An Evaluation for Cotton Fiber Length Distribution Measurements of

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International Journal of Fiber and Textile Research
Universal Research Publications. All rights reserved
ISSN 2277-7156
Original Article
AN EVALUATION FOR COTTON FIBER LENGTH DISTRIBUTION
MEASUREMENTS OF DIFFERENT METHODS
Ibrahim A. M. Ebaido
Cotton Research Institute (CRI), Agricultural Research Center (ARC), Giza, Egypt
Email:[email protected]
Received 01 January 2014; accepted 06 March 2014
Abstract
The seven Egyptian commercial cotton varieties, which have wide range of fiber length distribution, were used for the
purpose of characterization of the relationship between fiber length parameter of cotton obtained from both the
conventional as well as the hi-tech instruments to give an idea of the similarity in fiber length distributions and their
effectiveness. The instruments used to measure fiber length distribution measurements include Suter-Webb array, AFIS (by
number and by weight) and HVI (USDA and ICC modes). Comparisons between the three methods indicate that the
measurements of mean length correlate well with each other; and also longer fibers length measurements. Whereas length
uniformity and short fibers show weak associations among their measurements. Discriminations of mean length and longer
fibers are similar among the samples for three methods. However, Suter-Webb array shows the greater discrimination of
length uniformity and short fibers than HVI and AFIS. Although the tedious Suter-Webb array method may yield sharper
distinctions in length distribution measurements among different cottons; AFIS and HVI give strongly related measures of
mean length and longer fibers. Whereas, length uniformity and short fibers measurements still need some efforts to gain
realistic.
© 2014 Universal Research Publications. All rights reserved
Keywords: AFIS, Cotton, Fiber Length Distribution, HVI, Suter-Webb
INTRODUCTION
Fiber length is critical for textile processing and varies
greatly for different cottons due to genetic differences [1].
Measuring a fiber beard instead of individual fibers
provides a rapid account for those fiber length parameters,
for example, the widely used High Volume Instrument
(HVI) system [2]. In HVI testing, the specimen fibers are
picked up by the needles of a comb/clamp through holes of
the HVI Fibrosampler. The collected specimen fibers are
in the form of a tapered beard. The beard is brushed and
combed to remove loose fibers and fiber crimp. By
scanning light attenuation at each length (from the tip of
the longest fiber in the beard to the baseline of the clamp),
the instrument determines the fiber mass at each length of
the beard. The mass-length curve obtained from measuring
this tapered beard is called a fibrogram.
The original theory of the fibrogram as developed by
[3] and [4] has served as the basis of subsequent cotton
length measurement methods based on such tapered fiber
beards. Following [4] pioneering work, various
developments have been made. [5] Generated fiber length
distributions in discrete form cotton fiber fibrograms.
5
Those generated distributions were presented as graphical
bar charts, not as mathematic functions. [6] Provided a
comprehensive appraisal and developed a series of
equations for computing different fiber length parameters
from fibrograms. [7] Described the basic ideas of the
fibrogram theory starting from a frequency diagram and
establishing geometrical and probabilistic interpretations
for single fiber length, two fiber length and multiple fiber
length populations.
[8] Showed that the mean length and the proportion of
fibers can be obtained from the fibrogram. [9] Applied a
new approach to generate the fibrogram from the length
array data similar to [7] method. They assumed a random
catching and holding of fibers within each of the length
groups generating a triangular distribution by relative
weight for each length group. [10] Discussed the concept
of short fibers content (SFC) and showed relationships
between SFC and other fibers length parameters and
functions. Later they determined empirical relationships
between SFC and the HVI length. The most fundamental,
direct (and tedious) measure of fiber length distribution is
the Suter-Webb array method in which a comb-sorting
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
technique is used to segregate the fibers into length groups,
each of which are weighed on an analytical balance. The
AFIS (Advanced Fiber Information System) instrument is
also a direct measurement of fiber length distribution, as it
utilizes a mechanical opener to inject individual fibers into
a rapid air stream where the length of each fiber can be
measured a high speed electro/optic system [11]. There is
some legitimate concern that the AFIS mechanical
opener/individualizer causes some fiber breakage [12].
