# Using specimens from the CIRAD Kourou wood collection to build a database of properties

Jacques Beauchêne, Nadine Amusant, Jeremy Cigna, Soepe Koese, Bernard Thibaut

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Jacques Beauchêne, Nadine Amusant, Jeremy Cigna, Soepe Koese, Bernard Thibaut. Using specimens from the CIRAD Kourou wood collection to build a database of properties. Bois et Forêts des Tropiques, 2022, 352, pp.61-70. 10.19182/bft2022.352.a36936. hal-04459865

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# Using specimens from the CIRAD Kourou wood collection to build a database of properties

Jacques BEAUCHÊNE¹

Nadine AMUSANT¹

Jeremy CIGNA²

Soepe KOESE¹

Bernard THIBAUT³

¹CIRAD
UMR Écologie des Forêts de Guyane
(EcoFoG)
AgroParisTech, CNRS, INRA, Université
des Antilles, Université de Guyane
97310 Kourou
France

²Institut des Sciences du Végétal
91190 Gif-sur-Yvette
France

³Laboratoire de Mécanique et Génie Civil (LMGC)
CNRS, Université de Montpellier
34090 Montpellier
France

**Auteur correspondant /**
**Corresponding author:**
Jacques BEAUCHÊNE -
jacques.beauchene@cirad.fr

<figure><img src="image_2.png" /><figcaption>**Photo 1.**
The 445 samples used to measure the modulus and the damping coefficient. The manufacturing of custom-made storage racks limits the risk of error and optimizes handling of the samples.
Photo J. Beauchêne.</figcaption></figure>

**Doi:** 10.19182/bft2022.351.a36936 - Droit d'auteur © 2022, Bois et Forêts des Tropiques - © Cirad - Date de soumission : 10 novembre 2020 ; date d'acceptation : 17 novembre 2021 ; date de publication : 1er mai 2022.

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cirad

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Licence Creative Commons :
Attribution - 4.0 International.
Attribution-4.0 International (CC BY 4.0)

**Citer l'article / To cite the article**
Beauchêne J., Amusant N., Cigna J., Koese S., Thibaut B., 2022. Using specimens from the CIRAD Kourou wood collection to build a database of properties. Bois et Forêts des Tropiques, 352: 61-70. Doi: https://doi.org/10.19182/bft2022.352.a36936
RÉSUMÉ

Création d'une base de données sur les
propriétés des bois à partir de spécimens
de la collection Kourou du Cirad

Un xylarium, comme celui de Kourou en
Guyane française, est une collection unique
de spécimens de bois rassemblés sur de
nombreuses années et représentant une
grande diversité interspecifique. Outre l'uti-
lisation classique de telles collections pour
l'anatomie systématique, elles peuvent
servir à créer une base de données tech-
nologique en utilisant des échantillons
supplémentaires prélevés sur le même
arbre comme spécimens de référence. Des
tests physiques, mécaniques et de dura-
bilité ont été réalisés sur des planches de
10 × 60 × 100 mm³ (L étant la dimension
la plus longue, la largeur et l'épaisseur
étant les dimensions transversales mais
pas toujours parfaitement radiales ou
tangentielles) représentant 445 essences
ligneuses appartenant à 63 familles pré-
sentes en Guyane française. Les densités
des bois varient de 250 à 1 300 kg/m³, avec
une moyenne de 786 kg/m³. Les valeurs
des autres propriétés sont également très
variables, tout comme le module d'élasticité
longitudinal (de 0,6 à 37 GPa), des échantil-
lons très rigides, des lianas et des stipes de
palmiers ayant également été testés. Les
correlations entre les différents paramètres
mesurés sur les 445 essences testées nous
ont permis d'identifier plusieurs relations
entre les propriétés du bois, par exemple :
les bois clairs sont moins sujets au retrait,
mais plus sujets à la pourriture (l'inverse
est vrai pour les bois rouges) ; les bois à
faible coefficient d'amortissement sont
généralement plus foncés, plus rouges,
plus denses et plus résistants à la pourri-
ture. Cette base de données ne peut pas
être utilisée pour caractériser une essence
particulière puisqu'un spécimen seulement
est disponible pour chacune, mais elle peut
être utilisée pour étudier les relations entre
des propriétés et des descripteurs facile-
ment mesurables liés à la structure du bois
(densité ou module, par exemple) ou à la
chimie du bois (couleur, durabilité...). Enfin,
cette base de données fournit les bases
pour de futures banques de données plus
importantes comprenant beaucoup plus de
spécimens de chaque essence, utiles pour
rechercher des propriétés particulières
au sein de certaines familles ou certains
genres, comme une durabilité naturelle
élevée malgré une densité du bois plutôt
faible, ou un coefficient d'amortissement
faible accompagné d'un module spécifique
élevé.

Mots-clés : xylarium, propriétés des bois,
bois tropicaux, Guyane française.

