Joseph G. Montalvo

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

Reported here is the development of a comparative reflectance model that predicts the relative change in NIR diffuse reflectance of cotton, a hollow fiber, according to the cross-sectional dimensions of perimeter, wall thickness, and wall area. Two cotton groupings are considered: paired cottons and any number of cottons of the same perimeter. The model is based on a single wavelength of NIR light and the critical assumption that the total fiber length in the optical path is constant for cottons of the same perimeter. Combinations of paired dimensional variables are derived and classified by selection rules as “allowed” or “forbidden.” Seven allowed nontrivial combinations of perimeter, wall thickness, and wall area are identified. On the basis of the derived equation that optical density (O.D., log 1/R units) is a linear function of wall thickness at constant perimeter, comparative reflectances are predicted for all seven nontrivial combinations. The predicted comparative reflectances at a single wavelength range from nonunique (i.e., overlap or equivalent O.D.) to unique; those across many wavelengths are all unique. Also, a mechanism is proposed to explain the interaction of photons with fiber. Finally, the fundamental fiber property sensed is elucidated in three-dimensional (3-D) and 2-D fiber space.

Near Infrared Measurement of Cotton Fiber Micronaire, Maturity and Fineness - a Comparative Investigation

A key cotton fiber quality property is micronaire, which acts as an indicator of the fiber’s maturity and fineness. Previous studies have demonstrated the ability of Near Infrared (NIR) instrumentation to measure these cotton properties with varying degrees of success, but these studies did not provide conclusions on the capabilities of NIR spectroscopy as a general technique for these analyses. Recent advances in NIR technology could result in improved measurements of these cotton properties. A comparative investigation was implemented to determine the capabilities of modern commercial bench-top and portable NIR systems to monitor cotton fiber micronaire, maturity, and fineness in order to gain insight as to the “universality” of the NIR measurements for these fiber properties. Cotton samples were analyzed on five commercial systems and an older, custom-built system. Very good spectral agreement was observed between the portable and bench-top NIR units. The rapid and simultaneous measurement of cotton micronaire, maturity, and fineness by multiple commercial systems was demonstrated and compared favorably to the custom system, but without the delay and cost in building custom units. For the bench-top NIR systems, all end-state criteria were successfully meet. The “universal” nature of the NIR measurement of these cotton fiber properties was validated for commercial NIR systems. As expected, the NIR results for the portable NIR units were normally not as good as those for the bench-top instruments, but they were very acceptable for demonstrating the potential for the portable units to measure these cotton fiber properties.

Near Infrared Measurement of Cotton Fiber Micronaire by Portable Near Infrared Instrumentation

In the U.S.A., cotton is classed (primary quality parameters) by the Uster ® High Volume Instrument (HVI), which must be maintained under tightly controlled laboratory environmental conditions. Improved and fast response quality measurement systems and tools are needed to rapidly assess the quality of cotton. One key area of emphasis and need is the development and implementation of new fast-response quality measurements that can be used not only in the laboratory but which also can be adapted to field and at-line quality measurements. A program was implemented to determine the ability of portable near-infrared (NIR) instrumentation to monitor critical fiber properties of cotton samples in the laboratory, at-line, and in the field, with initial emphasis on the laboratory measurement of cotton fiber micronaire. Micronaire is a key cotton property, and it is an indicator of the fiber’s maturity and fineness. Distinct NIR spectral differences between samples with varying micronaire were observed. A comparative evaluation was performed to determine optimum instrumental conditions for laboratory cotton micronaire measurements. The comparative evaluation established that the optimum instrumental conditions for laboratory measurements of micronaire was obtained with the use of a glass-covered sampling port and increased instrumental gain, with high R 2 values, low residuals, and with ≤ 12% outliers. For a NIR measurement with potential for multiple simultaneous analyses and non-laboratory measurements, the micronaire measurement was fast (< 3 min per sample) and easy to perform. The rapid and accurate laboratory measurement of cotton fiber micronaire with portable NIR instrumentation was demonstrated.

Studies to measure cotton fibre length, strength, micronaire and colour by vis/NIR reflectance spectroscopy. Part II: Principal components regression

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 cottons 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.

A Comparative Study of NIR Diffuse Reflectance of Cottons Grouped According to Fiber Cross-Sectional Dimensions. Part II: Optical Path Simulations

In Part I of this series, a model was proposed to predict the comparative NIR reflectance of cottons grouped according to cross-sectional dimensions. The critical assumption in the model is that total fiber length in the diffuse reflectance optical path is constant among cottons of the same perimeter. This paper introduces an alternative assumption: that the volume of solid cellulose (i.e., mass) in the diffuse reflectance optical path is constant for cottons of the same perimeter. Optical path simulations are used to predict the consequences of either assumption. One method of simulation is based on diffuse reflectance calculations and the other on relating diffuse reflectance to diffuse transmittance. In the diffuse reflectance calculations, 13 variables are included in the simulation model. Relating reflectance to transmittance is justified because sample weights for the latter can be selected a priori to produce either a constant total fiber length or a constant volume of solid cellulose in the optical path. The simulations support the premise that the critical assumption in the comparative reflectance model is correct. The study goes further to produce diagnostic criteria from the simulation results for testing the assumptions.

