*"Strengthening collaboration on
innovative wood quality research"*

**"High throughput" measurement of wood quality
for genetic studies and breeding programs**

Jean-Paul Charpentier, INRA
and
AGPF INRA Orleans team

INSTITUT
FRANÇAIS
FINLANDE

<figure><img src="image_1.png" /></figure>

<figure><img src="image_2.png" /></figure>

LIBERTÉ • Egalité • Fraternité
RÉPUBLIQUE FRANÇAISE
MINISTÈRE DE L'Éducation nationale
dél'enseignement supérieur et de la Recherche
AMÉDÁSSE DE FRANCE ET FOUŁANCE
different types of wood quality assessment methods

Destructive methods

Non-destructive methods
<figure><img src="image_3.png" /></figure>

Destructive methods

- in general, completely and definitively destructives for trees

- usually expensive and non adapted for genetic studies with a great sampling

- avantage : accessibility of a great quantity of matter
Destructive methods

Some wood property measurements :

<figure><img src="image_4.png" /></figure>

MOE,
wood stiffness,
different tests for mechanical properties
natural durability with fungi tests
chemical properties

......

<figure><img src="image_5.png" /></figure>
Non-destructive methods

□ With sampling

<figure><img src="image_6.png" /></figure>

Sampling of a small sample of wood,
non lethal for the tree

<figure><img src="image_7.png" /></figure>

Increment cores

Infradensity

Microdensitometry

Chemical properties

<figure><img src="image_8.png" /></figure>

→ wood chips by drilling
Chemical properties
(if little material is required)

<figure><img src="image_9.png" /></figure>
# Evolution of laboratory analytical methods

## Orientation towards:

* As high throughput as possible

* less costly

* more automated as possible

* miniaturized for less matter use
Sample preparation for analysis:

→ wood is a hard material and difficult to work if it is to be grinded

➤ design and development of robots
(1) grinder and (2) wood powder dispenser
(1)

<figure><img src="image_10.png" /></figure>

xyloforest
Research & Innovation Faret Bois

(2)

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>
Evolution of laboratory analytical methods (2)

Evaluation of the natural durability other than the standard
method with wooden board from increment cores and by
means of X-ray microdensitometry

<figure><img src="image_15.png" /><figcaption>C. puteana</figcaption></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

(with collaboration
Ivalsa CNR Firenze, Italy)

Macchioni N, Palanti S, Rozenberg P (2007),
Wood Science and Technology 41(5):417-426.

In preparation: Francesca Alderighi, Jean-Paul CHARPENTIER, Sabrina Palanti and Luc E. Pâques; T4F work, will be probably submitted International Biodeterioration & Biodegradation
Evolution of laboratory analytical methods (3)

Miniaturized process for high throughput screening of the
saccharification potential of lignocellulosic biomasses

(1) Biomass preparation

(2) Pretreatment

(3) Enzymatic hydrolysis

<figure><img src="image_18.png" /></figure>

Lignocellulosic
biomass

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

xyloforest
Biotech & Innovation Center Bus

Grinding and distribution
of biomass by robots

5 mg / well

<figure><img src="image_22.png" /></figure>

Essential for good
accuracy and
repeatability

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

96-wells plates in
Hastelloy
(heat resistant)

<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>

Enzymatic hydrolysis
without pretreatment

Steam (180°C)

<figure><img src="image_27.png" /></figure>

Enzymatic Hydrolysis
(50°C, Ctec-2)

<figure><img src="image_28.png" /></figure>

Steam generator
Cellkraft®

Reactor for
pretreatment
PARR Instrument®

<figure><img src="image_29.png" /></figure>

Belmokhtar et al.,
Frontiers in Plant
Science, 2017

<figure><img src="image_30.png" /></figure>

Projet

FUTUROL
PROCETHOL 2G

<figure><img src="image_31.png" /></figure>

INRA
SCIENCE & IMPACT

<figure><img src="image_32.png" /></figure>

GENOBOTS

<figure><img src="image_33.png" /></figure>

Chromatography
(HPLC)

<figure><img src="image_34.png" /></figure>

Enzymatic dosage
(colorimetric)

Determination of released sugars
(Glucose and xylose)

JP. CHARPENTIER

French (INRA)/Finnish (Luke) workshop

09

<figure><img src="image_35.png" /></figure>

INRA
SCIENCE & IMPACT

<figure><img src="image_36.png" /></figure>

<figure><img src="image_37.png" /></figure>

High throughput measurement
of wood quality

"Strengthening collaboration on innovative wood quality research"

Viikki, Finland, 29-30/08/2017
# Evolution of laboratory analytical methods (3)

