Mitrović et al., 2019, Biologica Nyssana 10(2) 10 (2) December 2019: 65-75 DOI: 10.5281/zenodo.3600172 Serbian spruce (Picea omorika (Pančić) Purkyné) - endemicity and advantages Review Article Aleksandra Lj. Mitrović Institute for Multidisciplinary Research, University of Belgrade, Kneza Višeslava 1, 11000 Belgrade, Serbia mita@imsi.rs (corresponding author) Jelena Bogdanović Pristov Institute for Multidisciplinary Research, University of Belgrade, Kneza Višeslava 1, 11000 Belgrade, Serbia mala@imsi.rs Jasna Simonović Radosavljević Institute for Multidisciplinary Research, University of Belgrade, Kneza Višeslava 1, 11000 Belgrade, Serbia jasna@imsi.rs Lloyd Donaldson Scion, Private Bag 3020, Rotorua 3010, New Zealand lloyd.donaldson@scionresearch.com Ksenija Radotić Institute for Multidisciplinary Research, University of Belgrade, Kneza Višeslava 1, 11000 Belgrade, Serbia xenia@imsi.rs Received: July 09, 2019 Revised: October 12, 2019 Accepted: December 06, 2019 Abstract: Conifers, as a response to mechanical stress, such as wind and stem lean, form reaction wood called compression wood (CW). CW occurs in a range of gra- dations from near normal wood (NW) to severe CW (SCW). As the severity of CW affects the mechanical and chemical properties of wood, and as CW has limited value in the forest products industry, it is desirable to be able to meas- ure CW severity. Picea omorika belong to slow-growing conifer species in which CW typically occurs in a severe form. We developed different morpho- metric and non-morphometric methods for estimation of CW severity tested on wood samples of P. omorika juvenile trees exposed to long term static bending. This specific review is aimed at presenting P. omorika as one of the most adaptable spruces, and as a good model for testing of methods for esti- mation of compression wood severity. First, we summarize main knowledge about P. omorika, features of CW, and methods for assessment of wood qual- ity. Then, we present breifly our recently published methods for estimation of compression wood severity tested on P. omorika juvenile wood samples. Key words: cell wall, cellulose fibrils, compression wood, fluorescence-detected linear dichroism microscopy, double wall thickness Apstract: Omorika (Picea omorika (Pančić) Purkiné) - endemičnost i perspektive Konifere kao odgovor na mehanički stres (vetar, savijanje) formiraju reak- ciono drvo koje se naziva kompresiono drvo (CW). CW se javlja u nizu gradacija od skoro normalnog drveta (NW) do jako izraženog CW (SCW). S obzirom da stepen izraženosti osobina CW ima značajan uticaj na mehaničke i hemijske osobine drveta i da CW ima ograničenu vrednost za drvnu industriju, poželjno je moći odrediti stepen izraženosti osobina CW u uzorku. Picea omorika spada u sporo rastuće četinarske vrste kod kojih se CW tipočno javlja u jako izraženoj formi. Mi smo razvili nekoliko morfo- metrijskih i ne-morfometrijskih metoda za procenu izraženosti osobina CW u uzorku, testiranih na uzorcima drveta juvenilnih stabala P. omorika koja su bila izložena dugotajnom statičkom savijanju. Ovaj revijski rad ima za cilj da predstavi Pančićevu omoriku kao jednu od najadaptabilnijih smrča i kao dobar model za testiranje metoda za procenu izraženosti osobina CW u uzorku. U prvom delu sumiramo znanja o Pančićevoj omorici, osobinama CW i metodama za procenu kvaliteta drveta, a u drugom ukratko predstav- ljamo naše nedavno objavljene metode za za procenu izraženosti osobina CW u uzorku, testirane na uzorcima drveta juvenilnih stabala P. omorika. Ključne reči: ćelijski zid, celulozni fibrili, kompresiono drvo, fluorescentna konfokalna mikroskopija, debljina ćelijskog zida Introduction Picea omorika (Pančić) Purkynĕ is a a rare and endangered tertiary relict and endemic species (Jovanović, 1970). Despite its endemism, P. omorika is considered as one of the most adaptable spruces (Sevill et al., 2017). Conifers, as a response to mechanical stress, form reaction wood called compression wood (CW) (Timell, 1986). CW occurs in a range of gradations from near normal wood (NW) to severe CW (SCW). The degree of development of particular features of CW does not necessarily change in parallel to each other, so the severity of a given tracheid is represent- ed as a function of the degrees of development of in- dividual features, mainly lignification, helical cavi- © 2019 Mitrović et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and build upon your work non-commercially under the same license as the original. 