A Comparative Study of NIR Diffuse Reflectance of Cottons Grouped According to Fiber Cross-Sectional Dimensions. Part I: Fundamentals

Montalvo, JR Joseph G.

doi:10.1366/0003702914336426

Cited by 20 publications

(5 citation statements)

References 2 publications

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“…In addition, FT-NIR instruments are capable of carrying out measurements on samples with longer path lengths than that of FT-IR spectrometers (Perkampus, 1995). These advantages make the study of textiles using FT-NIR, specifically for cotton, very attractive (Rodgers, 2002;Thomasson and Shearer, 1995;Camjani and Muller, 1996;Thibodeaux, 1992;Rodgers and Beck, 2005;Rodgers and Beck, 2009;Rodgers and Ghosh, 2008;Montalvo, et al, 1991).…”

Section: Comparison Of the Ft-ir And Ft-nirmentioning

confidence: 99%

Fourier Transform Spectroscopy of Cotton and Cotton Trash

Fortier¹

2012

Fourier Transform - Materials Analysis

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Section: Comparison Of the Ft-ir And Ft-nirmentioning

confidence: 99%

Fourier Transform Spectroscopy of Cotton and Cotton Trash

Fortier¹

2012

Fourier Transform - Materials Analysis

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“…On the other hand, MIC is a function of wall thickness and perimeter, both of which are sensed concurrently in the 1100-2498 nm region of the spectrum due to light absorption by the cellulosic wall of the fibre. [8][9][10][11] The primary spectral region for both colour measures is the 400-1100 nm region because radiation in the visible range senses electronic structures (i.e. colour functional groups) of molecules.…”

Section: Underlying Spectroscopic Mechanismsmentioning

confidence: 99%

Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by vis/NIR Reflectance Spectroscopy. Part II: Principal Components Regression

Montalvo

Buco

Ramey

1994

Journal of Near Infrared Spectroscopy

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In Part I of this series, both cotton fibre property and reflectance spectra data on 185 US cottons including four Pimas were analysed by descriptive statistics. In this paper, principal components regression (PCR) models for measuring six properties from the cotton's vis/NIR reflectance spectra are critically examined. These properties are upper-half mean length (UHM), uniformity index (UI), bundle strength (STR), micronaire (MIC) and colour (Rd and +b). The spectra were recorded with a scanning spectrophotometer in the wavelength range from 400 to 2498 nm. A variety of spectral processing options, some of which give improved PCR analysis results, were applied prior to the regressions and allowed for testing of over 100 PCR models. All PCR model results are based on the PRESS statistic by one-out-rotation, a fast approximation of the PRESS statistic (to reduce computer time) or on cluster analysis using separate calibration and validation data sets. The standard error of prediction (SEP) of all the properties except UHM compared well to the reference method precision. The precision of the UHM measure by reflectance spectroscopy was strongly influenced by the sample repack error. The SEP of UHM, UI and STR was improved by excluding the Pimas from the data set.

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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

confidence: 99%

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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A Comparative Study of NIR Diffuse Reflectance of Cottons Grouped According to Fiber Cross-Sectional Dimensions. Part I: Fundamentals

Cited by 20 publications

References 2 publications

Fourier Transform Spectroscopy of Cotton and Cotton Trash

Fourier Transform Spectroscopy of Cotton and Cotton Trash

Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by vis/NIR Reflectance Spectroscopy. Part II: Principal Components Regression

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

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