首页> 外文期刊>Geoderma: An International Journal of Soil Science >Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.
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Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.

机译:可见,近红外,中红外或组合漫反射光谱法可同时评估各种土壤特性。

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摘要

Historically, our understanding of the soil and assessment of its quality and function has been gained through routine soil chemical and physical laboratory analysis. There is a global thrust towards the development of more time- and cost-efficient methodologies for soil analysis as there is a great demand for larger amounts of good quality, inexpensive soil data to be used in environmental monitoring, modelling and precision agriculture. Diffuse reflectance spectroscopy provides a good alternative that may be used to enhance or replace conventional methods of soil analysis, as it overcomes some of their limitations. Spectroscopy is rapid, timely, less expensive, non-destructive, straightforward and sometimes more accurate than conventional analysis. Furthermore, a single spectrum allows for simultaneous characterisation of various soil properties and the techniques are adaptable for 'on-the-go' field use. The aims of this paper are threefold: (i) determine the value of qualitative analysis in the visible (VIS) (400-700 nm), near infrared (NIR) (700-2500 nm) and mid infrared (MIR) (2500-25 000 nm); (ii) compare the simultaneous predictions of a number of different soil properties in each of these regions and the combined VIS-NIR-MIR to determine whether the combined information produces better predictions of soil properties than each of the individual regions; and (iii) deduce which of these regions may be best suited for simultaneous analysis of various soil properties. In this instance we implemented partial least-squares regression (PLSR) to construct calibration models, which were independently validated for the prediction of various soil properties from the soil spectra. The soil properties examined were soil pHCa, pHw, lime requirement (LR), organic carbon (OC), clay, silt, sand, cation exchange capacity (CEC), exchangeable calcium (Ca), exchangeable aluminium (Al), nitrate-nitrogen (NO3-N), available phosphorus (PCol), exchangeable potassium (K) and electrical conductivity (EC). Our results demonstrated the value of qualitative soil interpretations using the loading weight vectors from the PLSR decomposition. The MIR was more suitable than the VIS or NIR for this type of analysis due to the higher incidence spectral bands in this region as well as the higher intensity and specificity of the signal. Quantitatively, the accuracy of PLSR predictions in each of the VIS, NIR, MIR and VIS-NIR-MIR spectral regions varied considerably amongst properties. However, more accurate predictions were obtained using the MIR for pH, LR, OC, CEC, clay, silt and sand contents, P and EC. The NIR produced more accurate predictions for exchangeable Al and K than any of the ranges. There were only minor improvements in predictions of clay, silt and sand content using the combined VIS-NIR-MIR range. This work demonstrates the potential of diffuse reflectance spectroscopy using the VIS, NIR and MIR for more efficient soil analysis and the acquisition of soil information..
机译:历史上,我们通过常规的土壤化学和物理实验室分析获得了对土壤的了解并对其质量和功能进行了评估。由于对用于环境监测,建模和精确农业的大量高质量,廉价土壤数据的大量需求,全球都在寻求开发更具时间和成本效益的方法进行土壤分析。漫反射光谱法提供了一个很好的选择,可以克服传统方法的某些局限性,从而增强或替代传统的土壤分析方法。光谱法比常规分析方法快速,及时,便宜,无损,简单,有时甚至更准确。此外,单个光谱可以同时表征各种土壤特性,并且该技术适用于“随身携带”田间使用。本文的目的是三方面的:(i)确定可见光(VIS)(400-700 nm),近红外(NIR)(700-2500 nm)和中红外(MIR)(2500-500 nm)定性分析的价值25 000 nm); (ii)比较这些区域中每个区域的多种不同土壤性质的同时预测以及组合的VIS-NIR-MIR,以确定合并的信息是否比每个单独区域对土壤性质的预测更好; (iii)推论哪些区域最适合同时分析各种土壤特性。在这种情况下,我们实施了偏最小二乘回归(PLSR)来构建校准模型,该模型可独立验证以用于根据土壤光谱预测各种土壤特性。检查的土壤性质为土壤pHCa,pHw,石灰需求(LR),有机碳(OC),粘土,淤泥,沙,阳离子交换容量(CEC),可交换钙(Ca),可交换铝(Al),硝酸盐氮(NO3-N),有效磷(PCol),可交换钾(K)和电导率(EC)。我们的结果证明了使用PLSR分解中的荷载权重向量进行定性土壤解释的价值。 MIR比VIS或NIR更适合这种类型的分析,因为该区域的入射光谱带较高,并且信号的强度和特异性更高。从数量上看,各个属性的VIS,NIR,MIR和VIS-NIR-MIR光谱区域中PLSR预测的准确性存在很大差异。但是,使用MIR对pH,LR,OC,CEC,粘土,淤泥和沙含量,P和EC进行了更准确的预测。 NIR比任何范围都能更准确地预测可交换的Al和K。使用组合的VIS-NIR-MIR范围,对粘土,粉砂和沙子含量的预测只有很小的改进。这项工作证明了使用VIS,NIR和MIR进行漫反射光谱的潜力,可以更有效地进行土壤分析和获取土壤信息。

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