Indian Journal of Fibre & Textile Research
Vol. 39, March 2014, pp. 14-23
Stochastic analysis of major physical properties of coconut fibre
S Sengupta1,a, G Basu1, R Chakraborty1 & C J Thampi2
1
National Institute of Research on Jute and Allied Fibre Technology, 12 Regent Park, Kolkata 700 040, India
2
T. M. Natural Resource Research & Development Centre, Thiruvananthapuram 695 583, India
Received 15 January 2013; revised received and accepted 6 May 2013
Distribution profile and inter-relation of major dimensional and mechanical property parameters of raw coconut fibre
have been studied with the help of computerized statistical tool. Relations among the properties are evaluated using the bestfit transformation functions calculated through correlation coefficient. Four different types of defects have been identified
and analyzed. All the properties are found to be asymmetric in nature and positively skewed. Diameter of a fibre varies
along its length with tapering shape at both the ends. Three physical characteristics, namely length, diameter and linear
density, are positively correlated among themselves and also with breaking load. They are negatively correlated with
specific work of rupture in exponential manner. Flexural rigidity is positively correlated with diameter and linear density.
No correlation has been observed for tenacity and elongation of fibre with length, diameter and linear density. Evaluation of
length and diameter would be sufficient for quicker mode approximate assessment of quality (grading) for commercial grade
coconut fibre lot.
Keywords: Coconut fibre, Distribution profile, Physical properties, Statistical analysis
1 Introduction
Coconut trees are grown in tropical countries like
India, Sri Lanka, Myanmar, Thailand, Malaysia,
Indonesia, Philippines, Fiji, etc. mainly for the high
oil content of the endosperm (copra), which is widely
used in both food and non-food industries, e.g. edible
oil, margarine and soaps. The coconut husk is
extracted after removal of nut. The fibrous material
contained in the husk is used for manufacturing of
household ropes and other coir based products like
mattresses, carpets, mats, brushes, sacking, etc.
Brown fibre is harvested from fully ripened coconut.
Internal consumption and export of such sustainable
material as coconut fibre and pith is increasing at a
substantial rate for the last several years1. Mature
brown fibres contain more lignin and less cellulose
and so are stronger but less flexible. White fibres are
harvested from the coconuts before they are fully
ripened2. The fibre is separated from the husk by
mechanical, chemical, and biological methods3, where
the mechanical extraction is a common practice,
although fibre quality and fibre loss are affected
significantly4. Some major plus points about coconut
fibre are that it is agro based, secondary crop,
annually renewable, biodegradable and available at a
——————
a
Corresponding author.
E-mail: [email protected]
low cost. Coconut fibre does not loose strength on
storage and on exposure to sunlight. In spite of having
a number of favourable properties, the fibre is being
used for producing household goods at manually
operated traditional machines at rural and
unorganized sector for decades; potentiality of the
eco-sustainable fibre has still not been properly
explored for making high performance and/or valueadded products.
Some discreet information5-7 has also been reported
on properties of coconut fibre. But the analysis
of the basic physical properties of coconut fibre is
scanty. Reports on variability of the property
parameters of some other natural fibres are available
recently8-11. For the qualitative segregation of coconut
fibre with the aim for designing the machines and
processing to produce high performance products,
it is essential to know the properties of fibre and its
inter-relation.
So, in the present study, an exhaustive effort has
been made to understand the distribution behavior and
variability of some of the major dimensional
properties (viz., length, diameter, linear density),
and mechanical behaviour (viz., breaking tenacity,
breaking extension, specific work of rupture, flexural
rigidity) of the coconut fibre. An attempt has also
been made to understand the inter-relation between
SENGUPTA et al.: STOCHASTIC ANALYSIS OF MAJOR PHYSICAL PROPERTIES OF COCONUT FIBRE
different properties of the coconut fibre. Naturally
occurring defects in coconut fibre have also been
identified and analysed. The reported work is a step
forward for evolution of quality-cum-commercial
grading system for coconut fibre.
2 Materials and Methods
15
Specific flexural rigidity, mN-mm²/tex²
= (0.0047WL² × cos θ/tan θ)/(linear density of
fibre in tex)² × 104
where W is the suspended load in mN; L, the
perimeter of the ring; θ= 493 × d/L; and d, the
deflection of the bottom of the ring loop under the
action of the load.
2.1 Materials
Unretted (raw) brown coconut fibres (Cocos
nucifera) from 14 different locations of Tamil Nadu
and Kerala states of India were collected for the
study.