65 13th Symposium on the Flora of Southeastern Serbia and Neighboring Regions ties and cell wall thickness (Yumoto et al., 1983). As CW has limited value in the forest products industry it is of great importance to be able to measure CW severity (Altaner et al., 2009). In recent years we worked on the development of different morphometric and non-morphometric methods for distinguishing wood samples on the compression severity scale. They are based on tra- cheid double wall thickness (Nedzved et al., 2018), cellulose microfibrils order (Savić et al., 2016), or variation in lignin structure (Mitrović et al., 2015). We used confocal fluorescence microscopy and spectroscopy, combined with development of ad- ditional equipment, new algorithms and statistical analysis. We tested our methods on stem samples of P. omorika juvenile trees exposed to long term static bending. Picea omorika belongs to slow-growing conifer species, its wood is characterized by small, densely packed tracheids, while CW typically occurs in a severe form (Timell 1986; Donaldson et al., 2004). Juvenile conifer wood is characterized by randomly distributed mild compression wood (MCW), NW of- ten being absent (Donaldson et al., 2004). These are the features that suggest P. omorika juvenile wood as a good choice of samples for evaluation of the precision of methods suggested for estimation of compression wood severity. Our methods for distinguishing wood samples on a compression severity scale provide a fine gradation from NW to the severest form of CW, compression severity scales being partially different. These meth- ods, alone or in combination with each other, could be a useful tool for fine gradation of wood samples on the compression severity scale, either in the esti- mation of wood quality or environmental influences during growth and developmental process. They confirm juvenile P. omorika stem samples as a good choice of samples for evaluation of the methods sug- gested for compression wood severity estimation. Picea omorika: endemicity, natural range, habitat, planting outside its natural range Picea omorika (Pančić) Purkynĕ is a slow growing endemic coniferous species and Tertiary relict of the European flora. Its natural habitat is fragmented and reduced to the middle and upper courses of the Dri- na River, in Western Serbia and Eastern Bosnia and Herzegovina (Jovanović, 1970, Sevill et al., 2017). The species was widespread in Europe and Asia, but after the Pleistocene glaciations, this region repre- sents species long-term, cryptic and last refugium (Aleksić & Geburek, 2014). An Asian origin of Ser- bian spruce has been recently confirmed (Lockwood et al., 2013), grouping P. omorika with the Cauca- sian P. orientalis, and the two Japanese endemics P. alcoquiana and P. maximowiczii. Serbian spruce an- cestors appeared in Asia at the end of the Neogene, but the increasing seasonality and aridity during the late Miocene led to the extinction of Picea in the mid latitudes of Eurasia. Until the middle of the 19th century, the natural range of P. omorika was more continuous and less fragmented than it is today (Sevill et al., 2017). It has been legally protected since 1964. Its current distribution is on one side the result of anthropo- genic factors such as general forest clearance and harvesting for timber, pastoralism and wildfires (Jovanović, 1986; Sevill et al., 2017). Fire has per- haps been the biggest threat, and logging has been a subsidiary one (Sevill et al., 2017). On the other side the limited natural range of Serbian spruce is the re- sult of the species poor competing ability. It retreats to areas less inhabitable by its competitors, predomi- nantly Picea abies and Fagus orientalis (Johnson, 1993; Jovanović, 2000). It inhabits open habitats comprising cliffs and forest clearings, characterized by a strong northerly wind, snow, and rockfalls. The climate in its natural range is characterized by very high humidity, high precipitation, regularly distrib- uted over the year, deep snow cover which lasts 4-5 months, and low winter temperatures. Picea omori- ka is drought