Modeling Soil Organic Carbon Content Using Mid-Infrared Absorbance Spectra and a Nonnegative MCR-ALS Analysis

A new approach based on mid-IR absorbance spectra is proposed for modeling total organic carbon (TOC) content of soils. This approach involves a first-time bilinear decomposition of soil mid-IR absorbance spectra using nonnegative multivariate curve resolution (MCR) with an alternating least squares...

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Published in:Soil & Environmental Health 2025-01, Vol.3 (1), p.100123, Article 100123
Main Authors: Borisover, Mikhail, Lado, Marcos, Levy, Guy J.
Format: Article
Language:English
Subjects:
Carbon storage capacity
dominating SOM pools
MCR-ALS
Mid-IR spectroscopy
physicochemical model
Soil health
soil organic matter (SOM)
SOM-Mineral interactions
The beer-Lambert law
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Levy, Guy J.
description A new approach based on mid-IR absorbance spectra is proposed for modeling total organic carbon (TOC) content of soils. This approach involves a first-time bilinear decomposition of soil mid-IR absorbance spectra using nonnegative multivariate curve resolution (MCR) with an alternating least squares (ALS) algorithm. An MCR-ALS-derived component signifies a chemically meaningful combination of soil constituents. A new mechanistic model has been developed to link the soil composition, expressed in terms of ratios of MCR-ALS-based concentration scores of the identified components, to soil TOC value. Nonnegative MCR-ALS decomposition, performed for 213 mid-IR absorbance spectra of soil samples collected in the north and south of Israel, yielded four components. Fitting the mechanistic model-derived TOC to the experimental TOC values exhibited a TOC content threshold that affected model performance. TOC content
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This approach involves a first-time bilinear decomposition of soil mid-IR absorbance spectra using nonnegative multivariate curve resolution (MCR) with an alternating least squares (ALS) algorithm. An MCR-ALS-derived component signifies a chemically meaningful combination of soil constituents. A new mechanistic model has been developed to link the soil composition, expressed in terms of ratios of MCR-ALS-based concentration scores of the identified components, to soil TOC value. Nonnegative MCR-ALS decomposition, performed for 213 mid-IR absorbance spectra of soil samples collected in the north and south of Israel, yielded four components. Fitting the mechanistic model-derived TOC to the experimental TOC values exhibited a TOC content threshold that affected model performance. TOC content &lt;1.0 % w w-1 was represented by the root mean square deviation of 0.18% and 62% of the variance explained, whereas for larger TOC values, a sharp decline in model performance was observed. The existence of this TOC threshold in determining model performance suggested that successful TOC modeling (below 1%) could be indirect and related to IR spectral fingerprints of minerals binding soil organic matter (SOM) and forming organo-mineral complexes. Thus, a SOM fraction having weak interactions with soil minerals was poorly accounted for in a particular set of soil samples. This dependency of the model performance on soil TOC range proposes that it might be possible to differentiate between soil samples based on their different dominating SOM pools, mineral-associated ones and those having weak interactions with minerals. Further studies, especially in soils with high SOM content, are needed to validate our findings. [Display omitted] •Soil mid-IR absorbance spectra were decomposed using the non-negative MCR-ALS•The identified components are characterized by concentration scores and IR spectra•A mechanistic model is used to link scores of MCR-ALS components to soil TOC values•Model success in predicting soil TOC content depended on a threshold TOC level•The detected threshold can help identify different types of soil organic matter</description><identifier>ISSN: 2949-9194</identifier><identifier>EISSN: 2949-9194</identifier><identifier>DOI: 10.1016/j.seh.2024.100123</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Carbon storage capacity ; dominating SOM pools ; MCR-ALS ; Mid-IR spectroscopy ; physicochemical model ; Soil health ; soil organic matter (SOM) ; SOM-Mineral interactions ; The beer-Lambert law</subject><ispartof>Soil &amp; Environmental Health, 2025-01, Vol.3 (1), p.100123, Article 100123</ispartof><rights>2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2033-d2d863a7f50325cdcb361d33ad3a94c3fc9235a48d6f80fe94bce96055fc9fa63</cites><orcidid>0000-0002-3706-6500</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Borisover, Mikhail</creatorcontrib><creatorcontrib>Lado, Marcos</creatorcontrib><creatorcontrib>Levy, Guy J.</creatorcontrib><title>Modeling Soil Organic Carbon Content Using Mid-Infrared Absorbance Spectra and a Nonnegative MCR-ALS Analysis</title><title>Soil &amp; Environmental Health</title><description>A new approach based on mid-IR absorbance spectra is proposed for modeling total organic carbon (TOC) content of soils. This approach involves a first-time bilinear decomposition of soil mid-IR absorbance spectra using nonnegative multivariate curve resolution (MCR) with an alternating least squares (ALS) algorithm. An MCR-ALS-derived component signifies a chemically meaningful combination of soil constituents. A new mechanistic model has been developed to link the soil composition, expressed in terms of ratios of MCR-ALS-based concentration scores of the identified components, to soil TOC value. Nonnegative MCR-ALS decomposition, performed for 213 mid-IR absorbance spectra of soil samples collected in the north and south of Israel, yielded four components. Fitting the mechanistic model-derived TOC to the experimental TOC values exhibited a TOC content threshold that affected model performance. TOC content &lt;1.0 % w w-1 was represented by the root mean square deviation of 0.18% and 62% of the variance explained, whereas for larger TOC values, a sharp decline in model performance was observed. 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The existence of this TOC threshold in determining model performance suggested that successful TOC modeling (below 1%) could be indirect and related to IR spectral fingerprints of minerals binding soil organic matter (SOM) and forming organo-mineral complexes. Thus, a SOM fraction having weak interactions with soil minerals was poorly accounted for in a particular set of soil samples. This dependency of the model performance on soil TOC range proposes that it might be possible to differentiate between soil samples based on their different dominating SOM pools, mineral-associated ones and those having weak interactions with minerals. Further studies, especially in soils with high SOM content, are needed to validate our findings. 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subjects Carbon storage capacity
dominating SOM pools
MCR-ALS
Mid-IR spectroscopy
physicochemical model
Soil health
soil organic matter (SOM)
SOM-Mineral interactions
The beer-Lambert law
title Modeling Soil Organic Carbon Content Using Mid-Infrared Absorbance Spectra and a Nonnegative MCR-ALS Analysis
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