Density, Extractives and Decay Resistance Variabilities Within

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Density, extractives and decay resistance variabilities within branch wood from four agroforestry hardwood species F Terrasse, L Brancheriau, R Marchal, N Boutahar, S Lotte, D Guibal, L Pignolet, K Candelier

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F Terrasse, L Brancheriau, R Marchal, N Boutahar, S Lotte, et al.. Density, extractives and decay resistance variabilities within branch wood from four agroforestry hardwood species. iForest: Bio- geosciences and Forestry, Italian Society of Silviculture and Forest Ecology, 2021, 14 (3), pp.212-220. 10.3832/ifor3693-014. hal-03224030

HAL Id: hal-03224030 https://hal.archives-ouvertes.fr/hal-03224030 Submitted on 11 May 2021

HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Research Article ii FF o o r r e e s s t t doi: 10.3832/ifor3693-014 Biogeosciences and Forestry vol. 14, pp. 212-220

Density, extractives and decay resistance variabilities within branch wood from four agroforestry hardwood species

Florence Terrasse (1-2), Agroforestry practices like pruning trees to control the light flux to crops pro- Loic Brancheriau (1-2), duce every year a large volume of branches which is valorized by farmers as mulching or energy fuel. However, according to the literature, the wood of (3) Remy Marchal , branches shows higher rates of polyphenols than stem wood and this can open Nabila Boutahar (1-2), some new perspectives for branch exploitation. In this study, the wood proper- Sylvain Lotte (1-2), ties (density, mechanical properties, extractive content and decay resistance) (1-2) were determined on branches of different sizes from oak, chestnut, poplar Daniel Guibal , and walnut trees collected in two agroforestry systems. These properties were Luc Pignolet (1-2), evaluated according to the wood age and the sampling position along the radial Kevin Candelier (1-2) and longitudinal axes of the branch. All samples were analyzed by NIR-Spec- troscopy and a predicting model aimed to assess the branch wood properties has been developed. Wood characteristics largely vary between species and do not exactly follow the same trends from one species to another. Overall, hardwood density of branches is similar to that of trunks, the content in wood extractives follows similar evolutions, and the decay resistance of branch wood does not seem to be really impacted by its position along the branch. Reliable NIRS models were built to easily predict the wood density and extractives content of agroforestry branches. The extractives content and the decay resistance of branch hardwood appear to be substantially lower than those of trunks, which suggests a non-suitability of branch wood for developing high- valued green chemistry.

Keywords: Agroforestry, Branches, NIR-Spectrometry, Wood Quality

Introduction 1991), biodiversity conservation (Michon & large amounts of carbon, thereby contrib￹ - In many tropical countries, agroforestry De Foresta 1992) and above all in climate uting to mitigate the effects of climate systems provide both services for agricul- change mitigation (Hamon et al. 2009). change and providing a highly valuable ture and for non-food economic sectors Agroforestry trees differ from forestry woody resource to be used for various pur- (housing and energy). Agroforestry is de- trees in two ways: their roots dig deeper poses. Since six decades, European coun- fined as any landscape use system associat- (Mulia & Dupraz 2006), and they also grow tries (including France) have massively ex- ing trees or any other ligneous perennial faster and produce more biomass, most cluded trees from the cropfields in order to plants with animal and/or vegetal produc- likely because there is less competition for intensify mechanized agriculture. However, tions on the same surface unit (Nair 1990). the light and other resources (Dupraz & the current agro-ecological transition is go- Such a system provide not only environ- Liagre 2008). In addition, agroforestry ing to reverse this trend through the de- mental but also economic and social bene- trees usually grow in more fertilized soils sign of new agroforestry systems. fits to farming communities (Nair 1993, than those of forest trees. In some cases, Besides agricultural products, the main Sanchez 1995). Agroforestry play an impor- an agroforestry tree will produce about product specific to agroforestry systems is tant role in pests and pathogens control three times more biomass than a tree of wood. Trunks, branches and twigs all (World Agroforestry Centre – Jamnadass et the same age in a forest (Gavaland & Bur- have different potential uses due to their al. 2013), food security (Guitton 1994), soil nel 2005). This increased biomass enables diverse characteristics (ADEME/Atlanbois protection and natural amendment (Young agroforestry trees to potentially stock 2016) which are summarized in Fig. S1 (Sup- plementary material). Throughout their life cycle, agroforestry trees mostly yield prun- (1) CIRAD, Research Unit BioWooEB, 34000, Montpellier (France); (2) BioWooEB, Université ing wood from branches, which has the de Montpellier, CIRAD, Montpellier (France); (3) “Arts et Metiers” Institute of Technology, same wood orthotropic cylindrical organi- LABOMAP, HESAM University, F-71250 Cluny (France) zation as trunks (Fig. S1) and currently is mostly used as Ramial Chipped Wood @ Kevin Candelier ([email protected]) (RCW) or animal litter (Malignier & Bala- guer 2017). Received: Nov 09, 2020 - Accepted: Mar 01, 2021 Branch wood has been poorly investigated compared to stem wood, and cur- Citation: Terrasse F, Brancheriau L, Marchal R, Boutahar N, Lotte S, Guibal D, Pignolet L, rently there is a lack of data which could Candelier K (2021). Density, extractives and decay resistance variabilities within branch support any potential added-value of the wood from four agroforestry hardwood species. iForest 14: 212-220. – doi: 10.3832/ifor3693- branches for any production path. 014 [online 2021-05-02] Regarding the physical aspects, some studies reported that the mechanical char- Communicated by: Luigi Todaro acteristics of branches’ wood are usually reduced compared to those of the trunks