ABSTRACT

Using specimens from the CIRAD Kourou
wood collection to build a database
of properties

A Xylarium, like the one in Kourou in French
Guiana, is a unique collection of wood
specimens gathered over many years that
represents high interspecific diversity. In
addition to the standard use of such col-
lections for systematic anatomy, a tech-
nological database can be created using
supplementary specimens taken from the
same tree as the reference specimens.
Physical, mechanical and durability tests
were performed on wood planks measuring
10 × 60 × 100 mm³ (L is the longest direc-
tion, width and thickness are not always
perfectly radial or tangential, just trans-
verse) representing 445 woody species
belonging to 63 families found in French
Guiana. Wood densities ranged from 250 to
1,300 kg/m³, with an average of 786 kg/m³
The other properties also covered a wide
range of values, as did the longitudinal
modulus of elasticity (ranging from 0.6 to
37 GPa), as samples from lianas, palm sti-
pes and very stiff woods were also tested.
The correlations between the different
parameters measured on the 445 species
tested allowed us to identify some rela-
tionships between wood properties, e.g.:
(i) light colored woods are less prone to
shrinkage, but more prone to rot (the oppo-
site is true for red woods); (ii) woods with a
low damping coefficient are generally dar-
ker, redder, denser, and more resistant to
rot. This database cannot be used to cha-
acterize a particular species as only one
specimen is available for each species, but
it can be used to study the relationships
between properties and easily measured
descriptors related to wood structure (e.g.
density, modulus) or wood chemistry (e.g.
color, durability). Finally, this database
provides the foundation for future bigger
databases including many more specimens
of each species that will be useful to search
for particular properties in certain families
or genera, for example, high natural durabi-
lity despite rather low wood density, or low
damping along with a high specific modu-
lus.

Keywords: wood collection,
wood proprieties, tropical wood,
French Guiana

RESUMEN

Utilización de ejemplares de la colección
de madera del CIRAD Kourou
para constituir una base de datos
sobre las propiedades de la madera

El Xylarium de Kourou en Guayana Francesa es una colección única de muestras de madera reunidas a lo largo de muchos años, que representa una gran diversidad de especies. Además del uso estándar de estas colecciones para la anatomía sistemática, se puede crear una base de datos tecnológica utilizando muestras adicionales tomas del mismo árbol como muestras de referencia. Se realizaron pruebas físicas, mecánicas y de durabilidad en tablones de 10 × 60 × 100 mm³ (L es la dimensión más larga, la anchura y el grosor son las dimensiones transversales, aunque no siempre perfectamente radiales o tangenciales). Estos tablones provienen de 445 especies leñosas pertenecientes a 63 familias encontradas en la Guayana Francesa. Las densidades de la madera oscilaron entre 250 y 1 300 kg/m³, con una media de 786 kg/m³. Los valores de las demás propiedades también variaron mucho, al igual que el módulo de elasticidad longitudinal (de 0,6 a 37 GPa), ya que también se probaron muestras muy rígidas, lianas y estipes de palmeras. A partir de las correlaciones entre los diferentes parámetros medidos en las 445 especies analizadas, identificamos diferentes relaciones entre las propiedades de la madera, por ejemplo: (i) las maderas de color claro son menos propensas a la contracción, pero más propensas a la putrefacción (lo contrario es cierto para las maderas rojas); (ii) las maderas con un bajo coeficiente de amortiguación son generalmente más oscuras, más rojas, más densas y más resistentes a la putrefacción. Esta base de datos no puede utilizarse para caracterizar una especie concreta, ya que sólo se dispone de un ejemplar para cada especie, pero puede utilizarse para estudiar las relaciones entre las propiedades y los descriptores fácilmente medibles relacionados con la estructura de la madera (por ejemplo, densidad y módulo) o la química de la madera (por ejemplo, color y durabilidad). Por último, esta base de datos proporciona fundamentos para futuras bases de datos más amplias que incluyan muchos más ejemplares de cada especie, lo que será útil para buscar propiedades particulares en ciertas familias o géneros, como una alta durabilidad natural a pesar de una densidad de la madera más bien baja, o una baja amortiguación junto con un alto módulo específico.

Palabras clave: colección de madera, propiedades de la madera, madera tropical, Guayana Francesa.
## Introduction

The CIRAD wood collection named 'Xylarium', in Kourou, French Guiana, consists of an anatomical reference collection with a CTFT (Centre technique forestier tropical, Technical Centre for Tropical Forests, the former name of CIRAD's forestry activities) identifier for each different tree. It is an extension of the main CIRAD wood collection kept in Montpellier, France (Langbour et al., 2019). The Kourou Xylarium is devoted to local species, with links to the Cayenne (another town, Prefecture of French Guiana) herbarium<fnref n="1" />. A collection of duplicate specimens taken from the same tree (i.e. with the same CTFT ID) was added to be used for other studies including destructive tests. This duplicate collection comprises 4,285 duplicates from 1,449 trees (references or accessions) belonging to 505 species, 240 genera, and 75 families. It was collected between 1977 and 2005. We selected the best shaped wooden plates to sample 445 species.

A long-term testing procedure was undertaken throughout the 20th century on many tropical species (around one thousand of the eight thousand referenced in the CIRAD wood collection). Among them, some Guianese species have already been tested: the chemical composition of 47 species was tested (Gérard et al., 2019), fungal rot resistance against different fungi in 71 species was tested, and the physical and mechanical properties of 124 species were tested (to be published). Measuring 445 species represents enormous progress even though it only represents one fourth of the list of 1,600 Guianese tree taxa (Molino et al., 2009).

