M.Schwanninger & L.E. Pâques BOKUV-Vienna / INRA-Orléans

Near-Infra-Red Spectroscopy – NIRS (High performance tool)

The electromagnetic spectrum

What is (Vibrational) Spectroscopy?

Spectroscopy: The study of the interactions between electromagnetic radiation

(energy, light) and matter.

Vibrational Spectroscopy

Vibrational spectroscopy is a method of chemical analysis where the sample is

illuminated with incident radiation in order to excite molecular vibrations. Vibrational

excitation is caused by the molecule absorbing, reflecting or scattering a particular

discrete amount of energy. There are two major types of vibrational spectroscopy:

Infrared (IR) and Raman.

Valence vibrations Deformation vibrations

Symmetrical stretching Scissoring Wagging

Antisymmetrical stretching Rocking Twisting

What kind of vibrations can appear in the MIR? Simple diatomic molecules have only one bond, which may stretch. More complex molecules have many bonds leading to infrared absorptions at characteristic wavelength that may be related to chemical groups. Stretching (valance) vibrations occur at lower wavelength than deformation vibrations. For example, the atoms in a CH2 group (Carbon atom green, Hydrogen atom blue), commonly found in organic compounds can vibrate in six different ways (normal modes):

What is a Spectrum? Spectrum: A plot or display showing the amount of interaction between

radiation (light) and a sample as a function of wavelength (wavenumber) or

frequency.

H2O

Comparison of MIR and NIR spectroscopy

How does MIR spectra look like and which information can be obtained?

FT-IR (MIR) spectra of milled pine wood and components

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Abso

rban

ce

Wavenumber (cm-1)

Pine woodHolocelluloseCelluloseMilled Wood Lignin

Comparison of MIR and NIR spectroscopy

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log(

1/R

efl.)

Wavenumber (cm-1)

Beech Spruce

How does NIR spectra look like and which information can be obtained?

FT-NIR spectra of milled spruce and beech wood

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Evaluation of MIR and NIR spectra Qualitative: differences in bands

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sorb

ance

Wavenumber (cm-1)

Spruce Lime

Different species Different components

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Abso

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Wavenumber (cm-1)

Pine woodHolocelluloseCelluloseMilled Wood Lignin

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log(

1/R

efl.)

Wavenumber (cm-1)

Beech Spruce

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log(

1/R

efl.)

Wavenumber (cm-1)

Beech Spruce Cellulose

Xylan from birch MWL spruce

MIR

NIR

Evaluation of MIR and NIR spectra

How does NIR spectra look like and which information can be obtained?

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A

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0.02

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53505600585061006350660068507100Wavenumber [cm-1]

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strong H-bonded O-H ofcrystalline cellulose

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Figure. (left side) Polarised FT-NIR absorbance spectra (baseline corrected) of radial spruce wood sections (black) and wood sections degraded by P. placenta - 16% mass loss (grey). A: 7300 – 3800 cm-1, B: 7200 – 5350 cm-1. Thin lines: spectra recorded in 0° polarisation; thick lines: spectra recorded in 90° polarisation. (right side) Cellulose structure

e.g. orientation of bondings in cellulose

Evaluation of MIR and NIR spectra

Qualitative: changes of band heights and band heights ratios

Different numbers of acetyl groups due to chemical modification

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Log

(1/R

efl.)

0%6.5%10.2%14.9%20.2%24.1%26.7%

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6.5%

10.2%

14.9%

20.2%

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WOOD

HO-lignin

HO-hemicelluloses

HO-cellulose

Acetylation with acetic acid anhydride

hemicelluloses-O-R

lignin-O-R

cellulose-O-R

Stefke B, Windeisen E, Schwanninger M, Hinterstoisser B (2008) Determination of the weight percentage gain and of the acetyl group content of acetylated wood by means of different infrared spectroscopic methods. Analytical Chemistry 80:1272-1279

Principal Component Analysis (PCA)

Schwanninger, M., B. Hinterstoisser, Gradinger, C., Messner, K., Fackler, K. Journal of Near Infrared Spectroscopy 12(6): 397-409. (2004)

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PC1

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Differentation between strains of fungi grown on wood up to 14 days 2nd derivatives of NIR spectra of fungi-treated spruce wood