y properties were then compared to those r Fig. 1 - Sam- t of wood from the trunk of the same trees. s pling, pro- e Additionally, all samples were analyzed by r cessing and o NIR-Spectroscopy with the aim of develop-

F selection of ing a fast system to assess the branch d wood sam- wood properties directly in the field. n ples. a s

e Material and methods c n e Tree selection i c The selected hardwoods species were s o sweet chestnut (Castanea Sativa Mill.), pe- e dunculate oak (Quercus robur), hybrid wal- g o

i nut (Juglans × intermedia [C. DC.] Carrière, B

hybrid Juglans nigra × Juglans regia) and hy- –

brid poplar (Populus generosa Henry). t s Chestnuts and oaks were sampled near e r Fougères, France (48° 21′ 05.62″ N, 01° 12′ o 16.65″ W), while poplars and walnuts were F i sampled near Alès, France (44° 07′ 37.934″ N. 04° 05′ 0.067″ E). The sampled chestnuts and oaks were planted as grasslands’ hedges, whereas walnuts and poplars were planted within grasslands plots (intraplot). The selected trees were sampled in Feb- ruary 2019 to limit the seasonal impact on wood chemical composition (i.e., starch in sapwood). A total of 9 trees were sampled from which 15 branches were taken (one to three branches per tree). The details are summarized in Fig. 1. For each species, the harvested branches were split in three sectors according to their distance to the tree trunk. The three branch sectors were defined as follows: (Gurau et al. 2008). Other researchers in- These are non-structural wood cell compo- • Sector 1: 100% of the branch diameter at vestigated the density and anatomy of nents of low molecular weight which act as the knot’s level; branches in several species (Dadzie et al. natural chemical products mainly protect- • Sector 2: 70-90% ± 3% of the branch diam- 2016, Kiaei et al. 2014), finding that in most ing lignocellulose from fungal and micro- eter at the knot’s level; cases the wood density of branches seems bial attacks (Pecha & Garcia-Perez 2015). • Sector 3: 40-70% ± 5% of the branch diam- to be higher than that of the trunks. Yet, This study investigated the potential of eter at the knot’s level. this characteristic, as most of other wood branch wood from agroforestry practices A total of 45 branch sectors were sam- characteristics, seems to be highly variable as base material to develop green chem- pled. The age of the branch wood is re- depending on the tree species considered. istry and/or to manufacture biomaterials. ported in Tab. 1, according to the tree spe- Such differences also appear when consid- Farmers prune their trees every year to cies and the branch sector. Based on these ering wood chemical properties, which manage light reaching the ground, and the data, we supposed than the majority of strongly change moving from one tree or- harvested biomass can help improve the wood samples is mainly composed by sap- gan to another. Tree knots along the stem economic model of agroforestry plots. To wood portion or sometimes by transition have been particularly studied, resulting in test the suitability of such a woody bio- wood, as for example in sector 1 for chest- most cases richer in extractives than trunks mass to the above goals, wood physical nut. and branches both in hardwoods and soft- and chemical characteristics were investi- woods (Košíková 2009, Kebbi-Benkeder gated on branches from four species of Sample partitioning, conditioning and 2015). Furthermore, branches seem to be agroforestry hardwoods collected in inter- density measurement richer in extractives than the trunk clear plot systems (oak and chestnut) and in al- Each of the 45 branch sectors was firstly wood, although they are poorer than the ley-cropped system (poplar and walnut). cut into diametric vertical planks (30 mm knots (Xu et al. 2007, Morikawa et al. 2014). The evolution of wood density, extractives width) using a band saw (Fig. 1), taking They also present a higher durability than content and durability with the age of care of including both normal and tension the trunks (Dadzie & Amoah 2015), due to wood along the radial and longitudinal wood (wherever present). The planks were the higher content of wood extractives. axes of the branches was assessed. These then cut into wood sticks (15 × 5 mm2) at four radial locations. The wood sticks were then cut into test pieces sized 25 × 15 × 5 Tab. 1 - Age of the branch wood according to the position sector in the branch for the mm3 (L: longitudinal; T: tangential; R: ra- four hardwood species. dial). These samples were stabilized at a moisture content (MC) of 12% in humid air Branch Age of the branch wood (years) at 20 °C ± 2 °C and 65 % ± 5 % RH. Air-dried density of samples was determined by Sector Chestnut Oak Walnut Poplar weighing and measuring their volume us- Sector 1 9 ± 1 18 ± 4 14 ± 2 14 ± 5 ing a vernier caliper, prior to further test- Sector 2 8 ± 1 15 ± 2 13 ± 1 12 ± 5 ing. Overall, 1080 samples were prepared Sector 3 6 ± 1 11 ± 1 12 ± 1 10 ± 4 and used as shown in Fig. 1. In addition, increment cores (5 mm in di-

