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Plant Science Today (PST)

Research Articles

Vol. 12 No. sp4 (2025): Recent Advances in Agriculture by Young Minds - III

Integrated assessment of soil quality using PCA-derived indices and spatial zonation in a micro-watershed

DOI
https://doi.org/10.14719/pst.11964
Submitted
24 September 2025
Published
11-11-2025

Abstract

Soil quality assessment is crucial for sustainable land management, integrating physical, chemical and biological soil properties into a single measurable index. This study evaluated soil quality in a micro-watershed using Principal Component Analysis (PCA) and cluster analysis tools to delineate management zones. Sixty three soil samples were collected horizon-wise and analyzed for texture, pH, electrical conductivity, organic carbon, exchangeable cations, Cation Exchange Capacity (CEC) and base saturation (BS %). PCA revealed four key components explaining 90.5 % of total data variability. A Minimum Data Set (MDS) was derived based on strong factor loadings, including sand, silt, clay, base saturation percentage and CEC. The Soil Quality Index (SQI) was computed using standardized z-scores, weighted by each component’s variance contribution, resulting in a comprehensive SQI (CSQI) ranging from -0.48 to 1.18. Approximately 20 % of soils were classified as very good, 40 % as good and the remaining 40 % as fair to very poor. Cluster analysis (k-means and hierarchical) grouped the soils into three fertility zones, with fine-textured, nutrient-rich soils corresponding to the highest CSQI values. Spatial analysis and thematic mapping highlighted that soils with higher clay, CEC and BS % were concentrated in depositional zones and exhibited superior quality, whereas coarse-textured upland soils were nutrient-poor and vulnerable to degradation. These findings underscore the need for site-specific interventions in low-SQI areas, including organic matter addition, nutrient balancing, erosion control and adoption of conservation agriculture practices. In contrast, high-quality zones can maintain current management to sustain productivity. Overall, the integration of PCA-based SQI with GIS spatial modelling proved effective for identifying soil heterogeneity and prioritizing area-specific management strategies, ensuring improved soil resilience and sustainable productivity in the Bankanahalli micro-watershed, characterized predominantly by Alfisols.

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