Measuring Molecular Strain in Rewetted and Never-Dried Eucalypt

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Measuring molecular strain in rewetted and neverdried eucalypt wood with Raman spectroscopy Fei Guo, and Clemens M. Altaner Biomacromolecules, Just Accepted Manuscript • DOI: 10.1021/acs.biomac.9b00808 • Publication Date (Web): 17 Jul 2019 Downloaded from pubs.acs.org on July 21, 2019

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Biomacromolecules

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Measuring molecular strain in rewetted and never-

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dried eucalypt wood with Raman spectroscopy

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Fei Guo1, 2, Clemens M. Altaner2*

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AUTHOR ADDRESS

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1 College

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China

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2 New

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New Zealand

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KEYWORDS: band shift, E. regnans, E. quadrangulata, growth stress, molecular deformation,

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of Furnishings and Industrial Design, Nanjing Forestry University, 210037, Nanjing,

Zealand School of Forestry, University of Canterbury, Private Bag 4800, Christchurch,

tensile strain, PLS.

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1 Environment ACS Paragon Plus

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ABSTRACT

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To measure growth strain in wood using Raman spectroscopy, we investigated the Raman spectra

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of rewetted (water-saturated) E. regnans and green E. quadrangulata wood during tensile and

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four-point bending tests. Partial least squares models to predict tensile strain were built from the

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Raman spectra. The best model could predict tensile strain with a root mean square error of 427.5

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>?: Apart from the widely reported band shift at 1095 cm@ upon mechanical strain, spectral

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changes at 1420, 1120, 895, 456 cm@ were identified. The assignments of these bands were

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discussed in relation to the molecular deformation of cellulose. The band shift rates during tensile

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tests were @ :,. and @ : $ cm@ /% for rewetted E. regnans and green E. quadrangulata wood,

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respectively. We successfully detected the release of molecular growth strain in green eucalyptus

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wood with Raman spectroscopy by observing band shifts of the 1095 cm@ signal. Further, there

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was a moderate correlation (r = 0.48) between growth-strain measured with strain gauges and the

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1095 cm@ band position. The precision of the prediction of growth strain using Raman

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spectroscopy was negatively affected by variation attributed to the inhomogeneity of wood on the

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millimeter scale and instrumental instability.

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1 INTRODUCTION

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Raman and mid-infrared (MIR) spectroscopy are complementary techniques measuring

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vibrational frequencies of chemical bonds 1. The former is based on the Raman scattering

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phenomenon, while the latter detects the absorption of electromagnetic radiation. With

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technological advances, Raman spectroscopy is gaining popularity in various applications

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including material identification 2, forensic and pharmaceutical analysis 3 as well as chemical


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distribution imaging of plant cell walls 4, 5. Portable Raman spectrometers are commercially

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available 6, opening up the possibility of measuring wood properties in the field rapidly and non-

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destructively. Compared to infrared spectroscopy, Raman spectroscopy is insensitive to water,

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which interferes with the structural information of plant material 7 as it is typically water

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saturated when alive. Challenges of using Raman spectroscopy on lignocellulosic materials are

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the laser-excited florescence from lignin, which causes an intense background masking the

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Raman signal, and the high energy of the laser, which leads to thermal decomposition of the

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sample. Using 1064 nm near infrared (NIR) lasers dramatically reduces florescence from lignin 8

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and water immersion sampling lessens thermal degradation 9.

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Mechanical stress induces both macroscopic and molecular deformation of wood and cellulose.

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Axial elongation and lateral contraction of the cellulose crystal lattice in wood was observed

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upon tensile stress by X-ray diffraction 10, 11. Deformation of crystalline cellulose will cause

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changes in vibrational frequencies of chemical bonds, which were observed as band shifts in

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MIR 12, 13, near infrared (NIR) 14 and Raman spectra 15. IR spectroscopy detected the deformation

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of the COC glycosidic bonds at 1160 cm@ and intramolecular O3H O5 groups at 3348 cm@

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NIR band shifts at 6286 ± 5 cm@ and 6470 ± 10 cm@ indicated intramolecular hydrogen bonds

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of crystalline cellulose elongated under tensile strain 14.

