Direct observation of bulk and surface chemical morphologies of Ginkgo biloba leaves by Fourier transform mid- and near-infrared microspectroscopic imaging

A Rapid Non-Targeted Method for Detecting the Adulteration of Black Pepper with a Broad Range of Endogenous and Exogenous Material at Economically Motivating Levels Using Micro-ATR-FT-MIR Imaging

Infrared spectroscopy is often used as a simple, fast, and green method to screen for economically motivated adulteration in spices. However, conventional microscopy remains the reference method. In this research, the combination of microscopy and Fourier-transform infrared spectroscopy in mapping mode, namely, micro-FTIR imaging, along with Principle Component Analysis were used to develop a non-targeted method for detecting a broad range of organic and mineral bulking agents that could potentially be used to adulterate black pepper. This method, based on the spatial distribution of black pepper chemical composition, has been thoroughly validated as a one-class, non-targeted classification method. Results are categorized as Typical or Atypical, where an Atypical result indicates a high probability of adulteration. For an Atypical outcome, a multitool investigational approach is then used for the detection and identification of the potential adulterant.

Principles and Applications of Vibrational Spectroscopic Imaging in Plant Science: A Review

Detailed knowledge about plant chemical constituents and their distributions from organ level to sub-cellular level is of critical interest to basic and applied sciences. Spectral imaging techniques offer unparalleled advantages in that regard. The core advantage of these technologies is that they acquire spatially distributed semi-quantitative information of high specificity towards chemical constituents of plants. This forms invaluable asset in the studies on plant biochemical and structural features. In certain applications, non-invasive analysis is possible. The information harvested through spectral imaging can be used for exploration of plant biochemistry, physiology, metabolism, classification, and phenotyping among others, with significant gains for basic and applied research. This article aims to present a general perspective about vibrational spectral imaging/micro-spectroscopy in the context of plant research. Within the scope of this review are infrared (IR), near-infrared (NIR) and Raman imaging techniques. To better expose the potential and limitations of these techniques, fluorescence imaging is briefly overviewed as a method relatively less flexible but particularly powerful for the investigation of photosynthesis. Included is a brief introduction to the physical, instrumental, and data-analytical background essential for the applications of imaging techniques. The applications are discussed on the basis of recent literature.

Integrated recognition and quantitative detection of starch in surimi by infrared spectroscopy and spectroscopic imaging

Surimi products have become increasingly-consumed food with prominent characteristics of high nutrition and convenience and its supply falls short of demand. However, due to exhausted fishery resource in recent years, surimi adulteration, such as addition of plant proteins, starch and other animal origin meat, is becoming serious, so recognition of these exogenous substances has become an urgent issue. In this study, Fourier transform infrared spectroscopy (FT-IR) combined with infrared spectroscopic imaging could distinguish heterogeneity in surimi qualitatively and quantitatively and obtain integral chemical images so that spatial distribution of each component in surimi could be visually displayed, thus a rapid recognition method and a prediction model were developed. The different starch contents in surimi had been primarily identified through intensity change of infrared absorption peaks at 1045cm^-1 and 988cm^-1, specifically with peak shifts to 1041cm^-1 and to 992cm^-1, respectively. In infrared imaging analysis, principal components (PCs) were separated and one key PC was confirmed as starch by characteristic peaks comparison at 1147cm^-1, 1075cm^-1, 997cm^-1 and 930cm^-1. Meanwhile, an established statistic model could predict starch content in surimi correctly with a reliable correlation coefficient (R=0.9856) and root mean square error of prediction (RMSEP=5.64). Therefore, FT-IR combined with infrared spectroscopic imaging could be applicable to integrally recognize and quantitatively detect starch in surimi.

