Determinations of soil carbon and nitrogen stocks are important to evaluate land fertility and agricultural potential and because of their influence on the global climate. Spectroscopic determinations are faster, cheaper and less pollutant than traditional methods. The potential use of spectroscopy in the visible (Vis), near infrared (NIR) and mid-infrared (MIR) regions and their combination to estimate total C and N concentrations were evaluated using seven different pre-processing and two regression models and comparing to the concentrations determined by dry combustion of 701 soil samples from different soil classes and land uses in Northeast Brazil. Better C and N concentration predictions were obtained with the MIR region than with the Vis-NIR region and no significant improvement occurred when the two spectra were combined. The support vector machine (SVM) and the partial least squares (PLSR) models had similar performances both for C and N. The multiplicative scatter correction pre-processing is recommended for C and the standard normal transformation technique for N. Equations to estimate soil C and N concentrations of the predominant soil classes in the region and of the set of all classes are provided. Their high accuracy confirm the potential of reflectance spectroscopy as a useful and rapid tool to quantify C and N concentrations in different tropical soils and under different land uses.

测定土壤中的碳和氮储量对于评估土地肥力和农业潜力以及对全球气候的影响非常重要。光谱测定比传统方法更快，更便宜且污染物更少。使用七个不同的预处理和两个回归模型评估了光谱在可见（Vis），近红外（NIR）和中红外（MIR）区域中的潜在用途及其组合来估算总C和N浓度，并与通过巴西东北部701种不同土壤类型和土地利用的土壤样品的干烧确定浓度。使用MIR区域获得的C和N浓度预测要比使用Vis-NIR区域获得的更好，并且当将两个光谱合并使用时，并没有明显改善。支持向量机（SVM）和偏最小二乘（PLSR）模型在C和N上都有相似的性能。建议对C和N使用标准正态转换技术进行乘法散射校正预处理。估算土壤C的方程式提供了该地区和所有类别中主要土壤类别的N浓度。它们的高精度证实了反射光谱法作为量化不同热带土壤和不同土地利用下的碳和氮浓度的有用和快速工具的潜力。提供了估算该地区主要土壤类别和所有类别集合中土壤碳和氮浓度的方程。它们的高精度证实了反射光谱法作为量化不同热带土壤和不同土地利用下的碳和氮浓度的有用和快速工具的潜力。提供了估算该地区主要土壤类别和所有类别集合中土壤碳和氮浓度的方程。它们的高精度证实了反射光谱法作为量化不同热带土壤和不同土地利用下的碳和氮浓度的有用和快速工具的潜力。