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Raman spectroscopy has been a powerful tool to study the molecular deformation of polymer

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fibers. 16 reported that the Raman frequencies assigned to the backbone structure of

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polydiacetylene decreased with the elongation of fibers. Following this work, Raman

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spectroscopy was used to study the molecular deformation of regenerated cellulose 17. The

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Raman band shift at around 1095 cm@ , assigned to the stretching of the cellulose ring structure,


13.


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has also been reported for wood, flax and hemp fibers 18-20. However, the effect of mechanical

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strain on other regions in the Raman spectra is not well understood.

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Growth stresses in trees, accumulated during cell wall maturation 21, cause problems like end-

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splitting, heart checking and collapse and are the major cause restricting plantation-grown

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eucalypts from in solid wood processing 22. Growth strain, similar to mechanical strain, causes

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deformation of wood and cellulose on the molecular level 23. Methods to measure growth strain

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in trees, the Nicholson technique 24, the CIRAD-Forêt method 25, log splitting 26 and the strain

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gauge method 27, are destructive or time consuming. Rapid and non-destructive evaluation of

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growth stress is needed to segregate logs with low growth strain for high-value solid wood uses.

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Raman spectroscopy could potentially measure growth strain quickly and non-destructively by

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accurate determination of vibrational frequencies. Previous studies on the deformation

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mechanism of cellulosic materials focused on small areas of single fibers using a Raman

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microscope, requiring elaborate sample preparation. However, Raman spectrometers capable of

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direct surface sampling are available, enabling the collection of spectra without the limitation of

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sample size. This is also advantageous as mechanical properties of wood have been known to

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depend on sample size 28. Thin wood samples were shown to have different load-displacement

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curves compared to bulk wood 29 and the modulus of elasticity of microtomed wood sections

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were lower than that of normal sized specimens 30.

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In this study, thick wood strips were mechanically stretched to confirm the effect of strain on

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Raman spectra, previously only reported for microscopic samples, differing in their mechanical

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behavior. Band shift rates were calculated to quantify molecular strain in rewetted and green

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wood. Following on from this, the release of growth strain was monitored by Raman


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spectroscopy on green, never-dried stems before finally evaluating the possibility of measuring

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growth strain in green stems using Raman spectroscopy.

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2 MATERIALS AND METHODS

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2.1 Tensile tests of rewetted and green wood monitored by Raman spectroscopy

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An air-dry Eucalyptus regnans board with an oven-dry density of 0.51 g/cm3 was sourced from

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Canterbury, New Zealand. The microfibril angle (MFA) of the E. regnans wood was 7°

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(standard deviation of 2.9°), as previously measured by X-ray diffraction. Ten wood strips with a

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thickness of 0.5 to 1 mm (radial) were cut with a circular saw from the sapwood of the air-dry E.

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regnans board and sanded before being cut into the shape shown in Figure 1. Wood sample used

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for tensile tests while collecting Raman spectra. The grain (longitudinal direction) runs along the

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longest dimension of the sample. Dimensions are labelled in millimeters.

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. The samples were re-saturated through immersion in water for at least 7 days and were referred

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to as “rewetted” wood in this study. A 2-year old E. quadrangulata tree with an oven-dry density

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of 0.68 g/cm3 was harvested from a site in Woodville, New Zealand. The tree was kept in water

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during transport to the lab. Eight wood strips were prepared from the never-dried green tree in

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accordance to the procedure described above for the E. regnans samples. E. quadrangulata

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samples were put in a sealed plastic bag and stored in a freezer until tested.



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Figure 1. Wood sample used for tensile tests while collecting Raman spectra. The grain

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(longitudinal direction) runs along the longest dimension of the sample. Dimensions are labelled

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in millimeters.