Loading plots

Scores plots

Traceability of wood by NIR

Trees of Norway spruce from 75 locations in 14 European countries

2163 samples (trees) measured

x 5 spectra/sample

= 10815 spectra

More details in: A. Sandak, J. Sandak, M. Negri (2011) Relationship between near-infrared (NIR) spectra and the geographical provenance of timber, Wood Science and Technology – 45(1):35–48

Traceability of wood by NIR

PCA of Norway spruce wood of different European provenances

More details in: A. Sandak, J. Sandak, M. Negri (2011) Relationship between near-infrared (NIR) spectra and the geographical provenance of timber, Wood Science and Technology – 45(1):35–48

Austria ▲ Bulgaria ▼ Czech Republic ■ Croatia ■ Estonia Finland France Germany Hungary Italy Norway Poland Romania Sweden

Heartwood extractives

• widely determine wood colour, and

• play a major role in decay resistance against fungi

(especially terpenoids, stilbenes, lignans and polyphenols)

• are usually determined directly through wet-lab chemistry methods

(extraction with different solvents, gravimetric determination of the residuum)

Applications to lignocellulosics

Determination of heartwood extractives contents in Larix sp.1

1 N. Gierlinger, M. Schwanninger, B. Hinterstoisser and R. Wimmer, "Rapid determination of heartwood extractives in Larix sp. by means of Fourier transform near infrared spectroscopy", J Near Infrared Spec 10(3), 203-214 (2002).

milling drying

NIR

wood meal wood disk extractives

content

PLS-R Model

extraction

Applications to lignocellulosics

Determination of the natural durability of Larix sp.

Coniophora puteana

Larch wood after 16 weeks growth of the fungi: Coniophora puteana and Gloeophyllum trabeum

Gloeophyllum trabeum Gloeophyllum trabeum

Gloeophyllum trabeum Gloeophyllum trabeum treated larch wood

After removal of the mycel and drying

and weighing

Applications to lignocellulosics

Three brown rot fungi for the wood decay tests: Coniophora puteana, Gloeophyllum trabeum and Poria placenta (data not shown)

Test specimens from heartwood 50 mm x 25 mm x 15 mm

EN 113

C. put.

G. trab.

P. plac.

reserve

Eval.

100 boards with five samples per fungus and board = 500 samples per fungus

radial

Inoculation with a fungi

Wood decay tests

NIR

Collection of three NIR spectra per specimen from the radial surface (12% moisture content)

After 16 weeks

weighing

Determination of the natural durability of Larix sp.

PLS-R Model

Mass loss NIR spectra

Applications to lignocellulosics

Determination of the lignin content of Picea abies

milling drying wood meal

wood disk extraction extractives-free

wood meal

NIR

PLS-R model

lignin determination

Klason lignin and acid soluble lignin

results = total lignin content

and / or

NIR fibre optic

FTIR imaging (mapping)

Lignin distibution in larch wood

Johner, N. (Bruker), Schwanninger, M., Gierlinger, N. (BOKU) 2002

NIR imaging

NIR imaging of a larch wood strip and a Scots pine disk

Wallbäcks L. and Lundqvist S.-O. (INNVENTIA) 2013

Applications to lignocellulosics

Further applications: determination (prediction) of Kappa number

Alves A, Santos A, da Silva Perez D, Rodrigues J, Pereira H, Simões R, Schwanninger M (2007) NIR PLSR model selection for Kappa number

prediction of Maritime pine Kraft pulps. Wood Science and Technology 41:491-499

H/G ratio Alves A, Schwanninger M, Pereira H, Rodrigues J (2006) Calibration of NIR to assess lignin composition (H/G ratio) in maritime pine wood using

analytical pyrolysis as the reference method. Holzforschung 60:29-31

Biotechnology – Biopulping / Fungi treatment / Biodegradation Fackler K, Gradinger C, Hinterstoisser B, Messner K, Schwanninger M (2006) Lignin degradation by white rot fungi on spruce wood shavings

during short-time solid-state fermentations monitored by near infrared spectroscopy. Enzyme and Microbial Technology 39:1476-1483

Fackler K, Gradinger C, Schmutzer M, Tavzes C, Burgert I, Schwanninger M, Hinterstoisser B, Watanabe T, Messner K (2007) Biotechnological

Wood Modification with Selective White-Rot Fungi and Its Molecular Mechanisms. Food Technology and Biotechnology 45:269-276

Fackler K, Schmutzer M, Manoch L, Schwanninger M, Hinterstoisser B, Ters T, Messner K, Gradinger C (2007) Evaluation of the selectivity of

white rot isolates using near infrared spectroscopic techniques. Enzyme and Microbial Technology 41:881-887

