Teng Jing, He Zheng-wei, Ni Zhong-yun, Zhao Yin-quan, Zhang Zhi
Guang Pu Xue Yu Guang Pu Fen Xi. 2016 Nov;36(11):3637-42.
In order to solve the problem of high cost and low efficiency by using the traditional soil geochemical survey methods, this paper studied the simple detection method of soil heavy metal content with visible and near-infrared reflectance spectroscopy. The study collected visible and near-infrared reflectance spectroscopy of soil samples in Xifanping mining area; then treated the reflectance spectroscopy with six mathematic changes such as differentials and continuum removal in advance; the next step was to select characteristic wavelengths that were sensitive to soil copper content by using stepwise regression method and Pearson correlation coefficient as set of comprehensive characteristic variables; finally, utilized different methods and parameters of characteristic variable selection to build the soil total copper content models and tested them. Results showed that: to extract the information of copper content in soil, the performance of different spectral transform methods varied, and each spectrum transform method corresponded to its certain sensitive spectral ranges; the inversion models based on the integrated spectrum transform information were better than that based on only one kind of spectrum transform information; as for establishing the prediction model of soil copper content by using the integrated spectrum transform information, backward elimination was better than forward selection and stepwise selection, and when the Removal is 0.20, the optimum model was obtained, its coefficients of determination(R(2))and determination coefficients of prediction(R(2)(pre))reached 0.851 and 0.830, root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 0.349 and 0.468 mg·kg(-1). The model has a good precision, and it provides a train of thought for the detection of other soil heavy metal elements with visible and near-infrared reflectance spectroscopy.
为了解决传统土壤地球化学调查方法成本高、效率低的问题，本文研究了利用可见-近红外反射光谱法简单检测土壤重金属含量的方法。研究采集了西范坪矿区土壤样品的可见-近红外反射光谱；然后预先对反射光谱进行微分、连续统去除等六种数学变换处理；下一步是采用逐步回归法和皮尔逊相关系数选择对土壤铜含量敏感的特征波长作为综合特征变量集；最后，利用不同的特征变量选择方法和参数建立土壤总铜含量模型并进行检验。结果表明：在提取土壤中铜含量信息时，不同光谱变换方法的性能各异，每种光谱变换方法都对应其特定的敏感光谱范围；基于综合光谱变换信息的反演模型优于仅基于一种光谱变换信息的模型；在利用综合光谱变换信息建立土壤铜含量预测模型时，向后剔除法优于向前选择法和逐步选择法，当去除率为0.20时，获得最优模型，其决定系数（R²）和预测决定系数（R²(pre)）分别达到0.851和0.830，校准均方根误差（RMSEC）和预测均方根误差（RMSEP）分别为0.349和0.468 mg·kg⁻¹。该模型具有良好的精度，为利用可见-近红外反射光谱法检测其他土壤重金属元素提供了思路。