Also, many of the fibers passing through the instrument
are not presented in a manner that enables measurement;
therefore, these fibers are excluded from the results. The
fiber breakage makes getting repeatable measurements
among instruments very difficult, while the exclusion of
various fibers from the sample raises (unanswered)
questions about possible bias in the measurement.
Recent research shows that the parameters commonly
used to characterize the fiber length (mean length, short
fiber content…) present multiple shortcomings and are for
instance not usable by cotton breeders to improve length
distribution, or by ginners and textile manufacturers to
reliably optimize the fiber behavior during processing [13],
[14], [15], [16] and [17]. The present research seeks to
overcome this lack of reliable parameters by acquiring a
better understanding of the cotton fiber length alterations.
The approach is to consider the process from the seed to
the yarn and to establish parametric models describing the
fiber length distribution and its alterations [18]. With such
adequate parameterization of the length distribution,
breeders, agronomist and processors will have access to
more accurate information allowing interpretation and use
of the distribution data. Because of different methods are
used for the determination of the same parameters, it is
expected that the results for a particular parameter
expressed by different methods agree numerically within a
narrow tolerance zone. If not, at least they should follow
the same trend.
The present investigation intends to correlate the same
fiber length parameter of cotton obtained from both the
conventional as well as the hi-tech instruments, with each
other to give an idea of the similarity or variations in fiber
length distributions obtained from various instruments.
And investigate the relationship between these
distributions and the true fiber length distribution.
2. MATERIALS AND METHODS
The seven Egyptian commercial cotton varieties, which
have wide range of fiber length, were used for the study.
Four of these varieties belong to the extra-long staple
category, i.e., Giza 70, Giza 87, Giza 88 and Giza 92.
While the other three ones belong to the long staple class,
i.e., Giza 86, Giza 80 and Giza 90.
The fiber length parameters were obtained on instruments
located at:
2.1. Cotton Research Institute (CRI) in Giza, Egypt
After sampling, the hand-made slivers were prepared,
loose cotton lint was used for the High Volume Instrument
(HVI) testing [19], which provides measurement of several
characteristics, but only the fiber length parameters
according to USDA calibration, viz. upper half mean
(UHM), mean length (ML), uniformity index (UI) and short
6
fiber index (SFI), have been dealt with in the paper.
While hand-made slivers were used for testing fiber length
distribution by weight with Suter-Webb array method [19],
which provides upper quartile length (UQL), mean length
(ML), short fiber content (SFC) and coefficient of variation
(CV %) which is reflects regularity (how the uniform of
length distribution). Before testing, cotton samples were
conditioned for at least 48 hours at 65% ± 2% RH and 21o
C ± 2ºC prior to testing;
2.2. South India Textile Research Association (SITRA)
in Coimbatore, India
After sampling, the hand-made slivers were prepared, loose
cotton lint was used for HVI testing [19], which provides
measurement of 2.5 % SL, uniformity ratio (UR) and short
fiber index (SFI) according to International Calibration
Cotton (ICC) mode.
While hand-made slivers were used for testing fiber length
distribution with the AFIS (Advanced Fiber Information
System) according to [19], which used to determine fiber
length parameters by weight and by number (5000 fibers
were used for measurements per sample), i.e., UQL, 5 %
SL, ML, SFC and CV % which gave the same
interpretation in Suter-Webb about length regularity
(uniformity).
All the tests were carried out under standard atmospheric
conditions of 65 % ± 2 % RH and 27º C ± 2º C
temperature. All data gathered were computed using
XLSTAT software to compare mean values of fiber length
distributions; descriptive statistics obtained from different
instruments and correlate each one of these distributions
with others.