## Miniaturized process for high throughput screening of the saccharification potential of lignocellulosic biomasses

<figure><img src="image_38.png" /></figure>

Belmokhtar et al.,
Frontiers in Plant
Science, 2017

<figure><img src="image_39.png" /></figure>

Projet

FUTUROL
PROCETHOL 2G

<figure><img src="image_40.png" /></figure>

INRA
SCIENCE & IMPACT

<figure><img src="image_41.png" /></figure>

GENOBOTS
# Evolution of laboratory analytical methods (3)

## New process for saccharification potential

### An application:

## Study of saccharification potential on poplar biomass

<figure><img src="image_42.png" /></figure>

vSRC 2 years

<figure><img src="image_43.png" /></figure>

SRC 11 years

<figure><img src="image_44.png" /></figure>

The test allows discrimination between biomass
Indirect evaluation of wood properties
by Near InfraRed Spectroscopy (NIRS)

On powder → destructive for samples

On solid wood → non-destructive for
samples

<figure><img src="image_45.png" /></figure>

**Wood properties evaluated:**
Chemical (structural, extractives, specific molecules)
Physical (densité,...)
Mechanical (MOE, MOR,...)
Perkin Elmer
Near and Middle InfraRed
Spectroscope and imager

Physical (densité,...)

Mechanical (MOE, MOR,...)

Complexe : natural durability, cavitation vulnerability, ......

Tsuchikawa and Kobori, J Wood Sci (2015), 61:213-220
# Indirect evaluation of wood properties by Near InfraRed Spectroscopy (NIRS)

NIRS is a multiparametric, fast, and non-destructive technique

<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /></figure>

<figure><img src="image_48.png" /><figcaption>Extractives in Larch wood</figcaption></figure>

<figure><img src="image_49.png" /><figcaption>Poplar</figcaption></figure>

Discrimination of provenances
Structuring phenomic diversity

<figure><img src="image_50.png" /></figure>

Discrimination and prediction of unknown samples, for example in Larch
## NIRS methodology

### Poplar
*(Populus nigra)*

Genetic architecture of lignocellulosic biomass yield and quality in black poplar for its use in biorefinery

Development of NIR spectroscopy calibrations for the genetic analysis of wood properties in natural populations of *Populus nigra*

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /></figure>

<figure><img src="image_53.png" /></figure>

$n = 5,814$

<figure><img src="image_54.png" /></figure>

<figure><img src="image_55.png" /></figure>

Selection of a Reference sample set (n = 120)
(Kennard and Stone, 1969)

* Field trials at 2 sites (Orleans, France; Savigliano, Italy)

* Wood samples: 3 main stem harvests of 2-yr-old trees in 2-3 biological replicates

* 800 samples / 289 genotypes in Orleans in 2010 (Orl2010)

* 2,810 samples / 1,066 genotypes in Orleans in 2012 (Orl2012)

* 2,204 samples / 777 genotypes in Savigliano in 2011 (Sav2011)

**Standard methods:**

* Wet chemistry

* HPLC

* Analytical pyrolysis

**Cell wall chemistry traits:**

* Sugar content: Glucose, Xyl/Glu

* Lignin composition (H/G, S/G)

* Lignin content:

* Klason lignin,

* Py-lignin,

* Acid-soluble lignin

Duplicate
analysis

Chemical
analysis

Calibration set
(n = ~ 5/6)

Calibration models
with LOO cross-validation

<figure><img src="image_56.png" /></figure>

<figure><img src="image_57.png" /></figure>

Predictions
(n = 5,814)

<figure><img src="image_58.png" /></figure>

Genetic
analysis

Validation set
(n = ~1/6)

<figure><img src="image_59.png" /></figure>

Gebreselassie et al,
2017_industrial
Crops&Products 107_159-171

<figure><img src="image_60.png" /></figure>

<figure><img src="image_61.png" /></figure>

<figure><img src="image_62.png" /></figure>
NIRS methodology

Poplar (Populus nigra)

NIRS calibration models for different chemical wood properties:

<table><thead><tr><th rowspan="2">Trait</th><th rowspan="2">Model type</th><th colspan="4">Calibration set (n = ~ 5/6)</th><th colspan="3">Validation set (n = ~ 1/6)</th><th rowspan="2">RMSE of lab. Method</th></tr><tr><th>Factors</th><th>R<sup>2</sup><sub>cv</sub></th><th>RMSE<sub>cv</sub></th><th>Nb. obs</th><th>R<sup>2</sup><sub>val</sub></th><th>RMSE<sub>val</sub></th><th>Nb. obs.</th></tr></thead><tbody><tr><td>Glucose</td><td>global</td><td>6</td><td>0.76</td><td>1.49</td><td>94</td><td>0.64</td><td>1.25</td><td>18</td><td>1.87</td></tr><tr><td>Xylose/Glucose</td><td>global</td><td>8</td><td>0.79</td><td>0.02</td><td>90</td><td>0.75</td><td>0.02</td><td>20</td><td>0.03</td></tr><tr><td>H/G ratio</td><td>global</td><td>8</td><td>0.82</td><td>0.02</td><td>92</td><td>0.83</td><td>0.02</td><td>19</td><td>0.01</td></tr><tr><td>S/G ratio</td><td>global</td><td>12</td><td>0.84</td><td>0.03</td><td>91</td><td>0.72</td><td>0.04</td><td>21</td><td>0.03</td></tr><tr><td>Klason lignin</td><td>Site</td><td>6</td><td>0.78</td><td>0.94</td><td>56</td><td>0.6</td><td>1.31</td><td>13</td><td>1.61</td></tr><tr><td>Py-lignin</td><td>Site</td><td>8</td><td>0.79</td><td>0.39</td><td>26</td><td>0.73</td><td>0.35</td><td>6</td><td>1.49</td></tr><tr><td>Acid-soluble lignin</td><td>Site</td><td>8</td><td>0.77</td><td>0.16</td><td>30</td><td>0.79</td><td>0.15</td><td>6</td><td>0.32</td></tr></tbody></table>
# NIRS methodology

## Poplar (Populus nigra)

NIRS calibration models for different chemical wood properties:

<figure><img src="image_63.png" /></figure>
## NIRS methodology

### Poplar (Populus nigra)

Broad-sense heritability ($H^2_i$) estimates of NIR-predicted wood chemical traits:

<figure><img src="image_64.png" /></figure>

* Predicted wood properties were under moderate to high genetic control ($H^2_i$ ranging from 0.25 to 0.68).

* Site differences were apparent in the expression of the phenotypes.
# Evolution of laboratory analytical methods (4)

## NIRS methodology

European Larch; small wood boards from increment cores, 104 Larch trees from 28 families full brothers from a factorial crossing design

<figure><img src="image_65.png" /></figure>

## Chemical Analysis:

Extractives, total phenol content (Folin reagent method)

TAX, DHK (HPLC)

<figure><img src="image_66.png" /></figure>
NIRS calibration models obtained on wood powder for
extratives and phenolic molecules

<figure><img src="image_67.png" /></figure>

Extractives: R² = 0,92 with 13 outliers

<figure><img src="image_68.png" /></figure>

Tax + DHK: R² = 0,72 with 10 outliers
NIRS methodology

<figure><img src="image_69.png" /></figure>

Mass loss data with
attack by fungi
(Ivalsa, Italy)

<figure><img src="image_70.png" /></figure>

NIRS measurement:
8 spectra/block in
different faces

NIRS Calibration models for a complexe
property of wood:
natural durability of larch wood

European Larch; blocks sawn in
heartwood of 104 Larch trees from 28
families full brothers from a factorial
crossing design

<figure><img src="image_71.png" /></figure>

A great
variation
of type of
blocks
## NIRS methodology

<figure><img src="image_72.png" /></figure>

Mass loss data with
attack by fungi
(Ivalsa)

<figure><img src="image_73.png" /></figure>

NIRS measurement: 8
spectra/block in
different faces

Mlmean_reelle

<figure><img src="image_74.png" /></figure>

<figure><img src="image_75.png" /></figure>

A great
variation
of type of
blocks
## Evaluation of stilbenes in Scots pine heartwood

<figure><img src="image_76.png" /></figure>

<figure><img src="image_77.png" /></figure>

<figure><img src="image_78.png" /></figure>

<figure><img src="image_79.png" /></figure>

Number of observations: 212 for calibration and 262 for validation

R²: 0.90 for calibration and 0.87 for validation set

<figure><img src="image_80.png" /></figure>

<figure><img src="image_81.png" /></figure>
## Evaluation of stilbenes in Scots pine heartwood

