Following laser induced changes of plant phenylpropanoids by Raman microscopy

Raman spectrum model transfer method based on Cycle-GAN

The disparity in hardware quality among various models of Raman spectrometers gives rise to variations in the acquired Raman spectral data, even when the same substance is collected under identical external conditions. Conventionally, models constructed using data obtained from a particular instrument exhibit issues such as limited applicability or poor performance when deployed to different instruments. Currently, numerous model transfer algorithms grounded in chemometrics have been developed, all aiming to establish a mapping relationship capable of transforming spectral data from the source domain to the target domain. With the advancement of deep learning techniques, the utilization of deep learning enables the effective resolution of nonlinear mapping relationships between two spectral vectors. In the field of image translation, the Cycle-Consistent Adversarial Networks, Cycle-GAN, has already achieved mutual transformation between two distinct style images. However, due to images being multidimensional matrix data, unlike one-dimensional spectral data vectors, we have constructed a deep learning network based on Cycle-GAN for vector-to-vector transformation. This network allows the direct conversion of spectral data from the source domain to the target domain, without requiring parameter adjustments or other operations. Compared with traditional chemometric methods, our method is more intelligent and efficient. Finally, the cosine similarity between the source domain data and the transformed target domain data exceeds 99%.

Recent advances and applications of laser-based imaging techniques in food crops and products: a critical review

To meet the growing demand for food quality and safety, there is a pressing need for fast and visible techniques to monitor the food crop and product production processing, and to understand the chemical changes that occur during these processes. Herein, the fundamental principles, instruments, and characteristics of three major laser-based imaging techniques (LBITs), namely, laser-induced breakdown spectroscopy, Raman spectroscopy, and laser ablation-inductively coupled plasma-mass spectrometry, are introduced. Additionally, the advances, challenges, and prospects for the application of LBITs in food crops and products are discussed. In recent years, LBITs have played a crucial role in mapping primary metabolites, secondary metabolites, nanoparticles, toxic metals, and mineral elements in food crops, as well as visualizing food adulteration, composition changes, pesticide residue, microbial contamination, and elements in food products. However, LBITs are still facing challenges in achieving accurate and sensitive quantification of compositions due to the complex sample matrix and minimal laser sampling quantity. Thus, further research is required to develop comprehensive data processing strategies and signal enhancement methods. With the continued development of imaging methods and equipment, LBITs have the potential to further explore chemical distribution mechanisms and ensure the safety and quality of food crops and products.

3D (x-y-t) Raman imaging of tomato fruit cuticle: Microchemistry during development

The cuticle is a protective extracellular matrix that covers the above-ground epidermis of land plants. Here, we studied the cuticle of tomato (Solanum lycopersicum L.) fruits in situ using confocal Raman microscopy. Microsections from cuticles isolated at different developmental stages were scanned to visualize cuticle components with a spatial resolution of 342 nm by univariate and multivariate data analysis. Three main components, cutin, polysaccharides, and aromatics, were identified, with the latter exhibiting the strongest Raman scattering intensity. Phenolic acids and flavonoids were differentiated within the cuticle, and three schematic cuticle models were identified during development. Phenolic acids were found across the entire cuticle at the earliest stage of development, i.e. during the formation of the procuticle layer. Based on a mixture analysis with reference component spectra, the phenolic acids were identified as mainly esterified p-coumaric acid together with free p-hydroxybenzoic acid. During the cell expansion period of growth, phenolic acids accumulated in an outermost layer of the cuticle and in the middle region of the pegs. In these stages of development, cellulose and pectin were detected next to the inner cuticle region, close to the epidermal cell where flavonoid impregnation started during ripening. In the first ripening stage, chalconaringenin was observed, while methoxylated chalcones were chosen by the algorithm to fit the mature cuticle spectra. The colocation of carbohydrates, esterified p-coumaric acid, and methoxylated chalconaringenin suggests that the latter two link polysaccharide and cutin domains. Elucidating the different distribution of aromatics within the cuticle, suggests important functions: (1) overall impregnation conferring mechanical and thermal functions (2) the outermost phenolic acid layer displaying UV-B protection of the plant tissue.

Wood-Water Relations Affected by Anhydride and Formaldehyde Modification of Wood

The moisture uptake of wood is influenced by accessible hydroxyl groups acting as sorption sites and the water-available cell wall space. To what extent do these mechanisms control the moisture uptake in wood needs to be addressed. For this purpose, we modified sorption site density and cell wall space by wood treatments with acetic anhydride or formaldehyde and investigated their effects on moisture uptake. Chemical changes at the cell wall level caused by the treatments were first determined by confocal Raman imaging. Following this, the deuterium exchange method was used to gravimetrically measure the hydroxyl accessibility, while the moisture uptake and the consequent swelling of the wood were determined by dynamic measurements of mass and dimensions within the hygroscopic range. The results showed that the effectiveness in reducing the moisture content of untreated wood across the hygroscopic range differed between the anhydride- and formaldehyde-modified wood. We also observed a poor correlation of accessible hydroxyl concentration in formaldehyde-modified wood with weight percentage gain and water uptake. Moreover, the dynamic mass and dimension analysis indicated that the reduction in swelling in formalized wood was affected by an unidentified mechanism in addition to reduced moisture content.