213 iForest 14: 212-220 Properties variability of agroforestry branch woods

ameter, 20 cm long) were taken from the fungus. The incubation of test pieces was models. The data was divided into two y r trunk of sampled trees near the insertion carried out for 8 weeks in a climatic cham- sets: a calibration set (2/3 of the total num- t s zone of branches (1 core per branch, total- ber (22 ± 2 °C and 70 ± 5% RH). Once the ber of samples) and a validation set (1/3). e r

ing 15 cores samples). Each core was cut in fungal exposure was completed, samples The property values to predict were first o F three parts (5 mm in diameter, 25 mm were carefully cleaned from the fungus. All sorted and the validation set was built by long) that were used for extraction (using samples were then oven dried at 103 °C for picking one sample on three. The k-fold d n a a protocol similar to that describe below), 48 h and weighed (m5). Mass loss (ML, %) cross validation method was used on the s

in order to compare the extractive content due to the decay degradation of the sam- calibration set with 10 random segments. e of the stem wood to that of the wood ple was calculated as (eqn. 2): The quality of the models was given by c n from the corresponding branches. computing the following parameters (Naes e m4−m5 i ML(%)= ⋅100 (2) et al. 2004): the coefficient of determina- c m4 s Extraction processes tion of calibration (R²C), the standard error o All experimental procedures used in the The wood durability classes were then at- of calibration (SEC), the root mean square e g o

determination of the extractive content tributed according to the XP-CEN/TS-15083- error of cross validation (RMSECV), the co- i B

were adapted, with minor modifications, 1 (2006) standard. efficient of determination of calibration – from Rowell et al. (2005). (R²P), the root mean square error of predic- t

