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Combined TPEF and SHG Imaging for the Microstructural Characterization of Different Wood Species Used in Artworks

Combined TPEF and SHG Imaging for the Microstructural Characterization of Different Wood Species... hv photonics Article Combined TPEF and SHG Imaging for the Microstructural Characterization of Different Wood Species Used in Artworks 1 , 1 2 , 3 4 5 1 Alice Dal Fovo * , Sara Mattana , Marco Marchetti , Monica Anichini , Alessio Giovannelli , Enrico Baria , 1 1 , 3 Raffaella Fontana and Riccardo Cicchi National Research Council, National Institute of Optics (CNR-INO), Largo E. Fermi 6, 50125 Firenze, Italy; sara.mattana@ino.cnr.it (S.M.); enrico.baria@ino.cnr.it (E.B.); raffaella.fontana@ino.it (R.F.); riccardo.cicchi@ino.cnr.it (R.C.) Department of Physics, University of Florence, Via G. Sansone 1, 50019 Sesto Fiorentino, Italy; m.marchetti@l4t.it European Laboratory for Non-Linear Spectroscopy (LENS), Via N. Carrara 1, 50019 Sesto Fiorentino, Italy National Research Council, Institute of BioEconomy (CNR-IBE), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy; monica.anichini@ibe.cnr.it National Research Council, Research Institute on Terrestrial Ecosystems (CNR-IRET), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy; alessio.giovannelli@cnr.it * Correspondence: alice.dalfovo@ino.cnr.it Abstract: The morphological and chemical conformation of wood microstructures is characteristic of individual species and strongly influences the macromechanical properties of the material, as well as its sensitivity to deterioration factors. Noninvasive techniques enabling the visualization of wood microstructures, while simultaneously providing compositional information, can significantly facilitate the analysis of wooden artworks for conservation purposes. In this paper, we present the application of combined two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) imaging as a versatile diagnostic tool for the microcharacterization of three hardwood species never analyzed by this method. Multimodal mapping of the molecular constituents based on the Citation: Dal Fovo, A.; Mattana, S.; detected nonlinear signals provides useful information for studying the biological and biochemical Marchetti, M.; Anichini, M.; deterioration of wood, opening a new field of application for a well-established and widely used Giovannelli, A.; Baria, E.; Fontana, R.; imaging technology. Cicchi, R. Combined TPEF and SHG Imaging for the Microstructural Keywords: second-harmonic generation; two-photon excited fluorescence; wood microstructure; Characterization of Different Wood cellulose; lignin; starch Species Used in Artworks. Photonics 2022, 9, 170. https://doi.org/ 10.3390/photonics9030170 Received: 6 January 2022 1. Introduction Accepted: 7 March 2022 Wood has been used extensively since ancient times with both a structural and decora- Published: 10 March 2022 tive function in a variety of art objects, ranging from sculptures to paintings and musical Publisher’s Note: MDPI stays neutral instruments. The multiscale and anisotropic structure of wood is highly hygroscopic due with regard to jurisdictional claims in to the presence of differently oriented pores, for which the peculiar size and shape are key published maps and institutional affil- parameters for differentiation among wood species [1,2]. Given the importance of cell walls iations. in the growth and morphogenesis of the microstructures, it is of great interest to investigate how molecular components are organized in the three dimensions [3]. The geometry of the microstructures determines the accessibility of degradative organisms and substances and, thus, is strictly related to biological and biochemical degradation [4]. Moreover, the sensi- Copyright: © 2022 by the authors. tivity of wood cells to environmental changes can be monitored based on the alterations Licensee MDPI, Basel, Switzerland. occurring at the molecular level, which strongly influence the macromechanical properties This article is an open access article of the timber or wood products [5]. distributed under the terms and The main chemical components of wood cells, namely cellulose, hemicellulose, and conditions of the Creative Commons lignin, are characterized by nonlinear optical (NLO) properties, which can be exploited Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ to obtain morphological, structural, and compositional information on the microstruc- 4.0/). tures [6–8]. NLO microscopies are well-established 3D imaging techniques that have been Photonics 2022, 9, 170. https://doi.org/10.3390/photonics9030170 https://www.mdpi.com/journal/photonics Photonics 2022, 9, 170 2 of 11 widely applied in the biological field for the label-free nondestructive investigation of physio-pathological processes in live samples at a subcellular spatial resolution [9]. The combined use of different NLO microscopy modalities, such as two- and three-photon ex- cited fluorescence (TPEF [10] and 3PF [11,12]) and second- and third-harmonic generation (SHG [13] and THG [14]), provides complementary information based on the detection of fluorophores (by TPEF and 3PF), crystalline or highly organized structures without inversion symmetry (by SHG), and local differences in refractive index and dispersion, i.e., interfaces (by THG) [15]. Nonlinear processes are generated through the interaction of atoms and/or molecules with two or more photons within the same quantum event. Being second- or higher-order optical processes, their inherent low probability to occur requires a high spatial and temporal density of photons, which is typically achieved with tightly focused ultrashort-pulsed lasers. Nonlinear processes allow using near-infrared photons for exciting molecular transitions, which are typically located in the blue/UV spectral range. The major advantage, compared to linear optical techniques, is that non- linear optical signals (SHG, THG, TPEF, and 3PF) can be generated at higher penetration depths (exceeding 500 m in biological tissues [16]) due to the reduced light scattering and absorption of the infrared excitation wavelengths [9]. Furthermore, given the square or cubic dependence of the signal on excitation intensity, the efficient nonlinear interaction is typically confined to a femtoliter region around the focal point, as only ballistic photons contribute to the excitation process. This enables high-resolution sectioning with drastically diminished out-of-focus damages. The noninvasiveness of the technique, which is a crucial requirement in artwork diagnostics, can be ensured by simply monitoring the variation in TPEF signal intensity as a forewarning of photochemical changes inside the focal volume of the laser beam [17]. The microstructure of wood consists of cells arranged along the axis of the trunk and developed with the parenchyma rays from the core of the tree to the bark (Figure 1) [18]. Cel- lular arrangement and morphology determine substantial anatomical differences between softwoods—i.e., gymnosperms (conifers)—and hardwoods—i.e., angiosperms (flowering plants) (see Section 2.2. Microstructural Features) [19]. The supramolecular conformation of cellulose, which resembles that of collagen in both morphology and symmetry, may yield a strong SHG signal similar to collagen due to the hierarchical structure and the parallel orientation of the composite molecular chains. Furthermore, the strong birefringence and chirality of the polysaccharide chains of cellulose may significantly increase SHG intensity, which is another similarity with the array of polypeptides in collagen [20]. The generation of SH from cellulose is also strongly dependent on the orientation of microfibrils, which develop predominantly along the axis of longitudinal arrays of cells [20]. Another possible source of an SHG signal in wood is starch, a mixture of the two polysaccharides amylose and amylopectin. Within the stem, starch is stored in large amounts in the companion cells of the phloem (inner side of the bark) and in the parenchyma ray of the xylem. Starch represents a long-term carbon reserve in a wide variety of or- ganisms, such as seeds and tubers, and a temporary reserve in photosynthetic tissues, specifically in chloroplasts. In particular, Amylose is often highly crystalline and, thus, is likely to generate second-harmonic signals [8]. Starch emits stronger SHG signals than cellu- lose due to the reverse orientation of glucose residues in the polysaccharidic chains [21,22]. Therefore, SHG imaging of cellulose requires rather high laser powers (above optimal val- ues for live cell imaging), whereas starch can be easily imaged at laser fluencies compatible with extended cell viability. Cell walls exhibit natural fluorescence due to the presence of lignin [23]. The emission covers a broad spectral range (blue, green, and red) depending on the excitation wave- length (with maximum absorbance by lignin at 280 nm) and on the pH of the molecular environment [24]. The fluorescence can differ significantly in hardwood and softwood species both in terms of intensity and spectral emission [25,26]. It has been observed that fluorescence from lignin can also be generated nonlinearly, namely through three- and Photonics 2022, 9, 170 3 of 11 two-photon absorption at 840–860 nm [8,27]. While lignin is the predominant fluorophore Photonics 2022, 9, x FOR PEER REVIEW 3 of 11 in cell walls, the polysaccharide components, such as cellulose and starch, are considered not fluorescent [28]. Figure 1. Wood sections at the macroscale (top left); schematic microstructure of hardwood species Figure 1. Wood sections at the macroscale (top left); schematic microstructure of hardwood species (top middle) with NLO images (diameter = 200 μm) of the microstructure of poplar xylem in trans- (top middle) with NLO images (diameter = 200 m) of the microstructure of poplar xylem in verse and radial sections (top right). Schematic representation of cell wall layers—ML, middle la- transverse and radial sections (top right). Schematic representation of cell wall layers—ML, middle mella; P, primary cell wall; S1, S2, and S3, sublayers of secondary cell wall (bottom left); close up of a microfibril bundle from S2 showing individual crystallites of cellulose glued together by the in- lamella; P, primary cell wall; S1, S2, and S3, sublayers of secondary cell wall (bottom left); close up terfibrillar compounds of hemicellulose and lignin (bottom right). of a microfibril bundle from S2 showing individual crystallites of cellulose glued together by the interfibrillar compounds of