2.3. INSTRUMENTS
2.3.1. High Volume Instrument (HVI)
High volume instrument (HVI) system provides
measurement of fiber length, length uniformity and short fiber
(fibers shorter than half inch) through measures the light
intensity that goes through a sample of fibers. The less amount
of light can go through the sample, the longer the fibers are (use
of light in the distribution of staple length measurements), and
therefore such measurement leads to obtaining a chart called
length-frequency curve or fibrogram beard (Fig. 1). That chart
(fibrogram) presenting the relationship between the amount of
light going through the sample and the fiber length was
corresponding to this value. These values or parameters is
usually defined depending on the standard samples used in the
calibration of the HVI to mean lengths, e.g. the upper half mean
length (UHML), which is the mean length of the longer half
(50%) of the fiber, and the mean length (ML) are more
commonly used since they describe the mean of all or a set
portion of fibers represented in the fibrogram, these parameters
used after response to a USDA proposal considered at the
triennial conference in 1995, and called USDA's calibration
standards for HVI measurements after incorporated into the
Universal Standards Agreement.
The other parameters used in the expression for the length
of staple is Span lengths (SL) or International Calibration
Cotton (ICC) mode, which came about as a result of a
technical shortcoming in the ability of the first digital
Fibrograph to graphically run a tangent to the fibrogram,
represent fiber extension distances, e.g. the 2.5 % SL
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
represents the distance the longest 2.5 % of fibers extended
from the comb. Length uniformity is expressed either as the
uniformity index or uniformity ratio. Both terms are ratios
of measurements from the fibrogram, where uniformity
index refers to the ratio between the mean length and the
upper half mean length and the uniformity ratio refers to
the ratio of the 50% SL to the 2.5% SL.
The most common definition of short fiber is the proportion
by mass of fiber shorter than one half inch. Short fiber is
not measured directly by any instrument employed in HVI
lines. Instead short fiber content (SFC), short fiber index
(SFI) is estimated indirectly using the fibrogram
measurements of UHML and ML or 2.5% SL and 50% SL
as the main variables in prediction equations.
Fig1. Typical Fibrogram HVI length distribution
2.3.2. Suter-Webb array (SW)
This method consists of a bed of upright and parallel
combs which control the fibers and arranged it in the form of
an array of uniform density in the descending order of length.
In this way enable the sample (fibers) to be fractionated into
length groups for determining cumulative fiber length
distribution by weight in parameters upper quartile length
(UQL), mean length (ML) and % short fibers (SFC) as
illustrated in Fig. 2 and dispersion percentage which is
expressed as (CV%). The disadvantages of this device are
time consuming (2 hrs per sample) and calls for considerable
operator skill in sampling and preparing the diagram (Fig. 2).
Fig2. Short fiber content and upper quartile length in the
beard of staple
2.3.3. Advanced Fiber Information System (AFIS)
This instrument measures length, alongside it also
measures fineness, maturity, circularity, etc. of each fiber
fed, and from the data so obtained provides average length
of individual fibers in a sliver fed to the system, as also the
length distribution both by number and weight, this
7
distribution gives the following parameters effective length
(UQL), Mean length (ML), % short fibers (SFC) and
dispersion percentage which is expressed as (CV%) after
measuring the individual fiber length for a selected weight
and number of fibers which can be varied between 1000
and 10000. Other parameters the instrument can measure
are immature fiber content, neps/g and percentage of dust
and trash.
2.4. DEFINITIONS
The fiber length can be described by its distribution by
number that expresses the probability of occurrence of a
fiber within the length group, or it can be described by its
distribution by weight that expresses the weight of fibers in
each length group.
1. Mean length (ML)
The mean length ML is obtained by summing the product
of fiber length and its weight, then dividing by the total
weight of the fibers.
