A method combining FTIR-ATR and Raman spectroscopy to determine soil organic matter: Improvement of prediction accuracy using competitive adaptive reweighted sampling (CARS)
Graphical abstract
Introduction
Soil nutrient management is essential for China’s agro-ecosystem. As the key indicator of soil nutrient status and fertility, soil organic matter (SOM) provides nutrients mainly through the humification process (Manlay et al., 2007). The level and variation of SOM content are highly related with soil water and the formation of soil aggregates (Sarker et al., 2018, Obour et al., 2018). Decrease of SOM could indirectly cause soil degradation and affect global climate change (Davidson and Janssens, 2006).
The development of efficient and accurate methods for SOM analysis is of high importance for precision agriculture (Zheng et al., 2016). Currently, the main method used to determine SOM is the combustion method. The wet combustion method, or the more recently used dry combustion method (Meersmans et al., 2009, Wielopolski et al., 2011, Beltrame et al., 2016), commonly requires extensive sample preparation and inevitably involves reagent contamination. These techniques are consequently destructive, laborious, time and energy consuming (Senesi and Senesi, 2016).
Spectroscopic approaches are alternatively developed for nutrient analysis in soils. Plenty of previous studies demonstrated the potential of infrared spectroscopy in characterizing the structure of complex matrix, such as the organic macromolecule (Inbar et al., 1989, Haberhauer et al., 1998). Such FTIR spectra could obtain numerous bands that are diagnostic and valuable to analyze information, which are related to the functional groups that SOM contains (Solomon et al., 2005). The application of spectroscopic techniques may provide particular advantages over the chemical methods, including their minimal sample preparation and the strong statistical power in need of a very small amount of soil samples (Lohumi et al., 2015). Due to the easy detection of some target attributes and free generation of residual reagents in comparison to chemical methods, spectroscopic approaches have been preferable for quantitative analysis in the field of soil science, especially for analyzing soil sample in batches rapidly (Malone et al., 2017).
Among these infrared methods, the mid-infrared attenuated total reflection (FTIR-ATR) spectroscopy is a nondestructive technique which has already been used to characterize soil properties in many research (Ge et al., 2014, Linker et al., 2005, Linker et al., 2006). FTIR-ATR works based on the principle of the reflected light after the selective absorption of the sample within the frequency range of the incident light (Huck, 2016). The ATR spectroscopy has special advantages by solving problems always encountered in the application of infrared transmission spectroscopy. For example, preparation of pellets for the operation of transmission spectroscopy may interfere with water bands of the acquired spectra, mainly due to the hydroscopic property of KBr reagent (Solomon et al., 2005, Tanaka et al., 2001).
Although significant progress has been made in SOM investigation using infrared techniques (Nkwain et al., 2018), advances in SOM characterization could further benefit from the progress made in nondestructive Raman spectroscopy technique to get information about the chemical composition of complex organic material in soils. Raman spectroscopy has been widely used in geology, food chemistry and forensic science (Wille et al., 2014, Kammrath et al., 2018, Yang and Ying, 2011). However, despite the complementarity of Raman spectroscopy and infrared techniques from the perspective of their principle, routine application of Raman spectroscopy for SOM analysis has been largely limited by the intensive fluorescence effect caused by the humic in soil (Edwards et al., 2012). Thus, as a typical vibrational spectroscopy, Raman spectroscopy is not usually a preferred approach for SOM analysis.
Therefore, it is crucial to use appropriate chemometric approaches to build calibration models to exploit information related to the structure of SOM and further increase the prediction accuracy of the attributes. The combination of Raman and infrared measurements with chemometric data treatments has offered considerable reliability for the determination of organic matter in soil samples. In a previous study, partial least square regression (PLSR) was used to build calibration models to quantitatively determine SOM with FTIR-PAS and Raman spectroscopies (Xing et al., 2016). Our results have emphasized that Raman spectroscopy could be used for characterization of farmland soils and that it can be combined with the FTIR-PAS technique to estimate the SOM content in agriculture soils. In the context of soil characterization, it is beyond doubt that ATR and Raman spectroscopies, can provide complementary information. However, despite the reported potential of PAS-Raman spectroscopy for SOM evaluation, the suitability of other types of infrared spectroscopy technique, such as ATR spectroscopy has not yet been tested, in combination with Raman spectroscopy to predict SOM.
The application of ATR and Raman spectroscopy in parallel is thus an attracting focus of the present study. Here, we aim to establish a green analytical methodology for the determination of SOM and report the result of a similar study into the determination of SOM, by combining soil Raman and ATR spectroscopy, with more advanced strategy of data fusion.
Section snippets
Soil sample and preparation
Total 194 soil samples from China’s croplands were collected for this study. Four types of surface soils (0–20 cm) were included: black soil, Fluvo-aquic soil, paddy soil and red soil. They were collected from Heilongjiang province, Shandong province, Jiangsu province and Jiangxi province, respectively (Fig. 1). For each site, a representative sample was composed by five random mixed samples. Soil samples were subsequently air-dried at room temperature, crushed and passed through a 2-mm mesh
Soil FTIR-ATR and Raman spectra
Fig. 4 shows the FT-IR-ATR spectra for representative soil types used in this study. Generally, the spectral curve was relatively flat in the range from 1300 cm−1 to 4000 cm−1. Main absorption bands for soil FTIR-ATR spectra included peaks at ∼780 cm−1, ∼910 cm−1, ∼990 cm−1, ∼1440 cm−1, ∼1640 cm−1, ∼1550 cm−1, 3360 cm−1, ∼3620 cm−1 and ∼3690 cm−1. According to relevant literatures, the peaks around 910 and 990 cm−1 were due to Al-OH deformation vibration in aluminosilicate and clay minerals (
Conclusions
The present approach focused on the combined use of FTIR-ATR and Raman spectroscopies in providing fast and complementary information about organic matter of agricultural soils. FTIR-ATR and Raman spectra of 194 soil samples from China croplands were collected. The ability of both techniques for the prediction of SOM individually has been evaluated. Generally, the model performance based on the ATR spectra was comparable to that obtained with the corrected Raman spectroscopy. The strategy of
CRediT authorship contribution statement
Zhe Xing: Conceptualization, Investigation, Formal analysis, Visualization, Writing – original draft. Changwen Du: Conceptualization, Writing – review & editing, Project administration, Funding acquisition, Supervision. Yazhen Shen: Investigation, Formal analysis. Fei Ma: Formal analysis. Jianmin Zhou: Writing – review & editing, Project administration.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
Funding.
This work was supported by the National Natural Science Foundation of China [42077019] and the Strategic Priority Research Program of the Chinese Academy of Sciences [XDA28040500, XDA28120400].
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