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

Near-infrared transmission spectroscopy (NITS) is applied to thin cotton webs to measure fiber fineness (expressed either as specific surface—the external surface area per unit weight of fiber—or as cross-sectional perimeter). We report here the development and successful testing of a mathematical model that predicts a linear relationship between fineness and light-scattering intensity (optical density, log 1/T) by a thin cotton web. With a thin web of fibers in the light beam, absorption of photons out of the beam is negligible. When the detector is placed several inches from the web, only the photons passing between the fibers strike the light detector. Photons that strike a fiber are scattered out of the light beam and away from the detector. Thus the fineness of the fiber controls the propagation of light to the detector. The premise that specific surface is proportional to optical density when the weight of fiber in the light beam is constant is shown experimentally (probability, p < 0.0045). Also, the premise that perimeter is proportional to optical density when the total length of fiber in the light beam is constant is shown experimetally (p < 0.0070). These results are based on analysis of 9 cottons; 810 webs were produced, computer sorted by weight, and the scatter spectra recorded for 360 webs.

Biased Experimental Fineness and Maturity Results

In an earlier paper, we developed models and performed computer simulations to understand the variability in coefficients of determination (R2) between fineness and maturity, micronaire and fineness, and micronaire and maturity of cotton. We subsequently concentrated on derivation and testing of several diagnostic models to enhance the R2 and provide information about the analytical quality (accuracy) of the results. We then introduced modeling of biased fineness and maturity results. Error functions were derived based on micronaire values, specifically, Lords micronaire model. This paper demonstrates testing of a key diagnostic model on two different sample sets of 21 cottons. The results from one sample set — analyzed on the fineness and maturity tester — fit the model. Results from the other sample set — analyzed on both the advanced fiber information system (AFIS) A-2 and AFISPRO — demonstrate a lack of fit to the diagnostic model. This lack of fit is due to bias in the AFIS fineness and maturity measurements compared to the more traditional Lords micronaire model. As a consequence of the bias, the dynamic range of the AFIS raw data for both fineness and maturity is very narrow. Results are confirmed by image analysis.

Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by Vis/NIR Reflectance Spectroscopy. Part I: Descriptive Statistics of Fibre Properties and Reflectance Spectra

Fibre property data representing the 1989 and 1990 crop years and its reflectance spectra are analysed using standard error, regression and correlation analysis. The six properties of interest are upper-half mean length, uniformity index, strength and micronaire measured on two high volume instrument systems placed side-by-side, and colour (Rd and +b) measured by the traditional lab system. Visible (vis) and near infrared (NIR) reflectance spectra are observed on a scanning spectrophotometer, and span the 400–2500 nm range. Three findings highlight the research. One, a diagnostic test is presented to decide, a priori of reflectance spectroscopy, the degree to which the mean property values have reduced random error. Two, the standard error of replicate spectra provides a way to probe the fibre mass in the diffuse reflectance optical path. The spectral error is strongly influenced by both how the cotton is packed into the spectrophotometric cell and the non-homogeneity of the sample. And three, correlations between the spectra confirm that some visible and NIR wavelength regions contain mutually exclusive information about the properties of this natural staple.

Theoretical and Experimental Profiles of Fiber Fineness and Maturity Using the Shirley Micromat and the Zellweger Uster Advanced Fiber Information System Module

Past research has demonstrated that the fundamental properties of wall thickness and perimeter, computed from the fmt (Micromat model) readings, produce better correlations with the Southern Regional Research Center (SRRC) near-infrared high volume instrumentation (nir hvi) than similar property data from the afis fineness and maturity module. (The nir hvi analyzes about 3,000,000 fibers or 30 g, the Micromat 400,000 fibers or 4 g, and the afis 5000 fibers or 0.05 g, a single fiber at a time.) To help understand these differences in correlation, we probe the random and systematic variations in the Micromat and afis data using appropriate data analysis techniques. We present descriptive statistics and an internal correlation of paired means from replicate measurements, and we compare the fit of wall thickness versus perimeter with the expected theoretical fit. Preliminary results suggest that the Micromat is more robust in representing changes in mean wall thickness and perimeter values. Direct comparison of wall thickness and perimeter from each method shows that although the relationships are highly significant, the values are different.

A Critical Evaluation of the Relationships Between Arealometer Instrument Values and Cotton Fiber Perimeter Part I: Fundamentals and Computer Simulation

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 fibers 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.