<figure><img src="image_82.png" /></figure>

<figure><img src="image_83.png" /></figure>

<figure><img src="image_84.png" /></figure>

<figure><img src="image_85.png" /></figure>

<figure><img src="image_86.png" /></figure>

<figure><img src="image_87.png" /></figure>

<figure><img src="image_88.png" /></figure>

Number of observations: 212 for calibration and 262 for validation

R²: 0.90 for calibration and 0.87 for validation set

* Heritabilities: 257 samples measured using GC-MS, UVRRS and NIRS

$$ -h_{STB}^2 = 0.85, SD_{h2} = 0.30 \text{ (GC-MS)} $$

$$ -h_{STB}^2 = 0.84, SD_{h2} = 0.29 \text{ (NIRS)} $$

$$ -h_{STB}^2 = 0.33, SD_{h2} = 0.21 \text{ (UVRRS)} $$
Non-destructive methods

□ Without sampling

→ *in situ* method,
directly on standing trees

→ *pilodyn*
resistograph
acoustic methods
Near InfraRed Spectroscopy (NIRS)

<figure><img src="image_89.png" /></figure>

Development of *in situ* rapid, non-destructive, accurate, and economically viable wood quality assessment methods would be of great interest to tree breeders and forest managers and for genetic studies.
<figure><img src="image_90.png" /></figure>

**Non-destructive methods**

<figure><img src="image_91.png" /></figure>

Without sampling

→ *in situ* method,

directly on standing trees

pilodyn

→ resistograph

acoustic methods

Near InfraRed Spectroscopy (NIRS)

<figure><img src="image_92.png" /></figure>

Development of *in situ* rapid, non-destructive, accurate, and economically viable wood quality assessment methods would be of great interest to tree breeders and forest managers and for genetic studies.
<figure><img src="image_93.png" /></figure>

Non-destructive methods

□ Without sampling

→ *in situ* method,
directly on standing trees

pilodyn

resistograph

→ acoustic methods
Near InfraRed Spectroscopy (NIRS)

<figure><img src="image_94.png" /></figure>

Development of *in situ* rapid, non-destructive, accurate, and economically viable wood quality assessment methods would be of great interest to tree breeders and forest managers and for genetic studies.
Non-destructive methods

☐ Without sampling

→ *in situ* method,
directly on standing trees

pilodyn

resistograph

acoustic methods

in new development → Near InfraRed Spectroscopy (NIRS)

<figure><img src="image_95.png" /></figure>

Development of *in situ* rapid, non-destructive, accurate, and economically viable wood quality assessment methods would be of great interest to tree breeders and forest managers and for genetic studies.
resistograph

<figure><img src="image_96.png" /></figure>

<figure><img src="image_97.png" /></figure>

A needle shaft diameter of 1.5mm with a flat tip 3mm wide were found to be a good compromise for achieving maximum resolution and stability, while causing the least damage to the sample.

<figure><img src="image_98.png" /></figure>

<figure><img src="image_99.png" /></figure>

<figure><img src="image_100.png" /></figure>
## resistograph

<figure><img src="image_101.png" /></figure>

## Douglas-fir clones analysis

<figure><img src="image_102.png" /></figure>

Drill mean

Feed mean

<figure><img src="image_103.png" /></figure>

SD drill

SD feed

<table><thead><tr><td>Caractère</td><td>Feed mean</td><td>Pilodyn</td><td>Diamètre 1,30m</td></tr></thead><tbody><tr><td>Drill mean</td><td>0,97 **</td><td>-0,66**</td><td>-0,28 ns</td></tr><tr><td>Feed mean</td><td></td><td>-0,73**</td><td>-0,19 ns</td></tr><tr><td>Pilodyn</td><td></td><td></td><td>0,36 ns</td></tr></tbody></table>

<table><thead><tr><td>Caractère</td><td>Héritabilité (SL)</td></tr></thead><tbody><tr><td>Drill mean</td><td>0,42</td></tr><tr><td>Feed mean</td><td>0,38</td></tr><tr><td>Pilodyn</td><td>0,45</td></tr><tr><td>Diamètre 1,30m</td><td>0,41</td></tr></tbody></table>
## Non-destructive in-situ methods
### Acoustic methods

<figure><img src="image_104.png" /></figure>

<figure><img src="image_105.png" /></figure>

In collaboration with Spanish colleagues in
the framework of the TopWood project

On standing trees, we test different
equipments on different species

Wood basic properties evaluated:

Microdensity, MOE, MFA, fiber Length, Basic density, dimensional stability, vulnerability to cavitation

<figure><img src="image_106.png" /></figure>

$$MOE= \rho \cdot V^2$$

Wang, Wood Sci Technol (2013) 47:965–975

Affected by diameter, modelisation is necessary
<figure><img src="image_107.png" /></figure>

Some first results:

Correlation with basic density in *Eucalyptus globulus* but not in *Pinus* (*ponderosa*, *pinaster*, *radiata*).