Raman micro-spectroscopy of two types of acetylated Norway spruce wood at controlled relative humidity

Water is a key element for wood performance, as water molecules interact with the wood structure and affect important material characteristics such as mechanical properties and durability. Understanding wood-water interactions is consequently essential for all applications of wood, including the design of wood materials with improved durability by chemical modification. In this work, we used Raman micro-spectroscopy in combination with a specially designed moisture chamber to map molecular groups in wood cell walls under controlled moisture conditions in the hygroscopic range. We analyzed both untreated and chemically modified (acetylated to achieve two different spatial distributions of acetyl groups within the cell wall) Norway spruce wood. By moisture conditioning the specimens successively to 5, 50, and 95% relative humidity using deuterium oxide (D₂O), we localized the moisture in the cell walls as well as distinguished between hydroxyl groups accessible and inaccessible to water. The combination of Raman micro-spectroscopy with a moisturizing system with deuterium oxide allowed unprecedented mapping of wood-water interactions. The results confirm lower moisture uptake in acetylated samples, and furthermore showed that the location of moisture within the cell wall of acetylated wood is linked to the regions where acetylation is less pronounced. The study demonstrates the local effect that targeted acetylation has on moisture uptake in wood cell walls, and introduces a novel experimental set-up for simultaneously exploring sub-micron level wood chemistry and moisture in wood under hygroscopic conditions.

A Guide to Elucidate the Hidden Multicomponent Layered Structure of Plant Cuticles by Raman Imaging

The cuticle covers almost all plant organs as the outermost layer and serves as a transpiration barrier, sunscreen, and first line of defense against pathogens. Waxes, fatty acids, and aromatic components build chemically and structurally diverse layers with different functionality. So far, electron microscopy has elucidated structure, while isolation, extraction, and analysis procedures have revealed chemistry. With this method paper, we close the missing link by demonstrating how Raman microscopy gives detailed information about chemistry and structure of the native cuticle on the microscale. We introduce an optimized experimental workflow, covering the whole process of sample preparation, Raman imaging experiment, data analysis, and interpretation and show the versatility of the approach on cuticles of a spruce needle, a tomato peel, and an Arabidopsis stem. We include laser polarization experiments to deduce the orientation of molecules and multivariate data analysis to separate cuticle layers and verify their molecular composition. Based on the three investigated cuticles, we discuss the chemical and structural diversity and validate our findings by comparing models based on our spectroscopic data with the current view of the cuticle. We amend the model by adding the distribution of cinnamic acids and flavonoids within the cuticle layers and their transition to the epidermal layer. Raman imaging proves as a non-destructive and fast approach to assess the chemical and structural variability in space and time. It might become a valuable tool to tackle knowledge gaps in plant cuticle research.

Multiscale investigation on the chemical and anatomical changes of lignocellulosic biomass for different severities of hydrothermal treatment

The chemical changes sustained by lignocellulosic biomass during hydrothermal treatment are reflected at multiple scales. This study proposes to benefit from this multiscale nature in order to provide a global understanding of biomass alterations during hydrothermal treatment. For this purpose, complementary imaging techniques-confocal Raman microscopy and X-ray nano-tomography-analysed by image processing and coupled to chemical measurements were used. This unique combination of analyses provided valuable information on topochemical and morphological changes of poplar samples, without the artefacts of sample preparation. At the cell wall level, holocellulose hydrolysis and lignin modifications were observed, which corresponded to anatomical modifications observed at higher scales. Overall, after treatment, samples shrank and had thinner cell walls. When subjected to more severe pre-treatments, cells were disrupted and detached from adjacent cells. Anatomical changes were then used to obtain quantitative indicators of the treatment severity. The effects of treatment at different scales can thus be quantitatively connected in both directions, from micro to macro and from macro to micro.

Even Visually Intact Cell Walls in Waterlogged Archaeological Wood Are Chemically Deteriorated and Mechanically Fragile: A Case of a 170 Year-Old Shipwreck

Structural and chemical deterioration and its impact on cell wall mechanics were investigated for visually intact cell walls (VICWs) in waterlogged archaeological wood (WAW). Cell wall mechanical properties were examined by nanoindentation without prior embedding. WAW showed more than 25% decrease of both hardness and elastic modulus. Changes of cell wall composition, cellulose crystallite structure and porosity were investigated by ATR-FTIR imaging, Raman imaging, wet chemistry, ¹³C-solid state NMR, pyrolysis-GC/MS, wide angle X-ray scattering, and N₂ nitrogen adsorption. VICWs in WAW possessed a cleavage of carboxyl in side chains of xylan, a serious loss of polysaccharides, and a partial breakage of β-O-4 interlinks in lignin. This was accompanied by a higher amount of mesopores in cell walls. Even VICWs in WAW were severely deteriorated at the nanoscale with impact on mechanics, which has strong implications for the conservation of archaeological shipwrecks.