Enhanced chemical and spatial recognition of fish bones in surimi by Tri-step infrared spectroscopy and infrared microspectroscopic imaging

Surimi is an intermediate product with an increasing popularity worldwide. Discrimination of impurities like fish bones in surimi has become an urgent issue owing to the food safety and the improved requirements for assessment methods in identification of surimi quality and grades. A Tri-step infrared spectroscopy, including Fourier transform infrared spectroscopy (FT-IR), second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR) has been applied to integrally discriminate different contents (1%-8%) of fish bones in surimi at macro-scale. Meanwhile, attenuated total reflection infrared spectroscopy (ATR-IR) microspectroscopic imaging has been employed to recognize and identify the location of fish bones (less than 1.0 mm in size) in micro-scale. Fishbone characteristic infrared absorption peak at 1011 cm^-1 contributes to surimi peaks at 1045 cm^-1 and 988 cm^-1 confirmed by calculation of their peak heights and ratios of peak areas in original spectra. SD-IR spectra enhance the difference in range of 1440-500 cm^-1, and specifically peak intensity at 599 cm^-1 is significantly increased in surimi with 3%-8% fish bones. Moreover, 2DCOS-IR spectra reveal that surimi containing fish bones have increased intensity of auto-peaks at 525 cm^-1, 519 cm^-1, 512 cm^-1 and 505 cm^-1 mainly contributed by hydroxyapatite and collagen. In ATR-IR microspectroscopic images, a clear fishbone shape (800 × 200 μm) corresponding to its visible image is clearly observed in principal component (PC) score image, which is confirmed as a fish bone by corresponding pixel spectra. Furthermore, the single-wavenumber image shows the spatial chemical distribution of various components for both the fish bone and surimi. Consequently, fish bones can be integrally recognized by physical and chemical imaging manners. It has been demonstrated that the developed Tri-step infrared spectroscopy and ATR-IR microspectroscopic imaging could be applicable for rapidly recognizing impurities and adulterants in surimi.

Quantitative visualization of lignocellulose components in transverse sections of moso bamboo based on FTIR macro- and micro-spectroscopy coupled with chemometrics

BACKGROUND

Due to the increasing demands of energy and depletion of fossil fuel, bamboo is considered to be one of the most important renewable biological resources on the basis of its advantages of rapid growth ability and rich reserves. Cellulose, hemicellulose, and lignin are the three most important constituents in moso bamboo. Their concentrations and, especially, their microscopic distributions greatly affect their utilization efficiency and other physical properties as a biomass resource. However, no studies have achieved a quantitative visualization of the distribution of lignocellulose concentrations in transverse sections of bamboo. Therefore, this study proposed the use of quantitative multivariate spectral analysis to reveal the micro-chemical distribution of lignocelluloses in bamboo based on an integration of FTIR macro- and micro-spectroscopic imaging techniques.

RESULTS

Multivariate calibration models for the quantitative determination of lignocelluloses of bamboo were developed based on FTIR macro-spectroscopy, and the quantitative calibration models based on the FTIR characteristic bands showed an excellent performance with determination coefficients of 0.933, 0.878, and 0.912 for cellulose, hemicellulose, and lignin, respectively. These quantitative models were then utilized to the FTIR micro-spectroscopy of bamboo transverse sections which were corrected using a direct standardization algorithm. Subsequently, the micro-chemical distributions of cellulose, hemicellulose, and lignin were obtained based on the integration of the multivariate calibration models and corrected FTIR micro-spectroscopy. The combination of the multivariate calibration models and calibration transfer algorithm resulted in a final quantitative visualization of the chemical distributions of lignocelluloses in moso bamboos.

CONCLUSIONS

Integration of the FTIR macro- and micro-spectroscopic imaging techniques can provide comprehensive information that can be used to exploit the resource of moso bamboo to develop biofuels and biosynthetic materials.

A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis

Plant cells, tissues and organs are composed of various biomolecules arranged as structurally diverse units, which represent heterogeneity at microscopic levels. Molecular knowledge about those constituents with their localization in such complexity is very crucial for both basic and applied plant sciences. In this context, infrared imaging techniques have advantages over conventional methods to investigate heterogeneous plant structures in providing quantitative and qualitative analyses with spatial distribution of the components. Thus, particularly, with the use of proper analytical approaches and sampling methods, these technologies offer significant information for the studies on plant classification, physiology, ecology, genetics, pathology and other related disciplines. This review aims to present a general perspective about near-infrared and mid-infrared imaging/microspectroscopy in plant research. It is addressed to compare potentialities of these methodologies with their advantages and limitations. With regard to the organization of the document, the first section will introduce the respective underlying principles followed by instrumentation, sampling techniques, sample preparations, measurement, and an overview of spectral pre-processing and multivariate analysis. The last section will review selected applications in the literature.