Xylarium wood collections are also long-term records of biological activity and tree function, particular weather conditions, or catastrophic events that occurred in the past (Beeckman, 2003). Xylarium collections are used as reference tools for species identification of woody plants, or dendrochronology from annual increments and more recently, for their biochemical or isotopic memory (Cornish et al., 2013). However, apart from wood density (Maniatis et al., 2011; Langbour et al., 2019), which is sometimes available in these collections, they have only very recently been used to collect other technological data (Deklerck et al., 2019, 2020). As the use of duplicates to take measurements with the aim of creating a large database of wood properties is being promoted as a future use for wood collections (Langbour et al., 2019), we tested the opportunity using the Kourou Xylarium duplicates.

## Material

A total of 445 duplicate specimens originating from 445 species (one specimen per species), 213 genera and 63 families were tested. The samples were air dried wood specimens measuring 130 × 10 × 60 mm³ (L is the longest direction, width and thickness are not always perfec-

tly radial or tangential, just transverse). All the samples had been stored in the collection cabinet for more than 10 years. Mean stabilized moisture content was 11.3%. Only specimens of heartwood were used. First, each specimen was sanded on one side to measure fresh color. However, the color revealed by sanding is not necessarily the color of fresh wood, as some specimens underwent slow in-depth oxidation of secondary metabolites during storage.

Next, the specimen was cut into pieces for different uses (figure 1): 130 × 2 × 10 mm³ for mechanical tests, 100 × 5 × 10 mm³ for decay tests, 30 × 5 × 10 mm³ for shrinkage tests, 20 × 10 × 10 mm³ to measure moisture content and further chemical analysis.

<figure><img src="image_7.png" /><figcaption>**Figure 1.**
Specimens cut from a single anatomical plate.
MC: 20 × 10 × 10 mm³ specimen for the measurement of moisture content. Ch: 20 × 10 × 10 mm³ specimen destined for different chemical measurements (not made in the present study). S: 30 × 5 × 10 mm³ specimen to measure shrinkage. D: 100 × 5 × 10 mm³ specimen to measure natural durability. VT: 130 × 2 × 10 mm³ specimen for vibratory tests.</figcaption></figure>

## Methods

### Measurement of color

Measurements were taken at three different representative locations on the surface of the specimen (the orientation was generally slab board or alternate quarter) using a Minolta colorimeter (Spectrophotometer 2500d). The illuminant D65 and the 10° standard observer were used as measurement standards. The surface area observed was 59 mm² (small opening of 8.7 mm) and the spectral reflection setting was excluded. Reflectance data were collected at 10 nm intervals over the visible spectrum (from 400 to 700 nm). The data are expressed in the CIE L*a*b* color space (Nishino et al., 1998) defined by the

<footnote n="1">¹ https://herbier-guyane.ird.fr</footnote>
International Commission on Illumination (CIE). The colorimetric parameters correspond to:

* L*: clarity, black = 0 and white = 100;

* a*: red (positive) and green (negative) components;

* b*: yellow (positive) and blue (negative) components.

The hue angle $H = atan(b/a*)$ was also calculated.

## Density and volumetric shrinkage

The three samples (20 × 5 × 9 mm³) were used for each reference. The sample was a rectangular parallelepiped whose three perpendicular dimensions were measured with a comparator (precision: 1 µm) of Mitutoyo brand, which made it possible to calculate the volume (V). The mass (M) was measured with a Sartorius precision balance (precision: 0.0002 mg):

* corresponding to the standard conditions in the cabinet (dry wood close to 12% moisture content, $M_{12}$ and $V_{12}$);

* fully saturated ($M_s$ and $V_s$);

* in the anhydrous state, after reaching equilibrium in an oven heated at 103 °C ($M_a$ and $V_a$).

Different values can be calculated for wood density:

* dry density $D_{12} = M_{12}/V_{12}$;

* anhydrous density $D_a = M_a/V_a$;

* saturated density; $D_s = M_s/V_s$;

* basic density $BD = M_a/V_s$;

* conversion factor (Vieilledent et al., 2018) for basic density from air dry density: $CF = BD/D_{12}$.

Total volumetric shrinkage (VS) is calculated using the formula: $VS = (V_s - V_a)/V_s$.

## Mechanical measurements

The three samples (120 × 2 × 9 mm³) were used for each reference. A vibratory test was used with non-contact forced vibrations of free-free beams placed on elastic supports positioned at the two nodes of the first mode (Brémaud et al., 2012). Dimensions (m), mass (kg), resonant frequency (Hz) and damping coefficient ($\tan\delta$)<fnref n="2" /> at the resonant frequency were measured in this test. Using mass and dimension, the density (kg/m³) of the specimen (ρ) was calculated as mass/volume ratio. The specific modulus (SM in m<fnref n="2" />/s<fnref n="2" />) was calculated using Bernoulli's equation (Brémaud et al., 2012). SM is both the square value of sound speed in the longitudinal direction in the wood and the ratio of the longitudinal modulus of elasticity (E) to the density: $SM = E/\rho$. The modulus of elasticity was calculated using the formula: $E = \rho * SM$.

