生态与农村环境学报 ›› 2018, Vol. 34 ›› Issue (3): 282-287.doi: 10.11934/j.issn.1673-4831.2018.03.013

• 研究方法 • 上一篇    

应用近红外光谱快速分析生物炭性质

单瑞峰, 孙小银, 王萧, 甄书仙   

  1. 曲阜师范大学地理与旅游学院/南四湖湿地生态与环境保护山东省高校重点实验室, 山东 日照 276826
  • 收稿日期:2017-09-13 出版日期:2018-03-25 发布日期:2018-03-23
  • 通讯作者: 单瑞峰,E-mail:ruifengshan@sina.com E-mail:ruifengshan@sina.com
  • 作者简介:单瑞峰(1978-),女,山东菏泽人,讲师,博士,主要从事环境分析和化学计量学方面的研究。E-mail:ruifengshan@sina.com
  • 基金资助:

    国家自然科学基金(41501542);山东省重点研发计划(2016GNC110017);山东省中青年科学家奖励基金(BS2013NY009);山东省高校科技计划(J13LF02)

Properties Analysis of Biochar Using Near-Infrared Spectroscopy

SHAN Rui-feng, SUN Xiao-yin, WANG Xiao, ZHEN Shu-xian   

  1. College of Geography and Tourism, Qufu Normal University/Key Laboratory of Wetland Ecology and Environmental Protection in Nansi Lake of Shandong Province, Rizhao 276826, China
  • Received:2017-09-13 Online:2018-03-25 Published:2018-03-23

摘要:

为了快速分析不同热解温度条件下制备的生物炭性质的差异,以玉米秸秆为原料,应用近红外光谱技术并结合偏最小二乘和最小二乘支持向量机回归方法对300、400、500和600℃条件下制备的生物炭性质进行预测,采用主成分分析和线性判别分析对生物炭的热解温度进行判别。结果表明,所建方法对于灰分、固定碳、C和H的预测效果较好,预测均方根误差和剩余预测偏差分别为0.024 2、0.029 9、0.016 9、0.001 7和1.32、3.50、3.44、5.66,其决定系数分别为0.974 2、0.912 6、0.912 5及0.927 4。线性判别分析对生物炭热解温度的判别准确度为100%。相对于湿化学方法,近红外光谱技术分析生物炭的性质具有快速、无损等特点,该方法的建立对于生物炭的广泛应用具有重要意义。

关键词: 生物炭, 热解温度, 近红外光谱, 理化性质, 预测

Abstract:

In order to rapidly determine difference between biochars produced at different temperatures in property, partial least squares (PLS) and least squares support vector regression (LSSVR) were used to predict properties of the biochars produced out of corn stalk through pyrolysis at 300, 400, 500 and 600℃ and then principal component analysis (PCA) and linear discrimination analysis (LDA) were done of the biochars to determine which one was pyrolyzed at what temperature. Prediction and analysis of the biochars for properties such as contents of ash, fixed carbon, carbon (C), and hydrogen (H) was performed using a near-infrared spectroscopy coupled with several statistical approaches, with root mean squares error of prediction (RMSEP) being 0.024 2, 0.029 9, 0.016 9 and 0.001 7, residual predictive deviation (RPD) being 1.32, 3.50, 3.44 and 5.66, and corresponding coefficients determination (R2) being 0.974 2, 0.912 6, 0.912 5 and 0.927 4, respectively. Moreover, the determination of temperature at which the biochars had been pyrolyzed was done successfully with 100% accuracy with LDA. Results show that compared with the wet chemical method, near-infrared spectroscopy features rapidity and non-destructiveness in analyzing biochar properties. The proposed method is of great significance to wide application of biochar.

Key words: biochar, pyrolysis temperature, near-infrared spectroscopy, physical and chemical property, prediction

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