Each sample was dried at 103 °C to deter- Near infrared spectroscopy tion (RMSEP), the ratio of performance to s e mine its initial anhydrous mass (m2) and measurements deviation (RPD). r then extracted in a soxhlet with Toluene : Near infrared spectra were obtained in o F Ethanol (Sigma Aldrich, 32201-M) 2:1 (v:v) the radial tangential plane of all test Results and discussions i solution (2 × 6 h, intercalated by 15 h of pieces, after a stabilization step performed maceration in the extraction solvents) fol- at 20 °C ± 2 °C and 65 % ± 5 % RH. Chaix et al. Prediction of the wood density and lowing by distilled water (2 × 6 h, interca- (2015) showed that regression models yield extractive content by NIRS modelling lated by 15 h of maceration in the extrac- accurate predictions when measurements Fig. 2A presents the comparison of the tion solvents), and then dried at 103 °C for are made on this plane. A Bruker Vector 22/ density values predicted by PLS regression ® 48 h to obtain the anhydrous mass (m3). N spectrophotometer (Bruker Co., Biller- with the measured ones. Ten components The wood extractive content (E), in per- ica, MS, USA) and the OPUS® software ver. were selected for the model. The coeffi- centage of dry weight (DW), was deter- 5.5 were used in diffuse reflectance mode cient of determination value was R²C = 0.91 mined according to the following equation with a sintered gold standard as reference. (SEC = 0.04 g cm-3, RMSECV = 0.05 g cm-3) (eqn. 1): Data were measured for wavelengths be- for the calibration set. The predictive per- tween 9000 to 4000 cm-1 (1100 to 2500 formance of the model on the validation (m2−m3) E (% DW)= ⋅100 (1) -1 m nm), in 8 cm increments. The spectra were set was R²P = 0.89, with a RMSEP value of 2 composed by 648 wavelengths of reflec- 0.05 g cm-3. The values of SEC, RMSECV and where m2 is the theoretical anhydrous tance values. Sixteen scans were per- RMSEP were sufficiently close and showed mass of the test piece before extractions formed and averaged for each measure- that the model was robust. The value of and m3 is its anhydrous mass after the ex- ment in order to improve the signal-to- the ratio of performance to deviation was tractions. A total of 540 samples were noise ratio. RPD = 3.0, highlighting that this model was characterized for their extraction rate. suitable for predictions (Williams & Sober- Statistical analysis ing 1993). These results were in agreement Decay resistance tests Statistical analysis was performed using with previous published studies (Gindlet et To carry out the durability screening test, the software RStudio Desktop® ver. 1.2 al. 2001, Schimleck et al. 2003, Mora et al. the two following decay fungi were used: (RStudio Inc., Boston, MS, USA). To under- 2008, Hein et al. 2009, Leblon et al. 2013). Trametes versicolor (L.) Lloyd (TV) and Co- stand the evolution of the characteristics Schimleck et al. (2003) showed that it was niophora puteana (Schumach.) P. Karst. measured within branches, Kruskall-Wallis possible to accurately calibrate NIR models (CP), respectively a white rot and a brown tests have been applied on each potential for a wide range of species that represent rot fungi. These two fungi has been se- explicative factor and response variable. different taxa, wood chemistry and physi- lected because they are mandatory by the For each test indicating an effect of a fac- cal properties. NIR absorbance spectra are XP-CEN/TS-15083-1 (2006) standard in the tor on a studied variable, Wilcoxon tests related to the chemical composition of the determination of natural decay resistance were used to investigate the nature of this tested wood sample (Leblon et al. 2013). of hardwood species. effect and the significance of the differ- The NIR spectroscopy technique is usable Decay tests were performed according to ences between different groups. in assessing wood physical properties (in- the procedure described by Bravery (1978). NIRS spectra were first transformed cluding density) because these properties Sterile culture media were prepared with (Naes et al. 2004) with a Standard Normal vary with the chemical properties within a 40 ± 0.5 g of malt extract and 20 ± 0.5 g of Variate (SNV) correction to reduce the ef- tree, but also because the infrared light powdered agar dissolved in 1 L of distilled fect of irregularities of surface and the in- contains information of chemical compo- water. They were then molded in glass con- tra spectrum variability (correction of the nents (light absorption) associated with tainers, closed by cotton plugs to enable light dispersion). The second derivative physical characteristics (light scattered) air circulation. The jellified culture media was then computed using the algorithm of like surface texture or porosity (Burns & were inoculated with a piece of 1 cm in di- Savitzky Golay with a smoothing range of Ciurczak 2008, Schwanninger et al. 2011, ameter. Then, the containers were incu- 21 data points and a third degree polyno- Sandak et al. 2016). bated for two weeks in climatic chambers mial (Savitzky & Golay 1964). The use of Fig. 2B shows the result of the PLS regres- (22 ± 2 °C and 70 ± 5 % RH), until a full colo- this derivative allowed to separate overlap- sion to predict the extractive contents. The nization of the medium by the mycelium ping peaks and correct the baseline devia- model was built with 7 components, and was reached. tion of spectra. Mathematical corrections the R²C value was 0.86 (SEC = 0.95% and Weight and humidity of the conditioned were applied using the software package RMSECV = 1.05%) for the calibration set. wood block samples were measured to de- “prospectr” ver. 0.1.3. NIRS models to pre- The coefficient of determination for the termine their theoretical anhydrous mass dict the density, the extractive contents validation set was R²P = 0.85, with a RMSEP (m4), and then sterilized in an autoclave at and the mass loss were developed with the value of 0.96%. As with density, this model 121 °C by two successive steps of 20 min, Partial Least Squares (PLS) regression was found to be robust, and the value of before decay resistance tests. Two hun- method using the software package “pls”, the ratio RPD was 2.6. Investigations on dred seventy test pieces were tested per ver. 2.7.1. No outlier was removed in the wood chemical composition, specifically on iForest 14: 212-220 214 Terrasse F et al. - iForest 14: 212-220 y r Fig. 2 - Relationship between t s measured and predicted den- e r sity (A) and branch wood o