<figure><img src="image_108.png" /></figure>

<figure><img src="image_109.png" /></figure>

Correlation sonic velocity with
MFA in *Pinus pinaster* but not in
*Eucaliptus*
Douglas-fir, MOE evaluation on
standing trees
R²=0,60

<figure><img src="image_110.png" /></figure>

Merlo et al (2014)

<figure><img src="image_111.png" /></figure>

<figure><img src="image_112.png" /></figure>
## Non-destructive in-situ methods

<figure><img src="image_113.png" /></figure>

NIRS

<figure><img src="image_114.png" /></figure>

<figure><img src="image_115.png" /></figure>

## And now the portable NIRS technology ......?

* Proposed equipments are currently being in great evolution

* Portable technology already used in agriculture with embedded systems

* In the wood industry, some studies by researchers, not yet known routine use

<figure><img src="image_116.png" /></figure>

> Acquisition of spectra on standing trees: a new research axis
**Non-destructive in-situ methods**

**portable NIRS technology**

**Development of portable NIRS equipments...... more and more miniaturized**

* compact and fully integrated devices and

* apparatus using an optical fiber

**<u>Advantage:</u>**

direct use in the field,

on standing trees

on logs

in primary transformation wood factories

**<u>Interest:</u>**

can allow a first selection, a first sort according to criteria of interest

**<u>Our own experience in AGPF INRA team:</u>**

first tests since 2014 on poplar (on leaves)

equipment loans from several suppliers, testing of various equipments

acquisition of two different equipments (2016, 2017)

now, several current projects with portable NIRS actions (GenTree, TopWood, EmPIR, Chêne&Vin)

<figure><img src="image_117.png" /></figure>
Non-destructive in-situ methods
portable NIRS technology

First tests with MicoNIR on clones of eucalyptus in Spain (Madera+,
TopWood project) (Nov-Dec 2016, April 2017)

<figure><img src="image_118.png" /></figure>

MADERA+

<figure><img src="image_119.png" /></figure>

<figure><img src="image_120.png" /></figure>

INRA
SCIENCE & IMPACT

<figure><img src="image_121.png" /></figure>

<figure><img src="image_122.png" /></figure>
<figure><img src="image_123.png" /><figcaption>MicoNIR</figcaption></figure>

<figure><img src="image_124.png" /></figure>
<figure><img src="image_125.png" /></figure>

<figure><img src="image_126.png" /></figure>

<figure><img src="image_127.png" /><figcaption>legend("topleft", legend = levels(data_micronir_euca_ok$SampleType), lty = 1, lwd = 2, col = couleur,</figcaption></figure>

NIR spectra obtained with MicoNIR

<figure><img src="image_128.png" /></figure>

<figure><img src="image_129.png" /></figure>
<figure><img src="image_130.png" /></figure>

<figure><img src="image_131.png" /></figure>

# First NIRS models for density (MDM) and infradensity

MDM5cm

<figure><img src="image_132.png" /></figure>

infradensity

<figure><img src="image_133.png" /></figure>
# Non-destructive in-situ methods
# portable NIRS technology

First tests with NIRQuest with optical fiber

The objective is to validate procedure of taking
spectra on surface of trunk and into the trunk
with the optical fiber

<figure><img src="image_134.png" /></figure>

- On black poplar, old trees (April and July 2017) correlation with parameter measured on increment cores (density)

<figure><img src="image_135.png" /></figure>

- On Scots pine, ISS Evoltree, Punkaharju, Finland (August 2017) correlation with parameter measured on increment cores (stilbene content) and comparison with fluorescence method
Non-destructive in-situ methods
portable NIRS technology

<figure><img src="image_136.png" /><figcaption>Poplar, Loire River, France
NIRQuest</figcaption></figure>
<figure><img src="image_137.png" /><figcaption>NIRQuest</figcaption></figure>
<figure><img src="image_138.png" /><figcaption>#### NIRQuest</figcaption></figure>
MicroNIR and NIRQuest

<figure><img src="image_139.png" /></figure>

<figure><img src="image_140.png" /></figure>

<figure><img src="image_141.png" /></figure>
#### NIRQuest

<figure><img src="image_142.png" /></figure>

<figure><img src="image_143.png" /></figure>
Non-destructive *in-situ* methods

portable NIRS technology

Perspectives on the use of portable NIRS in the forest/wood sector

On standing trees:

- early selection or before thinning: management assistance and decision-making

- possible parameters of selection: wood quality, resistance to diseases, resistance to drought (cavitation), ...

On felled trees, logs:

- selection and sorting for optimized and oriented use, optimization of sales

- possible parameters of selection: wood quality (chemical, physical, and mechanical properties), natural durability, discrimination of species of same genus (oak), ...

- traceability

<figure><img src="image_144.png" /></figure>
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