Gary R. Gamble

Chemical, microscopic, and instrumental analysis of graded flax fibre and yarn

A series of flax fibre and yarn samples that had been commercially graded low, medium, and high quality were analysed by light microscopy, wet chemical analysis, Raman spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy to determine characteristics which could be related to quality ratings for each sample type. Light microscopy revealed fragments of cuticular and epidermal material bound to the fibres. As the quality ratings improved, fewer of these fragments were found and greater separation of the fibre bundles to smaller bundles and, in some cases, elementary fibres occurred indicating more efficient retting. Chemical evaluation showed that, as quality of the yarns increased, amounts of fatty acid and long-chain alcohols as well as dihydroxy fatty acids decreased. Chemical data on fibre did not show consistent trends with quality. Raman spectroscopy showed increasing amounts of cellulose and decreasing amounts of aromatics and hydrocarbons with increasing quality, which paralleled the chemical data. NMR analysis showed nearly equal amounts of crystalline cellulose regardless of quality for both fibre and yarn samples. The strengths and weaknesses of each analytical method are discussed. This initial study suggested that chemical constituents characteristic of cutin and waxes could be used as an initial marker of quality. © 1999 Society of Chemical Industry

Characterization of Attenuated Total Reflection Infrared Spectral Intensity Variations of Immature and Mature Cotton Fibers by Two-Dimensional Correlation Analysis

Two-dimensional (2D) correlation analysis was applied to characterize the attenuated total reflection (ATR) spectral intensity fluctuations of immature and mature cotton fibers. Prior to 2D analysis, the spectra were leveled to zero at the peak intensity of 1800 cm−1 and then were normalized at the peak intensity of 660 cm−1 to subjectively correct the variations resulting from ATR sampling. Next, normalized spectra were subjected to principal component analysis (PCA), and two clusters of immature and mature fibers were confirmed on the basis of the first principal component (PC1) negative and positive scores, respectively. The normalized spectra clearly demonstrated the intensity increase or decrease of the bands ascribed to different C–O confirmations of primary alcohols in the 1050–950 cm−1 region, which was not apparent from raw ATR spectra. The PC1 increasing-induced 2D correlation analysis revealed remarkable differences between the immature and mature fibers. Of interest were that: (1) Both intensity increase of two bands at 968 and 956 cm−1 and the shifting of 968 cm−1 in immature fibers to 956 cm−1 in mature fibers, together with the intensity decreasing and shifting of the 1048 and 1042 cm−1 bands, are the characteristics of cotton fiber development and maturation. (2) Intensities of most bands in the 1800–1200 cm−1 region decreased with the fiber growth, suggesting they are from either noncellulosic components or CH and OH fractions in amorphous celluloses. (3) The reverse sequence of intensity variations of the bands in the 1100–1000 cm−1 and 1000–900 cm−1 region of asynchronous spectra indicated a different mechanism of compositional and structural changes in developing cotton fibers at different growth stages.

Two-Dimensional Attenuated Total Reflection Infrared Correlation Spectroscopy Study of the Desorption Process of Water-Soaked Cotton Fibers

Two-dimensional (2D) correlation analysis was applied to characterize the attenuated total reflection (ATR) spectral intensity fluctuations of native cotton fibers with various water contents. Prior to 2D analysis, the spectra were leveled to zero at the peak intensity of 1800 cm−1 and then were normalized at the peak intensity of 660 cm−1 to subjectively correct the changes resulting from water diffusion in fibers and resultant density dilution. Next, a new spectral set was subjected to principal component analysis (PCA) and two clusters of hydrated (≥13.3%) and dehydrated (<13.3%) fibers were obtained. Synchronous and asynchronous 2D correlation spectra from individual ATR spectral sets enhanced spectral resolution and provided insights about water-content-dependent intensity variations not readily accessible from one-dimensional ATR spectra. The 2D results revealed remarkable differences corresponding to water loss between the hydrated and dehydrated fibers. Of interest were that: (1) the intensity of the 1640 cm−1 water band remains in a steady state for hydrated fibers but decreases for dehydrated fibers; (2) during the desorption process of adsorbed water, small and water-soluble carbonyl species (i.e., esters, acids, carboxylates, and proteins) begin to accumulate on the cotton surface, resulting in possible changes in the coloration and surface chemistry of native cotton fibers that were rained on prior to harvesting; (3) intensities of bands in the 1200 to 950 cm−1 region exhibit a more apparent intensity increase than those in the 1500 to 1200 cm−1 region, indicating the sensitivity of the 1200 to 950 cm−1 infrared (IR) region to intra- and inter-molecular hydrogen bonding in fiber celluloses; and (4) the 750 cm−1 band, ascribed to the unstable Iα phase in amorphous regions, might originate from the cellulose–water complex through hydrogen bonding.

