Soil organic matter characterisation by photometric indices or photon correlation spectroscopy: are they comparable?

Abstract

Soil organic matter (SOM) is a complex component of soil that acts as basis for most of the soil forming processes. SOM characteristics, including quantity, spatial distribution, molecular size and composition, are the results of environmental effects. SOM is definitely hard to be measured in situ, therefore most investigations are based on incomplete SOM extractions or other proxies. Even though, the traditional humus concept that polymerisation degree of SOM molecules are proportional to their stability are refuted, the concerning proxies for SOM composition predictions are still in use. These are mainly based on the photometric investigations of alkali extractions. However, this extraction method received many rightful critiques, it still could be a possible alternative, since it is quite simple, cheap and represented much more SOM than water extractions. This study aimed to compare SOM composition results based on carbon-nitrogen ratio and alkali extractions measured by UV-vis spectrometry and photon correlation spectrometry on the same soil used as forest and crop field. SOM composition proxies provided inconsistent results using the NaOH extraction method compared with photon correlation. Therefore, the application of organo-mineral SOM protection theory in association with the photometric proxies seems to be difficult in the case of the investigated Luvisol. On the other hand, photon correlation spectroscopy provided results in line with the published results of the organo-mineral stabilization theory that suggested alkali extraction with special care could be a useful alternative. However, due to the known imperfections of it, the application of in situ measurement methods would be preferable.

Estimation of the Total Soil Nitrogen Based on a Differential Evolution Algorithm from ZY1-02D Hyperspectral Satellite Imagery

“…PLSR is a popular multivariate statistical technique for forecasting soil element content using hyperspectral data [43,44], which can address the issue of spectral band covariance. The PLSR approach compares several dependent variables to numerous independent variables in a multivariate statistical regression modeling setting.…”

“…Overall, the SVM model had a better estimation ability for TN content. An SVM is a machine learning model used for solving non-linear problems [13,44] and can accurately estimate TN content and capture the link between TN content and complex spectral data. According to this study's findings, the accuracy of the SVM model was increased when the DE technique was applied to extract the feature variables from the LBC.…”

Applications of stable carbon isotopes in soil science with special attention to natural 13C abundance approach

“…Agricultural land use disturbs the natural SOM system, e.g. by affecting the aggregate size and stability of SOM (Bilandžija, D. et al 2017;Jakab, G. et al 2018b). With the help of 13 C natural abundance these effects can be examined in more detail, as stable carbon isotopes widen the scope of land use research.…”

Talajok vasásványainak környezetjelző szerepe

“…A réti talajok morfológiai fejlődésében (szintezettség kialakulása, szerves anyag felhalmozódás, ásványi fázis differenciálódása) redox állapot változások alapvető szerepet játszanak (ALLER 1994, BALL-WILLIAMS 1974, JAKAB et al 2018, GIANNETTA 2019, HARTEMINK-MCSWEENEY 2014, RENNERT et al 2018. Az Eh és pH értékek által meghatározott körülmények a talaj szervesanyag mennyiségi és minőségi paraméterein túl a redox-szenzitív ásványok stabilitására, illetve átalakulására is hatással vannak.…”