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A purpose-built tensile test rig 14 was placed under a dispersive Raman spectrometer (Sierra 2.0,

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Metrohm Raman, USA) equipped with a 1064 nm NIR laser and an InGaAs array detector. The

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wood samples were mechanically stretched while simultaneously collecting Raman spectra at

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twelve strain levels, increasing progressively from “Strain 0” (approx. 0 >?< to “Strain 11”

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(maximum strain of approx. 4500 >?< with increments of approximately 410 >?) before returning

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to the relaxed (RL) state. Applied macroscopic strain was measured by strain gauges (FLA-5-11,

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Tokyo Sokki Kenkyujo, Japan) glued (Loctite 454, Australia) onto the samples and connected to

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a TC-31K strain-meter (Tokyo Sokki Kenkyujo, Japan). Strain was defined as the amount of

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deformation per unit length and 1 >? equals to 1×10@. strain. The wood surface was kept wet

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during spectra collection to restrict thermal decomposition 31 and improve spectral quality 9. Two

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Raman spectra were taken at each strain level in the region from 2300 to 200 cm@ with a laser

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power of 500 mW and an integration time of 30 to 35 s. In total 26 spectra were acquired for

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each sample. The spectrometer featured orbital raster scan (ORS), a technique to reduce sample

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damage by moving the laser over a measuring area of 1 to 2 mm in diameter. The polarization

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direction of the incident light was parallel with the longitudinal direction of the wood samples.


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Biomacromolecules

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2.4 Data analysis

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In order to visualize the band shift caused by mechanical strain at around 1095 cm@ upon tensile

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stress, Raman spectra were processed and plotted in R 33. Raman spectra were smoothed using

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the Savitzky-Golay filter with a window length of 9 in the “signal” package 34 before being

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normalized using the standard normal variate (SNV) method 35 in the range of 1180 to 950 cm@ .

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For E. regnans wood upon tensile tests, PLS models were built to predict the applied mechanical

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strain based on Raman spectra in the region between 2300 and 200 cm@ . The 258 spectra from

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10 E. regnans samples were split randomly into a training group with 180 spectra and a

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validation group with 78 spectra using the “sample” function in R. Five PLS models were

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developed using leave-one-out (LOO) cross-validation with the “pls” package 36 based on

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different spectra pre-processing, including baseline correction, SNV normalization, second

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derivatives and spectra truncation (1180 ~ 950 cm@ ). Baseline correction was conducted with a

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modified polynomial algorithm in the “baseline” package 37. Coefficients of determination (R2)

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and root mean squared errors (RMSE) of the PLS models for the training and the validation

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group were extracted.

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Spectral changes caused by mechanical strain were also analyzed by the regression coefficients

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plot of the PLS model and ‘slope’ spectra. ‘Slope’ spectra were calculated to show the rate of

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change in spectral intensity at each wavenumber induced by mechanical strain as described

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previously 14, 38. It was calculated from baseline corrected and normalized spectra. The average

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‘slope’ spectrum was calculated as the average of 10 ‘slope’ spectra of 10 rewetted E. regnans

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samples. To quantify the band shift at around 1095 cm@ , a Cauchy-Lorentzian function was used



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to fit the spectra in the range from 1103 to 1084 cm@ using the nonlinear least squares method in

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R. Band positions were extracted from the fitted model.

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3 RESULTS AND DISCUSSIONS

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3.1 Raman spectra of rewetted wood under tensile strain

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3.1.1 Visualization of Raman band shifts

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The signal intensity of Raman bands mainly depends on laser power and its frequency,

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polarizability and concentration of the chemical group, as well as the sample orientation 39. For

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biological materials, fluorescence and various physical effects such as surface roughness, particle

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size and sample inhomogeneity have noticeable influence on the Raman scattering intensity as

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well 40, 41. Due to these interfering factors, the intensities of the Raman spectra of the rewetted

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wood fluctuated and it was difficult to identify the small spectral changes caused by mechanical

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strain from the original spectra (Figure 4A). The fluctuations in the spectra could be removed by

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SNV normalization in range from 1180 to 950 cm@ , allowing to determine the effect of

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mechanical tensile strain on the position of the band centered at around 1095 cm@ (Figure 4A

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inset). The 1095 cm@ band was assigned to CC and CO stretching of the cellulose ring structure

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17, 42,

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cellulose backbone. This band shift had been reported for regenerated cellulose as well as single

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wood and other natural fibers using Raman microscopy 18, 19, 43-45. Our results showed that this

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tensile strain induced Raman band shift can also be observed in relatively thick (>0.5 mm) E.