2.2 Methods
2.2.1 Sampling Process
Raw fibre of 1 kg was collected from each of
14 locations by random sampling method. Then it was
mixed well. A representative sample of 50 g was
collected from the fibre-mix. From this, fibres were
collected at random for the testing. These fibres were
put into a desiccator for 48 h at 65% relative humidity
and at 27°C for conditioning before estimation of
properties.
2.2.2 Measurement of Length, Diameter and Linear Density
Fibres were mounted on the board with cellotape
separately and straightened. Length of each fibre was
measured using a travelling microscope. Diameter of
fibres was measured using a projection microscope
with ×30 magnification. The fineness of fibres
was measured by standard gravimetric method taking
10 mm cut lengths. The fineness of fibre has been
expressed in terms of linear density12.
2.2.3 Measurement of Mechanical Properties
The tensile property of coconut single fibre was
tested on Instron-5567 tensile tester. The test length
and strain rate were maintained at 20 mm and
20 mm/min respectively. Strength of the fibre
is expressed by breaking tenacity (cN/tex) and
calculated by the ratio of maximum load (cN) to
the linear density (tex) of that fibre.
Flexural rigidity was measured by the ring-loop
method13. A mandrel was used for the preparation of
fibre rings of 3.121 cm diameter. The fibre ring was
supported on a hook and diameter was measured.
Now, a specific weight of 0.01 g/tex was suspended
on the fibre ring to give a deflection. The loading
time of 60 s was allowed and the new position of the
ring was determined. Specific flexural rigidity was
expressed as follows:
2.2.4 Measurement of Defects
To identify different natural defects in the coconut
fibre, 100 g each from 14 samples was collected. Each
sample was hand-opened and individualized to find
out the defects present into the fibre. For this, an
optical microscope of ×20 magnification was used.
The quantity of each defect was expressed in per cent
based on the weight of fibre.
3 Results and Discussion
3.1 Distribution of Different Properties of Coconut Fibre
Table 1 summarizes the statistical distribution data,
viz. extreme values, mean, median, mode, coefficient
of variation (CV), skewness, standard error of
skewness, kurtosis and standard error of kurtosis, of
property parameters of coconut fibre. It is clear from
the table that all the physical properties have high
variation. Majority of the fibres are lying in the range
of 4 - 12 cm length, 100 - 200 micron diameter and
10 - 20 tex linear density. This is mainly attributed
to their natural inheritance. In coconut fibre, this
variability is much higher due to poor extraction
process and unorganized collection which mixes
fibres of different maturity and varieties. To test the
normality of all the characteristics, its skewness and
kurtosis were evaluated. All the properties were
shown to have skewed asymmetric curve. Similarly,
kurtosis values, which are not zero, indicate that none
of the characteristics follow normal distribution;
either it is leptokurtic (positive value) or platykurtic
(negative value). The distribution curves are shown in
Fig. 1. Since it is evident that all the characteristics
are asymmetric in nature, Kolmogorov-Smirnov
(K-S) goodness-of-fit test14,15 is applied at a
significance level α ≥ 0.5 to ascertain the best-fit
curve, where highest K-S probability value represents
the best asymmetric curve. Table 2 shows the K-S
distribution and K-S probability values of fibre
length for different probability density functions.
