Non-destructive wood identification using X-ray µCT scanning: which resolution do we need?
Tropical wood species
Wood identification
X-ray µCT-scanning
Journal
Plant methods
ISSN: 1746-4811
Titre abrégé: Plant Methods
Pays: England
ID NLM: 101245798
Informations de publication
Date de publication:
24 Jun 2024
24 Jun 2024
Historique:
received:
07
03
2024
accepted:
30
05
2024
medline:
25
6
2024
pubmed:
25
6
2024
entrez:
24
6
2024
Statut:
epublish
Résumé
Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1 µm, 3 µm, 8 µm and 15 µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features. For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1 µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3 µm, the scans at 1 µm and 8 µm were successful in more than half of the studied cases, and even the 15 µm resolution showed a high potential for 40% of the samples. The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species.
Sections du résumé
BACKGROUND
BACKGROUND
Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1 µm, 3 µm, 8 µm and 15 µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features.
RESULTS
RESULTS
For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1 µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3 µm, the scans at 1 µm and 8 µm were successful in more than half of the studied cases, and even the 15 µm resolution showed a high potential for 40% of the samples.
CONCLUSIONS
CONCLUSIONS
The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species.
Identifiants
pubmed: 38915095
doi: 10.1186/s13007-024-01216-0
pii: 10.1186/s13007-024-01216-0
doi:
Types de publication
Journal Article
Langues
eng
Pagination
98Subventions
Organisme : Belgian Federal Science Policy Office
ID : B2/191/p2/TOCOWO
Organisme : Belgian Federal Science Policy Office
ID : FED-tWIN2019-prf-075
Organisme : Bijzonder Onderzoeksfonds UGent
ID : BOF.COR.2022.008
Informations de copyright
© 2024. The Author(s).
Références
Low MC, Schmitz N, Boeschoten LE, Cabezas JA, Cramm M, Haag V, Koch G, Meyer-Sand B, Paredes-Villanueva K, Price E, Thornhill A, Van Brusselen J, Zuidema PA, Deklerck V, Dormontt E, Shapcott A, Lowe AJ. Tracing the world’s timber: the status of scientific verification technologies for species and origin identification. IAWA J. 2022;44:63–84.
Cartwright CR. The principles, procedures and pitfalls in identifying archaeological and historical wood samples. Ann Bot. 2015;116:1–13.
pubmed: 25953039
pmcid: 4479747
da Silva J, Bordalo R, Pissarra J. Wood identification: an overview of current and past methods. Estudos de Conservacao e Restauro. 2022;12:45–68.
Hubau W, Van den Bulcke J, Kitin P, Mees F, Baert G, Verschuren D, Nsenga L, Van Acker J, Beeckman H. Ancient charcoal as a natural archive for paleofire regime and vegetation change in the Mayumbe, Democratic Republic of the Congo. Quat Res. 2013;80:326–40.
Lindbladh M, Fraver S, Edvardsson J, Felton A. Past forest composition, structures and processes—how paleoecology can contribute to forest conservation. Biol Conserv. 2013;168:116–27.
Stobbe A, Gumnior M. Paleoecology as a tool for the future management of forest ecosystems in Hesse (Central Germany): beech (Fagus sylvatica L.) versus Lime (Tilia cordata Mill.). Forests. 2021;12:924–44.
Cufar K, Beeckman H, Frelih M, Krze L, Hubau W, Merela M. Wood identification in objects of the Bambuti people from the Congo in the collection of the Slovene ethnographic museum. Les/Wood. 2022;71:5–24.
Puhar EG, Korat L, Eric M, Jaklic A, Solina F. Microtomographic analysis of a paleolithic wooden point from the Ljubljanica river. Sensors. 2022;22:23–69.
