Online monitoring of the hygromechanical properties of spruce tracheid cell walls at the nanoscale

Online monitoring of the hygromechanical properties of spruce tracheid cell walls at the nanoscale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Online monitoring of the hygromechanical properties of spruce tracheid cell walls at the nanoscale Raphaël Coste, Véronique Aguié-Béghin, Hugues Clivot, Dominique Derome, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8132624/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract AFM PeakForce QNM under controlled relative humidity (RH) was applied to continuously monitor the indentation modulus (IM) of Norway spruce ( Picea abies ) earlywood (EW) and latewood (LW) tracheid cell walls over three sorption/desorption (S/D) cycles. The IM of the different cell wall layers were close between early- and latewoods indicating small differences between their chemical compositions. AFM IR indicate a gradient of lignin and cellulose across the cell wall with an increase of lignin and a decrease of cellulose from the S2 to the S1 and finally to the CC. Earlywood and latewood cell walls display the same hygro–nanomechanical behavior during S/D cycle, i.e., the IM decrease with during sorption up to 85% and re–increase during desorption. Gaussian fits of the IM distribution were narrower for late wood than early wood and vary with the type of layer and with the relative humidity. The responses of the indentation moduli to RH of the cell wall layers in early- and latewood were fitted according to a three-parameter logistic function. Significant differences are observed for the S2 in both EW and LW indicating a higher slope in the response of indentation moduli to RH between 15 and 50% RH in desorption as compared to sorption. For both desorption and sorption, the comparison between EW vs LW reveals differences in CC and S1, with a higher slope in moduli response to RH in LW between 15 and 50% RH and the opposite between 50 to 85% RH. Spruce Cell wall Relative humidity Nanomechanical properties AFM–IR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Spruce is widely used for wood–frame construction (Olsson 2021 ), massive wood structures, furniture, pulpwood for paper and even as tone–wood for the manufacturing of musical instruments (Caudullo, Tinner and de Rigo 2016 ). However, as a cellulosic–based material, spruce is very hygroscopic and has the ability to absorb moisture which can lead to dimensional and physicochemical changes affecting therefore its potential uses (Celino et al. 2013 ; Derome et al. 2013 ; Hill et al. 2024 ; Nguyen et al. 2021 ; Roels and Tijskens 2022 ). As softwood, the main cells forming earlywood and latewood are the tracheids (Bertaud and Holmbom 2004 ). Earlywood tracheids have larger diameters (radial lumen diameter ~ 40 µm) and thinner cell walls (CW) (tangential CW thickness ~ 1–3 µm) compared to latewood ones (radial lumen diameter ~ 10 µm and tangential CW thickness ~ 3–9 µm) (Derome, Zillig and Carmeliet 2012 ). At the microscale, spruce tracheids display, like all plant fibers, a cell wall formed of concentric layers, known as the middle lamella (ML) and the primary wall (PW), forming together the compound middle lamella (CML) and the secondary cell wall (SCW) composed of the S1, S2 and S3 sub–layers (Fig. 1 ). The morphological and structural features of spruce tracheid cell walls have been investigated at micro/nanoscale in several studies using different imaging techniques, such as, TEM (Fromm et al. 2003 ), SEM (Fromm et al. 2003 ; Zimmermann et al. 2007 ), FESEM (Donaldson 2007 ; Zimmermann et al. 2007 ), synchroton X–ray CT (Derome et al. 2011 ; Patera et al. 2013 ) and AFM (Casdorff et al. 2018 ; Gusenbauer et al. 2020 ; Hanley and Gray 1994 ). The S1 and S3 sub–layers are very thin (~ 50–200 nm range) compared to the S2 sub–layer which represent around 75–85% of the total cell wall thickness (Plomion, Leprovost and Stokes 2001). Spruce wood consists of approximately 40–45% of cellulose, 20–35% of hemicelluloses and 20–30% of lignin (Bertaud and Holmbom 2004 ; Harris 1993 ; Scheller and Ulvskov 2010 ; Wang et al. 2018 ), exhibiting chemical and structural heterogeneities at the cell wall level. More recently, chemical analysis of earlywood and latewood of Scots pine ( Pinus sylvestris ) suggested few variations in the interactions between lignin and hemicellulose (Liszka et al. 2023 ). The spatial distribution of the polysaccharides (cellulose, hemicelluloses and also including pectin) and the lignin across the spruce tracheid cell walls was investigated by different authors using immunocytochemistry (Pilate et al. 2004 ; Donaldson and Knox 2012 ) or imaging techniques such as UV microscopy (Fergus et al. 1969 ), Raman microscopy (Agarwal 2006 ; Gierlinger, Keplinger and Harrington 2012 ; Hänninen, Kontturi and Vuorinen 2011 ) or, more recently, nano–infrared techniques (Gusenbauer et al. 2020 ; Kesari et al. 2021 ). The results revealed that the SCW is rich in cellulose and contains a fair amount of hemicellulose and lignin whereas the cell corner (CC) and the CML are rich in lignin, with low amount in hemicellulose and pectin and only a little of cellulose. Hemicelluloses of spruce cell walls mainly consist of galactoglucomannans (GGM) with a minor part of glucuronoarabinoxylans (GAX) in SCW whereas CC and CML contain xyloglucans(Scheller and Ulvskov 2010 ). Cellulose is mainly of crystalline nature and form cellulose microfibrils (CMF). These fibrils make an angle with the cell axis, the so–called MFA (microfibril angle), which is of a few degrees, so almost parallel to the tracheid axis, in the S2 sub–layer and in the 70–90° range, thus almost transversal, in the S1 and S3 sub–layers (Donaldson 2008 ). The relationship between the chemical composition and macromolecular architecture of the cell walls with their mechanical properties has been extensively studied in the literature (Arnould et al. 2022 ; Arnould et al. 2017 ; Bergander and Salmén 2002 ; Casdorff, Keplinger and Burgert 2017 ; Clair et al. 2003 ; Gindl et al. 2004 ; Wimmer and Lucas 1997 ), and even simulated atomistically (Zhang et al. 2022 ). The results indicated a higher indentation modulus in the SCW than in the CC, which is attributed to the high content of oriented cellulose in the secondary cell wall whereas the cell corner is mainly composed of lignin. In addition, the role of the cellulose MFA on the mechanical properties is now very well known, the lower the MFA, the higher the longitudinal mechanical properties (Burgert and Keplinger 2013 ). Due to its hygroscopic nature, wood is very sensitive to environmental conditions and specifically to the changes of the ambient RH. In the literature, the hygroscopic behavior of plant fibers (Celino et al. 2013 ; Pejic et al. 2008 ; Saikia 2010 ), the time required for equilibrium (Huttunen and Vinha 2023 ) and the effects of the RH on plant physicochemical properties (Placet, Cisse and Boubakar 2011 ; Stamboulis, Baillie and Peijs 2001 ; Symington et al. 2009 ) have already been discussed. It has been shown that water sorption in plant fibers involves significant dimensional and structural changes (Celino et al. 2013 ; Derome et al. 2013 ; Derome et al. 2012 ), even at the secondary cell wall level (Rafsanjani et al. 2014 ; Zhan, Lyu and Eder 2021 ). Recently, wood deformation of earlywood and latewood of Masson pine in response to moisture desorption has been studied with a multiscale approach (Gao et al. 2024 ). The mechanical properties of the cell wall have been investigated by means of nanoindentation and are dependent on the RH (Arzola-Villegas et al. 2025 ; Bertinetti et al. 2014 ; Guo et al. 2015 ; Wagner 2015; Youssefian, Jakes and Rahbar 2017 ). Nanoindentation presents however two limitations. First, nanoindentation is a destructive technique that irreversibly deforms the sample (plastic deformation) during the indentation cycle modifying the integrity of the macromolecular assemblies inside the cell walls. Therefore, the mechanical properties obtained can be biased due to ultrastructural changes in the sample, which prevents continuous monitoring of these properties in response to progressive changes in the RH. Second, the large radius of the indenter limits the experiments to the thickest layers of the wood cell walls, i.e., the S2 and the CC. Thus, a technique which offers a better spatial resolution should be preferred to distinguish all layers of the wood cell wall. For decades, atomic force microscopy (AFM) has been recognized to combine a high spatial resolution and the ability to probe the physicochemical properties of materials (Binnig, Quate and Gerber 1986 ). Several studies using AFM on plants have emerged (Arnould and Arinero 2015 ; Arnould et al. 2022 ; Casdorff, Keplinger and Burgert 2017 ; Clair et al. 2003 ; Coste et al. 2021 ; Muraille et al. 2017 ; Tetard, Passian and Thundat 2010 ), but these studies were all done at one specific RH. The effects of RH on the physicochemical properties of plant cell walls and bioinspired lignocellulosic films have been investigated at the nanoscale using AFM (Coste et al. 2020 ; Marcuello et al. 2020 ; Muraille et al. 2015 ), but not on wood. The main objective of this study is to give a better understanding of the effect of the RH on the nanomechanical properties of spruce earlywood and latewood cell walls. The chemical composition and the hygroscopic behavior of earlywood and latewood are determined by infrared spectroscopy (FTIR) and dynamic vapor sorption (DVS) respectively whereas chemical variations at the cell wall layer level are assessed using AFM infrared spectroscopy (AFM–IR) and the hygromechanical behavior is inspected with AFM by continuous monitoring of the nanomechanical properties in response to progressive changes in the RH. Materials and methods Sample preparation The specimen studied was taken from Norway spruce heartwood (Picea abies (L.) Karst.) and collected between 1 m and 4 m from the base of the trunk of tree felled in South Germany around 2002. A microtome (HM 355S Microm Microtech, France) with a steel knife was used to perform a first surfacing on one of the ends of an unembedded piece of spruce (25 x 6 x 6 mm 3 ). A diamond knife (Histo, Diatome, Switzerland) was used to smooth the surface. A final polishing was performed using a second diamond knife (Cryo 35°, Diatome, Switzerland) at low speed for better results. Finally, 2 µm thin sections were cut and directly fixed on an AFM disk using double side transparent adhesive pads (Brüker, Santa Barbara) (Fig. 2 ). The same samples were used for AFM nanomechanical and AFM infrared measurements. The AFM scans stayed clear from the edges of the cell walls to avoid the lumen (holes) and potential damage of the AFM tip. In consequence, the S3 layer was not analyzed in this study. FTIR measurements Spruce slices of earlywood and latewood (25 mm x 6 mm x 1 mm) were isolated under stereo microscope for mid infrared analysis using a Nicolet 6700 Thermo Electron FTIR spectrometer in attenuated total reflection (ATR) mode (RH = 40–50% and T = 21 ± 2°C). For both earlywood and latewood slices, 6 records were performed in the range 3800–800 cm –1 . Each record corresponds to an average of 32 scans with a spectral resolution of 4 cm –1 . The baseline of the spectra was corrected using OMNIC software and normalized by applying a correction factor 1000/(A 3800–800 ), where A 3800–800 is the area of the spectra between 3800–800 cm –1 . AFM–IR Nanoscale infrared analysis (Dazzi et al. 2012 ) and chemical maps were collected on a AFM–IR2 (Bruker, Santa Barbara, USA) using a pulsed infrared quantum cascade laser (QCL) to excite the samples. PR–EXTNIR–A probes (Bruker, USA), with nominal spring constant of 0.4 N/m, were used. AFM–IR spectra were collected over the 1900 to 900 cm –1 wavelength range of the QCL laser in ambient air RH = 40–50% and at T = 21 ± 2°C. As specific energies corresponding to the vibrational modes of the polymers in spruce cell walls are absorbed, heat is released to the lattice giving rise to local photothermal expansion. The pulsed nature of the excitation sets the cantilever, in contact with the surface, into oscillation (or ringing). By applying a Fast Fourier Transform (FFT) to the cantilever signal S(t) captured by the photodetector, the signal is represented in frequency space. Several peaks were observed in the FFT spectrum, peaks which correspond to the contact resonance modes of the cantilever. The amplitude and frequency of the first mode were monitored as a function of the wavenumber. The resulting amplitude vs wavenumber curve corresponds to a localized IR spectrum of the plant cell wall. The AFM–IR spectra were subjected to a Savitzky–Golay smoothing (polynomial order 3 side points 5), baselined and normalized using the correction factor 1000/(A 900–1900 ) where A 900–1900 corresponds to the area under the curves over the 1900–900 cm –1 wavenumber range using Origin software. Sorption isotherms Isotherms of the water vapor sorption/desorption (S/D) were acquired using a DVS (Hiden Isochema Ltd.). A cube of 5 mg of Norway spruce LW or EW was first placed in the microbalance stainless–steel basket (precision of 0.1 µg) before being transferred to a hermetic reactor connected to a thermo–regulated water bath monitored with temperature and RH sensors. RH was obtained with a flow mixture of wet and dry nitrogen. The S/D sequence was as follows: sorption (S) from RH = 5% to RH = 10% and then steps of 10% up to 90% RH followed by desorption (D) through the same points at a constant and regulated T = 20°C. The drying sequence to obtain the dry mass of the sample was performed after the 3rd cycle and was as following: 4 h at T = 40°C and then 8 h at T = 20°C, under a flow of dry nitrogen. The moisture content (MC) was calculated using Eq. ( 1 ) where m eq and m d correspond to the mass measured at equilibrium for a fixed RH and the mass of dried sample respectively. $$\:MC\left(\text{\%}\right)=\left(\frac{{m}_{eq}-{m}_{d}}{{m}_{d}}\right).100$$ 1 The sorption isotherms were fitted by the Park model using Eq. ( 2 ). The calculated Park parameters are gathered in Table 1 . The Park model is composed of three terms conceptually related to three sorption processes. The first term, with the parameters A L and β L , is the Langmuir sorption corresponding to the sorption until specific sites are saturated, in the absence of swelling; the second term, with the parameter k H is the Henry’s law of sorption, in which the concentration of water increases linearly with increasing RH; and the third term represented by a power function corresponds to the formation of water clusters. $$\:C=\frac{{A}_{L}.