Spectral fusion by Outer Product Analysis (OPA) to improve predictions of soil organic C

Author(s)

Terra, Fabricio S. ^{[1, 2, 3]} ; Rossel, Raphael A. Viscarra ^[2] ; Dematte, Jose A. M. ^[1]

Affiliation

^[1] Univ Sao Paulo, Luiz de Queiroz Coll Agr, Dept Soil Sci, Av Padua Dias 11, POB 9, BR-13418900 Piracicaba, SP - Brazil

^[2] CSIRO Land & Water, Bruce E Butler Lab, POB 1700, Canberra, ACT 2600 - Australia

^[3] Univ Fed Pelotas, Ctr Technol Dev Water Resources Engn, Bairro Ctr, Campus Porto, R Gomes Carneiro 01, BR-96610010 Pelotas, RS - Brazil

• Document type: Journal article
• Source: Geoderma; v. 335, p. 35-46, FEB 1 2019.
• Web of Science Citations: 7

Abstract

Soil organic carbon (C) is an important indicator of agricultural and environmental quality. It improves soil fertility and helps to mitigate greenhouse gas emissions. Soil spectroscopy with either vis-NIR (350-2500 nm) or mid-IR (4000-400 cm(-1)) spectra have been used successfully to predict organic C concentrations in soil. However, research to improve predictions of soil organic C by simply combining vis-NIR and mid-IR spectra to model them together has been unsuccessful. Here we use the Outer Product Analysis (OPA) to fuse vis-NIR and mid-IR spectra by bringing them into a common spectral domain. Using the fused data, we derived models to predict soil organic C and compared its predictions to those derived with vis-NIR and mid-IR models separately. We analyzed 1259 tropical soil samples from surface and subsurface layers across agricultural areas in Central Brazil. Soil organic C contents were determined by a modified Walkley-Black method, and vis-NIR and mid-IR reflectance spectra were obtained with a FieldSpec Pro and a Nicolet 6700 Fourier Transformed Infrared (FT-IR), respectively. Reflectances were log-transformed into absorbances. The mean content of soil organic C was 9.14 g kg(-1) (SD = 5.64 g kg(-1)). The OPA algorithm was used to emphasize co-evolutions of each spectral domain into the same one by multiplying the absorbances from both sets of spectra to produce a matrix with all possible products between them. Support Vector Machine with linear kernel function was used for the spectroscopic modeling. Predictions of soil organic C using vis-NIR, mid-IR, and fused spectra were statistically compared by the Tukey's test using the coefficient of determination (R-2), root mean squared error (RMSE), and ratio of performance to interquartile distance (RPIQ). Absorbances in vis-NIR and mid-IR were emphasized in the common spectral domain presenting stronger correlations with soil organic C than individual ranges. Soil organic C predictions with the OPA fused spectra were significantly better (R 2 = 0.81, RMSE = 2.42 g kg(-1), and RPIQ = 2.87) than those with vis-NIR (R-2 = 0.69, RMSE = 3.38 g kg(-1), and RPIQ = 2.08) or mid-IR spectra (R-2 = 0.77, RMSE = 2.90 g kg(-1), and RPIQ = 2.43). Fusing vis-NIR and mid-IR spectra by OPA improves predictions of soil organic C. (AU)

• FAPESP's process: 09/54144-8 - Acquisition of technological equipment for environmental monitoring and agricultural planning, with an emphasis on soil science
• Grantee: José Alexandre Melo Demattê
• Support Opportunities: Multi-user Equipment Program