Infrared and Raman spectra of lignin substructures: Dibenzodioxocin

Vibrational spectroscopy is a very suitable tool for investigating the plant cell wall in situ with almost no sample preparation. The structural information of all different constituents is contained in a single spectrum. Interpretation therefore heavily relies on reference spectra and understanding of the vibrational behavior of the components under study. For the first time, we show infrared (IR) and Raman spectra of dibenzodioxocin (DBDO), an important lignin substructure. A detailed vibrational assignment of the molecule, based on quantum chemical computations, is given in the Supporting Information; the main results are found in the paper. Furthermore, we show IR and Raman spectra of synthetic guaiacyl lignin (dehydrogenation polymer-G-DHP). Raman spectra of DBDO and G-DHP both differ with respect to the excitation wavelength and therefore reveal different features of the substructure/polymer. This study confirms the idea previously put forward that Raman at 532 nm selectively probes end groups of lignin, whereas Raman at 785 nm and IR seem to represent the majority of lignin substructures.

Raman Imaging of Plant Cell Walls

Raman imaging is a microspectroscopic approach revealing the chemistry and structure of plant cell walls in situ on the micro- and nanoscale. The method is based on the Raman effect (inelastic scattering) that takes place when monochromatic laser light interacts with matter. The scattered light conveys a change in energy that is inherent of the involved molecule vibrations. The Raman spectra are thus characteristic for the chemical structure of the molecules and can be recorded spatially ordered with a lateral resolution of about 300 nm. Based on thousands of acquired Raman spectra, images can be assessed using univariate as well as multivariate data analysis approaches. One advantage compared to staining or labeling techniques is that not only one image is obtained as a result but different components and characteristics can be displayed in several images. Furthermore, as every pixel corresponds to a Raman spectrum, which is a kind of "molecular fingerprint," the imaging results should always be evaluated and further details revealed by analysis (e.g., band assignment) of extracted spectra. In this chapter, the basic theoretical background of the technique and instrumentation are described together with sample preparation requirements and tips for high-quality plant tissue sections and successful Raman measurements. Typical Raman spectra of the different plant cell wall components are shown as well as an exemplified analysis of Raman data acquired on the model plant Arabidopsis. Important preprocessing methods of the spectra are included as well as single component image generation (univariate) and spectral unmixing by means of multivariate approaches (e.g., vertex component analysis).

Correlative FLIM-confocal-Raman mapping applied to plant lignin composition and autofluorescence

Fluorescence lifetime imaging microscopy (FLIM) is a useful tool for discriminating fluorescent moieties, based on photon lifetimes, that cannot be otherwise resolved by looking solely at their excitation/emission characteristics. We present a method for correlative FLIM-confocal-Raman imaging and its application to lignin composition studies in the woody stems of the plant model Arabidopsis thaliana. Lignin is autofluorescent and exhibits characteristic fluorescence lifetimes attributed to its composition. Its composition can be further resolved by Raman microscopy to multiple peaks that represent different components. A lignin biosynthetic mutant is found to have a marked difference in fluorescence lifetime and corresponds to a change in composition as demonstrated by the Raman output.

Infrared and Raman spectra of lignin substructures: Coniferyl alcohol, abietin, and coniferyl aldehyde

Anatomical and chemical information can be linked by Raman imaging. Behind every pixel of the image is a Raman spectrum, which contains all the information as a molecular fingerprint. Yet to understand the spectra, the bands have to be assigned to components and their molecular structures. Although the lignin distribution is easily tracked in plant tissues, the assignment of the spectra is not good enough to allow in-depth analysis of the composition. Assignments of three lignin model compounds were derived from polarization measurements and quantum-chemical computations. Raman spectra of coniferyl alcohol crystals showed orientation dependence, which helped in band assignment. Abietin showed a Raman spectrum that was very similar to the spectrum of coniferyl alcohol, whereas its IR spectrum was very different due to bands of the sugar moiety. The Raman spectrum of coniferyl aldehyde is affected by the crystal order of molecules. All three compounds show much stronger band intensities than unconjugated single aromatic rings, indicating that the bulk of the lignin structure has significantly reduced contribution to Raman band intensities. Therefore, it is possible to highlight certain structures of lignin with Raman spectroscopy, because low amounts of a compound do not necessarily mean weak features in the spectrum.