Brunswick P, Cuthbertson D, Yan J, Chua CC, Duchesne I, Isabel N, Evans PD, Gasson P, Kite G, Bruno J, van Aggelen G, Shang D. A practical study of CITES wood species identification by untargeted DART/QTOF, GC/QTOF and LC/QTOF together with machine learning processes and statistical analysis. Environ Adv. 2021;5:1–10.
Deklerck V, Lancaster CA, Van Acker J, Espinoza EO, Van den Bulcke J, Beeckman H. Chemical fingerprinting of wood sampled along a pith-to-bark gradient for individual comparison and provenance identification. Forests. 2020;11:1–13.
Shang D, Brunswick P, Yan J, Bruno J, Duchesne I, Isabel N, Van Aggelen G, Kim M, Evans PD. Chemotyping and identification of protected Dalbergia timber using gas chromatography quadrupole time of flight mass spectrometry. J Chromatogr A. 2020;1615:460775.
pubmed: 31959455
Akhmetzyanov L, Copini P, Sass-Klaassen U, Schroeder H, de Groot GA, Laros I, Daly A. DNA of centuries-old timber can reveal its origin. Sci Rep. 2020;10:1–10.
Jiao L, Liu X, Jiang X, Yin Y. Extraction and amplification of DNA from aged and archaeological Populus euphratica wood for species identification. Holzforschung. 2015;69:925–31.
Stagno V, Moricca C, Sadori L, Dell’Aglio E, Reale R, Capuani S. Evaluation of the efficacy of micro-magnetic resonance Imaging compared with light microscopy to investigate the anatomy of modern and ancient waterlogged wood. Magn Reson Imaging. 2023;102:164–78.
pubmed: 37348742
Brodersen C. Visualizing wood anatomy in three dimensions with high-resolution X-ray micro-tomography (MCT)—a review. IAWA J. 2013;34:408–24.
Duncan K, Czymmek K, Jiang N, Thies A, Topp C. X-ray microscopy enables multiscale high-resolution imaging of plant cells, tissues, and organs. Plant Physiol. 2022;188:831–45.
pubmed: 34618094
Gabner M, Salaberger D, Okochi T. The need for high resolution µ-X-ray CT in dendrochronology identification. In: Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis. 2009.
Steppe K, Cnudde V, Girard C, Lemeur R, Cnudde J-P, Jacobs P. Use of X-ray computed microtomography for non-invasive determination of wood anatomical characteristics. J Struct Biol. 2004;148:11–21.
pubmed: 15363784
Haneca K, Deforce K, Boone MN, Van Loo D, Dierick M, Van Acker J, Van den Bulcke J. X-ray sub-micron tomography as a tool for the study of archaeological wood preserved through the corrosion of metal objects. Archaeometry. 2011;54:893–905.
Van den Bulcke J, Boone M, Van Acker J, Stevens M, Van Hoorebeke L. X-ray tomography as a tool for detailed anatomical analysis. Ann For Sci. 2009;66:508–20.
Fioravanti M, Di Giulio G, Signorini G, Rognoni G, Sodini N, Tromba G, Zanini F. Non-invasive wood identification of historical musical bows. IAWA J. 2017;38:285–96.
Haag V, Dremel K, Zabler S. Volumetric imaging by micro computed tomography: a suitable tool for wood identification of charcoal. IAWA J. 2022;44:210–24.
Rankin K, Hazell Z, Middleton A, Mavrogordato M. Micro-focus X-ray CT scanning of two rare wooden objects from the wreck of the London and its application in heritage science and conservation. J Archaeol Sci. 2021;39:103158.
Stelzener J, Millon S. X-ray computed tomography for the anatomical and dendrochronological analysis of archaeological wood. J Archaeol Sci. 2015;55:188–96.
Wheeler E. Inside wood—a web resource for hardwood anatomy. IAWA J. 2011;32:199–211.
Deklerck V. National treasure: valorisation of the Federal Xylarium in Belgium for timber identification and wood technology. Ghent University, Faculty of Bioscience Engineering. 2019.