Fackler K, Schwanninger M, Gradinger C, Hinterstoisser B, Messner K (2007) Qualitative and quantitative changes of beech wood degraded by

wood rotting basidiomycetes monitored by Fourier transform infrared spectroscopic methods and multivariate data analysis. FEMS Microbiological

Letters 271:162-169

Fackler K, Schwanninger M, Gradinger C, Srebotnik E, Hinterstoisser B, Messner K (2007) Fungal decay of spruce and beech wood assessed by

near-infrared spectroscopy in combination with uni- and multivariate data analysis. Holzforschung 61:680-687

Schwanninger M, Hinterstoisser B, Gradinger C, Messner K, Fackler K (2004) Examination of spruce wood biodegraded by Ceriporiopsis

subvermispora using near and mid infrared spectroscopy. Journal of Near Infrared Spectroscopy 12:397-409

Applications to lignocellulosics

Further applications: determination (prediction) of Chemical / thermal modification / photodegradation

Stefke B, Windeisen E, Schwanninger M, Hinterstoisser B (2008) Determination of the weight percentage gain and of the acetyl group content of

acetylated wood by means of different infrared spectroscopic methods. Analytical Chemistry 80:1272-1279

Schwanninger M, Hinterstoisser B, Gierlinger N, Wimmer R, Hanger J (2004) Application of Fourier transform near infrared Spectroscopy (FT-

NIR) to thermally modified wood. Holz Als Roh-Und Werkstoff 62:483-485

Hansmann C, Schwanninger M, Stefke B, Hinterstoisser B, Gindl W (2004) UV-microscopic analysis of acetylated spruce and birch cell walls.

Holzforschung 58:483-488

Müller U, Rätzsch M, Schwanninger M, Steiner M, Zobl H (2003) Yellowing and IR-changes of spruce wood as result of UV-irradiation. Journal of

Photochemistry and Photobiology B: Biology 69:97-105

Wood components (lignin, extractives, ....) Rodrigues J, Alves A, Pereira H, Perez DDS, Chantre G, Schwanninger M (2006) NIR PLSR results obtained by calibration with noisy, low-

precision reference values: Are the results acceptable? Holzforschung 60:402-408

Gierlinger N, Jacques D, Schwanninger M, Wimmer R, Hinterstoisser B, Pâques LE (2003) Rapid prediction of natural durability of larch

heartwood using Fourier transform near-infrared spectroscopy. Canadian Journal of Forest Research 33:1727-1736

Gierlinger N, Schwanninger M, Hinterstoisser B, Wimmer R (2002) Rapid determination of heartwood extractives in Larix sp. by means of Fourier

transform near infrared spectroscopy. Journal of Near Infrared Spectroscopy 10:203-214

Gierlinger N, Schwanninger M, Wimmer R (2004) Characteristics and classification of Fourier-transform near infrared spectra of the heartwood of

different larch species (Larix sp.). Journal of Near Infrared Spectroscopy 12:113-119

Applications to lignocellulosics

Further applications: determination (prediction) of Wood components (lignin, extractives, ....)

Rodrigues J, Alves A, Pereira H, Perez DDS, Chantre G, Schwanninger M (2006) NIR PLSR results obtained by calibration with noisy, low-

precision reference values: Are the results acceptable? Holzforschung 60:402-408

Gierlinger N, Jacques D, Schwanninger M, Wimmer R, Hinterstoisser B, Pâques LE (2003) Rapid prediction of natural durability of larch

heartwood using Fourier transform near-infrared spectroscopy. Canadian Journal of Forest Research 33:1727-1736

Gierlinger N, Schwanninger M, Hinterstoisser B, Wimmer R (2002) Rapid determination of heartwood extractives in Larix sp. by means of Fourier

transform near infrared spectroscopy. Journal of Near Infrared Spectroscopy 10:203-214

Gierlinger N, Schwanninger M, Wimmer R (2004) Characteristics and classification of Fourier-transform near infrared spectra of the heartwood of

different larch species (Larix sp.). Journal of Near Infrared Spectroscopy 12:113-119