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regnans wood strips, with mechanical behavior similar to solid wood 30. A strong linear

indicating the elongation of cellulose chains and weakening of the covalent bonds in the


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relationship (r = 0.997) was found between the peak position and the applied strain (Figure 4B).

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As strain increased from @$ >? to 4649 >?) the band position shifted from 1095.35 to 1093.57

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cm@ . The band shift rate for this sample was @ :-4 cm@ /%, which was greater compared to the

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values ;@ :

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to 3.2.

to @ :. cm@ /%) reported for single wood fibers 19. For a detailed discussion refer

198 199

Figure 4 Unmodified Raman spectra at 12 tensile strain levels of one rewetted E. regnans wood

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sample (A) and the corresponding band shifts of the 1095 cm@ band (B). Inset (A) shows the

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band at 1095 cm@ after SNV normalization in the region of 1180 to 950 cm@ . “Strain 0” to

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“Strain 3” were represented with solid lines, “Strain 4” to “Strain 7” with dashed lines and

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“Strain 8” to “Strain 11” with dotted lines, each in the color sequence blue, red, pink and green.

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The band at 1095 cm@ shifted 1.78 cm@ to lower frequencies with a strain increase of 4702 >?:

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3.1.2 Predicting strain based on Raman spectra using PLS modelling

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Table 1 shows the effects of spectral processing on the PLS models to predict mechanical strain

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in wood. Baseline correction aimed to remove the effects of lignin fluorescence, while

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normalization attempted to compensate multiplicative effects such as laser fluctuation and



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uncertainties in focusing 40. Second derivative is another way to reduce baseline effects and

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truncation to the region from 1180 to 950 cm@ eliminated many variables unaffected by

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mechanical strain. The root mean square error of cross-validation (RMSECV) ranged from 354.7

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to 493.1 >?) while the coefficient of determination of cross-validation (R2CV) varied between

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0.89 and 0.94 (Table 1). Using the models with the validation data resulted in comparable

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statistics, indicating no over-fitting. Baseline correction followed by normalization resulted in

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the best performing PLS model (RMSEP = 397.2 >?< using 4 components. The predicted and

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measured strain for the training group for this PLS model was shown in Figure 5A. The

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distribution of residuals suggested an unbiased model (Figure 5B). The models based on

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truncated spectra in the region of 1180 to 950 cm@ and unmodified spectra achieved slightly

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reduced model statistics with RMSEP of 426.7 and 443.6 >?) respectively. However, more

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components were required for the unmodified spectra (Table 1). PLS modelling coupled with

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reflection NIR spectroscopy was successfully used to predict bending (R2 V 0.90) and tensile

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load (R2 = 0.96) on small air-dry wood samples 46, 47. As NIR is sensitive to moisture, this

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technique is of limited use for wood with high moisture content. Non-destructive reflection NIR

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measurements of mechanical strain in green wood were found to be less accurate (R2 = 0.36),

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due to the high moisture content interfering with structural information and a low signal to noise

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ratio 7.

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Table 1 Metrics of PLS models utilizing unmodified and processed Raman spectra to predict

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mechanical strain in rewetted E. regnans wood. The spectral region was 2300 to 200 cm@ , except

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for the truncated spectra, for which ranged from 1180 to 950 cm@ .

Pre-processing method

Training group Number of 2 components R CV RMSECV


Validation group R2P RMSEP

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Raw data Baseline correction Baseline correction + SNV Second derivative Truncation + SNV

0.91 0.91 0.94 0.89 0.93

440.5 432.8 354.7 493.1 385.9

6 4 4 3 3

0.92 0.92 0.94 0.90 0.93

443.6 456.1 397.2 510.5 426.7

230 231

SNV: standard normal variate (SNV) normalization; CV: Leave-one-out cross-validation;

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RMSECV: root mean squared error of cross-validation using the training data; RMSEP: root mean

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squared error of prediction for the validation data; R2: coefficient of determination.

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Figure 5 Measured versus predicted tensile strain of rewetted E. regnans wood (A) and distribution

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of the residuals (B) for the PLS model based on baseline corrected and SNV normalized Raman

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spectra of the training data.

