Application of FTIR-PAS and Raman spectroscopies for the determination of organic matter in farmland soils
Application of FTIR-PAS and Raman spectroscopies for the determination of organic matter in farmland soils
复制标题
DOI：
10.1016/j.talanta.2016.05.076
复制
发表时间：
2016-09-01
期刊：
影响因子：
6.1
通讯作者：
Zhou, Jianmin
中科院分区：
文献类型：
--
作者：
Xing, Zhe;Du, Changwen;Zhou, Jianmin
在土壤分析中，拉曼光谱法的应用不如红外光谱法广泛，主要原因是荧光干扰。利用傅里叶变换红外光声（FTIR-PAS）和拉曼光谱（Raman）技术，研究了偏最小二乘回归（PLSR）分析预测土壤有机质（SOM）的可行性。采集了194个农田土壤样品，用FTIR和拉曼光谱仪分别在4000-400 cm（-1）和180-3200 cm（-1）的光谱范围内进行扫描。对于PLSR模型，将组合数据集分为146个样本作为校准集（75%）和48个样本作为验证集（25%）。使用留一交叉验证确定分析因子的最佳数量。结果表明，FTIR-PAS和拉曼光谱可以独立预测土壤有机质，验证集的R-2>0.70，RPD > 1.8。与单独应用FTIR-PAS和拉曼光谱相比，结合FTIR-PAS和拉曼光谱对SOM进行了准确预测，验证集的R-2=0.81和RPD=2.18。通过统计评估大量的PLS模型，模型群体分析证实，PLS模型的准确性可以通过组合FTIR-PAS和拉曼光谱来增加。总之，FTIR-PAS和拉曼光谱的组合是一个有前途的替代土壤特性，特别是对SUM的预测，由于FTIR-PAS（极性振动）和拉曼光谱（非极性振动）的互补信息的可用性。(C)2016爱思唯尔B. V.保留所有权利。
In soil analysis, Raman spectroscopy is not as widely used as infrared spectroscopy mainly owing to fluorescence interferences. This paper investigated the feasibility of Fourier-transform infrared photo acoustic (FTIR-PAS) and Raman spectroscopies for predicting soil organic matter (SOM) using partial least squares regression (PLSR) analysis. 194 farmland soil samples were collected and scanned with FTIR and Raman spectrometers in the spectral range of 4000-400 cm(-1) and 180-3200 cm(-1), respectively. For the PLSR models, the combined dataset was split into 146 samples as the calibration set (75%) and 48 samples as the validation set (25%). The optimal number of analytical factors was determined using a leave-one-out cross-validation. The results showed that SOM could be predicted using FTIR-PAS and Raman spectroscopies independently, with R-2>0.70 and RPD > 1.8 for the validation sets. In comparison to the single applications of FTIR-PAS and Raman spectroscopies, accurate prediction of SOM was made by combining FTIR-PAS and Raman spectroscopies, with R-2=0.81 and RPD=2.18 for the validation sets. By statistically assessing large amounts of PLS models, model-population analysis confirmed that the accuracy of the PLS model can be increased by combining FTIR-PAS and Raman spectroscopies. In conclusion, the combination of FTIR-PAS and Raman spectroscopies is a promising alternative for soil characterization, especially for the prediction of SUM, owing to the availability of complementary information from both FTIR-PAS (polar vibrations) and Raman spectroscopy (non-polar vibrations). (C) 2016 Elsevier B.V. All rights reserved.