Yongliang Liu

Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study.

Color, instrumental texture, and sensory attributes of steaks from 24 beef carcasses at 2, 4, 8, 14, and 21 days post mortem were predicted by visible/near infrared (visible/NIR) reflectance spectroscopy in 400-1080 nm region. Predicting the Hunter a, b, and E* yielded the coefficient of determination (R(2)) in calibration to be 0.78-0.90, and R(2) was between 0.49 and 0.55 for tenderness, Hunter L, sensory chewiness and juiciness. The prediction R(2) for tenderness was in the range of 0.22-0.72 when the samples were segregated according to the aging days. Based on partial least square (PLS) model predicted tenderness, beef samples were classified into tender and tough classes with a correct classification of 83%. Soft independent modeling of class analogy of principal component analysis (SIMCA/PCA) model of measured tenderness showed great promise in the classification of tender and tough meats with over 96% success.

Two-dimensional Fourier transform Raman correlation spectroscopy determination of the glycosidic linkages in amylose and amylopectin.

Amylose and amylopectin are two major carbohydrates in cereal and cereal food products. Both of these polysaccharides have complex conformations that affect their physical, chemical, and biological activities,1 despite the fact that they are mainly made up of a-(1→4)-linked Dglucose residues. Generally, amylose has been considered to be a linear polymer through a-D-(1→4) glycosidic linkages (Fig. 1), although now there is evidence that amylose is not completely linear. Amylopectin is a branched polymer, and a branch point occurs approximately every 20–25 glucose units when a chain of a-D(1→4) glucose units is linked to the C-6 hydroxymethyl position of a glucose molecule through an a-D-(1→6) glycosidic linkage. Thus, about 4–5% of the glucose units in amylopectin are involved in branch points. Clearly, both the relative proportions of amylose to amylopectin and a-D-(1→6) branch points depend on the source of the starch.2 Raman spectroscopy has found considerable applica-

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

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.

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.

Characterization of Developmental Immature Fiber ( im) Mutant and Texas Marker-1 (TM-1) Cotton Fibers Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy.

The immature fiber (im) mutant is one type of cotton fiber mutant with unique characteristics of non-fluffy cotton bolls. Compared to its near-isogenic wild type Texas Marker-1 (TM-1), im fiber has a thin secondary cell wall and is less mature. In this work, we applied the previously proposed principal component analysis (PCA) and simple algorithms to analyze the attenuated total reflection Fourier transform infrared (ATR FT-IR) spectra of developmental im and TM-1 fibers. The results from these approaches could not effectively and consistently indicate the inherent difference between TM-1 and im fibers at the same developmental stage. The difference between TM-1 and corresponding im fibers was detected when comparing the normalized intensity variations of the 730 cm−1 bands. The 730 cm−1 band intensities in developmental im fibers are temporally lower than those in developmental TM-1 fibers although they became similar when the TM-1 and im fibers are fully mature. The observation might imply the likelihood of temporal reduction of amorphous regions in developmental im fibers rather than in developmental TM-1 fibers.

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.

Improving NIR Model for the Prediction of Cotton Fiber Strength

Cotton fiber strength is an important quality characteristic that is directly related to the manufacturing of quality consumer goods. Currently, two types of instruments have been implemented to assess cotton fiber strength, namely, the automation oriented high volume instrument (HVI) and the laboratory based Stelometer. Each has unique merits but correlation between two readings was reported to be relatively low. Nevertheless, two strength values from two independent testing should be highly correlated. This concept could be applied to determine the appropriate samples in calibration set, prior to develop NIR model on HVI strength. For the first time, we proposed a pre-screening procedure to determine appropriate calibration samples in NIR models. As a validation and complementary approach, the FT-IR spectra were collected on small broken Stelometer specimens (~0.4 mg) and correlated with cotton Stelometer strength. The results suggested that the capability of NIR model on HVI strength is in good agreement with that of FT-IR model on Stelometer strength, verifying the potential of NIR technique in robust, reliable and quantitative determination of HVI strength.

Evaluation of 3 Cotton Trash Measurement Methods by Visible / Near-Infrared Reflectance Spectroscopy

Currently, 3 types of instrumentals have been developed to assess the trash content in lint cotton fibers, namely, Shirley analyzer (SA), advanced fiber information system (AFIS), and high volume instrumentation (HVI). Each of these devices has its unique advantages, and comprehensive comparison between them has not been attempted. Visible / near infrared (NIR) spectroscopy could be a potential and independent tool for their evaluation. Partial least squares (PLS) regression models, relating the spectral response in 400-2500 nm visible/NIR region to the respective SA, AFIS, and HVI readings, were developed in various spectral ranges from two chemometric packages (Foss Vision and Thermo Grams/AI) and then compared. Because of different strategies to select calibration and validation samples between two commercial packages, resultant NIR trash models were inconsistent. 2 HVI and AFIS readings were observed to have better model performances in Thermo Grams/AI approach than in Foss Vision, and are acceptable for quantitative determination of cotton trash content. Furthermore, considering the different sampling species between reference and spectral measurement, 90% confidential interval was applied to remove outlier samples. The recalibrated models verified that HVI trash module might be the most promising one in precise and accurate determination of trash content in lint cottons.