2. Coefficient of fiber length variation (CV %)
The coefficient of variation of fiber length CV % is the
ratio of σ divided by the mean length ML: CV % = (σ /ML)
× 100. Where σ is standard deviation of fiber length.
3. Upper quartile length (UQL)
The upper quartile length is defined as the length that is
exceeded by 25% of fibers by weight.
4. Upper half mean length (UHML)
The UHML is the average length of the longest one-half of
the fibers
5. Span length (SL)
The percentage span length % indicates the percentage of
fibers that extends a specified distance or longer. The 2.5 %
and 50 % are the most commonly used by industry.
6. Uniformity index (UI %)
UI % is the ratio of the mean length divided by the upper
half-mean length. It is a measure of the uniformity of fiber
lengths in the sample expressed as a percent:
UI % = (ML / UHML) × 100.
7. Uniformity ratio (UR %)
UR % is the ratio of the 50% span length to the 2.5 % span
length. It is a smaller value than the UI % by a factor close
to 1.8
UR % = (50 % SL / 2.5 % SL) × 100.
8. Short fiber content (SFC %)
SFC % is the percentage by weight of fibers less than one
half inch (12.7 mm).
3. RESULTS AND DISCUSION
Fiber length in a cotton sample has length distribution
corresponding to variation in fiber length of individual
fibers. If one can measure separately all the individual
fibers present in a sample, he would be able to get the true
distribution of the fiber length. But this is almost
impossible. However, a true representative tuft constituting
thousands of fibers taken from the sample can also give a
distribution almost similar to the true distribution.
Moreover, the measurements of lengths of individual fibers
for a few thousand fibers are also difficult and time
consuming, though not impossible. The idea of carrying out
tests for measurement of fiber length distributions is to get
the most accurate and reproducible results. Reproducibility
of results generally depends on proper sampling and the
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
Table 1. Glossary of variable names
SW-ML
Suter-Webb mean length (mm)
SW-UQL
Suter-Webb upper quartile length (mm)
SW-CV
Coefficient of variation of Suter-Webb mean length (%)
SW-SFC
Suter-Webb short fiber content (%)
HVI-ML
HVI mean length according to USDA mode (mm)
HVI-50%SL
HVI 50% span length according to ICC mode (mm)
HVI-UHM
HVI upper half mean length according to USDA mode (mm)
HVI-2.5%SL
HVI 2.5% span length according to ICC mode (mm)
HVI-UI
HVI length uniformity according to USDA mode (%)
HVI-UR
HVI length uniformity according to ICC mode (%)
HVI-SFI(U)
HVI short fiber index according to USDA mode (%)
HVI-SFI(I)
HVI short fiber index according to ICC mode (%)
AFIS-MLN
AFIS mean length by number (mm)
AFIS-MLW
AFIS mean length by weight (mm)
AFIS-5%SL
AFIS 5 % span length by number (mm)
AFIS-UQL
AFIS upper quartile length by weight (mm)
AFIS-NCV
Coefficient of variation of AFIS mean length by number (%)
AFIS-WCV
Coefficient of variation of AFIS mean length by weight (%)
AFIS-SFCN
AFIS short fiber content by number (%)
AFIS-SFCW
AFIS short fiber content by weight (%)
inherent variability in the material. But the accuracy of
measurement of a parameter depends on the physical
principals used in the test method. The following
discussion shows limitations in determination of fiber
length distribution using Suter-Webb array, HVI and AFIS.
These limitations are mainly due to the limitation of
physical test methods used for these determinations.
3.1. Mean length and 50 % span length measurements
A compilation of the significant statistical parameters
of the five mean length measurements is given in Table 2.
These include: minimum (MIN); maximum (MAX); mean;
standard deviation (SD) and coefficient of variation
(CV=100X SD/Mean). The mean values for mean length
for each measurement for all samples range between 24.34
and 29.7 mm; whereas, 50 % SL ranged less between 13.07
and 20.2 mm. The 50 % SL is the least discriminating
having the smallest SD (1.17) and CV % (7.62). The AFISMLW is the most sensitive with the largest range of values
(24.3 – 32.1 mm) and the greatest SD (2.9) and CV %
(9.91).