Exudate Protein Composition and Meat Tenderness of Broiler Breast Fillets

The relationship between meat tenderness and the protein composition of muscle exudates collected from broiler breast fillets deboned at different postmortem times was investigated. A total of 85 broilers were processed and breast fillets from each carcass were deboned at either 2 h (early-deboned, EB) or 24 h (control) postmortem. One fillet per carcass was used for 1 d postmortem meat tenderness measurements and the other fillet was stored at 4°C until 6 d postmortem for the collection of exudate prior to tenderness evaluation. Protein content and composition of muscle exudates were determined by a biuret assay and SDS-PAGE. Fillet pH, color, drip loss, and cook loss were also measured. Early-deboned fillets exhibited greater (P < 0.05) Warner-Bratzler shear force (WBSF) than controls at 1 d (7.4 vs. 3.1 kg) and 6 d (4.1 vs. 2.5 kg). Deboning time did not influence pH or color values (L*a*b*). Control fillets exhibited less drip loss after 6 d of storage (P = 0.005) and less cook loss at 1 and 6 d (P < 0.001). Exudate protein concentration was not influenced by deboning time. From the SDS-PAGE profiles of the exudates, the relative abundances of seventeen protein bands were quantified. Electrophoresis analysis revealed that, in general, the protein profiles of exudates from control and EB fillets were not distinct from each other. However, the band corresponding to 225 kDa was more abundant in controls (P = 0.021). Although the protein concentrations and SDS-PAGE profiles of muscle exudates varied widely between breast fillets, variations in exudate protein characteristics were not strongly associated with changes in the tenderness of broiler breast meat due to the combined effects of postmortem deboning time and post-deboning aging.

Solid State13C NMR and Diffuse Reflectance Mid-Infrared Spectroscopic Analysis of the Effects of Retting on the Chemical Composition of KenafFibre

Bast ribbons from Tainung 1 (T 1 ) and Guatemala 45 (G 45 ) cultivars of kenaf (Hibiscus cannabinus) were subjected to a chemical retting process. The resulting changes at the base and tip regions of each cultivar were analysed using solid-state 13 C NMR and diffuse reflectance mid-infrared spectroscopies. Chemical retting was performed by boiling the substrates in NaOH (70 g litre -1 ) + NaHSO 3 (5 g litre -1 ) for 1 h, after which they were neutralised, washed and air dried. This process produced large decreases in the non-cellulosic components, though 25% of the phenolic component was left undegraded, and cellulose crystallinity was increased by ∼5% over that in unretted samples.

Hyperspectral imaging using a color camera and its application for pathogen detection

This paper reports the results of a feasibility study for the development of a hyperspectral image recovery (reconstruction) technique using a RGB color camera and regression analysis in order to detect and classify colonies of foodborne pathogens. The target bacterial pathogens were the six representative non-O157 Shiga-toxin producing Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) grown in Petri dishes of Rainbow agar. The purpose of the feasibility study was to evaluate whether a DSLR camera (Nikon D700) could be used to predict hyperspectral images in the wavelength range from 400 to 1,000 nm and even to predict the types of pathogens using a hyperspectral STEC classification algorithm that was previously developed. Unlike many other studies using color charts with known and noise-free spectra for training reconstruction models, this work used hyperspectral and color images, separately measured by a hyperspectral imaging spectrometer and the DSLR color camera. The color images were calibrated (i.e. normalized) to relative reflectance, subsampled and spatially registered to match with counterpart pixels in hyperspectral images that were also calibrated to relative reflectance. Polynomial multivariate least-squares regression (PMLR) was previously developed with simulated color images. In this study, partial least squares regression (PLSR) was also evaluated as a spectral recovery technique to minimize multicollinearity and overfitting. The two spectral recovery models (PMLR and PLSR) and their parameters were evaluated by cross-validation. The QR decomposition was used to find a numerically more stable solution of the regression equation. The preliminary results showed that PLSR was more effective especially with higher order polynomial regressions than PMLR. The best classification accuracy measured with an independent test set was about 90%. The results suggest the potential of cost-effective color imaging using hyperspectral image classification algorithms for rapidly differentiating pathogens in agar plates.