F extractive content (B) by

d NIRS modelling. (a) Calibra- n tion set with different marks a

s by species; (b) calibration and e

c validation set (white circle: n calibration set; black circles: e i validation set). Continuous c s lines represent regression o

e lines, while dotted lines are g the identity lines (y = x). o i B

– t s e r o F i

extractive contents, using NIR were previ- linked to the restricted spectral range and phyllum trabeum and Coniophora puteana. ously reported (Meder et al. 1999, Esteves resolution of the portable spectrometer. The authors obtained a coefficient of deter- & Pereira 2008, Gierlinger et al. 2002, The quality of the model might also have mination from cross validation of 0.93 and Tsuchikawa & Kobori 2015, Razafimahatra- been the result of mixing of different a RMSEP value of 3.3% for Coniophora pute- tra et al. 2018). Our results are in agree- chemical signature between species, add- ana (with radial surface tests and a second ment with the findings of the aforemen- ing to quantitative variations of composi- derivative pre-processing). tioned studies. Wood extractives include tion within each chemical signature in each In the present study, the regression co- heterogeneous groups of chemical com- species. efficients between the data predicted by pounds, and they can be grouped by the NIRS models and the observed data are type of solvent used during their extrac- Predictability of the fungal durability by very low when all the species are consid- tion (Gierlinger et al. 2002, Razafimahatra- NIRS modelling ered together (0.43 and 0.53 for TV and CP, tra et al. 2018). Gierlinger et al. (2002) de- Wood degradation is a topic of high inter- respectively). The white rot induced mass veloped NIR models on wood powder and est in NIR wood research because it allows loss is approached with a precision of ± 11% on solid wood to determine the hot water the detection of chemical changes as spec- of the dry weight, and the brown rot in- and acetone extractive content of Larix sp. tral variation (Tsuchikawa & Kobori 2015). duced mass loss with a precision of ± 7%. The authors stated that the solid wood Fackler & Schwanninger (2010) used NIR Those precision levels are insufficient to re- models were less predictive than those de- spectroscopy to investigate the overtones liably determine the durability classes of rived from wood powder because addi- of C-H and O-H stretching vibrations; in par- the wood. In that case, the NIRS models tional factors, such as the varying wood ticular, to better understand degradation cannot be used to build reliable prediction structure (e.g., earlywood vs. latewood processes of lignin, cellulose and hemicel- models of the white and brown rot in- within annual rings), sample geometry or luloses during brown rot. The mass losses duced mass losses. surface properties, might add to the exist- induced by brown rots (Coniophora pute- NIRS provides measures directly linked to ing complex chemistry. The characteristics ana, Gloeophyllum trabeum) and a white the chemistry of the wood since it mea- of the models related to solid wood were rot (Trametes versicolor) were predicted by sures chemical bonds. As a consequence, it R²P = 0.74 (RMSEP = 1.88%) for the hot wa- NIRS measurements on Sequoia semper- is expected that reliable models could be ter extractives contents, and R²P = 0.78 virens (D. Don) Endl. samples (Jones et al. built to accurately assess the wood bio- (RMSEP = 0.36%) for the acetone extractive 2011). The spectra were acquired on the ra- chemical composition (i.e., extractive con- content. A multi-species model was devel- dial-longitudinal face of wood blocks. The tent) and its density, which is strongly cor- oped by Razafimahatratra et al. (2018) to authors found RPD ratios in cross-valida- related to this first variable. Although determine the ethanol-toluene extractive tion between 1.3 to 1.4, and stated that the wood extractives and density are often contents with a portable spectrometer. models could be used to separate the correlated with wood durability, the NIRS The main characteristics were a coefficient heartwood for high and low values of mass models do not accurately predict the decay of determination of cross validation of 0.64 loss with fungal decay testing. Sykacek et resistance of branch wood. The chemical and a RMSECV value of 1.54%. The authors al. (2006) investigated the natural durabil- composition of the extractive fraction of reported that the quality of the model was ity of Larix spp. using the test fungi Gloeo- wood (chemical signature) largely depend