tolerant, its cold hardiness limit is be- tween -28 °C and -23 °C, it tolerates wide soil pH range and polluted urban conditions (Sevill et al., 2017). In short, it is adapted to extreme environmen- tal conditions. Planting Serbian spruce outside its natural range has a long tradition in Europe since the late 19th century. In addition to the initial use as orna- mental plant species in parks, Serbian spruce has a long tradition of use in forestry (Ivetić & Aleksić, 2016). It is grown to a small extent for Christmas trees, timber and paper production, particularly in northern Europe, although its slow growth makes it less important than Sitka spruce or Norway spruce (Sevill et al., 2017). However, in Britain P. omorika and P. orientalis are among the alternative species to Sitka spruce and Norway spruces particularly in areas where they might be subject to damage due to drought as the impacts of climate change (Sevill et al., 2017). The great value of this species appears to be successful planting in places where other spruces are susceptible to injury by drought or spring frosts. At present, Serbian spruce is of major importance only as an ornamental tree, mainly in northern Eu- rope and North America. It is regarded as one of the most attractive spruces because of its elegant form and the ability to grow on a wide range of soils (Se- vill et al., 2017). Despite its endemism, P. omorika is considered as one of the most adaptable spruces. 66 BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages Wood properties in the forest products industry and methods for estimation of wood quality Forest products industry is based on wood proper- ties, while wood properties are directly determined by cell arrangement, cell size and shape, and cell wall structure and thickness. In softwood species differences in wood structure result from genetic and abiotic factors: 1) plant age (Zobel & Sprague, 1998; Burdon et al., 2004) - juvenile wood and mature wood; 2) season of maturation within the growth ring (Uggla et al., 2001) – early wood (EW) and late wood (LW); or 3) mechanical stress as a conse- quence of wind and stem lean (Timell, 1986) - com- pression wood, opposite wood and normal wood. In the forest products industry, juvenile wood, early wood and compression wood, generally have limited value, and therefore determination of their amounts is of great importance. In this regard, different mor- phometric and non-morphometric methods were de- veloped for the evaluation of wood quality (Tab. 1). The number of developed methods speak in favor of their significance for the forest products industry. Compression wood - reaction wood in conifers: formation, occurrence, range of gradations The resistance of trees to mechanical perturbation depends on structural modifications for mechanical BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages 67 strength. The formation of reaction wood in the stem is a reaction of the tree to leaning, as part of the geo- tropic response. In conifers, reaction wood is known as compression wood (Timell, 1986). Its formation occurs on the lower side of the leaning stem (Fig. 1), resulting in eccentric growth (Timell, 1986; Don- aldson & Singh, 2013). Inclination at the high angle results in severe compression wood (SCW) forma- tion (Yumoto et al., 1983). CW occurs in a range of gradations from near NW to SCW, mild CW (MCW) forming a continuum between NW and SCW (Fig. 1). Wood opposite to the CW in the same growth ring is termed opposite wood (OW) (Fig. 1), while wood from growth rings that do not contain any CW is termed normal wood (NW). Also, in the leaning stem, compression wood severity declines from the stem base to the top of the stem (Fig. 1). Wood tracheid cell walls are composed of several layers containing an ordered array of cellulose mi- crofibrils, embedded in a matrix of polysaccharides such as pectin, hemicellulose, and lignin (Harris, 2006). CW is characterized by (Fig. 2): increased tracheid wall thickness, reduced lumen diameter, rounder cell cross-sectional profile, presence of intercellular spaces, absence of the S3 cell wall lay- er and presence of helical cavities in the S2 layer, compared to NW (Donaldson et al., 2004; Donald- son & Singh, 2013). CW is highly lignified, with the changed composition of lignin, increased