There is a strong physical relationship between specific modulus (SM) and damping coefficient ($\tan\delta$) of mean standard wood (the wood is presumed to be free of extractives) (Brémaud et al., 2012, 2013) due to the microstructure of the cell wall (mainly micro-fibril angle): $\tan\delta = 10^A * SM^B$, where A = 1.23 and B = 0.68.

If the damping coefficient differs from the standard value ($\tan\delta_s$) calculated from the specific modulus value, there is a relative deviation from standard damping ($DS\delta = (\tan\delta - \tan\delta_s)/\tan\delta$), mainly due to the chemical composition of the cell wall (Brémaud et al., 2012, 2013). This deviation was calculated for all the specimens.

## Decay resistance

The test protocol for measuring the natural durability of wood is based on the European standard XP CEN / TS 15083-2 and the American standard AWPA E14-07 (Van Acker et al., 2003; Amusant et al., 2014). The test protocol consists in estimating the lifetime of thin specimens in contact with a forest floor, in our case, collected from the Paracou experimental forest in French Guiana (Gourlet-Fleury et al., 2004). Five samples ($R \times T \times L = 10 \times 5 \times 90 \text{ mm}^3$) were taken from each anatomical plate, representing one repetition per month over the five-month experiment. Each specimen was first dried for 48 hours at 103 °C, then weighed and planted vertically in the soil with 80% of its length immersed in the wet soil. These specimens were interspersed with standard *Virola michelii* reference test specimens evenly distributed in the bins. Each month, one specimen per individual, as well as a control specimen, were taken, dried at 103 °C for 48 hours, and weighed giving the mass loss (ML) of each test piece. The ML of a species at month 6 was estimated from the median value of the slope adjusted over the first 5 months.

<figure><img src="image_8.png" /><figcaption>**Figure 2.** Relationship between damping and specific modulus. Red circles, actual value: experimental results for both damping coefficient and specific modulus. Black curve, standard value: damping coefficient values calculated from experimental specific modulus.</figcaption></figure>

<footnote n="2">² The damping coefficient (or loss factor, $\tan\delta$) is determined, in the time domain, through the logarithmic decrement ($\lambda = \pi * \tan\delta$) of amplitudes, after stopping excitation, which is fixed at resonant frequency Fr.</footnote>
<figure><img src="image_9.png" /><figcaption>**Figure 3.** Histograms of density and coefficient factor. The red curve represents the best fitting normal distribution of the values (for a better readability the units of D12 are expressed in kg/m³).</figcaption></figure>

## Data base and statistical methods

Basic statistical analyses were performed using XLSTAT software. The data description table includes the number of specimens, minimum, maximum, 1st quartile, median, 3rd quartile and mean (with its standard deviation) values for each parameter, as well as the coefficient of variation (CV). Skew (Pearson) and kurtosis (Pearson) of the distribution were already available in the dataset (Beauchêne et al., 2021). A box plot is also included for each parameter. The box plot shows the quartiles (the band inside the box is the median). The whiskers in the box plot represent the lowest data item still within the 1.5 IQR (inter quartile range) of the lower quartile, and the highest data item still within the 1.5 IQR of the upper quartile.

For the histograms, the amplitude of each parameter was chosen to provide a clear description of the data. The normality of the distribution was checked using a Shapiro-Wilk test. Pearson type correlation analysis was used for normal distribution, and Spearman's tests for non-normal distribution.

## Results

### Distribution of the values

Figure 2 shows that the best fitting relationship between damping coefficient (tanδ) and specific modulus (SM) is very close to the standard curve. The tanδ values are distributed on the two sides of the standard curve, as already shown in another study (Brémaud et al., 2012).

At 12% moisture content, there was a wide range of densities (250-1,300 kg/m³) typical of tropical woods (Langbour et al., 2019). There was a small shift towards high density values that could be due to the selection of specimens used in the present study, but the mean density value (786 kg/m³) of the 1,694 specimens from French Guiana is almost identical to the mean density value of the Cirad wood collection as a whole (784 kg/m³). In contrast, the

range of coefficient factors (Basic Density/Density at 12% moisture content) was very narrow (figure 3), basic density and density at 12% moisture content were proportional, with a very high coefficient of determination (R² = 0.98). The mean CF (0.816) was very close to the CF in the data base containing physical data for 872 species (0.828, in Vieillard et al., 2018). The statistical tests proved that none of these distributions were normal, so Spearman's test was used for correlation analysis.

The distributions of the different parameters are shown as box plots in figure 4. It should be noted that there are some very low values for SM (below 5 Mm²/s²) not found in usual wood measurements (severe compression wood can go down to 5 Mm²/s²). These very low values are those of liana wood (Rowe and Speck, 2005; Köhler et al., 2000) and juvenile palm xylem (the mature palm xylem measured in this study had the usual values), making the range of elastic modulus (E) wider than usual. Anyway, except for CF (CV = 4%) there was always a wide range of values for all parameters with CV greater than 25% except for L* (18%) and Hue (13%).

