Application of target partial least squares for analysis of Fourier transform infrared-attenuated total reflection hyperspectral images for characterization of the distribution of crop protection products on the leaf surface

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.

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.

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

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.

Micro- and macro-attenuated total reflection Fourier transform infrared spectroscopic imaging. Plenary Lecture at the 5th International Conference on Advanced Vibrational Spectroscopy, 2009, Melbourne, Australia

Fourier transform infrared (FT-IR) spectroscopic imaging has become a very powerful method in chemical analysis. In this review paper we describe a variety of opportunities for obtaining FT-IR images using the attenuated total reflection (ATR) approach and provide an overview of fundamental aspects, accessories, and applications in both micro- and macro-ATR imaging modes. The advantages and versatility of both ATR imaging modes are discussed and the spatial resolution of micro-ATR imaging is demonstrated. Micro-ATR imaging has opened up many new areas of study that were previously precluded by inadequate spatial resolution (polymer blends, pharmaceutical tablets, cross-sections of blood vessels or hair, surface of skin, single live cells, cancerous tissues). Recent applications of ATR imaging in polymer research, biomedical and forensic sciences, objects of cultural heritage, and other complex materials are outlined. The latest advances include obtaining spatially resolved chemical images from different depths within a sample, and surface-enhanced images for macro-ATR imaging have also been presented. Macro-ATR imaging is a valuable approach for high-throughput analysis of materials under controlled environments. Opportunities exist for chemical imaging of dynamic aqueous systems, such as dissolution, diffusion, microfluidics, or imaging of dynamic processes in live cells.