amounts of p-hydroxyphenyl monomers and increased con- Methods Parameter For estimation of M or ph om et ri c m et ho ds Manual or automated measure- ments on micrographs (Mork, 1928; Brown et al., 1949; Gofas & Tsoumis, 1975; Klisz, 2009; Selig et al., 2012) Automated measurements from distance maps reconstructed from digital images (Travis et al., 1996; Lorbach et al., 2012; Nedzved et al., 2018) cell wall area radial cell wall width double wall thickness cell lumen EW/LW ratio (Mork, 1928) Differences between juvenile and mature wood (Mitchell and Denne, 1997; Lous- tarinen, 2012) Compression wood severity (Andersson & Walter, 1995; Nyström & Hagman, 1999; Moëll & Fujita, 2004; Duncker & Spiecker, 2009; Nedzved et al., 2018) N on -m or ph om et ri c m et ho ds Fluorescence spectroscopy (Don- aldson et al., 2010) Chemical analysis (Nanayakkara et al., 2009) Scanning Fourier transform infra- red microspectroscopy and immu- nolabeling (Altaner et al., 2009) Fluorescence-detected linear di- chroism (FDLD) microscopy (Savić et al., 2016) Confocal microscopy (Donaldson et al., 2004) lignin and carbohydrate content/structure cellulose and noncel- lulosic polysaccharides composition and organi- zation microfibrillar angle Compression wood severity Table 1. Some of the methods for estimation of wood quality 68 densation of monomer units in the polymer (Timell, 1986). Consequently, CW contains less cellulose, with greatly increased amounts of galactan, and slightly lower amounts of mannan and xylan, together with a higher an- gle of cellulose microfibrils in the S2 layer of the cell wall, compared to NW (Nanayakkara et al., 2009; Donaldson & Knox, 2012; Don- aldson & Singh, 2013). The degree of development of particular features of CW does not necessarily change in parallel to each other, so the severity of a given tracheid is represented as a function of the degrees of development of individual features, mainly lignification, helical cavi- ties and cell wall thickness (Yumoto et al., 1983). Visual detection of compression wood severity, more precisely the determination of MCW, is difficult. As the severity of CW af- fects mechanical and chemical properties of wood in the forest products industry, it is desirable to be able to measure CW severity (Altaner et al., 2009). Fig. 1. Scheme of compression wood formation; compression wood occurs in a range of gradations from near normal wood to severe compression wood, mild compression wood forming a continuum between normal wood and severe compression wood; Compression wood severity declines from stem base to the top of the stem; NW – normal wood, CW – compression wood. MCW - mild compression wood, SCW - severe compression wood, OW – opposite wood Fig. 2. Scheme for changes in degree of development of tracheid cell wall features characterizing the transition from normal wood (NW) to severe compression wood (SCW), mild compression wood (MCW) forming a con- tinuum between NW and SCW; on the left – field emission scanning electron microscopy (FESEM) images of NW, on the right – FESEM images of SCW; NW – normal wood, MCW - mild compression wood, SCW - severe compression wood, S1, S2, S3 – layers of secondary cell wall BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages 69 Our morphometric and non- morphometric methods for distinguishing conifer wood samples on a compression severity scale In recent years we worked on the devel- opment of different morphometric and non-morphometric methods for distin- guishing wood samples on a compres- sion severity scale. The first method is based on tracheid double wall thick- ness analysis (Nedzved et al., 2018). The second method is based on cel- lulose microfibrils order (distribution and alignment of cellulose microfibrils) analysis in tracheid (double) walls (Savić et al., 2016). The third one we are still developing, based on the analy- sis of structural modifications of lignin, and it is related to our results published a few years ago (Mitrović et al., 2015). These 3 methods cover the main features of CW, related to changes in tracheid cell wall shape, lignin and cel- lulose organization. Hence, alone or in combination with each other, they could be suggested for use in fine gradation of wood samples on the compression se- verity scale, either in the estimation