Table 2. Overall results of mean length and 50% SL measures
SW
ML (mm)
ML
HVI
50%SL
AFIS
MLN
MLW
MIN
25.1
25.22
13.07
20.2
24.3
MAX
33.9
32.16
16.65
27.4
32.1
Mean
29.7
29.13
15.35
24.34
29.24
SD
2.33
2.24
1.17
2.34
2.9
CV%
7.84
7.68
7.62
9.61
9.91
In Figure 3, comparing the mean length and 50 % SL
measurements for the three instruments in this study. Each
set of data was sorted from the smallest to largest values.
8
The AFIS-MLW has the high variation and 50 % SL is the
lowest, which seemed to be flat. It needed to be pointed out
that the HVI-ML and AFIS-MLW data tend to track SWML better.
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
The Figure 4 illustrates the high values and largest range of
the AVIS-UQL; while the HVI measures (UHM and 2.5%
SL) show the smaller ranges.
The correlation matrix (Pearson's R-values) shown in
Table 3 indicates the relationship among mean length and
50 % SL measures. The inter-correlations between all five
variables are high significant (0.702 – 0.965). It is not
surprising that the highest R-value (0.965) is between
AFIS-MLW and AFIS-MLN. The lowest correlation value
is that of SW-ML with HVI-50%SL and HVI-ML (0.702
and 0.738 respectively)
Table 3. Correlation coefficients among mean length and
50% SL measures
AFIS-MLW
AFISMLN
HVI-50% SL
HVI-ML
SW-ML
HVI-ML
HVI-50% SL
AFIS-MLN
0.801**
0.786**
0.702**
0.738**
0.923**
0.870**
0.923**
0.891**
0.859**
0.965**
Because overall textile performance is largely dictated
by longer fibers in a distribution, it is appropriate also to
consider the longer fiber data. Suter-Webb and AFIS both
estimate the upper quartile length and 5 % SL, whereas
HVI, depending on fibrogram theory, measures upper half
mean (USDA mode) or 2.5 % SL (ICC mode). Descriptive
statistics for the measures of the longer fibers length
obtained from the three instruments are shown in Table 4.
The mean values for longer fibers length differ from
method (instrument) to another. The highest measure is
AFIS-5%SL (40.97 mm), while the lowest is the HVI2.5%SL (32.51 mm). The SW-UQL value (38.03 mm) is
higher than the AFIS-UQL value (34.63 mm). It is clearly
obvious; the AFIS-UQL is the most sensitive with the
largest SD (3.63) and CV % (9.8); whereas the HVI-UHM
is the least discriminating having the smallest SD (2.33)
and CV % (6.9).
Table 4. Overall results of the longer fibers length
measures
SW-UQL
MIN
MAX
Mean
SD
CV %
9
32.80
41.92
38.03
2.89
7.61
Table 5. Correlation coefficients among longer fiber length
measures
AFIS-UQL
AFIS-5%SL
HVI-2.5%SL
HVI-UHM
3.2. Longer fibers length measurements
HVI
UHM
2.5%SL
29.40
27.43
36.50
36.20
33.75
32.51
2.33
2.7
6.90
8.3
The correlation matrix of the Pearson correlations among
the five measures indicates the inter-correlations between
all five measures are quite high (greater than 0.90). It is not
surprising that the higher R-values are between the AFISUQL and AFIS-5%SL (0.981), and also between HVIUHM and HVI-2.5%SL (0.968).