{\beta\:}_{L}.{a}_{w}}{1+{\beta\:}_{L}.{a}_{w}}+{k}_{H}.{a}_{w}+{K}_{a}.{a}_{w}^{n}$$ 2 In this equation, A L is the concentration of specific sorption sites, β L is the affinity constant of water for these sites, k H is the constant of Henry’s law, K a corresponds to the number of cluster sites and n is the mean size of the clusters. AFM PeakForce QNM AFM measurements were conducted on a Multimode 8 AFM (Bruker, USA) in Peak Force Quantitative Nanoscale Mechanical mode (PeakForce QNM). The vertical AFM probe oscillation frequency for PeakForce QNM measurements was 2 kHz. The indentation depth was around 5 − 10 nm. RTESPA–525 AFM tips (Bruker probes, USA) with a nominal spring constant of 200 N/m and a nominal resonance frequency of 525 kHz were selected to match the expected spruce indentation modulus (IM) previously reported to be in the order of a few GPa. Each cantilever was calibrated according to a well–established protocol prior to use (Coste et al. 2020 ; Coste et al. 2021 ; Muraille et al. 2017 ). The deflection sensitivity of the cantilevers was obtained by performing indentation ramps on a clean sapphire surface three times. The deflection sensitivity corresponding to the average of the three measurements was used. The tip radius was determined by scanning a sharp–edge titanium roughness sample (model RS–15M, Bruker Probes, USA) and later confirmed by measuring the IM of a highly oriented pyrolytic graphite (HOPG) sample. The Sader’s method was used to evaluate the spring constant (Sader, Chon and Mulvaney 1999 ). For processing, the IM was calculated by fitting the linear region of the retracted part of the force curves using the Derjaguin–Muller–Toporov (DMT) model (Derjaguin, Muller and P. 1975) that takes into account adhesion forces, which are not negligible in our case. The AFM tip radius was measured using a tip check sample from Bruker and lied between 30 and 40 nm. Due to their different thickness, the final IM values of the S2, S1 and CC presented in this study correspond to the averages and standard deviations calculated over 2000, 200 and 500 individual IM measurements respectively. IM measurements were performed under controlled environmental conditions using a hermetic chamber connected to a system (WETSYS) using a mix of water vapor and nitrogen to get the desired RH. The RHs used were successively 15%, 40%, 50%, 60%, 85% and then back to 15% through the same points. A well calibrated humidity sensor data logger (Tinytag TV–4500) was placed inside the chamber to verify the RH. A three–parameter logistic function (Eq. 3 ) was found to represent well the response of the indentation moduli to RH and was used to fit this relationship (3). $$\:\mathfrak{I}\left(GPa\right)=\frac{d}{(1+{e}^{b\bullet\:(logRH-loge})}$$ 3 In this function, the parameter d corresponds to the upper horizontal asymptotes of the s–shaped curve, the parameter e is the inflection point of the curve and b is the slope factor of the regression. The nls function (package stats ) in R software version 4.4.2 (RCoreTeam 2024) was used to determine the nonlinear least–squares estimates of the parameters, when fitting the function on the responses of the moduli to RH. For both EW and LW, fittings were performed on the responses measured for 5 different zones of S2, S1 and CC. The aim is to determine whether the parameters obtained can reveal any significant differences in the responses of the moduli to RH between EW vs LW and for desorption vs sorption for S2, S1 and CC. Comparisons were made using estimates of the effect size, calculated by computing the natural log of the response ratios (Hedges, Gurevitch and Curtis 1999 ) for the different parameters between EW vs LW and desorption vs sorption using the escalc function of the metafor package (Viechtbauer 2010 ) from R Software. Results and discussion Moisture content in sorption/desorption cycles The hygroscopic properties of earlywood and latewood were monitored over three sorption/desorption (S/D) cycles. The results are shown in Fig. 3 . All S/D cycles display a sigmoidal shape with a hysteresis between sorption and desorption isotherms typical for wood and lignocellulosic materials (Guo et al. 2015 ; Muraille et al. 2015 ). Both earlywood and latewood display very similar hygroscopic behavior. The 1st S/D cycle (light blue in Fig. 3 a,b) is different from the 2nd (red) and the 3rd (black) cycles which are nearly identical both in terms of MC as well as in the shape of the hysteresis, shown in Fig. 3 c,d. The 1st cycle generally corresponds to the moisture history of the sample which is wiped by the end of the 1st cycle. Thus, we will only discuss the 2nd and 3rd cycles in the remainder of this work. The maximum MC at 90% RH is about 22 ± 1% for LW and 21 ± 1% for EW in line with the literature (Derome et al. 2012 ; Guo et al. 2015 ). The results in Fig. 3 a and Fig. 3 b show the red curve (2nd cycle) and the black curve (3rd cycle) practically overlapping for both earlywood and latewood. However, the relative hysteresis expressed as function of the MC (Fig. 3 c,d) shows slight differences of maximum 0.025% between latewood and earlywood at the low relative humidity, i.e. at 5 and 10% RH. This result suggests that, at low MC range, the water molecules have more difficulty to be desorbed during the 2nd and 3rd desorption for latewood than for earlywood and may be explained by slight variations in the interactions between hemicellulose and lignin as recently shown in Scot pine (Liszka et al. 2023 ). . To highlight potential differences between latewood and earlywood, the sorption isotherms of each S/D cycle of earlywood and latewood were fitted using the Park model (Eq. 2 ). This model is known to fit well the sorption isotherms of plant fibers (Bessadok et al. 2007 ) as well as bioinspired lignocellulosic films (Muraille et al. 2015 ). All the parameters are shown in Table 1 . Table 1 Park parameters of spruce earlywood and latewood S/D cycle A L K H K a n EW 2nd 0.019 0.153 0.117 7.2 3rd 0.020 0.152 0.117 7.1 LW 2nd 0.019 0.158 0.139 8.1 3rd 0.020 0.156 0.130 7.4 The A L parameter, referring to the MC in the monolayer region (RH ~ 0–15%) and related to the number of water molecule sites on the surface, is identical (0.019) for the 2nd cycle and (0.020) for the 3rd cycle for both earlywood and latewood. This result suggests that the adsorption process of the water molecules in the RH ~ 0–15% region is identical between the 2nd and 3rd cycles for both earlywood and latewood. Second, the K H parameter (Henry’s constant) refers to the tendency of water to form multilayer and corresponds to the 15–60% RH region. According to Table 1 , K H values are practically identical between the 2nd and 3rd cycles of both earlywood (0.153 and 0.152) and latewood (0.158 and 0.156). This result suggests, nonetheless, that the tendency to form multilayer slightly decreases from the 2nd to the 3rd cycle. The higher K H values for latewood compared to earlywood suggest that water molecules have more accessibility and/or sorption sites, thus distributing the formation of water multilayers. These values are similar to those measured on agave fibers (Bessadok et al. 2008 ). The last parameters K a and n correspond to the phenomenon of aggregation by the formation of water molecules aggregates in microcavities and pores. K a corresponds to the aggregation equilibrium constant and n represents the number of water molecules in aggregates. As shown in Table 1 , earlywood displays identical K a and n values for both S/D cycles (K a = 0.117 and n = 7.2 for 2nd cycle) and K a = 0.117 and n = 7.1 for 3rd cycle) indicating that the water aggregation, which concurrently leads to an increase in porosity, is not affected by the successive S/D cycles. For latewood, these values are larger (K a = 0.139 and n = 8.1 for the 2nd cycle and K a = 0.130 and n = 7.4 for the 3rd cycle). This result suggests that latewood undergoes more water aggregation sites. We note that our values of K a and n for wood are much lower than those identified in plant fibers or bioinspired films (Bessadok et al. 2009 ; Muraille et al. 2015 ). As a next step, FTIR analysis was used to assess any chemical differences between earlywood and latewood. Chemical characterization by FTIR Few studies have been carried out to compare the chemical composition between earlywood and latewood by means of FTIR on spruce (Fredriksson, Pedersen and Thygesen 2018 ; Guo et al. 2015 ) and on pine (Gao et al. 2024 ). Fredriksson et al. ( 2018 ) noticed a higher lignin content in earlywood than in latewood explained from the FTIR results by a larger proportion of lignin–rich middle lamella and from the Raman results, a higher lignin content in earlywood S2 layer compared to latewood S2 layer (Fredriksson, Pedersen and Thygesen 2018 ). In our case, earlywood and latewood FTIR spectra look very similar with only a few differences of intensity for some bands. The bands at 3288 cm –1 and 3332 cm –1 (OH–O stretching of bonded hydroxyl groups) show higher absorbance intensities for earlywood than latewood. Such difference could be explained by a higher absorbance in the 3800–2800 cm –1 region (O–H stretching) in EW than LW for RH below 50% as shown by Gao et al. ( 2024 ). In their study, the absorbance of EW shows a large increase at 32% RH whereas for LW this increase only appears at 60.8% RH. Our FTIR analysis was performed in 40–50% RH where EW was more sensitive to water absorbance than LW which could explain the higher absorbance in the 3800–3000 cm –1 region in our case. The bands at 1228 cm –1 (OH plane deformation), 1104 cm –1 (ring asymmetric valence), 1050 cm –1 (C–O stretching from C3–O3H secondary alcohol) and 1023 cm –1 (C = O stretching) have a slightly higher absorbance intensity for latewood than earlywood, suggesting few variations in the chemical composition of EW and LW in line with previous studies (Fredriksson, Pedersen and Thygesen 2018 ; Via, Fasina and Pan 2011 ). Although present, these differences in intensity are not significant enough to differentiate the chemical composition of earlywood and latewood by FTIR. Differences could exist on a lower scale, i.e. between the different layers that compose the tracheid walls. In this case, the FTIR is limited due to its spatial resolution which tends to average the signal coming from the whole wood tissue. To this end, the AFM–IR technique is a candidate of choice as it combines the higher spatial resolution of AFM with the chemical characterization of IR spectroscopy. Table 2 FTIR band assignments in the 3800–800 cm –1 region for spruce wood Band position (cm –1 ) Attribution References 807 Contribution due to glucomannan (Marchessault 1962 ) 872 Contribution due to glucomannan (Marchessault 1962 ) 896 Anomere C–groups, C1–H deformation, ring valence vibration (Bari et al. 2020 ; Schwanninger et al. 2004 ) 990 C6–O6H stretching from cellulose C–O stretching or –CH = CH– out of plane bending from lignin (Horikawa et al. 2019 ) 1023 C = O stretching in cellulose, hemicellulose and lignin (Bari et al. 2020 ) 1050 C–O stretching from C3–O3H secondary alcohol (Maréchal and Chanzy 2000 ) 1104 asymmetric in–phase ring stretching, C–C and C–CO stretching ring asymmetric valence vibration secondary alcohol group, C–O stretching of cellulose (Maréchal and Chanzy 2000 ; Schwanninger et al. 2004 ) 1140 Aromatic C–H in plane deformation; typical for G units; whereby G condensed > G etherified (Schwanninger et al. 2004 ) 1155 asymmetric C–O–C stretching vibration of cellulose (Schwanninger et al. 2004 ) 1208 C1–O–C4’ or O–H in plane bending from cellulose and hemicellulose (Horikawa et al. 2019 ; Schwanninger et al. 2004 ) 1228 OH plane deformation C–C, C–O, C = O stretch (Schwanninger et al. 2004 ) 1263 G ring plus C = O stretch (Faix 1991 ) 1316 CH 2 wagging vibration (Schwanninger et al. 2004 ) 1338 OH plane deformation vibration (Schwanninger et al. 2004 ) 1368 C–H bending of cellulose (Stevanic and Salmén 2009 ) 1422 C–OH bending vibration of the C2–OH groups (Stevanic and Salmén 2009 ) 1452 asymmetric C–H bending from methoxyl group (Faix 1991 ) 1460 CH 2 symmetric bending on the xylose ring (Stevanic and Salmén 2009 ) 1508 C = C aromatic skeletal vibrations (Faix 1991 ) 1596 C = C aromatic skeletal vibrations (Faix 1991 ) 1645 H–O–H deformation vibration of absorbed water and C = O stretching in lignin (Bari et al. 2020 ) 1730 C = O stretching vibration in the COOH group of glucuronic acid units of xylan (Stevanic and Salmén 2009 ) 2852 C–H stretching (Schwanninger et al. 2004 ) 2896 CH 2 valence vibration (Schwanninger et al. 2004 ) 2916 CH 2 valence vibration (Schwanninger et al. 2004 ) 3288 O(6)H … O(3) stretching of bonded hydroxyl groups intermolecular in cellulose (Bari et al. 2020 ; Schwanninger et al. 2004 ) 3332 O(3)H … O(5) stretching of bonded hydroxyl groups intermolecular in cellulose (Bari et al. 2020 ; Schwanninger et al. 2004 ) Infrared spectra of the tracheids cell walls were obtained at nanoscale (Fig. 5 a,b). AFM-IR was used with a top-down illumination setup which generally needs metal-coated (gold or platinum) cantilevers to increase the IR signal in order to achieve a better sensitivity. Such setup can induced spectral changes making comparison with conventional FTIR no longer possible (Mathurin et al. 2022 ). Nevertheless FTIR is used here as reference for the location of the peaks in line with Bhagia et al. ( 2022 ) that used conventional FTIR on isolated cellulose, hemicellulose and lignin to specify which biomass contribute to the AFM-IR bands (Bhagia et al. 2022 ). In our case, most of the AFM–IR band locations (Fig. 5 b) match well with the FTIR ones (Fig. 4 ). The major differences concern the band intensities that can greatly differ between EW and LW. These differences in intensity could be explained by the chemical architecture complexity and the heterogeneity of the cell walls made of entanglements of different polymers; different limitations of the AFM-IR technique such as the use of metal-coated cantilevers or its sensitivity to the surface roughness of the samples which, in the case of unembedded wood sections, can reach several tenths of nanometers. To better highlight potential chemical composition differences between EW and LW, different ratios of the IR amplitudes between 1732 cm –1 (acetyl groups in xylan; non–conjugated carbonyls), 1512 cm –1 and 1600 cm –1 (C = C aromatic skeletal vibrations) and 1372 cm –1 (C–H bending of cellulose) were calculated (Table 3 ). The CC of both EW and LW display the highest values for the I 1732 /I 1372 ratio suggesting a higher amount of carbonyl groups and a lower amount of carbohydrates in this layer with a much larger value for EW (1.32) compared to LW (0.59). The same trend exists between the S1 layers of EW (0.94) and LW (0.51) whereas the values of the S2 layers are in the same order of magnitude. The I 1512 /I 1732 ratio gives information about the amount of functional group of lignin relative to the amount of functional group of hemicellulose. Overall, the values of the ratios are higher in all the layers of LW compared to EW. There is no clear trend between EW and LW with the highest value being for the S2 of EW followed by the CC and finally the S1 layer whereas for LW the highest value is for the CC very close to the S2 layer and finally the lowest value for the S1 layer. Regarding the ratio I 1512 /I 1600 which is an indicator of the condensation degree of lignin, the values are higher for all the cell wall layers of LW compared to EW suggesting lower concentration of the non-condensed structures in LW than in EW. Furthermore, the S2 layer displays the highest value for both EW (1.26) and LW (1.70). The S1 and CC show an opposite trend between EW and LW with a higher value in the S1 and a lower value in the CC for EW and the opposite for LW. Finally, the values obtained for the I 1512 /I 1372 ratios show the same trend for both EW and LW. More specifically the values go from the lowest value for the S2 layer, followed by the S1 layer and finally the highest values for the CC. These results indicate a gradient of lignin and cellulose across the cell wall with an increase of lignin and a decrease of cellulose from the S2 to the S1 and finally to the CC in line with the theory of the chemical distribution in plant cell walls. Table 3 IR amplitude ratios of specific bands obtained by AFM-IR for earlywood and latewood Earlywood Latewood Calculated ratios S2 S1 CC S2 S1 CC I 1732 /I 1372 0.52 0.94 1.32 0.43 0.51 0.59 I 1512 /I 1732 0.88 0.71 0.79 1.22 1.08 1.25 I 1512 /I 1600 1.26 1.26 1.01 1.70 1.47 1.59 I 1512 /I 1372 0.46 0.67 1.04 0.53 0.56 0.74 Nanomechanical analysis The indentation moduli (IM) of spruce EW and LW tracheid cell walls in the S2, S1 and CC were continuously monitored over three S/D cycles. As mentioned earlier, only the results for the 2nd and the 3rd S/D cycles will be discussed in this section. The AFM IM maps obtained at each of the RH during cycle 3 (sorption and desorption) for LW and EW are available in Supplementary information (Fig. S1 ). These images clearly indicated the softening of S2 at 85% RH. Although not the focus of this investigation, the LW images (Fig. S1 ) allowed to determine a 7–10% swelling from 15 to 85% RH and a shrinkage of 5–7% in reverse from 85 to 15% RH in the radial direction, values which agree with literature (Derome et al. 2011 ). It was not possible to do the same for EW due to the absence of the lumen in the AFM images. Overall, averaging the data for S2, S1 and CC, EW and LW present the same hygromechanical behavior for all the layers as shown in Fig. 6 . During the 2nd S/D cycle, the IM decreases during the sorption from 15% RH to 85% RH then re-increases during desorption back to 15% RH; similar hygromechanical behavior occurs during the 3rd S/D cycle. Figure 7 displays the distributions of the IM and their corresponding Gaussian fits in cell wall layers CC, S1 and S2 at the different RH and for the 2nd and 3rd S/D cycles. CC consistently displays a narrower distribution compared to the S2 and the S1 layers, highlighting that CC is chemically more homogeneous composed mostly of lignin and non–cellulosic polysaccharides compared to the SCW which possesses in addition cellulose leading to higher heterogeneity in the polymer assemblies. The distributions of S2 and especially of S1 layers are larger showing low and broad Gaussian fits. The S1 layer is thin (~ 50–150 nm) making it difficult to extract as much AFM force spectroscopy local measurements as for the S2 and CC for analysis. In addition, the S1 layer lies between the S2 layer and the CC, so the IM obtained for the S1 could be biased by data taken at the interfaces S2/S1 and S1/CC. We note that the Gaussian fits vary not only with the type of layer but also with relative humidity. The Gaussian fits become narrower with increasing relative humidity and are larger at the beginning and at the end of the cycles. This result can be explained by the different dependence on MC of wood polymers. For instance, the CC is mainly rich in lignin and hemicellulose. The Young’s modulus of these two wood polymers in dry state is around 2 GPa for lignin and around 3–7 GPa for hemicellulose (Bergander and Salmén 2002 ). As hemicellulose is more hydrophilic than lignin, it is more softened by water than lignin. At higher MC, the IM of hemicellulose approaches the one of lignin, leading to more homogeneous nanomechanical properties across the cell wall layer. For each module and cycle, the density values given on the y-axis combined with bar width of 0.2 correspond to a total bar area of 1 The nanomechanical results are in the same order of magnitude as found in previous studies and typical of plant cell walls with higher IM in the S2 layer which is attributed to the presence of semi–crystalline cellulose microfibrils playing the role of reinforcement in the longitudinal direction of the cell wall followed by the S1 and finally the CC (Arnould et al. 2017 ; Casdorff, Keplinger and Burgert 2017 ; Coste et al. 2020 ; Melelli et al. 2020 ; Muraille et al. 2017 ). More precisely the low microfibril angle (MFA) in the S2 is a key parameter in the final nanomechanical properties as previously reported at macroscale (Burgert et al. 2002 ) as well as micro/sub–microscale (Arzola-Villegas et al. 2025 ; Burgert and Keplinger 2013 ; Gindl et al. 2004 ; Jäger et al. 2011 ; Tze et al. 2007 ). The orientation of the cellulose microfibrils in the fiber axis (S2) and in the transverse fiber direction (S1 and S3) results from an evolutionary mechanism that allows the whole tree to act as an efficient structure against gravity and environmental (wind) stresses. More precisely, in the S2 of mature wood, the MFA lies between 5–20 ° whereas in the S1 and S3 layers it is almost perpendicular to the longitudinal direction (Donaldson 2008 ). The cell corner shows the lowest IM which can be explained by the lack of cellulose microfibrils and the high content of lignin for which the modulus has been estimated at around 0.6–2 GPa (Bergander and Salmén 2002 ). The nanomechanical properties of the S1 are higher than the ones of the CC due to the presence of cellulose microfibrils but remain lower than the ones in the S2 because of the greater MFA almost perpendicular to the cell axis which is here also the direction of the applied force (Donaldson 2008 ). All the layers of the cell wall present the same general hygromechanical behavior of softening and hardening. The mechanism involves first a decrease of the IM during sorption from RH = 15% to RH = 85%. This result has already been shown in one of our previous studies on hemp xylem and bast fibers (Coste et al. 2020 ). A similar decrease of properties with increasing RH has been observed by molecular dynamics and seems to correspond to the formation of a layer of water molecules along amorphous polymeric chains (Chen et al. 2018 ; Zhang et al. 2021 ). Then during desorption, the IM increases and, taking into account the standard deviation, it appears that the IM returns to its initial IM. Slight differences are visible between the EW and LW for both cycles 2 and 3. To better highlight these differences, the coefficients of variation (CV (%) = standard deviation/average) of the indentation moduli were calculated for each layer of the EW and LW considering both cycles 2 and 3 (Fig. 8 ). First, the medians (middle quartiles) of the boxes are generally much higher in earlywood with values comprised between 10–23% (except for the S2 layer at 85% RH) whereas the medians of the boxes in latewood are all below 12%. Second, the coefficients of variation depend on the type of wood (EW or LW) but also on the cell wall layer. More precisely, in earlywood, the medians are the highest in the S1 layer, followed by the cell corner and exhibit the lowest values in the S2 layer. In latewood, the highest medians appear in the S2 layer, followed by the S1 layer and finally the cell corner. Third, earlywood not only exhibits higher medians but also generally higher inter-quartile ranges (height of the box) than in latewood. This result indicates higher disparities of coefficients of variation in EW than in LW. Altogether, these results help to highlight that mechanical behavior of earlywood at nanoscale is more affected by RH than latewood which is more stable to RH. Indeed, in latewood the boxes of each layer are close to each other for all the RH percentages. In order to compare the evolution of IM rather than the average value at each RH, the responses of the indentation moduli to RH were fitted according to a three parameter logistic function (see Eq. ( 3 ) in the Materials and Methods AFM PeakForce QNM section) ( Figure S2 ) and the estimated parameters ( b , d and e ) between EW vs LW and for desorption vs sorption were compared to determine potential significant differences in responses measured in CC, S1 and S2 while taking the data from the second and third cycle. The highest relative differences and variabilities are observed for the parameter b (Fig. 9 ) compared to parameters d and e for which few relative differences are detected (data not shown). When comparing desorption vs sorption (Fig. 9 a), significant differences are observed for the S2 in both EW and LW for the parameter b , with b being found lower in desorption, which indicates a higher slope in the curve describing the response of moduli to RH between 15 and 50% RH in desorption. The comparison of this latter parameter between EW vs LW (Fig. 9 b) reveals significant differences in CC and S1 (and consistently for both desorption and sorption) with a relatively lower value of b , which reflects a higher slope in moduli response to RH in LW between 15 and 50% RH and the opposite between 50 to 85% RH. Such responses could be related to the dimensional changes induced by the variations in RH (Zhan, Lyu and Eder 2021 ). Few studies have focused on moisture-induced deformation at the cell wall level while comparing early and late woods. Nevertheless Zhan et al. ( 2021 ) have shown a higher shrinking ratio than swelling ratio of the cell walls of Chinese fir along drying and water sorption respectively; and these changes were higher for cell walls of latewood than earlywood. In this study where dimensional changes at tissue, cell and cell wall levels were addressed using environmental scanning microscopy, the higher variation of the cell walls of latewood could be related to the higher cell wall proportion in the cross section of latewood. Conclusion AFM PeakForce QNM under controlled relative humidity (RH) was applied to continuously monitor the nanomechanical properties of same spruce specimen over three S/D cycles. While FTIR showed no major difference between earlywood and latewood, AFM–IR, with its higher spatial resolution, captured small differences along the cell walls from CC to the S2 layer. Combining cycle 2 and 3 data, few variations were shown for latewood than earlywood during sorption/desorption isotherms and the dispersion of IM decreased with highest RH. DVS analysis with Park’s model showed that LW undergoes more water aggregation sites and this aggregation was not affected by successive 2nd and 3rd cycles. AFM-IR analysis indicated that there is indeed a gradient of lignin and cellulose across the cell wall with particularly an increase of lignin for all the layers of LW compared to EW suggesting lower concentration of the non-condensed structures in LW than in EW. Finally, a three-parameter logistic function allows us to represent accurately the relationship between IM variation to RH and to reveal that the highest relative differences for the S2 in both EW and LW when comparing desorption vs sorption and also for CC and S1 in both sorption and desorption. In future work, dimensional changes and evaluation of water content at each wall layer could be considered to extend the relationship between nanomechanical properties and water content of plant cell walls. Declarations Conflict of Interest The authors declare no competing interests. Acknowledgement: The authors gratefully acknowledge Edwige Audibert and Miguel Pernes for their valuable contributions to collecting macroscope images and DVS data that supported this research. Author Contributions: R.C.: investigation, methodology, formal analysis, data curation, conceptualization, and drafting the original manuscript. V.A.B.: formal analysis, conceptualization, and review and editing of the manuscript. H.C.: data curation, formal analysis, visualization, and review and editing of the manuscript. M.M.: conceptualization, review and editing. D.D: conceptualization, review and editing, funding acquisition, and project supervision. B.C.: conceptualization, formal analysis, review and editing of the manuscript, funding acquisition, and project supervision. Funding: This work was carried out within the framework of the INTOS2 project supported by the French National Research Agency (ANR-18-CE93-0007) and the Swiss National Science Foundation. Data availability : Data are provided upon request. Competing Interest The authors declare no competing interests. References Agarwal UP (2006) Raman imaging to investigate ultrastructure and composition of plant cell walls: distribution of lignin and cellulose in black spruce wood (Picea mariana). Planta 224 (5):1141-53. Arnould O, Arinero R (2015) Towards a better understanding of wood cell wall characterisation with contact resonance atomic force microscopy. Composites Part A: Applied Science and Manufacturing 74:69-76. Arnould O, Siniscalco D, Bourmaud A, et al. (2017) Better insight into the nano-mechanical properties of flax fibre cell walls. 