【摘要】 为实现秸秆不同部位组分的快速无损检测,以玉米秸秆分离的皮、瓤、叶为研究对象,通过光谱采集分析和化学检测相结合的方法,对该玉米秸秆各部位中的纤维素及木质素的含量进行数据分析和试验验证。试验结果表明:光谱信息中H基团的振动强弱确定玉米秸秆纤维素与木质素的含量依次为皮>叶>瓤。纤维素模型采用1阶微分与标准化结合的预处理方式,木质素模型采用1阶微分与标准正态变量相结合的预处理方式,经过试验验证分析,预测模型的相对误差均小于3%,有较高的相关度和预测效果,表明利用FTIR技术对玉米秸秆的组分含量的检测数据可靠,在线检测效率高,可为快速检测秸秆组分提供新的测量方法和手段。更多还原

【Abstract】 The content of cellulose and lignin in the separated skin,core and leaves of corn straw were analyzed by means of combination of spectral analysis and chemical detection,and then the validity of prediction models were tested in order to realized the rapid nondestructive detection of the different parts of the components of straw. The results showed that the content of cellulose and lignin of corn straw were determined as skin,pulp and leaves sequence by the vibration strength of H group in spectral information. The cellulose model was pretreated by first order differentiation and standardization,and the lignin model was pretreated by first order differential and standard normal variables,The verification analysis of the experiment shows that the relative errors of the prediction models are less than 3% indicating a higher correlation and prediction effect. The results show that the test data online by FTIR of cellulose and lignin in the separated skin,pulp and leaves of corn straw content is reliable,It provides a new rapid nondestructive measuring method with high efficiency.更多还原