Tervuren Xylarium Wood Database. https://www.africamuseum.be/nl/research/collections_libraries/biology/collections/xylarium . Accessed 1 Dec 2023.
Vanden Abeele S, Beeckman H, De Mil T, De Troyer C, Deklerck V, Endledow H, Hubau W, Stoffelen P, Janssensn SB. When xylarium and herbarium meet: linking Tervuren xylarium wood samples with their herbarium specimens at Meise Botanic Garden. Biodivers Data J. 2021;9:1–11.
Dierick M, Van Loo D, Masschaele B, Van den Bulcke J, Van Acker J, Cnudde V, Van Hoorebeke L. Recent micro-CT scanner developments at UGCT. Nucl Instrum Methods Phys Res. 2014;324:35–40.
Vlassenbroeck J, Cnudde V, Masschaele B, Dierick M, Van Hoorebeke L, Jacobs P. A comparative and critical study of X-ray CT and neuron CT as non-destructive material evaluation techniques. Geol Soc Lond Spec Publ. 2006;271:277–85.
Boone M, Devulder W, Dierick M, Braant L, Pauwels E, Van Hoorebeke L. Comparison of two single-image phase-retrieval algorithms for in-line X-ray phase-contrast imaging. J Opt Soc Am. 2012;29:2667–72.
Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez J-Y, White D, Hartenstein V, Eliceiri K, Tomencak P, Cordona A. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9:676–82.
pubmed: 22743772
Tkac J, Toth T, Molnar V, Dovica M, Fedorko G. Possibilities of analysis of porous structures using industrial computed tomography. Eng Fail Anal. 2022;137:106296.
Committee IAWA. IAWA list of microscopic features for hardwood identification. IAWA Bulletin. 1989;10:201–32.
Koddenberg T, Militz H. Morphological imaging and quantification of axial xylem tissue in Fraxinus excelsior L. through X-ray micro-computed tomography. Micron. 2018;111:28–35.
pubmed: 29857175
Brodersen C, Roddy A. New frontiers in three-dimensional visualization of plant structure and function. Am J Bot. 2016;103:184–8.
pubmed: 26865119
Koddenberg T, Greving I, Hagemann J, Flenner S, Krause A, Laipple D, Klein K, Schmitt U, Schuster M, Wolf A, Seifert M, Ludwig V, Funk S, Militz H, Nopens M. Three-dimensional imaging of xylem at cell wall level through near field nano holotomography. Sci Rep. 2021;11:1–7.
Mahesh S, Kumar P, Ansari S. Rapid and economical method for the maceration of wood fibers in Boswellia serrata Roxb. Trop Plant Res. 2015;2:108–11.
Arzac A, Lopez-Cepero J, Babushkina E, Gomez S. Applying methods of hard tissues preparation for wood anatomy: imaging polished samples embedded in polymethylmethacrylate. Dendrochronologia. 2018;51:76–81.
Zhang X, Li L, Xu F. Chemical characteristics of wood cell wall with an emphasis on ultrastructure: a mini review. Forests. 2022;13:439.
Groenendijk P, Sass-Klaassen U, Bongers F, Zuidema PA. Potential of tree-ring analysis in a wet tropical forest: a case study on 22 commercial tree species in Central Africa. For Ecol Manage. 2014;323:65–78.
Quintilhan M, Santini L, Rodriguez D, Guillemot J, Cesilio G, Chambi-Legoas R, Nouvellon Y, Tomazello-Filho M. Growth-ring boundaries of tropical tree species: aiding delimitation by long histological sections and wood density profiles. Dendrochronologia. 2021;69:125878.
Van den Bulcke J, Boone M, Van Loo D, Van Hoorebeke L, Boone M, Wyffels F, Beeckman H, Van Acker J, De Mil T. Advanced X-ray CT scanning can boost tree ring research for earth system sciences. Ann Bot. 2019;124:837–47.
pubmed: 31361809
pmcid: 6868372