• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Wood Chemistry and Technology >Rapid Prediction of Different Wood Species Extractives and Lignin Content Using Near Infrared Spectroscopy
【24h】

Rapid Prediction of Different Wood Species Extractives and Lignin Content Using Near Infrared Spectroscopy

机译：近红外光谱法快速预测不同木材的提取物和木质素含量

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The feasibility of using Fourier transform near infrared spectroscopy (FT-NIR) to rapidly determine the lignin and extractive content of various wood species (including softwoods and hardwoods) was investigated. Partial Least Square regression analyses were performed to describe the relationships between the data sets of wet laboratory chemical data and the FT-N1R spectra. The selection of relevant wavenum-bers combined with the appropriate data pre-processing methods produced satisfactory prediction models. The test statistics (R~2, RMSECV, RMSEP, RPD) improved compared with the models over the wave number range 7500 cm~(-1) to 4000 cm~(-1). Automatic selection was superior to manual selection. The predicted lignin and extractive content models, using the full cross-validation in the appropriate wave number ranges (in cm~(-1)) of 5450.1 to 4246.7, 6102.1 to 4597.7, 6252.4 to 4246.7, and 6252.4 to 6098.1 using the spectral data preprocessing methods of the straight-line subtraction, minimum-maximum normalization, and first derivative + vector normalization, were established. The high R2 values were 0.9838, 0.9809, and 0.9625, respectively. The low RMSECV values were 0.425%, 0.452%, and 0.185%, respectively. RPD values were 7.86, 7.25, and 5.17, respectively. Predictions were very good, with R~2 of 0.9775, 0.9751, and 0.9521; RMSEP of 0.418%, 0.403%, and 0.206%; and RPD of 6.78, 6.7, and 4.57 for the lignin, 1% sodium hydroxide extractive, and ethanol-benzene extractive models, respectively.
机译：研究了使用傅里叶变换近红外光谱（FT-NIR）快速确定各种木材（包括软木和硬木）的木质素和提取物含量的可行性。进行了偏最小二乘回归分析以描述湿实验室化学数据的数据集与FT-N1R光谱之间的关系。相关波峰的选择与适当的数据预处理方法相结合，产生了令人满意的预测模型。在波数范围7500 cm〜（-1）至4000 cm〜（-1）范围内，与模型相比，测试统计量（R〜2，RMSECV，RMSEP，RPD）有所提高。自动选择优于手动选择。使用光谱数据在5450.1至4246.7、6102.1至4597.7、6252.4至4246.7和6252.4至6098.1的适当波数范围（以cm〜（-1）为单位）中使用完全交叉验证的预测木质素和提取物含量模型建立了直线减法，最小-最大归一化和一阶导数+向量归一化的预处理方法。高R2值分别为0.9838、0.9809和0.9625。低RMSECV值分别为0.425％，0.452％和0.185％。 RPD值分别为7.86、7.25和5.17。预测非常好，R〜2为0.9775、0.9751和0.9521； RMSEP为0.418％，0.403％和0.206％；木质素模型，1％氢氧化钠萃取模型和乙醇-苯萃取模型的RPD分别为6.78、6.7和4.57。

著录项

  • 来源
    《Journal of Wood Chemistry and Technology》 |2013年第1期|52-64|共13页
  • 作者

    WENMING HE; HUIREN HU;

  • 作者单位

    Tianjin University of Science and Technology, Tianjin Key Lab of Pulp and Paper Engineering, Tianjin, China;

    Tianjin University of Science and Technology, Tianjin Key Lab of Pulp and Paper Engineering, Tianjin, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    FT-NIR; wood; extractives; lignin;

    机译：FT-NIR;木;提取物;木质素;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号