Balance among calcium, magnesium and potassium levels affecting Asian Soybean Rust severity

Abstract

This work aimed to analyze the effect of the variation of the proportions of calcium in relation to the contentes of magnesium and potassium in the cationic capacity of change (CCC) of the soil, seeking to propitiate the appropriate balance of bases, so that the soybean plants presented good nutritional state and had conditions of resisting to the attack of Phakopsora pachyrhizi Syd. & P. Syd. The experiment was driven in randomized blocks with eight replications and the treatments consisted of doses of Ca:Mg:K in relation to CCC of the soil being:1) without correction of the bases (original soil with 3,8%:6,6%:2,4%); 2) 35:15:5; 3) 45:15:5; 4) 55:15:5; 5) 65:15:5; 6) 75:15:5. The soybean cultivar used in the experiment was BRS 184, sowed in mud vases containing dystrophic Red Latosol (Oxisol) as substrate. The inoculation was realized in the fenologic stadium V4. The disease severity was determined through visual notes considering the percentage foliate area with visible symptoms of the disease, being calculated the Area Under Disease Progress Curve (AUDPC). The data were submitted to the variance analysis (p<0.05) and fitting to regression models. The balance among the nutrientes was analyzed being calculated the index DRIS. The contents of nutrients, the matter dry indexes (MDI) and nutritional balance index (NBI) were inserted in the program ChecarDris for obtaining of the index DRIS. The results appeared that the percentages of 55% of calcium, 15% of magnesium and 5% of potassium, increase larger nutritional balance in the soybean providing to smallest area under disease progress curve (AUDPC), reduction in the severity of the rust (%), besides increase the largest productivity.

Predicting Asian Soybean Rust Epidemics Based on Off-Season Occurrence and El Niño Southern Oscillation Phenomenon in Paraná and Mato Grosso States, Brazil

“…Most forecasting models use only environmental factors; these usually include hours of wetness and temperature, considering that the pathogen and host (the other vertices of the triangular disease), are always present (M. C. Alves, Pozza, Costa, Carvalho, & L. S. Alves, 2011). In addition, the models usually not consider factors such as leaf age and susceptibility (Xavier, Martins, Fantin, & Canteri, 2017) and plant nutrition (Gaspar et al, 2015). The present study demonstrated that the presence of inoculum (the pathogen vertex) exerts a great influence on epidemics during the season.…”