| 土壤有机质近红外光谱分析的波段优选 |
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| 引用本文： | 王瑛瑛,宋良图. 土壤有机质近红外光谱分析的波段优选[J]. 仪表技术, 2014, 0(5): 4-6,14 |
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| 作者姓名： | 王瑛瑛 宋良图 |
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| 作者单位： | [1]中国科学技术大学自动化系,安徽合肥230026 [2]中国科学院合肥智能机械研究所,安徽合肥230031 |
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| 摘 要： | 利用Savitzky-Golay(SG)卷积平滑方法和标准正态变量变换(SNV)对土壤光谱数据进行处理后,通过对波段的优选建立了主成分回归(PCR)模型。结果表明,预测样本的相关系数可达到0.932 2,预测标准差(RMSEP)为0.041 1%。
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| 关 键 词： | 土壤有机质 近红外光谱 波段优选 主成分回归 |
Waveband Optimization of Near Infrared Analysis of Soil Organic Matter |
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| WANG Ying-ying,SONG Liang-tu. Waveband Optimization of Near Infrared Analysis of Soil Organic Matter[J]. Instrumentation Technology, 2014, 0(5): 4-6,14 |
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| Authors: | WANG Ying-ying SONG Liang-tu |
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| Affiliation: | 1. Department of Automation, University of Science and Technology of China, Hefei 230026, China; 2.Institute of Intelligent Machines, Chinese Academy of Science, Hefei 230031, China) |
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| Abstract: | The pretreatment methods of Savitzky-Golay and Standard Normal Variate Transformation（ SNV） are used to deal with the soil spectrum. In order to set up a better prediction model,waveband optimization is necessary. This paper presents a new way to make the waveband optimization. Meantime,the prediction model is built using the Principal Component Regression（ PCR）. The result shows that the correlation coefficient can reach 0. 932 2 and the standard error of prediction is 0. 041 1%. |
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| Keywords: | soil organic matter near infrared spectroscopy waveband optimization PCR |
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