The species shown in figure 5 were chosen as representative of the range of color margins in the color space: dark or light species (*Swartzia leblondii*, *Solanum leucocarpon*), high or small hue angle (*Peltogyne venosa*, *Pachira dolichocalyx*), red woods (*Guarea guidonia*, *Aspidosperma sandwithianum*), orange or dark brown woods (*Chrysophyllum pomiferum*, *Vouacapoua americana*). As reported by Nishino et al. (1998), all the color values are positioned in only one quadrant in the a*b* plane (the red/yellow) quadrant (figure 5). Black wood (ebony style) like *Swartzia leblondii* had nearly zero values for a* and b*, i.e. very dark grey. Lighter woods all had rather high values for b*, pale yellow, but not pale grey. Red woods had almost the same value for a* (red) and b* (yellow). They appear as red instead of orange because the b* values are often much higher than a* values. Strictly speaking, Purpleheart wood is the only dark red wood, but is perceived as purple, even though the b* value is slightly positive on the yellow axis (b* = 3.2).
## Correlation analysis

The statistical tests proved that none of these distributions were normal, so a Spearman's test was used for correlation analysis (table I).

Many correlation coefficients (R) were significant at the 0.1% level, but due to the large number of data, the lowest significant R was associated with a low (3%) coefficient of determination (R²).

Considering the color parameters, L* and hue were very strongly correlated so considering L* alone seems to be efficient (similar but better correlation coefficients with other parameters for L*). The correlations between L* and b* were strong and positive but negative between L* and a*. Light colored woods were rather yellow while dark colored woods were rather red. The link between a* and b* was rather weak and b* was not significantly correlated with any other parameters (except L*). Rather strong links were observed between L* or a* (but with opposite signs) and density, volumetric shrinkage, and mass loss. Light colored woods were less dense, less prone to shrinkage but more prone to rot (the reverse was found for red woods).

Density and specific modulus can be considered as independent parameters. SM was only strongly linked with modulus of elasticity (positive), damping coefficient (negative) and shrinkage (positive). Density (both BD and D12) was strongly linked with all parameters except b*, SM and CF. Dense woods had a lower damping coefficient or

mass loss but higher modulus or shrinkage. It is interesting to note that specific modulus and density, which are independent, had almost equally strong links with the same sign as modulus of elasticity, damping coefficient and shrinkage.

Deviation from the standard damping coefficient (DSδ) was quite closely linked with color (L* and a*), density, and mass loss. Woods with a lower damping coefficient than the standard were darker, redder, denser and more resistant to rot.

Nearly 50% of the coefficients of variation (CF = BD/D12) were due to variations in volumetric shrinkage. The latter is a useful parameter that can easily be measured at the same time as basic density if a more precise CF is needed.

## Discussion

Using a single wooden plate provided an initial overview but is not sufficient for the characterization of species, for which more duplicates sampled from different trees and from different positions in the tree are needed. Nevertheless, measuring different parameters and properties on the same material in a wide range of species is extremely useful to study the relationships between structural and chemical parameters and wood properties. It is also useful to screen for particular properties required for a specific use. For example, high natural durability represented by low mass loss values due to fungal degradation are good indicators of

presence of protective compounds such as antifungals, insecticides, or antioxidants (Amusant et al., 2014).

There are two successive levels of wood structure with specific mechanical behavior (i) the anatomical level, where wood is a cellular material, like honeycomb, (ii) the cell wall level, which is a fiber composite (Thibaut et al., 2001).

Cellular materials like honeycombs display extremely high anisotropy between in plane and out of plane directions (Gibson and Ashby, 1997) and properties consequently need to be defined with reference to the direction of the test. The key parameter for physical and mechanical properties is the volume proportion (α) of solid matter included in the cell wall. Wood mass depends on this proportion according to the relation M = α * V * ρ<sub>m</sub> where V is the global volume of the material, and ρ<sub>m</sub> is the density of cell wall matter (around 1,500 kg/m³). The wood density value: ρ = M/V = α* ρ<sub>m</sub> is directly proportional to α, so wood density is a key descriptor for wood as a cellular material.

<figure><img src="image_10.png" /><figcaption>**Figure 4.** Distribution (Tukey box plots) of the properties measured in 445 species. Box plot quartiles (the band inside the box is the median). Whiskers plot the lowest datum still within 1.5 IQR (inter quartile range) of the lower quartile, and the highest datum still within 1.5 IQR of the upper quartile. Black dots are outliers. L*: clarity coefficient; a*: red/green coefficient; b*: yellow/blue coefficient; Hue angle: angle of the color projection in the a*/b* plane; BD: basic density (kg/dm3); D12: density at level 12% moisture content; CF: conversion factor between density at 12% moisture content and basic density; VS: volumetric shrinkage (%); SM: specific modulus (Mm²/s²); E: longitudinal modulus of elasticity (GPa); tanδ: damping coefficient (%); DSδ: relative deviation from standard damping; ML: mass loss in the soil bed test (%).</figcaption></figure>
Table I.