The highest K-S probability value of 0.199 for
Weibull function indicates the best-fit function
for that property. All other properties of coconut
INDIAN J. FIBRE TEXT. RES., MARCH 2014
16
Table 1 — Property parameters of various physical characteristics of coconut fibre
Characteristics
Length, cm
Diameter, micron
Linear density, tex
Breaking tenacity
cN/tex
Breaking
extension, %
Specific work of
rupture, mJ/tex-m
Flexural rigidity,
mN-mm²
Specific flexural
rigidity×104,
mN-mm²
Sample
size
Minimum Maximum Mean Median Mode Coefficient Skewness Standard error Kurtosis Standard error
of
of skewness
of kurtosis
for normal
for normal
variation
distribution
distribution
102
102
102
62
3.80
83.30
4.60
3.85
26.4
550.0
140.0
47.1
14.08
244.60
36.80
14.10
12.9
5.8
200.0 166.6
25.2 Multiple
11.8 10.3
50.9
52.9
80.4
47.3
0.221
0.818
0.993
1.650
0.239
0.233
0.230
0.300
-1.328
-0.445
0.050
3.120
0.473
0.463
0.469
0.610
62
7.70
51.6
28.20 28.3 Multiple
37.5
0.190
0.310
-0.660
0.600
62
7.10
172.4
57.60 51.3 Multiple
56.6
0.920
0.310
0.990
0.600
33
36.80
2084.3
811.40 864.1 1121.4
69.7
0.680
0.420
-0.080
0.820
34
500.30
15343.6 3524.00 2554.5 Multiple
94.3
2.580
0.400
7.100
0.780
Fig. 1 — Distribution profile of coconut fibre (a) length, (b) diameter, (c) linear density, (d) Tenacity, (e) breaking elongation, (f)
specific work of rupture, (g) flexural rigidity, and (h) specific flexural rigidity
SENGUPTA et al.: STOCHASTIC ANALYSIS OF MAJOR PHYSICAL PROPERTIES OF COCONUT FIBRE
Table 2—Estimation of goodness of fit of different distribution
curves for fibre length of coconut fibre
Probability density
function
K-S da
Weibull
0.1012
0.1081
Extreme
0.1168
Rayleigh
0.1192
Lognormal
0.2
Exponential
Gamma
0.102
a
Kolmogorov-Smirnov distribution.
b
Kolmogorov-Smirnov probability.
K-S pb
0.199
0.145
0.094
0.083
<0.05
<0.05
Table 3— Best fit probability density function for different fibre
properties of coconut fibre
Property parameter
Length
Diameter
Linear density
Breaking strength
Breaking extension
Specific work of rupture
Flexural rigidity
Best fit probability
density function
Weibull
Extreme
Lognormal
Extreme
Weibull
Weibull
Extreme
K-S p
0.199
0.124
0.337
0.996
0.972
0.905
0.983
fibre were tested likewise and the best-fit function of
different properties along with its K-S probability
value are listed in Table 3.
This work deals with variation in different physical
properties within a lot of coconut fibres randomly
selected from mixture of fibres taken from a specified
agro-ecological region in India. Natural fibres
inherently differ from each other to a great extent.
Information on average values of various property
parameters and variability of each property
parameters is essential to a processor to identify or
to design processing machines to convert the fibre
to value-added products. For any industrially
processable fibre crop, an evenly distributed property
parameter is most desirable to the processor. The
results (Table 1) show that all the major property
parameters of coconut fibre are highly variable and
follows asymmetric distribution curve. It indicates the
chance of coming out with highly variable textile
products from processing machines inspite of taking
all the possible measures to produce regular threadlike materials (twines and cordages) and any finer
sheet-like materials. High variability in fibre length
(Fig. 1) causes high hairiness protruded from
thread surface. It becomes difficult to engineer
finer materials if the diameter is highly variable.
17
High variability in diameter and linear density
indicates that coconut fibre may be used in making
much coarser materials like house-hold ropes and
cordages. However, length-wise segregation of fibre
would solve the problem to a considerable extent.
Considering the asymmetric distribution [Fig 1(a)],
the fibres may be segregated in following three major
length-groups, namely (i) long, (ii) medium, and
(iii) short. Figures reveal that number of medium
length fibre is substantially higher than short followed
by long fibres. The distribution of diameter as well as
linear density values also shows nearly similar trend.
In this case, number of coarse fibre is substantially
higher than medium followed by fine fibres. So, the
fibre mix may also be sorted by diameter or linear
density [Figs 1(b) and (c)]. Due to differences
in linear densities, segregation may be done
by centrifugation or winnowing the fibre mix. The
segregated fibres may be used for producing three
different groups of materials. Long and coarse fibres
may be used for producing conventional ropes and
coarse mats, while medium length and fine fibre may
be used for making finer textiles materials with
improved property parameters, either elementarily or
in blends with other fibres. Short fibres may be used
in making flexible or semi-rigid composites and also
used as geofibre16 for soil stabilization.
It may be worth noting that distribution of
mechanical property parameters (viz., breaking
tenacity and elongation) are much less asymmetric
[Figs. 1(d) & (e)] as compared to the dimensional
property parameters. The coefficient of variation of
breaking tenacity (47.3%) and breaking extension
(37.5%) is lower than the CV of length (50.9%) and
diameter (52.9%). Specific flexural rigidity values
were highly asymmetric with CV, 94.3% [Fig 1(h)].
The increased coefficient variation, in this case, may
be attributed to the combination of the two highly
variable physical parameters, flexural rigidity and
linear density. The problem has been further
aggravated due to variation in diameter along the
length of individual fibre.
