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Conversions of soil pH values between different methods are required for the standardization of data from international scientific literature, soil test reports and soil databases. All commonly employed matrices (H 2 O, 0.01 M CaCl 2  and 1 M KCl) and relevant soil:solution ratios (1:1, 1:2.5, 1:4 and 1:5) used for pH measurement have yet to be compared using the same sample dataset. The combined effects of soil physiochemical properties on the accuracy and parsimony of soil pH conversions have also not been thoroughly examined. Therefore, the aim of this study was to investigate the mathematical relation between the most common methods of pH determination. A diverse set of soil samples (n = 57) dominated by low-activity clays were used to calibrate simple and multilinear pH conversion models. The combined effects of soil texture, carbon content and salinity on model parsimony and accuracy were critically evaluated. All pH determination methods were found to be highly reproducible and relatable to one another. It was found that simple linear equations are the most effective means of converting pH values (r 2  = 0.77–0.97; RMSE = 0.12–0.32), considering the trade-off between model complexity and accuracy. Simple direct conversion factors are not deemed sufficiently accurate for the purpose of agricultural management recommendations.

Simple and Multivariate Linear Regression Models for pH Conversion Between Measurement Techniques