Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Sustainable Soil Volatilome: Discrimination of Land Uses Through GC-MS-Identified Volatile Organic Compounds

Emoke Dalma Kovacs, Teodor Rusu, Melinda Haydee Kovacs

Separations · 2025

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Summary

This study demonstrates that soil volatilome profiling—the systematic analysis of volatile organic compounds—can serve as a sensitive diagnostic tool for distinguishing between soils managed under different land uses. Using gas chromatography–mass spectrometry analysis of headspace extracts from Cluj County soils, the authors identified 106 volatile compounds and found that oxygenated species dominated across all land uses, with forest soils exhibiting the highest concentration (77%) and greatest chemical complexity, whilst agricultural soils showed reduced diversity and more homogeneous volatile signatures. The findings support soil volatilomics as a potentially valuable indicator of land-use effects on soil biochemical processes and ecosystem condition.

Regional applicability

This study was conducted in Cluj County, Romania, in a temperate European climate. The methodology and findings are transferable to United Kingdom soil assessment contexts, as the analytical techniques are location-independent and the land-use gradient (forest, grassland, arable agriculture) is relevant to UK farming systems and conservation monitoring. However, UK-specific soil properties, climate conditions, and microbial communities may produce distinct volatile signatures requiring local validation.

Key measures

Volatile organic compound concentration and diversity; principal component analysis (PC1: 41.7%, PC2: 31.1%); partial least squares discriminant analysis (PLS-DA) with area under curve (AUC) values ranging from 0.810 to 0.868 for pairwise land-use comparisons; compound diversity counts by land use

Outcomes reported

The study identified and characterised 106 volatile organic compounds in soils across three land-use types (forest, grassland, agricultural) using headspace solid-phase microextraction and gas chromatography–mass spectrometry. Multivariate statistical analysis revealed distinct volatilome signatures that enable discrimination between land-use types, with forest soils showing the highest chemical complexity and agricultural soils the most homogeneous profiles.

Theme
Farming systems, soils & land use
Subject
Soil health assessment & monitoring
Study type
Research
Study design
Field trial / observational study
Source type
Peer-reviewed study
Status
Published
Geography
Romania
System type
Mixed farming
DOI
10.3390/separations12040092
Catalogue ID
SNmomgxwis-dvdpox

Topic tags

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