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Rapid prediction of natural durability of larchheartwood using Fourier transform near-infraredspectroscopy

Notburga Gierlinger, Dominique Jacques, Manfred Schwanninger,Rupert Wimmer, Barbara Hinterstoisser, and Luc E. Pâques

Abstract: The feasibility of Fourier transform near-infrared (FT-NIR) spectroscopy for rapidly determining the naturaldurability of the heartwood of larch trees (Larix decidua Mill. and Larix kaempferi (Lamb.) Carrière) was investigated.FT-NIR spectra were collected from solid wood with a fibre-optical probe. Basidiomycetes tests using Coniophoraputeana and Poria placenta were carried out on larch heartwood (European standard EN 113), with pine sapwood(Pinus sylvestris L.) used as a reference. The relative resistance to decay (x value) was calculated, and durabilityclasses were estimated according to European standard EN 350-1. Partial least squares regressions between the datasets of wood decay tests (x values) and the FT-NIR spectra were calculated. It was found that multiplicative scattercorrection considerably improved the model predictability. High coefficients of correlation (r) and low root meansquare errors of prediction (RMSEP) were obtained for cross validation based on wood decay tests with P. placenta(r = 0.92, RMSEP = 0.077, range 0.27–1.13) and C. puteana (r = 0.97, RMSEP = 0.078, range 0.07–1.58). Overall,NIR spectroscopy has proven to be an accurate and fast method for the nondestructive determination of natural durabil-ity, which might be highly relevant for intensive tree breeding programs and for efforts to optimize wood utilization.

Résumé : La possibilité d’utilisation de la spectrométrie dans le proche infra-rouge (transformée de Fourier (FT-NIR)pour la détermination rapide de la durabilité naturelle du bois de cœur de mélèze (Larix decidua Mill. and Larixkaempferi (Lamb.) Carrière) a été étudiée. Les spectres ont été obtenus à partir de bois massif au moyen d’une sonde àfibre optique. Les tests biologiques de durabilité naturelle du bois de coeur de mélèze (la norme européenne) ont étéconduits avec de deux champignons (Coniophora puteana et Poria placenta) avec pour référence de l’aubier de pinsylvestre. La perte de masse relative a été calculée (valeur x) et les classes de durabilité ont été déterminées suivant lanorme européenne EN 350-1. Des régressions partielles (méthode des moindres carrés) ont été calculées entre les va-leurs × issues des tests biologiques et les valeurs issues des spectres FT-NIR; une correction par la méthode de disper-sion multiplicative a considérablement amélioré les possibilités de prédiction du modèle. Des coefficients de corrélation(r) élevés et des valeurs faibles pour les erreurs types ont été obtenus lors de la validation du modèle, basée sur lestests biologiques soit avec P. placenta (r = 0,92, erreur type = 0,077, étendue 0,27–1,13) and C. puteana (r = 0,97, er-reur type = 0,078, étendue 0,07–1,58). En résumé, la spectrométrie infrarouge se révèle être une méthode précise et ra-pide pour une détermination non destructive de la durabilité naturelle du bois. Son utilisation en routine apparaît dès àprésent attractive dans le cadre de programmes intensifs d’amélioration et de sélection et pour une utilisation optimaledes bois.

Gierlinger et al. 1736Introduction

The ability of tree species heartwood to resist biologicaldegradation, referred to as “natural durability” or “decay re-sistance” (Eaton and Hale 1993), is an important wood-quality factor essential for environmentally friendly exterior

timber uses. Knowledge about natural durability comes frompractical experiences of end-users, from field tests, or fromstandardized laboratory tests (Willeitner and Peek 1997). Tocompare the natural durability of the wood of different treespecies, a classification based on the computation of “rela-tive resistance” is highly practical. This measure is ex-

Can. J. For. Res. 33: 1727–1736 (2003) doi: 10.1139/X03-092 © 2003 NRC Canada

1727

Received 18 December 2002. Accepted 27 March 2003. Published on the NRC Research Press Web site at http://cjfr.nrc.ca on25 August 2003.

