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Application of Visible/Near-Infrared Spectra in Modeling of Soil Total Phosphorus

机译:可见/近红外光谱在土壤总磷建模中的应用

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摘要

Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida,USA.Therefore,it is essential to analyze and predict the distribution of P in soils across large areas.This study was undertaken to model the variation of soil total phosphorus (TP) in Florida.A total of 448 soil samples were collected from different soil types.Soil samples were analyzed by chemical reference method and scanned in the visibleear-infrared (VNIR) region of 350-2 500 nm.Partial least squares regression (PLSR) calibration model was developed between chemical reference values and VNIR values.The coefficient of determination (R2) and the root mean squares error (RMSE) of calibration and validation sets,and the residual prediction deviation (RPD) were used to evaluate the models.The R2 in calibration and validation for log-transformed TP (log TP) were 0.69 and 0.65,respectively,indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra,and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types,being representative of Florida soil conditions.
机译:在美国佛罗里达州,土壤和水中磷的过量富集备受关注,引起了广泛关注。因此,对大面积土壤中磷的分布进行分析和预测是至关重要的。佛罗里达土壤总磷(TP)的变化。共收集了448种不同土壤类型的土壤样品。通过化学参考方法对土壤样品进行分析,并在350-2 500的可见/近红外(VNIR)区域进行扫描在化学参考值和VNIR值之间建立了偏最小二乘回归(PLSR)校准模型。校准和验证集的测定系数(R2)和均方根误差(RMSE),以及残留预测偏差(RPD)对数转换后的TP(log TP)的校准和验证中的R2分别为0.69和0.65,表明本研究中获得的VNIR校准至少占65%。仅使用VNIR光谱测得的对数TP的方差以及获得的2.82的高RPD均表明,本研究得出的光谱模型适用于多种土壤类型的TP预测,是佛罗里达州土壤状况的典型代表。

著录项

  • 来源
    《土壤圈(英文版)》 |2013年第4期|417-421|共5页
  • 作者

    HU Xue-Yu;

  • 作者单位

    School of Environmental Studies, China University of Geosciences, Wuhan 430074 China;

    Soil and Water Science Department, University of Florida, Gainesville, FL 32611 USA;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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