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3.1.3 Spectral changes analyzed by regression coefficients and the average ‘slope’ spectrum

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Both, regression coefficients of the PLS model and ‘slope’ spectra reflect spectral changes

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caused by mechanical strain, but were calculated with different algorithms. The regression

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coefficients of the PLS model represent the change in the response variable (i.e. tensile strain)



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induced by one unit change in the predictor variables (i.e. the Raman intensities at each

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wavenumber). As shown in Figure 6, the PLS regression coefficients and the average ‘slope’

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spectrum showed almost identical features, with spectral changes in the regions of 1500 to 850

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cm@ and 500 to 280 cm@ . Split peaks at 1420, 1120, 1095, 895, 456 cm@ with negative peaks

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immediately followed by positive peaks indicated band shifts to lower frequencies 38, 48.

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The most dominant Raman band shift induced by mechanical strain at around 1095 cm@ (Figure

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4 and Figure 6) was reported for various (ligno)cellulosic materials 18-20. The band at 1127 cm@

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was also previously reported to shift to lower wavenumbers for wood fibers under tensile strain

250

19.

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deformation of the cellulose skeleton 5. Additionally, in regenerated cellulose fibers the band at

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895 cm@ was also reported to shift upon stress, but with a lower sensitivity to strain than the

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band at 1095 cm@

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HCC at C6 of cellulose 9, 42, indicating that HCO and HCC at C6 were deformed upon tensile

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strain. NIR spectroscopy observed the deformation of 2OH, involved in intramolecular hydrogen

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bonds to O6, upon stretching 14, likely affecting the other covalent bonds connected to this group.

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The region from 1430 to 1350 cm@ was assigned to the bending vibrations of COH groups 42.

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Therefore, the Raman band shift at 1420 cm@ suggested the molecular deformation of COH

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groups, which was consistent with MIR and NIR evidence of tensile strain induced deformation

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of OH groups involved in hydrogen bonds 14, 49-51. Consistent with our observations, Raman band

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shifts at 1414, 1095 and 895 cm@ were reported for high-modulus cellulose fibers under tensile

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stress 52 and additionally at around 459 cm@ in single ramie fibers during tensile tests 53. The

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region between 250 and 550 cm@ was mainly attributed to the skeletal bending motions of

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cellulose, including CCC, COC, OCC and OCO bonds 42, 54.

Both bands were assigned to the stretching of cellulose CC and CO bonds, confirming the

17.

The band at 895 cm@ was tentatively assigned to the bending of HCO and


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Figure 6 Regression coefficients (grey) of the PLS model based on baseline corrected and

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normalized Raman spectra and the average ‘slope’ spectrum (black) for 10 rewetted E. regnans

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wood samples upon stretching in the region from 2300 to 200 cm@ . The dashed line shows a

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representative unmodified Raman spectrum of rewetted E. regnans wood.

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3.2 Quantification of Raman band shifts caused by stretching

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Apart from PLS modelling, another approach to predict strain is to use linear models based on

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the positions of the Raman band at around 1095 cm@ . Raman band positions at around 1095

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cm@ were determined by fitting a Cauchy-Lorentzian function to the signal. The dependence of

274

the Raman band position on tensile strain was quantified for rewetted E. regnans (Figure 7A)

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and green E. quadrangulata (Figure 7B) wood (Figure 7). As tensile strain increased from the

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relaxed state to the maximal applied strain level, the band at 1095 cm@ shifted to lower

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wavenumbers for both, previously dried water-saturated and never-dried green wood, indicating

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elongation of the cellulose ring structure. With the release of the applied tensile stress, the



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Raman band returned to its original position. No significant differences were found between the

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band positions before (“Strain 0”) and after the tensile tests (RL) (p = 0.31 and 0.27 for rewetted

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and green wood, respectively). Similar behavior has been reported for single wood fibers 19 but

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no similar studies have been done for bulk wood. This study showed that the Raman band at

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around 1095 cm@ was also sensitive to strain for wood samples with a thickness of 0.5 to 1 mm.

