日本落叶松化学性状的快速测定方法

公开一种日本落叶松木材化学性状检测方法，该方法包括获取若干样品；采用湿化学法测量每一样品的木质素、α-纤维素和综纤维素的实测浓度，建立浓度矩阵；，对采集的每一样品的近红外光谱数据进行预处理，得到样品在每一波长点处的吸光度，建立吸光度矩阵；根据浓度矩阵和吸光度矩阵采用偏最小二乘法建立木材化学性状初始检测模型；以部分样品作为训练集，以剩余部分样品作为预测集，训练和测试木材化学性状初始检测模型，得到木材化学性状最终检测模型；利用木材化学性状最终检测模型检测待测日本落叶松的木材化学性状，得到待测日本落叶松的木质素、α-纤维素和综纤维素的浓度。本发明实现了对日本落叶松木材化学性状快速且准确的检测。

A detection method for chemical traits of Japanese larch wood is disclosed. The method includes acquiring multiple samples. The actual concentrations of lignin, α-cellulose and holocellulose in each sample are measured via wet chemistry methods to establish a concentration matrix. Preprocessing is performed on the near-infrared spectral data of each collected sample to obtain the absorbance values of the sample at each wavelength point, thereby establishing an absorbance matrix. An initial detection model for wood chemical traits is established using partial least squares regression based on the concentration matrix and absorbance matrix. A portion of the samples are used as the training set, while the remaining samples serve as the prediction set to train and test the initial detection model, thus obtaining the final detection model for wood chemical traits. The final detection model for wood chemical traits is employed to detect the chemical traits of the target Japanese larch sample, yielding the concentrations of lignin, α-cellulose and holocellulose of the tested sample. The present invention realizes rapid and accurate detection of the chemical traits of Japanese larch wood.

搜集汇总

背景与挑战

背景概述

该数据集公开了一种日本落叶松木材化学性状的快速测定方法，基于近红外光谱数据和偏最小二乘法建立检测模型，用于测定木质素、α-纤维素和综纤维素的浓度。数据集属于'落叶松高效培育技术研究'项目，数据时间为2018年，数据量为660.49 KB，共享级别为协议共享数据，适用于植物学和林学研究领域。