Chemical morphology of Areca nut characterized directly by Fourier transform near-infrared and mid-infrared microspectroscopic imaging in reflection modes

Fourier transform near-infrared (NIR) and mid-infrared (MIR) imaging techniques are essential tools to characterize the chemical morphology of plant. The transmission imaging mode is mostly used to obtain easy-to-interpret spectra with high signal-to-noise ratio. However, the native chemical compositions and physical structures of plant samples may be altered when they are microtomed for the transmission tests. For the direct characterization of thick plant samples, the combination of the reflection NIR imaging and the attenuated total reflection (ATR) MIR imaging is proposed in this research. First, the reflection NIR imaging method can explore the whole sample quickly to find out typical regions in small sizes. Next, each small typical region can be measured by the ATR-MIR imaging method to reveal the molecular structures and spatial distributions of compounds of interest. As an example, the chemical morphology of Areca nut section is characterized directly by the above approach.

Emerging tools to study proteoglycan function during skeletal development

In the past 20years, appreciation for the varied roles of proteoglycans (PGs), which are specific types of sugar-coated proteins, has increased dramatically. PGs in the extracellular matrix were long known to impart structural functions to many tissues, especially articular cartilage, which cushions bones and allows mobility at skeletal joints. Indeed, osteoarthritis is a debilitating disease associated with loss of PGs in articular cartilage. Today, however, PGs have a demonstrated role in cell biological processes, such as growth factor signalling, prompting new perspectives on the etiology of PG-associated diseases. Here, we review diseases associated with defects in PG synthesis and sulfation, also highlighting current understanding of the underlying genetics, biochemistry, and cell biology. Since most research has analyzed a class of PGs called heparan sulfate PGs, more attention is paid here to studies of chondroitin sulfate PGs (CSPGs), which are abundant in cartilage. Interestingly, CSPG synthesis is tightly linked to the cell biological processes of secretion and lysosomal degradation, suggesting that these systems may be linked genetically. Animal models of loss of CSPG function have revealed CSPGs to impact skeletal development. Specifically, our work from a mutagenesis screen in zebrafish led to the hypothesis that cartilage PGs normally delay the timing of endochondral ossification. Finally, we outline emerging approaches in zebrafish that may revolutionize the study of cartilage PG function, including transgenic methods and novel imaging techniques. Our recent work with X-ray fluorescent imaging, for example, enables direct correlation of PG function with PG-dependent biological processes.

Vibrational microspectroscopy enables chemical characterization of single pollen grains as well as comparative analysis of plant species based on pollen ultrastructure

Chemical imaging of pollen by vibrational microspectroscopy enables characterization of pollen ultrastructure, in particular phenylpropanoid components in grain wall for comparative study of extant and extinct plant species. A detailed characterization of conifer (Pinales) pollen by vibrational microspectroscopy is presented. The main problems that arise during vibrational measurements were scatter and saturation issues in Fourier transform infrared (FTIR), and fluorescence and penetration depth issues in Raman. Single pollen grains larger than approx. 15 µm can be measured by FTIR microspectroscopy using conventional light sources, while smaller grains may be measured by employing synchrotron light sources. Pollen grains that were larger than 50 µm were too thick for FTIR imaging since the grain constituents absorbed almost all infrared light. Chemical images of pollen were obtained on sectioned samples, unveiling the distribution and concentration of proteins, carbohydrates, sporopollenins and lipids within pollen substructures. The comparative analysis of pollen species revealed that, compared with other Pinales pollens, Cedrus atlantica has a higher relative amount of lipid nutrients, as well as different chemical composition of grain wall sporopollenin. The pre-processing and data analysis, namely extended multiplicative signal correction and principal component analysis, offer simple estimate of imaging spectral data and indirect estimation of physical properties of pollen. The vibrational microspectroscopy study demonstrates that detailed chemical characterization of pollen can be obtained by measurement of an individual grain and pollen ultrastructure. Measurement of phenylpropanoid components in pollen grain wall could be used, not only for the reconstruction of past environments, but for assessment of diversity of plant species as well. Therefore, analysis of extant and extinct pollen species by vibrational spectroscopies is suggested as a valuable tool in biology, ecology and palaeosciences.