hemicellulose and lignin (bottom right). The supramolecular conformation of cellulose, which resembles that of collagen in both morphology and symmetry, may yield a strong SHG signal similar to collagen due To the best of our knowledge, the first 3D imaging of wood microstructures on an to the hierarchical structure and the parallel orientation of the composite molecular chains. Furthermore, the strong birefringence and chirality of the polysaccharide chains artistic object was performed in 2009, with a purposefully developed time-domain OCT of cellulose may significantly increase SHG intensity, which is another similarity with the system, based on an illumination source centered at 650 nm and reaching axial and trans- array of polypeptides in collagen [20]. The generation of SH from cellulose is also strongly verse resolutions of 1.5 and 1 m, respectively [18]. However, the visualization of wood dependent on the orientation of microfibrils, which develop predominantly along the axis cells provided by OCT tomograms lacked any chemical information. To overcome such a of longitudinal arrays of cells [20]. limit, some years later Another possible source of a , the same author applied n SHG si TPEF gnal in and wood SHG is ston arch, thin a mshavings ixture of the t ofw acer o polysaccharides amylose and amylopectin. Within the stem, starch is stored in large wood and a historical violin, obtaining both the imaging and the chemical characterization amounts in the companion cells of the phloem (inner side of the bark) and in the paren- of wood microstructures [27]. Although SHG emissions are generally more efficient in chyma ray of the xylem. Starch represents a long-term carbon reserve in a wide variety of the forward direction due to phase-matching conditions, it was demonstrated that the organisms, such as seeds and tubers, and a temporary reserve in photosynthetic tissues, SH signal can also specif be ical recor ly in chlorop ded inla the sts. backwar In particular d , dir Amylos ection e is of when ten high it is ly cr enhanced ystalline and by , tspecific hus, is likely to generate second-harmonic signals [8]. Starch emits stronger SHG signals than structures or backscattered in thick scattering wood samples [29]. cellulose due to the reverse orientation of glucose residues in the polysaccharidic chains In this work, we extended the application of TPEF-SHG imaging to three hardwood [21,22]. Therefore, SHG imaging of cellulose requires rather high laser powers (above op- species widely used in art production—poplar, beech, and chestnut—that have never been timal values for live cell imaging), whereas starch can be easily imaged at laser fluencies analyzed with these modalities. Nonlinear signals, collected in epi-detection, were com- compatible with extended cell viability. bined into intensity images Cell walls exh to dif ibit natur ferentiate al fluorescenc and quantify e due to chemical the presence of lignin components. [23]. The emission The purpose covers a broad spectral range (blue, green, and red) depending on the excitation wave- of this study is to provide a noninvasive and effective tool for the rapid recognition of wood length (with maximum absorbance by lignin at 280 nm) and on the pH of the molecular species used in art production based on compositional and morphological information at the micrometer level that can be profitably used for conservation and restoration purposes. 2. Materials and Methods 2.1. Samples Wood shavings were collected from mature trees of poplar (Populus tremula L.), beech (Fagus sylvatica L.), and chestnut (Castanea sativa M.) growing in a mixed forest in northern Photonics 2022, 9, 170 4 of 11 Tuscany, Italy. Prismatic wood samples (15  10  5 mm ) were obtained by notching a piece of stem with a blade in the tangential direction (Figure 1). The wood shavings were stored for a week at 4 C before the analysis. To test the applicability of the method on CH objects without sampling while fulfilling the noninvasiveness requirements, the samples were analyzed without any pretreatment, even if the addition of a solution of glycerine and water would have eased the observation of the microstructures [30]. 2.2. Microstructural Features The major components of the physical and chemical properties of wood are the distri- bution and number of different cell types, namely tracheids (constituting around 90% of the volume of softwood), vessels, parenchyma, and fibers (the main components in hard- woods) [31]. The latewood, also called summerwood, can be distinguished from earlywood or springwood because of the smaller radial dimensions of the cells and the thicker walls, which also is reflected in the higher density of the bulk. A further diagnostic element for the differentiation of wood species is the presence of isolated interruptions inside the cell walls of xylem conduits (i.e., vessels and tracheids), called “pits”, which connect different cells for the transfer of sap. The pit membrane has a key function in the overall hydraulic efficiency of plants, allowing water to diffuse between conduits but limiting the spread of embolism and vascular pathogens. The shape and dimension of pits significantly vary depending on the type of adjacent cells and, therefore, can be considered distinctive features of the wood species [32]. Looking more deeply into the microstructures, plant cells show a globular, elongated bag shape. The cell wall is a membrane composed of different layers, namely the primary (P) and the secondary (S) layers, which in turn is composed of three sublayers: S1, S2, and S3 (Figure 1). Adjacent cells are connected by an additional layer, called the middle lamella (ML). Inside the cell wall, laminar crystallites of cellulose are organized in microfibrils, which are embedded in a complex matrix of variously amor- phous polysaccharides (hemicellulose), cross-linked with lignin, a condensed polymer of coniferyl, sinapyl, or p-coumaryl alcohol (Figure 1) [31,33]. Cellulose is a linear chain of polysaccharidic molecules linked by -(1–4) glycosidic bonds displaying a twofold ribbon conformation. Many packing arrangements of the polysaccharidic chains are possible, and all are classifiable in cellulose I (the most abundant type, with parallel chains) and II (with antiparallel chains) [34]. Cellulose I naturally occurs in two distinct crystalline forms, I and I , showing triclinic and monoclinic symmetry, respectively. These well-ordered molecular chains are predominantly located in the secondary cell wall in variable propor- tions and crystallize into the thermodynamically stable microfibrils, with a typical diameter ranging from 1.2 to 4.8 nm and lengths between 60 and 150 nm [35]. The distribution of the microfibrils differs in quantity and arrangement depending on their location in the cell wall. While the content of cellulose is about the same in both softwood and hardwood, exceeding approximately 40–45% in weight of the dry matter in most wood species, lignin is present in different quantities (usually ranging from 18% to 25% in hardwoods and from 25% to 35% in softwoods). 2.3. Nonlinear Setup The nonlinear setup used for the analysis was developed at CNR-INO and is equipped with a dual-output Yb-based fiber fs-laser (Chameleon Discovery, Coherent Inc., Santa Clara, CA, USA). A detailed description of the system can be found elsewhere [36]. Based on previous applications of NLO on wood microstructures [27], the excitation wavelength was set at 840–850 nm (depending on the wood species), with a pulse duration of 140 fs and a repetition rate of 80 MHz, and with the power on the specimen ranging from 30 to 50 mW. Nonlinear signals coming from the sample were epi-collected using a Plan Apochromat20 objective lens (NA 0.75, WD 1 mm, Nikon, Nikon Minato, Tokyo, Japan) and detected with two photomultiplier tubes (H7422-40, Hamamatsu, Hamamatsu City, Japan) for simultaneous TPEF and SHG detection. A dichroic beam splitter filter with a 452 nm cutoff wavelength (FF452-Di01, Semrock Inc. New York, NY, USA) was used Photonics 2022, 9, 170 5 of 11 for separating TPEF from SHG. In more detail, the TPEF signal was transmitted by the dichroic and detected without any additional emission filters, which is in agreement with previous observations on TPEF emission’s spectral range of lignin [27]; the SHG signal was reflected by the dichroic and then filtered with a narrow band-pass filter centered at 420 nm (BrightLine 420/10–25 nm, Semrock Inc., New York, NY, USA). For each analyzed area, the TPEF and SHG signals were detected and displayed as intensity images, which were merged with a Java image processing software (see Figure S1 in the Supplementary Materials). Specifically, the TPEF and SHG images were assigned to the green and the red channels, respectively, thus enabling the distinction among components generating the different nonlinear signals (mainly starch, cellulose, and lignin) in a single image, as well as allowing for the visualization of micrometric features that are characteristic of each species. 3. Results 3.1. Poplar (Populus tremula L.) The microanalysis of poplar shavings (tangential section) revealed the peculiar size and Photonics 2022, 9, x FOR PEER REVIEW 6 of 11 shape of the cells composing this species (Figures 2 and 3). The observed vessels, which are uniformly distributed along the ring with dimensions slightly varying between latewood and earlywood zones, were relatively small (50–100 m), with circular or polygonal shapes. The parenchyma rays, mostly mono-seriated, showed homogenous shapes and sizes, which typically larger than in other wood species. The greyscale intensity images (Figure 2a,b), are typical of poplar. Bordered pits organized in lines, probably connecting fibers and obtained by optically summing all excited nonlinear signals, highlight the organization of vessels, were also observed. Their size, between 10 and 15 m, is typically larger than in pits, demonstrating that NLO microscopy can be used to noninvasively assess wood mi- other wood species. The greyscale intensity images (Figure 2a,b), obtained by optically crostructure with high resolution. A more detailed analysis can be performed by separat- summing all excited nonlinear signals, highlight the organization of pits, demonstrating that NLO microscopy can be used to noninvasively assess wood microstructure with high ing the two nonlinear contributions: The merged TPEF/SHG image (Figure 2c) shows sim- resolution. A more detailed analysis can be performed by separating the two nonlinear ilar microstructures while providing additional molecular information based on the spe- contributions: The merged TPEF/SHG image (Figure 2c) shows similar microstructures cific nonlinear contrast mechanism. The observed fluorescence signal (green-coded in the while providing additional molecular information based on the specific nonlinear contrast image) is predominant and indicative of the presence of lignin. Specifically, fluorescence mechanism. The observed fluorescence signal (green-coded in the image) is predominant emission can be ascribed to syringyl p-hydroxybenzoate lignin, which in poplar is local- and indicative of the presence of lignin. Specifically, fluorescence emission can be ascribed ized in the inner secondary fiber wall [25]. In the analyzed area, the SHG signal is almost to syringyl p-hydroxybenzoate lignin, which in poplar is localized in the inner secondary absent except for some traces (red spots) inside the pits (Figure 2c) that are ascribable to fiber wall [25]. In the analyzed area, the SHG signal is almost absent except for some traces starch grains, which are stored in the parenchyma rays and are visible through the pit (red spots) inside the pits (Figure 2c) that are ascribable to starch grains, which are stored in the parenchyma rays and are visible through the pit membrane. membrane. Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue ar- tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue arrow- 2 2 2 2 heads. rowheads. Greysca Gr le eyscale intensity intensity images ( images a) 100 (a × 10 ) 1000 μ100 m and ( m and b) 200 × (b) 200 200 μ 200 m ar m e obta are obtained ined by o by ptically sum optically ming all ex summing cited nonlinear all excited sig nonlinear nals, thu signals, s showin thus g both SHG showing both and TP SHGEF and sig TPEF nals ind signals istinindis- ctively. (c) tinctively. (c) TPEF/SHG merged image (200  200 m ) enabling the distinction between TPEF TPEF/SHG merged image (200 × 200 μm ) enabling the distinction between TPEF (green-coded) and SHG (red-co (green-coded) dedand ) signals, attributed to SHG (red-coded) signals, lignin and attributed starch (pointed out to lignin and starchby the red arrowheads), re- (pointed out by the red specti arrowheads), vely. respectively. Photonics 2022, 9, x FOR PEER REVIEW 6 of 11 typically larger than in other wood species. The greyscale intensity images (Figure 2a,b), obtained by optically summing all excited nonlinear signals, highlight the organization of pits, demonstrating that NLO microscopy can be used to noninvasively assess wood mi- crostructure with high resolution. A more detailed analysis can be performed by separat- ing the two nonlinear contributions: The merged TPEF/SHG image (Figure 2c) shows sim- ilar microstructures while providing additional molecular information based on the spe- cific nonlinear contrast mechanism. The observed fluorescence signal (green-coded in the image) is predominant and indicative of the presence of lignin. Specifically, fluorescence emission can be ascribed to syringyl p-hydroxybenzoate lignin, which in poplar is local- ized in the inner secondary fiber wall [25]. In the analyzed area, the SHG signal is almost absent except for some traces (red spots) inside the pits (Figure 2c) that are ascribable to starch grains, which are stored in the parenchyma rays and are visible through the pit membrane. Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue arrow- 2 2 heads. Greyscale intensity images (a) 100 × 100 μm and (b) 200 × 200 μm are obtained by optically summing all excited nonlinear signals, thus showing both SHG and TPEF signals indistinctively. (c) TPEF/SHG merged image (200 × 200 μm ) enabling the distinction between TPEF (green-coded) and Photonics 2022, 9, 170 SHG (red-coded) signals, attributed to lignin and starch (pointed out by the red arrowheads), re- 6 of 11 spectively. Figure 3. (a) Poplar greyscale NLO microscopy images (200  200 m ) and (b) corresponding TPEF/SHG merged images acquired at different depths inside the wood slice (tangential section), highlighting the presence of SHG emitters. Depths of recording from the sample’s surface are indicated in the top right corner (81 m scanning depth; 1 m sampling step). A slightly more intense SHG signal was detected when imaging deeper into the sample, as shown in the combined TPEF/SHG stacks (Figure 3b), which are reported in comparison to the corresponding greyscale images (Figure 3a). In this case, the SHG signal is confined to small spots and is probably located in the secondary cell walls of vessels. Weaker signals are distributed in the upper part of the analyzed area. 3.2. Beech (Fagus sylvatica L.) Vessels in beech can be found isolated or in the form of aggregates of 2–6 units. They are generally numerous and uniformly distributed inside the growth rings, with size ranging between 50 and 75 m. Big and abundant pits between vessels are usually organized in horizontal lines. The parenchyma rays, which are generally composed of several series of cells (up to 25), are clearly visible in three of the analyzed areas, as shown 2 2 in Figure 4a–c (FOV: 100  100 m ) (FOV: 200  200 m ). The TPEF/SHG axial stacks of the same area acquired with 5 m steps are reported in Figure 4. Contrary to poplar, the SHG signal (red-coded) generated in beech is more widespread inside xylem and phloem cells, especially inside the rays and around the fibers, as demonstrated by larger red areas observed in the tangential sections reported here. Possible sources of the SHG signal are crystalline cellulose and particularly starch in the form of crystalline amylose, which is common in beech microstructures, specifically in the area underneath the bark (where this sample was extracted). The fluorescence signal from the cells is predominantly due to lignin, which is distributed in the secondary wall layers. In beech fibers, lignin Photonics 2022, 9, x FOR PEER REVIEW 7 of 11 Figure 3. (a) Poplar greyscale NLO microscopy images (200 × 200 μm ) and (b) corresponding TPEF/SHG merged images acquired at different depths inside the wood slice (tangential section), highlighting the presence of SHG emitters. Depths of recording from the sample’s surface are indi- cated in the top right corner (81 μm scanning depth; 1 μm sampling step). A slightly more intense SHG signal was detected when imaging deeper into the sam- ple, as shown in the combined TPEF/SHG stacks (Figure 3b), which are reported in com- parison to the corresponding greyscale images (Figure 3a). In this case, the SHG signal is confined to small spots and is probably located in the secondary cell walls of vessels. Weaker signals are distributed in the upper part of the analyzed area. 3.2. Beech (Fagus sylvatica L.) Vessels in beech can be found isolated or in the form of aggregates of 2–6 units. They are generally numerous and uniformly distributed inside the growth rings, with size rang- ing between 50 and 75 μm. Big and abundant pits between vessels are usually organized in horizontal lines. The parenchyma rays, which are generally composed of several series of cells (up to 25), are clearly visible in three of the analyzed areas, as shown in Figure 4a– 2 2 c (FOV: 100 × 100 μm ) (FOV: 200 × 200 μm ). The TPEF/SHG axial stacks of the same area acquired with 5 μm steps are reported in Figure 4. Contrary to poplar, the SHG signal (red-coded) generated in beech is more widespread inside xylem and phloem cells, espe- cially inside the rays and around the fibers, as demonstrated by larger red areas observed in the tangential sections reported here. Possible sources of the SHG signal are crystalline Photonics 2022, 9, 170 7 of 11 cellulose and particularly starch in the form of crystalline amylose, which is common in beech microstructures, specifically in the area underneath the bark (where this sample was extracted). The fluorescence signal from the cells is predominantly due to lignin, which i follows s di the stdir ribut ection ed in of tcellulose he seconda micr ry w ofibrils all laclosely yers. In b , which eech fibers, lignin follows t are responsible for the lamellar he direc- tistr onuctur of cee ll[ ul 37 os ].e microfibrils closely, which are responsible for the lamellar structure [37]. Figure 4. Figure 4.Be Beech ech NLO micro NLO microscopy scopy images (excitation wave images (excitation wavele le ngth ngth 850 nm), showing the fibers (light 850 nm), showing the fibers (light- - blue arrowheads) in the tangential section and the aggregates of parenchyma rays (yellow arrow- blue arrowheads) in the tangential section and the aggregates of parenchyma rays (yellow arrow- heads) in the transverse section. Images are obtained from the maximum-intensity projection over heads) in the transverse section. Images are obtained from the maximum-intensity projection over all all acquired images in a stack (101 μm scanning depth; 1 μm sampling step), thus enhancing the acquired images in a stack (101 m scanning depth; 1 m sampling step), thus enhancing the visual- visualization of the inner details. (a,c) TPEF and SHG signals generated from lignin and cellu- ization of the inner details. (a,c) TPEF and SHG signals generated from lignin and cellulose/starch lose/starch are optically summed. (b,d) Merged TPEF/SHG image showing the morphology of rays are optically summed. (b,d) Merged TPEF/SHG image showing the morphology of rays and fibers, and fibers, as well as the distribution of SHG and fluorescence emitters. as well as the distribution of SHG and fluorescence emitters. 3.3.3. 3. CChestnut hestnut (C (Castanea astanea ssativa ativa M. M.) ) The microstructure in chestnut shavings is characterized by vessels (size of around The microstructure in chestnut shavings is characterized by vessels (size of around 10 m) arranged in oblique lines, which are typical of the latewood region. Conversely, ear- 10 μm) arranged in oblique lines, which are typical of the latewood region. Conversely, lywood is characterized by considerably larger vessels forming porous circles of 300–500 m earlywood is characterized by considerably larger vessels forming porous circles of 300– diameter. Pits between cells, which are larger in chestnut wood than in poplar and beech, 500 μm diameter. Pits between cells, which are larger in chestnut wood than in poplar and Photonics 2022, 9, x FOR PEER REVIEW 8 of 11 were not observed in the analyzed samples. External deformations of parenchyma radial beech, were not observed in the analyzed samples. External deformations of parenchyma and axial cells, partially occluding adjacent vessels, were observed in the tangential shaving radial and axial cells, partially occluding adjacent vessels, were observed in the tangential inside the transverse section of the parenchyma rays (Figure 5). These conformations were shaving inside the transverse section of the parenchyma rays (Figure 5). These confor- identified as tyloses, which are common in chestnut species. In the analyzed samples, samples, an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in mations were identified as tyloses, which are common in chestnut species. In the analyzed an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in small small aggregates, as observed in Figure 5a,c. aggregates, as observed in Figure 5a,c. Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an exci- excitation wavelength of 800 nm, a FOV of 200  200  2m , and a resolution of 1024  1024 pixels. tation wavelength of 800 nm, a FOV of 200 × 200 μm , and a resolution of 1024 × 1024 pixels. Tyloses Tyloses (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views xz and yz (Figure 6b), acquired over a depth of 80 m using an axial step of 1 m. xz and yz (Figure 6b), acquired over a depth of 80 μm using an axial step of 1 μm. Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. 4. Discussion This study shows that the combined application of TPEF and SHG imaging offers a noninvasive and effective tool for clear visualization and differentiation of key micro- structural features in different wood species. The 3D mapping allows for a qualitative discrimination/localization of the main molecular components of the cell walls (namely lignin, cellulose, and starch) due to their nonlinear optical properties. Such information is useful for comparing and characterizing different wood species, as well as for document- ing the effects of aging and/or restoration treatments on wooden artwork at the micro- structural level. The acquisition of nonlinear signals in the backward direction enables the analysis of samples of any thickness, thus enlarging the application of the method to a variety of objects. Moreover, it was demonstrated that well-resolved and well-contrasted TPEF/SHG images can be obtained from bulk wood samples with an air objective rather than a water-immersion one, despite a reduced NA. In this manner, liquid-sensitive and sometimes porous artwork materials can be fully preserved from damage. The use of po- larization-resolved SHG imaging can be exploited to obtain quantitative information and to determine the orientation of cellulose microfibrils [38], thus improving their visibility Photonics 2022, 9, x FOR PEER REVIEW 8 of 11 samples, an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in small aggregates, as observed in Figure 5a,c. Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an exci- tation wavelength of 800 nm, a FOV of 200 × 200 μm , and a resolution of 1024 × 1024 pixels. Tyloses (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. Photonics 2022, 9, 170 8 of 11 The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views xz and yz (Figure 6b), acquired over a depth of 80 μm using an axial step of 1 μm. Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. 4. Discussion 4. Discussion This study shows that the combined application of TPEF and SHG imaging offers a This study shows that the combined application of TPEF and SHG imaging offers a noninvasive and effective tool for clear visualization and differentiation of key microstruc- noninvasive and effective tool for clear visualization and differentiation of key micro- tural features in different wood species. The 3D mapping allows for a qualitative discrim- structural features in different wood species. The 3D mapping allows for a qualitative ination/localization of the main molecular components of the cell walls (namely lignin, discrimination/localization of the main molecular components of the cell walls (namely cellulose, and starch) due to their nonlinear optical properties. Such information is useful lignin, cellulose, and starch) due to their nonlinear optical properties. Such information is for comparing and characterizing different wood species, as well as for documenting the useful for comparing and characterizing different wood species, as well as for document- effects of aging and/or restoration treatments on wooden artwork at the microstructural ing the effects of aging and/or restoration treatments on wooden artwork at the micro- level. The acquisition of nonlinear signals in the backward direction enables the analysis structural level. The acquisition of nonlinear signals in the backward direction enables the of samples of any thickness, thus enlarging the application of the method to a variety of analysis of samples of any thickness, thus enlarging the application of the method to a objects. Moreover, it was demonstrated that well-resolved and well-contrasted TPEF/SHG variety of objects. Moreover, it was demonstrated that well-resolved and well-contrasted images can be obtained from bulk wood samples with an air objective rather than a water- TPEF/SHG images can be obtained from bulk wood samples with an air objective rather immersion one, despite a reduced NA. In this manner, liquid-sensitive and sometimes than a water-immersion one, despite a reduced NA. In this manner, liquid-sensitive and porous artwork materials can be fully preserved from damage. The use of polarization- sometimes porous artwork materials can be fully preserved from damage. The use of po- resolved SHG imaging can be exploited to obtain quantitative information and to determine larization-resolved SHG imaging can be exploited to obtain quantitative information and the orientation of cellulose microfibrils [38], thus improving their visibility in cell walls. to determine the orientation of cellulose microfibrils [38], thus improving their visibility Nonlinear microscopy can be profitably combined with coherent anti-Stokes Raman scatter- ing (CARS) for a more comprehensive characterization of the chemical components, using 1 1 the C=C vibration at 1600 cm as a lignin marker and the C-O-C vibration at 1100 cm as a cellulose marker [39]. It has already been shown that the integration of data obtained by TPEF-SHG and CARS enables the ability to monitor changes in cellulose supramolecular structure during enzymatic hydrolysis [40]. In addition, the level of unwanted fluorescence due to the crosstalk effect within the SHG channel should be considered in SHG/TPEF analyses. We evaluated the contribution of crosstalk on poplar samples from time-resolved measurements, resulting in approxi- mately 5%. Although this is a small percentage of the overall signal, this effect can vary significantly across wood species and conditions and increase with excitation wavelength, as observed in [41]. Thus, a compromise between safety and crosstalk must be considered when choosing the excitation wavelength: shorter wavelengths, although potentially more dangerous, result in less fluorescence crosstalk in the SHG channel; longer wavelengths, although safer, cause higher crosstalk. The reported results suggest that some of the effects of wood degradation can be monitored at the molecular level by combined TPEF/SHG imaging. Both weathering [42] and biological attack by fungi [43] cause an enrichment of the relative crystalline content of wood (cellulose) at the expense of the amorphous fractions (hemicellulose and lignin), with a concomitant increase in the size of crystallites and a reduction in molecular weight of cellulose due to thermo-oxidative processes [44]. Therefore, it is reasonable to expect that Photonics 2022, 9, 170 9 of 11 this variation in the relative amounts of wood microcomponents could result in a change of ratios between TPEF and SHG signals and, specifically, an increase in the SHG signal from cellulose. The contributions of the individual components can be quantified by measuring the intensity of their respective NL signals (see Supplementary Materials). Monitoring the stability of signals over time would also allow for testing on the effectiveness of protective treatments on wooden artifacts. Since the effects of degradation can vary greatly by wood species, a comparative study of the most commonly used species for artwork production can be extremely useful. 5. Conclusions This work paves the way for a systematic application of combined TPEF/SHG imag- ing on many wood species, which is necessary for a thorough characterization of the microstructures based on the nonlinear optical properties of the components. Considering that compact, flexible multiphoton microscopy systems have been already developed and successfully used in the biomedical field [45,46], a specific system allowing for in situ measurements of large objects is, without a doubt, feasible and highly suitable for the application of NLO analysis on works of art. Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/photonics9030170/s1, Figure S1: NLO microscopy images of poplar (a–c), beech (d–f), chestnut (g–i) shavings cut in the tangential section along the stem length direction. Images were acquired under the same experimental conditions and with 840–850 nm excitation wavelength. The 8-bit grey-scale images are the individual channels (red = SHG, and green = TPEF) of the merged SHG/TPEF images (c,f,i), and show the contribution of SHG (a,d,g) and TPEF (b,e,h) signals as the intensity of light at each pixel in the dynamic range 0–255. Author Contributions: Conceptualization, R.F., R.C. and A.D.F.; methodology, R.C., R.F. and A.D.F.; software, M.M.; validation, R.C. and R.F.; formal analysis, S.M., A.D.F. and E.B.; investigation, A.D.F. and S.M.; resources, R.C.; data curation, A.D.F., S.M. and E.B.; writing—original draft preparation, A.D.F.; writing—review and editing, A.D.F., R.C., A.G., R.F. and S.M.; visualization, M.M. and M.A.; supervision, R.F., R.C. and A.G.; project administration, R.F. and R.C.; funding acquisition, R.F. and R.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Regione Toscana (POR FSE 2014–2020, “Giovanisì”, Interven- tion Program “CNR4C”, CUP B15J19001040004) and the European H2020 IPERION CH Project (Inte- grated Platform for the European Research Infrastructure ON Cultural Heritage (GA 654028, WP6). Conflicts of Interest: The authors declare no conflict of interest. References 1. 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Combined TPEF and SHG Imaging for the Microstructural Characterization of Different Wood Species Used in Artworks