N. Gierlinger1 and R. Wimmer. Institute of Botany, BOKU – University of Natural Resources and Applied Life Sciences, Vienna,Gregor-Mendelstr. 33, A-1180 Vienna, Austria.D. Jacques. Centre de Recherche de la Nature des Forêts et du Bois, Avenue Maréchal Juin 23, B-5030 Gembloux, Belgium.M. Schwanninger and B. Hinterstoisser. Institute of Chemistry, BOKU – University of Natural Resources and Applied LifeSciences, Vienna, Muthgasse 18, A-1190 Vienna, Austria.L.E. Pâques. Institut National de la Recherche Agronomique, Unité d’Amélioration, Génétique et de Physiologie des Arbresforestiers, F-45166 Olivet CEDEX, France.

1Corresponding author (e-mail: [email protected]).

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pressed in a five-class system according to the Europeanstandard EN 350-1, with classes ranging from “nondurable”(class 5) to “highly durable” (class 1) (Bellmann 1988a; Eu-ropean Committee for Standardization 1994).

The natural durability of larch (Larix sp.) wood is de-scribed as being highly variable, ranging from nondurable tomoderately durable (class 5 to 3, European standard EN350-1) (Viitanen et al. 1997; Morell and Freitag 1995;Srinivasan et al. 1999; Nilsson 1997). This apparent variabil-ity may arise from problems that are linked to sample sizeand the reliability of the testing method itself, but it is alsoclearly linked to the large variability within and among trees,across sites, species, and genetic origins, and with tree age(Bellmann 1988b; Eaton and Hale 1993; Nilsson 1997; VanAcker et al. 1999; Jacques et al. 2002). Even though larchheartwood shows high variability in timber performance, itis valued for outdoor applications. More detailed investiga-tions about the level and variance of larch heartwood and itsnatural durability are needed and could be of benefit for treeimprovement programs as well as for the optimization ofwood utilization.

The significance of wood extractives for natural durabilitywas demonstrated as early as 1924 (Hawley et al. 1924), andit has been a repeatedly discussed topic in the literature (e.g.,Rudman 1963; Reyes-Chilpa et al. 1998; Celimene et al.1999; Schultz et al. 1990, 1995; Schultz and Nicholas 2000).Additionally, wood density and lignin quantity and type mayalso contribute to the susceptibility of heartwood to attackand spoilage by different bio-deteriorators (Eaton and Hale1993).

Near-infrared (NIR) spectroscopy has been shown to be apowerful and rapid tool for estimating parameters related towood chemistry, i.e., pulp yield and cellulose and lignin con-tent (Easty et al. 1990; Michell 1995; Schimleck et al. 1998;Schwanninger and Hinterstoisser 2001; Wright et al. 1990)as well as wood extractives (Schimleck et al. 1997;Gierlinger et al. 2002). Furthermore, studies have shown thatNIR spectroscopy was also capable of determining physico-mechanical properties, including basic density (Thygesen1994; Schimleck et al. 1999), mechanical strength (Hoff-meyer and Pedersen 1995; Gindl et al. 2001), and stiffness(Schimleck et al. 2002; Thumm and Meder 2001). It maytherefore be concluded that since all factors influencing nat-ural durability, i.e., heartwood extractives, lignin, and den-sity, may be successfully determined by NIR spectroscopy, itmay also have the potential to rapidly and nondestructivelypredict natural durability.

Thus, the purpose of this study was to investigate the fea-sibility of Fourier transform (FT)-NIR spectroscopy as amethod of estimating the natural durability of larch heart-

wood. Relative decay resistance after inoculation withConiophora puteana and Poria placenta was determined ac-cording to European standard EN 350-1 using wood fromplantation-grown European and Japanese larch (Larixdecidua Mill. and Larix kaempferi (Lamb.) Carrière), andthe resulting data set was utilized to establish calibrationmodels with acquired FT-NIR spectra.