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Thin wood samples, only a few cells thick, behave differently from bulk wood during tensile

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tests due to unrestricted cellular and supramolecular deformations caused by removing the

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supporting structure of neighboring tissue 29. With eucalyptus fibers having diameters of 10 to 20

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µm 55, this effect was minimized here, as the wood strips used in this study were comprised of

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more than 25 cells in thickness. For even larger wood samples MOE was shown to increase with

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sample thickness 28, 30.

290


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Figure 7 Dependence of the position of the Raman band at around 1095 cm@ on tensile strain for

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rewetted E. regnans (A) wood (n = 10) and green E. quadrangulata (B) wood (n = 8). Raman

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spectra were collected as mechanical strain increased stepwise from “Strain 0” (approx. 0 >?< to

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“Strain 11” (approx. 4500 >?< with a step of approx. 410 >? and then returned to the relaxed (RL)

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state.

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The mean Raman band position in the relaxed state for rewetted E. regnans and green E.

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quadrangulata was 1095.41 (±0.15) and 1095.26 (±0.17) cm@ , respectively (Table 2). The

298

difference in band position between E. regnans and E. quadrangulata was not statistically

299

significant (p = 0.08). The observed variation could be caused by instrumentation like laser

300

fluctuation or variation in chemical composition and wood anatomy features such as microfibril

301

angle and grain angle 56. Additionally, the drying history was reported to affect the cellulose

302

structure 57, 58.

303

The band shift rate with respect to strain for rewetted E. regnans and green E. quadrangulata

304

during the tensile tests was @ :,. and @ : $ cm@ /% (Table 2). The significantly lower (p ?:

cm@ /% for air-dried hemp fibers 20 and @ :

Species

Sample condition

Sample size

E. regnans

rewetted

10

E. quadrangulata

green

8

to @ :. cm@ /% for air-dried single wood

Band position (cm@ ) 1095.41 (0.15) 1095.26 (0.17)

Band shift rate (cm@ /%)

R2

@ :,. (0.48)

0.95 (0.02)

@ : $ (0.19)

0.89 (0.05)

327 328

3.3 Monitoring the release of growth stress using Raman spectroscopy

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Wood formed in the upper side of leaning hardwood trees, referred to as tension wood, is usually

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associated with high tensile stress 62. Correspondingly, growth strain ranged from 1294 to 1446


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>? in the tension sides and from @ -3 to 64 >? in the opposite sides of the e investigated E.

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bosistoana stems (Figure 8). Raman spectra were taken from these stems before and after

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releasing growth stress. For the tension sides, the band position shifted to higher wavenumbers (p

334

< 0.016) after cutting the grooves, suggesting the release of tensile strain (Figure 8). In contrast,

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no significant differences were found for the opposite sides (p > 0.140), attributed to the

336

relatively low stress levels in opposite wood and the detection limit of the Raman method.

337 338

Figure 8 Raman band positions of three leaning E. bosistoana trees before (open boxes) and after

339

(filled boxes) releasing growth stress. Positive strain values stand for tensile strain (contraction)

340

and negative values for compressive strain (expansion). “Side T” represents tension wood and

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“Side O” opposite wood.

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The variation in the Raman band positions was greater between the samples than within the

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samples. The reasons are not fully understood, but could be related to the variation of chemical

344

composition 63 and anatomical structures 55 at the millimeter scale. The variation between

345

samples is a challenge for the prediction of growth strain based on Raman band positions.

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3.4 Correlation of growth strain to the position of the 1095 cm@ Raman band



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Methods to measure growth strain in trees, including the Nicholson technique 24, the CIRAD-

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Forêt method 25 and the strain gauge method, had been reviewed by 64. The splitting test

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proposed by 26 estimates growth strain of the stem based on the opening at the ends after splitting

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the sample along the pith. This estimation will be affected by the three-dimensional distribution

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of growth strain throughout the whole sample. In contrast, the other methods are a localized

352

measurement of surface growth strain. Although linear correlations were found between the

353

methods 26, 27, it is still challenging to build quantitative relationships between the different

354

methods 22.

355

As shown in Figure 9A, a strong linear relationship (r = 0.78) was found between the average

356

growth strain measured by strain gauges and the EGS using the splitting method. But the growth

357

strain measured by strain gauges was significantly lower compared to the EGS using the splitting

358

method. Additionally, the growth strain measured with the strain gauges at each side of the same

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stem differed by up to more than four times (data not shown), confirming asymmetric SGS

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around the stem 24.

