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

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

doi:10.1186/s13595-022-01163-7

Cited by 5 publications

(4 citation statements)

References 28 publications

(6 reference statements)

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“…By conveying the boards longitudinally, this scanner provides different images of the four long faces of the boards, as well as local density and local orientation of the fibers. The principle of board scanning is presented in Figure 1 and thoroughly described in a dataper dealing with Douglas-fir (Longuetaud et al 2022). In the present study, only the fibre orientation measurement has been used and will therefore be described more in detail.…”

Section: Physical and Mechanical Properties Measurementsmentioning

confidence: 99%

“…Figure 1: Illustration of board scanning with side view on the top of the figure, and top view on the bottom of the figure, corresponding to left and top faces of the board, respectively. In the detail view, dashed lines represent a line of pixels which is recorded by the cameras while the board is conveyed longitudinally, and the greyed area with dotted line contour represents the region of interest used in the camera to treat ellipses information.From(Longuetaud et al 2022) …”

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confidence: 99%

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11th Hardwood Conference Proceedings

2024

Hardwood Conference Proceedings

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Black locust (Robinia pseudoacacia L.) is the most widespread non-native tree species in Europe and has had a significant impact on the Central European landscape and forestry. The black locust has many exceptional characteristics that represent considerable potential for use by man. The climate shift in recent decades in Central Europe could further strengthen the importance of this tree species. However, there are also risks arising from the invasiveness of the black locust. Like Hungary, Czechia has had many years of experience with this tree species. Still, the current approach between these two countries, particularly in conventional forestry, differs. This paper attempts to summarise how the management of Robinia and its stands is viewed in Czechia, where the common forestry utilization of black locust is currently not considered due to its invasiveness. The reason for a more reserved forestry attitude in Czechia can be associated with the relatively frequent stem deformities of Robinia stands, which are often attributed to frost. However, the frost deformities and low stem-form quality of some Robinia stands do not affect their vigour and potential to invade adjacent habitats. It often takes considerable effort to remove black locust, especially where the spreading of Robinia threatens valuable adjacent ecosystems. On the other hand, there is great potential for the use of Robinia in Czechia. It can be found in controlled energy crops, fast-growing plantations (lignicultures), some land reclamation projects or urban greenery. Robinia can also be grown in small stands or in groups of trees surrounded by arable land that does not allow the tree to spontaneously spread. Regarding the production plantations of Robinia, the Hungarian experience and breeding program can be very inspiring for Czechia. Generally, there is a move towards 'site-specific management', but with a strong emphasis on the precautionary principle. Finding and then consistently applying a balanced approach to black locust management that not only allows for the potential but also respects the risks of Robiniait is currently a key challenge for Czech forestry, landscape and nature conservation.

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Section: Physical and Mechanical Properties Measurementsmentioning

confidence: 99%

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confidence: 99%

11th Hardwood Conference Proceedings

2024

Hardwood Conference Proceedings

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“…This article and the corresponding database are complementary to the article already published on the Douglas fir part of the project (Longuetaud et al 2022a) and the associated database TreeTrace_Douglas fir (https:// doi. org/ 10.…”

Section: Introductionmentioning

confidence: 99%

Traceability and quality assessment of Norway spruce (Picea abies (L.) H.Karst.) logs: the TreeTrace_spruce database

Longuetaud

Schraml

Mothe

et al. 2023

Annals of Forest Science

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Key message The TreeTrace_spruce database contains images and measurements of 100 Norway spruce (Picea abies (L.) H.Karst.) logs from Northeastern France, each about 4.5 m long. The image database includes RGB images of large and small ends of the logs and hyperspectral and computed tomography (CT) images of wood discs sampled at both log ends. The 100 logs were also fully X-ray scanned with a CT device for roundwoods and their top surface was scanned with a terrestrial LiDAR device. The measurements performed on discs include wood local density, growth ring widths and pith location. This database is complementary to another one (TreeTrace_Douglas) resulting from the same ANR project TreeTrace, but if the objectives are similar, the protocols and conditions of acquisition are not the same for these two databases. TreeTrace_spruce dataset is available at https://doi.org/10.57745/WKLTJI and associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/cffee2f1-18e1-4b53-9f5b-6cc4c66f1cb8.

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“…Therefore, meticulous pith estimation in parawood is paramount to optimizing its use in furniture manufacturing. Recent advancements using X-ray computed tomography (CT) imaging underscore the importance of accurate pith estimation in enhancing wood utilization and the quality of end products [5,6].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Evaluation of Deep Neural Network Architectures for Parawood Pith Estimation

Kurdthongmee

2023

HighTech. Innov. J.

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Accurate pith estimation is crucial for maintaining the quality of wood products. This study delves into deep learning techniques for precise Parawood pith estimation, employing popular convolutional neural networks (ResNet50, MobileNet, and Xception) with adapted regression heads. Through variations in regression functions, optimizers, and training epochs, the most effective models were pinpointed. Xception, coupled with Huber Loss regression, Nadam optimizer, and 200 epochs, showcased superior performance, achieving a 4.48 mm mean error (with a standard deviation of 3.69 mm) in Parawood. Notably, benchmarking on the Douglas Fir dataset yielded similar results (2.81 mm mean error, standard deviation: 1.57 mm). These findings underscore deep learning's potential for Parawood and Douglas Fir pith estimation, offering substantial benefits to wood industry quality control and production efficiency. By harnessing advanced machine learning techniques, this study advances wood industry processes, promoting the adoption of state-of-the-art technology in forestry and wood science. Doi: 10.28991/HIJ-2023-04-03-06 Full Text: PDF

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

Cited by 5 publications

References 28 publications

11th Hardwood Conference Proceedings

11th Hardwood Conference Proceedings

Traceability and quality assessment of Norway spruce (Picea abies (L.) H.Karst.) logs: the TreeTrace_spruce database

Comprehensive Evaluation of Deep Neural Network Architectures for Parawood Pith Estimation

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