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首页> 外文期刊>Journal of Wood Chemistry and Technology >Predicting Extractives, Lignin, and Cellulose Contents Using Near Infrared Spectroscopy on Solid Wood in Eucalyptus globulus
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Predicting Extractives, Lignin, and Cellulose Contents Using Near Infrared Spectroscopy on Solid Wood in Eucalyptus globulus

机译：使用近红外光谱法对球形桉木中的提取物，木质素和纤维素含量进行预测

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摘要

Near infrared reflectance (NIR) spectroscopy can be used to reliably predict both the physical and chemical wood properties of Eucalyptus. However, studies have been based on ground wood, which is costly and time-consuming to obtain. Predicting wood traits from NIR spectral data taken from solid wood would greatly increase the speed and cost-effectiveness of this procedure. Existing ground wood calibrations were evaluated for the prediction of wood chemistry from NIR spectral data taken from solid wood. Extractives, acid-soluble lignin, and Klason lignin contents were poorly predicted. Total lignin and cellulose contents showed moderate relationships between laboratory values and the NIR predicted values. NIR calibrations were further developed specifically for predicting wood chemistry from solid wood. All calibrations had high R~2 values from 0.72 to 0.88, and standard errors of calibration were less than 1.37%. Calibration validation produced high correlation coefficients between predicted and laboratory values for extractives, Klason lignin, total lignin, and cellulose contents with R~2 values ranging from 0.67 to 0.87. Acid-soluble lignin content was poorly predicted. This study showed that NIR analysis on solid wood of E. globulus could be reliably used to predict extractives, lignin, and cellulose contents. It also determined that existing ground wood calibrations, although they could give crude estimates of the wood chemistry values, would need to be re-developed for accurate predictions from solid wood.
机译：近红外反射（NIR）光谱可用于可靠地预测桉树的物理和化学木材性能。然而，已经基于磨碎的木材进行研究，这是昂贵且耗时的。根据从实木获得的NIR光谱数据预测木材特性，将大大提高此过程的速度和成本效益。对现有的地面木材标定进行了评估，以根据从实木获取的NIR光谱数据预测木材化学成分。提取物，酸溶性木质素和Klason木质素含量预测不良。木质素和纤维素的总含量显示实验室值与NIR预测值之间的适度关系。近红外光谱校准被进一步开发，专门用于预测实木的化学成分。所有校准的R〜2值均在0.72至0.88之间，校准的标准误差小于1.37％。校准验证在提取物，Klason木质素，总木质素和纤维素含量的预测值与实验室值之间具有较高的相关系数，R〜2值介于0.67至0.87之间。酸溶性木质素含量预测不佳。这项研究表明，对球形小球藻的实木进行的近红外光谱分析可以可靠地用于预测提取物，木质素和纤维素含量。它还确定了现有的地面木材校准，尽管它们可以给出木材化学值的粗略估计，但仍需要重新开发，以根据实木进行准确的预测。

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