Subsoil-potassium depletion accounts for the nutrient budget in high-potassium agricultural soils.

Continuous potassium (K) removal without replenishment is progressively mining Argentinean soils. Our goals were to evaluate the sensitivity of soil-K to K budgets, quantify soil-K changes over time along the soil profile, and identify soil variables that regulate soil-K depletion. Four on-farm trials under two crop rotations including maize, wheat and soybean were evaluated. Three treatments were compared: (1) control (no fertilizer applied); (2) application of nitrogen, phosphorus, and sulfur fertilizers -NPS-; and (3) pristine condition. After nine years, crops removed from 258 to 556 kg K ha-1. Only two sites showed a decline in the exchangeable-K levels at 0-20 cm but unrelated to K budget. Topsoil exchangeable-K levels under agriculture resulted 48% lower than their pristine conditions, although still above response levels. Both soil exchangeable-K and slowly-exchangeable K vertical distribution patterns (0-100 cm) displayed substantial depletion relative to pristine conditions, mainly concentrated at subsoil (20-100 cm), with 55-83% for exchangeable-K, and 74-95% for slowly-exchangeable-K. Higher pristine levels of exchangeable-K and slowly-exchangeable-K and lower clay and silt contents resulted in higher soil-K depletion. Soil K management guidelines should consider both topsoil and subsoil nutrient status and variables related to soil K buffer capacity.

Bayesian approach for maize yield response to plant density from both agronomic and economic viewpoints in North America.

Targeting the right agronomic optimum plant density (AOPD) for maize (Zea mays L.) is a critical management decision, but even more when the seed cost and grain selling price are accounted for, i.e. economic OPD (EOPD). From the perspective of improving those estimates, past studies have focused on utilizing a Frequentist (classical) approach for obtaining single-point estimates for the yield-density models. Alternative analysis models such as Bayesian computational methods can provide more reliable estimation for AOPD, EOPD and yield at those optimal densities and better quantify the scope of uncertainty and variability that may be in the data. Thus, the aims of this research were to (i) quantify AOPD, EOPD and yield at those plant densities, (ii) obtain and compare clusters of yield-density for different attainable yields and latitudes, and (iii) characterize their influence on EOPD variability under different economic scenarios, i.e. seed cost to corn price ratios. Maize hybrid by seeding rate trials were conducted in 24 US states from 2010 to 2019, in at least one county per state. This study identified common yield-density response curves as well as plant density and yield optimums for 460 site-years. Locations below 40.5 N latitude showed a positive relationship between AOPD and maximum yield, in parallel to the high potential level of productivity. At these latitudes, EOPD depended mostly on the maximum attainable yield. For the northern latitudes, EOPD was not only dependent on the attainable yield but on the cost:price ratio, with high ratios favoring reductions in EOPD at similar yields. A significant contribution from the Bayesian method was realizing that the variability of the estimators for AOPD is sometimes greater than the adjustment accounting for seed cost. Our results point at the differential response across latitudes and commercial relative maturity, as well as the significant uncertainty in the prediction of AOPD, relative to the economic value of the crop and the seed cost adjustments.