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Classifying Wood Properties of Loblolly Pine Grown in Southern Brazil Using NIR-Hyperspectral Imaging

1
Department of Wood Science and Engineering, College of Forestry, Oregon State University, Corvallis, OR 97331, USA
2
Department of Wood Science and Technology, Federal University of Paraná, 80.210-170 Curitiba, Brazil
3
Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA
*
Author to whom correspondence should be addressed.
Forests 2020, 11(6), 686; https://doi.org/10.3390/f11060686
Received: 29 May 2020 / Revised: 10 June 2020 / Accepted: 16 June 2020 / Published: 18 June 2020
(This article belongs to the Section Wood Science)
Loblolly pine (Pinus taeda L.) is one of the most important commercial timber species in the world. While the species is native to the southeastern United States of America (USA), it has been widely planted in southern Brazil, where it is the most commonly planted exotic species. Interest exists in utilizing nondestructive testing methods for wood property assessment to aid in improving the wood quality of Brazilian grown loblolly pine. We used near-infrared hyperspectral imaging (NIR-HSI) on increment cores to provide data representative of the radial variation of families sampled from a 10-year-old progeny test located in Rio Negrinho municipality, Santa Catarina, Brazil. Hyperspectral images were averaged to provide an individual NIR spectrum per tree for cluster analysis (hierarchical complete linkage with square Euclidean distance) to identify trees with similar wood properties. Four clusters (0, 1, 2, 3) were identified, and based on SilviScan data for air-dry density, microfibril angle (MFA), and stiffness, clusters differed in average wood properties. Average ring data demonstrated that trees in Cluster 0 had the highest average ring densities, and those in Cluster 3 the lowest. Cluster 3 trees also had the lowest ring MFAs. NIR-HSI provides a rapid approach for collecting wood property data and, when coupled with cluster analysis, potentially, allows screening for desirable wood properties amongst families in tree improvement programs. View Full-Text
Keywords: density; loblolly pine; microfibril angle; near-infrared hyperspectral imaging; nondestructive evaluation; Pinus taeda; SilviScan; stiffness; tree improvement; wood quality density; loblolly pine; microfibril angle; near-infrared hyperspectral imaging; nondestructive evaluation; Pinus taeda; SilviScan; stiffness; tree improvement; wood quality
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Schimleck, L.; Matos, J.L.M.; Higa, A.; Trianoski, R.; Prata, J.G.; Dahlen, J. Classifying Wood Properties of Loblolly Pine Grown in Southern Brazil Using NIR-Hyperspectral Imaging. Forests 2020, 11, 686.

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