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利用近红外光谱法预测蓝桉心材抽出物含量。

Predicting extractives content of Eucalyptus bosistoana F. Muell. Heartwood from stem cores by near infrared spectroscopy.

机构信息

School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.

School of Forestry, University of Canterbury, Private Bag 4800, Christchurch, New Zealand.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2018 Jun 5;198:78-87. doi: 10.1016/j.saa.2018.02.068. Epub 2018 Mar 1.

Abstract

Time and resource are the restricting factors for the wider use of chemical information of wood in tree breeding programs. NIR offers an advantage over wet-chemical analysis in these aspects and is starting to be used for tree breeding. This work describes the development of a NIR-based assessment of extractive content in heartwood of E. bosistoana, which does not require milling and conditioning of the samples. This was achieved by applying the signal processing algorithms (external parameter orthogonalisation (EPO) and significance multivariate correlation (sMC)) to spectra obtained from solid wood cores, which were able to correct for moisture content, grain direction and sample form. The accuracy of extractive content predictions was further improved by variable selection, resulting in a root mean square error of 1.27%. Considering the range of extractive content in E. bosistoana heartwood of 1.3 to 15.0%, the developed NIR calibration has the potential to be used in an E. bosistoana breeding program or to assess the special variation in extractive content throughout a stem.

摘要

时间和资源是将木材化学信息更广泛地应用于树木育种计划的限制因素。近红外光谱(NIR)在这些方面优于湿法化学分析,并且开始用于树木育种。本工作描述了一种基于 NIR 的评估方法,用于评估 Eucalyptus bosistoana 心材中的抽提物含量,该方法不需要对样品进行研磨和预处理。这是通过将信号处理算法(外部参数正交化(EPO)和显著多元相关(sMC))应用于从实木芯获得的光谱来实现的,这些算法能够校正水分含量、颗粒方向和样品形状。通过变量选择进一步提高了抽提物含量预测的准确性,导致均方根误差为 1.27%。考虑到 Eucalyptus bosistoana 心材中抽提物含量的范围为 1.3 至 15.0%,所开发的 NIR 校准方法有可能用于 Eucalyptus bosistoana 育种计划,或评估整个树干中抽提物含量的特殊变化。

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