Soil organic carbon (SOC) originates from a complex mixture of organic materials, and to better understand its role in soil functions, one must characterise its chemical composition. However, current methods, such as solid-state ¹³C nuclear magnetic resonance (NMR) spectroscopy, are time-consuming and expensive. Diffuse reflectance spectroscopy in the visible, near infrared and mid-infrared regions (vis–NIR: 350–2500 nm; mid-IR: 4000–400 cm⁻¹) can also be used to characterise SOC chemistry; however, it is difficult to know the frequencies where the information occurs. Thus, we correlated the C functional groups from the ¹³C NMR to the frequencies in the vis–NIR and mid-IR spectra using two methods: (1) 2-dimensional correlations of ¹³C NMR spectra and the diffuse reflectance spectra, and (2) modelling the NMR functional C groups with the reflectance spectra using support vector machines (SVM) (validated using 5 times repeated 10-fold cross-validation). For the study, we used 99 mineral soils from the agricultural regions of Sweden. The results show clear correlations between organic functional C groups measured with NMR and specific frequencies in the vis–NIR and mid-IR spectra. While the 2D correlations showed general relationships (mainly related to the total SOC content), analysing the importance of the wavelengths in the SVM models revealed more detail. Generally, models using mid-IR spectra produced slightly better estimates than the vis–NIR. The best estimates were for the alkyl C group (R² = 0.83 and 0.85, vis–NIR and mid-IR, respectively), and the O/N-alkyl C group was the most difficult to estimate (R² = 0.34 and 0.38, vis–NIR and mid-IR, respectively). Combining ¹³C NMR with the cost-effective diffuse reflectance methods could potentially increase the number of measured samples and improve the spatial and temporal characterisation of SOC. However, more studies with a wider range of soil types and land management systems are needed to further evaluate the conditions under which these methods could be used.

中文翻译：

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漫反射光谱表征农业土壤中土壤有机碳的功能化学

土壤有机碳 (SOC) 源自有机材料的复杂混合物，为了更好地了解其在土壤功能中的作用，必须对其化学成分进行表征。然而，目前的方法，如固态¹³ C 核磁共振 (NMR) 光谱法，既耗时又昂贵。可见光、近红外和中红外区域（可见近红外：350-2500 nm；中红外：4000-400 cm ^-1）的漫反射光谱也可用于表征 SOC 化学；但是，很难知道信息出现的频率。^{因此，我们使用两种方法将13} C NMR 中的 C 官能团与可见近红外和中红外光谱中的频率相关联：(1) ¹³的二维相关性C NMR 光谱和漫反射光谱，以及 (2) 使用支持向量机 (SVM) 使用反射光谱对 NMR 官能团 C 基团进行建模（使用 5 次重复 10 倍交叉验证进行验证）。在这项研究中，我们使用了来自瑞典农业区的 99 种矿质土壤。结果表明，用 NMR 测量的有机官能团 C 基团与 vis-NIR 和 mid-IR 光谱中的特定频率之间存在明显的相关性。虽然 2D 相关性显示出一般关系（主要与总 SOC 含量有关），但分析 SVM 模型中波长的重要性揭示了更多细节。一般来说，使用中红外光谱的模型比可见近红外光谱产生的估计略好。最好的估计是烷基 C 基团（R ² = 0.83 和 0.85，分别为 vis-NIR 和 mid-IR），O/N-烷基 C 基团最难估计（R ²  = 0.34 和 0.38，分别为 vis-NIR 和 mid-IR）。将¹³ C NMR 与具有成本效益的漫反射方法相结合可能会增加测量样品的数量并改善 SOC 的空间和时间表征。然而，需要对更广泛的土壤类型和土地管理系统进行更多研究，以进一步评估可以使用这些方法的条件。