of wood quality or in the estimation of en- vironmental influences during growth and developmental process. We present here, in more detail, 2 methods, one morphometric (Nedzved et al., 2018) and one non-morphometric (Savić et al., 2016), for distinguishing wood samples on a compression sever- ity scale. In Tab. 2, the main charac- teristics, similarities, differences, and advantages of these methods are sum- marized. It is known that radial and tangential walls can vary significantly regarding different features of wood cell walls. So far, most investigations, regarding cel- lulose microfibrils (Donaldson, 2008), or other features of wood cell walls such as cell wall thickness (Mork, 1928), have been carried out on radial cell walls. Accordingly, our methods confirm the selection of radial walls for the analysis as an excellent choice of tracheid cell wall region for the deter- mination of MCW. Fig. 3. Reprinted by permission from: Springer Nature, Trees 32, 1347–1356; Nedzved et al. (2018) Automatic image processing mor- phometric method for the analysis of tracheid double wall thickness tested on juvenile Picea omorika trees exposed to static bending. Trees 32, 1347–1356.: The CLSM images (first column), corre- sponding binary images (second column) and distance maps (third column) of P. omorika stem samples; S1 and S2 – NW samples; S3 and S4 - MCW samples; S5 and S6 – SCW samples BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages 70 Compression wood – reaction wood in conifers: formation, occurrence, range of gradations Measurements of various anatomical character- istics of wood cells are of great importance in the research of wood structure. Tracheid double wall thickness, as an important wood anatomical feature, besides being known as an indicator of transition from EW to LW within an annual ring in gymno- sperms (the ratio between radial double wall thick- ness and cell lumen diameter, Mork, 1928), also characterizes the differences between juvenile and mature wood (Mitchell & Denne, 1997; Loustarinen, 2012), as well as between normal and compression wood (Timell, 1986; Plomion et al., 2001). Hence, the determination of tracheid double wall thickness is of great importance in estimation of wood quality. Image-processing techniques are used for estima- tion of the EW and LW ratio as a significant feature for forest products industry (Mork, 1928; Jagels & Dyer, 1983; Diao et al., 1999). However, such tech- niques for estimation of compression wood sever- ity were more (Duncker & Spiecker, 2009) or less (Andersson & Walter, 1995; Nyström & Hagman, 1999; Moëll & Fujita, 2004) successful in recogniz- ing MCW. For testing of our automatic image processing morphometric method for the analysis of tracheid double wall thickness (Nedzved et al., 2018) we used confocal laser scanning microscopy (CLSM) images of stem cross sections of juvenile P. omorika trees exposed to static bending. Our algorithm (Nedzved et al., 2018) was developed using Imagewarp A&B Software company (USA) and software for image analysis QTIP developed in United Institute of In- formatics Problems (UIIP), National Academy of Sciences (Belarus). It consists of the extraction of cell patterns from the original micrograph via bina- rization using Otsu’s threshold method (Otsu, 1979) and reconstruction of the distance maps (Kimmel et al., 1996). The use of Euclidian distance maps for calculat- ing the thickness of the wood cell wall was suggested earlier in estimations of pulp or paper quality (Travis et al., 1996; Koskenhely & Paulapuro, 2005; Selig et al., 2012; Lorbach et al., 2012). The novelty of our Fig. 4. Reprinted by permission from: Springer Nature, Trees 32, 1347–1356; Nedzved et al. (2018) Automatic image processing morphometric method for the analysis of tracheid double wall thickness tested on juvenile Picea omorika trees exposed to static bending. Trees 32, 1347–1356.: Distribution of double wall thickness of a) entire tracheid walls, b) tracheid at cell corners, c) tangential walls and d) radial walls, determined by morphological processing of structural elements with different orientation from distance maps obtained from the CLSM images of (S1 – S6) samples (Fig. 3); a, b, c, d, e, f - significant difference at 5% level of significance of the maxima positions