中文摘要：

土壤全氮是诊断土壤肥力水平和指导作物精确施肥所需的重要信息,建立土壤全氮的近红外光谱估测模型并对建模波段进行优化选择对于土壤养分信息快速获取和精确农业发展具有重要意义。该研究以中国中、东部地区5种主要类型土壤为研究对象,利用近红外光谱仪采集土壤样品的光谱信息,结合近红外区域分子振动特点选取全谱、合频、一倍频、二倍频和N-H基团及其组合的8个波段,采用多元散射校正等多种预处理方法组合进行处理,结合偏最小二乘法（PLS）对每个波谱区域进行定标建模。结果表明,利用4000～5500cm-1波谱区域结合附加散射校正处理过的原始光谱建立的模型精度表现最好,其内部互验证决定系数达到0.90,均方根误差为0.16。经不同类型土壤的观测资料检验,模型验证决定系数为0.91,均方根误差为0.15,相对分析误差RPD为3.40,表明模型具有极好的预测能力。因此,利用近红外光谱可以实现土壤全氮的快速估测,且以合频波段（4000～5500cm-1）为建模区域可以得到更好的预测效果。

英文摘要：

Soil total nitrogen content is regarded as an important index for soil fertility diagnosis and crop growth management direction, the rapid monitoring model and establishing optimum bands on soil nitrogen content is the key to swiftly obtain soil nutrient information and develop precision agriculture. Five types of soil （Paddy soil, Fluvo-aquic soil, Salinized fluvo-aquic soil, Saline soil, Dark soil with lime concretion） collected from the middle and eastern of China were measured in the near-infrared region （4 000-10 000 cm-1）. According to molecular vibration characteristics of full spectrum in the near infrared region, 8 wave bands （the whole region, combination region, the first overtone region, the second overtone region including the combination of bands referred above, and the protein functional group bands） were designed for establishing calibration models adopting multiplicative scatter correction（MSC） method. The calibration models for nitrogen content in soil samples were established by Partial Least Square （PLS） regression. The results showed that the prediction effect using MSC spectra in the combination region of 4 000-5 500 cm-1 was the best, the coefficient of determination and the root mean square error of cross-validation （RMSECV） for the calibration model were 0.90 and 0.16, respectively. Testing of the monitoring models with independent data of different types of soil samples indicated that determination coefficient and RMSE of validation were 0.91 and 0.15, respectively; RPD was 3.40. So, near-infrared diffuse reflection spectroscopy analysis technology can swiftly estimate total nitrogen content, and taking the combination band （4 000-5 500 cm-1） as modeling regional can get better calibration effect.