215 iForest 14: 212-220 Properties variability of agroforestry branch woods

on the woody species and this could ex- wise, the chestnut branches of the trees A pith: the closest to the bark, the denser the y r plain the difficulty to build an accurate and C, and the poplar branches of the trees wood is. The same tendency can be ob- t s

NIRS models to predict the fungal durabil- J and K all displayed significantly different served for oak, but neither for it nor for e r

ity of wood. densities. This intra-species density varia- walnut wood does the distance to the pith o F

tion was not detected for walnut trees. For significantly affect the density. It is rather the studied species, the wood density was clear that the variation in wood density d

Variability of branches wood air-dried n a density similar for all the branches within a single along the radius is very different among s

tree. species. For example some wood species e

Variations between branches like Dicorynia guianensis Amshoff show c n

The wood density of branches appeared Variations inside branches nearly no variations, while Parkia nitida e i different both among and within species. Within a branch, the wood density varied Miq. has a density variation from 0.2 to 0.5 c s -3 Oak branches wood (0.76 ± 0.06 g cm ) re- with the location of the wood. Fig. 3 shows between pith and bark, within the trunk o sulted to be denser than walnut (0.68 ± that the variation of wood density with the (Lehnebach et al. 2019). e g o

0.04), chestnut and poplar wood (0.59 ± distance from the trunk depends on the Overall, branch wood density significantly i -3 B

0.07 and 0.48 ± 0.07 g cm , respectively). species. Unless for poplar, the wood that decreases with the distance to the trunk –

Regarding the oak samples, the wood den- was closest to the trunk (sector 1: 0.67 ± and significantly increases with the dis- -3 t sities of the branches F0 and F2 (0.78 ± 0.13 g cm on average) showed a signifi- tance to the pith. For all the considered s

-3 e

0.04 and 0.80 ± 0.06 g cm , respectively) cantly higher density than woods located species, the wood density is quite similar r significantly differed from those of the further away from it (sectors 2 and 3: 0.61 ± between trunks and branches but this o F branches G1 and G2 (0.74 ± 0.04 and 0.72 ± 0.12 and 0.61 ± 0.11 g cm-3 on average, re- point is to be confirmed with specific trials. i 0.06 g cm-3, respectively) after the Wilcox- spectively). Concerning the radial location Sarmiento et al. (2011) highlighted that on tests, while there are no significant den- of the wood (Fig. 3), it appeared that the trunk and branch xylem densities of vari- sity variations between the branches of the wood density of chestnut and poplar ous French Guiana tree species were sig- oak F or between those of the oak G. Like- branches increases with the distance to the nificantly and positively correlated with ra-

Fig. 3 - Mean density of branch wood in four hardwood species Fig. 4 - Mean extractive content of branch wood in four hard- as a function of the distance to the trunk (left column) and to wood species as a function of the distance to the trunk (left the pith (right column). Bars followed by the same letter are column) and to the pith (right column). Bar followed by the not significantly different. same letter are not significantly different. iForest 14: 212-220 216 Terrasse F et al. - iForest 14: 212-220

y ical woods growing in dense forests that r Tab. 2 - Mean content of wood extractives (% dry weight) in the knots and clear heart- t the wood density increases with its dis- s wood of the four hardwood species (from Kebbi-Benkeder 2015 and *Pietarinen et al. e tance from the pith, but this is not true for r 2006a, 2006b). o the same species growing in open condi- F

tions like in plantations. Our result suggest d Component Chestnut Holm Oak Walnut Poplar* that the same pattern is to be found on n a

Knots (average of young, mild, old knots) 17.4 14.2 10.9 < 10 branch wood, as the average wood density s e Trunk heartwood 10.3 12.7 13.3 < 7 next to the pith is significantly lower than c that recorded at the distal end of the n Trunk sapwood 7.3 9.3 6.3 - e branch. i c s o Variability of extractive contents of e dial and longitudinal position within the is not so clear for all species and all grow- g branch woods o

i branch or the trunk. ing conditions. There are very few evidence B

Branch wood density decreases when the of typical variations in extractive content Variation among branches –