Material and methods

Forty-year-old larch trees, planted on sites in Germany,Belgium, and France, were sampled in this study. The treeswere part of an European provenance trial with selectedlarch provenances planted across Europe (Table 1). Groupsof European larch trees were selected from a greater investi-gated sample pool (described in Jacques et al. 2002), to pro-vide a high variation of decay resistance of even-agedplantation trees. Additionally, Japanese larch, which provedto have higher decay resistance (Jacques et al. 2002), wasadded to the sample set (Table 1). From each tree, a 2-m logwas cut above breast height, and from each log, a centralboard was sawn. A set of 24 samples was prepared fromeach tree, half were taken from the inner part of theheartwoood, and the second half were taken from the outerpart of the heartwood. Sixteen samples were submitted tonatural durability tests, and eight were used as standards forcalculating reference dry matter. Samples (50 × 25 ×15 mm) were all planed and placed in a standard climatechamber to equalize at 12% wood moisture content prior tofungal inoculation.

Wood decay testsThe natural durability of solid wood was determined ac-

cording to European standards EN 113 and EN 350-1 (Euro-pean Committee for Standardization 1994, 1996). A total of608 larch samples and reference samples of Scots pine(Pinus sylvestris L.) sapwood were tested. For each tree,eight samples were inoculated with Poria placenta (strainFPRL280), and another eight samples were inoculated withConiophora puteana (strain FPRL11E). After exposure for16 weeks, mycelium was removed from the samples prior todrying at 103 °C to a constant mass. The mass loss was cal-culated and divided by the mass loss of the pine reference,resulting in a ratio referred to as “x value”, as suggested bythe European standard EN 350-1 (Table 2). Mean valueswere calculated using two vertically adjacent samples (con-taining the same annual rings), leading to four values pertree and fungi (4 × 38 trees = 152 samples for NIR spectros-copy).

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1728 Can. J. For. Res. Vol. 33, 2003

Country Site Latitude, longitudeAltitude(m) Origin Species

No. oftrees Abbreviation*

France Coat-an-Noz 48°31′N, 03°25′W 200 Montgenevre Larix decidua 8 Mont-FFrance Coat-an-Noz 48°31′N, 03°25′W 200 Ina Larix kaempferi 10 Ina-FBelgium Nassogne 50°05′N, 05°20′E 320 Langau Larix decidua 10 Lang-BGermay Elm 52°00′N, 10°03′E 205 Blizyn Larix decidua 10 Bliz-D

*Abbreviations used in the figures.

Table 1. Sample and site description.



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https://www.researchgate.net/publication/237865882_Estimation_of_wood_stiffness_of_increment_cores_by_near-infrared_spectroscopy?el=1_x_8&enrichId=rgreq-3b7b5cb2-5c52-42a5-b13c-b9a9d02fabde&enrichSource=Y292ZXJQYWdlOzIzNzg2NjEyNjtBUzoxMDQ4ODg0MDI5NzI2ODlAMTQwMjAxODc1MzA5MQ==

https://www.researchgate.net/publication/231379012_The_Relation_between_Durability_and_Chemical_Composition_in_Wood?el=1_x_8&enrichId=rgreq-3b7b5cb2-5c52-42a5-b13c-b9a9d02fabde&enrichSource=Y292ZXJQYWdlOzIzNzg2NjEyNjtBUzoxMDQ4ODg0MDI5NzI2ODlAMTQwMjAxODc1MzA5MQ==

https://www.researchgate.net/publication/277163864_Among_and_within_provenance_variability_for_decay_resistance_of_Larch_wood_to_fungi?el=1_x_8&enrichId=rgreq-3b7b5cb2-5c52-42a5-b13c-b9a9d02fabde&enrichSource=Y292ZXJQYWdlOzIzNzg2NjEyNjtBUzoxMDQ4ODg0MDI5NzI2ODlAMTQwMjAxODc1MzA5MQ==

https://www.researchgate.net/publication/277163864_Among_and_within_provenance_variability_for_decay_resistance_of_Larch_wood_to_fungi?el=1_x_8&enrichId=rgreq-3b7b5cb2-5c52-42a5-b13c-b9a9d02fabde&enrichSource=Y292ZXJQYWdlOzIzNzg2NjEyNjtBUzoxMDQ4ODg0MDI5NzI2ODlAMTQwMjAxODc1MzA5MQ==