An approach to determine calibration samples in NIR modelling for cotton fibre strength

adopted for cotton fi bre quality assessment, little effort has been made to unravel the relationship between the two. In the latest study, 5 we have not only demonstrated the consistency of strength readings between two instruments if the strength readings were divided by cotton micronaire, but also developed a better NIR model by using the modifi ed strength index rather than using raw strength data as reference values. Nevertheless, two strength readings from two independent strength tests should be highly correlated if the cotton fi bres used for the testing are homogeneous. This concept could be implemented before developing a NIR model on cotton strength to select an appropriate sample set.

Assessment of recovered cotton fibre and trash contents in lint cotton waste by ultraviolet/visible/near-infrared reflectance spectroscopy

Lint cleaning at cotton processing facilities is performed in order to reduce the non-lint materials to the lowest level with minimal fibre damage. The resultant waste contains some degree of cotton fibre having equal quality to the fibre in the bale and, hence, is of great concern for operating cost and profit. Traditional methods for measuring the non-lint material, or trash, in the cotton industry, including the Shirley Analyzer and high volume instrumentation, are labour intensive and time consuming. Ultraviolet (UV)/visible/near infrared (NIR) spectroscopy, a rapid and easy sampling technique, was examined for its feasibility in determining the relative proportions of recovered cotton fibre and trash in lint cotton waste. Cotton waste was scanned in the region of 220–2500 nm and the reference value was measured by a Shirley Analyzer. Partial least squares regression models were developed in various spectral ranges and then compared. Although there were obvious spectral differences in the visible and NIR regions between trash and cotton fibre, the model performance from a narrow NIR region of 900–1700 nm was nearly equivalent to that from the full 226–2496 nm spectral region. Meanwhile, simple two-band difference algorithms utilising two unique bands were developed and also suggested the effectiveness of two NIR bands, at 900 nm and 1135 nm, in the assessment of fibre and trash components in cotton waste. Furthermore, considering the different sampling species between the reference and spectral measurements, a 90% confidence interval was applied to remove outlier samples from the calibration and validation sets. The recalibrated models revealed the feasibility of the NIR technique for the determination of visible trash and recovered cotton fibre content in lint cotton waste.

Simple XRD algorithm for direct determination of cotton crystallinity

Traditionally, XRD had been used to study the crystalline structure of cotton celluloses. Despite considerable efforts in developing the curve-fitting protocol to evaluate the crystallinity index (CI), in its present state, XRD measurement can only provide a qualitative or semi-quantitative assessment of the amounts of crystalline and amorphous cellulosic components in a sample. The greatest barrier to establish quantitative XRD is the lack of appropriate cellulose standards needed to calibrate the measurements. In practical, samples with known CIs are very difficult to be prepared or determined. As an approach, we might assign the samples with reported CIs from FT-IR procedure, in which the threeband ratios were first calculated and then were converted into CIs within a large and diversified pool of cotton fibers. This study reports the development of simple XRD algorithm, over time-consuming and subjective curve-fitting process, for direct determination of cotton cellulose CI by correlating XRD with the FT-IR CI references.

Development of simple algorithm for direct and rapid determination of cotton maturity from FT-IR spectroscopy

Fourier transform infrared (FT-IR) 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 1200-900 cm-1 region, and such spectral distinctions formed the basis on which to develop 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 FT-IR 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 MAFIS and between MIR and MIA among either International Cotton Calibration (ICC) 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.