Xiang-jun ZHONG, Li YANG, Dong-xing ZHANG, Tao CUI, Xian-tao HE, Zhao-hui DU. Effect of Different Particle Sizes on the Prediction of Soil Organic Matter Content by Visible-Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2022, 42(8): 2542

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- Spectroscopy and Spectral Analysis
- Vol. 42, Issue 8, 2542 (2022)

Fig. 1. Soil samples with different particle sizes
(a): 1~2 mm; (b): 0.5~1 mm; (c): 0.25~0.5 mm; (d): 0.1~0.25 mm; (e): <1 mm; (f): <0.1 mm
(a): 1~2 mm; (b): 0.5~1 mm; (c): 0.25~0.5 mm; (d): 0.1~0.25 mm; (e): <1 mm; (f): <0.1 mm

Fig. 2. Test instrument diagram
1: PC; 2: TOC; 3: PC; 4: Soil samples; 5: Standard white plate; 6: Fiber probe;7: Multifunctional testing platform; 8: NIR Quest; 9: QE Rro; 10: Light source (a): TOC analyzer; (b): Spectrum acquisition device
1: PC; 2: TOC; 3: PC; 4: Soil samples; 5: Standard white plate; 6: Fiber probe;7: Multifunctional testing platform; 8: NIR Quest; 9: QE Rro; 10: Light source (a): TOC analyzer; (b): Spectrum acquisition device

Fig. 3. Relationship between soil particle size and spectral reflectance
(a): Mean reflectance and variation coefficient of different soil particle sizes;(b): Mean reflectance of different soil particle sizes at different wavelengths
(a): Mean reflectance and variation coefficient of different soil particle sizes;(b): Mean reflectance of different soil particle sizes at different wavelengths

Fig. 4. Correlation between SOM content and reflectance of soil with different particle sizes
(a): SOM content and reflectance at R transform; (b): SOM content and reflectance at FDR transform
(a): SOM content and reflectance at R transform; (b): SOM content and reflectance at FDR transform

Fig. 5. Variable distribution of SOM content characteristics at different wavelengths based on CARS
(a): Distribution of characteristic variables of SOM content in soil with different particle diameters at different wavelengths;(b): Overlap times of characteristic variables of SOM content under different particle sizes
(a): Distribution of characteristic variables of SOM content in soil with different particle diameters at different wavelengths;(b): Overlap times of characteristic variables of SOM content under different particle sizes

Fig. 6. SOM characteristic variables distribution based on CARS method

Fig. 7. Construction and evaluation of SOM content models for different particle sizes

Fig. 8. Comparisons of Predicted values and measured values of different PLSR models
(a): R-PLSR model of all particle sizes; (b): FDR-PLSR model of all particle sizes; (c): CARS-PLSR model of all particle sizes;(d): CARS-PLSR model for particle size of 1~2 mm; (e): CARS-PLSR model for particle size of 0.5~1 mm;(f): CARS-PLSR model for particle size of 0.25~0.5 mm;(g): CARS-PLSR model for particle size of 0.1~0.25 mm ;(h): CARS-PLSR model for particle size of <0.1 mm; (i): CARS-PLSR model for particle size of <1 mm
(a): R-PLSR model of all particle sizes; (b): FDR-PLSR model of all particle sizes; (c): CARS-PLSR model of all particle sizes;(d): CARS-PLSR model for particle size of 1~2 mm; (e): CARS-PLSR model for particle size of 0.5~1 mm;(f): CARS-PLSR model for particle size of 0.25~0.5 mm;(g): CARS-PLSR model for particle size of 0.1~0.25 mm ;(h): CARS-PLSR model for particle size of <0.1 mm; (i): CARS-PLSR model for particle size of <1 mm
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Table 1. Statistics of soil organic matter content
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Table 2. Maximum correlation coefficient between SOM content and spectral reflectance under different particle sizes

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