3.2 Diameter Distribution along the Fibre Length
Figure 2 shows variation in fibre diameter along
the fibre length. Sixty fibres were selected randomly
and divided into three equal parts as fine, medium,
coarse according to its linear density. Diameter of all
the fibres were measured from base to tip in 1 cm
interval. The diameter of different fibres gradually
18
INDIAN J. FIBRE TEXT. RES., MARCH 2014
Fig. 2 — Variation in fibre diameter along the fibre length
(root-to tip direction) (a) coarse fibre (62 tex), (b) medium fibre
(25 tex) and (c) fine fibre (9.5 tex)
increases from base to a mid-point, and then starts
decreasing till the tip ends. The diameter of coarse
fibre changes from 493 micron to 263 micron having
the highest diameter at 550 micron with the
coefficient of variation of 21.2%. The diameter of fine
fibre changes from 93 micron to 91 micron having the
highest diameter of 187 micron with the coefficient of
variation of 25.6%. This may be one of the major
reasons for high coefficient of variation of different
fibre properties. Figure 2 reveals that individual fibre
possesses variable diameter along its length tapering
off at both the ends.
3.3 Inter-relation between two Fibre Properties
Among the fibre properties studied, length,
diameter and linear density can be studied easily.
A rough estimation of these parameters can be
done without any sophisticated instrument. A simple
stainless steel scale graduated in ten divisions of
a centimeter and an ordinary magnifying glass may
be used to measure length and diameter, whereas a
simple weighing balance may be used to get linear
density. Therefore, it has been tried to understand
the relationship (Table 4 and Figs 3-5) between
these three parameters individually with other fibre
properties so that those properties can be predicted
from these three primary parameters. The properties
which are poorly correlated and insignificant with
fibre length are not shown graphically.
Length is the most important primary parameter
to judge fibre quality. This study shows a good
correlation of fibre length with diameter (0.759),
linear density (0.799), braking load (0.834) and
specific work of rupture (0.743), out of which
first three are positively correlated, whereas specific
work of rupture is negatively correlated i.e with
increase of length it decreases. The significance
of these relations have also shown by student
t-test (significance level α ≥ 0.5) and corresponding
p value. Tenacity, breaking extension, flexural rigidity
and specific flexural rigidity are poorly correlated
with length and this is supported by the t-test and
p-values. Table 4 shows the best fit equations for
each relation. Diameter, linear density and braking
load follow the second order polynomial, whereas
specific work of rupture follows exponential curve.
Figures 3(a)-(d) show the effect of fiber length on
diameter, linear density, braking load and specific
work of rupture of fibres.
Diameter is another important primary parameter
for fibre quality assessment. This study shows a good
correlation of fibre diameter with length (0.799),
linear density (0.893), braking load (0.785), specific
work of rupture (0.826) and flexural rigidity (0.764)
out of which first three are positively correlated.
The significance of these relations is also shown
by student t-test (significance level α ≥ 0.5) and
corresponding p-value. Tenacity, breaking extension
and specific flexural rigidity are poorly correlated
with diameter and this is supported by the t-test and
p-values. Table 4 shows the best fit equations for each
relation. Diameter is related with linear density by
linear equation and load by second order polynomial,
whereas other properties exponentially. Figures 3(a)
and 4(a) - (d) show the effect of diameter on length,
linear density, breaking load, specific work of rupture
and flexural rigidity of fibres.
Linear density is an important primary fibre quality
for processability point of view. This study shows a
good correlation of linear density with length (0.799),
breaking load (0.804), specific work of rupture
(0.934) and flexural rigidity (0.739), out of which
length, braking load and flexural rigidity are
positively correlated i.e with increase of linear density
other parameters increases, whereas specific work of
rupture is negatively correlated i.e with increase of
linear density it decreases. The significance of these
relations is also shown by student t-test (significance
level α ≥ 0.5) and corresponding p-value. Tenacity,
breaking extension, and specific flexural rigidity are
poorly correlated with linear density and this is
supported by the t-test and p-values. Table 4 shows
the best fit equations for each relation. Diameter and
braking load follow the second order polynomial
SENGUPTA et al.: STOCHASTIC ANALYSIS OF MAJOR PHYSICAL PROPERTIES OF COCONUT FIBRE
Variable X
Variable Y
Length
Length
Length
Length
Length
Length
Diameter
Linear density
Breaking tenacity
Breaking load
Breaking extension
Specific work of
rupture
Length
Flexural rigidity
Length
Specific flexural
rigidity
Diameter
Linear density
Diameter
Breaking load
Diameter
Breaking tenacity
Diameter
Breaking extension
Diameter
Specific work of
rupture
Diameter
Flexural rigidity
Diameter
Specific flexural
rigidity
Linear density Breaking tenacity
Linear density Breaking load
Linear density Breaking extension
Linear density Specific work of
rupture
Linear density Flexural rigidity
Linear density Specific flexural
rigidity
p–Probability, * Insignificant.