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Supplementary Files CosteSupplementarymaterial.docx Supplementary Information Figure S1: AFM indentation moduli maps of latewood and earlywood obtained at each of the RH during cycle 3 (sorption and desorption) Figure S2: Fitting of the responses of the indentation moduli to RH according to a three parameter logistic function Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviews received at journal 19 Dec, 2025 Reviewers agreed at journal 11 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers invited by journal 10 Dec, 2025 Editor assigned by journal 10 Dec, 2025 Submission checks completed at journal 18 Nov, 2025 First submitted to journal 17 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8132624","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559539205,"identity":"6c418b96-d8c8-4594-ba2c-ea3bb682badc","order_by":0,"name":"Raphaël Coste","email":"","orcid":"","institution":"INRAE","correspondingAuthor":false,"prefix":"","firstName":"Raphaël","middleName":"","lastName":"Coste","suffix":""},{"id":559539206,"identity":"b15fd525-6a04-4d18-ab4b-e2bd0707538a","order_by":1,"name":"Véronique 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Bordeaux","correspondingAuthor":false,"prefix":"","firstName":"Michaël","middleName":"","lastName":"Molinari","suffix":""},{"id":559539210,"identity":"4ed7a8c3-e0b2-43a9-b811-f753dbdc6d12","order_by":5,"name":"Brigitte Chabbert","email":"data:image/png;base64,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","orcid":"","institution":"INRAE","correspondingAuthor":true,"prefix":"","firstName":"Brigitte","middleName":"","lastName":"Chabbert","suffix":""}],"badges":[],"createdAt":"2025-11-17 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16:18:02","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":182073,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/8e3a2e6552b0187e058e50cd.html"},{"id":98245597,"identity":"db574ea6-ecda-436e-9bad-f2999ae3dae9","added_by":"auto","created_at":"2025-12-15 16:18:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":181253,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Optical macroscope images of spruce tissue showing latewood and earlywood. (b) Scheme illustrating spruce cell wall layers arrangement\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/6f55c3ed85a6f8c45821797b.png"},{"id":98245767,"identity":"3552aa85-0538-4c9b-8763-143e8bcb4d55","added_by":"auto","created_at":"2025-12-15 16:18:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1242209,"visible":true,"origin":"","legend":"\u003cp\u003ePreparation of spruce samples for AFM characterization\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/f0ba14e245416202fbc20ddf.png"},{"id":98245588,"identity":"6cb0f46f-d899-45f9-af03-9d3edcacb89e","added_by":"auto","created_at":"2025-12-15 16:18:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":269346,"visible":true,"origin":"","legend":"\u003cp\u003eSorption isotherms of spruce LW (a) and EW (b) over three S/D cycles in the 5−90 % RH range. Relative hysteresis as function of the MC for LW (c) and EW (d); (MC\u003csub\u003ed\u003c/sub\u003e: MC during desorption; MC\u003csub\u003es\u003c/sub\u003e: MC during sorption)\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/d613c274f25e4b442e3ca75e.png"},{"id":98245526,"identity":"98210fd2-5330-4a52-b01b-915aeb2a376d","added_by":"auto","created_at":"2025-12-15 16:18:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":134059,"visible":true,"origin":"","legend":"\u003cp\u003eInfrared analysis of spruce wood (a) FTIR spectra of spruce EW (blue) and LW (red) in the 3800–800 cm\u003csup\u003e–1\u003c/sup\u003e range. (b) Zoom of the spectra in the 1800–800 cm\u003csup\u003e-1\u003c/sup\u003e range\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/04e8a7135e3486336dbf418e.png"},{"id":98245698,"identity":"0d603ca1-3e0b-476c-ae99-4d8a9b0a9c5b","added_by":"auto","created_at":"2025-12-15 16:18:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":332614,"visible":true,"origin":"","legend":"\u003cp\u003eAFM infrared analysis of spruce tracheids. (a) AFM topography images of EW (left) and LW (right). (b) Averaged AFM–IR spectra of the CC, S1 and S2 layers of spruce EW (top) and LW (bottom). Each spectrum corresponds to the average of the spectra indicated on the topography image with markers of corresponding color\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/2eae3905ccb6dd9d8666cb4d.png"},{"id":98434687,"identity":"c3b823db-63cb-4da5-93f5-5cb9b2ab8c2c","added_by":"auto","created_at":"2025-12-17 16:52:30","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":191101,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of IM in the S2 layer (blue curves), S1 (red curves) and CC (green curves) for EW (light colors) and LW (dark colors) during the 2\u003csup\u003end\u003c/sup\u003e and 3\u003csup\u003erd\u003c/sup\u003e S/D cycles separated on the figure by the dashed black line\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/6ed4966cbcb2b9da7e926658.jpeg"},{"id":98245584,"identity":"488f34f6-6c57-4f25-a330-9202ce75429b","added_by":"auto","created_at":"2025-12-15 16:18:08","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":968308,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of the IM and their corresponding Gaussian fits for the 2\u003csup\u003end\u003c/sup\u003e (dark colors) and the 3\u003csup\u003erd\u003c/sup\u003e (light colors) S/D cycles in the CC (green), S1 layer (red) and S2 layer (blue) of earlywood (left) and latewood (right).\u003c/p\u003e\n\u003cp\u003eFor each module and cycle, the density values given on the y-axis combined with bar width of 0.2 correspond to a total bar area of 1\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/df96d16d939d4266482afa56.jpeg"},{"id":98245675,"identity":"aa2fd399-b068-403c-b453-0fbc55e86999","added_by":"auto","created_at":"2025-12-15 16:18:17","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":194989,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot displaying the coefficients of variation (CV) of the IM in the S2, S1 and CC as a function of the RH. For better visibility, the green and blue boxes are voluntarily off-axis relative to the X-axis to avoid overlays. Each box was built with the CV values calculated during both sorption and desorption and during the 2nd and 3rd cycles at a specific RH percentage for the EW and the LW. Therefore, the boxes at 40 % RH, 50 % RH and 60 % RH were obtained with 4 CV values. However, as the 15 % RH corresponds to the end of the 2nd S/D cycle and to the beginning of the 3rd S/D cycle, the boxes at 15 % RH were built with 3 CV values. Also, as the 85 % RH corresponds to the return point of the S/D cycle, the boxes at 85 %RH were built with 2 CV values\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/f7194528a694b122b15e15d8.png"},{"id":98245511,"identity":"609111c6-1591-4666-8516-8ccd96da625f","added_by":"auto","created_at":"2025-12-15 16:18:00","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":698580,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Effects size of desorption relative to sorption on parameter \u003cem\u003eb\u003c/em\u003e from the equation (3) describing the moduli responses to RH for EW and LW in the CC, S1 and S2 layers (2\u003csup\u003end\u003c/sup\u003e and 3\u003csup\u003erd\u003c/sup\u003e S/D cycles) (b) Effects size of LW relative to EW on parameter \u003cem\u003eb\u003c/em\u003e from the equation (3) describing the moduli responses to RH during desorption and sorption in the CC, S1 and S2 layers (2\u003csup\u003end\u003c/sup\u003e and 3\u003csup\u003erd\u003c/sup\u003e S/D cycles)\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/0747886bb84f7acc7589b626.png"},{"id":98445110,"identity":"eb902d91-bb58-4624-8e4b-8dceaf738999","added_by":"auto","created_at":"2025-12-17 17:18:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5079200,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/72351873-15bc-4cc1-905a-2a7626039d2c.pdf"},{"id":98245355,"identity":"a125723a-2ad8-43e0-a3f1-7ab6fc22bfe5","added_by":"auto","created_at":"2025-12-15 16:17:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2245693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S1: \u003c/strong\u003eAFM indentation moduli maps of latewood and earlywood obtained at each of the RH during cycle 3 (sorption and desorption)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S2: \u003c/strong\u003eFitting of\u003cstrong\u003e \u003c/strong\u003ethe responses of the indentation moduli to RH according to a three parameter logistic function\u003c/p\u003e","description":"","filename":"CosteSupplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8132624/v1/573a506095a9ecd3cfecf0c6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Online monitoring of the hygromechanical properties of spruce tracheid cell walls at the nanoscale","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpruce is widely used for wood\u0026ndash;frame construction (Olsson \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), massive wood structures, furniture, pulpwood for paper and even as tone\u0026ndash;wood for the manufacturing of musical instruments (Caudullo, Tinner and de Rigo \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, as a cellulosic\u0026ndash;based material, spruce is very hygroscopic and has the ability to absorb moisture which can lead to dimensional and physicochemical changes affecting therefore its potential uses (Celino et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Derome et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hill et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nguyen et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Roels and Tijskens \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As softwood, the main cells forming earlywood and latewood are the tracheids (Bertaud and Holmbom \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Earlywood tracheids have larger diameters (radial lumen diameter\u0026thinsp;~\u0026thinsp;40 \u0026micro;m) and thinner cell walls (CW) (tangential CW thickness\u0026thinsp;~\u0026thinsp;1\u0026ndash;3 \u0026micro;m) compared to latewood ones (radial lumen diameter\u0026thinsp;~\u0026thinsp;10 \u0026micro;m and tangential CW thickness\u0026thinsp;~\u0026thinsp;3\u0026ndash;9 \u0026micro;m) (Derome, Zillig and Carmeliet \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). At the microscale, spruce tracheids display, like all plant fibers, a cell wall formed of concentric layers, known as the middle lamella (ML) and the primary wall (PW), forming together the compound middle lamella (CML) and the secondary cell wall (SCW) composed of the S1, S2 and S3 sub\u0026ndash;layers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe morphological and structural features of spruce tracheid cell walls have been investigated at micro/nanoscale in several studies using different imaging techniques, such as, TEM (Fromm et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), SEM (Fromm et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Zimmermann et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), FESEM (Donaldson \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Zimmermann et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), synchroton X\u0026ndash;ray CT (Derome et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Patera et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and AFM (Casdorff et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gusenbauer et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hanley and Gray \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The S1 and S3 sub\u0026ndash;layers are very thin (~\u0026thinsp;50\u0026ndash;200 nm range) compared to the S2 sub\u0026ndash;layer which represent around 75\u0026ndash;85% of the total cell wall thickness (Plomion, Leprovost and Stokes 2001). Spruce wood consists of approximately 40\u0026ndash;45% of cellulose, 20\u0026ndash;35% of hemicelluloses and 20\u0026ndash;30% of lignin (Bertaud and Holmbom \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Harris \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Scheller and Ulvskov \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), exhibiting chemical and structural heterogeneities at the cell wall level. More recently, chemical analysis of earlywood and latewood of Scots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e) suggested few variations in the interactions between lignin and hemicellulose (Liszka et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The spatial distribution of the polysaccharides (cellulose, hemicelluloses and also including pectin) and the lignin across the spruce tracheid cell walls was investigated by different authors using immunocytochemistry (Pilate et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Donaldson and Knox \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) or imaging techniques such as UV microscopy (Fergus et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1969\u003c/span\u003e), Raman microscopy (Agarwal \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gierlinger, Keplinger and