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- 2018
基于近红外光谱法快速测定秸秆堆腐过程中纤维素、半纤维素和木质素含量的研究
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Abstract:
探索建立秸秆化学成分的近红外快速准确检测模型,将有助于秸秆腐熟程度判定及秸秆利用产业在线控制。本研究利用添加堆腐剂对小麦秸秆进行腐熟试验,以腐熟过程中的小麦秸秆样品为研究对象,利用NIRS构建快速检测秸秆主要成分含量的定量检测模型。研究结果显示,可以通过NIRS在短时间内精准检测小麦秸秆腐解过程中纤维素、半纤维素、木质素的含量,定标相关系数Rc分别为0.976 7、0.980 5和0.984 8,矫正相关系数分别为0.984 1、0.987 2和0.989 8,全交互验证相关系数为0.979 8、0.989 2和0.987 3,RPD值分别为4.84、6.57和5.75均>3.0,定标效果良好。
Exploration and establishment of rapid contend determination of cellulose and, hemicellulose and lignin contents during wheat straw compose period based on Near-Infrared reflectance spectroscopy would help to determine crop residue decomposition degree and to realize industrial on-line control.In this study, a prediction model was established for rapid detection of cellulose, hemicellulose and lignin combined with partial least squares method using near infrared reflectance spectroscopy by adding compost maturity agent experiment on wheat straw, and the maturity in the process of wheat samples were taken as the research object.The results showed that the near infrared diffuse reflectance spectroscopy could quickly detect the content of cellulose, hemicellulose and lignin in the straw during decomposition process.The calibration correlation coefficient Rcs were respectively 0.976 7, 0.980 5, 0.984 8.The corrected correlation coefficients were 0.984 1, 0.987 2, 0.989 8, respectively.The cross validation correlation coefficient was 0.979 8, 0.989 2, 0.987 3.RPDs were 4.84, 6.57 and 5.75 and were all higher than 3.00 indicating good scaling effects.In summary, the model provided the necessary references for the rapid determination of the degree of straw maturity and industrialization.