•The reflection IR imaging approach was proposed to characterize thick plant samples.•The PHAC algorithm was proposed to create chemical images of multiple compounds.•Chemical morphology of Areca nut was studied by reflection NIR and ATR-MIR imaging.•Structures and distributions of primary compounds in Areca nut were revealed.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.

•FTIR microspectroscopic imaging is used to identify herbal powder preparations.•Multiple organic and inorganic ingredients can be detected directly at the same time.•All kinds of herb materials in Kouqiang Kuiyang San are successfully recognized.•Differences between natural Alumen and synthetic KAl(SO4)2·12H2O are indicated.Herbal powder preparation is a kind of widely-used herbal product in the form of powder mixture of herbal ingredients. Identification of herbal ingredients is the first and foremost step in assuring the quality, safety and efficacy of herbal powder preparations. In this research, Fourier transform infrared (FT-IR) microspectroscopic identification method is proposed for the direct and simultaneous recognition of multiple organic and inorganic ingredients in herbal powder preparations. First, the reference spectrum of characteristic particles of each herbal ingredient is assigned according to FT-IR results and other available information. Next, a statistical correlation threshold is determined as the lower limit of correlation coefficients between the reference spectrum and a larger number of calibration characteristic particles. After validation, the reference spectrum and correlation threshold can be used to identify herbal ingredient in mixture preparations. A herbal ingredient is supposed to be present if correlation coefficients between the reference spectrum and some sample particles are above the threshold. Using this method, all kinds of herbal materials in powder preparation Kouqiang Kuiyang San are identified successfully. This research shows the potential of FT-IR microspectroscopic identification method for the accurate and quick identification of ingredients in herbal powder preparations.

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.

•MW2DCOS and PCA were combined for the first time to interpret time serial spectra.•Three stages of the curing process of a paint sample were found by MW2DCOS and PCA.•Time-resolved spectral changes are shown in AP-MW2D correlation spectra.•The time-resolved relationship of spectral peaks is revealed by PP- and PL-MW2DCOS.Moving-window two-dimensional correlation spectroscopy (MW2DCOS) and principal component analysis (PCA) were combined to interpret the time serial infrared spectra. The curing process of an automotive paint sample was tracked by attenuated total reflection Fourier transform infrared spectroscopy. Score plots of the first and second principal components showed that the curing process contained three stages. Meanwhile, the loading spectra indicated that the solvent was a mixture of aromatic compounds. Absorption peaks which changed significantly in each stage were revealed by auto-peak MW2DCOS. Furthermore, point-line and point-point MW2DCOS demonstrated the time-resolved relationship between absorption peaks from toluene, xylene and resin. In summary, the evaporation of toluene was the first stage of the curing process of this automotive paint sample. Next, the mixture of o-xylene, m-xylene and p-xylene began to evaporate in the second stage. After the evaporation of the solvent, the solid paint membrane was formed. For the interpretation of the time serial spectra, PCA is useful to estimate the number of significant chemical components and to find out the important turning points of the process, while MW2DCOS can show the changes of the spectral peaks and the relationship between them step by step. The combination of PCA and MW2DCOS is very interesting to extract and display the time-resolved information in the time serial spectra.Graphical abstract

•The vibrational microspectroscopic identification method is proposed first.•Chemical compositions of hyphae and clumps in dry Poria powder are characterized.•Three types of hyphae are classified according to the infrared spectral features.•A new kind of spherical particles in dry Poria powder are found and studied.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.Graphical abstract

Fourier transform infrared microspectroscopy is a powerful tool to obtain knowledge about the spatial and/or temporal distributions of the chemical compositions of plants for better understanding of their biological properties. However, the chemical morphologies of plant leaves in the plane of the blade are barely studied, because sections in this plane for mid-infrared transmission measurements are difficult to obtain. Besides, native compositions may be changed by chemical reagents used when plant samples are microtomed. To improve methods for direct infrared microspectroscopic imaging of plant leaves in the plane of the blade, the bulk and surface chemical morphologies of nonmicrotomed Ginkgo biloba leaves were characterized by near-infrared transmission and mid-infrared attenuated total reflection microspectroscopic imaging. A new self-modeling curve resolution procedure was proposed to extract the spectral and concentration information of pure compounds. Primary and secondary metabolites of secretory cavities, veins, and mesophylls of Ginkgo biloba leaf blades were analyzed, and the distributions of cuticle, protein, calcium oxalate, cellulose, and ginkgolic acids on the adaxial surface were determined. By the integration of multiple infrared microspectroscopic imaging and chemometrics methods, it is possible to analyze nonmicrotomed leaves and other plant samples directly to understand their native chemical morphologies in detail.

It has been proved to be a very useful method to distinguish similar samples by two-dimensional correlation spectroscopy when they are hardly distinguished by the conventional one-dimensional spectroscopy. To acquire the quantitative description of the differences between samples, the similarity of the series dynamic spectra, which reflects the similarity of the samples themselves if obtained under the same perturbation condition, is evaluated by the symmetry of hetero 2DCOS map. Two parameters, the Euclidian distance and correlation coefficient between the upper left and lower right triangular parts of a hetero 2DCOS map, are introduced for the quantitative measure of the symmetry, which in turn characterizes the similarity of the responses of samples to a given perturbation. The above method is used to discriminate one genus of Astragalus from the others to ensure the medicinal efficacy and safety of the herb. Hypothesis tests show that the inter-distances between samples from different genera are significantly larger than the intra-ones within the same genera, while the inter-correlation coefficients are smaller than the intra-ones. The excellent result of the identification for all samples carried out by a t-test based on the distances indicates that this method provides an efficient technique for the quantitative evaluation of similarity between samples.