of variation for wood properties were relatively small

suggesting that response to selection in these traits may be limited, due to relatively low

additive genetic variation, despite their high heritabilities (Houle, 1992). The DBH in

Eucalyptus tereticornis is under genetic control was earlier demonstrated (Otegbeye, 1991).

Considering the existence of reasonable variability and fairly good genetic influence of these

characters, selection of trees based on pulp yield which incorporates these variables would

pay rich dividends. Similar studies were conducted in two different locations viz.,

Sathyamangalam and Gudalur in Eucalyptus grandis and the results indicated that high

heritability values for height, DBH, merchantable height, basic density, total extractives,

pentosans, lignin and cellulose. The genetic control of the chemical composition of wood has

not been studied as intensively as that of specific gravity or any other anatomical property of

wood. Lignin, cellulose and extractive contents included for study of inheritance (Zobel,

1971). The exhibition of higher PCV and GCV for height, DBH and merchantable height

whereas low to moderate PCV and GCV for basic density, total extractives, pentosans, lignin

and cellulose in the present study is in conformity with the above assertions. Pugazhendi

(1994) and Rajasekar (1994) also reported similar results in Eucalyptus species which thus

attests the findings of current investigation.

Correlation studies

The correlation study was employed using the data collected from the plus trees to

throw light on the association of traits for pulp yield components. This correlation studies

will also provide information about the relatedness of association in the parental population

to that of the progenies viz., clonal population performance. The phenotypic correlations

indicate the presence of relationships between traits that may be due to a similar response to

environmental conditions or to genetic associations. Genetic correlations are important for

determining the potential for concurrent or independent selection of traits.


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The knowledge of the interrelationship existing among different growth, form and wood

attributes is of crucial value to the tree breeder. If these were not known to the breeder,

selection for one trait may cause an inadvertent change in the other (Zobel and Van

Buijtenen, 1989). Some wood property traits are related but many are not (Zobel, 1971). In

the current study, the magnitude of genotypic correlation coefficients between all growth and

wood traits studied were found to be higher than the corresponding phenotypic correlation

coefficients. In phenotypic and genotypic correlation coefficient, unbleached pulp yield

showed a positive correlation with plant height, basal diameter, DBH and volume which are

obviously the contributing characters to unbleached pulp yield (Tables 2 and 3). Arbuthnot

(1991) stated that wood density was highly correlated with a number of pulp properties and

paper parameters. In the present study, basic density had positive phenotypic and genotypic

correlation coefficient with bulk density, ash content, holocellulose and unbleached pulp

yield and negative correlation with hot water solubility, one per cent NaOH solubility,

alcohol benzene extractives, acid insoluble lignin and pentosans (Tables 24 and 25). Negative

genetic correlations between growth and wood density have been reported in several genera

like Pinus (Squilance et al., 1962; Van Buijtenen, 1963; Stonecypher and Zobal, 1966; Dorn,

1969; Shelbourne et al., 1972; Sohn and Goddard, 1974; Nicholls et al., 1980); Douglas- Fir

(Mckimmi and Campbell, 1982); Populus trichocarpa (Reck, 1974) and Eucalyptus

camaldulensis (Siddiqui et al., 1979).

Correlations amongst the chemical wood traits were often strong and as expected in

terms of kraft pulping properties (Smook, 1992). A high pulp yield and cellulose content was

associated with low extractives and lignin contents both at the phenotypic and genotypic

levels. This was consistent with the phenotypic correlations reported by Wallis et al. (1996)

for eleven individuals of E. globulus. Miranda and Pereira (2001) examined thirty seven

provenances of E. globulus and reported a similar correlation between pulp yield and

extractives content at the provenance level, but not with total lignin content. Lignin and

extractives contents were generally positively correlated and Ona et al. (1998) found similar

relationships in a within-tree study of two E. globulus individuals. In E. nitens, Kube and

Raymond (2001) reported a very high negative genetic correlation between extractives and

cellulose contents. These studies collectively suggest that selection for increased pulp yield or

cellulose content are likely to result in a reduction in lignin and extractives contents, which

are favourable responses for a pulpwood breeding objective.


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The correlated effect of lignin on wood density is interesting as density is one of the

main selection traits in the Eucalyptus breeding programme. Basic density was negatively

correlated with lignin content. However, a negative genetic correlation has also been found

between density and lignin content in Pinus pinaster (Pot et al., 2002). It is therefore likely

that favourable lignin profiles are being indirectly selected along with high basic density.

Similar to other studies in E. globulus (Ona et al., 1998; Miranda and Pereira, 2001) no

apparent relationship was found between basic density and extractives content, although there

are reports of positive associations in both E. globulus (Washusen et al., 2001) and E. nitens

(Kube and Raymond, 2001).