UQL
35.18
44.20
40.97
3.4
8.41
28.81
38.72
34.63
3.63
9.8
HVI-UHM
0.915**
0.928**
0.917**
0.914**
0.944**
0.948**
0.968**
HVI
2.5%SL
AFIS
5% SL
0.910**
0.925**
0.981**
3.3. Fiber length uniformity
As there are various ways of expressing the length
uniformity of fibers, it is difficult to compare the length
uniformity
measures
of
different
methods
(instruments).Descriptive statistics for the fiber length
uniformity measures obtained from the three instruments
are shown in Table 6. The mean values of length
uniformity exhibit big differences among each of the five
measurements. The HVI-UI is the highest measure of
length uniformity (86.2) %, while the SW-CV is the lowest
measure (18.7 %). The largest variation is of the SW-CV
which has the highest SD (3.56) and CV % (12.03);
whereas the HVI-UR exhibits the narrowest range with
lowest SD (0.73) and CV % (1.52). Generally, the low
values of SD for the five measurements obvious the low
variations for those measurements.
Table 6. Overall results of fiber length uniformity measures
HVI
AFIS
5%SL
SW-UQL
MIN
MAX
Mean
SD
CV %
AFIS
SW-CV
UI
UR
12.9
83
46
40.2
29.1
26.5
89.2
48.7
45.6
34.4
18.7
86.2
47.2
42.7
31.9
3.56
1.73
0.73
1.34
1.47
12.03
2
1.52
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
NCV
3.14
WCV
4.61
Figure 5 illustrated to compare the five measures of length
uniformity measurement. The SW-CV exhibits the largest
range and the lowest values; whereas the HVI-UI has the
highest values. The HVI measures, especially uniformity
ratio (UR) have smaller variations; so seemed to be flat.
The inter-correlations among all fiber length uniformity
measurements are shown in Table 7. Looking at the
correlation matrix, it is found that most the measurements
of fiber length uniformity show insignificant correlations;
except for the significant and positive correlation
coefficients of AFIS-WCV with each of AFIS-NCV
(0.468) and HVI-UR (0.367). And also, the SW-CV exhibit
significant and negative correlation with HVI-UI (-0.439).
This means that the HVI-UI may be indicative of length
uniformity than that obtained from AFIS.
Table 7. Correlation coefficients among fiber length
uniformity measures
AFISWCV
AFIS-NCV
HVI-UR
HVI-UI
SW-CV
0.075
- 0.032
- 0.074
- 0.439*
HVI-UI
- 0.158
0.276
- 0.120
HVI-UR
0.367*
0.014
AFIS-NCV
0.468*
3.4. Short fibers measurements
Descriptive statistics for the five measures of short fibers
included in this study are shown in Table 8. These include
short fibers as measured by Suter-Webb array (SFC), HVI
(SFI) in two modes [USDA (U) & ICC (I)] and AFIS
(SFC) by number (N) and by weight (W). The mean values
for short fibers for each measurement range between 4.94
% (AFIS-SFCW) and 15.59 % (AFIS-SFCN). The HVISFI(I) is the least discriminating having the smallest SD
(0.40) and the narrowest range of values (4.51 – 6.16 %).
The SW-SFC is the most sensitive with the highest SD
(3.13) and the largest range of values (3.13 – 15.51%). It is
needed to point out that the high values of % CV values for
SW-SFC (39.17) and AFIS-SFCW (25.3) indicate the large
variation in these measures.
Figure 6 illustrates the comparison among the five
measures of short fibers measurement. The high values of
short fibers are for AFIS-SFCN with moderate range;
whereas the largest range is for SW-SFC. Each of HVI-SFI
(I) and HVI-SFI (U) data tend to track SW-SFC and AFISSFCW better.
The correlation matrix shown in Table 9 indicates the
relationships between each of the five measures of short
fibers. The correlation coefficient values among these
measurements are moderate (range between 0.276 and
0.862). The high significant correlation values are of SWSFC with each of AFIS-SFCN, AFIS-SFCW and HVI-SFI
(I). And also between the two measures of AFIS (SFCN
and SFCW). The correlation coefficient between measures
of the two modes of HVI is significant. Only the AFISSFCN and HVI-SFI (U) correlate insignificantly. Generally
these relationships mean that, measurements of AFIS
(N&W) and HVI (ICC mode) could be considering
represent measurement for short fiber instead of SuterWebb array, but to some extent.
