[1]高鑫,周凡,付宗营,等.利用时域核磁共振技术分析测定松木松脂[J].林业工程学报,2019,4(06):42-47.[doi:10.13360/j.issn.2096-1359.2019.06.006]
 GAO Xin,ZHOU Fan,FU Zongying,et al.Analysis of rosin in pine wood by time domain nuclear magnetic resonance[J].Journal of Forestry Engineering,2019,4(06):42-47.[doi:10.13360/j.issn.2096-1359.2019.06.006]
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利用时域核磁共振技术分析测定松木松脂()
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《林业工程学报》[ISSN:1001-8081/CN:32-1160/S]

卷:
4
期数:
2019年06期
页码:
42-47
栏目:
木材科学与技术
出版日期:
2019-11-20

文章信息/Info

Title:
Analysis of rosin in pine wood by time domain nuclear magnetic resonance
文章编号:
2096-1359(2019)06-0042-06
作者:
高鑫周凡付宗营周永东*
中国林业科学研究院木材工业研究所,北京 100091
Author(s):
GAO Xin ZHOU Fan FU Zongying ZHOU Yongdong*
Research Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China
关键词:
核磁共振 松脂 快速检测 时域 分析测定
Keywords:
nuclear magnetic resonance pine rosin rapid detection time domain analysis
分类号:
TS67
DOI:
10.13360/j.issn.2096-1359.2019.06.006
文献标志码:
A
摘要:
将时域核磁共振技术应用于针叶材内松脂弛豫特性分析与其含量快速检测,以推进该技术在木材科研与工业领域的应用。以马尾松和辐射松两种针叶材树种作为研究对象,对气干后的试样进行时域核磁共振T2弛豫检测,其后将试样真空干燥处理排除水分,再次进行T2弛豫检测,获得木材试样内松脂的T2弛豫分布。检测一定数量真空干燥后的试样,再对其进行乙醚抽提,获得试样内松脂质量,将试样反演峰面积和松脂质量进行回归拟合。结果表明,真空干燥后马尾松与辐射松试样内松脂T2弛豫分布呈现4~5个特征峰,其弛豫分布区间较宽,基本涵盖了0.01~200 ms范围区域。结合两个树种木材解剖构造特性可定性认为T2弛豫时间大于10 ms的特征峰来源于树脂道内松脂,小于10 ms的特征峰是由于松脂进入树脂道及其周边管胞壁内产生。试样内松脂T2反演峰面积与松脂质量经回归拟合后呈高度线性关系,拟合度高于98%。通过核磁共振法计算得到的松脂含量与溶剂抽提法测定结果平均偏差较小。研究结果明确了两种针叶材内松脂T2弛豫分布特性,结合木材解剖构造特性确定了其与特征峰的对应关系,同时建立了松脂弛豫信号与其质量关系,该技术可用于针叶材内松脂含量的快速测定。
Abstract:
In this study, as a rapid detection method, the time domain nuclear magnetic resonance technology was used to analyze the relaxation distribution characteristics of rosin in pine wood, which would promote the application of this technology in the wood research and industry.Two kinds of coniferous species of Pinus massoniana and Pinus radiate were used as research species.The time domain NMR T2 relaxation distributions of air-dried samples were detected, and the T2 relaxation distribution of moisture and pine rosin in samples were acquired.Then the samples were vacuum-dried to remove moisture.The T2 relaxation distributions were detected after the vacuum-drying again, and the T2 relaxation signals were only derived from the pine rosin in samples.The T2 relaxation distributions of a certain number of vacuum-dried samples were tested, and then subjected to diethyl ether extraction to obtain the pine rosin mass in the samples.The relationship between the T2 inversion peak area and pine rosin mass was analyzed by regression fitting.After the vacuum-drying, the T2 relaxation distributions of pine rosin in masson pine and radiate pine samples showed 4-5 characteristic peaks, and the relaxation distribution was ranged from 0.01 to 200 ms.Combining the anatomical characteristics of the two species, the T2 peak with relaxation time greater than 10 ms could be considered to be derived from pine rosin in the rosin canals.The T2 peak with relaxation time less than 10 ms could be due to the pine rosin permeating through the cell wall of rosin canals and surrounding tracheids.The relationship between T2 peak area and the mass of pine rosin in the sample showed highly linear correlation after the regression fitting, and the fitting correlation was higher than 98%.The average deviation between the pine rosin content calculated by the nuclear magnetic resonance method and the solvent extraction method was small.In this study, it was clarified the T2 relaxation distribution characteristics of pine rosin in two kinds of coniferous wood species, and it was also determined the corresponding relationship between the relaxation distribution characteristics and anatomical characteristics of wood.At the same time, it was established the relationship between the pine rosin T2 relaxation signal and mass of rosin.As a result, it was concluded that the time domain nuclear magnetic resonance technology could be used as a novel rapid detection method to determine the rosin content in pine wood.

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备注/Memo

备注/Memo:
收稿日期:2019-03-15 修回日期:2019-04-29 基金项目:中央级公益性科研院所基本科研业务专项(CAFYBB2018QA001)。 作者简介:高鑫,男,博士,研究方向为木材物理与干燥。通信作者:周永东,男,研究员。E-mail: zhouyd@caf.ac.cn
更新日期/Last Update: 2019-11-10