Harrington \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; H\u0026auml;nninen, Kontturi and Vuorinen \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) or, more recently, nano\u0026ndash;infrared techniques (Gusenbauer et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kesari et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The results revealed that the SCW is rich in cellulose and contains a fair amount of hemicellulose and lignin whereas the cell corner (CC) and the CML are rich in lignin, with low amount in hemicellulose and pectin and only a little of cellulose. Hemicelluloses of spruce cell walls mainly consist of galactoglucomannans (GGM) with a minor part of glucuronoarabinoxylans (GAX) in SCW whereas CC and CML contain xyloglucans(Scheller and Ulvskov \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Cellulose is mainly of crystalline nature and form cellulose microfibrils (CMF). These fibrils make an angle with the cell axis, the so\u0026ndash;called MFA (microfibril angle), which is of a few degrees, so almost parallel to the tracheid axis, in the S2 sub\u0026ndash;layer and in the 70\u0026ndash;90\u0026deg; range, thus almost transversal, in the S1 and S3 sub\u0026ndash;layers (Donaldson \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relationship between the chemical composition and macromolecular architecture of the cell walls with their mechanical properties has been extensively studied in the literature (Arnould et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Arnould et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bergander and Salm\u0026eacute;n \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Casdorff, Keplinger and Burgert \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Clair et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Gindl et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wimmer and Lucas \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), and even simulated atomistically (Zhang et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The results indicated a higher indentation modulus in the SCW than in the CC, which is attributed to the high content of oriented cellulose in the secondary cell wall whereas the cell corner is mainly composed of lignin. In addition, the role of the cellulose MFA on the mechanical properties is now very well known, the lower the MFA, the higher the longitudinal mechanical properties (Burgert and Keplinger \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDue to its hygroscopic nature, wood is very sensitive to environmental conditions and specifically to the changes of the ambient RH. In the literature, the hygroscopic behavior of plant fibers (Celino et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Pejic et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Saikia \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), the time required for equilibrium (Huttunen and Vinha \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and the effects of the RH on plant physicochemical properties (Placet, Cisse and Boubakar \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Stamboulis, Baillie and Peijs \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Symington et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) have already been discussed. It has been shown that water sorption in plant fibers involves significant dimensional and structural changes (Celino et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Derome et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Derome et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), even at the secondary cell wall level (Rafsanjani et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhan, Lyu and Eder \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Recently, wood deformation of earlywood and latewood of Masson pine in response to moisture desorption has been studied with a multiscale approach (Gao et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The mechanical properties of the cell wall have been investigated by means of nanoindentation and are dependent on the RH (Arzola-Villegas et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Bertinetti et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Guo et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wagner 2015; Youssefian, Jakes and Rahbar \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Nanoindentation presents however two limitations. First, nanoindentation is a destructive technique that irreversibly deforms the sample (plastic deformation) during the indentation cycle modifying the integrity of the macromolecular assemblies inside the cell walls. Therefore, the mechanical properties obtained can be biased due to ultrastructural changes in the sample, which prevents continuous monitoring of these properties in response to progressive changes in the RH. Second, the large radius of the indenter limits the experiments to the thickest layers of the wood cell walls, i.e., the S2 and the CC. Thus, a technique which offers a better spatial resolution should be preferred to distinguish all layers of the wood cell wall. For decades, atomic force microscopy (AFM) has been recognized to combine a high spatial resolution and the ability to probe the physicochemical properties of materials (Binnig, Quate and Gerber \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Several studies using AFM on plants have emerged (Arnould and Arinero \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Arnould et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Casdorff, Keplinger and Burgert \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Clair et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Coste et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tetard, Passian and Thundat \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), but these studies were all done at one specific RH. The effects of RH on the physicochemical properties of plant cell walls and bioinspired lignocellulosic films have been investigated at the nanoscale using AFM (Coste et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Marcuello et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), but not on wood.\u003c/p\u003e \u003cp\u003eThe main objective of this study is to give a better understanding of the effect of the RH on the nanomechanical properties of spruce earlywood and latewood cell walls. The chemical composition and the hygroscopic behavior of earlywood and latewood are determined by infrared spectroscopy (FTIR) and dynamic vapor sorption (DVS) respectively whereas chemical variations at the cell wall layer level are assessed using AFM infrared spectroscopy (AFM\u0026ndash;IR) and the hygromechanical behavior is inspected with AFM by continuous monitoring of the nanomechanical properties in response to progressive changes in the RH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample preparation\u003c/h2\u003e \u003cp\u003eThe specimen studied was taken from Norway spruce heartwood (Picea abies (L.) Karst.) and collected between 1 m and 4 m from the base of the trunk of tree felled in South Germany around 2002. A microtome (HM 355S Microm Microtech, France) with a steel knife was used to perform a first surfacing on one of the ends of an unembedded piece of spruce (25 x 6 x 6 mm\u003csup\u003e3\u003c/sup\u003e). A diamond knife (Histo, Diatome, Switzerland) was used to smooth the surface. A final polishing was performed using a second diamond knife (Cryo 35\u0026deg;, Diatome, Switzerland) at low speed for better results. Finally, 2 \u0026micro;m thin sections were cut and directly fixed on an AFM disk using double side transparent adhesive pads (Br\u0026uuml;ker, Santa Barbara) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The same samples were used for AFM nanomechanical and AFM infrared measurements. The AFM scans stayed clear from the edges of the cell walls to avoid the lumen (holes) and potential damage of the AFM tip. In consequence, the S3 layer was not analyzed in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFTIR measurements\u003c/h3\u003e\n\u003cp\u003eSpruce slices of earlywood and latewood (25 mm x 6 mm x 1 mm) were isolated under stereo microscope for mid infrared analysis using a Nicolet 6700 Thermo Electron FTIR spectrometer in attenuated total reflection (ATR) mode (RH\u0026thinsp;=\u0026thinsp;40\u0026ndash;50% and T\u0026thinsp;=\u0026thinsp;21\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C). For both earlywood and latewood slices, 6 records were performed in the range 3800\u0026ndash;800 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e. Each record corresponds to an average of 32 scans with a spectral resolution of 4 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e. The baseline of the spectra was corrected using OMNIC software and normalized by applying a correction factor 1000/(A\u003csub\u003e3800\u0026ndash;800\u003c/sub\u003e), where A\u003csub\u003e3800\u0026ndash;800\u003c/sub\u003e is the area of the spectra between 3800\u0026ndash;800 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eAFM–IR\u003c/h3\u003e\n\u003cp\u003eNanoscale infrared analysis (Dazzi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and chemical maps were collected on a AFM\u0026ndash;IR2 (Bruker, Santa Barbara, USA) using a pulsed infrared quantum cascade laser (QCL) to excite the samples. PR\u0026ndash;EXTNIR\u0026ndash;A probes (Bruker, USA), with nominal spring constant of 0.4 N/m, were used. AFM\u0026ndash;IR spectra were collected over the 1900 to 900 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e wavelength range of the QCL laser in ambient air RH\u0026thinsp;=\u0026thinsp;40\u0026ndash;50% and at T\u0026thinsp;=\u0026thinsp;21\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C. As specific energies corresponding to the vibrational modes of the polymers in spruce cell walls are absorbed, heat is released to the lattice giving rise to local photothermal expansion. The pulsed nature of the excitation sets the cantilever, in contact with the surface, into oscillation (or ringing). By applying a Fast Fourier Transform (FFT) to the cantilever signal S(t) captured by the photodetector, the signal is represented in frequency space. Several peaks were observed in the FFT spectrum, peaks which correspond to the contact resonance modes of the cantilever. The amplitude and frequency of the first mode were monitored as a function of the wavenumber. The resulting amplitude \u003cem\u003evs\u003c/em\u003e wavenumber curve corresponds to a localized IR spectrum of the plant cell wall. The AFM\u0026ndash;IR spectra were subjected to a Savitzky\u0026ndash;Golay smoothing (polynomial order 3 side points 5), baselined and normalized using the correction factor 1000/(A\u003csub\u003e900\u0026ndash;1900\u003c/sub\u003e) where A\u003csub\u003e900\u0026ndash;1900\u003c/sub\u003e corresponds to the area under the curves over the 1900\u0026ndash;900 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e wavenumber range using Origin software.\u003c/p\u003e\n\u003ch3\u003eSorption isotherms\u003c/h3\u003e\n\u003cp\u003eIsotherms of the water vapor sorption/desorption (S/D) were acquired using a DVS (Hiden Isochema Ltd.). A cube of 5 mg of Norway spruce LW or EW was first placed in the microbalance stainless\u0026ndash;steel basket (precision of 0.1 \u0026micro;g) before being transferred to a hermetic reactor connected to a thermo\u0026ndash;regulated water bath monitored with temperature and RH sensors. RH was obtained with a flow mixture of wet and dry nitrogen. The S/D sequence was as follows: sorption (S) from RH\u0026thinsp;=\u0026thinsp;5% to RH\u0026thinsp;=\u0026thinsp;10% and then steps of 10% up to 90% RH followed by desorption (D) through the same points at a constant and regulated T\u0026thinsp;=\u0026thinsp;20\u0026deg;C. The drying sequence to obtain the dry mass of the sample was performed after the 3rd cycle and was as following: 4 h at T\u0026thinsp;=\u0026thinsp;40\u0026deg;C and then 8 h at T\u0026thinsp;=\u0026thinsp;20\u0026deg;C, under a flow of dry nitrogen. The moisture content (MC) was calculated using Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) where m\u003csub\u003eeq\u003c/sub\u003e and m\u003csub\u003ed\u003c/sub\u003e correspond to the mass measured at equilibrium for a fixed RH and the mass of dried sample respectively.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:MC\\left(\\text{\\%}\\right)=\\left(\\frac{{m}_{eq}-{m}_{d}}{{m}_{d}}\\right).100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe sorption isotherms were fitted by the Park model using Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The calculated Park parameters are gathered in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The Park model is composed of three terms conceptually related to three sorption processes. The first term, with the parameters A\u003csub\u003eL\u003c/sub\u003e and β\u003csub\u003eL\u003c/sub\u003e, is the Langmuir sorption corresponding to the sorption until specific sites are saturated, in the absence of swelling; the second term, with the parameter k\u003csub\u003eH\u003c/sub\u003e is the Henry\u0026rsquo;s law of sorption, in which the concentration of water increases linearly with increasing RH; and the third term represented by a power function corresponds to the formation of water clusters.\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:C=\\frac{{A}_{L}.{\\beta\\:}_{L}.{a}_{w}}{1+{\\beta\\:}_{L}.{a}_{w}}+{k}_{H}.{a}_{w}+{K}_{a}.{a}_{w}^{n}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this equation, A\u003csub\u003eL\u003c/sub\u003e is the concentration of specific sorption sites, β\u003csub\u003eL\u003c/sub\u003e is the affinity constant of water for these sites, k\u003csub\u003eH\u003c/sub\u003e is the constant of Henry\u0026rsquo;s law, K\u003csub\u003ea\u003c/sub\u003e corresponds to the number of cluster sites and n is the mean size of the clusters.