Table 9. Correlation
measures
SWSFC
AFIS0.636**
SFCW
0.788**
AFIS0.576**
SFCN
0.333*
HVISFI(I)
HVISFI(U)
coefficients among short fiber
HVISFI(U)
0.367*
0.276
0.441*
HVISFI(I)
0.364*
0.441*
AFISSFCN
0.862**
SUMMARY AND CONCLUSIONS
This investigation aimed to characterization of the
relationship between fiber length measurements of cotton
obtained from both the conventional as well as the hi-tech
Table 8. Overall results of short fiber measures
instruments to give an idea of the similarity in fiber length
SW
HVI
AFIS
distributions and their effectiveness. The three methods
SFC
SFI(U)
SFCN SFCW
studied included using the Suter-Webb array method as
SFI(I)
compared with AFIS and HVI in two modes (USDA and
MIN
2.29
5.72
4.51 12.11
3.2
ICC).
MAX
15.51
7.41
6.16 18.62
8.45
Our results lead to the following conclusions: (1) The
Mean
distributions of mean fiber lengths are similar for Suter7.83
6.41
5.45 15.59
4.94
SD
Webb array and HVI modes, with Suter-Webb
3.13
0.43
0.40 1.9
1.25
CV %
differentiating narrowly more than HVI among the lots,
39.17
6.65
7.4
13
25.3
with low values of 50 % SL. Whereas, the AFIS mean
International Journal of Fiber and Textile Research 2014; 4(1): 5-11
10
length by weight and by number produced wider
distribution than Suter-Webb There is a strong degree of
linear association among the pairs of measurements
(0.702< r < 0.965). (2) The distributions of longer fibers
length measurements are similar, except for UHM which is
lowest, with AFIS-UQL by weight producing somewhat the
widest distribution of values, with highest values of AFIS5%SL. The linear associations among all measurements of
longer fibers length are strong (r ≤ 0.91). (3) Although the
Suter-Webb array exhibited the lowest value of fiber length
uniformity measurement, it is produced a wider distribution
than either HVI or AFIS. That is, Suter-Webb differentiated
the lots more than did the high-tech machines, especially
compared to HVI length uniformity measurements for lots.
However, there is a weak degree of linear association
between the pairs of short fiber measurements (0.014 < r <
0.468). (4) The Suter-Webb array produced a wider
distribution of short fibers measurement than either HVI or
AFIS. That is, Suter-Webb differentiated the lots more than
did the machine methods, especially compared to HVI
short fibers measurements for lots with low values of SFC.
Therewith, AFIS-SFC by weight seemed to be similar SWSFC, to some extent. There is a moderate degree of linear
association between the pairs of short fibers measurements
(0.276 < r < 0.862). (5) Although the tedious Suter-Webb
array method may yield sharper distinctions in length
distribution measurements among different cottons; AFIS
and HVI give strongly related measures of mean length and
longer fibers. Whereas, length uniformity and short fibers
measurements still need some efforts to gain realistic. (6)
Given the associations among similar fiber length
properties produced by the three methods, there is little
reason to perform the expensive and tedious Suter-Webb
array in order to obtain length distribution measures if
either HVI or AFIS data are available. Likewise, if length
measurements have been made by one instrument, little
additional information about fiber length is gained by
obtaining measurements from the other one.
4. REFERENCES
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
A. Basra. Cotton Fibers: Developmental Biology
Quality Improvement, and Textile Processing. Food
Products Press, Binghamton, NY. (2000).
M. Suh and P.E. Sasser. Technological and Economic
17.