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hv photonics Article Combined TPEF and SHG Imaging for the Microstructural Characterization of Different Wood Species Used in Artworks 1 , 1 2 , 3 4 5 1 Alice Dal Fovo * , Sara Mattana , Marco Marchetti , Monica Anichini , Alessio Giovannelli , Enrico Baria , 1 1 , 3 Raffaella Fontana and Riccardo Cicchi National Research Council, National Institute of Optics (CNR-INO), Largo E. Fermi 6, 50125 Firenze, Italy; sara.mattana@ino.cnr.it (S.M.); enrico.baria@ino.cnr.it (E.B.); raffaella.fontana@ino.it (R.F.); riccardo.cicchi@ino.cnr.it (R.C.) Department of Physics, University of Florence, Via G. Sansone 1, 50019 Sesto Fiorentino, Italy; m.marchetti@l4t.it European Laboratory for Non-Linear Spectroscopy (LENS), Via N. Carrara 1, 50019 Sesto Fiorentino, Italy National Research Council, Institute of BioEconomy (CNR-IBE), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy; monica.anichini@ibe.cnr.it National Research Council, Research Institute on Terrestrial Ecosystems (CNR-IRET), Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy; alessio.giovannelli@cnr.it * Correspondence: alice.dalfovo@ino.cnr.it Abstract: The morphological and chemical conformation of wood microstructures is characteristic of individual species and strongly influences the macromechanical properties of the material, as well as its sensitivity to deterioration factors. Noninvasive techniques enabling the visualization of wood microstructures, while simultaneously providing compositional information, can significantly facilitate the analysis of wooden artworks for conservation purposes. In this paper, we present the application of combined two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) imaging as a versatile diagnostic tool for the microcharacterization of three hardwood species never analyzed by this method. Multimodal mapping of the molecular constituents based on the Citation: Dal Fovo, A.; Mattana, S.; detected nonlinear signals provides useful information for studying the biological and biochemical Marchetti, M.; Anichini, M.; deterioration of wood, opening a new field of application for a well-established and widely used Giovannelli, A.; Baria, E.; Fontana, R.; imaging technology. Cicchi, R. Combined TPEF and SHG Imaging for the Microstructural Keywords: second-harmonic generation; two-photon excited fluorescence; wood microstructure; Characterization of Different Wood cellulose; lignin; starch Species Used in Artworks. Photonics 2022, 9, 170. https://doi.org/ 10.3390/photonics9030170 Received: 6 January 2022 1. Introduction Accepted: 7 March 2022 Wood has been used extensively since ancient times with both a structural and decora- Published: 10 March 2022 tive function in a variety of art objects, ranging from sculptures to paintings and musical Publisher’s Note: MDPI stays neutral instruments. The multiscale and anisotropic structure of wood is highly hygroscopic due with regard to jurisdictional claims in to the presence of differently oriented pores, for which the peculiar size and shape are key published maps and institutional affil- parameters for differentiation among wood species [1,2]. Given the importance of cell walls iations. in the growth and morphogenesis of the microstructures, it is of great interest to investigate how molecular components are organized in the three dimensions [3]. The geometry of the microstructures determines the accessibility of degradative organisms and substances and, thus, is strictly related to biological and biochemical degradation [4]. Moreover, the sensi- Copyright: © 2022 by the authors. tivity of wood cells to environmental changes can be monitored based on the alterations Licensee MDPI, Basel, Switzerland. occurring at the molecular level, which strongly influence the macromechanical properties This article is an open access article of the timber or wood products [5]. distributed under the terms and The main chemical components of wood cells, namely cellulose, hemicellulose, and conditions of the Creative Commons lignin, are characterized by nonlinear optical (NLO) properties, which can be exploited Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ to obtain morphological, structural, and compositional information on the microstruc- 4.0/). tures [6–8]. NLO microscopies are well-established 3D imaging techniques that have been Photonics 2022, 9, 170. https://doi.org/10.3390/photonics9030170 https://www.mdpi.com/journal/photonics Photonics 2022, 9, 170 2 of 11 widely applied in the biological field for the label-free nondestructive investigation of physio-pathological processes in live samples at a subcellular spatial resolution [9]. The combined use of different NLO microscopy modalities, such as two- and three-photon ex- cited fluorescence (TPEF [10] and 3PF [11,12]) and second- and third-harmonic generation (SHG [13] and THG [14]), provides complementary information based on the detection of fluorophores (by TPEF and 3PF), crystalline or highly organized structures without inversion symmetry (by SHG), and local differences in refractive index and dispersion, i.e., interfaces (by THG) [15]. Nonlinear processes are generated through the interaction of atoms and/or molecules with two or more photons within the same quantum event. Being second- or higher-order optical processes, their inherent low probability to occur requires a high spatial and temporal density of photons, which is typically achieved with tightly focused ultrashort-pulsed lasers. Nonlinear processes allow using near-infrared photons for exciting molecular transitions, which are typically located in the blue/UV spectral range. The major advantage, compared to linear optical techniques, is that non- linear optical signals (SHG, THG, TPEF, and 3PF) can be generated at higher penetration depths (exceeding 500 m in biological tissues [16]) due to the reduced light scattering and absorption of the infrared excitation wavelengths [9]. Furthermore, given the square or cubic dependence of the signal on excitation intensity, the efficient nonlinear interaction is typically confined to a femtoliter region around the focal point, as only ballistic photons contribute to the excitation process. This enables high-resolution sectioning with drastically diminished out-of-focus damages. The noninvasiveness of the technique, which is a crucial requirement in artwork diagnostics, can be ensured by simply monitoring the variation in TPEF signal intensity as a forewarning of photochemical changes inside the focal volume of the laser beam [17]. The microstructure of wood consists of cells arranged along the axis of the trunk and developed with the parenchyma rays from the core of the tree to the bark (Figure 1) [18]. Cel- lular arrangement and morphology determine substantial anatomical differences between softwoods—i.e., gymnosperms (conifers)—and hardwoods—i.e., angiosperms (flowering plants) (see Section 2.2. Microstructural Features) [19]. The supramolecular conformation of cellulose, which resembles that of collagen in both morphology and symmetry, may yield a strong SHG signal similar to collagen due to the hierarchical structure and the parallel orientation of the composite molecular chains. Furthermore, the strong birefringence and chirality of the polysaccharide chains of cellulose may significantly increase SHG intensity, which is another similarity with the array of polypeptides in collagen [20]. The generation of SH from cellulose is also strongly dependent on the orientation of microfibrils, which develop predominantly along the axis of longitudinal arrays of cells [20]. Another possible source of an SHG signal in wood is starch, a mixture of the two polysaccharides amylose and amylopectin. Within the stem, starch is stored in large amounts in the companion cells of the phloem (inner side of the bark) and in the parenchyma ray of the xylem. Starch represents a long-term carbon reserve in a wide variety of or- ganisms, such as seeds and tubers, and a temporary reserve in photosynthetic tissues, specifically in chloroplasts. In particular, Amylose is often highly crystalline and, thus, is likely to generate second-harmonic signals [8]. Starch emits stronger SHG signals than cellu- lose due to the reverse orientation of glucose residues in the polysaccharidic chains [21,22]. Therefore, SHG imaging of cellulose requires rather high laser powers (above optimal val- ues for live cell imaging), whereas starch can be easily imaged at laser fluencies compatible with extended cell viability. Cell walls exhibit natural fluorescence due to the presence of lignin [23]. The emission covers a broad spectral range (blue, green, and red) depending on the excitation wave- length (with maximum absorbance by lignin at 280 nm) and on the pH of the molecular environment [24]. The fluorescence can differ significantly in hardwood and softwood species both in terms of intensity and spectral emission [25,26]. It has been observed that fluorescence from lignin can also be generated nonlinearly, namely through three- and Photonics 2022, 9, 170 3 of 11 two-photon absorption at 840–860 nm [8,27]. While lignin is the predominant fluorophore Photonics 2022, 9, x FOR PEER REVIEW 3 of 11 in cell walls, the polysaccharide components, such as cellulose and starch, are considered not fluorescent [28]. Figure 1. Wood sections at the macroscale (top left); schematic microstructure of hardwood species Figure 1. Wood sections at the macroscale (top left); schematic microstructure of hardwood species (top middle) with NLO images (diameter = 200 μm) of the microstructure of poplar xylem in trans- (top middle) with NLO images (diameter = 200 m) of the microstructure of poplar xylem in verse and radial sections (top right). Schematic representation of cell wall layers—ML, middle la- transverse and radial sections (top right). Schematic representation of cell wall layers—ML, middle mella; P, primary cell wall; S1, S2, and S3, sublayers of secondary cell wall (bottom left); close up of a microfibril bundle from S2 showing individual crystallites of cellulose glued together by the in- lamella; P, primary cell wall; S1, S2, and S3, sublayers of secondary cell wall (bottom left); close up terfibrillar compounds of hemicellulose and lignin (bottom right). of a microfibril bundle from S2 showing individual crystallites of cellulose glued together by the interfibrillar compounds of hemicellulose and lignin (bottom right). The supramolecular conformation of cellulose, which resembles that of collagen in both morphology and symmetry, may yield a strong SHG signal similar to collagen due To the best of our knowledge, the first 3D imaging of wood microstructures on an to the hierarchical structure and the parallel orientation of the composite molecular chains. Furthermore, the strong birefringence and chirality of the polysaccharide chains artistic object was performed in 