distance to the trunk increases (Fig. 3). The associated to juvenility, mainly because the As shown in Fig. 4, the wood extractive t s fact that the sections of wood furthest deposition of extractives in the heartwood contents were the highest in oak branches e r from the trunk likely contain more juvenile occurs much later than the thickening of and slightly lower in walnut branches, o wood than those closest to the trunk could the cell walls. On old trees with good dura- while being still significantly higher in these F i explain this phenomenon. Gryc et al. (2011) bility, the resistance to rot is often much than in poplar and chestnut branches. and Latorraca et al. (2011) showed that the lower near the pith but this is mostly due Within species, the extractive content of juvenile wood of 115 old-grown Norway to the age of the heartwood and its extrac- branch wood did not significantly differ, spruce (Picea abies Karst.), 98 old-grown tives near the pith. In addition, the wood neither among the same trees nor among Scots pine (Pinus sylvestris L.) and 80 old- density is related to the tree structure (An- different trees. Considering all species, the grown European larch (Larix decidua Mill.) ten et al. 2010) and the trunk/branch junc- extractive content seems to be lower in from the Czech Republic and 14 old-grown tion has to be strong and resistant to the branches than in the knots and even Black locust (Robinia pseudoacacia L.) trees degradation, with mechanical stresses very than in the trunk (Tab. 2), according to the from different forest sites in Eastern-Ger- different from the trunk, due to the in- findings of Kebbi-Benkeder (2015). This ten- many and Eastern Hungary, is produced clined growing of the branch. dency has been confirmed in oaks and wal- during the first five year of life of the tree The studied wood characteristics also nuts in this study. The extractive content and it is less dense, less rich in extractives present a radial pattern within branches has been evaluated on increment cores and less durable than mature wood which that follows the same pattern as within sampled in the trunk near the branch inser- is produced later. However, such tendency trunks. McLean et al. (2011) noticed in trop- tion zone and in the sapwood area (near the bark). On average, oak branches con- Fig. 5 - Natural tained 7.9 ± 1.5% of extractives and their durability of branch corresponding samples from the nearby wood exposed to trunk contained 10.6%. Walnut branches (A) Trametes versi- contained 5.4 ± 0.9% of wood extractives color (L.) Lloyd. and while their trunk had 7.62%. Chestnut and for (B) Coniophora poplar branches were the poorest in wood puteana (Schu- extractives as they only contained 3.2 ± mach.) P. Karst. 0.9% and 2.0 ± 0.8% of those, respectively. (1, 2, 3): position of the wood sample Variation within branches along the branch, Oak and chestnut extractive rates tended in order of increas- to increase with distance from the trunk ing distance from (Fig. 4), but this tendency was only signifi- the trunk (see text cant between the group of the two first for further details). sectors and the last one and did not appear (<33, 33-66, >66%): in the case of walnut and poplar branches. radial position of In the radial direction, chestnut and poplar the wood sample showed a slight but significant increase of within the branch extractive rates with the distance from the diameter, in order pith of the branches (Fig. 4). Such an evolu- of increasing dis- tion did not appear in the case of walnut tance from the and oak wood, which had the same extrac- pith. tive content level in the three radial posi- tions. Globally, the variation of extractive contents linked to the distance from the pith is quite low and never exceed +1%. Pooling the data of the four hardwoods species altogether, it appeared that the distance to the trunks did not significantly impact on the wood extractive contents. However, the radial locations of the wood in the branch did slightly differ in extraction contents, which increased when ap- proaching the bark (5.3 ± 2.5%), perhaps showing a bark neighborhood effect, as the bark is usually rich of extractives. In addition, there are strong differences in ex-

217 iForest 14: 212-220 Properties variability of agroforestry branch woods

tractives in the sapwood, which can be due y Tab. 3 - Mean values and standard deviations (SD) of mass loss due to fungal degrada- r to nutrients like starch with high levels of t tion and the associated wood durability classes (according to XP-CEN/TS-15083-1 s variation depending on the season, and in e 2006) against Trametes versicolor (L.) Lloyd (TV) and Coniophora puteana (CP) and r the heartwood where extractives are main- o

comparison with the durability class of trunk wood from similar woody species F ly defense products with no significant variation among seasons. (*: CIRAD 2012a, 2012b, 2012c, 2012d). d n a

Wood Species s

Variability of fungal decays of branch Parameter e woods origin Chestnut Oak Walnut Poplar c n

Branches Mean Mass loss due to TV (%) 34.4 28.2 39.0 35.4 e i

White rot (Trametes versicolor - TV) c SD Mass loss due to TV (%) 0.2 0.1 0.1 0.1 s

Wood mass loss induced by white rot o showed a large variation (Fig. 5A). Walnut Durability class - TV 5 4 5 5 e g

Mean Mass loss due to CP (%) 10.4 17.7 22.60 19.5 o wood showed the highest range of values i B