In the present study, cellulose yield had positive correlation with total height, basal diameter,

DBH, volume, basic density, bulk density and one per cent NaOH extractives whereas

negative correlation with ash content, hot water solubility, alcohol benzene extractives, acid

insoluble lignin and pentosans. However, the strength and direction of the genetic correlation

between pulp yield or cellulose content with growth was not clear due to the low number and

highly variable nature of independent estimates. More robust estimates of correlation among

these key pulpwood traits (Borralho et al., 1993; Greaves et al., 1997) are required if the

economic worth of genetic gains made through index selection are to be maximized in

pulpwood breeding programmes (Ponzoni and Newman, 1989); Schneeberger et al., 1992).

Path coefficients for growth and wood traits

The path analysis permits the separation of direct effects from indirect effects through

other related traits by partitioning the genotypic correlation coefficients (Dewey and Lu,

1959). The maximum positive direct effect was exerted by DBH (1.578) on unbleached pulp

yield followed by bulk density (0.573), holocellulose (0.530), one per cent NaOH solubility

(0.316), total height (0.259) and alcohol benzene extractives (0.151) (Table 4). The present

investigation envisaged that high and positive association coupled with intensive direct effect

of DBH on unbleached pulp yield indicated that the DBH could be the selection criterion in

Eucalyptus improvement programmes and also for utilization in the industrial wood

plantation programmes.

From a comprehensive perspective, total height, DBH and holocellulose contents were

contributing directly to cellulose yield per tree or unbleached pulp yield. The DBH exercised

its influence indirectly the available reports relate to path analysis of growth traits (Rathinam

et al., 1981; Surendran, 1982) and not chemical wood attributes. Therefore the growth


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attributes viz., total height, basal diameter, DBH and wood quality traits viz., unbleached

pulp yield may be considered important in the improvement in pulp yield per tree.

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51. Van Buijtenen, J.P. 1963. Heritability estimates of wood properties and their relation to growth rate in Pinus taeda. 1st World Council For. Gen. Tree. Improv., Stockholm, Sweden, 13pp.

52. Wallis A.F.A., R.H. Wearne and P.J. Wright. 1996. Analytical characteristics of plantation eucalypt woods relating to kraft pulp yields. Appita J., 49: 427-432.

53. Washusen, R., P. Ades, R. Evans and P. Vinden. 2001. Relationships between density, shrinkage, extractives content and microfibril angle in tension wood from three provenances of 10-year-old Eucalyptus globulus Labill. Holzforschung, 55: 176-182.

54. Zobel, B.J. 1971. The genetic improvement of Southern pines. Sci. Amer., 225: 94-103. 55. Zobel, B.J. and J.P. van Buijtenen. 1989. Wood variation its causes and control. Timell, T.E. (ed.).

Springer Series in Wood Science, Springer-Verlag, Berlin. 363 p.

Table 1. Genetic parameters of growth and wood traits

Characters GCV (%)

PCV (%)

Heritability (%)

GA (%) of mean

Total height 14.46 16.04 81.23 26.84 Basal diameter 14.60 18.43 62.68 23.79 DBH 15.83 18.64 72.09 27.68 Volume 39.02 45.24 74.39 69.33 Basic density 8.42 8.66 94.62 16.88 Bulk density 6.23 6.28 98.59 12.75 Ash content 24.49 25.88 89.53 47.73 Hot water solubility 11.75 13.06 80.93 21.77 One cent NaOH solubility 6.17 6.63 86.63 11.83 Alcohol benzene extractives 27.73 29.17 90.42 54.33 Acid insoluble lignin 5.79 5.85 97.97 11.80 Pentosans 10.01 10.12 96.35 20.24 Holocellulose 2.37 2.45 93.57 4.73 Unbleached pulp yield 4.05 4.29 89.02 7.86


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Table 2. Genotypic correlation coefficient of growth and wood traits

Characters Total height

Basal diameter

DBH Volume Basic

density Bulk

density Ash

content Hot water solubility

One per cent

NaOH solubility

Alcohol benzene

extractive

Acid insoluble

lignin Pentosans

Holo-cellulose

Unblea ched pulp

yield

Total height 1.000 0.585** 0.473** 0.663** -0.339 0.038 -0.256 0.456** 0.213 0.381* 0.412* 0.343* 0.038 0.068 Basal diameter 1.000 0.964** 0.983** 0.124 0.110 -0.330 -0.139 0.210 0.204 0.063 -0.098 0.234 0.345* DBH 1.000 0.966** 0.010 -0.042 -0.245 -0.146 0.108 0.154 0.047 -0.082 0.086 0.237 Volume 1.000 -0.130 -0.075 -0.301 0.015 0.218 0.215 0.169 0.058 0.088 0.198 Basic density 1.000 0.595** 0.021 -0.564 -0.325 -0.331 -0.673 -0.456 0.270 0.264 Bulk density 1.000 -0.159 -0.249 -0.290 -0.391 -0.433 -0.272 0.315* 0.538** Ash content 1.000 0.246 0.109 0.198 -0.073 0.010 -0.457 -0.448

