Annals of Forest Science (Nov 2022)

Traceability and quality assessment of Douglas fir (Pseudotsuga menziesii (Mirb.) Franco) logs: the TreeTrace_Douglas database

  • Fleur Longuetaud,
  • Guillaume Pot,
  • Frédéric Mothe,
  • Alexis Barthelemy,
  • Rémi Decelle,
  • Florian Delconte,
  • Xihe Ge,
  • Grégoire Guillaume,
  • Théo Mancini,
  • Tojo Ravoajanahary,
  • Jean-Claude Butaud,
  • Robert Collet,
  • Isabelle Debled-Rennesson,
  • Bertrand Marcon,
  • Phuc Ngo,
  • Benjamin Roux,
  • Joffrey Viguier

DOI
https://doi.org/10.1186/s13595-022-01163-7
Journal volume & issue
Vol. 79, no. 1
pp. 1 – 21

Abstract

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Key message The TreeTrace_Douglas database includes images and measurements at several stages of the processing of Douglas fir logs, from sawmill logyard to machine grading and destructive testing of boards, and is suitable for research on quality assessment and traceability. A total of 52 long logs, 156 short logs, 208 wood discs, and 346 boards were analyzed. The image data includes RGB images of log ends and board ends, RGB images and CT slices of strips, and a set of images of the boards (RGB, laser, and X-rays) obtained with an industrial board grading machine. The measurements include wood density, growth ring widths, pith and board location in the logs, heartwood and sapwood areas, mechanical properties of each board obtained by vibratory and static testing, and visual grading of the boards. Dataset is available at https://doi.org/10.15454/YUNEGL and associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/d9eef6e4-f195-41f4-b6c2-2ab46adc637e .

Keywords