Journal
EUROPEAN JOURNAL OF SOIL SCIENCE
Volume 62, Issue 5, Pages 728-732Publisher
WILEY-BLACKWELL
DOI: 10.1111/j.1365-2389.2011.01386.x
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- ARC
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Soil pH is the most routinely measured soil property for assessing plant nutrient availability. Nevertheless, there are various techniques for soil pH measurement, which vary with regard to the solution used and the soil-to-solution ratio. Soil pH is commonly measured in water or 0.01 m CaCl(2). Soil pH in CaCl(2) is usually preferred as it is less affected by soil electrolyte concentration and provides a more consistent measurement. Therefore there is a need to convert measurement values between the two methods. Previous models reported linear and curvilinear relationships between the two measurements. However, the pH difference between measurements in water and CaCl(2) is related to the soil solution electrolyte concentration. We observed that the pH difference between the two methods became smaller with increasing soil electrical conductivity (EC). We therefore developed models that relate pH in CaCl(2) and water and incorporate EC values. We calibrated a linear and a non-linear model (artificial neural networks, ANN) using 9817 soil samples from Queensland, Australia. Soil pH in water and CaCl(2) and EC were measured with a 1:5 soil-to-solution ratio. The results show that incorporating EC in the prediction model improves the prediction of pH in CaCl(2) significantly. We validated these models using 4576 independent samples obtained from a diverse range of soils across Australia. Although the linear and ANN models performed similarly, the ANN (which has a curvilinear relationship) provided a better prediction and aligns with the theory that for acid and alkaline pH values, the difference between pH in water and CaCl(2) is less than that for pHs between 4.5 and 7.
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