Hot water solubility

1.000 0.245 0.556** 0.585** 0.553** -0.293 -0.410

One per cent NaOH solubility

1.000 0.081 0.219 0.231 0.051 0.018

Alcohol benzene extractives

1.000 0.573** 0.325* -0.517 -0.556

Acid insoluble lignin

1.000 0.553** -0.377 -0.509

Pentosans 1.000 -0.407 -0.456 Holocellulose 1.000 0.740** Unbleached pulp yield

1.000


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Table 3. Phenotypic correlation coefficient of growth and wood traits


Basal diameter

DBH Volume Basic

density Bulk

density Ash

content

Hot water

solubility

One per cent

NaOH solubility

Alcohol benzene

extractives

Acid insoluble

lignin Pentosans

Holo-cellulose

Unbleached pulp yield

Total height 1.000 0.478** 0.392* 0.606** -0.295 0.045 -0.234 0.333* 0.171 0.291 0.377* 0.283 0.090 0.067

Basal diameter

1.000 0.780** 0.784** 0.082 0.099 -0.310 -0.099 0.138 0.110 0.052 -0.122 0.208 0.220

DBH 1.000 0.951** 0.005 -0.027 -0.242 -0.136 0.135 0.117 0.043 -0.076 0.108 0.214 Volume 1.000 -0.109 -0.054 -0.300 -0.014 0.220 0.161 0.146 0.041 0.135 0.190 Basic density 1.000 0.573** 0.018 -0.498 -0.287 -0.309 -0.650 -0.441 0.267 0.250 Bulk density 1.000 -0.153 -0.221 -0.268 -0.368 -0.422 -0.262 0.306 0.506** Ash content 1.000 0.240 0.054 0.190 -0.058 0.011 -0.428 -0.400 Hot water Solubility

1.000 0.192 0.454** 0.527** 0.503** -0.266 -0.340

One per cent NaOH Solubility

1.000 0.062 0.203 0.217 0.054 0.013


1.000 0.540** 0.319* -0.494 -0.489


1.000 0.539** -0.359 -0.473

Pentosans 1.000 -0.400 -0.411Holocellulose 1.000 0.679** Unbleached pulp yield

1.000


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Table 4. Path coefficient analysis for growth and wood traits Vs unbleached pulp yield


Basal diameter DBH Volume

Basic density

Bulk density

Ash content

Hot water

solubility

One per cent

NaOH solubility

Alcohol benzene

extractives

Acid insoluble

lignin Pentosans Holocellulose

Total height 0.259 -0.455 0.747 -0.592 0.119 0.022 0.057 -0.080 0.067 0.057 -0.124 -0.029 0.020 Basal diameter 0.151 -0.777 1.521 -0.877 -0.043 0.063 0.072 0.024 0.066 0.031 -0.019 0.008 0.124DBH 0.122 -0.749 1.578 -0.862 -0.004 -0.024 0.054 0.026 0.034 0.023 -0.014 0.007 0.046 Volume 0.171 -0.764 1.524 -0.892 0.046 -0.043 0.066 -0.003 0.069 0.033 -0.051 -0.005 0.047 Basic density -0.087 -0.096 0.016 0.116 -0.351 0.341 -0.005 0.099 -0.103 -0.050 0.202 0.038 0.143Bulk density 0.010 -0.086 -0.066 0.067 -0.209 0.573 0.035 0.044 -0.092 -0.059 0.130 0.023 0.167 Ash content -0.066 0.256 -0.386 0.268 -0.007 -0.091 -0.221 -0.043 0.034 0.030 0.022 -0.001 -0.242 Hot water solubility

0.118 0.108 -0.231 -0.014 0.198 -0.143 -0.054 -0.175 0.077 0.084 -0.176 -0.047 -0.156

One per cent NaOH solubility

0.055 -0.163 0.171 -0.195 0.114 -0.166 -0.024 -0.043 0.316 0.012 -0.066 -0.019 0.027


0.098 -0.158 0.243 -0.192 0.116 -0.224 -0.044 -0.098 0.026 0.151 -0.172 -0.027 -0.274


0.106 -0.049 0.074 -0.150 0.236 -0.248 0.016 -0.103 0.069 0.086 -0.300 -0.047 -0.200

Pentosans 0.089 0.076 -0.130 -0.052 0.160 -0.156 -0.002 -0.097 0.073 0.049 -0.166 -0.084 -0.216 Holocellulose 0. 010 -0.182 0.136 -0.078 -0.095 0.181 0.101 0.051 0.016 -0.078 0.113 0.034 0.530

Residual effects = 0.4020 (Diagonal values are direct effect)

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ISSN 2320 -5083 Journal of International · Dr. Vijay Pithadia, Ph.D, Director - Sri Aurobindo Institute of Management Rajkot, India. Er. R. Bhuvanewari Devi M. Tech, MCIHT Highway