Potassium Recycling From Corn and Soybean Tissue and Soil-Test Temporal Variability.

Research is needed to better identify reasons for high temporal soil-test K variation. This study investigated K recycling from corn and soybean tissue to the soil and its impact on soil-test K of samples collected in the fall immediately after grain harvest or in before planting the crops. Soil and plant samples were collected during two years from 13 Iowa field trials. Two trials were managed with continuous corn and 11 trials were managed with corn-soybean rotations. The trials included several K application rates, but only a control receiving no K and a high K rate (168 kg K ha^-1) were used for this study. Potassium was analyzed in grain and vegetative tissue at the physiological maturity stage (PM) and at harvest time, and also in crop residue at roughly 45-day intervals from harvest until early spring (2 to 3 weeks before planting the next crop). The largest soybean K loss (excluding K in grain) occurred between PM and harvest, but for corn the loss was approximately similar between PM and harvest and between harvest and late fall. There was little residue K loss during winter for both crops (with soils frozen or covered by snow), but there was an additional small loss in early spring. On average across sites and K rates, only 14% of the K accumulated in soybean vegetative tissue at PM remained in the residue by early spring. For corn, results were more variable, but on average 32% of the K accumulated in vegetative tissue at PM remained in the residue by spring. The K loss from residue was well correlated with the soil-test K increase from fall to spring (r = 0.75 for corn residue and r =0.86 for soybean residue). The relationship between the K loss from vegetative tissue or residue and precipitation for all trials is being studied at this time. The study demonstrated that the rate of K loss to soil from vegetative plant tissue and residue explains a significant proportion of usually high post-harvest soil-test K temporal variability.