FT-NIR spectroscopyFT-NIR spectra were recorded on a Bruker FT-IR spec-

trometer (EQUINOX 55) equipped with a NIR fibre-opticalprobe to measure the diffuse reflected light on a 10-mm2

spot. A germanium-diode detector with a cutoff wave num-ber at 5100 cm–1 (1961 nm) was used, and the measurementspectrum ranged between 9970 cm–1 (1003 nm) and5100 cm–1 (1961 nm). The thermoplastic resin Spectralonserved as a reference. With a spectral resolution of 20 cm–1

(636 data points), 100 scans per spectrum were acquired andaveraged. Four spectra were acquired from freshly cut sur-faces of cross sections of the ovendried standard samples,which were used for calculating the reference dry matter butnot for the decay tests. Spectra were measured at equallyspaced distances in the radial direction along the centrelineof the transverse plane, and the mean spectra were used forcalibration.

Data analysisChemometric modelling was performed with the

Unscrambler software package (version 7.6, CAMO ASA).For preprocessing, the algorithms of full multiplicative scat-ter correction (MSC, the mean spectrum of the calibrationset used as base spectrum) of the first and second derivativewere applied. Spectra were processed (smoothed and de-rived) according to Savitzky and Golay (1964), by means ofa nine-point smoothing filter and a second-order polynomial.Wavelength selection was done manually as well as automat-ically by means of the Martens uncertainty test (Westad andMartens 2002) to eliminate unimportant variables to simplifythe models and make them more reliable. Calibrations weredeveloped using partial least squares regression. The meanNIR spectra were regressed against the natural durabilitydata, and by means of full cross validation with one sampleomitted, a significant number of principal components orfactors were obtained. The root mean square error was cal-culated for the calibration samples (RMSEC) and for thepredicted samples (RMSEP, %RMSEP = RMSEP/mean).

Results

Variation of natural durabilityTable 2 gives relative frequencies of natural durability

classes according to the European standard EN350-1. For

P. placenta, almost half of the samples were classified asslightly durable, 30% were moderately durable, and the re-mainder (20%) were nondurable. Mass losses after exposureto C. puteana resulted in an even more scattered picture,with 10% being very durable at one end of the scale, and12% being nondurable on the other end, while the majority(42%) of the samples were classified as moderately durable.

The relationship between the x values obtained from thetwo fungi is shown in Fig. 1. A correlation of r = 0.61 andan axis intercept of –0.22 between the two x values is no-ticed. In some cases, the classification results produced bythe two fungi differed by one or two classes, as shown bythe axis intercept. As seen in Fig. 1, large variation wasfound among and also within each provenance. The prove-nances Ina (Japanese larch) and Blizyn (European larch)tended to be in lower durability classes (meaning higher du-rability), whereas samples of the provenance Langau (Euro-

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Gierlinger et al. 1729

Relative frequency

Durabilityclass Description

Results oflaboratory test(x)* P. placenta C. puteana

1 Very durable x ≤ 0.15 — 102 Durable 0.15 < x ≤ 0.3 1 153 Moderately durable 0.3 < x ≤ 0.6 30 424 Slightly durable 0.6 < x ≤ 0.9 49 215 Not durable 0.9 < x 20 12

Note: The x value is the mean mass loss of the test specimen divided by the mean mass lossof the reference specimen.

Table 2. Description of the durability classes according to European standard EN350-1, and the relative frequency obtained within the specified classes after inocula-tion with Poria placenta and Coniophora puteana.

Fig. 1. Relationship between the x values obtained after inocula-tion with two test fungi (Poria placenta and Coniophoraputeana). The samples are marked according to their prove-nances and sites (see Table 1).



pean larch) tended to be classified as not or slightly durable(Fig. 1).

