NIR-based models for estimating selected physical and chemical wood properties from fast-growing plantations

Abstract

As a faster, reliable, and low cost technique, applicable to large samplings, near infrared (NIR) spectroscopy technology has been widely applied for high-throughput phenotyping in forest breeding programmes. The aim of this study was to develop multivariate models for estimating the chemical and physical properties of juvenile wood based on NIR signatures of milled wood. Moreover, two approaches, namely, external validation by clone and by age, were tested to validate the model for estimating extractive content. NIR spectra of wood specimens taken from three clones of Eucalyptus urophylla (one to six years old) grown in southern Brazil were used to calibrate and validate models for predicting the wood basic density, total extractives, ash content, holocellulose content, syringyl to guaiacyl ratio (S/G) and elementary components of the wood. PLS-R models were validated by an independent set of wood specimens and presented promising statistics for the estimating wood density (R2p = 0.768), extractives (R2p = 0.912), ash (R2p = 0.936) and carbon (R2p = 0.697) contents from NIR signatures measured in the milled wood of young trees. Furthermore, NIR models for estimating the extractive content of wood were validated using the clones or ages left out of the training sets. Most models presented satisfactory statistics (R2 > 90%) and could be applied to routine laboratory analyses or to select potential trees in Eucalyptus breeding programmes.

Plant phenotyping relevance

NIRスペクトルから若齢ユーカリ木材の物理・化学形質を推定するモデルを開発し、クローン別・樹齢別に独立検証しており、森林育種向けの表現型取得手法が中心である。

Code and data availability

The article describes NIR spectra of Eucalyptus wood powder and PLS-R models, but no blocks contain any data availability statement, public deposit, or authors' URL for the spectral dataset, reference measurements, or models. The only URLs mentioned are the journal site and a cited FAOSTAT reference, neither of which是a

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