Spearman's correlation coefficients. Characters in bold: significant correlation at the 0.1% level with R² > 5%. Characters in italics: significant correlation at the 0.1% level with R² < 5%. L*: clarity coefficient; a*: red/green coefficient; b*: yellow/blue coefficient; Hue angle: angle of the color projection in the a*/b* plane; BD: basic density (kg/dm3); D12: density at level 12% moisture content; CF: conversion factor between density at 12% moisture content and basic density; VS: volumetric shrinkage (%); SM: specific modulus (Mm²/s²); E: longitudinal modulus of elasticity (GPa); tanδ: damping coefficient (%); DSδ: relative deviation from standard damping; ML: mass loss in the soil bed test (%).

<table><thead><tr><th>Variables</th><th>L*</th><th>a*</th><th>b*</th><th>Hue</th><th>BD</th><th>D12</th><th>CF</th><th>VS</th><th>SM</th><th>E</th><th>Tanδ</th><th>DSδ</th><th>ML</th></tr></thead><tbody><tr><td>L*</td><td>1</td><td>-0.514</td><td>0.480</td><td>0.814</td><td>-0.593</td><td>-0.578</td><td>-0.017</td><td>-0.266</td><td>0.115</td><td>-0.341</td><td>0.208</td><td>0.320</td><td>0.526</td></tr><tr><td>a*</td><td>-0.514</td><td>1</td><td>0.175</td><td>-0.726</td><td>0.452</td><td>0.437</td><td>0.002</td><td>0.255</td><td>-0.035</td><td>0.284</td><td>-0.197</td><td>-0.266</td><td>-0.417</td></tr><tr><td>b*</td><td>0.480</td><td>0.175</td><td>1</td><td>0.484</td><td>-0.134</td><td>-0.134</td><td>0.016</td><td>-0.042</td><td>0.050</td><td>-0.054</td><td>-0.011</td><td>0.012</td><td>0.040</td></tr><tr><td>Hue</td><td>0.814</td><td>-0.726</td><td>0.484</td><td>1</td><td>-0.515</td><td>-0.501</td><td>-0.018</td><td>-0.255</td><td>0.077</td><td>-0.304</td><td>0.176</td><td>0.254</td><td>0.434</td></tr><tr><td>BD</td><td>-0.593</td><td>0.452</td><td>-0.134</td><td>-0.515</td><td>1</td><td>0.992</td><td>-0.169</td><td>0.542</td><td>0.129</td><td>0.760</td><td>-0.379</td><td>-0.293</td><td>-0.644</td></tr><tr><td>D12</td><td>-0.578</td><td>0.437</td><td>-0.134</td><td>-0.501</td><td>0.992</td><td>1</td><td>-0.272</td><td>0.604</td><td>0.155</td><td>0.781</td><td>-0.359</td><td>-0.257</td><td>-0.604</td></tr><tr><td>CF</td><td>-0.017</td><td>0.002</td><td>0.016</td><td>-0.018</td><td>-0.169</td><td>-0.272</td><td>1</td><td>-0.678</td><td>-0.256</td><td>-0.351</td><td>-0.066</td><td>-0.219</td><td>-0.192</td></tr><tr><td>VS</td><td>-0.266</td><td>0.255</td><td>-0.042</td><td>-0.255</td><td>0.542</td><td>0.604</td><td>-0.678</td><td>1</td><td>0.445</td><td>0.668</td><td>-0.234</td><td>0.024</td><td>-0.187</td></tr><tr><td>SM</td><td>0.115</td><td>-0.035</td><td>0.050</td><td>0.077</td><td>0.129</td><td>0.155</td><td>-0.256</td><td>0.445</td><td>1</td><td>0.689</td><td>-0.563</td><td>0.048</td><td>-0.070</td></tr><tr><td>E</td><td>-0.341</td><td>0.284</td><td>-0.054</td><td>-0.304</td><td>0.760</td><td>0.781</td><td>-0.351</td><td>0.668</td><td>0.689</td><td>1</td><td>-0.587</td><td>-0.156</td><td>-0.468</td></tr><tr><td>Tanδ</td><td>0.208</td><td>-0.197</td><td>-0.011</td><td>0.176</td><td>-0.379</td><td>-0.359</td><td>-0.066</td><td>-0.234</td><td>-0.563</td><td>-0.587</td><td>1</td><td>0.735</td><td>0.397</td></tr><tr><td>DSδ</td><td>0.320</td><td>-0.266</td><td>0.012</td><td>0.254</td><td>-0.293</td><td>-0.257</td><td>-0.219</td><td>0.024</td><td>0.048</td><td>-0.156</td><td>0.735</td><td>1</td><td>0.373</td></tr><tr><td>ML</td><td>0.526</td><td>-0.417</td><td>0.040</td><td>0.434</td><td>-0.644</td><td>-0.604</td><td>-0.192</td><td>-0.187</td><td>-0.070</td><td>-0.468</td><td>0.397</td><td>0.373</td><td>1</td></tr></tbody></table>

