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Determination of Soil Parameters in Apple-Growing Regions by Near- and Mid-Infrared Spectroscopy

文献类型： 外文期刊

作者： Dong Yi-Wei 1 ; Yang Shi-Qi 2 ; Xu Chun-Ying 1 ; Li Yu-Zhong 1 ; Bai Wei 3 ; Fan Zhong-Nan 2 ; Wang Ya-Nan 2 ; Li Qiao-Zh 1 ;

作者机构： 1.Minist Agr, Key Lab Dryland Farming & Water Saving Agr, Beijing 100081, Peoples R China

2.Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Beijing 100081, Peoples R China

3.Minist Agr, Key Lab Agroenvironm & Climate Change, Beijing 100081, Peoples R China

关键词： heavy metals;partial least square regression;prediction accuracy;soil quality;spectroscopic method

期刊名称：PEDOSPHERE （ 影响因子：3.911； 五年影响因子：4.814 ）

ISSN： 1002-0160

年卷期： 2011 年 21 卷 5 期

页码：

收录情况： SCI

摘要： Soil quality monitoring is important in precision agriculture. This study aimed to examine the possibility of assessing the soil parameters in apple-growing regions using spectroscopic methods. A total of 111 soil samples were collected from 11 typical sites of apple orchards, and the croplands surrounding them. Near-infrared (NIR) and mid-infrared (MIR) spectra, combined with partial least square regression, were used to predict the soil parameters, including organic matter (OM) content, pH, and the contents of As, Cu, Zn, Pb, and Cr. Organic matter and pH were closely correlated with As and the heavy metals. The NIR. model showed a high prediction accuracy for the determination of OM, pH, and As, with correlation coefficients (r) of 0.89, 0.89, and 0.90, respectively. The predictions of these three parameters by MIR showed reduced accuracy, with r values of 0.77, 0.84, and 0.92, respectively. The heavy metals could also be measured by spectroscopy due to their correlation with organic matter. Both NIR and MIR had high correlation coefficients for the determination of Cu, Zn, and Cr, with standard errors of prediction of 2.95, 10.48, and 9.49 mg kg(-1) for NIR and 3.69, 5.84, and 6.94 mg kg(-1) for MIR., respectively. Pb content behaved differently from the other parameters. Both NIR and MIR underestimated Pb content, with r values of 0.67 and 0.56 and standard errors of prediction of 3.46 and 2.99, respectively. Cu and Zn had a higher correlation with OM and pH and were better predicted than Pb and Cr. Thus, NIR spectra could accurately predict several soil parameters, metallic and nonmetallic, simultaneously, and were more feasible than MIR in analyzing soil parameters in the study area.

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