Variation of NIR spectraThe NIR diffuse reflectance spectra of the samples from

the same durability classes were averaged. As shown inFigs. 2A and 2B, these averaged spectra demonstrated a con-siderable baseline shift, especially between 6300 cm–1

(1587 nm) and 5100 cm–1 (1960 nm). For the P. placentasamples, the baseline shifts were more distinctive than forthe C. puteana samples, and a clear differentiation of dura-bility classes is shown. After MSC, differences were reduced(Figs. 2C and 2D); however, closer examination of the re-

gion from 6300 cm–1 (1587 nm) to 5300 cm–1 (1887 nm) in-dicated a clear association with the durability classes for theP. placenta group as well as for the C. puteana ones(Figs. 2C and 2D).

Spectral variability among the durability classes was alsoinvestigated through principal components analysis (Figs. 3Aand 3B). The scores plot with unmodified spectra (Fig. 3A)showed no patterns among the samples, whereas after apply-ing MSC to the spectra, a separation according to their dur-ability classes was observed (Fig. 3B). Besides principalcomponent (PC) 1 vs. PC 2, where the best separation wasseen, PC 2 vs. PC 3, PC 3 vs. PC 4, and PC 1 vs. PC 3 werealso investigated.

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Fig. 2. (A–D) Differences in the spectra of the wood samples when averaged in their natural durability classes (1 to 5). Spectra arepooled according to the results obtained from wood decay tests after Poria placenta (A) and Coniophora puteana (B) inoculation. Fig-ures 2C and 2D show the differences after multiplicative scatter correction (MSC).



Calibration models for the estimation of naturaldurability

A summary of the calibration models established with therelative mass loss data from P. placenta decay tests is foundin Table 3. The calibrations were highly acceptable (r =0.86–0.92), and it is shown that data preprocessing, espe-cially MSC, significantly improved the calibrations: r valuesincreased from 0.84 to 0.92 for calibration and from 0.82 to0.91 for cross validation, whereas root mean square errorsimproved from 0.098 to 0.073 for calibration and from 0.103to 0.077 for cross validation. The positive effect of MSC, asshown in the principal component analysis, was confirmed

by the improved model statistics. Automatic wave numberselection with the Martens uncertainty test led to compara-bly good test statistics, accompanied by a reduction in thenumber of principal components required from six to four.The wave number range between 6300 cm–1 (1587 nm) and5100 cm–1 (1960 nm), which exhibited the greatest differ-ences between the mean spectra of the durability classes(Figs. 2A–2D), resulted in a poorer calibration than usingwave numbers selected through the Martens uncertainty test(Table 3). However, compared with models without datapreprocessing with the entire wave number region included,model diagnostics (r, RMSEC, RMSEP) were even better,

© 2003 NRC Canada


Fig. 2 (concluded).



although only one principal component was necessary (Ta-ble 3). Calibration models established with the mass lossdata from C. puteana showed similar performance (Table 4).The improvement of the models after applying MSC waseven more drastic: r values increased from 0.79 to 0.97 forcalibration and from 0.76 to 0.97 for cross validation,whereas root mean square errors decreased from 0.191 to0.072 for calibration and from 0.201 to 0.078 for cross vali-dation.

NIR-predicted versus laboratory-determined x values areshown in Figs. 4A and 4B. The results were obtained fromcross-validation models using the entire wave number rangeand after MSC. Figure 4 shows once again the broader rangefor x values obtained from C. puteana tests and the superiorityof this model compared with the model based on P. placentatests. In most cases, the predicted and true durability classeswere the same, and the models were very well fit to the datafor all four provenances over the whole range (Fig. 4).

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Fig. 3. Scores plot of principal components (PC) 1 and 2 of the spectra before (A) and after multiplicative scatter correction (B). Sam-ples are marked according to the durability classes (class 1 to 5, description see Table 2) determined through wood decay tests usingPoria placenta.



© 2003 NRC Canada


Discussion

As Vittanen et al. (1997) demonstrated, natural durabilitydepends among others on tree species, tree age, and thewithin-tree position (e.g., inner vs. outer heartwood). Thiswas recently confirmed by Jaques et al. (2002) with a largesample set, who, in addition to observing that Japanese larchhad higher natural durability than European larch, also notedhuge variability across provenances, and among and withintrees. The large variation found in this study is due to differ-ent sources, including species (European and Japaneselarch), provenances (confounded with sites), and also thevariation observed among and within trees (inner and outerpart). The calculated mean durability classes, class 4 ifbased on P. placenta and class 3 if based on C. puteana,were well in agreement with results from Vittanen et al.(1997). If attacks of various fungi result in different durabil-ity classes, the score obtained for the most aggressive fungusmay be used (Van Acker et al. 1999). In our case,C. puteana was most aggressive and produced at the sametime more variable decay results.

