基于红外光声光谱的农作物秸秆导热系数定量分析  

Rapid Quantitative Analysis of Crop Straws' Thermal Conductivity Based on Infrared Photoacoustic Spectroscopy

作　　者：黄光群[1] 段宏伟 何金鸿 韩鲁佳[1] HUANG Guangqun;DUAN Hongwei;HE Jinhong;HAN Lujia(College of Engineering, China Agricultural University, Beijing 100083, China)

机构地区：[1]中国农业大学工学院,北京100083

出　　处：《农业机械学报》2018年第7期342-347,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：欧盟框架计划项目(690142);教育部创新团队发展计划项目(IRT1293);国家重点研发计划项目(2018YFD0800102)

摘　　要：选用我国华北地区具有代表性的小麦、玉米、水稻秸秆样品,对比研究了偏最小二乘(PLSR)和高斯核支持向量机(RBF-SVR)分别构建单一和混合种类秸秆全波段定量分析模型的效果,探讨了红外光声光谱耦合化学计量学方法构建我国主要粮食作物秸秆导热系数定量分析模型的可行性。研究发现,小麦秸秆和水稻秸秆导热系数RBF-SVR非线性模型,以及玉米秸秆、混合种类秸秆的PLSR线性模型效果较优。进一步应用蚁群算法与上述最优建模方法相结合,构建了更加优化的小麦秸秆、玉米秸秆、水稻秸秆和混合秸秆导热系数模型,验证决定系数(R_p^2)分别为0.77、0.83、0.96和0.79,验证均方差(RMSEP)分别为0.007 8、0.015、0.005 9、0.014 W/(m·K),验证相对分析误差(RPD)分别为2.81、2.41、7.39和2.15。研究结果表明,红外光声光谱技术结合先进适用的化学计量学方法可实现我国主要粮食作物秸秆导热系数的快速定量分析,但混合秸秆模型预测精度仍需进一步提升。Rapid determination of thermal conductivity is of great significance for realizing high-efficient and value-added utilization of crop straw. The feasibility of infrared photoacoustic spectroscopy coupled with chemometrics for developing the quantitative models of main crop straws’ thermal conductivity in China was investigated. The representative samples of wheat, corn and rice straws were initially acquired from North China, and the full-band models of single and mixed kinds of straws were then developed by using the partial least squares regression （PLSR） and Gaussian kernel support vector regression （RBF-SVR）. By comparing the model effects of PLSR and RBF-SVR, it was found that the full band RBF-SVR models of wheat stalk and rice straw had better performances, while the full band PLSR models were more appropriate for corn and mixed straws. Moreover, based on the combination of above mentioned optimal modeling method and the ant colony algorithm, the new feature models of wheat, corn, rice and mixed straws showed better performances, which yielded determination coefficient of prediction set （Rp^2） of 0.77, 0.83, 0.96 and 0.79, root mean square error of prediction set （RMSEP） of 0.0078, 0.015, 0.0059 and 0.014W/（m·K）, relative percent deviation of prediction set （RPD） of 2.81, 2.41, 7.39 and 2.15, respectively. Results showed that FTIR-photoacoustic spectroscopy coupled with applicable chemometrics had good potential for rapid quantitative analysis of main crop straws’ thermal conductivity in China.

关 键 词：农作物秸秆 导热系数 红外光声光谱 偏最小二乘 高斯核支持向量机 蚁群算法 

分 类 号：S210[农业科学—农业机械化工程]