Data-driven signal-resolving approaches of infrared spectra to explore the macroscopic and microscopic spatial distribution of organic and inorganic compounds in plant

The nondestructive and label-free infrared (IR) spectroscopy is a direct tool to characterize the spatial distribution of organic and inorganic compounds in plant. Since plant samples are usually complex mixtures, signal-resolving methods are necessary to find the spectral features of compounds of interest in the signal-overlapped IR spectra. In this research, two approaches using existing data-driven signal-resolving methods are proposed to interpret the IR spectra of plant samples. If the number of spectra is small, "tri-step identification" can enhance the spectral resolution to separate and identify the overlapped bands. First, the envelope bands of the original spectrum are interpreted according to the spectra-structure correlations. Then the spectrum is differentiated to resolve the underlying peaks in each envelope band. Finally, two-dimensional correlation spectroscopy is used to enhance the spectral resolution further. For a large number of spectra, "tri-step decomposition" can resolve the spectra by multivariate methods to obtain the structural and semi-quantitative information about the chemical components. Principal component analysis is used first to explore the existing signal types without any prior knowledge. Then the spectra are decomposed by self-modeling curve resolution methods to estimate the spectra and contents of significant chemical components. At last, targeted methods such as partial least squares target can explore the content profiles of specific components sensitively. As an example, the macroscopic and microscopic distribution of eugenol and calcium oxalate in the bud of clove is studied.

Chemical profiling of Jatropha tissues under different torrefaction conditions: application to biomass waste recovery

Gradual depletion of the world petroleum reserves and the impact of environmental pollution highlight the importance of developing alternative energy resources such as plant biomass. To address these issues, intensive research has focused on the plant Jatropha curcas, which serves as a rich source of biodiesel because of its high seed oil content. However, producing biodiesel from Jatropha generates large amounts of biomass waste that are difficult to use. Therefore, the objective of our research was to analyze the effects of different conditions of torrefaction on Jatropha biomass. Six different types of Jatropha tissues (seed coat, kernel, stem, xylem, bark, and leaf) were torrefied at four different temperature conditions (200°C, 250°C, 300°C, and 350°C), and changes in the metabolite composition of the torrefied products were determined by Fourier transform-infrared spectroscopy and nuclear magnetic resonance analyses. Cellulose was gradually converted to oligosaccharides in the temperature range of 200°C–300°C and completely degraded at 350°C. Hemicellulose residues showed different degradation patterns depending on the tissue, whereas glucuronoxylan efficiently decomposed between 300°C and 350°C. Heat-induced depolymerization of starch to maltodextrin started between 200°C and 250°C, and oligomer sugar structure degradation occurred at higher temperatures. Lignin degraded at each temperature, e.g., syringyl (S) degraded at lower temperatures than guaiacyl (G). Finally, the toxic compound phorbol ester degraded gradually starting at 235°C and efficiently just below 300°C. These results suggest that torrefaction is a feasible treatment for further processing of residual biomass to biorefinery stock or fertilizer.

Vibrational microspectroscopic identification of powdered traditional medicines: chemical micromorphology of Poria observed by infrared and Raman microspectroscopy

Microscopic identification using optical microscopes is a simple and effective method to identify powdered traditional medicines made from plants, animals and fungi. Sometimes, the criteria based on physical properties of the microscopic characteristics of drug powder may be ambiguous, which makes the microscopic identification method subjective and empirical to some extent. In this research, the vibrational microspectroscopic identification method is proposed for more explicit discrimination of powdered traditional medicines. The chemical micromorphology, i.e., chemical compositions and related physical morphologies, of the drug powder can be profiled objectively and quantitatively by infrared and Raman microspectroscopy, leading to better understanding about the formation mechanisms of microscopic characteristics and more accurate identification criteria. As an example, the powder of Poria, which is one of the most used traditional Chinese medicines, is studied in this research. Three types of hyphae are classified according to their infrared spectral features in the region from 1200 to 900 cm(-1). Different kinds of polysaccharides indicate that these hyphae may be in different stages of the growth. The granular and branched clumps observed by the optical microscope may be formed from the aggregation of the mature hyphae with β-D-glucan reserves. The newfound spherical particles may originate from the exuded droplets in the fresh Poria because they are both composed of α-D-glucan. The results are helpful to understand the development of the hyphae and the formation of active polysaccharides in Poria and to establish accurate microspectroscopic identification criteria.