of Gaussian curves between samples S1 – S6; µ - mean values, σ – standard deviation BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages 71 method is the use of morphological image process- ing of structural elements with different orientation (Dougherty, 1992) on Euclidian distance maps re- constructed from microscopic images, allowing de- termination of the distribution of tracheid double wall thickness separately for tangential walls, radial walls, and cell corners (it yields valuable informa- tion on circularity/rectangularity of cross-sectional profile of tracheid cell wall). We applied IBM SPSS software, Nonlinear Curve Fit function, for fitting the Gaussian curves on the data (distribution of double wall thickness in pixels) to show the overall variation in tracheid dou- ble wall thickness in a response to mechanical stress. For comparison of the maxima positions of Gaus- sian curves between samples, one-way ANOVA and Duncan test were used. As a result, our nonmorpho- metric image processing method provides a fine gra- dation of P. omorika juvenile wood samples on the compression severity scale from NW to SCW (Fig. 4 a-d), suggesting that it could be used as a tool for estimation of compression wood severity. In addition, as different regions of P. omorika tracheid cell wall show somewhat different cell wall thickening in response to mechanical stress (Fig. 4), compression severity scales based on double wall thickness distribution of entire tracheids, tracheids at cell corners, tangential and radial walls, differ to some degree. Radial walls- double wall thickness distribution (Fig. 4d) shows the additional advan- tage and specificity over a number of methods for estimation of compression wood severity: it groups, and consequently sharply distinguishes MCW sam- ples from SCW samples. Our non-morphometric method for estimation of compression wood severity based on cellulose microfibrils order (Savić et al., 2016) - short report The distribution and orientation of cellulose microfi- brils (MFs) in wood cell walls is determined by both, genetic and abiotic factors. Genetic factors include: cell wall layer (primary wall, S1, S2, S3 layer of sec- ondary cell wall), position (radial or tangential cell wall), plant age (juvenile or mature wood), season of maturation within the growth ring (early and late wood), while abiotic factors include wind and stem lean (compression wood, normal wood). Since cellulose fibrils, as reinforcing material in conifer wood cell walls, determine tracheid cell wall properties and wood quality, one of the most fre- quently measured ultrastructural variables in wood cell wall is microfibrilar angle (MFA) (Donaldson, 2008). Various microscopic techniques have been used to study the orientation of cellulose microfibrils in the wood cell wall, using variations in polarised light techniques or directly visualizing orientation of the microfibrils (Donaldson, 2008). In our method for estimation of compression wood severity (Savić et al., 2016) we observed the relative order of cel- lulose fibrils in cell walls. Fluorescence detected linear dichroism (FDLD) imaging was performed using confocal laser scanning microscope (CLSM) additionally equipped with constructed differential polarization extension (DPLSM). FDLD microsco- py exploits fluorescence originating from cellulose fibrils stained specifically by Congo red, enabling screening of cellulose microfibrils order in the X–Y plane of the cross section, which means - separately in tangential and radial walls. The method was tested on stem cross sections of juvenile P. omorika trees exposed to static bending. Blue colour represents dipoles (cellulose fib- ers) predominantly parallel with X-axis (tangential walls), yellow colour indicates dipoles (cellulose fibers) oriented predominantly parallel with the Y- axis (radial walls) (Fig. 5), while the grey colour represents fibers orientated at about 45°. Image processing was performed using ImageJ program with macros developed for this analysis. FDLD images were quantified and presented as his- tograms (Fig. 5). The decrease in cellulose fibrils order from CW to NW samples is obvious, in both radial and tangential tracheid walls (Fig. 5). This is in line with Xu et al. (2011) work; they showed that the characteristics of