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The strength measurement made by the HVI systems is unlike the traditional laboratory measurements of  Pressley and Stelometer in several important ways. First of all the  test specimens  are  prepared in a very different manner. In the laboratory method the fibres are selected, combed and carefully prepared to align them in the jaw clamps. Each and every fibre spans the entire distance across the jaw surfaces and the space between the jaws.

In the HVI  instruments the fibres are ramdomly selected and  automatically prepared for testing. They are combed to remove loose fibres and to straighten the clamped fibres, also brushed to remove crimp before testing. The mechanization of  the specimen preparation techniques has resulted in a "tapered" specimen where fibre ends are found in the jaw clamp surfaces as well as in the space between the jaws.

A second important difference between traditional laboratory strength measurements and HVI strength measurements is that in the laboratory measurements the mass of  the broken fibres  is determined by weighing the test specimen. In the HVI systems the mass is determined by the less direct methods of light absorption and resistance to air flow. The HVI strength mass measurement is further complicated by having to measure the mass at the exact point of breaks on the tapered specimen.

A third significant  difference between laboratory and HVI strength measurements is the rate  or speed  at which the fibres are broken. The HVI systems break the fibres about 10 times faster than the laboratory methods.

Generally HVI grams per tex  readings are  1 to 2 units (3 to 5%) hihger in numerical value. In some individual cases that seem to be related to variety, the differences can be as much as 6 to 8% higher. This has not caused a great deal of problems in the US, perhaps because a precedent was set many years ago when we began adjusting our Stelometer strength values about 27% to put them on Presseley level.

Relative to the other HVI measurements, the strength measurement is less precise. Going back to our single bale of cotton and doing repeated measurements on the bale we shall find that 68% of  the readings will be within 1 g/tex of the bale  average. So if the bale has an average strength of 25 g.tex, 68% of  the individual readings will be betweeen 24 and 26 g/tex, and 95% between 23 and 27 g/tex.

Because of this range in the readings within a single bale, almost all HVI users  make either 2 or 4 tests per bale and average the readings. When the average readings are repeated within a  laboratory, the averages are repeated to within one strength unit about 80% of  the time. However, when comparisons are made between laboratories the agreement on individual bales to within  plus or minus 1 g/tex decreases to 55%.

This decrease in strength agreement between laboratories is probably related to the difficulty of holding a constant relative humidity in the test labs. Test data indicate that 1% shift in relative humidity will shift the strength level about 1% . For example, if the relative humidity in the laboratory changes 3% ( from 63 to 66%),  the strength would change about 1 g/tex ( from 24 to 25 g/tex)


The measurement of  cotton colour predates the measurement of micronaire, but because colour has always been an important component of classer's grade it has not received attention as an independent fibre property. However the measurement of colour was incorporated  into the very early HVI systems as one of the primary fibre properties.

Determination of cotton colour requires the measurement of two properties, the grayness and yellowness of the fibres. The grayness is a measure of the amount of light reflected from the mass of the fibre. We call this the reflectance or Rd value. The yellowness is measured on what we call Hunter's +b scale after the man who developed it. The other scales  that describe colour space (blue, red, green) are not measured becasue they are considered relatively constant for cotton.

Returning  once again to the measurements  on our single bale, we see that repeated measurements of colour are in good agreement. For grayness or reflectance readings, 68% of the  readings will be within 0.5 Rd units of the bale average, and 95% within one Rd unit for the average.

As for yellowness, over two-thirds of these readings will be within on-fourth of one +b unit of the average, and 95% within one-half of one +b unit. The grayness (Rd) and yellowness (+b) measurements are related to grade through a colour chart which was developed by a USDA researcher. The USDA test of 77000 bales showed the colour readings to be the most repeateable of all data between  laboratories; 87% of the bales repeated within one grayness(Rd) unit, and 85% repeated within one-half of one yellowness(+b) unit.


The HVI systems measure trash or non-lint content by use of video camera to determine the amount of  surface area of the sample that is covered with dark spots.  As the camera scans the surface of the sample, the video output drops when a dark spot (presumed to be trash) is encountered. The video signal is processed by a microcomputer to determine the number of dark spots encountered (COUNT) and the per cent of the surface area covered by the dark spots (AREA). The area  and count data are used in an equation to predict the amount of visible non-lint content as measured on the Shirley Analyser. The HVI trash data output is a two-digit number which gives the predicted non-lint content for  that  bale. For example, a trash reading of 28 would mean that the predicted Shirley Analyser visible non-lint content of that bale would be 2.8%.

While the video trash instruments have been around for several years,  But the data suggest that the prediction of non-lint content is accurate to about 0.75% non lint, and that the  measurements are repeatable 95% of the time to within 1% non-lint content.


The measure of short-fiber content (SFC) in Motion Control's HVI systems is based on the fiber length distribution throughout the test specimen.

It is not the staple length that is so important but the short fiber content which is important. It is better to prefer a lower commercial staple, but with a much lower short-fibre content.

