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中国农学通报 ›› 2013, Vol. 29 ›› Issue (35): 182-186.doi: 10.11924/j.issn.1000-6850.2013-0091

所属专题: 玉米

• 工程 机械 水利 装备 • 上一篇    下一篇

近红外光谱法测定玉米秸秆纤维素和半纤维素含量

刘会影 李国立 薛冬桦 徐洪章 叶小金   

  • 收稿日期:2013-01-09 修回日期:2013-02-26 出版日期:2013-12-15 发布日期:2013-12-15
  • 基金资助:
    吉林省科技厅项目

Determination of cellulose and hemicellulose in corn straw by near infrared reflectance spectroscopy

  • Received:2013-01-09 Revised:2013-02-26 Online:2013-12-15 Published:2013-12-15

摘要: 为了解玉米秸秆资源可转化碳水化合物物质基础,建立了玉米秸秆中纤维素及半纤维素近红外分析模型。利用傅里叶变换近红外漫反射光谱(NIRS)技术和化学计量学软件,结合偏最小二乘法(PLS),通过光谱采集,进行了近红外光谱模型预测及验证。探讨了不同预处理方法对玉米秸秆纤维素和半纤维素含量的NIRS模型影响,获得理想分析模型,相关系数(R)≥0.909。实验结果表明模型对纤维素、半纤维素含量预测平均相对误差为2.34%和2.13%,预测值与化学值误差较小。说明该模型可准确、快速并大量检测玉米秸秆中纤维素和半纤维素含量,提高秸秆生物质资源利用率,促进生物质转化工艺过程。

关键词: 水体污染, 水体污染

Abstract: To understand corn straw carbohydrate composition, a corn straw cellulose and hemicellulose contents model was developed using Near-infrared Spectroscopy (NIRS). An ideal model was obtained after multiple trial-and-error prediction/validation processes, using spectrum analysis together with partial least squares (PLS) method. Based on this model, influences of different pretreatment methods on corn straw cellulose and hemicellulose contents were investigated. A correlation coefficient of 0.909 was achieved. Compared with the experimental data, the values predicted by this NIRS model have mean relative errors of 2.34% and 2.13% for cellulose and hemicellulose contents, respectively. This model is capable of accurately and quickly analyzing corn straw cellulose and hemicellulose contents at industrial scale, which is beneficial to the utilization of biomass resources and the biomass conversion process.

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