Differences in the mean spectra between 6300 cm–1

(1587 nm) and 5300 cm–1 (1887 nm) are associated with thedurability classes (Figs. 2C–2D). This region includes firstovertones from C—H stretch of =CH2, methyl groups,methylen groups, and aromatic substances, and O—Hstretch/C—O stretch second overtone combinations presentin all main components of wood (e.g., cellulose, extractives,and lignin) (Shenk et al. 2001). Heartwood extractives play amajor role in natural durability, and for larch wood a strongcorrelation between the total amount of phenols and thex value was found recently (Gierlinger et al. 2003). Theflavonoid taxifolin (3,3′,4′,5,7-pentahydroxyflavanone), whichis known to be a major phenolic compound in larch heart-wood (Hegnauer 1962), shows strong bands within the rangefrom 6300 to 5300 cm–1 (1587–1887 nm) (Gierlinger et al.2002).

Statistics for both fungi demonstrated that good calibra-tions can be obtained to predict wood decay and confirmedthe assumption that calibrations can be used to rapidly pre-dict natural durability. Correlation coefficients were as highas 0.97 and comparable to those obtained from NIR models

Whole region*Automaticrestriction

Manualrestriction†

Nopreprocessing

1st-derivativeMSC

2nd-derivativeMSC MSC MSC MSC

r (calibration) 0.84 0.88 0.88 0.92 0.91 0.87r (cross validation) 0.82 0.87 0.86 0.91 0.90 0.86RMSEC 0.098 0.087 0.086 0.073 0.075 0.090RMSEP 0.103 0.090 0.093 0.077 0.079 0.091%RMSEP 14 12 13 11 11 13No. of PCs 5 3 5 6 4 1

Note: The mean and range for the x value were 0.72 and 0.27–1.13, respectively. RMSEC, root mean square errorof the calibration samples; RMSEP, root mean square error of the predicted samples; PC, principal components; MSC,multiplicative scatter correction.

*The wave number and wave length for the whole region are 9970–5100 cm–1 and 1000–1960 nm, respectively.†The wave number and wave length for manual restriction are 6300–5100 cm–1 and 1587–1960 nm, respectively.

Table 3. Statistics of partial least squares regression models for the prediction of x values based on themass loss after Poria placenta attack, with different preprocessing methods as well as manual and auto-matic (Martens uncertainty test) restriction of the wave number range.

Whole region*Automaticrestriction

Manualrestriction†

Nopreprocessing

1st-derivativeMSC

2nd-derivativeMSC MSC MSC MSC

r (calibration) 0.79 0.84 0.83 0.97 0.97 0.84r (cross validation) 0.76 0.82 0.82 0.97 0.97 0.83RMSEC 0.191 0.170 0.172 0.072 0.073 0.167RMSEP 0.201 0.177 0.177 0.078 0.08 0.175%RMSEP 38 33 33 14 15 33No. of PCs 5 3 2 6 6 4

Note: The mean and range for the x value were 0.53 and 0.07–1.58, respectively. RMSEC, root mean square errorof the calibration samples; RMSEP, root mean square error of the predicted samples; PC, principal components; MSC,multiplicative scatter correction.

*The wave number and wave length for the whole region are 9970–5100 cm–1 and 1000–1960 nm, respectively.†The wave number and wave length for manual restriction are 6300–5100 cm–1 and 1587–1960 nm, respectively.