The following data were taken on yarns produced under identical conditions and whose cotton fibers were identical in all properties except for short-fiber content. The effects on ends down and several aspects of yarn quality are shown below.

  LOT -A, (8.6% SFC) LOT-B (11.6% SFC)
Ends down / 1000 hrs 7.9 12.8
Skein strength (lb) 108.1 97.4
Single end strength g/tex 15 14.5
apperance index 106 89
Evenness (CV%) 16 17.3
Thin places 15 36
Thick places 229 364
Minor Defects 312 389


These results show that an increase of short-fiber content in cotton is detrimental to process efficiency and product quality.

HVI systems measure length parameters of cotton samples by the fibrogram technique. The following  assumptions describe the fibrogram sampling process:

  • The fibrogram sample is taken from some population of fibres
  • The probability of sampling a particular fiber is proportional to its length
  • A sampled fiber will be held at a random point along its length
  • A sampled fiber will project two ends away from the holding point, such that all of the ends will be parallel and aligned at the holding  point.
  • All fibers have the same uniform density


The High Volume Instruments also provide empirical equations of short fibre content based on the results of cotton produced in the United States in a particular year.

Short Fibre Index = 122.56 - (12.87 x UHM) - (1.22 x UI)

where UHM - Upper Half Mean Length (inches)
UI - Uniformity Index

Short Fibre Index = 90.34 - (37.47 x SL2) - (0.90 x UR)

Where SL2 - 2.5% Span length (inches)
UR - Uniformity Ratio



Near infrared analysis provides a fast, safe and easy means to measure cotton maturity, fineness and sugar content at HVI speed without the need for time consuming sample preparation or fiber blending.

This technology is based on the near infrared reflectance spectroscopy principle in the wavelength range of 750 to 2500 nanometers. Differences of maturity in cotton fibers are recognized through distinctly different NIR absorbance spectra. NIR technology also allows for  the measurement of sugar content by separating the absorbance characteristics of various sugars from the  absorbance of cotton material.

Cotton maturity is the best indicator of potential dyeing problems in cotton products. Immature fibers do not absorb dye as well as mature fibers. This results in a variety of dye-related appearance problems such as barre, reduced color yield, and white specks. Barre is an unwanted striped appearance in fabric, and is often a result of using yarns containing fibres of different maturity levels.  For dyed yarn, color yield is diminished when immature fibres are used. White specks are small spots in the yarn or fabric which do not dye at all. These specks are usually attributed to neps (tangled clusters of very immature fibers)

NIR  maturity and dye uptake in cotton yarns have been shown to correlate highly with maturity as measured by NIR.  A correlation of R=0.96 was obtained for a set of 15 cottons.

In a joint study by ITT and a European research organization, 45 cottons from four continents were tested for maturity using the NIR method and the SHIRLEY Development Fineness/ Maturity tester(FMT). For these samples, NIR and FMT maturity correlated very highly (R=0.94).

On 15 cottons from different growth areas of the USA , NIR maturity was found to correlate with r2 = 0.9 through a method developed by the United States Department of Agriculture (USDA).  In this method, fibres are cross-sectioned and microscopically evaluated.

Sugar Content is a valid indicator of potential processing problems. Near infrared analysis, because of its adaptability to HVI, allows for screening of bales prior to use. The information serves to selected bales to avoid preparaion of cotton mixes of bales with excessive sugar content. COTTON STICKINESS consists of two major causes- honeydew form white flies and aphids and high level of natural plant sugars. Both are periodic problems which cause efficiency losses in yarn manufacturing

The problems  with the randomly distributed honeydew contamination often results in costly production interruptions and requires immediate action often as severe as discontinuing the use of contaminated cottons.

Natural plant sugars are more evenly distributed and cause problems of residue build-up, lint accumulation and roll laps. Quality problems created by plant sugar stickiness are often more critical in the spinning process than the honeydew stickiness. Lint residues which accumulate on machine parts in various processes will break loose and become part of the fiber mass resulting in yarn imperfections. An effective way to control cotton stickiness in processing is to blend sticky and nonsticky cottons. Knowing the sugar content of each bale  of cotton used in each mix minimizes day-to-day variations in processing efficiency and products more consistent yarn quality. Screening the bale inventory for sugar content prior to processing will allow the selection of mixes with good processing characteristics while also utilizing the entire bale inventory.

The relationship between percent sugar content by NIR analysis and the Perkins method shows an excellent correlation of r2=0.95. The amount of reducing material on cotton fiber in the Perkins method is determined by comparing the reducing ability of the water extract of the fiber to that of a standard reducing substance. Using the NIR method,  the amount of reducing sugar in cotton is measured.

The popularity of HVI testing has steadily gained since the introduction of the technology in the early 1960s.

Timely, valuable information, promotion of communication, standardization of measurements, optimization of processes, development of new products and cost control are the outstanding benefits of technology.

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