361

The positions of the Raman band at around 1095 cm@ were moderately correlated (r = 0.48) with

362

growth strain measured using strain gauges (Figure 9B), but only a lower correlation (r = 0.27)

363

was found between the Raman band positions and the EGS (data not shown). This agreed with

364

the understanding that the Raman measurements reflected the localized molecular strain in the

365

stem and that this strain is variable throughout the stem 24.

366

The intercept of the linear fit was 1095.24 cm@ , consistent with the band position in the relaxed

367

state for green E. quadrangulata wood strips (Table 2). However, the slope of the linear fit was

368

@-: cm@ /%, more than twice the band shift rate of mechanically deformed samples (Table 2).


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369

This suggested that the growth strain measured by strain gauges were underestimated, while the

370

band shift rate based on EGS calculated from the splitting test was @ :$ cm@ /%, similar to

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those obtained by mechanical strain (Table 2). Similar discrepancies were reported between the

372

CIRAD-Forêt method and strain gauge measurements (Yoshida & Okuyama, 2002). The groove

373

depth and the distance to the strain gauge can affect the measured growth strain 27. The

374

surrounding wood tissue will impede the release of growth stresses 21. Additionally, according to

375

an X-ray diffraction study (Toba et al., 2013), molecular growth stress remained in a wood block

376

after being removed from the living stem. It is likely that not all growth stresses were released in

377

this experiment.

378 379

Figure 9 Relationship between growth strain measured by strain gauges and the estimated growth

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strain (EGS) by the splitting method (A) and the dependence of the Raman band at around 1095



381

cm@ on growth strain measured by strain gauges (B). Each band position was calculated as the

382

average of 9 Raman spectra collected on the wood surface at the location of the strain gauge.

383 384

While this study has shown that molecular strain causing surface growth strain in stems can be

385

detected with Raman spectroscopy, technological advances are needed for Raman spectroscopy

386

to become commercially feasible for non-destructive segregation of eucalyptus logs for solid

387

wood processing. The relatively low correlation (r = 0.48) in the present study implied that

388

estimations of growth strain by Raman spectroscopy will result in falsely rejected usable logs.

389

This might be acceptable for a pulp chip business, aiming to increase revenue by identifying top

390

logs suitable for solid wood production, but is likely to be uneconomic for high value solid wood

391

plantations, which will lose revenue by falsely rejecting quality logs. Technological challenges

392

like measurement time and the focusing procedure of the dispersive system renders industrial

393

applications inefficient. Furthermore, assuming a band shift rate of @ cm@ /%, 1000 >? only

394

induces a band shift of 0.3 cm@ , making it necessary to address factors like instrumental

395

uncertainties, sample surface conditions, fluorescence, as well as variations in wood properties

396

and growth strain 24, 25, 65. Better prediction of growth strain can be expected with a Raman

397

instrument that can cover a larger surface area and averaging out local variations in chemical

398

composition and growth strain.

399 400 401

4 CONCLUSION


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402

A partial least squares model based on pre-processed spectra was able to predict mechanical

403

strain with a root mean square error of 397.2 >? and R2 of 0.94. The major spectral changes

404

caused by mechanical strain were in the regions of 1500 to 850 cm@ and 500 to 280 cm@ . Apart

405

from the predominant band shift at 1095 cm@ , detailed analysis suggested that mechanical strain

406

also caused Raman band shifts at 1420, 1120, 895, 456 cm@ . The spectral changes could be

407

interpreted as the molecular deformation of the cellulose skeleton, HCO and HCC groups at C6

408

as well as COH structures. Further, studies with green wood indicated that the Raman band shift

409

rate with respect to strain was lower in never-dried green wood than previously dried rewetted

410

wood. The release of growth strain was successfully detected by Raman spectroscopy based on

411

the band positions at around 1095 cm@ . A moderate correlation was found between the band

412

positions at around 1095 cm@ and the growth strain measured by strain gauges, indicating that

413

the technology can potentially be used to segregate logs for solid wood production in certain

414

circumstances. However, improvements in Raman instrumentation, allowing more precise

415

measurements and spatial averaging, are needed.