2009, with a purposefully developed time-domain OCT of cellulose may significantly increase SHG intensity, which is another similarity with the system, based on an illumination source centered at 650 nm and reaching axial and trans- array of polypeptides in collagen [20]. The generation of SH from cellulose is also strongly verse resolutions of 1.5 and 1 m, respectively [18]. However, the visualization of wood dependent on the orientation of microfibrils, which develop predominantly along the axis cells provided by OCT tomograms lacked any chemical information. To overcome such a of longitudinal arrays of cells [20]. limit, some years later Another possible source of a , the same author applied n SHG si TPEF gnal in and wood SHG is ston arch, thin a mshavings ixture of the t ofw acer o polysaccharides amylose and amylopectin. Within the stem, starch is stored in large wood and a historical violin, obtaining both the imaging and the chemical characterization amounts in the companion cells of the phloem (inner side of the bark) and in the paren- of wood microstructures [27]. Although SHG emissions are generally more efficient in chyma ray of the xylem. Starch represents a long-term carbon reserve in a wide variety of the forward direction due to phase-matching conditions, it was demonstrated that the organisms, such as seeds and tubers, and a temporary reserve in photosynthetic tissues, SH signal can also specif be ical recor ly in chlorop ded inla the sts. backwar In particular d , dir Amylos ection e is of when ten high it is ly cr enhanced ystalline and by , tspecific hus, is likely to generate second-harmonic signals [8]. Starch emits stronger SHG signals than structures or backscattered in thick scattering wood samples [29]. cellulose due to the reverse orientation of glucose residues in the polysaccharidic chains In this work, we extended the application of TPEF-SHG imaging to three hardwood [21,22]. Therefore, SHG imaging of cellulose requires rather high laser powers (above op- species widely used in art production—poplar, beech, and chestnut—that have never been timal values for live cell imaging), whereas starch can be easily imaged at laser fluencies analyzed with these modalities. Nonlinear signals, collected in epi-detection, were com- compatible with extended cell viability. bined into intensity images Cell walls exh to dif ibit natur ferentiate al fluorescenc and quantify e due to chemical the presence of lignin components. [23]. The emission The purpose covers a broad spectral range (blue, green, and red) depending on the excitation wave- of this study is to provide a noninvasive and effective tool for the rapid recognition of wood length (with maximum absorbance by lignin at 280 nm) and on the pH of the molecular species used in art production based on compositional and morphological information at the micrometer level that can be profitably used for conservation and restoration purposes. 2. Materials and Methods 2.1. Samples Wood shavings were collected from mature trees of poplar (Populus tremula L.), beech (Fagus sylvatica L.), and chestnut (Castanea sativa M.) growing in a mixed forest in northern Photonics 2022, 9, 170 4 of 11 Tuscany, Italy. Prismatic wood samples (15  10  5 mm ) were obtained by notching a piece of stem with a blade in the tangential direction (Figure 1). The wood shavings were stored for a week at 4 C before the analysis. To test the applicability of the method on CH objects without sampling while fulfilling the noninvasiveness requirements, the samples were analyzed without any pretreatment, even if the addition of a solution of glycerine and water would have eased the observation of the microstructures [30]. 2.2. Microstructural Features The major components of the physical and chemical properties of wood are the distri- bution and number of different cell types, namely tracheids (constituting around 90% of the volume of softwood), vessels, parenchyma, and fibers (the main components in hard- woods) [31]. The latewood, also called summerwood, can be distinguished from earlywood or springwood because of the smaller radial dimensions of the cells and the thicker walls, which also is reflected in the higher density of the bulk. A further diagnostic element for the differentiation of wood species is the presence of isolated interruptions inside the cell walls of xylem conduits (i.e., vessels and tracheids), called “pits”, which connect different cells for the transfer of sap. The pit membrane has a key function in the overall hydraulic efficiency of plants, allowing water to diffuse between conduits but limiting the spread of embolism and vascular pathogens. The shape and dimension of pits significantly vary depending on the type of adjacent cells and, therefore, can be considered distinctive features of the wood species [32]. Looking more deeply into the microstructures, plant cells show a globular, elongated bag shape. The cell wall is a membrane composed of different layers, namely the primary (P) and the secondary (S) layers, which in turn is composed of three sublayers: S1, S2, and S3 (Figure 1). Adjacent cells are connected by an additional layer, called the middle lamella (ML). Inside the cell wall, laminar crystallites of cellulose are organized in microfibrils, which are embedded in a complex matrix of variously amor- phous polysaccharides (hemicellulose), cross-linked with lignin, a condensed polymer of coniferyl, sinapyl, or p-coumaryl alcohol (Figure 1) [31,33]. Cellulose is a linear chain of polysaccharidic molecules linked by -(1–4) glycosidic bonds displaying a twofold ribbon conformation. Many packing arrangements of the polysaccharidic chains are possible, and all are classifiable in cellulose I (the most abundant type, with parallel chains) and II (with antiparallel chains) [34]. Cellulose I naturally occurs in two distinct crystalline forms, I and I , showing triclinic and monoclinic symmetry, respectively. These well-ordered molecular chains are predominantly located in the secondary cell wall in variable propor- tions and crystallize into the thermodynamically stable microfibrils, with a typical diameter ranging from 1.2 to 4.8 nm and lengths between 60 and 150 nm [35]. The distribution of the microfibrils differs in quantity and arrangement depending on their location in the cell wall. While the content of cellulose is about the same in both softwood and hardwood, exceeding approximately 40–45% in weight of the dry matter in most wood species, lignin is present in different quantities (usually ranging from 18% to 25% in hardwoods and from 25% to 35% in softwoods). 2.3. Nonlinear Setup The nonlinear setup used for the analysis was developed at CNR-INO and is equipped with a dual-output Yb-based fiber fs-laser (Chameleon Discovery, Coherent Inc., Santa Clara, CA, USA). A detailed description of the system can be found elsewhere [36]. Based on previous applications of NLO on wood microstructures [27], the excitation wavelength was set at 840–850 nm (depending on the wood species), with a pulse duration of 140 fs and a repetition rate of 80 MHz, and with the power on the specimen ranging from 30 to 50 mW. Nonlinear signals coming from the sample were epi-collected using a Plan Apochromat20 objective lens (NA 0.75, WD 1 mm, Nikon, Nikon Minato, Tokyo, Japan) and detected with two photomultiplier tubes (H7422-40, Hamamatsu, Hamamatsu City, Japan) for simultaneous TPEF and SHG detection. A dichroic beam splitter filter with a 452 nm cutoff wavelength (FF452-Di01, Semrock Inc. New York, NY, USA) was used Photonics 2022, 9, 170 5 of 11 for separating TPEF from SHG. In more detail, the TPEF signal was transmitted by the dichroic and detected without any additional emission filters, which is in agreement with previous observations on TPEF emission’s spectral range of lignin [27]; the SHG signal was reflected by the dichroic and then filtered with a narrow band-pass filter centered at 420 nm (BrightLine 420/10–25 nm, Semrock Inc., New York, NY, USA). For each analyzed area, the TPEF and SHG signals were detected and displayed as intensity images, which were merged with a Java image processing software (see Figure S1 in the Supplementary Materials). Specifically, the TPEF and SHG images were assigned to the green and the red channels, respectively, thus enabling the distinction among components generating the different nonlinear signals (mainly starch, cellulose, and lignin) in a single image, as well as allowing for the visualization of micrometric features that are characteristic of each species. 3. Results 3.1. Poplar (Populus tremula L.) The microanalysis of poplar shavings (tangential section) revealed the peculiar size and Photonics 2022, 9, x FOR PEER REVIEW 6 of 11 shape of the cells composing this species (Figures 2 and 3). The observed vessels, which are uniformly distributed along the ring with dimensions slightly varying between latewood and earlywood zones, were relatively small (50–100 m), with circular or polygonal shapes. The parenchyma rays, mostly mono-seriated, showed homogenous shapes and sizes, which typically larger than in other wood species. The greyscale intensity images (Figure 2a,b), are typical of poplar. Bordered pits organized in lines, probably connecting fibers and obtained by optically summing all excited nonlinear signals, highlight the organization of vessels, were also observed. Their size, between 10 and 15 m, is typically larger than in pits, demonstrating that NLO microscopy can be used to noninvasively assess wood mi- other wood species. The greyscale intensity images (Figure 2a,b), obtained by optically crostructure with high resolution. A more detailed analysis can be performed by separat- summing all excited nonlinear signals, highlight the organization of pits, demonstrating that NLO microscopy can be used to noninvasively assess wood microstructure with high ing the two nonlinear contributions: The merged TPEF/SHG image (Figure 2c) shows sim- resolution. A more detailed analysis can be performed by separating the two nonlinear ilar microstructures while providing additional molecular information based on the spe- contributions: The merged TPEF/SHG image (Figure 2c) shows similar microstructures cific nonlinear contrast mechanism. The observed fluorescence signal (green-coded in the while providing additional molecular information based on the specific nonlinear contrast image) is predominant and indicative of the presence of lignin. Specifically, fluorescence mechanism. The observed fluorescence signal (green-coded in the image) is predominant emission can be ascribed to syringyl p-hydroxybenzoate lignin, which in poplar is local- and indicative of the presence of lignin. Specifically, fluorescence emission can be ascribed ized in the inner secondary fiber wall [25]. In the analyzed area, the SHG signal is almost to syringyl p-hydroxybenzoate lignin, which in poplar is localized in the inner secondary absent except for some traces (red spots) inside the pits (Figure 2c) that are ascribable to fiber wall [25]. In the analyzed area, the SHG signal is almost absent except for some traces starch grains, which are stored in the parenchyma rays and are visible through the pit (red spots) inside the pits (Figure 2c) that are ascribable to starch grains, which are stored in the parenchyma rays and are visible through the pit membrane. membrane. Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue ar- tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue arrow- 2 2 2 2 heads. rowheads. Greysca Gr le eyscale intensity intensity images ( images a) 100 (a × 10 ) 1000 μ100 m and ( m and b) 200 × (b) 200 200 μ 200 m ar m e obta are obtained ined by o by ptically sum optically ming all ex summing cited nonlinear all excited sig nonlinear nals, thu signals, s showin thus g both SHG showing both and TP SHGEF and sig TPEF nals ind signals istinindis- ctively. (c) tinctively. (c) TPEF/SHG merged image (200  200 m ) enabling the distinction between TPEF TPEF/SHG merged image (200 × 200 μm ) enabling the distinction between TPEF (green-coded) and SHG (red-co (green-coded) dedand ) signals, attributed to SHG (red-coded) signals, lignin and attributed starch (pointed out to lignin and starchby the red arrowheads), re- (pointed out by the red specti arrowheads), vely. respectively. Photonics 2022, 9, x FOR PEER REVIEW 6 of 11 typically larger than in other wood species. The greyscale intensity images (Figure 2a,b), obtained by optically summing all excited nonlinear signals, highlight the organization of pits, demonstrating that NLO microscopy can be used to noninvasively assess wood mi- crostructure with high resolution. A more detailed analysis can be performed by separat- ing the two nonlinear contributions: The merged TPEF/SHG image (Figure 2c) shows sim- ilar microstructures while providing additional molecular information based on the spe- cific nonlinear contrast mechanism. The observed fluorescence signal (green-coded in the image) is predominant and indicative of the presence of lignin. Specifically, fluorescence emission can be ascribed to syringyl p-hydroxybenzoate lignin, which in poplar is local- ized in the inner secondary fiber wall [25]. In the analyzed area, the SHG signal is almost absent except for some traces (red spots) inside the pits (Figure 2c) that are ascribable to starch grains, which are stored in the parenchyma rays and are visible through the pit membrane. Figure 2. NLO microscopy images of poplar shavings cut along the direction of the stem on the tangential plane (excitation wavelength 840 nm). Bordered pits are pointed out by light-blue arrow- 2 2 heads. Greyscale intensity images (a) 100 × 100 μm and (b) 200 × 200 μm are obtained by optically summing all excited nonlinear signals, thus showing both SHG and TPEF signals indistinctively. (c) TPEF/SHG merged image (200 × 200 μm ) enabling the distinction between TPEF (green-coded) and Photonics 2022, 9, 170 SHG (red-coded) signals, attributed to lignin and starch (pointed out by the red arrowheads), re- 6 of 11 spectively. Figure 3. (a) Poplar greyscale NLO microscopy images (200  200 m ) and (b) corresponding TPEF/SHG merged images acquired at different depths inside the wood slice (tangential section), highlighting the presence of SHG emitters. Depths of recording from the sample’s surface are indicated in the top right corner (81 m scanning depth; 1 m sampling step). A slightly more intense SHG signal was detected when imaging deeper into the sample, as shown in the combined TPEF/SHG stacks (Figure 3b), which are reported in comparison to the corresponding greyscale images (Figure 3a). In this case, the SHG signal is confined to small spots and is probably located in the secondary cell walls of vessels. Weaker signals are distributed in the upper part of the analyzed area. 3.2. Beech (Fagus sylvatica L.) Vessels in beech can be found isolated or in the form of aggregates of 2–6 units. They are generally numerous and uniformly distributed inside the growth rings, with size ranging between 50 and 75 m. Big and abundant pits between vessels are usually organized in horizontal lines. The parenchyma rays, which are generally composed of several series of cells (up to 25), are clearly visible in three of the analyzed areas, as shown 2 2 in Figure 4a–c (FOV: 100  100 m ) (FOV: 200  200 m ). The TPEF/SHG axial stacks of the same area acquired with 5 m steps are reported in Figure 4. Contrary to poplar, the SHG signal (red-coded) generated in beech is more widespread inside xylem and phloem cells, especially inside the rays and around the fibers, as demonstrated by larger red areas observed in the tangential sections reported here. Possible sources of the SHG signal are crystalline cellulose and particularly starch in the form of crystalline amylose, which is common in beech microstructures, specifically in the area underneath the bark (where this sample was extracted). The fluorescence signal from the cells is predominantly due to lignin, which is distributed in the secondary wall layers. In beech fibers, lignin Photonics 2022, 9, x FOR PEER REVIEW 7 of 11 Figure 3. (a) Poplar greyscale NLO microscopy images (200 × 200 μm ) and (b) corresponding TPEF/SHG merged images acquired at different depths inside the wood slice (tangential section), highlighting the presence of SHG emitters. Depths of recording from the sample’s surface are indi- cated in the top right corner (81 μm scanning depth; 1 μm sampling step). A slightly more intense SHG signal was detected when imaging deeper into the sam- ple, as shown in the combined TPEF/SHG stacks (Figure 3b), which are reported in com- parison to the corresponding greyscale images (Figure 3a). In this case, the SHG signal is confined to small spots and is probably located in the secondary cell walls of vessels. Weaker signals are distributed in the upper part of the analyzed area. 3.2. Beech (Fagus sylvatica L.) Vessels in beech can be found isolated or in the form of aggregates of 2–6 units. They are generally numerous and uniformly distributed inside the growth rings, with size rang- ing between 50 and 75 μm. Big and abundant pits between vessels are usually organized in horizontal lines. The parenchyma rays, which are generally composed of several series of cells (up to 25), are clearly visible in three of the analyzed areas, as shown in Figure 4a– 2 2 c (FOV: 100 × 100 μm ) (FOV: 200 × 200 μm ). The TPEF/SHG axial stacks of the same area acquired with 5 μm steps are reported in Figure 4. Contrary to poplar, the SHG signal (red-coded) generated in beech is more widespread inside xylem and phloem cells, espe- cially inside the rays and around the fibers, as demonstrated by larger red areas observed in the tangential sections reported here. Possible sources of the SHG signal are crystalline Photonics 2022, 9, 170 7 of 11 cellulose and particularly starch in the form of crystalline amylose, which is common in beech microstructures, specifically in the area underneath the bark (where this sample was extracted). The fluorescence signal from the cells is predominantly due to lignin, which i follows s di the stdir ribut ection ed in of tcellulose he seconda micr ry w ofibrils all laclosely yers. In b , which eech fibers, lignin follows t are responsible for the lamellar he direc- tistr onuctur of cee ll[ ul 37 os ].e microfibrils closely, which are responsible for the lamellar structure [37]. Figure 4. Figure 4.Be Beech ech NLO micro NLO microscopy scopy images (excitation wave images (excitation wavele le ngth ngth 850 nm), showing the fibers (light 850 nm), showing the fibers (light- - blue arrowheads) in the tangential section and the aggregates of parenchyma rays (yellow arrow- blue arrowheads) in the tangential section and the aggregates of parenchyma rays (yellow arrow- heads) in the transverse section. Images are obtained from the maximum-intensity projection over heads) in the transverse section. Images are obtained from the maximum-intensity projection over all all acquired images in a stack (101 μm scanning depth; 1 μm sampling step), thus enhancing the acquired images in a stack (101 m scanning depth; 1 m sampling step), thus enhancing the visual- visualization of the inner details. (a,c) TPEF and SHG signals generated from lignin and cellu- ization of the inner details. (a,c) TPEF and SHG signals generated from lignin and cellulose/starch lose/starch are optically summed. (b,d) Merged TPEF/SHG image showing the morphology of rays are optically summed. (b,d) Merged TPEF/SHG image showing the morphology of rays and fibers, and fibers, as well as the distribution of SHG and fluorescence emitters. as well as the distribution of SHG and fluorescence emitters. 3.3.3. 3. CChestnut hestnut (C (Castanea astanea ssativa ativa M. M.) ) The microstructure in chestnut shavings is characterized by vessels (size of around The microstructure in chestnut shavings is characterized by vessels (size of around 10 m) arranged in oblique lines, which are typical of the latewood region. Conversely, ear- 10 μm) arranged in oblique lines, which are typical of the latewood region. Conversely, lywood is characterized by considerably larger vessels forming porous circles of 300–500 m earlywood is characterized by considerably larger vessels forming porous circles of 300– diameter. Pits between cells, which are larger in chestnut wood than in poplar and beech, 500 μm diameter. Pits between cells, which are larger in chestnut wood than in poplar and Photonics 2022, 9, x FOR PEER REVIEW 8 of 11 were not observed in the analyzed samples. External deformations of parenchyma radial beech, were not observed in the analyzed samples. External deformations of parenchyma and axial cells, partially occluding adjacent vessels, were observed in the tangential shaving radial and axial cells, partially occluding adjacent vessels, were observed in the tangential inside the transverse section of the parenchyma rays (Figure 5). These conformations were shaving inside the transverse section of the parenchyma rays (Figure 5). These confor- identified as tyloses, which are common in chestnut species. In the analyzed samples, samples, an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in mations were identified as tyloses, which are common in chestnut species. In the analyzed an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in small small aggregates, as observed in Figure 5a,c. aggregates, as observed in Figure 5a,c. Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an exci- excitation wavelength of 800 nm, a FOV of 200  200  2m , and a resolution of 1024  1024 pixels. tation wavelength of 800 nm, a FOV of 200 × 200 μm , and a resolution of 1024 × 1024 pixels. Tyloses Tyloses (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views xz and yz (Figure 6b), acquired over a depth of 80 m using an axial step of 1 m. xz and yz (Figure 6b), acquired over a depth of 80 μm using an axial step of 1 μm. Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. 4. Discussion This study shows that the combined application of TPEF and SHG imaging offers a noninvasive and effective tool for clear visualization and differentiation of key micro- structural features in different wood species. The 3D mapping allows for a qualitative discrimination/localization of the main molecular components of the cell walls (namely lignin, cellulose, and starch) due to their nonlinear optical properties. Such information is useful for comparing and characterizing different wood species, as well as for document- ing the effects of aging and/or restoration treatments on wooden artwork at the micro- structural level. The acquisition of nonlinear signals in the backward direction enables the analysis of samples of any thickness, thus enlarging the application of the method to a variety of objects. Moreover, it was demonstrated that well-resolved and well-contrasted TPEF/SHG images can be obtained from bulk wood samples with an air objective rather than a water-immersion one, despite a reduced NA. In this manner, liquid-sensitive and sometimes porous artwork materials can be fully preserved from damage. The use of po- larization-resolved SHG imaging can be exploited to obtain quantitative information and to determine the orientation of cellulose microfibrils [38], thus improving their visibility Photonics 2022, 9, x FOR PEER REVIEW 8 of 11 samples, an SHG signal, possibly emitted by crystalline cellulose, was detected mainly in small aggregates, as observed in Figure 5a,c. Figure 5. (a) SHG, (b) TPEF, and (c) merged TPEF/SHG images of chestnut acquired using an exci- tation wavelength of 800 nm, a FOV of 200 × 200 μm , and a resolution of 1024 × 1024 pixels. Tyloses (pointed out by the yellow arrowheads) are visible inside the parenchyma rays. Photonics 2022, 9, 170 8 of 11 The SHG signal is also evident in the TPEF/SHG image stack with orthogonal views xz and yz (Figure 6b), acquired over a depth of 80 μm using an axial step of 1 μm. Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged Figure 6. (a) Greyscale NLO microscopy image of chestnut and (b) orthogonal views of a merged TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting TPEF/SHG image stack showing the presence of isolated aggregates of material strongly emitting SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. SHG signals (red-coded) and TPEF signals (green-coded) generated by lignin. 4. Discussion 4. Discussion This study shows that the combined application of TPEF and SHG imaging offers a This study shows that the combined application of TPEF and SHG imaging offers a noninvasive and effective tool for clear visualization and differentiation of key microstruc- noninvasive and effective tool for clear visualization and differentiation of key micro- tural features in different wood species. The 3D mapping allows for a qualitative discrim- structural features in different wood species. The 3D mapping allows for a qualitative ination/localization of the main molecular components of the cell walls (namely lignin, discrimination/localization of the main molecular components of the cell walls (namely cellulose, and starch) due to their nonlinear optical properties. Such information is useful lignin, cellulose, and starch) due to their nonlinear optical properties. Such information is for comparing and characterizing different wood species, as well as for documenting the useful for comparing and characterizing different wood species, as well as for document- effects of aging and/or restoration treatments on wooden artwork at the microstructural ing the effects of aging and/or restoration treatments on wooden artwork at the micro- level. The acquisition of nonlinear signals in the backward direction enables the analysis structural level. The acquisition of nonlinear signals in the backward direction enables the of samples of any thickness, thus enlarging the application of the method to a variety of analysis of samples of any thickness, thus enlarging the application of the method to a objects. Moreover, it was demonstrated that well-resolved and well-contrasted TPEF/SHG variety of objects. Moreover, it was demonstrated that well-resolved and well-contrasted images can be obtained from bulk wood samples with an air objective rather than a water- TPEF/SHG images can be obtained from bulk wood samples with an air objective rather immersion one, despite a reduced NA. In this manner, liquid-sensitive and sometimes than a water-immersion one, despite a reduced NA. In this manner, liquid-sensitive and porous artwork materials can be fully preserved from damage. The use of polarization- sometimes porous artwork materials can be fully preserved from damage. The use of po- resolved SHG imaging can be exploited to obtain quantitative information and to determine larization-resolved SHG imaging can be exploited to obtain quantitative information and the orientation of cellulose microfibrils [38], thus improving their visibility in cell walls. to determine the orientation of cellulose microfibrils [38], thus improving their visibility Nonlinear microscopy can be profitably combined with coherent anti-Stokes Raman scatter- ing (CARS) for a more comprehensive characterization of the chemical components, using 1 1 the C=C vibration at 1600 cm as a lignin marker and the C-O-C vibration at 1100 cm as a cellulose marker [39]. It has already been shown that the integration of data obtained by TPEF-SHG and CARS enables the ability to monitor changes in cellulose supramolecular structure during enzymatic hydrolysis [40]. In addition, the level of unwanted fluorescence due to the crosstalk effect within the SHG channel should be considered in SHG/TPEF analyses. We evaluated the contribution of crosstalk on poplar samples from time-resolved measurements, resulting in approxi- mately 5%. Although this is a small percentage of the overall signal, this effect can vary significantly across wood species and conditions and increase with excitation wavelength, as observed in [41]. Thus, a compromise between safety and crosstalk must be considered when choosing the excitation wavelength: shorter wavelengths, although potentially more dangerous, result in less fluorescence crosstalk in the SHG channel; longer wavelengths, although safer, cause higher crosstalk. The reported results suggest that some of the effects of wood degradation can be monitored at the molecular level by combined TPEF/SHG imaging. Both weathering [42] and biological attack by fungi [43] cause an enrichment of the relative crystalline content of wood (cellulose) at the expense of the amorphous fractions (hemicellulose and lignin), with a concomitant increase in the size of crystallites and a reduction in molecular weight of cellulose due to thermo-oxidative processes [44]. Therefore, it is reasonable to expect that Photonics 2022, 9, 170 9 of 11 this variation in the relative amounts of wood microcomponents could result in a change of ratios between TPEF and SHG signals and, specifically, an increase in the SHG signal from cellulose. The contributions of the individual components can be quantified by measuring the intensity of their respective NL signals (see Supplementary Materials). Monitoring the stability of signals over time would also allow for testing on the effectiveness of protective treatments on wooden artifacts. Since the effects of degradation can vary greatly by wood species, a comparative study of the most commonly used species for artwork production can be extremely useful. 5. Conclusions This work paves the way for a systematic application of combined TPEF/SHG imag- ing on many wood species, which is necessary for a thorough characterization of the microstructures based on the nonlinear optical properties of the components. Considering that compact, flexible multiphoton microscopy systems have been already developed and successfully used in the biomedical field [45,46], a specific system allowing for in situ measurements of large objects is, without a doubt, feasible and highly suitable for the application of NLO analysis on works of art. Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/photonics9030170/s1, Figure S1: NLO microscopy images of poplar (a–c), beech (d–f), chestnut (g–i) shavings cut in the tangential section along the stem length direction. Images were acquired under the same experimental conditions and with 840–850 nm excitation wavelength. The 8-bit grey-scale images are the individual channels (red = SHG, and green = TPEF) of the merged SHG/TPEF images (c,f,i), and show the contribution of SHG (a,d,g) and TPEF (b,e,h) signals as the intensity of light at each pixel in the dynamic range 0–255. Author Contributions: Conceptualization, R.F., R.C. and A.D.F.; methodology, R.C., R.F. and A.D.F.; software, M.M.; validation, R.C. and R.F.; formal analysis, S.M., A.D.F. and E.B.; investigation, A.D.F. and S.M.; resources, R.C.; data curation, A.D.F., S.M. and E.B.; writing—original draft preparation, A.D.F.; writing—review and editing, A.D.F., R.C., A.G., R.F. and S.M.; visualization, M.M. and M.A.; supervision, R.F., R.C. and A.G.; project administration, R.F. and R.C.; funding acquisition, R.F. and R.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Regione Toscana (POR FSE 2014–2020, “Giovanisì”, Interven- tion Program “CNR4C”, CUP B15J19001040004) and the European H2020 IPERION CH Project (Inte- grated Platform for the European Research Infrastructure ON Cultural Heritage (GA 654028, WP6). Conflicts of Interest: The authors declare no conflict of interest. References 1. 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Journal

Photonics – Multidisciplinary Digital Publishing Institute

Published: Mar 10, 2022

Keywords: second-harmonic generation; two-photon excited fluorescence; wood microstructure; cellulose; lignin; starch

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