Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models

Year 2025, Volume: 9 Issue: 4, 1150 - 1161, 26.12.2025

Süreyya Betül Rufaioğlu , Fatma Kaplan , Ali Volkan Bilgili

https://doi.org/10.31015/2025.4.14.r

Abstract

This study aimed to evaluate the effects of different land use types (Melissa officinalis, cotton, pistachio, and uncultivated) on the physicochemical and biochemical properties of soils developed on the same parent material under semi-arid conditions, and to assess the potential of Visible–Near Infrared Spectroscopy (VNIRS) for predicting these soil attributes. The soils in the study area are formed on limestone-derived colluvial–alluvial deposits characteristic of the Harran soil series, classified as Vertic Calciorthids (Soil Taxonomy) and Calcic Vertisols (WRB). Laboratory analyses included soil texture, pH, electrical conductivity (EC), calcium carbonate, organic matter (OM), water retention parameters, and enzyme activities (β-glucosidase, dehydrogenase, alkaline phosphatase). Spectral reflectance data in the 350–2500 nm range were used to develop Partial Least Squares Regression (PLSR) models for soil property estimation. The models demonstrated good calibration performance for EC (R² = 0.93), OM (R² = 0.49), and dehydrogenase activity (R² = 0.93), while validation accuracy remained modest (R² = 0.46, 0.43, and 0.75, respectively), reflecting the limitations of the small sample size. Texture-related parameters (sand, silt, clay) showed limited predictive accuracy (R² = 0.10). Distinct absorption bands at 1400, 1900, and 2200 nm were associated with soil moisture and clay minerals. Although Melissa-cultivated soils tended to show higher organic matter and enzyme activity, these differences should be interpreted cautiously due to the limited number of samples, representing only preliminary indications rather than generalizable trends. Overall, the findings suggest that VNIRS has potential as a rapid and cost-effective approach for characterizing soil biochemical indicators and supporting sustainable land management in semi-arid regions, but further studies with larger datasets are needed to confirm its predictive reliability.

Keywords

Land use , Soil enzyme activity , VNIRS , PLSR , Soil biochemical properties

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