A thermal time model for optimising herbicide dose in maize

Maize is sown in Iran from mid‐April to early September. Weather, weed flora and crop growth stage all vary over this time span, which changes herbicide efficacy. To avoid any excessive or inadequate usage of herbicide, we propose an empirical model that predicts the optimum dose based on the thermal time accumulated by maize after sowing. We planted maize in May and August in 2016 and 2017, arranged in a split‐plot design with four replications. Main plots were herbicide timing ranging from 2 to 8 leaves of maize, and sub‐plots were herbicide dose. Weed response to herbicide dose was parameterised using the standard dose–response model against thermal time (TT) of application. The parameter W0 weed fresh weight (WFW) in plots not treated with herbicide increased linearly, ED50 (the dose to decrease W0 by 50%) increased exponentially, and b (the slope of the curve at linear decrease) decreased exponentially with TT. We replaced the parameters by their specified function of change over TT resulting in a combined model, which predicts WFW from herbicide dose and application time. A hyperbolic model described the yield loss as a function of WFW. We included this relationship in a more developed model, which predicts per cent yield loss based on herbicide dose and application TT. The model performed well over validation tests with R2 ≥ 0.90. We recommend an early herbicide application not later than 600 TT after maize sowing that allows reduced dose, as we found a steady decrease in herbicide efficiency with delaying application time.