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

Süreyya Betül Rufaioğlu; Fatma Kaplan; Ali Volkan Bilgili

doi:10.31015/2025.4.14.r

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

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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Details

Primary Language

English

Subjects

Agricultural Systems Analysis and Modelling

Journal Section

Research Article

Authors

Süreyya Betül Rufaioğlu ^*
0009-0006-0225-7629
Türkiye

Fatma Kaplan
0000-0002-4873-3997
Türkiye

Ali Volkan Bilgili
0000-0002-4727-8283
Türkiye

Early Pub Date

December 16, 2025

Publication Date

December 26, 2025

Submission Date

October 9, 2025

Acceptance Date

December 6, 2025

Published in Issue

Year 2025 Volume: 9 Number: 4

DOI

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

IZ

https://izlik.org/JA33FJ86KN

APA

Rufaioğlu, S. B., Kaplan, F., & Bilgili, A. V. (2025). Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models. International Journal of Agriculture Environment and Food Sciences, 9(4), 1150-1161. https://doi.org/10.31015/2025.4.14.r

AMA

1.Rufaioğlu SB, Kaplan F, Bilgili AV. Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models. int. j. agric. environ. food sci. 2025;9(4):1150-1161. doi:10.31015/2025.4.14.r

Chicago

Rufaioğlu, Süreyya Betül, Fatma Kaplan, and Ali Volkan Bilgili. 2025. “Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models”. International Journal of Agriculture Environment and Food Sciences 9 (4): 1150-61. https://doi.org/10.31015/2025.4.14.r.

EndNote

Rufaioğlu SB, Kaplan F, Bilgili AV (December 1, 2025) Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models. International Journal of Agriculture Environment and Food Sciences 9 4 1150–1161.

IEEE

[1]S. B. Rufaioğlu, F. Kaplan, and A. V. Bilgili, “Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models”, int. j. agric. environ. food sci., vol. 9, no. 4, pp. 1150–1161, Dec. 2025, doi: 10.31015/2025.4.14.r.

ISNAD

Rufaioğlu, Süreyya Betül - Kaplan, Fatma - Bilgili, Ali Volkan. “Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models”. International Journal of Agriculture Environment and Food Sciences 9/4 (December 1, 2025): 1150-1161. https://doi.org/10.31015/2025.4.14.r.

JAMA

1.Rufaioğlu SB, Kaplan F, Bilgili AV. Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models. int. j. agric. environ. food sci. 2025;9:1150–1161.

MLA

Rufaioğlu, Süreyya Betül, et al. “Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models”. International Journal of Agriculture Environment and Food Sciences, vol. 9, no. 4, Dec. 2025, pp. 1150-61, doi:10.31015/2025.4.14.r.

Vancouver

1.Süreyya Betül Rufaioğlu, Fatma Kaplan, Ali Volkan Bilgili. Prediction of Soil Physicochemical and Biochemical Attributes under Different Land Uses through VNIRS–Based PLSR Models. int. j. agric. environ. food sci. 2025 Dec. 1;9(4):1150-61. doi:10.31015/2025.4.14.r

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

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

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