In contrast to most man-made honeycombs, wood cell walls are not isotropic, homogeneous material. Like other complex fiber composite materials, the cell wall has two main components: crystalline nano-cellulose fibers (NCF) with a very high modulus of elasticity (MOE) embedded in a more or less homogeneous matrix with a much lower MOE (Déjardin et al., 2010; Gibson, 2012). The properties of the material comprising the cell wall depend on the proportion and orientation of NCF on the one hand (Donaldson, 2008), and on the chemical composition of the matrix on the other. Most of the mass in the secondary wall (which is responsible for nearly all wood properties) is concentrated in the S₂ layer, usually with small NCF angles (5° to 25°) relative to the main cell direction, while the S₁ layer is much thinner with high NCF angles (70° to 80°) relative to the main cell direction. Because the S₂ layer is responsible for a very large proportion of properties in the cell direction, the cell wall material is termed S₂ and the S₂ NCF angle is termed micro-fibril angle (MFA) as if it were the only active angle of the fiber

<figure><img src="image_11.png" /><figcaption>Figure 5.</figcaption></figure>

Examples of the wide range of colors of the species tested.
composite. In fact, the S<sub>2</sub> layer can play a significant role
in transverse properties like shrinkage, if its proportion of
mass is not too low, as is the case in thin walled fibers.

Variation in cellulose content between species is
rather low with a coefficient of variation (CV) of only 10%
whereas the CV for density is around 30% (Gérard *et al.*,
2019), and the density of the cell wall is nearly constant,
so MFA is the key factor for the longitudinal MOE (E<sub>m</sub>) of
the matter forming the wood cells (Cave, 1969). Like wood
density, wood MOE (E) is proportional to cell wall MOE (E<sub>m</sub>)
through the relation E = α * E<sub>m</sub>

Thus, whatever the density, E/ρ = E<sub>m</sub>/ρ<sub>m</sub> and
E<sub>m</sub> = ρ<sub>m</sub> * E/ρ. Cell wall density (ρ<sub>m</sub>) is constant, so the
cell wall MOE, a key property of the material, is always
proportional to the specific modulus (SM = E/ρ) and the
SM is a simple key parameter of the mechanical behavior
of the cell wall, like density (ρ) is a key parameter of the
behavior of honeycomb, and these parameters should be
independent, as was the case in the present study. MOE
is the product SM * ρ, so by construction, wood MOE is
fully described by density and SM, and here, SM variations
explained nearly as much variation in MOE as density
(R<sup>2</sup> = 48% and 58% respectively).

For volumetric shrinkage, the situation is similar,
variations in Density and SM explain most variations in
shrinkage (R² = 30% and 20% respectively). However, the
relationship between shrinkage and density is not simple.
Making holes in metal does not change its dilatation factor
following a change in temperature. As the direct expres-
sion of the proportion of solid matter, wood density is
closely linked to the ratio of cell wall thickness to fiber
diameter. Fiber diameter is determined by lignification
of the primary wall, whereas cell wall thickness is mainly
linked to the secondary wall where the S₂ layer is gene-
rally far thicker than the S₁ layer (Déjardin et al., 2010; Bor-
rega et al., 2015). Crystalline fiber reinforcement is longi-
tudinal in S₂ whereas it is transversal in S₁. Shrinkage in
S2 is linked to MFA, which is very low in the longitudinal
direction but increases with the MFA value, which is high in
transverse directions but decreases with an increase in the
MFA. Due to its lack of thickness and fiber orientation, S1
has no influence on longitudinal shrinkage but may reduce
transverse shrinkage if S2 is not too thick. Consequently,
low density means transverse shrinkage will be low (and
volumetric shrinkage will also automatically be low)
because the S1 layer represents a higher proportion in the
secondary wall. Models of the MOE of wood mechanical
behavior (Yamamoto and Kojima, 2002; Qing and Mishnae-
vsky, 2009), and of shrinkage (Yamamoto et al., 2001) show
the causal relationship between these properties and
structural parameters as α (proportion of matter in the
cellular solid) and MFA (anisotropy of the fiber composite
material). But only half the variations are linked to these
two structural parameters. The chemical composition of
the cell wall matrix would thus also be expected to have a
major influence.

As predicted by models (Brémaud et al., 2010, 2013),
vibration damping was linked to MFA like SM, and the cor-
relation between tanδ and SM was significant at the 0.1%

level and was rather high (R² = 30%) and tends to explain
only one third of damping variations. Here again, matrix
chemistry would be expected to play an important role.

The two basic chemical components of the matrix
are (i) the main wall polymers such as hemicelluloses and
lignin, (ii) extraneous components such as extractives and
minerals. Extractives and lignin are known to be linked to
color (Baar et al., 2014; Gierlinger et al., 2004; Mayer et al.,
2006), shrinkage (Bossu et al., 2016; Leonardon et al., 2010;
Royer et al., 2010), mass loss (Rodrigues et al., 2012; Sun-
dararaj et al., 2015) and relative deviation from standard
damping (Minato et al., 2010; Brémaud et al., 2011, 2013) in
a rather complex causal way (each molecule in the extrac-
tion cocktail can have a positive or negative influence on
these properties). This common influence could explain
the significant correlations between all these properties.