(median value of 39.0%), followed by pop- SD Mass loss due to CP (%) 0.1 0.1 0.1 0.1 – lar (median value of 35.4 %) and chestnut

Durability class - CP 3 4 4 4 t

(median value of 34.4%) then oak (median s Durability class 5 4 5 5 e value of 28.2 %), which was in this case the r most durable wood. Trunk Durability class (CIRAD*) 2 2 3 3 o F According to wood durability classes re- i garding white rot (Tab. 3), it seems that for all wood species, the durability of heart- The large dispersion of ML values could wood density along the branches de- wood and sapwood from branches was be due to the wide range of diameters and creased with the distance to the trunk and particularly lower than that recorded for ages of the branches sampled in this study. slightly increased with the distance to the the trunk heartwood. The durability screening tests ideally re- pith. A similar pattern was observed for the quire the presence of several growth rings extractive content of wood, but at a much Brown rot (Coniphora puteana - CP) on a single sample and the test pieces lower level in branches than in trunks. Ac- A tendency similar to that observed with were often too small to meet this require- cording to the literature, also wood dura- TV can also be detected with CP (Fig. 5B), ment, which can lessen the precision of the bility of the four hardwood species was mainly in oak (except for the wood near results. Further, the measures were based much lower in branches than in trunks, but the pith) and chestnut wood; indeed, we on the dry weight of wood samples and, it seemed to decrease with the distance to found a decrease of durability when the ra- with a thickness of 5 mm only, it is possible the trunk and the pith. These last observa- tio of sapwood grows (Fig. 5B). Pooling the that the sole manipulation of the test tions should be considered cautiously and data obtained for all the species, the dis- pieces altered their relative humidity, thus additional experiments with bigger test tance to the trunk significantly affected the introducing a bias in the observed results. pieces should be done to consolidate these wood durability, which is in contrast with conclusions. Ultimately, this study did not what observed when the radial position Conclusion reveal any manifest suitability of branch was considered (Fig. 6). This study provides new knowledge on wood from agroforestry practices for Wood durability tended to decrease from branch wood from agroforestry systems, green chemistry, because of the quite low the trunk to the branch extremity and from which are still under-studied so far. The re- extractive ratios. However, further studies the pith to the bark. This trend mainly con- sults obtained highlight the evolution and on the composition of wood extractive cerned chestnut and walnut, and is likely variability of the physical and chemical might throw light on the possible existence due to the higher ratio of sapwood when characteristics of branch wood from agroof molecule of interest in branch wood. Al- moving from the trunk to the branch ends forestry hardwoods. As reported by previ- though woods from trunk and branches or from the pith to the bark. When the ous studies, wood density was quite similar have a similar chemical signature for each data obtained for all the four species were in branches and in trunks. Indeed, the given species, the content level of some pooled, the distances to the trunk and to the pith had a significant effect on branch wood durability (Fig. 6). Fig. 6 - Median mass Globally, the durability of the four hard- loss (% of dry weight) of woods regarding brown rot fungi was branch hardwood, de- higher than that towards white rot fungi, pending on the infect- which is consistent with previous findings ing fungi and the dis- reported in the literature (Sun et al. 2017). tance to the trunk (A) Overall, the averages of mass loss were and to the pith (B). Val- 17.6% and 34.2% for CP and TV, respectively. ues followed by the Walnut was always the less durable spe- same letter are not sig- cies, whilst oak the more durable to white nificantly different. rot and chestnut the more resistant to brown rot. Our results showed that the coefficient of variation is higher for extractive contents than for density in almost every case. This was expected to some extent, as the variation of mass loss due to degradation is linked to both the chemical variation in the nature and the content of extractives and to the action of the fungi itself. Therefore, even for wood from the same tree with very similar chemical composition, rather large CV values can be observed. iForest 14: 212-220 218 Terrasse F et al. - iForest 14: 212-220

y chemical compounds may be higher in the actéristiques technologiques de 245 essences Hamon X, Dupraz C, Liagre F (2009). L’Agrofor- r t branches than in the trunk. Furthermore, forestières tropicales, CIRAD, France, CIRAD, esterie, outil de séquestration du carbone en s e wood density in branches is equivalent to France, pp. 4. [in French] [online] URL: http:// agriculture [Agroforestry: a tool for carbon se- r

o that of trunks, which suggest similar me- tropix.cirad.fr/FichiersComplementaires/FR/Te questration in agriculture]. AGROOF, Bureau F

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