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Comparison of Near Infrared Reflectance Spectroscopy with Combustion and Chemical Methods for Soil Carbon Measurements in Agricultural Soils

机译:近红外反射光谱法与燃烧法和化学法测定农业土壤中土壤碳的比较

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摘要

As interest in soil organic carbon (SOC) dynamics increases, so do needs for rapid, accurate, and inexpensive methods for quantifying SOC. Objectives were to i) evaluate near infrared reflectance (NIR) spectroscopy potential to determine SOC and soil organic matter (SOM) in soils from across Tennessee, USA; and ii) evaluate potential upper limits of SOC from forest, pasture, no-tillage, and conventional tilled sites. Samples were analyzed via dry-combustion (SOC), Walkley-Black chemical SOM, and NIR. In addition, the sample particle size was classified to give five surface roughness levels to determine effects of particle size on NIR. Partial least squares regression was used to develop a model for predicting SOC as measured by NIR by comparing against SOM and SOC. Both NIR and SOM correlated well (R-2>0.9) with SOC (combustion). NIR is therefore considered a sufficiently accurate method for quantifying SOC in soils of Tennessee, with pasture and forested systems having the greatest accumulations.Abbreviations SOC, soil organic carbon; NIR, Near Infrared Reflectance Spectroscopy; MTREC, Middle Tennessee Research and Education Center; RECM, Research and Education Center at Milan; PREC, Plateau Research and Education Center; PLS, Partial least squares.
机译:随着对土壤有机碳(SOC)动力学的兴趣增加,对用于定量SOC的快速,准确且廉价的方法的需求也在增加。目的是:i)评估近红外反射(NIR)光谱学潜力,以确定美国田纳西州土壤中的SOC和土壤有机质(SOM); ii)评估来自森林,牧场,免耕和常规耕种地点的SOC的潜在上限。通过干燃烧(SOC),Walkley-Black化学SOM和NIR分析样品。另外,将样品粒度分类以给出五个表面粗糙度水平,以确定粒度对NIR的影响。使用偏最小二乘回归开发了一个模型,用于通过与SOM和SOC进行比较来预测通过NIR测量的SOC。 NIR和SOM均与SOC(燃烧)相关性良好(R-2> 0.9)。因此,NIR被认为是定量田纳西州土壤中SOC的一种足够准确的方法,其中牧草和森林系统具有最大的积累量。 NIR,近红外反射光谱; MTREC,田纳西州中部研究与教育中心; RECM,米兰研究与教育中心; PREC,高原研究与教育中心; PLS,偏最小二乘。

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