Zhang Juan-Juan, Tian Yong-Chao, Zhu Yan, Yao Xia, Cao Wei-Xing
Jiangsu Provincial Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing, China.
Ying Yong Sheng Tai Xue Bao. 2009 Aug;20(8):1896-904.
Taking the air-dried samples of five soil types from middle and eastern China as test materials, the correlations of their organic matter content with the spectral reflectance of near-infrared (1000-2500 nm), and with the ratio index (RI), difference index (DI), and normalized difference index (ND) of the first derivative values of the reflectance between two bands were studied. Based on this, the key spectral indices and the quantitative models for estimating soil organic matter (SOM) content were developed. After corrected with Multiplicative Scatter Correction (MSC) and Savitzky-Golay (SG) smoothing methods, the spectral reflectance of near-infrared had an obviously high correlation with SOM, compared with the original spectral reflectance, while the corrected spectral indices of the first derivative values of the reflectance between two bands took the intermediate position. The correlation of the spectral indices with SOM was in the order of was DI > RI > ND, regardless the composition of the original spectral reflectance or the first derivative spectra. The DI of the reflectance of near-infrared between 1883 and 2065 nm corrected with MSC and SG smoothing methods [DI(CR1883, CR2065)] had the best linear correlations with SOM. The test of the monitoring model based on DI(CR1883, CR2065) with the independent datasets of SOM showed that the R2 and RMSE validation values were 0.837 and 4.06, respectively. Comparing with the results from the Partial Least Square (PLS) method, the monitoring model based on DI (CR1883, CR2065) was somewhat inferior. However, the DI(CR1883, CR2065) only needed two reflectance bands, and the monitoring model was simpler, being able to provide more available information for developing portable instruments, and a good spectral index for estimating SOM content.
以中国中东部地区5种土壤类型的风干样品为试验材料,研究了其有机质含量与近红外(1000 - 2500 nm)光谱反射率以及与两波段反射率一阶导数的比值指数(RI)、差值指数(DI)和归一化差值指数(ND)之间的相关性。在此基础上,建立了估算土壤有机质(SOM)含量的关键光谱指数和定量模型。经多元散射校正(MSC)和Savitzky - Golay(SG)平滑方法校正后,近红外光谱反射率与SOM的相关性明显高于原始光谱反射率,而两波段反射率一阶导数的校正光谱指数处于中间位置。无论原始光谱反射率还是一阶导数光谱的组成如何,光谱指数与SOM的相关性顺序均为DI > RI > ND。经MSC和SG平滑方法校正的1883 - 2065 nm近红外反射率的DI [DI(CR1883, CR2065)]与SOM具有最佳线性相关性。基于DI(CR1883, CR2065)的监测模型对SOM独立数据集的测试表明,验证值R2和RMSE分别为0.837和4.06。与偏最小二乘法(PLS)的结果相比,基于DI(CR1883, CR2065)的监测模型略逊一筹。然而,DI(CR1883, CR2065)仅需两个反射率波段,监测模型更简单,能够为开发便携式仪器提供更多有用信息,是估算SOM含量的良好光谱指数。