首页> 外文期刊>European Journal of Soil Science >Determination of organic carbon and nitrogen in particulate organic matter and particle size fractions of Brookston clay loam soil using infrared spectroscopy.
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Determination of organic carbon and nitrogen in particulate organic matter and particle size fractions of Brookston clay loam soil using infrared spectroscopy.

机译:红外光谱法测定布鲁克斯顿粘土壤土中颗粒状有机质和粒度级分中的有机碳和氮。

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The objective of this study was to determine whether models developed from infrared spectroscopy could be used to estimate organic carbon (C) content, total nitrogen (N) content and the C:N ratio in the particulate organic matter (POM) and particle size fraction samples of Brookston clay loam. The POM model was developed with 165 samples, and the particle size fraction models were developed using 221 samples. Soil organic C and total N contents in the POM and particle size fractions (sand, 2000-53 micro m; silt, 53-2 micro m; clay, <2 micro m) were determined by using dry combustion techniques. The bulk soil samples were scanned from 4000 to 400 cm-1 for mid-infrared (MIR) spectra and from 8000 to 4000 cm-1 for near-infrared (NIR) spectra. Partial least squares regression (PLSR) analysis and the 'leave-one-out' cross-validation procedure were used for the model calibration and validation. Organic C and N content and C:N ratio in the POM were well predicted with both MIR- and NIR-PLSR models (Rcal2=0.84-0.92; Rval2=0.78-0.87). The predictions of organic C content in soil particle size fractions were also very good for the model calibration (Rcal2=0.84-0.94 for MIR and Rcal2=0.86-0.92 for NIR) and model validation (Rval2=0.79-0.94 for MIR and Rcal2=0.84-0.91 for NIR). The prediction of MIR- and NIR-PLSR models for the N content and the C:N ratio in the sand and clay fractions was also satisfactory (Rcal2=0.73-0.88; Rval2=0.67-0.85). However, the predictions for the N content and C:N ratio in the silt fraction were poor (Rcal2=0.23-0.55; Rcal2=0.20-0.40). The results indicate that both MIR and NIR methods can be used as alternative methods for estimating organic C and total N in the POM and particle size fractions of soil samples. However, the NIR model is better for estimating organic C and N in POM and sand fractions than the MIR model, whereas the MIR model is superior to the NIR model for estimating organic C in silt and clay fractions and N in clay fractions.
机译:这项研究的目的是确定是否可以使用红外光谱学开发的模型来估算有机碳(C)含量,总氮(N)含量以及颗粒有机物(POM)和颗粒尺寸分数中的C:N比布鲁克斯顿粘土壤土的样本。用165个样品开发了POM模型,并使用221个样品开发了粒径分级模型。通过使用干式燃烧技术测定了POM中的土壤有机碳和总N含量以及粒径分数(沙子为2000-53微米;淤泥为53-2微米;粘土为<2微米)。从4000到400 cm -1 的大块土壤样品扫描中红外(MIR)光谱,从8000到4000 cm -1 进行近红外(NIR)扫描光谱。偏最小二乘回归(PLSR)分析和“留一法”交叉验证程序用于模型校准和验证。使用MIR-和NIR-PLSR模型( R cal 2 都可以很好地预测POM中的有机C和N含量以及C:N比= 0.84-0.92; R val 2 = 0.78-0.87)。土壤颗粒级分中有机碳含量的预测也非常适合模型校准(MIR的 R cal 2 = 0.84-0.94和 R cal 2 = 0.86-0.92(用于NIR)和模型验证( R val 2 = 0.79-0.94(对于MIR, R cal 2 = 0.84-0.91)。 MIR-和NIR-PLSR模型对砂和粘土组分中N含量和C:N比的预测也令人满意( R cal 2 = 0.73-0.88; R val 2 = 0.67-0.85)。但是,对粉砂中氮含量和C:N比的预测很差( R cal 2 = 0.23-0.55; < i> R cal 2 = 0.20-0.40)。结果表明,MIR和NIR方法都可以用作估算土壤样品中POM和粒径分数中有机碳和总氮的替代方法。但是,NIR模型比MIR模型更好地估计POM和砂中的有机碳和N,而MIR模型优于NIR模型来估计粉质和粘土中的有机C和粘土中的N。

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