cellulose fibrils reinforcements in S2 layer of severe compression juvenile wood in- clude lower number, abundant dislocation segments and shorter length of cellulose MF, compared to NW. We additionally showed (Savić et al., 2016) that radial and tangential tracheid cell walls in P. omori- ka juvenile wood differ considerably regarding cel- lulose fibril order, and that FDLD of radial walls (Fig. 5 u), showing fine gradation from CW to NW, could be suggested as an easily applicable technique for estimation of CW severity. Picea omorika juvenile wood samples – a model for testing of methods for estima- tion of compression wood severity. We tested our methods on stem samples of P. omori- ka juvenile trees exposed to long term static bending (bending procedure described in detail in Mitrović et al., 2015). P. omorika belong to slow-growing conifer spe- cies in which CW typically occurs in a severe form (SCW) (Donaldson et al., 2004). Juvenile coni- fer wood is characterized by randomly distributed MCW, NW often being absent (Donaldson et al., 2004). These are the features that suggest P. omorika juvenile wood a good choice of samples for evalua- BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages 72 Fig. 5. Reprinted by permission from: Cambridge University Press, Microscоpy and Microanalysis 22, 361–367.; Savić et al. (2016) Fluorescence-detected linear dichroism of wood cell walls in juvenile Serbian spruce: estima- tion of compression wood severity. Microscоpy and Microanalysis 22, 361–367.: Fluorescence-detected linear dichroism (FDLD) images of P. omorika sections and corresponding anisotropy histograms. a: Normal wood (NW) samples; (e) mild compression wood (MCW) samples; (i,m) severe compression wood (SCW) samples; (b,f,j,o) pixel values were collected in the marked areas, in tangential walls (blue boxes) and in radial walls (yellow boxes), and used to obtain anisotropy distributions; (c,g,k,p) tangential walls FDLD distributions; (d,h,l,q) radial walls FDLD distributions; (t) overlaid distributions (c,g,k,p) with black lines representing corresponding Gaussian fits (white arrow represents gradual shifts toward gray—increasing number of disorientated fibrils); (u) overlaid distributions (d,h,l,q) with black lines representing corresponding Gaussian fits (white arrows represent gradual shifts toward gray—increasing number of disorientated fibrils); (r,s) schemes of NW and CW tracheid sections, respectively. Excitation at 488 nm, emission above 560 nm; image size is 64 × 64 μm BIOLOGICA NYSSANA ● 10 (2) December 2019: 65-75 Mitrović et al. ● Serbian spruce (Picea omorika (Pančić) Purkyné - endemicity and adventages tion of the precision of methods suggested for esti- mation of compression wood severity. After testing of our methods (Savić et al., 2016; Nedzved et al., 2018) on stem cross sections of ju- venile P. omorika trees exposed to long term static bending, we can confirm P. omorika juvenile wood samples as a good model for testing of methods sug- gested for estimation of compression wood severity. Conclusion Picea omorika, despite its endemism, and thanks to her adaptability and long tradition of planting, now- adays is present widely outside its natural range. We confirmed Picea omorika juvenile wood samples as a good model for testing of methods sug- gested for estimation of compression wood severity. Our methods, based on the analysis of tracheid double wall thickness, cellulose fibril order and structural modifications of lignin, using confocal fluorescence microscopy and spectroscopy, cover all the main features of CW. Therefore, alone or in com- bination with each other, they could be a useful tool for fine gradation of wood samples on compression severity scale, as a valuable advantage over many other methods for the estimation of compression wood severity, as the determination of mild com- pression wood is difficult. Hence they can be of great benefit either for estimation of wood quality in for- est products industry, or for estimation of environ- mental influences during growth and developmental process in tree physiology. Acknowledgements. This study was supported by Grant 173017 of the Ministry of Education, Science and Tech- nological Development of the Republic of Serbia. 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