我国苹果栽培区土壤参数的近红外光谱检测研究  

Determination of Soil Quality from Chinese Apple Plant Area by NIR Spectroscopy

作　　者：董一威[1] 黄金丽[1] 孙宝利[1] 白薇[1] 范中南[1] 王亚男[1] 刘亚伟[1] 仝乘风[1] 

机构地区：[1]中国农业科学院农业环境与可持续发展研究所,农业部农业环境与气候变化重点开放实验室,北京100081

出　　处：《光谱学与光谱分析》2009年第8期2075-2078,共4页Spectroscopy and Spectral Analysis

基　　金：财政部土壤有机质提升试点补贴项目(1251610721336);科技部国际科技合作计划项目(2006DFB32180)资助

摘　　要：在全国11个主要苹果栽培区及其附近农田处,共收集111份土壤样本作为研究对象。使用傅里叶近红外光谱仪采集在12500～4000cm-1光谱范围内的土样漫反射光谱信息,并采用偏最小二乘回归法分别建立土壤有机质含量和pH值的近红外定标模型。为了有效消除土壤颗粒不均匀性所带来的散射影响,同时扣除与土壤品质参数无关的光谱信息,研究运用变量标准化(SNV)、附加散射校正(MSC)和直接正交信号校正(DOSC)等光谱预处理方法,使模型精度得到显著提高。结果显示,经过DOSC处理后,土壤有机质含量和pH值的近红外定标模型效果达到最佳,其相关系数(r)分别达到0.953和0.937,预测误差均方根(RMSEP)分别为0.258(%)和0.248(%)。研究表明,利用近红外光谱技术可以快速检测我国主要苹果栽培区土壤的有机质含量和pH值,为土壤施肥提供指导,为果树栽培提供技术支持。In the present work, 111 soil samples from 11 different Chinese apple plant areas were used to take the diffuse reflection spectra from 12 500 to 4 000 cm^-1 by FT-NIR. The models of organic substance and pH value of soil samples were built by using partial least square regression （PLSR）. The calibration model gave the correlation coefficients of 0. 818 and 0. 836 for the two values respectively, with the root mean square error of prediction （RMSEP） of 0. 377 （%） and 0. 251, respectively. In order to improve the robustness and performance of calibration, several spectra preprocessing methods were employed, including standard normalized variate （SNV）, multiplicative scatter correction （MSC） and direct orthogonal signal correction （DOSC）. Finally, the performance of DOSC was found to be the best for organic substance and pH value with RMSEP of 0. 258（%） and 0. 248, respectively. The results showed that the technology of NIR spectroscopy was useful to nondestructive determination of the organic substance and pH value of soil. These research findings provide theoretic base for fertilization and pomiculture by means of NIR diffuse reflection.

关 键 词：近红外 土壤 有机质 PH值 直接正交信号校正 

分 类 号：TG115.3[金属学及工艺—物理冶金]