\u003c/p\u003e\n\u003ch3\u003eAFM PeakForce QNM\u003c/h3\u003e\n\u003cp\u003eAFM measurements were conducted on a Multimode 8 AFM (Bruker, USA) in Peak Force Quantitative Nanoscale Mechanical mode (PeakForce QNM). The vertical AFM probe oscillation frequency for PeakForce QNM measurements was 2 kHz. The indentation depth was around 5\u0026thinsp;\u0026minus;\u0026thinsp;10 nm. RTESPA\u0026ndash;525 AFM tips (Bruker probes, USA) with a nominal spring constant of 200 N/m and a nominal resonance frequency of 525 kHz were selected to match the expected spruce indentation modulus (IM) previously reported to be in the order of a few GPa. Each cantilever was calibrated according to a well\u0026ndash;established protocol prior to use (Coste et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Coste et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The deflection sensitivity of the cantilevers was obtained by performing indentation ramps on a clean sapphire surface three times. The deflection sensitivity corresponding to the average of the three measurements was used. The tip radius was determined by scanning a sharp\u0026ndash;edge titanium roughness sample (model RS\u0026ndash;15M, Bruker Probes, USA) and later confirmed by measuring the IM of a highly oriented pyrolytic graphite (HOPG) sample. The Sader\u0026rsquo;s method was used to evaluate the spring constant (Sader, Chon and Mulvaney \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). For processing, the IM was calculated by fitting the linear region of the retracted part of the force curves using the Derjaguin\u0026ndash;Muller\u0026ndash;Toporov (DMT) model (Derjaguin, Muller and P. 1975) that takes into account adhesion forces, which are not negligible in our case. The AFM tip radius was measured using a tip check sample from Bruker and lied between 30 and 40 nm. Due to their different thickness, the final IM values of the S2, S1 and CC presented in this study correspond to the averages and standard deviations calculated over 2000, 200 and 500 individual IM measurements respectively. IM measurements were performed under controlled environmental conditions using a hermetic chamber connected to a system (WETSYS) using a mix of water vapor and nitrogen to get the desired RH. The RHs used were successively 15%, 40%, 50%, 60%, 85% and then back to 15% through the same points. A well calibrated humidity sensor data logger (Tinytag TV\u0026ndash;4500) was placed inside the chamber to verify the RH.\u003c/p\u003e \u003cp\u003eA three\u0026ndash;parameter logistic function (Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) was found to represent well the response of the indentation moduli to RH and was used to fit this relationship (3).\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\mathfrak{I}\\left(GPa\\right)=\\frac{d}{(1+{e}^{b\\bullet\\:(logRH-loge})}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this function, the parameter \u003cem\u003ed\u003c/em\u003e corresponds to the upper horizontal asymptotes of the s\u0026ndash;shaped curve, the parameter \u003cem\u003ee\u003c/em\u003e is the inflection point of the curve and \u003cem\u003eb\u003c/em\u003e is the slope factor of the regression. The \u003cem\u003enls\u003c/em\u003e function (package \u003cem\u003estats\u003c/em\u003e) in R software version 4.4.2 (RCoreTeam 2024) was used to determine the nonlinear least\u0026ndash;squares estimates of the parameters, when fitting the function on the responses of the moduli to RH. For both EW and LW, fittings were performed on the responses measured for 5 different zones of S2, S1 and CC. The aim is to determine whether the parameters obtained can reveal any significant differences in the responses of the moduli to RH between EW \u003cem\u003evs\u003c/em\u003e LW and for desorption \u003cem\u003evs\u003c/em\u003e sorption for S2, S1 and CC. Comparisons were made using estimates of the effect size, calculated by computing the natural log of the response ratios (Hedges, Gurevitch and Curtis \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) for the different parameters between EW \u003cem\u003evs\u003c/em\u003e LW and desorption \u003cem\u003evs\u003c/em\u003e sorption using the \u003cem\u003eescalc\u003c/em\u003e function of the \u003cem\u003emetafor\u003c/em\u003e package (Viechtbauer \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) from R Software.\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMoisture content in sorption/desorption cycles\u003c/h2\u003e \u003cp\u003eThe hygroscopic properties of earlywood and latewood were monitored over three sorption/desorption (S/D) cycles. The results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. All S/D cycles display a sigmoidal shape with a hysteresis between sorption and desorption isotherms typical for wood and lignocellulosic materials (Guo et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Both earlywood and latewood display very similar hygroscopic behavior. The 1st S/D cycle (light blue in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea,b) is different from the 2nd (red) and the 3rd (black) cycles which are nearly identical both in terms of MC as well as in the shape of the hysteresis, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec,d. The 1st cycle generally corresponds to the moisture history of the sample which is wiped by the end of the 1st cycle. Thus, we will only discuss the 2nd and 3rd cycles in the remainder of this work. The maximum MC at 90% RH is about 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1% for LW and 21\u0026thinsp;\u0026plusmn;\u0026thinsp;1% for EW in line with the literature (Derome et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Guo et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The results in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb show the red curve (2nd cycle) and the black curve (3rd cycle) practically overlapping for both earlywood and latewood. However, the relative hysteresis expressed as function of the MC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec,d) shows slight differences of maximum 0.025% between latewood and earlywood at the low relative humidity, i.e. at 5 and 10% RH. This result suggests that, at low MC range, the water molecules have more difficulty to be desorbed during the 2nd and 3rd desorption for latewood than for earlywood and may be explained by slight variations in the interactions between hemicellulose and lignin as recently shown in Scot pine (Liszka et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo highlight potential differences between latewood and earlywood, the sorption isotherms of each S/D cycle of earlywood and latewood were fitted using the Park model (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This model is known to fit well the sorption isotherms of plant fibers (Bessadok et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) as well as bioinspired lignocellulosic films (Muraille et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). All the parameters are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePark parameters of spruce earlywood and latewood\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS/D cycle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK\u003csub\u003eH\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eK\u003csub\u003ea\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2nd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3rd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2nd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3rd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe A\u003csub\u003eL\u003c/sub\u003e parameter, referring to the MC in the monolayer region (RH\u0026thinsp;~\u0026thinsp;0\u0026ndash;15%) and related to the number of water molecule sites on the surface, is identical (0.019) for the 2nd cycle and (0.020) for the 3rd cycle for both earlywood and latewood. This result suggests that the adsorption process of the water molecules in the RH\u0026thinsp;~\u0026thinsp;0\u0026ndash;15% region is identical between the 2nd and 3rd cycles for both earlywood and latewood. Second, the K\u003csub\u003eH\u003c/sub\u003e parameter (Henry\u0026rsquo;s constant) refers to the tendency of water to form multilayer and corresponds to the 15\u0026ndash;60% RH region. According to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, K\u003csub\u003eH\u003c/sub\u003e values are practically identical between the 2nd and 3rd cycles of both earlywood (0.153 and 0.152) and latewood (0.158 and 0.156). This result suggests, nonetheless, that the tendency to form multilayer slightly decreases from the 2nd to the 3rd cycle. The higher K\u003csub\u003eH\u003c/sub\u003e values for latewood compared to earlywood suggest that water molecules have more accessibility and/or sorption sites, thus distributing the formation of water multilayers. These values are similar to those measured on agave fibers (Bessadok et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The last parameters K\u003csub\u003ea\u003c/sub\u003e and n correspond to the phenomenon of aggregation by the formation of water molecules aggregates in microcavities and pores. K\u003csub\u003ea\u003c/sub\u003e corresponds to the aggregation equilibrium constant and n represents the number of water molecules in aggregates. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, earlywood displays identical K\u003csub\u003ea\u003c/sub\u003e and n values for both S/D cycles (K\u003csub\u003ea\u003c/sub\u003e = 0.117 and n\u0026thinsp;=\u0026thinsp;7.2 for 2nd cycle) and K\u003csub\u003ea\u003c/sub\u003e = 0.117 and n\u0026thinsp;=\u0026thinsp;7.1 for 3rd cycle) indicating that the water aggregation, which concurrently leads to an increase in porosity, is not affected by the successive S/D cycles. For latewood, these values are larger (K\u003csub\u003ea\u003c/sub\u003e = 0.139 and n\u0026thinsp;=\u0026thinsp;8.1 for the 2nd cycle and K\u003csub\u003ea\u003c/sub\u003e = 0.130 and n\u0026thinsp;=\u0026thinsp;7.4 for the 3rd cycle). This result suggests that latewood undergoes more water aggregation sites. We note that our values of K\u003csub\u003ea\u003c/sub\u003e and n for wood are much lower than those identified in plant fibers or bioinspired films (Bessadok et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As a next step, FTIR analysis was used to assess any chemical differences between earlywood and latewood.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChemical characterization by FTIR\u003c/h3\u003e\n\u003cp\u003eFew studies have been carried out to compare the chemical composition between earlywood and latewood by means of FTIR on spruce (Fredriksson, Pedersen and Thygesen \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Guo et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and on pine (Gao et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Fredriksson et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) noticed a higher lignin content in earlywood than in latewood explained from the FTIR results by a larger proportion of lignin\u0026ndash;rich middle lamella and from the Raman results, a higher lignin content in earlywood S2 layer compared to latewood S2 layer (Fredriksson, Pedersen and Thygesen \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In our case, earlywood and latewood FTIR spectra look very similar with only a few differences of intensity for some bands. The bands at 3288 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e and 3332 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (OH\u0026ndash;O stretching of bonded hydroxyl groups) show higher absorbance intensities for earlywood than latewood. Such difference could be explained by a higher absorbance in the 3800\u0026ndash;2800 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e region (O\u0026ndash;H stretching) in EW than LW for RH below 50% as shown by Gao et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In their study, the absorbance of EW shows a large increase at 32% RH whereas for LW this increase only appears at 60.8% RH. Our FTIR analysis was performed in 40\u0026ndash;50% RH where EW was more sensitive to water absorbance than LW which could explain the higher absorbance in the 3800\u0026ndash;3000 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e region in our case. The bands at 1228 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (OH plane deformation), 1104 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (ring asymmetric valence), 1050 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (C\u0026ndash;O stretching from C3\u0026ndash;O3H secondary alcohol) and 1023 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (C\u0026thinsp;=\u0026thinsp;O stretching) have a slightly higher absorbance intensity for latewood than earlywood, suggesting few variations in the chemical composition of EW and LW in line with previous studies (Fredriksson, Pedersen and Thygesen \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Via, Fasina and Pan \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Although present, these differences in intensity are not significant enough to differentiate the chemical composition of earlywood and latewood by FTIR. Differences could exist on a lower scale, i.e. between the different layers that compose the tracheid walls. In this case, the FTIR is limited due to its spatial resolution which tends to average the signal coming from the whole wood tissue. To this end, the AFM\u0026ndash;IR technique is a candidate of choice as it combines the higher spatial resolution of AFM with the chemical characterization of IR spectroscopy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFTIR band assignments in the 3800\u0026ndash;800 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e region for spruce wood\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBand position (cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAttribution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContribution due to glucomannan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Marchessault \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1962\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContribution due to glucomannan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Marchessault \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1962\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnomere C\u0026ndash;groups, C1\u0026ndash;H\u003c/p\u003e \u003cp\u003edeformation, ring valence vibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bari et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC6\u0026ndash;O6H stretching from cellulose\u003c/p\u003e \u003cp\u003eC\u0026ndash;O stretching or \u0026ndash;CH\u0026thinsp;=\u0026thinsp;CH\u0026ndash; out of plane bending from lignin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Horikawa et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026thinsp;=\u0026thinsp;O stretching in cellulose, hemicellulose and lignin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bari et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026ndash;O stretching from C3\u0026ndash;O3H secondary alcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Mar\u0026eacute;chal and Chanzy \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2000\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003easymmetric in\u0026ndash;phase ring stretching, C\u0026ndash;C and C\u0026ndash;CO stretching\u003c/p\u003e \u003cp\u003ering asymmetric valence vibration\u003c/p\u003e \u003cp\u003esecondary alcohol group, C\u0026ndash;O stretching of cellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Mar\u0026eacute;chal and Chanzy \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAromatic C\u0026ndash;H in plane deformation; typical for\u003c/p\u003e \u003cp\u003eG units; whereby G condensed\u0026thinsp;\u0026gt;\u0026thinsp;G etherified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003easymmetric C\u0026ndash;O\u0026ndash;C stretching vibration of cellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1\u0026ndash;O\u0026ndash;C4\u0026rsquo; or O\u0026ndash;H in plane bending from cellulose and hemicellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Horikawa et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOH plane deformation\u003c/p\u003e \u003cp\u003eC\u0026ndash;C, C\u0026ndash;O, C\u0026thinsp;=\u0026thinsp;O stretch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eG ring plus C\u0026thinsp;=\u0026thinsp;O stretch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Faix \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1991\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCH\u003csub\u003e2\u003c/sub\u003e wagging vibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOH plane deformation vibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026ndash;H bending of cellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Stevanic and Salm\u0026eacute;n \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026ndash;OH bending vibration of the C2\u0026ndash;OH groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Stevanic and Salm\u0026eacute;n \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003easymmetric C\u0026ndash;H bending from methoxyl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Faix \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1991\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCH\u003csub\u003e2\u003c/sub\u003e symmetric bending on the xylose ring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Stevanic and Salm\u0026eacute;n \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026thinsp;=\u0026thinsp;C aromatic skeletal vibrations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Faix \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1991\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026thinsp;=\u0026thinsp;C aromatic skeletal vibrations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Faix \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1991\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eH\u0026ndash;O\u0026ndash;H deformation vibration of absorbed water and C\u0026thinsp;=\u0026thinsp;O stretching in lignin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bari et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026thinsp;=\u0026thinsp;O stretching vibration in the COOH group of glucuronic acid units of xylan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Stevanic and Salm\u0026eacute;n \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u0026ndash;H stretching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCH\u003csub\u003e2\u003c/sub\u003e valence vibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCH\u003csub\u003e2\u003c/sub\u003e valence vibration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO(6)H\u003csup\u003e\u0026hellip;\u003c/sup\u003eO(3) stretching of bonded hydroxyl groups intermolecular in cellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bari et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO(3)H\u003csup\u003e\u0026hellip;\u003c/sup\u003eO(5) stretching of bonded hydroxyl groups intermolecular in cellulose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Bari et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Schwanninger et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInfrared spectra of the tracheids cell walls were obtained at nanoscale (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea,b). AFM-IR was used with a top-down illumination setup which generally needs metal-coated (gold or platinum) cantilevers to increase the IR signal in order to achieve a better sensitivity. Such setup can induced spectral changes making comparison with conventional FTIR no longer possible (Mathurin et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nevertheless FTIR is used here as reference for the location of the peaks in line with Bhagia et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) that used conventional FTIR on isolated cellulose, hemicellulose and lignin to specify which biomass contribute to the AFM-IR bands (Bhagia et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In our case, most of the AFM\u0026ndash;IR band locations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb) match well with the FTIR ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The major differences concern the band intensities that can greatly differ between EW and LW. These differences in intensity could be explained by the chemical architecture complexity and the heterogeneity of the cell walls made of entanglements of different polymers; different limitations of the AFM-IR technique such as the use of metal-coated cantilevers or its sensitivity to the surface roughness of the samples which, in the case of unembedded wood sections, can reach several tenths of nanometers.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo better highlight potential chemical composition differences between EW and LW, different ratios of the IR amplitudes between 1732 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (acetyl groups in xylan; non\u0026ndash;conjugated carbonyls), 1512 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e and 1600 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (C\u0026thinsp;=\u0026thinsp;C aromatic skeletal vibrations) and 1372 cm\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (C\u0026ndash;H bending of cellulose) were calculated (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The CC of both EW and LW display the highest values for the I\u003csub\u003e1732\u003c/sub\u003e/I\u003csub\u003e1372\u003c/sub\u003e ratio suggesting a higher amount of carbonyl groups and a lower amount of carbohydrates in this layer with a much larger value for EW (1.32) compared to LW (0.59). The same trend exists between the S1 layers of EW (0.94) and LW (0.51) whereas the values of the S2 layers are in the same order of magnitude. The I\u003csub\u003e1512\u003c/sub\u003e/I\u003csub\u003e1732\u003c/sub\u003e ratio gives information about the amount of functional group of lignin relative to the amount of functional group of hemicellulose. Overall, the values of the ratios are higher in all the layers of LW compared to EW. There is no clear trend between EW and LW with the highest value being for the S2 of EW followed by the CC and finally the S1 layer whereas for LW the highest value is for the CC very close to the S2 layer and finally the lowest value for the S1 layer. Regarding the ratio I\u003csub\u003e1512\u003c/sub\u003e/I\u003csub\u003e1600\u003c/sub\u003e which is an indicator of the condensation degree of lignin, the values are higher for all the cell wall layers of LW compared to EW suggesting lower concentration of the non-condensed structures in LW than in EW. Furthermore, the S2 layer displays the highest value for both EW (1.26) and LW (1.70). The S1 and CC show an opposite trend between EW and LW with a higher value in the S1 and a lower value in the CC for EW and the opposite for LW. Finally, the values obtained for the I\u003csub\u003e1512\u003c/sub\u003e/I\u003csub\u003e1372\u003c/sub\u003e ratios show the same trend for both EW and LW. More specifically the values go from the lowest value for the S2 layer, followed by the S1 layer and finally the highest values for the CC. These results indicate a gradient of lignin and cellulose across the cell wall with an increase of lignin and a decrease of cellulose from the S2 to the S1 and finally to the CC in line with the theory of the chemical distribution in plant cell walls.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIR amplitude ratios of specific bands obtained by AFM-IR for earlywood and latewood\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEarlywood\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eLatewood\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalculated ratios\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003csub\u003e1732\u003c/sub\u003e/I\u003csub\u003e1372\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003csub\u003e1512\u003c/sub\u003e /I\u003csub\u003e1732\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003csub\u003e1512\u003c/sub\u003e/I\u003csub\u003e1600\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003csub\u003e1512\u003c/sub\u003e/I\u003csub\u003e1372\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNanomechanical analysis\u003c/h2\u003e \u003cp\u003eThe indentation moduli (IM) of spruce EW and LW tracheid cell walls in the S2, S1 and CC were continuously monitored over three S/D cycles. As mentioned earlier, only the results for the 2nd and the 3rd S/D cycles will be discussed in this section. The AFM IM maps obtained at each of the RH during cycle 3 (sorption and desorption) for LW and EW are available in Supplementary information (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These images clearly indicated the softening of S2 at 85% RH. Although not the focus of this investigation, the LW images (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) allowed to determine a 7\u0026ndash;10% swelling from 15 to 85% RH and a shrinkage of 5\u0026ndash;7% in reverse from 85 to 15% RH in the radial direction, values which agree with literature (Derome et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). It was not possible to do the same for EW due to the absence of the lumen in the AFM images. Overall, averaging the data for S2, S1 and CC, EW and LW present the same hygromechanical behavior for all the layers as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. During the 2nd S/D cycle, the IM decreases during the sorption from 15% RH to 85% RH then re-increases during desorption back to 15% RH; similar hygromechanical behavior occurs during the 3rd S/D cycle.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003e displays the distributions of the IM and their corresponding Gaussian fits in cell wall layers CC, S1 and S2 at the different RH and for the 2nd and 3rd S/D cycles. CC consistently displays a narrower distribution compared to the S2 and the S1 layers, highlighting that CC is chemically more homogeneous composed mostly of lignin and non\u0026ndash;cellulosic polysaccharides compared to the SCW which possesses in addition cellulose leading to higher heterogeneity in the polymer assemblies. The distributions of S2 and especially of S1 layers are larger showing low and broad Gaussian fits. The S1 layer is thin (~\u0026thinsp;50\u0026ndash;150 nm) making it difficult to extract as much AFM force spectroscopy local measurements as for the S2 and CC for analysis. In addition, the S1 layer lies between the S2 layer and the CC, so the IM obtained for the S1 could be biased by data taken at the interfaces S2/S1 and S1/CC. We note that the Gaussian fits vary not only with the type of layer but also with relative humidity. The Gaussian fits become narrower with increasing relative humidity and are larger at the beginning and at the end of the cycles. This result can be explained by the different dependence on MC of wood polymers. For instance, the CC is mainly rich in lignin and hemicellulose. The Young\u0026rsquo;s modulus of these two wood polymers in dry state is around 2 GPa for lignin and around 3\u0026ndash;7 GPa for hemicellulose (Bergander and Salm\u0026eacute;n \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). As hemicellulose is more hydrophilic than lignin, it is more softened by water than lignin. At higher MC, the IM of hemicellulose approaches the one of lignin, leading to more homogeneous nanomechanical properties across the cell wall layer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor each module and cycle, the density values given on the y-axis combined with bar width of 0.2 correspond to a total bar area of 1\u003c/p\u003e \u003cp\u003eThe nanomechanical results are in the same order of magnitude as found in previous studies and typical of plant cell walls with higher IM in the S2 layer which is attributed to the presence of semi\u0026ndash;crystalline cellulose microfibrils playing the role of reinforcement in the longitudinal direction of the cell wall followed by the S1 and finally the CC (Arnould et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Casdorff, Keplinger and Burgert \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Coste et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Melelli