Soil texture and organic matter prediction using Mehlich‐3 extractable nutrients

Abstract Soil organic matter (SOM) and texture are key properties influencing soil nutrient and water dynamics but are time‐consuming procedures for analytical laboratories. Our objective was to evaluate SOM and soil texture predictions using Mehlich‐3 nutrients and pH in Arkansas soils. Particle size was determined by the hydrometer method (2‐ and 8‐h readings) and SOM by loss on ignition. Two datasets were used to calibrate clay and sand (n = 409) and SOM (n = 1019) prediction models using simple and multiple regression. Estimated cation exchange capacity was highly correlated with clay, resulting in significant prediction models alone or combined with phosphorus (P); pH and copper (Cu); or pH, sodium (Na), and Cu (R2 = 0.84, 0.88, 0.89, and 0.90; p