Table 4 — Relations of different physical characteristics
Correlation Best-fit equation
Degree of
coefficient
freedom
Calculated
t-value
p-value
0.759
0.799
0.293
0.834
-0.272
-0.743
y = 0.533x2 - 5.525x + 153.1
y = 0.180x2 - 2.679x + 23.12
y = 1.809x2 - 19.31x + 208.8
y = 115.2e-0.07x
60
60
60
60
60
60
8.40
7.48
0.59
10.20
-2.44
-6.56
0.00001*
0.00010*
0.55500
0.00001*
0.01700*
0.00020*
0.423
-0.07
-
30
30
0.63
-0.40
0.53000
0.69000
0.893
0.785
-0.122
-0.437
-0.826
y = 0.255x - 21.31
y = -0.001x2 + 3.360x - 226.0
y = 190.3e-0.00x
60
60
60
60
60
15.38
11.50
-1.24
-2.94
-7.07
0.00001*
0.00010*
0.21900
0.00450*
0.00001*
0.764
-0.33
y = 117.3e-0.07x
-
30
30
6.27
-1.99
0.00003*
0.05400
-0.207
0.804
60
60
-1.91
8.70
0.06000
0.00010*
-0.316
-0.934
y = -0.066x2 + 15.83x +
0.656
y = 90.86e-0.02x
60
60
-3.42
-7.78
0.00110*
0.00001*
0.739
-0.302
y = 87.72e0.034x
-
30
30
7.98
-1.79
0.00002*
0.08200
whereas others are related exponentially. Figures 3(b)
and Figs 5(a) - (c) show the effect of linear density on
length, braking load, specific work of rupture and
flexural rigidity of fibres.
In all the cases, it is apparent that the relations
of easily measurable parameters (length, diameter
and linear density) with breaking tenacity and
specific flexural rigidity are very poor due to the
combined effect of very high variability of linear
density as well as basic parameter i.e breaking load
or flexural rigidity. High linear density variation
may be due to the age of the fibrous elements within
or between the nuts. On reaching the maturity level,
deposition of biological elements increases in
both longitudinal and radial directions of the
individual fibrous element as duration increases
before harvesting. Furthermore, the diameter as well
as linear density also varies along the length of fibre.
The breaking extension is always poorly correlated,
19
as it is mainly governed by weak places and
structural defects of fibres and not by the basic
fibre parameters. That is why the extensibility of
fibres is unpredictable by length, diameter and linear
density.
The best fit equations with significant correction
coefficient help to predict major fibre quality
parameters (linear density, breaking load, specific
work of rupture and flexural rigidity) by easily
measurable parameters (length and diameter). Since,
the grading is generally done at growers’ field or
at the market yard, our aim is to assess the quality
characteristics of fibre in shorter period of time
adopting minimum number of easily measurable
parameters. The predicted values will help to grade
the coconut fibre lot in farmers field by measuring
length and diameter using ordinary scale and
magnifying glass. By this process the farmer will
fetch good economic return from the fibre.
20
INDIAN J. FIBRE TEXT. RES., MARCH 2014
Fig. 3 — Effect of fibre length on (a) diameter, (b) linear density, (c) breaking load, and (d) specific work of rupture
Fig. 4 — Effect of diameter on (a) linear density, (b) breaking load, (c) specific work of rupture, and (d) flexural rigidity
SENGUPTA et al.: STOCHASTIC ANALYSIS OF MAJOR PHYSICAL PROPERTIES OF COCONUT FIBRE
21
Fig. 5 — Effect of linear density on (a) breaking load, (b) specific
work of rupture and, (c) flexural rigidity
Textile and non-textile products prepared from
the fibrous materials depend on fibre property and
structural parameters of end product17. The major
dimensional and mechanical property parameters of
fibres include length, diameter, linear density,
strength, elongation, work of rupture and flexural
rigidity. Longer and finer (lower linear density) fibre
produces stronger, regular and less hairy products.