Impact of HVI on Cotton and Cotton Textile
Industries. Journal of the Textile Institute Part 3,
87:43-59, (1996).
K.L. Hertel. An optical method for the length analysis
of cotton fibers. Textile Research Journal. 6:331-339,
(1936).
K.L. Hertel. A method of fiber-length analysis using
18.
the fibrograph. Textile Research Journal. 10:510-525,
(1940).
R.S. Krowicki, D.P. Thibodaux, and K.E. Duckett.
19.
Generating fiber length distribution from the
fibrogram. Textile Research Journal. 66:306-310,
(1996).
J.L. Woo. An appraisal of the length measures used for
cotton fibers. Journal of the Textile Institute, 58, 557–
572, (1967).
C. B. Landstreet. the Fibrogram: Its Concept and Use
in Measuring Cotton Fiber Length, Textile, Bull., 87,
No. 4, 54-57, (1961).
R. S. Krowicki, J. M. Hemstreet, and K. E. Dukett. A
Different Approach to Generating the Fibrogram from
Fiber-Length-Array Data, Part I: Theory, J. Text. Int.,
88 Part I, No. 1, 1-5, (1997).
R. S. Krowicki, J. M. Hemstreet, and K. E. Dukett. A
Different Approach to Generating the Fibrogram from
Fiber-Length-Array Data, Part II: Application, J. Tex.
Int., 89 Part I, No. 1, 1-8, (1998).
M. I. Zeidman, S. K. Batra, and P.Sasser. Determining
Short Fiber Content in Cotton, Part I: Some
Theoretical Fundamentals, Textile Res. J. 61 (1): 2130, (1991).
C.K. Bragg and F.M. Shofner. Rapid, Direct
Measurement of Short Fiber Content. Textile Res. J.
63(3), 171-176, (1993).
X. Cui, T.A. Calamari and Jr. Robert. An investigation
of cotton fiber lengths measured by HVI and AFIS.
The 10th EFS system research forum proceedings.
115-123, (1997).
K. Q. Robert and L. J. Blanchard. Cotton Cleanability.
Part I: Modeling Fiber Breakage. Textile Res. J., 67
(6): 417-42, (1997).
K. Q. Robert, J. B. Price and X.Cui. Cotton
Cleanability – Part II: Effect of Simple Random
Breakage on Fiber Length Distribution. Textile Res. J.,
70 (2): 108-115, (2000).
K. Q. Robert and X. Cui. Analysis of the Fraction of
Broken Fibers in Cotton. Cotton Incorporated
Fourteenth Annual Engineered Fiber Selection System
Conference Proceedings and Fourteenth Annual
Engineered Fiber Selection System Research Forum
Proceedings, pp.: 47-53 (June 11-13), (2001).
M. Krifa. AFIS Length Distribution in Cotton Spinning
Preparation. Beltwide Cotton Conferences – Cotton
Quality Measurements / Utilization, January 5-9, San
Antonio, Tx., National Cotton Council of America.
Memphis, TN, USA, pp. 3072-3076, (2004).
M. Krifa and E. Hequet. Experimental Assessment of
Cotton Fiber Behavior During Opening and Cleaning.
Proceedings of the Beltwide Cotton Conferences –
Cotton Utilization / Textile Technology Symposium,
January 4-7, New Orleans, LA, National Cotton
Council of America. Memphis, TN, USA, pp. 27132716, (2005).
M. Krifa. Fiber Length Distribution in Cotton
Processing: Dominant Features and Interaction Effects.
Textile Research Journal. 76:426-435, (2006).
ASTM. American Society for Testing and Materials.
Designation, (D: 1776-98, D: 1444-05, D: 4603-86, D:
5866-95) Test Methods, Philadelphia 3, Pa, U.S.A
(2005).
Source of support: Nil; Conflict of interest: None declared
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International Journal of Fiber and Textile Research 2014; 4(1): 5-11

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