Cellulose Henniges U, Schwanninger M, Potthast A (2009) Non-destructive determination of cellulose functional groups and molecular weight in pulp hand

sheets and historic papers by NIR-PLS-R. Carbohydrate Polymers 76:374-380

Poke FS, Raymond CA (2006) Predicting extractives, lignin, and cellulose contents using near infrared spectroscopy on solid wood in Eucalyptus

globulus. Journal of Wood Chemistry and Technology 26:187-199

Pulp yield Schimleck LR (2008) Near-infrared spectroscopy: a rapid non-destructive method for measuring wood properties, and its application to tree

breeding. New Zealand Journal of Forestry Science 38:14-35

Mora CR, Schimleck LR (2008) On the selection of samples for multivariate regression analysis: application to near-infrared (NIR) calibration

models for the prediction of pulp yield in Eucalyptus nitens. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere

38:2626-2634

Applications to lignocellulosics

Further applications: determination (prediction) of Special

Rodrigues J, Alves A, Pereira H, da Silva Perez D, Chantre G, Schwanninger M (2006) NIR PLSR results obtained by calibration with noisy, low-

precision reference values: Are the results acceptable? Holzforschung 60:402-408

Composts / Waste material Meissl K, Smidt E, Schwanninger M (2007) Prediction of humic acid content and respiration activity of biogenic waste by means of Fourier

transform infrared (FTIR) spectra and partial least squares regression (PLS-R) models. Talanta 72:791-799

Meissl K, Smidt E, Schwanninger M, Tintner J (2008) Determination of Humic Acids Content in Composts by Means of Near- and Mid-Infrared

Spectroscopy and Partial Least Squares Regression Models. Applied Spectroscopy 62:873-880

Smidt E, Lechner P, Schwanninger M, Haberhauer G, Gerzabek MH (2002) Characterization of waste organic matter by FT-IR spectroscopy:

Application in waste science. Applied Spectroscopy 56:1170-1175

Smidt E, Meissl K, Schwanninger M, Lechner P (2008) Classification of waste materials using Fourier transform infrared spectroscopy and soft

independent modeling of class analogy. Waste Management 28:1699-1710

Smidt E, Schwanninger M (2005) Characterization of waste materials using FTIR spectroscopy: Process monitoring and quality assessment.

Spectroscopy Letters 38:247-270

Reviews on the use of NIR for wood, pulp, and paper Tsuchikawa S and Schwanninger M (2013) A Review of Recent Near Infrared Research for Wood and Paper (Part 2). Applied Spectroscopy

Reviews 48(7): 560-587

Tsuchikawa S (2007) A Review of Recent Near Infrared Research for Wood and Paper. Applied Spectroscopy Reviews 42:43-71

Workman JJ (2001) Infrared and Raman spectroscopy in paper and pulp analysis. Applied Spectroscopy Reviews 36:139-168

Workman JJJ (1999) Review of process and non-invasive near-infrared and infrared spectroscopy: 1993-1999. Applied Spectroscopy Reviews

34:1-89

Infrared spectroscopy in T4F

NIR spectroscopy as a tool for indirect assessment of wood properties

a) Development or improvement of calibration models to predict wood properties

and new adaptive traits based on acquired infrared spectra

i. Feasibility of NIRS to predict hydraulic conductivity and vulnerability to

cavitation

ii. Lignin composition determined by analytical pyrolysis to be used for NIRS

calibrations

iii. Prediction of extractives content (e.g. phenolics) with NIRS in relation to

natural durability/ heartwood colour

iv. Prediction of mass loss of larch wood with existing NIR PLS-R models

v. Verification of the predicted mass losses by additional decay tests

vi. Comparison of DSC-TGA results with wet-chemical analysis results with

results from NIR imaging

Infrared spectroscopy in T4F

NIR spectroscopy as a tools for indirect assessment of wood properties

b) Calibration transfer

i. Standardization of NIRS calibration methods for important wood

properties

ii. Inter-laboratory tests on representative samples from several species for

different traits

iii. Development of calibration transfer protocols

c) Transfer to research infrastructure

i. Results on new methodologies and techniques for medium to high

throughput phenotyping will be disseminated towards researchers and

end-users, organisation of training workshops and presentations at

meetings

Thank you very much for your attention

BOKU Vienna: Gierlinger, N., Luss, S., Rosner, S., Schwanninger, M.

CIRAD Montpellier: Chaix, G.

CIS-Madeira Spain: Touza, M.

IICT Lisbon; Rodrigues, J.

INNVENTIA Stockholm: Lundqvist, S.-O., Wallbäcks, L.

INRA-Orléans: Charpentier, J.P., Pâques, L., Segura, V

IVALSA Trento: Sandak, A., Sandak, J.