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Estimating organic carbon content of soil in Papua New Guinea using infrared spectroscopy

机译:红外光谱估算巴布亚新几内亚土壤的有机碳含量

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Quantification of soil organic carbon (SOC) content is important for sustainable agricultural management and accurate carbon accounting. Infrared (IR) absorbance can be used to estimate SOC content, but the relationship differs between regions due to matrix effects. We developed an IR-based model specific for SOC in Papua New Guinean soils. A total of 437 samples from 0.0-0.3m depth were analysed for SOC using Dumas combustion. IR absorption spectra were collected from the same samples, and a predictive regression model was developed using the 6000-1030 cm-1 spectral range. Using a validation set, predicted SOC values resulting from the IR-based model compared well with values from Dumas combustion (R-2 = 0.905; ratio of performance-to-deviation = 5.64). Constraining wavelengths to positively correlated regions of the spectra was also explored and showed improved model performance (R-2 = 0.932). Overall, IR analysis provides a robust method for estimating SOC content for a range of Papua New Guinean soils.
机译:土壤有机碳(SoC)含量的定量对于可持续农业管理和准确的碳核算是重要的。红外线(IR)吸光度可用于估计SoC含量,但由于矩阵效应,该关系在区域之间的不同之处。我们开发了一个基于IR的模型,特定于巴布亚新几内亚土壤中的SOC。使用Dumas燃烧分析SoC的0.0-3M深度的437个样品。从相同的样品中收集IR吸收光谱,使用6000-1030cm-1光谱范围开发预测性回归模型。使用验证集,从基于IR的模型产生的预测SOC值良好地与来自Dumas燃烧的值相比(R-2 = 0.905;比率到偏差= 5.64)。还探讨了限制波长到光谱的正相关区域,并显示出改善的模型性能(R-2 = 0.932)。总体而言,红外分析提供了一种稳健的方法,用于估算SoC含量,用于一系列巴布亚新几内亚土壤。

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