Contrasting Covariance Patterns of Soil-Test Phosphorus and Potassium in Routine Agricultural Soil Records
Year: 2026
Type: article
Abstract: Routine soil analysis reports are widely generated, yet they are commonly interpreted one indicator at a time. When such records are compiled into databases, it becomes important to determine whether different soil-test indicators reflect the same general soil condition gradient or require context-specific interpretation. In this study, a cleaned analytical database was compiled from routine soil analysis records from northwestern Türkiye to examine the joint behavior of saturation percentage, pH, electrical conductivity, organic matter, available phosphorus, and available potassium. The extraction workflow yielded 1,450 rows from the uppermost reported soil layer, and a complete-case subset of 905 observations was retained for the main multivariate analyses. Descriptive review, Pearson and Spearman correlation analyses, targeted phosphorus pairwise analysis, principal component analysis, and grouped pH × organic matter summaries were used to evaluate co-variation. The results did not support a single fully coherent soil-property pattern. Saturation, pH, organic matter, and available potassium showed a comparatively regular shared structure, whereas available phosphorus was only partly aligned with that broader pattern. Phosphorus showed its clearest association with potassium and a weaker relation with organic matter, while its links with pH, saturation, and electrical conductivity were weak and scattered. Grouped pH × organic matter summaries further showed that potassium increased more regularly across contextual classes, whereas phosphorus behaved more unevenly. Overall, available potassium fitted the broader multivariate structure more consistently, whereas available phosphorus required direct contextual interpretation rather than being treated as a simple component of a general fertility axis.
Institutions: Central Research Institute, Dokuz Eylül University
Language: English
Subfield: Soil Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W7205709043