An Investigation of the Relationship between Cotton Fineness and Light Scattering from Thin Webs as Measured by Near-Infrared Transmission Spectroscopy

Montalvo, Joseph G.; Faught, Sherman E.; Buco, Steven M.

doi:10.1366/0003702894204353

Cited by 12 publications

(3 citation statements)

References 3 publications

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“…The indirect methods include instruments such as the advanced fiber information system (AFIS) 10 and Fineness and Maturity Tester (FMT), 11 and also the optical and imaging spectroscopic approach in near infrared (NIR) and visible regions. 12,13 Clearly, the direct methods are relatively accurate and precise but are time consuming and tedious, whereas the indirect methods depend on direct method reference readings to calibrate the systems for procedure accuracy and performance.…”

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Development of Fourier transform infrared spectroscopy in direct, non-destructive, and rapid determination of cotton fiber maturity

Liu

Thibodeaux

Gamble

2011

Textile Research Journal

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Fourier transform infrared (FTIR) spectra of seed and lint cottons were collected to explore the potential for the discrimination of immature cottons from mature ones and also for the determination of actual cotton maturity. Spectral features of immature and mature cottons revealed large differences in the 900—1200 cm1 region, and such spectral distinctions formed the basis on which to develop a simple three-band ratio algorithm for classification analysis. Next, an additional formula was created to assess the degree of cotton fiber maturity by converting the three-band ratios into an appropriate FTIR maturity (MIR) index. Furthermore, the MIR index was compared with parameters derived from traditional image analysis (IA) and advanced fiber information system (AFIS) measurements. Results indicated strong correlations (R2 > 0.89) between MIR and M AFIS and between MIR and MIA among either International Cotton Calibration standards or selected cotton maturity references. On the other hand, low correlations between the pairs were observed among regular cotton fibers, which likely resulted from the heterogeneous distribution of structural, physical, and chemical characteristics in cotton fibers and subsequent different sampling specimens for individual and independent measurement.

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confidence: 99%

Development of Fourier transform infrared spectroscopy in direct, non-destructive, and rapid determination of cotton fiber maturity

Liu

Thibodeaux

Gamble

2011

Textile Research Journal

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“…Basic research in this laboratory has shown unequivocally that NIRS senses t and P simultaneously and independently [10][11][12][13][14][15] . Consequently, all the other measures of maturity and fineness may be measured.…”

Section: Substitution Of Equation 1 Into Equation 3 Yields Equationmentioning

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A Critical Evaluation of the Relationships Between Arealometer Instrument Values and Cotton Fiber Perimeter

Montalvo

Vinyard

1993

Textile Research Journal

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Arealometer instrument values are computer simulated to study the error in the calculated fiber perimeter P due to instrumental errors. (This airflow device senses the fiber's specific surface at two different specimen compressions; P and wall thickness t are computed from the readings.) Systematic changes over time in instrument values from designated true values are classified into thirteen nontrivial combinations. Each combination results in different P values and, consequently, a unique drift or error in P. Simulations of 50,000 Arealometer observations using actual standard deviation data from a control cotton are also run. These simulations show that random variations in instrument values over time are, in effect, an unordered sequence of the nontrivial combinations. Also, a mean taken from only two to six Arealometer observations— the accepted practice—does not adequately characterize a cotton sample. Fundamental relationships are probed with partial and total derivatives of Arealometer functions. There is more variability in the calculated P than in the t value. The total differential dP accurately measures the error in P, given the error in the instrument values.Two important properties of cotton are its maturity and fineness. The fundamental measure of maturity is fiber wall thickness, and the fundamental measure of fineness is the fiber's cross-sectional perimeter. (All other geometric measures of maturity and fineness, such as fiber wall area, Micronaire, maturity index, and dye maturity, are, in fact, nothing more than different functions or combinations of wall thickness and perimeter. An infinite number of combinations of wall thickness and perimeter are possible [ 13 ] . ) Maturity and fineness also influence end-use properties such as mechanical processability, dye uptake, luster, fiber cohesion, yarn strength, and uniformity.Thus we write, for example, cross-sectional wall area ( WA ) and micronaire ( Mic) as functions of wall thickness and perimeter: See reference 10 for a proof of Equatiori 1. Equation 3 is given without proof; its derivation will be presented elsewhere: Substitution of Equation 1 into Equation 3 yields Equation 4:This labdratory is developing a high speed method of analysis for t and Phrased on near-infrared reflectance spectroscopy ( NIRS ). The speed of analysis by NIRS is comparable to that of high volume instruments ( HVI ) that currently measure several other components of cotton quality.Basic research in this laboratory has shown unequivocally that NIRS senses t and P simultaneously and independently [10][11][12][13][14][15] . Consequently, all the other measures of maturity and fineness may be measured. The observed NIR reflectance is primarily a function of t and P and, to a lesser extent, the impurities in cotton. (See Table I for a comparison of fiber properties sensed by the Micronaire instrument and by NIRS.)The reflectance R can be described by the simplified linear equationwhere OD is the reflectance in optical density units (i.e., log 1 /R) and a, b...

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“…It has been successfully applied for the quantification of reducing sugars on the cotton surface and for the prediction of cotton colour and physical attributes. [21][22][23][24][25][26][27][28] considering the unique nature of trash in cotton, few nIr studies have been conducted and the results obtained have raised challenges. for example, thomasson and Shearer 21 reported the optimal nIr models for eight cotton quality characteristics and observed the lowest r 2 value (0.60) for trash components.…”

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Assessment of Recovered Cotton Fibre and Trash Contents in Lint Cotton Waste by Ultraviolet/Visible/Near Infrared Reflectance Spectroscopy

Liu

Gamble

Thibodeaux

2010

Journal of Near Infrared Spectroscopy

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In the cotton industry, each processing stage produces a considerable amount of cotton waste, or trash. these wastes are mixtures of fractions from cotton plants (leaf, stem, seed coat and hull), cotton fibres that mingled in and other components (such as motes and dust). cotton wastes not only present a challenge to environmental management, but also reduce manufacturers' profits, as they contain some degree of cotton fibre with quality similar to that of the cleaned cotton. 1-3 therefore, a great concern in the cotton industry is to strengthen cleaning efficiency before and after the cotton ginning by developing various cleaning machines and procedures. 3-6

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An Investigation of the Relationship between Cotton Fineness and Light Scattering from Thin Webs as Measured by Near-Infrared Transmission Spectroscopy

Cited by 12 publications

References 3 publications

Development of Fourier transform infrared spectroscopy in direct, non-destructive, and rapid determination of cotton fiber maturity

Development of Fourier transform infrared spectroscopy in direct, non-destructive, and rapid determination of cotton fiber maturity

A Critical Evaluation of the Relationships Between Arealometer Instrument Values and Cotton Fiber Perimeter

Assessment of Recovered Cotton Fibre and Trash Contents in Lint Cotton Waste by Ultraviolet/Visible/Near Infrared Reflectance Spectroscopy

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