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首页> 外文期刊>European Journal of Soil Science >Using soil knowledge for the evaluation of mid-infrared diffuse reflectance spectroscopy for predicting soil physical and mechanical properties
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Using soil knowledge for the evaluation of mid-infrared diffuse reflectance spectroscopy for predicting soil physical and mechanical properties

机译:利用土壤知识评估中红外漫反射光谱法预测土壤的物理和机械性能

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Mid-infrared diffuse reflectance spectroscopy can provide rapid, cheap and relatively accurate predictions for a number of soil properties. Most studies have found that it is possible to estimate chemical properties that are related to surface and solid material composition. This paper focuses on prediction of physical and mechanical properties, with emphasis on the elucidation of possible mechanisms of prediction. Soil physical properties that are based on pore-space relationships such as bulk density, water retention and hydraulic conductivity cannot be predicted well using MIR spectroscopy. Hydraulic conductivity was measured using a tension-disc permeameter, excluding the macropore effect, but MIR spectroscopy did not give a good prediction. Properties based on the soil solid composition and surfaces such as clay content and shrink-swell potential can be predicted reasonably well. Macro-aggregate stability in water can be predicted reasonably as it has a strong correlation with carbon content in the soil. We found that most of the physical and mechanical properties can be related back to the fundamental soil properties such as clay content, carbon content, cation exchange capacity and bulk density. These connections have been explored previously in pedotransfer functions studies. The concept of a spectral soil inference system is reiterated: linking the spectra to basic soil properties and connecting basic soil properties to other functional soil properties via pedotransfer functions.
机译:中红外漫反射光谱可以为许多土壤特性提供快速,廉价和相对准确的预测。大多数研究发现,可以估算与表面和固体材料成分有关的化学性质。本文着重于物理和机械性能的预测,着重于阐明可能的预测机制。使用MIR光谱无法很好地预测基于孔隙空间关系的土壤物理特性,例如堆积密度,保水性和水力传导率。使用张力圆盘渗透仪测量了水力传导率,不包括大孔效应,但MIR光谱法无法给出良好的预测。可以合理地预测基于土壤固体成分和表面的特性,例如粘土含量和收缩膨胀势。由于它与土壤中的碳含量有很强的相关性,因此可以合理地预测水中的宏观聚集体稳定性。我们发现,大多数物理和机械性质都可以与土壤的基本性质相关,例如粘土含量,碳含量,阳离子交换容量和堆积密度。这些连接以前已经在pedotransfer函数研究中进行了探讨。重申了光谱土壤推断系统的概念:将光谱链接到基本土壤属性,并通过pedotransfer函数将基本土壤属性与其他功能性土壤属性连接。

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