Mass loss was rather closely correlated with white-
ness L* (R² = 27%) and reddish color a* (R² = 18%). This
means that darker or redder woods tend to be more resis-
tant to rot (Amusant et al., 2004; Moya and Berrocal, 2010).
To understand this correlation, we need to identify which
molecules are involved in darker or redder colors and to
test them against fungi.

Strictly speaking, there is no clear causal connection
between properties like color or mass loss and density.
Drilling small holes in a material does not change its color
and the small diameter of fungal hyphae enable them to
penetrate denser woods. Moreover, some very dense white
woods (mostly sapwoods) have been shown to be highly
sensitive to rot. However, the presence of reserve material
in the heartwood that has not been fully mobilized may
make the wood more attractive to the fungus (Magel et al.,
2000; Niamké et al., 2010). In the present study, very signif-
icant correlations (at the 0.1% level) were found between
density and color parameters L* and a* (R² = 34% and
21%, respectively) as well as mass loss (R² = 42%). Such
correlations have also been observed in other studies
(Nishino et al., 2000) and tropical woods are often consi-
dered to be dense, dark (or red) and resistant to fungi.
In the CIRAD wood collection (Langbour et al., 2019), the
mean density of tropical American woods (750 kg/m³) is
higher than that of temperate woods (660 kg/m³), but their
density range is wider: 240 to 1,320 kg/m³ for temperate
woods (in all regions of the Northern Hemisphere where
the climate includes periods of frost) and 100 to 1,340 kg/
m³ for tropical American woods.

It is highly probable that as yet unidentified parame-
ters have a strong influence on both extractives and on the
difference in density between species, in other words, long
living trees growing in hazardous conditions in terms of
wood predators (fungi, termites or *Cerambycidae*) should
have both high densities for hydraulic or mechanical rea-
sons (Hacke et al., 2001), and efficient extractives for wood
durability (Kraft et al., 2010; Aubry-Kientz et al., 2013). The
extractives give the wood a dark reddish color. Thus, the
observed strong correlations may be the consequence of
adaptive evolution rather than of the direct influence of
density on color or durability.
Conclusion

A data base of basic wood properties like density, color, MOE and acoustic damping, rot resistance, could be built using duplicate specimens taken from the CIRAD Xylarium wood collection in Kourou. Using the same process for the main CIRAD Xylarium in Montpellier would allow an enormous increase in data on different wood properties of many species in the world, without the need for additional sampling in the world's forests.

All the measurements were made on the same speci-
men, making it easy to correlate properties within a species.
This opens the way for the prediction of unknown properties
of a given species from easy to measure descriptors related
to wood structure (density, grain angle, sound of speed) or
wood chemistry (color, near infrared spectrometry).

In the present study, samples were cut individually
in order to study the chemical composition of each speci-
men, particularly the extractives. This involves a tremen-
dous amount of work with dedicated high flow techniques,
which was not possible in the present study. Nevertheless,
such studies are important for the future, both to build data
bases of species chemical signatures (species identifica-
tion) and to increase the number of descriptions of active
molecules present in tree heartwood.

Funding information

The constitution of the xylarium, the machining of the
samples were done with CIRAD's own funds, the recruitment
of the laboratory technician by "Investissements d'Avenir"
grant from the Agence Nationale de la Recherche (CEBA:
ANR-10-LABX-0025; ARBRE, ANR-11-LABX-0002-01), and
finally we benefited from the voluntary work of Professor
B. Thibaut, CNRS director emeritus.

Data access conditions

The data are freely available and have been uploaded to
the CIRAD dataverse [https://doi.org/10.18167/DVN1/R4G7BC](https://doi.org/10.18167/DVN1/R4G7BC)

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Beauchêne et al. – Author's contributions

<table><thead><tr><td>Contributor role</td><td>Contributor names</td></tr></thead><tbody><tr><td>Conceptualization</td><td>B. Thibaut, J. Beauchêne, N. Amusant</td></tr><tr><td>Data Curation</td><td>B. Thibaut, J. Beauchêne, N. Amusant, J. Cygna, S. Koese</td></tr><tr><td>Formal Analysis</td><td>B. Thibaut, J. Beauchêne, J. Cygna</td></tr><tr><td>Funding Acquisition</td><td>B. Thibaut, J. Beauchêne</td></tr><tr><td>Investigation</td><td>B. Thibaut, J. Beauchêne, J. Cygna</td></tr><tr><td>Methodology</td><td>B. Thibaut, J. Beauchêne, N. Amusant</td></tr><tr><td>Project Administration</td><td>J. Beauchêne</td></tr><tr><td>Resources</td><td>J. Beauchêne</td></tr><tr><td>Supervision</td><td>B. Thibaut, J. Beauchêne</td></tr><tr><td>Validation</td><td>B. Thibaut, J. Beauchêne</td></tr><tr><td>Visualization</td><td>B. Thibaut, J. Beauchêne</td></tr><tr><td>Writing – Original Draft Preparation</td><td>B. Thibaut</td></tr><tr><td>Writing – Review & Editing</td><td>B. Thibaut, J. Beauchêne, N. Amusant</td></tr></tbody></table>

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