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The Prediction of Pulpwood Extractives Content by Near Infrared Spectroscopy Combining with Lasso Algorithm
  
DOI:10.11981/j.issn.1000-6842.2015.04.22
Key Words:Lasso algorithm; near-infrared spectroscopy; pulpwood; extractive content
Fund Project:国家林业局948项目“农林剩余物制机械浆节能和减量技术引进”(2014-4-31)。
Author NameAffiliation
吴 珽1 1.中国林业科学研究院林产化学工业研究所,国家林业局林产化学工程重点开放性实验室,生物质化学利用国家工程实验室,江苏南京,210042 
房桂干1,* 1.中国林业科学研究院林产化学工业研究所,国家林业局林产化学工程重点开放性实验室,生物质化学利用国家工程实验室,江苏南京,210042 
梁 龙1 1.中国林业科学研究院林产化学工业研究所,国家林业局林产化学工程重点开放性实验室,生物质化学利用国家工程实验室,江苏南京,210042 
崔宏辉1 1.中国林业科学研究院林产化学工业研究所,国家林业局林产化学工程重点开放性实验室,生物质化学利用国家工程实验室,江苏南京,210042 
熊智新2 2.南京林业大学轻工科学与工程学院,江苏南京,210037 
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Abstract:
      The contents of cold water, hot water, benzene ethanol and 1.0% NaOH extractive of 144 pulpwood samples were analyzed using the traditional methods, meanwhile their near-infrared (NIR) spectra were also collected. After the pretreatment of original spectra, the optimal prediction models were established by using Lasso algorithm and cross-validation. The independent verification of the optimal prediction models showed the coefficients of determination (R2) were 0.9186, 0.9085, 0.9241 and 0.9760. The root mean square error of prediction (RMSEP) were 0.24%, 0.30%, 0.28% and 0.38%. The relative percent deviation (RPD) were 3.50, 3.31, 3.63 and 6.45. The absolute deviation (AD) were -0.42%~0.37%,-0.43%~0.41%,-0.47%~0.40%,-0.55%~0.57% respectively for cold water, hot water, benzene ethanol and 1.0% NaOH extractives. The prediction performance of the four models could meet the need of pulping and paper making industry and meanwhile Lasso algorithm was feasible for the prediction and analysis of pulpwood extractive content.
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