et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Muraille et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). More precisely the low microfibril angle (MFA) in the S2 is a key parameter in the final nanomechanical properties as previously reported at macroscale (Burgert et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) as well as micro/sub\u0026ndash;microscale (Arzola-Villegas et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Burgert and Keplinger \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gindl et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; J\u0026auml;ger et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Tze et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The orientation of the cellulose microfibrils in the fiber axis (S2) and in the transverse fiber direction (S1 and S3) results from an evolutionary mechanism that allows the whole tree to act as an efficient structure against gravity and environmental (wind) stresses. More precisely, in the S2 of mature wood, the MFA lies between 5\u0026ndash;20 \u0026deg; whereas in the S1 and S3 layers it is almost perpendicular to the longitudinal direction (Donaldson \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The cell corner shows the lowest IM which can be explained by the lack of cellulose microfibrils and the high content of lignin for which the modulus has been estimated at around 0.6\u0026ndash;2 GPa (Bergander and Salm\u0026eacute;n \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The nanomechanical properties of the S1 are higher than the ones of the CC due to the presence of cellulose microfibrils but remain lower than the ones in the S2 because of the greater MFA almost perpendicular to the cell axis which is here also the direction of the applied force (Donaldson \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). All the layers of the cell wall present the same general hygromechanical behavior of softening and hardening. The mechanism involves first a decrease of the IM during sorption from RH\u0026thinsp;=\u0026thinsp;15% to RH\u0026thinsp;=\u0026thinsp;85%. This result has already been shown in one of our previous studies on hemp xylem and bast fibers (Coste et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A similar decrease of properties with increasing RH has been observed by molecular dynamics and seems to correspond to the formation of a layer of water molecules along amorphous polymeric chains (Chen et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Then during desorption, the IM increases and, taking into account the standard deviation, it appears that the IM returns to its initial IM.\u003c/p\u003e \u003cp\u003eSlight differences are visible between the EW and LW for both cycles 2 and 3. To better highlight these differences, the coefficients of variation (CV (%)\u0026thinsp;=\u0026thinsp;standard deviation/average) of the indentation moduli were calculated for each layer of the EW and LW considering both cycles 2 and 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e). First, the medians (middle quartiles) of the boxes are generally much higher in earlywood with values comprised between 10\u0026ndash;23% (except for the S2 layer at 85% RH) whereas the medians of the boxes in latewood are all below 12%. Second, the coefficients of variation depend on the type of wood (EW or LW) but also on the cell wall layer. More precisely, in earlywood, the medians are the highest in the S1 layer, followed by the cell corner and exhibit the lowest values in the S2 layer. In latewood, the highest medians appear in the S2 layer, followed by the S1 layer and finally the cell corner. Third, earlywood not only exhibits higher medians but also generally higher inter-quartile ranges (height of the box) than in latewood. This result indicates higher disparities of coefficients of variation in EW than in LW. Altogether, these results help to highlight that mechanical behavior of earlywood at nanoscale is more affected by RH than latewood which is more stable to RH. Indeed, in latewood the boxes of each layer are close to each other for all the RH percentages.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn order to compare the evolution of IM rather than the average value at each RH, the responses of the indentation moduli to RH were fitted according to a three parameter logistic function (see Eq.\u0026nbsp;(\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) in the Materials and Methods AFM PeakForce QNM section) \u003cb\u003e(\u003c/b\u003eFigure S2\u003cb\u003e)\u003c/b\u003e and the estimated parameters (\u003cem\u003eb\u003c/em\u003e, \u003cem\u003ed\u003c/em\u003e and \u003cem\u003ee\u003c/em\u003e) between EW \u003cem\u003evs\u003c/em\u003e LW and for desorption \u003cem\u003evs\u003c/em\u003e sorption were compared to determine potential significant differences in responses measured in CC, S1 and S2 while taking the data from the second and third cycle. The highest relative differences and variabilities are observed for the parameter \u003cem\u003eb\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e9\u003c/span\u003e) compared to parameters \u003cem\u003ed\u003c/em\u003e and \u003cem\u003ee\u003c/em\u003e for which few relative differences are detected (data not shown). When comparing desorption \u003cem\u003evs\u003c/em\u003e sorption (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e9\u003c/span\u003ea), significant differences are observed for the S2 in both EW and LW for the parameter \u003cem\u003eb\u003c/em\u003e, with \u003cem\u003eb\u003c/em\u003e being found lower in desorption, which indicates a higher slope in the curve describing the response of moduli to RH between 15 and 50% RH in desorption. The comparison of this latter parameter between EW \u003cem\u003evs\u003c/em\u003e LW (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e9\u003c/span\u003eb) reveals significant differences in CC and S1 (and consistently for both desorption and sorption) with a relatively lower value of \u003cem\u003eb\u003c/em\u003e, which reflects a higher slope in moduli response to RH in LW between 15 and 50% RH and the opposite between 50 to 85% RH. Such responses could be related to the dimensional changes induced by the variations in RH (Zhan, Lyu and Eder \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Few studies have focused on moisture-induced deformation at the cell wall level while comparing early and late woods. Nevertheless Zhan et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) have shown a higher shrinking ratio than swelling ratio of the cell walls of Chinese fir along drying and water sorption respectively; and these changes were higher for cell walls of latewood than earlywood. In this study where dimensional changes at tissue, cell and cell wall levels were addressed using environmental scanning microscopy, the higher variation of the cell walls of latewood could be related to the higher cell wall proportion in the cross section of latewood.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAFM PeakForce QNM under controlled relative humidity (RH) was applied to continuously monitor the nanomechanical properties of same spruce specimen over three S/D cycles. While FTIR showed no major difference between earlywood and latewood, AFM\u0026ndash;IR, with its higher spatial resolution, captured small differences along the cell walls from CC to the S2 layer. Combining cycle 2 and 3 data, few variations were shown for latewood than earlywood during sorption/desorption isotherms and the dispersion of IM decreased with highest RH. DVS analysis with Park\u0026rsquo;s model showed that LW undergoes more water aggregation sites and this aggregation was not affected by successive 2nd and 3rd cycles. AFM-IR analysis indicated that there is indeed a gradient of lignin and cellulose across the cell wall with particularly an increase of lignin for all the layers of LW compared to EW suggesting lower concentration of the non-condensed structures in LW than in EW. Finally, a three-parameter logistic function allows us to represent accurately the relationship between IM variation to RH and to reveal that the highest relative differences for the S2 in both EW and LW when comparing desorption vs sorption and also for CC and S1 in both sorption and desorption. In future work, dimensional changes and evaluation of water content at each wall layer could be considered to extend the relationship between nanomechanical properties and water content of plant cell walls.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eThe authors gratefully acknowledge Edwige Audibert and Miguel Pernes for their valuable contributions to collecting macroscope images and DVS data that supported this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eR.C.: investigation, methodology, formal analysis, data curation, conceptualization, and drafting the original manuscript. V.A.B.: formal analysis, conceptualization, and review and editing of the manuscript. H.C.: data curation, formal analysis, visualization, and review and editing of the manuscript. M.M.: conceptualization, review and editing. D.D: conceptualization, review and editing, funding acquisition, and project supervision. B.C.: conceptualization, formal analysis, review and editing of the manuscript, funding acquisition, and project supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was carried out within the framework of the INTOS2 project supported by the French National\u003c/p\u003e\n\u003cp\u003eResearch Agency (ANR-18-CE93-0007) and the Swiss National Science Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e: Data are provided upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgarwal UP (2006) Raman imaging to investigate ultrastructure and composition of plant cell walls: distribution of lignin and cellulose in black spruce wood (Picea mariana). 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Composites Part B: Engineering 228:109449.\u003c/li\u003e\n\u003cli\u003eZimmermann T, Richter K, Bordeanu N, Sell J (2007) Arrangement of Cell-Wall Constituents in Chemically Treated Norway Spruce Tracheids. Wood and Fiber Science 39 (2):221 \u0026ndash; 231.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"wood-science-and-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wsat","sideBox":"Learn more about [Wood Science and Technology](http://link.springer.com/journal/226)","snPcode":"226","submissionUrl":"https://submission.nature.com/new-submission/226/3","title":"Wood Science and Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Spruce, Cell wall, Relative humidity, Nanomechanical properties, AFM–IR","lastPublishedDoi":"10.21203/rs.3.rs-8132624/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8132624/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAFM PeakForce QNM under controlled relative humidity (RH) was applied to continuously monitor the indentation modulus (IM) of Norway spruce (\u003cem\u003ePicea abies\u003c/em\u003e) earlywood (EW) and latewood (LW) tracheid cell walls over three sorption/desorption (S/D) cycles. The IM of the different cell wall layers were close between early- and latewoods indicating small differences between their chemical compositions. AFM IR indicate a gradient of lignin and cellulose across the cell wall with an increase of lignin and a decrease of cellulose from the S2 to the S1 and finally to the CC. Earlywood and latewood cell walls display the same hygro\u0026ndash;nanomechanical behavior during S/D cycle, i.e., the IM decrease with during sorption up to 85% and re\u0026ndash;increase during desorption. Gaussian fits of the IM distribution were narrower for late wood than early wood and vary with the type of layer and with the relative humidity. The responses of the indentation moduli to RH of the cell wall layers in early- and latewood were fitted according to a three-parameter logistic function. Significant differences are observed for the S2 in both EW and LW indicating a higher slope in the response of indentation moduli to RH between 15 and 50% RH in desorption as compared to sorption. For both desorption and sorption, the comparison between EW \u003cem\u003evs\u003c/em\u003e LW reveals differences in CC and S1, with a higher slope in moduli response to RH in LW between 15 and 50% RH and the opposite between 50 to 85% RH.\u003c/p\u003e","manuscriptTitle":"Online monitoring of the hygromechanical properties of spruce tracheid cell walls at the nanoscale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 16:10:03","doi":"10.21203/rs.3.rs-8132624/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-19T16:28:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T14:51:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-19T19:21:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295894637507192208922401866871170212216","date":"2025-12-11T07:17:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42122514882338959758509504908435323192","date":"2025-12-10T18:52:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"7362929096037003469482993875689238172","date":"2025-12-10T18:06:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-10T17:11:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T17:09:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-18T06:27:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"Wood Science and Technology","date":"2025-11-17T08:12:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"wood-science-and-technology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"wsat","sideBox":"Learn more about [Wood Science and Technology](http://link.springer.com/journal/226)","snPcode":"226","submissionUrl":"https://submission.nature.com/new-submission/226/3","title":"Wood Science and Technology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e09a0a84-c8f3-4118-8230-0d9256868a87","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-24T15:09:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 16:10:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8132624","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8132624","identity":"rs-8132624","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}