Table 4. Statistics of partial least squares regression models for the prediction of x values based on themass loss after Coniophora puteana attack, with different preprocessing methods as well as manual andautomatic (Martens uncertainty test) restriction of the wave number range.



to predict extractive contents (Gierlinger et al. 2002) andwood density (Thygesen 1994). In this study, only two repli-cated tests were used for the calibration, and improvementmay be gained by increasing the replicates for calibrationdata. The accuracy of laboratory reference data is a crucialfactor for the quality of NIR prediction models. Althoughthe accuracy of biological wood decay tests is poor com-pared with chemical analyses, surprisingly good results wereachieved in this work. Coates (2002) demonstrated that NIR

spectroscopic calibration equations might produce predic-tions at higher accuracy than laboratory reference valuesfrom the calibration set.

In a previous study on NIR-based calibration models forlarch heartwood extractives, the restricted wave numberrange below 7500 cm–1 (1333 nm) turned out to be wellsuited, with no relevant information lost and a reduction inthe number of factors (Gierlinger et al. 2002). Similar re-strictions in the calibration model for natural durability didlead to significant information losses, resulting in reducedpower of prediction. With automatic restriction by means ofthe Martens uncertainty test, only a few single wave numberswere removed, which turned out to be more appropriate.

Multiplicative scatter correction (MSC) reduced differ-ences among averaged spectra and improved the relation tonatural durability classes as well as the model statistics forboth fungi. Predicting basic density, Thygesen (1994) foundthat MSC did not provide a consistent improvement. Thismay be explained by the influence of wood structure on den-sity and that scatter in that case does not interfere, but pro-vides additional information. MSC only slightly improvedcalibrations developed to predict the extractive contents oflarch heartwood (Gierlinger et al. 2002), because scatter ef-fects on wood powder samples are minor. In this study thepartial least squares regression calibrations predicting natu-ral durability of solid wood samples were substantially im-proved by MSC. As natural durability is strongly influencedby extractives, the chemical information may be of primaryimportance and may be pronounced by removing scatter ef-fects.

NIR spectroscopy has proved to be a reliable tool for theprediction of natural durability. For a comprehensive predic-tion of the bioresistance of larch heartwood, NIR modelscould be developed by taking into account several test fungi,laboratory, and field decay tests. Although such calibrationmodels will be labor intensive, once established they will al-low data to be acquired non destructively within minutes andallow a high number of samples to be processed. Since spec-tra can be taken from small samples, it is possible to esti-mate natural durability even from standing trees by takingincrement cores. Therefore, it seems particularly suitable forseveral forestry and wood studies where large numbers ofwood samples must be analysed nondestructively. This isparticularly true for tree breeding programs where hundredsof genotypes need to be surveyed nondestructively, for silvi-cultural studies with the necessity to test effects of differenttreatments, or for intensive surveys of wood resources.

Conclusions

Partial least squares regression calibrations, based on FT-NIR spectra and reference data of standardized wood decaytests, were successfully applied to estimate the natural dura-bility of larch heartwood. The optimized and verified cali-brations could be put into practice for the forest and forest-products industry to efficiently determine natural durability.This will lead to a better knowledge on the variability andthe environmental and genetic control of natural durabilityby quickly measuring large numbers of samples accuratelyand nondestructively. It may break new ground for selectionwithin tree breeding programs and for optimized wood utili-

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1734 Can. J. For. Res. Vol. 33, 2003

Fig. 4. Relationship between the actual x values obtained fromwood decay tests after Poria placenta (A) and Coniophoraputeana (B) inoculation and the x values predicted by NIR in thecross-validation step using all wave numbers and multiplicativescatter corrected spectra. The samples are marked according totheir provenances and sites (see Table 1).



zation. Potentially durable trees may be selected off-line oron-line during the manufacture process, the latter could be-come reality with spectral cameras, operating in the NIR,becoming more readily available.

Acknowledgements

The research was funded by the European Union projectTowards a European Larch Wood Chain (Agriculture andAgro-Industry including Fisheries Programme of Researchand Technological Development (FAIR - 4th FrameworkProgramme) FAIR 98-3354) and the research project TheCauses of Natural Durability in Larch (P15903, AustrianScience Fund). We thank Dr. Wolfgang Gindl (Institute ofWood Science and Technology) for enabling the analysis us-ing the Unscrambler software.

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