Soft fibre (low flexural rigidity) requires much less
energy to twist a fibre bundle to make thread-like
material. Soft fibre also yields stronger and softer
textile materials. The increase in linear density,
caused due to increased deposition of lignocellulosic
Fig. 6 — Defects of coconut fibre (a) branched fibre, (b) insect
bite, (c) coconut pit and (d) mid joint
matters, restricts intermolecular movements during
bending, resulting in high rigidity. Toughness
(Specific work of rupture) depicts the combined effect
of fibre strength and elongation and it indicates end
use performance of the product. The stated fibre
parameters also decide some other important product
functional parameters, i.e. handle, insulation, etc.
3.4 Defects in Fibres
Four main defects are identified namely (i) coconut
peat, a dust-like matter of small particle size (10.64%);
22
INDIAN J. FIBRE TEXT. RES., MARCH 2014
(ii) mid-joint, a sticky bark-like matter at the middle
of fibre (6.03%), (iii) branched fibre, branching out
from the main fibrous element (2.35%) and (iv) insect
bite (2.31%). On physical verification, it is found that
the coco-peat would be removed from the fibres
during their mechanical processing, such as opening,
cleaning and drawing. Similarly, the mid-joints would
also be opened up during the same processing
machines. So, coco-peat and mid-joints may be
considered as minor defects. Though, weight loss to
an extent of 10% (or more) may cause monitory loss
to the fibre processing units. Some branched fibre and
insect bitten may be remained in the fibres even
after initial mechanical processing and this would not
be suitable for mechanical conversion to finer or
value-added end products. So, branched fibre and
insect bite may be considered as the major defect.
Different defects are shown in Figures 6(a) – (d).
Defects in fibre are one of the major parameters of
fibre quality in terms of its processability, generation
of waste and quality of the output of the machine.
Minor defects are generally eliminated during
processing of fibre and most of them are generally
dropped down during processing in the machines and
do not affect the end product quality. However, minor
defects have some economic importance due to the
waste generated from fibre lot. Among the major
defects, branched fibre may cause generation of
hairiness on the yarn surface. Insect bitten fibre
may affect strength and appearance properties of
the intermediate or of the end product.
4 Conclusion
4.1 Distribution of all the physical properties,
such as length, diameter, linear density, breaking
tenacity, breaking extension, specific work of rupture,
flexural rigidity, and specific flexural rigidity, of the
raw coconut fibres are of asymmetric nature with high
coefficient of variation.
4.2 All the properties are positively skewed.
Length, diameter, breaking extension and flexural
rigidity are of platykurtik distribution, while
breaking tenacity, specific work of rupture
and specific flexural rigidity are of leptokurtik
distribution.
4.3 Diameter of a fibre varies along its length
with tapering shape at the both ends.
4.4 Length, diameter and linear density (three
dimensional properties) are positively correlated
among themselves. All these properties are
positively correlated with breaking load and
negatively correlated with specific work of rupture.
Flexural rigidity is positively correlated with
diameter and linear density. The error in the
correlations are mainly due to high coefficient of
variation in the properties.
4.5 No correlation has been observed for tenacity
and elongation of fibre with its three dimensional
properties, viz length, diameter and linear density.
4.6 Two major and two minor defects are identified
in the raw fibre lots. The major defects identified are
branched fibre and short and/or weak fibre due to
insect bite, and minor defects are coconut peat and
mid-joint.
4.7 Evaluation of length, diameter (thickness) by
scale and magnifying glass would be sufficient for
quicker mode approximate assessment of quality for
commercial grade fibre lot. Evaluation of defects
mostly gives the economic value of the fibre lot and
may be assessed by separation and weighing
method.
4.8 It is recommended that long and coarse fibre
may be used for producing conventional ropes and
coarse mats, while medium length fibre may be used
for making finer textiles materials with improved
property parameters, either elementarily or in blends
with other fibres. Short fibres may be used in
making flexible or semi-rigid composites and also as
geofibre for soil stabilization.
Acknowledgement
Authors are grateful to Indian Council of
Agricultural Research, New Delhi, India for granting
National Agricultural Innovation Project, funded by
the World Bank.
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Satyanarayana K G, Pillai C K S, Sukumaran K, Pillai S G K,
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Moore H E, Genetes Herb, 11(2) (1973) 27.
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