Simulation of oat yield through biological and environmental variables for reducing fungicide application and increasing interval from application to grain harvest

Abstract

Simulation models based on biological and environmental variables allow the analysis of scenarios in proposing more sustainable management. The objectives is to identify potential biological and environmental variables for inclusion and validation of multiple linear regression model for yield simulation and analyze scenarios that promote yield and satisfactory control of foliar diseases, with longer intervals between the last fungicide application and the grain harvest. The study was conducted in 2015, 2016, 2017, in Augusto Pestana, RS, Brazil. The soil is classified as Oxisol and the climate of the region as Cfa type, by the Köppen classification. The experimental design was randomized blocks, with three replications, in a 22 x 4 factorial, for 22 oat cultivars (10 recommended and 12 no longer recommended) and 4 fungicide use conditions (no application; one application 60 days after emergence (DAE); two applications, 60, 75 DAE; and three applications, 60, 75, 90 DAE. In 2015 and 2016, the fungicide FOLICUR® CE was used, and in 2017 PRIMO®, at a dosage 0.75 and 0.3 liters ha-1, respectively. Necrotic leaf area, rainfall depth, mean minimum and maximum temperatures, thermal sum, and crop cycle period (days) are potential variables by the Stepwise technique in the simulation of oat yield, validating the use of the multiple linear regression. The condition with three fungicide applications, at 60, 75, 90 DAE, resulted in satisfactory foliar disease control and grain yield, while maintaining a long interval between the last fungicide application and the grain harvest, thus improving the safety of the product obtained