Spatial variation of wood density for Eucalyptus grandis by near infra red hyperspectral imaging combined with X-ray analysis

Chambi Legoas Roger, Tomazello Filho Mario, Gorretta Nathalie, Pasquini Célio, Vidal Cristiane, Roger Jean-Michel, Chaix Gilles. 2019. Spatial variation of wood density for Eucalyptus grandis by near infra red hyperspectral imaging combined with X-ray analysis. Pesquisa Florestal Brasileira, 39, n.spéc., Résumé : 175-176. IUFRO World Congress 2019 "Forest Research and Cooperation for Sustainable Development". 25, Curitiba, Brésil, 29 Septembre 2019/5 Octobre 2019.

https://doi.org/10.4336/2019.pfb.39e201902043

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Url - éditeur : https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2043/900 / Url - autre : https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/2043/

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Résumé : Most near-infrared spectroscopy (NIRS) studies for wood density use multiple spectral acquisitions taken manually at several points from pith to bark. Recently the use of near-infrared hyperspectral imaging (NIR- HSI) has shown good performance in predictions of wood properties allowing build high spatial resolution predictive images. The combined use of NIR-HSI and X-ray microdensity imaging (X-ray MDI) could be more practical for evaluation of spatial variation of wood density. The aim was to develop a wood density calibration model for NIR-HSI (625 µm pixel size) from X-ray MDI (30 µm pixel size) and evaluate the spatial variation of wood density along stem cross-section in Eucalyptus grandis trees. Wood discs were collected from 18 trees of 6 years old, submitted to two different water availability, located in Sao Paulo. Brazil. The challenge here was to match the pixels of X-ray MDI to pixels of NIR-HSI (in 2 mm width radial region) to transfer accurate values of wood density to each, pixel of NIR-HSI. The R2 of the model was 0. 72, while the root mean squared error was and 4.8 x 10-2 g cm-3 for the validation group. The prediction model allows comparing their spatial distributions according to the growth conditions. Trees with higher water stress showed higher wood density. Treatments showed a similar spatial variation or wood density. increasing from pith to bark. In perspective, these data will allow evaluating the spatial distribution of wood density inter and intra-tree rings in relation to meteorological variability.

Mots-clés Agrovoc : Eucalyptus grandis, spectroscopie infrarouge, spectroscopie aux rayons x, cerne, stress dû à la sécheresse, conditions météorologiques, modèle de simulation

Mots-clés géographiques Agrovoc : Brésil

Mots-clés complémentaires : Densité du bois

Classification Agris : K10 - Production forestière
K50 - Technologie des produits forestiers

Champ stratégique Cirad : CTS 7 (2019-) - Hors champs stratégiques

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