416 417

AUTHOR INFORMATION

418

Corresponding Author

419

*New Zealand School of Forestry, University of Canterbury, Private Bag 4800, Christchurch,

420

New Zealand.

421

Tel: +64 33695949. Email: [email protected].

422

Author Contributions



423

The manuscript was written through contributions of both authors. FG conducted the

424

experiments and drafted the manuscript. CA provided guidance to the experimental design and

425

manuscript revision. All authors have given approval to the final version of the manuscript.

426

ACKNOWLEDGMENT

427

This work was financially supported by the Ministry of Business, Innovation and Employment,

428

New Zealand, through the Specialty Wood Products Partnership (FFRX1501). Nigel Pink and

429

Gert Hendriks (University of Canterbury) helped with the preparation of the wood samples.

430 431

REFERENCES

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159x80mm (600 x 600 DPI)


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Figure 1. Wood sample used for tensile tests while collecting Raman spectra. The grain (longitudinal direction) runs along the longest dimension of the sample. Dimensions are labelled in millimeters. 83x37mm (600 x 600 DPI)



Figure 2. Schematic drawing of the experimental setup for monitoring the release of growth strain by Raman spectroscopy on green stems. The dashed red lines indicate the grooves cut to release growth stress. T: tension wood side; O: opposite wood side. 85x37mm (600 x 600 DPI)


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Figure 3. Illustration of evaluating growth strain of green stems using Raman spectroscopy. In total, 18 spectra were collected from each sample. The dashed red line indicates the cut for the splitting test. 85x34mm (600 x 600 DPI)



Figure 4 Unmodified Raman spectra at 12 tensile strain levels of one rewetted E. regnans wood sample (A) and the corresponding band shifts of the 1095 cm−1 band (B). Inset (A) shows the band at 1095 cm−1 after SNV normalisation in the region of 1180 to 950 cm−1. “Strain 0” to “Strain 3” were represented with solid lines, “Strain 4” to “Strain 7” with dashed lines and “Strain 8” to “Strain 11” with dotted lines, each in the color sequence blue, red, pink and green. The band at 1095 cm−1 shifted 1.78 cm−1 to lower frequencies with a strain increase of 4702 µε. 169x67mm (600 x 600 DPI)


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Figure 5 Measured versus predicted tensile strain of rewetted E. regnans wood (A) and distribution of the residuals (B) for the PLS model based on baseline corrected and SNV normalized Raman spectra of the training data 219x92mm (600 x 600 DPI)



Figure 6 Regression coefficients (grey) of the PLS model based on baseline corrected and normalized Raman spectra and the average ‘slope’ spectrum (black) for 10 strained rewetted E. regnans wood samples in the region from 2300 to 200 cm−1. The dashed line shows a representative unmodified Raman spectrum of rewetted E. regnans wood. 85x85mm (600 x 600 DPI)


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Figure 7 Dependence of the position of the Raman band at around 1095 cm−1 on tensile strain for rewetted E. regnans (A) wood (n = 10) and green E. quadrangulata (B) wood (n = 8). Raman spectra were collected as mechanical strain increased stepwise from “Strain 0” (approx. 0 µε) to “Strain 11” (approx. 4500 µε) with a step of approx. 410 µε and then returned to the relaxed (RL) state. 85x103mm (600 x 600 DPI)



Figure 8 Raman band positions of three leaning E. bosistoana trees before (open boxes) and after (filled boxes) releasing growth stress. Positive strain values stand for tensile strain (contraction) and negative values for compressive strain (expansion). “Side T” represents tension wood and “Side O” opposite wood. 169x66mm (600 x 600 DPI)


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Figure 9 Relationship between growth strain measured by strain gauges and the estimated growth strain (EGS) by the splitting method (A) and the dependence of the Raman band at around 1095 cm−1 on growth strain measured by strain gauges (B). Each band position was calculated as the average of 9 Raman spectra collected on the wood surface at the location of the strain gauge. 85x103mm (600 x 600 DPI)


Measuring Molecular Strain in Rewetted and Never-Dried Eucalypt

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